@article{12822, abstract = {Gears and cogwheels are elemental components of machines. They restrain degrees of freedom and channel power into a specified motion. Building and powering small-scale cogwheels are key steps toward feasible micro and nanomachinery. Assembly, energy injection, and control are, however, a challenge at the microscale. In contrast with passive gears, whose function is to transmit torques from one to another, interlocking and untethered active gears have the potential to unveil dynamics and functions untapped by externally driven mechanisms. Here, it is shown the assembly and control of a family of self-spinning cogwheels with varying teeth numbers and study the interlocking of multiple cogwheels. The teeth are formed by colloidal microswimmers that power the structure. The cogwheels are autonomous and active, showing persistent rotation. Leveraging the angular momentum of optical vortices, we control the direction of rotation of the cogwheels. The pairs of interlocking and active cogwheels that roll over each other in a random walk and have curvature-dependent mobility are studied. This behavior is leveraged to self-position parts and program microbots, demonstrating the ability to pick up, direct, and release a load. The work constitutes a step toward autonomous machinery with external control as well as (re)programmable microbots and matter.}, author = {Martinet, Quentin and Aubret, Antoine and Palacci, Jérémie A}, issn = {2640-4567}, journal = {Advanced Intelligent Systems}, number = {1}, publisher = {Wiley}, title = {{Rotation control, interlocking, and self‐positioning of active cogwheels}}, doi = {10.1002/aisy.202200129}, volume = {5}, year = {2023}, } @article{12818, abstract = {The multicellular organization of diverse systems, including embryos, intestines, and tumors relies on coordinated cell migration in curved environments. In these settings, cells establish supracellular patterns of motion, including collective rotation and invasion. While such collective modes have been studied extensively in flat systems, the consequences of geometrical and topological constraints on collective migration in curved systems are largely unknown. Here, we discover a collective mode of cell migration in rotating spherical tissues manifesting as a propagating single-wavelength velocity wave. This wave is accompanied by an apparently incompressible supracellular flow pattern featuring topological defects as dictated by the spherical topology. Using a minimal active particle model, we reveal that this collective mode arises from the effect of curvature on the active flocking behavior of a cell layer confined to a spherical surface. Our results thus identify curvature-induced velocity waves as a mode of collective cell migration, impacting the dynamical organization of 3D curved tissues.}, author = {Brandstätter, Tom and Brückner, David and Han, Yu Long and Alert, Ricard and Guo, Ming and Broedersz, Chase P.}, issn = {2041-1723}, journal = {Nature Communications}, publisher = {Springer Nature}, title = {{Curvature induces active velocity waves in rotating spherical tissues}}, doi = {10.1038/s41467-023-37054-2}, volume = {14}, year = {2023}, } @article{12819, abstract = {Reaching a high cavity population with a coherent pump in the strong-coupling regime of a single-atom laser is impossible due to the photon blockade effect. In this Letter, we experimentally demonstrate that in a single-atom maser based on a transmon strongly coupled to two resonators, it is possible to pump over a dozen photons into the system. The first high-quality resonator plays the role of a usual lasing cavity, and the second one presents a controlled dissipation channel, bolstering population inversion, and modifies the energy-level structure to lift the blockade. As confirmation of the lasing action, we observe conventional laser features such as a narrowing of the emission linewidth and external signal amplification. Additionally, we report unique single-atom features: self-quenching and several lasing thresholds.}, author = {Sokolova, Alesya and Kalacheva, D. A. and Fedorov, G. P. and Astafiev, O. V.}, issn = {2469-9934}, journal = {Physical Review A}, number = {3}, publisher = {American Physical Society}, title = {{Overcoming photon blockade in a circuit-QED single-atom maser with engineered metastability and strong coupling}}, doi = {10.1103/PhysRevA.107.L031701}, volume = {107}, year = {2023}, } @article{12861, abstract = {The field of indirect reciprocity investigates how social norms can foster cooperation when individuals continuously monitor and assess each other’s social interactions. By adhering to certain social norms, cooperating individuals can improve their reputation and, in turn, receive benefits from others. Eight social norms, known as the “leading eight," have been shown to effectively promote the evolution of cooperation as long as information is public and reliable. These norms categorize group members as either ’good’ or ’bad’. In this study, we examine a scenario where individuals instead assign nuanced reputation scores to each other, and only cooperate with those whose reputation exceeds a certain threshold. We find both analytically and through simulations that such quantitative assessments are error-correcting, thus facilitating cooperation in situations where information is private and unreliable. Moreover, our results identify four specific norms that are robust to such conditions, and may be relevant for helping to sustain cooperation in natural populations.}, author = {Schmid, Laura and Ekbatani, Farbod and Hilbe, Christian and Chatterjee, Krishnendu}, issn = {2041-1723}, journal = {Nature Communications}, publisher = {Springer Nature}, title = {{Quantitative assessment can stabilize indirect reciprocity under imperfect information}}, doi = {10.1038/s41467-023-37817-x}, volume = {14}, year = {2023}, } @article{12862, abstract = {Despite the considerable progress of in vivo neural recording techniques, inferring the biophysical mechanisms underlying large scale coordination of brain activity from neural data remains challenging. One obstacle is the difficulty to link high dimensional functional connectivity measures to mechanistic models of network activity. We address this issue by investigating spike-field coupling (SFC) measurements, which quantify the synchronization between, on the one hand, the action potentials produced by neurons, and on the other hand mesoscopic “field” signals, reflecting subthreshold activities at possibly multiple recording sites. As the number of recording sites gets large, the amount of pairwise SFC measurements becomes overwhelmingly challenging to interpret. We develop Generalized Phase Locking Analysis (GPLA) as an interpretable dimensionality reduction of this multivariate SFC. GPLA describes the dominant coupling between field activity and neural ensembles across space and frequencies. We show that GPLA features are biophysically interpretable when used in conjunction with appropriate network models, such that we can identify the influence of underlying circuit properties on these features. We demonstrate the statistical benefits and interpretability of this approach in various computational models and Utah array recordings. The results suggest that GPLA, used jointly with biophysical modeling, can help uncover the contribution of recurrent microcircuits to the spatio-temporal dynamics observed in multi-channel experimental recordings.}, author = {Safavi, Shervin and Panagiotaropoulos, Theofanis I. and Kapoor, Vishal and Ramirez Villegas, Juan F and Logothetis, Nikos K. and Besserve, Michel}, issn = {1553-7358}, journal = {PLoS Computational Biology}, number = {4}, publisher = {Public Library of Science}, title = {{Uncovering the organization of neural circuits with Generalized Phase Locking Analysis}}, doi = {10.1371/journal.pcbi.1010983}, volume = {19}, year = {2023}, } @article{12879, abstract = {Machine learning (ML) has been widely applied to chemical property prediction, most prominently for the energies and forces in molecules and materials. The strong interest in predicting energies in particular has led to a ‘local energy’-based paradigm for modern atomistic ML models, which ensures size-extensivity and a linear scaling of computational cost with system size. However, many electronic properties (such as excitation energies or ionization energies) do not necessarily scale linearly with system size and may even be spatially localized. Using size-extensive models in these cases can lead to large errors. In this work, we explore different strategies for learning intensive and localized properties, using HOMO energies in organic molecules as a representative test case. In particular, we analyze the pooling functions that atomistic neural networks use to predict molecular properties, and suggest an orbital weighted average (OWA) approach that enables the accurate prediction of orbital energies and locations.}, author = {Chen, Ke and Kunkel, Christian and Cheng, Bingqing and Reuter, Karsten and Margraf, Johannes T.}, issn = {2041-6539}, journal = {Chemical Science}, publisher = {Royal Society of Chemistry}, title = {{Physics-inspired machine learning of localized intensive properties}}, doi = {10.1039/d3sc00841j}, year = {2023}, } @article{12878, abstract = {Salicylic acid (SA) plays important roles in different aspects of plant development, including root growth, where auxin is also a major player by means of its asymmetric distribution. However, the mechanism underlying the effect of SA on the development of rice roots remains poorly understood. Here, we show that SA inhibits rice root growth by interfering with auxin transport associated with the OsPIN3t- and clathrin-mediated gene regulatory network (GRN). SA inhibits root growth as well as Brefeldin A-sensitive trafficking through a non-canonical SA signaling mechanism. Transcriptome analysis of rice seedlings treated with SA revealed that the OsPIN3t auxin transporter is at the center of a GRN involving the coat protein clathrin. The root growth and endocytic trafficking in both the pin3t and clathrin heavy chain mutants were SA insensitivity. SA inhibitory effect on the endocytosis of OsPIN3t was dependent on clathrin; however, the root growth and endocytic trafficking mediated by tyrphostin A23 (TyrA23) were independent of the pin3t mutant under SA treatment. These data reveal that SA affects rice root growth through the convergence of transcriptional and non-SA signaling mechanisms involving OsPIN3t-mediated auxin transport and clathrin-mediated trafficking as key components.}, author = {Jiang, Lihui and Yao, Baolin and Zhang, Xiaoyan and Wu, Lixia and Fu, Qijing and Zhao, Yiting and Cao, Yuxin and Zhu, Ruomeng and Lu, Xinqi and Huang, Wuying and Zhao, Jianping and Li, Kuixiu and Zhao, Shuanglu and Han, Li and Zhou, Xuan and Luo, Chongyu and Zhu, Haiyan and Yang, Jing and Huang, Huichuan and Zhu, Zhengge and He, Xiahong and Friml, Jiří and Zhang, Zhongkai and Liu, Changning and Du, Yunlong}, issn = {1365-313X}, journal = {Plant Journal}, number = {1}, pages = {155--174}, publisher = {Wiley}, title = {{Salicylic acid inhibits rice endocytic protein trafficking mediated by OsPIN3t and clathrin to affect root growth}}, doi = {10.1111/tpj.16218}, volume = {115}, year = {2023}, } @article{12876, abstract = {Motivation: The problem of model inference is of fundamental importance to systems biology. Logical models (e.g. Boolean networks; BNs) represent a computationally attractive approach capable of handling large biological networks. The models are typically inferred from experimental data. However, even with a substantial amount of experimental data supported by some prior knowledge, existing inference methods often focus on a small sample of admissible candidate models only. Results: We propose Boolean network sketches as a new formal instrument for the inference of Boolean networks. A sketch integrates (typically partial) knowledge about the network’s topology and the update logic (obtained through, e.g. a biological knowledge base or a literature search), as well as further assumptions about the properties of the network’s transitions (e.g. the form of its attractor landscape), and additional restrictions on the model dynamics given by the measured experimental data. Our new BNs inference algorithm starts with an ‘initial’ sketch, which is extended by adding restrictions representing experimental data to a ‘data-informed’ sketch and subsequently computes all BNs consistent with the data-informed sketch. Our algorithm is based on a symbolic representation and coloured model-checking. Our approach is unique in its ability to cover a broad spectrum of knowledge and efficiently produce a compact representation of all inferred BNs. We evaluate the method on a non-trivial collection of real-world and simulated data.}, author = {Beneš, Nikola and Brim, Luboš and Huvar, Ondřej and Pastva, Samuel and Šafránek, David}, issn = {1367-4811}, journal = {Bioinformatics}, number = {4}, publisher = {Oxford Academic}, title = {{Boolean network sketches: A unifying framework for logical model inference}}, doi = {10.1093/bioinformatics/btad158}, volume = {39}, year = {2023}, } @article{12880, abstract = {Peripheral heterochromatin positioning depends on nuclear envelope associated proteins and repressive histone modifications. Here we show that overexpression (OE) of Lamin B1 (LmnB1) leads to the redistribution of peripheral heterochromatin into heterochromatic foci within the nucleoplasm. These changes represent a perturbation of heterochromatin binding at the nuclear periphery (NP) through a mechanism independent from altering other heterochromatin anchors or histone post-translational modifications. We further show that LmnB1 OE alters gene expression. These changes do not correlate with different levels of H3K9me3, but a significant number of the misregulated genes were likely mislocalized away from the NP upon LmnB1 OE. We also observed an enrichment of developmental processes amongst the upregulated genes. ~74% of these genes were normally repressed in our cell type, suggesting that LmnB1 OE promotes gene de-repression. This demonstrates a broader consequence of LmnB1 OE on cell fate, and highlights the importance of maintaining proper levels of LmnB1.}, author = {Kaneshiro, Jeanae M. and Capitanio, Juliana S. and Hetzer, Martin W}, issn = {1949-1042}, journal = {Nucleus}, number = {1}, publisher = {Taylor & Francis}, title = {{Lamin B1 overexpression alters chromatin organization and gene expression}}, doi = {10.1080/19491034.2023.2202548}, volume = {14}, year = {2023}, } @article{12914, abstract = {We numerically study two methods of measuring tunneling times using a quantum clock. In the conventional method using the Larmor clock, we show that the Larmor tunneling time can be shorter for higher tunneling barriers. In the second method, we study the probability of a spin-flip of a particle when it is transmitted through a potential barrier including a spatially rotating field interacting with its spin. According to the adiabatic theorem, the probability depends on the velocity of the particle inside the barrier. It is numerically observed that the probability increases for higher barriers, which is consistent with the result obtained by the Larmor clock. By comparing outcomes for different initial spin states, we suggest that one of the main causes of the apparent decrease in the tunneling time can be the filtering effect occurring at the end of the barrier.}, author = {Suzuki, Fumika and Unruh, William G.}, issn = {2469-9934}, journal = {Physical Review A}, number = {4}, publisher = {American Physical Society}, title = {{Numerical quantum clock simulations for measuring tunneling times}}, doi = {10.1103/PhysRevA.107.042216}, volume = {107}, year = {2023}, }