Objective: o develop an onset risk prediction nomogram for patients with homocysteine-type (H-type) hypertension (HTH) based on pulse diagram parameters to assist early clinical prediction and diagnosis of HTH. Methods: Patients diagnosed with essential hypertension and admitted to Shanghai Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai Hospital of Traditional Chinese Medicine, and Shanghai Hospital of Integrated Traditional Chinese and Western Medicine from July 6th 2020 to June 16th 2021, and from August 11th 2023 to January 22nd 2024, were enrolled in this retrospective research. The baselines and clinical biochemical indicators of patients were collected. The SMART-I TCM pulse instrument was applied to gather pulse diagram parameters. Multivariate logistic regression was adopted to analyze the risk factors for HTH. RStudio was employed to construct the nomogram model, receiver operating characteristic (ROC) curve, and calibration curve (bootstrap self-sampling 200 times), and clinical decision curve were drawn to evaluate the model’s discrimination and clinical effectiveness. Results: A total of 168 hospitalized patients with essential hypertension were selected and divided into non-HTH group (n = 29) and HTH group (n = 139). Compared with non-HTH group, HTH group had a lower body mass index (BMI), and higher proportions of male patients and drinkers (P < 0.05). The ventricular wall thickening (VWT) could not be determined. The proportions of left common carotid intima-media wall thickness (LCCIMWT) and serum creatinine (SCR) were higher in HTH group (P < 0.05). The pulse diagram parameter As was significantly higher, and H4/H1 and T1/T were lower in HTH group (P < 0.05). Gender, alcohol consumption, serum creatinine, and the pulse diagram parameter H4/H1 were identified as independent risk factors for HTH (P < 0.05). The nomogram’s area under the ROC curve (AUC) was 0.795 [95% confidence interval (CI): (0.706 6, 0.882 8)], with a specificity of 0.724 and sensitivity of 0.799. After 200 times repeated bootstrap self-samplings, the calibration curve showed that the simulated curve fits well with the actual curve (x2 = 9.5002, P = 0.301 9). The clinical decision curve indicated that the nomogram’s applicability was optimal when the threshold for predicting HTH was between 0.38 and 1.00. Conclusion The nomogram model could be valuable for predicting the onset risk of HTH and pulse diagram parameters can facilitate early screening and prevention of HTH.

Objective To analyze the effect of residual cholesterol (RC) on hearing loss in noise-exposed workers. Methods A total of 3 412 workers engaged in noise operation work in an underground railway enterprise were selected as the research subjects using the judgment sampling method. Their occupational health examination data were collected to analyze the relationship between RC and hearing loss. Results The noise intensity of workplace in the underground rail enterprise was 80.0-85.0 (81.4±3.2) dB(A). The detection rate of hearing loss was 20.2% (691/3 412). The rates of abnormal total cholesterol, triacylglycerol, high density lipoprotein cholesterol (HDL-C) and low density lipoprotein cholesterol were 35.6%, 25.7%, 9.5% and 42.4%, respectively. The median and the 25th and 75th percentiles [M(P₂₅,P₇₅)] of RC level were 0.24 (0.15, 0.37) mmol/L. The levels of total cholesterol, triacylglycerol and RC of workers in hearing loss group were higher than those in normal hearing group [M(P₂₅,P₇₅): 4.91(4.37, 5.58) vs 4.84(4.30, 5.46) mmol/L, 1.29(0.91, 1.93) vs 1.16(0.82, 1.67) mmol/L, 0.26(0.16, 0.41) vs 0.24(0.14, 0.37) mmol/L, all P<0.05]. The detection rate of hearing loss in abnormal triglyceride group was higher than that in normal triglyceride group (24.8% vs 18.7%, P<0.01), and the detection rate of hearing loss in abnormal HDL-C group was higher than that in normal HDL-C group (25.0% vs 19.8%, P<0.05). The higher the serum RC level, the higher the detection rate of hearing loss (P<0.01). Multivariate logistic regression result showed that individual with older age, longer work time and higher serum RC level had higher risk of hearing abnormality (all P<0.05), and the risk of hearing abnormality was higher in patients with abnormal fasting blood glucose than patients with normal faseing blood glucose (P<0.05) after controlling for confounding factors such as gender, alcohol consumption, body mass index, and elevated blood pressure. However, abnormal triacylglycerol and HDL-C levels were not significantly related to the risk of hearing abnormality (both P>0.05). Conclusion Serum RC levels are an independent risk factor for hearing loss among noise-exposed workers exposed to noise level of 80.0-85.0 dB(A) in the workplace.

Objective To observe the value of synthetic MRI(SyMRI)MAGnetic resonance image Compilation(MAGiC)sequence parameters for differentiating cervical squamous cell carcinoma and cervical adenocarcinoma.Methods Sixty-six patients with pathologically confirmed cervical cancer were retrospectively enrolled and divided into cervical squamous cell carcinoma group(n=56)and cervical adenocarcinoma group(n=10).Quantitative MAGiC parameters were collected and compared between groups,and those being significantly different were combined to construct a logistic regression model.The performance of each parameter alone and their combination for differentiating cervical squamous cell carcinoma and cervical adenocarcinoma was evaluated with receiver operating characteristic(ROC)curve and the area under the curve(AUC).Results In cervical adenocarcinoma group,lesions's T1 and T2 were higher,while R1 and R2 were lower than those in cervical squamous cell carcinoma group(all P＜0.05).No statistically significant difference of proton density was found between groups(P＞0.05).The AUC of T1,T2,R1,R2 alone and their combination for differentiating cervical squamous cell carcinoma and cervical adenocarcinoma was 0.959,0.945,0.961,0.942 and 0.996,respectively,and no significant difference was found between each two ones(Z=0.267 to 1.396,all P＞0.05).Conclusion SyMRI had high value for differentiating cervical squamous cell carcinoma and cervical adenocarcinoma.

Objective To use imaging features of pulmonary nodules to predict the risk of lymph node metastasis in patients with cT1-stage non-small cell lung cancer (NSCLC), providing a reference for clinical decision-making. Methods A retrospective analysis was conducted on the imaging features and postoperative pathological results of cT1 NSCLC patients who underwent surgical treatment at Linyi People’s Hospital from July 2019 to July 2022. Patients were grouped and analyzed according to lymph node metastasis status. Results A total of 1 123 patients were included, comprising 471 males and 652 females, with a median age of 59 (52, 66) years. Comparative analysis revealed that sex, age, nodule location, nodule size on imaging, solid component size, consolidation tumor ratio (CTR), average CT value, and tumor proximity to the pleura all influenced lymph node metastasis. A nomogram was constructed, indicating that the probability of lymph node metastasis in cT1 NSCLC was positively correlated with solid component size, CTR, and average CT value of the pulmonary nodule, and negatively correlated with patient age. The area under the receiver operating characteristic curve was 0.929. Conclusion For cT1 NSCLC patients, the probability of lymph node metastasis can be predicted by measuring the solid component size, CTR, and average CT value of the pulmonary nodule, in conjunction with patient age. However, relying solely on pulmonary nodule imaging characteristics is insufficient to determine a specific lymph node dissection strategy.

Objective To construct a model for predicting the risk of essential hypertension accompanied by left ventricular hypertrophy using machine learning algorithms based on pulse diagram parameters;To explore its clinical application value.Methods A total of 295 patients with essential hypertension who were hospitalized in Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine,Shanghai Hospital of Traditional Chinese Medicine and Shanghai Hospital of Integrated Traditional Chinese and Western Medicine were selected from July 2020 to May 2021 and July 2023 to July 2024.According to the echocardiographic results,the selected research subjects were divided into the essential hypertension with left ventricular hypertrophy group(referred to as the"LVH group")and the essential hypertension without left ventricular hypertrophy group(referred to as the"non-LVH group").The general data and clinical biochemical indicators were collected,and the pulse diagram parameters of the patients were detected using the SMART-I type TCM digital pulse analyzer.A clinical prediction model was constructed based on decision tree,support vector machine and extreme gradient boosting model algorithms.The predictive performance of the model was evaluated in terms of discrimination,calibration and clinical prediction ability by using the receiver operating characteristic(ROC)curve,calibration curve and decision curve analysis respectively.The influence of each predictive factor on the risk of LVH in essential hypertension was explained based on the SHAP algorithm.Results Compared with the non-LVH group,the BMI,the proportion of males,drinkers and smokers was lower in the LVH group,with statistical significance(P<0.05);the thickened ventricular wall,left ventricular internal dimension enlargement,left common carotid artery intima-media thickness and high density lipoprotein cholesterol were higher in the LVH group than in the non-LVH group(P<0.05);the left common carotid peak systolic velocity,left common carotid resistance index,serum uric acid and serum creatinine were lower in the LVH group than in the non-LVH group(P<0.05).The pulse diagram parameters T4,T,W1,W2,H3/H1 and H4/H1 were higher in the LVH group than in the non-LVH group(P<0.05).The areas of the ROC curves of the models constructed by the three types of machine learning algorithms were 0.887,0.962 and 0.873 respectively,indicating that the model had good discrimination and certain diagnostic efficacy.The calibration curve suggested that the prediction accuracy of the model was average;the clinical decision curve showed that XGBoost model has a higher net benefit.Conclusion The interpretable model constructed based on pulse diagram parameters and machine learning algorithms can be used as a reliable tool for predicting the risk of essential hypertension with LVH.

Objective To construct a model for predicting the risk of essential hypertension accompanied by left ventricular hypertrophy using machine learning algorithms based on pulse diagram parameters;To explore its clinical application value.Methods A total of 295 patients with essential hypertension who were hospitalized in Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine,Shanghai Hospital of Traditional Chinese Medicine and Shanghai Hospital of Integrated Traditional Chinese and Western Medicine were selected from July 2020 to May 2021 and July 2023 to July 2024.According to the echocardiographic results,the selected research subjects were divided into the essential hypertension with left ventricular hypertrophy group(referred to as the"LVH group")and the essential hypertension without left ventricular hypertrophy group(referred to as the"non-LVH group").The general data and clinical biochemical indicators were collected,and the pulse diagram parameters of the patients were detected using the SMART-I type TCM digital pulse analyzer.A clinical prediction model was constructed based on decision tree,support vector machine and extreme gradient boosting model algorithms.The predictive performance of the model was evaluated in terms of discrimination,calibration and clinical prediction ability by using the receiver operating characteristic(ROC)curve,calibration curve and decision curve analysis respectively.The influence of each predictive factor on the risk of LVH in essential hypertension was explained based on the SHAP algorithm.Results Compared with the non-LVH group,the BMI,the proportion of males,drinkers and smokers was lower in the LVH group,with statistical significance(P<0.05);the thickened ventricular wall,left ventricular internal dimension enlargement,left common carotid artery intima-media thickness and high density lipoprotein cholesterol were higher in the LVH group than in the non-LVH group(P<0.05);the left common carotid peak systolic velocity,left common carotid resistance index,serum uric acid and serum creatinine were lower in the LVH group than in the non-LVH group(P<0.05).The pulse diagram parameters T4,T,W1,W2,H3/H1 and H4/H1 were higher in the LVH group than in the non-LVH group(P<0.05).The areas of the ROC curves of the models constructed by the three types of machine learning algorithms were 0.887,0.962 and 0.873 respectively,indicating that the model had good discrimination and certain diagnostic efficacy.The calibration curve suggested that the prediction accuracy of the model was average;the clinical decision curve showed that XGBoost model has a higher net benefit.Conclusion The interpretable model constructed based on pulse diagram parameters and machine learning algorithms can be used as a reliable tool for predicting the risk of essential hypertension with LVH.

Objective To observe the value of synthetic MRI(SyMRI)MAGnetic resonance image Compilation(MAGiC)sequence parameters for differentiating cervical squamous cell carcinoma and cervical adenocarcinoma.Methods Sixty-six patients with pathologically confirmed cervical cancer were retrospectively enrolled and divided into cervical squamous cell carcinoma group(n=56)and cervical adenocarcinoma group(n=10).Quantitative MAGiC parameters were collected and compared between groups,and those being significantly different were combined to construct a logistic regression model.The performance of each parameter alone and their combination for differentiating cervical squamous cell carcinoma and cervical adenocarcinoma was evaluated with receiver operating characteristic(ROC)curve and the area under the curve(AUC).Results In cervical adenocarcinoma group,lesions's T1 and T2 were higher,while R1 and R2 were lower than those in cervical squamous cell carcinoma group(all P＜0.05).No statistically significant difference of proton density was found between groups(P＞0.05).The AUC of T1,T2,R1,R2 alone and their combination for differentiating cervical squamous cell carcinoma and cervical adenocarcinoma was 0.959,0.945,0.961,0.942 and 0.996,respectively,and no significant difference was found between each two ones(Z=0.267 to 1.396,all P＞0.05).Conclusion SyMRI had high value for differentiating cervical squamous cell carcinoma and cervical adenocarcinoma.

Objective:To investigate the effect and mechanism of vitamin K2 on vascular calcification in a type 2 diabetes rat model.Methods:Thirty male Wistar rats,6 weeks old,were acclimatized for 7 days.Ten rats were randomly selected as the negative control group,fed a normal diet,and injected with an equal amount of citrate buffer.The remaining rats were fed a high-fat and high-sugar diet for 4 weeks,and then type 2 diabetes was induced by intraperitoneal injection of streptozotocin.After successful induction of the diabetes model,the diabetic rats were numbered by body weight and divided into the diabetes group and the diabetes+vitamin K2 group according to the principle of stratified random grouping.These two groups were fed a high-fat diet and a high-fat diet containing vitamin K2,respectively,while the control group continued to be fed a normal diet.After 13 weeks of feeding,the rats were sacrificed for sample collection,and blood glucose and vascular calcium concentration were measured.Von Kossa staining was used for histopathological detection.The relative expression levels of hypoxia-inducible factor-1α(HIF-1α),pyruvate dehydrogenase kinase 4(PDK4),matrix Gla protein(MGP),and bone morphogenetic protein-2(BMP-2)mRNA and proteins were measured by qRT-PCR and Western blot,respectively.Results:Compared with the control group,blood glucose levels in the diabetes group and diabetes+vitamin K2 group were significantly elevated(P＜0.01),but there was no significant difference between the two groups.There was no significant difference in vascular calcium concentration among the three groups(P＞0.05).Von Kossa staining showed that the control group exhibited normal vascular structures,while the diabetes group showed a large number of brown-black calcification plaques between elastic fibers in the vascular media.The diabetes+vitamin K2 group had either no calcification plaques or only a few brown-black calcification plaques.Compared with the control group,the expression levels of PDK4,MGP,and BMP-2 mRNA and proteins were higher in the diabetes group(P＜0.05),but there was no significant difference in the expression level of HIF-1α.Only the expression level of PKD4 protein had significance between the control group and diabetes+vitamin K2 group(P＜0.05).There was no significant difference in the above indexes between the diabetic group and diabetic+vitamin K2 group(P＞0.05).Conclusions:Type 2 diabetes mellitus may cause vascular calcification by increasing the expression of PDK4,which in turn leads to increased expression of BMP-2 and MGP.Vitamin K2 can inhibit vascular calcification in diabetes.

Objective:To study the correlation between zinc finger protein A20 (A20) and basic fibroblast growth factor (BFGF) and liver fibrosis in chronic hepatitis B.Methods:A retrospective study was conducted to select 120 patients with chronic hepatitis B diagnosed and treated in the Fifth Hospital of Shijiazhuang City from January 2019 to December 2020, all of whom underwent liver tissue biopsy, and 25 cases of liver pathological specimens who underwent liver hemangioma resection were selected. The correlation between the expression of A20 and BFGF in liver tissue and the stage of hepatic fibrosis and inflammation were analyzed.Results:The expression of A20 in the S1 - S4 phase was higher than that in the S0 phase: (6.12 ± 1.22)%, (10.18 ± 2.43)%, (16.94 ± 5.06)%, (25.99 ± 7.57)% vs. (0.81 ± 0.29)%; the expression of BFGF in the S1 - S4 phase was higher than that in the S0 phase: (6.12 ± 1.22)%, (10.18 ± 2.43)%, (16.94 ± 5.06)%, (25.99 ± 7.57)% vs. (0.81 ± 0.29)%, there were statistical differences ( P<0.05). The expression of A20 in the G1 - G4 phase was higher than that in the G0 phase: (6.56 ± 1.87)%, (10.01 ± 3.29)%, (15.54 ± 5.01)%, (25.86 ± 8.02)% vs. (0.85 ± 0.71)%; the expression of BFGF in the G1 - G4 phase was higher than that in the G0 phase: (5.91 ± 1.52)%, (9.65 ± 2.48)%, (15.03 ± 4.86)%, (24.62 ± 7.22)% vs. (0.79 ± 0.41)%, there were statistical differences ( P<0.05). The results of Pearson test showed that there was a positive correlation between liver A20 and BFGF ( r = 0.824, P<0.05). Conclusions:The expressions of A20 and BFGF in liver tissue increase with the aggravation of liver pathological fibrosis and inflammation, which can be used as important indicators to evaluate the severity of liver fibrosis.

ObjectiveTo observe the protective effect and mechanism of Tianhuang formula (THF) against renal injury in hyperuricemia nephropathy (HN) mice through network pharmacology. MethodAll mice were randomly divided into a normal group, a model group, a febuxostat group (5 mg·kg^-1), a low-dose THF group (L-THF, 60 mg·kg^-1), and a high-dose THF group (H-THF, 120 mg·kg^-1). The mice in the normal group were treated with 0.5% sodium carboxymethylcellulose (CMC-Na) by gavage daily. The HN model was induced by oral administration of 500 mg·kg^-1 hypoxanthine and intraperitoneal injection of 200 mg·kg^-1 oteracil potassium in mice except for those in the blank group. The mice in the groups with drug intervention were treated with corresponding drugs by gavage for three weeks. The levels of serum uric acid, creatinine, urea nitrogen, and 24-h albuminuria were measured. The renal injury was observed by hematoxylin-eosin (HE) staining and PAS staining, and renal fibrosis was observed by Sirius red staining. The effects and molecular mechanism of THF in HN mice were analyzed by Western blot, network pharmacology, and molecular docking. ResultBiochemical results indicated that compared with model group, BUN and 24 h urinary protein levels were significantly decreased in L-THF group (P<0.05), SUA and SCr levels were significantly decreased (P<0.01), and SUA, BUN, SCr and 24 h urinary protein levels in H-THF group were significantly decreased (P<0.01). The results of pathological staining showed that the kidney injury and interstitial fibrosis were improved in different doses of THF groups (P<0.05). Western blot results showed that the Nod-like receptor heat protein domain associated protein 3 (NLRP3) inflammatorome, interleukin-1β (IL-1β), fibronectin (FN), uric acid transporter 1 (URAT1), phosphorylated p65 (p-p65) and phosphorylated nuclear transcription factor (NF) -κB were inhibited in the H-THF group The expression of protein-producing α (p-IκBα) was reduced to the normal level (P<0.01), but the expression of IL-1β, URAT1 and p-IκBα in HN mice was not affected in the L-THF group. ConclusionTHF ameliorates renal inflammation and fibrosis by inhibiting the activation of NF-κB and NLRP3 inflammasomes to alleviate HN