Journal of Research in Medical Sciences
Volume:29 Issue: 2, Feb 2024

According to the report of the World Health Organization, mental disorders are one of the 10 most important causes of disability in the world. This study was conducted with the aim of determining the number and frequency of latent classes of depression and its determinants in Isfahan university of medical students.

A total of 1408 medical students from Isfahan University of Medical Sciences, Iran, were enrolled in the study in 2017. The symptoms and severity of depression were assessed using the standard Hospital Anxiety and Depression scale questionnaire. Latent class analysis was applied to seven symptoms of depression, all of which had four levels. Latent class subgroups were compared using the Chi‑square test and analysis of variance test. The regression model was used to check the relationship between identified classes and related factors. Analyzes were done using SPSS‑21 and Mplus7 software.

In this study, three latent classes were identified, that is, the group of healthy people, the group of borderline people, and the group of people suspected of depression. The prevalence of identified latent classes among medical students is 0.52, 0.32, and 0.16%, respectively. The regression results showed that compared to the healthy group, the factors affecting depression in the borderline and suspicious group were increasing age, female gender, interest in the field of study, physical activity, history of depression, and history of anxiety.

The three classes that were identified based on the students’ answers to the depression symptoms questions differed only based on severity. The history of depression and anxiety were the strongest predictors of latent classes of depression.

This retrospective cohort study aimed to evaluate the effect of lifestyle factors (e.g., smoking, drinking, physical exercise, and sleep duration) on the long‑term survival of gastric cancer (GC) patients after radical resection.

GC patients after radical resection were enrolled from January 2016 to December 2017. Their baseline clinical data, lifestyle factors, and prognosis were collected. The primary endpoint was all‑cause death. The relationship between the variables and survival was examined using the Cox proportional hazards model.

A total of 309 patients were enrolled and 296 patients were followed up for a median of 54.0 months, with 130 confirmed deaths. Older age (>60 years) (hazard ratio [HR]: 1.307, 95% confidence interval [CI]: 1.056–2.161, P = 0.006), advanced tumor, node, and metastasis stage (P < 0.05), poorly pathological differentiation (HR: 1.765, 95% CI: 1.080–2.884, P = 0.023), history of smoking (P < 0.001), never physical exercise (HR: 2.057, 95% CI: 1.170–3.617, P = 0.012), long sleep duration (≥8 h) (HR: 4.160, 95% CI: 1.501–11.533, P = 0.006), and short sleep duration (<6 h) (HR: 3.417, 95% CI: 1.312–8.900, P = 0.012) were independent indicators of a poor overall survival in GC patients after radical resection.

Smoking cessation, proper sleep duration, and regular physical exercise habits can improve the long‑term survival of GC patients after radical resection.

Cancer development is aided by the role of long noncoding RNAs (lncRNAs) that act as competing endogenous RNAs (ceRNAs) absorbing microRNAs (miRNAs). We aimed to discover a novel regulatory axis in colorectal cancer (CRC) and potential biomarkers based on miR‑616‑3p.

The gene expression omnibus database was mined for differentially expressed lncRNAs (DELs) and mRNAs. LncRNAs and mRNAs were predicted using the RegRNA and TargetScan databases. A combination of the ciBioPortal and Ensemble databases was used to locate the mRNAs. Cytoscape 3.7.1‑built CeRNA networks. A quantitative real‑time polymerase chain reaction (qRT‑PCR) was utilized to confirm the expression levels of these RNA molecules. Statistical analyses were implemented by GraphPad Prism 9.

qRT‑PCR showed (Linc01282, lnc‑MYADM‑1:1, and Zinc Finger Protein 347 [ZNF347]) were overexpressed whereas, (salt‑inducible kinases 1 [SIK1], and miR‑616‑3p) were down regulated.

These results identify unique, unreported lncRNAs as CRC prognostic biomarkers, as well as prospective mRNAs as new treatment targets and predictive biomarkers for CRC. In addition, our study uncovered unexplored ceRNA networks that should be studied further in CRC.

Myocardial infarction (MI) can lead to higher cellular damage, making cell‑free DNA (cfDNA) a potential biomarker for assessing disease severity. The aim of this study is to evaluate survival predictions using cfDNA measurements and assess its correlation with MI.

A direct fluorescence assay was employed to measure cfDNA content in the blood samples of participants. The inclusion criteria included patients who gave informed consent, suffering from ST‑elevation myocardial infraction (STEMI) based on established diagnostic criteria (joint ESC/ACC guidelines), between the age of 18 and 80 years old, and had elevated troponin biomarker levels. The study included 150 patients diagnosed with STEMI and 50 healthy volunteers as controls. Serial monitoring of patients was conducted to track their postdisease status. The rate of change of cfDNA was calculated and daily measurements for 7 days were recorded.

Mean levels of cfDNA were found to be 5.93 times higher in patients with STEMI compared to healthy controls, providing clear evidence of a clinical correlation between cfDNA and STEMI. Patients were further categorized based on their survival status within a 90‑day period. The study observed a strong predictive relationship between the rate of change of cfDNA during daily measurements and survival outcomes. To assess its predictive capability, a receiver operating characteristics (ROC) curve analysis was performed. The ROC analysis identified an optimal cutoff value of 2.50 for cfDNA, with a sensitivity of 81.5% and specificity of 74.0% in predicting disease outcomes.

This study demonstrates a robust association between cfDNA and STEMI, indicating that cfDNA levels can be a valuable early prognostic factor for patients. Serial measurements of cfDNA during early disease onset hold promise as an effective approach for predicting survival outcomes in MI patients.

Protein‑1 (PD‑1) and programmed cell death 1 ligand 1 (PD‑L1) therapy have become an important treatment approach for patients with advanced nonsmall cell lung cancer (NSCLC), but primary or secondary resistance remains a challenge for some patients. PD‑1/PD‑L1 combined with anti‑angiogenic drugs (AAs) in NSCLC patients have potential synergistic effects, and the survival benefit may vary based on a treatment order. To investigate the efficacy of PD‑1/PD‑L1 combined with AAs as the treatment for patients with advanced NSCLC.

We comprehensively searched EMBASE, PubMed, Web of Science, CNKI, VIP, and Wanfang databases from January 2017 to September 2022. The Cochrane risk bias tool evaluated the quality of included randomized clinical trials. Newcastle‑Ottawa‑Scale score was used to evaluate the quality of retrospective studies. Publication bias was evaluated by funnel plot, Begg’s test, and Egger’s test.

Seventeen articles were finally selected, involving 5182 patients. Meta‑analysis results showed that PD1/PD‑L1 combined with AAs therapy significantly improved progression‑free survival (PFS) (hazard ratio [HR] = 0.61, 95% confidence interval [CI]: 0.50–0.75, P < 0.00001), overall survival (OS) (HR = 0.79, 95% CI: 0.71–0.88, P < 0.00001), and objective response rate (ORR) (risk ratio = 0.88, 95% CI: 0.81–0.96, P = 0.004), with the statistically significant difference. The sensitivity analysis demonstrated the robustness of the PFS, ORR, and OS.

The combination of PD‑1/PD‑L1 inhibitors with AAs in treating advanced patients has exhibited notable therapeutic advantages when contrasted with monotherapy. Specifically, the administration of PD‑1/PD‑L1 inhibitors in conjunction with AAs, or sequential treatment involving PD‑1/PD‑L1 followed by AAs, has shown enhanced therapeutic efficacy in this patient population.