bluuebunny/crossref_metadata_2025_split huggingface dataset:
Verbal fluency tests assess global cognitive status but have limited diagnostic differentiation: Evidence from a large-scale examination of six neurodegenerative diseases
Authors: Henderson Shalom K. , Peterson Katie A. , Patterson Karalyn , Lambon Ralph Matthew A. , Rowe James B. 
Published: August 2022

AbstractObjectiveVerbal fluency is clinically widely used but its utility in differentiating between neurodegenerative dementias and progressive aphasias, and from healthy controls, remains unclear. We assessed whether the total number of words produced, their psycholinguistic properties, and production order effects could differentiate between Alzheimer’s disease (AD), behavioural variant of frontotemporal dementia (bvFTD), non-fluent and semantic variants of primary progressive aphasia (PPA), progressive supranuclear palsy (PSP), corticobasal syndrome (CBS), and healthy controls.MethodsCategory and letter fluency tasks were administered to 33 controls and 139 patients at their baseline clinical visit: 18 AD, 16 bvFTD, 26 nfvPPA, 26 svPPA, 36 PSP, and 17 CBS. We assessed group differences for total words, psycholinguistic word properties, and associations between production order and exemplar psycholinguistic properties. Receiver Operating Characteristic (ROC) curves determined which measure could best discriminate patient groups and controls.ResultsTotal word count distinguished controls from all patient groups, but neither this measure nor the word properties differentiated the patient groups. ROC curves revealed that, when comparing controls to patients, the strongest discriminators were total word count followed by word frequency. Word frequency was the strongest discriminator for svPPA versus other groups. Fluency word counts were associated with global severity as measured by Addenbrooke’s Cognitive Examination-Revised (ACE-R).ConclusionsVerbal fluency is an efficient test for assessing global brain-cognitive health but has limited utility in differentiating between cognitively- and anatomically-disparate patient groups. This outcome is consistent with the fact that verbal fluency requires many different aspects of higher cognition and language.
Exogenous sequences in tumors and immune cells (exotic): a tool for estimating the microbe abundances in tumor RNAseq data
Authors: Hoyd Rebecca , Wheeler Caroline E , Liu YunZhou , Singh Malvenderjit Jagjit , Muniak Mitchell , Denko Nicolas , Carbone David , Mo Xiaokui , Spakowicz Daniel 
Published: August 2022

AbstractThe microbiome affects cancer, from carcinogenesis to response to treatments. New evidence suggests that microbes are also present in many tumors, though the scope of how they affect tumor biology and clinical outcomes is unclear. A broad survey of tumor microbiome samples across several independent datasets is needed to identify robust correlations for follow-up testing. We created a tool to carefully identify the tumor microbiome within RNAseq datasets and then applied it to samples collected through the Oncology Research Information Exchange Network (ORIEN) and The Cancer Genome Atlas (TCGA). We showed how the processing removes contaminants and batch effects to yield microbe abundances consistent with non-high-throughput sequencing-based approaches. We sought to establish clinical relevance by correlating the microbe abundances with various clinical and tumor measurements, such as age and tumor hypoxia. This process leveraged the two datasets and raised up only the concordant (significant and in the same direction) associations. We identify associations with survival and clinical variables that are highly cancer-specific and relatively few associations with immune composition. Finally, we explore potential mechanisms by which microbes and tumors may interact using a network approach. Alistipes, a common gut commensal, showed the highest network degree centrality and was associated with genes related to metabolism and inflammation. The exotic tool can support the discovery of microbes in tumors in a way that leverages the many existing and growing RNAseq datasets.Statement of SignificanceThe intrinsic tumor microbiome holds great potential for its ability to predict various aspects of cancer biology and as a target for rational manipulation. Here, we describe a tool to quantify microbes from within tumor RNAseq and apply it to two independent datasets. We show new associations with clinical variables that justify biomarker uses and more experimentation into the mechanisms by which tumor microbiomes affect cancer outcomes.
A Neural Index Reflecting the Amount of Cognitive Resources Available during Memory Encoding: A Model-based Approach
Authors: Ma Si , Popov Vencislav , Zhang Qiong 
Published: August 2022

AbstractHumans have a limited amount of cognitive resources to process various cognitive operations at a given moment. The Source of Activation Confusion (SAC) model of episodic memory proposes that resources are consumed during each processing and once depleted they need time to recover gradually. This has been supported by a series of behavioral findings in the past. However, the neural substrate of the resources is not known. In the present study, over an existing EEG dataset of a free recall task (Kahana et al., 2022), we provided a neural index reflecting the amount of cognitive resources available for forming new memory traces. Unique to our approach, we obtained the neural index not through correlating neural patterns with behavior outcomes or experimental conditions, but by demonstrating its alignment with a latent quantity of cognitive resources inferred from the SAC model. In addition, we showed that the identified neural index can be used to propose novel hypothesis regarding other long-term memory phenomena. Specifically, we found that according to the neural index, neural encoding patterns for subsequently recalled items correspond to greater available cognitive resources compared with that for subsequently unrecalled items. This provides a mechanistic account for the long-established subsequent memory effects (SMEs, i.e. differential neural encoding patterns between subsequently recalled versus subsequently unrecalled items), which has been previously associated with attention, fatigue and properties of the stimuli.
Transcriptomic and epigenetic assessment of ageing male skin identifies disruption of Ca2+homeostasis; exacerbated by smoking and UV exposure
Authors: Pease Louise I. , Wordsworth James , Shanley Daryl 
Published: August 2022

ABSTRACTSkin ageing has been widely associated with the formation and presence of increasing quantities of senescent cells, the presence of which are thought to reduce cell renewal. This study aimed to identify key factors influencing fibroblast and skin aging in European males using RNA-seq data. Key differences in study designs included known sources of biological differences (sex, age, ethnicity), experimental differences, and environmental factors known to accelerate skin ageing (smoking, UV exposure) as well as study specific batch effects which complicated the analysis. To overcome these complications samples were stratified by these factors and differential expression assessed using Salmon and CuffDiff. Functional enrichment and consistency across studies, stratification’s and tools identified age related alterations in the transcriptomes of fibroblasts and skin. Functional enrichment of results identified alterations in protein targeting to membranes and the ER, and altered calcium homeostasis in aged fibroblasts. Extension to skin controlled for differences in fibroblast culturing methods confirming transient age related alterations in intracellular calcium homeostasis. In middle aged males (40-65) increased keratinisation, skin, epithelial and epidermal development was seen in conjunction with alterations to ER Ca2+uptake, leading to the identification of related processes including; an unfolded protein response, altered metabolism, increased MMP expression, and altered Ca2+handling, which were further exacerbated by UV-exposure. Interestingly the genes and processes subsequently decreased in old males (> 65), which exhibited signs of increased senescence. Extension to Illumina 450k array data from ageing skin uncovered evidence of epigenetic regulation; genes and isoforms with overlapping differentially methylated CpGs were differentially expressed. Smoking led to additional enrichment of genes relating to tissue development, cell adhesion, vasculature development, peptide cross-linking, calcium homeostasis, cancer and senescence. The results consistently identified alterations in ER and golgi Ca2+uptake, which disrupt intracellular and extracellular calcium gradients that regulate metabolic and differentiation signalling in skin and fibroblasts, leading to age related declines skin structure and function. Interestingly many diseases and infections with overlapping molecular consequences, (ER Ca2+stress, reduced protein targeting to membranes) including COVID-19 are identified by the analysis, suggesting that COVID-19 infection compounds pre-existing cellular stresses in aged males, which could help explain higher COVID-19 mortality rates in aged males, as well as highlighting potential ways to reduce them.
Probe set selection for targeted spatial transcriptomics
Authors: Kuemmerle Louis B. , Luecken Malte D. , Firsova Alexandra B. , de Andrade e Sousa Lisa Barros , Straßer Lena , Heumos Lukas , Mekki Ilhem Isra , Mahbubani Krishnaa T. , Sountoulidis Alexandros , Balassa Tamás , Kovacs Ferenc , Horvath Peter , Piraud Marie , Ertürk Ali , Samakovlis Christos , Theis Fabian J. 
Published: August 2022

AbstractTargeted spatial transcriptomics methods capture the topology of cell types and states in tissues at single cell- and subcellular resolution by measuring the expression of a predefined set of genes. The selection of an optimal set of probed genes is crucial for capturing and interpreting the spatial signals present in a tissue. However, current selections often rely on marker genes, precluding them from detecting continuous spatial signals or novel states. We present Spapros, an end-to-end probe set selection pipeline that optimizes both probe set specificity for cell type identification and within-cell-type expression variation to resolve spatially distinct populations while taking into account prior knowledge, as well as probe design and expression constraints. To facilitate data analysis and interpretation, Spapros also provides rules for cell type identification. We evaluated Spapros by selecting probes on 6 different data sets and built an evaluation pipeline with 12 quality metrics to find that Spapros outperforms other selection approaches in both cell type recovery and recovering expression variation beyond cell types. Furthermore, we used Spapros to design a SCRINSHOT experiment of adult lung tissue to demonstrate how probes selected with Spapros identify cell types of interest and detect spatial variation even within cell types. Spapros enables optimal probe set selection, probe set evaluation, and probe design, as a freely available Python package.
Red blood cell lingering modulates hematocrit distribution in the microcirculation
Authors: Rashidi Yazdan , Simionato Greta , Zhou Qi , John Thomas , Kihm Alexander , Bendaoud Mohammed , Krüger Timm , Bernabeu Miguel O. , Kaestner Lars , Laschke Matthias W. , Menger Michael D. , Wagner Christian , Darras Alexis 
Published: August 2022

AbstractThe distribution of red blood cells (RBCs) in the microcirculation determines the oxygen delivery and solute transport to tissues. This process relies on the partitioning of RBCs at successive bifurcations throughout the microvascular network and it is known since the last century that RBCs partition disproportionately to the fractional blood flow rate, therefore leading to heterogeneity of the hematocrit (i.e. volume fraction of RBCs in blood) in microvessels. Usually, downstream of a microvascular bifurcation, the vessel branch with a higher fraction of blood flow receives an even higher fraction of RBC flux. However, both temporal and time-average deviations from this phaseseparation law have been observed in recent works. Here, we quantify how the microscopic behavior of RBCs lingering (i.e. RBCs temporarily residing near the bifurcation apex with diminished velocity) influences their partitioning, through combined in vivo experiments and in silico simulations. We developed an approach to quantify the cell lingering at highly-confined capillary-level bifurcations and demonstrate that it correlates with deviations of the phase-separation process from established empirical predictions by Pries et al. Furthermore, we shed light on how the bifurcation geometry and cell membrane rigidity can affect the lingering behavior of RBCs, e.g. rigid cells tend to linger less than softer ones. Taken together, RBC lingering is an important mechanism that should be considered when studying how abnormal RBC rigidity in diseases such as malaria and sickle-cell disease could hinder the microcirculatory blood flow or how the vascular networks are altered under pathological conditions (e.g. thrombosis, aneurysm).
Enhanced methionine cycle suppresses naïve CD8+ T-cell maturation
Authors: Saragovi A , Zheng X , Abramovich I , Cohen-Daniel L , Zhuoning L , Raifer H , Omar I , Swisa A , Kuchersky M , Drori A , Marini F , Toker O , Somech R , Schmidl Ch , Hendrickson RC , Gottlieb E , Huber M , Berger M 
Published: August 2022

AbstractThe metabolic pathways controlling naive CD8+ T (Tn) cell maturation following thymic egress remain mostly undefined. This is important because immature Tn are a major component of peripheral immune tolerance in newborns and under lymphopenia. In this study we demonstrate that TMRM, a mitochondrial membrane potential marker, could be applied to rapidly identify an immature Tn cell population in the periphery. Applying this marker to perform metabolic and proteomic analysis, we show that immature Tn cells maintain accelerated methionine cycle in respect to mature Tn. This unique metabolic state was associated with restricted Tbx21 locus and diminished immune response in vitro and in vivo. Following our findings, we demonstrate that inhibition of methionine cycle leads to rapid functional maturation of Tn and recovery of immune response to stimuli. Our work provides insight into the way the rate of methionine cycling regulates T cell maturation, opening a path for metabolic manipulation of immune tolerance.
Leaf side determines the relative importance of dispersal versus host filtering in the phyllosphere microbiome
Authors: Smets Wenke , Chock Mason K , Walsh Corinne M , Vanderburgh Caihong Qiu , Kau Ethan , Lindow Steve E , Fierer Noah , Koskella Britt 
Published: August 2022

AbstractLeaf surface-associated bacterial communities play a significant role in plant health and have therefore been the focus of increasing interest. Despite this, we currently lack a predictive understanding of how leaf-associated bacterial communities are structured within and across hosts, including how leaf traits shape this variation and how community assembly processes may differ across distinct microbial habitats on a leaf. In this study, we characterize the composition of bacterial phyllosphere communities from the upper and lower leaf surfaces of 66 plants across 24 species grown at a common site using 16S rRNA amplicon sequencing. By comparing leaves that vary in pH and stomatal densities and analyzing the leaf surfaces separately, we were able to test the key factors shaping the phyllosphere across host plant species from diverse geographical origins. We found a surprisingly large shared/core microbiome across species, as well as a strong effect of plant species and native origin in shaping composition. Importantly, we found the lower leaf side, where pH values are generally lower and stomatal densities higher, to have lower taxonomic richness relative to the upper leaf side. While the upper leaf side community appears to be more strongly influenced by dispersal effects, the lower leaf appears to be more strongly influenced by plant host filtering effects, as supported by higher relative abundance of shared core taxa and higher signatures of endemism. This work highlights important differences in community assembly processes across the upper and lower leaf microbiomes and underscores the importance of considering differences among habitats within a host when explaining microbial community assembly and composition.
Resistance screening and in-silico characterization of cloned novel RGA from multi race resistant Lentil germplasm against Fusarium wilt (Fusarium oxysporum f. sp. lentis)
Authors: Nishmitha K , Singh Rakesh , Dubey Sunil C , Akthar Jameel , Kamil Deeba 
Published: August 2022

AbstractFusarium wilt caused by Fusarium oxysporum f. sp. lentis (Fol) is the most devastating disease of lentil present worldwide and in India. Identification of multi-race fusarium wilt resistance genes and incorporation into existing cultivar will help to reduce yield loss. In the present study, a hundred lentil germplasm were screened against seven prevalent races of Fol and accession IC201561, EC714243 and EC718238 were identified resistant. The typical R gene codes for the nucleotide-binding site and leucine-rich repeats (NBS-LRR) at the C terminal linked to either Toll/interleukin 1-like receptor (TIR) or coiled-coil (CC) at the N terminal. In the present study degenerate primers designed from the NBS region amplifying P-loop to GLPLA motif isolated forty-five resistance gene analogues (RGA) from identified resistant accessions. The sequence alignment identified both classes of RGA, TIR and non-TIR based on the presence of Aspartate (D) and Tryptophan (W) at the end of kinase motif respectively. The phylogenetic analysis grouped RGA into six classes, LRGA1 to LRGA6 determining the diversity of RGA present in the host. Grouping of RGA identified from Lens nigricans, LnRGA 2, 9, 13 with I2 reveals a probable role in Fusarium resistance. The similarity index of 27.85% to 86.98% was found among RGA and 26.83% to 49.41% between known R genes, I2, Gpa2, M and L6. Active binding sites present along the conserved motifs have grouped the RGA into 13 groups. ADP/ATP being the potential ligand determines ATP binding and ATP hydrolysis activity of RGA. The isolated RGA can be used in developing marker linked to the functional R gene. Further, expression analysis and full-length gene isolation further pave path to identifying the molecular mechanism involved in resistance.
Deriving Schwann Cells from hPSCs Enables Disease Modeling and Drug Discovery for Diabetic Peripheral Neuropathy
Authors: Majd Homa , Amin Sadaf , Ghazizadeh Zaniar , Cesiulis Andrius , Arroyo Edgardo , Lankford Karen , Farahvashi Sina , Chemel Angeline K. , Okoye Mesomachukwu , Scantlen Megan D. , Tchieu Jason , Calder Elizabeth L. , Le Rouzic Valerie , Arab Abolfazl , Goodarzi Hani , Pasternak Gavril , Kocsis Jeffery D. , Chen Shuibing , Studer Lorenz , Fattahi Faranak 
Published: August 2022

SUMMARYSchwann cells (SCs) are the myelinating and non-myelinating glia of the peripheral nervous system (PNS) and are essential for its function. Defects in SCs are associated with many PNS disorders including diabetic peripheral neuropathy (DPN), a condition affecting millions of patients. Here we present a strategy for deriving and purifying SCs from human pluripotent stem cells (hPSCs). The scalable cultures of SCs allow basic and translational applications such as high-resolution molecular and functional characterization, developmental studies, modeling and mechanistic understanding of SC diseases and drug discovery. Our hPSC-derived SCs recapitulate the key molecular features of primary SCs and are capable of engrafting efficiently and producing myelin in injured sciatic nerves in rats. We further established an hPSC-based in vitro model of DPN that revealed the selective vulnerability of human SCs to hyperglycemia-induced cytotoxicity. We established a high-throughput screening system that identified a candidate drug that counteracts glucose-mediated cytotoxicity in SCs and normalizes glucose-induced transcriptional and metabolic abnormalities in SCs. Treatment of hyperglycemic mice with this drug candidate rescues sensory function, prevents SC death, and counteracts myelin damage in sciatic nerves suggesting considerable potential as a novel treatment for DPN.
Development and evaluation of statistical and Artificial Intelligence approaches with microbial shotgun metagenomics data as an untargeted screening tool for use in food production
Authors: Beck Kristen L. , Haiminen Niina , Agarwal Akshay , Carrieri Anna Paola , Madgwick Matthew , Kelly Jennifer , Pylro Victor , Kawas Ban , Wiedmann Martin , Ganda Erika 
Published: August 2022

ABSTRACTThe increasing knowledge of microbial ecology in food products relating to quality and safety and the established usefulness of machine learning algorithms for anomaly detection in multiple scenarios suggests that the application of microbiome data in food production systems for anomaly detection could be a valuable approach to be used in food systems. These methods could be used to identify ingredients that deviate from their typical microbial composition, which could indicate food fraud or safety issues. The objective of this study was to assess the feasibility of using shotgun sequencing data as input into anomaly detection algorithms using fluid milk as a model system. Contrastive PCA, cluster-based methods, and explainable AI were evaluated for the detection of two anomalous sample classes using longitudinal metagenomic profiling of fluid milk compared to baseline samples collected under comparable circumstances. Traditional methods (alpha and beta diversity, clustering-based contrastive PCA, MDS, and dendrograms) failed to differentiate anomalous sample classes; however, explainable AI was able to classify anomalous vs. baseline samples and indicate microbial drivers in association with antibiotic use. We validated the potential for explainable AI to classify different milk sources using larger publicly available fluid milk 16s rDNA sequencing datasets and demonstrated that explainable AI is able to differentiate between milk storage methods, processing stage, and season. Our results indicate the application of artificial intelligence continues to hold promise in the realm of microbiome data analysis and could present further opportunities for downstream analytic automation to aid in food safety and quality.IMPORTANCEWe evaluated the feasibility of using untargeted metagenomic se-quencing of raw milk for detecting anomalous food ingredient content with artificial intelligence methods in a study specifically designed to test this hypothesis. We also show through analysis of publicly available fluid milk microbial data that our artificial intelligence approach is able to successfully predict milk in different stages of process-ing. The approach could potentially be applied in the food industry for safety and quality control.