bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical Assessment of a Plasma AT(N) Panel for Alzheimer’s Disease
Authors: Collier Bradley B. , Chappell Matthew R. , Brandon Whitney C. , Le Tien , Harris Ayla B. , Volpe Joseph M. , Martone Robert , Winslow John W. , Boles Deborah , Valcour Andre , Grant Russell P. 
Published: August 2024

1.AbstractImportanceWith the emergence of new therapeutics for treatment of Alzheimer’s disease, there is currently a critical need for sensitive and accurate blood-based tests to assist with the diagnosis and treatment of Alzheimer’s disease.ObjectiveTo determine the clinical validity of an analytically validated plasma panel for the assessment of Alzheimer’s disease.Design, Setting, and ParticipantsThis cross-sectional study measured biomarkers representative of the Alzheimer’s disease AT(N) framework in 200 plasma specimens acquired from the Australian Imaging, Biomarker & Lifestyle (AIBL) Study of Ageing. Specimens were obtained from amyloid PET negative subjects classified as cognitively unimpaired (n = 75) and amyloid PET positive subjects classified as having no cognitive impairment (n = 49), mild cognitive impairment (n = 26), or Alzheimer’s disease dementia (n = 50).ExposuresAmyloid PET and plasma Aβ42/40, pTau181, and NfL.Main Outcomes and MeasuresTo assess the utility of the plasma panel to assess onset and progression of Alzheimer’s disease with respect to amyloid PET results and cognitive impairment.ResultsA difference was observed for each assay with respect to amyloid status (p<0.0001). Receiver operating characteristic (ROC) analysis of clinical specimen results from validated assays produced an area-under-the-curve (AUC) of 0.941 for Aβ42/40, 0.847 for pTau181, and 0.666 for NfL (p < 0.0001 for all biomarkers). The sensitivity (96.0%) and specificity (86.7%) observed for Aβ42/40 measurements meets current recommendations for triage testing. In addition, plasma levels of pTau181 and NfL were also found to increase with worsening cognitive impairment.Conclusions and RelevanceThe clinical concordance with amyloid PET for each biomarker is consistent with the biological progression of the AD continuum. As such, the availability of this AT(N) panel will provide clinicians with a simple blood-based means to provide evidence of AD pathological changes and could help identify AD patients much faster, shorten the overall AD patient diagnostic journey, and enable earlier treatment interventions.
HuTAge: a Comprehensive Human Tissue- and Cell-specific Ageing Signature Atlas
Authors: Himori Koichi , Bingyuan Zhang , Hatta Kazuki , Matsui Yusuke 
Published: August 2024

AbstractSummaryAgeing is a complex process that involves interorgan and intercellular interactions. To obtain a clear understanding of ageing, cross-tissue single-cell data resources are required. However, a complete resource for humans is not available. To bridge this gap, we developed HuTAge, a comprehensive resource that integrates cross-tissue age-related information from The Genotype-Tissue Expression project with cross-tissue single-cell information from Tabula Sapiens to provide human tissue- and cell-specific ageing molecular information.Availability and ImplementationHuTAge is implemented within an R Shiny application and can be freely accessed athttps://igcore.cloud/GerOmics/HuTAge/home. The source code is available athttps://github.com/matsui-lab/HuTAge.Contacthimori.koichi.b5@f.mail.nagoya-u.ac.jp
All-Diamond Boron-Doped Microelectrodes for Neurochemical Sensing with Fast-Scan Cyclic Voltammetry
Authors: Gupta Bhavna , Kepros Brandon , Landgraf Jann B. , Becker Michael F. , Li Wen , Purcell Erin K. , Siegenthaler James R. 
Published: August 2024

AbstractNeurochemical sensing with implantable devices has gained remarkable attention over the last few decades. A promising area of this research is the progress of novel electrodes as electrochemical tools for neurotransmitter detection in the brain. The boron-doped diamond (BDD) electrode is one such candidate that previously has been reported for its excellent electrochemical properties, including a wide working potential, superior chemical inertness and mechanical stability, good biocompatibility and resistance to fouling. Meanwhile, limited research has been conducted on the BDD as a microelectrode for neurochemical detection. Our team has developed a freestanding, all diamond microelectrode consisting of a boron-doped polycrystalline diamond core, encapsulated in an insulating polycrystalline diamond shell, with a cleaved planar tip for electrochemical sensing. This all-diamond electrode is advantageous due to its – (1) batch fabrication using wafer technology that eliminates traditional hand fabrication errors and inconsistencies, (2) absence of metal-based wires, or foundations, to improve biocompatibility and flexibility, and (3) sp3carbon surface with resistance to biofouling, i.e. adsorption of proteins or unwanted molecules at the electrode surface in a biological environment that impedes overall electrode performance. Here, we provide findings on further in vitro testing and development of the freestanding boron-doped diamond microelectrode (BDDME) for neurotransmitter detection using fast scan cyclic voltammetry (FSCV). In this report, we elaborate on – 1) an updated fabrication scheme and work flow to generate all diamond BDDMEs, 2) slow scan cyclic voltammetry measurements of reference and target analytes to understand basic electrochemical behavior of the electrode, and 3) FSCV characterization of common neurotransmitters, and overall favorability of serotonin (5-HT) detection. The BDDME showed a 2-fold increased FSCV response for 5-HT in comparison to dopamine (DA), with a limit of detection of 0.16 µM for 5-HT and 0.26 µM for DA. These results are intended to expand on the development of the next generation BDDME and guide future in vivo experiments, adding to the growing body of literature on implantable devices for neurochemical sensing.
Material Properties Of The Embryonic Small Intestine During Buckling Morphogenesis
Authors: Gao Jenny , Martin Lucia , Loffet Elise A. , Durel John F. , Oikonomou Panagiotis , Nerurkar Nandan L. 
Published: August 2024

AbstractDuring embryonic development, tissues undergo dramatic deformations as functional morphologies are stereotypically sculpted from simple rudiments. Formation of healthy, functional organs therefore requires tight control over the material properties of embryonic tissues during development, yet the biological basis of embryonic tissue mechanics is poorly understood. The present study investigates the mechanics of the embryonic small intestine, a tissue that is compactly organized in the body cavity by a mechanical instability during development, wherein differential elongation rates between the intestinal tube and its attached mesentery create compressive forces that buckle the tube into loops with wavelength and curvature that are tightly conserved for a given species. Focusing on the intestinal tube, we combined micromechanical testing with histologic analyses and enzymatic degradation experiments to conclude that elastic fibers closely associated with intestinal smooth muscle layers are responsible for the bending stiffness of the tube, and for establishing its pronounced mechanical anisotropy. These findings provide insights into the developmental role of elastic fibers in controlling tissue stiffness, and raise new questions on the physiologic function of elastic fibers in the intestine during adulthood.GRAPHICAL ABSTRACT
Epigenetic clock and lifespan prediction in the short-lived killifishNothobranchius furzeri
Authors: Giannuzzi Chiara , Baumgart Mario , Neri Francesco , Cellerino Alessandro 
Published: August 2024

AbstractAging, characterized by a gradual decline in organismal fitness, is the primary risk factor for numerous diseases including cancer, cardiovascular, and neurodegenerative disorders. The inter-individual variability in aging and disease susceptibility has led to the concept of “biological age,” an indirect measure of an individual’s relative fitness. Epigenetic changes, particularly DNA methylation, have emerged as reliable biomarkers for estimating biological age, leading to the development of predictive models known as epigenetic clocks. Initially created for humans, these clocks have been extended to various mammalian species. Here we set to expand these tools for the short-lived killifish,Nothobranchius furzeri. This species, with its remarkably short lifespan and expression of canonical aging hallmarks, offers a unique model for experimental aging studies.We developed an epigenetic clock forN. furzeriusing reduced-representation bisulfite sequencing (RRBS) to analyze DNA methylation in brain and caudal fin tissues across different ages. Our study involved generating comprehensive DNA methylation datasets and employing machine learning to create predictive models based on individual CpG sites and co-methylation modules. These models demonstrated high accuracy in estimating chronological age, with a median absolute error of 3 weeks (7.5% of median lifespan) for a clock based on methylation of individual CpG and 1.5 weeks (3.7% of median lifespan) for an eigenvector-based clock.Our investigation extended to assessing epigenetic age acceleration in different strains and the potential resetting effect of regeneration on fin tissue. Notably, our models indicated that a shorter-lived strain has accelerated epigenetic aging and that regeneration does not reset, but may decelerate epigenetic aging. Additionally, we used longitudinal data to develop an “epigenetic timer” for direct prediction of individual lifespan based on fin biopsies and eigenvector-based method, achieving a median absolute error of 4.5 weeks in the prediction of actual age of death. This surprising result underscores the existence of intrinsic determinants of lifespan established early in life.This study presents the first epigenetic clocks and lifespan predictors forN. furzeri, highlighting their potential as aging biomarkers and sets the stage for future research on life-extending interventions in this model organism.
CRISPR-Cas9 mediated deletions ofFvMYB46reduces fruit set and biosynthesis of flavonoids inFragaria vesca
Authors: Rai Arti , Skårn Magne Nordang , Elameen Abdelhameed , Tengs Torstein , Amundsen Mathias Rudolf , Bjorå Oskar S. , Haugland Lisa K. , Yakovlev Igor A. , Brurberg May Bente , Thorstensen Tage 
Published: August 2024

AbstractSecondary metabolites produced by the phenylpropanoid pathway, which is regulated by transcription factors of the MYB family, play crucial roles in this early phase of fruit development. The MYB46 transcription factor is a key regulator of secondary cell wall structure and lignin and flavonoid biosynthesis in many plants, but little is known about its activity in flowers and berries inF. vesca. For functional analysis of FvMYB46, we designed a CRISPR-Cas9 construct with an endogenousF. vescaspecific U6-promoter for efficient and specific expression of two gRNAs targeting the first exon ofFvMYB46. This generated mutants with an in frame 81-bp deletion of the first conserved MYB-domain or an out of frame 82-bp deletion potentially knocking out the gene function. In both types of mutant plants, pollen germination and the frequency of flowers developing to mature berries was significantly reduced compared to wild type. Transcriptomic analysis of flowers demonstrated that FvMYB46 is positively regulating the expression of genes involved in pollen germination, homeostasis of reactive oxygen species (ROS) and the phenylpropanoid pathway, including secondary cell wall biosynthesis and flavonoid biosynthesis, while has a negative impact on carbohydrate metabolism. In FvMYB46-mutant flowers, the flavonols and flavan-3-olscontent, especially epicatechin, quercetin-glucoside and kaempferol-3-coumaroylhexoside were reduced, and we observed a local reduction of lignin content in anthers. Together these results suggest that MYB46 control fertility and efficient fruit set by regulating cell wall structure, flavonoid biosynthesis, carbohydrate metabolism and ROS-signaling in flowers and early fruit development inF. vesca.
Conclusions about Neural Network to Brain Alignment are Profoundly Impacted by the Similarity Measure
Authors: Soni Ansh , Srivastava Sudhanshu , Kording Konrad , Khosla Meenakshi 
Published: August 2024

AbstractDeep neural networks are popular models of brain activity, and many studies ask which neural networks provide the best fit. To make such comparisons, the papers use similarity measures such as Linear Predictivity or Representational Similarity Analysis (RSA). It is often assumed that these measures yield comparable results, making their choice inconsequential, but is it? Here we ask if and how the choice of measure affects conclusions. We find that the choice of measure influences layer-area correspondence as well as the ranking of models. We explore how these choices impact prior conclusions about which neural networks are most “brain-like”. Our results suggest that widely held conclusions regarding the relative alignment of different neural network models with brain activity have fragile foundations.
HLA polymorphism impacts immune response to neoepitopes and survival in APOBEC-mutated cancers
Authors: Borzooee Faezeh , Heravi-Moussavi Alireza , Larijani Mani 
Published: August 2024

SummaryAPOBEC3A and APOBEC3B genome mutators drive tumor evolution and drug resistance but may also generate neoepitopes for cytotoxic T cells (CTL). Given the extensive polymorphism of Class I HLA, the CTL immunopeptidome, comprised of all 8-11mer peptides presented by an individual’s six HLA class I alleles, varies person-to-person. We predicted the genome-wide impact of APOBEC3A/B-driven mutations on the immunogenicity of the immunopeptidomes of several thousand class I HLA alleles. Analysis of several billion APOBEC3-mediated mutations revealed that HLA class I alleles vary markedly in the susceptibility of their immunopeptidome to mutations. A subset of alleles of A1-A3 and B44 supertype supported increased neoepitopes. Notably, the immunogenicity changes supported by an individual’s HLA class I alleles in response to APOBEC3 mutations predict survival in APOBEC3-mutated tumors and correlate with CTL activation. Thus, immunogenicity changes mediated by APOBEC3s impact survival, making HLA class I genotype a prognostic marker in APOBEC3-mutated tumors.
Resurrection of the Plant Immune Receptor Sr50 to Overcome Pathogen Immune Evasion
Authors: Seong Kyungyong , Wei Wei , Sent Sophie C , Vega Brandon , Dee Amanda , Ramirez-Bernardino Griselda , Kumar Rakesh , Parra Lorena , Saur Isabel ML , Krasileva Ksenia 
Published: August 2024

AbstractPathogen-driven plant diseases cause significant crop losses worldwide. The introgression of intracellular nucleotide-binding leucine-rich repeat receptor (NLR) genes into elite crop cultivars is a common strategy for disease control, yet pathogens rapidly evolve to evade NLR-mediated immunity. The NLR geneSr50protects wheat against stem rust, a devastating disease caused by the fungal pathogenPuccinia graminisf. sp.tritici(Pgt). However, mutations in AvrSr50 allowedPgtto evade Sr50 recognition, leading to resistance breakdown. Advances in protein structure modeling can enable targeted NLR engineering to restore recognition of escaped effectors. Here, we combined iterative computational structural analyses and site-directed mutagenesis to engineer Sr50 recognition of AvrSr50QCMJC, aPgteffector variant that evades wild-type Sr50 detection. Derived by molecular docking, our initial structural model identified the K711D substitution in Sr50, which partially restored AvrSr50QCMJCrecognition. Enhancing Sr50K711Dexpression via strong promoters compensated for weak recognition and restored robust immune responses. Further structural refinements led to the generation of five double and two triple receptor mutants. These engineered mutants, absent in nature, showed robust dual recognition for AvrSr50 and AvrSr50QCMJCin bothNicotiana benthamianaand wheat protoplasts. Notably, the K711D substitution was essential and synergistic with the additional substitutions for AvrSr50QCMJCrecognition, demonstrating protein epistasis. Furthermore, this single substitution altered AlphaFold 2 predictions, enabling accurate modeling of the Sr50K711D–AvrSr50 complex structure, consistent with our final structural hypothesis. Collectively, this study outlines a framework for NLR engineering to counteract pathogen adaptation and provides novel Sr50 variants with potential for stem rust resistance.
Insights into the role of dopamine in rhizosphere microbiome assembly
Authors: Ding Yezhang , Vogel Hunter K. , Zhai Yi , Carlson Hans K. , Andeer Peter F. , Novak Vlastimil , Kim Nakian , Bowen Benjamin P. , Golini Amber N. , Kosina Suzanne M. , Coleman-Derr Devin , Vogel John P. , Northen Trent R. 
Published: August 2024

AbstractDopamine plays a critical role in animal physiology and interactions with gut microbes. In plants, dopamine is known to function in plant defense and abiotic stress tolerance; however, its role in mediating plant-microbiome interactions remains unexplored. In this study, we observed that dopamine is one of the most abundant exometabolites with natural variation in root exudates across diverseBrachypodium distachyonlines, suggesting a potential role in rhizosphere microbial assembly. To further investigate this, we colonized ten naturalB. distachyonlines with a 16-member bacterial synthetic community (SynCom), collected paired metabolomic and 16S rRNA sequencing data, and performed an association analysis. Our results revealed that dopamine levels in root exudates were significantly associated with the abundance of six SynCom members in a hydroponic system.In vitrogrowth studies demonstrated that dopamine had a significant effect on the growth of the same six bacterial isolates. Additionally, treating soil directly with dopamine enriched Actinobacteria, consistent with both the SynCom-dopamine correlations and the isolate growth results. Collectively, our study underscores the selective influence of dopamine on rhizosphere microbial communities, with implications for precision microbiome management.
Optimizing the detection of biological signals through a semi-automated feature selection tool
Authors: Arini Gabriel Santos , Mencucin Luiz Gabriel , de Felício Rafael , Feitosa Luís Guilherme Pereira , Rezende-Teixeira Paula , Tsuji Henrique , Pilon Alan , Pinho Danielle Rocha , Costa-Lotufo Letícia Veras , Lopes Norberto Peporine , Trivella Daniela Barretto Barbosa , da Silva Ricardo Roberto 
Published: August 2024

AbstractUntargeted metabolomics is often used in studies that aim to trace the metabolic profile in a broad context, with the data-dependent acquisition (DDA) mode being the most commonly used method. However, this approach has the limitation that not all detected ions are fragmented in the data acquisition process, in addition to the lack of specificity regarding the process of fragmentation of biological signals. The present work aims to extend the detection of biological signals and contribute to overcoming the fragmentation limits of the DDA mode with a dynamic procedure that combines experimental and in silico approaches. Metabolomic analysis was performed on three different species of actinomycetes using liquid chromatography coupled to mass spectrometry. The data obtained were preprocessed by the MZmine software and processed by the custom package, RegFilter. RegFilter allowed the coverage of the entire chromatographic run and the selection of precursor ions for fragmentation that were previously missed in DDA mode. Most of the ions selected by the tool could be annotated through three levels of annotation, presenting biological relevant candidates. In addition, the tool offers the possibility of creating local spectral libraries curated according to the user’s interests. Thus, the adoption of a dynamic analysis flow using RegFilter allowed for detection optimization of biological signals, previously absent in the DDA mode. In addition, this workflow enables the creation and search of in-house tailored custom libraries.
Causal modeling in large-scale data to improve identification of adults at risk for combined and common variable immunodeficiencies
Authors: Papanastasiou Giorgos , Scutari Marco , Tachdjian Raffi , Hernandez-Trujillo Vivian , Raasch Jason , Billmeyer Kaylyn , Vasilyev Nikolay V , Ivanov Vladimir 
Published: August 2024

AbstractCombined immunodeficiencies (CID) and common variable immunodeficiencies (CVID), prevalent yet substantially underdiagnosed primary immunodeficiency disorders, necessitate improved early detection strategies. Leveraging large-scale electronic health record (EHR) data from four nationwide US cohorts, we developed a novel causal Bayesian Network (BN) model to unravel the complex interplay of antecedent clinical phenotypes associated with CID/CVID. Consensus directed acyclic graphs (DAGs) were constructed, which demonstrated robust predictive performance (ROC AUC in unseen data within each cohort ranged from 0.77-0.61) and generalizability (ROC AUC across all unseen cohort evaluations ranged from 0.72-0.56) in identifying CID/CVID across diverse patient populations, created using different inclusion criteria. These consensus DAGs elucidate causal relationships between comorbidities preceding CID/CVID diagnosis, including autoimmune and blood disorders, lymphomas, organ damage or inflammation, respiratory conditions, genetic anomalies, recurrent infections, and allergies. Further evaluation through causal inference and by expert clinical immunologists substantiates the clinical relevance of the identified phenotypic trajectories within the consensus DAGs. These findings hold promise for translation into improved clinical practice, potentially leading to earlier identification and intervention for adults at risk of CID/CVID.
Disruption of outdoor activities caused by wildfires increases disease circulation
Authors: Arregui-Garcıa Beatriz , Ascione Claudio , Pera Arianna , Wang Boxuan , Stocco Davide , Carlson Colin J. , Bansal Shweta , Valdano Eugenio , Pullano Giulia 
Published: August 2024

AbstractAlthough climate change poses a well-established risk to human health, present-day health impacts, particularly those resulting from climate-induced behavioral changes, are under-quantified. Analyzing the U.S. West Coast wildfires of September 2020, we found that poor air quality drives people indoors, increasing the circulation of airborne pathogens like COVID-19. Indoor masking rates as low as 10% can mitigate this risk, offering a clear path to enhance public health responses during wildfires.