bluuebunny/crossref_metadata_2025_split huggingface dataset:
Disruption of Circadian Clock Induces Abnormal Mammary Morphology and Aggressive Basal Tumorigenesis by Enhancing LILRB4 Signaling
Authors: Ogunlusi Olajumoke , Sarkar Mrinmoy , Chakrabarti Arhit , Boland Devon J , Nguyen Tristan , Sampson James , Nguyen Christian , Fails Danielle , Jones-Hall Yava , Fu Loning , Mallick Bani , Keene Alex , Jones Jeff , Sarkar Tapasree Roy 
Published: March 2024

AbstractEpidemiological studies have shown that circadian rhythm disruption (CRD) is associated with the risk of breast cancer. However, the role of CRD in mammary gland morphology and aggressive basal mammary tumorigenesis and the molecular mechanisms underlying CRD and cancer risk remain unknown. To investigate the effect of CRD on aggressive tumorigenesis, a genetically engineered mouse model that recapitulates the human basal type of breast cancer was used for this study. The effect of CRD on mammary gland morphology was investigated using wild-type mice model. The impact of CRD on the tumor microenvironment was investigated using the tumors from LD12:12 and CRD mice via scRNA seq. ScRNA seq was substantiated by multiplexing immunostaining, flow cytometry, and realtime PCR. The effect of LILRB4 immunotherapy on CRD-induced tumorigenesis was also investigated. Here we identified the impact of CRD on basal tumorigenesis and mammary gland morphology and identified the role of LILRB4 on CRD-induced lung metastasis. We found that chronic CRD disrupted mouse mammary gland morphology and increased tumor burden, and lung metastasis and induced an immunosuppressive tumor microenvironment by enhancing LILRB4a expression. Moreover, CRD increased the M2-macrophage and regulatory T-cell populations but decreased the M1-macrophage, and dendritic cell populations. Furthermore, targeted immunotherapy against LILRB4 reduced CRD-induced immunosuppressive microenvironment and lung metastasis. These findings identify and implicate LILRB4a as a link between CRD and aggressive mammary tumorigenesis. This study also establishes the potential role of the targeted LILRB4a immunotherapy as an inhibitor of CRD-induced lung metastasis.
Forage conservation is a neglected nitrous oxide source
Authors: Yang Seongmin , Mahmood Maheen , Baral Rudra , Wu Hui , Almloff Marc , Stanton Lauren E. , Min Doohong , Smiley Brenda K. , Iiams J. Chris , Yu Jisang , Im Jeongdae 
Published: March 2024

Agricultural activities are the major anthropogenic source of nitrous oxide (N2O), an important greenhouse gas and ozone-depleting substance. However, the role of forage conservation as a potential source of N2O has rarely been studied. We investigated N2O production from the simulated silage of the three major crops—maize, alfalfa, and sorghum—used for silage in the US, which comprises over 90% of the total silage production. Our findings revealed a substantial N2O could be generated, which potentially places forage conservation as the third largest N2O source in the agricultural sector. Notably, the application of chlorate as an additive significantly reduced N2O production, but neither acetylene nor intermittent exposure to oxygen showed any impact. Overall, the results highlight that denitrifiers, rather than nitrifiers, are responsible for N2O production from silage, which was confirmed by molecular analyses. Our study reveals a previously unexplored source of N2O and provides a crucial mechanistic understanding for effective mitigation strategies.Significance StatementN2O is the third most important greenhouse gas (GHG) and agriculture contributes 80% of the total anthropogenic emissions in the US. The major sources of N2O in the agricultural sector identified by the USEPA include agricultural land management, manure management, and the field burning of agricultural residues. Here, we show that forage conservation could be a significant unaccounted source of N2O, surpassing the field burning by 30. Our study provides a mechanistic understanding of N2O production and a simple and effective remedy for reducing N2O emissions. The findings have substantial implications for mitigating climate change, informing policy-makers, and guiding future research on reducing greenhouse gas emissions from livestock production.
Mapping single-cell developmental potential in health and disease with interpretable deep learning
Authors: Kang Minji , Armenteros Jose Juan Almagro , Gulati Gunsagar S. , Gleyzer Rachel , Avagyan Susanna , Brown Erin L. , Zhang Wubing , Usmani Abul , Earland Noah , Wu Zhenqin , Zou James , Fields Ryan C. , Chen David Y. , Chaudhuri Aadel A. , Newman Aaron M. 
Published: March 2024

AbstractSingle-cell RNA sequencing (scRNA-seq) has transformed our understanding of cell fate in developmental systems. However, identifying the molecular hallmarks of potency – the capacity of a cell to differentiate into other cell types – has remained challenging. Here, we introduce CytoTRACE 2, an interpretable deep learning framework for characterizing potency and differentiation states on an absolute scale from scRNA-seq data. Across 31 human and mouse scRNA-seq datasets encompassing 28 tissue types, CytoTRACE 2 outperformed existing methods for recovering experimentally determined potency levels and differentiation states covering the entire range of cellular ontogeny. Moreover, it reconstructed the temporal hierarchy of mouse embryogenesis across 62 timepoints; identified pan-tissue expression programs that discriminate major potency levels; and facilitated discovery of cellular phenotypes in cancer linked to survival and immunotherapy resistance. Our results illuminate a fundamental feature of cell biology and provide a broadly applicable platform for delineating single-cell differentiation landscapes in health and disease.
When spatial attention cannot be divided: Quadrantic enhancement of early visual processing across task–relevant and irrelevant locations
Authors: Özkan Mert , Störmer Viola 
Published: March 2024

AbstractSpatial attention enables us to select regions of space and prioritize visual processing at the attended locations. Previous research has shown that spatial attention can be flexibly tuned to broader or narrower regions in space, and in some cases be split amongst multiple locations. Here, we investigate how attentional resources are distributed within a visual quadrant when participants are instructed to either focus attention narrowly, broadly, or split attention among two non-contiguous locations. Using a combination of behavior and steady-state visual-evoked potentials (SSVEP), the oscillatory response of the visual cortex to incoming flickering stimuli, we find clear evidence for ineffective splitting of spatial attention within a visual quadrant. Importantly, by assessing visual-cortical processing across locations at a high spatial resolution (by flickering nearby locations at distinct frequencies), our results reveal that attention was distributed in the exact same manner regardless of whether participants were instructed to attend broadly across a large region of space, or divide attention amongst two non-contiguous locations: In both cases, the intermediate location showed the strongest boost in visual-cortical processing, no matter whether it was the center of the attended region (broad-focus condition), or the uncued, to-be-ignored location (split-focus condition). Thus, the present study provides strong evidence that when trying to attend to multiple separate locations within a visual quadrant, sustained attention inadvertently enhances visual processing at the intermediate location even when it is detrimental to task performance.
Evidence for the key roles of thePseudomonas syringaemobilome in shaping biotic interactions
Authors: Holtappels D. , Rickus G.E.J. , Morgan T. , de Rezende R. R. , Koskella B. , Alfenas-Zerbini P. 
Published: March 2024

AbstractThe mobilome, defined as the collection of mobile genetic elements within a bacterial genome, plays a critical role in the adaptation of bacteria to abiotic and biotic drivers. In particular, prophages have been reported to contribute to bacterial resistance to virulent bacteriophages, the competitive interaction of bacterial hosts within microbial communities, and in pathogenicity and virulence. It is therefore critical to better understand the role of prophages in distributing genes and functions within and among bacterial species to predict how bacteria adapt to their biotic environment.Pseudomonas syringaeoffers an ideal study system to ask these questions both because of its broad range of lifestyles (spanning from environmental growth to plant pathogens) and its high intraspecies diversity. To examine the role of the mobilome in this species complex, we compared 590 genomes available from public databases and annotated the defense mechanisms, effectors, and prophages in the genomes. We found that this species complex has an elaborate phage pandefensome consisting of 139 defense mechanisms. Host-associatedP. syringaeisolates were found to have both elaborate phage defensomes and effectoromes. Assessing taxonomical signatures of the observed prophages uncovered broad differences in the types and numbers of genes encoded by different phage families, emphasizing how the evolutionary advantages conferred to hosts will depend on the prophage composition and offering insight to how these genes might disperse within a community. Our study highlights the intimate association of phage families with their hosts and uncovers their key role in shaping ecology for this widespread species complex.Significance statementThe bacterial accessory genome, including the mobilome and prophages, plays a critical role in shaping bacterial adaptation to abiotic and biotic drivers. These prophages are widespread across bacterial taxa and likely maintained because of their evolutionary advantage. Our ability to predict how a bacterial population will evolve over time requires a better understanding of where key functional traits arrive. To address this question, we assessed prophage-encoded phage defenses and effector acrossPseudomonas syringae. We show that prophages carrying these genes belong to specific phage taxa with differences in the types of genes encoded. This emphasizes the evolutionary advantage of these prophages, offering a framework to uncover how these genes disperse within microbial communities and their role in pathogen evolution.
Anti-JOVI.1 antibody to detect clonal T cell populations: implementation into a diagnostic flow cytometry laboratory and correlation with clinical findings
Authors: Reardon Benjamin , Hsu Jennifer , Smith Sandy , van der Linde Riana , Brown David A. , Tegg Elizabeth , Sasson Sarah C. 
Published: March 2024

AbstractThe development of a high through-put flow cytometric assay for the identification of clonal T cells has proved challenging. We assessed the surface expression of a specific T Cell Receptor β-chain constant region using conjugated anti-JOV1.1 monoclonal antibodies to identify clonal T cell populations in a large diagnostic flow cytometry laboratory within a quaternary referral hospital. 37 cases were analysed. We identified 15 cases of clonal JOVI.1 expression, 7 of which had a consensus diagnosis of T-cell lymphoproliferative disease (TLPD). The remaining 22 cases had polyclonal JOVI.1 expression, none of which had a consensus diagnosis of TLPD, resulting in a sensitivity of 100% and specificity of 73%. When clonal NK-T cells were excluded, specificity further improves to 97%. These results provide real-world data and support the widespread adoption of this assay into diagnostic use.
Large Language Model in Medical Information Extraction from Titles and Abstracts with Prompt Engineering Strategies: A Comparative Study of GPT-3.5 and GPT-4
Authors: Tang Yiyi , Xiao Ziyan , Li Xue , Fang Qiwen , Zhang Qingpeng , Fong Daniel Yee Tak , Lai Francisco Tsz Tsun , Chui Celine Sze Ling , Chan Esther Wai Yin , Wong Ian Chi Kei ,   Research Data Collaboration Task Force
Published: March 2024

AbstractBackgroundWhile it is believed that large language models (LLMs) have the potential to facilitate the review of medical literature, their accuracy, stability and prompt strategies in complex settings have not been adequately investigated. Our study assessed the capabilities of GPT-3.5 and GPT-4.0 in extracting information from publication abstracts. We also validated the impact of prompt engineering strategies and the effectiveness of evaluating metrics.MethodologyWe adopted a stratified sampling method to select 100 publications from nineteen departments in the LKS Faculty of Medicine, The University of Hong Kong, published between 2015 and 2023. GPT-3.5 and GPT-4.0 were instructed to extract seven pieces of information – study design, sample size, data source, patient, intervention, comparison, and outcomes – from titles and abstracts. The experiment incorporated three prompt engineering strategies: persona, chain-of-thought and few-shot prompting. Three metrics were employed to assess the alignment between the GPT output and the ground truth: ROUGE-1, BERTScore and a self-developed LLM Evaluator with improved capability of semantic understanding. Finally, we evaluated the proportion of appropriate answers among different GPT versions and prompt engineering strategies.ResultsThe average accuracy of GPT-4.0, when paired with the optimal prompt engineering strategy, ranged from 0.736 to 0.978 among the seven items measured by the LLM evaluator.Sensitivity of GPT is higher than the specificity, with an average sensiti ity score of 0.8550 while scoring only 0.7353 in specificity. The GPT version was shown to be a statistically significant factor impacting accuracy, while prompt engineering strategies did not exhibit cumulative effects. Additionally, the LLM evaluator outperformed the ROUGE-1 and BERTScore in assessing the alignment of information.ConclusionOur result confirms the effectiveness and stability of LLMs in extracting medical information, suggesting their potential as efficient tools for literature review. We recommend utilizing an advanced version of LLMs and the prompt should be tailored to specific tasks. Additionally, LLMs show promise as an evaluation tool related for complex information.
Socio-ecological heterogeneity and uncertainty in the elimination of human schistosomiasis
Authors: Neves M. Inês , Milne Gregory C , Webster Joanne P. , Walker Martin 
Published: March 2024

AbstractSchistosomiasis is a neglected tropical disease caused by parasitic flatworms which infect approximately 240 million people worldwide living in poverty, mostly in sub-Saharan Africa. The World Health Organization (WHO) aims to eliminate schistosomiasis by 2030, predominantly relying on a strategy of mass drug administration (MDA) using praziquantel. The effectiveness of MDA can vary widely among disease foci. Mathematical modelling is increasingly being used to understand the transmission dynamics of schistosomiasis and for predicting the effectiveness of MDA and time frames to elimination. Due to the highly focal nature of schistosomiasis, many key parameters influencing its transmission are likely highly geographically variable. Yet typically models do not fully integrate this uncertainty into predictions. This can lead to unrealistic expectations on the prospects for elimination. Here, we present a schistosomiasis transmission model to evaluate how uncertainty in parameters relating to local socio-ecological conditions influence resilience of the parasite population to intervention and the effectiveness of MDA. We discuss the growing importance of incorporating uncertainty in mathematical models for this and other NTDs to enable transparent communication of predictions as we move towards the 2030 elimination goals.
Trans-ancestral Genome Wide Association Study of Sporadic and Recurrent Miscarriage
Authors: Reynoso Alexandra , Nandakumar Priyanka , Shi Jingchunzi , Bielenberg Jessica ,   23andMe Research Team, Holmes Michael V. , Aslibekyan Stella 
Published: March 2024

AbstractMiscarriage is a common adverse pregnancy outcome, impacting approximately 15% of pregnancies. Herein, we present results of the largest trans-ancestral genome wide association study for miscarriage to date, based on 334,593 cases of sporadic, and 52,087 cases of recurrent miscarriage in the 23andMe, Inc. Research Cohort. We identified 10 novel genome-wide significant associations for sporadic miscarriage, and one for recurrent miscarriage. These loci mapped to genes with roles in neural development and telomere length, and to developmental disorders including autism spectrum disorder. Three variants, with similar directionality and magnitude of effect, replicated in a previously published GWAS. Using Mendelian randomization and triangulation, robust evidence was found for smoking causally increasing the risk of sporadic (genetic liability to ever vs never smoking: OR 1.13; 95%CI: 1.11-1.15; P=2.61e-42) and recurrent (OR 1.25; 95%CI: 1.21-1.30; P=5.47e-34) miscarriage, with moderate, yet triangulating, evidence identified for a potential etiological role of caffeine consumption.
Exposing Vulnerabilities in Clinical LLMs Through Data Poisoning Attacks: Case Study in Breast Cancer
Authors: Das Avisha , Tariq Amara , Batalini Felipe , Dhara Boddhisattwa , Banerjee Imon 
Published: March 2024

AbstractTraining Large Language Models (LLMs) with billions of parameters on a dataset and publishing the model for public access is the standard practice currently. Despite their transformative impact on natural language processing, public LLMs present notable vulnerabilities given the source of training data is often web-based or crowdsourced, and hence can be manipulated by perpetrators. We delve into the vulnerabilities of clinical LLMs, particularly BioGPT which is trained on publicly available biomedical literature and clinical notes from MIMIC-III, in the realm of data poisoning attacks. Exploring susceptibility to data poisoning-based attacks on de-identified breast cancer clinical notes, our approach is the first one to assess the extent of such attacks and our findings reveal successful manipulation of LLM outputs. Through this work, we emphasize on the urgency of comprehending these vulnerabilities in LLMs, and encourage the mindful and responsible usage of LLMs in the clinical domain.
A T6SS in the coral pathogenVibrio coralliilyticussecretes an arsenal of anti-eukaryotic effectors and contributes to virulence
Authors: Mass Shir , Cohen Hadar , Gerlic Motti , Ushijima Blake , van Kessel Julia C. , Bosis Eran , Salomon Dor 
Published: March 2024

AbstractVibrio coralliilyticus(Vcor) is a pathogen of coral and shellfish, leading to devastating economic and ecological consequences worldwide. Although rising ocean temperatures correlate with increasedVcorpathogenicity, the specific molecular mechanisms and determinants contributing to virulence remain poorly understood. Here, we systematically analyzed the type VI secretion system (T6SS), a contact-dependent toxin delivery apparatus, inVcor. We identified two omnipresent T6SSs that are activated at temperatures in whichVcorbecomes virulent; T6SS1 is an antibacterial system mediating interbacterial competition, whereas T6SS2 mediates anti-eukaryotic toxicity and contributes to mortality during infection of an aquatic model organism,Artemia salina. Using comparative proteomics, we identified the T6SS1 and T6SS2 toxin arsenals of threeVcorstrains with distinct disease etiologies. Remarkably, T6SS2 secretes at least nine novel anti-eukaryotic toxins comprising core and accessory repertoires. We propose that T6SSs differently contribute toVcor’s virulence: T6SS2 plays a direct role by targeting the host, while T6SS1 plays an indirect role by eliminating competitors.Author SummaryCoral reefs are diverse ecosystems providing habitats for various fish, invertebrates, and microorganisms. Climate change, leading to rising ocean water temperatures, correlates with coral bleaching and mass mortality events. An implicated causal agent of coral disease outbreaks is the marine bacteriumVibrio coralliilyticus. Here, we found that two toxin injection systems present in allVibrio coralliilyticusstrains are regulated by temperature; we revealed the toxins that they secrete and their function in competition against rival bacteria and in the intoxication of an animal host. Our findings implicate these systems as previously unappreciated contributors toVibrio coralliilyticusvirulence, illuminating possible targets to treat or prevent coral infection.
Interplay of IGF1R and estrogen signaling regulates hematopoietic stem and progenitor cells
Authors: Xie Ying , Xiang Dongxi , Hu Xin , Pakula Hubert , Park Eun-Sil , Chi Jiadong , Linn Douglas E. , Tao Luwei , Li Zhe 
Published: March 2024

AbstractTissue stem cells often exhibit developmental stage-specific and sexually dimorphic properties, but the underlying mechanism remains largely elusive. By characterizing IGF1R signaling in hematopoietic cells, here we report that its disruption exerts sex-specific effects in adult hematopoietic stem and progenitor cells (HSPCs). Loss of IGF1R decreases the HSPC population in females but not in males, in part due to a reduction in HSPC proliferation induced by estrogen. In addition, the adult female microenvironment enhances engraftment of wild-type but notIgf1r-null HSPCs. In contrast, during gestation, when both female and male fetuses are exposed to placental estrogens, loss of IGF1R reduces the numbers of their fetal liver HSPCs regardless of sex. Collectively, these data support the interplay of IGF1R and estrogen pathways in HSPCs and suggest that the proliferation-promoting effect of estrogen on HSPCs is in part mediated via IGF1R signaling.
MAP4 kinase-regulated reduced CLSTN1 expression in medulloblastoma is associated with increased invasiveness
Authors: Sönmez Ece , Yan Shen , Lin Meng-Syuan , Baumgartner Martin 
Published: March 2024

AbstractDe-regulated protein expression contributes to tumor growth and progression in medulloblastoma (MB), the most common malignant brain tumor in children. MB is associated with impaired differentiation of specific neural progenitors, suggesting that the deregulation of proteins involved in neural physiology could contribute to the transformed phenotype in MB.Calsynthenin 1 (CLSTN1) is a neuronal protein involved in cell-cell interaction, vesicle trafficking, and synaptic signaling. We previously identified CLSTN1 as a putative target of the pro-invasive kinase MAP4K4, which we found to reduce CLSTN1 surface expression. Herein, we explored the expression and functional significance of CLSTN1 in MB. We found thatCLSTN1expression is decreased in primary MB tumors compared to tumor-free cerebellum or brain tissues. CLSTN1 is expressed in laboratory-established MB cell lines, where it localized to the plasma membrane, intracellular vesicular structures, and regions of cell-cell contact. The reduction of CLSTN1 expression significantly increased growth factor-driven invasiveness. Pharmacological inhibition of MAP4 kinases caused increased CLSTN1 expression and CLSTN1 accumulation in cell-cell contacts. Co-culture of tumor cells with astrocytes increased CLSTN1 localization in cell-cell contacts, which was further enhanced by MAP4K inhibition.Our study revealed a repressive function of CLSTN1 in growth-factor-driven invasiveness in MB and its potential implication in homologous and heterologous interactions of the tumor cells with cells in their microenvironment.