bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modeling functional cell types in spike train data
Authors: Zdeblick Daniel N. , Shea-Brown Eric T. , Witten Daniela M. , Buice Michael A. 
Published: March 2023

AbstractA major goal of computational neuroscience is to build accurate models of the activity of neurons that can be used to interpret their function in circuits. Here, we explore usingfunctional cell typesto refine single-cell models by grouping them into functionally relevant classes. Formally, we define a hierarchical generative model for cell types, single-cell parameters, and neural responses, and then derive an expectation-maximization algorithm with variational inference that maximizes the likelihood of the neural recordings. We apply this “simultaneous” method to estimate cell types and fit single-cell models from simulated data, and find that it accurately recovers the ground truth parameters. We then apply our approach toin vitroneural recordings from neurons in mouse primary visual cortex, and find that it yields improved prediction of single-cell activity. We demonstrate that the discovered cell-type clusters are well separated and generalizable, and thus amenable to interpretation. We then compare discovered cluster memberships with locational, morphological, and transcriptomic data. Our findings reveal the potential to improve models of neural responses by explicitly allowing for shared functional properties across neurons.Author SummaryComputational neuroscience has its roots in fitting and interpreting predictive models of the activity of individual neurons. In recent years, more attention has focused on models of how ensembles of neurons work together to perform computations. However, fitting these more complex models to data is challenging, limiting our ability to use them to understand real neural systems. One idea that has improved our understanding of populations of neurons iscell types, where neurons of the same type have similar properties. While the idea of cell types is old, recent work has focused on functional cell types, where the properties of interest are derived from fitted predictive models of the activity of single neurons. In this work, we develop a method thatsimultaneouslyfits a predictive model of each neuron’s activity and groups neurons into functional cell types. Compared to existing techniques, this method produces more accurate models of single-cell neural activity and better groupings of neurons into types. This method can thus contribute in using cell types to better understanding the components of neural systems based on our increasingly rich observations of their functional responses.
Simultaneous mapping of epigenetic inter-haplotype, inter-cell and inter-individual variation via the discovery of jointly regulated CpGs in pooled sequencing data
Authors: Planterose Jiménez Benjamin , Kolar Brontë , Kayser Manfred , Vidaki Athina 
Published: March 2023

AbstractIn the post-GWAS era, great interest has arisen in the mapping of epigenetic inter-individual variation towards investigating the emergence of phenotype in health and disease. Relevant DNA methylation methodologies – epigenome-wide association studies (EWAS), methylation quantitative traitloci(mQTL) mapping and allele-specific methylation (ASM) analysis – can each map certain sources of epigenetic variation and all depend on matching phenotypic/genotypic data. Here, to avoid these requirements, we developed Binokulars, a novel randomization test that identifies signatures of joint CpG regulation from reads spanning multiple CpGs. We tested and benchmarked our novel approach against EWAS and ASM on pooled whole-genome bisulfite sequencing (WGBS) data from whole blood, sperm and combined. As a result, Binokulars simultaneously discovered regions associated with imprinting, cell type- and tissue-specific regulation, mQTL, ageing and other (still unknown) epigenetic processes. To verify examples of mQTL and polymorphic imprinting, we developed JRC_sorter, another novel tool that classifies regions based on epigenotype models, which we deployed on non-pooled WGBS data from cord blood. In the future, this approach can be applied on larger pools to simultaneously map and characterise inter-haplotype, inter-cell and inter-individual variation in DNA methylation in a cost-effective fashion, a relevant pursuit towards phenome-mapping in the post-GWAS era.
Metabolomics investigation of post-mortem human pericardial fluid
Authors: Chighine Alberto , Stocchero Matteo , Ferino Giulio , De-Giorgio Fabio , Conte Celeste , Nioi Matteo , d’Aloja Ernesto , Locci Emanuela 
Published: March 2023

AbstractIntroductionDue to its peculiar anatomy and physiology, the pericardial fluid is a biological matrix of particular interest in the forensic field. Despite this, the available literature has mainly focused on post-mortem biochemistry and forensic toxicology, while to the best of authors’ knowledge post-mortem metabolomics has never been applied. Similarly, estimation of the time since death or Post-Mortem Interval based on pericardial fluids has still rarely been attempted.ObjectivesWe applied a metabolomic approach based on1H Nuclear Magnetic Resonance Spectroscopy to ascertain the feasibility of monitoring post-mortem metabolite changes on human pericardial fluids with the aim of building a multivariate regression model for Post-Mortem Interval estimation.MethodsPericardial fluid samples were collected in 24 consecutive judicial autopsies, in a time frame ranging from 16 to 170 hours after death. The only exclusion criterion was the quantitative and/or qualitative alteration of the sample. Two different extraction protocols were applied for low molecular weight metabolites selection, namely ultrafiltration and liquid-liquid extraction. Our metabolomic approach was based on the use of1H Nuclear Magnetic Resonance and multivariate statistical data analysis.ResultsThe pericardial fluid samples treated with the two experimental protocols did not show significant differences in the distribution of the metabolites detected. A post-mortem interval estimation model based on 18 pericardial fluid samples was validated with an independent set of 6 samples, giving a prediction error of 33 - 34 hours depending on the experimental protocol used. By narrowing the window to post-mortem intervals below 100 hours, the prediction power of the model was significantly improved with an error of 13-15 hours depending on the extraction protocol. Choline, glycine, ethanolamine, and hypoxanthine were the most relevant metabolites in the prediction model.ConclusionThe present study, although preliminary, shows that PF samples collected from a real forensic scenario represent a biofluid of interest for post-mortem metabolomics, with particular regard to the estimation of the time since death.
HIV-differentiated metabolite N-Acetyl-L-Alanine dysregulates human natural killer cell responses toMycobacterium tuberculosisinfection
Authors: Yang Baojun , Mukherjee Tanmoy , Radhakrishnan Rajesh , Paidipally Padmaja , Ansari Danish , John Sahana , Vankayalapati Ramakrishna , Tripathi Deepak , Yi Guohua 
Published: March 2023

AbstractBackgroundMycobacterium tuberculosis(Mtb) has latently infected over two billion people worldwide (LTBI) and causes 1.8 million deaths each year. Human immunodeficiency virus (HIV) co-infection with Mtb will affect the Mtb progression and increase the risk of developing active tuberculosis by 10-20 times compared to the HIV-LTBI+ patients. It is crucial to understand how HIV can dysregulate immune responses in LTBI+ individuals.MethodsPlasma samples collected from healthy and HIV-infected individuals were investigated by liquid chromatography-mass spectrometry (LC-MS), and the metabolic data were analyzed using an online platform Metabo-Analyst. ELISA, surface and intracellular staining, flow cytometry, quantitative reverse transcription PCR (qRT-PCR) were performed by standard procedure to determine the surface markers, cytokines and other signaling molecule expression. Seahorse extra cellular flux assays were used to measure the mitochondrial oxidative phosphorylation and glycolysis.ResultsSix metabolites were significantly less abundant, and two were significantly higher in abundance in HIV+ individuals compared to healthy donors. One of the HIV-upregulated metabolites, N-Acetyl-L-Alanine (ALA), inhibits pro-inflammatory cytokine IFN-□ production by NK cells of LTBI+ individuals. ALA inhibits glycolysis of LTBI+ individuals’ NK cells in response toMtb.ConclusionsOur findings demonstrate that HIV infection enhances plasma ALA levels to inhibit NK cell-mediated immune responses toMtbinfection, offering a new understanding of the HIV-Mtbinteraction and providing the implication of nutrition intervention and therapy for HIV-Mtbco-infected patients.
Coarse-Grained Molecular Simulations and Ensemble-Based Mutational Profiling of Protein Stability in the Different Functional Forms of the SARS-CoV-2 Spike Trimers : Balancing Stability and Adaptability in BA.1, BA.2 and BA.2.75 Variants
Authors: Verkhivker Gennady , Alshahrani Mohammed , Gupta Grace 
Published: March 2023

AbstractThe evolutionary and functional studies suggested that the emergence of the Omicron variants can be determined by multiple fitness trade-offs including the immune escape, binding affinity, conformational plasticity, protein stability and allosteric modulation. In this study, we embarked on a systematic comparative analysis of the conformational dynamics, electrostatics, protein stability and allostery in the different functional states of spike trimers for BA.1, BA.2, and BA.2.75 variants. Using efficient and accurate coarse-grained simulations and atomistic reconstruction of the ensembles, we examined conformational dynamics of the spike trimers that agrees with the recent functional studies, suggesting that BA.2.75 trimers are the most stable among these variants. A systematic mutational scanning of the inter-protomer interfaces in the spike trimers revealed a group of conserved structural stability hotspots that play a key role in modulation of functional dynamics and are also involved in the inter-protomer couplings through local contacts and interaction networks with the Omicron mutational sites. The results of mutational scanning provided evidence that BA.2.75 trimers are more stable than BA.2 and comparable in stability to BA.1 variant. Using dynamic network modeling of the S Omicron BA.1, BA.2 and BA.2.75 trimers we showed that the key network positions driving long-range signaling are associated with the major stability hotspots that are inter-connected along potential communication pathways, while sites of Omicron mutations may often correspond to weak spots of stability and allostery but are coupled to the major stability hotspots through interaction networks. The presented analysis of the BA.1, BA.2 and BA.2.75 trimers suggested that thermodynamic stability of BA.1 and BA.2.75 variants may be intimately linked with the residue interaction network organization that allows for a broad ensemble of allosteric communications in which signaling between structural stability hotspots may be modulated by the Omicron mutational sites. The findings provided plausible rationale for mechanisms in which Omicron mutations can evolve to balance thermodynamic stability and conformational adaptability in order to ensure proper tradeoff between stability, binding and immune escape.
Aging Atlas Reveals Cell-Type-Specific Regulation of Pro-longevity Strategies
Authors: Gao Shihong Max , Qi Yanyan , Zhang Qinghao , Mohammed Aaron S. , Lee Yi-Tang , Guan Youchen , Li Hongjie , Fu Yusi , Wang Meng C. 
Published: March 2023

AbstractOrganism aging occurs at the multicellular level; however, how pro-longevity mechanisms slow down aging in different cell types remains unclear. We generated single-cell transcriptomic atlases across the lifespan ofCaenorhabditis elegansunder different pro-longevity conditions (http://mengwanglab.org/atlas). We found cell-specific, age-related changes across somatic and germ cell types and developed transcriptomic aging clocks for different tissues. These clocks enabled us to determine tissue-specific aging-slowing effects of different pro-longevity mechanisms, and identify major cell types sensitive to these regulations. Additionally, we provided a systemic view of alternative polyadenylation events in different cell types, as well as their cell-type-specific changes during aging and under different pro-longevity conditions. Together, this study provides molecular insights into how aging occurs in different cell types and how they respond to pro-longevity strategies.
A live-cell platform to isolate phenotypically defined subpopulations for spatial multi-omic profiling
Authors: Khatib Tala O. , Amanso Angelica M. , Pedro Brian , Knippler Christina M. , Summerbell Emily R. , Zohbi Najdat M. , Konen Jessica M. , Mouw Janna K. , Marcus Adam I. 
Published: March 2023

ABSTRACTNumerous techniques have been employed to deconstruct the heterogeneity observed in normal and diseased cellular populations, including single cell RNA sequencing,in situhybridization, and flow cytometry. While these approaches have revolutionized our understanding of heterogeneity, in isolation they cannot correlate phenotypic information within a physiologically relevant live-cell state, with molecular profiles. This inability to integrate a historical live-cell phenotype, such as invasiveness, cell:cell interactions, and changes in spatial positioning, with multi-omic data, creates a gap in understanding cellular heterogeneity. We sought to address this gap by employing lab technologies to design a detailed protocol, termed Spatiotemporal Genomics and Cellular Analysis (SaGA), for the precise imaging-based selection, isolation, and expansion of phenotypically distinct live-cells. We begin with cells stably expressing a photoconvertible fluorescent protein and employ live cell confocal microscopy to photoconvert a user-defined single cell or set of cells displaying a phenotype of interest. The total population is then extracted from its microenvironment, and the optically highlighted cells are isolated using fluorescence activated cell sorting. SaGA-isolated cells can then be subjected to multi-omics analysis or cellular propagation forin vitroorin vivostudies. This protocol can be applied to a variety of conditions, creating protocol flexibility for user-specific research interests. The SaGA technique can be accomplished in one workday by non-specialists and results in a phenotypically defined cellular subpopulation for integration with multi-omics techniques. We envision this approach providing multi-dimensional datasets exploring the relationship between live-cell phenotype and multi-omic heterogeneity within normal and diseased cellular populations.
Integrating metabolic scaling and coexistence theories
Authors: Saavedra Serguei , Arroyo José Ignacio , Deng Jie , Marquet Pablo A. , Kempes Christopher P. 
Published: March 2023

AbstractMetabolic scaling theory has been pivotal in formalizing the expected energy expenditures across populations as a function of body size. Coexistence theory has provided a mathematization of the tolerated effects of environmental perturbations on a given set of interacting populations as a function of interspecific interactions. Yet, it has been challenging to explain how coexistence patterns observed in ecological communities, such as the inverse relationship between population abundance and mean body size, can be unified under both theories. Here, we provide the foundation for a tractable, scalable, and extendable framework to study the coexistence of resource-mediated competing populations as a function of their mean body size. For a fixed thermal domain and response, this integration reveals that the metabolically predicted -3/4 power dependence of carrying capacity on body size specifies the distribution of environmental carrying capacities that tends to maximize the tolerance to random environmental perturbations within large communities. In line with empirical observations, our integration predicts that such a distribution leads to equilibrium biomasses that are independent from body size, and consequently, to equilibrium abundances that are inversely related to body size. This integration opens new opportunities to increase our understanding of how metabolic scaling relationships at the population level can shape processes at the community level.
Impact of in vivo cyclic reprogramming on the choroid plexus
Authors: Lopez Jessica Avila , Abboud Clauda , Ibrahim Maged , Ahumada Javier Rocha , Avino Mariano , Plourde Mélanie , Fernandes Karl , Bentzinger C. Florian , Laurent Benoit 
Published: March 2023

AbstractIn vivo reprogramming using the transient expression of Oct3/4, Sox2, Klf4 and c□Myc (OSKM) transcription factors can be used to induce tissue regeneration. A cyclic regime for short□term OSKM expression has been shown to promote regeneration of several organs however its impact on the brain remains largely unknown. We investigated the effects of a cyclic short-term OSKM expression on the choroid plexus (CP), a highly vascularized tissue found within the brain ventricles which is responsible for producing the cerebrospinal fluid (CSF). Transient reprogramming was done on 8-week-old mice carrying the polycistronic OSKM cassette under tetracycline operator (tetO) and confirmed the successful transient reprogramming. We then performed the analysis of the CP at cellular and molecular levels. The CP tissue exhibited minor morphological changes in height and area of epithelial cells. We did not observe any significant differences in the integrity of the brain-CSF barrier but noticed an increase of NKCC1 expression, a protein involved in CSF production. A whole transcriptome analysis (RNA-seq) was also carried on the tissue and showed no difference in gene expression after the transient reprogramming, at the exception of blood-related genes. Our results indicate that surprisingly the CP mainly remains insensible to in vivo transient reprogramming as only morphological and protein changes were observed in the tissue, suggesting that translational changes might be at stake during the reprogramming process but are not present at the transcriptomic level. Our results also highlight that more tailored strategies need to be developed for exploring the potential of CP reprogramming in regenerative medicine.
Cerebellar Activity in PINK1 Knockout Rats during Volitional Gait
Authors: DeAngelo Valerie , Hilliard Justin D , Chiang Chia-Han , Viventi Jonathan , McConnell George C 
Published: March 2023

AbstractPreclinical models of Parkinson’s disease are imperative to gain insight into the neural circuits that contribute to gait dysfunction in advanced stages of the disease. The PTEN-induced putative kinase 1 (P1) knockout (KO) early onset model of Parkinson’s disease may be a useful rodent model to study the effects of neurotransmitter degeneration caused by loss of P1 function on brain activity during volitional gait. The goal of this study was to measure changes in neural activity at the cerebellar vermis (CBLv) at 8 months of age. Gait deficits, except run speed, were not significantly different from age-matched wild-type (WT) controls as previously reported. P1KO (n=4) and WT (n=4) rats were implanted with a micro-electrocorticographic array placed over CBLv lobules VI (a, b, and c) and VII. Local field potential recordings were obtained during volitional gait across a runway. Power spectral analysis and coherence analysis were used to quantify network oscillatory activity in frequency bands of interest. CBLv power was hypoactive in the beta (VIb, VIc, and VII) and alpha (VII) bands at CBLv lobules VIb, VIc, and VII in P1KO rats compared to WT controls during gait (p<0.05). These results suggest that gait improvement in P1KO rats at 8 months may be a compensatory mechanism attributed to movement corrections caused by decreased inhibition of the alpha band of CBLv lobule VII and beta band of lobules VIb, VIc, and VII. The P1KO model may be a valuable tool for understanding the circuit mechanisms underlying gait dysfunction in early-onset Parkinson’s disease patients with functional loss of P1. Future studies investigating the CBLv as a potential biomarker and therapeutic target for the treatment of gait dysfunction in Parkinson’s disease are warranted.
Personalized Risk Prediction for Cancer Survivors: A Bayesian Semi-parametric Recurrent Event Model with Competing Outcomes
Authors: Nguyen Nam H , Shin Seung Jun , Dodd-Eaton Elissa B , Ning Jing , Wang Wenyi 
Published: March 2023

AbstractMultiple primary cancers are increasingly more frequent due to improved survival of cancer patients. Characteristics of the first primary cancer largely impact the risk of developing subsequent primary cancers. Hence, model-based risk characterization of cancer survivors that captures patient-specific variables is needed for healthcare policy making. We propose a Bayesian semi-parametric framework, where the occurrence processes of the competing cancer types follow independent non-homogeneous Poisson processes and adjust for covariates including the type and age at diagnosis of the first primary. Applying this framework to a historically collected cohort with families presenting a highly enriched history of multiple primary tumors and diverse cancer types, we have derived a suite of age-to-onset penetrance curves for cancer survivors. This includes penetrance estimates for second primary lung cancer, potentially impactful to ongoing cancer screening decisions. Using Receiver Operating Characteristic (ROC) curves, we have validated the good predictive performance of our models in predicting second primary lung cancer, sarcoma, breast cancer, and all other cancers combined, with areas under the curves (AUCs) at 0.89, 0.91, 0.76 and 0.68, respectively. In conclusion, our framework provides covariate-adjusted quantitative risk assessment for cancer survivors, hence moving a step closer to personalized health management for this unique population.
Drug-tolerant persister B-cell precursor acute lymphoblastic leukemia cells
Authors: Zhang Mingfeng , Yang Lu , Chen David , Heisterkamp Nora 
Published: March 2023

AbstractReduced responsiveness of precursor B-acute lymphoblastic leukemia (BCP-ALL) to chemotherapy can be inferred when leukemia cells persist after 28 days of initial treatment. Survival of these long-term persister (LTP) / minimal residual disease (MRD) cells is partly due to bone marrow stromal cells that protect them under conditions of chemotherapy stress. We used RNA-seq to analyse BCP-ALL cells that survived a long-term, 30-day vincristine chemotherapy treatment while in co-culture with bone marrow stromal cells. RNAs of as many as 10% of the protein-encoding genes were differentially expressed. There was substantial overlap with genes associated with MRD cell persistence reported in other studies. The top pathway regulated in the LTP cells was that involving p53, a master regulator of a spectrum of responses relevant to drug resistance and cytotoxic drug exposure including control of autophagy. We tested a select number of genes for contribution to BCP-ALL cell survival using Cas9/CRISPR in a 2-step selection, initially for overall effect on cell fitness, followed by 21 days of exposure to vincristine. Many genes involved in autophagy and lysosomal function were found to contribute to survival both at steady-state and during drug treatment. We also identified MYH9, NCSTN and KIAA2013 as specific genes contributing to fitness of BCP-ALL cells. CD44 was not essential for growth under steady state conditions but was needed for survival of vincristine treatment. Finally, although the drug transporter ABCC1/MRP1 is not overexpressed in BCP-ALL, a functional gene was needed for DTP cells to survive treatment with vincristine. This suggests that addition of possible ABCC1 inhibitors during induction therapy could provide benefit in eradication of minimal residual disease in patients treated with a chemotherapy regimen that includes vincristine.