UNASSIGNED: Myocardial infarction (MI) is a chronic cardiovascular disease. This study aims to discern potentially angiogenesis- and epithelial mesenchymal transition (EMT)-related genes as biomarkers for MI diagnosis through bioinformatics.
UNASSIGNED: All datasets and angiogenesis- and EMT-related genes were collected from the public database. The differentially expressed genes (DEGs) of MI and MI-related genes were acquired. DEGs, MI-related genes, and angiogenesis- and EMT-related genes were intersected to obtain hub genes. Functional enrichment, immune microenvironment, and transcription factors (TFs)-hub genes regulatory network analysis were performed. The diagnostic markers and models were developed and validated. Drug prediction and molecular docking were performed. Finally, diagnostic markers expressions were validated using RT-qPCR.
UNASSIGNED: A total of 224 angiogenesis- and EMT-related genes, 2,897 DEGs, 1,217 MI-related genes, and 9 hub genes were acquired. The immune infiltration levels of plasma cells, T cells CD4 memory activated, monocytes, macrophages M0, mast cells resting, and neutrophils were higher in patients with MI. LRPAP1, COLGALT1, QSOX1, THBD, VCAN, PLOD1, and PLAUR as the diagnostic markers were identified and used to construct diagnostic models, which can distinguish MI from controls well. Then, 9 drugs were screened, and the binding energies ranged from -7.08 to -5.21 kcal/mol. RT-qPCR results showed that the expression of LRPAP1, PLAUR, and PLOD1 was significantly increased in the MI group.
UNASSIGNED: The 7 diagnostic markers may play potential roles in MI and could contribute to improved future diagnostics.

UNASSIGNED: Gastric cancer (GC), a malignant epithelial tumor, is the fourth leading cause of cancer-related death worldwide. Therapeutic strategies for GC, despite the biggest challenges, can significantly improve survival rates through early detection and effective screening methods.
UNASSIGNED: To provide brief information on the necessity of multiple specific diagnostic, prognostic, and predictive markers for GC.
UNASSIGNED: This review was conducted using a variety of search engines, including PubMed Central, Scopus, Web of Science, Google Scholar, and others.
UNASSIGNED: Some potential biomarkers that provide essential information include circulating tumor cells (CTCs), DNA methylation, claudin 18.2, fibroblast growth factor receptor 2 (FGFR2), long noncoding RNAs (lncRNAs), cell-free DNA (cfDNA), microRNAs, and serum pepsinogens.
UNASSIGNED: Multiple tumor markers are essential for screening, tumor identification, staging, prognostic assessment, and monitoring recurrence after therapy due to the absence of a single tumor indicator for diagnosing, prognosticating, and predicting GC.

Ginsenosides in ginseng are known for their potential health benefits, including antioxidant properties and their potential to exhibit anticancer effects. Besides a various range of coding genes, ginsenosides impose their efficacy by targeting noncoding RNAs. Long noncoding RNA ( lncRNA) has gained significant attention from both basic and clinical oncology fields due to its involvement in various cancer cell activities such as proliferation, apoptosis, metastasis, and autophagy. These events can be achieved either by lncRNA alone or in association with microRNAs or proteins. This review aims to summarize the diverse activities of lncRNAs that are regulated by ginsenosides, focusing on their role in regulating target genes through signaling pathways in human diseases. We highlight the results of studies on the expression profiles of lncRNAs induced by ginsenosides in efforts to inhibit cancer cell proliferation. Finally, we discuss the potential and challenges of utilizing lncRNAs as diagnostic markers for disease treatment.

BACKGROUND: Ovarian cancer is insidious and usually detected in advanced stages of the disease. As the ovaries are pelvic organs, changes in their pelvic fluid metabolites may be associated with ovarian cancer.
METHODS: Metabolomic changes in the pelvic fluid were detected using liquid chromatography-tandem mass spectrometry (LC-MS/MS) in patients with ovarian cancer, ovarian cysts and uterine fibroids. Area under the curve (AUC) analysis was used to assess the diagnostic performance of lipid metabolites and blood tumor indices. The Pearson correlation algorithm was used to analyze the correlation between clinical characteristics and lipid metabolites in ovarian cancer patients.
RESULTS: There were 24 lipid metabolites significantly changed in the pelvic fluid of ovarian cancer patients (p < 0.05). Palmitoylcarnitine, lipoamide, lipid metabolites, and blood tumor indices (CA15-3 and CA125) showed AUC > 0.8, with palmitoylcarnitine reaching a high of 0.942. In addition, we found that some lipid metabolites were significantly associated with the clinical stage, abdominal water volume, lymphatic metastasis, and recurrence (p < 0.05, r > 0.5).
CONCLUSIONS: Levels of specific lipid metabolites are potential biomarkers of ovarian cancer and may play a key role in the early diagnosis and prognostic assessment of ovarian cancer.
CONCLUSIONS: Our results showed that pelvic metabolites, especially some lipid metabolites, play an important role in the diagnosis of ovarian cancer. Meanwhile, partial lipid metabolites were closely associated with the clinical presentation and prognosis of patients with ovarian cancer. We believe that our study makes a significant contribution to the literature because it provides a potential approach that is more effective for ovarian cancer detection.

UNASSIGNED: Acute appendicitis is currently considered one of the most common acute surgical diseases of the abdomen and requires emergency surgery. It is also one of the most common abdominal emergencies in both developed and developing countries. The current study is aimed at assessing the specificity and sensitivity of Ultrasound and Computed Tomography in the diagnosis of appendicitis as well as the prevalence of its complications. The association of appendicitis with several laboratory findings will also be evaluated.
UNASSIGNED: A retrospective study was conducted at Dallah-Namar Hospital, Riyadh City, Saudi Arabia.
UNASSIGNED: 720 patients were differentially diagnosed with appendicitis in the study area. Of these, 618 patients had US abdomen/pelvis, with 15 (2.4%) showing positive findings. Amongst the 203 patients noted to have undergone abdominal CT,8 (4.0%) was found to have positive findings.
UNASSIGNED: The sensitivity of the US was determined to be relatively low. Also, serum creatinine was found to be elevated among all patients diagnosed with appendicitis. Further research with a larger sample size is needed to be conducted to further support the current findings.

BACKGROUND: Osteoarthritis (OA) is a prevalent joint disorder characterized by cartilage degeneration and joint inflammation. Liquid-liquid phase separation (LLPS), a biophysical process involved in cellular organization, has recently gained attention in OA research. However, the relationship between LLPS and OA remains poorly understood.
METHODS: We analyzed gene expression data from the GSE48556 dataset to identify LLPS-related genes associated with OA. Differential expression analysis, enrichment analyses, and machine learning algorithms were employed to explore the functional significance of LLPS-related genes in OA and then construct a diagnostic model for OA. In addition, IL-1β as a pro-inflammatory factor to establish an in vitro OA model, and the protein expression levels of OA biomarkers were detected by western blot.
RESULTS: A total of 145 LLPS-related genes were screened in OA samples. Enrichment analyses revealed these genes were mainly enriched in mRNA metabolic processes, cytoplasmic granules, and insulin resistance. Four characteristic genes for OA were selected by using machine learning algorithms, including ADRB2, H3F3B, GNL3L, and PELO. These genes showed satisfactory diagnostic values. Furthermore, there were association between these biomarkers and immune cells, including T cells CD8 and monocytes. In vitro experiments showed that IL-1β stimulation significantly inhibited the cell viability of chondrocytes and enhanced the levels of pro-inflammatory factors, that could mimic the inflammatory state of OA. The expression levels of GNL3L and H3F3B proteins in IL-1β group were obviously lower than those in control group, while levels of ADRB2 and PELO were higher, which was consistent with the results of bioinformatics analysis.
CONCLUSIONS: Our study identifies LLPS-related genes as potential diagnostic biomarkers for OA. These findings provide insights into the molecular mechanisms underlying OA pathogenesis and offer opportunities for the development of novel therapeutic strategies.

With the development of gene testing technology, we have found many different genes, and lncRNA is one of them. LncRNAs refer to a non-protein coding RNA molecule with a length of more than 200bp, which is one of the focuses of research on human malignant diseases such as LUAD. LncRNAs act as an oncogene or inhibitor to regulate the occurrence and progression of tumors. The differential expression of LncRNAs promotes or inhibits the progression of lung adenocarcinoma by affecting cell proliferation, metastasis, invasion, and apoptosis, thus affecting the prognosis and survival rate of patients. Therefore, LncRNAs can be used as a potential target for diagnosis and treatment of cancer. The early diagnosis of the disease was made through the detection of tumor markers. Because lung adenocarcinoma is not easy to diagnose in the early stage and tumor markers are easy to ignore, LncRNAs play an important role in the diagnosis and treatment of lung adenocarcinoma. The main purpose of this article is to summarize the known effects of LncRNAs on lung adenocarcinoma, the effect of differential expression of LncRNAs on the progression of lung adenocarcinoma, and related signal transduction pathways. And to provide a new idea for the future research of lung adenocarcinoma-related LncRNAs.

During pregnancy, there is a link between disruption of maternal immune tolerance and preeclampsia, but the molecular mechanisms that regulate maternal and fetal immune tolerance remain unclear. This study employs bioinformatics to identify new markers related to placental immune tolerance and explore their potential role in predicting preeclampsia. Analyzing preeclampsia-related gene expression profiles in the Gene Expression Omnibus (GEO) dataset reveals 211 differentially expressed genes (DEGs) in the placenta, mainly influencing immune cell differentiation and response pathways. Employing weighted gene co-expression network analysis (WGCNA) and lasso regression, four potential target genes (ANKRD37, CRH, LEP, SIGLEC6) are identified for potential prediction of preeclampsia. Validation using the GSE4707 dataset confirmed the diagnostic and predictive potential of these candidate genes. RT-qPCR verified up-regulation in the placenta, while ELISA showed their correlation with immune tolerance factors associated with placental immune tolerance. As a result of this study, identifies potential biomarkers associated with placental immunity and contributes to understanding the molecular mechanism of preeclampsia.

The intestinal microbiota is a crucial environmental factor in the development of inflammatory bowel disease (IBD). The abundance of Faecalibacterium prausnitzii is significantly decreased in IBD patients, which is used as a biomarker for IBD diagnosis. However, this can be observed in both IBD and colorectal cancer, which would confound the diagnostic results. Thus, we first established a new model for predicting Crohn\'s disease (CD) with high precision according to gene characteristics based on single nucleotide variants (SNVs). Next, five gene markers belonging to two species, F. prausnitzii and Eubacterium rectale, that were enriched in the CD group were obtained to build a CD prediction model, and high accuracy in distinguishing the CD and control groups was observed in the discovery (area under curve [AUC] = 91.13%) and validation cohorts (AUC = 79.55%). The model still maintained high accuracy after expanding the healthy cohort (AUC = 89.75%). High disease specificity in distinguishing CD and CRC groups (AUC = 95.74%) was also proven. This study establishes a novel diagnostic method for predicting IBD that also provides unprecedented insight for the early, painless diagnosis of other non-communicable diseases.

Aim: The present study aimed to figure out the potential role of exosomal microRNAs, and their targeted genes in HNC detection/diagnosis. Methods: In the present study, exosomes were extracted from the serum samples of 400 HNC patients and 400 healthy controls. Exosomes were characterized using TEM, NTA, TEM-immunogold labeling and ELISA. Quantitative PCR was used to measure the expression level of exosomal miRNA-19a, miRNA-19b and targeted genes SMAD2 and SMAD4 in HNC patients and controls. Results: The deregulation of miR-19a (p < 0.01), miR-19b (p < 0.03), SMAD2 (p < 0.04) and SMAD4 (p < 0.04) was observed in HNC patients vs controls. Conclusion: ROC curve and Kaplan-Meier analysis showed the good diagnostic/prognostic value of selected exosomal microRNAs and related genes in HNC patients.
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