Cutaneous squamous cell carcinoma (CSCC) is the second most common malignant tumor of the skin. B7 homolog 4 (B7-H4) and B7-H5 (B7 homolog 5) are associated with a variety of tumors. Investigate the potential role of B7-H4 and B7-H5 in regulating the tumorigenesis and progression of CSCC. B7-H4 and B7-H5 transcriptome data were collected from GEO and TCGA databases and subjected to bioinformatical analysis by protein-protein interaction (PPI) network, functional enrichment analysis, immune analysis, and drug-gene interaction prediction analysis. We characterized the expression of B7-H4 and B7-H5 in carcinoma tissues of CSCC patients by immunohistochemistry. Meanwhile, the clinical correlation of B7-H4 and B7-H5 in CSCC was explored by statistical analysis. B7-H4 and B7-H5 genes were under-expressed in CSCC and correlated with tumor staging. According to GO and KEGG Pathway enrichment analysis, B7-H4, and B7-H5 can regulate the proliferation and activation of T cells, lymphocytes, and monocytes, and the expression of cytokines, such as IL-6 and IL-10, in CSCC. B7-H4 and B7-H5 are also jointly involved in the occurrence and development of CSCC via the JAK-STAT and Notch signaling pathways. We found that B7-H4 and B7-H5 proteins were abnormally highly expressed in CSCC tissue and correlated with tumor size and stage. Our findings offer new insights into the pathogenesis of CSCC and suggest that B7-H4 and B7-H5 are novel tissue biomarkers and promising therapeutic targets for CSCC.

Non-small cell lung cancer (NSCLC) is a malignant tumor with low overall cure and survival rates. Uncovering abnormally expressed genes is significantly important for developing novel targeted therapies in NSCLC. This study aimed to discover new differentially expressed genes (DEGs) of NSCLC. The DEGs of NSCLC were identified in eight data sets from Gene Expression Omnibus (GEO) database. The expression profiles and the prognostic significance of SCN4B in LUAD and LUSC were analyzed using GEPIA database. LinkedOmics was used to identify co-expressed genes with SCN4B, which were further subjected to KEGG pathway enrichment analysis. SCN4B-overexpressing plasmid (pcDNA/SCN4B) was transfected into A549 and NCI-H2170 cells to elevate the expression of SCN4B. MTT and TUNEL assays were performed to evaluate cell viability and apoptosis. Relying on the screened DEGs from GEO database, we identified that SCN4B was significantly downregulated in LUAD and LUSC. We confirmed the downregulation of SCN4B in NSCLC tissues using GEPIA database. SCN4B has a prognostic value in LUAD, but not LUSC. KEGG pathway enrichment analysis of SCN4B-related genes showed that cGMP-PKG signaling pathway might be involved in the role of SCN4B in NSCLC. Overexpression of SCN4B in A549 and NCI-H2170 cells inhibited the cell viability. Besides, SCN4B overexpression induced apoptosis of A549 and NCI-H2170 cells. SCN4B inhibited the expression of PKG1 and p-CREB in NSCLC cells. Moreover, the inhibitory effects of SCN4B on tumor malignancy were attenuated by the activator of PKG. In conclusion, integrated bioinformatical analysis proved that SCN4B was downregulated and had a prognostic significance in NSCLC. In vitro experimental studies demonstrated that SCN4B regulated NSCLC cells viability and apoptosis via inhibiting cGMP-PKG signaling pathway.

Antimicrobial resistance is a global health threat that requires innovative strategies against drug-resistant bacteria. Our study focuses on enoyl-acyl carrier protein reductases (ENRs), in particular FabI, FabK, FabV, and InhA, as potential antimicrobial agents. Despite their promising potential, the lack of clinical approvals for inhibitors such as triclosan and isoniazid underscores the challenges in achieving preclinical success. In our study, we curated and analyzed a dataset of 1412 small molecules recognized as ENR inhibitors, investigating different structural variants. Using advanced cheminformatic tools, we mapped the physicochemical landscape and identified specific structural features as key determinants of bioactivity. Furthermore, we investigated whether the compounds conform to Lipinski rules, PAINS, and Brenk filters, which are crucial for the advancement of compounds in development pipelines. Furthermore, we investigated structural diversity using four different representations: Chemotype diversity, molecular similarity, t-SNE visualization, molecular complexity, and cluster analysis. By using advanced bioinformatics tools such as matched molecular pairs (MMP) analysis, machine learning, and SHAP analysis, we were able to improve our understanding of the activity cliques and the precise effects of the functional groups. In summary, this chemoinformatic investigation has unraveled the FAB inhibitors and provided insights into rational antimicrobial design, seamlessly integrating computation into the discovery of new antimicrobial agents.

UNASSIGNED: Intracranial aneurysms (IAs) represent protrusions in the vascular wall, with their growth and wall thinning influenced by various factors. These processes can culminate in the rupture of the aneurysm, leading to subarachnoid hemorrhage (SAH). Unfortunately, over half of the patients prove unable to withstand SAH, succumbing to adverse outcomes despite intensive therapeutic interventions, even in premier medical facilities. This study seeks to discern the pivotal microRNAs (miRNAs) and genes associated with the formation and progression of IAs.
UNASSIGNED: The investigation gathered expression data of miRNAs (from GSE66240) and mRNAs (from GSE158558) within human aneurysm tissue and superficial temporal artery (STA) samples, categorizing them into IA and normal groups. This classification was based on the Gene Expression Omnibus (GEO) database.
UNASSIGNED: A total of 70 differentially expressed microRNAs (DEMs) and 815 differentially expressed mRNAs (DEGs) were pinpointed concerning IA. Subsequently, a miRNA-mRNA network was constructed, incorporating 9 significantly upregulated DEMs and 211 significantly downregulated DEGs. Simultaneously, functional enrichment and pathway analyses were conducted on both DEMs and DEGs. Through protein-protein interaction (PPI) network analysis and functional enrichment, 9 significantly upregulated DEMs (hsa-miR-188-5p, hsa-miR-590-5p, hsa-miR-320b, hsa-miR-423-5p, hsa-miR-140-5p, hsa-miR-486-5p, hsa-miR-320a, hsa-miR-342-3p, and hsa-miR-532-5p) and 50 key genes (such as ATP6V1G1, KBTBD6, VIM, PA2G4, DYNLL1, METTL21A, MDH2, etc.) were identified, suggesting their potential significant role in IA. Among these genes, ten were notably negatively regulated by at least two key miRNAs.
UNASSIGNED: The findings of this study provide valuable insights into the potential pathogenic mechanisms underlying IA by elucidating a miRNA-mRNA network. This comprehensive approach sheds light on the intricate interplay between miRNAs and genes, offering a deeper understanding of the molecular dynamics involved in IA development and progression.

BACKGROUND: Alzheimer\'s disease (AD) and Parkinson\'s disease (PD), two common irreversible neurodegenerative diseases, share similar early stage syndromes, such as olfaction dysfunction. Yet, the potential comorbidity mechanism of AD and PD was not fully elucidated.
METHODS: The gene expression profiles of GSE5281 and GSE8397 were downloaded from the Gene Expression Omnibus (GEO) database. We utilized a series of bioinformatics analyses to screen the overlapped differentially expressed genes (DEGs). The hub genes were further identified by the plugin CytoHubba of Cytoscape and validated in the hippocampus (HIP) samples of APP/PS-1 transgenic mice and the substantial nigra (SN) samples of A53T transgenic mice by real-time quantitative polymerase chain reaction (RT-qPCR). Meanwhile, the expression of the target genes in the olfactory epithelium/bulb was detected by RT-qPCR. Finally, molecular docking was used to screen potential compounds for the target gene.
RESULTS: One hundred seventy-four overlapped DEGs were identified in AD and PD. Five of the top ten enrichment pathways mainly focused on the synapse. Five hub genes were identified and further validated. As a common factor in AD and PD, the changes of synaptosomal-associated protein 25 (SNAP25) mRNA in olfactory epithelium/bulb were significantly decreased and had a strong association with those in the HIP and SN samples. Pazopanib was the optimal compound targeting SNAP25, with a binding energy of - 9.2 kcal/mol.
CONCLUSIONS: Our results provided a theoretical basis for understanding the comorbidity mechanism of AD and PD and highlighted that SNAP25 in the olfactory epithelium may serve as a potential target for early detection and intervention in both AD and PD.

Using Mendelian Randomization (MR) and large-scale Genome-Wide Association Study (GWAS) data, this study aimed to investigate the potential causative relationship between testosterone and sex hormone-binding globulin (SHBG) levels and the onset of several cancers, including pathway enrichment analyses of single nucleotide polymorphisms (SNPs) associated with cancer allowed for a comprehensive bioinformatics approach, which offered a deeper biological understanding of these relationships. The results indicated that increased testosterone levels in women were associated with a higher risk of breast and cervical cancers but a lower risk of ovarian cancer. Conversely, increased testosterone was linked to lower stomach cancer risk for men, whereas high SHBG levels were related to decreased risks of breast and prostate cancers. The corresponding genes of the identified SNPs, as revealed by pathway enrichment analysis, were involved in significant metabolic and proliferative pathways. These findings emphasize the need for further research into the biological mechanisms behind these associations, paving the way for potential targeted interventions in preventing and treating these cancers.

This study investigated the role of apoptosis-related genes in thoracic aortic aneurysms (TAA) and provided more insights into TAA\'s pathogenesis and molecular mechanisms.
Two gene expression datasets (GSE9106 and GSE26155) were retrieved from the Gene Expression Omnibus (GEO) database. Apoptosis-related genes were obtained from the KEGG apoptosis pathway (hsa04210). Differentially expressed apoptosis-related genes were identified by performing differential expression analysis using limma for TAA blood and tissue samples. GO and KEGG enrichment analysis of the differentially expressed apoptosis genes was performed using the Metascape web tool. The miRNA-mRNA regulatory network was reconstructed using the ENCORI and miRDB databases, and functional enrichment analysis was performed on the related miRNAs using the miEAA tool. The correlation between the expression levels of differentially expressed apoptosis-related genes and genes involved in immune infiltration in TAA was calculated using the CIBERSORT algorithm. The apoptosis modification patterns mediated by differentially expressed apoptosis-related genes were systematically assessed in TAA samples.
A total of 9 differentially-expressed apoptosis-related genes were identified in TAA samples compared with normal samples. 150 miRNAs and 6 mRNAs regulatory networks were reconstructed using the ENCORI and miRDB databases. Immune infiltration analysis revealed that the GZMB had the strongest positive correlation with activated NK cells and the DFFA presented the strongest positive correlation with T cells follicular helper. 3 distinct apoptosis modification patterns mediated by 9 differentially-expressed apoptosis-related genes were identified. They differ in immune characteristics and drug sensitivity, and their biological functions in these subtypes were further studied.
This study identified key apoptosis-related genes related to TAA and evaluated the modification patterns of key apoptosis genes in TAA, providing insights into potential targets and mechanisms of TAA pathogenesis and progression.

Ketamine, a racemic mixture of esketamine (S-ketamine) and arketamine (R-ketamine), has received particular attention for its rapid antidepressant and antisuicidal effects. NMDA receptor inhibition has been indicated as one of the main mechanisms of action of the racemic mixture, but other pharmacological targets have also been proposed. This study aimed to explore the possible multiple targets of ketamine enantiomers related to their antidepressant and antisuicidal effects. To this end, targets were predicted using Swiss Target Prediction software for each ketamine enantiomer. Targets related to depression and suicide were collected by the Gene Cards database. The intersections of targets were analyzed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Network pharmacology analysis was performed using Gene Mania and Cytoscape software. Molecular docking was used to predict the main targets of the network. The results indicated that esketamine and arketamine share some biological targets, particularly NMDA receptor and phosphodiesterases 3A, 7A, and 5A but have specific molecular targets. While esketamine is predicted to interact with the GABAergic system, arketamine may interact with macrophage migration inhibitory factor (MIF). Both ketamine enantiomers activate neuroplasticity-related signaling pathways and show addiction potential. Our results identified novel, poorly explored molecular targets that may be related to the beneficial effects of esketamine and arketamine against depression and suicide.

Preinjury of peripheral nerves triggers dorsal root ganglia (DRG) axon regeneration, a biological change that is more pronounced in young mice than in old mice, but the complex mechanism has not been clearly explained. Here, we aim to gain insight into the mechanisms of axon regeneration after conditioning lesion in different age groups of mice, thereby providing effective therapeutic targets for central nervous system (CNS) injury.
The microarray GSE58982 and GSE96051 were downloaded and analyzed to identify differentially expressed genes (DEGs). The protein-protein interaction (PPI) network, the miRNA-TF-target gene network, and the drug-hub gene network of conditioning lesion were constructed. The L4 and L5 DRGs, which were previously axotomized by the sciatic nerve conditioning lesions, were harvested for qRT-PCR. Furthermore, histological and behavioral tests were performed to assess the therapeutic effects of the candidate drug telmisartan in spinal cord injury (SCI).
A total of 693 and 885 DEGs were screened in the old and young mice, respectively. Functional enrichment indicates that shared DEGs are involved in the inflammatory response, innate immune response, and ion transport. QRT-PCR results showed that in DRGs with preinjury of peripheral nerve, Timp1, P2ry6, Nckap1l, Csf1, Ccl9, Anxa1, and C3 were upregulated, while Agtr1a was downregulated. Based on the bioinformatics analysis of DRG after conditioning lesion, Agtr1a was selected as a potential therapeutic target for the SCI treatment. In vivo experiments showed that telmisartan promoted axonal regeneration after SCI by downregulating AGTR1 expression.
This study provides a comprehensive map of transcriptional changes that discriminate between young and old DRGs in response to injury. The hub genes and their related drugs that may affect the axonal regeneration program after conditioning lesion were identified. These findings revealed the speculative pathogenic mechanism involved in conditioning-dependent regenerative growth and may have translational significance for the development of CNS injury treatment in the future.

Purine metabolism is an important branch of metabolic reprogramming and has received increasing attention in cancer research. Ovarian cancer is an extremely dangerous gynecologic malignancy for which there are no adequate tools to predict prognostic risk. Here, we identified a prognostic signature consisting of nine genes related to purine metabolism, including ACSM1, CACNA1C, EPHA4, TPM3, PDIA4, JUNB, EXOSC4, TRPM2, and CXCL9. The risk groups defined by the signature are able to distinguish the prognostic risk and the immune landscape of patients. In particular, the risk scores offer promising personalized drug options. By combining risk scores with clinical characteristics, we have created a more detailed composite nomogram that allows for a more complete and individualized prediction of prognosis. In addition, we demonstrated metabolic differences between platinum-resistant and platinum-sensitive ovarian cancer cells. In summary, we have performed the first comprehensive analysis of genes related to purine metabolism in ovarian cancer patients and created a feasible prognostic signature that will aid in risk prediction and support personalized medicine.