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Cusp universality for correlated random matrices
No full textFor correlated real symmetric or complex Hermitian random matrices, we prove
that the local eigenvalue statistics at any cusp singularity are universal.
Since the density of states typically exhibits only square root edge or cubic
root cusp singularities, our result completes the proof of the
Wigner-Dyson-Mehta universality conjecture in all spectral regimes for a very
general class of random matrices. Previously only the bulk and the edge
universality were established in this generality [arXiv:1804.07744], while cusp
universality was proven only for Wigner-type matrices with independent entries
[arXiv:1809.03971, arXiv:1811.04055]. As our main technical input, we prove an
optimal local law at the cusp using the Zigzag strategy, a recursive tandem of
the characteristic flow method and a Green function comparison argument.
Moreover, our proof of the optimal local law holds uniformly in the spectrum,
thus also re-establishing universality of the local eigenvalue statistics in
the previously studied bulk [arXiv:1705.10661] and edge [arXiv:1804.07744]
regimes
Advances in Neural Information Processing Systems
No full textThe rising footprint of machine learning has led to a focus on imposing model
sparsity as a means of reducing computational and memory costs. For deep neural
networks (DNNs), the state-of-the-art accuracy-vs-sparsity is achieved by heuristics
inspired by the classical Optimal Brain Surgeon (OBS) framework [LeCun et al.,
1989, Hassibi and Stork, 1992, Hassibi et al., 1993], which leverages loss curvature
information to make better pruning decisions. Yet, these results still lack a solid
theoretical understanding, and it is unclear whether they can be improved by
leveraging connections to the wealth of work on sparse recovery algorithms. In this
paper, we draw new connections between these two areas and present new sparse
recovery algorithms inspired by the OBS framework that comes with theoretical
guarantees under reasonable assumptions and have strong practical performance.
Specifically, our work starts from the observation that we can leverage curvature
information in OBS-like fashion upon the projection step of classic iterative sparse
recovery algorithms such as IHT. We show for the first time that this leads both
to improved convergence bounds under standard assumptions. Furthermore, we
present extensions of this approach to the practical task of obtaining accurate sparse
DNNs, and validate it experimentally at scale for Transformer-based models on
vision and language tasks
Concerted transcriptional regulation of the morphogenesis of hypothalamic neurons by ONECUT3
No full textAcquisition of specialized cellular features is controlled by the ordered expression of transcription factors (TFs) along differentiation trajectories. Here, we find a member of the Onecut TF family, ONECUT3, expressed in postmitotic neurons that leave their Ascl1+/Onecut1/2+ proliferative domain in the vertebrate hypothalamus to instruct neuronal differentiation. We combined single-cell RNA-seq and gain-of-function experiments for gene network reconstruction to show that ONECUT3 affects the polarization and morphogenesis of both hypothalamic GABA-derived dopamine and thyrotropin-releasing hormone (TRH)+ glutamate neurons through neuron navigator-2 (NAV2). In vivo, siRNA-mediated knockdown of ONECUT3 in neonatal mice reduced NAV2 mRNA, as well as neurite complexity in Onecut3-containing neurons, while genetic deletion of Onecut3/ceh-48 in C. elegans impaired neurocircuit wiring, and sensory discrimination-based behaviors. Thus, ONECUT3, conserved across neuronal subtypes and many species, underpins the polarization and morphological plasticity of phenotypically distinct neurons that descend from a common pool of Ascl1+ progenitors in the hypothalamus
Calorie restriction increases insulin sensitivity to promote beta cell homeostasis and longevity in mice
No full textCaloric restriction (CR) can extend the organism life- and health-span by improving glucose homeostasis. How CR affects the structure-function of pancreatic beta cells remains unknown. We used single nucleus transcriptomics to show that CR increases the expression of genes for beta cell identity, protein processing, and organelle homeostasis. Gene regulatory network analysis reveal that CR activates transcription factors important for beta cell identity and homeostasis, while imaging metabolomics demonstrates that beta cells upon CR are more energetically competent. In fact, high-resolution microscopy show that CR reduces beta cell mitophagy to increase mitochondria mass and the potential for ATP generation. However, CR beta cells have impaired adaptive proliferation in response to high fat diet feeding. Finally, we show that long-term CR delays the onset of beta cell aging hallmarks and promotes cell longevity by reducing beta cell turnover. Therefore, CR could be a feasible approach to preserve compromised beta cell structure-function during aging and diabetes
Coat stiffening can explain invagination of clathrin-coated membranes
No full textClathrin-mediated endocytosis is the main pathway used by eukaryotic cells to take up extracellular material, but the dominant physical mechanisms driving this process are still elusive. Recently, several high-resolution imaging techniques have been used on different cell lines to measure the geometrical properties of clathrin-coated pits over their whole lifetime. Here, we first show that the combination of all datasets with the recently introduced cooperative curvature model defines a consensus pathway, which is characterized by a flat-to-curved transition at finite area, followed by linear growth and subsequent saturation of curvature. We then apply an energetic model for the composite of the plasma membrane and clathrin coat to this consensus pathway to show that the dominant mechanism for invagination could be coat stiffening, which might originate from cooperative interactions between the different clathrin molecules and progressively drives the system toward its intrinsic curvature. Our theory predicts that two length scales determine the invagination pathway, namely the patch size at which the flat-to-curved transition occurs and the final pit radius
ISTA thesis
No full textPoxviruses are large pleomorphic double-stranded DNA viruses that include well known members such as variola virus, the causative agent of smallpox, Mpox virus, as well as Vaccinia virus (VACV), which serves as a vaccination strain for formerly mentioned viruses. VACV is a valuable model for studying large pleomorphic DNA viruses in general and poxviruses specifically, as many features, such as core morphology and structural proteins, are well conserved within this family. Despite decades of research, our understanding of the structural components and proteins that comprise the poxvirus core in mature virions remains limited. Although major core proteins were identified via indirect experimental evidence, the core's complexity, with its large size, structure and number of involved proteins, has hindered efforts to achieve high-resolution insights and to define the roles of the individual proteins. The specific protein composition of the core's individual layers, including the palisade layer and the inner core wall, has remained unclear. In this study, we have merged multiple approaches, including single particle cryo electron microscopy of purified virus cores, cryo-electron tomography and subtomogram averaging of mature virions and molecular modeling to elucidate the structural determinants of the VACV core. Due to the lack of experimentally derived structures, either in situ or reconstituted in vitro, we used Alphafold to predict models of the putative major core protein candidates, A10, 23k, A3, A4, and L4. Our results show that the VACV core is composed of several layers with varying local symmetries, forming more intricate interactions than observed previously. This allowed us to identify several molecular building blocks forming the viral core lattice. In particular, we identified trimers of protein A10 as a major core structure that forms the palisade layer of the viral core. Additionally, we revealed that six petals of a flower shaped core pore within the core wall are composed of A10 trimers. Furthermore, we obtained a cryo-EM density for the inner core wall that could potentially accommodate an A3 dimer. Integrating descriptions of protein interactions from previous studies enabled us to provide a detailed structural model of the poxvirus core wall, and our findings indicate that the interactions within A10 trimers are likely consistent across orthopox- and parapoxviruses. This combined application of cryo-SPA and cryo-ET can help overcome obstacles in studying complex virus structures in the future, including their key assembly proteins, interactions, and the formation into a core lattice. Our work provides important fundamental new insights into poxvirus core architecture, also considering the recent re-emergence of poxviruses
STK19 drives transcription-coupled repair by stimulating repair complex stability, RNA Pol II ubiquitylation, and TFIIH recruitment
No full textTranscription-coupled nucleotide excision repair (TC-NER) efficiently eliminates DNA damage that impedes gene transcription by RNA polymerase II (RNA Pol II). TC-NER is initiated by the recognition of lesion-stalled RNA Pol II by CSB, which recruits the CRL4CSA ubiquitin ligase and UVSSA. RNA Pol II ubiquitylation at RPB1-K1268 by CRL4CSA serves as a critical TC-NER checkpoint, governing RNA Pol II stability and initiating DNA damage excision by TFIIH recruitment. However, the precise regulatory mechanisms of CRL4CSA activity and TFIIH recruitment remain elusive. Here, we reveal human serine/threonine-protein kinase 19 (STK19) as a TC-NER factor, which is essential for correct DNA damage removal and subsequent transcription restart. Cryogenic electron microscopy (cryo-EM) studies demonstrate that STK19 is an integral part of the RNA Pol II-TC-NER complex, bridging CSA, UVSSA, RNA Pol II, and downstream DNA. STK19 stimulates TC-NER complex stability and CRL4CSA activity, resulting in efficient RNA Pol II ubiquitylation and correct UVSSA and TFIIH binding. These findings underscore the crucial role of STK19 as a core TC-NER component
Predicting the geolocation of tweets using transformer models on customized data
No full textThis research is aimed to solve the tweet/user geolocation prediction task and provide a flexible methodology for the geo-tagging of textual big data. The suggested approach implements neural networks for natural language processing (NLP) to estimate the location as coordinate pairs (longitude, latitude) and two-dimensional Gaussian Mixture Models (GMMs). The scope of proposed models has been finetuned on a Twitter dataset using pretrained Bidirectional Encoder Representations from Transformers (BERT) as base models. Performance metrics show a median error of fewer than 30 km on a worldwide-level, and fewer than 15 km on the US-level datasets for the models trained and evaluated on text features of tweets' content and metadata context. Our source code and data are available at https://github.com/K4TEL/geo-twitter.git
Intriguing properties of robust classification
No full textDespite extensive research since the community learned about adversarial
examples 10 years ago, we still do not know how to train high-accuracy
classifiers that are guaranteed to be robust to small perturbations of their
inputs. Previous works often argued that this might be because no classifier
exists that is robust and accurate at the same time. However, in computer
vision this assumption does not match reality where humans are usually accurate
and robust on most tasks of interest. We offer an alternative explanation and
show that in certain settings robust generalization is only possible with
unrealistically large amounts of data. More precisely we find a setting where a
robust classifier exists, it is easy to learn an accurate classifier, yet it
requires an exponential amount of data to learn a robust classifier. Based on
this theoretical result, we explore how well robust classifiers generalize on
datasets such as CIFAR-10. We come to the conclusion that on this datasets, the
limitation of current robust models also lies in the generalization, and that
they require a lot of data to do well on the test set. We also show that the
problem is not in the expressiveness or generalization capabilities of current
architectures, and that there are low magnitude features in the data which are
useful for non-robust generalization but are not available for robust
classifiers
Measuring stellar surface rotation and activity with the PLATO mission. I. Strategy and application to simulated light curves
No full textThe Planetary Transits and Oscillations of stars mission (PLATO) will allow us to measure surface rotation and monitor photometric activity of tens of thousands of main sequence solar-type and subgiant stars. This paper is the first of a series dedicated to the preparation of the analysis of stellar surface rotation and photospheric activity with the near-future PLATO data. We describe in this work the strategy that will be implemented in the PLATO pipeline to measure stellar surface rotation, photometric activity, and long-term modulations. The algorithms are applied on both noise-free and noisy simulations of solar-type stars, which include activity cycles, latitudinal differential rotation, and spot evolution. PLATO simulated systematics are included in the noisy light curves. We show that surface rotation periods can be recovered with confidence for most of the stars with only six months of observations and that the recovery rate of the analysis significantly improves as additional observations are collected. This means that the first PLATO data release will already provide a substantial set of measurements for this quantity, with a significant refinement on their quality as the instrument obtains longer light curves. Measuring the Schwabe-like magnetic activity cycle during the mission will require that the same field be observed over a significant timescale (more than four years). Nevertheless, PLATO will provide a vast and robust sample of solar-type stars with constraints on the activity-cycle length. Such a sample is lacking from previous missions dedicated to space photometry