Objective: To investigate the prevalence of hepatitis B and hepatitis C in Hotan Prefecture, Xinjiang Uygur Autonomous Region, so as to provide insights into prevention and intervention strategies for viral hepatitis for these populations. Methods: Data on hepatitis B and hepatitis C cases in Hotan Prefecture from 2016 to 2022 were collected through the Chinese Disease Prevention and Control Information System. The temporal, demographic and regional distribution characteristics of hepatitis B and hepatitis C incidence were analyzed using the descriptively epidemiological method. The trends in the incidence of hepatitis B and hepatitis C from 2016 to 2022 were analyzed using average annual percent change (AAPC). Results: A total of 8 910 hepatitis B cases and 4 106 hepatitis C cases were reported in Hotan Prefecture from 2016 to 2022, with average annual incidences of 55.60/105 and 25.61/105, respectively. The average annual incidence of hepatitis B in males was 66.78/105, which was higher than that in females (43.83/105, P<0.05). The average annual incidence of hepatitis C in males was 25.70/105, while in females it was 25.36/105, with no statistically significant difference (P>0.05). With increasing age, the incidence of hepatitis B showed an "M"-shaped trend, with the highest average annual incidence in the age group of 20-<30 years (97.20/105); the incidence of hepatitis C first increased and then decreased, with the highest average annual incidence in the age group of 70-<80 years (102.50/105). The majority of the cases were farmers/migrant workers, with 5 610 (62.96%) and 2 963 cases (72.16%), respectively. The top three counties with higher average annual incidences of hepatitis B were Minfeng County (84.78/105), Karakax County (81.69/105) and Lop County (72.20/105), and the top three counties with higher average annual incidences of hepatitis C were Pishan County (46.92/105), Karakax County (35.62/105) and Hotan County (26.31/105). The incidences of hepatitis B and hepatitis C in Hotan Prefecture showed downward trends from 2016 to 2022 (AAPC=-10.711% and -16.594%, both P<0.05), with consistent trends observed in Hotan City, Hotan County, Pishan County and Qira County (all P<0.05). Conclusions From 2016 to 2022, the incidences of hepatitis B and hepatitis C in Hotan Prefecture both showed downward trends. Young and middle-aged adults, males, and farmers/migrant workers were the high-risk populations for hepatitis B, while middle-aged and elderly adults and farmers/migrant workers were the high-risk populations for hepatitis C.

Guided by the concept of quality by design(QbD), this study optimizes the calcination and quenching process of calcined Magnetitum and establishes the XRD characteristic spectra of calcined Magnetitum, providing a scientific basis for the formulation of quality standards. Based on the processing methods and quality requirements of Magnetitum in the Chinese Pharmacopoeia, the critical process parameters(CPPs) identified were calcination temperature, calcination time, particle size, laying thickness, and the number of vinegar quenching cycles. The critical quality attributes(CQAs) included Fe mass fraction, Fe~(2+) dissolution, and surface color. The weight coefficients were determined by combining Analytic Hierarchy Process(AHP) and the criteria importance though intercrieria correlation(CRITIC) method, and the calcination process was optimized using orthogonal experimentation. Surface color was selected as a CQA, and based on the principle of color value, the surface color of calcined Magnetitum was objectively quantified. The vinegar quenching process was then optimized to determine the best processing conditions. X-ray diffraction(XRD) was used to establish the characteristic spectra of calcined Magnetitum, and methods such as similarity evaluation, cluster analysis, and orthogonal partial least squares-discriminant analysis(OPLS-DA) were used to evaluate the quality of the spectra. The optimized calcined Magnetitum preparation process was found to be calcination at 750 ℃ for 1 h, with a laying thickness of 4 cm, a particle size of 0.4-0.8 cm, and one vinegar quenching cycle(Magnetitum-vinegar ratio 10∶3), which was stable and feasible. The XRD characteristic spectra analysis method, featuring 9 common peaks as fingerprint information, was established. The average correlation coefficient ranged from 0.839 5-0.988 1, and the average angle cosine ranged from 0.914 4 to 0.995 6, indicating good similarity. Cluster analysis results showed that Magnetitum and calcined Magnetitum could be grouped together, with similar compositions. OPLS-DA discriminant analysis identified three key characteristic peaks, with Fe_2O_3 being the distinguishing component between the two. The final optimized processing method is stable and feasible, and the XRD characteristic spectra of calcined Magnetitum was initially established, providing a reference for subsequent quality control and the formulation of quality standards for calcined Magnetitum.
X-Ray Diffraction/methods* ; Drugs, Chinese Herbal/chemistry* ; Quality Control ; Particle Size

The therapeutic effects of Yueju Pills on depression and cardiovascular diseases have been widely recognized. Previous studies have shown that the drug can significantly improve depressive-like behaviors induced by chronic unpredictable mild stress(CUMS) combined with atherosclerosis(AS). Given the complex pathogenesis of psychocardiac diseases, this study integrated metabolomics and network pharmacology to systematically elucidate the mechanism of Yueju Pills in alleviating depressive symptoms in psychocardiac diseases. The results demonstrate that, after Yueju Pill intervention, the levels of 9 abnormal metabolites in the hippocampus restore to normal ranges, primarily involving key pathways or signaling pathways, including the cyclic adenosine monophosphate(cAMP), mammalian target of rapamycin(mTOR), glycine/serine/threonine metabolism, and aminoacyl-tRNA biosynthesis. In a high-fat diet-induced CUMS ApoE~(-/-) mouse model, Yueju Pills significantly increases adenosine monophosphate(AMP) levels and decreases L-alanine and D-glyceric acid levels in the hippocampus. In conclusion, Yueju Pills exert antidepressant effects by regulating multiple metabolic axes, including glycine/serine/threonine metabolism and the cAMP, mTOR signaling pathways. Network pharmacology predictions reveal that the treatment of CUMS combined with AS by its core active components may be realized through modulating pathways concerning neuroinflammation and synaptic plasticity, including serine/threonine-protein kinase 1(AKT1), mitogen-activated protein kinase 1(MAPK1), and prostaglandin-endoperoxide synthase 2(PTGS2). This study provides a theoretical reference for the clinical application of Yueju Pills in alleviating the depressive symptoms of psychocardiac diseases.
Animals ; Network Pharmacology ; Mice ; Drugs, Chinese Herbal/administration & dosage* ; Metabolomics ; Male ; Depression/genetics* ; Humans ; Hippocampus/drug effects* ; Mice, Inbred C57BL ; Signal Transduction/drug effects*

OBJECTIVE: To investigate the relationship between physical activity and genetic risk and their combined effects on the risk of developing chronic obstructive pulmonary disease. METHODS: This prospective cohort study included 318,085 biobank participants from the UK. Physical activity was assessed using the short form of the International Physical Activity Questionnaire. The participants were stratified into low-, intermediate-, and high-genetic-risk groups based on their polygenic risk scores. Multivariate Cox regression models and multiplicative interaction analyses were used. RESULTS: During a median follow-up period of 13 years, 9,209 participants were diagnosed with chronic obstructive pulmonary disease. For low genetic risk, compared to low physical activity, the hazard ratios ( HRs) for moderate and high physical activity were 0.853 (95% confidence interval [ CI]: 0.748-0.972) and 0.831 (95% CI: 0.727-0.950), respectively. For intermediate genetic risk, the HRs were 0.829 (95% CI: 0.758-0.905) and 0.835 (95% CI: 0.764-0.914), respectively. For participants with high genetic risk, the HRs were 0.809 (95% CI: 0.746-0.877) and 0.818 (95% CI: 0.754-0.888), respectively. A significant interaction was observed between genetic risk and physical activity. CONCLUSION Moderate or high levels of physical activity were associated with a lower risk of developing chronic obstructive pulmonary disease across all genetic risk groups, highlighting the need to tailor activity interventions for genetically susceptible individuals.
Humans ; Pulmonary Disease, Chronic Obstructive/epidemiology* ; Exercise ; Male ; Female ; Middle Aged ; Prospective Studies ; Aged ; Genetic Predisposition to Disease ; Risk Factors ; United Kingdom/epidemiology* ; Incidence ; Adult

ObjectiveThe purpose of this study was to investigate the effects of transcutaneous electrical acupoint stimulation (TEAS) on cognitive function of vascular dementia (VD) rats and its mechanism. MethodsVD rat model was established by modified two-vessel occlusion (2-VO). After modeling, TEAS and electroacupuncture (EA) were used to stimulate Baihui and Zusanli points of rats respectively for 14 d. After treatment, novel object recognition test, Morris water maze test, and Y maze test were used to evaluate the spatial memory and learning ability of rats. Hematoxylin and eosin staining was used to observe the morphology of hippocampal neurons. Transmission electron microscopy was used to observe the ultrastructure of hippocampal mitochondria. Enzyme-linked immunosorbent assay kits were used to detected the levels of SOD, CAT, GSH-Px, MDA and ROS in serum of rats. Western blot was used to detect the expression of PGC-1α, TFAM, HO-1, NQO1 proteins in the hippocampus, Keap1 protein in the cytoplasm and Nrf2, NRF1 proteins in the nucleus. ResultsAfter treatment for 14 d, compared to the model group, the escape latency of VD rats decreased, while the discrimination index, the times of rats crossing the original platform area, the residence time in the original platform quadrant, and the percentage of alternation increased. TEAS can improve the structure of hippocampal neurons and mitochondria of VD rats, showing that neurons were arranged more regularly and distributed more evenly, nuclear membrane and nucleoli were clearer, and mitochondrial swelling were reduced, mitochondrial matrix density were increased, and mitochondrial cristae were more obvious. The levels of SOD, GSH-Px and CAT in serum increased significantly, while the concentration of MDA and ROS decreased. TEAS also up-regulated the expression levels of PGC-1α TFAM, NQO1 and HO-1 proteins in the hippocampus and Nrf2, NRF1 proteins in the nucleus, but down-regulated the Keap1 protein in the cytoplasm. ConclusionTEAS can improve cognition, hippocampal neurons and mitochondrial structure of VD rats, and the effect is better than EA. The mechanism may be the activation of PGC-1α mediated mitochondrial biogenesis and antioxidant stress, which also provides a potential therapeutic technology and experimental basis for the treatment of VD.

Objective To observe the clinical efficacy of Shuangye San(the prescription mainly composed of Mori Folium and Nelumbinis Folium)in the treatment of type 2 diabetes mellitus(T2DM)complicated with non-alcoholic fatty liver disease(NAFLD)of spleen deficiency and phlegm stasis type.Methods A total of 80 patients with T2DM complicated with NAFLD of spleen deficiency and phlegm stasis type were randomly divided into a treatment group and a control group,with 40 cases in each group.The control group was treated with conventional western medicine for lowering blood glucose and lipid,protecting liver and lowering enzymes.The treatment group was treated with the granules of Shuangye San orally on the basis of treatment for the control group.The course of treatment lasted for three months.The changes of traditional Chinese medicine(TCM)syndrome scores,homeostasis model assessment of insulin resistance(HOMA-IR),fasting insulin(FINS),fasting blood glucose(FBG),2-hour postprandial blood glucose(2hPG),glycosylated hemoglobin(HbA1C),total cholesterol(TC),triglyceride(TG),low-density lipoprotein cholesterol(LDL-C),high-density lipoprotein cholesterol(HDL-C),liver function indicators and B-ultrasound grading of fatty liver in the two groups were observed before and after treatment.After treatment,the clinical efficacy and safety of the two groups were evaluated.Results(1)After three months of treatment,the total effective rate of the treatment group was 85.00％(34/40),and that of the control group was 70.00％(28/40).The intergroup comparison(tested by chi-square test)showed that the efficacy of the treatment group was significantly superior to that of the control group(P＜0.01).(2)After treatment,the scores of TCM symptoms of obese physique,heaviness and weakness in the limbs,shortness of breath and unwilling to talk,tightness and stabbing pain in the chest,abdominal distension and poor appetite in the two groups were decreased compared with those before treatment(P＜0.05),and the decrease of TCM syndrome scores in the treatment group was significantly superior to that in the control group(P＜0.05).(3)After treatment,the levels of glucose and lipid metabolism indicators of FINS,HOMA-IR,FBG,2hPG,HbA1C,TC,TG and LDL-C in the two groups were significantly decreased compared with those before treatment(P＜0.05),and the level of HDL-C was significantly increased compared with that before treatment(P＜0.05).The decrease of FINS,HOMA-IR,FBG,2hPG,HbA1C,TC,TG and LDL-C levels and the increase of HDL-C levels in the treatment group were significantly superior to those in the control group(P＜0.05).(4)After treatment,the levels of liver function indicators of alanine aminotransferase(ALT),aspartate aminotransferase(AST)and gamma-glutamyl transpeptidase(GGT)in the two groups were significantly decreased compared with those before treatment(P＜0.05),and the decrease of liver function indicators in the treatment group was significantly superior to that in the control group(P＜0.05).(5)After treatment,the B-ultrasound grading of fatty liver of the two groups was significantly improved compared with that before treatment(P＜0.05),and the improvement of fatty liver B-ultrasound grading in the treatment group was significantly superior to that in the control group,and the difference was statistically significant(P＜0.05).(6)During the treatment,there were no adverse reactions such as impairment of liver and kidney function and abnormalities in routine blood,urine and stool test in the two groups.Conclusion Shuangye San exerts certain effect in the treatment of T2DM complicated with NAFLD of spleen deficiency and phlegm stasis type.It can alleviate the clinical symptoms of patients,correct the disorder of glucose and lipid metabolism,and improve liver function and fatty liver B-ultrasound grading.

Purpose::Cerebral edema (CE) is the main secondary injury following traumatic brain injury (TBI) caused by road traffic accidents (RTAs). It is challenging to be predicted timely. In this study, we aimed to develop a prediction model for CE by identifying its risk factors and comparing the timing of edema occurrence in TBI patients with varying levels of injuries.Methods::This case-control study included 218 patients with TBI caused by RTAs. The cohort was divided into CE and non-CE groups, according to CT results within 7 days. Demographic data, imaging data, and clinical data were collected and analyzed. Quantitative variables that follow normal distribution were presented as mean ± standard deviation, those that do not follow normal distribution were presented as median (Q 1, Q 3). Categorical variables were expressed as percentages. The Chi-square test and logistic regression analysis were used to identify risk factors for CE. Logistic curve fitting was performed to predict the time to secondary CE in TBI patients with different levels of injuries. The efficacy of the model was evaluated using the receiver operator characteristic curve. Results::According to the study, almost half (47.3%) of the patients were found to have CE. The risk factors associated with CE were bilateral frontal lobe contusion, unilateral frontal lobe contusion, cerebral contusion, subarachnoid hemorrhage, and abbreviated injury scale (AIS). The odds ratio values for these factors were 7.27 (95% confidence interval ( CI): 2.08 -25.42, p = 0.002), 2.85 (95% CI: 1.11 -7.31, p = 0.030), 2.62 (95% CI: 1.12 -6.13, p = 0.027), 2.44 (95% CI: 1.25 -4.76, p = 0.009), and 1.5 (95% CI: 1.10 -2.04, p = 0.009), respectively. We also observed that patients with mild/moderate TBI (AIS ≤ 3) had a 50% probability of developing CE 19.7 h after injury (χ 2= 13.82, adjusted R2 = 0.51), while patients with severe TBI (AIS > 3) developed CE after 12.5 h (χ 2= 18.48, adjusted R2 = 0.54). Finally, we conducted a receiver operator characteristic curve analysis of CE time, which showed an area under the curve of 0.744 and 0.672 for severe and mild/moderate TBI, respectively. Conclusion::Our study found that the onset of CE in individuals with TBI resulting from RTAs was correlated with the severity of the injury. Specifically, those with more severe injuries experienced an earlier onset of CE. These findings suggest that there is a critical time window for clinical intervention in cases of CE secondary to TBI.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.