UNASSIGNED: The rapid spread of plasmid-mediated tet(X4) conferring high tigecycline resistance poses a significant threat to public health. Escherichia coli as the most common pathogen which carries tet(X4) has been widely disseminated in China. Thus, comprehensive investigations are required to understand the mechanism of transmission of tet(X4)-positive E. coli.
UNASSIGNED: In this study, a total of 775 nonduplicate samples were collected in Guangdong, China from 2019 to 2020. We screened for tet(X4)-positive E. coli by PCR amplification and species identification. Furthermore, we analyzed the phylogenetics and genetic context of tet(X4)-positive E. coli through whole-genome sequencing and long-reads sequencing.
UNASSIGNED: Overall, 146 (18.84%) tet(X4)-positive E. coli were isolated, comprising 2 isolates from humans and 144 isolates from pigs. The majority of tet(X4)-positive E. coli exhibited resistance to multiple antibiotics but all of them were susceptible to amikacin and colistin. Phylogenetic analysis showed that ST877, ST871, and ST195 emerged as the predominant sequence types in tet(X4)-positive E. coli. Further analysis revealed various genetic environments associated with the horizontal transfer of tet(X4). Notably, a 100-kbp large fragment insertion was discovered downstream of tet(X4), containing a replicon and a 40-kbp gene cluster for the bacterial type IV secretion system.
UNASSIGNED: The high colonization rate of tet(X4)-positive E. coli in animals suggests that colonization as a key factor in its dissemination to humans. Diverse genetic context may contribute to the transfer of tet(X4). Our findings underline the urgent need for controlling the spread of plasmid-mediated tigecycline resistance.

BACKGROUND: Osteoporosis (OP) is characterized by bone mass decrease and bone tissue microarchitectural deterioration in bone tissue. This study identified potential biomarkers for early diagnosis of OP and elucidated the mechanism of OP.
METHODS: Gene expression profiles were downloaded from Gene Expression Omnibus (GEO) for the GSE56814 dataset. A gene co-expression network was constructed using weighted gene co-expression network analysis (WGCNA) to identify key modules associated with healthy and OP samples. Functional enrichment analysis was conducted using the R clusterProfiler package for modules to construct the transcriptional regulatory factor networks. We used the \"ggpubr\" package in R to screen for differentially expressed genes between the two samples. Gene set variation analysis (GSVA) was employed to further validate hub gene expression levels between normal and OP samples using RT-PCR and immunofluorescence to evaluate the potential biological changes in various samples.
RESULTS: There was a distinction between the normal and OP conditions based on the preserved significant module. A total of 100 genes with the highest MM scores were considered key genes. Functional enrichment analysis suggested that the top 10 biological processes, cellular component and molecular functions were enriched. The Toll-like receptor signaling pathway, TNF signaling pathway, PI3K-Akt signaling pathway, osteoclast differentiation, JAK-STAT signaling pathway, and chemokine signaling pathway were identified by Kyoto Encyclopedia of Genes and Genomes pathway analysis. SIRT1 and ZNF350 were identified by Wilcoxon algorithm as hub differentially expressed transcriptional regulatory factors that promote OP progression by affecting oxidative phosphorylation, apoptosis, PI3K-Akt-mTOR signaling, and p53 pathway. According to RT-PCR and immunostaining results, SIRT1 and ZNF350 levels were significantly higher in OP samples than in normal samples.
CONCLUSIONS: SIRT1 and ZNF350 are important transcriptional regulatory factors for the pathogenesis of OP and may be novel biomarkers for OP treatment.

Caffeine has been extensively studied in the context of CNS pathologies as many researchers have shown that consuming it reduces pro-inflammatory biomarkers, potentially delaying the progression of neurodegenerative pathologies. Several lines of evidence suggest that adenosine receptors, especially A1 and A2A receptors, are the main targets of its neuroprotective action. We found that caffeine pretreatment 15 min before LPS administration reduced the expression of Il1b in the hippocampus and striatum. The harmful modulation of caffeine-induced inflammatory response involved the downregulation of the expression of A2A receptors, especially in the hippocampus. Caffeine treatment alone promoted the downregulation of the adenosinergic receptor Adora2A; however, this promotion effect was reversed by LPS. Although administering caffeine increased the expression of the enzymes DNA methyltransferases 1 and 3A and decreased the expression of the demethylase enzyme Tet1, this effect was reversed by LPS in the hippocampus of mice that were administered Caffeine + LPS, relative to the basal condition; no significant differences were observed in the methylation status of the promoter regions of adenosine receptors. Finally, the bioinformatics analysis of the expanded network demonstrated the following results: the Adora2B gene connects the extended networks of the adenosine receptors Adora1 and Adora2A; the Mapk3 and Esr1 genes connect the extended Adora1 network; the Mapk4 and Arrb2 genes connect the extended Adora2A network with the extended network of the proinflammatory cytokine Il1β. These results indicated that the anti-inflammatory effects of acute caffeine administration in the hippocampus may be mediated by a complex network of interdependencies between the Adora2B and Adora2A genes.

Background: Globally, the most common form of arrhythmias is atrial fibrillation (AF), which causes severe morbidity, mortality, and socioeconomic burden. The application of machine learning algorithms in combination with weighted gene co-expression network analysis (WGCNA) can be used to screen genes, therefore, we aimed to screen for potential biomarkers associated with AF development using this integrated bioinformatics approach. Methods: On the basis of the AF endocardium gene expression profiles GSE79768 and GSE115574 from the Gene Expression Omnibus database, differentially expressed genes (DEGs) between AF and sinus rhythm samples were identified. DEGs enrichment analysis and transcription factor screening were then performed. Hub genes for AF were screened using WGCNA and machine learning algorithms, and the diagnostic accuracy was assessed by the receiver operating characteristic (ROC) curves. GSE41177 was used as the validation set for verification. Subsequently, we identified the specific signaling pathways in which the key biomarkers were involved, using gene set enrichment analysis and reverse prediction of mRNA-miRNA interaction pairs. Finally, we explored the associations between the hub genes and immune microenvironment and immune regulation. Results: Fifty-seven DEGs were identified, and the two hub genes, hypoxia inducible factor 1 subunit alpha inhibitor (HIF1AN) and mitochondrial inner membrane protein MPV17 (MPV17), were screened using WGCNA combined with machine learning algorithms. The areas under the receiver operating characteristic curves for MPV17 and HIF1AN validated that two genes predicted AF development, and the differential expression of the hub genes was verified in the external validation dataset. Enrichment analysis showed that MPV17 and HIF1AN affect mitochondrial dysfunction, oxidative stress, gap junctions, and other signaling pathway functions. Immune cell infiltration and immunomodulatory correlation analyses showed that MPV17 and HIF1AN are strongly correlated with the content of immune cells and significantly correlated with HLA expression. Conclusion: The identification of hub genes associated with AF using WGCNA combined with machine learning algorithms and their correlation with immune cells and immune gene expression can elucidate the molecular mechanisms underlying AF occurrence. This may further identify more accurate and effective biomarkers and therapeutic targets for the diagnosis and treatment of AF.

UNASSIGNED: Our study aimed to elucidate the association between single nucleotide polymorphisms (SNPs) in CYP2B6 gene and susceptibility to lung cancer (LC).
UNASSIGNED: Five SNPs in CYP2B6 were genotyped in Chinese Han population (507 cases and 505 controls) utilizing Agena MassARRAY. The relationship between these SNPs and LC susceptibility was assessed using odds ratios, 95% confidence intervals, and χ2 tests. Additionally, multifactor dimensionality reduction was employed to analyze SNP-SNP interactions. Bioinformatics methods were applied to investigate the function of these SNPs.
UNASSIGNED: We found that rs2099361 was associated with an increased susceptibility to LC in the codominant model (OR = 1.31, p = 0.045). Stratification analysis revealed the allele G at rs4803418 and the allele T at rs4803420 of CYP2B6 (BMI >24 kg/m2) were significantly linked to decreased susceptibility of LC. Conversely, the allele C at rs12979270 (BMI >24 kg/m2) showed increased susceptibility to LC. Moreover, a robust redundant relationship between rs12979270 and rs4803420 was identified in the study. According to the VannoPortal database, we found that rs4803420, rs12979270 and rs2099361 may modulate the binding affinity of LMNB1, SP1 and HDAC2, respectively.
UNASSIGNED: Our results suggest that SNPs in the CYP2B6 gene play crucial roles in LC susceptibility.

UNASSIGNED: Malignant gliomas are the most prevalent and fatal types of primary malignant brain tumors with poor prognosis. Protein phosphatase 3 catalytic subunit beta (PPP3CB) is a pivotal constituent of the Ca2+/calmodulin-dependent serine/threonine protein phosphatases and widely expressed in brain. We aimed at identifying whether PPP3CB has potential in being a novel biomarker of malignant gliomas, bringing new insights to clinical management and therapy.
UNASSIGNED: Transcriptomes and clinical data of Glioblastoma (GBM) and low-grade glioma (LGG) samples were downloaded from TCGA and CGGA. We first explored the expressional and survival features of tumor tissues. Then, PPP3CB-associated genes were identified and their functional pathways were explored through GSEA analyses. Western blotting was conducted to modify PPP3CB expression. Samples of glioma patients and healthy controls were collected and immunohistochemistry (IHC) staining was performed to detect protein level. Further, we carried out an immune infiltration analysis, explored the correlation between PPP3CB and immune checkpoint genes, as well as to assessed the tumor mutation burden (TMB) and tumor microenvironment score (TMEscore) of PPP3CB.
UNASSIGNED: PPP3CB expression in malignant glioma tissues was significantly downregulated and was considered an independent prognostic factor. Several functional pathways were observed through functional pathway analyses. PPP3CB\'s expression was strongly related to the infiltration of various immune cells and expression of key immune checkpoint genes. PPP3CB expression in high-grade gliomas was significantly lower, affecting glioma cells\' proliferation and apoptosis in vitro.
UNASSIGNED: PPP3CB was a potential biomarker for the diagnosis and prognosis of malignant gliomas.

SOX9 plays a crucial role in the male reproductive system, brain, and kidneys. In this study, we firstly analyzed the complete cDNA sequence and expression patterns for SOX9 from Gekko japonicus SOX9 (gjSOX9), carried out bioinformatic analyses of physiochemical properties, structure, and phylogenetic evolution, and compared these with other members of the gjSOX family. The results indicate that gjSOX9 cDNA comprises 1895 bp with a 1482 bp ORF encoding 494aa. gjSOX9 was not only expressed in various adult tissues but also exhibited a special spatiotemporal expression pattern in gonad tissues. gjSOX9 was predicted to be a hydrophilic nucleoprotein with a characteristic HMG-Box harboring a newly identified unique sequence, \"YKYQPRRR\", only present in SOXE members. Among the 20 SOX9 orthologs, gjSOX9 shares the closest genetic relationships with Eublepharis macularius SOX9, Sphacrodactylus townsendi SOX9, and Hemicordylus capensis SOX9. gjSOX9 and gjSOX10 possessed identical physicochemical properties and subcellular locations and were tightly clustered with gjSOX8 in the SOXE group. Sixteen gjSOX family members were divided into six groups: SOXB, C, D, E, F, and H with gjSOX8, 9, and 10 in SOXE among 150 SOX homologs. Collectively, the available data in this study not only facilitate a deep exploration of the functions and molecular regulation mechanisms of the gjSOX9 and gjSOX families in G. japonicus but also contribute to basic research regarding the origin and evolution of SOX9 homologs or even sex-determination mode in reptiles.

Antiphospholipid syndrome (APS) is a group of clinical syndromes of thrombosis or adverse pregnancy outcomes caused by antiphospholipid antibodies, which increase the incidence of in vitro fertilization failure in patients with infertility. However, the common mechanism of repeated implantation failure (RIF) with APS is unclear. This study aimed to search for potential diagnostic genes and potential therapeutic targets for RIF with APS.
To obtain differentially expressed genes (DEGs), we downloaded the APS and RIF datasets separately from the public Gene Expression Omnibus database and performed differential expression analysis. We then identified the common DEGs of APS and RIF. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed, and we then generated protein-protein interaction. Furthermore, immune infiltration was investigated by using the CIBERSORT algorithm on the APS and RIF datasets. LASSO regression analysis was used to screen for candidate diagnostic genes. To evaluate the diagnostic value, we developed a nomogram and validated it with receiver operating characteristic curves, then analyzed these genes in the Comparative Toxicogenomics Database. Finally, the Drug Gene Interaction Database was searched for potential therapeutic drugs, and the interactions between drugs, genes, and immune cells were depicted with a Sankey diagram.
There were 11 common DEGs identified: four downregulated and seven upregulated. The common DEG analysis suggested that an imbalance of immune system-related cells and molecules may be a common feature in the pathophysiology of APS and RIF. Following validation, MARK2, CCDC71, GATA2, and KLRC3 were identified as candidate diagnostic genes. Finally, Acetaminophen and Fasudil were predicted as two candidate drugs.
Four immune-associated candidate diagnostic genes (MARK2, CCDC71, GATA2, and KLRC3) were identified, and a nomogram for RIF with APS diagnosis was developed. Our findings may aid in the investigation of potential biological mechanisms linking APS and RIF, as well as potential targets for diagnosis and treatment.

In the species-rich Phylum Arthropoda, the mitochondrial genome is relatively well conserved both in terms of number and order of genes. However, specific clades have a \'typical\' gene order that differs from the putative arthropod ancestral arrangement. The aim of this work was to compare the rate of mitochondrial gene rearrangements at inter- and intra-taxonomic levels in the Arthropoda and to postulate the most parsimonious ancestral orders representing the four major arthropod lineages. For this purpose, we performed a comparative genomic analysis of arthropod mitochondrial genomes available in the NCBI database. Using a combination of bioinformatics methods that examined mitochondrial gene rearrangements in 464 species of arthropods from three subphyla (Chelicerata, Myriapoda, and Crustacea [except Hexapoda, previously analyzed]), we observed differences in the rate of rearrangement within major lineages. A higher rate of mitochondrial genome rearrangement was observed in Crustacea and Chelicerata compared to Myriapoda. Likewise, early branching clades exhibit less variability in mitochondrial genome order than late branching clades, within each subphylum. We identified \'hot regions\' in the mitochondrial genome of each studied subphylum, and postulated the most likely ancestral gene order in each subphylum and taxonomic order. Our work provides new evidence on the evolutionary dynamics of mitochondrial genome gene order in arthropods and new mitochondrial genome architectures in different taxonomic divisions within each major lineage of arthropods.

Background: Intervertebral disc degeneration (IVDD), which contributes to stenosis of the spinal segment, commonly causes lower back pain. The process of IVDD degradation entails gradual structural adjustments accompanied by extreme transformations in metabolic homeostasis. However, the molecular and cellular mechanisms associated with IVDD are poorly understood. Methods: The RNA-sequencing datasets GSE34095 and GSE56081 were obtained from the Gene Expression Omnibus (GEO) database. Ferroptosis-related differentially expressed genes (DEGs) were identified from these gene sets. The protein-protein interaction (PPI) network was established and visualized using the STRING database and Cytoscape software, and the key functional modules of ferroptosis-related genes were identified. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the DEGs. Weighted gene co-expression network analysis (WGCNA), immune infiltration analysis in the GEO database, and other GSE series were used as validation datasets. The xCELL algorithm was performed to investigate the immune cell infiltration differences between the degenerated IVDD and control groups. Results: The major genes involved in nucleus pulposus tissue immune infiltration and ferroptosis-related genes were mined by bioinformatics analysis. A total of 3,056 DEGs were obtained between the IVDD tissue and control groups. The DEGs were enriched in the cell cycle; apoptosis; necroptosis; and the PI3K-Akt, Hippo, and HIF-1 signaling pathways. PCR and Western blot techniques were utilized to confirm the differential ferroptosis-related genes. The results indicated that the protein expression levels of NCOA4 and PCBP1 were elevated, while the protein expression level of GPX4 was reduced in NPCs following IL-1β treatment. Our study has found that severe disc tissue degeneration leads to a noteworthy increase in the expression of CD8A in naive T cells, CCR7 in memory CD4+ cells, GZMB in natural killer (NK) cells, and CD163 and CD45 in macrophages. Conclusion: Our data demonstrate that ferroptosis occurs in IVDD, suggesting that ferroptosis may also increase IVDD improvement by triggering immune infiltration. This work was conducted to further understand IVDD pathogenesis and identify new treatment strategies.