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Although it is well known that the morphology of Gram-negative rods changes on exposure to antibiotics, the morphology of antibiotic-resistant bacteria in the absence of antibiotics has not been widely investigated. Here, we studied the morphologies of 10 antibiotic-resistant strains of Escherichia coli and used bioinformatics tools to classify the resistant cells under light microscopy in the absence of antibiotics. The antibiotic-resistant strains showed differences in morphology from the sensitive parental strain, and the differences were most prominent in the quinolone-and β-lactam-resistant bacteria. A cluster analysis revealed increased proportions of fatter or shorter cells in the antibiotic-resistant strains. A correlation analysis of morphological features and gene expression suggested that genes related to energy metabolism and antibiotic resistance were highly correlated with the morphological characteristics of the resistant strains. Our newly proposed deep learning method for single-cell classification achieved a high level of performance in classifying quinolone-and β-lactam-resistant strains. [ABSTRACT FROM AUTHOR]

Background: Metabolic dysfunction-associated steatohepatitis (MASH) is a highly prevalent liver disease globally, with a significant risk of progressing to cirrhosis and even liver cancer. Efferocytosis, a process implicated in a broad spectrum of chronic inflammatory disorders, has been reported to be associated with the pathogenesis of MASH; however, its precise role remains obscure. Thus, we aimed to identify and validate efferocytosis linked signatures for detection of MASH. Methods: We retrieved gene expression patterns of MASH from the GEO database and then focused on assessing the differential expression of efferocytosis-related genes (EFRGs) between MASH and control groups. This analysis was followed by a series of in-depth investigations, including protein-protein interaction (PPI), correlation analysis, and functional enrichment analysis, to uncover the molecular interactions and pathways at play. To screen for biomarkers for diagnosis, we applied machine learning algorithm to identify hub genes and constructed a clinical predictive model. Additionally, we conducted immune infiltration and single-cell transcriptome analyses in both MASH and control samples, providing insights into the immune cell landscape and cellular heterogeneity in these conditions. Results: This research pinpointed 39 genes exhibiting a robust correlation with efferocytosis in MASH. Among these, five potential diagnostic biomarkers--TREM2, TIMD4, STAB1, C1QC, and DYNLT1--were screened using two distinct machine learning models. Subsequent external validation and animal experimentation validated the upregulation of TREM2 and downregulation of TIMD4 in MASH samples. Notably, both TREM2 and TIMD4 demonstrated area under the curve (AUC) values exceeding 0.9, underscoring their significant potential in facilitating the diagnosis of MASH. Conclusion: Our study comprehensively elucidated the relationship between MASH and efferocytosis, constructing a favorable diagnostic model. Furthermore, we identified potential therapeutic targets for MASH treatment and offered novel insights into unraveling the underlying mechanisms of this disease. [ABSTRACT FROM AUTHOR]

Abiotic stress affects the growth and development of maize (Zea mays). The regulator of chromosome condensation 1 (RCC1)-containing proteins (RCPs) plays crucial roles in plant growth and development and response to abiotic stresses. However, a comprehensive analysis of the maize RCP family has not been reported in detail. This study presents a systematic bioinformatics analysis of the ZmRCP family, identifying a total of 30 members distributed across nine chromosomes. The physicochemical properties and cis-acting elements in the promoters of ZmRCP members are predicted. The results of subcellular localization showed that ZmRCP3 and ZmRCP10 are targeted to mitochondria and ZmRCP2 is localized in the nucleus. A heatmap of expression levels among family members under abiotic stress conditions revealed varying degrees of induced expression, and the expression levels of 10 ZmRCP members were quantified using RT-qPCR under abiotic stress and plant hormone treatments. The results showed that ZmRCP members exhibit induced or inhibited responses to these abiotic stresses and plant hormones. These results contribute to a better understanding of the evolutionary history and potential role of the ZmRCP family in mediating responses to abiotic stress in maize. [ABSTRACT FROM AUTHOR]

Calciprotein particles (CPPs) are essential circulating scavengers of excessive Ca2+ and PO43− ions, representing a vehicle that removes them from the human body and precludes extraskeletal calcification. Having been internalised by endothelial cells (ECs), CPPs induce their dysfunction, which is accompanied by a remarkable molecular reconfiguration, although little is known about this process's extracellular signatures. Here, we applied ultra-high performance liquid chromatography-tandem mass spectrometry to perform a secretome-wide profiling of the cell culture supernatant from primary human coronary artery ECs (HCAECs) and internal thoracic artery ECs (HITAECs) treated with primary CPPs (CPP-P), secondary CPPs (CPP-S), magnesiprotein particles (MPPs), or Ca2+/Mg2+-free Dulbecco's phosphate-buffered saline (DPBS) for 24 h. Incubation with CPP-P/CPP-S significantly altered the profiles of secreted proteins, delineating physiological and pathological endothelial secretomes. Neither pathway enrichment analysis nor the interrogation of protein–protein interactions detected extracellular matrix- and basement membrane-related molecular terms in the protein datasets from CPP-P/CPP-S-treated ECs. Both proteomic profiling and enzyme-linked immunosorbent assay identified an increased level of protectin (CD59) and reduced levels of osteonectin (SPARC), perlecan (HSPG2), and fibronectin (FN1) in the cell culture supernatant upon CPP-P/CPP-S treatment. Elevated soluble CD59 and decreased release of basement membrane components might be considered as potential signs of dysfunctional endothelium. [ABSTRACT FROM AUTHOR]

There is a paucity of research examining the molecular mechanisms underlying sex differences of clinical phenotypes and the prognosis in hypertrophic cardiomyopathy (HCM). The dataset GSE36961 was retrieved from Gene Expression Omnibus (GEO) database and comprehensive bioinformatics was employed to identify the core genes linked to sex differences in HCM patients. Additionally, gene set enrichment analysis (GSEA) was conducted to detect downstream signalling pathways. Furthermore, experimental validation was carried out using hearts from spontaneously hypertensive rats (SHRs). A comprehensive analysis revealed the identification of 208 differentially expressed genes (DEGs) in female patients with HCM with a notable downregulation of seven core genes. Notably, there were sex differences in the expression of ras dexamethasone‐induced protein 1 (RASD1) and myosin 6 (MYH6) in HCM. Gene ontology (GO) analysis and GSEA demonstrated an enrichment of autophagy‐related processes in disease progression in HCM females. Specifically, spearman's correlation analysis revealed a positive correlation between nicotinamide phosphoribosyl transferase (NAMPT) and RASD1 levels, particularly among female patients (R = 0.569, p < 0.001). Additionally, animal models confirmed that cardiac hypertrophy was more pronounced in SHR females compared to males. SHR females exhibited lower mRNA and protein expressions of RASD1 and NAMPT, which were associated with impaired autophagy. In this study, bioinformatics and validation using external data sets and animal models of left ventricular hypertrophy suggested that the RASD1/NAMPT axis is potentially a crucial mechanism underlying the elevated risk of cardiovascular disorders in HCM females, also pointing potentially prognostic biomarkers. [ABSTRACT FROM AUTHOR]

Spinal cord injury (SCI) is a serious disease without effective therapeutic strategies. To identify the potential treatments for SCI, it is extremely important to explore the underlying mechanism. Current studies demonstrate that anoikis might play an important role in SCI. In this study, we aimed to identify the key anoikis-related genes (ARGs) providing therapeutic targets for SCI. The mRNA expression matrix of GSE45006 was downloaded from the Gene Expression Omnibus (GEO) database, and the ARGs were downloaded from the Molecular Signatures Database (MSigDB database). Then, the potential differentially expressed ARGs were identified. Next, correlation analysis, gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein–protein interaction (PPI) analysis were employed for the differentially expressed ARGs. Moreover, miRNA-gene networks were constructed by the hub ARGs. Finally, RNA expression of the top ten hub ARGs was validated in the SCI cell model and rat SCI model. A total of 27 common differentially expressed ARGs were identified at different time points (1, 3, 7, and 14 days) following SCI. The GO and KEGG enrichment analysis of these ARGs indicated several enriched terms related to proliferation, cell cycle, and apoptotic process. The PPI results revealed that most of the ARGs interacted with each other. Ten hub ARGs were further screened, and all the 10 genes were validated in the SCI cell model. In the rat model, only seven genes were validated eventually. We identified 27 differentially expressed ARGs of the SCI through bioinformatic analysis. Seven real hub ARGs (CCND1, FN1, IGF1, MYC, STAT3, TGFB1, and TP53) were identified eventually. These results may expand our understanding of SCI and contribute to the exploration of potential SCI targets. [ABSTRACT FROM AUTHOR]

Competitive endogenous RNAs (ceRNA) theory has been proved in numerous biological processes. Nevertheless, there is a lack of research applying the ceRNA theory to the study of vascular calcification (VC) in chronic kidney diseases (CKD). In the present study, a ceRNA network was constructed after conducting transcriptome sequencing of differentially expressed genes, followed by experimental validation to identify a new target for the diagnosis and treatment of vascular calcification. Total RNA was extracted from β‐glycerophosphate (β‐GP) cultured vascular smooth muscle cells (VSMCs) on Day 7. Illumina HiSeq platform was utilized to build sequencing libraries. GO and KEGG analysis was conducted to identify the function of the differentially expressed genes. Protein–protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. A ceRNA network was established based on TargetScan, miRDB, miRWALK, and miRanda database. Western blot and qRT‐PCR were used to explore the expression level of protein and RNA, respectively. The direct binding sites were confirmed by dual‐luciferase reporter assay. In total, 647 differentially expressed lncRNAs and 289 differentially expressed mRNAs were identified (|log2FC| ≥ 1, p <.05). The function of differentially expressed mRNAs was mainly enriched in negative regulation of osteoblast differentiation, regulation of RNA metabolic process, and other typical pathways. The ceRNA network was generated with a total of 107 interaction pairs. The lncRNA Prrc2c/miR‐145‐5p/Smad3 axis was considered a potential regulatory pathway within the ceRNA network. The regulatory relationship and targets of this ceRNA axis were validated via in vitro experiments. For the first time, we found that lncRNA Prrc2c was highly expressed and promoted calcification of VSMCs. Luciferase reporter assay showed that lncRNA Prrc2c could bind miR‐145‐5p at site 1755–1761. Similarly, luciferase reporter assay showed that miR‐145‐5p inhibited Smad3 expression by binding to its 3′UTR. Our findings provide a comprehensive examination of the ceRNA networks in vascular smooth muscle cells (VSMCs) treated with high phosphorate. Specifically, we have identified the role of lncRNA Prrc2c in promoting VSMC calcification through the miR‐145‐5p/Smad3 axis. [ABSTRACT FROM AUTHOR]

Background: Metabolic reprogramming is one of the hallmarks of cancer, and in breast cancer (BC), several metabolic enzymes are overexpressed and overactivated. One of these, Enolase 1 (ENO1), catalyses glycolysis and is involved in the regulation of multiple signalling pathways. Objectives: This study aimed to evaluate in silico the prognostic and predictive effects of ENO1 expression in BC. Design: This is a bioinformatic in silico analysis. Methods: Using available online platforms (Kaplan–Meier [KM] plotter, receiver operating characteristic curve [ROC] plotter, cBioPortal, Genotype-2-Outcome [G-2-O], MethSurv, and Tumour–Immune System Interaction Database [TISIDB]), we performed a bioinformatic in silico analysis to establish the prognostic and predictive effects related to ENO1 expression in BC. A network analysis was performed using the Oncomine platform, and signalling, epigenetic, and immune regulation pathways were explored. Results: ENO1 was overexpressed in all the analysed Oncomine, epigenetic, and immune pathways in triple-negative, but not in hormone receptor–positive BCs. In human epidermal growth factor receptor 2 (HER2)-positive BCs, ENO1 expression showed a mixed profile. Analysis on disease progression and histological types showed ENO1 overexpression in ductal in situ and invasive carcinoma, in high-grade tumours followed by advanced or metastasis and was linked to worse survival. High ENO1 expression was also associated with relapse-free, distant metastasis-free and overall survival, irrespectively of treatment and was mainly related to basal subtype. Conclusion: ENO1 overexpression recruits a range of signalling pathways during disease progression conferring a worse prognosis and can be potentially used as a biomarker of disease progression and therapeutic target, particularly in triple-negative and in ductal invasive carcinoma. [ABSTRACT FROM AUTHOR]

Background: Head and neck squamous cell carcinoma (HNSCC) is the sixth most prevalent malignancy worldwide, with high incidence and poor survival rates. RBP1 is highly expressed in several kinds of cancer and plays a potential prognostic factor. However, the relationship between RBP1 and HNSCC were analyzed based on The Cancer Genome Atlas (TCGA) database. Materials and methods: RBP1 expression and clinical information were obtained from the Cancer Genome Atlas (TCGA) database. Tumor tissue and adjacent normal tissue of 6 HNSCC patients were collected to analyze the RBP1 mRNA expression level by quantitative PCR. Cox regression analysis was used to evaluate the prognostic values of RBP1 and clinical data in HNSCC. A nomogram was also established to predict the impact of RBP1 on prognosis based on Cox multivariate results. The methylation level of RBP1 in HNSC and its prognosis were analyzed in UALACN and MethSurv. Finally, the potential biological functions of RBP1 were investigated using gene set enrichment analysis (GSEA) and single sample GSEA (ssGSEA). Results: The mRNA expression levels of RBP1 were highly expressed in HNSCC tissue. The Cox analyses demonstrate that highly-expressed RBP1 is an independent prognosis marker(P < 0.05). ROC curve analysis showed that performances of RBP1 (area under the ROC curve: 0.887, sensitivity: 84.1%, specificity: 79.9%). The methylation was increased in HNSCC patients compared with normal subjects(P < 0.05) and was associated with better prognosis at sites cg06208339, cg12298268, cg12497564, cg15288618, cg20532370, cg23448348. Additionally, RBP1 expression is mildly associated with immune cell infiltration and immunological checkpoints. Conclusion: RBP1 is overexpressed and associated with poor patient prognosis in head and neck squamous cell carcinoma. [ABSTRACT FROM AUTHOR]

Chronic migraines have been described chiefly only from a clinical perspective. However, searching for reliable molecular markers has allowed for the discovery of the expression of different genes mainly associated with inflammation, neuro-vascularization, and pain-related pathways. The interest in microRNAs (miRs) that can regulate the expression of these genes has gained significant relevance since multiple miRs could play a key role in regulating these events. In this study, miRs were searched in samples from patients with chronic migraine, and the inclusion criteria were carefully reviewed. Different bioinformatic tools, such as miRbase, targetscan, miRPath, tissue atlas, and miR2Disease, were used to analyze the samples. Our findings revealed that some of the miRs were expressed more (miR-197, miR-101, miR-92a, miR-375, and miR-146b) and less (miR-133a/b, miR-134, miR-195, and miR-340) than others. We concluded that, during chronic migraine, common pathways, such as inflammation, vascularization, neurodevelopment, nociceptive pain, and pharmacological resistance, were associated with this disease. [ABSTRACT FROM AUTHOR]

Background: Gliomas are aggressive brain tumors with poor prognosis. Understanding the tumor immune microenvironment (TIME) in gliomas is essential for developing effective immunotherapies. This study aimed to identify TIME-related biomarkers in glioma using bioinformatic analysis of RNA-seq data. Methods: In this study, we employed weighted gene co-expression network analysis (WGCNA) on bulk RNA-seq data to identify TIME-related genes. To identify prognostic genes, we performed univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. Based on these genes, we constructed a prognostic signature and delineated risk groups. To validate the prognostic signature, external validation was conducted. Results: CD8 + T cell infiltration was strongly correlated with glioma patient prognosis. We identified 115 CD8 + T cell-related genes through integrative analysis of bulk-seq data. CDCA5, KIF11, and KIF4A were found to be significant immune-related genes (IRGs) associated with overall survival in glioma patients and served as independent prognostic factors. We developed a prognostic nomogram that incorporated these genes, age, gender, and grade, providing a reliable tool for clinicians to predict patient survival probabilities. The nomogram's predictions were supported by calibration plots, further validating its accuracy. Conclusion: In conclusion, our study identifies CD8 + T cell infiltration as a strong predictor of glioma patient outcomes and highlights the prognostic value of genes. The developed prognostic nomogram, incorporating these genes along with clinical factors, provides a reliable tool for predicting patient survival probabilities and has important implications for personalized treatment decisions in glioma. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Agricultural Science & Technology (1008-0864) is the property of Journal of Agricultural Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Although it is well known that the morphology of Gram-negative rods changes on exposure to antibiotics, the morphology of antibiotic-resistant bacteria in the absence of antibiotics has not been widely investigated. Here, we studied the morphologies of 10 antibiotic-resistant strains of Escherichia coli and used bioinformatics tools to classify the resistant cells under light microscopy in the absence of antibiotics. The antibiotic-resistant strains showed differences in morphology from the sensitive parental strain, and the differences were most prominent in the quinolone-and β-lactam-resistant bacteria. A cluster analysis revealed increased proportions of fatter or shorter cells in the antibiotic-resistant strains. A correlation analysis of morphological features and gene expression suggested that genes related to energy metabolism and antibiotic resistance were highly correlated with the morphological characteristics of the resistant strains. Our newly proposed deep learning method for single-cell classification achieved a high level of performance in classifying quinolone-and ß-lactam-resistant strains. [ABSTRACT FROM AUTHOR]

High-altitude pulmonary edema (HAPE) is a fatal threat for sojourners who ascend rapidly without sufficient acclimatization. Acclimatized sojourners and adapted natives are both insensitive to HAPE but have different physiological traits and molecular bases. In this study, based on GSE52209, the gene expression profiles of HAPE patients were compared with those of acclimatized sojourners and adapted natives, with the common and divergent differentially expressed genes (DEGs) and their hub genes identified, respectively. Bioinformatic methodologies for functional enrichment analysis, immune infiltration, diagnostic model construction, competing endogenous RNA (ceRNA) analysis and drug prediction were performed to detect potential biological functions and molecular mechanisms. Next, an array of in vivo experiments in a HAPE rat model and in vitro experiments in HUVECs were conducted to verify the results of the bioinformatic analysis. The enriched pathways of DEGs and immune landscapes for HAPE were significantly different between sojourners and natives, and the common DEGs were enriched mainly in the pathways of development and immunity. Nomograms revealed that the upregulation of TNF-α and downregulation of RPLP0 exhibited high diagnostic efficiency for HAPE in both sojourners and natives, which was further validated in the HAPE rat model. The addition of TNF-α and RPLP0 knockdown activated apoptosis signaling in endothelial cells (ECs) and enhanced endothelial permeability. In conclusion, TNF-α and RPLP0 are shared biomarkers and molecular bases for HAPE susceptibility during the acclimatization/adaptation/maladaptation processes in sojourners and natives, inspiring new ideas for predicting and treating HAPE. [ABSTRACT FROM AUTHOR]

Background: There is limited research on cholesterol metabolism-related genes (CM-RGs) in non-alcoholic fatty liver disease (NAFLD), despite hypercholesterolemia being a recognized risk factor. The role of CM-RGs in NAFLD remains unclear. Methods: The differentially expressed genes (DEGs) between NAFLD and control were acquired by differential expression analysis. The differentially expressed genes associated with cholesterol metabolism (DE-CM-RGs) were identified and functional enrichment analyses were performed. Protein-protein interaction network analysis and a two-sample Mendelian randomization study were utilized for identifying hub genes. Nomogram model, competing endogenous RNA and messenger RNA-drug networks were established. In addition, immunoinfiltration analysis was performed. Results: We identified four hub genes (MVK, HMGCS1, TM7SF2, and FDPS) linked to NAFLD risk. MVK and TM7SF2 were protective factors, HMGCS1 and FDPS were risk factors for NAFLD. The area under the curve values of nomograms in GSE135251 and GSE126848 were 0.79 and 0.848, respectively. The gene set enrichment analysis indicated that hub genes participated in calcium signaling pathways and biosynthesis of unsaturated fatty acids. NAFLD patients showed increased CD56dim NK cells and Th17. Tretinoin, alendronate, zoledronic acid, and quercetin are potential target agents in NAFLD. Conclusion: Our study has linked cholesterol metabolism genes (MVK, HMGCS1, TM7SF2, and FDPS) to NAFLD, providing a promising diagnostic framework, identifying treatment targets, and offering novel perspectives into its mechanisms. [ABSTRACT FROM AUTHOR]

Copyright of Food & Fermentation Industries is the property of Food & Fermentation Industries and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: The biological mechanisms driving orthodontic tooth movement (OTM) remain incompletely understood. Gingival crevicular fluid (GCF) is an important indicator of the periodontal bioprocess, providing valuable cues for probing the molecular mechanisms of OTM. Methods: A rigorous review of the clinical studies over the past decade was conducted after registering the protocol with PROSPERO and adhering to inclusion criteria comprising human subjects, specified force magnitudes and force application modes. The thorough screening investigated differentially expressed proteins (DEPs) in GCF associated with OTM. Protein-protein interaction (PPI) analysis was carried out using the STRING database, followed by further refinement through Cytoscape to isolate top hub proteins. Results: A comprehensive summarization of the OTM-related GCF studies was conducted, followed by an in-depth exploration of biomarkers within the GCF. We identified 13 DEPs, including ALP, IL-1β, IL-6, Leptin, MMP-1, MMP-3, MMP-8, MMP-9, PGE2, TGF-β1, TNF-α, OPG, RANKL. Bioinformatic analysis spotlighted the top 10 hub proteins and their interactions involved in OTM. Based on these findings, we have proposed a hypothetic diagram for the time-course bioprocess in OTM, which involves three phases containing sequential cellular and molecular components and their interplay network. Conclusions: This work has further improved our understanding to the bioprocess of OTM, suggesting biomarkers as potential modulating targets to enhance OTM, mitigate adverse effects and support real-time monitoring and personalized orthodontic cycles. [ABSTRACT FROM AUTHOR]

Background: Protein–protein interactions are the primary means through which proteins carry out their functions. These interactions thus have crucial roles in life activities. The wide availability of fully sequenced animal and plant genomes has facilitated establishment of relatively complete global protein interaction networks for some model species. The genomes of cultivated and wild peanut (Arachis hypogaea L.) have also been sequenced, but the functions of most of the encoded proteins remain unclear. Results: We here used homologous mapping of validated protein interaction data from model species to generate complete peanut protein interaction networks for A. hypogaea cv. 'Tifrunner' (282,619 pairs), A. hypogaea cv. 'Shitouqi' (256,441 pairs), A. monticola (440,470 pairs), A. duranensis (136,363 pairs), and A. ipaensis (172,813 pairs). A detailed analysis was conducted for a putative disease-resistance subnetwork in the Tifrunner network to identify candidate genes and validate functional interactions. The network suggested that DX2UEH and its interacting partners may participate in peanut resistance to bacterial wilt; this was preliminarily validated with overexpression experiments in peanut. Conclusion: Our results provide valuable new information for future analyses of gene and protein functions and regulatory networks in peanut. [ABSTRACT FROM AUTHOR]

Silique development exerts significant impacts on crop yield. CRPs (Cysteine-rich peptides) can mediate cell–cell communication during plant reproduction and development. However, the functional characterization and regulatory mechanisms of CRPs in silique development remain unclear. In this study, we identified many CRP genes downstream of the CRP gene TPD1 (TAPETUM DETERMINANT1) during silique development using a microarray assay. The novel Arabidopsis thaliana pollen-borne CRPs, the PCP-Bs (for pollen coat protein B-class) gene AtPCP-Ba, along with TPD1, are essential for silique development. The AtPCP-Ba was significantly down-regulated in tpd1 flower buds but up-regulated in OE-TPD1 flower buds and siliques. The silencing of AtPCP-Ba compromised the wider silique of OE-TPD1 plants and inhibited the morphology of OE-TPD1 siliques to the size observed in the wild type. A total of 258 CRPs were identified with the bioinformatic analysis in Arabidopsis, Brassica napus, Glycine max, Oryza sativa, Sorghum bicolor, and Zea mays. Based on the evolutionary tree classification, all CRP members can be categorized into five subgroups. Notably, 107 CRP genes were predicted to exhibit abundant expression in flowers and fruits. Most cysteine-rich peptides exhibited high expression levels in Arabidopsis and Brassica napus. These findings suggested the involvement of the CRP AtPCP-Ba in the TPD1 signaling pathway, thereby regulating silique development in Arabidopsis. [ABSTRACT FROM AUTHOR]

Introduction: Chronic alcoholism is one of the most common neurological diseases in modern society. However, the key mechanisms underlying learning and memory impairments caused by chronic alcohol exposure remain unclear. In this study, a microRNA-messenger RNA (miRNA-mRNA) network was constructed to explore the potential function of key genes in chronic alcohol exposure, their effects on the hippocampus, and their mechanisms which facilitate brain injury in mice. Methods: The Morris water maze test was used to assess the learning ability of mice in each group. Mitochondrial ATPase activity and H2S levels in the hippocampi of mice were determined. Differentially expressed miRNAs and mRNAs in the mouse hippocampus were identified using second-generation sequencing. Using the TargetScan, miRTarBase, and miRDB databases, we predicted miRNA target genes and constructed a miRNA-mRNA regulatory network. Furthermore, using the Gene Ontology and KEGG databases we performed functional enrichment and protein-protein interaction analyses. Real-time quantitative polymerase chain reaction (qPCR) and other methods were employed to verify the mRNA expression of related genes. Results: The Morris water maze test revealed that mice exposed to chronic alcohol exhibited a significantly reduced learning ability compared to the control group (p < 0.05). Compared with the control group, the activity of mitochondrial ATPase in the hippocampal tissue of alcohol-treated mice was significantly decreased (p < 0.01), suggesting brain injury. In the model group, H2S significantly increased in the mice hippocampi (p < 0.01), indicating that chronic alcohol exposure could activate cystathionine β-synthase (CBS) and catalyze the mass formation of H2S, suggesting brain injury. A total of 208 differentially expressed miRNAs and 377 differentially expressed mRNAs were screened through bioinformatic analysis. Enrichment analysis indicated that the main pathways were involved in neurodegeneration and regulation of the Wnt signaling pathway. The PCR detected a significant down regulation in the expressions of FOS and EGR1 genes. Discussion: Consequently, chronic alcohol exposure may regulate the expression of FOS and EGR1 in the hippocampus through miR-222-3p, miR- 132-3p, miR-212-3p, and miR-191-5p, reduce the activity of hippocampal mitochondrial ATPase, activate CBS, catalyze the large amount of H2S formation, and destroy the mitochondrial structure, resulting in decreased learning ability. Our findings revealed valuable genes and miRNAs for the study of chronic alcohol exposure. [ABSTRACT FROM AUTHOR]

Background: The purpose of this study is to investigate the causal effect and potential mechanisms between telomere length and abdominal aortic aneurysm (AAA). Methods: Summary statistics of telomere length and AAA were derived from IEU open genome-wide association studies and FinnGen R9, respectively. Bidirectional Mendelian randomization (MR) analysis was conducted to reveal the causal relationship between AAA and telomere length. Three transcriptome datasets were retrieved from the Gene Expression Omnibus database and telomere related genes was down-loaded from TelNet. The overlapping genes of AAA related differentially expressed genes (DEGs), module genes, and telomere related genes were used for further investigation. Telomere related diagnostic biomarkers of AAA were selected with machine learning algorisms and validated in datasets and murine AAA model. The correlation between biomarkers and immune infiltration landscape was established. Results: Telomere length was found to have a suggestive negative associations with AAA [IVW, OR 95%CI = 0.558 (0.317-0.701), P < 0.0001], while AAA showed no suggestive effect on telomere length [IVW, OR 95%CI = 0.997 (0.990-1.004), P = 0.4061]. A total of 40 genes was considered as telomere related DEGs of AAA. PLCH2, PRKCQ, and SMG1 were selected as biomarkers after multiple algorithms and validation. Immune infiltration analysis and single cell mRNA analysis revealed that PLCH2 and PRKCQ were mainly expressed on T cells, while SMG1 predominantly expressed on T cells, B cells, and monocytes. Murine AAA model experiments further validated the elevated expression of biomarkers. Conclusion: We found a suggestive effect of telomere length on AAA and revealed the potential biomarkers and immune mechanism of telomere length on AAA. This may shed new light for diagnosis and therapeutics on AAA [ABSTRACT FROM AUTHOR]

Purpose: This study aims to reveal the mechanism of fibroblast‐related mitochondrial genes on keloid formation and explore promising signature genes for keloid diagnosis. Method: The distribution of fibroblasts between the keloid sample and control sample based on three keloid datasets, followed by the differentially expressed genes (DEGs) investigation and associated enrichment analysis. Then, hub genes were explored based on DEGs, mitochondrial genes from an online database, as well as fibroblast‐related genes that were revealed by WCGNA. Subsequently, signature genes were screened through machine learning, and their diagnostic value was validated by nomogram. Moreover, the targeted drugs and related transcriptional regulation of these genes were analyzed. Finally, the verification analysis was performed on signature genes using qPCR analysis. Result: A total of totally 329 DEGs were revealed based on three datasets, followed by enrichment analysis. WGCNA revealed a total of 258 fibroblast‐related genes, which were primarily assembled in functions like muscle tissue development. By using machine learning, we screened four signature genes (ACSF2, ALDH1B1, OCIAD2, and SIRT4) based on eight hub genes (fibroblast‐related mitochondrial genes). Nomogram and validation analyses confirmed the well‐diagnostic performance of these four genes in keloid. Immune infiltration and drug correlation analyses showed that SIRT4 was significantly associated with immune cell type 2 T helper cells and molecular drug cyclosporin. All these findings provided new perspectives for the clinical diagnosis and therapy of keloid. Conclusion: The fibroblast‐related mitochondrial genes including SIRT4, OCIAD2, ALDH1B1, and ACSF2 were novel signature genes for keloid diagnosis, offering novel targets and strategies for diagnosis and therapy of keloid. [ABSTRACT FROM AUTHOR]

Background: The current study's objective is to evaluate the molecular genetic mechanisms influencing the biological behavior of hepatocellular carcinoma (HCC) by analyzing the transcriptomic and epigenetic signatures of the tumors. Methods: Transcriptomic data were downloaded from the NCBI GEO database. We investigated the expression differences between the GSE46444 (48 cirrhotic tissues versus 88 HCC tissues) and GSE63898 (168 cirrhotic tissues versus 228 HCC tissues) data sets using GEO2R. Differentially expressed genes were evaluated using GO and KEGG metabolic pathway analysis websites. Whole genome bisulfite sequencing (WGBS) and Methylated DNA Immunoprecipitation Sequencing (MeDIP-Seq) data sets (26 HCC tissues versus 26 adjacent non-tumoral tissues) were also downloaded from the NCBI SRA database. These data sets were analyzed using Bismark and QSEA, respectively. The methylation differences between the groups were assessed using functional enrichment analysis. Results: In the GSE46444 data set, 80 genes were upregulated, and 315 genes were downregulated in the tumor tissue (HCC tissue) compared to the non-tumor cirrhotic tissue. In the GSE63898 data set, 1261 genes were upregulated, and 458 genes were downregulated in the cirrhotic tissue compared to the tumor tissues. WGBS revealed that 20 protein-coding loci were hypermethylated. while the hypomethylated regions were non-protein-coding. The methylated residues of the tumor tissue, non-tumorous cirrhotic tissue, and healthy tissue were comparable. MeDIP-Seq, conducted on tumoral and non-tumoral tissues, identified hypermethylated or hypomethylated areas as protein-coding regions. The functional enrichment analysis indicated that these genes were related to pathways including peroxisome, focal adhesion, mTOR, RAP1, Phospholipase D, Ras, and PI3K/AKT signal transduction. Conclusions: The investigation of transcriptomic and epigenetic mechanisms identified several genes significant in the biological behavior of HCC. These genes present potential targets for the development of targeted therapy. [ABSTRACT FROM AUTHOR]

Objective: At present, targeting molecular-pharmacological therapy is still difficult in neutrophilic asthma. The investigation aims to identify and validate mitochondrion-related gene signatures for diagnosis and specific targeting therapeutics in neutrophilic asthma. Methods: Bronchial biopsy samples of neutrophilic asthma and healthy people were identified from the GSE143303 dataset and then matched with human mitochondrial gene data to obtain mitochondria-related differential genes (MitoDEGs). Signature mitochondria-related diagnostic markers were jointly screened by support vector machine (SVM) analysis, least absolute shrinkage, and selection operator (LASSO) regression. The expression of marker MitoDEGs was evaluated by validation datasets GSE147878 and GSE43696. The diagnostic value was evaluated by receiver operating characteristic (ROC) curve analysis. Meanwhile, the infiltrating immune cells were analyzed by the CIBERSORT. Finally, oxidative stress level and mitochondrial functional morphology for asthmatic mice and BEAS-2B cells were evaluated. The expression of signature MitoDEGs was verified by qPCR. Results: 67 MitoDEGs were identified. Five signature MitoDEGs (SOD2, MTHFD2, PPTC7, NME6, and SLC25A18) were further screened out. The area under the curve (AUC) of signature MitoDEGs presented a good diagnostic performance (more than 0.9). There were significant differences in the expression of signature MitoDEGs between neutrophilic asthma and non-neutrophilic asthma. In addition, the basic features of mitochondrial dysfunction were demonstrated by in vitro and in vivo experiments. The expression of signature MitoDEGs in the neutrophilic asthma mice presented a significant difference from the control group. Conclusions: These MitoDEGs signatures in neutrophilic asthma may hold potential as anchor diagnostic and therapeutic targets in neutrophilic asthma. [ABSTRACT FROM AUTHOR]

Breast cancer (BC) remains a significant public health concern globally, with a high number of reported cases and a substantial number of deaths every year. Accumulating reactive oxygen species (ROS) and oxidative stress are related to BC and the Glutathione S‐transferases Mu (GSTM) family is one of the most important enzymatic detoxifiers associated with many cancers. In this study, UALCAN, Kaplan‐Meier plotter, bc‐GenExMiner, cBioPortal, STRING, Enrichr, and TIMER databases were employed to carry out a comprehensive bioinformatic analysis and provide new insight into the prognostic value of GSTMs in BC. GSTM2‐5 genes in mRNA and protein levels were found to be expressed at lower levels in breast tumors compared to normal tissues, and reduction in mRNA levels is linked to shorter overall survival (OS) and relapse‐free survival (RFS). The lower mRNA levels of GSTMs were strongly associated with the worse Scarff‐Bloom‐Richardson (SBR) grades (p < 0.0001). The mRNA levels of all five GSTMs were substantially higher in estrogen receptor (ER)‐positive and progesterone receptor (PR)‐positive compared to ER‐negative and PR‐negative BC patients. As well, when nodal status was compared, GSTM1, GSTM3, and GSTM5 were significantly higher in nodal‐positive BC patients (p <.01). Furthermore, GSTM4 had the most gene alteration (4%) among other family members, and GSTM5 showed the strongest correlation with CD4+ T cells (Cor=.234, p = 2.22e‐13). In conclusion, our results suggest that GSTM family members may be helpful as biomarkers for prognosis and as therapeutic targets in BC. [ABSTRACT FROM AUTHOR]

Circular RNAs (circRNAs) play a crucial regulatory role in malignant tumor metastasis. This study focused on the role of bone metastasis-related circRBMS3 in breast cancer. Two circRNA microarray datasets were obtained from the GEO database and overlapped bone metastasis-related circRNAs in breast cancer. CircRBMS3 expression was validated in bone metastasis tissues by RT-qPCR. Cellular CCK-8 assay and Transwell assays were performed to measure the effect of circRBMS3 in breast cancer cells. Bioinformatic analyses were performed to identify the binding miRNAs of circRBMS3 and downstream mRNAs. Online database STRING and Cytoscape software were used to analyze PPI interaction and conduct the ceRNA network. GEO database analysis showed that circRBMS3 was one of the upregulated circRNAs among all the metastatic cells. CircRBMS3 was increased in bone metastasis breast cancer tissues compared to non-bone metastasis tissues and associated with poor 3-year overall survival. CircRBMS3 knockdown repressed breast cancer cell proliferation, migration, and invasion, as well as bone resorption gene and osteoclast phenotype gene expression. CircRBMS3 was found to bind withmiR-654-3p. Subsequently, downstream mRNAs were predicted, and the circRBMS3 miR-654-3p-mRNA network was established. In conclusion, circRBMS3 expression was upregulated in bone metastasis breast cancer and might be a potential prognostic marker for patients. Silencing circRBMS3 restrained breast cancer cell proliferation, migration, and invasion, as well as associated with bone metastasis. The circRBMS3-miR-654-3p-mRNAs network elucidated potential mechanisms underlying bone metastasis in breast cancer. [ABSTRACT FROM AUTHOR]

Objectives: Renal cell carcinoma (RCC) is the most common cancer of the kidney. This study aims to evaluate the potential predictive value of E-cadherin, a marker of the epithelial mesenchymal transit (EMT) process that has been associated with tumor metastasis. Methods: We searched PubMed, Embase, and Cochrane Library to identify prospective studies. Hazard ratios (HRs), odds ratios (ORs), and 95% confidence intervals (CIs) were summarized to validate the relationship between E-cadherin and survival and clinical characteristics. The quality of the included studies was assessed using the NOS table. Then, we analyzed genetic data and clinical characteristics from The Cancer Genome Atlas Program (TCGA) database using R language with the dplyr package for validation. Results: Including 21 articles. The analysis revealed a strong link between high E-cadherin expression and favorable prognosis (for OS, HR = 0.35, 95% CI: 0.19–0.62; for PFS, HR = 0.19, 95% CI: 0.03–0.53; for DSS, HR = 0.25, 95% CI: 0.08–0.76; for RFS, HR = 0.71, 95% CI: 0.44–1.16; for DFS, HR = 0.28, 95% CI: 0.13-0.61; for T stage, OR = 0.21, 95% CI: 0.11–0.41; for N stage, OR = 0.07, 95%CI: 0.02-0.25; for M stage, OR = 0.12, 95% CI: 0.02–0.60; for clinical stage, OR = 0.29, 95% CI: 0.18–0.47; for nuclear grade, OR = 0.23, 95% CI: 0.13–0.41; for tumor size, OR = 0.49, 95% CI: 0.26–0.92). The findings were supported by bioinformatic analysis which used TCGA RCC patient's cohort (P < 0.01). Conclusion: Based on the current data, E-cadherin may predict a better prognosis in RCC patients. [ABSTRACT FROM AUTHOR]

Backgrounds: The ossification of the ligamentum flavum (OLF) is one of the major causes of thoracic myelopathy. Previous studies indicated there might be a potential link between metabolic disorder and pathogenesis of OLF. The aim of this study was to determine the potential role of metabolic disorder in the pathogenesis of OLF using the strict bioinformatic workflow for metabolism‐related genes and experimental validation. Methods: A series of bioinformatic approaches based on metabolism‐related genes were conducted to compare the metabolism score between OLF tissues and normal ligamentum flavum (LF) tissues using the single sample gene set enrichment analysis. The OLF‐related and metabolism‐related differentially expressed genes (OMDEGs) were screened out, and the biological functions of OMDEGs were explored, including the Gene Ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes enrichment analysis, and protein–protein interaction. The competing endogenous RNA (ceRNA) network based on pairs of miRNA‐hub OMDEGs was constructed. The correlation analysis was conducted to explore the potential relationship between metabolic disorder and immunity abnormality in OLF. In the end, the cell experiments were performed to validate the roles of GBE1 and TNF‐α in the osteogenic differentiation of LF cells. Results: There was a significant difference of metabolism score between OLF tissues and normal LF tissues. Forty‐nine OMDEGs were screened out and their biological functions were determined. The ceRNA network containing three hub OMDEGs and five differentially expressed miRNAs (DEmiRNAs) was built. The correlation analysis between hub OMDEGs and OLF‐related infiltrating immune cells indicated that metabolic disorder might contribute to the OLF via altering the local immune status of LF tissues. The cell experiments determined the important roles of GBE1 expression and TNF‐α in the osteogenic differentiation of LF cells. Conclusions: This research, for the first time, preliminarily illustrated the vital role of metabolic disorder in the pathogenesis of OLF using strict bioinformatic algorithms and experimental validation for metabolism‐related genes, which could provide new insights for investigating disease mechanism and screening effective therapeutic targets of OLF in the future. [ABSTRACT FROM AUTHOR]

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Photodynamic therapy (PDT) is a promising cancer treatment. This study investigated the antitumor effects and mechanisms of a novel photosensitizer meso-5-[-diethylene triamine pentaacetic acid-aminophenyl]-10,15,20-triphenyl-porphyrin (DTP) mediated PDT (DTP-PDT). Cell viability, reactive oxygen species (ROS), and apoptosis were measured with a Cell Counting Kit-8 assay, DCFH-DA fluorescent probe, and Hoechst staining, respectively. Cell apoptosis- and autophagy-related proteins were examined using western blotting. RNA sequencing was used to screen differentially expressed mRNAs (DERs), and bioinformatic analysis was performed to identify the major biological events after DTP-PDT. Our results show that DTP-PDT inhibited cell growth and induced ROS generation in MCF-7 and SGC7901 cells. The ROS scavenger N-acetyl-L-cysteine (NAC) and the P38 MAPK inhibitor SB203580 alleviated DTP-PDT-induced cytotoxicity. DTP-PDT induced cell apoptosis together with upregulated Bax and downregulated Bcl-2, which could also be inhibited by NAC or SB203580. The level of LC3B-II, a marker of autophagy, was increased by DTP-PDT. A total of 3496 DERs were obtained after DTP-PDT. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses indicated that DERs included those involved in cytosolic ribosomes, the nuclear lumen, protein binding, cell cycle, protein targeting to the endoplasmic reticulum, and ribosomal DNA replication. Disease Ontology and Reactome enrichment analyses indicated that DERs were associated with a variety of cancers and cell cycle checkpoints. Protein-protein interaction results demonstrated that cdk1 and rps27a ranked in the top 10 interacting genes. Therefore, DTP-PDT could inhibit cell growth and induce cell apoptosis and autophagy, partly through ROS and the P38 MAPK signaling pathway. Genes associated with the cell cycle, ribosomes, DNA replication, and protein binding may be the key changes in DTP-PDT-mediated cytotoxicity. [ABSTRACT FROM AUTHOR]

Abstract Background CD147 belongs to the immunoglobulin superfamily, also known as Basigin (BSG), and is a highly glycosylated single transmembrane glycoprotein present in various tissues. Meta and bioinformatic analyses were used to explore the correlation between CD147 expression and the clinicopathological characteristics prognosis of breast cancer. Method Literature related to breast cancer was retrieved through PubMed and CNKI databases, and a meta-analysis was conducted using Review Manager 5.2 software. Results The meta-analysis revealed that all articles included data on 522 patients with breast cancer and 492 normal tissues. CD147 expression in breast cancer tissue was higher compared to that in normal tissue([8.92–139.52]; p

Abstract Background Head and neck squamous cell carcinoma (HNSCC) is the sixth most prevalent malignancy worldwide, with high incidence and poor survival rates. RBP1 is highly expressed in several kinds of cancer and plays a potential prognostic factor. However, the relationship between RBP1 and HNSCC were analyzed based on The Cancer Genome Atlas (TCGA) database. Materials and methods RBP1 expression and clinical information were obtained from the Cancer Genome Atlas (TCGA) database. Tumor tissue and adjacent normal tissue of 6 HNSCC patients were collected to analyze the RBP1 mRNA expression level by quantitative PCR. Cox regression analysis was used to evaluate the prognostic values of RBP1 and clinical data in HNSCC. A nomogram was also established to predict the impact of RBP1 on prognosis based on Cox multivariate results. The methylation level of RBP1 in HNSC and its prognosis were analyzed in UALACN and MethSurv. Finally, the potential biological functions of RBP1 were investigated using gene set enrichment analysis (GSEA) and single sample GSEA (ssGSEA). Results The mRNA expression levels of RBP1 were highly expressed in HNSCC tissue. The Cox analyses demonstrate that highly-expressed RBP1 is an independent prognosis marker(P

Abstract Background Muscle atrophy is a typical affliction in patients affected by knee Osteoarthritis (KOA). This study aimed to examine the potential pathogenesis and biomarkers that coalesce to induce muscle atrophy, primarily through the utilization of bioinformatics analysis. Methods Two distinct public datasets of osteoarthritis and muscle atrophy (GSE82107 and GSE205431) were subjected to differential gene expression analysis and gene set enrichment analysis (GSEA) to probe for common differentially expressed genes (DEGs) and conduct transcription factor (TF) enrichment analysis from such genes. Venn diagrams were used to identify the target TF, followed by the construction of a protein-protein interaction (PPI) network of the common DEGs governed by the target TF. Hub genes were determined through the CytoHubba plug-in whilst their biological functions were assessed using GSEA analysis in the GTEx database. To validate the study, reverse transcriptase real-time quantitative polymerase chain reaction (qRT-PCR), enzyme-linked immunosorbent assay (ELISA), and Flow Cytometry techniques were employed. Results A total of 138 common DEGs of osteoarthritis and muscle atrophy were identified, with 16 TFs exhibiting notable expression patterns in both datasets. Venn diagram analysis identified early growth response gene-1 (EGR1) as the target TF, enriched in critical pathways such as epithelial mesenchymal transition, tumor necrosis factor-alpha signaling NF-κB, and inflammatory response. PPI analysis revealed five hub genes, including EGR1, FOS, FOSB, KLF2, and JUNB. The reliability of EGR1 was confirmed by validation testing, corroborating bioinformatics analysis trends. Conclusions EGR1, FOS, FOSB, KLF2, and JUNB are intricately involved in muscle atrophy development. High EGR1 expression directly regulated these hub genes, significantly influencing postoperative muscle atrophy progression in KOA patients.

Abstract Background Gliomas are aggressive brain tumors with poor prognosis. Understanding the tumor immune microenvironment (TIME) in gliomas is essential for developing effective immunotherapies. This study aimed to identify TIME-related biomarkers in glioma using bioinformatic analysis of RNA-seq data. Methods In this study, we employed weighted gene co-expression network analysis (WGCNA) on bulk RNA-seq data to identify TIME-related genes. To identify prognostic genes, we performed univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. Based on these genes, we constructed a prognostic signature and delineated risk groups. To validate the prognostic signature, external validation was conducted. Results CD8 + T cell infiltration was strongly correlated with glioma patient prognosis. We identified 115 CD8 + T cell-related genes through integrative analysis of bulk-seq data. CDCA5, KIF11, and KIF4A were found to be significant immune-related genes (IRGs) associated with overall survival in glioma patients and served as independent prognostic factors. We developed a prognostic nomogram that incorporated these genes, age, gender, and grade, providing a reliable tool for clinicians to predict patient survival probabilities. The nomogram’s predictions were supported by calibration plots, further validating its accuracy. Conclusion In conclusion, our study identifies CD8 + T cell infiltration as a strong predictor of glioma patient outcomes and highlights the prognostic value of genes. The developed prognostic nomogram, incorporating these genes along with clinical factors, provides a reliable tool for predicting patient survival probabilities and has important implications for personalized treatment decisions in glioma.

Abstract Background Protein–protein interactions are the primary means through which proteins carry out their functions. These interactions thus have crucial roles in life activities. The wide availability of fully sequenced animal and plant genomes has facilitated establishment of relatively complete global protein interaction networks for some model species. The genomes of cultivated and wild peanut (Arachis hypogaea L.) have also been sequenced, but the functions of most of the encoded proteins remain unclear. Results We here used homologous mapping of validated protein interaction data from model species to generate complete peanut protein interaction networks for A. hypogaea cv. ‘Tifrunner’ (282,619 pairs), A. hypogaea cv. ‘Shitouqi’ (256,441 pairs), A. monticola (440,470 pairs), A. duranensis (136,363 pairs), and A. ipaensis (172,813 pairs). A detailed analysis was conducted for a putative disease-resistance subnetwork in the Tifrunner network to identify candidate genes and validate functional interactions. The network suggested that DX2UEH and its interacting partners may participate in peanut resistance to bacterial wilt; this was preliminarily validated with overexpression experiments in peanut. Conclusion Our results provide valuable new information for future analyses of gene and protein functions and regulatory networks in peanut.

Abstract Background The biological mechanisms driving orthodontic tooth movement (OTM) remain incompletely understood. Gingival crevicular fluid (GCF) is an important indicator of the periodontal bioprocess, providing valuable cues for probing the molecular mechanisms of OTM. Methods A rigorous review of the clinical studies over the past decade was conducted after registering the protocol with PROSPERO and adhering to inclusion criteria comprising human subjects, specified force magnitudes and force application modes. The thorough screening investigated differentially expressed proteins (DEPs) in GCF associated with OTM. Protein-protein interaction (PPI) analysis was carried out using the STRING database, followed by further refinement through Cytoscape to isolate top hub proteins. Results A comprehensive summarization of the OTM-related GCF studies was conducted, followed by an in-depth exploration of biomarkers within the GCF. We identified 13 DEPs, including ALP, IL-1β, IL-6, Leptin, MMP-1, MMP-3, MMP-8, MMP-9, PGE2, TGF-β1, TNF-α, OPG, RANKL. Bioinformatic analysis spotlighted the top 10 hub proteins and their interactions involved in OTM. Based on these findings, we have proposed a hypothetic diagram for the time-course bioprocess in OTM, which involves three phases containing sequential cellular and molecular components and their interplay network. Conclusions This work has further improved our understanding to the bioprocess of OTM, suggesting biomarkers as potential modulating targets to enhance OTM, mitigate adverse effects and support real-time monitoring and personalized orthodontic cycles.

Background: CD147 belongs to the immunoglobulin superfamily, also known as Basigin (BSG), and is a highly glycosylated single transmembrane glycoprotein present in various tissues. Meta and bioinformatic analyses were used to explore the correlation between CD147 expression and the clinicopathological characteristics prognosis of breast cancer. Method: Literature related to breast cancer was retrieved through PubMed and CNKI databases, and a meta-analysis was conducted using Review Manager 5.2 software. Results: The meta-analysis revealed that all articles included data on 522 patients with breast cancer and 492 normal tissues. CD147 expression in breast cancer tissue was higher compared to that in normal tissue([8.92–139.52]; p < 0.00001 I2 = 80%) and negatively correlated with LM, clinical stage, histological grade, and ER positive expression. Bioinformatic analysis revealed that the expression of CD147 in breast cancer tissue was higher than that in normal tissue, and its high expression was closely related to the clinicopathological characteristics of patients, such as LM, histological grading, and clinical staging. According to the TIMER database, CD147 expression was closely related to immune cell infiltration in breast cancer. Conclusion: These results indicated that high CD147 expression might be closely linked to the occurrence as well as the development of breast cancer, and can function as a good indicator of prognosis in the future, providing new methods and ideas for the prevention and treatment of breast cancer. [ABSTRACT FROM AUTHOR]

Arteriovenous fistula (AVF) is currently the preferred vascular access for hemodialysis patients. However, the low maturation rate of AVF severely affects its use in patients. A more comprehensive understanding and study of the mechanisms of AVF maturation is urgently needed. In this study, we downloaded the publicly available datasets (GSE119296 and GSE220796) from the Gene Expression Omnibus (GEO) and merged them for subsequent analysis. We screened 84 differentially expressed genes (DEGs) and performed the functional enrichment analysis. Next, we integrated the results obtained from the degree algorithm provided by the Cytohubba plug-in, Molecular complex detection (MCODE) plug-in, weighted gene correlation network analysis (WGCNA), and Least absolute shrinkage and selection operator (LASSO) logistic regression. This integration allowed us to identify CTSG as a hub gene associated with AVF maturation. Through the literature search and Pearson's correlation analysis, the genes matrix metalloproteinase 2 (MMP2) and MMP9 were identified as potential downstream effectors of CTSG. We then collected three immature clinical AVF vein samples and three mature samples and validated the expression of CTSG using immunohistochemistry (IHC) and double-immunofluorescence staining. The IHC results demonstrated a significant decrease in CTSG expression levels in the immature AVF vein samples compared to the mature samples. The results of double-immunofluorescence staining revealed that CTSG was expressed in both the intima and media of AVF veins. Moreover, the expression of CTSG in vascular smooth muscle cells (VSMCs) was significantly higher in the mature samples compared to the immature samples. The results of Masson's trichrome and collagen I IHC staining demonstrated a higher extent of collagen deposition in the media of immature AVF veins compared to the mature. By constructing an in vitro CTSG overexpression model in VSMCs, we found that CTSG upregulated the expression of MMP2 and MMP9 while downregulating the expression of collagen I and collagen III. Furthermore, CTSG was found to inhibit VSMC migration. CTSG may promote AVF maturation by stimulating the secretion of MMP2 and MMP9 from VSMCs and reducing the extent of medial fibrosis in AVF veins by inhibiting the secretion of collagen I and collagen III. [ABSTRACT FROM AUTHOR]

Abstract Prostate cancer remains a complex and challenging disease, necessitating innovative approaches for prognosis and therapeutic guidance. This study integrates machine learning techniques to develop a novel mitophagy-related long non-coding RNA (lncRNA) signature for predicting the progression of prostate cancer. Leveraging the TCGA-PRAD dataset, we identify a set of four key lncRNAs and formulate a riskscore, revealing its potential as a prognostic indicator. Subsequent analyses unravel the intricate connections between riskscore, immune cell infiltration, mutational landscapes, and treatment outcomes. Notably, the pan-cancer exploration of YEATS2-AS1 highlights its pervasive impact, demonstrating elevated expression across various malignancies. Furthermore, drug sensitivity predictions based on riskscore guide personalized chemotherapy strategies, with drugs like Carmustine and Entinostat showing distinct suitability for high and low-risk group patients. Regression analysis exposes significant correlations between the mitophagy-related lncRNAs, riskscore, and key mitophagy-related genes. Molecular docking analyses reveal promising interactions between Cyclophosphamide and proteins encoded by these genes, suggesting potential therapeutic avenues. This comprehensive study not only introduces a robust prognostic tool but also provides valuable insights into the molecular intricacies and potential therapeutic interventions in prostate cancer, paving the way for more personalized and effective clinical approaches.

Abstract Increasing evidence suggests that mitophagy is crucially involved in the progression of polycystic ovary syndrome (PCOS). Exploration of PCOS-specific biomarkers related to mitophagy is expected to provide critical insights into disease pathogenesis. In this study, we employed bioinformatic analyses and machine learning algorithms to determine novel biomarkers for PCOS that may be tied with mitophagy. A grand total of 12 differential expressed mitophagy-related genes (DE‐MRGs) associated with PCOS were identified. TOMM5 and MAP1LC3A among the 12 DE‐MRGs were recognized as potential marker genes by LASSO, RF and SVM‐RFE algorithms. The area under the ROC curve (AUROC) of MAP1LC3A were all greater than 0.8 both in the training set and validation sets. The CIBERSORT analysis indicated a potential association between alterations in the immune microenvironment of PCOS individuals and MAP1LC3A expression. In addition, we found that MAP1LC3A was positively related to the testosterone levels of PCOS patients. Overall, MAP1LC3A was identified as optimal PCOS-specific biomarkers related to mitophagy. Our findings created a diagnostic strength and offered a perspective for investigating the mitophagy process in PCOS.

Abstract Background The search for new bioactive natural compounds with anticancer activity is still of great importance. Even though their potential for diagnostics and treatment of cancer has already been proved, the availability is still limited. Hypericin, a naphthodianthrone isolated essentially from plant source Hypericum perforatum L. along with other related anthraquinones and bisanthraquinones belongs to this group of compounds. Although it has been proven that hypericin is synthesized by the polyketide pathway in plants, none of the candidate genes coding for key enzymes has been experimentally validated yet. Despite the rare occurrence of anthraquinones in plants, their presence in microorganisms, including endophytic fungi, is quite common. Unlike plants, several biosynthetic genes grouped into clusters (BGCs) in fungal endophytes have already been characterized. Results The aim of this work was to predict, identify and characterize the anthraquinone BGCs in de novo assembled and functionally annotated genomes of selected endophytic fungal isolates (Fusarium oxysporum, Plectosphaerella cucumerina, Scedosporium apiospermum, Diaporthe eres, Canariomyces subthermophilus) obtained from different tissues of Hypericum spp. The number of predicted type I polyketide synthase (PKS) BGCs in the studied genomes varied. The non-reducing type I PKS lacking thioesterase domain and adjacent discrete gene encoding protein with product release function were identified only in the genomes of C. subthermophilus and D. eres. A candidate bisanthraquinone BGC was predicted in C. subthermophilus genome and comprised genes coding the enzymes that catalyze formation of the basic anthraquinone skeleton (PKS, metallo-beta-lactamase, decarboxylase, anthrone oxygenase), putative dimerization enzyme (cytochrome P450 monooxygenase), other tailoring enzymes (oxidoreductase, dehydrogenase/reductase), and non-catalytic proteins (fungal transcription factor, transporter protein). Conclusions The results provide an insight into genetic background of anthraquinone biosynthesis in Hypericum-borne endophytes. The predicted bisanthraquinone gene cluster represents a basis for functional validation of the candidate biosynthetic genes in a simple eukaryotic system as a prospective biotechnological alternative for production of hypericin and related bioactive anthraquinones.

IgA nephropathy (IgAN) and Sjogren's syndrome (SS) are two autoimmune diseases with undetermined etiology and related to abnormal activation of lymphocytes. This study aims to explore the crucial genes, pathways and immune cells between IgAN and SS. Gene expression profiles of IgAN and SS were obtained from the Gene Expression Omnibus and Nephroseq data. Differentially expressed gene (DEG) and weighted gene co-expression network analyses (WGCNA) were done to identify common genes. Enrichment analysis and protein–protein interaction network were used to explore potential molecular pathways and crosstalk genes between IgAN and SS. The results were further verified by external validation and immunohistochemistry (IHC) analysis. Additionally, immune cell analysis and transcription factor prediction were also conducted. The DEG analysis revealed 28 commonly up-regulated genes, while WGCNA identified 98 interactively positive-correlated module genes between IgAN and SS. The enrichment analysis suggested that these genes were mainly involved in the biological processes of response to virus and antigen processing and presentation. The external validation and IHC analysis identified 5 hub genes (PSMB8, PSMB9, IFI44, ISG15, and CD53). In the immune cell analysis, the effector memory CD8 T and T follicular helper cells were significantly activated, and the corresponding proportions showed positively correlations with the expressions of the 5 hub genes in the two autoimmune diseases. Together, our data identified the crosstalk genes, molecular pathways, and immune cells underlying the IgAN and SS, which provides valuable insights into the intricate mechanisms of these diseases and offers potential intervention targets. [ABSTRACT FROM AUTHOR]

Ferroptosis has been observed to play an important role during erythrocyte differentiation (ED). However, the biological gene markers and ferroptosis mechanisms in ED remain unknown. We downloaded the datasets of ED in human umbilical cord blood-derived CD34+ cells from the Gene Expression Omnibus database. Using median differentiation time, the sample was categorized into long and short groups. The differentially expressed ferroptosis-related genes (DE-FRGs) were screened using differential expression analysis. The enrichment analyses and a protein-protein interaction (PPI) network were conducted. To predict the ED stage, a logistic regression model was constructed using the least absolute shrinkage and selection operator (LASSO). Overall, 22 DE-FRGs were identified. Ferroptosisrelated pathways were enriched using Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes. Gene Set Enrichment Analysis and Gene Set Variation Analysis revealed the primary involvement of DE-FRGs in JAK-STAT, MAPK, PI3K-AKT-mTORC1, WNT, and NOTCH signaling pathways. Ten-hub DE-FRGs were obtained using PPI analysis. Furthermore, we constructed mRNA-microRNA (miRNA) and mRNA-transcription factor networks. Immune cell infiltration levels differed significantly during ED. LASSO regression analysis established a signature using six DE-FRGs (ATF3, CDH2, CHAC1, DDR2, DPP4, and GDF15) related to the ED stage. Bioinformatic analyses identified ferroptosis-associated genes during ED, which were further validated. Overall, we identified ferroptosis-related genes to predict their correlations in ED. Exploring the underlying mechanisms of ferroptosis may help us better understand pathophysiological changes in ED and provide new evidence for clinical transformation. [ABSTRACT FROM AUTHOR]

The Qingfei Paidu decoction (QFPDD) is a widely acclaimed therapeutic formula employed nationwide for the clinical management of coronavirus disease 2019 (COVID-19). QFPDD exerts a synergistic therapeutic effect, characterized by its multi-component, multi-target, and multi-pathway action. However, the intricate interactions among the ingredients and targets within QFPDD and their systematic effects in multiple tissues remain undetermined. To address this, we qualitatively characterized the chemical components of QFPDD. We integrated multi-tissue transcriptomic analysis with GraphDTA, a deep learning model, to screen for potential compound–target interactions of QFPDD in multiple tissues. We predicted 13 key active compounds, 127 potential targets and 27 pathways associated with QFPDD across six different tissues. Notably, oleanolic acid-AXL exhibited leading affinity in the heart, blood, and liver. Molecular docking and molecular dynamics simulation confirmed their strong binding affinity. The robust interaction between oleanolic acid and the AXL receptor suggests that AXL is a promising target for developing clinical intervention strategies. Through the construction of a multi-tissue compound–target interaction network, our study further elucidated the mechanisms through which QFPDD effectively combats COVID-19 in multiple tissues. Our work also establishes a framework for future investigations into the systemic effects of other Traditional Chinese Medicine (TCM) formulas in disease treatment. [ABSTRACT FROM AUTHOR]

Background: Neutrophil extracellular traps (NETs) are related to the prognosis of cancer patients. Nevertheless, the potential prognostic values of NETs in skin cutaneous melanoma (SKCM) remains largely unknown. Materials and methods: The NET‐related gene signature was constructed by LASSO Cox regression analysis using the TCGA‐SKCM cohort. The overall survival (OS) and immune status in SKCM patients between the high‐ and low‐NET score (high‐score, low‐score) groups were explored. The scRNA‐seq dataset GSE115978 was used to understand the role of NET score in SKCM at single cell resolution. Results: A five NET genes‐based signature (TLR2, CLEC6A, PDE4B, SLC22A4 and CYP4F3) was constructed as the NET‐related prognostic model for SKCM. The OS of SKCM patients with low‐score was better than that in patients with high‐score. Additionally, NET score was negatively associated with infiltration of some immune cells (e.g. type I Macrophages, CD8‐T cells, CD4‐T cells). Moreover, patients with high‐score had low stromal, immune and ESTIMATE scores. Furthermore, drug sensitivity analysis results showed that Lapatinib, Trametinib and Erlotinib may have better therapeutic advantages in patients with high‐score. Conclusion: We established a NET‐related five gene signature in SKCM and found that the NET‐related signature may exhibit a good predictive ability for SKCM prognosis. The NET score may not only predict the survival outcome and drug sensitivity in SKCM, but also reflect the immune conditions of SKCM patients. [ABSTRACT FROM AUTHOR]

Osteoarthritis (OA) is a widespread inflammatory joint disease with significant global disability burden. Cuproptosis, a newly identified mode of cell death, has emerged as a crucial factor in various pathological conditions, including OA. In this context, our study aims to investigate the intrinsic relationship between cuproptosis‐related genes (CRGs) and OA, and assess their potential as biomarkers for OA diagnosis and treatment. Datasets from the GEO databases were analysed the differential expression of CRGs, leading to the identification of 10 key CRGs (CDKN2A, DLD, FDX1, GLS, LIAS, LIPT1, MTF1, PDHA1, DLAT and PDHB). A logistic regression analysis and calibration curves were used to show excellent diagnostic accuracy. Consensus clustering revealed two CRG patterns, with Cluster 1 indicating a closer association with OA progression. RT‐PCR confirmed a significant increase in the expression levels of these nine key genes in IL‐1β‐induced C28/i2 cells, and the expression of CDKN2A and FDX1 were also elevated in conditioned monocytes, while the expression of GLS and MTF1 were significantly decreased. In vitro experiments demonstrated that the expression levels of these 7/10 CRGs were significantly increased in chondrocytes induced by IL‐1β, and upon stimulation with cuproptosis inducers, chondrocyte apoptosis was exacerbated, accompanied by an increase in the expression of cuproptosis‐related proteins. These further substantiated our research findings and indicated that the nine selected cuproptosis genes have high potential for application in the diagnosis of OA. [ABSTRACT FROM AUTHOR]

Prostate cancer remains a complex and challenging disease, necessitating innovative approaches for prognosis and therapeutic guidance. This study integrates machine learning techniques to develop a novel mitophagy-related long non-coding RNA (lncRNA) signature for predicting the progression of prostate cancer. Leveraging the TCGA-PRAD dataset, we identify a set of four key lncRNAs and formulate a riskscore, revealing its potential as a prognostic indicator. Subsequent analyses unravel the intricate connections between riskscore, immune cell infiltration, mutational landscapes, and treatment outcomes. Notably, the pan-cancer exploration of YEATS2-AS1 highlights its pervasive impact, demonstrating elevated expression across various malignancies. Furthermore, drug sensitivity predictions based on riskscore guide personalized chemotherapy strategies, with drugs like Carmustine and Entinostat showing distinct suitability for high and low-risk group patients. Regression analysis exposes significant correlations between the mitophagy-related lncRNAs, riskscore, and key mitophagy-related genes. Molecular docking analyses reveal promising interactions between Cyclophosphamide and proteins encoded by these genes, suggesting potential therapeutic avenues. This comprehensive study not only introduces a robust prognostic tool but also provides valuable insights into the molecular intricacies and potential therapeutic interventions in prostate cancer, paving the way for more personalized and effective clinical approaches. [ABSTRACT FROM AUTHOR]

The progression of Toxoplasma gondii (T. gondii) invasion is aided by rhoptry proteins (ROPs), which are also crucial for the parasite's survival in host cells. In this study, in silico analysis was performed to examine the various aspects of the ROP29 protein, such as physicochemical properties, potential T‐ and B‐cell epitopes, and other significant features. The research revealed that there were 55 possible sites for posttranslational modification in the ROP29 protein. The secondary structure of the ROP29 protein consists of a random coil, an alpha‐helix, and an extended strand, which account for 49.69%, 36.81%, and 13.50%, respectively. Moreover, a number of putative T‐ and B‐cell epitopes for ROP29 were found. The Ramachandran plot showed that 88.91% (crude model) and 97.54% (refine model) of the amino acid residues were located in the favored regions. Also, the testing of this protein's antigenicity and allergenicity showed that it was nonallergenic and immunogenic. Our results suggested that employing in silico tools to apply structural and functional predictions to the ROP29 protein can lower the likelihood that laboratory investigations will fail. This research served as a crucial foundation for further research. More research is required in the future in suitable animal model employing ROP29 alone or in combination with other antigens. [ABSTRACT FROM AUTHOR]

Increasing evidence suggests that mitophagy is crucially involved in the progression of polycystic ovary syndrome (PCOS). Exploration of PCOS-specific biomarkers related to mitophagy is expected to provide critical insights into disease pathogenesis. In this study, we employed bioinformatic analyses and machine learning algorithms to determine novel biomarkers for PCOS that may be tied with mitophagy. A grand total of 12 differential expressed mitophagy-related genes (DE‐MRGs) associated with PCOS were identified. TOMM5 and MAP1LC3A among the 12 DE‐MRGs were recognized as potential marker genes by LASSO, RF and SVM‐RFE algorithms. The area under the ROC curve (AUROC) of MAP1LC3A were all greater than 0.8 both in the training set and validation sets. The CIBERSORT analysis indicated a potential association between alterations in the immune microenvironment of PCOS individuals and MAP1LC3A expression. In addition, we found that MAP1LC3A was positively related to the testosterone levels of PCOS patients. Overall, MAP1LC3A was identified as optimal PCOS-specific biomarkers related to mitophagy. Our findings created a diagnostic strength and offered a perspective for investigating the mitophagy process in PCOS. [ABSTRACT FROM AUTHOR]

Delta-12 fatty acid desaturases (FAD2s) actively regulate stress responses and cell differentiation in living organisms. In this study, six homologous FAD2 genes were identified based on the genome sequence of Lentinula edodes. Then, the six FAD2 protein sequences were analyzed using bioinformatics tools, including ExPASy ProtParam, SignalP, TMHMM, and TargetP. These analyses were performed to predict the physical and chemical properties, signal peptides, and transmembrane and conserved domains of these proteins. The polypeptide sequences were aligned, and a maximum likelihood phylogenetic tree was constructed using MEGA 7.0 software to elucidate the phylogenetic relationships between homologous FAD2 sequences. The results demonstrated that the FAD2 proteins contained three conserved histidine-rich regions (HXXXH, HXXHH, and HXXHH), which included eight histidine residues. The linoleic acid content and FAD2 enzyme activity were further analyzed, and the levels in the mutagenic heat-tolerant strain 18N44 were lower than those in the wild-type strain 18. Interestingly, the expression levels of the FAD2-2 and FAD2-3 genes under heat stress in strain 18N44 were lower than those in strain 18. These findings indicated that FAD2-2 and FAD2-3 may play major roles in the synthesis of linoleic acid during heat stress. [ABSTRACT FROM AUTHOR]