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Immunobiology May 2024Trauma is statistically a significant cause of mortality among patients across countries. Nevertheless, the precise correlation between genetic diagnostic markers and...
BACKGROUND
Trauma is statistically a significant cause of mortality among patients across countries. Nevertheless, the precise correlation between genetic diagnostic markers and the intricate mechanism of trauma remains indistinct.
METHODS
Our study exclusively centered on trauma patients and selected three trauma-related datasets from the Gene Expression Omnibus (GEO) database, all of which had blood samples collected within post-traumatic 12 h. Differential gene screening, the WGCNA and Cytoscape software were employed to analyze the two datasets, with a particular emphasis on the top 100 genes selected based on MCC algorithm scores. A logistic diagnostic model was constructed by analyzing the intersection genes in the third dataset, leading to the identification of diagnostic biomarkers with high efficiency. The global immune landscape of these patients was extensively investigated using a multidimensional approach. Meanwhile, the underlying pathological and physiological mechanisms associated with early trauma status are summarized by integrating existing literature.
RESULTS
Out of these two GEO datasets, 21 overlapping genes were identified and incorporated into in the logistic diagnostic model constructed in the GSE36809 dataset. A panel of 9 genes was uncovered as a diagnostic biomarker, and their expression and correlation were subsequently verified. Additionally, by virtue of various algorithms, the findings revealed an upregulation of neutrophil expression and a downregulation of CD8+ T cell expression, indicating characteristic early trauma-induced inflammation activation and immune suppression. The correlation observed between the feature genes and immune cells serves to validate the exceptional diagnostic capability of these 9 genes in identifying trauma status and their promising potential for patients who could benefit from targeted immune interventions. Drawing from these findings, the discussion section offers insights into the underlying pathological and physiological mechanisms at play.
CONCLUSION
Our research has discovered a novel diagnostic biomarker and unveiled its association with post-traumatic immune alterations. This breakthrough enables accurate and timely diagnosis of early trauma, facilitating the implementation of appropriate healthcare interventions.
Topics: Humans; Wounds and Injuries; Inflammation; Biomarkers; Gene Expression Profiling; Computational Biology; Transcriptome; Databases, Genetic; Immune Evasion; Gene Regulatory Networks
PubMed: 38593729
DOI: 10.1016/j.imbio.2024.152801 -
Journal of King Saud University.... Oct 2023Gene expression data is typically high dimensional with a limited number of samples and contain many features that are unrelated to the disease of interest. Existing...
AIM
Gene expression data is typically high dimensional with a limited number of samples and contain many features that are unrelated to the disease of interest. Existing unsupervised feature selection algorithms primarily focus on the significance of features in maintaining the data structure while not taking into account the redundancy among features. Determining the appropriate number of significant features is another challenge.
METHOD
In this paper, we propose a clustering-guided unsupervised feature selection (CGUFS) algorithm for gene expression data that addresses these problems. Our proposed algorithm introduces three improvements over existing algorithms. For the problem that existing clustering algorithms require artificially specifying the number of clusters, we propose an adaptive -value strategy to assign appropriate pseudo-labels to each sample by iteratively updating a change function. For the problem that existing algorithms fail to consider the redundancy among features, we propose a feature grouping strategy to group highly redundant features. For the problem that the existing algorithms cannot filter the redundant features, we propose an adaptive filtering strategy to determine the feature combinations to be retained by calculating the potentially effective features and potentially redundant features of each feature group.
RESULT
Experimental results show that the average accuracy (ACC) and matthews correlation coefficient (MCC) indexes of the C4.5 classifier on the optimal features selected by the CGUFS algorithm reach 74.37% and 63.84%, respectively, significantly superior to the existing algorithms.
CONCLUSION
Similarly, the average ACC and MCC indexes of the Adaboost classifier on the optimal features selected by the CGUFS algorithm are significantly superior to the existing algorithms. In addition, statistical experiment results show significant differences between the CGUFS algorithm and the existing algorithms.
PubMed: 38567001
DOI: 10.1016/j.jksuci.2023.101731 -
Molecular Therapy. Methods & Clinical... Jun 2024Gene therapies and associated technologies are transforming biomedical research and enabling novel therapeutic options for patients living with debilitating and...
Gene therapies and associated technologies are transforming biomedical research and enabling novel therapeutic options for patients living with debilitating and incurable genetic disorders. The vector system based on recombinant adeno-associated viral vectors (AAVs) has shown great promise in recent clinical trials for genetic diseases of multiple organs, such as the liver and the nervous system. Despite recent successes toward the development of novel bioengineered AAV variants for improved transduction of primary human tissues and cells, vectors that can efficiently transduce human Schwann cells (hSCs) have yet to be identified. Here, we report the application of the functional transduction-RNA selection method in primary hSCs for the development of AAV variants for specific and efficient transgene delivery to hSCs. The two identified capsid variants, Pep2hSC1 and Pep2hSC2, show conserved potency for delivery across various , , and models of hSCs. These novel AAV capsids will serve as valuable research tools, forming the basis for therapeutic solutions for both SC-related disorders or peripheral nervous system injury.
PubMed: 38558569
DOI: 10.1016/j.omtm.2024.101234 -
Anais Brasileiros de Dermatologia Mar 2024Merkel cell polyomavirus (MCPyV), a human polyomavirus that is unequivocally linked to merkel cell carcinoma (MCC), has been found in association with keratinocytes...
BACKGROUND
Merkel cell polyomavirus (MCPyV), a human polyomavirus that is unequivocally linked to merkel cell carcinoma (MCC), has been found in association with keratinocytes carcinomas (KC), especially basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (cSCC). Nevertheless, there is scarce information about the possible involvement of MCPyV in the development of KC.
OBJECTIVES
To assess the presence of MCPyV DNA and Large-T Antigen (LT-Ag) via Polymerase Chain Reaction (PCR) and Immunohistochemistry (IHC) in cases of KC, and to correlate its presence with immunohistochemical markers p16, p53, and ki67, tumor type and subtype, sun-exposed location, and epidemiological data.
METHODS
The prevalence of MCPyV DNA, LT-Ag, and immunohistochemical markers p16, p53, and ki67 was assessed by PCR and Immunohistochemistry (IHC) in 127 cases of KC, these results were correlated with tumor type and subtype, sun-exposed location, and epidemiological data.
RESULTS
The MCPyV DNA was detected in 42.57% (43 of 101) cases by PCR, the LT-Ag was detected in 16.4% (20 of 122) of cases, p16 in 81.5% (97 of 119), p53 in 66.4% (83 of 125), ki67 in 89% (73 of 82). No correlation between MCPyV LT-Ag and DNA confronted with tumor type, subtype, location site, and immunohistochemical markers was found. A single correlation between the MCPyV LT-Ag and cSCC tumors and peri-tumoral lymphocyte cells was noted.
STUDY LIMITATIONS
Further steps need to be taken to better evaluate the MCPyV influence and its possible role in KC carcinogenesis, as the evaluation of the virus genome state, the gene sequence that encodes LT-Ag in the KC tumor cells, and in situ hybridization for viral DNA or RNA in these cells.
CONCLUSIONS
Despite the frequent detection of MCPyV in KC, the data available so far does not support the hypothesis of a causal relationship between them.
PubMed: 38555263
DOI: 10.1016/j.abd.2023.12.002 -
BMC Medical Genomics Mar 2024Mice are routinely utilized as animal models of drug-induced liver injury (DILI), however, there are significant differences in the pathogenesis between mice and humans....
OBJECTIVE
Mice are routinely utilized as animal models of drug-induced liver injury (DILI), however, there are significant differences in the pathogenesis between mice and humans. This study aimed to compare gene expression between humans and mice in acetaminophen (APAP)-induced liver injury (AILI), and investigate the similarities and differences in biological processes between the two species.
METHODS
A pair of public datasets (GSE218879 and GSE120652) obtained from GEO were analyzed using "Limma" package in R language, and differentially expressed genes (DEGs) were identified, including co-expressed DEGs (co-DEGs) and specific-expressed DEGS (specific-DEGs). Analysis of Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed analyses for specific-DEGs and co-DEGs. The co-DEGs were also used to construct transcription factor (TF)-gene network, gene-miRNA interactions network and protein-protein interaction (PPI) network for analyzing hub genes.
RESULTS
Mouse samples contained 1052 up-regulated genes and 1064 down-regulated genes, while human samples contained 1156 up-regulated genes and 1557 down-regulated genes. After taking the intersection between the DEGs, only 154 co-down-regulated and 89 co-up-regulated DEGs were identified, with a proportion of less than 10%. It was suggested that significant differences in gene expression between mice and humans in drug-induced liver injury. Mouse-specific-DEGs predominantly engaged in processes related to apoptosis and endoplasmic reticulum stress, while human-specific-DEGs were concentrated around catabolic process. Analysis of co-regulated genes reveals showed that they were mainly enriched in biosynthetic and metabolism-related processes. Then a PPI network which contains 189 nodes and 380 edges was constructed from the co-DEGs and two modules were obtained by Mcode. We screened out 10 hub genes by three algorithms of Degree, MCC and MNC, including CYP7A1, LSS, SREBF1, FASN, CD44, SPP1, ITGAV, ANXA5, LGALS3 and PDGFRA. Besides, TFs such as FOXC1, HINFP, NFKB1, miRNAs like mir-744-5p, mir-335-5p, mir-149-3p, mir-218-5p, mir-10a-5p may be the key regulatory factors of hub genes.
CONCLUSIONS
The DEGs of AILI mice models and those of patients were compared, and common biological processes were identified. The signaling pathways and hub genes in co-expression were identified between mice and humans through a series of bioinformatics analyses, which may be more valuable to reveal molecular mechanisms of AILI.
Topics: Humans; Animals; Mice; Acetaminophen; Chemical and Drug Induced Liver Injury, Chronic; Gene Expression Profiling; MicroRNAs; Gene Regulatory Networks; Computational Biology; Gene Expression
PubMed: 38549107
DOI: 10.1186/s12920-024-01848-0 -
Microorganisms Feb 2024Coxsackievirus-A6 (CV-A6) is responsible for more severe dermatological manifestations compared to other enteroviruses such as CV-A10, CV-A16, and EV-A71, causing HFMD...
Coxsackievirus-A6 (CV-A6) is responsible for more severe dermatological manifestations compared to other enteroviruses such as CV-A10, CV-A16, and EV-A71, causing HFMD in children and adults. Between 2005 and 2007, the recombinant subclade D3/RF-A started to expand globally, and a CV-A6 pandemic started. The study aimed to conduct whole-genome sequencing (WGS) of an isolated CV-A6 strain from currently circulating HFMD cases from India in 2022. Gene-specific RT-PCR and sequencing were used to perform molecular characterization of the isolated virus. Confirmation of these isolates was also performed by transmission electron microscopy and WGS. Among eleven positive clinical enterovirus specimens, eight CV-A6 strains were successfully isolated in the RD cell line. Isolates confirmed the presence of the CV-A6 strain based on VP1 and VP2 gene-specific RT-PCR. Sequences of isolates were clustered and identified as the novel CV-A6 strain of the D3/Y sub-genotype in India. The studies revealed that the D3/Y sub-genotype is being introduced into Indian circulation. The predicted putative functional loops found in VP1 of CV-A6 showed that the nucleotide sequences of the amino acid were a remarkably conserved loop prediction compatible with neutralizing linear epitopes. Therefore, this strain represents a potential candidate for vaccine development and antiviral studies.
PubMed: 38543541
DOI: 10.3390/microorganisms12030490 -
Experimental Dermatology Mar 2024Merkel cell carcinoma (MCC) is a high-grade skin cancer, but spontaneous regression is observed at a markedly higher frequency than in other carcinomas. Although...
Merkel cell carcinoma (MCC) is a high-grade skin cancer, but spontaneous regression is observed at a markedly higher frequency than in other carcinomas. Although spontaneous regression is a phenomenon that greatly impacts treatment planning, we still cannot predict it. We previously reported on the prognostic impact of the presence or absence of tertiary lymphoid structures (TLS) and of Merkel cell polyomavirus (MCPyV) infection. To learn more about the spontaneous regression of MCC, detailed analyses were performed focusing on spontaneous regression cases. We collected 71 Japanese patients with MCC including 6 cases of spontaneous regression. Samples were analysed by immunostaining, spatial single-cell analysis using PhenoCycler, and RNA sequencing using the next-generation sequencer (NGS). All 6 cases of spontaneous regression were positive for MCPyV. TLS was positive in all 5 cases analysed. Spatial single-cell analyses revealed that PD-L1-positive tumour cells were in close proximity to CD20-positive B cell and CD3-, 4-positive T cells. Gene set enrichment analysis between MCPyV-positive and TLS-positive samples and other samples showed significantly high enrichment of "B-cell-mediated immunity" gene sets in the MCPyV-positive and TLS-positive groups. In conclusion, TLS may play an important role in the spontaneous regression of MCC.
Topics: Humans; Carcinoma, Merkel Cell; Skin Neoplasms; Remission, Spontaneous; Tertiary Lymphoid Structures; Tumor Virus Infections; Polyomavirus Infections; Merkel cell polyomavirus
PubMed: 38532566
DOI: 10.1111/exd.15062 -
Environmental Research Jul 2024Haloarchaea with the capacity to degrade alkanes is promising to deal with petroleum pollution in hypersaline environments. However, only a limited number of...
Haloarchaea with the capacity to degrade alkanes is promising to deal with petroleum pollution in hypersaline environments. However, only a limited number of haloarchaeal species are investigated, and their pathway and mechanism for alkane degradation remain unclear. In this study, Halogranum rubrum RO2-11, a haloarchaeal strain, verified the ability to degrade kerosene and hexadecane in 184 g/L NaCl, with 53% and 52% degradation rates after 9 and 4 days, respectively. Genome sequencing and gene annotation indicated that strain RO2-11 possesses a complete potential alkane-degrading pathway, of which alkane hydroxylases may include CYP450, AlmA, and LadA. Transcriptome and metabolome analyses revealed that the upregulation of related genes in TCA cycle, lysine biosynthesis, and acetylation may help improve hexadecane degradation. Additionally, an alternative degrading pathway of hexadecane based on dual-terminal β-oxidation may occur in strain RO2-11. It is likely to be the first report of alkane degradation by the genus Halogranum, which may be helpful for applications of oil-pollution bioremediation under high-salt conditions.
Topics: Alkanes; Biodegradation, Environmental; Halobacteriaceae; Multiomics
PubMed: 38522738
DOI: 10.1016/j.envres.2024.118751 -
Journal of Cellular and Molecular... Apr 2024The present research focused on identifying necroptosis-related differentially expressed genes (NRDEGs) in spinal cord injury (SCI) to highlight potential therapeutic...
The present research focused on identifying necroptosis-related differentially expressed genes (NRDEGs) in spinal cord injury (SCI) to highlight potential therapeutic and prognostic target genes in clinical SCI. Three SCI-related datasets were downloaded, including GSE151371, GSE5296 and GSE47681. MSigDB and KEGG datasets were searched for necroptosis-related genes (NRGs). Differentially expressed genes (DEGs) and NRGs were intersected to obtain NRDEGs. The MCC algorithm was employed to select the first 10 genes as hub genes. A protein-protein interaction (PPI) network related to NRDEGs was developed utilizing STRING. Several databases were searched to predict interactions between hub genes and miRNAs, transcription factors, potential drugs, and small molecules. Immunoassays were performed to identify DEGs using CIBERSORTx. Additionally, qRT-PCR was carried out to verify NRDEGs in an animal model of SCI. Combined analysis of all datasets identified 15 co-expressed DEGs and NRGs. GO and KEGG pathway analyses highlighted DEGs mostly belonged to pathways associated with necroptosis and apoptosis. Hub gene expression analysis showed high accuracy in SCI diagnosis was associated with the expression of CHMP7 and FADD. A total of two hub genes, i.e. CHMP7, FADD, were considered potential targets for SCI therapy.
Topics: Animals; Necroptosis; Computational Biology; Gene Expression Profiling; MicroRNAs; Spinal Cord Injuries
PubMed: 38509743
DOI: 10.1111/jcmm.18219 -
Applied Biochemistry and Biotechnology Mar 2024Gastric cancer (GC) is a malignant tumor with global incidence and death ranking fifth and fourth, respectively. GC patients nevertheless have a poor prognosis despite...
Gastric cancer (GC) is a malignant tumor with global incidence and death ranking fifth and fourth, respectively. GC patients nevertheless have a poor prognosis despite the effectiveness of more advanced chemotherapy and surgical treatment options. The second most frequently mutated gene in GC is PI3Kalpha, a confirmed oncogene that results in abnormal PI3K/AKT/mTOR signaling, causing enhanced translation, proliferation, and survival, and is mutated in 7-25% of GC patients. The protein PI3Kalpha was targeted in the present study by utilizing machine learning (ML), molecular docking, and simulation. A total of 9214 molecules from the DrugBank database were chosen for the first screening. A training set for 6770 compounds tested against PI3Kalpha was assessed to create a quantitative structure-activity relationship-based machine learning model using five different classification algorithms: random forest, random tree, J48 pruned tree, decision stump, and REPTree. Furthermore, consideration was given to the random forest classifier for screening based on its performance index (Kappa statistics, ROC, and MCC). Overall, 1539 of the 9214 drug bank compounds were predicted to be active. Thereafter, three pharmacological filters, Lipinski's rule, Ghose filter, and Veber rule, were applied to test the drug-like properties of the screened compounds. Twenty-six of 1593 compounds showed excellent drug-like properties and were further considered for molecular docking. Thereafter, two compounds were screened as hits because they possessed the molecular docked position with the lowest binding energy and an excellent bonding profile. The binding stability of the selected compounds was further assessed through molecular dynamics simulations for up to 100 ns. Furthermore, compound 1-(3-(2,4-dimethylthiazol-5-YL)-4-oxo-2,4-dihydroindeno[1,2-C]pyrazol-5-YL)-3-(4-methylpiperazin-1-YL) urea was selected as a potential hit in the final screening by analyzing a number of parameters, including the Rg, RMSD, RMSF, H bonding, and SASA profile. Therefore, we conclude that compound 1-(3-(2, 4-dimethylthiazol-5-YL)-4-oxo-2,4-dihydroindeno[1,2-C]pyrazol-5-YL)-3-(4-methylpiperazin-1-YL) urea has efficient inhibitory potential against PI3Kalpha protein and could be utilized for the development of effective drugs against GC.
PubMed: 38507171
DOI: 10.1007/s12010-024-04898-3