bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recursive Prefix-Free Parsing for Building Big BWTs
Authors: Oliva Marco , Gagie Travis , Boucher Christina 
Published: January 2023

AbstractPrefix-free parsing is useful for a wide variety of purposes including building the BWT, constructing the suffix array, and supporting compressed suffix tree operations. This linear-time algorithm uses a rolling hash to break an input string into substrings, where the resulting set of unique substrings has the property that none of the substrings’ suffixes (of more than a certain length) is a proper prefix of any of the other substrings’ suffixes. Hence, the name prefix-free parsing. This set of unique substrings is referred to as thedictionary. Theparseis the ordered list of dictionary strings that defines the input string. Prior empirical results demonstrated the size of the parse is more burdensome than the size of the dictionary for large, repetitive inputs. Hence, the question arises as to how the size of the parse can scale satisfactorily with the input. Here, we describe our algorithm,recursive prefix-free parsing, which accomplishes this by computing the prefix-free parse of the parse produced by prefix-free parsing an input string. Although conceptually simple, building the BWT from the parse-of-the-parse and the dictionaries is significantly more challenging. We solve and implement this problem. Our experimental results show that recursive prefix-free parsing is extremely effective in reducing the memory needed to build the run-length encoded BWT of the input. Our implementation is open source and available athttps://github.com/marco-oliva/r-pfbwt.
lmeEEG: Mass linear mixed-effects modeling of EEG data with crossed random effects
Authors: Visalli Antonino , Montefinese Maria , Viviani Giada , Finos Livio , Vallesi Antonino , Ambrosini Ettore 
Published: January 2023

AbstractBackgroundMixed-effects models are the current standard for the analysis of behavioral studies in psycholinguistics and related fields, given their ability to simultaneously model crossed random effects for subjects and items. However, they are hardly applied in neuroimaging and psychophysiology, where the use of mass univariate analyses in combination with permutation testing would be too computationally demanding to be practicable with mixed models.New methodHere, we propose and validate an analytical strategy that enables the use of linear mixed models (LMM) with crossed random intercepts in mass univariate analyses of EEG data (lmeEEG). It avoids the unfeasible computational costs that would arise from massive permutation testing with LMM using a simple solution: removing random-effects contributions from EEG data and performing mass univariate linear analysis and permutations on the obtained marginal EEG.ResultslmeEEG showed excellent performance properties in terms of power and false positive rate.Comparison with existing methodslmeEEG overcomes the computational costs of standard available approaches (our method was indeed more than 300 times faster).ConclusionslmeEEG allows researchers to use mixed models with EEG mass univariate analyses. Thanks to the possibility offered by the method described here, we anticipate that LMM will become increasingly important in neuroscience. Data and codes are available atosf.io/kw87a. The codes and a tutorial are also available atgithub.com/antovis86/lmeEEG.
The phosphodiesterase 2A regulates lymphatic endothelial development via cGMP-mediated control of Notch signaling
Authors: Carlantoni Claudia , Liekfeld Leon , Hemkemeyer Sandra A. , Schreier Danny , Saygi Ceren , Kurelic Roberta , Cardarelli Silvia , Kalucka Joanna , Schulte Christian , Beerens Manu , Mailer Reiner , Schäffer Tilman , Naro Fabio , Pellegrini Manuela , Nikolaev Viacheslav O. , Renné Thomas , Frye Maike 
Published: January 2023

AbstractDuring vascular development endothelial junctions mature and vessel integrity is established to form the endothelial barrier. The molecular mechanisms by which lymphatic vessels induce cell contact inhibition are not understood. Here, we uncover the cGMP-dependent phosphodiesterase 2A (PDE2A) as a selective regulator of lymphatic, but not blood endothelial contact inhibition. Conditional deletion ofPde2ain mouse embryos reveals severe lymphatic dysplasia, while large blood vessel architecture remains unaltered. In the absence of PDE2A, human lymphatic endothelial cells fail to induce mature junctions and cell cycle arrest, while cGMP levels, but not cAMP levels, are increased. Loss of PDE2A-mediated cGMP hydrolysis leads to downregulation of NOTCH signaling. Vice versa, DLL4-induced NOTCH activation restores junctional maturation in PDE2A-deficient lymphatic endothelial cells. Our data demonstrate that PDE2A selectively modulates a crosstalk between cGMP and NOTCH signaling to finetune lymphatic development and suggest that PDE2A may be a druggable target to control lymphatic leakage and regeneration.
Towards reproducible models of sequence learning: replication and analysis of a modular spiking network with reward-based learning
Authors: Zajzon Barna , Duarte Renato , Morrison Abigail 
Published: January 2023

AbstractTo acquire statistical regularities from the world, the brain must reliably process, and learn from, spatiotemporally structured information. Although an increasing number of computational models have attempted to explain how such sequence learning may be implemented in the neural hardware, many remain limited in functionality or lack biophysical plausibility. If we are to harvest the knowledge within these models and arrive at a deeper mechanistic understanding of sequential processing in cortical circuits, it is critical that the models and their findings are accessible, reproducible, and quantitatively comparable. Here we illustrate the importance of these aspects by providing a thorough investigation of a recent model proposed by Cone and Shouval (2021). We re-implement the modular columnar architecture and reward-based learning rule in the open-source NEST simulator, and successfully replicate the main findings of the original study. Building on these, we perform an in-depth analysis of the model’s robustness to parameter settings and underlying assumptions, highlighting its strengths and weaknesses. We demonstrate a limitation of the model consisting in the hard-wiring of the sequence order in the connectivity patterns, and suggest possible solutions. Finally, we show that the core functionality of the model is retained under more biologically-plausible constraints.
A Scalable Framework for Closed-Loop Neuromodulation with Deep Learning
Authors: Gebodh Nigel , Miskovic Vladimir , Laszlo Sarah , Datta Abhishek , Bikson Marom 
Published: January 2023

AbstractClosed-loop neuromodulation measures dynamic neural or physiological activity to optimize interventions for clinical and nonclinical behavioral, cognitive, wellness, attentional, or general task performance enhancement. Conventional closed-loop stimulation approaches can contain biased biomarker detection (decoders and error-based triggering) and stimulation-type application. We present and verify a novel deep learning framework for designing and deploying flexible, data-driven, automated closed-loop neuromodulation that is scalable using diverse datasets, agnostic to stimulation technology (supporting multi-modal stimulation: tACS, tDCS, tFUS, TMS), and without the need for personalized ground-truth performance data. Our approach is based on identified periods of responsiveness – detected states that result in a change in performance when stimulation is applied compared to no stimulation. To demonstrate our framework, we acquire, analyze, and apply a data-driven approach to our open sourced GX dataset, which includes concurrent physiological (ECG, EOG) and neuronal (EEG) measures, paired with continuous vigilance/attention-fatigue tracking, and High-Definition transcranial electrical stimulation (HD-tES). Our framework’s decision process for intervention application identified 88.26% of trials as correct applications, showed potential improvement with varying stimulation types, or missed opportunities to stimulate, whereas 11.25% of trials were predicted to stimulate at inopportune times. With emerging datasets and stimulation technologies, our unifying and integrative framework; leveraging deep learning (Convolutional Neural Networks - CNNs); demonstrates the adaptability and feasibility of automated multimodal neuromodulation for both clinical and nonclinical applications.
Simple Causal Relationships in Gene Expression Discovered through Deep Learned Collective Variables
Authors: Wang Ching-Hao , Vetsigian Kalin , Lin Chris , Firth Finnian , Bradley Glyn , Granovsky Lena , England Jeremy L. 
Published: January 2023

AbstractDevelopments in high-content phenotypic screening with single-cell read-out hold the promise of revealing interactions and functional relationships between genes at the genomic scale scale. However, the high-dimensionality and noisiness of gene expression makes this endeavor highly challenging when treated as a conventional problem in causal machine learning, both because of the statistical power required and because of the limits on computational tractability. Here we take different tack, and propose a deep-learning approach that finds low-dimensional representations of gene expression in which the response to genetic perturbation is highly predictable. We demonstrate that the interactions between genes that are cooperative in these representations are highly consistent with known ground-truth in terms of causal ordering, functional relatedness, and synergistic impact on cell growth and death. Our novel, statistical physics-inspired approach provides a tractable means through which to examine the response the living cell to perturbation, employing coarse graining that reduces data requirements and focuses on identifying simple relationships between groups of genes.Author summaryUnderstanding the causal relationships between genes and the functions of a cell’s molecular components has long been a challenge in biology and biomedicine. With recent advancements in technologies that manipulate and measure the activity of thousands of genes at once at the single-cell level, scientists are now afforded with the opportunity to interrogate such relationships at scale. However, extracting useful information from the vast readouts of these technologies is non-trivial, in part due to their many-dimensional and noisy nature. Here we develop a machine learning model that allows for the interpretation of complex genetic perturbations in terms of a simple set of causal relations. By analyzing cooperative groups of genes identified by our model, we demonstrate the model can group genes accurately based on their biological function, their relative ordering up- or downstream in the flow of causation, and how their activities combine to affect cell growth and death. Our approach complements existing machine learning methods in providing a simple way to interpret causal mechanism governing genetic interactions and functional states of cells.
Gravitational and mechanical forces drive mitochondrial translation
Authors: Wakigawa Taisei , Kimura Yusuke , Mito Mari , Tsubaki Toshiya , Lee Muhoon , Nakamura Koki , Khan Abdul Haseeb , Saito Hironori , Yamamori Tohru , Yamazaki Tomokazu , Higashibata Akira , Tsuboi Tatsuhisa , Hirabayashi Yusuke , Takeuchi-Tomita Nono , Saito Taku , Higashitani Atsushi , Shichino Yuichi , Iwasaki Shintaro 
Published: January 2023

AbstractLife on Earth has evolved in a form suitable for the gravitational force of 1 ×g. Although the pivotal role of gravity in gene expression has been revealed by multiomics approaches in space-flown samples and astronauts, the molecular details of how mammalian cells harness gravity have remained unclear. Here, we showed that mitochondria utilize gravity to activate protein synthesis within the organelle. Genome-wide ribosome profiling revealed reduced mitochondrial translation in mammalian cells andCaenorhabditis elegansunder both microgravity at the International Space Station and simulated microgravity in a 3D-clinostat on the ground. We found that attenuation of cell adhesion through laminin–integrin interactions causes the phenotype. The downstream signaling pathway including FAK, RAC1, PAK1, BAD, and Bcl-2 family proteins in the cytosol, and mitochondrial fatty acid synthesis (mtFAS) pathway in the matrix maintain mitochondrial translation at high level. Mechanistically, a decreased level of mitochondrial malonyl-CoA, which is consumed by activated mtFAS, leads to a reduction in the malonylation of the translational machinery and an increase in the initiation and elongation ofin organellotranslation. Consistent with the role of integrin as a mechanosensor, we observed a decrease in mitochondrial translation via the minimization of mechanical stress in mouse skeletal muscle. Our work provides mechanistic insights into how cells convert gravitational and mechanical forces into translation in an energy-producing organelle.
A multi-kingdom genetic barcoding system for precise target clone isolation
Authors: Ishiguro Soh , Ishida Kana , Sakata Rina C. , Mori Hideto , Takana Mamoru , King Samuel , Bashth Omar , Ichiraku Minori , Masuyama Nanami , Takimoto Ren , Kijima Yusuke , Adel Arman , Toyoshima Hiromi , Seki Motoaki , Oh Ju Hee , Archambault Anne-Sophie , Nishida Keiji , Kondo Akihiko , Kuhara Satoru , Aburatani Hiroyuki , Klein Geltink Ramon I. , Takashima Yasuhiro , Shakiba Nika , Yachie Nozomu 
Published: January 2023

Clonal heterogeneity underlies diverse biological processes, including cancer progression, cell differentiation, and microbial evolution. Cell tagging strategies with DNA barcodes have recently enabled analysis of clone size dynamics and clone-restricted transcriptomic landscapes of heterogeneous populations. However, isolating a target clone that displays a specific phenotype from a complex population remains challenging. Here, we present a new multi-kingdom genetic barcoding system, CloneSelect, in which a target cell clone can be triggered to express a reporter gene for isolation through barcode-specific CRISPR base editing. In CloneSelect, cells are first barcoded and propagated so their subpopulation can be subjected to a given experiment. A clone that shows a phenotype or genotype of interest at a given time can then be isolated from the initial or subsequent cell pools stored throughout the experimental timecourse. This novel CRISPR-barcode genetics platform provides many new ways of analyzing and manipulating mammalian, yeast, and bacterial systems.TeaserA multi-kingdom CRISPR-activatable barcoding system enables the precise isolation of target barcode-labeled clones from a complex cell population.
Predictors of sensorimotor adaption: insights from over 100,000 reaches
Authors: Tsay Jonathan S. , Asmerian Hrach , Germine Laura T. , Wilmer Jeremy , Ivry Richard B. , Nakayama Ken 
Published: January 2023

AbstractSensorimotor adaptation is essential for keeping our movements well-calibrated in response to changes in the body and environment. For over a century, we have studied sensorimotor adaptation in highly controlled laboratory settings that typically involve small sample sizes. While this approach has proven useful to characterize different learning processes, laboratory studies are typically very underpowered to generate data suited for exploring the myriad of factors that may modulate motor performance. Here, using a citizen science website (testmybrain.org), we collected over 2000 sessions on a visuomotor rotation task. This unique dataset has allowed us to replicate classic motor findings, reconcile controversial findings in the learning and memory literature, and discover novel constraints underlying dissociable implicit and explicit learning processes supporting sensorimotor adaptation. Taken together, this study suggests that large-scale motor learning studies hold enormous potential to advance sensorimotor neuroscience.
Metabolic responses of normal rat kidneys to a high salt intake
Authors: Shimada Satoshi , Hoffmann Brian R. , Yang Chun , Kurth Theresa , Greene Andrew S. , Liang Mingyu , Dash Ranjan K. , Cowley Allen W. 
Published: January 2023

AbstractIn the present study, novel methods were developed which allowed continuous (24/7) measurement of blood pressure (BP) and renal blood flow (RBF) in freely moving rats and the intermittent collection of arterial and renal venous blood to estimate kidney metabolic fluxes of O2and metabolites. The study determined the effects of a high salt (HS) diet upon whole kidney O2consumption and the metabolomic profiles of normal Sprague Dawley (SD) rats. A separate group of rats was studied to determine changes in the cortex (Cx) and outer medulla (OM) tissue metabolomic and mRNAseq profiles before and following the switch from a 0.4% to a 4.0% NaCl diet. Significant changes in the metabolomic and transcriptomic profiles occurred with feeding of the HS diet. A progressive increase of kidney O2consumption was found despite a reduction in expression of most of the mRNA encoding enzymes of TCA cycle. Increased glycolysis was evident with the elevation of mRNA expression encoding key glycolytic enzymes and release of pyruvate and lactate from the kidney in the renal venous blood. Glycolytic production of NADH is used in either the production of lactate or oxidized via the malate aspartate shuttle. Aerobic glycolysis (e.g., Warburg-effect) may account for the needed increase in cellular energy. The study provides evidence that kidney metabolism responds to a HS diet enabling enhanced energy production while protecting from oxidate stress and injury.
Intrathecal [64Cu]Cu-albumin PET reveals age-related decline of cerebrospinal fluid (CSF)-lymphatic efflux
Authors: Sarker Azmal , Suh Minseok , Choi Yoori , Park Ji Yong , Lee Yun-Sang , Lee Dong Soo 
Published: January 2023

ABSTRACTAge-related cognitive decline is associated with dysfunctional lymphatic efflux of cerebrospinal fluid (CSF) through meningeal lymphatic vessels. Intrathecal [64Cu]Cu-albumin positron emission tomography (PET) was applied in mice for the evaluation of lymphatic efflux of CSF and its age-related variation. [64Cu]Cu-albumin PET was done at multiple time points after intrathecal injection of [64Cu]Cu-albumin with the infusion speed of 700 nl/min in the adult and aged mice of 15–25 months old age. CSF clearance and paravertebral lymph nodes were quantified after injection and at later stationary phase. Representing perturbed state by 6 μl (1/7 of CSF volume with twice the production rate for 9 minutes of intrathecal injection) and at the next day of stationary return of CSF dynamics in mice, CSF clearance half-time from the subarachnoid space was 93.4 ± 19.7 in adult and 123.3 ± 15.6 minutes in aged mice (p = 0.01). The % injected dose at 4, 6 and 24 hours were higher in aged mice than in the adult mice (p < 0.05) and the visualized paravertebral lymph node activity tended to be lower in the aged, which was different from [64Cu]Cu-NOTA or [64Cu]Cu-ESION PET. [64Cu]Cu-albumin PET enabled quantification of CSF-lymphatic efflux over all the levels of brain spinal cords and visualization with quantifiability of lymph node activity. [64Cu]Cu-albumin PET revealed an age-related decrease in CSF-lymphatic efflux due to less efflux from the subarachnoid space, especially at stationary phase in the aged mice.
Sex chromosome evolution in beetles
Authors: Bracewell Ryan , Tran Anita , Chatla Kamalakar , Bachtrog Doris 
Published: January 2023

AbstractBeetles are the most species-rich group of animals and harbor diverse karyotypes. Most species have XY sex chromosomes, but X0 sex determination mechanisms are also common in some groups. We generated a whole-chromosome assembly of a beetle species with a neo-sex chromosome and utilize eleven additional beetle genomes, to reconstruct karyotype evolution across Coleoptera. We identify ancestral linkage groups, termed Stevens elements, that share a conserved set of genes across beetles. While the ancestral X chromosome is maintained across beetles, we find independent additions of autosomes to the ancestral sex chromosomes. These neo-sex chromosomes evolve the stereotypical properties of sex chromosomes, including the evolution of dosage compensation, and a non-random distribution of genes with sex-biased expression. Beetles thus provide a novel model to gain a better understanding of the diverse forces driving sex chromosome evolution.
Targeted Screening and Identification of Chlorhexidine as a Pro-myogenic Circadian Clock Activator
Authors: Kiperman Tali , Li Weini , Xiong Xuekai , Li Hongzhi , Horne David , Ma Ke 
Published: January 2023

AbstractBackgroundCircadian clock is an evolutionarily-conserved mechanism that exerts pervasive temporal control in stem cell behavior. This time-keeping machinery is required for orchestrating myogenic progenitor properties in regenerative myogenesis that ameliorates muscular dystrophy. Here we report a screening platform to discover circadian clock modulators that promote myogenesis, with the identification of chlorhexidine (CHX) as a clock-activating molecule with pro-myogenic activities.MethodsA high-throughput molecular docking pipeline was applied to identify candidate compounds with a structural fit for a hydrophobic pocket within the key circadian transcription factor protein, Circadian Locomotor Output Cycles Kaput (CLOCK). Secondary biochemical screen for clock-modulatory activities of these molecules were preformed, together with functional validations of myogenic regulations to identify modulators with pro-myogenic properties.ResultsCHX was identified as a clock activator that promotes distinct aspects of myogenesis. CHX activated circadian clock that reduced cycling period length and augmented amplitude. This action was mediated by the targeted CLOCK structure via augmented interaction with heterodimer partner Bmal1, leading to enhanced CLOCK/Bmal1-controlled transcription with up-regulation of core clock genes. Consistent with its clock-activating function, CHX displayed robust effects on stimulating myogenic differentiation in a clock-dependent manner. In addition, CHX augmented the proliferative and migratory activities of myoblasts.ConclusionOur findings demonstrate the feasibility of a screening platform to discover clock modulators with myogenic regulatory activities. Discovery of CHX as a pro-myogenic molecule could be applicable to promote regenerative capacities in ameliorating dystrophic or degenerative muscle diseases.