bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of Reduced Spectral Resolution on Temporal-Coherence-Based Source Segregation
Authors: Viswanathan Vibha , Heinz Michael G. , Shinn-Cunningham Barbara G. 
Published: March 2024

1.AbstractHearing-impaired listeners struggle to understand speech in noise, even when using cochlear implants (CIs) or hearing aids. Successful listening in noisy environments depends on the brain’s ability to organize a mixture of sound sources into distinct perceptual streams (i.e., source segregation). In normal-hearing listeners, temporal coherence of sound fluctuations across frequency channels supports this process by promoting grouping of elements belonging to a single acoustic source. We hypothesized that reduced spectral resolution—a hallmark of both electric/CI (from current spread) and acoustic (from broadened tuning) hearing with sensorineural hearing loss—degrades segregation based on temporal coherence. This is because reduced frequency resolution decreases the likelihood that a single sound source dominates the activity driving any specific channel; concomitantly, it increases the correlation in activity across channels. Consistent with our hypothesis, predictions from a physiologically plausible model of temporal-coherence-based segregation suggest that CI current spread reduces comodulation masking release (CMR; a correlate of temporal-coherence processing) and speech intelligibility in noise. These predictions are consistent with our behavioral data with simulated CI listening. Our model also predicts smaller CMR with increasing levels of outer-hair-cell damage. These results suggest that reduced spectral resolution relative to normal hearing impairs temporal-coherence-based segregation and speech-in-noise outcomes.
Environmental complexity modulates information processing and the balance between decision-making systems
Authors: Mugan Ugurcan , Hoffman Samantha L. , Redish A. David 
Published: March 2024

SummaryBehavior in naturalistic scenarios occurs in diverse environments. Adaptive strategies rely on multiple neural circuits and competing decision-systems. However, past studies of rodent decision-making have largely measured behavior in simple environments. To fill this gap, we recorded neural ensembles from hippocampus (HC), dorsolateral striatum (DLS), and medial prefrontal cortex (mPFC) while rats foraged for food under changing rules in environments with varying topological complexity. Environmental complexity increased behavioral variability, lengthened HC nonlocal sequences, and modulated action caching. We found contrasting representations between DLS and HC, supporting a competition between decision systems. mPFC activity was indicative of setting this balance, in particular predicting the extent of HC non-local coding. Inactivating mPFC impaired short-term behavioral adaptation and produced long-term deficits in balancing decision systems. Our findings reveal the dynamic nature of decision-making systems and how environmental complexity modulates their engagement with implications for behavior in naturalistic environments.
Bridging Domains in Chronic Lower Back Pain: Large Language Models and Ontology-driven Strategies for Knowledge Graph Construction
Authors: Anderson Paul , Lin Damon , Davidson Jean , Migler Theresa , Ho Iris , Koenig Cooper , Bittner Madeline , Kaplan Samuel , Paraiso Mayumi , Buhn Nasreen , Stokes Emily , Hunt Tony , Ropella Glen , Lotz Jeffrey 
Published: March 2024

AbstractLink prediction and entity resolution play pivotal roles in uncovering hidden relationships within networks and ensuring data quality in the era of heterogeneous data integration. This paper explores the utilization of large language models to enhance link prediction, particularly through knowledge graphs derived from transdisciplinary literature. Investigating zero-shot entity resolution techniques, we examine the impact of ontology-based and large language model approaches on the stability of link prediction results. Through a case study focusing on chronic lower back pain research, we analyze workflow decisions and their influence on prediction outcomes. Our research underscores the importance of robust methodologies in improving predictive accuracy and data integration across diverse domains.
Morphometric Analysis of the Thymic Epithelial Cell (TEC) Network Using Integrated and Orthogonal Digital Pathology Approaches
Authors: Lagou Maria K. , Argyris Dimitrios G. , Vodopyanov Stepan , Gunther-Cummins Leslie , Hardas Alexandros , Poutahidis Theofilos , Panorias Christos , DesMarais Sophia , Entenberg Conner , Carpenter Randall S. , Guzik Hillary , Nishku Xheni , Churaman Joseph , Maryanovich Maria , DesMarais Vera , Macaluso Frank P. , Karagiannis George S. 
Published: March 2024

ABSTRACTThe thymus, a central primary lymphoid organ of the immune system, plays a key role in T cell development. Surprisingly, the thymus is quite neglected with regards to standardized pathology approaches and practices for assessing structure and function. Most studies use multispectral flow cytometry to define the dynamic composition of the thymus at the cell population level, but they are limited by lack of contextual insight. This knowledge gap hinders our understanding of various thymic conditions and pathologies, particularly how they affect thymic architecture, and subsequently, immune competence. Here, we introduce a digital pathology pipeline to address these challenges. Our approach can be coupled to analytical algorithms and utilizes rationalized morphometric assessments of thymic tissue, ranging from tissue-wide down to microanatomical and ultrastructural levels. This pipeline enables the quantitative assessment of putative changes and adaptations of thymic structure to stimuli, offering valuable insights into the pathophysiology of thymic disorders. This versatile pipeline can be applied to a wide range of conditions that may directly or indirectly affect thymic structure, ranging from various cytotoxic stimuli inducing acute thymic involution to autoimmune diseases, such as myasthenia gravis. Here, we demonstrate applicability of the method in a mouse model of age-dependent thymic involution, both by confirming established knowledge, and by providing novel insights on intrathymic remodeling in the aged thymus. Our orthogonal pipeline, with its high versatility and depth of analysis, promises to be a valuable and practical toolset for both basic and translational immunology laboratories investigating thymic function and disease.
In-Space Fabrication of Janus Base Nano-Matrix for Improved Assembly and Bioactivities
Authors: Yau Anne , Landolina Maxwell , Snow Mari Anne , Mesci Pinar , Williams Brandon , Hoying Jay , Duflo Derek , Wu Honglu , Stoudemire Jana , Hernandez Rose , Chen Yupeng 
Published: March 2024

AbstractIn-space manufacturing of nanomaterials is a promising concept while having limited successful examples. DNA-inspired Janus base nanomaterials (JBNs), used for therapeutics delivery and tissue regeneration, are fabricated via a controlled self-assembly process in water at ambient temperature, making them highly suitable for in-space manufacturing. For the first time, we designed and accomplished the production of JBNs on orbit during the Axiom-2 (Ax-2) mission demonstrating great promising and benefits of in-space manufacturing of nanomaterials.
Non-invasive laser speckle imaging of extra-embryonic blood vessels in intact few-days-old avian eggs
Authors: Dong Zhenyu , Mahler Simon , Readhead Carol , Chen Xi , Dickson Maya , Bronner Marianne E. , Yang Changhuei 
Published: March 2024

AbstractImaging blood vessels in early-stage avian embryos has a wide range of practical applications for developmental biology studies, drug and vaccine testing, and early sex determination. Optical imaging such as brightfield transmission imaging offers a compelling solution due to its safe non-ionizing radiation, and operational benefits. However, it comes with challenges such as eggshell opacity and light scattering. To address these, we have revisited an approach based on laser speckle contrast imaging (LSCI) and demonstrated a high quality, comprehensive and non-invasive visualization of blood vessels in few-days-old chicken eggs, with blood vessel as small as 100 µm in diameter (with LSCI profile full-width-at-half-maximum of 275 µm). We present its non-invasive use for monitoring blood flow, measuring the embryo’s heartbeat, and determining the embryo’s developmental stages using machine learning with 85% accuracy from stage HH15 to HH22. This method can potentially be used for non-invasive longitudinal studies of cardiovascular development and angiogenesis, as well as egg screening for the poultry industry.
Evaluation of ChatGPT’s Usefulness and Accuracy in Diagnostic Surgical Pathology
Authors: Guastafierro Vincenzo , Corbitt Devin Nicole , Bressan Alessandra , Fernandes Bethania , Mintemur Ömer , Magnoli Francesca , Ronchi Susanna , Rosa Stefano La , Uccella Silvia , Renne Salvatore Lorenzo 
Published: March 2024

AbstractChatGPT is an artificial intelligence capable of processing and generating human-like language. ChatGPT’s role within clinical patient care and medical education has been explored; however, assessment of its potential in supporting histopathological diagnosis is lacking. In this study, we assessed ChatGPT’s reliability in addressing pathology-related diagnostic questions across 10 subspecialties, as well as its ability to provide scientific references. We created five clinico-pathological scenarios for each subspecialty, posed to ChatGPT as open-ended or multiple-choice questions. Each question either asked for scientific references or not. Outputs were assessed by six pathologists according to: 1) usefulness in supporting the diagnosis and 2) absolute number of errors. All references were manually verified. We used directed acyclic graphs and structural causal models to determine the effect of each scenario type, field, question modality and pathologist evaluation. Overall, we yielded 894 evaluations. ChatGPT provided useful answers in 62.2% of cases. 32.1% of outputs contained no errors, while the remaining contained at least one error (maximum 18). ChatGPT provided 214 bibliographic references: 70.1% were correct, 12.1% were inaccurate and 17.8% did not correspond to a publication. Scenario variability had the greatest impact on ratings, followed by prompting strategy. Finally, latent knowledge across the fields showed minimal variation. In conclusion, ChatGPT provided useful responses in one-third of cases, but the number of errors and variability highlight that it is not yet adequate for everyday diagnostic practice and should be used with discretion as a support tool. The lack of thoroughness in providing references also suggests caution should be employed even when used as a self-learning tool. It is essential to recognize the irreplaceable role of human experts in synthesizing images, clinical data and experience for the intricate task of histopathological diagnosis.
Burden of renal anemia in 204 countries and territories, 1990-2021 : results from the Global Burden of Disease Study 2021
Authors: Chu Feifan , Ji Jinzhong , Ma Yuning , Guan Qing , Chen Lumin , Chen Zujie , Ji Qiwei , Sun Mingxin , Zhang Hui , Huang Tingyang , Song Haihan , Lin Xiuquan , Zhou Hao 
Published: March 2024

AbstractRenal anemia has inflicted a certain degree of loss on global health. However, there are no systematically analyses on the burden of renal anemia.We analyzed global prevalence and years lived with disability (YLDs) of renal anemia from 1990 to 2021. Based on the Socio-Demographic Index (SDI), combined with cross-national inequality analysis, frontier analysis and age-period-cohort (APC) model analysis, the prevalence and YLDs differences between different aspects were compared.Since 1990, the prevalence and YLDs of renal anemia in 2021 have shown an upward trend. In countries with medium and low levels of development, the burden of renal anemia is particularly severe among people over 60 years. A series of analyses based on the SDI revealed a negative correlation between the prevalence of renal anemia and SDI.Thus, Public health policies targeting renal anemia should give priority to the elderly in medium- and low-development areas.
Seq2MAIT: A Novel Deep Learning Framework for Identifying Mucosal Associated Invariant T (MAIT) Cells
Authors: ElAbd Hesham , Byron Rachel , Woodhouse Steven , Robinett Brittney , Sulc Joe , Franke Andre , Pesesky Mitchell , Zhou Wenyu , Chen-Harris Haiyin , Howie Bryan , Taniguchi Ruth , Robins Harlan 
Published: March 2024

AbstractMucosal-associated invariant T (MAIT) cells are a group of unconventional T cells that mainly recognize bacterial vitamin B metabolites presented on MHC-related protein 1 (MR1). MAIT cells have been shown to play an important role in controlling bacterial infection and in responding to viral infections. Furthermore, MAIT cells have been implicated in different chronic inflammatory diseases such as inflammatory bowel disease and multiple sclerosis. Despite their involvement in different physiological and pathological processes, a deeper understanding of MAIT cells is still lacking. Arguably, this can be attributed to the difficulty of quantifying and measuring MAIT cells in different biological samples which is commonly done using flow cytometry-based methods and single-cell-based RNA sequencing techniques. These methods mostly require fresh samples which are difficult to obtain, especially from tissues, have low to medium throughput, and are costly and labor-intensive. To address these limitations, we developed sequence-to-MAIT (Seq2MAIT) which is a transformer-based deep neural network capable of identifying MAIT cells in bulk TCR-sequencing datasets, enabling the quantification of MAIT cells from any biological materials where human DNA is available. BenchmarkingSeq2MAITacross different test datasets showed an average area-under-the-receiver-operator-curve (AU[ROC]) >0.80. In conclusion,Seq2MAITis a novel, economical, and scalable method for identifying and quantifying MAIT cells in virtually any biological sample.
Alteration of nociceptive Schwann cells in a mouse model of high-fat diet induced diabetic peripheral neuropathy
Authors: Rastoldo Guillaume , Jaafar Ali K. , Aurélie-Paulo-Ramos  , Thouvenot Katy , Planesse Cynthia , Bringart Matthieu , Gonthier Marie-Paule , Lambert Gilles , Bourane Steeve 
Published: March 2024

AbstractDiabetic peripheral neuropathy (DPN) is characterized by progressive and symmetrical sensory abnormalities and constitutes one of the earliest and main complications of diabetes. DPN is characterized by heterogeneous sensory symptoms such as chronic pain, tingling, burning or loss of sensation. Nociceptive Schwann cells (nSCs), a recently identified subtypes of dermal Schwann cells support terminal nerve fibers in mouse skin and contribute to mechanical sensation and neuropathic pain. While terminal nerve fibers density is evaluated in DPN models, there is currently no data about nSCs number and integrity during the early stages of the disease. In the present study, we determined the quantitative differences in terminal nerve fiber density as well as nSCs number and cellular extensions between control and high-fat diet (HFD) induced diabetic mice presenting with a neuropathic phenotype. We also characterized L1CAM as a reliable and specific marker of nSCs, a cell type previously assessed by the expression of S100β and Sox10. Interestingly, we observed a decrease in intraepidermal nerve fiber density (IENFD) associated with a significant reduction of nSCs in the glabrous foot skin of neuropathic mice. Overall, this study identifies L1CAM as a new marker of nSCs and indicates that these cells are impacted in diabetic peripheral neuropathy.
Multi-modal comparison of molecular programs driving nurse cell death and clearance inDrosophila melanogasteroogenesis
Authors: Bandyadka Shruthi , Lebo Diane PV , Mondragon Albert , Serizier Sandy B , Kwan Julian , Peterson Jeanne S , Chasse Alexandra Y , Jenkins Victoria , Calikyan Anoush , Ortega Anthony , Campbell Joshua D , Emili Andrew , McCall Kimberly 
Published: March 2024

AbstractThe death and clearance of nurse cells is a consequential milestone inDrosophila melanogasteroogenesis. In preparation for oviposition, the germline-derived nurse cells bequeath to the developing oocyte all their cytoplasmic contents and undergo programmed cell death. The death of the nurse cells is controlled non-autonomously and is precipitated by epithelial follicle cells of somatic origin acquiring a squamous morphology and acidifying the nurse cells externally. Alternatively, stressors such as starvation can induce the death of nurse cells earlier in mid-oogenesis, manifesting apoptosis signatures, followed by their engulfment by epithelial follicle cells. To identify and contrast the molecular pathways underlying these morphologically and genetically distinct cell death paradigms, both mediated by follicle cells, we compared their genome-wide transcriptional, translational, and secretion profiles before and after differentiating to acquire a phagocytic capability, as well as during well-fed and nutrient-deprived conditions. By coupling the GAL4-UAS system to Translating Ribosome Affinity Purification (TRAP-seq) and proximity labeling (HRP-KDEL) followed by Liquid Chromatography tandem mass-spectrometry, we performed high-throughput screens to identify pathways selectively activated or repressed by follicle cells to employ nurse cell-clearance routines contextually and preferentially. We also integrated two publicly available single-cell RNAseq atlases of theDrosophilaovary to define the transcriptomic profiles of follicle cells. In this report, we describe the genes and major pathways identified in the screens and the striking consequences toDrosophila melanogasteroogenesis caused by RNAi perturbation of prioritized candidates. To the best of our knowledge, our study is the first of its kind to comprehensively characterize two distinct apoptotic and non-apoptotic cell death paradigms in the same multi-cellular system. Beyond molecular differences in cell death, our investigation may also provide insights into how key systemic trade-offs are made between survival and reproduction when faced with physiological stress.
Lowering glucose enhances BACE1 activity and Aβ generation in mouse brain slice cultures
Authors: Sheppard Olivia , Humphrey Robert , Durrant Claire S. , Coleman Michael P. 
Published: March 2024

AbstractNumerous environmental risk factors are now recognised as contributors to the onset and progression of Alzheimer’s disease (AD). It is probable that, in most instances, AD arises from a combination of genetic predisposition and environmental influences. In particular, there is a strong correlation between vascular impairment and dementia, yet the specific mechanisms by which vascular impairment and AD are linked, remain unknown. Hypoglycaemia can occur both due to vascular impairment, and due to fluctuating glucose levels in the context of diabetes, another risk factor for AD, and could potentially be involved in disease pathogenesis. To assess whether low glucose could contribute to the build-up of brain amyloid-β (Aβ) seen in AD, we exposed wildtype mouse organotypic hippocampal slice cultures (OHSCs) to varying glucose concentrations. Lowering glucose levels leads to an elevation in both Aβ1-42and Aβ1-40secreted into the culture medium, accompanied by an increased accumulation of Aβ within the slice tissue. This effect is replicated in OHSCs derived from the TgCRND8 mouse model of overexpressed, mutant APP and in human SH-SY5Y cells. The heightened Aβ levels are likely attributed to an upregulation of BACE1 activity, which is also observed with lowered glucose levels. In contrast, OHSCs subject to hypoxia exhibited no alterations in Aβ levels whether singularly, or in combination of hypoglycaemia. Finally, we found that alternative energy sources such as pyruvate, fructose 1,6-bisphosphate, and lactate can alleviate heightened Aβ levels, when given in combination with lowered glucose. This study underscores the capacity to induce an increase in Aβ in a wildtypeex vivosystem by selectively decreasing glucose levels.
Transcriptional characterization of cocaine withdrawal versus extinction within nucleus accumbens
Authors: Martínez-Rivera Freddyson J. , Holt Leanne M. , Minier-Toribio Angélica , Estill Molly , Yeh Szu-Ying , Tofani Solange , Futamura Rita , Browne Caleb J. , Mews Philipp , Shen Li , Nestler Eric J. 
Published: March 2024

AbstractSubstance use disorder is characterized by a maladaptive imbalance wherein drug seeking persists despite negative consequences or drug unavailability. This imbalance correlates with neurobiological alterations some of which are amplified during forced abstinence, thereby compromising the capacity of extinction-based approaches to prevent relapse. Cocaine use disorder (CUD) exemplifies this phenomenon in which neurobiological modifications hijack brain reward regions such as the nucleus accumbens (NAc) to manifest craving and withdrawal-like symptoms. While increasing evidence links transcriptional changes in the NAc to specific phases of addiction, genome-wide changes in gene expression during withdrawal vs. extinction (WD/Ext) have not been examined in a context- and NAc-subregion-specific manner. Here, we used cocaine self-administration (SA) in rats combined with RNA-sequencing (RNA-seq) of NAc subregions (core and shell) to transcriptionally profile the impact of experiencing withdrawal in the home cage or in the previous drug context or experiencing extinction training. As expected, home-cage withdrawal maintained drug seeking in the previous drug context, whereas extinction training reduced it. By contrast, withdrawal involving repetitive exposure to the previous drug context increased drug-seeking behavior. Bioinformatic analyses of RNA-seq data revealed gene expression patterns, networks, motifs, and biological functions specific to these behavioral conditions and NAc subregions. Comparing transcriptomic analysis of the NAc of patients with CUD highlighted conserved gene signatures, especially with rats that were repetitively exposed to the previous drug context. Collectively, these behavioral and transcriptional correlates of several withdrawal-extinction settings reveal fundamental and translational information about potential molecular mechanisms to attenuate drug-associated memories.