ObjectiveFrom the perspective of cardiovascular-kidney-metabolic （CKM） syndrome， this study aims to construct and validate a diagnostic machine learning model integrating traditional Chinese and Western medicine for severe coronary artery stenosis in patients with CKM， thereby providing clinical decision-making support for patients with borderline lesions. MethodsBased on a retrospective study design， a total of 535 hospitalized patients from two independent campuses of Jiangsu Province Hospital of Traditional Chinese Medicine： the main campus （from January 2024 to August 2024） and Zidong branch （from September 2024 to December 2024） were screened. Data from the main campus were randomly divided into the training dataset （376 cases） and the internal validation dataset （95 cases） at a 4∶1 ratio， while data from Zidong branch served as the external validation dataset （64 cases）. Risk factors were analyzed and screened through literature review， expert interviews， and the least absolute shrinkage and selection operator （LASSO） algorithm. Nine machine learning algorithms were utilized to construct diagnostic models. Comparative analyses of common evaluation metrics， calibration curves， and decision curves were conducted to select the model through internal and external validation. The Shapley additive explanations （SHAP） method and two cases were utilized to help understand the operational logic of the best model. Finally， the best model was applied to patients with borderline lesions to calculate diagnostic efficacy. ResultsNine risk factors were screened by LASSO regression， such as phlegm， hematoma， stagnation， deficiency， hypertension duration， gender， arterial stiffness index （ASI）， uric acid to high-density lipoprotein cholesterol ratio （UHR）， and glycosylated hemoglobin （HbA1c）. After comparison from multiple dimensions， the light gradient boosting machine （LightGBM） was the best model， achieving area under the curve （AUC） of 0.918 （95% confidence interval （CI）： 0.890-0.945） in the training dataset， 0.885 （95%CI： 0.820-0.951） in the internal validation dataset， and 0.897 （95%CI： 0.818-0.975） in the external validation dataset. Calibration curves indicated good consistency in the predicted probabilities， while decision curve analysis showed clinical benefit when threshold probabilities were less than 90%. SHAP importance rankings were stagnation， deficiency， hematoma， HbA1c， gender， phlegm， hypertension duration， ASI， and UHR. When applied to the patients with borderline lesions， the diagnostic model achieved an AUC of 0.783 （95%CI： 0.637-0.930）， with 73% of patients with actual severe stenosis getting benefit. ConclusionGuided by clinical value， the diagnostic model integrating traditional Chinese and Western medicine established in this study demonstrates favorable performance， providing a basis for clinical diagnosis， treatment， and decision-making in patients with CKM.

ObjectiveFrom the perspective of cardiovascular-kidney-metabolic （CKM） syndrome， this study aims to construct and validate a diagnostic machine learning model integrating traditional Chinese and Western medicine for severe coronary artery stenosis in patients with CKM， thereby providing clinical decision-making support for patients with borderline lesions. MethodsBased on a retrospective study design， a total of 535 hospitalized patients from two independent campuses of Jiangsu Province Hospital of Traditional Chinese Medicine： the main campus （from January 2024 to August 2024） and Zidong branch （from September 2024 to December 2024） were screened. Data from the main campus were randomly divided into the training dataset （376 cases） and the internal validation dataset （95 cases） at a 4∶1 ratio， while data from Zidong branch served as the external validation dataset （64 cases）. Risk factors were analyzed and screened through literature review， expert interviews， and the least absolute shrinkage and selection operator （LASSO） algorithm. Nine machine learning algorithms were utilized to construct diagnostic models. Comparative analyses of common evaluation metrics， calibration curves， and decision curves were conducted to select the model through internal and external validation. The Shapley additive explanations （SHAP） method and two cases were utilized to help understand the operational logic of the best model. Finally， the best model was applied to patients with borderline lesions to calculate diagnostic efficacy. ResultsNine risk factors were screened by LASSO regression， such as phlegm， hematoma， stagnation， deficiency， hypertension duration， gender， arterial stiffness index （ASI）， uric acid to high-density lipoprotein cholesterol ratio （UHR）， and glycosylated hemoglobin （HbA1c）. After comparison from multiple dimensions， the light gradient boosting machine （LightGBM） was the best model， achieving area under the curve （AUC） of 0.918 （95% confidence interval （CI）： 0.890-0.945） in the training dataset， 0.885 （95%CI： 0.820-0.951） in the internal validation dataset， and 0.897 （95%CI： 0.818-0.975） in the external validation dataset. Calibration curves indicated good consistency in the predicted probabilities， while decision curve analysis showed clinical benefit when threshold probabilities were less than 90%. SHAP importance rankings were stagnation， deficiency， hematoma， HbA1c， gender， phlegm， hypertension duration， ASI， and UHR. When applied to the patients with borderline lesions， the diagnostic model achieved an AUC of 0.783 （95%CI： 0.637-0.930）， with 73% of patients with actual severe stenosis getting benefit. ConclusionGuided by clinical value， the diagnostic model integrating traditional Chinese and Western medicine established in this study demonstrates favorable performance， providing a basis for clinical diagnosis， treatment， and decision-making in patients with CKM.

[摘 要] 目的：探讨lncRNA DLEU2通过EZH2/H3K27me3途径调控IKKα介导甲状腺癌（TC）放射性碘抵抗的作用机制。方法：利用TCGA数据库分析TC中DLEU2的表达及其与EZH2的相关性。构建放射性碘抵抗的TPC-1细胞（RR-TPC-1细胞）模型及裸鼠移植瘤模型，通过敲低或过表达DLEU2（si-DLEU2/OE-DLEU2）、抑制EZH2（UNC1999）、过表达IKKα（OE-IKKα）进行干预，采用qPCR、WB、RIP、ChIP、CCK-8、流式细胞术、TUNEL染色及体内成瘤实验检测基因与蛋白表达、表观修饰、细胞增殖、凋亡及肿瘤生长。结果：TCGA分析显示，DLEU2在TC组织中显著上调（P < 0.001），与患者不良预后相关（P = 0.008 4），且与EZH2表达呈正相关（r = 0.390, P < 0.001）；RIP证实EZH2与DLEU2存在相互作用/结合（P < 0.05）。体外实验表明，敲低DLEU2可显著下调RR-TPC-1细胞中EZH2、IKKα表达及H3K27me3修饰水平，抑制NF-κB通路活化（P < 0.05或P < 0.01），抑制细胞增殖、促进凋亡（均P < 0.05）。联合敲低DLEU2与抑制EZH2进一步增强上述效应，而过表达IKKα则可部分逆转上述效应（P < 0.05或P < 0.01）。体内实验进一步证实，敲低DLEU2联合抑制EZH2可显著抑制移植瘤生长，增加肿瘤细胞凋亡（均P < 0.01）；IKKα过表达则部分逆转上述抗肿瘤效应（P < 0.05或P < 0.01）。结论：lncRNA DLEU2通过招募EZH2催化H3K27me3修饰，间接激活IKKα/NF-κB信号并形成正反馈环路，介导TPC-1细胞131I抵抗。

Objective To investigate the prevalence of thyroid nodules in the physical examination population in Mianyang region and analyze its association with metabolic syndrome. Methods A retrospective study was conducted on 9 978 individuals who underwent health examinations at our hospital from January 2024 to May 2025. Thyroid examinations were performed using color Doppler ultrasound to analyze the prevalence of thyroid nodules in this population. Clinical data of all subjects were collected, and logistic regression analysis was employed to assess the association between metabolic syndrome and the risk of thyroid nodule development. Results The prevalence of thyroid nodules in the physical examination population of Mianyang region was 17.98% (1 794/9 978). The logistic regression results showed that after adjusting for gender, age, BMI, occupation, consumption of non-iodized salt, staying up late, daily sleep duration, anxiety, and depression, metabolic syndrome (OR=6.593, 95% CI: 3.961-10.975) was associated with thyroid nodules (P<0.05). Conclusion The prevalence of thyroid nodules among the physical examination population in the Mianyang area is 17.98%, and metabolic syndrome remains associated with the risk of thyroid nodules after effectively controlling for confounding factors.

ObjectiveTo explore the expression levels of long non-coding RNA （lncRNA） H19 and microRNA-22-3p （miR-22-3p） in the serum of patients with acute myocardial infarction （AMI） and their diagnostic value for AMI. MethodsA total of 176 AMI patients were selected as the experimental group and were divided into ST-segment elevation myocardial infarction （STEMI） group （n=95） and non-ST-segment elevation myocardial infarction （NSTEMI） group （n=81） based on their medical history and electrocardiogram. Meanwhile， 156 patients with negative angiography during the same period were selected as the control group （CON group）. The relative expression levels of lncRNA H19 and miR-22-3p in the serum of the two groups were detected by real-time fluorescence quantitative polymerase chain reaction. The diagnostic value of miR-22-3p and lncRNA H19 in AMI was evaluated by receiver operating characteristic curve （ROC） analysis. The levels of serum cardiac troponin I （cTnI）， creatine kinase （CK）， creatine kinase MB isoenzyme （CK-MB）， and high-sensitivity C-reactive protein （CRP） were detected in all study subjects. Spearman correlation analyses were used to evaluate the correlations between lncRNA H19 and miR-22-3p and cTnI， CK， CK-MB and CRP. ResultsCompared with the control group， the expression level of lncRNA H19 was upregulated and the expression level of miR-22-3p was downregulated in the AMI group （all P<0.01）； compared with the NSTEMI group， the expression level of lncRNA H19 was upregulated and the expression level of miR-22-3p was downregulated in the STEMI group （P<0.01）. The areas under the ROC curves （AUC） for the diagnosis of AMI by miR-22-3p， lncRNA H19 and their combination were 0.555， 0.977， and 0.983， respectively. lncRNA H19 was positively correlated with cTnI， CK， CK-MB and CRP （P<0.05）， and negatively correlated with left ventricular ejection fraction （LVEF） （P<0.001）； miR-22-3p was negatively correlated with cTnI， CK and CRP， and positively correlated with LVEF （P<0.05）. ConclusionThe expression level of lncRNA H19 is elevated and the expression level of miR-22-3p decreased in AMI patients， and their levels may have potential value as an auxiliary biomarker for AMI diagnosis and cardiac function assessment.

Objective To analyze the epidemiology and trends of measles,tuberculosis,pertussis,scarlet fever,influenza,mumps and rubella in Beijing between 2014 and 2023 in order to provide data for prevention and control of related diseases.Methods Data on the incidences of seven respiratory infectious diseases in Beijing between 2014 and 2023 was collected.Descriptive epidemiological methods were employed to analyze their demographic,temporal and spatial distribution.Joinpoint regression analysis was used to assess temporal trends in incidence.Results A total of 1 406 777 cases of seven respiratory infectious diseases were reported in Beijing between 2014 and 2023,which corresponded to an average crude rate of 649.76/100 000 reported annually.The crude rate of incidencewas higher among females than among males,with the most vulnerable age groups being 0-4 years and 5-19 years,and was higher in the six districts than on the outskirts.Most of the respiratory infectious diseases peaked in winter and spring.The annual increase in the incidence of respiratory infectious diseases in Beijing in this period averaged 27.27％,with no statistically significant differences in trends.The incidence rates of measles,tuberculosis,scarlet fever,mumps and rubella decreased significantly while those of pertussis and influenza increased,but with no statistically significant difference.Conclusion The overall incidence of major respiratory infectious diseases in Beijing is increasing.It is recommended that more people get vaccinated,surveillance of such diseases as pertussis and influenza be enhanced,and regional health resources be allocated more effectively,all of which will be critical to subsequent prevention and control of respiratory infectious diseases in Beijing.

OBJECTIVE: To explore the genetic basis for a girl with primary microcephaly and growth retardation. METHODS: A girl who was admitted to Guangdong Maternal and Child Health Care Hospital in was selected as the study subject. Peripheral blood samples were collected from the child and her parents. Trio whole exome sequencing was carried out, and candidate variants were verified by Sanger sequencing and bioinformatic analysis. This study was approved by the Medical Ethnics Committee of Guangdong Maternal and Child Health Care Hospital (Ethics No. 202201278). RESULTS: DNA sequencing revealed that the child has harbored compound heterozygous variants of the WDR62 gene, including a frameshifting c.2963delC (p.Pro988Argfs*80) variant in exon 24 which was inherited from the unaffected father, and a nonsense c.3163G>T (p.Glu1055*) variant in exon 26, which was inherited from her unaffected mother. Both variants were predicted to affect the reading frame of the WDR62 gene. CONCLUSION Based on the clinical manifestations, results of genetic testing and pedigree analysis, the compound heterozygous variants were predicted to underlay the pathogenesis of microcephaly and growth retardation in this child. Above discovery has expanded the mutational spectrum for WDR62-associated Primary microcephaly type 2, and facilitated genetic counseling for the family.
Female ; Humans ; Cell Cycle Proteins ; Heterozygote ; Microcephaly/genetics* ; Mutation ; Nerve Tissue Proteins/genetics* ; Pedigree

Arginine methylation is a critical post-translational modification that plays multifaceted biological functions. However, the manipulation of protein arginine methylation largely depends on genetic or pharmaceutic inhibition of the regulatory enzymes, protein arginine methyltransferases (PRMTs), or non-methylation substitution of corresponding arginine residue to lysine or alanine of protein of interest (POI), which inevitably affects other substrates, or disrupts the structure of POI. Thus, it urges an approach to specifically modulate the arginine methylation of a POI under physiological conditions. To this end, we report the discovery of a methylation tagging system (MeTAG), that enables targeted modification of protein arginine methylation. Through bridging the methyltransferase PRMT5 proximity to a POI, MeTAG facilitates the arginine methylation of POIs, including known arginine methylated proteins, androgen receptor (AR) and protein kinase B (AKT), as well as a neo-substrate E1A binding protein (p300), in a reversible and PRMT5-dependent manner. Moreover, MeTAG can regulate downstream signaling in a methylation dependent manner, leading to downregulation of PSMA mRNA level and activation of AKT. Therefore, MeTAG represents a feasible approach to modulate protein methylation and thereby perturbs protein function in biological and therapeutic contexts.

In this study, araucarene diterpenes, characterized by a pimarene skeleton with a variably oxidized side chain at C-13, were investigated. A total of 16 araucarene diterpenoids and their derivatives were isolated from the woods of Agathis dammara, including 11 previously unreported compounds: dammaradione (1), dammarones D-G (2, 5, 14, 15), dammaric acids B-F (8-12), and dammarol (16). The structures of these new compounds were elucidated using high-resolution electrospray ionization mass spectroscopy (HR-ESI-MS) and one-dimensional/two-dimensional (1D/2D) nuclear magnetic resonance (NMR), while their absolute configurations were determined through the electronic circular dichroism (ECD) exciton chirality method and Snatzke's method. The hypoglycemic activity of all isolated compounds was evaluated using a transgenic zebrafish model, and a structure-activity relationship (SAR) analysis was conducted. Araucarone (3) and dammaric acid C (9), serving as representative compounds, demonstrated significant hypoglycemic effects on zebrafish. The primary mechanism involves the promotion of pancreatic β cell regeneration and glucose uptake. Specifically, these compounds enhance the differentiation of pancreatic endocrine precursor cells (PEP cells) into β cells in zebrafish.
Zebrafish ; Animals ; Diterpenes/isolation & purification* ; Insulin-Secreting Cells/cytology* ; Glucose/metabolism* ; Hypoglycemic Agents/isolation & purification* ; Molecular Structure ; Structure-Activity Relationship ; Plant Extracts/pharmacology* ; Regeneration/drug effects*