bluuebunny/crossref_metadata_2025_split huggingface dataset:
Constructing Biologically Constrained RNNs via Dale’s Backprop and Topologically-Informed Pruning
Authors: Balwani Aishwarya H. , Wang Alex Q. , Najafi Farzaneh , Choi Hannah 
Published: January 2025

AbstractRecurrent neural networks (RNNs) have emerged as a prominent tool for modeling cortical function, and yet their conventional architecture is lacking in physiological and anatomical fidelity. In particular, these models often fail to incorporate two crucial biological constraints: i) Dale’s law, i.e., sign constraints that preserve the “type” of projections from individual neurons, and ii) Structured connectivity motifs, i.e., highly sparse yet defined connections amongst various neuronal populations. Both constraints are known to impair learning performance in artificial neural networks, especially when trained to perform complicated tasks; but as modern experimental methodologies allow us to record from diverse neuronal populations spanning multiple brain regions, using RNN models to study neuronal interactions without incorporating these fundamental biological properties raises questions regarding the validity of the insights gleaned from them. To address these concerns, our work develops methods that let us train RNNs which respect Dale’s law whilst simultaneously maintaining a specific sparse connectivity pattern across the entire network. We provide mathematical grounding and guarantees for our approaches incorporating both types of constraints, and show empirically that our models match the performance of RNNs trained without any constraints. Finally, we demonstrate the utility of our methods for inferring multi-regional interactions by training RNN models of the cortical network to reconstruct 2-photon calcium imaging data during visual behaviour in mice, whilst enforcing data-driven, cell-type specific connectivity constraints between various neuronal populations spread across multiple cortical layers and brain areas. In doing so, we find that the interactions inferred by our model corroborate experimental findings in agreement with the theory of predictive coding, thus validating the applicability of our methods.
Macroevolution of fly wings proceeds along developmental lines of least resistance
Authors: Rohner Patrick T. , Berger David 
Published: January 2025

AbstractEvolutionary change necessitates genetic variation, and a reigning paradigm in biology is that rates of microevolution can be predicted from estimates of available genetic variation within populations. However, the accuracy of such predictions should decay on longer evolutionary timescales, as the influence of genetic constraints diminishes. Here, we show that intrinsic developmental variability and standing genetic variation in wing shape in two distantly related flies,Drosophila melanogasterandSepsis punctum, are aligned and predict deep divergence in the dipteran phylogeny, spanning >900 taxa and 185 My. This alignment cannot easily be explained by constraint hypotheses unless most of the quantified standing genetic variation is associated with deleterious side-effects and effectively unusable for evolution. However, phenotyping of 71 genetic lines ofS. punctumrevealed no covariation between wing shape and fitness, lending no support to this hypothesis. We also find little evidence for genetic constraints on the pace of wing shape evolution along the dipteran phylogeny. Instead, correlational selection related to allometric scaling, simultaneously shaping developmental bias and deep divergence in fly wings, emerges as a potential explanation for the observed alignment. This suggests that pervasive natural selection has the potential to shape developmental architectures of some morphological characters such that their intrinsic variability predicts their long-term evolution.
BDNF in Ventrolateral Orbitofrontal Cortex to Dorsolateral Striatum Circuit Moderates Alcohol Consumption and Gates Alcohol Habit
Authors: Gunasekaran Sowmya , Moffat Jeffrey J. , Epstein Joshua D. , Phamluong Khanhky , Ehinger Yann , Ron Dorit 
Published: January 2025

AbstractBDNF plays a crucial role in shaping the structure and function of neurons. BDNF signaling in the dorsolateral striatum (DLS) is part of an endogenous pathway that protects against the development of alcohol use disorder (AUD). Dysregulation of BDNF levels in the cortex or dysfunction of BDNF/TrkB signaling in the DLS results in the escalation of alcohol drinking and compulsive alcohol use. The major source of BDNF in the striatum is the prefrontal cortex. We identified a small ensemble of BDNF-positive neurons in the ventrolateral orbitofrontal cortex (vlOFC), a region involved in AUD, that extend axonal projections to the DLS. We speculated that BDNF in vlOFC-to-DLS circuit may play a role in limiting alcohol drinking and that heavy alcohol use disrupts this protective pathway. We found thatBDNFexpression is reduced in the vlOFC of male but not female mice after long-term cycles of binge alcohol drinking and withdrawal. We discovered that overexpression of BDNF in vlOFC-to-DLS but not in vlOFC-to-dorsomedial striatum (DMS) or M2 motor cortex-to-DLS circuit reduces alcohol but not sucrose intake and preference. The DLS plays a major role in habitual behaviors. We hypothesized that BDNF in vlOFC-to-DLS circuitry controls alcohol intake by gating habitual alcohol seeking. We found that BDNF over-expression in vlOFC-to-DLS circuit and systemic administration of BDNF receptor TrkB agonist, LM22A-4, biases habitually trained mice towards goal-directed alcohol seeking. Together, our data suggest that BDNF in a small ensemble of vlOFC-to-DLS neurons gates alcohol intake by attenuating habitual alcohol seeking.
Cleanet: robust doublet detection in cytometry data based on protein expression patterns
Authors: Ionita Matei , McKeague Michelle L. , Painter Mark M. , Mathew Divij , Pattekar Ajinkya , Maseda Damian , Wherry E. John , Greenplate Allison R. 
Published: January 2025

AbstractFlow and mass cytometry experiments are essential for profiling immune cells at single cell resolution. Better understanding of human immunology increasingly involves analyzing studies at the scale of hundreds or thousands of samples, with data analysis a significant bottleneck. This trend increases the demand for automated analysis methods. In particular, a common preprocessing step in cytometry data analysis is distinguishing single cells from doublets (or multiplets), events in which two (or more) cells pass simultaneously through the detector. Typically, doublets are identified on two-dimensional density plots, using their high measured values for DNA intercalators (mass cytometry) or scattering channels (flow cytometry). Despite its popularity, this bivariate gating method is sometimes imprecise: for example, we show that bivariate gating of mass cytometry data can mistake single eosinophils for doublets, due to their high DNA content. Taking inspiration from methods already used in single cell transcriptomics, but not in the cytometry community, we propose an alternative approach. Our method, called Cleanet, first simulates doublet events, then identifies true events with protein expression similar to the simulated doublets. This simple method is completely automated and detects both homotypic and heterotypic doublets. We validate it in datasets acquired with mass and flow cytometry; moreover, we verify with imaging flow cytometry that events predicted to be doublets truly consist of multiple cells. Cleanet can also classify doublets based on their component cell types, which potentially enables the study of cell-cell interactions, mining extra information out of doublet events that would otherwise be discarded. As a proof of concept, we demonstrate that Cleanet can detect a treatment-specific increase in interactions between two cell lines. By automating doublet detection and classification, we aim to streamline the data analysis in large cytometry studies and provide a more accurate picture of both immune cell populations and cell-cell interactions.
Rosace-AA: Enhancing Interpretation of Deep Mutational Scanning Data with Amino Acid Substitution and Position-Specific Insights
Authors: Rao Jingyou , Wang Mingsen , Howard Matthew K , Macdonald Christian , Fraser James S. , Coyote-Maestas Willow , Pimentel Harold 
Published: January 2025

AbstractProteins are dynamic systems whose function and behavior are sensitive to environmental conditions and often involve multiple cellular roles. Deep mutational scanning (DMS) experiments generate extensive datasets to capture the functional consequences of mutations. However, the sheer volume of data presents challenges in visualization and interpretation. Current approaches often rely on heatmaps, but these methods fail to capture the nuanced effects of amino acid (AA) substitutions, which are essential for understanding mutational impact. To address this, we extend the Rosace framework withRosace-AA, a model that incorporates both position-specific information and AA substitution trends. Using substitution matrices like BLOSUM90,Rosace-AAoffers a flexible and interpretable approach to summarize DMS data oil both protein-level and position-level. We demonstrate its utility across datasets, including OCTI and MET kinase, showing thatRosace-AAhighlights key positions where mutations deviate from expected substitution patterns and captures functionally relevant variation in protein behavior across multiple DMS screens. These results suggest thatRosace-AAenables more robust and interpretable analysis of complex DMS datasets.
Role of drug induced nuclear CTSL (nCTSL) in DNA damage response in cancer- therapeutic implications
Authors: Thirsangu Prabhu , Jin Ling , Ray Upasana , Zhao Anya , Wu Xinyan , Hou Xiaonan , VanBlaricom Jamison L , Aalam Syed Mohamed Musheer , Oberg Ann , Kannan Nagarajan , Weroha John , Chien Jeremy , Kaufmann Scott H , Bakkum-Gamez Jamie N , Shridhar Viji 
Published: January 2025

ABSTRACTIn our efforts to enhance sensitivity to PARP inhibitors, we identified clofarabine (CLF) as a potential therapy for drug-resistant ovarian cancer and nuclear trafficking of Cathepsin L (CTSL) as a treatment- responsive biomarker. Using PARP inhibitor-sensitive and -resistant OC cell lines, ex vivo cultures of patient-derived ovarian ascites (OVA), primary ovarian tumors, and xenografts (PDX), we found that CLF monotherapy induces nuclear CTSL (nCTSL) in CLF-responsive cells (CLF-r) and sensitizes them to PARP inhibitors olaparib and rucaparib. In CLF non-responsive cells (CLF-nr), a combination of CLF with olaparib is necessary for nCTSL trafficking and synergy. CLF+olaparib synergy was observed in 47% of CLF-r and 24% of CLF-nr OVA samples. Drug-induced nCTSL is crucial for DNA damage response, including cell cycle arrest and apoptosis. Knockdown of CTSL in both CLF-r and CLF-nr cells conferred resistance to the CLF+olaparib combination, emphasizing nCTSL’s role in the DNA damage response pathway (DDR). Mechanistically, CLF facilitates CTSL nuclear import via KPNB1 in CLF-r cells. In CLF-nr cells, both olaparib and CLF are needed to facilitate CTSL nuclear import. Additionally, CLF downregulates the nuclear export protein CRM1 (XPO1) in both cohorts. Interestingly, CLF does not downregulate CRM1 in a subset of OVAs (29%), and they were classified as CLF-resistant (CLF- Res). In these samples, inhibiting CRM1 with KPT8602 restored synergy between CLF and PARP inhibitors. In vivo, CLF-r and CLF-nr PDX models exhibited enhanced DDR, reduced tumor burden, and prolonged survival with the CLF+olaparib combination. These findings suggest the CLF+olaparib combination is a promising therapeutic strategy for drug-resistant OC by inducing DDR through CTSL nuclear localization.
Inhibition of Glutamine Metabolism Suppresses Tumor Progression through Remodeling of the Macrophage Immune Microenvironment
Authors: Li Tianhe , Akhtarkhavari Sepehr , Chang Tu-Yung , Shen Yao-An , Yang JinMing , Slusher Barbara , Shih Ie-Ming , Gaillard Stephanie , Wang Tian-Li 
Published: January 2025

AbstractBackgroundTargeting glutamine metabolism has emerged as a promising strategy in cancer therapy. However, several barriers, such asin vivoanti-tumor efficacy, drug toxicity, and safety, remain to be overcome to achieve clinical utility. Prior preclinicalin vivostudies had generated encouraging data showing promises of cancer metabolism targeting drugs, although most were performed on immune-deficient murine models. It is being recognized that aside from tumor cells, normal cells such as immune cells in the tumor microenvironment may also utilize glutamine for maintaining physiological functions. To provide an in-depth view of glutamine antagonist (GLNi) treatment on the tumor immune microenvironment, the current study made several unique approaches.MethodFirst, to evaluate GLNi treatment modality that potentially involves immune cells, the study was performed on immunocompetent murine models of gynecological cancers. Second, to enhance safety and reduce potential off-target effects, we developed a GLNi prodrug, JHU083, which is bio-activated restrictively in cancer tissues. Third, to unbiasedly decode the response of single cells in the tumor microenvironment to GLNi treatment, single-cell RNA sequencing (scRNA-seq) was performed on cells prepared from tumors of the JHU083 or vehicle control-treated mice.ResultsIn both immunocompetent murine tumor models, we observed a significant anti-tumor efficacy, resulting in reduced tumor burden and impeded tumor progression. Similarly, in both tumor models, scRNA-seq revealed significantly impeded immunosuppressive M2-like macrophages by JHU083, while the treatment spared pro-inflammatory M1-like tumor macrophages. In many tumor microenvironment (TME) cells, JHU083 downregulated genes regulated by Myc and hypoxia. M2 macrophages’ greater sensitivity to glutamine antagonism when compared to M1 macrophages or monocytes was further validated onex vivocultures of bone marrow-derived macrophages.ConclusionOur findings support a converged mechanism of glutamine metabolism antagonists. JHU083 exerted its anti-tumor efficacy through not only direct targeting of glutamine-addicted cancer cells but also by suppressing glutamine-dependent M2 macrophages, leading to a shift in the M1/M2 macrophage landscape in favor of an immune-stimulatory microenvironment.
The “value perspectives of nature” scale: A validated scale to measure plural value perspectives of future nature from a transformative angle
Authors: Buijs Arjen E. , Dressel Sabrina , Jacobsen Jette B. , de Kruiff Tim M. , Uribe Laura Quintero , Smith Angus M. , Gamborg Christian 
Published: January 2025

AbstractJust sustainability transformation is a process of change that has a dual commitment to human well-being and environmental sustainability. Inclusive transformation critically depends on recognition of the plural values of nature in society. Lack of value alignment can lead to profound disagreements with those in society not sharing the same views on nature.To explore plural value perspectives, we introduce the Value Perspectives of Nature (VPN) scale. This scale builds on existing value literature and measurement scales as well as on transformative approaches, most notable the Nature Futures Framework.Using a seven-step process that includes qualitative expert evaluations, cognitive interviews, and three rounds of quantitative pre-testing and validation, the scale is developed, refined, and validated across five European countries (representative sample; N=1000).The final VPN scale consists of 11 items, measuring instrumental value perspectives (material and nonmaterial contributions to people), relational value perspectives (place attachment and identity; Fulfilment and well-being; Spirituality; and Kinship) and intrinsic value perspectives (nature as an end in itself and acknowledgement of the rights of nature). The final validation study shows moderate to high internal consistency, reliability, and predictive validity of the scale across all countries.While existing scales often focus on single values, the VPN is the first cross-culturally validated scale that integrates intrinsic, instrumental, and relational value perspectives into one composite scale with a focus on changes for the future. Based on the development and analysis of the VPN, we discuss several theoretical and conceptual issues in relation to relational values.Policy implications: The VPN scale can be used in survey research to understand attitudes towards nature restoration measures. This may facilitate dialogue on effective and just transformative change in nature, through sensitising to the plural values of diverse communities. It may also be used to monitor the diversity of value perspectives over time and between communities and stakeholders. Understanding such changes in mind-sets and taking into account concerns from critical groups in society will help navigate towards positive nature futures supported by the general public.
A new map of South Manchurian mixed forests facilitates the estimation of their area for conservation purposes
Authors: Dzizyurova Violetta , Dudov Sergey , Petrenko Tatyana , Krestov Pavel , Grishchenko Mikhail , Korznikov Kirill 
Published: January 2025

AbstractQuestionsSouth Manchurian mixed forests (SMMFs) are among the most species-rich forest ecosystems in the world’s temperate zone. These forests are experiencing significant degradation and have largely been replaced by secondary forests or agricultural lands and anthropogenic non-forest vegetation. A precise quantitative assessment of the remaining forest area is crucial due to their high conservation value. This study aims to assess the current area of these forests and evaluate changes over a historical period.LocationKorean Peninsula, northeastern China, and southern Primorsky Krai in Russia.MethodsWe used the original SMMFs distribution dataset, including vegetation relevés, literature on the distribution of these forests, and regional small-scale maps, to create a training set for classifying satellite data. We used Landsat Analysis Ready Data (1997–2001 and 2017–2021) as the basis for mapping. Mapping accuracy and area were estimated using a random stratified sampling, and forest changes were evaluated. Original relevés and literature sources were used to verify SMMFs distribution.ResultsThe total area of SMMFs was estimated at 2,791.5±1,496.2 km², with significant uncertainty due to limited data from North Korea. Our results indicate that 45% of SMMFs are located in North Korea, 32% in Russia, 20% in China, and 3% in South Korea. Although historical declines in SMMF area have been documented, no significant changes were detected over the past 20 years. In 2021, SMMFs are highly fragmented ecosystems, primarily associated with protected areas.ConclusionsWe developed a high-accuracy (0.97±0.03) map of mixed forests using remote sensing techniques. This map facilitates the identification of valuable temperate forest regions and enhances understanding of current forest distribution. Our map is essential for planning restoration and conservation efforts for these critical ecosystems.
A novel murine tail model for radiation-induced skin injury following localized irradiation at varying doses
Authors: Wang Guojian , Zhao Na , Long Shuang , Gao Jining , Zhou Qing , Ran Xinze , Wang Junping , Wang Tao 
Published: January 2025

AbstractBackgroundRadiation therapy is one cornerstone of oncologic treatment. Radiation-induced skin injury (RISI) is a dose-limiting complication of radiotherapy. RISI is also common in victims of accidental exposure, which often aggravates the patient’s condition and becomes a difficult medical issue. However, the damage mechanisms of RISI remain unclear, and the prevention and treatment measures are limited. An appropriate animal model holds great significance for addressing these issues.MethodsC57BL/6 mice were employed to establish RISI model by irradiating 2 cm section of the mouse tail with 20Gy, 30Gy, and 40Gy of single irradiation. Skin injuries were scored with a modified semi-quantitative scale. H&E staining, IHC for dopachrome tautomerase (DTC) and Masson staining were used for histopathological evaluations of RISI.ResultsWe innovatively established animal models of RISI through tail irradiation. The model mice showed typical symptoms of dry desquamation, moist desquamation, ulcers and necrosis in the irradiated area, which were highly similar to the clinical manifestations. Concurrently, we discovered that in the later stage of this model, the interstitial tissue at irradiated site presented a fibrotic phenotype with good dose dependence. It should be noted that tail irradiation causes dynamic changes in skin melanin, with early excessive deposition and late loss, which renders the observation of radiation-induced skin erythema difficult. For this reason, we specifically revised the scoring criteria for RISI.ConclusionIn conclusion, this study established an easily operable and highly reproducible tail irradiation model, providing a novel platform for in-depth research on the mechanisms and translational applications of RISI.
Physiologically Relevant Coculture Model for Oral Microbial-Host Interactions
Authors: Pang Zeyang , Cady Nicole , Cen Lujia , Schmidt Thomas M. , He Xuesong , Li Jiahe 
Published: January 2025

AbstractUnderstanding microbial-host interactions in the oral cavity is essential for elucidating oral disease pathogenesis and its systemic implications.In vitrobacteria-host cell coculture models have enabled fundamental studies to characterize bacterial infection and host responses in a reductionist yet reproducible manner. However, existingin vitrococulture models fail to replicate the physiological oxygen gradients critical for studying these interactions. Here, we present an asymmetric gas coculture system that simulates the oral microenvironment by maintaining distinct normoxic and anaerobic conditions for gingival epithelial cells and anaerobic bacteria, respectively. UsingFusobacterium nucleatum, a key oral pathobiont, we demonstrate that the system preserves bacterial viability and supports the integrity of telomerase-immortalized gingival keratinocytes. Compared to conventional models, this system enhanced bacterial invasion, elevated intracellular bacterial loads, and elicited more robust host pro-inflammatory responses, including increased secretion of CXCL10, IL-6, and IL-8. Additionally, the model enabled precise evaluation of antibiotic efficacy against intracellular pathogens. These results underscore the utility of this coculture platform for studying oral microbial pathogenesis and screening therapeutics, offering a physiologically relevant approach to advance oral and systemic health research.TOC