bluuebunny/crossref_metadata_2025_split huggingface dataset:
Follicular Bcl6 reactivity is associated with a unique immune landscape and spatial transcriptome in COVID-19
Authors: Brenna Cloe , Bernat Bramon Mora , Ioannidou Kalliopi , Burgermeister Simon , Bodelet Julien , Siebmanns Mia , Georgakis Spiros , Orfanakis Michail , Sédille Nazanin , Feinstein Matthew J , Lomasney Jon W , Chen Oliver Y. , Pantaleo Giuseppe , Berezowska Sabina , Leval Laurence De , Gottardo Raphael , Petrovas Constantinos 
Published: November 2024

ABSTRACTThe regulation of follicular (F) and germinal center (GC) immune reactivity in human lymph nodes (LNs), particularly during the early stages of viral infections, remains poorly understood. We have analyzed lung-draining lymph nodes (LD-LNs) from COVID-19 autopsies using multiplex imaging and spatial transcriptomics to examine the immune landscape and with respect to the aging. We identified three subgroups of Reactive Follicles (RFs) based on Bcl6 prevalence, RF-Bcl6no/low, RF-Bcl6int and RF-Bcl6high. RF-Bcl6high tissues express a distinct B/TFH immune landscape associated with increased prevalence of proliferating B- and TFH-cell subsets. Comparison between LD-LNs and matched subdiaphragmatic LNs revealed a disconnected Bcl6 reactivity between the two anatomical sites. LD-LNs Bcl6 reactivity was associated with a distinct spatial transcriptomic profile. TH1-associated genes/pathways (e.g. CXCR3, STAT5, TNF signaling) were significantly upregulated in RF-Bcl6no/low tissues while the RF-Bcl6high tissues exhibited significant upregulation of GC-promoting genes/pathways (e.g. CXCL13, B cell receptor signaling). Despite the similar prevalence, the in-situ transcriptome profiling indicates a higher monocyte/macrophage functionality in “Aged” compared to “Young” follicles from donors with comparable Bcl6 reactivity. Our findings reveal a heterogeneous F/GC landscape in COVID-19 LD-LNs and highlight specific molecular targets and pathways that could regulate human F/GC immune dynamics during early viral infections.
Evaluating the Survival and Removal ofEscherichia colifrom Surfaces Made with Traditional and Sustainable Cement-Based Materials in Field-Relevant Conditions
Authors: Anderson Claire E. , Hernandez Jason , Hanif Suhi , Owens Lauren , Crider Yoshika , Billington Sarah L. , Lepech Michael , Boehm Alexandria B. , Benjamin-Chung Jade 
Published: November 2024

AbstractSoil household floors are common in low- and middle-income countries (LMICs) and can serve as reservoirs of enteric pathogens. Cement-based floors may interrupt pathogen transmission, but little is known about pathogen survival or removal from cement-based surfaces. This study investigated the survival ofEscherichia coli(E. coli), an indicator of fecal contamination, on cement-based surfaces and evaluated its reduction through common household activities (mopping, sweeping, and walking). We comparedE. colifate on three mixes: 1) Ordinary Portland Cement (OPC) concrete (used in the United States), 2) OPC mortar (used in Bangladesh), and 3) OPC mortar with fly ash (a sustainable alternative to the Bangladesh mix). Additionally, we compared outcomes on cement-based surfaces with and without soil and at two temperatures representing the dry and wet seasons in Bangladesh. After 4 hours on the cement-based surfaces,E. colidecayed more than 1.1 log10(C/Co) under all conditions tested, which is significantly faster than in bulk soils. The higher temperature increased the decay rate constant (p = 5.56*10−8) while soil presence decreased it (p = 2.80*10−6). Sweeping and mopping resulted in high levels of removal for all mixes, with a mean removal of 71% and 78%, respectively, versus 22% for walking. The concrete and mortar mix designs did not impactE. colisurvival or removal (p > 0.20). Cement-based floors made with a fly ash mix performed similarly to traditional cement-based floors, supporting its potential use as a more sustainable intervention to reduce fecal contamination in rural LMIC household settings.ImportanceCement-based surfaces may serve as a health intervention to reduce the fecal-oral transmission of pathogens in household settings, but there is a critical lack of evidence about the fate of indicator organisms on these surfaces, especially in field-relevant conditions. This study provides some of the first insights intoE. colisurvival on cement-based surfaces and the effectiveness of daily activities for removingE. coli. Additionally, this study explores the fate ofE. colion cement-based surfaces made with fly ash (which contributes fewer CO2emissions) versus traditional cement mixes. We found thatE. colihad similar survival and removal across all mix designs, demonstrating that fly ash mixes are feasible for use in household settings (e.g., in floors). The findings enhance understanding of fecal-oral transmission pathways and support the use of fly ash mixes in cement-based flooring in future epidemiologic studies assessing effects on enteric disease burdens.
Automated cell detection for immediate early gene-expressing neurons using inhomogeneous background subtraction in fluorescent images
Authors: Osanai Hisayuki , Arai Miari , Kitamura Takashi , Ogawa Sachie K. 
Published: November 2024

AbstractAlthough many methods for automated fluorescent-labeled cell detection have been proposed, not all of them assume a highly inhomogeneous background arising from complex biological structures. Here, we propose an automated cell detection algorithm that accounts for and subtracts the inhomogeneous background by avoiding high-intensity pixels in the blur filtering calculation. Cells were detected by intensity thresholding in the background-subtracted image, and the algorithm’s performance was tested on NeuN- and c-Fos-stained images in the mouse prefrontal cortex and hippocampal dentate gyrus. In addition, applications in c-Fos positive cell counting and the quantification for the expression level in double-labeled cells were demonstrated. Our method of automated detection after background assumption (ADABA) offers the advantage of high-throughput and unbiased analysis in regions with complex biological structures that produce inhomogeneous background.Highlights- We proposed a method to assume and subtract inhomogeneous background pattern.(79/85)- Cells were automatically detected in the background-subtracted image.(71/85)- The automated detection results corresponded with the manual detection.(73/85)- Detection of IEG positive cells and overlapping with neural marker were demonstrated.(85/85)
RID-Rihaczek Phase Synchrony Method Applied to Resting-State EEG: Simultaneous prediction of visuospatial tracking, verbal communication, executive function, neuro-cognitive health, and intelligence
Authors: Miyatsu Toshiya , Mahyari Arash , Rogala Jacek , Broderick Timothy , Pirolli Peter 
Published: November 2024

AbstractBrain activity at a resting state and functional connectivity represent individuals’ neural configurations that can be used to predict various performance and trait measures. Yet, most of the previous empirical demonstrations of this phenomena are limited to using resting-state neuroimaging to predict a single task performance/trait measure, and a few studies that predicted multiple task performance/traits measures employed conceptually similar tasks to produce converging evidence for their topic of investigation. In the current paper, we applied RID-Rihazcek phase synchrony, a nonlinear time-frequency-based method for neural computation, to resting-state EEG data and simultaneously predicted a wide variety of measures: standard shooting task performance and novel verbal communication-based team shooting task performance in a simulator, visuo-spatial tracking task performance (Neurotracker), executive function (verbal fluency task), fluid and crystalized Intelligence (Multidimensional Aptitude Battery II: MAB-II), and neurocognitive functioning (Automated Neuropsychological Assessment Metrics-4: ANAM-4) with the averageR2= .60. Our findings show great promise for RID-Rihazcek phase synchrony and resting-state EEG in general to be used in aptitude assessment.
Hormonal contraceptive intake during adolescence and cortical brain measures in the ABCD Study
Authors: Heller Carina , Dhamala Elvisha , Bottenhorn Katherine L. , Herting Megan M. , Bossé Brian , De La Rosa Jennifer S. , Farland Leslie V. , Allen Alicia M. , Barth Claudia , Petersen Nicole 
Published: November 2024

AbstractAdolescence is a critical period in human development, marked by rapid changes in brain structure and function, influenced, in part, by sex steroids. During adolescence, females may initiate the use of hormonal contraception, which suppresses ovarian production of estradiol and progesterone. Here, we examined the impact of hormonal contraceptive use on adolescent brain structures using magnetic resonance imaging data from 1,234 individuals from the ABCD Study (average age = 14 years). We investigated differences in cortical thickness, surface area, and volume in hormonal contraceptive-users compared to non-users. Statistically significant differences were observed in several regions, and differences in cortical thickness of the paracentral gyrus survived familywise error correction. Estradiol, testosterone and DHEA levels negatively correlated with cortical thickness, surface area, and volume across both hormonal contraceptive-users and non-users only at an uncorrected threshold. These findings highlight the need to further study longitudinal effects of hormonal contraceptives and endogenous hormone changes on brain development in the ABCD Study and related datasets as these data become available.
Cerebellar-Prefrontal Connectivity Predicts Negative Symptom Severity Across the Psychosis Spectrum
Authors: Yarrell Sean A. , Blyth Sophia H. , Rogers Baxter P. , Huang Anna , Moussa-Tooks Alexandra B. , Woodward Neil D. , Heckers Stephan , Brady Roscoe O. , Ward Heather Burrell 
Published: November 2024

AbstractBackgroundNegative symptom severity predicts functional outcome and quality life in people with psychosis. However, negative symptoms are poorly responsive to antipsychotic medication and existing literature has not converged on their neurobiological basis. Previous work in small schizophrenia samples has observed that lower cerebellar-prefrontal connectivity is associated with higher negative symptom severity and demonstrated in a separate neuromodulation experiment that increasing cerebellar-prefrontal connectivity reduced negative symptom severity. We sought to expand this finding to test associations between cerebellar-prefrontal connectivity with negative symptom severity and cognitive performance in a large, transdiagnostic sample of individuals with psychotic disorders.MethodsIn this study, 260 individuals with psychotic disorders underwent resting-state MRI and clinical characterization. Negative symptom severity was measured using the Positive and Negative Symptoms Scale, and cognitive performance was assessed with the Screen for Cognitive Impairment in Psychiatry. Using a previously identified cerebellar region as a seed, we performed seed to whole brain analyses and regressed connectivity against negative symptom severity, using age and sex as covariates.ResultsConsistent with prior work, we identified relationships between higher cerebellar-prefrontal connectivity and lower negative symptom severity (r=-0.17, p=.007). Higher cerebellar-prefrontal connectivity was also associated with better delayed verbal learning (r=.13, p=.034).ConclusionsOur results provide further evidence supporting the relationship between cerebellar-prefrontal connectivity and negative symptom severity and cognitive performance. Larger, randomized, sham-controlled neuromodulation studies should test if increasing cerebellar-prefrontal connectivity leads to reductions in negative symptoms in psychosis.
MOSAIC: A Pipeline for MicrobiOme Studies Analytical Integration and Correction
Authors: Fu Chenlian , Lu Jiuyao , Zhao Ni , Ling Wodan 
Published: November 2024

AbstractLarge-scale and consortium microbiome studies have enabled identification of reliable population-level biomedical signals, wherein integration is essential to eliminate unwanted variations between batches or studies and retain biological signals. Many strategies, each with distinct advantages and limitations, have been adapted or developed for microbiome data. The optimal strategy for a given study needs to be determined on a data-specific, case-by-case basis. Here, we develop the first-of-its-kind MicrobiOme Studies Analytical Integration and Correction (MOSAIC) pipeline to enable a convenient, fair, and comprehensive comparison of integration strategies. It includes modules for pre-processing, integration, and evaluation of artifact removal and signal preservation, using metrics relevant to common microbiome analyses, including alpha and beta diversities, disease prediction, and differential abundance analysis. We applied MOSAIC to extensive real-world and simulated data and found that though no single strategy excels in all aspects, yet certain strategies, the ComBat and ConQuR families, perform better overall.
Complex optogenetic spatial patterning with split recombinase
Authors: Kinstlinger Ian S. , Neu Erin M. , Mowry Shea K. , Tous Cristina , Kotton Darrell N. , Wong Wilson W. 
Published: November 2024

AbstractLight is a powerful and flexible input into engineered biological systems and is particularly well-suited for spatially controlling genetic circuits. While many light-responsive molecular effectors have been developed, there remains a gap in the feasibility of using them to spatially define cell fate. We addressed this problem by employing recombinase as a sensitive light-switchable circuit element which can permanently program cell fate in response to transient illumination. We show that by combining recombinase switches with hardware for precise spatial illumination, large scale heterogeneous populations of cells can be generatedin situwith high resolution. We envision that this approach will enable new types of multicellular synthetic circuit engineering where the role of initial cell patterning can be directly studied with both high throughput and tight control.
Biochemical, structural, and single-molecule characterization of LIG1 active site mutants demonstrate role of F635 and F872 residues for faithful ligation
Authors: Kalaycioğlu Mustafa , Gulkis Mitchell , Lee Kar Men , Chatterjee Surajit , Balu Kanal , Tang Qun , Ratcliffe Jacob E. , Castro Erick , Almahdor Danah , Çağlayan Melike 
Published: November 2024

AbstractHuman DNA ligase 1 (LIG1) finalizes DNA repair pathways by an ultimate ligation step and discriminates against nicks containing unusual ends, yet the contribution of the conserved active site residues for faithful end joining remains unknown. Here, using biochemistry, X-ray crystallography, and single-molecule approaches, we comprehensively characterized LIG1 mutants carrying Ala(A) and Leu(L) substitutions at the active site residues Phe(F)635 and Phe(F)872. Our results showed an abolished ligation of nick DNA substrates with all 12 non-canonical mismatches, while the mutagenic nick sealing of oxidatively damaged ends by wild-type enzyme is significantly reduced by F635A/L and F872A/L substitutions. Furthermore, sugar discrimination against a single ribonucleotide at 3’- or 5’-end of nick DNA is distinctly affected depending on architecture of 3’-terminus:template base pairing. Finally, our LIG1 structures demonstrated the importance of DNA end alignment governed by the distance to nick site through F635 and F872 residues, and single-molecule measurements showed similar nick DNA binding modes for LIG1 wild-type and active site mutants in real-time. Overall, our study provides a mechanistic insight into the mechanism by which conserved F635 and F872 residues contribute to ligation efficiency of nick repair intermediates that mimic DNA polymerase-mediated mismatch, damaged, or ribonucleotide insertion products and how LIG1 ensures faithful end joining at the final step of DNA repair to maintain genome integrity.
DNA StairLoop: Achieving High Error-correcting and Parallel-processing Capabilities in DNA-based Data Storage
Authors: Yan Zihui , Qu Guanjin , Chen Xin , Zheng Gang , Wu Huaming 
Published: November 2024

AbstractDNA-based data storage is a promising solution to the challenges of large-scale data storage. However, the low throughput of the mainstream inkjet-based DNA synthesis method has hindered its widespread adoption. In contrast, high-throughput electrochemical synthesis provides higher throughput but with more nucleotide insertion, deletion, and substitution errors. Here, we propose an innovative coding scheme with high error correction capabilities, called DNA StairLoop. This coding scheme features a staircase interleaver and allows for component codes such as the convolutional code and the ow-density Parity-check code, allowing for flexible adaptation of the coding scheme. Both the row and the column decoders are soft input and soft output, enabling further improvement in data recovery accuracy through iterative decoding. The staircase interleaver facilitates extensive parallel decoding capabilities while effectively preserving parallelism across a multitude of nodes. In the in vitro experiment, DNA StairLoop successfully recovered the raw information in a staircase block with a nucleotide error rate of more than 8%. The simulations revealed that the DNA StairLoop can correct 10% nucleotide errors. Moreover, in parallel computing processing, the decoding time of our code continues to decrease dramatically.
Reliability of large language model knowledge across brand and generic cancer drug names
Authors: Gallifant Jack , Chen Shan , Jain Sandeep K. , Moreira Pedro , Topaloglu Umit , Aerts Hugo JWL , Warner Jeremy L. , Cava William G. La , Bitterman Danielle S. 
Published: November 2024

AbstractPurposeTo evaluate the performance and consistency of large language models (LLMs) across brand and generic oncology drug names in various clinical tasks, addressing concerns about potential fluctuations in LLM performance due to subtle phrasing differences that could impact patient care.MethodsThis study evaluated three LLMs (GPT-3.5-turbo-0125, GPT-4-turbo, and GPT-4o) using drug names from the HemOnc ontology. The assessment included 367 generic-to-brand and 2,516 brand-to-generic pairs, 1,000 drug-drug interaction synthetic patient cases, and 2,438 immune-related adverse event (irAE) cases. LLMs were tested on drug name recognition, word association, drug-drug interaction (DDI) detection, and irAE diagnosis using both brand and generic drug names.ResultsLLMs demonstrated high accuracy in matching brand and generic names (GPT-4o: 97.38% for brand, 94.71% for generic, p < 0.0001). However, they showed significant inconsistencies in word association tasks. GPT-3.5-turbo-0125 exhibited biases favoring brand names for effectiveness (OR 1.43, p < 0.05) and being side-effect-free (OR 1.76, p < 0.05). DDI detection accuracy was poor across all models (<26%), with no significant differences between brand and generic names. Sentiment analysis revealed significant differences, particularly in GPT-3.5-turbo-0125 (brand mean 0.6703, generic mean 0.9482, p < 0.0001). Consistency in irAE diagnosis varied across models.Conclusions and RelevanceDespite high proficiency in name-matching, LLMs exhibit inconsistencies when processing brand versus generic drug names in more complex tasks. These findings highlight the need for increased awareness, improved robustness assessment methods, and the development of more consistent systems for handling nomenclature variations in clinical applications of LLMs.Context SummaryKey objectiveThis study aimed to assess the consistency of large language models (LLMs) in handling brand and generic oncology drug names across various tasks, including drug-drug interaction detection and adverse event identification.Knowledge generatedLLMs demonstrated high accuracy in matching brand and generic names but showed significant inconsistencies in more complex tasks. Notable, models exhibited significant differences in attributing brand versus generic names to positive terms and sentiment.
Decoding the biology of ethnic differences in asthma
Authors: Ni Duan , Nanan Ralph 
Published: November 2024

AbstractEthnicity seems to be a risk factor for asthma and its exacerbation, but no general consensus has been reached so far. Ethnic diversity and differences have long been overlooked and most studies in these regards are observational, lacking in-depth mechanistic insights.Harnessing comprehensive transcriptomic data at organ system and single cell levels, we comparatively analyzed the signalling landscapes of African American/Black (AA) and other ethnicities. In healthy individuals, most AA PBMC subsets exhibited elevated IL2-STAT5 signals, which is critically implicated in asthma pathogenesis. This extended to various compartments (bronchial and airway epithelium, circulating CD4+T cells and blood) in asthma, where AA upregulated IL2-STAT5 pathway relative to other ethnicities. Mechanistically, the increased IL2-STAT5 signalling correlated with enhanced T cell migration and recruitment. Together, they might contribute to the greater predisposition towards asthma exacerbation in AA.This first-of-its-kind study sheds some in-depth insights into the biology of ethnic differences in asthma. Our findings, if further validated, will be valuable for future asthma research and clinical practice like therapeutic development and treatment guidance, highlighting the need for ethnicity diversity and inclusions in these areas.
Sex-specific risk of smoking for abdominal aortic aneurysm and exploration of potential mechanism: meta-analysis and prospective cohort study
Authors: Welsh Paul , Pouncey Anna-Louise , Powell Janet T 
Published: November 2024

AbstractBackgroundSmoking is the strongest modifiable risk factor for abdominal aortic aneurysm (AAA). This study aims to confirm whether smoking is a stronger risk factor in women than men and identify contributory reasons, including inflammation, for any sex-specific difference observed.MethodsSystematic review and meta-analysis, conducted according to PRISMA guidance (Prospero registration (CRD2024586609)). Data sources were Medline, Embase, and CENTRAL. Population-based studies reporting risk of AAA, adjusted for age and cardiovascular risk factors, for women versus men, were included. These were complemented by data from the UK Biobank (UKB) cohort, which also were assessed for sex-specific effects of smoking on incident atherosclerotic cardiovascular disease (ASCVD). Results: Meta-analysis of 6 studies (including UKB), 2001-2024) showed that the relative risk ratio of current versus never-smokers for incident AAA in women versus men was 1.78 [95%CI 1.32, 2.38]. Comparison of the sex-specific relative risks of current smoking and number of cigarettes/day were similar in the UKB cohort and these risks were much higher for AAA than for ASCVD, but the risks of pack-years were similar. Sex-specific risks of current smoking for AAA were not significantly modified by inflammatory markers (including C-reactive protein, alkaline phosphatase and white blood cell count), lung function or physical activity. Stopping smoking reduced the risk of AAA by almost half in both sexes. Conclusions: The risk of developing AAA by current smokers is almost twice as high in women versus men. Inflammation was not a major modifier and other reasons for the disparity must be sought.