bluuebunny/crossref_metadata_2025_split huggingface dataset:
Projecting the potential impact of an Omicron XBB.1.5 wave in Shanghai, China
Authors: Liu Hengcong , Xu Xiangyanyu , Deng Xiaowei , Hu Zexin , Sun Ruijia , Zou Junyi , Dong Jiayi , Wu Qianhui , Chen Xinhua , Yi Lan , Cai Jun , Zhang Juanjuan , Ajelli Marco , Yu Hongjie 
Published: May 2023

AbstractChina experienced a major nationwide wave of SARS-CoV-2 infections in December 2022, immediately after lifting strict interventions, despite the majority of the population having already received inactivated COVID-19 vaccines. Due to the rapid waning of protection and the emergence of Omicron XBB.1.5, the risk of another COVID-19 wave remains high. It is still unclear whether the health care system will be able to manage the demand during this potential XBB.1.5 wave and if the number of associated deaths can be reduced to a level comparable to that of seasonal influenza. Thus, we developed a mathematical model of XBB.1.5 transmission using Shanghai as a case study. We found that a potential XBB.1.5 wave is less likely to overwhelm the health care system and would result in a death toll comparable to that of seasonal influenza, albeit still larger, especially among elderly individuals. Our analyses show that a combination of vaccines and antiviral drugs can effectively mitigate an XBB.1.5 epidemic, with a projected number of deaths of 2.08 per 10,000 individuals.This figure corresponds to a 70–80% decrease compared to the previous Omicron wave and is comparable to the level of seasonal influenza. The peak prevalence of hospital admissions and ICU admissions are projected at 28.89 and 2.28 per 10,000 individuals, respectively, suggesting the need for a moderate increase in the capacity of the health care system. Our findings emphasize the importance of improving vaccination coverage, particularly among the older population, and the use of antiviral treatments.
Ability to detect fake news predicts sub-national variation in COVID-19 vaccine uptake across the UK
Authors: Loomba Sahil , Maertens Rakoen , Roozenbeek Jon , Götz Friedrich M. , van der Linden Sander , de Figueiredo Alexandre 
Published: May 2023

AbstractSusceptibility to believing false or misleading information is associated with a range of adverse outcomes. However, it is notoriously difficult to study the link between susceptibility to misinformation and consequential real-world behaviors such as vaccine uptake. In this preregistered study, we devise a large-scale socio-spatial model that combines the rigor of a psychometrically validated test of misinformation susceptibility administered to a nationally representative sample of 16,477 individuals with COVID-19 vaccine uptake data of 129 sub-national regions published by the United Kingdom (UK) government, to show that the general ability to detect misinformation strongly and positively predicts regional vaccine uptake in the UK. We put this practically significant correlational effect size into perspective by noting how psychological interventions that reduce individuals’ misinformation susceptibility could be associated with additional vaccine uptake.
Polygenic Risk Associated with Alzheimer’s Disease and Other Traits Influences Genes Involved in T Cell Signaling and Activation
Authors: Dressman Dallin , Tasaki Shinya , Yu Lei , Schneider Julie , Bennett David A. , Elyaman Wassim , Vardarajan Badri 
Published: May 2023

AbstractT cells, members of the adaptive immune system known for their ability to respond to an enormous variety of pathogens and other insults, are increasingly recognized as important mediators of pathology in neurodegeneration and other diseases. Previously, we and others have shown that T cell gene expression phenotypes are regulated by genetic variants associated with autoimmune disease, neurodegenerative disease, and inflammatory processes. However, many complex diseases have polygenic risk with thousands of common variants contributing a small amount to disease heritability. Here, we compute the polygenic risk score (PRS) of several autoimmune, neurological, and psychiatric disorders and present the first correlation of these PRSs with T cell gene expression, using transcriptomic and genomic sequencing data from a cohort of Alzheimer’s disease (AD) patients and age-matched controls. We validate our AD PRS against clinical metrics in our cohort and then compare PRS-associated genes across traits and four T cell subtypes. Several genes and biological pathways associated with the PRS for these traits relate to functions such as T cell chemotaxis, differentiation, response to and production of cytokines, and regulation of T cell receptor signaling. We also found that the trait-associated gene expression signature for certain traits was polarized towards a particular T cell subset, such as CD4+ for autoimmune disease traits or CD8+ for some psychiatric disease traits. Our findings may help guide efforts in precision medicine to target specific T cell functions in individuals with high polygenic risk for various complex diseases.
Custom-engineered hydrogels for delivery of human iPSC-derived neurons into the injured cervical spinal cord
Authors: Doulames V.M. , Marquardt L.M. , Hefferon M.E. , Baugh N. , Suhar R.A. , Wang A.T. , Dubbin K. , Weimann J.M. , Palmer T.D. , Plant G.W. , Heilshorn S.C. 
Published: May 2023

AbstractCervical damage is the most prevalent type of spinal cord injury clinically, although few preclinical research studies focus on this anatomical region of injury. Here we present a combinatorial therapy composed of a custom-engineered, injectable hydrogel and human induced pluripotent stem cell (iPSC)-derived deep cortical neurons. The biomimetic hydrogel has a modular design that includes a protein-engineered component to allow customization of the cell-adhesive peptide sequence and a synthetic polymer component to allow customization of the gel mechanical properties.In vitrostudies with encapsulated iPSC-neurons were used to select a bespoke hydrogel formulation that maintains cell viability and promotes neurite extension. Following injection into the injured cervical spinal cord in a rat contusion model, the hydrogel biodegraded over six weeks without causing any adverse reaction. Compared to cell delivery using saline, the hydrogel significantly improved the reproducibility of cell transplantation and integration into the host tissue. Across three metrics of animal behavior, this combinatorial therapy significantly improved sensorimotor function by six weeks post transplantation. Taken together, these findings demonstrate that design of a combinatorial therapy that includes a gel customized for a specific fate-restricted cell type can induce regeneration in the injured cervical spinal cord.
An Interpretable Bayesian Clustering Approach with Feature Selection for Analyzing Spatially Resolved Transcriptomics Data
Authors: Li Huimin , Jiang Xi , Guo Lei , Xie Yang , Xu Lin , Li Qiwei 
Published: May 2023

SummaryRecent breakthroughs in spatially resolved transcriptomics (SRT) technologies have enabled comprehensive molecular characterization at the spot or cellular level while preserving spatial information. Cells are the fundamental building blocks of tissues, organized into distinct yet connected components. Although many non-spatial and spatial clustering approaches have been used to partition the entire region into mutually exclusive spatial domains based on the SRT high-dimensional molecular profile, most require an ad-hoc selection of less interpretable dimensional-reduction techniques. To overcome this challenge, we propose a zero-inflated negative binomial mixture model to cluster spots or cells based on their molecular profiles. To increase interpretability, we employ a feature selection mechanism to provide a low-dimensional summary of the SRT molecular profile in terms of discriminating genes that shed light on the clustering result. We further incorporate the SRT geospatial profileviaa Markov random field prior. We demonstrate how this joint modeling strategy improves clustering accuracy, compared with alternative state-of-the-art approaches, through simulation studies and two real data applications.
Primary nasal viral infection rewires the tissue-scale memory response
Authors: Kazer Samuel W. , Match Colette Matysiak , Langan Erica M. , Messou Marie-Angèle , LaSalle Thomas J. , O’Leary Elise , Marbourg Jessica , Naughton Katherine , von Andrian Ulrich H. , Ordovas-Montanes Jose 
Published: May 2023

ABSTRACTThe nasal mucosa is frequently the initial site of respiratory viral infection, replication, and transmission. Recent work has started to clarify the independent responses of epithelial, myeloid, and lymphoid cells to viral infection in the nasal mucosa, but their spatiotemporal coordination and relative contributions remain unclear. Furthermore, understanding whether and how primary infection shapes tissue-scale memory responses to secondary challenge is critical for the rational design of nasal-targeting therapeutics and vaccines. Here, we generated a single-cell RNA-sequencing (scRNA-seq) atlas of the murine nasal mucosa sampling three distinct regions before and during primary and secondary influenza infection. Primary infection was largely restricted to respiratory mucosa and induced stepwise changes in cell type, subset, and state composition over time. Type I Interferon (IFN)-responsive neutrophils appeared 2 days post infection (dpi) and preceded transient IFN-responsive/cycling epithelial cell responses 5 dpi, which coincided with broader antiviral monocyte and NK cell accumulation. By 8 dpi, monocyte-derived macrophages (MDMs) expressingCxcl9andCxcl16arose alongside effector cytotoxic CD8 andIfng-expressing CD4 T cells. Following viral clearance (14 dpi), rare, previously undescribedKrt13+nasalimmune-interactingfloorepithelial (KNIIFE) cells expressing multiple genes with immune communication potential increased concurrently with tissue-resident memory T (TRM)-like cells and early IgG+/IgA+ plasmablasts. Proportionality analysis coupled with cell-cell communication inference, alongside validation by in situ microscopy, underscored the CXCL16–CXCR6 signaling axis between MDMs and effector CD8 T cells 8dpi and KNIIFE cells and TRM cells 14 dpi. Secondary influenza challenge with a homologous or heterologous strain administered 60 dpi induced an accelerated and coordinated myeloid and lymphoid response without epithelial proliferation, illustrating how tissue-scale memory to natural infection engages both myeloid and lymphoid cells to reduce epithelial regenerative burden. Together, this atlas serves as a reference for viral infection in the upper respiratory tract and highlights the efficacy of local coordinated memory responses upon rechallenge.
Mitosis sets nuclear homeostasis of cancer cells under confinement
Authors: Mouelhi Malèke , Saffon Alexis , Roinard Morgane , Delanoë-Ayari Hélène , Monnier Sylvain , Rivière Charlotte 
Published: May 2023

AbstractDuring their life, mammalian cells are subjected to numerous mechanical constraints, especially in pathological contexts such as cancer. Recent studies have highlighted the central role of the nucleus in sensing mechanical cues, but they only focus on short periods of time, and so far, whether cells can adapt to prolonged confinement remains unknown. Here, we reveal the unsuspected role of mitosis in the long-term adaptation of nuclei to prolonged uniaxial confinement. For the colorectal cancer cell line investigated, following the first confined cell division, a new homeostatic state was reached by nuclei: they were smaller, and had reset the tension of their envelope. This adaptation through mitosis relied both on the nuclear tension sensor cPLA2 and the contractility machinery. We report for the first time a mechano-adaptation during mitosis, a process that could be crucial to adapt to stresses in the tumor microenvironment. We therefore anticipate that our work could provide new insight into cancer cell plasticity and cancer relapse.Significance StatementMost cell types undergo significant deformation throughout their life cycles. Immune cells must deform to navigate through dense matrices, while cancer cells in solid tumors experience squeezing from neighboring cells. The nucleus, central for many cell function, is the stiffest and largest organelle. Understanding its long-term response to spatial constraints is hence crucial yet largely unexplored.In this study, we investigate how a colorectal cancer cell line adapts to prolonged confined environments, with a particular focus on nuclear dynamics under continuous squeezing.Our groundbreaking findings reveal for the first time a mechano-adaptation during mitosis leading to a decrease in nuclear size.This research contributes to the fundamental understanding of cellular mechanosensing, opening new avenues for cancer biology research.
EVRC: Reconstruction of chromosome 3D structure models using Error-Vector Resultant algorithm with Clustering coefficient
Authors: Wang Xiao , Li Jie , Gu Wei-Cheng , Ma Bin-Guang 
Published: May 2023

AbstractReconstruction of 3D structure models is of great importance for the study of chromosome function. In this paper, we present a novel reconstruction algorithm, called EVRC, which utilizes co-clustering coefficients and error-vector resultant for chromosome 3D structure reconstruction. To evaluate the effectiveness and accuracy of the EVRC algorithm, we applied it to simulation datasets and real human Hi-C datasets. The results show that the reconstructed structures have high similarity to the original/real structures, indicating the effectiveness and robustness of the EVRC algorithm. Furthermore, we applied the algorithm to the 3D conformation reconstruction of the wild-type and mutantArabidopsis thalianachromosomes and demonstrated the differences in structural characteristics between different chromosomes. We also accurately showed the conformational change in the centromere region of the mutant compared with the wild-type ofArabidopsischromosome 1. Our EVRC algorithm is a valuable software tool for the field of chromatin structure reconstruction, and holds great promise for advancing our understanding on the chromosome functions.
DeSide: A unified deep learning approach for cellular decomposition of bulk tumors based on limited scRNA-seq data
Authors: Xiong Xin , Liu Yerong , Pu Dandan , Yang Zhu , Bi Zedong , Tian Liang , Li Xuefei 
Published: May 2023

AbstractCellular decomposition employing bulk RNA-sequencing (RNA-seq) has been consistently under investigation due to its high fidelity, ease of use, and cost-effectiveness compared to single cell RNA-sequencing (scRNA-seq). However, the intricate nature of the tumor microenvironment, and the significant heterogeneity among patients and cells have made it challenging to precisely evaluate the cellular composition of solid tumors using a unified model. In this work, we developed DeSide, a deep learning and single-cell decomposition method for solid tumors, to estimate proportions of cell types presented in tumor samples. Our new deep neural network (DNN) architecture considers only non-cancerous cells during the training process, indirectly calculating the proportion of cancerous cells. This approach avoids directly handling the often more variable heterogeneity of cancerous cells, and instead leverages scRNA-seq data from three different cancer types to empower the DNN model with a robust generalization capability across diverse cancers. Additionally, we used a new sampling method and filtering strategies to simulate the gene expression profiles (GEPs) of solid tumors, creating a carefully controlled training set that could be compared to the bulk RNA-seq data from The Cancer Genome Atlas (TCGA), a database of bulk RNA-seq data collected from cancer patients. Relying on limited yet diverse scRNA-seq data, our approach outperformed current methods in accurately predicting the celluar composition of samples from TCGA and an additional validation set. Furthermore, we demonstrated that the predicted cellular composition can be utilized to stratify cancer patients into different groups with varying overall survival rates. With increased availability of scRNA-seq data for various types of tumors, DeSide holds the potential for a more precise cellular decomposition model using bulk RNA-seq.
NRF2 activation in the heart induces glucose metabolic reprogramming and mediates cardioprotection via upregulation of the pentose phosphate pathway
Authors: Zoccarato Anna , Smyrnias Ioannis , Reumiller Christina M , Hafstad Anne D , Chong Mei , Richards Daniel A , Santos Celio XC , Visnagri Asjad , Bromage Daniel I , Zhang Xiaohong , Sawyer Greta , Thompson Richard , Shah Ajay M 
Published: May 2023

AbstractRationaleThe transcription factor NRF2 is well recognized as a master regulator of antioxidant responses and cytoprotective genes. Previous studies showed that NRF2 protects mouse hearts during chronic hemodynamic overload at least in part by reducing oxidative stress. Evidence from other tissues suggests that NRF2 may modulate glucose intermediary metabolism but whether NRF2 has such effects in the heart is unclear.ObjectiveTo investigate the role of NRF2 in regulating glucose intermediary metabolism and cardiac function during disease stress.Methods and ResultsCardiomyocyte-specific Keap1 knockout (csKeap1KO) mice, deficient in the endogenous inhibitor of NRF2, were used as a novel model of constitutively active NRF2 signaling. Targeted metabolomics and isotopomer analysis were employed in studies with13C6-glucose in csKeap1KO and wild-type (WT) mice. Pharmacological and genetic approaches were utilized in neonatal rat ventricular cardiomyocytes (NRVM) to explore molecular mechanisms. We found that cardiac-specific activation of NRF2 upregulated key enzymes of the Pentose Phosphate Pathway (PPP), redirected glucose metabolism towards the PPP and protected the heart against pressure overload-induced cardiac dysfunction.In vitro, knockdown of Keap1 upregulated PPP enzymes and reduced cell death in NRVM subjected to chronic neurohumoral stimulation. These pro-survival effects were abolished by pharmacological inhibition of the PPP or silencing of the PPP rate-limiting enzyme glucose-6-phosphate dehydrogenase (G6PD). Knockdown of NRF2 in NRVM increased stress-induced DNA damage which was rescued by supplementing the cells with either NADPH or nucleosides, the two main products of the PPP. Activation of NRF2 also protected the heart against myocardial infarction-induced DNA damage, dysfunction, and adverse remodeling.ConclusionsThese results indicate that NRF2 regulates cardiac metabolic reprogramming by stimulating the diversion of glucose into the PPP, thereby providing cardiac protection during stress by generating NADPH and providing nucleotides to prevent stress-induced DNA damage.
Phototaxis is a state-dependent behavioral sequence inHydra vulgaris
Authors: Kim Soonyoung , Robinson Jacob T. 
Published: May 2023

AbstractUnderstanding how internal states like satiety are connected to animal behavior is a fundamental question in neuroscience.Hydra vulgaris, a freshwater cnidarian with only eleven neuronal cell types, serves as a tractable model system for studying state-dependent behaviors. We find that starvedHydraconsistently moves toward light, while fedHydrado not. By modeling this behavior as a set of three sequences - head orientation, jump distance, and jump rate -we demonstrate that the satiety state only affects the rate of the animal jumping to a new position, while the orientation and jump distance are unaffected. These findings yield insights into how internal states in a simple organism,Hydra, affect specific elements of a behavior, and offer general principles for studying the relationship between state-dependent behaviors and their underlying molecular mechanisms.
Resolving the unsolved: Comprehensive assessment of tandem repeats at scale
Authors: Dolzhenko Egor , English Adam , Dashnow Harriet , De Sena Brandine Guilherme , Mokveld Tom , Rowell William J. , Karniski Caitlin , Kronenberg Zev , Danzi Matt C. , Cheung Warren , Bi Chengpeng , Farrow Emily , Wenger Aaron , Martínez-Cerdeño Verónica , Bartley Trevor D , Jin Peng , Nelson David , Zuchner Stephan , Pastinen Tomi , Quinlan Aaron R. , Sedlazeck Fritz J. , Eberle Michael A 
Published: May 2023

AbstractTandem repeat (TR) variation is associated with gene expression changes and over 50 rare monogenic diseases. Recent advances in sequencing have enabled accurate, long reads that can characterize the full-length sequence and methylation profile of TRs. However, despite these advances in sequencing technology, computational methods to fully profile tandem repeats across the genome do not exist. To address this gap, we introduce tools for tandem repeat genotyping (TRGT), visualization and an accompanying TR database. TRGT accurately resolves the length and sequence composition of TR regions in the human genome. Assessing 937,122 TRs, TRGT showed a Mendelian concordance of 99.56%, allowing a single repeat unit difference. In six samples with known repeat expansions, TRGT detected all repeat expansions while also identifying methylation signals, mosaicism, and providing finer resolution of repeat length. Additionally, we release a database with allele sequences and methylation levels for 937,122 TRs across 100 genomes.
Spatial connectivity increases ecosystem resilience towards an ongoing regime shift
Authors: Olin Agnes B. , Bergström Ulf , Bodin Örjan , Sundblad Göran , Eriksson Britas Klemens , Erlandsson Mårten , Fredriksson Ronny , Eklöf Johan S. 
Published: May 2023

AbstractEcosystem regime shifts can have severe ecological and economic consequences, making it a top priority to understand how to make systems more resilient. Theory predicts that spatial connectivity and the local environment interact to shape resilience, but empirical studies are scarce. Here, we use >7000 fish samplings from the Baltic Sea coast to test this prediction in an ongoing, spatially propagating shift in dominance from predatory fish to an opportunistic mesopredator, with cascading effects throughout the food web. After controlling for the influence of the driver (increasing mesopredator densities), we find that predatory fish habitat connectivity increases resilience towards the shift, but only when densities of fish-eating top predators (seals, cormorants) are low. Resilience also increases with temperature, likely through boosted predatory fish growth and recruitment. These findings confirm theoretical predictions that spatial connectivity and the local environment can act together to shape resilience towards regime shifts.