Postgraduate Medical Journal最新文献

Fibrosis is a prevalent pathological condition observed in various organs and tissues. It primarily arises from the excessive and abnormal accumulation of the extracellular matrix, resulting in the structural and functional impairment of tissues and organs, which can culminate in death. Many forms of fibrosis, including liver, cardiac, pulmonary, and renal fibrosis, are considered irreversible. Maternally expressed gene 3 (MEG3) is an imprinted RNA gene. Historically, the downregulation of MEG3 has been linked to tumor pathogenesis. However, recent studies indicate an emerging association of MEG3 with fibrotic diseases. In this review, we delve into the current understanding of MEG3's role in fibrosis, aiming to shed light on the molecular mechanisms of fibrosis and the potential of MEG3 as a novel therapeutic target.

Purpose: This study sought to investigate the causal effects of circulating C-reactive protein (CRP) level on risk of asthma and its subtypes by two-sample Mendelian randomization (MR) analysis.

Methods: We utilized single nucleotide polymorphisms (SNPs) associated with both CRP and outcomes of asthma, allergic asthma, and obesity-related asthma as genetic variables via a genome-wide summary association study (GWAS). MR analysis mainly based on the inverse variance weighted (IVW) method was performed to infer the causal relationship between exposure and outcomes. Cochran's Q test and MR-Egger regression analysis were performed to determine respectively the heterogeneity and pleiotropy among instrumental variables (IVs), and leave-one-out analysis was conducted to determine the stability of the MR results.

Results: In our study, 42 SNPs were identified as IVs for MR analyses. According to the primary inference results by IVW methods, circulating CRP was demonstrated to be significantly associated with risk of asthma [odds ratio (OR): 1.046; 95% confidence interval (95% CI): 1.004-1.090; P = .030] and obesity-related asthma (OR: 1.072; 95% CI: 1.009-1.138; P = 0.025), whereas no distinct causality with allergic asthma was found (OR: 1.051; 95% CI: 0.994-1.112; P = .081). Sensitivity analyses indicated that there was no horizontal pleiotropy among IVs, and the MR results were proved to be robust by leave-one-out sensitivity analysis, despite the presence of heterogeneity.

Conclusion: The present study suggested that higher CRP might genetically predict an increased risk of developing asthma and obesity-related asthma, without causality with allergic asthma.

Background: Despite previous concerns about ocular side effects related to amiodarone, the relationship between amiodarone and cataract remains uncertain. Therefore, this study aimed to assess the potential association between amiodarone use and the subsequent risk of cataract, taking into account potential confounders.

Methods: This population-based, active comparator-controlled cohort study utilized the data from the Taiwan National Health Insurance program and involved adults over 40 years old between 2001 and 2013. We analyzed 12 055 new amiodarone users and contrasted them with a propafenone user cohort. The primary outcome was the incidence of cataract. Inverse-probability treatment-weighting (IPTW) was further used to eliminate the potential confounding effects, and Cox proportional-hazard regression analyses were performed to calculate the risk of cataract. Serial subgroup analyses were also performed.

Results: In the main analysis, amiodarone users did not exhibit a significant causal relationship in both full cohort [adjusted hazard ratio (aHR): 0.994, 95% confidence interval (CI): 0.913-1.082] and IPTW cohort (IPTW-aHR 0.977, 95% CI: 0.900-1.060). Furthermore, it is important to highlight a significantly reduced risk of cataract among patients with heart failure (IPTW-aHR 0.708, 95% CI: 0.554-0.905) and during the 2-year follow-up period (IPTW-aHR 0.889, 95% CI: 0.794-0.996), implying potential advantages linked to the use of amiodarone.

Conclusions: The study found no increased risk of cataract with amiodarone, one of the most frequently used antiarrhythmic medications, compared to the use of propafenone. Future research is recommended to explore potential mechanisms and their implications for clinical practice.

Purpose: To explore the relationship between liver fat content (LFC) and nonalcoholic fatty liver disease (NAFLD) and determine the new threshold of LFC to diagnose NAFLD.

Methods: The data from questionnaire survey, general physical examination, laboratory examination, and image examination were collected. Multivariate regression analysis, receiver operating characteristic curve analysis, smooth curve fitting, and threshold effect analysis were performed using the R software to investigate the relationship between LFC and NAFLD and to identify the new threshold of LFC to diagnose NAFLD.

Results: The prevalence of NAFLD was 30.42%, with a significantly higher prevalence in men than in women. Regression analyses demonstrated that LFC odds ratio [95% confidence interval (CI)] was 1.28 (95% CI: 1.24-1.31) in fully-adjust model. Analysis of the LFC quartile, with Q1 as a reference, revealed that the odds ratios of NAFLD were 1.47 (95% CI: 1.08-1.99), 2.29 (95% CI: 1.72-3.06), and 10.02 (95% CI: 7.45-13.47) for Q2, Q3, and Q4 groups, respectively. Smooth curve fitting and threshold effect analysis displayed a nonlinear relationship between LFC and NAFLD, and the threshold was 4.5%. The receiver operating characteristic curve indicated that when LFC was 4.5%, the area under curve (95% CI) was 0.80 (0.79-0.82), and the sensitivity and specificity of LFC in diagnosing NAFLD were 0.64% and 0.82%, respectively.

Conclusion: The relationship between LFC and NAFLD was sigmoidal, with an inflection point of 4.5%.

The microbes in the gut are crucial for maintaining the body's immune system and overall gut health. However, it is not fully understood how an unstable gut environment can lead to more severe cases of SARS-CoV-2 infection. The gut microbiota also plays a role in the gut-brain axis and interacts with the central nervous system through metabolic and neuroendocrine pathways. The interaction between the microbiota and the host's body involves hormonal, immune, and neural pathways, and any disruption in the balance of gut bacteria can lead to dysbiosis, which contributes to pathogen growth. In this context, we discuss how dysbiosis could contribute to comorbidities that increase susceptibility to SARS-CoV-2. Probiotics and fecal microbiota transplantation have successfully treated infectious and non-infectious inflammatory-related diseases, the most common comorbidities. These treatments could be adjuvant therapies for COVID-19 infection by restoring gut homeostasis and balancing the gut microbiota.

Purpose: To construct a clinical noncontrastive computed tomography (NCCT) deep learning joint model for predicting early hematoma expansion (HE) after cerebral hemorrhage (sICH) and evaluate its predictive performance.

Methods: All 254 patients with primary cerebral hemorrhage from January 2017 to December 2022 in the General Hospital of the Western Theater Command were included. According to the criteria of hematoma enlargement exceeding 33% or the volume exceeding 6 ml, the patients were divided into the HE group and the hematoma non-enlargement (NHE) group. Multiple models and the 10-fold cross-validation method were used to screen the most valuable features and model the probability of predicting HE. The area under the curve (AUC) was used to analyze the prediction efficiency of each model for HE.

Results: They were randomly divided into a training set of 204 cases in an 8:2 ratio and 50 cases of the test set. The clinical imaging deep feature joint model (22 features) predicted the area under the curve of HE as follows: clinical Navie Bayes model AUC 0.779, traditional radiology logistic regression (LR) model AUC 0.818, deep learning LR model AUC 0.873, and clinical NCCT deep learning multilayer perceptron model AUC 0.921.

Conclusion: The combined clinical imaging deep learning model has a high predictive effect for early HE in sICH patients, which is helpful for clinical individualized assessment of the risk of early HE in sICH patients.

Background: Endometriosis is a poorly understood disease that affects up to 196 million women worldwide and imposes high costs in terms of economic burden and quality of life of women. Traits of circulating lipids have been related to the onset and progression of endometriosis in previous observational studies but the results have remained contradictory.

Methods: We performed univariable and multivariable Mendelian randomization (MR) analyses using instrument variables to genetically predict the associations of low-density lipoprotein (LDL) and high-density lipoprotein (HDL) cholesterol, triglycerides, and apolipoprotein (apo) A-I and B from the UK Biobank with endometriosis (consisting of 8288 cases and 68 969 controls from the FinnGen consortium). The inverse-variance weighted (IVW) method was used as the primary estimate, whereas MR-Egger and weighted median were conducted as complements to the IVW model.

Results: Increased levels of triglycerides were associated with higher risk of endometriosis and endometriosis of the pelvic peritoneum in the univariable MR analyses. In multivariable MR analysis including apoB, LDL cholesterol, and triglycerides in the same model, triglycerides still retained a robust effect. Decreased levels of apoA-I and HDL cholesterol were associated with increased risk of endometriosis and endometriosis of the pelvic peritoneum in univariable MR analyses. After mutual adjustment, HDL cholesterol retained a robust effect whereas the association for apoA-I was attenuated.

Conclusions: This is the first MR-based evidence to suggest that triglycerides and HDL cholesterol are the predominant traits that account for the aetiological relationship of lipoprotein lipids with risk of endometriosis, in particular endometriosis of the pelvic peritoneum. Further well-designed randomized controlled trials are needed to address these results.

Purpose: (i) To analyze age-adjusted incidence rates of synchronous bone metastases diagnosed alongside primary malignancy from 2010 to 2018 in the US population, (ii) determine the incidence proportions (IPs) and characteristics of synchronous bone metastases among newly diagnosed cancer patients in the USA especially pediatric cases, and (iii) assess the implications of synchronous bone metastases on cancer patient's survival, and identify the survival risk factors for these cancer patients.

Methods: Utilizing data from the Surveillance, Epidemiology, and End Results (SEER) program (2010-2018), we calculated age-adjusted IPs and annual percentage change (APC), and employed logistic regression and Cox regression models for our analysis.

Results: 3 300 736 cancer patients were identified. The age-adjusted incidence rates of synchronous bone metastases increased from 2010 (18.04/100 000) to 2018 (20.89/100 000; APC: 2.3, 95% confidence interval [CI], 1.4-3.1), but decreased in lung cancer (average APC: -1.0, 95% CI, -1.8 to -0.3). The highest IPs were observed in pediatric neuroblastoma (43.2%; 95% CI, 39.8%-46.7%) and adult small cell carcinoma (23.1%; 95% CI, 22.7%-23.4%). Multivariate logistic analyses revealed that primary tumor characteristics were correlated with higher bone metastases risk. Survival analyses also showed varied prognostic outcomes based on metastasis sites and demographics among cancer patients. Landmark analyses further indicated among long-term cancer survivors (≥3 and ≥5 years), patients with de novo bone metastases had the poorest survival rates compared with those with other synchronous metastases (P < 0.001).

Conclusion: This study provides a population-based estimation of the incidence and prognosis for synchronous bone metastases. Our findings highlight the need for early identification of high-risk groups and multidisciplinary approaches to improve prognosis of cancer patients with de novo bone metastases.