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This study investigates the mechanical behavior and damage mechanisms of thin-walled glass/epoxy filament wound tubes under quasi-static lateral loads. The novelty is that the tubes are reinforced in critical areas using strip composite patches to provide a topology-optimized tube, and their damage mechanisms and mechanical performance are compared to that of un-reinforced (reference) tubes. To detect the types of damage mechanisms and their progression, the Acoustic Emission (AE) method is employed, accompanied by data clustering analysis. The loading conditions are simulated using the finite element method, and the results are validated through experimental testing. The findings confirm that the inclusion of reinforcing patches improves the stress distribution, leading to enhanced load carrying capacity, stiffness, and energy absorption. Compared to the reference tubes, the reinforced tubes exhibit a remarkable increase of 23.25% in the load carrying capacity, 33.46% in the tube's stiffness, and 23.67% in energy absorption. The analysis of the AE results reveals that both the reference and reinforced tubes experience damage mechanisms such as matrix cracking, fiber-matrix debonding, delamination, and fiber fracture. However, after matrix cracking, delamination becomes dominant in the reinforced tubes, while fiber failure prevails in the reference tubes. Moreover, by combining the AE energy and mechanical energy using the Sentry function, it is observed that the reinforced tubes exhibit a lower rate of damage propagation, indicating superior resistance to damage propagation compared to the reference tubes.
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Rapid progress in proteomics and large-scale profiling of biological systems at the protein level necessitates the continued development of efficient computational tools for the analysis and interpretation of proteomics data. Here, we present the piNET server that facilitates integrated annotation, analysis and visualization of quantitative proteomics data, with emphasis on PTM networks and integration with the LINCS library of chemical and genetic perturbation signatures in order to provide further mechanistic and functional insights. The primary input for the server consists of a set of peptides or proteins, optionally with PTM sites, and their corresponding abundance values. Several interconnected workflows can be used to generate: (i) interactive graphs and tables providing comprehensive annotation and mapping between peptides and proteins with PTM sites; (ii) high resolution and interactive visualization for enzyme-substrate networks, including kinases and their phospho-peptide targets; (iii) mapping and visualization of LINCS signature connectivity for chemical inhibitors or genetic knockdown of enzymes upstream of their target PTM sites. piNET has been built using a modular Spring-Boot JAVA platform as a fast, versatile and easy to use tool. The Apache Lucene indexing is used for fast mapping of peptides into UniProt entries for the human, mouse and other commonly used model organism proteomes. PTM-centric network analyses combine PhosphoSitePlus, iPTMnet and SIGNOR databases of validated enzyme-substrate relationships, for kinase networks augmented by DeepPhos predictions and sequence-based mapping of PhosphoSitePlus consensus motifs. Concordant LINCS signatures are mapped using iLINCS. For each workflow, a RESTful API counterpart can be used to generate the results programmatically in the json format. The server is available at http://pinet-server.org, and it is free and open to all users without login requirement.
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Processamento de Proteína Pós-Traducional , Proteômica/métodos , Software , Animais , Gráficos por Computador , Enzimas/metabolismo , Humanos , Internet , Camundongos , Peptídeos/química , Peptídeos/metabolismo , Proteínas/química , Proteínas/metabolismo , Fluxo de TrabalhoRESUMO
The Library of Integrated Network-Based Cellular Signatures (LINCS) is an NIH Common Fund program with the goal of generating a large-scale and comprehensive catalogue of perturbation-response signatures by utilizing a diverse collection of perturbations across many model systems and assay types. The LINCS Data Portal (LDP) has been the primary access point for the compendium of LINCS data and has been widely utilized. Here, we report the first major update of LDP (http://lincsportal.ccs.miami.edu/signatures) with substantial changes in the data architecture and APIs, a completely redesigned user interface, and enhanced curated metadata annotations to support more advanced, intuitive and deeper querying, exploration and analysis capabilities. The cornerstone of this update has been the decision to reprocess all high-level LINCS datasets and make them accessible at the data point level enabling users to directly access and download any subset of signatures across the entire library independent from the originating source, project or assay. Access to the individual signatures also enables the newly implemented signature search functionality, which utilizes the iLINCS platform to identify conditions that mimic or reverse gene set queries. A newly designed query interface enables global metadata search with autosuggest across all annotations associated with perturbations, model systems, and signatures.
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Biologia Celular , Bases de Dados Factuais , Ensaios Clínicos como Assunto , Biologia Computacional , Curadoria de Dados , Humanos , Armazenamento e Recuperação da Informação , Metadados , National Institutes of Health (U.S.) , Estados Unidos , Interface Usuário-ComputadorRESUMO
The formation of multiple delaminations is a frequently observed damage mechanism in composite materials, exerting a more pronounced influence on their strength properties compared to single delaminations. To tackle this issue, the incorporation of nanoparticles has been investigated as a means to enhance composite materials. This study aims to examine the effects of nano-additives, specifically carbon nanotubes and nanosilica, on the flexural behavior of glass/epoxy composites containing multiple embedded delaminations. The acoustic emission technique is employed to gain deeper insights into the damage mechanisms associated with flexural failure. Artificial delaminations of varying sizes, arranged in a triangular pattern, were introduced into four interlayers of a [(0/90)2]s oriented glass/epoxy composite. The findings reveal a notable reduction in flexural properties due to the presence of multiple delaminations. However, the addition of nanoparticles demonstrates a significant improvement in the flexural behavior of the multi-delaminated specimens. The most substantial enhancement is observed in the composite incorporating 0.3 wt% nanosilica + 0.5 wt% carbon nanotubes. Furthermore, genetic K-means and hierarchical clustering techniques are employed to classify different damage mechanisms based on the peak frequency and amplitude of the acoustic emission signals. The results indicate that the hierarchical clustering method outperforms the genetic K-means method in accurately clustering the acoustic emission signals. Moreover, the incorporation of nanoparticles' impact on the occurrence of distinct damage mechanisms is evaluated through the analysis of acoustic signals using Wavelet Packet Transform. By investigating the flexural behavior of nanomodified multi-delaminated composites and employing the acoustic emission technique, this study offers valuable insights into the role of nanoparticles in enhancing the mechanical properties and monitoring the damage mechanisms of composite materials.
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OBJECTIVE: Systemic lupus erythematosus (SLE), an autoimmune disease with incompletely understood etiology, has a strong genetic component. Although genome-wide association studies (GWASs) have revealed multiple SLE susceptibility loci and associated single-nucleotide polymorphisms (SNPs), the precise causal variants, target genes, cell types, tissues, and mechanisms of action remain largely unknown. METHODS: Here, we report a comprehensive post-GWAS analysis using extensive bioinformatics, molecular modeling, and integrative functional genomic and epigenomic analyses to optimize fine-mapping. We compile and cross-reference immune cell-specific expression quantitative trait loci (cis- and trans-expression quantitative trait loci) with promoter capture high-throughput capture chromatin conformation (PCHi-C), allele-specific chromatin accessibility, and massively parallel reporter assay data to define predisposing variants and target genes. We experimentally validate a predicted locus using CRISPR/Cas9 genome editing, quantitative polymerase chain reaction, and Western blot. RESULTS: Anchoring on 452 index SNPs, we selected 9,931 high linkage disequilibrium (r2 > 0.8) SNPs and defined 182 independent non-human leukocyte antigen (HLA) SLE loci. The 3,746 SNPs from 143 loci were identified as regulating 564 unique genes. Target genes are enriched in lupus-related tissues and associated with other autoimmune diseases. Of these, 329 SNPs (106 loci) showed significant allele-specific chromatin accessibility and/or enhancer activity, indicating regulatory potential. Using CRISPR/Cas9, we validated reference SNP identifier 57668933 (rs57668933) as a functional variant regulating multiple targets, including SLE-risk gene ELF1 in B cells. CONCLUSION: We demonstrate and validate post-GWAS strategies for using multidimensional data to prioritize likely causal variants with cognate gene targets underlying SLE pathogenesis. Our results provide a catalog of significantly SLE-associated SNPs and loci, target genes, and likely biochemical mechanisms to guide experimental characterization.
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Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Lúpus Eritematoso Sistêmico , Polimorfismo de Nucleotídeo Único , Locos de Características Quantitativas , Lúpus Eritematoso Sistêmico/genética , Humanos , Predisposição Genética para Doença/genética , Alelos , Biologia ComputacionalRESUMO
Microalgae have been remarkably taken into account due to their wide applications in the biopharmaceutical, nutraceutical and bio-energy fields. However, contamination of microalgae with bacteria still appears to be a concern, adversely impacting products' quality and process efficiency. Microalgae decontamination with conventional techniques is usually expensive and time-consuming. Moreover, damage to microalgae cells is highly possible. Asymmetric contraction-expansion microchannels (Asym-CEMCs) are promising passive microfluidic devices that can overcome conventional techniques' drawbacks with their standing-out features. However, the flexibility of Asym-CEMCs performance arising from their various tunable geometrical parameters results in the fact that their performance for separating a target particle cannot be predicted without an investigation. In this work, for the first time, Asym-CEMCs were numerically studied for the removal of a very conventional bacteria, B. subtilis (1 µm), from one of the most popular microalgae, C. vulgaris (5.7 µm). The influences of the microchannel aspect ratio, length and width ratios of the expansion-to-contraction zones, and the total flow rate on the separation resolution and focusing width of the particles were investigated by a 3D numerical model. The aspect ratio had the strongest influence on the Asym-CEMC performance, however, the length ratio had no considerable effect on the results. A decrease in the aspect ratio augmented the shear-induced lift force and Dean drag force, leading to a significant separation resolution improvement. Microalgae decontamination was also enhanced by an increase in the total flow rate and expansion-to-contraction width ratio. Finally, a locally optimized Asym-CEMC with an aspect ratio of one and expansion-to-contraction width and length ratios of 4.7 and 2.07, respectively, was proposed, leading to complete microalgae decontamination with a high normalized separation resolution of 0.6. In a word, Asym-CEMCs with tailored dimensions are promising for successfully decontaminating microalgae from bacteria.
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Objectives: Systemic lupus erythematosus (SLE), an autoimmune disease with incompletely understood etiology, has a strong genetic component. Although genome-wide association studies (GWAS) have revealed multiple SLE susceptibility loci and associated single nucleotide polymorphisms (SNPs), the precise causal variants, target genes, cell types, tissues, and mechanisms of action remain largely unknown. Methods: Here, we report a comprehensive post-GWAS analysis using extensive bioinformatics, molecular modeling, and integrative functional genomic and epigenomic analyses to optimize fine-mapping. We compile and cross-reference immune cell-specific expression quantitative trait loci ( cis - and trans -eQTLs) with promoter-capture Hi-C, allele-specific chromatin accessibility, and massively parallel reporter assay data to define predisposing variants and target genes. We experimentally validate a predicted locus using CRISPR/Cas9 genome editing, qPCR, and Western blot. Results: Anchoring on 452 index SNPs, we selected 9,931 high-linkage disequilibrium (r 2 >0.8) SNPs and defined 182 independent non-HLA SLE loci. 3,746 SNPs from 143 loci were identified as regulating 564 unique genes. Target genes are enriched in lupus-related tissues and associated with other autoimmune diseases. Of these, 329 SNPs (106 loci) showed significant allele-specific chromatin accessibility and/or enhancer activity, indicating regulatory potential. Using CRISPR/Cas9, we validated rs57668933 as a functional variant regulating multiple targets, including SLE risk gene ELF1 , in B-cells. Conclusion: We demonstrate and validate post-GWAS strategies for utilizing multi-dimensional data to prioritize likely causal variants with cognate gene targets underlying SLE pathogenesis. Our results provide a catalog of significantly SLE-associated SNPs and loci, target genes, and likely biochemical mechanisms, to guide experimental characterization.
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Systemic lupus erythematosus (SLE) is a complex autoimmune disease with a strong genetic basis. Despite the identification of several single nucleotide polymorphisms (SNPs) near the SLC15A4 gene that are significantly associated with SLE across multiple populations, specific causal SNP(s) and molecular mechanisms responsible for disease susceptibility are unknown. To address this gap, we employed bioinformatics, expression quantitative trait loci (eQTLs), and 3D chromatin interaction analysis to nominate a likely functional variant, rs35907548, in an active intronic enhancer of SLC15A4 . Through luciferase reporter assays followed by chromatin immunoprecipitation (ChIP)-qPCR, we observed significant allele-specific enhancer effects of rs35907548 in diverse cell lines. The rs35907548 risk allele T is associated with increased regulatory activity and target gene expression, as shown by eQTLs and chromosome conformation capture (3C)-qPCR. The latter revealed long-range chromatin interactions between the rs35907548 enhancer and the promoters of SLC15A4, GLTLD1 , and an uncharacterized lncRNA. The enhancer-promoter interactions and expression effects were validated by CRISPR/Cas9 knock-out (KO) of the locus in HL60 promyeloblast cells. KO cells also displayed dramatically dysregulated endolysosomal pH regulation. Together, our data show that the rs35907548 risk allele affects multiple aspects of cellular physiology and may directly contribute to SLE.
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Systemic lupus erythematosus (SLE) is a complex autoimmune disease with a strong genetic basis. Despite the identification of several single nucleotide polymorphisms (SNPs) near the SLC15A4 gene that are significantly associated with SLE across multiple populations, specific causal SNP(s) and molecular mechanisms responsible for disease susceptibility are unknown. To address this gap, we employed bioinformatics, expression quantitative trait loci (eQTLs), and 3D chromatin interaction analysis to nominate a likely functional variant, rs35907548, in an active intronic enhancer of SLC15A4. Through luciferase reporter assays followed by chromatin immunoprecipitation (ChIP)-qPCR, we observed significant allele-specific enhancer effects of rs35907548 in diverse cell lines. The rs35907548 risk allele T is associated with increased regulatory activity and target gene expression, as shown by eQTLs and chromosome conformation capture (3C)-qPCR. The latter revealed long-range chromatin interactions between the rs35907548 enhancer and the promoters of SLC15A4, GLTLD1, and an uncharacterized lncRNA. The enhancer-promoter interactions and expression effects were validated by CRISPR/Cas9 knock-out (KO) of the locus in HL60 promyeloblast cells. KO cells also displayed dramatically dysregulated endolysosomal pH regulation. Together, our data show that the rs35907548 risk allele affects multiple aspects of cellular physiology and may directly contribute to SLE.
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Genome-wide association studies have identified 2p13.1 as a prominent susceptibility locus for systemic lupus erythematosus (SLE)a complex, multisystem autoimmune disease. However, the identity of underlying causal variant (s) and molecular mechanisms for increasing disease susceptibility are poorly understood. Using meta-analysis (cases = 10,252, controls = 21,604) followed by conditional analysis, bioinformatic annotation, and eQTL and 3D-chromatin interaction analyses, we computationally prioritized potential functional variants and subsequently experimentally validated their effects. Ethnicity-specific meta-analysis revealed striking allele frequency differences between Asian and European ancestries, but with similar odds ratios. We identified 20 genome-wide significant (p < 5 × 10−8) variants, and conditional analysis pinpointed two potential functional variants, rs6705628 and rs2272165, likely to explain the association. The two SNPs are near DGUOK, mitochondrial deoxyguanosine kinase, and its associated antisense RNA DGUOK-AS1. Using luciferase reporter gene assays, we found significant cell type- and allele-specific promoter activity at rs6705628 and enhancer activity at rs2272165. This is supported by ChIP-qPCR showing allele-specific binding with three histone marks (H3K27ac, H3K4me3, and H3K4me1), RNA polymerase II (Pol II), transcriptional coactivator p300, CCCTC-binding factor (CTCF), and transcription factor ARID3A. Transcriptome data across 28 immune cell types from Asians showed both SNPs are cell-type-specific but only in B-cells. Splicing QTLs showed strong regulation of DGUOK-AS1. Genotype-specific DGOUK protein levels are supported by Western blots. Promoter capture Hi-C data revealed long-range chromatin interactions between rs2272165 and several nearby promoters, including DGUOK. Taken together, we provide mechanistic insights into how two noncoding variants underlie SLE risk at the 2p13.1 locus.
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Estudo de Associação Genômica Ampla , Lúpus Eritematoso Sistêmico , Cromatina/genética , Humanos , Lúpus Eritematoso Sistêmico/genética , Polimorfismo de Nucleotídeo Único , Locos de Características QuantitativasRESUMO
There are only a few platforms that integrate multiple omics data types, bioinformatics tools, and interfaces for integrative analyses and visualization that do not require programming skills. Here we present iLINCS ( http://ilincs.org ), an integrative web-based platform for analysis of omics data and signatures of cellular perturbations. The platform facilitates mining and re-analysis of the large collection of omics datasets (>34,000), pre-computed signatures (>200,000), and their connections, as well as the analysis of user-submitted omics signatures of diseases and cellular perturbations. iLINCS analysis workflows integrate vast omics data resources and a range of analytics and interactive visualization tools into a comprehensive platform for analysis of omics signatures. iLINCS user-friendly interfaces enable execution of sophisticated analyses of omics signatures, mechanism of action analysis, and signature-driven drug repositioning. We illustrate the utility of iLINCS with three use cases involving analysis of cancer proteogenomic signatures, COVID 19 transcriptomic signatures and mTOR signaling.
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COVID-19 , Neoplasias , COVID-19/genética , Biologia Computacional , Humanos , Neoplasias/genética , Software , Transcriptoma , Fluxo de TrabalhoRESUMO
OBJECTIVE: In a recent genome-wide association study, a significant genetic association between rs34330 of CDKN1B and risk of systemic lupus erythematosus (SLE) in Han Chinese was identified. This study was undertaken to validate the reported association and elucidate the biochemical mechanisms underlying the effect of the variant. METHODS: We performed an allelic association analysis in patients with SLE, followed by a meta-analysis assessing genome-wide association data across 11 independent cohorts (n = 28,872). In silico bioinformatics analysis and experimental validation in SLE-relevant cell lines were applied to determine the functional consequences of rs34330. RESULTS: We replicated a genetic association between SLE and rs34330 (meta-analysis P = 5.29 × 10-22 , odds ratio 0.84 [95% confidence interval 0.81-0.87]). Follow-up bioinformatics and expression quantitative trait locus analysis suggested that rs34330 is located in active chromatin and potentially regulates several target genes. Using luciferase and chromatin immunoprecipitation-real-time quantitative polymerase chain reaction, we demonstrated substantial allele-specific promoter and enhancer activity, and allele-specific binding of 3 histone marks (H3K27ac, H3K4me3, and H3K4me1), RNA polymerase II (Pol II), CCCTC-binding factor, and a critical immune transcription factor (interferon regulatory factor 1 [IRF-1]). Chromosome conformation capture revealed long-range chromatin interactions between rs34330 and the promoters of neighboring genes APOLD1 and DDX47, and effects on CDKN1B and the other target genes were directly validated by clustered regularly interspaced short palindromic repeat (CRISPR)-based genome editing. Finally, CRISPR/dead CRISPR-associated protein 9-based epigenetic activation/silencing confirmed these results. Gene-edited cell lines also showed higher levels of proliferation and apoptosis. CONCLUSION: Collectively, these findings suggest a mechanism whereby the rs34330 risk allele (C) influences the presence of histone marks, RNA Pol II, and IRF-1 transcription factor to regulate expression of several target genes linked to proliferation and apoptosis. This process could potentially underlie the association of rs34330 with SLE.
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Apoptose/genética , Proliferação de Células/genética , Inibidor de Quinase Dependente de Ciclina p27/genética , Lúpus Eritematoso Sistêmico/genética , Polimorfismo de Nucleotídeo Único , Alelos , Biologia Computacional , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Humanos , Regiões Promotoras GenéticasRESUMO
The vast amount of RNA-seq data deposited in Gene Expression Omnibus (GEO) and Sequence Read Archive (SRA) is still a grossly underutilized resource for biomedical research. To remove technical roadblocks for reusing these data, we have developed a web-application GREIN (GEO RNA-seq Experiments Interactive Navigator) which provides user-friendly interfaces to manipulate and analyze GEO RNA-seq data. GREIN is powered by the back-end computational pipeline for uniform processing of RNA-seq data and the large number (>6,500) of already processed datasets. The front-end user interfaces provide a wealth of user-analytics options including sub-setting and downloading processed data, interactive visualization, statistical power analyses, construction of differential gene expression signatures and their comprehensive functional characterization, and connectivity analysis with LINCS L1000 data. The combination of the massive amount of back-end data and front-end analytics options driven by user-friendly interfaces makes GREIN a unique open-source resource for re-using GEO RNA-seq data. GREIN is accessible at: https://shiny.ilincs.org/grein , the source code at: https://github.com/uc-bd2k/grein , and the Docker container at: https://hub.docker.com/r/ucbd2k/grein .