bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neuroprotective potential of fisetin in an experimental model of spinal cord injury: via modulation of NF-κB/IκBα pathway
Authors: Cui Jing , Fan Jingshi , Li Huanxia , Zhang Jinku , Tong Jianzhou 
Published: January 2021

Aim
To evaluate neuroprotective efficacy of fisetin against the experimental model of spinal cord injury (SCI).

Materials and methods
SCI was induced in male Sprague-Dawley rats by placing an aneurysm clip extradurally. Rats were treated either with vehicle or fisetin for 28 days after SCI.

Results
Treatment with fisetin significantly attenuated SCI-induced alternations in mechano-tactile and thermal allodynia, hyperalgesia and nerve conduction velocities. SCI-induced upregulated tumor necrosis factor-alpha, interleukins, inducible nitric oxide synthase, cyclooxygenase-II, Bcl-2-associated X protein and caspase-3 mRNA expressions in the spinal cord and these were markedly reduced by fisetin. Spinal nuclear factor kappa B and nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor-alpha protein levels were also significantly downregulated by fisetin. Hematoxylin and eosin staining of spinal cord suggested that fisetin significantly ameliorated histological aberrations such as neuronal degeneration, necrosis and inflammatory infiltration induced in it.

Conclusion
Fisetin exerts neuroprotection via modulation of nuclear factor kappa B/nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor-alpha pathway by inhibiting release of inflammatory mediators (inducible nitric oxide synthase and cyclooxygenase-II), proinflammatory cytokines (tumor necrosis factor-alpha and interleukins), apoptotic mediators (Bcl-2-associated X protein and caspase-3).
Development of Novel Measures for Alzheimer’s Disease Prevention Trials (NoMAD)
Authors: Bell Sophie A. , Cohen Hannah R. , Lee Seonjoo , Kim Hyun , Ciarleglio Adam , Andrews Howard , Rivera Andres M. , Igwe Kay , Brickman Adam M. , Devanand D.P. , Harvey Philip D. , Schneider Lon S. , Goldberg Terry E. 
Published: January 2021

ABSTRACTIntroductionAssessment of cognition and everyday function is essential in clinical trials for Alzheimer’s disease (AD). Two novel measures of cognition (No Practice Effects (NPE) cognitive battery and Miami Computerized Functional Assessment Scale (CFAS)) were designed to have robust psychometric properties and reduced practice and ceiling effects. This study aims to evaluate if the NPE and CFAS demonstrate stronger psychometric properties and reduced practice effects compared with established measures, including the Preclinical Alzheimer Cognitive Composite (PACC), Alzheimer’s Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), and Functional Activities Questionnaire (FAQ).MethodsThis parallel group, four-site study will randomize 320 cognitively intact adults aged 60 to 85 years to novel or well-established measures of cognition and function. All participants will receive assessments at baseline (week 0), week 12, and week 52, as well as a brain MRI scan and Apolipoprotein E genetic test at study entry. Analyses will determine psychometric properties of the NPE and CFAS, compare the sensitivity of measures to AD risk markers, and identify cognitive domains within the NPE.DiscussionPractice effects have been a major limitation of Alzheimer’s disease clinical trials that typically assess cognitive changes over serial assessments. Detection of functional impairment in cognitively normal individuals with biomarkers for Alzheimer’s disease requires instruments sensitive to very subtle functional changes. This study is intended to support the validation of two new composite measures, the NPE battery and the CFAS, which may advance clinical testing of interventions for individuals across the spectrum of early stage Alzheimer’s disease.Trial RegistrationNCT03900273
Metabolic markers distinguish COVID-19 from other intensive care patients and show potential to stratify for disease risk
Authors: Schmelter Franziska , Foeh Bandik , Mallagaray Alvaro , Rahmoeller Johann , Ehlers Marc , Lehrian Selina , Kopylow Vera von , Künsting Inga , Lixenfeld Anne Sophie , Martin Emily , Ragab Mohab , Borsche Max , Balck Alexander , Vollstedt Eva Juliane , Meyer-Saraei Roza , Kreutzmann Fabian , Eitel Ingo , Taube Stefan , Klein Christine , Katalinic Alexander , Rupp Jan , Jantzen Eckard , Graf Tobias , Sina Christian , Günther Ulrich L 
Published: January 2021

AbstractCoronavirus disease 2019 (COVID-19) is a viral infection affecting multiple organ systems of great significance for metabolic processes. Thus. there is increasing interest in metabolic and lipoprotein signatures of the disease and early analyses have demonstrated metabolic pattern typical for atherosclerotic and hepatic damage in COVID-19 patients. However, it remains unclear whether these are specific for COVID-19 or a general marker of critical illness. To answer this question, we have analyzed 276 serum samples from 92 individuals using NMR metabolomics, including longitudinally collected samples from 5 COVID-19 and 11 cardiogenic shock intensive care patients, 18 SARS-CoV-2 antibody-positive individuals, and 58 healthy controls.COVID-19 patients showed a distinct metabolic serum profile, including changes typical for severe dyslipidemia and a deeply altered metabolic status compared to healthy controls. Specifically, VLDL parameters, IDL particles, large-sized LDL particles, and the ApoB100/ApoA1 ratio were significantly increased, whereas HDL fractions were decreased. Moreover, a similarly perturbed profile was apparent, even when compared to other ICU patients suffering from cardiogenic shock, highlighting the impact of COVID-19 especially on lipid metabolism and energy status. COVID-19 patients were separated with an AUROC of 1.0 when compared to both healthy controls and cardiogenic shock patients. Anti-SARS-CoV-2 antibody-positive individuals without acute COVID-19 did not show a significantly perturbed metabolic profile compared to age- and sex-matched healthy controls, but SARS-CoV-2 antibody-titers correlated significantly with metabolic parameters, including levels of glycine, ApoA2, and small-sized LDL and HDL subfractions. Our data suggest that NMR metabolic profiles are suitable for COVID-19 patient stratification and post-treatment monitoring.
Large-scale genetic association and single cell accessible chromatin mapping defines cell type-specific mechanisms of type 1 diabetes risk
Authors: Chiou Joshua , Geusz Ryan J , Okino Mei-Lin , Han Jee Yun , Miller Michael , Benaglio Paola , Huang Serina , Korgaonkar Katha , Heller Sandra , Kleger Alexander , Preissl Sebastian , Gorkin David U , Sander Maike , Gaulton Kyle J 
Published: January 2021

ABSTRACTTranslating genome-wide association studies (GWAS) of complex disease into mechanistic insight requires a comprehensive understanding of risk variant effects on disease-relevant cell types. To uncover cell type-specific mechanisms of type 1 diabetes (T1D) risk, we combined genetic association mapping and single cell epigenomics. We performed the largest to-date GWAS of T1D in 489,679 samples imputed into 59.2M variants, which identified 74 novel association signals including several large-effect rare variants. Fine-mapping of 141 total signals substantially improved resolution of causal variant credible sets, which primarily mapped to non-coding sequence. To annotate cell type-specific regulatory mechanisms of T1D risk variants, we mapped 448,142 candidatecis-regulatory elements (cCREs) in pancreas and peripheral blood mononuclear cell types using snATAC-seq of 131,554 nuclei. T1D risk variants were enriched in cCREs active in CD4+ T cells as well as several additional cell types including pancreatic exocrine acinar and ductal cells. High-probability T1D risk variants at multiple signals mapped to exocrine-specific cCREs including novel loci nearCEL, GP2andCFTR. At theCFTRlocus, the likely causal variant rs7795896 mapped in a ductal-specific distal cCRE which regulatedCFTRand the risk allele reduced transcription factor binding, enhancer activity andCFTRexpression in ductal cells. These findings support a role for the exocrine pancreas in T1D pathogenesis and highlight the power of combining large-scale GWAS and single cell epigenomics to provide insight into the cellular origins of complex disease.
A single-cell based precision medicine approach using glioblastoma patient-specific models
Authors: Park James H. , Feroze Abdullah H. , Emerson Samuel N. , Mihalas Anca B. , Keene C. Dirk , Cimino Patrick J. , de Lomana Adrian Lopez Garcia , Kannan Kavya , Wu Wei-Ju , Turkarslan Serdar , Baliga Nitin S. , Patel Anoop P. 
Published: January 2021

AbstractGlioblastoma (GBM) is a heterogeneous tumor made up of cell states that evolve over time. Here, we modeled tumor evolutionary trajectories during standard-of-care treatment using multimodal single-cell analysis of a primary tumor sample, corresponding mouse xenografts subjected to standard of care therapy, and recurrent tumor at autopsy. We mined the multimodal data with single cell SYstems Genetics Network AnaLysis (scSYGNAL) to identify a network of 52 regulators that mediate treatment-induced shifts in xenograft tumor-cell states that were also reflected in recurrence. By integrating scSYGNAL-derived regulatory network information with transcription factor accessibility deviations derived from single-cell ATAC-seq data, we developed consensus networks that regulate subpopulations of primary and recurrent tumor cells. Finally, by matching targeted therapies to active regulatory networks underlying tumor evolutionary trajectories, we provide a framework for applying single-cell-based precision medicine approaches in a concurrent, neo-adjuvant, or recurrent setting.SummaryInference of mechanistic drivers of therapy-induced evolution of glioblastoma at single cell resolution using RNA-seq and ATAC-seq from patient samples and model systems undergoing standard-of-care treatment informs strategy for identification of tumor evolutionary trajectories and possible cell state-directed therapeutics.
RBCeq: An Integrated Bioinformatics Algorithm Designed to Improve Blood Type Compatibility Testing
Authors: Jadhao Sudhir , Davison Candice , Roulis Eileen V. , Schoeman Elizna M. , Divate Mayur , Shankar Arvind Jaya , Lee Simon , Pecheniuk Natalie M. , Irving David O , Hyland Catherine A. , Flower Robert L. , Nagaraj Shivashankar H. 
Published: January 2021

AbstractWhile blood transfusion is an essential cornerstone of hematological care, patients that require repetitive transfusion remain at persistent risk of alloimmunization due to the diversity of human blood group polymorphisms. Next-generation sequencing (NGS) is an effective means of identifying genotypic and phenotypic variations among the blood groups, while the accurate interpretation of such NGS data is currently hampered by a lack of accessibility to bioinformatics support. To address this unmet need, we have developed the RBCeq (https://www.rbceq.org/) platform, which consists of a novel bioinformatics algorithm coupled with a user-friendly web server capable of comprehensively delineating different blood group variants from genomics data with advanced visualization of results. The software profiles genomic data for 36 blood group systems, including two transcription factors and can identify small genetic alterations, including small indels and copy number variants. The RBCeq algorithm was validated on 403 samples which include 58 complex serology cases from Australian Red Cross LifeBlood, 100 samples from The MedSeq Project (phs000958) and a further 245 from Indigenous Australian participants. The final blood typing data from RBCeq was 99.83% concordant for 403 samples (85 different antigens in 21 blood group systems) with that listed from the International Society for Blood Transfusion database.
The cost of correcting for error during sensorimotor adaptation
Authors: Sedaghat-Nejad Ehsan , Shadmehr Reza 
Published: January 2021

AbstractLearning from error is often a slow process. To accelerate learning, previous motor adaptation studies have focused on explicit factors such as reward or punishment, but the results have been inconsistent. Here, we considered the idea that a movement error carries an implicit cost for the organism because the act of correcting for error consumes time and energy. If this implicit cost could be modulated, it may robustly alter how the brain learns from error. To vary the cost of error, we considered a simple saccade adaptation task but combined it with motion discrimination: movement errors resulted in corrective saccades, but those corrections took time away from acquiring information in the discrimination task. We then modulated error cost using coherence of the discrimination task and found that when error cost was large, pupil diameter increased, and the brain learned more from error. However, when error cost was small, the pupil constricted, and the brain learned less from the same error. Thus, during sensorimotor adaptation, the act of correcting for error carried an implicit cost for the brain. Modulating this cost affects how the brain learns from error.
Maternal infection promotes offspring tissue-specific immune fitness
Authors: Lim Ai Ing , McFadden Taryn , Link Verena M. , Han Seong-Ji , Karlsson Rose-Marie , Stacy Apollo , Farley Taylor K. , Harrison Oliver J. , Shih Han-Yu , Cameron Heather A. , Belkaid Yasmine 
Published: January 2021

AbstractThe mammalian immune system has evolved in the face of microbial exposure. How maternal infection experienced at distinct developmental stages shapes the offspring immune system remains poorly understood. Here we show that during pregnancy, maternally restricted infection can have permanent and tissue-specific impacts on offspring immunity. Mechanistically, maternal IL-6 produced in response to infection can specifically and directly impose epigenetic changes on fetal intestinal epithelial cells. Such imprinting is associated with long-lasting impacts on intestinal immune homeostasis, characterized by enhanced tonic immunity to the microbiota and heightened Th17 responses within the gut, but not at other barrier sites. Furthermore, the offspring from IL-6-exposed dams developed enhanced protective immunity to gastrointestinal infection. Together, this work demonstrates that maternal infection experienced during pregnancy can be coopted by the fetus to promote long-term tissue-specific fitness.Summary sentenceInfection-induced maternal IL-6 impacts offspring epithelial cells, resulting in heightened immunity to the microbiota and pathogens.
A causal test of affect processing bias in response to affect regulation
Authors: Bush Keith A. , Kilts Clinton D. 
Published: January 2021

AbstractIn this study we merged methods from machine learning and human neuroimaging to causally test the role of self-induced affect processing states in biasing the affect processing of subsequent image stimuli. To test this causal relationship we developed a novel paradigm in which (n=40) healthy adult participants observed affective neural decodings of their real-time functional magnetic resonance image (rtfMRI) responses as feedback to guide explicit regulation of their brain (and corollary affect processing) state towards a positive valence goal state. By this method individual differences in affect regulation ability were controlled. Attaining this brain-affect goal state triggered the presentation of pseudo-randomly selected affectively congruent (positive valence) or incongruent (negative valence) image stimuli drawn from the International Affective Picture Set. Separately, subjects passively viewed randomly triggered positively and negatively valent image stimuli during fMRI acquisition. Multivariate neural decodings of the affect processing induced by these stimuli were modeled using the task trial type (state- versus randomly-triggered) as the fixed-effect of a general linear mixed-effects model. Random effects were modeled subject-wise. We found that self-induction of a positive valence brain state significantly positively biased valence processing of subsequent stimuli. As a manipulation check, we validated affect processing state induction achieved by the image stimuli using independent psychophysiological response measures of hedonic valence and autonomic arousal. We also validated the predictive fidelity of the trained neural decoding models using brain states induced by an out-of-sample set of image stimuli. Beyond its contribution to our understanding of the neural mechanisms that bias affect processing this work demonstrated the viability of novel experimental paradigms triggered by pre-defined cognitive states. This line of individual differences research potentially provides neuroimaging scientists with a valuable tool for causal exploration of the roles and identities of intrinsic cognitive processing mechanisms that shape our perceptual processing of sensory stimuli.
Characterisation of the R2R3 Myb subgroup 9 family of transcription factors in tomato
Authors: Davis Gwen. V. , Glover Beverley. J. 
Published: January 2021

AbstractTomato (Solanum lycopersicum)has many epidermal cell outgrowths including conical cells and multiple types of trichomes. These include the anther-specific trichome mesh which holds the anthers connate. The R2R3 Myb Subgroup 9 family of transcription factors is involved in development of epidermal cell outgrowths throughout the angiosperms. No previous study has examined all members of this transcription factor family in a single species. All 7R2R3 Myb Subgroup 9genes were isolated from tomato. They were ectopically expressed in tobacco to assess their ability to induce epidermal cell outgrowth. Endogenous expression patterns were examined by semi-quantitative RT-PCR at different stages of floral development relative to the development of anther trichomes. We report variation in the degree of epidermal cell outgrowth produced in transgenic tobacco for each ectopically expressed gene. Based on expression profile and ectopic activity,SlMIXTA-2is likely involved in the production of leaf trichomes whileSlMYB17-2is the best candidate for the regulation of the anther trichome mesh. Analysis of the phenotypes of transgenic plants ectopically expressing all 7 genes has revealed the different extent to which members of the same transcription factor subfamily can induce cellular outgrowth.HighlightCharacterisation of all members of an important family of transcription factors within tomato showing that all are able to induce epidermal cell outgrowths to varying degrees.
Learning interpretable cellular and gene signature embeddings from single-cell transcriptomic data
Authors: Zhao Yifan , Cai Huiyu , Zhang Zuobai , Tang Jian , Li Yue 
Published: January 2021

AbstractThe advent of single-cell RNA sequencing (scRNA-seq) technologies has revolutionized transcriptomic studies. However, large-scale integrative analysis of scRNA-seq data remains a challenge largely due to unwanted batch effects and the limited transferabilty, interpretability, and scalability of the existing computational methods. We present single-cell Embedded Topic Model (scETM). Our key contribution is the utilization of a transferable neural-network-based encoder while having an interpretable linear decoder via a matrix tri-factorization. In particular, scETM simultaneously learns an encoder network to infer cell type mixture and a set of highly interpretable gene embeddings, topic embeddings, and batch effect linear intercepts from multiple scRNA-seq datasets. scETM is scalable to over 106cells and confers remarkable cross-tissue and cross-species zero-shot transfer-learning performance. Using gene set enrichment analysis, we find that scETM-learned topics are enriched in biologically meaningful and disease-related pathways. Lastly, scETM enables the incorporation of known gene sets into the gene embeddings, thereby directly learning the associations between pathways and topics via the topic embeddings.
CAR-NK Cells Effectively Target the D614 and G614 SARS-CoV-2-infected Cells
Authors: Ma Minh , Badeti Saiaditya , Chen Chih-Hsiung , Pinter Abraham , Jiang Qingkui , Shi Lanbo , Zhou Renping , Xu Huanbin , Li Qingsheng , Gause William , Liu Dongfang 
Published: January 2021

ABSTRACTSevere Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is highly contagious presenting a significant public health issue. Current therapies used to treat coronavirus disease 2019 (COVID-19) include monoclonal antibody cocktail, convalescent plasma, antivirals, immunomodulators, and anticoagulants, though the current therapeutic options remain limited and expensive. The vaccines from Pfizer and Moderna have recently been authorized for emergency use, which are invaluable for the prevention of SARS-CoV-2 infection. However, their long-term side effects are not yet to be documented, and populations with immunocompromised conditions (e.g., organ-transplantation and immunodeficient patients) may not be able to mount an effective immune response. In addition, there are concerns that wide-scale immunity to SARS-CoV-2 may introduce immune pressure that could select for escape mutants to the existing vaccines and monoclonal antibody therapies. Emerging evidence has shown that chimeric antigen receptor (CAR)- natural killer (NK) immunotherapy has potent antitumor response in hematologic cancers with minimal adverse effects in recent studies, however, the potentials of CAR-NK cells in preventing and treating severe cases of COVID-19 has not yet been fully exploited. Here, we improve upon a novel approach for the generation of CAR-NK cells for targeting SARS-CoV-2 and its D614G mutant. CAR-NK cells were generated using the scFv domain of S309 (henceforward, S309-CAR-NK), a SARS-CoV and SARS-CoV-2 neutralizing antibody that targets the highly conserved region of SARS-CoV-2 spike (S) glycoprotein, therefore would be more likely to recognize different variants of SARS-CoV-2 isolates. S309-CAR-NK cells can specifically bind to pseudotyped SARS-CoV-2 virus and its D614G mutant. Furthermore, S309-CAR-NK cells can specifically kill target cells expressing SARS-CoV-2 S proteinin vitroand show superior killing activity and cytokine production, compared to that of the recently published CR3022-CAR-NK cells. Thus, these results pave the way for generating ‘off-the-shelf’ S309-CAR-NK cells for treatment in high-risk individuals as well as provide an alternative strategy for patients unresponsive to current vaccines.