Postgraduate Medical Journal最新文献

{"title":"Mechanisms of intestinal flora in colorectal cancer.","authors":"Junchuan Li, Li Liu, Xiaoqiong Zhong, Runxin Yang","doi":"10.1093/postmj/qgaf026","DOIUrl":"https://doi.org/10.1093/postmj/qgaf026","url":null,"abstract":"<p><p>The intestinal flora is a complex community of microbes that inhabit the digestive tract and live with their hosts symbiotically. Several gastrointestinal diseases, such as colorectal cancer (CRC), have been associated with dysbiosis, an imbalance between beneficial and opportunistic pathogens. Dysbiosis breaks the mucosal barrier, leading to inflammation and cancer. Increased numbers of harmful bacteria, such as Escherichia coli (E. coli) and Enterotoxigenic Bacteroides fragilis (ETBF), have been associated with chronic inflammation and the release of carcinogenic mediators, increasing the chances of inflammatory dysplasia. Compared with a healthy person, CRC patients showed reduced bacterial diversity and abundance, while Firmicutes and Bacteroidetes were increased. Specific bacteria have also been linked to the development and progression of CRC, such as E. coli, ETBF, and Enterococcus faecalis. Therefore, the aim was to analyze the association between the gut microbiota and CRC. Further research could assess the advantages of modulating the intestinal flora as protection for high-risk patients against CRC, affecting disease prognosis and patients' life.</p>","PeriodicalId":20374,"journal":{"name":"Postgraduate Medical Journal","volume":" ","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143557810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying novel risk targets in inflammatory skin diseases by comprehensive proteome-wide Mendelian randomization study.","authors":"Yajia Li, Ziqin Cao, Jianhuang Wu","doi":"10.1093/postmj/qgaf032","DOIUrl":"https://doi.org/10.1093/postmj/qgaf032","url":null,"abstract":"<p><strong>Background: </strong>Despite advances in cancer biomarkers and targeted therapies, early diagnosis and treatment of inflammatory skin diseases remain challenging. This study aims to identify circulating proteins causally linked to inflammatory skin diseases, including acne, atopic dermatitis, systemic lupus erythematosus, psoriasis, rosacea, and urticaria, through a Mendelian randomization (MR) framework.</p><p><strong>Methods: </strong>A large-scale MR analysis was performed to assess the causal effects of thousands of plasma proteins on common inflammatory skin diseases. Additional methods, including Steiger filtering, transcriptome-wide association studies, summary data-based MR, protein-protein interaction networks, pathway enrichment analyses, Bayesian colocalization, and drug target evaluation, were employed to validate MR findings and explore therapeutic targets.</p><p><strong>Results: </strong>This study identified >100 circulating proteins that may be involved in inflammatory skin diseases. Tier 1 therapeutic targets include RARRES2, SERPINC1, GALK1, and ECM1 for atopic dermatitis and RARRES2, PPID, and IL1RL1 for acne, rosacea, and urticaria. These proteins represent promising avenues for developing new treatments, with the potential to improve diagnostics and therapeutic strategies in the future.</p><p><strong>Conclusion: </strong>This MR analysis revealed numerous plasma proteins associated with inflammatory skin diseases, offering insights into protein-mediated mechanisms and highlighting promising therapeutic targets for future interventions. Key message What is already known on this topic  Inflammatory skin diseases, including psoriasis, atopic dermatitis, and acne, are complex conditions linked to systemic factors such as alterations in circulating plasma proteins. Previous studies have identified certain proteins involved in skin immune responses; however, a comprehensive understanding of their causal roles remains lacking. What this study adds  This study utilized a large-scale proteome-wide Mendelian randomization analysis to identify >100 circulating proteins causally linked to inflammatory skin diseases. Notably, proteins such as RARRES2, SERPINC1, and ECM1 were highlighted as potential therapeutic targets for atopic dermatitis and acne, among others. How this study might affect research, practice, or policy  The findings provide novel insights into protein-mediated mechanisms underlying inflammatory skin diseases, suggesting new diagnostic and therapeutic avenues. Future research should focus on validating these protein targets in clinical settings and exploring their potential for therapeutic intervention.</p>","PeriodicalId":20374,"journal":{"name":"Postgraduate Medical Journal","volume":" ","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143557805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rituximab therapy for connective tissue disease-associated interstitial lung disease: a systematic review and meta-analysis.","authors":"Jiaqi Zhang, Yanjun Wan, Liheng Liu, Yan Tang, Pingping Li, Hui Huang","doi":"10.1093/postmj/qgaf034","DOIUrl":"https://doi.org/10.1093/postmj/qgaf034","url":null,"abstract":"<p><strong>Background: </strong>Rituximab (RTX) is utilized for treating connective tissue disease-associated interstitial lung disease (CTD-ILD) by eliminating pathogenic B cells, yet its clinical benefit remains debated. This study evaluates RTX's efficacy and safety in CTD-ILD.</p><p><strong>Methods: </strong>A literature search was conducted in PubMed, Embase, and Cochrane Library for studies on RTX in CTD-ILD up to May 24, 2024. The Joanna Briggs Institute checklist assessed study quality. Changes in forced vital capacity (FVC%) and diffusing capacity of the lungs for carbon monoxide (DLCO%) before and after RTX use were compared, and analyzed between RTX and control groups.</p><p><strong>Results: </strong>1052 CTD-ILD patients from 40 studies were analyzed. RTX significantly improved FVC% (WMD = 7.10, 95% CI = 4.58-9.62, P < 0.05) and DLCO% (WMD = 5.26, 95% CI = 2.86-7.65, P < 0.01), and reduced the modified Rodnan skin score (mRSS) (WMD = -6.58, 95% CI = -8.27 to -4.89, P < 0.01) and prednisone dose (WMD = -6.94, 95% CI = -11.96 to -1.92, P < 0.01). Among RTX-treated patients, 30.3% improved, 45.3% remained stable, and 10.0% progressed. Adverse effects included infection (22.4%), hospitalization (6.7%), and mortality (5.0%).</p><p><strong>Conclusions: </strong>RTX significantly enhances lung function in CTD-ILD patients, as shown in this systematic review and meta-analysis.</p><p><strong>Systematic review registration: </strong>PROSPERO, identifier CRD42024520084.</p>","PeriodicalId":20374,"journal":{"name":"Postgraduate Medical Journal","volume":" ","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143567684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine-learning models to predict serious adverse hospitalization events after ACS.","authors":"Hui Gao, Xuanze Liu, Dongyuan Sun, Xue Liu, Yasong Wang, Zhiqiang Zhang, Yaling Han, Xiaozeng Wang","doi":"10.1093/postmj/qgae180","DOIUrl":"https://doi.org/10.1093/postmj/qgae180","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;We developed a risk stratification model to predict serious adverse hospitalization events (mortality, cardiac shock, cardiac arrest) (SAHE) after acute coronary syndrome (ACS) based on machine-learning models and logistic regression model.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This cohort study is based on the CCC-ACS project. The primary efficacy outcomes were SAHE. Clinical prediction models were established based on five machine-learning (XGBoost, RF, MLP, KNN, and stacking model) and logistic regression models.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Among the 112 363 patients in the study, age (55-65 years: OR: 1.392; 95%CI: 1.212-1.600; 65-75 years: OR: 1.878; 95%CI: 1.647-2.144; ≥75 year: OR: 2.976; 95%CI: 2.615-3.393), history of diabetes mellitus (OR: 1.188; 95%CI: 1.083-1.302), history of renal failure (OR: 1.645; 95%CI: 1.311-2.044), heart rate (60-100 beats/min: OR: 0.468; 95%CI: 0.409-0.536; ≥100 beats/min: OR: 0.540; 95%CI: 0.454-0.643), shock index (0.4-0.8: OR: 1.796; 95%CI: 1.440-2.264; ≥0.8: OR: 5.883; 95%CI: 4.619-7.561), KILLIP (II: OR: 1.171; 95%CI: 1.048-1.306; III: OR: 1.696; 95%CI: 1.469-1.952; IV: OR: 7.811; 95%CI: 7.023-8.684), and cardiac arrest at admission (OR: 12.507; 95%CI: 10.757-14.530) were independent predictors of severe adverse hospitalization events for ACS patients. In several machine-learning models, RF (AUC: 0.817; 95%CI: 0.808-0.826) and XGBoost (AUC: 0.816; 95%CI: 0.807-0.825) also showed good discrimination in the training set, which ranked the first two positions. They also presented good accuracy and the best clinical benefits in the decision curve analysis. In addition, logistic regression was able to discriminate the SAHE (AUC: 0.816; 95%CI: 0.807-0.825) and performed the best prediction accuracy (0.822; 95%CI: 0.822-0.822) compared to several machine-learning models. Model calibration and decision curve analysis showed these prediction models have similar predictive performance. Based on these findings, we developed two CCC-ACS In-hospital Major Adverse Events Risk Scores and its online calculator. One is based on machine-learning model (https://ccc-acs-sae-3-xcnjsvoccusjwkfhfthh44.streamlit.app/), and another is based on logistic regression model (https://ccc-acs-sae-logistic-9te57ylnq3kazkeuyc7dub.streamlit.app/), offering a validated tool to predict survival for patients with ACS during hospitalization.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Machine-learning-based approaches for identifying predictors of SAHE after an ACS were feasible and practical. Based on this, we developed two online risk prediction websites for clinicians' decision-making. The CCC-ACS-MSAE score showed accurate discriminative capabilities for predicting severe adverse hospitalization events and might help guide clinical decision-making. Key messages: Three research questions and three bullet points What is already known on this topic? Observational studies have identified risk factors for in-hospital death i","PeriodicalId":20374,"journal":{"name":"Postgraduate Medical Journal","volume":" ","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143557807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of cardiovascular health in the associations between insulin resistance, future cardiovascular disease, and all-cause mortality.","authors":"Weida Qiu, Chang Xiong, Kehao Zeng, Liwen Li, Zhiping Gao","doi":"10.1093/postmj/qgaf033","DOIUrl":"https://doi.org/10.1093/postmj/qgaf033","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Whether cardiovascular health (CVH) modifies the associations between insulin resistance (IR) and prognosis remains unclear. This study aims to evaluate the varying relationships between IR, future cardiovascular disease (CVD), and all-cause mortality across different CVH statuses.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This was a nationwide cohort study using data from the China Health and Nutrition Survey. The CVH was assessed using the Life's Essential 8 (LE8) metrics, and IR was determined by the homeostasis model assessment of insulin resistance (HOMA-IR) index and the triglyceride-glucose (TyG) index. The study outcomes included incident CVD and all-cause mortality.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;47.0% of the included participants (n = 8635) were men, and the mean age (SD) was 49.7 (15.8) years, with 37.5%, 51.6%, and 10.9% having poor, intermediate, and ideal CVH. During a 6-year follow-up, 482 (5.6%) participants had incident CVD, and 435 individuals died (incidence rate: 7.9 (95% CI: 7.2, 8.7) 1000 person-years). HOMA-IR and the TyG index were positively associated with increased risks of CVD and mortality among participants with intermediate or poor CVH, while no significant associations were found between IR indexes with CVD and death in those with ideal CVH (P for interaction &lt; .05). 13.0% and 16.8% of the associations between CVH and CVD were mediated by HOMA-IR and the TyG index. Similar significant indirect effects of HOMA-IR and the TyG index on the relationship between CVH and all-cause mortality were observed.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;CVH significantly modified the associations between two IR surrogates and long-term CVD and all-cause mortality. Increased risk probabilities of future CVD and mortality were observed among individuals with intermediate or poor CVH. IR mediated a substantial proportion of the associations between CVH and CVD and all-cause mortality, emphasizing the importance of maintaining healthy behaviors and factors to reduce the burden of CVD and mitigate the detrimental impact of IR. Key message What is already known on this subject  The global prevalence of insulin resistance (IR) and diabetes mellitus (DM) is extremely high and their associated disease burden is heavy. Ideal cardiovascular health (CVH) is significant associated with a lower risk of IR and better prognosis. What this study adds  Only 10.9% of the participants maintained ideal CVH in this large Chinese cohort, while more than one-third had poor CVH. CVH significantly modified the associations between two IR surrogates and long-term CVD and all-cause mortality. Increased risk probabilities of future CVD and mortality were observed among individuals with intermediate or poor CVH. IR mediated a substantial proportion of the associations between CVH and CVD and all-cause mortality. How this study might affect research, practice, or policy  Our study indicated that a large number of Chinese citizens still have ","PeriodicalId":20374,"journal":{"name":"Postgraduate Medical Journal","volume":" ","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143557437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Drug selection in the management of acute low back pain and sciatica: consideration of pain characteristics and drug metabolism.","authors":"Chao Zhang, Qian Wu","doi":"10.1093/postmj/qgaf025","DOIUrl":"https://doi.org/10.1093/postmj/qgaf025","url":null,"abstract":"","PeriodicalId":20374,"journal":{"name":"Postgraduate Medical Journal","volume":" ","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143483605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hyperkalaemia: the unintended consequence of prescribing Co-trimoxazole for complex infections.","authors":"Andrew Lazarowicz, Matthew O'Connor, Audrey Morris, Angus McFadyen, Sharon Irvine, Chris Isles","doi":"10.1093/postmj/qgaf022","DOIUrl":"https://doi.org/10.1093/postmj/qgaf022","url":null,"abstract":"","PeriodicalId":20374,"journal":{"name":"Postgraduate Medical Journal","volume":" ","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143459010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Academic pressure behind the suicide crisis of doctoral students at the Indian Institute of Technology: rethinking doctoral education policies.","authors":"Bo Gao","doi":"10.1093/postmj/qgaf030","DOIUrl":"https://doi.org/10.1093/postmj/qgaf030","url":null,"abstract":"","PeriodicalId":20374,"journal":{"name":"Postgraduate Medical Journal","volume":" ","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143458968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Can you(th) afford healthcare? The case of financial microtoxicity.","authors":"Christos Tsagkaris, Islam Kourampi, Kyriaki Apergi","doi":"10.1093/postmj/qgaf029","DOIUrl":"https://doi.org/10.1093/postmj/qgaf029","url":null,"abstract":"","PeriodicalId":20374,"journal":{"name":"Postgraduate Medical Journal","volume":" ","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143458984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comprehensive analysis of aging-related gene expression patterns and identification of potential intervention targets.","authors":"Sha Yang, Jianning Song, Min Deng, Si Cheng","doi":"10.1093/postmj/qgae131","DOIUrl":"10.1093/postmj/qgae131","url":null,"abstract":"<p><strong>Purpose: </strong>This study aims to understand the molecular mechanisms underlying the aging process and identify potential interventions to mitigate age-related decline and diseases.</p><p><strong>Methods: </strong>This study utilized the GSE168753 dataset to conduct comprehensive differential gene expression analysis and co-expression module analysis. Machine learning and Mendelian randomization analyses were employed to identify core aging-associated genes and potential drug targets. Molecular docking simulations and mediation analysis were also performed to explore potential compounds and mediators involved in the aging process.</p><p><strong>Results: </strong>The analysis identified 4164 differentially expressed genes, with 1893 upregulated and 2271 downregulated genes. Co-expression analysis revealed 21 modules, including both positively and negatively correlated modules between older age and younger age groups. Further exploration identified 509 aging-related genes with distinct biological functions. Machine learning and Mendelian randomization analyses identified eight core genes associated with aging, including DPP9, GNAZ, and RELL2. Molecular docking simulations suggested resveratrol, folic acid, and ethinyl estradiol as potential compounds capable of attenuating aging through modulation of RELL2 expression. Mediation analysis indicated that eosinophil counts and neutrophil count might act as mediators in the causal relationship between genes and aging-related indicators.</p><p><strong>Conclusion: </strong>This comprehensive study provides valuable insights into the molecular mechanisms of aging and offers important implications for the development of anti-aging therapeutics. Key Messages What is already known on this topic - Prior research outlines aging's complexity, necessitating precise molecular targets for intervention. What this study adds - This study identifies novel aging-related genes, potential drug targets, and therapeutic compounds, advancing our understanding of aging mechanisms. How this study might affect research, practice, or policy - Findings may inform targeted therapies for age-related conditions, influencing future research and clinical practices.</p>","PeriodicalId":20374,"journal":{"name":"Postgraduate Medical Journal","volume":" ","pages":"219-231"},"PeriodicalIF":3.6,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142366275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}