To analyze the clinical and genetic features of oculopharyngodistal myopathy (OPDM) patients and compare the phenotypic differences among various causative genes.

ObjectiveTo investigate the status and influencing factors of latent tuberculosis infection (LTBI) among close contacts of patients with bacteriologically confirmed pulmonary tuberculosis in Jing’an District, Shanghai, and to provide scientific evidence for the development of tuberculosis infection testing and preventive intervention strategies for close contacts of bacteriologically positive patients. MethodsFrom October 2022 to October 2023, patients with bacteriological confirmed pulmonary tuberculosis registered in Jing’an District, Shanghai, and their close contacts were enrolled as the research subjects. The close contacts were screened for tuberculosis infection using the interferon-γ release assay (IGRA). The chi-square test and binary logistic regression model were used to analyze factors influencing LTBI. ResultsA total of 112 close contacts were included, of whom 30 (26.79%) were male and 82 (73.21%) were female. The age ranged from 1 to 86 years, with a median (25th, 75th percentiles) of 47.50 (32.25, 61.00) years. The infection rate of LTBI was 21.43% (24/112), and the incidence of active pulmonary tuberculosis was 2.68% (3/112). Univariate analyses showed that a positive sputum smear of the index case, being a direct relative of the index case, co-living, and not wearing a mask were significantly associated with LTBI (all P<0.05). Multivariate logistic regression analyses showed that the risk of latent infection in close contacts of the index case with a positive sputum smear was 6.50 times higher than in those with a negative sputum smear (95%CI: 1.82‒23.25, P=0.004). ConclusionThe infection rate of LTBI in close contacts of patients with bacteriologically confirmed pulmonary tuberculosis in Jing’an District, Shanghai, is relatively high, and close contacts of sputum smear-positive patients face an even higher risk of infection. Therefore, tuberculosis infection screening and follow-up management should be strengthened for this population.

Objective: To investigate the chemical compositions of Maxing Shigan Decoction (麻杏石甘汤, MXSGD) and elucidate its anti-influenza A virus (IAV) mechanism from prediction to validation. Methods: Ultra high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was employed to analyze the chemical compositions of MXSGD. Network pharmacology theories were used to screen and identify shared targets of both the potential targets of active ingredients of MXSGD and IAV. A protein-protein interaction (PPI) network was then constructed, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. The binding stability between core bioactive compounds and key targets was validated by molecular docking and dynamic simulations. A total of 24 BALB/c mice were infected with IAV to build IAV mouse models. After successful modelling, the mouse models were randomly divided into model, MXSGD high-dose (2.8 g/kg), MXSGD low-dose (1.4 g/kg), and oseltamivir (20.14 mg/kg) groups, with an additional normal mice as control group (n = 6 per group). The treatments were administered by gavage daily between 8:00 a.m. and 10:00 a.m. for five consecutive days. Upon completion of the administration, the body weight ratio, lung index, protein content in the bronchoalveolar lavage fluid (BALF), and the levels of inflammatory factors including interleukin (IL)-6 and tumor necrosis factor (TNF)-α in mice were measured to preliminarily analyze the therapeutic efficacy of MXSGD against IAV infection. Furthermore, the expression levels of mechanistic target of rapamycin (mTOR), hypoxia inducible factor (HIF)-1α, and vascular endothelial growth factor (VEGF) proteins in the HIF-1 signaling pathway, which was enriched by network pharmacology, were detected by Western blot. Results: A total of 212 chemical components in MXSGD were identified by the UPLC-MS/MS method. These chemical components can be classified into 9 primary categories and 31 secondary categories. After intersecting the chemical component targets with IAV-related targets, a total of 567 potential MXSGD components targeting IAV were identified. The construction of PPI network and the results of both GO and KEGG enrichment analyses revealed that the anti-IAV effects of MXSGD were associated with multiple pathways, including apoptosis, TNF, HIF-1, and IL-17 signaling pathways. The results of molecular docking demonstrated that the binding energies between the core compound 1-methoxyphaseollin and key targets including HIF-1α, mTOR, and VEGF were all lower than – 5.0 kcal/mol. Furthermore, molecular dynamics simulations confirmed the structural stability of the resulting complexes. Animal experiments showed that compared with the normal controls, IAV-infected mice showed significantly reduced body weight ratio, markedly increased lung index, protein content in BALF, and the levels of inflammatory factors such as IL-6 and TNF-α (P < 0.01), thereby causing damage to the lung tissue; consequently, the expression levels of mTOR, HIF-1α, and VEGF proteins in the lung tissues of these mice were significantly elevated (P < 0.01). However, after MXSGD treatment, the mouse models presented a significant increase in body weight ratio, as well as marked decreases in lung index, protein content in BALF, and the levels of inflammatory factors including IL-6 and TNF-α (P < 0.01). Furthermore, the therapy alleviated IAV-induced injuries and significantly downregulated the expression levels of mTOR, HIF-1α, and VEGF proteins in lung tissues (P < 0.01 or P < 0.05). Conclusion MXSGD exerts anti-IAV effects through multi-component, multi-target, and multi-pathway synergism. Among them, 1-methoxyphaseollin is identified as a potential key component, which alleviates virus-induced lung injury and inflammatory response via the regulation of HIF-1 signaling pathway, providing experimental evidence for the clinical application of MXSGD.

Objective: To establish a progressive research strategy for “colonic components analysis - efficacy verification and mechanism exploration - gut microbiota”, screen pharmacodynamic substances, and investigate their mechanism via gut microbiota. Methods: The pharmacodynamics of Gegen Qinlian decoction (GQD) were assessed using a mouse model of dextran sulfate sodium-induced ulcerative colitis (UC). Ultra-performance liquid chromatography-quadrupole-orbitrap mass spectrometer was used to identify the prototype and metabolic components of GQD in the colon during UC. To analyze the structure and function of characteristic genera of GQD and its active components, 16S rRNA sequencing was performed. Results: We identified 67 prototypic and 14 metabolic components of GQD in the UC colon. The primary prototype components are flavonoids and alkaloids, including puerarin (PUE), baicalin (BAI), and berberine (BER). The metabolism was predominantly sulfonation. Efficacy verification showed that the main active components, puerarin, baicalin, and berberine, had good therapeutic effects on UC. The results of 16S rRNA gene sequencing showed that GQD improved UC by regulating the structure and function of the gut microbiota. The abundance of gut microbiota involved in the metabolism of the prototype components was influenced by the corresponding components. The function prediction results showed that PUE was the most comparable to GQD, with 24 consistent pathways. BAI and BER showed comparable gut microbiota regulation pathways. Characteristic pathways of BER include glucometabolic processes. Conclusion This study focused on the key issues in the gut microbiota pathway and developed a progressive research strategy to understand the transformation mechanisms of colonic components. This research systematically analyzed the active components and metabolic transformation of GQD in the colon during the pathological state of UC, as well as changes in the structure and function of the gut microbiota, clarified the mechanism of GQD and its active components in improving UC via the gut microbiota pathway.

Objective:To report the clinical, imaging, and pathological features of a case of MYH7 gene-related scapuloperoneal myosin storage myopathy. Methods:Clinical data were collected from a patient with MYH7 gene-related scapuloperoneal myosin storage myopathy who presented to Peking University First Hospital in February 2025. The patient was evaluated with muscle magnetic resonance imaging, muscle biopsy, and whole-exome sequencing. Results:The patient was a 52-year-old female, with a 12-year history of progressive difficulty in foot dorsiflexion, exercise-induced fatigue, and lower limb pain. Over the past 3 years, she developed proximal upper limb weakness and post-exertional myalgia. Physical examination revealed scapuloperoneal weakness distribution accompanied by sensorineural hearing loss. Electromyography demonstrated myogenic changes in the deltoid and tibialis anterior muscles. Serum creatine kinase levels were within normal limits. Lower limb magnetic resonance imaging showed mild atrophy of the thigh muscles and significant fatty infiltration in the tibialis anterior, extensor hallucis longus, and extensor digitorum longus. Tibialis anterior muscle biopsy revealed dystrophic-like changes with sub-sarcolemmal hyaline bodies containing abundant granulofilamentous material. Whole exome sequencing identified a heterozygous pathogenic variant of c.5352_5354del(p.K1784del) in the MYH7 gene. Conclusions:This patient is the first reported one in China with MYH7 gene-related scapuloperoneal myosin storage myopathy, exhibiting characteristic scapuloperoneal weakness, selective fatty infiltration of the anterior lower leg muscles on imaging and sub-sarcolemmal hyaline body pathological changes. The diagnosis of this disease relies on characteristic pathological findings and genetic test results.

Objective:To explore the application value of the artificial intelligence (AI) morphological assisted analysis system in the pre-classification of blood cells in patients with acute myeloid leukemia, myelodysplasia-related (AML-MR).Methods:A retrospective analysis was conducted on the bone marrow and peripheral blood cell morphology of patients initially diagnosed with AML-MR at Taizhou Hospital in Zhejiang Province from September 1, 2022, to December 31, 2023. A total of 44 patients, including 25 males and 19 females, with a median age of 71 (63.5, 75.3) years. Bone marrow and peripheral blood morphology were examined using the Morphogo cell morphology assisted analysis system, with the artificial classification results serving as the gold standard. A confusion matrix was constructed to evaluate the precision, sensitivity, and specificity of the AI system in identifying various cell types in bone marrow and peripheral blood for AML-MR diagnosis. The impact of dysplastic hematopoiesis on AI pre-classification was analyzed by comparing AI and manual classification results.Results:The AI system completed the pre-classification of 44 bone marrow smears and 42 corresponding peripheral blood smears from AML-MR patients. For bone marrow smears, the precision, sensitivity, and specificity of AI in pre-classifying blast cells were 85.78%, 91.01%, and 94.58%, respectively. For peripheral blood smears, these values were 87.11%, 87.05%, and 98.29%, respectively. The precision and sensitivity of AI in pre-classifying promyelocytes were 54.26% and 46.93%, respectively, while for monocytes, they were 58.16% and 68.34%, both lower than those for blast cells. The precision and sensitivity of AI in identifying myelocytes and metamyelocytes also decreased (77.47%, 66.25% and 81.91%, 63.29%, respectively). The precision and sensitivity of AI in pre-classifying erythroblasts/proerythroblasts (67.71%, 69.89%) were lower than those for polychromatic and orthochromatic normoblasts (83.43%, 85.53% and 92.97%, 86.96%, respectively). The confusion matrix and comparative analysis of AI and manual classification indicated that the decline in AI pre-classification precision and sensitivity was due to frequent misclassification between promonocytes and monocytes, as well as between monocytes and promyelocytes. Additionally, this decline is associated with dysplasia. However, the impact of dysplasia on the AI pre-classification of mature-stage granulocytes was minimal.Conclusion:The AI system demonstrated high precision, sensitivity, and specificity in pre-classifying blast cells in bone marrow and peripheral blood smears from AML-MR patients. The AI-assisted morphological analysis system can be effectively utilized for the pre-classification of blood cells in AML-MR patients.

Objective:To explore the immunophenotypic differences between acute promyelocytic leukemia (APL) and APL-like NPM1 mutant acute myeloid leukemia (NPM1mutAML) using flow cytometry, and to investigate early diagnostic markers for differentiating APL from NPM1mutAML.Methods:A retrospective study was conducted on 72 cases of APL diagnosed at Taizhou Hospital, affiliated with Wenzhou Medical University, from February 2nd, 2018 to December 16th, 2023, including 42 male and 30 female patients with a median age of 42 (32, 57) years old. Based on morphology, 51 cases were classified as the coarse-granular type and 21 cases as the fine-granular type. Additionally, 45 cases of NPM1mutAML, comprising 20 male and 25 female patients with a median age of 58 (47, 65) years old, were included. Of these, 12 cases were classified as the coarse-granular type and 33 as the fine-granular type. Immunophenotypic analysis was performed using multiparameter flow cytometry, and all patients underwent cytogenetic analysis for chromosome karyotyping. FISH analysis was used for detecting the PML-RARα fusion gene in APL cases, and sequencing was used for identifying NPM1 mutations in NPM1mutAML patients. The antigen expression parameters (expression rate, median fluorescence intensity [MdFI], and coefficient of variation [ CV]) were analyzed using principal component analysis (PCA). The antigen expression rates were compared using the Wilcoxon rank-sum test, and the positive rates of antigens were compared using the Chi-square test. Sensitivity and specificity for diagnosis by the some antigens were evaluated using ROC curve analysis. Results:The immunophenotypic analysis revealed that the expression rates of CD123, CD64, CD13, and CD9 were significantly higher in APL compared to NPM1mutAML ( Z values of-6.72, -6.29, -5.63, -7.67, P<0.01). In the coarse-granular type, the expression rates of CD123 and CD9 in APL were also significantly higher than those in NPM1mutAML ( P<0.01). In the fine-granular type, the expression levels of CD123, CD13, CD64, and CD9 were significantly higher in APL than in NPM1mutAML ( P<0.01). ROC curve analysis showed that in the fine-granular type, the areas under the curve (AUC) for CD64, CD13, CD123, and CD9 in diagnosing APL and NPM1mutAML were 0.96, 0.89, 0.86, and 0.89, respectively ( P<0.01). In the coarse-granular type, the AUC for CD64 and CD13 were 0.49 and 0.51 ( P>0.05), while the AUC for CD123 and CD9 were 0.96 and 0.96 ( P<0.01). Principal component analysis (PCA) of antigen expression (expression rate, MdFI, CV) showed complete separation of the APL and NPM1mutAML groups. Conclusion:APL and APL-like NPM1mutAML patients exhibit distinct antigen expression profiles. Specifically, a combined detection of CD64, CD13, CD123, and CD9 can help to rapidly differentiate APL from APL-like NPM1mutAML at initial diagnosis.

Objective To analyze the monitoring data of cardio-cerebrovascular diseases prevention and control system in Yichang in 2022, and to provide data support and experience for the precise prevention and treatment of cardio-cerebrovascular diseases. Methods Acute cardiovascular and cerebrovascular event data were collected from the Yichang Cardio-cerebrovascular Events Monitoring System from January 1, 2022 to December 31, 2022. Descriptive analysis was conducted for the data collected. Statistical analysis was performed using SPSS 20.0 software, and a chi-square test was used to analyze the count data. Results A total of 37,217 cases of cardio-cerebrovascular events were monitored in Yichang in 2022. The crude incidence and the standardized incidence were 983.84/100,000 and 541.55/100,000, respectively. The incidence in males was higher than females (554.93/100,000 vs 428.91/100,000，χ² =464.52，P＜0.05). The top three diseases were cerebral infarction, acute myocardial infarction, and cerebral hemorrhage. The incidence of events increased with age, and 79.80% of the cases were over 60 years old. The main onset time was from May to August. Conclusion The use of the cardio-cerebrovascular events monitoring system in Yichang and the implementation of ^“mandatory reporting card^” monitoring can timely obtain the epidemic characteristics of the diseases, provide support for the precise formulation of prevention and control strategies and measures, reduce underreporting rates, and improve the monitoring system, which is worthy of reference and promotion.