@article{9908,
abstract = {About eight million animal species are estimated to live on Earth, and all except those belonging to one subphylum are invertebrates. Invertebrates are incredibly diverse in their morphologies, life histories, and in the range of the ecological niches that they occupy. A great variety of modes of reproduction and sex determination systems is also observed among them, and their mosaic-distribution across the phylogeny shows that transitions between them occur frequently and rapidly. Genetic conflict in its various forms is a long-standing theory to explain what drives those evolutionary transitions. Here, we review (1) the different modes of reproduction among invertebrate species, highlighting sexual reproduction as the probable ancestral state; (2) the paradoxical diversity of sex determination systems; (3) the different types of genetic conflicts that could drive the evolution of such different systems.},
author = {Picard, Marion A L and Vicoso, Beatriz and Bertrand, Stéphanie and Escriva, Hector},
issn = {20734425},
journal = {Genes},
number = {8},
publisher = {MDPI},
title = {{Diversity of modes of reproduction and sex determination systems in invertebrates, and the putative contribution of genetic conflict}},
doi = {10.3390/genes12081136},
volume = {12},
year = {2021},
}
@article{9829,
abstract = {In 2020, many in-person scientific events were canceled due to the COVID-19 pandemic, creating a vacuum in networking and knowledge exchange between scientists. To fill this void in scientific communication, a group of early career nanocrystal enthusiasts launched the virtual seminar series, News in Nanocrystals, in the summer of 2020. By the end of the year, the series had attracted over 850 participants from 46 countries. In this Nano Focus, we describe the process of organizing the News in Nanocrystals seminar series; discuss its growth, emphasizing what the organizers have learned in terms of diversity and accessibility; and provide an outlook for the next steps and future opportunities. This summary and analysis of experiences and learned lessons are intended to inform the broader scientific community, especially those who are looking for avenues to continue fostering discussion and scientific engagement virtually, both during the pandemic and after.},
author = {Baranov, Dmitry and Šverko, Tara and Moot, Taylor and Keller, Helena R. and Klein, Megan D. and Vishnu, E. K. and Balazs, Daniel and Shulenberger, Katherine E.},
issn = {1936086X},
journal = {ACS Nano},
number = {7},
pages = {10743–10747},
publisher = {American Chemical Society},
title = {{News in Nanocrystals seminar: Self-assembly of early career researchers toward globally accessible nanoscience}},
doi = {2021},
volume = {15},
year = {2021},
}
@inproceedings{9933,
abstract = {In this paper, we study the power and limitations of component-stable algorithms in the low-space model of Massively Parallel Computation (MPC). Recently Ghaffari, Kuhn and Uitto (FOCS 2019) introduced the class of component-stable low-space MPC algorithms, which are, informally, defined as algorithms for which the outputs reported by the nodes in different connected components are required to be independent. This very natural notion was introduced to capture most (if not all) of the known efficient MPC algorithms to date, and it was the first general class of MPC algorithms for which one can show non-trivial conditional lower bounds. In this paper we enhance the framework of component-stable algorithms and investigate its effect on the complexity of randomized and deterministic low-space MPC. Our key contributions include: 1) We revise and formalize the lifting approach of Ghaffari, Kuhn and Uitto. This requires a very delicate amendment of the notion of component stability, which allows us to fill in gaps in the earlier arguments. 2) We also extend the framework to obtain conditional lower bounds for deterministic algorithms and fine-grained lower bounds that depend on the maximum degree Δ. 3) We demonstrate a collection of natural graph problems for which non-component-stable algorithms break the conditional lower bound obtained for component-stable algorithms. This implies that, for both deterministic and randomized algorithms, component-stable algorithms are conditionally weaker than the non-component-stable ones.
Altogether our results imply that component-stability might limit the computational power of the low-space MPC model, paving the way for improved upper bounds that escape the conditional lower bound setting of Ghaffari, Kuhn, and Uitto.},
author = {Czumaj, Artur and Davies, Peter and Parter, Merav},
booktitle = {Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing},
isbn = {9781450385480},
location = {Virtual, Italy},
pages = {481–491},
publisher = {Association for Computing Machinery},
title = {{Component stability in low-space massively parallel computation}},
doi = {10.1145/3465084.3467903},
year = {2021},
}
@inproceedings{9935,
abstract = {We present a deterministic O(log log log n)-round low-space Massively Parallel Computation (MPC) algorithm for the classical problem of (Δ+1)-coloring on n-vertex graphs. In this model, every machine has sublinear local space of size n^φ for any arbitrary constant φ \in (0,1). Our algorithm works under the relaxed setting where each machine is allowed to perform exponential local computations, while respecting the n^φ space and bandwidth limitations.
Our key technical contribution is a novel derandomization of the ingenious (Δ+1)-coloring local algorithm by Chang-Li-Pettie (STOC 2018, SIAM J. Comput. 2020). The Chang-Li-Pettie algorithm runs in T_local =poly(loglog n) rounds, which sets the state-of-the-art randomized round complexity for the problem in the local model. Our derandomization employs a combination of tools, notably pseudorandom generators (PRG) and bounded-independence hash functions.
The achieved round complexity of O(logloglog n) rounds matches the bound of log(T_local ), which currently serves an upper bound barrier for all known randomized algorithms for locally-checkable problems in this model. Furthermore, no deterministic sublogarithmic low-space MPC algorithms for the (Δ+1)-coloring problem have been known before.},
author = {Czumaj, Artur and Davies, Peter and Parter, Merav},
booktitle = {Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing},
isbn = {978-1-4503-8548-0},
location = {Virtual, Italy},
pages = {469–479},
publisher = {Association for Computing Machinery},
title = {{Improved deterministic (Δ+1) coloring in low-space MPC}},
doi = {10.1145/3465084.3467937},
year = {2021},
}
@article{9952,
abstract = {Proper control of division orientation and symmetry, largely determined by spindle positioning, is essential to development and homeostasis. Spindle positioning has been extensively studied in cells dividing in two-dimensional (2D) environments and in epithelial tissues, where proteins such as NuMA (also known as NUMA1) orient division along the interphase long axis of the cell. However, little is known about how cells control spindle positioning in three-dimensional (3D) environments, such as early mammalian embryos and a variety of adult tissues. Here, we use mouse embryonic stem cells (ESCs), which grow in 3D colonies, as a model to investigate division in 3D. We observe that, at the periphery of 3D colonies, ESCs display high spindle mobility and divide asymmetrically. Our data suggest that enhanced spindle movements are due to unequal distribution of the cell–cell junction protein E-cadherin between future daughter cells. Interestingly, when cells progress towards differentiation, division becomes more symmetric, with more elongated shapes in metaphase and enhanced cortical NuMA recruitment in anaphase. Altogether, this study suggests that in 3D contexts, the geometry of the cell and its contacts with neighbors control division orientation and symmetry.},
author = {Chaigne, Agathe and Smith, Matthew B. and Cavestany, R. L. and Hannezo, Edouard B and Chalut, Kevin J. and Paluch, Ewa K.},
issn = {14779137},
journal = {Journal of Cell Science},
number = {14},
publisher = {The Company of Biologists},
title = {{Three-dimensional geometry controls division symmetry in stem cell colonies}},
doi = {10.1242/jcs.255018},
volume = {134},
year = {2021},
}
@inproceedings{9951,
abstract = {There has recently been a surge of interest in the computational and complexity properties of the population model, which assumes n anonymous, computationally-bounded nodes, interacting at random, with the goal of jointly computing global predicates. Significant work has gone towards investigating majority or consensus dynamics in this model: that is, assuming that every node is initially in one of two states X or Y, determine which state had higher initial count.
In this paper, we consider a natural generalization of majority/consensus, which we call comparison : in its simplest formulation, we are given two baseline states, X and Y, present in any initial configuration in fixed, but possibly small counts. One of these states has higher count than the other: we will assume |X_0| > C |Y_0| for some constant C > 1. The challenge is to design a protocol by which nodes can quickly and reliably decide on which of the baseline states X_0 and Y_0 has higher initial count. We begin by analyzing a simple and general dynamics solving the above comparison problem, which uses O( log n ) states per node, and converges in O(log n) (parallel) time, with high probability, to a state where the whole population votes on opinions X or Y at rates proportional to the initial concentrations of |X_0| vs. |Y_0|. We then describe how this procedure can be bootstrapped to solve comparison, i.e. have every node in the population reach the "correct'' decision, with probability 1 - o(1), at the cost of O (log log n) additional states. Further, we prove that this dynamics is self-stabilizing, in the sense that it converges to the correct decision from arbitrary initial states, and leak-robust, in the sense that it can withstand spurious faulty reactions, which are known to occur in practical implementations of population protocols. Our analysis is based on a new martingale concentration result relating the discrete-time evolution of a population protocol to its expected (steady-state) analysis, which should be a useful tool when analyzing opinion dynamics and epidemic dissemination in the population model.},
author = {Alistarh, Dan-Adrian and Töpfer, Martin and Uznański, Przemysław},
booktitle = {Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing},
isbn = {9781450385480},
location = {Virtual, Italy},
pages = {55--65},
publisher = {Association for Computing Machinery},
title = {{Comparison dynamics in population protocols}},
doi = {10.1145/3465084.3467915},
year = {2021},
}
@article{9874,
abstract = {Myocardial regeneration is restricted to early postnatal life, when mammalian cardiomyocytes still retain the ability to proliferate. The molecular cues that induce cell cycle arrest of neonatal cardiomyocytes towards terminally differentiated adult heart muscle cells remain obscure. Here we report that the miR-106b~25 cluster is higher expressed in the early postnatal myocardium and decreases in expression towards adulthood, especially under conditions of overload, and orchestrates the transition of cardiomyocyte hyperplasia towards cell cycle arrest and hypertrophy by virtue of its targetome. In line, gene delivery of miR-106b~25 to the mouse heart provokes cardiomyocyte proliferation by targeting a network of negative cell cycle regulators including E2f5, Cdkn1c, Ccne1 and Wee1. Conversely, gene-targeted miR-106b~25 null mice display spontaneous hypertrophic remodeling and exaggerated remodeling to overload by derepression of the prohypertrophic transcription factors Hand2 and Mef2d. Taking advantage of the regulatory function of miR-106b~25 on cardiomyocyte hyperplasia and hypertrophy, viral gene delivery of miR-106b~25 provokes nearly complete regeneration of the adult myocardium after ischemic injury. Our data demonstrate that exploitation of conserved molecular programs can enhance the regenerative capacity of the injured heart.},
author = {Raso, Andrea and Dirkx, Ellen and Sampaio-Pinto, Vasco and el Azzouzi, Hamid and Cubero, Ryan J and Sorensen, Daniel W. and Ottaviani, Lara and Olieslagers, Servé and Huibers, Manon M. and de Weger, Roel and Siddiqi, Sailay and Moimas, Silvia and Torrini, Consuelo and Zentillin, Lorena and Braga, Luca and Nascimento, Diana S. and da Costa Martins, Paula A. and van Berlo, Jop H. and Zacchigna, Serena and Giacca, Mauro and De Windt, Leon J.},
issn = {2041-1723},
journal = {Nature Communications},
number = {1},
publisher = {Springer Nature},
title = {{A microRNA program regulates the balance between cardiomyocyte hyperplasia and hypertrophy and stimulates cardiac regeneration}},
doi = {10.1038/s41467-021-25211-4},
volume = {12},
year = {2021},
}
@article{9793,
abstract = {Astrocytes extensively infiltrate the neuropil to regulate critical aspects of synaptic development and function. This process is regulated by transcellular interactions between astrocytes and neurons via cell adhesion molecules. How astrocytes coordinate developmental processes among one another to parse out the synaptic neuropil and form non-overlapping territories is unknown. Here we identify a molecular mechanism regulating astrocyte-astrocyte interactions during development to coordinate astrocyte morphogenesis and gap junction coupling. We show that hepaCAM, a disease-linked, astrocyte-enriched cell adhesion molecule, regulates astrocyte competition for territory and morphological complexity in the developing mouse cortex. Furthermore, conditional deletion of Hepacam from developing astrocytes significantly impairs gap junction coupling between astrocytes and disrupts the balance between synaptic excitation and inhibition. Mutations in HEPACAM cause megalencephalic leukoencephalopathy with subcortical cysts in humans. Therefore, our findings suggest that disruption of astrocyte self-organization mechanisms could be an underlying cause of neural pathology.},
author = {Baldwin, Katherine T. and Tan, Christabel X. and Strader, Samuel T. and Jiang, Changyu and Savage, Justin T. and Elorza-Vidal, Xabier and Contreras, Ximena and Rülicke, Thomas and Hippenmeyer, Simon and Estévez, Raúl and Ji, Ru-Rong and Eroglu, Cagla},
issn = {1097-4199},
journal = {Neuron},
number = {15},
pages = {2427--2442.e10},
publisher = {Elsevier},
title = {{HepaCAM controls astrocyte self-organization and coupling}},
doi = {10.1016/j.neuron.2021.05.025},
volume = {109},
year = {2021},
}
@article{9818,
abstract = {Triangle mesh-based simulations are able to produce satisfying animations of knitted and woven cloth; however, they lack the rich geometric detail of yarn-level simulations. Naive texturing approaches do not consider yarn-level physics, while full yarn-level simulations may become prohibitively expensive for large garments. We propose a method to animate yarn-level cloth geometry on top of an underlying deforming mesh in a mechanics-aware fashion. Using triangle strains to interpolate precomputed yarn geometry, we are able to reproduce effects such as knit loops tightening under stretching. In combination with precomputed mesh animation or real-time mesh simulation, our method is able to animate yarn-level cloth in real-time at large scales.},
author = {Sperl, Georg and Narain, Rahul and Wojtan, Christopher J},
issn = {15577368},
journal = {ACM Transactions on Graphics},
number = {4},
publisher = {Association for Computing Machinery},
title = {{Mechanics-aware deformation of yarn pattern geometry}},
doi = {10.1145/3450626.3459816},
volume = {40},
year = {2021},
}
@misc{9327,
abstract = {This archive contains the missing sweater mesh animations and displacement models for the code of "Mechanics-Aware Deformation of Yarn Pattern Geometry"
Code Repository: https://git.ist.ac.at/gsperl/MADYPG},
author = {Sperl, Georg and Narain, Rahul and Wojtan, Christopher J},
publisher = {IST Austria},
title = {{Mechanics-Aware Deformation of Yarn Pattern Geometry (Additional Animation/Model Data)}},
doi = {10.15479/AT:ISTA:9327},
year = {2021},
}