The ASK-SEAT: a competency-based assessment scale for students majoring in clinical medicine.

BACKGROUND: To validate a competency-based assessment scale for students majoring in clinical medicine, ASK-SEAT. Students' competency growth across grade years was also examined for trends and gaps. METHODS: Questionnaires were distributed online from May through August in 2018 to Year-2 to Year-6 students who majored in clinical medicine at the Shantou University Medical College (China). Cronbach alpha values were calculated for reliability of the scale, and exploratory factor analysis employed for structural validity. Predictive validity was explored by correlating Year-4 students' self-assessed competency ratings with their licensing examination scores (based on Kendall's tau-b values). All students' competency development over time was examined using the Mann-Whitney U test. RESULTS: A total of 760 questionnaires meeting the inclusion criteria were analyzed. The overall Cronbach's alpha value was 0.964, and the item-total correlations were all greater than 0.520. The overall KMO measure was 0.966 and the KMO measure for each item was greater than 0.930 (P < 0.001). The eigenvalues of the top 3 components extracted were all greater than 1, explaining 55.351, 7.382, and 5.316% of data variance respectively, and 68.048% cumulatively. These components were aligned with the competency dimensions of skills (S), knowledge (K), and attitude (A). Significant and positive correlations (0.135 < Kendall's tau-b < 0.276, p < 0.05) were found between Year-4 students' self-rated competency levels and their scores for the licensing examination. Steady competency growth was associated with almost all indicators, with the most pronounced growth in the domain of skills. A lack of steady growth was seen in the indicators of "applying the English language" and "conducting scientific research & innovating". CONCLUSIONS: The ASK-SEAT, a competency-based assessment scale developed to measure medical students' competency development shows good reliability and structural validity. For predictive validity, weak-to-moderate correlations are found between Year-4 students' self-assessment and their performance at the national licensing examination (Year-4 students start their clinical clerkship during the 2nd semester of their 4th year of study). Year-2 to Year-6 students demonstrate steady improvement in the great majority of clinical competency indicators, except in the indicators of "applying the English language" and "conducting scientific research & innovating".

Diagnostic accuracy of cryptococcal antigen test in pulmonary cryptococcosis: a protocol for a systematic review and meta-analysis.

BACKGROUND: The cryptococcal antigen (CrAg) test was proposed as a rapid diagnostic tool to identify cryptococcal meningitis in patients suffering from AIDS. Several studies have demonstrated its diagnostic performance in cryptococcal meningitis. However, the diagnostic performance of the CrAg test in serum or bronchoalveolar lavage fluid in patients with pulmonary cryptococcosis remains uncertain. Therefore, the purpose of this systematic review is to summarise the evidence concerning diagnostic performance of the CrAg test in patients with pulmonary cryptococcosis. METHODS AND ANALYSIS: Databases such as PubMed, EMBASE, Cochrane Database of Systematic Reviews, Web of Science, ClinicalTrials.gov, International Clinical Trials Registry Platform, Wanfang Database and China National Knowledge Infrastructure will be searched systematically. The titles and abstracts will be reviewed by two independent reviewers. The Quality Assessment of Diagnostic Accuracy Studies 2 tool will be used to evaluate the risk of bias and clinical applicability of each study. Potential sources of heterogeneity will be investigated through visual inspection of the paired forest plots and summary receiver operating characteristic plots. The pooled summary statistics for the area under the curve, sensitivities, specificities, likelihood ratios and diagnostic ORs with 95% CI will be reported. ETHICS AND DISSEMINATION: The underlying study is based on published articles thus does not require ethical approval. The findings of the systematic review and meta-analysis will be published in a peer-reviewed journal and disseminated in various scientific conferences and seminars. PROSPERO REGISTRATION NUMBER: CRD42022373321.

Identification of Enterocytozoon bieneusi in an HIV-negative bronchiectasis patient with respiratory infection based on metagenomic next-generation sequencing: A case report.

Bronchiectasis is often caused by serious infections. Infections caused by Enterocytozoon bieneusi (E. bieneusi) is most common in the immunocompromised host, such as HIV-positive patients. Herein, we reported an HIV-negative patient with bronchiectasis infected with E. bieneusi, which diagnosed by mNGS and validated by Sanger sequencing. During the treatment of albendazole, the patient gradually recovered. This is the first report of a case of respiratory E. bieneusi infection in a bronchiectasis patient. This finding highlights the efficacy of mNGS for pathogen diagnosis in bronchiectasis patients and the potential treatment option of albendazole for bronchiectasis patients with E. bieneusi infection.

Construction and analysis of evaluation model for medical students' innovation competency based on research-oriented biochemistry and molecular biology course in China.

Presently, a variety of policies and measures has implemented to enhance the scientific research and innovation ability of medical students, but in the process of practice, there are many problems, such as they lack of independent topic selection ability, weak scientific research skills, lack of autonomous learning ability, the research results are simple and ineffective, limited teacher guidance time and so on. This paper attempted to build an effective model for the promotion of medical students' scientific research and innovation ability, in order to establish an efficacy evaluation model of the "Medical students' Innovative Scientific Research Program." Undergraduates, graduate assistants, and tutors were interviewed with the Behavioral Event Interview technique, and a questionnaire of efficacy evaluation characteristics concluded from the interviews was formed. The questionnaire was conducted on medical students in the Medical students' Innovative Scientific Research Program, and the constructed model was analyzed using reliability analysis, validity analysis, and variation analysis. At the same time, the experimental teaching models are summarized and combed, and compared with other methods such as independent sample test. The results show the model could effectively evaluate the efficacy of the Medical students' Innovative Scientific Research Program and its teaching model is effective in cultivating medical students' learning and scientific research ability. It can provide theoretical support and practical reference for the evaluation and reform of the teaching modes related to the cultivation of scientific and innovative ability of medical students.

A homologous and molecular dual-targeted biomimetic nanocarrier for EGFR-related non-small cell lung cancer therapy.

The abnormal activation of epidermal growth factor receptor (EGFR) drives the development of non-small cell lung cancer (NSCLC). The EGFR-targeting tyrosine kinase inhibitor osimertinib is frequently used to clinically treat NSCLC and exhibits marked efficacy in patients with NSCLC who have an EGFR mutation. However, free osimertinib administration exhibits an inadequate response in vivo, with only ∼3% patients demonstrating a complete clinical response. Consequently, we designed a biomimetic nanoparticle (CMNP@Osi) comprising a polymeric nanoparticle core and tumor cell-derived membrane-coated shell that combines membrane-mediated homologous and molecular targeting for targeted drug delivery, thereby supporting a dual-target strategy for enhancing osimertinib efficacy. After intravenous injection, CMNP@Osi accumulates at tumor sites and displays enhanced uptake into cancer cells based on homologous targeting. Osimertinib is subsequently released into the cytoplasm, where it suppresses the phosphorylation of upstream EGFR and the downstream AKT signaling pathway and inhibits the proliferation of NSCLC cells. Thus, this dual-targeting strategy using a biomimetic nanocarrier can enhance molecular-targeted drug delivery and improve clinical efficacy.

Pretreatment radiomic biomarker for immunotherapy responder prediction in stage IB-IV NSCLC (LCDigital-IO Study): a multicenter retrospective study.

BACKGROUND: The predictive efficacy of current biomarker of immune checkpoint inhibitors (ICIs) is not sufficient. This study investigated the causality between radiomic biomarkers and immunotherapy response status in patients with stage IB-IV non-small cell lung cancer (NSCLC), including its biological context for ICIs treatment response prediction. METHODS: CT images from 319 patients with pretreatment NSCLC receiving immunotherapy between January 2015 and November 2021 were retrospectively collected and composed a discovery (n=214), independent validation (n=54), and external test cohort (n=51). A set of 851 features was extracted from tumorous and peritumoral volumes of interest (VOIs). The reference standard is the durable clinical benefit (DCB, sustained disease control for more than 6 months assessed via radiological evaluation). The predictive value of combined radiomic signature (CRS) for pathological response was subsequently assessed in another cohort of 98 patients with resectable NSCLC receiving ICIs preoperatively. The association between radiomic features and tumor immune landscape on the online data set (n=60) was also examined. A model combining clinical predictor and radiomic signatures was constructed to improve performance further. RESULTS: CRS discriminated DCB and non-DCB patients well in the training and validation cohorts with an area under the curve (AUC) of 0.82, 95% CI: 0.75 to 0.88, and 0.75, 95% CI: 0.64 to 0.87, respectively. In this study, the predictive value of CRS was better than programmed cell death ligand-1 (PD-L1) expression (AUC of PD-L1 subset: 0.59, 95% CI: 0.50 to 0.69) or clinical model (AUC: 0.66, 95% CI: 0.51 to 0.81). After combining the clinical signature with CRS, the predictive performance improved further with an AUC of 0.837, 0.790 and 0.781 in training, validation and D2 cohorts, respectively. When predicting pathological response, CRS divided patients into a major pathological response (MPR) and non-MPR group (AUC: 0.76, 95% CI: 0.67 to 0.81). Moreover, CRS showed a promising stratification ability on overall survival (HR: 0.49, 95% CI: 0.27 to 0.89; p=0.020) and progression-free survival (HR: 0.43, 95% CI: 0.26 to 0.74; p=0.002). CONCLUSION: By analyzing both tumorous and peritumoral regions of CT images in a radiomic strategy, we developed a non-invasive biomarker for distinguishing responders of ICIs therapy and stratifying their survival outcome efficiently, which may support the clinical decisions on the use of ICIs in advanced as well as patients with resectable NSCLC.

[Role of circular RNAs in immune-related diseases].

Objective Circular RNAs (circRNAs) are non-coding RNAs (ncRNA) circularized without a 3' polyadenylation [poly-(A)] tail or a 5' cap, resulting in a covalently closed loop structure. circRNAs were first discovered in RNA viruses in the 1970s, but only a small number of circRNAs were discovered at that time due to limitations in traditional polyadenylated transcriptome analyses. With the development of specific biochemical and computational methods, recent studies have shown the presence of abundant circRNAs in eukaryotic transcriptomes. circRNAs play vital roles in many physiological and pathological processes, such as acting as miRNA sponges, binding to RNA-binding proteins (RBPs), acting as transcriptional regulatory factors, and even serving as translation templates. Current evidence has shown that circRNAs can be potentially used as excellent biomarkers for diagnosis, therapeutic effect evaluation, and prognostic assessment of a variety of diseases, and they may also provide effective therapeutic targets due to their stability and tissue and development-stage specificity. This review focuses on the properties of circRNAs and their immune relationship to disease, and explores the role of circRNAs in immune-related diseases and the directions of future research.

Combining autophagy and immune characterizations to predict prognosis and therapeutic response in lung adenocarcinoma.

Background: Autophagy, a key regulator of programmed cell death, is critical for maintaining the stability of the intracellular environment. Increasing evidence has revealed the clinical importance of interactions between autophagy and immune status in lung adenocarcinoma. The present study evaluated the potential of autophagy-immune-derived biomarkers to predict prognosis and therapeutic response in patients with lung adenocarcinoma. Methods: Patients from the GSE72094 dataset were randomized 7:3 to a training set and an internal validation set. Three independent cohorts, TCGA, GSE31210, and GSE37745, were used for external verification. Unsupervised hierarchical clustering based on autophagy- and immune-associated genes was used to identify autophagy- and immune-associated molecular patterns, respectively. Significantly prognostic autophagy-immune genes were identified by LASSO analysis and by univariate and multivariate Cox regression analyses. Differences in tumor immune microenvironments, functional pathways, and potential therapeutic responses were investigated to differentiate high-risk and low-risk groups. Results: High autophagy status and high immune status were associated with improved overall survival. Autophagy and immune subtypes were merged into a two-dimensional index to characterize the combined prognostic classifier, with 535 genes defined as autophagy-immune-related differentially expressed genes (DEGs). Four genes (C4BPA, CD300LG, CD96, and S100P) were identified to construct an autophagy-immune-related prognostic risk model. Survival and receiver operating characteristic (ROC) curve analyses showed that this model was significantly prognostic of survival. Patterns of autophagy and immune genes differed in low- and high-risk patients. Enrichment of most immune infiltrating cells was greater, and the expression of crucial immune checkpoint molecules was higher, in the low-risk group. TIDE and immunotherapy clinical cohort analysis predicted that the low-risk group had more potential responders to immunotherapy. GO, KEGG, and GSEA function analysis identified immune- and autophagy-related pathways. Autophagy inducers were observed in patients in the low-risk group, whereas the high-risk group was sensitive to autophagy inhibitors. The expression of the four genes was assessed in clinical specimens and cell lines. Conclusions: The autophagy-immune-based gene signature represents a promising tool for risk stratification in patients with lung adenocarcinoma, guiding individualized targeted therapy or immunotherapy.

Identification of Prognostic Model Based on Immune-Related LncRNAs in Stage I-III Non-Small Cell Lung Cancer.

BACKGROUND: Long non-coding RNAs (lncRNAs) participate in the regulation of immune response and carcinogenesis, shaping tumor immune microenvironment, which could be utilized in the construction of prognostic signatures for non-small cell lung cancer (NSCLC) as supplements. METHODS: Data of patients with stage I-III NSCLC was downloaded from online databases. The least absolute shrinkage and selection operator was used to construct a lncRNA-based prognostic model. Differences in tumor immune microenvironments and pathways were explored for high-risk and low-risk groups, stratified by the model. We explored the potential association between the model and immunotherapy by the tumor immune dysfunction and exclusion algorithm. RESULTS: Our study extracted 15 immune-related lncRNAs to construct a prognostic model. Survival analysis suggested better survival probability in low-risk group in training and validation cohorts. The combination of tumor, node, and metastasis staging systems with immune-related lncRNA signatures presented higher prognostic efficacy than tumor, node, and metastasis staging systems. Single sample gene set enrichment analysis showed higher infiltration abundance in the low-risk group, including B cells (p<0.001), activated CD8+ T cells (p<0.01), CD4+ T cells (p<0.001), activated dendritic cells (p<0.01), and CD56+ Natural killer cells (p<0.01). Low-risk patients had significantly higher immune scores and estimated scores from the ESTIMATE algorithm. The predicted proportion of responders to immunotherapy was higher in the low-risk group. Critical pathways in the model were enriched in immune response and cytoskeleton. CONCLUSIONS: Our immune-related lncRNA model could describe the immune contexture of tumor microenvironments and facilitate clinical therapeutic strategies by improving the prognostic efficacy of traditional tumor staging systems.