bluuebunny/crossref_metadata_2025_split huggingface dataset:
Forward genetic screening in engineered colorectal cancer organoids identifies novel regulators of metastasis
Authors: Cramer Zvi , Wang Xin , Leu Nicolae Adrian , Monaghan Keara , Rhoades Joshua H. , Tian Yuhua , Rico Joshua , Mendez Diego , Petroni Ricardo , Kim Melissa S. , Matsuda Rina , Carrera Maria F. , Brodsky Igor E. , Li Ning , Lengner Christopher J. , Blanco M. Andrés 
Published: August 2023

SummaryCancer is the second leading cause of death globally, due primarily to metastatic dissemination and colonization of distal sites. Recurrent genetic drivers of metastasis are elusive, suggesting that, unlike the stereotyped mutations promoting primary tumor development, drivers of metastasis may be variable. Here, we interrogate pathways governing metastasis through CRISPR/Cas9-based forward genetic screening in a genetically defined colorectal adenocarcinoma tumor organoid (tumoroid) model using ex vivoinvasion screens and orthotopic,in vivoscreens for gain of metastatic potential. We identifyCtnna1andBcl2l13asbona fidemetastasis suppressors. CTNNA1 loss promotes carcinoma cell invasion and migration through an atypical EMT-like mechanism, whereas BCL2L13 loss promotes cell survival after extracellular matrix detachment and non-cell-autonomous macrophage polarization. Ultimately, this study provides a proof-of-principle that high-content forward genetic screening can be performed in tumor-organoid modelsin vivoand identifies novel regulators of colon cancer metastasis.
libpspm: A feature-rich numerical package for solving physiologically structured population models
Authors: Joshi Jaideep , Zhang Lai , Stefaniak Elisa Z. , Dieckmann Ulf , Brännström Åke 
Published: August 2023

AbstractFor a vast majority of organisms, life-history processes depend on their physiological state, such as body size, as well as on their environment. Size-structured population models, or more generally, physiologically structured population models (PSPMs), have emerged as powerful tools for modelling the population dynamics of organisms, as they account for the dependences of growth, mortality, and fecundity rates on an organism’s physiological state and capture feedbacks between a population’s structure and its environment, including all types of density regulation. However, despite their widespread appeal across biological disciplines, few numerical packages exist for solving PSPMs in an accessible and computationally efficient way. The main reason for this is that PSPMs typically involve solving partial differential equations (PDEs), and no single numerical method works universally best, or even at all, for all PDEs. Here, we present libpspm, a general-purpose numerical library for solving user-defined PSPMs. libpspm provides eight different methods for solving the PDEs underlying PSPMs, including four semi-implicit solvers that can be used for solving stiff problems. Users can choose the desired method without changing the code specifying the PSPM. libpspm allows for predicting the dynamics of multiple physiologically structured or unstructured species, each of which can have its own distinct set of physiological states and demographic functions. By separating model definition from model solution, libpspm can make PSPM-based modelling accessible to non-specialists and thus promote the widespread adoption of PSPMs.
Contrastive learning explains the emergence and function of visual category-selective regions
Authors: Prince Jacob S. , Alvarez George A. , Konkle Talia 
Published: August 2023

AbstractModular and distributed coding theories of category selectivity along the human ventral visual stream have long existed in tension. Here, we present a reconciling framework –contrastive coding– based on a series of analyses relating category selectivity within biological and artificial neural networks. We discover that, in models trained with contrastive self-supervised objectives over a rich natural image diet, category-selective tuning naturally emerges for faces, bodies, scenes, and words. Further, lesions of these model units lead to selective, dissociable recognition deficits, highlighting their distinct functional roles in information processing. Finally, these pre-identified units can predict neural responses in all corresponding face-, scene-, body-, and word-selective regions of human visual cortex, under a highly constrained sparse-positive encoding procedure. The success of this single model indicates that brain-like functional specialization can emerge without category-specific learning pressures, as the system learns to untangle rich image content. Contrastive coding, therefore, provides a unifying account of object category emergence and representation in the human brain.
Extensive long-range polycomb interactions and weak compartmentalization are hallmarks of human neuronal 3D genome
Authors: Pletenev Ilya A. , Bazarevich Maria , Zagirova Diana R. , Kononkova Anna D. , Cherkasov Alexander V. , Efimova Olga I. , Tiukacheva Eugenia A. , Morozov Kirill V. , Ulianov Kirill A. , Komkov Dmitriy , Tvorogova Anna V. , Golimbet Vera E. , Kondratyev Nikolay V. , Razin Sergey V. , Khaitovich Philipp , Ulianov Sergey V. , Khrameeva Ekaterina E. 
Published: August 2023

ABSTRACTChromatin architecture regulates gene expression and shapes cellular identity, particularly in neuronal cells. Specifically, polycomb group (PcG) proteins enable establishment and maintenance of neuronal cell type by reorganizing chromatin into repressive domains that limit the expression of fate-determining genes and sustain distinct gene expression patterns in neurons. Here, we map the 3D genome architecture in neuronal and non-neuronal cells isolated from the Wernicke’s area of four human brains and comprehensively analyze neuron-specific aspects of chromatin organization. We find that genome segregation into active and inactive compartments is greatly reduced in neurons compared to other brain cells. Furthermore, neuronal Hi-C maps reveal strong long-range interactions, forming a specific network of PcG-mediated contacts in neurons that is nearly absent in other brain cells. These interacting loci contain developmental transcription factors with repressed expression in neurons and other mature brain cells. But only in neurons, they are rich in bivalent promoters occupied by H3K4me3 histone modification together with H3K27me3, which points to a possible functional role of PcG contacts in neurons. Importantly, other layers of chromatin organization also exhibit a distinct structure in neurons, characterized by an increase in short-range interactions and a decrease in long-range ones.
Do Goats Recognise Humans Cross-Modally?
Authors: Mason Marianne A. , Semple Stuart , Marshall Harry H. , McElligott Alan G. 
Published: August 2023

ABSTRACTRecognition plays a key role in the social lives of gregarious species, enabling animals to distinguish among social partners and tailor their behaviour accordingly. As domesticated animals regularly interact with humans, as well as members of their own species, we might expect mechanisms used to discriminate between conspecifics to also apply to humans. Given that goats can combine visual and vocal cues to recognize one another, we investigated whether this cross-modal recognition extends to discriminating among familiar humans. We presented 28 goats with facial photographs of familiar people and two repeated playbacks of a voice, either congruent (from the same person) or incongruent with that photograph (from a different person). When cues were incongruent, violating their expectations, we expected goats to respond faster and for longer after playbacks and show increases in physiological arousal (increased heart rate and/or decreased heart rate variability). We found the increase in latency that goats took to respond as the playback series progressed was greater when the face and voice were incongruent. As differences were not as predicted and only observed in one response measured, our evidence is tentative, but the variation in latency to look between congruency conditions suggests goat cross-modal recognition extends to humans. If this is the case, not only would this further demonstrate the flexibility of complex recognition systems to discriminate among members of a very different species, but indicates goats can produce mental representations for familiar people, a key component of individual recognition.
Decreased myelin-related gene expression in the nucleus accumbens during spontaneous neonatal opioid withdrawal in the absence of long-term behavioral effects in adult outbred CFW mice
Authors: Borrelli Kristyn N. , Wingfield Kelly K. , Yao Emily J. , Zamorano Catalina A. , Sena Katherine D. , Beierle Jacob A. , Roos Michelle A. , Zhang Huiping , Wachman Elisha M. , Bryant Camron D. 
Published: August 2023

ABSTRACTPrenatal opioid exposure is a major health concern in the United States, with the incidence of neonatal opioid withdrawal syndrome (NOWS) escalating in recent years. NOWS occurs upon cessation ofin uteroopioid exposure and is characterized by increased irritability, disrupted sleep patterns, high-pitched crying, and dysregulated feeding. The main pharmacological strategy for alleviating symptoms is treatment with replacement opioids. The neural mechanisms mediating NOWS and the long-term neurobehavioral effects are poorly understood. We used a third trimester-approximate model in which neonatal outbred pups (Carworth Farms White; CFW) were administered once-daily morphine (15 mg/kg, s.c.) from postnatal day (P) day 1 through P14 and were then assessed for behavioral and transcriptomic adaptations within the nucleus accumbens (NAc) on P15. We also investigated the long-term effects of perinatal morphine exposure on adult learning and reward sensitivity. We observed significant weight deficits, spontaneous thermal hyperalgesia, and altered ultrasonic vocalization (USV) profiles following repeated morphine and during spontaneous withdrawal. Transcriptome analysis of NAc from opioid-withdrawn P15 neonates via bulk mRNA sequencing identified an enrichment profile consistent with downregulation of myelin-associated transcripts. Despite the neonatal behavioral and molecular effects, there were no significant long-term effects of perinatal morphine exposure on adult spatial memory function in the Barnes Maze, emotional learning in fear conditioning, or in baseline or methamphetamine-potentiated reward sensitivity as measured via intracranial self-stimulation. Thus, the once daily third trimester-approximate exposure regimen, while inducing NOWS model traits and significant transcriptomic effects in neonates, had no significant long-term effects on adult behaviors.HIGHLIGHTSWe replicated some NOWS model traits via 1x-daily morphine (P1-P14).We found a downregulation of myelination genes in nucleus accumbens on P15.There were no effects on learning/memory or reward sensitivity in adults.
Dynamic clustering of genomics cohorts beyond race, ethnicity—and ancestry
Authors: Mohsen Hussein , Blenman Kim , Emani Prashant S. , Morris Quaid , Carrot-Zhang Jian , Pusztai Lajos 
Published: August 2023

AbstractBackgroundRecent decades have witnessed a steady decrease in the use of race categories in genomic studies. While studies that still include race categories vary in goal and type, these categories already build on a history during which racial color lines have been enforced and adjusted in the service of social and political systems of power and disenfranchisement. For early modern biological classification systems, data collection was also considerably arbitrary and limited. Fixed, discrete classifications have limited the study of human biodiversity and disrupted widely spread genetic and phenotypic continuums across geographic scales. Relatedly, the use of broad and predefined classification schemes—e.g. continent-based—across traits can risk missing important trait-specific genomic signals.ResultsTo address these issues, we introduce a dynamic approach to clustering human genomics cohorts on a trait-specific level and without using a set of predefined categories. We tested the approach on whole-exome sequencing datasets in ten cancer types and partitioned them based on germline variants in cancer-relevant genes that could confer cancer type-specific disease predisposition. Results demonstrate clustering patterns that transcend discrete continent-based categories across cancer types. Functional analysis based on cancer type-specific clusterings also captures the fundamental biological processes underlying cancer, differentiates between dynamic clusters on a functional level, and identifies novel potential drivers overlooked by a continent-based clustering model.ConclusionsThrough a trait-based lens, the dynamic clustering approach reveals genomic patterns that transcend predefined classification categories. We propose that coupled with diverse data collection, new clustering approaches have the potential to draw a more complete portrait of genomic variation and to address, in parallel, technical and social aspects of studying human biodiversity.
Enhancing Opioid Bioactivity Predictions through Integration of Ligand-Based and Structure-Based Drug Discovery Strategies with Transfer and Deep Learning Techniques
Authors: Provasi Davide , Filizola Marta 
Published: August 2023

ABSTRACTThe opioid epidemic has cast a shadow over public health, necessitating immediate action to address its devastating consequences. To effectively combat this crisis, it is crucial to discover better opioid drugs with reduced addiction potential. Artificial intelligence-based and other machine learning tools, particularly deep learning models, have garnered significant attention in recent years for their potential to advance drug discovery. However, utilizing these tools poses challenges, especially when training samples are insufficient to achieve adequate prediction performance. In this study, we investigate the effectiveness of transfer learning using combined ligand-based and structure-based molecular descriptors from the entire opioid receptor (OR) subfamily in building robust deep learning models for enhanced bioactivity prediction of opioid ligands at each individual OR subtype. Our studies hold the potential to greatly advance opioid research by enabling the rapid identification of novel chemical probes with specific bioactivities, which can aid in the study of receptor function and contribute to the future development of improved opioid therapeutics.
Comparison of Screening Guidelines for Cardiovascular disease Prevention and Early Detection:a scoping review
Authors: Darwesh Badawy Mohammed Abd ElFattah Mohammed , Naing Lin , Tuah Nik Ani Afiqah 
Published: August 2023

ABSTRACTObjectiveGlobally, cardiovascular disease (CVD) has a significant role in morbidity and early death. This review’s objective is to provide a summary of the strengths and weaknesses in the variety of screening guidelines made by several international organizations for the early identification and prevention of CVD.MethodsAs the reporting guideline for this review, we used Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR). We performed a scoping review using a few guideline-specific databases. We tabulated the main key differences between the included screening guidelines for CVD prevention and early detection from different perspectives.ResultsWe included a total of 20 unique guidelines that were developed by various organizations throughout the world and focused on screening for CVD prevention and early detection out of the 2,466 guidelines discovered by our search based on our eligibility criteria. We concluded that the target populations, CVD risk assessment techniques, outcomes, and categories of the chosen CVD prevention guidelines widely varied. Additionally, some guidelines adopted no grading scheme for their evidence, while others did not advocate the use of any imaging screening tools in their evaluation of the CVD risk.ConclusionsThis scoping review highlights the areas of each guideline’s strengths and weaknesses and conducts a systematic comparison of a number of worldwide guidelines for CVD prevention and early diagnosis.What is already known in this review?Based on the most recent evidence and consensus among experts, each nation creates its own set of guidelines for the early detection and prevention of CVD.What this review addsThis review conducted a systematic comparison and summarized the strengths and weaknesses of the various screening guidelines made by numerous international organizations for the early detection and prevention of CVD.• How this review might affect research, practice or policyThis review provided opportunities to improve the future development of the clinical practice guidelines for CVD prevention and early detection.
Divergent warning patterns influence male and female mating behaviours in a tropical butterfly
Authors: Kuo Chi-Yun , Melo-Flóres Lina , Aragón Andrea , Oberweiser Morgan M. , McMillan W. Owen , Pardo-Diaz Carolina , Salazar Camilo , Merrill Richard M. 
Published: August 2023

AbstractTraits under divergent ecological selection that also function during mating can be important in maintaining species boundaries. Few studies have considered mutual mate choice, where both males and females base mating decisions on the same trait. We investigated the contribution of visual preference to assortative mating between an aposematic butterflyHeliconius cydnoand its sympatric relativeH. melpomene. Wing colouration inHeliconiusbutterflies evolved as a warning signal but also functions as a mating cue. We predicted that both sexes ofH. cydnocontributed to assortative mating by exhibiting visual preference towards conspecific wing colouration. We analysed published and new data from preference experiments, in which males were presented with conspecific andH. melpomenefemales. We also recorded female responses and mating outcomes in choice experiments, involving conspecific males with either the original white or artificially painted red forewing bands. Both sexes ofH. cydnoresponded more positively towards the conspecific colouration, yet male colouration did not predict mating outcomes in female choice experiments. As courtships are initiated by males in butterflies, our findings suggest that female visual preference might be of secondary importance in preventing gene flow betweenH. cydnoandH. melpomene.
Identification of a Novel Hypoxia-induced Inflammatory Cell Death Pathway
Authors: Bhardwaj Abhishek , Antonelli Maria , Ueberheide Beatrix , Neel Benjamin G. 
Published: August 2023

SummaryHypoxic cancer cells resist many anti-neoplastic therapies and can seed recurrence. We found previously that PTP1B deficiency promotes HER2+ breast cancer cell death in hypoxia by activating RNF213, an ∼600kDa protein containing AAA-ATPase domains and two ubiquitin ligase domains (RING and RZ) that also is implicated in Moyamoya disease (MMD), lipotoxicity, and innate immunity. Here we report that PTP1B and ABL1/2 reciprocally control RNF213 phosphorylation on tyrosine-1275. This phosphorylation promotes RNF213 oligomerization and RZ domain activation. The RZ domain ubiquitylates CYLD/SPATA2, and together with the LUBAC complex, induces their degradation. Decreased CYLD/SPATA2 causes NF-κB activation, which together with hypoxia-induced ER-stress triggers GDSMD-dependent pyroptosis. Mutagenesis experiments show that the RING domain negatively regulates the RZ domain.CYLD-deleted HER2+ cell-derived xenografts phenocopy the effects of PTP1B deficiency, and reconstitutingRNF213knockout lines with RNF213 mutants shows that the RZ domain mediates PTP1B-dependent tumor cell death. Our results identify a novel, potentially targetable PTP1B/RNF213/CYCLD/SPATA pathway critical for controlling inflammatory cell death in hypoxic tumors that could be exploited to target hypoxic tumor cells, potentially turning “cold” tumors “hot”. Our findings also reveal new insights into RNF213 regulation, and have potentially important implications for the pathogenesis of MMD, atherosclerosis, and inflammatory and auto-immune disorders.
A Novel Simulation Framework for Validation of Ecological Network Inference
Authors: Kusch Erik , Vinton Anna C. 
Published: August 2023

ABSTRACTUnderstanding how the differential magnitude and sign of ecological interactions vary across space is vital to assessing ecosystem resilience to biodiversity loss and predict community assemblies. This necessity for ecological network knowledge and their labour-intensive sampling requirements has spurred the creation of ecological network inference methodology. Recent research has identified inconsistencies in networks inferred using different approaches thus necessitating quantification of inference performance to facilitate choice of network inference approach.Here we develop a data simulation method to generate data products fit for network inference and subsequently quantify the validity of two well-established ecological interaction network inference methods – HMSC and COOCCUR. The simulation framework we present here can be parameterised using real-world information (e.g., biological interactions observed in-situ and bioclimatic niche preferences) thus representing network inference capabilities in real-world applications. Using this framework, it is thus possible to evaluate the performance of any ecological network inference approach.We identify a concerningly large range in accuracy of inferred networks as compared to true, realisable association networks. These differences in inference accuracy are governed by a paradigm of input data types and environmental parameter estimation as previously suggested. To establish a workflow for quantification of network inference reliability, we suggest analysis procedures with which to explore inference and detection probabilities of association types of different identity and sign with respect to bioclimatic niche preferences and association strength of association partner-species.With this study, we provide the groundwork with which to validate and compare ecological network inference methods, and ultimately vastly increase our ability to understand and predict species biodiversity across space and time.
SynGAP regulates synaptic plasticity and cognition independent of its catalytic activity
Authors: Araki Yoichi , Rajkovich Kacey E. , Gerber Elizabeth E. , Gamache Timothy R. , Johnson Richard C. , Tran Thanh Hai , Liu Bian , Hong Ingie , Kirkwood Alfredo , Huganir Richard 
Published: August 2023

AbstractSynGAP is an abundant synaptic GTPase-activating protein (GAP) critical for synaptic plasticity, learning, memory, and cognition. Mutations inSYNGAP1in humans result in intellectual disability, autistic-like behaviors, and epilepsy. HeterozygousSyngap1knockout mice display deficits in synaptic plasticity, learning, and memory, and exhibit seizures. It is unclear whether SynGAP imparts structural properties at synapses independent of its GAP activity. Here, we report that inactivating mutations within the SynGAP GAP domain do not inhibit synaptic plasticity or cause behavioral deficits. Instead, SynGAP modulates synaptic strength by physically competing with the AMPA- receptor-TARP complex, the major excitatory receptor complex in the brain, in the formation of molecular condensates with synaptic scaffolding proteins. These results have significant implications for the development of therapeutic treatments forSYNGAP1- related neurodevelopmental disorders.One-Sentence SummarySynGAP regulates synaptic plasticity and cognition due to its phase separation properties instead of its catalytic activity.