bluuebunny/crossref_metadata_2025_split huggingface dataset:
Functional memory T cells are derived from exhausted clones and expanded by checkpoint blockade
Authors: Raposo Colin J. , Yan Patrick K. , Chen Andy Y. , Majidi Saba , Hiam-Galvez Kamir J. , Satpathy Ansuman T. 
Published: February 2025

SummaryImmune checkpoint blockade can facilitate tumor clearance by T cells, resulting in long term patient survival. However, the capacity of exhausted CD8+T cells (Tex), present during chronic antigen exposure, to form memory after antigen clearance remains unclear. Here, we performed longitudinal single cell RNA/T cell receptor sequencing and ATAC-sequencing on antigen-specific T cells after the clearance of chronic lymphocytic choriomeningitis virus (LCMV) infection. These data revealed the formation of a robust population of memory CD8+T cells that transcriptionally, epigenetically, and functionally resemble central memory T cells (Tcm) that form after clearance of acute infection. To lineage trace the origin and memory recall response of Tex-derived memory clones, we utilized T cell receptor sequencing over the course of primary infection and rechallenge. We show that chronic Tcm are a clonally distinct lineage of Tex derived from progenitor exhausted cells, persist long-term in the absence of antigen, and undergo rapid clonal expansion during rechallenge. Finally, we demonstrate that αPD-L1 immune checkpoint blockade after chronic LCMV infection preferentially expands clones which form Tcm after clearance. Together, these data support the concept that chronically stimulated T cells formbona fidefunctional memory T cells through an analogous differentiation pathway to acutely stimulated T cells, which may have significant implications for enhancing immune memory to cancer through checkpoint blockade and vaccination.
Neighbor density-dependent facilitation promotes coexistence and internal oscillation
Authors: Buche Lisa , Shoemaker Lauren G. , Hallett Lauren M. , Vesk Peter , Godoy Oscar , Mayfield Margaret 
Published: February 2025

AbstractThe ability of species to form diverse communities is not fully understood. Species are known to interact in various ways with their neighborhood. Despite this, common models of species coexistence assume that per capita interactions are constant and competitive, even as the environment changes. In this study, we investigate how neighbor density-dependent variation in the strength and sign of species interactions changes species and community dynamics. We show that by including these sources of variation, predictions of ecological dynamics are significantly improved compared to outcomes of typical models that hold interaction strengths constant. We compared how well models based on different functions of neighbor density and identity did in describing population trajectories (i.e., persistence over time) and community dynamics (i.e., temporal stability, synchrony and degree of oscillation) in simulated two-species communities and a real diverse annual plant system. In our simulated communities, we found the highest level of coexistence between species pairs when species interactions varied from competitive to facilitative according to neighbor density (i.e., following a sigmoid function). Introducing within-guild facilitation through a nonlinear bounded function allowed populations, both simulated and empirical, to avoid extinction or runaway growth. In fact, nonlinear bounded functions (i.e., exponential and sigmoid functions) predicted population trends over time within the range of abundances observed over the last 10 years. With the sigmoid function, the simulated communities of two species displayed a higher probability of synchrony and oscillation than other functional forms. These simulated communities did not always show temporal stability but were predicted to coexist. Overall, varying species interactions lead to realistic ecological trajectories and community dynamics when bounded by asymptotes based on neighbor density. These findings are important for advancing our understanding of how diverse communities are sustained and for operationalizing ecological theory in the study of the real world.
A phototaxis assay to measure sublethal effects of pesticides on bees
Authors: Sancho Gonzalo , Albacete Sergio , Azpiazu Celeste , Sgolastra Fabio , Rodrigo Anselm , Bosch Jordi 
Published: February 2025

AbstractPesticides are considered a main driver of world-wide bee declines. In agricultural areas, bees are exposed to combinations of pesticides at low concentrations. The extent to which these low levels may cause sublethal effects remains unknown. Laboratory methods to detect sublethal effects are needed as a first step in assessing the potential hazards of pesticides at low concentrations. Current bee risk assessment schemes rely on a single species, the highly socialApis mellifera, and provide insufficient coverage of sublethal effects. Due to fundamental life history differences, available tests cannot be applied to solitary bees. We provide a simple phototaxis assay to detect sublethal pesticide effects on bees. The assay is highly effective (only 6.63% of the bees failed to respond) and provides an unambiguous binary response (bees either walk straight to the light source or walk erratically across the arena). We validate the assay by conducting two experiments. In the first one, we estimate dose-response curves and calculate ED50 and benchmark dose (BMD) values of an insecticide onOsmia bicornisandO. tricornis. In the second one, we assess the effects of three insecticide doses, alone and in combination with a fungicide, inO. cornutaandA. mellifera. These experiments show that our assay can detect effects of field-realistic levels of acetamiprid exposure as low as 1-30 ng/bee. The phototaxis assay can be used to obtain relevant ecotoxicological endpoints at low sublethal concentrations in both solitary and honey bees, thus contributing to fill an important gap in bee risk assessment.
Quantitative Evaluation of Normal Cerebrospinal fluid flow in Sylvian aqueduct and perivascular spaces of middle cerebral artery and circle of Willis using 2D phase -contrast MRI imaging
Authors: D. Le Rosemarie Faustina , Karmonik Christof , Regnier-Golanov Angelique S. , Golanov Eugene V. , Britz Gavin W. 
Published: February 2025

AbstractRecently, it was proposed that CSF flow constitutes a critical part of the glymphatic system, playing a critical role in various brain abnormalities from Alzheimer’s disease to hydrocephalus. Thus, measurement of CSF flow has been increasingly used for diagnostic and clinical monitoring purposes. Phase-contrast MRI has been used to determine CSF flow. However, CSF flow in the periarterial spaces of the circle of Willis and the middle cerebral artery which are important conduits remain unexplored. We employed phase-contrast MRI to explore CSF flow along the perivascular spaces of the circle of Willis and the middle cerebral artery to establish baseline parameters of CSF and compare them with the Sylvian aqueduct. To analyze CSF flow in the perivascular space, we developed a new, semi-automated method for outlining the perivascular space and extracting CSF flow parameters. The twenty-four healthy participants were recruited to achieve an even distribution by age (mean: 40 ± 11) and gender (13 males). We validated our routine for CSF flow measurements by comparing CSF flow in the Sylvian aqueduct (0.00700 mL/s) with the range of literature values, 0.0049-0.0432 mL/s. For all CSF parameters, the circle of Willis and middle cerebral artery were differed from the Sylvian aqueduct. For most CSF flow parameters, the 95% confidence intervals of the circle of Willis and middle cerebral artery overlap. The linear mixed models and general linear mixed models for flow indicate strong effects of the conduits. CSF velocity in these conduits were lower 0.159 cm/s and 0.198 cm/s respectively than in the Sylvian aqueduct. Overall, differences in CSF flow parameters between sex and age groups were negligible. In this study, we have validated our routine and established baseline values of CSF flow along the circle of Willis and the middle cerebral artery as well as highlighted the limited influence of sex and/or age.
The membrane skeleton density of red blood cells inMYH9-related disease patients is decreased
Authors: Sun Shaopeng , Pan Jiabin , Zhang Ning , Jin Xianghong , Zhu Tie-nan , Kang Zhijie , Hao Jihong , Li Xiang-dong 
Published: February 2025

AbstractMYH9-related disease (MYH9-RD) is a rare autosomal dominant disorder caused by mutations inMYH9gene, which encodes the heavy chain of nonmuscle myosin IIA. Nearly allMYH9-RD patients present with macrothrombocytopenia, characterized by decreased platelet count and increased platelet size. In this study, we collected blood samples from threeMYH9-RD patients (R702S, D1424N, and R1464C) and unexpectedly found that the actin levels in the red blood cells (RBCs) from all threeMYH9-RD patients are substantially lower than the healthy controls. We further revealed that the levels of two RBC membrane skeleton proteins, α-spectrin and tropomodulin, are also reduced inMYH9-RD RBCs. We showed that the membrane skeleton ofMYH9-RD RBCs was more porous and thatMYH9-RD RBCs produced more severe deformation under hyperosmotic pressure compared to healthy controls. We conclude thatMYH9-RD mutations reduce the RBC membrane skeleton density and impair its mechanical properties, and propose that defects in the membrane skeleton network in RBCs may be a common symptom inMYH9-RD.Key pointsThe levels of membrane skeleton proteins and the density of membrane skeleton network in RBCs ofMYH9-RD patients are reduced.MYH9-RD RBCs produce greater deformation under hypertonic conditions compared to healthy controls.
Competence of DNA Tetrahedron and Exosomes as Nanocarriers for Epirubicin drug delivery in Breast Cancer Cells
Authors: Saleem Afnan , Bhat Sahar Saleem , Gani Ubaid , Shafi Nausheen , Vaswani Payal , Dar Lateef A , Nazir Junaid , Ahmad Sheikh F , Bhatia Dhiraj , Ahmad Syed Mudasir 
Published: February 2025

AbstractEpirubicin, a chemotherapeutic agent, is used in treatment of metastatic breast cancer treatment. However, poor intracellular delivery and systemic toxicity are its major limitations. Our study evaluates the use of DNA tetrahedron (TD) structures and exosomes for targeted delivery of epirubicin to enhance its therapeutic efficacy. Increased intracellular concentration of epirubicin was observed in Flow cytometer when delivered via the TD: Epi system compared to free epirubicin. Cell viability assays using Annexin V-FITC and propidium iodide staining revealed higher apoptosis rates in the TD: Epi system. Exosomes, primarily 100 ± 20 nm in size (99% of particles), exhibit a - 28.5 mV zeta potential, ensuring colloidal stability. SEM and TEM confirm their spherical shape, uniform size, and double membrane structure. The TD: Epi system showed the highest efficacy in RT-qPCR analysis, followed by Epirubicin + Exosomes systems and epirubicin alone, further corroborated with western blot results. While exosomes also provided improved delivery and therapeutic outcomes compared to free epirubicin, they were less effective than the TD: Epi system. These results suggest that the TD carrier significantly enhances the delivery and apoptotic efficacy of epirubicin when compared to exosome-based delivery or epirubicin alone offering a promising strategy for improving treatment outcomes.Graphical Abstract
ImmunoMatch learns and predicts cognate pairing of heavy and light immunoglobulin chains
Authors: Guo Dongjun , Dunn-Walters Deborah K. , Fraternali Franca , Ng Joseph C. F. 
Published: February 2025

AbstractThe development of stable antibodies formed by compatible heavy (H) and light (L) chain pairs is crucial in both thein vivomaturation of antibody-producing cells and theex vivodesigns of therapeutic antibodies. We present here a novel machine learning framework, ImmunoMatch, for deciphering the molecular rules governing the pairing of antibody chains. Fine-tuned on an antibody-specific language model, ImmunoMatch learns from paired H and L sequences from single human B cells to distinguish cognate H-L pairs and randomly paired sequences. We find that the predictive performance of ImmunoMatch can be augmented by training separate models on the two types of antibody L chains in humans,κandλ, in line with thein vivomechanism of B cell development in the bone marrow. Using ImmunoMatch, we illustrate that refinement of H-L chain pairing is a hallmark of B cell maturation in both healthy and disease conditions. We find further that ImmunoMatch is sensitive to sequence differences at the H-L interface. ImmunoMatch focusses on H-L chain pairing as a specific, under-explored problem in antibody developability, and facilitates the computational assessment and modelling of stably assembled immunoglobulins towards large-scale optimisation of efficacious antibody therapeutics.
Single Cell Resolution Tracking of Cutaneous T-Cell Lymphoma Reveals Clonal Evolution in Disease Progression
Authors: Dorando Hannah K. , Andrews Jared M. , Borcherding Nicholas C. , Quinn Chaz C. , Schmidt Jennifer A. , Khatavkar Oam U. , Aluri Jahnavi , Harmon Michael T. , Watkins Marcus P. , Frank Anastasia , Cooper Megan A. , Musiek Amy C. , Mehta-Shah Neha , Payton Jacqueline E. 
Published: February 2025

ABSTRACTCutaneous T-cell lymphoma (CTCL) remains a challenging disease due to its significant heterogeneity, therapy resistance, and relentless progression. Multi-omics technologies offer the potential to provide uniquely precise views of disease progression and response to therapy. We present here a comprehensive multi-omics view of CTCL clonal evolution, incorporating exome, whole genome, epigenome, bulk-, single cell (sc) VDJ-, and scRNA-sequencing of 114 clinically annotated serial skin, peripheral blood, and lymph node samples from 35 CTCL patients. We leveraged this extensive dataset to define the molecular underpinnings of CTCL progression in individual patients at single cell resolution with the goal of identifying clinically useful biomarkers and therapeutic targets. Our studies identified a large number of recurrent progression-associated clonal genomic alterations; we highlight mutation of CCR4, PI3K signaling, and PD-1 checkpoint pathways as evasion tactics deployed by malignant T cells. We also identified a gain of function mutation in STAT3 (D661Y) and demonstrated by CUT&RUN-seq that it enhances binding to transcription start sites of genes in Rho GTPase pathways, which we previously reported to have activated chromatin and increased expression in HDACi-resistant CTCL. These data provide further support for a previously unrecognized role for Rho GTPase pathway dysregulation in CTCL progression. A striking number of progression-associated mutations occurred in chromatin methylation modifiers, including EZH2, suggesting that EZH1/2 inhibition may also benefit patients with CTCL. Knowledge of these molecular changes should be leveraged for improved disease monitoring, biomarker-informed clinical trial design, and new therapeutic strategies in this challenging and incurable cancer.
Pedigree-based genome-wide imputation using a low-density amplicon panel for the highly polymorphic Pacific oysterCrassostrea(Magallana)gigas
Authors: Sutherland Ben J. G. , Divilov Konstantin , Thompson Neil F. , Delomas Thomas A. , Lunda Spencer L. , Langdon Christopher J. , Green Timothy J. 
Published: February 2025

AbstractHigh-density genomic data are instrumental for selective breeding, but the high costs associated with these approaches can hinder progress, as is the case for most aquaculture species. A strategy to reduce genotyping costs is to genotype a few select animals at high-density (e.g., parents, grandparents), and large numbers of other animals at low density (e.g., offspring), then impute genotypes. This has been demonstratedin silicofor Pacific oysterCrassostrea(Magallana)gigasbut was particularly challenging relative to other species and has never been empirically tested. Here, four families of Pacific oysters, bred via marker-assisted selection for variation at a locus for ostreid herpesvirus 1 (OsHV-1) survivorship, were exposed to OsHV-1 then genotyped using a low-density amplicon panel (n = 240). Parents were genotyped with the amplicon panel and whole-genome resequencing data. Offspring genotypes were imputed, and accuracy was characterized against a hold-out dataset. Imputation reduced minor allele frequencies and enriched homozygosity. Anin silicothree-generation analysis was used to investigate the effect of deepening the pedigree, which generated superior results (genotype concordance = 84.5%, allelic dosage r = 0.73), although the two-generation imputation is likely sufficient for selection decisions (GC = 75.3%; r = 0.63). Genome-wide associations to OsHV-1 survivorship with imputed data identified major effect loci on the expected chromosome 8, but in a different region than expected, pointing to a potentially more complex genetic architecture for the trait. These methods demonstrate the empirical utility of amplicon panel-based genome-wide imputation in shellfish, and thus enable low-cost selective breeding techniques.
Clonal Heterogeneity in Human Pancreatic Ductal Adenocarcinoma and Its Impact on Tumor Progression
Authors: Kalfakakou Despoina , Cameron Daniel C. , Kawaler Emily A. , Tsuda Motoyuki , Wang Lidong , Jing Xiaohong , Hajdu Cristina , Tamayo Dylan L. , Shim Yoona , Ackermann Amanda , Weissinger Daniel , Zimny Hayley , Hernandez Rosmel , Beier Matthew , Dimartino Dacia , Meyn Peter , Rice Kalina , Selvaraj Shanmugapriya , Loomis Cynthia , Heguy Adriana , Lund Amanda W. , Sears Rosalie C. , Welling Theodore H. , Dolgalev Igor , Tsirigos Aristotelis , Simeone Diane M. 
Published: February 2025

ABSTRACTPancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer characterized by profound desmoplasia and cellular heterogeneity, which cannot be fully resolved using traditional bulk sequencing approaches. To understand the contribution of this heterogeneity to PDAC biology, we analyzed a large cohort of primary human PDAC samples (n = 62), profiling 443,451 single cells and 53,236 spatial transcriptomic spots using a combined single-cell RNA sequencing and spatial transcriptomics approach. Our analysis revealed significant intratumoral heterogeneity, with multiple genetically distinct neoplastic clones co-existing within individual tumors. These clones exhibited diverse transcriptional states and subtype profiles, challenging the traditional binary classification of PDAC into basal and classical subtypes; instead, our findings support a transcriptional continuum influenced by clonal evolution and spatial organization. Additionally, these clones each interacted uniquely with surrounding cell types in the tumor microenvironment. Phylogenetic analysis uncovered a rare but consistent classical-to-basal clonal transition associated withMYCamplification and immune response depletion, which were validated experimentally, suggesting a mechanism driving the emergence of a more aggressive basal clonal phenotype. Spatial analyses further revealed dispersed clones enriched for epithelial-to-mesenchymal transition (EMT) activity and immune suppression, correlating with metastatic potential and colonization of lymph node niches. These dispersed clones tended to transition toward a basal phenotype, contributing to disease progression. Our findings highlight the critical role of clonal diversity, transcriptional plasticity, and TME interactions in shaping human PDAC biology. This work provides new insights into the molecular and spatial heterogeneity of PDAC and offers potential avenues for therapeutic intervention targeting clonal evolution and the mechanisms driving metastasis.
Stem Cell-Parenchymal Fusion: Communication and Gene Regulation
Authors: Huang JoAnne , Nazaryabrbekoh Fateme , Kim Joohyun , Jung Jangwook P. 
Published: February 2025

AbstractWe investigated the cellular and molecular consequences of accidental cell fusion between mHL1 and mMSC cell lines using previously published single-cell RNA sequencing (scRNA-seq) data. We characterized the resulting cell types, their communication patterns, and underlying gene regulatory networks. Initial analyses identified four distinct cell types (mHL1, mHL1 fusion, mMSC, and mMSC fusion), which were also consolidated into three clusters via unsupervised learning. Differential gene expression analysis revealed diverse cell type associations with shared and exclusive gene expression. Single-cell compatible weighted gene co-expression network analysis (WGCNA) linked specific gene modules to distinct cell types and associated biological processes, including muscle contraction and metabolism in mHL1/mHL1 fusion, and extracellular matrix (ECM) formation and lipid metabolism in mMSC fusion. Cell-cell communication analysis revealed distinct intercellular communication patterns, with mMSC primarily acting as a ligand and mHL1 as both ligand and receptor. Reducing cell type complexity progressively simplified communication networks and altered pathway enrichment, while ECM-receptor pathways remained largely unchanged, with only minor shifts in ligand-receptor pairs. Interestingly, removing parental cells from the analysis altered cell type assignments, underscoring the influence of parental cell presence on fusion outcomes. Finally, gene regulatory network analysis identified key transcription factors (TFs) driving cell identity, distinguishing between master regulators and TFs with high cell-type specificity. These findings demonstrate the power of integrating multiple inter- and intra-cellular communication analysis approaches to dissect the complex interplay between cell type, communication, and gene regulation in cell fusion.
Germline and somatic variation influence nuclear-mitochondrial crosstalk in tumourigenesis
Authors: Daunesse Maëlle , Sundaram Vasavi , Kentepozidou Elissavet , Connelly John , Anderson Craig J. ,   Liver Cancer Evolution Consortium, López-Bigas Núria , Semple Colin A. , Odom Duncan T. , Taylor Martin S. , Roller Maša , Aitken Sarah J. , Flicek Paul 
Published: February 2025

AbstractHepatocellular carcinoma is the most prevalent primary liver cancer and arises from hepatocytes, which are very metabolically active and contain abundant mitochondria. Despite extensive characterisation of nuclear driver genes and pathways, the role of crosstalk between the mitochondrial and nuclear genomes in mitochondrial mutagenesis remains poorly understood. To address this, we leveraged a chemical carcinogenesis model of liver cancer in four mouse strains. We analysed hundreds of tumours with paired whole-genome sequencing and total RNA sequencing to comprehensively characterise mitochondrial mutations and expression. Followingde novoassembly of three new mitochondrial genomes, we devised an accurate and efficient heteroplasmy detection approach and analysed mitochondrial DNA (mtDNA) content and transcription. Across strains, there was high concordance of the number of heteroplasmies, mutation signatures, and variant allele frequencies. In contrast, the heteroplasmy rate and genic locations differed between strains, suggesting strain-specificity in DNA repair mechanisms in early tumour development. Independent of age or environmental factors, tumours had lower mtDNA content than adjacent normal liver, suggesting mitochondrial loss during tumourigenesis. Additionally, within individual strains, mtDNA content differences were associated with nuclear driver gene choice. Our comprehensive characterisation of mitochondrial genomes and expression patterns demonstrates that both germline and somatic genetic variation influence tumour mtDNA content, mutation patterns, and gene expression.