@article{14447, abstract = {Auxin belongs among major phytohormones and governs multiple aspects of plant growth and development. The establishment of auxin concentration gradients, determines, among other processes, plant organ positioning and growth responses to environmental stimuli. Herein we report the synthesis of new NBD- or DNS-labelled IAA derivatives and the elucidation of their biological activity, fluorescence properties and subcellular accumulation patterns in planta. These novel compounds did not show auxin-like activity, but instead antagonized physiological auxin effects. The DNS-labelled derivatives FL5 and FL6 showed strong anti-auxin activity in roots and hypocotyls, which also occurred at the level of gene transcription as confirmed by quantitative PCR analysis. The auxin antagonism of our derivatives was further demonstrated in vitro using an SPR-based binding assay. The NBD-labelled compound FL4 with the best fluorescence properties proved to be unsuitable to study auxin accumulation patterns in planta. On the other hand, the strongest anti-auxin activity possessing compounds FL5 and FL6 could be useful to study binding mechanisms to auxin receptors and for manipulations of auxin-regulated processes.}, author = {Bieleszová, Kristýna and Hladík, Pavel and Kubala, Martin and Napier, Richard and Brunoni, Federica and Gelová, Zuzana and Fiedler, Lukas and Kulich, Ivan and Strnad, Miroslav and Doležal, Karel and Novák, Ondřej and Friml, Jiří and Žukauskaitė, Asta}, issn = {1573-5087}, journal = {Plant Growth Regulation}, publisher = {Springer Nature}, title = {{New fluorescent auxin derivatives: anti-auxin activity and accumulation patterns in Arabidopsis thaliana}}, doi = {10.1007/s10725-023-01083-0}, year = {2023}, } @inproceedings{14448, abstract = {We consider the problem of solving LP relaxations of MAP-MRF inference problems, and in particular the method proposed recently in [16], [35]. As a key computational subroutine, it uses a variant of the Frank-Wolfe (FW) method to minimize a smooth convex function over a combinatorial polytope. We propose an efficient implementation of this subroutine based on in-face Frank-Wolfe directions, introduced in [4] in a different context. More generally, we define an abstract data structure for a combinatorial subproblem that enables in-face FW directions, and describe its specialization for tree-structured MAP-MRF inference subproblems. Experimental results indicate that the resulting method is the current state-of-art LP solver for some classes of problems. Our code is available at pub.ist.ac.at/~vnk/papers/IN-FACE-FW.html.}, author = {Kolmogorov, Vladimir}, booktitle = {Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition}, isbn = {9798350301298}, issn = {1063-6919}, location = {Vancouver, Canada}, pages = {11980--11989}, publisher = {IEEE}, title = {{Solving relaxations of MAP-MRF problems: Combinatorial in-face Frank-Wolfe directions}}, doi = {10.1109/CVPR52729.2023.01153}, volume = {2023}, year = {2023}, } @article{14449, abstract = {The rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which could substantially improve healthcare practices in the era of precision medicine. However, several challenges must be addressed to exploit the benefits of ML in this field fully. In particular, there is a need to establish “gold standard” protocols for conducting ML analysis experiments and improve interactions between microbiome researchers and ML experts. The Machine Learning Techniques in Human Microbiome Studies (ML4Microbiome) COST Action CA18131 is a European network established in 2019 to promote collaboration between discovery-oriented microbiome researchers and data-driven ML experts to optimize and standardize ML approaches for microbiome analysis. This perspective paper presents the key achievements of ML4Microbiome, which include identifying predictive and discriminatory ‘omics’ features, improving repeatability and comparability, developing automation procedures, and defining priority areas for the novel development of ML methods targeting the microbiome. The insights gained from ML4Microbiome will help to maximize the potential of ML in microbiome research and pave the way for new and improved healthcare practices.}, author = {D’Elia, Domenica and Truu, Jaak and Lahti, Leo and Berland, Magali and Papoutsoglou, Georgios and Ceci, Michelangelo and Zomer, Aldert and Lopes, Marta B. and Ibrahimi, Eliana and Gruca, Aleksandra and Nechyporenko, Alina and Frohme, Marcus and Klammsteiner, Thomas and Pau, Enrique Carrillo De Santa and Marcos-Zambrano, Laura Judith and Hron, Karel and Pio, Gianvito and Simeon, Andrea and Suharoschi, Ramona and Moreno-Indias, Isabel and Temko, Andriy and Nedyalkova, Miroslava and Apostol, Elena Simona and Truică, Ciprian Octavian and Shigdel, Rajesh and Telalović, Jasminka Hasić and Bongcam-Rudloff, Erik and Przymus, Piotr and Jordamović, Naida Babić and Falquet, Laurent and Tarazona, Sonia and Sampri, Alexia and Isola, Gaetano and Pérez-Serrano, David and Trajkovik, Vladimir and Klucar, Lubos and Loncar-Turukalo, Tatjana and Havulinna, Aki S. and Jansen, Christian and Bertelsen, Randi J. and Claesson, Marcus Joakim}, issn = {1664-302X}, journal = {Frontiers in Microbiology}, publisher = {Frontiers}, title = {{Advancing microbiome research with machine learning: Key findings from the ML4Microbiome COST action}}, doi = {10.3389/fmicb.2023.1257002}, volume = {14}, year = {2023}, } @article{14451, abstract = {We investigate the potential of Multi-Objective, Deep Reinforcement Learning for stock and cryptocurrency single-asset trading: in particular, we consider a Multi-Objective algorithm which generalizes the reward functions and discount factor (i.e., these components are not specified a priori, but incorporated in the learning process). Firstly, using several important assets (BTCUSD, ETHUSDT, XRPUSDT, AAPL, SPY, NIFTY50), we verify the reward generalization property of the proposed Multi-Objective algorithm, and provide preliminary statistical evidence showing increased predictive stability over the corresponding Single-Objective strategy. Secondly, we show that the Multi-Objective algorithm has a clear edge over the corresponding Single-Objective strategy when the reward mechanism is sparse (i.e., when non-null feedback is infrequent over time). Finally, we discuss the generalization properties with respect to the discount factor. The entirety of our code is provided in open-source format.}, author = {Cornalba, Federico and Disselkamp, Constantin and Scassola, Davide and Helf, Christopher}, issn = {1433-3058}, journal = {Neural Computing and Applications}, publisher = {Springer Nature}, title = {{Multi-objective reward generalization: improving performance of Deep Reinforcement Learning for applications in single-asset trading}}, doi = {10.1007/s00521-023-09033-7}, year = {2023}, } @article{14452, abstract = {The classical infinitesimal model is a simple and robust model for the inheritance of quantitative traits. In this model, a quantitative trait is expressed as the sum of a genetic and an environmental component, and the genetic component of offspring traits within a family follows a normal distribution around the average of the parents’ trait values, and has a variance that is independent of the parental traits. In previous work, we showed that when trait values are determined by the sum of a large number of additive Mendelian factors, each of small effect, one can justify the infinitesimal model as a limit of Mendelian inheritance. In this paper, we show that this result extends to include dominance. We define the model in terms of classical quantities of quantitative genetics, before justifying it as a limit of Mendelian inheritance as the number, M, of underlying loci tends to infinity. As in the additive case, the multivariate normal distribution of trait values across the pedigree can be expressed in terms of variance components in an ancestral population and probabilities of identity by descent determined by the pedigree. Now, with just first-order dominance effects, we require two-, three-, and four-way identities. We also show that, even if we condition on parental trait values, the “shared” and “residual” components of trait values within each family will be asymptotically normally distributed as the number of loci tends to infinity, with an error of order 1/M−−√⁠. We illustrate our results with some numerical examples.}, author = {Barton, Nicholas H and Etheridge, Alison M. and Véber, Amandine}, issn = {1943-2631}, journal = {Genetics}, number = {2}, publisher = {Oxford Academic}, title = {{The infinitesimal model with dominance}}, doi = {10.1093/genetics/iyad133}, volume = {225}, year = {2023}, } @article{14453, abstract = {Squall lines are substantially influenced by the interaction of low-level shear with cold pools associated with convective downdrafts. Beyond an optimal shear amplitude, squall lines tend to orient themselves at an angle with respect to the low-level shear. While the mechanisms behind squall line orientation seem to be increasingly well understood, uncertainties remain on the implications of this orientation. Roca and Fiolleau (2020, https://doi.org/10.1038/s43247-020-00015-4) show that long lived mesoscale convective systems, including squall lines, are disproportionately involved in rainfall extremes in the tropics. This article investigates the influence of the interaction between low-level shear and squall line outflow on squall line generated precipitation extrema in the tropics. Using a cloud resolving model, simulated squall lines in radiative convective equilibrium amid a shear-dominated regime (super optimal), a balanced regime (optimal), and an outflow dominated regime (suboptimal). Our results show that precipitation extremes in squall lines are 40% more intense in the case of optimal shear and remain 30% superior in the superoptimal regime relative to a disorganized case. With a theoretical scaling of precipitation extremes (C. Muller & Takayabu, 2020, https://doi.org/10.1088/1748-9326/ab7130), we show that the condensation rates control the amplification of precipitation extremes in tropical squall lines, mainly due to its change in vertical mass flux (dynamic component). The reduction of dilution by entrainment explains half of this change, consistent with Mulholland et al. (2021, https://doi.org/10.1175/jas-d-20-0299.1). The other half is explained by increased cloud-base velocity intensity in optimal and superoptimal squall lines.}, author = {Abramian, Sophie and Muller, Caroline J and Risi, Camille}, issn = {1942-2466}, journal = {Journal of Advances in Modeling Earth Systems}, number = {10}, publisher = {Wiley}, title = {{Extreme precipitation in tropical squall lines}}, doi = {10.1029/2022MS003477}, volume = {15}, year = {2023}, } @inproceedings{14454, abstract = {As AI and machine-learned software are used increasingly for making decisions that affect humans, it is imperative that they remain fair and unbiased in their decisions. To complement design-time bias mitigation measures, runtime verification techniques have been introduced recently to monitor the algorithmic fairness of deployed systems. Previous monitoring techniques assume full observability of the states of the (unknown) monitored system. Moreover, they can monitor only fairness properties that are specified as arithmetic expressions over the probabilities of different events. In this work, we extend fairness monitoring to systems modeled as partially observed Markov chains (POMC), and to specifications containing arithmetic expressions over the expected values of numerical functions on event sequences. The only assumptions we make are that the underlying POMC is aperiodic and starts in the stationary distribution, with a bound on its mixing time being known. These assumptions enable us to estimate a given property for the entire distribution of possible executions of the monitored POMC, by observing only a single execution. Our monitors observe a long run of the system and, after each new observation, output updated PAC-estimates of how fair or biased the system is. The monitors are computationally lightweight and, using a prototype implementation, we demonstrate their effectiveness on several real-world examples.}, author = {Henzinger, Thomas A and Kueffner, Konstantin and Mallik, Kaushik}, booktitle = {23rd International Conference on Runtime Verification}, isbn = {9783031442667}, issn = {1611-3349}, location = {Thessaloniki, Greece}, pages = {291--311}, publisher = {Springer Nature}, title = {{Monitoring algorithmic fairness under partial observations}}, doi = {10.1007/978-3-031-44267-4_15}, volume = {14245}, year = {2023}, } @article{14455, author = {Narzisi, Antonio and Halladay, Alycia and Masi, Gabriele and Novarino, Gaia and Lord, Catherine}, issn = {1664-0640}, journal = {Frontiers in Psychiatry}, publisher = {Frontiers}, title = {{Tempering expectations: Considerations on the current state of stem cells therapy for autism treatment}}, doi = {10.3389/fpsyt.2023.1287879}, volume = {14}, year = {2023}, } @inproceedings{14456, abstract = {In this paper, we present novel algorithms that efficiently compute a shortest reconfiguration sequence between two given dominating sets in trees and interval graphs under the TOKEN SLIDING model. In this problem, a graph is provided along with its two dominating sets, which can be imagined as tokens placed on vertices. The objective is to find a shortest sequence of dominating sets that transforms one set into the other, with each set in the sequence resulting from sliding a single token in the previous set. While identifying any sequence has been well studied, our work presents the first polynomial algorithms for this optimization variant in the context of dominating sets.}, author = {Křišťan, Jan Matyáš and Svoboda, Jakub}, booktitle = {24th International Symposium on Fundamentals of Computation Theory}, isbn = {9783031435867}, issn = {1611-3349}, location = {Trier, Germany}, pages = {333--347}, publisher = {Springer Nature}, title = {{Shortest dominating set reconfiguration under token sliding}}, doi = {10.1007/978-3-031-43587-4_24}, volume = {14292}, year = {2023}, } @inproceedings{14457, abstract = {Threshold secret sharing allows a dealer to split a secret s into n shares, such that any t shares allow for reconstructing s, but no t-1 shares reveal any information about s. Leakage-resilient secret sharing requires that the secret remains hidden, even when an adversary additionally obtains a limited amount of leakage from every share. Benhamouda et al. (CRYPTO’18) proved that Shamir’s secret sharing scheme is one bit leakage-resilient for reconstruction threshold t≥0.85n and conjectured that the same holds for t = c.n for any constant 0≤c≤1. Nielsen and Simkin (EUROCRYPT’20) showed that this is the best one can hope for by proving that Shamir’s scheme is not secure against one-bit leakage when t0c.n/log(n). In this work, we strengthen the lower bound of Nielsen and Simkin. We consider noisy leakage-resilience, where a random subset of leakages is replaced by uniformly random noise. We prove a lower bound for Shamir’s secret sharing, similar to that of Nielsen and Simkin, which holds even when a constant fraction of leakages is replaced by random noise. To this end, we first prove a lower bound on the share size of any noisy-leakage-resilient sharing scheme. We then use this lower bound to show that there exist universal constants c1, c2, such that for sufficiently large n it holds that Shamir’s secret sharing scheme is not noisy-leakage-resilient for t≤c1.n/log(n), even when a c2 fraction of leakages are replaced by random noise. }, author = {Hoffmann, Charlotte and Simkin, Mark}, booktitle = {8th International Conference on Cryptology and Information Security in Latin America}, isbn = {9783031444685}, issn = {1611-3349}, location = {Quito, Ecuador}, pages = {215--228}, publisher = {Springer Nature}, title = {{Stronger lower bounds for leakage-resilient secret sharing}}, doi = {10.1007/978-3-031-44469-2_11}, volume = {14168}, year = {2023}, } @inproceedings{14458, abstract = {We show for the first time that large-scale generative pretrained transformer (GPT) family models can be pruned to at least 50% sparsity in one-shot, without any retraining, at minimal loss of accuracy. This is achieved via a new pruning method called SparseGPT, specifically designed to work efficiently and accurately on massive GPT-family models. We can execute SparseGPT on the largest available open-source models, OPT-175B and BLOOM-176B, in under 4.5 hours, and can reach 60% unstructured sparsity with negligible increase in perplexity: remarkably, more than 100 billion weights from these models can be ignored at inference time. SparseGPT generalizes to semi-structured (2:4 and 4:8) patterns, and is compatible with weight quantization approaches. The code is available at: https://github.com/IST-DASLab/sparsegpt.}, author = {Frantar, Elias and Alistarh, Dan-Adrian}, booktitle = {Proceedings of the 40th International Conference on Machine Learning}, issn = {2640-3498}, location = {Honolulu, Hawaii, HI, United States}, pages = {10323--10337}, publisher = {ML Research Press}, title = {{SparseGPT: Massive language models can be accurately pruned in one-shot}}, volume = {202}, year = {2023}, } @inproceedings{14459, abstract = {Autoencoders are a popular model in many branches of machine learning and lossy data compression. However, their fundamental limits, the performance of gradient methods and the features learnt during optimization remain poorly understood, even in the two-layer setting. In fact, earlier work has considered either linear autoencoders or specific training regimes (leading to vanishing or diverging compression rates). Our paper addresses this gap by focusing on non-linear two-layer autoencoders trained in the challenging proportional regime in which the input dimension scales linearly with the size of the representation. Our results characterize the minimizers of the population risk, and show that such minimizers are achieved by gradient methods; their structure is also unveiled, thus leading to a concise description of the features obtained via training. For the special case of a sign activation function, our analysis establishes the fundamental limits for the lossy compression of Gaussian sources via (shallow) autoencoders. Finally, while the results are proved for Gaussian data, numerical simulations on standard datasets display the universality of the theoretical predictions.}, author = {Shevchenko, Aleksandr and Kögler, Kevin and Hassani, Hamed and Mondelli, Marco}, booktitle = {Proceedings of the 40th International Conference on Machine Learning}, issn = {2640-3498}, location = {Honolulu, Hawaii, HI, United States}, pages = {31151--31209}, publisher = {ML Research Press}, title = {{Fundamental limits of two-layer autoencoders, and achieving them with gradient methods}}, volume = {202}, year = {2023}, } @inproceedings{14460, abstract = {We provide an efficient implementation of the backpropagation algorithm, specialized to the case where the weights of the neural network being trained are sparse. Our algorithm is general, as it applies to arbitrary (unstructured) sparsity and common layer types (e.g., convolutional or linear). We provide a fast vectorized implementation on commodity CPUs, and show that it can yield speedups in end-to-end runtime experiments, both in transfer learning using already-sparsified networks, and in training sparse networks from scratch. Thus, our results provide the first support for sparse training on commodity hardware.}, author = {Nikdan, Mahdi and Pegolotti, Tommaso and Iofinova, Eugenia B and Kurtic, Eldar and Alistarh, Dan-Adrian}, booktitle = {Proceedings of the 40th International Conference on Machine Learning}, issn = {2640-3498}, location = {Honolulu, Hawaii, HI, United States}, pages = {26215--26227}, publisher = {ML Research Press}, title = {{SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge}}, volume = {202}, year = {2023}, } @inproceedings{14461, abstract = {Communication-reduction techniques are a popular way to improve scalability in data-parallel training of deep neural networks (DNNs). The recent emergence of large language models such as GPT has created the need for new approaches to exploit data-parallelism. Among these, fully-sharded data parallel (FSDP) training is highly popular, yet it still encounters scalability bottlenecks. One reason is that applying compression techniques to FSDP is challenging: as the vast majority of the communication involves the model’s weights, direct compression alters convergence and leads to accuracy loss. We present QSDP, a variant of FSDP which supports both gradient and weight quantization with theoretical guarantees, is simple to implement and has essentially no overheads. To derive QSDP we prove that a natural modification of SGD achieves convergence even when we only maintain quantized weights, and thus the domain over which we train consists of quantized points and is, therefore, highly non-convex. We validate this approach by training GPT-family models with up to 1.3 billion parameters on a multi-node cluster. Experiments show that QSDP preserves model accuracy, while completely removing the communication bottlenecks of FSDP, providing end-to-end speedups of up to 2.2x.}, author = {Markov, Ilia and Vladu, Adrian and Guo, Qi and Alistarh, Dan-Adrian}, booktitle = {Proceedings of the 40th International Conference on Machine Learning}, issn = {2640-3498}, location = {Honolulu, Hawaii, HI, United States}, pages = {24020--24044}, publisher = {ML Research Press}, title = {{Quantized distributed training of large models with convergence guarantees}}, volume = {202}, year = {2023}, } @inproceedings{14462, abstract = {We study fine-grained error bounds for differentially private algorithms for counting under continual observation. Our main insight is that the matrix mechanism when using lower-triangular matrices can be used in the continual observation model. More specifically, we give an explicit factorization for the counting matrix Mcount and upper bound the error explicitly. We also give a fine-grained analysis, specifying the exact constant in the upper bound. Our analysis is based on upper and lower bounds of the completely bounded norm (cb-norm) of Mcount . Along the way, we improve the best-known bound of 28 years by Mathias (SIAM Journal on Matrix Analysis and Applications, 1993) on the cb-norm of Mcount for a large range of the dimension of Mcount. Furthermore, we are the first to give concrete error bounds for various problems under continual observation such as binary counting, maintaining a histogram, releasing an approximately cut-preserving synthetic graph, many graph-based statistics, and substring and episode counting. Finally, we note that our result can be used to get a fine-grained error bound for non-interactive local learning and the first lower bounds on the additive error for (ϵ,δ)-differentially-private counting under continual observation. Subsequent to this work, Henzinger et al. (SODA, 2023) showed that our factorization also achieves fine-grained mean-squared error.}, author = {Fichtenberger, Hendrik and Henzinger, Monika H and Upadhyay, Jalaj}, booktitle = {Proceedings of the 40th International Conference on Machine Learning}, issn = {2640-3498}, location = {Honolulu, Hawaii, HI, United States}, pages = {10072--10092}, publisher = {ML Research Press}, title = {{Constant matters: Fine-grained error bound on differentially private continual observation}}, volume = {202}, year = {2023}, } @article{14463, abstract = {Inversions are thought to play a key role in adaptation and speciation, suppressing recombination between diverging populations. Genes influencing adaptive traits cluster in inversions, and changes in inversion frequencies are associated with environmental differences. However, in many organisms, it is unclear if inversions are geographically and taxonomically widespread. The intertidal snail, Littorina saxatilis, is one such example. Strong associations between putative polymorphic inversions and phenotypic differences have been demonstrated between two ecotypes of L. saxatilis in Sweden and inferred elsewhere, but no direct evidence for inversion polymorphism currently exists across the species range. Using whole genome data from 107 snails, most inversion polymorphisms were found to be widespread across the species range. The frequencies of some inversion arrangements were significantly different among ecotypes, suggesting a parallel adaptive role. Many inversions were also polymorphic in the sister species, L. arcana, hinting at an ancient origin.}, author = {Reeve, James and Butlin, Roger K. and Koch, Eva L. and Stankowski, Sean and Faria, Rui}, issn = {1365-294X}, journal = {Molecular Ecology}, publisher = {Wiley}, title = {{Chromosomal inversion polymorphisms are widespread across the species ranges of rough periwinkles (Littorina saxatilis and L. arcana)}}, doi = {10.1111/mec.17160}, year = {2023}, } @article{14464, abstract = {Given a triangle Δ, we study the problem of determining the smallest enclosing and largest embedded isosceles triangles of Δ with respect to area and perimeter. This problem was initially posed by Nandakumar [17, 22] and was first studied by Kiss, Pach, and Somlai [13], who showed that if Δ′ is the smallest area isosceles triangle containing Δ, then Δ′ and Δ share a side and an angle. In the present paper, we prove that for any triangle Δ, every maximum area isosceles triangle embedded in Δ and every maximum perimeter isosceles triangle embedded in Δ shares a side and an angle with Δ. Somewhat surprisingly, the case of minimum perimeter enclosing triangles is different: there are infinite families of triangles Δ whose minimum perimeter isosceles containers do not share a side and an angle with Δ.}, author = {Ambrus, Áron and Csikós, Mónika and Kiss, Gergely and Pach, János and Somlai, Gábor}, issn = {1793-6373}, journal = {International Journal of Foundations of Computer Science}, number = {7}, pages = {737--760}, publisher = {World Scientific Publishing}, title = {{Optimal embedded and enclosing isosceles triangles}}, doi = {10.1142/S012905412342008X}, volume = {34}, year = {2023}, } @article{14466, abstract = {The first long-lived turbulent structures observable in planar shear flows take the form of localized stripes, inclined with respect to the mean flow direction. The dynamics of these stripes is central to transition, and recent studies proposed an analogy to directed percolation where the stripes’ proliferation is ultimately responsible for the turbulence becoming sustained. In the present study we focus on the internal stripe dynamics as well as on the eventual stripe expansion, and we compare the underlying mechanisms in pressure- and shear-driven planar flows, respectively, plane-Poiseuille and plane-Couette flow. Despite the similarities of the overall laminar–turbulence patterns, the stripe proliferation processes in the two cases are fundamentally different. Starting from the growth and sustenance of individual stripes, we find that in plane-Couette flow new streaks are created stochastically throughout the stripe whereas in plane-Poiseuille flow streak creation is deterministic and occurs locally at the downstream tip. Because of the up/downstream symmetry, Couette stripes, in contrast to Poiseuille stripes, have two weak and two strong laminar turbulent interfaces. These differences in symmetry as well as in internal growth give rise to two fundamentally different stripe splitting mechanisms. In plane-Poiseuille flow splitting is connected to the elongational growth of the original stripe, and it results from a break-off/shedding of the stripe's tail. In plane-Couette flow splitting follows from a broadening of the original stripe and a division along the stripe into two slimmer stripes.}, author = {Marensi, Elena and Yalniz, Gökhan and Hof, Björn}, issn = {1469-7645}, journal = {Journal of Fluid Mechanics}, keywords = {turbulence, transition to turbulence, patterns}, publisher = {Cambridge University Press}, title = {{Dynamics and proliferation of turbulent stripes in plane-Poiseuille and plane-Couette flows}}, doi = {10.1017/jfm.2023.780}, volume = {974}, year = {2023}, } @misc{14472, abstract = {Data related to the following paper: "Stress granules plug and stabilize damaged endolysosomal membranes" (https://doi.org/10.1038/s41586-023-06726-w) Abstract: Endomembrane damage represents a form of stress that is detrimental for eukaryotic cells. To cope with this threat, cells possess mechanisms that repair the damage and restore cellular homeostasis. Endomembrane damage also results in organelle instability and the mechanisms by which cells stabilize damaged endomembranes to enable membrane repair remains unknown. In this work we use a minimal coarse-grained molecular dynamics system to explore how lipid vesicles undergoing poration in a protein-rich medium can be plugged and stabilised by condensate formation. The solution of proteins in and out of the vesicle is described by beads dispersed in implicit solvent. The membrane is described as a one-bead-thick fluid elastic layer of mechanical properties that mimic biological membranes. We tune the interactions between solution beads in the different compartments to capture the differences between the cytoplasmic and endosomal protein solutions and explore how the system responds to different degrees of membrane poration. We find that, in the right interaction regime, condensates form rapidly at the damage site upon solution mixing and act as a plug that prevents futher mixing and destabilisation of the vesicle. Further, when the condensate can interact with the membrane (wetting interactions) we find that it mediates pore sealing and membrane repair. This research is part of the work published in "Stress granules plug and stabilize damaged endolysosomal membranes", Bussi et al, Nature, 2023 - 10.1038/s41586-023-06726-w.}, author = {Vanhille-Campos, Christian Eduardo and Šarić, Anđela}, publisher = {Institute of Science and Technology Austria}, title = {{Stress granules plug and stabilize damaged endolysosomal membranes}}, doi = {10.15479/AT:ISTA:14472}, year = {2023}, } @unpublished{14478, abstract = {Entire chromosomes are typically only transmitted vertically from one generation to the next. The horizontal transfer of such chromosomes has long been considered improbable, yet gained recent support in several pathogenic fungi where it may affect the fitness or host specificity. To date, it is unknown how these transfers occur, how common they are and whether they can occur between different species. In this study, we show multiple independent instances of horizontal transfers of the same accessory chromosome between two distinct strains of the asexual entomopathogenic fungusMetarhizium robertsiiduring experimental co-infection of its insect host, the Argentine ant. Notably, only the one chromosome – but no other – was transferred from the donor to the recipient strain. The recipient strain, now harboring the accessory chromosome, exhibited a competitive advantage under certain host conditions. By phylogenetic analysis we further demonstrate that the same accessory chromosome was horizontally transferred in a natural environment betweenM. robertsiiand another congeneric insect pathogen,M. guizhouense. Hence horizontal chromosome transfer is not limited to the observed frequent events within species during experimental infections but also occurs naturally across species. The transferred accessory chromosome contains genes that might be involved in its preferential horizontal transfer, encoding putative histones and histone-modifying enzymes, but also putative virulence factors that may support its establishment. Our study reveals that both intra- and interspecies horizontal transfer of entire chromosomes is more frequent than previously assumed, likely representing a not uncommon mechanism for gene exchange.Significance StatementThe enormous success of bacterial pathogens has been attributed to their ability to exchange genetic material between one another. Similarly, in eukaryotes, horizontal transfer of genetic material allowed the spread of virulence factors across species. The horizontal transfer of whole chromosomes could be an important pathway for such exchange of genetic material, but little is known about the origin of transferable chromosomes and how frequently they are exchanged. Here, we show that the transfer of accessory chromosomes - chromosomes that are non-essential but may provide fitness benefits - is common during fungal co-infections and is even possible between distant pathogenic species, highlighting the importance of horizontal gene transfer via chromosome transfer also for the evolution and function of eukaryotic pathogens.}, author = {Habig, Michael and Grasse, Anna V and Müller, Judith and Stukenbrock, Eva H. and Leitner, Hanna and Cremer, Sylvia}, booktitle = {bioRxiv}, title = {{Frequent horizontal chromosome transfer between asexual fungal insect pathogens}}, doi = {10.1101/2023.09.18.558174}, year = {2023}, }