TY - JOUR AB - Chronic psychological stress is one of the most important triggers and environmental risk factors for neuropsychiatric disorders. Chronic stress can influence all organs via the secretion of stress hormones, including glucocorticoids by the adrenal glands, which coordinate the stress response across the body. In the brain, glucocorticoid receptors (GR) are expressed by various cell types including microglia, which are its resident immune cells regulating stress-induced inflammatory processes. To study the roles of microglial GR under normal homeostatic conditions and following chronic stress, we generated a mouse model in which the GR gene is depleted in microglia specifically at adulthood to prevent developmental confounds. We first confirmed that microglia were depleted in GR in our model in males and females among the cingulate cortex and the hippocampus, both stress-sensitive brain regions. Then, cohorts of microglial-GR depleted and wild-type (WT) adult female mice were housed for 3 weeks in a standard or stressful condition, using a chronic unpredictable mild stress (CUMS) paradigm. CUMS induced stress-related behavior in both microglial-GR depleted and WT animals as demonstrated by a decrease of both saccharine preference and progressive ratio breakpoint. Nevertheless, the hippocampal microglial and neural mechanisms underlying the adaptation to stress occurred differently between the two genotypes. Upon CUMS exposure, microglial morphology was altered in the WT controls, without any apparent effect in microglial-GR depleted mice. Furthermore, in the standard environment condition, GR depleted-microglia showed increased expression of pro-inflammatory genes, and genes involved in microglial homeostatic functions (such as Trem2, Cx3cr1 and Mertk). On the contrary, in CUMS condition, GR depleted-microglia showed reduced expression levels of pro-inflammatory genes and increased neuroprotective as well as anti-inflammatory genes compared to WT-microglia. Moreover, in microglial-GR depleted mice, but not in WT mice, CUMS led to a significant reduction of CA1 long-term potentiation and paired-pulse ratio. Lastly, differences in adult hippocampal neurogenesis were observed between the genotypes during normal homeostatic conditions, with microglial-GR deficiency increasing the formation of newborn neurons in the dentate gyrus subgranular zone independently from stress exposure. Together, these findings indicate that, although the deletion of microglial GR did not prevent the animal’s ability to respond to stress, it contributed to modulating hippocampal functions in both standard and stressful conditions, notably by shaping the microglial response to chronic stress. AU - Picard, Katherine AU - Bisht, Kanchan AU - Poggini, Silvia AU - Garofalo, Stefano AU - Golia, Maria Teresa AU - Basilico, Bernadette AU - Abdallah, Fatima AU - Ciano Albanese, Naomi AU - Amrein, Irmgard AU - Vernoux, Nathalie AU - Sharma, Kaushik AU - Hui, Chin Wai AU - C. Savage, Julie AU - Limatola, Cristina AU - Ragozzino, Davide AU - Maggi, Laura AU - Branchi, Igor AU - Tremblay, Marie Ève ID - 9953 JF - Brain, Behavior, and Immunity SN - 0889-1591 TI - Microglial-glucocorticoid receptor depletion alters the response of hippocampal microglia and neurons in a chronic unpredictable mild stress paradigm in female mice VL - 97 ER - TY - JOUR AB - Composite materials offer numerous advantages in a wide range of applications, including thermoelectrics. Here, semiconductor–metal composites are produced by just blending nanoparticles of a sulfide semiconductor obtained in aqueous solution and at room temperature with a metallic Cu powder. The obtained blend is annealed in a reducing atmosphere and afterward consolidated into dense polycrystalline pellets through spark plasma sintering (SPS). We observe that, during the annealing process, the presence of metallic copper activates a partial reduction of the PbS, resulting in the formation of PbS–Pb–CuxS composites. The presence of metallic lead during the SPS process habilitates the liquid-phase sintering of the composite. Besides, by comparing the transport properties of PbS, the PbS–Pb–CuxS composites, and PbS–CuxS composites obtained by blending PbS and CuxS nanoparticles, we demonstrate that the presence of metallic lead decisively contributes to a strong increase of the charge carrier concentration through spillover of charge carriers enabled by the low work function of lead. The increase in charge carrier concentration translates into much higher electrical conductivities and moderately lower Seebeck coefficients. These properties translate into power factors up to 2.1 mW m–1 K–2 at ambient temperature, well above those of PbS and PbS + CuxS. Additionally, the presence of multiple phases in the final composite results in a notable decrease in the lattice thermal conductivity. Overall, the introduction of metallic copper in the initial blend results in a significant improvement of the thermoelectric performance of PbS, reaching a dimensionless thermoelectric figure of merit ZT = 1.1 at 750 K, which represents about a 400% increase over bare PbS. Besides, an average ZTave = 0.72 in the temperature range 320–773 K is demonstrated. AU - Li, Mengyao AU - Liu, Yu AU - Zhang, Yu AU - Han, Xu AU - Xiao, Ke AU - Nabahat, Mehran AU - Arbiol, Jordi AU - Llorca, Jordi AU - Ibáñez, Maria AU - Cabot, Andreu ID - 10327 IS - 43 JF - ACS Applied Materials and Interfaces KW - CuxS KW - PbS KW - energy conversion KW - nanocomposite KW - nanoparticle KW - solution synthesis KW - thermoelectric SN - 1944-8244 TI - PbS–Pb–CuxS composites for thermoelectric application VL - 13 ER - TY - JOUR AB - Cu2–xS has become one of the most promising thermoelectric materials for application in the middle-high temperature range. Its advantages include the abundance, low cost, and safety of its elements and a high performance at relatively elevated temperatures. However, stability issues limit its operation current and temperature, thus calling for the optimization of the material performance in the middle temperature range. Here, we present a synthetic protocol for large scale production of covellite CuS nanoparticles at ambient temperature and atmosphere, and using water as a solvent. The crystal phase and stoichiometry of the particles are afterward tuned through an annealing process at a moderate temperature under inert or reducing atmosphere. While annealing under argon results in Cu1.8S nanopowder with a rhombohedral crystal phase, annealing in an atmosphere containing hydrogen leads to tetragonal Cu1.96S. High temperature X-ray diffraction analysis shows the material annealed in argon to transform to the cubic phase at ca. 400 K, while the material annealed in the presence of hydrogen undergoes two phase transitions, first to hexagonal and then to the cubic structure. The annealing atmosphere, temperature, and time allow adjustment of the density of copper vacancies and thus tuning of the charge carrier concentration and material transport properties. In this direction, the material annealed under Ar is characterized by higher electrical conductivities but lower Seebeck coefficients than the material annealed in the presence of hydrogen. By optimizing the charge carrier concentration through the annealing time, Cu2–xS with record figures of merit in the middle temperature range, up to 1.41 at 710 K, is obtained. We finally demonstrate that this strategy, based on a low-cost and scalable solution synthesis process, is also suitable for the production of high performance Cu2–xS layers using high throughput and cost-effective printing technologies. AU - Li, Mengyao AU - Liu, Yu AU - Zhang, Yu AU - Han, Xu AU - Zhang, Ting AU - Zuo, Yong AU - Xie, Chenyang AU - Xiao, Ke AU - Arbiol, Jordi AU - Llorca, Jordi AU - Ibáñez, Maria AU - Liu, Junfeng AU - Cabot, Andreu ID - 9235 IS - 3 JF - ACS Nano KW - General Engineering KW - General Physics and Astronomy KW - General Materials Science SN - 1936-0851 TI - Effect of the annealing atmosphere on crystal phase and thermoelectric properties of copper sulfide VL - 15 ER - TY - JOUR AB - Two common representations of close packings of identical spheres consisting of hexagonal layers, called Barlow stackings, appear abundantly in minerals and metals. These motifs, however, occupy an identical portion of space and bear identical first-order topological signatures as measured by persistent homology. Here we present a novel method based on k-fold covers that unambiguously distinguishes between these patterns. Moreover, our approach provides topological evidence that the FCC motif is the more stable of the two in the context of evolving experimental sphere packings during the transition from disordered to an ordered state. We conclude that our approach can be generalised to distinguish between various Barlow stackings manifested in minerals and metals. AU - Osang, Georg F AU - Edelsbrunner, Herbert AU - Saadatfar, Mohammad ID - 10204 IS - 40 JF - Soft Matter SN - 1744-683X TI - Topological signatures and stability of hexagonal close packing and Barlow stackings VL - 17 ER - TY - CONF AB - We firstly introduce the self-assembled growth of highly uniform Ge quantum wires with controllable position, distance and length on patterned Si (001) substrates. We then present the electrically tunable strong spin-orbit coupling, the first Ge hole spin qubit and ultrafast operation of hole spin qubit in the Ge/Si quantum wires. AU - Gao, Fei AU - Zhang, Jie Yin AU - Wang, Jian Huan AU - Ming, Ming AU - Wang, Tina AU - Zhang, Jian Jun AU - Watzinger, Hannes AU - Kukucka, Josip AU - Vukušić, Lada AU - Katsaros, Georgios AU - Wang, Ke AU - Xu, Gang AU - Li, Hai Ou AU - Guo, Guo Ping ID - 9464 SN - 9781728181769 T2 - 2021 5th IEEE Electron Devices Technology and Manufacturing Conference, EDTM 2021 TI - Ge/Si quantum wires for quantum computing ER - TY - CONF AB - Given a finite set A ⊂ ℝ^d, let Cov_{r,k} denote the set of all points within distance r to at least k points of A. Allowing r and k to vary, we obtain a 2-parameter family of spaces that grow larger when r increases or k decreases, called the multicover bifiltration. Motivated by the problem of computing the homology of this bifiltration, we introduce two closely related combinatorial bifiltrations, one polyhedral and the other simplicial, which are both topologically equivalent to the multicover bifiltration and far smaller than a Čech-based model considered in prior work of Sheehy. Our polyhedral construction is a bifiltration of the rhomboid tiling of Edelsbrunner and Osang, and can be efficiently computed using a variant of an algorithm given by these authors as well. Using an implementation for dimension 2 and 3, we provide experimental results. Our simplicial construction is useful for understanding the polyhedral construction and proving its correctness. AU - Corbet, René AU - Kerber, Michael AU - Lesnick, Michael AU - Osang, Georg F ID - 9605 SN - 18688969 T2 - Leibniz International Proceedings in Informatics TI - Computing the multicover bifiltration VL - 189 ER - TY - CONF AB - Isomanifolds are the generalization of isosurfaces to arbitrary dimension and codimension, i.e. submanifolds of ℝ^d defined as the zero set of some multivariate multivalued smooth function f: ℝ^d → ℝ^{d-n}, where n is the intrinsic dimension of the manifold. A natural way to approximate a smooth isomanifold M is to consider its Piecewise-Linear (PL) approximation M̂ based on a triangulation 𝒯 of the ambient space ℝ^d. In this paper, we describe a simple algorithm to trace isomanifolds from a given starting point. The algorithm works for arbitrary dimensions n and d, and any precision D. Our main result is that, when f (or M) has bounded complexity, the complexity of the algorithm is polynomial in d and δ = 1/D (and unavoidably exponential in n). Since it is known that for δ = Ω (d^{2.5}), M̂ is O(D²)-close and isotopic to M, our algorithm produces a faithful PL-approximation of isomanifolds of bounded complexity in time polynomial in d. Combining this algorithm with dimensionality reduction techniques, the dependency on d in the size of M̂ can be completely removed with high probability. We also show that the algorithm can handle isomanifolds with boundary and, more generally, isostratifolds. The algorithm for isomanifolds with boundary has been implemented and experimental results are reported, showing that it is practical and can handle cases that are far ahead of the state-of-the-art. AU - Boissonnat, Jean-Daniel AU - Kachanovich, Siargey AU - Wintraecken, Mathijs ID - 9441 SN - 1868-8969 T2 - 37th International Symposium on Computational Geometry (SoCG 2021) TI - Tracing isomanifolds in Rd in time polynomial in d using Coxeter-Freudenthal-Kuhn triangulations VL - 189 ER - TY - JOUR AB - We consider the core algorithmic problems related to verification of systems with respect to three classical quantitative properties, namely, the mean-payoff, the ratio, and the minimum initial credit for energy property. The algorithmic problem given a graph and a quantitative property asks to compute the optimal value (the infimum value over all traces) from every node of the graph. We consider graphs with bounded treewidth—a class that contains the control flow graphs of most programs. Let n denote the number of nodes of a graph, m the number of edges (for bounded treewidth 𝑚=𝑂(𝑛)) and W the largest absolute value of the weights. Our main theoretical results are as follows. First, for the minimum initial credit problem we show that (1) for general graphs the problem can be solved in 𝑂(𝑛2⋅𝑚) time and the associated decision problem in 𝑂(𝑛⋅𝑚) time, improving the previous known 𝑂(𝑛3⋅𝑚⋅log(𝑛⋅𝑊)) and 𝑂(𝑛2⋅𝑚) bounds, respectively; and (2) for bounded treewidth graphs we present an algorithm that requires 𝑂(𝑛⋅log𝑛) time. Second, for bounded treewidth graphs we present an algorithm that approximates the mean-payoff value within a factor of 1+𝜖 in time 𝑂(𝑛⋅log(𝑛/𝜖)) as compared to the classical exact algorithms on general graphs that require quadratic time. Third, for the ratio property we present an algorithm that for bounded treewidth graphs works in time 𝑂(𝑛⋅log(|𝑎⋅𝑏|))=𝑂(𝑛⋅log(𝑛⋅𝑊)), when the output is 𝑎𝑏, as compared to the previously best known algorithm on general graphs with running time 𝑂(𝑛2⋅log(𝑛⋅𝑊)). We have implemented some of our algorithms and show that they present a significant speedup on standard benchmarks. AU - Chatterjee, Krishnendu AU - Ibsen-Jensen, Rasmus AU - Pavlogiannis, Andreas ID - 9393 JF - Formal Methods in System Design SN - 0925-9856 TI - Faster algorithms for quantitative verification in bounded treewidth graphs VL - 57 ER - TY - CONF AB - In the multiway cut problem we are given a weighted undirected graph G=(V,E) and a set T⊆V of k terminals. The goal is to find a minimum weight set of edges E′⊆E with the property that by removing E′ from G all the terminals become disconnected. In this paper we present a simple local search approximation algorithm for the multiway cut problem with approximation ratio 2−2k . We present an experimental evaluation of the performance of our local search algorithm and show that it greatly outperforms the isolation heuristic of Dalhaus et al. and it has similar performance as the much more complex algorithms of Calinescu et al., Sharma and Vondrak, and Buchbinder et al. which have the currently best known approximation ratios for this problem. AU - Bloch-Hansen, Andrew AU - Samei, Nasim AU - Solis-Oba, Roberto ID - 9227 SN - 0302-9743 T2 - Conference on Algorithms and Discrete Applied Mathematics TI - Experimental evaluation of a local search approximation algorithm for the multiway cut problem VL - 12601 ER - TY - JOUR AB - The paper introduces an inertial extragradient subgradient method with self-adaptive step sizes for solving equilibrium problems in real Hilbert spaces. Weak convergence of the proposed method is obtained under the condition that the bifunction is pseudomonotone and Lipchitz continuous. Linear convergence is also given when the bifunction is strongly pseudomonotone and Lipchitz continuous. Numerical implementations and comparisons with other related inertial methods are given using test problems including a real-world application to Nash–Cournot oligopolistic electricity market equilibrium model. AU - Shehu, Yekini AU - Iyiola, Olaniyi S. AU - Thong, Duong Viet AU - Van, Nguyen Thi Cam ID - 8817 IS - 2 JF - Mathematical Methods of Operations Research SN - 1432-2994 TI - An inertial subgradient extragradient algorithm extended to pseudomonotone equilibrium problems VL - 93 ER - TY - JOUR AB - We consider inertial iteration methods for Fermat–Weber location problem and primal–dual three-operator splitting in real Hilbert spaces. To do these, we first obtain weak convergence analysis and nonasymptotic O(1/n) convergence rate of the inertial Krasnoselskii–Mann iteration for fixed point of nonexpansive operators in infinite dimensional real Hilbert spaces under some seemingly easy to implement conditions on the iterative parameters. One of our contributions is that the convergence analysis and rate of convergence results are obtained using conditions which appear not complicated and restrictive as assumed in other previous related results in the literature. We then show that Fermat–Weber location problem and primal–dual three-operator splitting are special cases of fixed point problem of nonexpansive mapping and consequently obtain the convergence analysis of inertial iteration methods for Fermat–Weber location problem and primal–dual three-operator splitting in real Hilbert spaces. Some numerical implementations are drawn from primal–dual three-operator splitting to support the theoretical analysis. AU - Iyiola, Olaniyi S. AU - Shehu, Yekini ID - 9315 IS - 2 JF - Results in Mathematics SN - 1422-6383 TI - New convergence results for inertial Krasnoselskii–Mann iterations in Hilbert spaces with applications VL - 76 ER - TY - JOUR AB - In this paper, we propose a new iterative method with alternated inertial step for solving split common null point problem in real Hilbert spaces. We obtain weak convergence of the proposed iterative algorithm. Furthermore, we introduce the notion of bounded linear regularity property for the split common null point problem and obtain the linear convergence property for the new algorithm under some mild assumptions. Finally, we provide some numerical examples to demonstrate the performance and efficiency of the proposed method. AU - Ogbuisi, Ferdinard U. AU - Shehu, Yekini AU - Yao, Jen Chih ID - 9365 JF - Optimization SN - 0233-1934 TI - Convergence analysis of new inertial method for the split common null point problem ER - TY - JOUR AB - The early development of many organisms involves the folding of cell monolayers, but this behaviour is difficult to reproduce in vitro; therefore, both mechanistic causes and effects of local curvature remain unclear. Here we study epithelial cell monolayers on corrugated hydrogels engineered into wavy patterns, examining how concave and convex curvatures affect cellular and nuclear shape. We find that substrate curvature affects monolayer thickness, which is larger in valleys than crests. We show that this feature generically arises in a vertex model, leading to the hypothesis that cells may sense curvature by modifying the thickness of the tissue. We find that local curvature also affects nuclear morphology and positioning, which we explain by extending the vertex model to take into account membrane–nucleus interactions, encoding thickness modulation in changes to nuclear deformation and position. We propose that curvature governs the spatial distribution of yes-associated proteins via nuclear shape and density changes. We show that curvature also induces significant variations in lamins, chromatin condensation and cell proliferation rate in folded epithelial tissues. Together, this work identifies active cell mechanics and nuclear mechanoadaptation as the key players of the mechanistic regulation of epithelia to substrate curvature. AU - Luciano, Marine AU - Xue, Shi-lei AU - De Vos, Winnok H. AU - Redondo-Morata, Lorena AU - Surin, Mathieu AU - Lafont, Frank AU - Hannezo, Edouard B AU - Gabriele, Sylvain ID - 10365 IS - 12 JF - Nature Physics SN - 1745-2473 TI - Cell monolayers sense curvature by exploiting active mechanics and nuclear mechanoadaptation VL - 17 ER - TY - JOUR AB - In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field. AU - Klionsky, Daniel J. AU - Abdel-Aziz, Amal Kamal AU - Abdelfatah, Sara AU - Abdellatif, Mahmoud AU - Abdoli, Asghar AU - Abel, Steffen AU - Abeliovich, Hagai AU - Abildgaard, Marie H. AU - Abudu, Yakubu Princely AU - Acevedo-Arozena, Abraham AU - Adamopoulos, Iannis E. AU - Adeli, Khosrow AU - Adolph, Timon E. AU - Adornetto, Annagrazia AU - Aflaki, Elma AU - Agam, Galila AU - Agarwal, Anupam AU - Aggarwal, Bharat B. AU - Agnello, Maria AU - Agostinis, Patrizia AU - Agrewala, Javed N. AU - Agrotis, Alexander AU - Aguilar, Patricia V. AU - Ahmad, S. Tariq AU - Ahmed, Zubair M. AU - Ahumada-Castro, Ulises AU - Aits, Sonja AU - Aizawa, Shu AU - Akkoc, Yunus AU - Akoumianaki, Tonia AU - Akpinar, Hafize Aysin AU - Al-Abd, Ahmed M. AU - Al-Akra, Lina AU - Al-Gharaibeh, Abeer AU - Alaoui-Jamali, Moulay A. AU - Alberti, Simon AU - Alcocer-Gómez, Elísabet AU - Alessandri, Cristiano AU - Ali, Muhammad AU - Alim Al-Bari, M. Abdul AU - Aliwaini, Saeb AU - Alizadeh, Javad AU - Almacellas, Eugènia AU - Almasan, Alexandru AU - Alonso, Alicia AU - Alonso, Guillermo D. AU - Altan-Bonnet, Nihal AU - Altieri, Dario C. AU - Álvarez, Élida M.C. AU - Alves, Sara AU - Alves Da Costa, Cristine AU - Alzaharna, Mazen M. AU - Amadio, Marialaura AU - Amantini, Consuelo AU - Amaral, Cristina AU - Ambrosio, Susanna AU - Amer, Amal O. AU - Ammanathan, Veena AU - An, Zhenyi AU - Andersen, Stig U. AU - Andrabi, Shaida A. AU - Andrade-Silva, Magaiver AU - Andres, Allen M. AU - Angelini, Sabrina AU - Ann, David AU - Anozie, Uche C. AU - Ansari, Mohammad Y. AU - Antas, Pedro AU - Antebi, Adam AU - Antón, Zuriñe AU - Anwar, Tahira AU - Apetoh, Lionel AU - Apostolova, Nadezda AU - Araki, Toshiyuki AU - Araki, Yasuhiro AU - Arasaki, Kohei AU - Araújo, Wagner L. AU - Araya, Jun AU - Arden, Catherine AU - Arévalo, Maria Angeles AU - Arguelles, Sandro AU - Arias, Esperanza AU - Arikkath, Jyothi AU - Arimoto, Hirokazu AU - Ariosa, Aileen R. AU - Armstrong-James, Darius AU - Arnauné-Pelloquin, Laetitia AU - Aroca, Angeles AU - Arroyo, Daniela S. AU - Arsov, Ivica AU - Artero, Rubén AU - Asaro, Dalia Maria Lucia AU - Aschner, Michael AU - Ashrafizadeh, Milad AU - Ashur-Fabian, Osnat AU - Atanasov, Atanas G. AU - Au, Alicia K. AU - Auberger, Patrick AU - Auner, Holger W. AU - Aurelian, Laure AU - Autelli, Riccardo AU - Avagliano, Laura AU - Ávalos, Yenniffer AU - Aveic, Sanja AU - Aveleira, Célia Alexandra AU - Avin-Wittenberg, Tamar AU - Aydin, Yucel AU - Ayton, Scott AU - Ayyadevara, Srinivas AU - Azzopardi, Maria AU - Baba, Misuzu AU - Backer, Jonathan M. AU - Backues, Steven K. AU - Bae, Dong Hun AU - Bae, Ok Nam AU - Bae, Soo Han AU - Baehrecke, Eric H. AU - Baek, Ahruem AU - Baek, Seung Hoon AU - Baek, Sung Hee AU - Bagetta, Giacinto AU - Bagniewska-Zadworna, Agnieszka AU - Bai, Hua AU - Bai, Jie AU - Bai, Xiyuan AU - Bai, Yidong AU - Bairagi, Nandadulal AU - Baksi, Shounak AU - Balbi, Teresa AU - Baldari, Cosima T. AU - Balduini, Walter AU - Ballabio, Andrea AU - Ballester, Maria AU - Balazadeh, Salma AU - Balzan, Rena AU - Bandopadhyay, Rina AU - Banerjee, Sreeparna AU - Banerjee, Sulagna AU - Bánréti, Ágnes AU - Bao, Yan AU - Baptista, Mauricio S. AU - Baracca, Alessandra AU - Barbati, Cristiana AU - Bargiela, Ariadna AU - Barilà, Daniela AU - Barlow, Peter G. AU - Barmada, Sami J. AU - Barreiro, Esther AU - Barreto, George E. AU - Bartek, Jiri AU - Bartel, Bonnie AU - Bartolome, Alberto AU - Barve, Gaurav R. AU - Basagoudanavar, Suresh H. AU - Bassham, Diane C. AU - Bast, Robert C. AU - Basu, Alakananda AU - Batoko, Henri AU - Batten, Isabella AU - Baulieu, Etienne E. AU - Baumgarner, Bradley L. AU - Bayry, Jagadeesh AU - Beale, Rupert AU - Beau, Isabelle AU - Beaumatin, Florian AU - Bechara, Luiz R.G. AU - Beck, George R. AU - Beers, Michael F. AU - Begun, Jakob AU - Behrends, Christian AU - Behrens, Georg M.N. AU - Bei, Roberto AU - Bejarano, Eloy AU - Bel, Shai AU - Behl, Christian AU - Belaid, Amine AU - Belgareh-Touzé, Naïma AU - Bellarosa, Cristina AU - Belleudi, Francesca AU - Belló Pérez, Melissa AU - Bello-Morales, Raquel AU - Beltran, Jackeline Soares De Oliveira AU - Beltran, Sebastián AU - Benbrook, Doris Mangiaracina AU - Bendorius, Mykolas AU - Benitez, Bruno A. AU - Benito-Cuesta, Irene AU - Bensalem, Julien AU - Berchtold, Martin W. AU - Berezowska, Sabina AU - Bergamaschi, Daniele AU - Bergami, Matteo AU - Bergmann, Andreas AU - Berliocchi, Laura AU - Berlioz-Torrent, Clarisse AU - Bernard, Amélie AU - Berthoux, Lionel AU - Besirli, Cagri G. AU - Besteiro, Sebastien AU - Betin, Virginie M. AU - Beyaert, Rudi AU - Bezbradica, Jelena S. AU - Bhaskar, Kiran AU - Bhatia-Kissova, Ingrid AU - Bhattacharya, Resham AU - Bhattacharya, Sujoy AU - Bhattacharyya, Shalmoli AU - Bhuiyan, Md Shenuarin AU - Bhutia, Sujit Kumar AU - Bi, Lanrong AU - Bi, Xiaolin AU - Biden, Trevor J. AU - Bijian, Krikor AU - Billes, Viktor A. AU - Binart, Nadine AU - Bincoletto, Claudia AU - Birgisdottir, Asa B. AU - Bjorkoy, Geir AU - Blanco, Gonzalo AU - Blas-Garcia, Ana AU - Blasiak, Janusz AU - Blomgran, Robert AU - Blomgren, Klas AU - Blum, Janice S. AU - Boada-Romero, Emilio AU - Boban, Mirta AU - Boesze-Battaglia, Kathleen AU - Boeuf, Philippe AU - Boland, Barry AU - Bomont, Pascale AU - Bonaldo, Paolo AU - Bonam, Srinivasa Reddy AU - Bonfili, Laura AU - Bonifacino, Juan S. AU - Boone, Brian A. AU - Bootman, Martin D. AU - Bordi, Matteo AU - Borner, Christoph AU - Bornhauser, Beat C. AU - Borthakur, Gautam AU - Bosch, Jürgen AU - Bose, Santanu AU - Botana, Luis M. AU - Botas, Juan AU - Boulanger, Chantal M. AU - Boulton, Michael E. AU - Bourdenx, Mathieu AU - Bourgeois, Benjamin AU - Bourke, Nollaig M. AU - Bousquet, Guilhem AU - Boya, Patricia AU - Bozhkov, Peter V. AU - Bozi, Luiz H.M. AU - Bozkurt, Tolga O. AU - Brackney, Doug E. AU - Brandts, Christian H. AU - Braun, Ralf J. AU - Braus, Gerhard H. AU - Bravo-Sagua, Roberto AU - Bravo-San Pedro, José M. AU - Brest, Patrick AU - Bringer, Marie Agnès AU - Briones-Herrera, Alfredo AU - Broaddus, V. Courtney AU - Brodersen, Peter AU - Brodsky, Jeffrey L. AU - Brody, Steven L. AU - Bronson, Paola G. AU - Bronstein, Jeff M. AU - Brown, Carolyn N. AU - Brown, Rhoderick E. AU - Brum, Patricia C. AU - Brumell, John H. AU - Brunetti-Pierri, Nicola AU - Bruno, Daniele AU - Bryson-Richardson, Robert J. AU - Bucci, Cecilia AU - Buchrieser, Carmen AU - Bueno, Marta AU - Buitrago-Molina, Laura Elisa AU - Buraschi, Simone AU - Buch, Shilpa AU - Buchan, J. Ross AU - Buckingham, Erin M. AU - Budak, Hikmet AU - Budini, Mauricio AU - Bultynck, Geert AU - Burada, Florin AU - Burgoyne, Joseph R. AU - Burón, M. Isabel AU - Bustos, Victor AU - Büttner, Sabrina AU - Butturini, Elena AU - Byrd, Aaron AU - Cabas, Isabel AU - Cabrera-Benitez, Sandra AU - Cadwell, Ken AU - Cai, Jingjing AU - Cai, Lu AU - Cai, Qian AU - Cairó, Montserrat AU - Calbet, Jose A. AU - Caldwell, Guy A. AU - Caldwell, Kim A. AU - Call, Jarrod A. AU - Calvani, Riccardo AU - Calvo, Ana C. AU - Calvo-Rubio Barrera, Miguel AU - Camara, Niels O.S. AU - Camonis, Jacques H. AU - Camougrand, Nadine AU - Campanella, Michelangelo AU - Campbell, Edward M. AU - Campbell-Valois, François Xavier AU - Campello, Silvia AU - Campesi, Ilaria AU - Campos, Juliane C. AU - Camuzard, Olivier AU - Cancino, Jorge AU - Candido De Almeida, Danilo AU - Canesi, Laura AU - Caniggia, Isabella AU - Canonico, Barbara AU - Cantí, Carles AU - Cao, Bin AU - Caraglia, Michele AU - Caramés, Beatriz AU - Carchman, Evie H. AU - Cardenal-Muñoz, Elena AU - Cardenas, Cesar AU - Cardenas, Luis AU - Cardoso, Sandra M. AU - Carew, Jennifer S. AU - Carle, Georges F. AU - Carleton, Gillian AU - Carloni, Silvia AU - Carmona-Gutierrez, Didac AU - Carneiro, Leticia A. AU - Carnevali, Oliana AU - Carosi, Julian M. AU - Carra, Serena AU - Carrier, Alice AU - Carrier, Lucie AU - Carroll, Bernadette AU - Carter, A. Brent AU - Carvalho, Andreia Neves AU - Casanova, Magali AU - Casas, Caty AU - Casas, Josefina AU - Cassioli, Chiara AU - Castillo, Eliseo F. AU - Castillo, Karen AU - Castillo-Lluva, Sonia AU - Castoldi, Francesca AU - Castori, Marco AU - Castro, Ariel F. AU - Castro-Caldas, Margarida AU - Castro-Hernandez, Javier AU - Castro-Obregon, Susana AU - Catz, Sergio D. AU - Cavadas, Claudia AU - Cavaliere, Federica AU - Cavallini, Gabriella AU - Cavinato, Maria AU - Cayuela, Maria L. AU - Cebollada Rica, Paula AU - Cecarini, Valentina AU - Cecconi, Francesco AU - Cechowska-Pasko, Marzanna AU - Cenci, Simone AU - Ceperuelo-Mallafré, Victòria AU - Cerqueira, João J. AU - Cerutti, Janete M. AU - Cervia, Davide AU - Cetintas, Vildan Bozok AU - Cetrullo, Silvia AU - Chae, Han Jung AU - Chagin, Andrei S. AU - Chai, Chee Yin AU - Chakrabarti, Gopal AU - Chakrabarti, Oishee AU - Chakraborty, Tapas AU - Chakraborty, Trinad AU - Chami, Mounia AU - Chamilos, Georgios AU - Chan, David W. AU - Chan, Edmond Y.W. AU - Chan, Edward D. AU - Chan, H. Y.Edwin AU - Chan, Helen H. AU - Chan, Hung AU - Chan, Matthew T.V. AU - Chan, Yau Sang AU - Chandra, Partha K. AU - Chang, Chih Peng AU - Chang, Chunmei AU - Chang, Hao Chun AU - Chang, Kai AU - Chao, Jie AU - Chapman, Tracey AU - Charlet-Berguerand, Nicolas AU - Chatterjee, Samrat AU - Chaube, Shail K. AU - Chaudhary, Anu AU - Chauhan, Santosh AU - Chaum, Edward AU - Checler, Frédéric AU - Cheetham, Michael E. AU - Chen, Chang Shi AU - Chen, Guang Chao AU - Chen, Jian Fu AU - Chen, Liam L. AU - Chen, Leilei AU - Chen, Lin AU - Chen, Mingliang AU - Chen, Mu Kuan AU - Chen, Ning AU - Chen, Quan AU - Chen, Ruey Hwa AU - Chen, Shi AU - Chen, Wei AU - Chen, Weiqiang AU - Chen, Xin Ming AU - Chen, Xiong Wen AU - Chen, Xu AU - Chen, Yan AU - Chen, Ye Guang AU - Chen, Yingyu AU - Chen, Yongqiang AU - Chen, Yu Jen AU - Chen, Yue Qin AU - Chen, Zhefan Stephen AU - Chen, Zhi AU - Chen, Zhi Hua AU - Chen, Zhijian J. AU - Chen, Zhixiang AU - Cheng, Hanhua AU - Cheng, Jun AU - Cheng, Shi Yuan AU - Cheng, Wei AU - Cheng, Xiaodong AU - Cheng, Xiu Tang AU - Cheng, Yiyun AU - Cheng, Zhiyong AU - Chen, Zhong AU - Cheong, Heesun AU - Cheong, Jit Kong AU - Chernyak, Boris V. AU - Cherry, Sara AU - Cheung, Chi Fai Randy AU - Cheung, Chun Hei Antonio AU - Cheung, King Ho AU - Chevet, Eric AU - Chi, Richard J. AU - Chiang, Alan Kwok Shing AU - Chiaradonna, Ferdinando AU - Chiarelli, Roberto AU - Chiariello, Mario AU - Chica, Nathalia AU - Chiocca, Susanna AU - Chiong, Mario AU - Chiou, Shih Hwa AU - Chiramel, Abhilash I. AU - Chiurchiù, Valerio AU - Cho, Dong Hyung AU - Choe, Seong Kyu AU - Choi, Augustine M.K. AU - Choi, Mary E. AU - Choudhury, Kamalika Roy AU - Chow, Norman S. AU - Chu, Charleen T. AU - Chua, Jason P. AU - Chua, John Jia En AU - Chung, Hyewon AU - Chung, Kin Pan AU - Chung, Seockhoon AU - Chung, So Hyang AU - Chung, Yuen Li AU - Cianfanelli, Valentina AU - Ciechomska, Iwona A. AU - Cifuentes, Mariana AU - Cinque, Laura AU - Cirak, Sebahattin AU - Cirone, Mara AU - Clague, Michael J. AU - Clarke, Robert AU - Clementi, Emilio AU - Coccia, Eliana M. AU - Codogno, Patrice AU - Cohen, Ehud AU - Cohen, Mickael M. AU - Colasanti, Tania AU - Colasuonno, Fiorella AU - Colbert, Robert A. AU - Colell, Anna AU - Čolić, Miodrag AU - Coll, Nuria S. AU - Collins, Mark O. AU - Colombo, María I. AU - Colón-Ramos, Daniel A. AU - Combaret, Lydie AU - Comincini, Sergio AU - Cominetti, Márcia R. AU - Consiglio, Antonella AU - Conte, Andrea AU - Conti, Fabrizio AU - Contu, Viorica Raluca AU - Cookson, Mark R. AU - Coombs, Kevin M. AU - Coppens, Isabelle AU - Corasaniti, Maria Tiziana AU - Corkery, Dale P. AU - Cordes, Nils AU - Cortese, Katia AU - Costa, Maria Do Carmo AU - Costantino, Sarah AU - Costelli, Paola AU - Coto-Montes, Ana AU - Crack, Peter J. AU - Crespo, Jose L. AU - Criollo, Alfredo AU - Crippa, Valeria AU - Cristofani, Riccardo AU - Csizmadia, Tamas AU - Cuadrado, Antonio AU - Cui, Bing AU - Cui, Jun AU - Cui, Yixian AU - Cui, Yong AU - Culetto, Emmanuel AU - Cumino, Andrea C. AU - Cybulsky, Andrey V. AU - Czaja, Mark J. AU - Czuczwar, Stanislaw J. AU - D’Adamo, Stefania AU - D’Amelio, Marcello AU - D’Arcangelo, Daniela AU - D’Lugos, Andrew C. AU - D’Orazi, Gabriella AU - Da Silva, James A. AU - Dafsari, Hormos Salimi AU - Dagda, Ruben K. AU - Dagdas, Yasin AU - Daglia, Maria AU - Dai, Xiaoxia AU - Dai, Yun AU - Dai, Yuyuan AU - Dal Col, Jessica AU - Dalhaimer, Paul AU - Dalla Valle, Luisa AU - Dallenga, Tobias AU - Dalmasso, Guillaume AU - Damme, Markus AU - Dando, Ilaria AU - Dantuma, Nico P. AU - Darling, April L. AU - Das, Hiranmoy AU - Dasarathy, Srinivasan AU - Dasari, Santosh K. AU - Dash, Srikanta AU - Daumke, Oliver AU - Dauphinee, Adrian N. AU - Davies, Jeffrey S. AU - Dávila, Valeria A. AU - Davis, Roger J. AU - Davis, Tanja AU - Dayalan Naidu, Sharadha AU - De Amicis, Francesca AU - De Bosscher, Karolien AU - De Felice, Francesca AU - De Franceschi, Lucia AU - De Leonibus, Chiara AU - De Mattos Barbosa, Mayara G. AU - De Meyer, Guido R.Y. AU - De Milito, Angelo AU - De Nunzio, Cosimo AU - De Palma, Clara AU - De Santi, Mauro AU - De Virgilio, Claudio AU - De Zio, Daniela AU - Debnath, Jayanta AU - Debosch, Brian J. AU - Decuypere, Jean Paul AU - Deehan, Mark A. AU - Deflorian, Gianluca AU - Degregori, James AU - Dehay, Benjamin AU - Del Rio, Gabriel AU - Delaney, Joe R. AU - Delbridge, Lea M.D. AU - Delorme-Axford, Elizabeth AU - Delpino, M. Victoria AU - Demarchi, Francesca AU - Dembitz, Vilma AU - Demers, Nicholas D. AU - Deng, Hongbin AU - Deng, Zhiqiang AU - Dengjel, Joern AU - Dent, Paul AU - Denton, Donna AU - Depamphilis, Melvin L. AU - Der, Channing J. AU - Deretic, Vojo AU - Descoteaux, Albert AU - Devis, Laura AU - Devkota, Sushil AU - Devuyst, Olivier AU - Dewson, Grant AU - Dharmasivam, Mahendiran AU - Dhiman, Rohan AU - Di Bernardo, Diego AU - Di Cristina, Manlio AU - Di Domenico, Fabio AU - Di Fazio, Pietro AU - Di Fonzo, Alessio AU - Di Guardo, Giovanni AU - Di Guglielmo, Gianni M. AU - Di Leo, Luca AU - Di Malta, Chiara AU - Di Nardo, Alessia AU - Di Rienzo, Martina AU - Di Sano, Federica AU - Diallinas, George AU - Diao, Jiajie AU - Diaz-Araya, Guillermo AU - Díaz-Laviada, Inés AU - Dickinson, Jared M. AU - Diederich, Marc AU - Dieudé, Mélanie AU - Dikic, Ivan AU - Ding, Shiping AU - Ding, Wen Xing AU - Dini, Luciana AU - Dinić, Jelena AU - Dinic, Miroslav AU - Dinkova-Kostova, Albena T. AU - Dionne, Marc S. AU - Distler, Jörg H.W. AU - Diwan, Abhinav AU - Dixon, Ian M.C. AU - Djavaheri-Mergny, Mojgan AU - Dobrinski, Ina AU - Dobrovinskaya, Oxana AU - Dobrowolski, Radek AU - Dobson, Renwick C.J. AU - Đokić, Jelena AU - Dokmeci Emre, Serap AU - Donadelli, Massimo AU - Dong, Bo AU - Dong, Xiaonan AU - Dong, Zhiwu AU - Dorn, Gerald W. AU - Dotsch, Volker AU - Dou, Huan AU - Dou, Juan AU - Dowaidar, Moataz AU - Dridi, Sami AU - Drucker, Liat AU - Du, Ailian AU - Du, Caigan AU - Du, Guangwei AU - Du, Hai Ning AU - Du, Li Lin AU - Du Toit, André AU - Duan, Shao Bin AU - Duan, Xiaoqiong AU - Duarte, Sónia P. AU - Dubrovska, Anna AU - Dunlop, Elaine A. AU - Dupont, Nicolas AU - Durán, Raúl V. AU - Dwarakanath, Bilikere S. AU - Dyshlovoy, Sergey A. AU - Ebrahimi-Fakhari, Darius AU - Eckhart, Leopold AU - Edelstein, Charles L. AU - Efferth, Thomas AU - Eftekharpour, Eftekhar AU - Eichinger, Ludwig AU - Eid, Nabil AU - Eisenberg, Tobias AU - Eissa, N. Tony AU - Eissa, Sanaa AU - Ejarque, Miriam AU - El Andaloussi, Abdeljabar AU - El-Hage, Nazira AU - El-Naggar, Shahenda AU - Eleuteri, Anna Maria AU - El-Shafey, Eman S. AU - Elgendy, Mohamed AU - Eliopoulos, Aristides G. AU - Elizalde, María M. AU - Elks, Philip M. AU - Elsasser, Hans Peter AU - Elsherbiny, Eslam S. AU - Emerling, Brooke M. AU - Emre, N. C.Tolga AU - Eng, Christina H. AU - Engedal, Nikolai AU - Engelbrecht, Anna Mart AU - Engelsen, Agnete S.T. AU - Enserink, Jorrit M. AU - Escalante, Ricardo AU - Esclatine, Audrey AU - Escobar-Henriques, Mafalda AU - Eskelinen, Eeva Liisa AU - Espert, Lucile AU - Eusebio, Makandjou Ola AU - Fabrias, Gemma AU - Fabrizi, Cinzia AU - Facchiano, Antonio AU - Facchiano, Francesco AU - Fadeel, Bengt AU - Fader, Claudio AU - Faesen, Alex C. AU - Fairlie, W. Douglas AU - Falcó, Alberto AU - Falkenburger, Bjorn H. AU - Fan, Daping AU - Fan, Jie AU - Fan, Yanbo AU - Fang, Evandro F. AU - Fang, Yanshan AU - Fang, Yognqi AU - Fanto, Manolis AU - Farfel-Becker, Tamar AU - Faure, Mathias AU - Fazeli, Gholamreza AU - Fedele, Anthony O. AU - Feldman, Arthur M. AU - Feng, Du AU - Feng, Jiachun AU - Feng, Lifeng AU - Feng, Yibin AU - Feng, Yuchen AU - Feng, Wei AU - Fenz Araujo, Thais AU - Ferguson, Thomas A. AU - Fernández, Álvaro F. AU - Fernandez-Checa, Jose C. AU - Fernández-Veledo, Sonia AU - Fernie, Alisdair R. AU - Ferrante, Anthony W. AU - Ferraresi, Alessandra AU - Ferrari, Merari F. AU - Ferreira, Julio C.B. AU - Ferro-Novick, Susan AU - Figueras, Antonio AU - Filadi, Riccardo AU - Filigheddu, Nicoletta AU - Filippi-Chiela, Eduardo AU - Filomeni, Giuseppe AU - Fimia, Gian Maria AU - Fineschi, Vittorio AU - Finetti, Francesca AU - Finkbeiner, Steven AU - Fisher, Edward A. AU - Fisher, Paul B. AU - Flamigni, Flavio AU - Fliesler, Steven J. AU - Flo, Trude H. AU - Florance, Ida AU - Florey, Oliver AU - Florio, Tullio AU - Fodor, Erika AU - Follo, Carlo AU - Fon, Edward A. AU - Forlino, Antonella AU - Fornai, Francesco AU - Fortini, Paola AU - Fracassi, Anna AU - Fraldi, Alessandro AU - Franco, Brunella AU - Franco, Rodrigo AU - Franconi, Flavia AU - Frankel, Lisa B. AU - Friedman, Scott L. AU - Fröhlich, Leopold F. AU - Frühbeck, Gema AU - Fuentes, Jose M. AU - Fujiki, Yukio AU - Fujita, Naonobu AU - Fujiwara, Yuuki AU - Fukuda, Mitsunori AU - Fulda, Simone AU - Furic, Luc AU - Furuya, Norihiko AU - Fusco, Carmela AU - Gack, Michaela U. AU - Gaffke, Lidia AU - Galadari, Sehamuddin AU - Galasso, Alessia AU - Galindo, Maria F. AU - Gallolu Kankanamalage, Sachith AU - Galluzzi, Lorenzo AU - Galy, Vincent AU - Gammoh, Noor AU - Gan, Boyi AU - Ganley, Ian G. AU - Gao, Feng AU - Gao, Hui AU - Gao, Minghui AU - Gao, Ping AU - Gao, Shou Jiang AU - Gao, Wentao AU - Gao, Xiaobo AU - Garcera, Ana AU - Garcia, Maria Noé AU - Garcia, Verónica E. AU - García-Del Portillo, Francisco AU - Garcia-Escudero, Vega AU - Garcia-Garcia, Aracely AU - Garcia-Macia, Marina AU - García-Moreno, Diana AU - Garcia-Ruiz, Carmen AU - García-Sanz, Patricia AU - Garg, Abhishek D. AU - Gargini, Ricardo AU - Garofalo, Tina AU - Garry, Robert F. AU - Gassen, Nils C. AU - Gatica, Damian AU - Ge, Liang AU - Ge, Wanzhong AU - Geiss-Friedlander, Ruth AU - Gelfi, Cecilia AU - Genschik, Pascal AU - Gentle, Ian E. AU - Gerbino, Valeria AU - Gerhardt, Christoph AU - Germain, Kyla AU - Germain, Marc AU - Gewirtz, David A. AU - Ghasemipour Afshar, Elham AU - Ghavami, Saeid AU - Ghigo, Alessandra AU - Ghosh, Manosij AU - Giamas, Georgios AU - Giampietri, Claudia AU - Giatromanolaki, Alexandra AU - Gibson, Gary E. AU - Gibson, Spencer B. AU - Ginet, Vanessa AU - Giniger, Edward AU - Giorgi, Carlotta AU - Girao, Henrique AU - Girardin, Stephen E. AU - Giridharan, Mridhula AU - Giuliano, Sandy AU - Giulivi, Cecilia AU - Giuriato, Sylvie AU - Giustiniani, Julien AU - Gluschko, Alexander AU - Goder, Veit AU - Goginashvili, Alexander AU - Golab, Jakub AU - Goldstone, David C. AU - Golebiewska, Anna AU - Gomes, Luciana R. AU - Gomez, Rodrigo AU - Gómez-Sánchez, Rubén AU - Gomez-Puerto, Maria Catalina AU - Gomez-Sintes, Raquel AU - Gong, Qingqiu AU - Goni, Felix M. AU - González-Gallego, Javier AU - Gonzalez-Hernandez, Tomas AU - Gonzalez-Polo, Rosa A. AU - Gonzalez-Reyes, Jose A. AU - González-Rodríguez, Patricia AU - Goping, Ing Swie AU - Gorbatyuk, Marina S. AU - Gorbunov, Nikolai V. AU - Görgülü, Kıvanç AU - Gorojod, Roxana M. AU - Gorski, Sharon M. AU - Goruppi, Sandro AU - Gotor, Cecilia AU - Gottlieb, Roberta A. AU - Gozes, Illana AU - Gozuacik, Devrim AU - Graef, Martin AU - Gräler, Markus H. AU - Granatiero, Veronica AU - Grasso, Daniel AU - Gray, Joshua P. AU - Green, Douglas R. AU - Greenhough, Alexander AU - Gregory, Stephen L. AU - Griffin, Edward F. AU - Grinstaff, Mark W. AU - Gros, Frederic AU - Grose, Charles AU - Gross, Angelina S. AU - Gruber, Florian AU - Grumati, Paolo AU - Grune, Tilman AU - Gu, Xueyan AU - Guan, Jun Lin AU - Guardia, Carlos M. AU - Guda, Kishore AU - Guerra, Flora AU - Guerri, Consuelo AU - Guha, Prasun AU - Guillén, Carlos AU - Gujar, Shashi AU - Gukovskaya, Anna AU - Gukovsky, Ilya AU - Gunst, Jan AU - Günther, Andreas AU - Guntur, Anyonya R. AU - Guo, Chuanyong AU - Guo, Chun AU - Guo, Hongqing AU - Guo, Lian Wang AU - Guo, Ming AU - Gupta, Pawan AU - Gupta, Shashi Kumar AU - Gupta, Swapnil AU - Gupta, Veer Bala AU - Gupta, Vivek AU - Gustafsson, Asa B. AU - Gutterman, David D. AU - H.B, Ranjitha AU - Haapasalo, Annakaisa AU - Haber, James E. AU - Hać, Aleksandra AU - Hadano, Shinji AU - Hafrén, Anders J. AU - Haidar, Mansour AU - Hall, Belinda S. AU - Halldén, Gunnel AU - Hamacher-Brady, Anne AU - Hamann, Andrea AU - Hamasaki, Maho AU - Han, Weidong AU - Hansen, Malene AU - Hanson, Phyllis I. . AU - Hao, Zijian AU - Harada, Masaru AU - Harhaji-Trajkovic, Ljubica AU - Hariharan, Nirmala AU - Haroon, Nigil AU - Harris, James AU - Hasegawa, Takafumi AU - Hasima Nagoor, Noor AU - Haspel, Jeffrey A. AU - Haucke, Volker AU - Hawkins, Wayne D. AU - Hay, Bruce A. AU - Haynes, Cole M. AU - Hayrabedyan, Soren B. AU - Hays, Thomas S. AU - He, Congcong AU - He, Qin AU - He, Rong Rong AU - He, You Wen AU - He, Yu Ying AU - Heakal, Yasser AU - Heberle, Alexander M. AU - Hejtmancik, J. Fielding AU - Helgason, Gudmundur Vignir AU - Henkel, Vanessa AU - Herb, Marc AU - Hergovich, Alexander AU - Herman-Antosiewicz, Anna AU - Hernández, Agustín AU - Hernandez, Carlos AU - Hernandez-Diaz, Sergio AU - Hernandez-Gea, Virginia AU - Herpin, Amaury AU - Herreros, Judit AU - Hervás, Javier H. AU - Hesselson, Daniel AU - Hetz, Claudio AU - Heussler, Volker T. AU - Higuchi, Yujiro AU - Hilfiker, Sabine AU - Hill, Joseph A. AU - Hlavacek, William S. AU - Ho, Emmanuel A. AU - Ho, Idy H.T. AU - Ho, Philip Wing Lok AU - Ho, Shu Leong AU - Ho, Wan Yun AU - Hobbs, G. Aaron AU - Hochstrasser, Mark AU - Hoet, Peter H.M. AU - Hofius, Daniel AU - Hofman, Paul AU - Höhn, Annika AU - Holmberg, Carina I. AU - Hombrebueno, Jose R. AU - Yi-Ren Hong, Chang Won Hong AU - Hooper, Lora V. AU - Hoppe, Thorsten AU - Horos, Rastislav AU - Hoshida, Yujin AU - Hsin, I. Lun AU - Hsu, Hsin Yun AU - Hu, Bing AU - Hu, Dong AU - Hu, Li Fang AU - Hu, Ming Chang AU - Hu, Ronggui AU - Hu, Wei AU - Hu, Yu Chen AU - Hu, Zhuo Wei AU - Hua, Fang AU - Hua, Jinlian AU - Hua, Yingqi AU - Huan, Chongmin AU - Huang, Canhua AU - Huang, Chuanshu AU - Huang, Chuanxin AU - Huang, Chunling AU - Huang, Haishan AU - Huang, Kun AU - Huang, Michael L.H. AU - Huang, Rui AU - Huang, Shan AU - Huang, Tianzhi AU - Huang, Xing AU - Huang, Yuxiang Jack AU - Huber, Tobias B. AU - Hubert, Virginie AU - Hubner, Christian A. AU - Hughes, Stephanie M. AU - Hughes, William E. AU - Humbert, Magali AU - Hummer, Gerhard AU - Hurley, James H. AU - Hussain, Sabah AU - Hussain, Salik AU - Hussey, Patrick J. AU - Hutabarat, Martina AU - Hwang, Hui Yun AU - Hwang, Seungmin AU - Ieni, Antonio AU - Ikeda, Fumiyo AU - Imagawa, Yusuke AU - Imai, Yuzuru AU - Imbriano, Carol AU - Imoto, Masaya AU - Inman, Denise M. AU - Inoki, Ken AU - Iovanna, Juan AU - Iozzo, Renato V. AU - Ippolito, Giuseppe AU - Irazoqui, Javier E. AU - Iribarren, Pablo AU - Ishaq, Mohd AU - Ishikawa, Makoto AU - Ishimwe, Nestor AU - Isidoro, Ciro AU - Ismail, Nahed AU - Issazadeh-Navikas, Shohreh AU - Itakura, Eisuke AU - Ito, Daisuke AU - Ivankovic, Davor AU - Ivanova, Saška AU - Iyer, Anand Krishnan V. AU - Izquierdo, José M. AU - Izumi, Masanori AU - Jäättelä, Marja AU - Jabir, Majid Sakhi AU - Jackson, William T. AU - Jacobo-Herrera, Nadia AU - Jacomin, Anne Claire AU - Jacquin, Elise AU - Jadiya, Pooja AU - Jaeschke, Hartmut AU - Jagannath, Chinnaswamy AU - Jakobi, Arjen J. AU - Jakobsson, Johan AU - Janji, Bassam AU - Jansen-Dürr, Pidder AU - Jansson, Patric J. AU - Jantsch, Jonathan AU - Januszewski, Sławomir AU - Jassey, Alagie AU - Jean, Steve AU - Jeltsch-David, Hélène AU - Jendelova, Pavla AU - Jenny, Andreas AU - Jensen, Thomas E. AU - Jessen, Niels AU - Jewell, Jenna L. AU - Ji, Jing AU - Jia, Lijun AU - Jia, Rui AU - Jiang, Liwen AU - Jiang, Qing AU - Jiang, Richeng AU - Jiang, Teng AU - Jiang, Xuejun AU - Jiang, Yu AU - Jimenez-Sanchez, Maria AU - Jin, Eun Jung AU - Jin, Fengyan AU - Jin, Hongchuan AU - Jin, Li AU - Jin, Luqi AU - Jin, Meiyan AU - Jin, Si AU - Jo, Eun Kyeong AU - Joffre, Carine AU - Johansen, Terje AU - Johnson, Gail V.W. AU - Johnston, Simon A. AU - Jokitalo, Eija AU - Jolly, Mohit Kumar AU - Joosten, Leo A.B. AU - Jordan, Joaquin AU - Joseph, Bertrand AU - Ju, Dianwen AU - Ju, Jeong Sun AU - Ju, Jingfang AU - Juárez, Esmeralda AU - Judith, Delphine AU - Juhász, Gábor AU - Jun, Youngsoo AU - Jung, Chang Hwa AU - Jung, Sung Chul AU - Jung, Yong Keun AU - Jungbluth, Heinz AU - Jungverdorben, Johannes AU - Just, Steffen AU - Kaarniranta, Kai AU - Kaasik, Allen AU - Kabuta, Tomohiro AU - Kaganovich, Daniel AU - Kahana, Alon AU - Kain, Renate AU - Kajimura, Shinjo AU - Kalamvoki, Maria AU - Kalia, Manjula AU - Kalinowski, Danuta S. AU - Kaludercic, Nina AU - Kalvari, Ioanna AU - Kaminska, Joanna AU - Kaminskyy, Vitaliy O. AU - Kanamori, Hiromitsu AU - Kanasaki, Keizo AU - Kang, Chanhee AU - Kang, Rui AU - Kang, Sang Sun AU - Kaniyappan, Senthilvelrajan AU - Kanki, Tomotake AU - Kanneganti, Thirumala Devi AU - Kanthasamy, Anumantha G. AU - Kanthasamy, Arthi AU - Kantorow, Marc AU - Kapuy, Orsolya AU - Karamouzis, Michalis V. AU - Karim, Md Razaul AU - Karmakar, Parimal AU - Katare, Rajesh G. AU - Kato, Masaru AU - Kaufmann, Stefan H.E. AU - Kauppinen, Anu AU - Kaushal, Gur P. AU - Kaushik, Susmita AU - Kawasaki, Kiyoshi AU - Kazan, Kemal AU - Ke, Po Yuan AU - Keating, Damien J. AU - Keber, Ursula AU - Kehrl, John H. AU - Keller, Kate E. AU - Keller, Christian W. AU - Kemper, Jongsook Kim AU - Kenific, Candia M. AU - Kepp, Oliver AU - Kermorgant, Stephanie AU - Kern, Andreas AU - Ketteler, Robin AU - Keulers, Tom G. AU - Khalfin, Boris AU - Khalil, Hany AU - Khambu, Bilon AU - Khan, Shahid Y. AU - Khandelwal, Vinoth Kumar Megraj AU - Khandia, Rekha AU - Kho, Widuri AU - Khobrekar, Noopur V. AU - Khuansuwan, Sataree AU - Khundadze, Mukhran AU - Killackey, Samuel A. AU - Kim, Dasol AU - Kim, Deok Ryong AU - Kim, Do Hyung AU - Kim, Dong Eun AU - Kim, Eun Young AU - Kim, Eun Kyoung AU - Kim, Hak Rim AU - Kim, Hee Sik AU - Hyung-Ryong Kim, Unknown AU - Kim, Jeong Hun AU - Kim, Jin Kyung AU - Kim, Jin Hoi AU - Kim, Joungmok AU - Kim, Ju Hwan AU - Kim, Keun Il AU - Kim, Peter K. AU - Kim, Seong Jun AU - Kimball, Scot R. AU - Kimchi, Adi AU - Kimmelman, Alec C. AU - Kimura, Tomonori AU - King, Matthew A. AU - Kinghorn, Kerri J. AU - Kinsey, Conan G. AU - Kirkin, Vladimir AU - Kirshenbaum, Lorrie A. AU - Kiselev, Sergey L. AU - Kishi, Shuji AU - Kitamoto, Katsuhiko AU - Kitaoka, Yasushi AU - Kitazato, Kaio AU - Kitsis, Richard N. AU - Kittler, Josef T. AU - Kjaerulff, Ole AU - Klein, Peter S. AU - Klopstock, Thomas AU - Klucken, Jochen AU - Knævelsrud, Helene AU - Knorr, Roland L. AU - Ko, Ben C.B. AU - Ko, Fred AU - Ko, Jiunn Liang AU - Kobayashi, Hotaka AU - Kobayashi, Satoru AU - Koch, Ina AU - Koch, Jan C. AU - Koenig, Ulrich AU - Kögel, Donat AU - Koh, Young Ho AU - Koike, Masato AU - Kohlwein, Sepp D. AU - Kocaturk, Nur M. AU - Komatsu, Masaaki AU - König, Jeannette AU - Kono, Toru AU - Kopp, Benjamin T. AU - Korcsmaros, Tamas AU - Korkmaz, Gözde AU - Korolchuk, Viktor I. AU - Korsnes, Mónica Suárez AU - Koskela, Ali AU - Kota, Janaiah AU - Kotake, Yaichiro AU - Kotler, Monica L. AU - Kou, Yanjun AU - Koukourakis, Michael I. AU - Koustas, Evangelos AU - Kovacs, Attila L. AU - Kovács, Tibor AU - Koya, Daisuke AU - Kozako, Tomohiro AU - Kraft, Claudine AU - Krainc, Dimitri AU - Krämer, Helmut AU - Krasnodembskaya, Anna D. AU - Kretz-Remy, Carole AU - Kroemer, Guido AU - Ktistakis, Nicholas T. AU - Kuchitsu, Kazuyuki AU - Kuenen, Sabine AU - Kuerschner, Lars AU - Kukar, Thomas AU - Kumar, Ajay AU - Kumar, Ashok AU - Kumar, Deepak AU - Kumar, Dhiraj AU - Kumar, Sharad AU - Kume, Shinji AU - Kumsta, Caroline AU - Kundu, Chanakya N. AU - Kundu, Mondira AU - Kunnumakkara, Ajaikumar B. AU - Kurgan, Lukasz AU - Kutateladze, Tatiana G. AU - Kutlu, Ozlem AU - Kwak, Seong Ae AU - Kwon, Ho Jeong AU - Kwon, Taeg Kyu AU - Kwon, Yong Tae AU - Kyrmizi, Irene AU - La Spada, Albert AU - Labonté, Patrick AU - Ladoire, Sylvain AU - Laface, Ilaria AU - Lafont, Frank AU - Lagace, Diane C. AU - Lahiri, Vikramjit AU - Lai, Zhibing AU - Laird, Angela S. AU - Lakkaraju, Aparna AU - Lamark, Trond AU - Lan, Sheng Hui AU - Landajuela, Ane AU - Lane, Darius J.R. AU - Lane, Jon D. AU - Lang, Charles H. AU - Lange, Carsten AU - Langel, Ülo AU - Langer, Rupert AU - Lapaquette, Pierre AU - Laporte, Jocelyn AU - Larusso, Nicholas F. AU - Lastres-Becker, Isabel AU - Lau, Wilson Chun Yu AU - Laurie, Gordon W. AU - Lavandero, Sergio AU - Law, Betty Yuen Kwan AU - Law, Helen Ka Wai AU - Layfield, Rob AU - Le, Weidong AU - Le Stunff, Herve AU - Leary, Alexandre Y. AU - Lebrun, Jean Jacques AU - Leck, Lionel Y.W. AU - Leduc-Gaudet, Jean Philippe AU - Lee, Changwook AU - Lee, Chung Pei AU - Lee, Da Hye AU - Lee, Edward B. AU - Lee, Erinna F. AU - Lee, Gyun Min AU - Lee, He Jin AU - Lee, Heung Kyu AU - Lee, Jae Man AU - Lee, Jason S. AU - Lee, Jin A. AU - Lee, Joo Yong AU - Lee, Jun Hee AU - Lee, Michael AU - Lee, Min Goo AU - Lee, Min Jae AU - Lee, Myung Shik AU - Lee, Sang Yoon AU - Lee, Seung Jae AU - Lee, Stella Y. AU - Lee, Sung Bae AU - Lee, Won Hee AU - Lee, Ying Ray AU - Lee, Yong Ho AU - Lee, Youngil AU - Lefebvre, Christophe AU - Legouis, Renaud AU - Lei, Yu L. AU - Lei, Yuchen AU - Leikin, Sergey AU - Leitinger, Gerd AU - Lemus, Leticia AU - Leng, Shuilong AU - Lenoir, Olivia AU - Lenz, Guido AU - Lenz, Heinz Josef AU - Lenzi, Paola AU - León, Yolanda AU - Leopoldino, Andréia M. AU - Leschczyk, Christoph AU - Leskelä, Stina AU - Letellier, Elisabeth AU - Leung, Chi Ting AU - Leung, Po Sing AU - Leventhal, Jeremy S. AU - Levine, Beth AU - Lewis, Patrick A. AU - Ley, Klaus AU - Li, Bin AU - Li, Da Qiang AU - Li, Jianming AU - Li, Jing AU - Li, Jiong AU - Li, Ke AU - Li, Liwu AU - Li, Mei AU - Li, Min AU - Li, Min AU - Li, Ming AU - Li, Mingchuan AU - Li, Pin Lan AU - Li, Ming Qing AU - Li, Qing AU - Li, Sheng AU - Li, Tiangang AU - Li, Wei AU - Li, Wenming AU - Li, Xue AU - Li, Yi Ping AU - Li, Yuan AU - Li, Zhiqiang AU - Li, Zhiyong AU - Li, Zhiyuan AU - Lian, Jiqin AU - Liang, Chengyu AU - Liang, Qiangrong AU - Liang, Weicheng AU - Liang, Yongheng AU - Liang, Yong Tian AU - Liao, Guanghong AU - Liao, Lujian AU - Liao, Mingzhi AU - Liao, Yung Feng AU - Librizzi, Mariangela AU - Lie, Pearl P.Y. AU - Lilly, Mary A. AU - Lim, Hyunjung J. AU - Lima, Thania R.R. AU - Limana, Federica AU - Lin, Chao AU - Lin, Chih Wen AU - Lin, Dar Shong AU - Lin, Fu Cheng AU - Lin, Jiandie D. AU - Lin, Kurt M. AU - Lin, Kwang Huei AU - Lin, Liang Tzung AU - Lin, Pei Hui AU - Lin, Qiong AU - Lin, Shaofeng AU - Lin, Su Ju AU - Lin, Wenyu AU - Lin, Xueying AU - Lin, Yao Xin AU - Lin, Yee Shin AU - Linden, Rafael AU - Lindner, Paula AU - Ling, Shuo Chien AU - Lingor, Paul AU - Linnemann, Amelia K. AU - Liou, Yih Cherng AU - Lipinski, Marta M. AU - Lipovšek, Saška AU - Lira, Vitor A. AU - Lisiak, Natalia AU - Liton, Paloma B. AU - Liu, Chao AU - Liu, Ching Hsuan AU - Liu, Chun Feng AU - Liu, Cui Hua AU - Liu, Fang AU - Liu, Hao AU - Liu, Hsiao Sheng AU - Liu, Hua Feng AU - Liu, Huifang AU - Liu, Jia AU - Liu, Jing AU - Liu, Julia AU - Liu, Leyuan AU - Liu, Longhua AU - Liu, Meilian AU - Liu, Qin AU - Liu, Wei AU - Liu, Wende AU - Liu, Xiao Hong AU - Liu, Xiaodong AU - Liu, Xingguo AU - Liu, Xu AU - Liu, Xuedong AU - Liu, Yanfen AU - Liu, Yang AU - Liu, Yang AU - Liu, Yueyang AU - Liu, Yule AU - Livingston, J. Andrew AU - Lizard, Gerard AU - Lizcano, Jose M. AU - Ljubojevic-Holzer, Senka AU - Lleonart, Matilde E. AU - Llobet-Navàs, David AU - Llorente, Alicia AU - Lo, Chih Hung AU - Lobato-Márquez, Damián AU - Long, Qi AU - Long, Yun Chau AU - Loos, Ben AU - Loos, Julia A. AU - López, Manuela G. AU - López-Doménech, Guillermo AU - López-Guerrero, José Antonio AU - López-Jiménez, Ana T. AU - López-Pérez, Óscar AU - López-Valero, Israel AU - Lorenowicz, Magdalena J. AU - Lorente, Mar AU - Lorincz, Peter AU - Lossi, Laura AU - Lotersztajn, Sophie AU - Lovat, Penny E. AU - Lovell, Jonathan F. AU - Lovy, Alenka AU - Lőw, Péter AU - Lu, Guang AU - Lu, Haocheng AU - Lu, Jia Hong AU - Lu, Jin Jian AU - Lu, Mengji AU - Lu, Shuyan AU - Luciani, Alessandro AU - Lucocq, John M. AU - Ludovico, Paula AU - Luftig, Micah A. AU - Luhr, Morten AU - Luis-Ravelo, Diego AU - Lum, Julian J. AU - Luna-Dulcey, Liany AU - Lund, Anders H. AU - Lund, Viktor K. AU - Lünemann, Jan D. AU - Lüningschrör, Patrick AU - Luo, Honglin AU - Luo, Rongcan AU - Luo, Shouqing AU - Luo, Zhi AU - Luparello, Claudio AU - Lüscher, Bernhard AU - Luu, Luan AU - Lyakhovich, Alex AU - Lyamzaev, Konstantin G. AU - Lystad, Alf Håkon AU - Lytvynchuk, Lyubomyr AU - Ma, Alvin C. AU - Ma, Changle AU - Ma, Mengxiao AU - Ma, Ning Fang AU - Ma, Quan Hong AU - Ma, Xinliang AU - Ma, Yueyun AU - Ma, Zhenyi AU - Macdougald, Ormond A. AU - Macian, Fernando AU - Macintosh, Gustavo C. AU - Mackeigan, Jeffrey P. AU - Macleod, Kay F. AU - Maday, Sandra AU - Madeo, Frank AU - Madesh, Muniswamy AU - Madl, Tobias AU - Madrigal-Matute, Julio AU - Maeda, Akiko AU - Maejima, Yasuhiro AU - Magarinos, Marta AU - Mahavadi, Poornima AU - Maiani, Emiliano AU - Maiese, Kenneth AU - Maiti, Panchanan AU - Maiuri, Maria Chiara AU - Majello, Barbara AU - Major, Michael B. AU - Makareeva, Elena AU - Malik, Fayaz AU - Mallilankaraman, Karthik AU - Malorni, Walter AU - Maloyan, Alina AU - Mammadova, Najiba AU - Man, Gene Chi Wai AU - Manai, Federico AU - Mancias, Joseph D. AU - Mandelkow, Eva Maria AU - Mandell, Michael A. AU - Manfredi, Angelo A. AU - Manjili, Masoud H. AU - Manjithaya, Ravi AU - Manque, Patricio AU - Manshian, Bella B. AU - Manzano, Raquel AU - Manzoni, Claudia AU - Mao, Kai AU - Marchese, Cinzia AU - Marchetti, Sandrine AU - Marconi, Anna Maria AU - Marcucci, Fabrizio AU - Mardente, Stefania AU - Mareninova, Olga A. AU - Margeta, Marta AU - Mari, Muriel AU - Marinelli, Sara AU - Marinelli, Oliviero AU - Mariño, Guillermo AU - Mariotto, Sofia AU - Marshall, Richard S. AU - Marten, Mark R. AU - Martens, Sascha AU - Martin, Alexandre P.J. AU - Martin, Katie R. AU - Martin, Sara AU - Martin, Shaun AU - Martín-Segura, Adrián AU - Martín-Acebes, Miguel A. AU - Martin-Burriel, Inmaculada AU - Martin-Rincon, Marcos AU - Martin-Sanz, Paloma AU - Martina, José A. AU - Martinet, Wim AU - Martinez, Aitor AU - Martinez, Ana AU - Martinez, Jennifer AU - Martinez Velazquez, Moises AU - Martinez-Lopez, Nuria AU - Martinez-Vicente, Marta AU - Martins, Daniel O. AU - Martins, Joilson O. AU - Martins, Waleska K. AU - Martins-Marques, Tania AU - Marzetti, Emanuele AU - Masaldan, Shashank AU - Masclaux-Daubresse, Celine AU - Mashek, Douglas G. AU - Massa, Valentina AU - Massieu, Lourdes AU - Masson, Glenn R. AU - Masuelli, Laura AU - Masyuk, Anatoliy I. AU - Masyuk, Tetyana V. AU - Matarrese, Paola AU - Matheu, Ander AU - Matoba, Satoaki AU - Matsuzaki, Sachiko AU - Mattar, Pamela AU - Matte, Alessandro AU - Mattoscio, Domenico AU - Mauriz, José L. AU - Mauthe, Mario AU - Mauvezin, Caroline AU - Maverakis, Emanual AU - Maycotte, Paola AU - Mayer, Johanna AU - Mazzoccoli, Gianluigi AU - Mazzoni, Cristina AU - Mazzulli, Joseph R. AU - Mccarty, Nami AU - Mcdonald, Christine AU - Mcgill, Mitchell R. AU - Mckenna, Sharon L. AU - Mclaughlin, Beth Ann AU - Mcloughlin, Fionn AU - Mcniven, Mark A. AU - Mcwilliams, Thomas G. AU - Mechta-Grigoriou, Fatima AU - Medeiros, Tania Catarina AU - Medina, Diego L. AU - Megeney, Lynn A. AU - Megyeri, Klara AU - Mehrpour, Maryam AU - Mehta, Jawahar L. AU - Meijer, Alfred J. AU - Meijer, Annemarie H. AU - Mejlvang, Jakob AU - Meléndez, Alicia AU - Melk, Annette AU - Memisoglu, Gonen AU - Mendes, Alexandrina F. AU - Meng, Delong AU - Meng, Fei AU - Meng, Tian AU - Menna-Barreto, Rubem AU - Menon, Manoj B. AU - Mercer, Carol AU - Mercier, Anne E. AU - Mergny, Jean Louis AU - Merighi, Adalberto AU - Merkley, Seth D. AU - Merla, Giuseppe AU - Meske, Volker AU - Mestre, Ana Cecilia AU - Metur, Shree Padma AU - Meyer, Christian AU - Meyer, Hemmo AU - Mi, Wenyi AU - Mialet-Perez, Jeanne AU - Miao, Junying AU - Micale, Lucia AU - Miki, Yasuo AU - Milan, Enrico AU - Milczarek, Małgorzata AU - Miller, Dana L. AU - Miller, Samuel I. AU - Miller, Silke AU - Millward, Steven W. AU - Milosevic, Ira AU - Minina, Elena A. AU - Mirzaei, Hamed AU - Mirzaei, Hamid Reza AU - Mirzaei, Mehdi AU - Mishra, Amit AU - Mishra, Nandita AU - Mishra, Paras Kumar AU - Misirkic Marjanovic, Maja AU - Misasi, Roberta AU - Misra, Amit AU - Misso, Gabriella AU - Mitchell, Claire AU - Mitou, Geraldine AU - Miura, Tetsuji AU - Miyamoto, Shigeki AU - Miyazaki, Makoto AU - Miyazaki, Mitsunori AU - Miyazaki, Taiga AU - Miyazawa, Keisuke AU - Mizushima, Noboru AU - Mogensen, Trine H. AU - Mograbi, Baharia AU - Mohammadinejad, Reza AU - Mohamud, Yasir AU - Mohanty, Abhishek AU - Mohapatra, Sipra AU - Möhlmann, Torsten AU - Mohmmed, Asif AU - Moles, Anna AU - Moley, Kelle H. AU - Molinari, Maurizio AU - Mollace, Vincenzo AU - Møller, Andreas Buch AU - Mollereau, Bertrand AU - Mollinedo, Faustino AU - Montagna, Costanza AU - Monteiro, Mervyn J. AU - Montella, Andrea AU - Montes, L. Ruth AU - Montico, Barbara AU - Mony, Vinod K. AU - Monzio Compagnoni, Giacomo AU - Moore, Michael N. AU - Moosavi, Mohammad A. AU - Mora, Ana L. AU - Mora, Marina AU - Morales-Alamo, David AU - Moratalla, Rosario AU - Moreira, Paula I. AU - Morelli, Elena AU - Moreno, Sandra AU - Moreno-Blas, Daniel AU - Moresi, Viviana AU - Morga, Benjamin AU - Morgan, Alwena H. AU - Morin, Fabrice AU - Morishita, Hideaki AU - Moritz, Orson L. AU - Moriyama, Mariko AU - Moriyasu, Yuji AU - Morleo, Manuela AU - Morselli, Eugenia AU - Moruno-Manchon, Jose F. AU - Moscat, Jorge AU - Mostowy, Serge AU - Motori, Elisa AU - Moura, Andrea Felinto AU - Moustaid-Moussa, Naima AU - Mrakovcic, Maria AU - Muciño-Hernández, Gabriel AU - Mukherjee, Anupam AU - Mukhopadhyay, Subhadip AU - Mulcahy Levy, Jean M. AU - Mulero, Victoriano AU - Muller, Sylviane AU - Münch, Christian AU - Munjal, Ashok AU - Munoz-Canoves, Pura AU - Muñoz-Galdeano, Teresa AU - Münz, Christian AU - Murakawa, Tomokazu AU - Muratori, Claudia AU - Murphy, Brona M. AU - Murphy, J. Patrick AU - Murthy, Aditya AU - Myöhänen, Timo T. AU - Mysorekar, Indira U. AU - Mytych, Jennifer AU - Nabavi, Seyed Mohammad AU - Nabissi, Massimo AU - Nagy, Péter AU - Nah, Jihoon AU - Nahimana, Aimable AU - Nakagawa, Ichiro AU - Nakamura, Ken AU - Nakatogawa, Hitoshi AU - Nandi, Shyam S. AU - Nanjundan, Meera AU - Nanni, Monica AU - Napolitano, Gennaro AU - Nardacci, Roberta AU - Narita, Masashi AU - Nassif, Melissa AU - Nathan, Ilana AU - Natsumeda, Manabu AU - Naude, Ryno J. AU - Naumann, Christin AU - Naveiras, Olaia AU - Navid, Fatemeh AU - Nawrocki, Steffan T. AU - Nazarko, Taras Y. AU - Nazio, Francesca AU - Negoita, Florentina AU - Neill, Thomas AU - Neisch, Amanda L. AU - Neri, Luca M. AU - Netea, Mihai G. AU - Neubert, Patrick AU - Neufeld, Thomas P. AU - Neumann, Dietbert AU - Neutzner, Albert AU - Newton, Phillip T. AU - Ney, Paul A. AU - Nezis, Ioannis P. AU - Ng, Charlene C.W. AU - Ng, Tzi Bun AU - Nguyen, Hang T.T. AU - Nguyen, Long T. AU - Ni, Hong Min AU - Ní Cheallaigh, Clíona AU - Ni, Zhenhong AU - Nicolao, M. Celeste AU - Nicoli, Francesco AU - Nieto-Diaz, Manuel AU - Nilsson, Per AU - Ning, Shunbin AU - Niranjan, Rituraj AU - Nishimune, Hiroshi AU - Niso-Santano, Mireia AU - Nixon, Ralph A. AU - Nobili, Annalisa AU - Nobrega, Clevio AU - Noda, Takeshi AU - Nogueira-Recalde, Uxía AU - Nolan, Trevor M. AU - Nombela, Ivan AU - Novak, Ivana AU - Novoa, Beatriz AU - Nozawa, Takashi AU - Nukina, Nobuyuki AU - Nussbaum-Krammer, Carmen AU - Nylandsted, Jesper AU - O’Donovan, Tracey R. AU - O’Leary, Seónadh M. AU - O’Rourke, Eyleen J. AU - O’Sullivan, Mary P. AU - O’Sullivan, Timothy E. AU - Oddo, Salvatore AU - Oehme, Ina AU - Ogawa, Michinaga AU - Ogier-Denis, Eric AU - Ogmundsdottir, Margret H. AU - Ogretmen, Besim AU - Oh, Goo Taeg AU - Oh, Seon Hee AU - Oh, Young J. AU - Ohama, Takashi AU - Ohashi, Yohei AU - Ohmuraya, Masaki AU - Oikonomou, Vasileios AU - Ojha, Rani AU - Okamoto, Koji AU - Okazawa, Hitoshi AU - Oku, Masahide AU - Oliván, Sara AU - Oliveira, Jorge M.A. AU - Ollmann, Michael AU - Olzmann, James A. AU - Omari, Shakib AU - Omary, M. Bishr AU - Önal, Gizem AU - Ondrej, Martin AU - Ong, Sang Bing AU - Ong, Sang Ging AU - Onnis, Anna AU - Orellana, Juan A. AU - Orellana-Muñoz, Sara AU - Ortega-Villaizan, Maria Del Mar AU - Ortiz-Gonzalez, Xilma R. AU - Ortona, Elena AU - Osiewacz, Heinz D. AU - Osman, Abdel Hamid K. AU - Osta, Rosario AU - Otegui, Marisa S. AU - Otsu, Kinya AU - Ott, Christiane AU - Ottobrini, Luisa AU - Ou, Jing Hsiung James AU - Outeiro, Tiago F. AU - Oynebraten, Inger AU - Ozturk, Melek AU - Pagès, Gilles AU - Pahari, Susanta AU - Pajares, Marta AU - Pajvani, Utpal B. AU - Pal, Rituraj AU - Paladino, Simona AU - Pallet, Nicolas AU - Palmieri, Michela AU - Palmisano, Giuseppe AU - Palumbo, Camilla AU - Pampaloni, Francesco AU - Pan, Lifeng AU - Pan, Qingjun AU - Pan, Wenliang AU - Pan, Xin AU - Panasyuk, Ganna AU - Pandey, Rahul AU - Pandey, Udai B. AU - Pandya, Vrajesh AU - Paneni, Francesco AU - Pang, Shirley Y. AU - Panzarini, Elisa AU - Papademetrio, Daniela L. AU - Papaleo, Elena AU - Papinski, Daniel AU - Papp, Diana AU - Park, Eun Chan AU - Park, Hwan Tae AU - Park, Ji Man AU - Park, Jong In AU - Park, Joon Tae AU - Park, Junsoo AU - Park, Sang Chul AU - Park, Sang Youel AU - Parola, Abraham H. AU - Parys, Jan B. AU - Pasquier, Adrien AU - Pasquier, Benoit AU - Passos, João F. AU - Pastore, Nunzia AU - Patel, Hemal H. AU - Patschan, Daniel AU - Pattingre, Sophie AU - Pedraza-Alva, Gustavo AU - Pedraza-Chaverri, Jose AU - Pedrozo, Zully AU - Pei, Gang AU - Pei, Jianming AU - Peled-Zehavi, Hadas AU - Pellegrini, Joaquín M. AU - Pelletier, Joffrey AU - Peñalva, Miguel A. AU - Peng, Di AU - Peng, Ying AU - Penna, Fabio AU - Pennuto, Maria AU - Pentimalli, Francesca AU - Pereira, Cláudia M.F. AU - Pereira, Gustavo J.S. AU - Pereira, Lilian C. AU - Pereira De Almeida, Luis AU - Perera, Nirma D. AU - Pérez-Lara, Ángel AU - Perez-Oliva, Ana B. AU - Pérez-Pérez, María Esther AU - Periyasamy, Palsamy AU - Perl, Andras AU - Perrotta, Cristiana AU - Perrotta, Ida AU - Pestell, Richard G. AU - Petersen, Morten AU - Petrache, Irina AU - Petrovski, Goran AU - Pfirrmann, Thorsten AU - Pfister, Astrid S. AU - Philips, Jennifer A. AU - Pi, Huifeng AU - Picca, Anna AU - Pickrell, Alicia M. AU - Picot, Sandy AU - Pierantoni, Giovanna M. AU - Pierdominici, Marina AU - Pierre, Philippe AU - Pierrefite-Carle, Valérie AU - Pierzynowska, Karolina AU - Pietrocola, Federico AU - Pietruczuk, Miroslawa AU - Pignata, Claudio AU - Pimentel-Muiños, Felipe X. AU - Pinar, Mario AU - Pinheiro, Roberta O. AU - Pinkas-Kramarski, Ronit AU - Pinton, Paolo AU - Pircs, Karolina AU - Piya, Sujan AU - Pizzo, Paola AU - Plantinga, Theo S. AU - Platta, Harald W. AU - Plaza-Zabala, Ainhoa AU - Plomann, Markus AU - Plotnikov, Egor Y. AU - Plun-Favreau, Helene AU - Pluta, Ryszard AU - Pocock, Roger AU - Pöggeler, Stefanie AU - Pohl, Christian AU - Poirot, Marc AU - Poletti, Angelo AU - Ponpuak, Marisa AU - Popelka, Hana AU - Popova, Blagovesta AU - Porta, Helena AU - Porte Alcon, Soledad AU - Portilla-Fernandez, Eliana AU - Post, Martin AU - Potts, Malia B. AU - Poulton, Joanna AU - Powers, Ted AU - Prahlad, Veena AU - Prajsnar, Tomasz K. AU - Praticò, Domenico AU - Prencipe, Rosaria AU - Priault, Muriel AU - Proikas-Cezanne, Tassula AU - Promponas, Vasilis J. AU - Proud, Christopher G. AU - Puertollano, Rosa AU - Puglielli, Luigi AU - Pulinilkunnil, Thomas AU - Puri, Deepika AU - Puri, Rajat AU - Puyal, Julien AU - Qi, Xiaopeng AU - Qi, Yongmei AU - Qian, Wenbin AU - Qiang, Lei AU - Qiu, Yu AU - Quadrilatero, Joe AU - Quarleri, Jorge AU - Raben, Nina AU - Rabinowich, Hannah AU - Ragona, Debora AU - Ragusa, Michael J. AU - Rahimi, Nader AU - Rahmati, Marveh AU - Raia, Valeria AU - Raimundo, Nuno AU - Rajasekaran, Namakkal Soorappan AU - Ramachandra Rao, Sriganesh AU - Rami, Abdelhaq AU - Ramírez-Pardo, Ignacio AU - Ramsden, David B. AU - Randow, Felix AU - Rangarajan, Pundi N. AU - Ranieri, Danilo AU - Rao, Hai AU - Rao, Lang AU - Rao, Rekha AU - Rathore, Sumit AU - Ratnayaka, J. Arjuna AU - Ratovitski, Edward A. AU - Ravanan, Palaniyandi AU - Ravegnini, Gloria AU - Ray, Swapan K. AU - Razani, Babak AU - Rebecca, Vito AU - Reggiori, Fulvio AU - Régnier-Vigouroux, Anne AU - Reichert, Andreas S. AU - Reigada, David AU - Reiling, Jan H. AU - Rein, Theo AU - Reipert, Siegfried AU - Rekha, Rokeya Sultana AU - Ren, Hongmei AU - Ren, Jun AU - Ren, Weichao AU - Renault, Tristan AU - Renga, Giorgia AU - Reue, Karen AU - Rewitz, Kim AU - Ribeiro De Andrade Ramos, Bruna AU - Riazuddin, S. Amer AU - Ribeiro-Rodrigues, Teresa M. AU - Ricci, Jean Ehrland AU - Ricci, Romeo AU - Riccio, Victoria AU - Richardson, Des R. AU - Rikihisa, Yasuko AU - Risbud, Makarand V. AU - Risueño, Ruth M. AU - Ritis, Konstantinos AU - Rizza, Salvatore AU - Rizzuto, Rosario AU - Roberts, Helen C. AU - Roberts, Luke D. AU - Robinson, Katherine J. AU - Roccheri, Maria Carmela AU - Rocchi, Stephane AU - Rodney, George G. AU - Rodrigues, Tiago AU - Rodrigues Silva, Vagner Ramon AU - Rodriguez, Amaia AU - Rodriguez-Barrueco, Ruth AU - Rodriguez-Henche, Nieves AU - Rodriguez-Rocha, Humberto AU - Roelofs, Jeroen AU - Rogers, Robert S. AU - Rogov, Vladimir V. AU - Rojo, Ana I. AU - Rolka, Krzysztof AU - Romanello, Vanina AU - Romani, Luigina AU - Romano, Alessandra AU - Romano, Patricia S. AU - Romeo-Guitart, David AU - Romero, Luis C. AU - Romero, Montserrat AU - Roney, Joseph C. AU - Rongo, Christopher AU - Roperto, Sante AU - Rosenfeldt, Mathias T. AU - Rosenstiel, Philip AU - Rosenwald, Anne G. AU - Roth, Kevin A. AU - Roth, Lynn AU - Roth, Steven AU - Rouschop, Kasper M.A. AU - Roussel, Benoit D. AU - Roux, Sophie AU - Rovere-Querini, Patrizia AU - Roy, Ajit AU - Rozieres, Aurore AU - Ruano, Diego AU - Rubinsztein, David C. AU - Rubtsova, Maria P. AU - Ruckdeschel, Klaus AU - Ruckenstuhl, Christoph AU - Rudolf, Emil AU - Rudolf, Rüdiger AU - Ruggieri, Alessandra AU - Ruparelia, Avnika Ashok AU - Rusmini, Paola AU - Russell, Ryan R. AU - Russo, Gian Luigi AU - Russo, Maria AU - Russo, Rossella AU - Ryabaya, Oxana O. AU - Ryan, Kevin M. AU - Ryu, Kwon Yul AU - Sabater-Arcis, Maria AU - Sachdev, Ulka AU - Sacher, Michael AU - Sachse, Carsten AU - Sadhu, Abhishek AU - Sadoshima, Junichi AU - Safren, Nathaniel AU - Saftig, Paul AU - Sagona, Antonia P. AU - Sahay, Gaurav AU - Sahebkar, Amirhossein AU - Sahin, Mustafa AU - Sahin, Ozgur AU - Sahni, Sumit AU - Saito, Nayuta AU - Saito, Shigeru AU - Saito, Tsunenori AU - Sakai, Ryohei AU - Sakai, Yasuyoshi AU - Sakamaki, Jun Ichi AU - Saksela, Kalle AU - Salazar, Gloria AU - Salazar-Degracia, Anna AU - Salekdeh, Ghasem H. AU - Saluja, Ashok K. AU - Sampaio-Marques, Belém AU - Sanchez, Maria Cecilia AU - Sanchez-Alcazar, Jose A. AU - Sanchez-Vera, Victoria AU - Sancho-Shimizu, Vanessa AU - Sanderson, J. Thomas AU - Sandri, Marco AU - Santaguida, Stefano AU - Santambrogio, Laura AU - Santana, Magda M. AU - Santoni, Giorgio AU - Sanz, Alberto AU - Sanz, Pascual AU - Saran, Shweta AU - Sardiello, Marco AU - Sargeant, Timothy J. AU - Sarin, Apurva AU - Sarkar, Chinmoy AU - Sarkar, Sovan AU - Sarrias, Maria Rosa AU - Sarkar, Surajit AU - Sarmah, Dipanka Tanu AU - Sarparanta, Jaakko AU - Sathyanarayan, Aishwarya AU - Sathyanarayanan, Ranganayaki AU - Scaglione, K. Matthew AU - Scatozza, Francesca AU - Schaefer, Liliana AU - Schafer, Zachary T. AU - Schaible, Ulrich E. AU - Schapira, Anthony H.V. AU - Scharl, Michael AU - Schatzl, Hermann M. AU - Schein, Catherine H. AU - Scheper, Wiep AU - Scheuring, David AU - Schiaffino, Maria Vittoria AU - Schiappacassi, Monica AU - Schindl, Rainer AU - Schlattner, Uwe AU - Schmidt, Oliver AU - Schmitt, Roland AU - Schmidt, Stephen D. AU - Schmitz, Ingo AU - Schmukler, Eran AU - Schneider, Anja AU - Schneider, Bianca E. AU - Schober, Romana AU - Schoijet, Alejandra C. AU - Schott, Micah B. AU - Schramm, Michael AU - Schröder, Bernd AU - Schuh, Kai AU - Schüller, Christoph AU - Schulze, Ryan J. AU - Schürmanns, Lea AU - Schwamborn, Jens C. AU - Schwarten, Melanie AU - Scialo, Filippo AU - Sciarretta, Sebastiano AU - Scott, Melanie J. AU - Scotto, Kathleen W. AU - Scovassi, A. Ivana AU - Scrima, Andrea AU - Scrivo, Aurora AU - Sebastian, David AU - Sebti, Salwa AU - Sedej, Simon AU - Segatori, Laura AU - Segev, Nava AU - Seglen, Per O. AU - Seiliez, Iban AU - Seki, Ekihiro AU - Selleck, Scott B. AU - Sellke, Frank W. AU - Selsby, Joshua T. AU - Sendtner, Michael AU - Senturk, Serif AU - Seranova, Elena AU - Sergi, Consolato AU - Serra-Moreno, Ruth AU - Sesaki, Hiromi AU - Settembre, Carmine AU - Setty, Subba Rao Gangi AU - Sgarbi, Gianluca AU - Sha, Ou AU - Shacka, John J. AU - Shah, Javeed A. AU - Shang, Dantong AU - Shao, Changshun AU - Shao, Feng AU - Sharbati, Soroush AU - Sharkey, Lisa M. AU - Sharma, Dipali AU - Sharma, Gaurav AU - Sharma, Kulbhushan AU - Sharma, Pawan AU - Sharma, Surendra AU - Shen, Han Ming AU - Shen, Hongtao AU - Shen, Jiangang AU - Shen, Ming AU - Shen, Weili AU - Shen, Zheni AU - Sheng, Rui AU - Sheng, Zhi AU - Sheng, Zu Hang AU - Shi, Jianjian AU - Shi, Xiaobing AU - Shi, Ying Hong AU - Shiba-Fukushima, Kahori AU - Shieh, Jeng Jer AU - Shimada, Yohta AU - Shimizu, Shigeomi AU - Shimozawa, Makoto AU - Shintani, Takahiro AU - Shoemaker, Christopher J. AU - Shojaei, Shahla AU - Shoji, Ikuo AU - Shravage, Bhupendra V. AU - Shridhar, Viji AU - Shu, Chih Wen AU - Shu, Hong Bing AU - Shui, Ke AU - Shukla, Arvind K. AU - Shutt, Timothy E. AU - Sica, Valentina AU - Siddiqui, Aleem AU - Sierra, Amanda AU - Sierra-Torre, Virginia AU - Signorelli, Santiago AU - Sil, Payel AU - Silva, Bruno J.De Andrade AU - Silva, Johnatas D. AU - Silva-Pavez, Eduardo AU - Silvente-Poirot, Sandrine AU - Simmonds, Rachel E. AU - Simon, Anna Katharina AU - Simon, Hans Uwe AU - Simons, Matias AU - Singh, Anurag AU - Singh, Lalit P. AU - Singh, Rajat AU - Singh, Shivendra V. AU - Singh, Shrawan K. AU - Singh, Sudha B. AU - Singh, Sunaina AU - Singh, Surinder Pal AU - Sinha, Debasish AU - Sinha, Rohit Anthony AU - Sinha, Sangita AU - Sirko, Agnieszka AU - Sirohi, Kapil AU - Sivridis, Efthimios L. AU - Skendros, Panagiotis AU - Skirycz, Aleksandra AU - Slaninová, Iva AU - Smaili, Soraya S. AU - Smertenko, Andrei AU - Smith, Matthew D. AU - Soenen, Stefaan J. AU - Sohn, Eun Jung AU - Sok, Sophia P.M. AU - Solaini, Giancarlo AU - Soldati, Thierry AU - Soleimanpour, Scott A. AU - Soler, Rosa M. AU - Solovchenko, Alexei AU - Somarelli, Jason A. AU - Sonawane, Avinash AU - Song, Fuyong AU - Song, Hyun Kyu AU - Song, Ju Xian AU - Song, Kunhua AU - Song, Zhiyin AU - Soria, Leandro R. AU - Sorice, Maurizio AU - Soukas, Alexander A. AU - Soukup, Sandra Fausia AU - Sousa, Diana AU - Sousa, Nadia AU - Spagnuolo, Paul A. AU - Spector, Stephen A. AU - Srinivas Bharath, M. M. AU - St. Clair, Daret AU - Stagni, Venturina AU - Staiano, Leopoldo AU - Stalnecker, Clint A. AU - Stankov, Metodi V. AU - Stathopulos, Peter B. AU - Stefan, Katja AU - Stefan, Sven Marcel AU - Stefanis, Leonidas AU - Steffan, Joan S. AU - Steinkasserer, Alexander AU - Stenmark, Harald AU - Sterneckert, Jared AU - Stevens, Craig AU - Stoka, Veronika AU - Storch, Stephan AU - Stork, Björn AU - Strappazzon, Flavie AU - Strohecker, Anne Marie AU - Stupack, Dwayne G. AU - Su, Huanxing AU - Su, Ling Yan AU - Su, Longxiang AU - Suarez-Fontes, Ana M. AU - Subauste, Carlos S. AU - Subbian, Selvakumar AU - Subirada, Paula V. AU - Sudhandiran, Ganapasam AU - Sue, Carolyn M. AU - Sui, Xinbing AU - Summers, Corey AU - Sun, Guangchao AU - Sun, Jun AU - Sun, Kang AU - Sun, Meng Xiang AU - Sun, Qiming AU - Sun, Yi AU - Sun, Zhongjie AU - Sunahara, Karen K.S. AU - Sundberg, Eva AU - Susztak, Katalin AU - Sutovsky, Peter AU - Suzuki, Hidekazu AU - Sweeney, Gary AU - Symons, J. David AU - Sze, Stephen Cho Wing AU - Szewczyk, Nathaniel J. AU - Tabęcka-Łonczynska, Anna AU - Tabolacci, Claudio AU - Tacke, Frank AU - Taegtmeyer, Heinrich AU - Tafani, Marco AU - Tagaya, Mitsuo AU - Tai, Haoran AU - Tait, Stephen W.G. AU - Takahashi, Yoshinori AU - Takats, Szabolcs AU - Talwar, Priti AU - Tam, Chit AU - Tam, Shing Yau AU - Tampellini, Davide AU - Tamura, Atsushi AU - Tan, Chong Teik AU - Tan, Eng King AU - Tan, Ya Qin AU - Tanaka, Masaki AU - Tanaka, Motomasa AU - Tang, Daolin AU - Tang, Jingfeng AU - Tang, Tie Shan AU - Tanida, Isei AU - Tao, Zhipeng AU - Taouis, Mohammed AU - Tatenhorst, Lars AU - Tavernarakis, Nektarios AU - Taylor, Allen AU - Taylor, Gregory A. AU - Taylor, Joan M. AU - Tchetina, Elena AU - Tee, Andrew R. AU - Tegeder, Irmgard AU - Teis, David AU - Teixeira, Natercia AU - Teixeira-Clerc, Fatima AU - Tekirdag, Kumsal A. AU - Tencomnao, Tewin AU - Tenreiro, Sandra AU - Tepikin, Alexei V. AU - Testillano, Pilar S. AU - Tettamanti, Gianluca AU - Tharaux, Pierre Louis AU - Thedieck, Kathrin AU - Thekkinghat, Arvind A. AU - Thellung, Stefano AU - Thinwa, Josephine W. AU - Thirumalaikumar, V. P. AU - Thomas, Sufi Mary AU - Thomes, Paul G. AU - Thorburn, Andrew AU - Thukral, Lipi AU - Thum, Thomas AU - Thumm, Michael AU - Tian, Ling AU - Tichy, Ales AU - Till, Andreas AU - Timmerman, Vincent AU - Titorenko, Vladimir I. AU - Todi, Sokol V. AU - Todorova, Krassimira AU - Toivonen, Janne M. AU - Tomaipitinca, Luana AU - Tomar, Dhanendra AU - Tomas-Zapico, Cristina AU - Tomić, Sergej AU - Tong, Benjamin Chun Kit AU - Tong, Chao AU - Tong, Xin AU - Tooze, Sharon A. AU - Torgersen, Maria L. AU - Torii, Satoru AU - Torres-López, Liliana AU - Torriglia, Alicia AU - Towers, Christina G. AU - Towns, Roberto AU - Toyokuni, Shinya AU - Trajkovic, Vladimir AU - Tramontano, Donatella AU - Tran, Quynh Giao AU - Travassos, Leonardo H. AU - Trelford, Charles B. AU - Tremel, Shirley AU - Trougakos, Ioannis P. AU - Tsao, Betty P. AU - Tschan, Mario P. AU - Tse, Hung Fat AU - Tse, Tak Fu AU - Tsugawa, Hitoshi AU - Tsvetkov, Andrey S. AU - Tumbarello, David A. AU - Tumtas, Yasin AU - Tuñón, María J. AU - Turcotte, Sandra AU - Turk, Boris AU - Turk, Vito AU - Turner, Bradley J. AU - Tuxworth, Richard I. AU - Tyler, Jessica K. AU - Tyutereva, Elena V. AU - Uchiyama, Yasuo AU - Ugun-Klusek, Aslihan AU - Uhlig, Holm H. AU - Ułamek-Kozioł, Marzena AU - Ulasov, Ilya V. AU - Umekawa, Midori AU - Ungermann, Christian AU - Unno, Rei AU - Urbe, Sylvie AU - Uribe-Carretero, Elisabet AU - Üstün, Suayib AU - Uversky, Vladimir N. AU - Vaccari, Thomas AU - Vaccaro, Maria I. AU - Vahsen, Björn F. AU - Vakifahmetoglu-Norberg, Helin AU - Valdor, Rut AU - Valente, Maria J. AU - Valko, Ayelén AU - Vallee, Richard B. AU - Valverde, Angela M. AU - Van Den Berghe, Greet AU - Van Der Veen, Stijn AU - Van Kaer, Luc AU - Van Loosdregt, Jorg AU - Van Wijk, Sjoerd J.L. AU - Vandenberghe, Wim AU - Vanhorebeek, Ilse AU - Vannier-Santos, Marcos A. AU - Vannini, Nicola AU - Vanrell, M. Cristina AU - Vantaggiato, Chiara AU - Varano, Gabriele AU - Varela-Nieto, Isabel AU - Varga, Máté AU - Vasconcelos, M. Helena AU - Vats, Somya AU - Vavvas, Demetrios G. AU - Vega-Naredo, Ignacio AU - Vega-Rubin-De-Celis, Silvia AU - Velasco, Guillermo AU - Velázquez, Ariadna P. AU - Vellai, Tibor AU - Vellenga, Edo AU - Velotti, Francesca AU - Verdier, Mireille AU - Verginis, Panayotis AU - Vergne, Isabelle AU - Verkade, Paul AU - Verma, Manish AU - Verstreken, Patrik AU - Vervliet, Tim AU - Vervoorts, Jörg AU - Vessoni, Alexandre T. AU - Victor, Victor M. AU - Vidal, Michel AU - Vidoni, Chiara AU - Vieira, Otilia V. AU - Vierstra, Richard D. AU - Viganó, Sonia AU - Vihinen, Helena AU - Vijayan, Vinoy AU - Vila, Miquel AU - Vilar, Marçal AU - Villalba, José M. AU - Villalobo, Antonio AU - Villarejo-Zori, Beatriz AU - Villarroya, Francesc AU - Villarroya, Joan AU - Vincent, Olivier AU - Vindis, Cecile AU - Viret, Christophe AU - Viscomi, Maria Teresa AU - Visnjic, Dora AU - Vitale, Ilio AU - Vocadlo, David J. AU - Voitsekhovskaja, Olga V. AU - Volonté, Cinzia AU - Volta, Mattia AU - Vomero, Marta AU - Von Haefen, Clarissa AU - Vooijs, Marc A. AU - Voos, Wolfgang AU - Vucicevic, Ljubica AU - Wade-Martins, Richard AU - Waguri, Satoshi AU - Waite, Kenrick A. AU - Wakatsuki, Shuji AU - Walker, David W. AU - Walker, Mark J. AU - Walker, Simon A. AU - Walter, Jochen AU - Wandosell, Francisco G. AU - Wang, Bo AU - Wang, Chao Yung AU - Wang, Chen AU - Wang, Chenran AU - Wang, Chenwei AU - Wang, Cun Yu AU - Wang, Dong AU - Wang, Fangyang AU - Wang, Feng AU - Wang, Fengming AU - Wang, Guansong AU - Wang, Han AU - Wang, Hao AU - Wang, Hexiang AU - Wang, Hong Gang AU - Wang, Jianrong AU - Wang, Jigang AU - Wang, Jiou AU - Wang, Jundong AU - Wang, Kui AU - Wang, Lianrong AU - Wang, Liming AU - Wang, Maggie Haitian AU - Wang, Meiqing AU - Wang, Nanbu AU - Wang, Pengwei AU - Wang, Peipei AU - Wang, Ping AU - Wang, Ping AU - Wang, Qing Jun AU - Wang, Qing AU - Wang, Qing Kenneth AU - Wang, Qiong A. AU - Wang, Wen Tao AU - Wang, Wuyang AU - Wang, Xinnan AU - Wang, Xuejun AU - Wang, Yan AU - Wang, Yanchang AU - Wang, Yanzhuang AU - Wang, Yen Yun AU - Wang, Yihua AU - Wang, Yipeng AU - Wang, Yu AU - Wang, Yuqi AU - Wang, Zhe AU - Wang, Zhenyu AU - Wang, Zhouguang AU - Warnes, Gary AU - Warnsmann, Verena AU - Watada, Hirotaka AU - Watanabe, Eizo AU - Watchon, Maxinne AU - Wawrzyńska, Anna AU - Weaver, Timothy E. AU - Wegrzyn, Grzegorz AU - Wehman, Ann M. AU - Wei, Huafeng AU - Wei, Lei AU - Wei, Taotao AU - Wei, Yongjie AU - Weiergräber, Oliver H. AU - Weihl, Conrad C. AU - Weindl, Günther AU - Weiskirchen, Ralf AU - Wells, Alan AU - Wen, Runxia H. AU - Wen, Xin AU - Werner, Antonia AU - Weykopf, Beatrice AU - Wheatley, Sally P. AU - Whitton, J. Lindsay AU - Whitworth, Alexander J. AU - Wiktorska, Katarzyna AU - Wildenberg, Manon E. AU - Wileman, Tom AU - Wilkinson, Simon AU - Willbold, Dieter AU - Williams, Brett AU - Williams, Robin S.B. AU - Williams, Roger L. AU - Williamson, Peter R. AU - Wilson, Richard A. AU - Winner, Beate AU - Winsor, Nathaniel J. AU - Witkin, Steven S. AU - Wodrich, Harald AU - Woehlbier, Ute AU - Wollert, Thomas AU - Wong, Esther AU - Wong, Jack Ho AU - Wong, Richard W. AU - Wong, Vincent Kam Wai AU - Wong, W. Wei Lynn AU - Wu, An Guo AU - Wu, Chengbiao AU - Wu, Jian AU - Wu, Junfang AU - Wu, Kenneth K. AU - Wu, Min AU - Wu, Shan Ying AU - Wu, Shengzhou AU - Wu, Shu Yan AU - Wu, Shufang AU - Wu, William K.K. AU - Wu, Xiaohong AU - Wu, Xiaoqing AU - Wu, Yao Wen AU - Wu, Yihua AU - Xavier, Ramnik J. AU - Xia, Hongguang AU - Xia, Lixin AU - Xia, Zhengyuan AU - Xiang, Ge AU - Xiang, Jin AU - Xiang, Mingliang AU - Xiang, Wei AU - Xiao, Bin AU - Xiao, Guozhi AU - Xiao, Hengyi AU - Xiao, Hong Tao AU - Xiao, Jian AU - Xiao, Lan AU - Xiao, Shi AU - Xiao, Yin AU - Xie, Baoming AU - Xie, Chuan Ming AU - Xie, Min AU - Xie, Yuxiang AU - Xie, Zhiping AU - Xie, Zhonglin AU - Xilouri, Maria AU - Xu, Congfeng AU - Xu, En AU - Xu, Haoxing AU - Xu, Jing AU - Xu, Jin Rong AU - Xu, Liang AU - Xu, Wen Wen AU - Xu, Xiulong AU - Xue, Yu AU - Yakhine-Diop, Sokhna M.S. AU - Yamaguchi, Masamitsu AU - Yamaguchi, Osamu AU - Yamamoto, Ai AU - Yamashina, Shunhei AU - Yan, Shengmin AU - Yan, Shian Jang AU - Yan, Zhen AU - Yanagi, Yasuo AU - Yang, Chuanbin AU - Yang, Dun Sheng AU - Yang, Huan AU - Yang, Huang Tian AU - Yang, Hui AU - Yang, Jin Ming AU - Yang, Jing AU - Yang, Jingyu AU - Yang, Ling AU - Yang, Liu AU - Yang, Ming AU - Yang, Pei Ming AU - Yang, Qian AU - Yang, Seungwon AU - Yang, Shu AU - Yang, Shun Fa AU - Yang, Wannian AU - Yang, Wei Yuan AU - Yang, Xiaoyong AU - Yang, Xuesong AU - Yang, Yi AU - Yang, Ying AU - Yao, Honghong AU - Yao, Shenggen AU - Yao, Xiaoqiang AU - Yao, Yong Gang AU - Yao, Yong Ming AU - Yasui, Takahiro AU - Yazdankhah, Meysam AU - Yen, Paul M. AU - Yi, Cong AU - Yin, Xiao Ming AU - Yin, Yanhai AU - Yin, Zhangyuan AU - Yin, Ziyi AU - Ying, Meidan AU - Ying, Zheng AU - Yip, Calvin K. AU - Yiu, Stephanie Pei Tung AU - Yoo, Young H. AU - Yoshida, Kiyotsugu AU - Yoshii, Saori R. AU - Yoshimori, Tamotsu AU - Yousefi, Bahman AU - Yu, Boxuan AU - Yu, Haiyang AU - Yu, Jun AU - Yu, Jun AU - Yu, Li AU - Yu, Ming Lung AU - Yu, Seong Woon AU - Yu, Victor C. AU - Yu, W. Haung AU - Yu, Zhengping AU - Yu, Zhou AU - Yuan, Junying AU - Yuan, Ling Qing AU - Yuan, Shilin AU - Yuan, Shyng Shiou F. AU - Yuan, Yanggang AU - Yuan, Zengqiang AU - Yue, Jianbo AU - Yue, Zhenyu AU - Yun, Jeanho AU - Yung, Raymond L. AU - Zacks, David N. AU - Zaffagnini, Gabriele AU - Zambelli, Vanessa O. AU - Zanella, Isabella AU - Zang, Qun S. AU - Zanivan, Sara AU - Zappavigna, Silvia AU - Zaragoza, Pilar AU - Zarbalis, Konstantinos S. AU - Zarebkohan, Amir AU - Zarrouk, Amira AU - Zeitlin, Scott O. AU - Zeng, Jialiu AU - Zeng, Ju Deng AU - Žerovnik, Eva AU - Zhan, Lixuan AU - Zhang, Bin AU - Zhang, Donna D. AU - Zhang, Hanlin AU - Zhang, Hong AU - Zhang, Hong AU - Zhang, Honghe AU - Zhang, Huafeng AU - Zhang, Huaye AU - Zhang, Hui AU - Zhang, Hui Ling AU - Zhang, Jianbin AU - Zhang, Jianhua AU - Zhang, Jing Pu AU - Zhang, Kalin Y.B. AU - Zhang, Leshuai W. AU - Zhang, Lin AU - Zhang, Lisheng AU - Zhang, Lu AU - Zhang, Luoying AU - Zhang, Menghuan AU - Zhang, Peng AU - Zhang, Sheng AU - Zhang, Wei AU - Zhang, Xiangnan AU - Zhang, Xiao Wei AU - Zhang, Xiaolei AU - Zhang, Xiaoyan AU - Zhang, Xin AU - Zhang, Xinxin AU - Zhang, Xu Dong AU - Zhang, Yang AU - Zhang, Yanjin AU - Zhang, Yi AU - Zhang, Ying Dong AU - Zhang, Yingmei AU - Zhang, Yuan Yuan AU - Zhang, Yuchen AU - Zhang, Zhe AU - Zhang, Zhengguang AU - Zhang, Zhibing AU - Zhang, Zhihai AU - Zhang, Zhiyong AU - Zhang, Zili AU - Zhao, Haobin AU - Zhao, Lei AU - Zhao, Shuang AU - Zhao, Tongbiao AU - Zhao, Xiao Fan AU - Zhao, Ying AU - Zhao, Yongchao AU - Zhao, Yongliang AU - Zhao, Yuting AU - Zheng, Guoping AU - Zheng, Kai AU - Zheng, Ling AU - Zheng, Shizhong AU - Zheng, Xi Long AU - Zheng, Yi AU - Zheng, Zu Guo AU - Zhivotovsky, Boris AU - Zhong, Qing AU - Zhou, Ao AU - Zhou, Ben AU - Zhou, Cefan AU - Zhou, Gang AU - Zhou, Hao AU - Zhou, Hong AU - Zhou, Hongbo AU - Zhou, Jie AU - Zhou, Jing AU - Zhou, Jing AU - Zhou, Jiyong AU - Zhou, Kailiang AU - Zhou, Rongjia AU - Zhou, Xu Jie AU - Zhou, Yanshuang AU - Zhou, Yinghong AU - Zhou, Yubin AU - Zhou, Zheng Yu AU - Zhou, Zhou AU - Zhu, Binglin AU - Zhu, Changlian AU - Zhu, Guo Qing AU - Zhu, Haining AU - Zhu, Hongxin AU - Zhu, Hua AU - Zhu, Wei Guo AU - Zhu, Yanping AU - Zhu, Yushan AU - Zhuang, Haixia AU - Zhuang, Xiaohong AU - Zientara-Rytter, Katarzyna AU - Zimmermann, Christine M. AU - Ziviani, Elena AU - Zoladek, Teresa AU - Zong, Wei Xing AU - Zorov, Dmitry B. AU - Zorzano, Antonio AU - Zou, Weiping AU - Zou, Zhen AU - Zou, Zhengzhi AU - Zuryn, Steven AU - Zwerschke, Werner AU - Brand-Saberi, Beate AU - Dong, X. Charlie AU - Kenchappa, Chandra Shekar AU - Li, Zuguo AU - Lin, Yong AU - Oshima, Shigeru AU - Rong, Yueguang AU - Sluimer, Judith C. AU - Stallings, Christina L. AU - Tong, Chun Kit ID - 9298 IS - 1 JF - Autophagy SN - 1554-8627 TI - Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition) VL - 17 ER - TY - JOUR AB - We develop a version of Ekedahl’s geometric sieve for integral quadratic forms of rank at least five. As one ranges over the zeros of such quadratic forms, we use the sieve to compute the density of coprime values of polynomials, and furthermore, to address a question about local solubility in families of varieties parameterised by the zeros. AU - Browning, Timothy D AU - Heath-Brown, Roger ID - 8742 IS - 1 JF - Forum Mathematicum SN - 0933-7741 TI - The geometric sieve for quadrics VL - 33 ER - TY - THES AB - Many security definitions come in two flavors: a stronger “adaptive” flavor, where the adversary can arbitrarily make various choices during the course of the attack, and a weaker “selective” flavor where the adversary must commit to some or all of their choices a-priori. For example, in the context of identity-based encryption, selective security requires the adversary to decide on the identity of the attacked party at the very beginning of the game whereas adaptive security allows the attacker to first see the master public key and some secret keys before making this choice. Often, it appears to be much easier to achieve selective security than it is to achieve adaptive security. A series of several recent works shows how to cleverly achieve adaptive security in several such scenarios including generalized selective decryption [Pan07][FJP15], constrained PRFs [FKPR14], and Yao’s garbled circuits [JW16]. Although the above works expressed vague intuition that they share a common technique, the connection was never made precise. In this work we present a new framework (published at Crypto ’17 [JKK+17a]) that connects all of these works and allows us to present them in a unified and simplified fashion. Having the framework in place, we show how to achieve adaptive security for proxy re-encryption schemes (published at PKC ’19 [FKKP19]) and provide the first adaptive security proofs for continuous group key agreement protocols (published at S&P ’21 [KPW+21]). Questioning optimality of our framework, we then show that currently used proof techniques cannot lead to significantly better security guarantees for "graph-building" games (published at TCC ’21 [KKPW21a]). These games cover generalized selective decryption, as well as the security of prominent constructions for constrained PRFs, continuous group key agreement, and proxy re-encryption. Finally, we revisit the adaptive security of Yao’s garbled circuits and extend the analysis of Jafargholi and Wichs in two directions: While they prove adaptive security only for a modified construction with increased online complexity, we provide the first positive results for the original construction by Yao (published at TCC ’21 [KKP21a]). On the negative side, we prove that the results of Jafargholi and Wichs are essentially optimal by showing that no black-box reduction can provide a significantly better security bound (published at Crypto ’21 [KKPW21c]). AU - Klein, Karen ID - 10035 SN - 2663-337X TI - On the adaptive security of graph-based games ER - TY - CONF AB - The security of cryptographic primitives and protocols against adversaries that are allowed to make adaptive choices (e.g., which parties to corrupt or which queries to make) is notoriously difficult to establish. A broad theoretical framework was introduced by Jafargholi et al. [Crypto’17] for this purpose. In this paper we initiate the study of lower bounds on loss in adaptive security for certain cryptographic protocols considered in the framework. We prove lower bounds that almost match the upper bounds (proven using the framework) for proxy re-encryption, prefix-constrained PRFs and generalized selective decryption, a security game that captures the security of certain group messaging and broadcast encryption schemes. Those primitives have in common that their security game involves an underlying graph that can be adaptively built by the adversary. Some of our lower bounds only apply to a restricted class of black-box reductions which we term “oblivious” (the existing upper bounds are of this restricted type), some apply to the broader but still restricted class of non-rewinding reductions, while our lower bound for proxy re-encryption applies to all black-box reductions. The fact that some of our lower bounds seem to crucially rely on obliviousness or at least a non-rewinding reduction hints to the exciting possibility that the existing upper bounds can be improved by using more sophisticated reductions. Our main conceptual contribution is a two-player multi-stage game called the Builder-Pebbler Game. We can translate bounds on the winning probabilities for various instantiations of this game into cryptographic lower bounds for the above-mentioned primitives using oracle separation techniques. AU - Kamath Hosdurg, Chethan AU - Klein, Karen AU - Pietrzak, Krzysztof Z AU - Walter, Michael ID - 10410 SN - 0302-9743 T2 - 19th International Conference TI - The cost of adaptivity in security games on graphs VL - 13043 ER - TY - CONF AB - The security of cryptographic primitives and protocols against adversaries that are allowed to make adaptive choices (e.g., which parties to corrupt or which queries to make) is notoriously difficult to establish. A broad theoretical framework was introduced by Jafargholi et al. [Crypto’17] for this purpose. In this paper we initiate the study of lower bounds on loss in adaptive security for certain cryptographic protocols considered in the framework. We prove lower bounds that almost match the upper bounds (proven using the framework) for proxy re-encryption, prefix-constrained PRFs and generalized selective decryption, a security game that captures the security of certain group messaging and broadcast encryption schemes. Those primitives have in common that their security game involves an underlying graph that can be adaptively built by the adversary. Some of our lower bounds only apply to a restricted class of black-box reductions which we term “oblivious” (the existing upper bounds are of this restricted type), some apply to the broader but still restricted class of non-rewinding reductions, while our lower bound for proxy re-encryption applies to all black-box reductions. The fact that some of our lower bounds seem to crucially rely on obliviousness or at least a non-rewinding reduction hints to the exciting possibility that the existing upper bounds can be improved by using more sophisticated reductions. Our main conceptual contribution is a two-player multi-stage game called the Builder-Pebbler Game. We can translate bounds on the winning probabilities for various instantiations of this game into cryptographic lower bounds for the above-mentioned primitives using oracle separation techniques. AU - Kamath Hosdurg, Chethan AU - Klein, Karen AU - Pietrzak, Krzysztof Z AU - Walter, Michael ID - 10048 T2 - 19th Theory of Cryptography Conference 2021 TI - The cost of adaptivity in security games on graphs ER - TY - JOUR AB - We prove an adiabatic theorem for the Landau–Pekar equations. This allows us to derive new results on the accuracy of their use as effective equations for the time evolution generated by the Fröhlich Hamiltonian with large coupling constant α. In particular, we show that the time evolution of Pekar product states with coherent phonon field and the electron being trapped by the phonons is well approximated by the Landau–Pekar equations until times short compared to α2. AU - Leopold, Nikolai K AU - Rademacher, Simone Anna Elvira AU - Schlein, Benjamin AU - Seiringer, Robert ID - 10738 IS - 7 JF - Analysis and PDE SN - 2157-5045 TI - The Landau–Pekar equations: Adiabatic theorem and accuracy VL - 14 ER - TY - THES AB - The scalability of concurrent data structures and distributed algorithms strongly depends on reducing the contention for shared resources and the costs of synchronization and communication. We show how such cost reductions can be attained by relaxing the strict consistency conditions required by sequential implementations. In the first part of the thesis, we consider relaxation in the context of concurrent data structures. Specifically, in data structures such as priority queues, imposing strong semantics renders scalability impossible, since a correct implementation of the remove operation should return only the element with highest priority. Intuitively, attempting to invoke remove operations concurrently creates a race condition. This bottleneck can be circumvented by relaxing semantics of the affected data structure, thus allowing removal of the elements which are no longer required to have the highest priority. We prove that the randomized implementations of relaxed data structures provide provable guarantees on the priority of the removed elements even under concurrency. Additionally, we show that in some cases the relaxed data structures can be used to scale the classical algorithms which are usually implemented with the exact ones. In the second part, we study parallel variants of the stochastic gradient descent (SGD) algorithm, which distribute computation among the multiple processors, thus reducing the running time. Unfortunately, in order for standard parallel SGD to succeed, each processor has to maintain a local copy of the necessary model parameter, which is identical to the local copies of other processors; the overheads from this perfect consistency in terms of communication and synchronization can negate the speedup gained by distributing the computation. We show that the consistency conditions required by SGD can be relaxed, allowing the algorithm to be more flexible in terms of tolerating quantized communication, asynchrony, or even crash faults, while its convergence remains asymptotically the same. AU - Nadiradze, Giorgi ID - 10429 SN - 2663-337X TI - On achieving scalability through relaxation ER - TY - CONF AB - Decentralized optimization is emerging as a viable alternative for scalable distributed machine learning, but also introduces new challenges in terms of synchronization costs. To this end, several communication-reduction techniques, such as non-blocking communication, quantization, and local steps, have been explored in the decentralized setting. Due to the complexity of analyzing optimization in such a relaxed setting, this line of work often assumes \emph{global} communication rounds, which require additional synchronization. In this paper, we consider decentralized optimization in the simpler, but harder to analyze, \emph{asynchronous gossip} model, in which communication occurs in discrete, randomly chosen pairings among nodes. Perhaps surprisingly, we show that a variant of SGD called \emph{SwarmSGD} still converges in this setting, even if \emph{non-blocking communication}, \emph{quantization}, and \emph{local steps} are all applied \emph{in conjunction}, and even if the node data distributions and underlying graph topology are both \emph{heterogenous}. Our analysis is based on a new connection with multi-dimensional load-balancing processes. We implement this algorithm and deploy it in a super-computing environment, showing that it can outperform previous decentralized methods in terms of end-to-end training time, and that it can even rival carefully-tuned large-batch SGD for certain tasks. AU - Nadiradze, Giorgi AU - Sabour, Amirmojtaba AU - Davies, Peter AU - Li, Shigang AU - Alistarh, Dan-Adrian ID - 10435 T2 - 35th Conference on Neural Information Processing Systems TI - Asynchronous decentralized SGD with quantized and local updates ER - TY - CONF AB - We study the problem of estimating a rank-$1$ signal in the presence of rotationally invariant noise-a class of perturbations more general than Gaussian noise. Principal Component Analysis (PCA) provides a natural estimator, and sharp results on its performance have been obtained in the high-dimensional regime. Recently, an Approximate Message Passing (AMP) algorithm has been proposed as an alternative estimator with the potential to improve the accuracy of PCA. However, the existing analysis of AMP requires an initialization that is both correlated with the signal and independent of the noise, which is often unrealistic in practice. In this work, we combine the two methods, and propose to initialize AMP with PCA. Our main result is a rigorous asymptotic characterization of the performance of this estimator. Both the AMP algorithm and its analysis differ from those previously derived in the Gaussian setting: at every iteration, our AMP algorithm requires a specific term to account for PCA initialization, while in the Gaussian case, PCA initialization affects only the first iteration of AMP. The proof is based on a two-phase artificial AMP that first approximates the PCA estimator and then mimics the true AMP. Our numerical simulations show an excellent agreement between AMP results and theoretical predictions, and suggest an interesting open direction on achieving Bayes-optimal performance. AU - Mondelli, Marco AU - Venkataramanan, Ramji ID - 10593 SN - 1049-5258 T2 - 35th Conference on Neural Information Processing Systems TI - PCA initialization for approximate message passing in rotationally invariant models VL - 35 ER - TY - CONF AB - The question of how and why the phenomenon of mode connectivity occurs in training deep neural networks has gained remarkable attention in the research community. From a theoretical perspective, two possible explanations have been proposed: (i) the loss function has connected sublevel sets, and (ii) the solutions found by stochastic gradient descent are dropout stable. While these explanations provide insights into the phenomenon, their assumptions are not always satisfied in practice. In particular, the first approach requires the network to have one layer with order of N neurons (N being the number of training samples), while the second one requires the loss to be almost invariant after removing half of the neurons at each layer (up to some rescaling of the remaining ones). In this work, we improve both conditions by exploiting the quality of the features at every intermediate layer together with a milder over-parameterization condition. More specifically, we show that: (i) under generic assumptions on the features of intermediate layers, it suffices that the last two hidden layers have order of N−−√ neurons, and (ii) if subsets of features at each layer are linearly separable, then no over-parameterization is needed to show the connectivity. Our experiments confirm that the proposed condition ensures the connectivity of solutions found by stochastic gradient descent, even in settings where the previous requirements do not hold. AU - Nguyen, Quynh AU - Bréchet, Pierre AU - Mondelli, Marco ID - 10594 SN - 1049-5258 T2 - 35th Conference on Neural Information Processing Systems TI - When are solutions connected in deep networks? VL - 35 ER - TY - JOUR AB - The quantum bits (qubits) on which superconducting quantum computers are based have energy scales corresponding to photons with GHz frequencies. The energy of photons in the gigahertz domain is too low to allow transmission through the noisy room-temperature environment, where the signal would be lost in thermal noise. Optical photons, on the other hand, have much higher energies, and signals can be detected using highly efficient single-photon detectors. Transduction from microwave to optical frequencies is therefore a potential enabling technology for quantum devices. However, in such a device the optical pump can be a source of thermal noise and thus degrade the fidelity; the similarity of input microwave state to the output optical state. In order to investigate the magnitude of this effect we model the sub-Kelvin thermal behavior of an electro-optic transducer based on a lithium niobate whispering gallery mode resonator. We find that there is an optimum power level for a continuous pump, whilst pulsed operation of the pump increases the fidelity of the conversion. AU - Mobassem, Sonia AU - Lambert, Nicholas J. AU - Rueda Sanchez, Alfredo R AU - Fink, Johannes M AU - Leuchs, Gerd AU - Schwefel, Harald G.L. ID - 9815 IS - 4 JF - Quantum Science and Technology TI - Thermal noise in electro-optic devices at cryogenic temperatures VL - 6 ER - TY - GEN AB - Redox mediators could catalyse otherwise slow and energy-inefficient cycling of Li-S and Li-O 2 batteries by shuttling electrons/holes between the electrode and the solid insulating storage materials. For mediators to work efficiently they need to oxidize the solid with fast kinetics yet the lowest possible overpotential. Here, we found that when the redox potentials of mediators are tuned via, e.g., Li + concentration in the electrolyte, they exhibit distinct threshold potentials, where the kinetics accelerate several-fold within a range as small as 10 mV. This phenomenon is independent of types of mediators and electrolyte. The acceleration originates from the overpotentials required to activate fast Li + /e – extraction and the following chemical step at specific abundant surface facets. Efficient redox catalysis at insulating solids requires therefore carefully considering the surface conditions of the storage materials and electrolyte-dependent redox potentials, which may be tuned by salt concentrations or solvents. AU - Cao, Deqing AU - Shen, Xiaoxiao AU - Wang, Aiping AU - Yu, Fengjiao AU - Wu, Yuping AU - Shi, Siqi AU - Freunberger, Stefan Alexander AU - Chen, Yuhui ID - 9978 KW - Catalysis KW - Energy engineering KW - Materials theory and modeling T2 - Research Square TI - Sharp kinetic acceleration potentials during mediated redox catalysis of insulators ER - TY - JOUR AB - P-glycoprotein (ABCB1) and breast cancer resistance protein (ABCG2) restrict at the blood–brain barrier (BBB) the brain distribution of the majority of currently known molecularly targeted anticancer drugs. To improve brain delivery of dual ABCB1/ABCG2 substrates, both ABCB1 and ABCG2 need to be inhibited simultaneously at the BBB. We examined the feasibility of simultaneous ABCB1/ABCG2 inhibition with i.v. co-infusion of erlotinib and tariquidar by studying brain distribution of the model ABCB1/ABCG2 substrate [11C]erlotinib in mice and rhesus macaques with PET. Tolerability of the erlotinib/tariquidar combination was assessed in human embryonic stem cell-derived cerebral organoids. In mice and macaques, baseline brain distribution of [11C]erlotinib was low (brain distribution volume, VT,brain < 0.3 mL/cm3). Co-infusion of erlotinib and tariquidar increased VT,brain in mice by 3.0-fold and in macaques by 3.4- to 5.0-fold, while infusion of erlotinib alone or tariquidar alone led to less pronounced VT,brain increases in both species. Treatment of cerebral organoids with erlotinib/tariquidar led to an induction of Caspase-3-dependent apoptosis. Co-infusion of erlotinib/tariquidar may potentially allow for complete ABCB1/ABCG2 inhibition at the BBB, while simultaneously achieving brain-targeted EGFR inhibition. Our protocol may be applicable to enhance brain delivery of molecularly targeted anticancer drugs for a more effective treatment of brain tumors. AU - Tournier, N AU - Goutal, S AU - Mairinger, S AU - Lozano, IH AU - Filip, T AU - Sauberer, M AU - Caillé, F AU - Breuil, L AU - Stanek, J AU - Freeman, AF AU - Novarino, Gaia AU - Truillet, C AU - Wanek, T AU - Langer, O ID - 8730 IS - 7 JF - Journal of Cerebral Blood Flow and Metabolism SN - 0271-678x TI - Complete inhibition of ABCB1 and ABCG2 at the blood-brain barrier by co-infusion of erlotinib and tariquidar to improve brain delivery of the model ABCB1/ABCG2 substrate [11C]erlotinib VL - 41 ER - TY - JOUR AB - A primary roadblock to our understanding of speciation is that it usually occurs over a timeframe that is too long to study from start to finish. The idea of a speciation continuum provides something of a solution to this problem; rather than observing the entire process, we can simply reconstruct it from the multitude of speciation events that surround us. But what do we really mean when we talk about the speciation continuum, and can it really help us understand speciation? We explored these questions using a literature review and online survey of speciation researchers. Although most researchers were familiar with the concept and thought it was useful, our survey revealed extensive disagreement about what the speciation continuum actually tells us. This is due partly to the lack of a clear definition. Here, we provide an explicit definition that is compatible with the Biological Species Concept. That is, the speciation continuum is a continuum of reproductive isolation. After outlining the logic of the definition in light of alternatives, we explain why attempts to reconstruct the speciation process from present‐day populations will ultimately fail. We then outline how we think the speciation continuum concept can continue to act as a foundation for understanding the continuum of reproductive isolation that surrounds us. AU - Stankowski, Sean AU - Ravinet, Mark ID - 9383 IS - 6 JF - Evolution SN - 0014-3820 TI - Defining the speciation continuum VL - 75 ER - TY - JOUR AB - Growth regulation tailors development in plants to their environment. A prominent example of this is the response to gravity, in which shoots bend up and roots bend down1. This paradox is based on opposite effects of the phytohormone auxin, which promotes cell expansion in shoots while inhibiting it in roots via a yet unknown cellular mechanism2. Here, by combining microfluidics, live imaging, genetic engineering and phosphoproteomics in Arabidopsis thaliana, we advance understanding of how auxin inhibits root growth. We show that auxin activates two distinct, antagonistically acting signalling pathways that converge on rapid regulation of apoplastic pH, a causative determinant of growth. Cell surface-based TRANSMEMBRANE KINASE1 (TMK1) interacts with and mediates phosphorylation and activation of plasma membrane H+-ATPases for apoplast acidification, while intracellular canonical auxin signalling promotes net cellular H+ influx, causing apoplast alkalinization. Simultaneous activation of these two counteracting mechanisms poises roots for rapid, fine-tuned growth modulation in navigating complex soil environments. AU - Li, Lanxin AU - Verstraeten, Inge AU - Roosjen, Mark AU - Takahashi, Koji AU - Rodriguez Solovey, Lesia AU - Merrin, Jack AU - Chen, Jian AU - Shabala, Lana AU - Smet, Wouter AU - Ren, Hong AU - Vanneste, Steffen AU - Shabala, Sergey AU - De Rybel, Bert AU - Weijers, Dolf AU - Kinoshita, Toshinori AU - Gray, William M. AU - Friml, Jiří ID - 10223 IS - 7884 JF - Nature KW - Multidisciplinary SN - 00280836 TI - Cell surface and intracellular auxin signalling for H+ fluxes in root growth VL - 599 ER - TY - JOUR AB - When B cells encounter membrane-bound antigens, the formation and coalescence of B cell antigen receptor (BCR) microclusters amplifies BCR signaling. The ability of B cells to probe the surface of antigen-presenting cells (APCs) and respond to APC-bound antigens requires remodeling of the actin cytoskeleton. Initial BCR signaling stimulates actin-related protein (Arp) 2/3 complex-dependent actin polymerization, which drives B cell spreading as well as the centripetal movement and coalescence of BCR microclusters at the B cell-APC synapse. Sustained actin polymerization depends on concomitant actin filament depolymerization, which enables the recycling of actin monomers and Arp2/3 complexes. Cofilin-mediated severing of actin filaments is a rate-limiting step in the morphological changes that occur during immune synapse formation. Hence, regulators of cofilin activity such as WD repeat-containing protein 1 (Wdr1), LIM domain kinase (LIMK), and coactosin-like 1 (Cotl1) may also be essential for actin-dependent processes in B cells. Wdr1 enhances cofilin-mediated actin disassembly. Conversely, Cotl1 competes with cofilin for binding to actin and LIMK phosphorylates cofilin and prevents it from binding to actin filaments. We now show that Wdr1 and LIMK have distinct roles in BCR-induced assembly of the peripheral actin structures that drive B cell spreading, and that cofilin, Wdr1, and LIMK all contribute to the actin-dependent amplification of BCR signaling at the immune synapse. Depleting Cotl1 had no effect on these processes. Thus, the Wdr1-LIMK-cofilin axis is critical for BCR-induced actin remodeling and for B cell responses to APC-bound antigens. AU - Bolger-Munro, Madison AU - Choi, Kate AU - Cheung, Faith AU - Liu, Yi Tian AU - Dang-Lawson, May AU - Deretic, Nikola AU - Keane, Connor AU - Gold, Michael R. ID - 9379 JF - Frontiers in Cell and Developmental Biology KW - B cell KW - actin KW - immune synapse KW - cell spreading KW - cofilin KW - WDR1 (AIP1) KW - LIM domain kinase KW - B cell receptor (BCR) TI - The Wdr1-LIMK-Cofilin axis controls B cell antigen receptor-induced actin remodeling and signaling at the immune synapse VL - 9 ER - TY - JOUR AB - A central goal in systems neuroscience is to understand the functions performed by neural circuits. Previous top-down models addressed this question by comparing the behaviour of an ideal model circuit, optimised to perform a given function, with neural recordings. However, this requires guessing in advance what function is being performed, which may not be possible for many neural systems. To address this, we propose an inverse reinforcement learning (RL) framework for inferring the function performed by a neural network from data. We assume that the responses of each neuron in a network are optimised so as to drive the network towards ‘rewarded’ states, that are desirable for performing a given function. We then show how one can use inverse RL to infer the reward function optimised by the network from observing its responses. This inferred reward function can be used to predict how the neural network should adapt its dynamics to perform the same function when the external environment or network structure changes. This could lead to theoretical predictions about how neural network dynamics adapt to deal with cell death and/or varying sensory stimulus statistics. AU - Chalk, Matthew J AU - Tkačik, Gašper AU - Marre, Olivier ID - 9362 IS - 4 JF - PLoS ONE TI - Inferring the function performed by a recurrent neural network VL - 16 ER - TY - JOUR AB - Size control is a fundamental question in biology, showing incremental complexity in plants, whose cells possess a rigid cell wall. The phytohormone auxin is a vital growth regulator with central importance for differential growth control. Our results indicate that auxin-reliant growth programs affect the molecular complexity of xyloglucans, the major type of cell wall hemicellulose in eudicots. Auxin-dependent induction and repression of growth coincide with reduced and enhanced molecular complexity of xyloglucans, respectively. In agreement with a proposed function in growth control, genetic interference with xyloglucan side decorations distinctly modulates auxin-dependent differential growth rates. Our work proposes that auxin-dependent growth programs have a spatially defined effect on xyloglucan’s molecular structure, which in turn affects cell wall mechanics and specifies differential, gravitropic hypocotyl growth. AU - Velasquez, Silvia Melina AU - Guo, Xiaoyuan AU - Gallemi, Marçal AU - Aryal, Bibek AU - Venhuizen, Peter AU - Barbez, Elke AU - Dünser, Kai Alexander AU - Darino, Martin AU - Pӗnčík, Aleš AU - Novák, Ondřej AU - Kalyna, Maria AU - Mouille, Gregory AU - Benková, Eva AU - Bhalerao, Rishikesh P. AU - Mravec, Jozef AU - Kleine-Vehn, Jürgen ID - 9986 IS - 17 JF - International Journal of Molecular Sciences KW - auxin KW - growth KW - cell wall KW - xyloglucans KW - hypocotyls KW - gravitropism SN - 1661-6596 TI - Xyloglucan remodeling defines auxin-dependent differential tissue expansion in plants VL - 22 ER - TY - JOUR AB - Transposable elements exist widely throughout plant genomes and play important roles in plant evolution. Auxin is an important regulator that is traditionally associated with root development and drought stress adaptation. The DEEPER ROOTING 1 (DRO1) gene is a key component of rice drought avoidance. Here, we identified a transposon that acts as an autonomous auxin‐responsive promoter and its presence at specific genome positions conveys physiological adaptations related to drought avoidance. Rice varieties with high and auxin‐mediated transcription of DRO1 in the root tip show deeper and longer root phenotypes and are thus better adapted to drought. The INDITTO2 transposon contains an auxin response element and displays auxin‐responsive promoter activity; it is thus able to convey auxin regulation of transcription to genes in its proximity. In the rice Acuce, which displays DRO1‐mediated drought adaptation, the INDITTO2 transposon was found to be inserted at the promoter region of the DRO1 locus. Transgenesis‐based insertion of the INDITTO2 transposon into the DRO1 promoter of the non‐adapted rice variety Nipponbare was sufficient to promote its drought avoidance. Our data identify an example of how transposons can act as promoters and convey hormonal regulation to nearby loci, improving plant fitness in response to different abiotic stresses. AU - Zhao, Y AU - Wu, L AU - Fu, Q AU - Wang, D AU - Li, J AU - Yao, B AU - Yu, S AU - Jiang, L AU - Qian, J AU - Zhou, X AU - Han, L AU - Zhao, S AU - Ma, C AU - Zhang, Y AU - Luo, C AU - Dong, Q AU - Li, S AU - Zhang, L AU - Jiang, X AU - Li, Y AU - Luo, H AU - Li, K AU - Yang, J AU - Luo, Q AU - Li, L AU - Peng, S AU - Huang, H AU - Zuo, Z AU - Liu, C AU - Wang, L AU - Li, C AU - He, X AU - Friml, Jiří AU - Du, Y ID - 9189 IS - 6 JF - Plant, Cell & Environment SN - 0140-7791 TI - INDITTO2 transposon conveys auxin-mediated DRO1 transcription for rice drought avoidance VL - 44 ER - TY - GEN AB - This paper establishes new connections between many-body quantum systems, One-body Reduced Density Matrices Functional Theory (1RDMFT) and Optimal Transport (OT), by interpreting the problem of computing the ground-state energy of a finite dimensional composite quantum system at positive temperature as a non-commutative entropy regularized Optimal Transport problem. We develop a new approach to fully characterize the dual-primal solutions in such non-commutative setting. The mathematical formalism is particularly relevant in quantum chemistry: numerical realizations of the many-electron ground state energy can be computed via a non-commutative version of Sinkhorn algorithm. Our approach allows to prove convergence and robustness of this algorithm, which, to our best knowledge, were unknown even in the two marginal case. Our methods are based on careful a priori estimates in the dual problem, which we believe to be of independent interest. Finally, the above results are extended in 1RDMFT setting, where bosonic or fermionic symmetry conditions are enforced on the problem. AU - Feliciangeli, Dario AU - Gerolin, Augusto AU - Portinale, Lorenzo ID - 9792 T2 - arXiv TI - A non-commutative entropic optimal transport approach to quantum composite systems at positive temperature ER - TY - JOUR AB - Adeno-associated viruses (AAVs) are widely used to deliver genetic material in vivo to distinct cell types such as neurons or glial cells, allowing for targeted manipulation. Transduction of microglia is mostly excluded from this strategy, likely due to the cells’ heterogeneous state upon environmental changes, which makes AAV design challenging. Here, we established the retina as a model system for microglial AAV validation and optimization. First, we show that AAV2/6 transduced microglia in both synaptic layers, where layer preference corresponds to the intravitreal or subretinal delivery method. Surprisingly, we observed significantly enhanced microglial transduction during photoreceptor degeneration. Thus, we modified the AAV6 capsid to reduce heparin binding by introducing four point mutations (K531E, R576Q, K493S, and K459S), resulting in increased microglial transduction in the outer plexiform layer. Finally, to improve microglial-specific transduction, we validated a Cre-dependent transgene delivery cassette for use in combination with the Cx3cr1CreERT2 mouse line. Together, our results provide a foundation for future studies optimizing AAV-mediated microglia transduction and highlight that environmental conditions influence microglial transduction efficiency. AU - Maes, Margaret E AU - Wögenstein, Gabriele M. AU - Colombo, Gloria AU - Casado Polanco, Raquel AU - Siegert, Sandra ID - 10655 JF - Molecular Therapy - Methods and Clinical Development TI - Optimizing AAV2/6 microglial targeting identified enhanced efficiency in the photoreceptor degenerative environment VL - 23 ER - TY - JOUR AB - Enzymatic digestion of the extracellular matrix with chondroitinase-ABC reinstates juvenile-like plasticity in the adult cortex as it also disassembles the perineuronal nets (PNNs). The disadvantage of the enzyme is that it must be applied intracerebrally and it degrades the ECM for several weeks. Here, we provide two minimally invasive and transient protocols for microglia-enabled PNN disassembly in mouse cortex: repeated treatment with ketamine-xylazine-acepromazine (KXA) anesthesia and 60-Hz light entrainment. We also discuss how to analyze PNNs within microglial endosomes-lysosomes. For complete details on the use and execution of this protocol, please refer to Venturino et al. (2021). AU - Venturino, Alessandro AU - Siegert, Sandra ID - 10565 IS - 4 JF - STAR Protocols TI - Minimally invasive protocols and quantification for microglia-mediated perineuronal net disassembly in mouse brain VL - 2 ER - TY - JOUR AB - Mosaic analysis with double markers (MADM) technology enables the generation of genetic mosaic tissue in mice. MADM enables concomitant fluorescent cell labeling and introduction of a mutation of a gene of interest with single-cell resolution. This protocol highlights major steps for the generation of genetic mosaic tissue and the isolation and processing of respective tissues for downstream histological analysis. For complete details on the use and execution of this protocol, please refer to Contreras et al. (2021). AU - Amberg, Nicole AU - Hippenmeyer, Simon ID - 10321 IS - 4 JF - STAR Protocols TI - Genetic mosaic dissection of candidate genes in mice using mosaic analysis with double markers VL - 2 ER - TY - JOUR AB - A precise quantitative description of the ultrastructural characteristics underlying biological mechanisms is often key to their understanding. This is particularly true for dynamic extra- and intracellular filamentous assemblies, playing a role in cell motility, cell integrity, cytokinesis, tissue formation and maintenance. For example, genetic manipulation or modulation of actin regulatory proteins frequently manifests in changes of the morphology, dynamics, and ultrastructural architecture of actin filament-rich cell peripheral structures, such as lamellipodia or filopodia. However, the observed ultrastructural effects often remain subtle and require sufficiently large datasets for appropriate quantitative analysis. The acquisition of such large datasets has been enabled by recent advances in high-throughput cryo-electron tomography (cryo-ET) methods. This also necessitates the development of complementary approaches to maximize the extraction of relevant biological information. We have developed a computational toolbox for the semi-automatic quantification of segmented and vectorized filamentous networks from pre-processed cryo-electron tomograms, facilitating the analysis and cross-comparison of multiple experimental conditions. GUI-based components simplify the processing of data and allow users to obtain a large number of ultrastructural parameters describing filamentous assemblies. We demonstrate the feasibility of this workflow by analyzing cryo-ET data of untreated and chemically perturbed branched actin filament networks and that of parallel actin filament arrays. In principle, the computational toolbox presented here is applicable for data analysis comprising any type of filaments in regular (i.e. parallel) or random arrangement. We show that it can ease the identification of key differences between experimental groups and facilitate the in-depth analysis of ultrastructural data in a time-efficient manner. AU - Dimchev, Georgi A AU - Amiri, Behnam AU - Fäßler, Florian AU - Falcke, Martin AU - Schur, Florian KM ID - 10290 IS - 4 JF - Journal of Structural Biology KW - Structural Biology SN - 1047-8477 TI - Computational toolbox for ultrastructural quantitative analysis of filament networks in cryo-ET data VL - 213 ER - TY - CONF AB - Payment channel networks are a promising approach to improve the scalability of cryptocurrencies: they allow to perform transactions in a peer-to-peer fashion, along multihop routes in the network, without requiring consensus on the blockchain. However, during the discovery of cost-efficient routes for the transaction, critical information may be revealed about the transacting entities. This paper initiates the study of privacy-preserving route discovery mechanisms for payment channel networks. In particular, we present LightPIR, an approach which allows a client to learn the shortest (or cheapest in terms of fees) path between two nodes without revealing any information about the endpoints of the transaction to the servers. The two main observations which allow for an efficient solution in LightPIR are that: (1) surprisingly, hub labelling algorithms – which were developed to preprocess “street network like” graphs so one can later efficiently compute shortest paths – also perform well for the graphs underlying payment channel networks, and that (2) hub labelling algorithms can be conveniently combined with private information retrieval. LightPIR relies on a simple hub labeling heuristic on top of existing hub labeling algorithms which leverages the specific topological features of cryptocurrency networks to further minimize storage and bandwidth overheads. In a case study considering the Lightning network, we show that our approach is an order of magnitude more efficient compared to a privacy-preserving baseline based on using private information retrieval on a database that stores all pairs shortest paths. AU - Pietrzak, Krzysztof Z AU - Salem, Iosif AU - Schmid, Stefan AU - Yeo, Michelle X ID - 9969 SN - 978-1-6654-4501-6 TI - LightPIR: Privacy-preserving route discovery for payment channel networks ER - TY - CONF AB - We present a new approach to proving non-termination of non-deterministic integer programs. Our technique is rather simple but efficient. It relies on a purely syntactic reversal of the program's transition system followed by a constraint-based invariant synthesis with constraints coming from both the original and the reversed transition system. The latter task is performed by a simple call to an off-the-shelf SMT-solver, which allows us to leverage the latest advances in SMT-solving. Moreover, our method offers a combination of features not present (as a whole) in previous approaches: it handles programs with non-determinism, provides relative completeness guarantees and supports programs with polynomial arithmetic. The experiments performed with our prototype tool RevTerm show that our approach, despite its simplicity and stronger theoretical guarantees, is at least on par with the state-of-the-art tools, often achieving a non-trivial improvement under a proper configuration of its parameters. AU - Chatterjee, Krishnendu AU - Goharshady, Ehsan Kafshdar AU - Novotný, Petr AU - Zikelic, Dorde ID - 9644 SN - 9781450383912 T2 - Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation TI - Proving non-termination by program reversal ER - TY - JOUR AB - The quantum approximate optimization algorithm (QAOA) is a prospective near-term quantum algorithm due to its modest circuit depth and promising benchmarks. However, an external parameter optimization required in the QAOA could become a performance bottleneck. This motivates studies of the optimization landscape and search for heuristic ways of parameter initialization. In this work we visualize the optimization landscape of the QAOA applied to the MaxCut problem on random graphs, demonstrating that random initialization of the QAOA is prone to converging to local minima with suboptimal performance. We introduce the initialization of QAOA parameters based on the Trotterized quantum annealing (TQA) protocol, parameterized by the Trotter time step. We find that the TQA initialization allows to circumvent the issue of false minima for a broad range of time steps, yielding the same performance as the best result out of an exponentially scaling number of random initializations. Moreover, we demonstrate that the optimal value of the time step coincides with the point of proliferation of Trotter errors in quantum annealing. Our results suggest practical ways of initializing QAOA protocols on near-term quantum devices and reveal new connections between QAOA and quantum annealing. AU - Sack, Stefan AU - Serbyn, Maksym ID - 9760 JF - Quantum TI - Quantum annealing initialization of the quantum approximate optimization algorithm VL - 5 ER - TY - CONF AB - We consider the almost-sure (a.s.) termination problem for probabilistic programs, which are a stochastic extension of classical imperative programs. Lexicographic ranking functions provide a sound and practical approach for termination of non-probabilistic programs, and their extension to probabilistic programs is achieved via lexicographic ranking supermartingales (LexRSMs). However, LexRSMs introduced in the previous work have a limitation that impedes their automation: all of their components have to be non-negative in all reachable states. This might result in LexRSM not existing even for simple terminating programs. Our contributions are twofold: First, we introduce a generalization of LexRSMs which allows for some components to be negative. This standard feature of non-probabilistic termination proofs was hitherto not known to be sound in the probabilistic setting, as the soundness proof requires a careful analysis of the underlying stochastic process. Second, we present polynomial-time algorithms using our generalized LexRSMs for proving a.s. termination in broad classes of linear-arithmetic programs. AU - Chatterjee, Krishnendu AU - Goharshady, Ehsan Kafshdar AU - Novotný, Petr AU - Zárevúcky, Jiří AU - Zikelic, Dorde ID - 10414 SN - 0302-9743 T2 - 24th International Symposium on Formal Methods TI - On lexicographic proof rules for probabilistic termination VL - 13047 ER - TY - JOUR AB - Research on two-dimensional (2D) materials has been explosively increasing in last seventeen years in varying subjects including condensed matter physics, electronic engineering, materials science, and chemistry since the mechanical exfoliation of graphene in 2004. Starting from graphene, 2D materials now have become a big family with numerous members and diverse categories. The unique structural features and physicochemical properties of 2D materials make them one class of the most appealing candidates for a wide range of potential applications. In particular, we have seen some major breakthroughs made in the field of 2D materials in last five years not only in developing novel synthetic methods and exploring new structures/properties but also in identifying innovative applications and pushing forward commercialisation. In this review, we provide a critical summary on the recent progress made in the field of 2D materials with a particular focus on last five years. After a brief background introduction, we first discuss the major synthetic methods for 2D materials, including the mechanical exfoliation, liquid exfoliation, vapor phase deposition, and wet-chemical synthesis as well as phase engineering of 2D materials belonging to the field of phase engineering of nanomaterials (PEN). We then introduce the superconducting/optical/magnetic properties and chirality of 2D materials along with newly emerging magic angle 2D superlattices. Following that, the promising applications of 2D materials in electronics, optoelectronics, catalysis, energy storage, solar cells, biomedicine, sensors, environments, etc. are described sequentially. Thereafter, we present the theoretic calculations and simulations of 2D materials. Finally, after concluding the current progress, we provide some personal discussions on the existing challenges and future outlooks in this rapidly developing field. AU - Chang, Cheng AU - Chen, Wei AU - Chen, Ye AU - Chen, Yonghua AU - Chen, Yu AU - Ding, Feng AU - Fan, Chunhai AU - Fan, Hong Jin AU - Fan, Zhanxi AU - Gong, Cheng AU - Gong, Yongji AU - He, Qiyuan AU - Hong, Xun AU - Hu, Sheng AU - Hu, Weida AU - Huang, Wei AU - Huang, Yuan AU - Ji, Wei AU - Li, Dehui AU - Li, Lain Jong AU - Li, Qiang AU - Lin, Li AU - Ling, Chongyi AU - Liu, Minghua AU - Liu, Nan AU - Liu, Zhuang AU - Loh, Kian Ping AU - Ma, Jianmin AU - Miao, Feng AU - Peng, Hailin AU - Shao, Mingfei AU - Song, Li AU - Su, Shao AU - Sun, Shuo AU - Tan, Chaoliang AU - Tang, Zhiyong AU - Wang, Dingsheng AU - Wang, Huan AU - Wang, Jinlan AU - Wang, Xin AU - Wang, Xinran AU - Wee, Andrew T.S. AU - Wei, Zhongming AU - Wu, Yuen AU - Wu, Zhong Shuai AU - Xiong, Jie AU - Xiong, Qihua AU - Xu, Weigao AU - Yin, Peng AU - Zeng, Haibo AU - Zeng, Zhiyuan AU - Zhai, Tianyou AU - Zhang, Han AU - Zhang, Hui AU - Zhang, Qichun AU - Zhang, Tierui AU - Zhang, Xiang AU - Zhao, Li Dong AU - Zhao, Meiting AU - Zhao, Weijie AU - Zhao, Yunxuan AU - Zhou, Kai Ge AU - Zhou, Xing AU - Zhou, Yu AU - Zhu, Hongwei AU - Zhang, Hua AU - Liu, Zhongfan ID - 14800 IS - 12 JF - Acta Physico-Chimica Sinica SN - 1001-4861 TI - Recent progress on two-dimensional materials VL - 37 ER - TY - CONF AB - Neural-network classifiers achieve high accuracy when predicting the class of an input that they were trained to identify. Maintaining this accuracy in dynamic environments, where inputs frequently fall outside the fixed set of initially known classes, remains a challenge. The typical approach is to detect inputs from novel classes and retrain the classifier on an augmented dataset. However, not only the classifier but also the detection mechanism needs to adapt in order to distinguish between newly learned and yet unknown input classes. To address this challenge, we introduce an algorithmic framework for active monitoring of a neural network. A monitor wrapped in our framework operates in parallel with the neural network and interacts with a human user via a series of interpretable labeling queries for incremental adaptation. In addition, we propose an adaptive quantitative monitor to improve precision. An experimental evaluation on a diverse set of benchmarks with varying numbers of classes confirms the benefits of our active monitoring framework in dynamic scenarios. AU - Lukina, Anna AU - Schilling, Christian AU - Henzinger, Thomas A ID - 10206 KW - monitoring KW - neural networks KW - novelty detection SN - 0302-9743 T2 - 21st International Conference on Runtime Verification TI - Into the unknown: active monitoring of neural networks VL - 12974 ER - TY - JOUR AB - We consider the Fröhlich Hamiltonian with large coupling constant α. For initial data of Pekar product form with coherent phonon field and with the electron minimizing the corresponding energy, we provide a norm approximation of the evolution, valid up to times of order α2. The approximation is given in terms of a Pekar product state, evolved through the Landau-Pekar equations, corrected by a Bogoliubov dynamics taking quantum fluctuations into account. This allows us to show that the Landau-Pekar equations approximately describe the evolution of the electron- and one-phonon reduced density matrices under the Fröhlich dynamics up to times of order α2. AU - Leopold, Nikolai K AU - Mitrouskas, David Johannes AU - Rademacher, Simone Anna Elvira AU - Schlein, Benjamin AU - Seiringer, Robert ID - 14889 IS - 4 JF - Pure and Applied Analysis SN - 2578-5893 TI - Landau–Pekar equations and quantum fluctuations for the dynamics of a strongly coupled polaron VL - 3 ER - TY - JOUR AB - We consider a system of N interacting bosons in the mean-field scaling regime and construct corrections to the Bogoliubov dynamics that approximate the true N-body dynamics in norm to arbitrary precision. The N-independent corrections are given in terms of the solutions of the Bogoliubov and Hartree equations and satisfy a generalized form of Wick's theorem. We determine the n-point correlation functions of the excitations around the condensate, as well as the reduced densities of the N-body system, to arbitrary accuracy, given only the knowledge of the two-point functions of a quasi-free state and the solution of the Hartree equation. In this way, the complex problem of computing all n-point correlation functions for an interacting N-body system is essentially reduced to the problem of solving the Hartree equation and the PDEs for the Bogoliubov two-point functions. AU - Bossmann, Lea AU - Petrat, Sören P AU - Pickl, Peter AU - Soffer, Avy ID - 14890 IS - 4 JF - Pure and Applied Analysis SN - 2578-5893 TI - Beyond Bogoliubov dynamics VL - 3 ER - TY - JOUR AB - We consider random n×n matrices X with independent and centered entries and a general variance profile. We show that the spectral radius of X converges with very high probability to the square root of the spectral radius of the variance matrix of X when n tends to infinity. We also establish the optimal rate of convergence, that is a new result even for general i.i.d. matrices beyond the explicitly solvable Gaussian cases. The main ingredient is the proof of the local inhomogeneous circular law [arXiv:1612.07776] at the spectral edge. AU - Alt, Johannes AU - Erdös, László AU - Krüger, Torben H ID - 15013 IS - 2 JF - Probability and Mathematical Physics SN - 2690-0998 TI - Spectral radius of random matrices with independent entries VL - 2 ER - TY - JOUR AB - Clathrin-mediated endocytosis is the major route of entry of cargos into cells and thus underpins many physiological processes. During endocytosis, an area of flat membrane is remodeled by proteins to create a spherical vesicle against intracellular forces. The protein machinery which mediates this membrane bending in plants is unknown. However, it is known that plant endocytosis is actin independent, thus indicating that plants utilize a unique mechanism to mediate membrane bending against high-turgor pressure compared to other model systems. Here, we investigate the TPLATE complex, a plant-specific endocytosis protein complex. It has been thought to function as a classical adaptor functioning underneath the clathrin coat. However, by using biochemical and advanced live microscopy approaches, we found that TPLATE is peripherally associated with clathrin-coated vesicles and localizes at the rim of endocytosis events. As this localization is more fitting to the protein machinery involved in membrane bending during endocytosis, we examined cells in which the TPLATE complex was disrupted and found that the clathrin structures present as flat patches. This suggests a requirement of the TPLATE complex for membrane bending during plant clathrin–mediated endocytosis. Next, we used in vitro biophysical assays to confirm that the TPLATE complex possesses protein domains with intrinsic membrane remodeling activity. These results redefine the role of the TPLATE complex and implicate it as a key component of the evolutionarily distinct plant endocytosis mechanism, which mediates endocytic membrane bending against the high-turgor pressure in plant cells. AU - Johnson, Alexander J AU - Dahhan, Dana A AU - Gnyliukh, Nataliia AU - Kaufmann, Walter AU - Zheden, Vanessa AU - Costanzo, Tommaso AU - Mahou, Pierre AU - Hrtyan, Mónika AU - Wang, Jie AU - Aguilera Servin, Juan L AU - van Damme, Daniël AU - Beaurepaire, Emmanuel AU - Loose, Martin AU - Bednarek, Sebastian Y AU - Friml, Jiří ID - 9887 IS - 51 JF - Proceedings of the National Academy of Sciences TI - The TPLATE complex mediates membrane bending during plant clathrin-mediated endocytosis VL - 118 ER - TY - CHAP AB - Hybrid zones are narrow geographic regions where different populations, races or interbreeding species meet and mate, producing mixed ‘hybrid’ offspring. They are relatively common and can be found in a diverse range of organisms and environments. The study of hybrid zones has played an important role in our understanding of the origin of species, with hybrid zones having been described as ‘natural laboratories’. This is because they allow us to study,in situ, the conditions and evolutionary forces that enable divergent taxa to remain distinct despite some ongoing gene exchange between them. AU - Stankowski, Sean AU - Shipilina, Daria AU - Westram, Anja M ID - 14984 SN - 9780470016176 T2 - Encyclopedia of Life Sciences TI - Hybrid Zones VL - 2 ER - TY - CHAP AB - The goal of zero-shot learning is to construct a classifier that can identify object classes for which no training examples are available. When training data for some of the object classes is available but not for others, the name generalized zero-shot learning is commonly used. In a wider sense, the phrase zero-shot is also used to describe other machine learning-based approaches that require no training data from the problem of interest, such as zero-shot action recognition or zero-shot machine translation. AU - Lampert, Christoph ED - Ikeuchi, Katsushi ID - 14987 SN - 9783030634155 T2 - Computer Vision TI - Zero-Shot Learning ER - TY - GEN AB - Raw data generated from the publication - The TPLATE complex mediates membrane bending during plant clathrin-mediated endocytosis by Johnson et al., 2021 In PNAS AU - Johnson, Alexander J ID - 14988 TI - Raw data from Johnson et al, PNAS, 2021 ER -