bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cryogenic non-invasive 3D X-ray phase-contrast imaging of unfixed, intact mouse joints reveals shifting chondrocyte hypertrophy across the endochondral interface
Authors: Evans L. A. E. , Vezeleva D. , Bodey A.J. , Lee P. D. , Poologasundarampillai G. , Pitsillides A. A. 
Published: February 2024

AbstractObjectivesi) develop and use a new cryogenically-enhanced phase contrast method to visualise hyaline articular cartilage (HAC); ii) to measure HAC, articular calcified cartilage (ACC) and total articular cartilage thicknesses in male STR/Ort (osteoarthritis, OA) and CBA (healthy) mouse tibial epiphyses, reflecting divergent OA predisposition, at three age timepoints chosen to reflect pre-OA, OA onset and late-progression; iii) to compare HAC, trans-zonal and ACC 3D chondrocyte anatomy in tibial epiphyses.MethodsSTR/Ort and CBA mouse knees (n=4 per age and strain group) were synchrotron-CT scanned at high-resolution while fresh frozen, without staining, fixation, dissection or dehydration of the joint capsule. Both cartilage thickness and cellular characteristics (chondrocyte n=420) were manually measured and statistically compared (SPSS).ResultsCryo-enhanced phase contrast allowed cartilage to be seen in full thickness with cellular detail. HAC was thicker in STR/Ort than age-matched CBA mice in 16/24 knee joint compartments and timepoints (all p<0.04). In contrast, HAC was thicker only in the posterior lateral femur of CBA mice at 10weeks (p<0.001, Table 1). ACC and total cartilage were also thicker in STR/Orts. Trans-zonal chondrocytes were smaller than ACC and HAC chondrocytes (p-values<0.001, volumes 878, 1,567μm3and 1,348μm3respectively).ConclusionsCryogenically-enhanced phase-contrast imaging allowed cellular detail to be seen in 3D as never before in HAC in this (or any other) model. Our findings challenge current understanding by associating STR/Ort OA vulnerability with regions of thick, rather than thinning-with-age, cartilage. Our data affirm an association between excessively hypertrophic chondrocytes and OA is present in STR/Ort mice.
Predicting cell type-specific extracellular vesicle biology using an organism-wide single cell transcriptomic atlas – insights from theTabula Muris
Authors: LaRocca Thomas J. , Lark Daniel S. 
Published: February 2024

ABSTRACTExtracellular vesicles (EVs) like exosomes are functional nanoparticles trafficked between cells and found in every biofluid. An incomplete understanding of which cells, from which tissues, are trafficking EVsin vivohas limited our ability to use EVs as biomarkers and therapeutics. However, recent discoveries have linked EV secretion to expression of genes and proteins responsible for EV biogenesis and found as cargo, which suggests that emerging “cell atlas” datasets could be used to begin understanding EV biology at the level of the organism and possibly in rare cell populations. To explore this possibility, here we analyzed 67 genes that are directly implicated in EV biogenesis and secretion, or carried as cargo, in ∼44,000 cells obtained from 117 cell populations of theTabula Muris. We found that the most abundant proteins found as EV cargo (tetraspanins and syndecans) were also the most abundant EV genes expressed across all cell populations, but the expression of these genes varied greatly among cell populations. Expression variance analysis also identified dynamic and constitutively expressed genes with implications for EV secretion. Finally, we used EV gene co-expression analysis to define cell population-specific transcriptional networks. Our analysis is the first, to our knowledge, to predict tissue- and cell type-specific EV biology at the level of the organism and in rare cell populations. As such, we expect this resource to be the first of many valuable tools for predicting the endogenous impact of specific cell populations on EV function in health and disease.
Can we predict the predation pressure of owned domestic cats on all birds in the United States?
Authors: Philippe-Lesaffre Martin 
Published: February 2024

AbstractDomestic cats (Felis catus) have shared a common history with humans since their domestication 10,000 years ago and today they are one of the world’s most widespread predatory mammals. Different populations of domestic cats around the world show a high degree of variability in terms of their autonomy from humans for feeding or moving about, with common descriptions ranging from owned domestic cats to feral domestic cats on the spectrum from the most dependent to the most autonomous about humans. Distinguishing between owned and other domestic cats, I proposed a framework based on machine learning and citizen science data to predict the annual predation pressure on bird species per domestic cat considering traits, phylogeny and geographical distribution. Leveraging the Random Forest model and data from Mori et al. (2019), I assessed the predation pressure for each native continental bird species of the United States.Findings revealed that geographical distribution, phylogeny and traits influenced the predictive value of predation pressure, while a specific trait combination was also associated with high predation pressure. Furthermore, 35% of species experienced high predation pressure from owned domestic cats regardless of the existing threats. The results are consistent with former empirical evidence of predation by domestic cats in the United States and highlight the urgency of understanding the ecological impact of domestic cats. By producing a quantitative value for predation pressure, the framework allows the development of more reliable models of species extinction risk, including for the effects of domestic cat predation, and thus the use of more specific management strategies to sensitive populations. Although the study requires further refinement, the framework offers promising insights. With expanded citizen science protocols, it could help improve the extinction risk models and guide precise management strategies, which are crucial for mitigating the impact of domestic cats on native wildlife.
Bayesian Workflow for Generative Modeling in Computational Psychiatry
Authors: Hess Alexander J. , Iglesias Sandra , Köchli Laura , Marino Stephanie , Müller-Schrader Matthias , Rigoux Lionel , Mathys Christoph , Harrison Olivia K. , Heinzle Jakob , Frässle Stefan , Stephan Klaas Enno 
Published: February 2024

AbstractComputational (generative) modelling of behaviour has considerable potential for clinical applications. In order to unlock the potential of generative models, reliable statistical inference is crucial. For this, Bayesian workflow has been suggested which, however, has rarely been applied in Translational Neuromodeling and Computational Psychiatry (TN/CP) so far. Here, we present a worked example of Bayesian workflow in the context of a typical application scenario for TN/CP.This application example uses Hierarchical Gaussian Filter (HGF) models, a family of computational models for hierarchical Bayesian belief updating. When equipped with a suitable response model, HGF models can be fit to behavioural data from cognitive tasks; these data frequently consist of binary responses and are typically univariate. This poses challenges for statistical inference due to the limited information contained in such data. We present a novel set of response models that allow for simultaneous inference from multivariate (here: two) behavioural data types. Using both simulations and empirical data from a speed-incentivised associative reward learning (SPIRL) task, we show that harnessing information from two different data streams (binary responses and continuous response times) improves the accuracy of inference (specifically, identifiability of parameters and models). Moreover, we find a linear relationship between log-transformed response times in the SPIRL task and participants’ uncertainty about the outcome.Our analysis illustrates the benefits of Bayesian workflow for a typical use case in TN/CP. We argue that adopting Bayesian workflow for generative modelling helps increase the transparency and robustness of results, which in turn is of fundamental importance for the long-term success of TN/CP.
Temporal characterization of the viral load of psittacine beak and feather disease virus in rosy-faced lovebirds (Agapornis roseicollis)
Authors: Lam Derek Kong , Kei Poon Emily Shui , Sin Simon Yung Wa 
Published: February 2024

AbstractPsittacine beak and feather disease virus (PBFDV) is a widespread and highly pathogenic virus in parrots (Psittaciformes), threatening both captive and wild populations over the world. The disease typically presents with feather and beak abnormalities, along with possible immune system suppression. No cure or commercialized vaccine is currently available. Our understanding of the Psittacine beak and feather disease often come from infected individuals with visible symptoms. Limited knowledge exists regarding the pathology and role of asymptomatic individuals in disease transmission. Asymptomatic individuals could shed virus in their crop secretion, feces, or feathers. In this study, we investigated the temporal change in viral load in feather and fecal samples from 17 asymptomatic rosy-faced lovebirds (Agapornis roseicollis). We developed a qPCR assay for PBFDV viral load quantification in the studied lovebirds. Our results showed that most of the individuals had very low viral load, while three individuals with high viral load at the beginning of the experiment were observed to exhibit a decreasing trend in viral load in both fecal and feather samples. Surprisingly, the viral load in an individual can drop from a high level to an undetectable level within three months, which is contrary to the prevailing notion that the disease is highly lethal with few reports of complete recovery. We also showed that viral load in feathers was higher than in feces. Our study provides valuable insights into the infection dynamics of PBFDV in asymptomatic individuals and contribute to the understanding of disease transmission in parrots.
Confounding factors in targeted degradation of short-lived proteins
Authors: Vetma Vesna , Casarez-Perez Laura , Eliaš Ján , Stingu Andrea , Kombara Anju , Gmaschitz Teresa , Braun Nina , Ciftci Tuncay , Dahmann Georg , Diers Emelyne , Gerstberger Thomas , Greb Peter , Kidd Giorgia , Kofink Christiane , Puoti Ilaria , Spiteri Valentina , Trainor Nicole , Westermaier Yvonne , Whitworth Claire , Ciulli Alessio , Farnaby William , McAulay Kirsten , Frost Aileen B. , Chessum Nicola , Koegl Manfred 
Published: February 2024

SummaryTargeted protein degradation has recently emerged as a novel option in drug discovery. Natural protein half-life is expected to affect the efficacy of degrading agents, but to what extent it influences target protein degradation has not been systematically explored. Using mathematical modelling of protein degradation, we demonstrate that the natural half-life of a target protein has a dramatic effect on the level of protein degradation induced by a degrader agent which can pose significant hurdles to screening efforts. Moreover, we show that upon screening for degraders of short-lived proteins, agents that stall protein synthesis, such as GSPT1 degraders and generally cytotoxic compounds, deceptively appear as protein degrading agents. This is exemplified by the disappearance of short-lived proteins such as MCL1 and MDM2 upon GSPT1 degradation and upon treatment with cytotoxic agents such as doxorubicin. These findings have implications for target selection as well as for the type of control experiments required to conclude that a novel agent works as a bona fide targeted protein degrader.
Emergence of neural persistence: Insights from computational modelling
Authors: Verma Vishal 
Published: February 2024

AbstractThe persistent neural activity at a global scale, either stationary or oscillatory, can be explained by the use of the excitatory-inhibitory neural network models. This state of the network, as can be inferred, is crucial for the information processing and the memorizing ability of the brain. Though the goal for persistence to exist is apparent; from where the network achieves its ability to show a rich variety of the persistent dynamical states is unclear. The following study investigates the possible reasons for the persistence of neuronal networks in two parts; numerically and analytically. Presently, it shows that the action of the inhibitory components, among other favourable factors, plays a key role in starting and stabilizing neural activity. The results strongly support previous research conducted with both simpler and more specialized neural network models, as well as neurophysiological experiments.PACS numbers (2006 scheme)05.40.-a, 05.45.-a, 87.00, 89.00
Simulating Colloid Motion in Spinning Suspension: Internal Dynamics in Orbital Shaker
Authors: Zhao Neil , Zheng Diana 
Published: February 2024

AbstractColloid suspensions in the form of mammalian or bacterial cell mixtures in orbital shakers are commonly encountered in biomedical research. An understanding of particle motion in these conditions would provide insight into bulk colloid behavior and distribution under short and long timeframes. Such data can be used to supplement and clarify existing concepts of biological phenomena encountered in the laboratory setting. It can also aid biomedical researchers in experiment design and data interpretation. We present a MATLAB based simulation of colloid motion under rotary agitation. Our simulation setup is modular and therefore designed to act as a scaffold that can be customized to simulate different mammalian, bacterial, or particle properties in liquid suspension.
Single-nucleus multiomics reveals the gene-regulatory networks underlying sex determination of murine primordial germ cells
Authors: Alexander Adriana K. , Rodriguez Karina F. , Chen Yu-Ying , Amato Ciro M. , Estermann Martin A. , Nicol Barbara , Xu Xin , Yao Humphrey Hung-Chang 
Published: February 2024

AbstractAccurate specification of female and male germ cells during embryonic development is critical for sexual reproduction. Primordial germ cells (PGCs) are the bipotential precursors of mature gametes that commit to an oogenic or spermatogenic fate in response to sex-determining cues from the fetal gonad. The critical processes required for PGCs to integrate and respond to signals from the somatic environment in gonads are not understood. In this study, we developed the first single-nucleus multiomics map of chromatin accessibility and gene expression during murine PGC development in both XX and XY embryos. Profiling of cell-type specific transcriptomes and regions of open chromatin from the same cell captured the molecular signatures and gene networks underlying PGC sex determination. Joint RNA and ATAC data for single PGCs resolved previously unreported PGC subpopulations and cataloged a multimodal reference atlas of differentiating PGC clusters. We discovered that regulatory element accessibility precedes gene expression during PGC development, suggesting that changes in chromatin accessibility may prime PGC lineage commitment prior to differentiation. Similarly, we found that sexual dimorphism in chromatin accessibility and gene expression increased temporally in PGCs. Combining single-nucleus sequencing data, we computationally mapped the cohort of transcription factors that regulate the expression of sexually dimorphic genes in PGCs. For example, the gene regulatory networks of XX PGCs are enriched for the transcription factors, TFAP2c, TCFL5, GATA2, MGA, NR6A1, TBX4, and ZFX. Sex-specific enrichment of the forkhead-box and POU6 families of transcription factors was also observed in XY PGCs. Finally, we determined the temporal expression patterns of WNT, BMP, and RA signaling during PGC sex determination, and our discovery analyses identified potentially new cell communication pathways between supporting cells and PGCs. Our results illustrate the diversity of factors involved in programming PGCs towards a sex-specific fate.
CAMKV Kinase Signaling Is a Novel Therapeutic Avenue with Prognostic Relevance in Neuroblastoma
Authors: Yu Yang , Zhao Yanling , Shi Zhongcheng , Cheng Feng , Wang Larry L. , Choi Jong Min , Li Kan , Silverman Daniel , Qi Dan , Wang Jun , Agarwal Saurabh , Rood Brian R , Dome Jeffrey S. , Fabbri Muller , Yi Joanna S. , Wu Erxi , Jung Sung Yun , Zhang Chunchao , Yang Jianhua 
Published: February 2024

AbstractNeuroblastoma (NB) can be a highly aggressive malignancy in children. However, the precise mechanisms driving NB tumorigenesis remain elusive. This study revealed the critical role of CREB phosphorylation in NB cell proliferation. By employing a CRISPR-Cas9 knockout screen targeting calcium/calmodulin-dependent protein kinase (CaMK) family members, we identified the CaM kinase-like vesicle-associated (CAMKV) protein as a kinase that mediates direct phosphorylation of CREB to promote NB cell proliferation.CAMKVwas found to be a transcriptional target of MYCN/MYC in NB cells. CAMKV knockout and knockdown effectively suppressed NB cell proliferation and tumor growth both in vitro and in vivo. Bioinformatic analysis revealed that high CAMKV expression is significantly correlated with poor patient survival. High-risk NB frequently had high CAMKV protein levels by Immunohistochemical staining. Integrated transcriptomic and proteomic analyses of CAMKV knockdown cells unveiled downstream targets involved in CAMKV-regulated phosphorylation and signaling pathways, many of which are linked to neural development and cancer progression. We identified small molecule inhibitors targeting CAMKV and further demonstrated the efficacy of one inhibitor in suppressing NB tumor growth and prolonging the survival of mice bearing xenografted tumors. These findings reveal a critical role for CAMKV kinase signaling in NB growth and identified CAMKV kinase as a potential therapeutic target and prognostic marker for patients with NB.
Effective Population Size in Field Pea
Authors: Johnson Josephine Princy , Piche Lisa , Worral Hannah , Atanda Sikiru Adeniyi , Coyne Clarice J. , McGee Rebecca , McPhee Kevin , Bandillo Nonoy 
Published: February 2024

AbstractBackgroundEffective population size (Ne) is a pivotal parameter in population genetics as it can provide information on the rate of inbreeding and the contemporary status of genetic diversity in breeding populations. The population with smallerNecan lead to faster inbreeding, with little potential for genetic gain making selections ineffective. The importance ofNehas become increasingly recognized in plant breeding, which can help breeders monitor and enhance the genetic variability or redesign their selection protocols. Here, we present the firstNeestimates based on linkage disequilibrium (LD) in the pea genome.ResultsWe calculated and comparedNeusing SNP markers from North Dakota State University (NDSU) modern breeding lines and United States Department of Agriculture (USDA) diversity panel. The extent of LD was highly variable not only between populations but also among different regions and chromosomes of the genome. Overall, NDSU had a higher and longer-range LD than the USDA that could extend up to 500Kb, with a genome-wide averager2of 0.57 (vs 0.34), likely due to its lower recombination rates and the selection background. The estimatedNefor the USDA was nearly three-fold higher (Ne=174) than NDSU (Ne=64), which can be confounded by a high degree of population structure due to the selfing nature of pea.ConclusionsOur results provided insights into the genetic diversity of the germplasm studied, which can guide plant breeders to actively monitorNein successive cycles of breeding to sustain viability of the breeding efforts in the long term.
Polygenic Risk for Alcohol Use Disorder Affects Cellular Responses to Ethanol Exposure in a Human Microglial Cell Model
Authors: Li Xindi , Liu Jiayi , Boreland Andrew J. , Kapadia Sneha , Zhang Siwei , Stillitano Alessandro C. , Abbo Yara , Clark Lorraine , Lai Dongbing , Liu Yunlong , Barr Peter B , Meyers Jacquelyn L. , Kamarajan Chella , Kuang Weipeng , Agrawal Arpana , Slesinger Paul A. , Dick Danielle , Salvatore Jessica , Tischfield Jay , Duan Jubao , Edenberg Howard J. , Kreimer Anat , Hart Ronald P. , Pang Zhiping P. 
Published: February 2024

AbstractPolygenic risk scores (PRS) assess genetic susceptibility to Alcohol Use Disorder (AUD), yet their molecular implications remain underexplored. Neuroimmune interactions, particularly in microglia, are recognized as significant contributors to AUD pathophysiology. We investigated the interplay between AUD PRS and ethanol in human microglia derived from iPSCs from individuals with high- or low-PRS (HPRS or LPRS) of AUD. Ethanol exposure induced elevated CD68 expression and morphological changes in microglia, with differential responses between HPRS and LPRS microglial cells. Transcriptomic analysis revealed expression differences in MHCII complex and phagocytosis-related genes following ethanol exposure; HPRS microglial cells displayed enhanced phagocytosis and increasedCLEC7Aexpression, unlike LPRS microglial cells. Synapse numbers in co-cultures of induced neurons with microglia after alcohol exposure were lower in HRPS co-cultures, suggesting possible excess synapse pruning. This study provides insights into the intricate relationship between AUD PRS, ethanol, and microglial function, potentially influencing neuronal functions in developing AUD.
Overcoming brain-derived therapeutic resistance in HER2+ breast cancer brain metastasis
Authors: Ippolitov Danyyl , Lin Yi-Han , Spence Jeremy , Glogowska Aleksandra , Thanasupawat Thatchawan , Beiko Jason , Del Bigio Marc R. , Xu Xin , Wang Amy , Calvo Raul , Kapoor Abhijeet , Marugan Juan J , Henderson Mark J , Klonisch Thomas , Hombach-Klonisch Sabine 
Published: February 2024

ABSTRACTBrain metastasis of HER2+ breast cancer occurs in about 50% of all women with metastatic HER2+ breast cancer and confers poor prognosis for patients. Despite effective HER2-targeted treatments of peripheral HER2+ breast cancer with Trastuzumab +/-HER2 inhibitors, limited brain permeability renders these treatments inefficient for HER2+ breast cancer brain metastasis (BCBM). The scarcity of suitable patient-derived in-vivo models for HER2+ BCBM has compromised the study of molecular mechanisms that promote growth and therapeutic resistance in brain metastasis. We have generated and characterized new HER2+ BCBM cells (BCBM94) isolated from a patient HER2+ brain metastasis. Repeated hematogenic xenografting of BCBM94 consistently generated BCBM in mice. The clinically used receptor tyrosine kinase inhibitor (RTKi) Lapatinib blocked phosphorylation of all ErbB1-4 receptors and induced the intrinsic apoptosis pathway in BCBM94. Neuregulin-1 (NRG1), a ligand for ErbB3 and ErbB4 that is abundantly expressed in the brain, was able to rescue Lapatinib-induced apoptosis and clonogenic ability in BCBM94 and in HER2+ BT474. ErbB3 was essential to mediate the NRG1-induced survival pathway that involved PI3K-AKT signalling and the phosphorylation of BAD at serine 136 to prevent apoptosis. High throughput RTKi screening identified the brain penetrable Poziotinib as highly potent compound to reduce cell viability in HER2+ BCBM in the presence of NRG1. Successful in-vivo ablation of BCBM94- and BT474-derived HER2+ brain tumors was achieved upon two weeks of treatment with Poziotinib. MRI revealed BCBM remission upon poziotinib, but not with Lapatinib treatment. In conclusion, we have established a new patient-derived HER2+ BCBM in-vivo model and identified Poziotinib as highly efficacious RTKi with excellent brain penetrability that abrogated HER2+ BCBM brain tumors in our mouse models.