bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical Features of Genetic Resilience in Chronic Obstructive Pulmonary Disease
Authors: Ghosh Auyon J. , Moll Matthew , Hess Jonathan , Hobbs Brian D. , Love Angela , Coyne Liam , Cho Michael H. , Castaldi Peter , Middleton Frank A. , Perl Andras , Silverman Edwin K. , Hersh Craig P. , Glatt Stephen J. 
Published: March 2023

AbstractIntroductionIn the personalized risk quantification of chronic obstructive pulmonary disease (COPD), genome-wide association studies and polygenic risk scores (PRS) complement traditional risk factors, such as age and cigarette smoking. However, despite being at considerable levels of risk, some individuals do not develop COPD. Research on COPD resilience remains largely unexplored.MethodsWe applied the previously published COPD PRS to whole genome sequencing data from non-Hispanic white and African American individuals in the COPDGene study. We defined genetic resilience as individuals unaffected by COPD with a polygenic risk score above the 90thpercentile. We defined risk-matched case individuals as those with COPD (i.e., FEV1/FVC < 0.70) and a PRS above the 90thpercentile. We defined low risk individuals without COPD (i.e., FEV1/FVC > 0.70) as a polygenic risk score below the 10thpercentile. We compared genetically resilient individuals to risk-matched individuals with COPD and low risk individuals by demographics, lung function, respiratory symptoms, co-morbidities, and chest CT scan measurements. We also performed survival analyses, differential expression analysis, and matching for sensitivity analyses.ResultsWe identified 211 resilient individuals without COPD, 605 genetic risk-matched individuals with COPD, and 527 low-risk individuals without COPD. Resilient individuals had higher FEV1% predicted and lower percent emphysema. In contrast, resilient individuals had higher airway wall thickness compared to low-risk unaffected individuals. While there was no difference in survival between low-risk and resilient individuals, resilient individuals had higher survival compared to risk matched cases. We also identified two genes that were differentially expressed between low-risk unaffected individuals and resilient individuals.ConclusionGenetically resilient individuals had a reduced burden of COPD disease-related measures compared to risk-matched cases but had subtly increased measures compared to low-risk unaffected individuals. Further genetic studies will be needed to illuminate the underlying pathobiology of our observations.
Evaluation of Atrial Fibrillation Detection in short-term Photoplethysmography (PPG) signals using artificial intelligence
Authors: Talukdar Debjyoti , de Deus Luis Felipe , Sehgal Nikhil 
Published: March 2023

ABSTRACTAtrial Fibrillation (AFIB) is a common atrial arrhythmia that affects millions of people worldwide. However, most of the time, AFIB is paroxysmal and can pass unnoticed in medical exams therefore regular screening is required. This paper proposes machine learning methods to detect AFIB from short-term ECG and PPG signals. Several experiments were conducted across five different databases with three of them containing ECG signals and the other two consisting of only PPG signals. A total of 269,842 signal segments were analyzed across all datasets (212,266 were of normal sinus rhythm (NSR) and 57,576 corresponded to AFIB segments). Experiments were conducted to investigate the hypothesis that a machine learning model trained to predict AFIB from ECG segments, could be used to predict AFIB from PPG segments. A random forest machine learning algorithm achieved the best accuracy and achieved a 90% accuracy rate on the UMMC dataset (216 samples) and a 97% accuracy rate on the MIMIC-III dataset (2,134 samples). The ability to detect AFIB with significant accuracy using machine learning algorithms from PPG signals, which can be acquired via non-invasive contact or contactless, is a promising step forward toward the goal of achieving large-scale screening for AFIB.
Dynamics of Eastern equine encephalitis virus during the 2019 outbreak in the Northeast United States
Authors: Hill Verity , Koch Robert T. , Bialosuknia Sean M. , Ngo Kiet , Zink Steven D. , Koetzner Cheri A. , Maffei Joseph G. , Dupuis Alan P. , Backenson P. Bryon , Oliver JoAnne , Bransfield Angela B. , Misencik Michael J. , Petruff Tanya A. , Shepard John J. , Warren Joshua L. , Gill Mandev S. , Baele Guy , Vogels Chantal B.F. , Gallagher Glen , Burns Paul , Hentoff Aaron , Smole Sandra , Brown Catherine , Osborne Matthew , Kramer Laura D. , Armstrong Philip M. , Ciota Alexander T. , Grubaugh Nathan D. 
Published: March 2023

AbstractEastern equine encephalitis virus (EEEV) causes a rare but severe disease in horses and humans, and is maintained in an enzootic transmission cycle between songbirds andCuliseta melanuramosquitoes. In 2019, the largest EEEV outbreak in the United States for more than 50 years occurred, centered in the Northeast. To explore the dynamics of the outbreak, we sequenced 80 isolates of EEEV and combined them with existing genomic data. We found that, like previous years, cases were driven by frequent short-lived virus introductions into the Northeast from Florida. Once in the Northeast, we found that Massachusetts was important for regional spread. We found no evidence of any changes in viral, human, or bird factors which would explain the increase in cases in 2019. By using detailed mosquito surveillance data collected by Massachusetts and Connecticut, however, we found that the abundance ofCs. melanurawas exceptionally high in 2019, as was the EEEV infection rate. We employed these mosquito data to build a negative binomial regression model and applied it to estimate early season risks of human or horse cases. We found that the month of first detection of EEEV in mosquito surveillance data and vector index (abundance multiplied by infection rate) were predictive of cases later in the season. We therefore highlight the importance of mosquito surveillance programs as an integral part of public health and disease control.
Computer Vision Analysis of Specimen Mammography to Predict Margin Status
Authors: Chen Kevin A , Kirchoff Kathryn E , Butler Logan R , Holloway Alexa D , Kapadia Muneera R , Gallagher Kristalyn K , Gomez Shawn M 
Published: March 2023

AbstractIntra-operative specimen mammography is a valuable tool in breast cancer surgery, providing immediate assessment of margins for a resected tumor. However, the accuracy of specimen mammography in detecting microscopic margin positivity is low. We sought to develop a deep learning-based model to predict the pathologic margin status of resected breast tumors using specimen mammography. A dataset of specimen mammography images matched with pathology reports describing margin status was collected. Models pre-trained on radiologic images were developed and compared with models pre-trained on non-medical images. Model performance was assessed using sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). The dataset included 821 images and 53% had positive margins. For three out of four model architectures tested, models pre-trained on radiologic images outperformed domain-agnostic models. The highest performing model, InceptionV3, showed a sensitivity of 84%, a specificity of 42%, and AUROC of 0.71. These results compare favorably with the published literature on surgeon and radiologist interpretation of specimen mammography. With further development, these models could assist clinicians with identifying positive margins intra-operatively and decrease the rate of positive margins and re-operation in breast-conserving surgery.
Correlates of suicidal behaviors and genetic risk among United States veterans with schizophrenia or bipolar I disorder
Authors: Bigdeli Tim B. , Barr Peter B. , Rajeevan Nallakkandi , Graham David P. , Li Yuli , Meyers Jacquelyn L. , Gorman Bryan R. , Peterson Roseann E. , Sayward Frederick , Radhakrishnan Krishnan , Natarajan Sundar , Nielsen David A. , Wilkinson Anna V. , Malhotra Anil K. , Zhao Hongyu , Brophy Mary , Shi Yunling , O’Leary Timothy J. , Gleason Theresa , Przygodzki Ronald , Pyarajan Saiju , Muralidhar Sumitra , Gaziano J. Michael ,   Million Veteran Program (MVP),   Cooperative Studies Program (CSP) #572, Huang Grant D. , Concato John , Siever Larry J. , DeLisi Lynn E. , Kimbrel Nathan A. , Beckham Jean C. , Swann Alan C. , Kosten Thomas R. , Fanous Ayman H. , Aslan Mihaela , Harvey Philip D. 
Published: March 2023

ABSTRACTObjectivePersons diagnosed with schizophrenia (SCZ) or bipolar I disorder (BPI) are at high risk for self-injurious behavior, suicidal ideation, and suicidal behaviors (SB). Characterizing associations between diagnosed mental and physical health problems, prior pharmacological treatments, and aggregate genetic factors has potential to inform risk stratification and mitigation strategies.MethodsIn this study of 3,942 SCZ and 5,414 BPI patients receiving VA care, self-reported SB and ideation were assessed using the Columbia Suicide Severity Rating Scale (C-SSRS). These cross-sectional data were integrated with electronic health records (EHR), and compared by lifetime diagnoses, treatment histories, follow-up screenings, and mortality data. Polygenic scores (PGS) for traits related to psychiatric disorders, substance use, and cognition were constructed using available genomic data, and exploratory genome-wide association studies were performed to identify and prioritize specific loci.ResultsOnly 20% of veterans who self-reported SB had a corroborating ICD-9/10 code in their EHR; and among those who denied prior behaviors, more than 20% reported new-onset SB at follow-up. SB were associated with a range of psychiatric and non-psychiatric diagnoses, and with treatment with specific classes of psychotropic medications (e.g., antidepressants, antipsychotics, etc.). PGS for externalizing behaviors, smoking, suicide attempt, and major depressive disorder were also associated with attempt and ideation.ConclusionsAmong individuals with a diagnosed mental illness, a GWAS for SB did not yield any significant loci. Self-reported SB were strongly associated with clinical variables across several EHR domains. Overall, clinical and polygenic analyses point to sequelae of substance-use related behaviors and other psychiatric comorbidities as strong correlates of prior and subsequent SB. Nonetheless, past SB was frequently not documented in clinical settings, underscoring the value of regular screening based on direct, in-person assessments, especially among high-risk individuals.
The MYO1B and MYO5B motor proteins and the SNX27 sorting nexin regulate membrane mucin MUC17 trafficking in enterocytes
Authors: Jäverfelt Sofia , Hellsén Gustaf , Kaji Izumi , Goldenring James R. , Pelaseyed Thaher 
Published: March 2023

AbstractA dense glycocalyx, composed of the megaDalton-sized membrane mucin MUC17, coats the microvilli in the apical brush border of transporting intestinal epithelial cells, called enterocytes. The establishment of the MUC17-based glycocalyx in the mouse small intestine occurs at the critical suckling-weaning transition. The enterocytic glycocalyx extends 1 µm into the intestinal lumen and prevents the gut bacteria from directly attaching to the enterocytes. To date, the mechanism behind apical targeting of MUC17 to the brush border remains unknown. Here, we show that the actin-based motor proteins MYO1B and MYO5B, and the sorting nexin SNX27 regulate the intracellular trafficking of MUC17 in enterocytes. We demonstrate that MUC17 turnover at the brush border is slow and controlled by MYO1B and SNX27. Furthermore, we report that MYO1B regulates MUC17 protein levels in enterocytes, whereas MYO5B specifically governs MUC17 levels at the brush border. Together, our results extend our understanding of the intracellular trafficking of membrane mucins and provide mechanistic insights into how defective trafficking pathways render enterocytes sensitive to bacterial invasion.
Re-analysis of lipidomic data reveals Specialised Pro-Resolution Lipid Mediators (SPMs) to be lower than quantifiable limits of assay in a human model of resolving inflammation
Authors: Homer Natalie ZM , Andrew Ruth , Gilroy Derek W 
Published: March 2023

ABSTRACTUsing a model of UV-killedE. colidriven dermal inflammation in healthy human volunteers we originally reported that following inflammatory resolution there was the infiltration of macrophages, which, through prostanoids including prostaglandin (PG)E2, imprints long-term tissue immunity. In addition to the prostanoids, we also presented data on levels ofSpecialisedPro-Resolution LipidMediators (SPMs) throughout inflammatory onset, resolution and post-resolution phases of this model. However, our collaborators who carried out the lipidomic analysis received a complaint concerning how they generally present SPM data in their publications, namely their use of graphical illustrations to depict data. Importantly, such lipidomic illustrations were used in our human UV-killedE. colistudy. Therefore, in the interest of transparency and to replace these illustrations with more meaningful images, the original data from our human UV-killedE. colimodel were re-analysed by two independent experts. It transpires that the integrated areas of the chromatographic peaks of the SPM lipid mediators were below the amounts that could be reliably either detected and/or quantified using community standards for quantitation. Here we show the outcome of this reanalysis. Importantly, with prostanoids including PGE2being robustly detected, this re-analysis does not alter the original report that post-resolution PGs imprint tissue immunity.
Molecular Consequences of Peripheral Influenza A Infection on Cell Populations in the Murine Hypothalamus
Authors: Lemcke René , Egebjerg Christine , Berendtsen Nicolai T. , Egerod Kristoffer L. , Thomsen Allan R. , Pers Tune H. , Christensen Jan P. , Kornum Birgitte R. 
Published: March 2023

AbstractInfection with Influenza A virus (IAV) causes the well-known symptoms of the flu, including fever, loss of appetite and excessive sleepiness. These responses, mediated by the brain, will normally disappear once the virus is cleared from the system, but a severe respiratory virus infection may cause long-lasting neurological disturbances. These include encephalitis lethargica and narcolepsy. The mechanisms behind such long lasting changes are unknown. The hypothalamus is a central regulator of the homeostatic response during a viral challenge. To gain insight into the neuronal and non-neuronal molecular changes during an IAV infection, we intranasally infected mice with an H1N1 virus and extracted the brain at different time points. Using single-nucleus RNA sequencing (snRNA-seq) of the hypothalamus, we identify transcriptional effects in all identified cell populations. The snRNA-seq data showed the most pronounced transcriptional response at 3 days past infection, with a strong downregulation of genes across all cell types. General immune processes were mainly impacted in microglia, the brain resident immune cells, where we found increased numbers of cells expressing pro-inflammatory gene networks. In addition, we found that most neuronal cell populations downregulated genes contributing to the energy homeostasis in mitochondria and protein translation in the cytosol, indicating potential reduced cellular and neuronal activity. This might be a preventive mechanism in neuronal cells to avoid intracellular viral replication and attack by phagocytosing cells. The change of microglia gene activity suggest that this is complemented by a shift in microglia activity to provide increased surveillance of their surroundings.
Generation of Schwann cell derived melanocytes from hPSCs identifies pro-metastatic factors in melanoma
Authors: Samuel Ryan M. , Navickas Albertas , Maynard Ashley , Gaylord Eliza A. , Garcia Kristle , Bhat Samyukta , Majd Homa , Richter Mikayla N. , Elder Nicholas , Le Daniel , Nguyen Phi , Shibata Bradley , Llabata Marta Losa , Selleri Licia , Laird Diana J. , Darmanis Spyros , Goodarzi Hani , Fattahi Faranak 
Published: March 2023

Summary/AbstractThe neural crest (NC) is highly multipotent and generates diverse lineages in the developing embryo. However, spatiotemporally distinct NC populations display differences in fate potential, such as increased gliogenic and parasympathetic potential from later migrating, nerve-associated Schwann cell precursors (SCPs). Interestingly, while melanogenic potential is shared by both early migrating NC and SCPs, differences in melanocyte identity resulting from differentiation through these temporally distinct progenitors have not been determined. Here, we leverage a human pluripotent stem cell (hPSC) model of NC temporal patterning to comprehensively characterize human NC heterogeneity, fate bias, and lineage development. We captured the transition of NC differentiation between temporally and transcriptionally distinct melanogenic progenitors and identified modules of candidate transcription factor and signaling activity associated with this transition. For the first time, we established a protocol for the directed differentiation of melanocytes from hPSCs through a SCP intermediate, termed trajectory 2 (T2) melanocytes. Leveraging an existing protocol for differentiating early NC-derived melanocytes, termed trajectory 1 (T1), we performed the first comprehensive comparison of transcriptional and functional differences between these distinct melanocyte populations, revealing differences in pigmentation and unique expression of transcription factors, ligands, receptors and surface markers. We found a significant link between the T2 melanocyte transcriptional signature and decreased survival in melanoma patients in the cancer genome atlas (TCGA). We performed anin vivoCRISPRi screen of T1 and T2 melanocyte signature genes in a human melanoma cell line and discovered several T2-specific markers that promote lung metastasis in mice. We further demonstrated that one of these factors, SNRPB, regulates the splicing of transcripts involved in metastasis relevant functions such as migration, cell adhesion and proliferation. Overall, this study identifies distinct developmental trajectories as a source of diversity in melanocytes and implicates the unique molecular signature of SCP-derived melanocytes in metastatic melanoma.
Species Delimitation Under Allopatry: Genomic Divergences Within and Across Continents in Lepidoptera
Authors: Joshi Mukta , Espeland Marianne , Huemer Peter , deWaard Jeremy , Mutanen Marko 
Published: March 2023

ABSTRACTDelimitation of allopatric populations into species remains subjective and largely arbitrary. Many cold-adapted species from the subarctic and Central and Southern European Mountain systems display frequent allopatry with disjunct distributions of their populations. The same concerns Holarctic species which are many and which almost regularly show various degrees of differentiation between the continents. In this study, we analyze high- throughput target enrichment data for ten groups of arctic-alpine and Holarctic lepidopteran species sampled from four main regions across the Holarctic realm – Fennoscandia, North America, Alps and Altai. We first aimed to assess whether the genetic differences in the nuclear genome reflect observed DNA barcode divergences and second, whether the gap between population and species-level differences can be dissected using genomic data. We compared the phylogenetic trees and uncorrected pairwise genetic distances obtained from target enrichment and the mitochondrial cytochrome oxidase I (COI) barcodes for each of the study species. Additionally, we also performed a suite of population genetic and species delimitation analyses to further shed light on patterns of intraspecific variation using a large number of nuclear markers. We observed that in about one half of the cases, DNA barcodes tended to show phylogenetic relationships similar to the target enrichment markers. We report varying levels of nuclear genetic differentiation among the populations analyzed, starting from low differentiation of geographically separated populations to the deeper separation of some Nearctic population and further arctic-alpine disjunction. Given that no single consistent pattern emerged across different case studies, we demonstrate that the delimitation of allopatric populations into species could be done much more efficiently and in a consistent manner if based on a large set of universal genetic loci, which would help in reaching standards for taxonomic delimitation of allopatric populations.
Application of fuzzy measures to move towards the cyber-taxonomy
Authors: Ciguene Richardson , Mozziconacci Julien , Clément Francis , Miralles Aurélien 
Published: March 2023

AbstractThe species inventory of global biodiversity is constantly revised and refined by taxonomic research, through the addition of newly discovered species. This almost three century old project provide a knowledge foundation essential for humankind, and notably to develop appropriate conservation strategies. This task relies on the study of millions of specimens housed all around the world in natural history collections. Since two decades, taxonomy generates a plethoric amount of numeric data every year, and notably through the digitization of collection specimens, gradually transforms into a big data science. In this line, the French National Museum of Natural History (MNHN) has embarked into a major research and engineering challenge within its information system, in order to facilitate the transition towards cyber-taxonomic practices which require a facilitated access to data on reference collection specimens housed all over the world. To this end, a first mandatory step is to automatically complete classification data usually associated to collection specimens found in multiple databases. We use here fuzzy approaches to connect one database with other databases and match identical specimens found in each databases together.