Post-traumatic stress disorder (PTSD) is a relatively common but complex mental illness with a range of diverse risk factors. Typical symptoms include the re-experience or avoidance of traumatic events, cognitive impairment, and hypervigilance. While the exact pathogenesis of PTSD is unclear, many studies indicate that epigenetic regulation plays a key role in its development. Specifically, numerous studies have indicated that the levels of histone acetylation and methylation, DNA methylation, and noncoding RNA are altered in PTSD patients. Further to this, natural products have been found to achieve epigenetic regulation of PTSD by regulating the expression of epigenetic enzymes, long noncoding RNA (lncRNA), and miRNA, thereby playing a role in improving PTSD symptoms. To date, however, no epigenetic regulation related drugs have been used in the treatment of PTSD. Furthermore, while natural products that can epigenetically regulate PTSD have received increasing levels of attention, there have not yet been any systematic reports on the topic. Here, we summarized the roles and mechanisms of natural products in the epigenetic regulation of PTSD, providing a novel and unique perspective that will help to guide the development and application of new PTSD treatments.

Objective:To develop and validate a machine learning (ML) noninvasive model based on routine laboratory parameters to preoperatively predict the microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC).Methods:A total of 629 HCC patients who underwent hepatectomy at the First Affiliated Hospital of Fujian Medical University between January 2019 and December 2023 were retrospectively enrolled in this study and were divided chronologically into a training set ( n=464) and internal validation set ( n=165). A cohort with 190 HCC patients from Fujian Provincial Hospital were used as an external validation set. Preoperatively demographic features, tumor size and routine laboratory data were collected. All patients were divided into MVI-positive or MVI-negative group. The Boruta algorithm and LASSO regression algorithm were used to screen out related features in the training set. Eight different ML algorithms including multivariate logistic regression, decision tree (DT), random forest (RF), extreme gradient boosting (XGboost), k-nearest neighbor (KNN), support vector machine (SVM), light gradient boosting machine (LGBM) and Naive Bayes were used to construct the prediction models. The predictive performances of these models on training and internal validation sets were evaluated by the receiver operating characteristic (ROC) curve with the area under the curve (AUC). The ML model with the highest AUC values was defined as the optimal model and its performance was further validated in the external validation set. The calibration curve showed that the probability value curve was close to the actual occurrence probability curve, and the DCA showed that it could be applied within the threshold probability range of 0.3-0.8 to obtain net benefits. Results:After screening, eight parameters including α-fetoprotein (AFP), protein induced by vitamin K absence Ⅱ (PIVKA-Ⅱ), tumor size, eosinophil count, neutrophil count, creatinine, ApoA1 and total bilirubin were finally selected for the construction of the preoperative prediction model for MVI in HCC. Among all the tested eight ML algorithms, XGboost obtained the optimal performance with an AUC of 0.820 in training set, an AUC of 0.803 in internal testing set and an AUC of 0.758 in external testing set. Further stratified analysis showed that the AUC for preoperatively predicting MVI by XGboost was 0.817 for HCC patients with positive hepatitis B surface antigen, 0.779 for male patients and 0.790 for elder patients. The calibration curves showed good agreement between observed and predicted values and the decision curve analysis curve showed relatively higher net benefits.Conclusions:We successfully established and verified a novel XGboost model based on eight routine laboratory parameters with relatively high and reliable predictive accuracy to preoperatively predict MVI in HCC.

Objective:To investigate the distribution of health needs and healthcare workforce demands among potential service users in community health service institurions (CHSIs) and establish a comprehensive health needs profile for targeted service development.Methods:This is a cross-sectional study. A questionnaire survey (55 items for adults and 39 items for minors) was conducted among 564 residents aged 3-65 in Dapuqiao Subdistrict, Shanghai from March to May 2024. A health sketch model was developed, encompassing five dimensions (intake, basal metabolism, consumption, influencing factors, and somatosensory perception). Health issues were mapped to standardized healthcare services, and annual standardized workloads (SW) were calculated to quantify human resource demands. Results:Among 534 valid responses (94.68% response rate), 355 from the adults and 179 from minors, the top health issues for adults were irregular diet, nutritional imbalance, obesity, somatic fatigue, and disordered eating; for minors, they were nutritional imbalance, medication overuse, insufficient physical activity, picky eating, and anorexia. The total annual SW required to address these needs was 3 906 807.93. Among them, the total SW for each age group was as follows: the total annual SW demand for children aged between 3 and 5 years old was 24 108.90, for children aged between 6 and 11 years old was 141 355.70, for adolescents aged between 12 and 17 years old was 29 813.74, 223 475.50 for 18-24 year olds, 476 426.53 for 25-34 year olds, 1 221 105.84 for 35-44 year olds, 812 200.22 for 45-54 year olds; and 978 321.50 for 55-65 year olds. Workforce allocation analysis revealed a total demand for 139.84 standardized personnel, with rehabilitation therapists (38.16), general practitioners (35.69), and nurses (27.34) being the top three required roles.Conclusions:Health needs and workforce demands vary significantly across age groups. This study provides a data-driven framework for optimizing community health services through stratified health needs profiling and precision resource allocation. Future strategies should prioritize tailored interventions and workforce planning to bridge service gaps and enhance health outcomes.

Objective:To investigate the descrepancy between current supply and demand based on standardiized workload for rational human resource allocation in community health service centers.Methods:A retrospective study was conducted in Dapuqiao Community Health Service Center of Shanghai Huangpu District from January 1st to December 3lst 2023. The current status of demand and supply were analyzed using the 2023 data of the institution. The standardised workload was measured according to the potential basic medical and public health service needs based on the disease profile and population groups in the community. The discrepancy between the current supply and theoretical demand was analyzed.Results:A total of 36 634 patients paid 277 262 visits in outpatient clinics of Dapuqiao Community Health Service Center in 2023. There are total 161 employees in the center, 124 of whom are female (77.02%). The actual calibrated workload of basic medical care and public health service in the center calculated on fee-based medical service items in 2023 was 2 888 425.61 and 455 898.35, respectively; while the theoretically calibrated workload was 5 416 492.42 and 711 230.94, respectively. The center employed 131 medical and health workers currently, calibrated as 90.67 employees based on current demand, while it should be 183.74 calibrated on the theoretical demand, there was a certain discrepancy between the current staffing and the standard staffing based on the standardized workload calculation.Conclusion:At present, the actual standardized workload of basic medical and public health services in Dapuqiao Community Health Service Center still has room for improvement, but there is a certain gap between the current human resource allocation and the demand.

ObjectiveTo study the mechanism of Huanglian Jiedutang （HLJDT） in treating mice with atherosclerosis （AS） by improving ferroptosis. MethodsA total of 10 SPF C57BL/6J mice were selected as a normal group， and 50 ApoE^-/- mice were randomly divided into five groups： model group， low-dose group of HLJDT， medium-dose group of HLJDT， high-dose group of HLJDT， and atorvastatin （ATV） group. ApoE^-/- mice were fed a high-fat diet for eight weeks to establish the AS model， and at the 9th week， they were given normal saline， low， medium， and high doses of HLJDT （3.9， 7.8， 15.6 g·kg^-1·d^-1）， and atorvastatin calcium tablets （0.01 g·kg^-1·d^-1）， respectively， for a total of eight weeks. The formation of aortic plaque in mice was observed by gross oil red O staining and Masson staining. The levels of total cholesterol （TC）， low-density lipoprotein cholesterol （LDL-C）， triglyceride （TG）， and high-density lipoprotein cholesterol （HDL-C） in blood fat were measured by the automatic biochemical analyzer， and the mitochondrial structure of the aorta was observed by transmission electron microscopy. The content of serum superoxide dismutase （SOD） in serum was detected by enzyme-linked immunosorbent assay （ELISA）. The content of reduced glutathione （GSH） in serum was detected by the microplate method， and that of malondialdehyde （MDA） in serum was detected by the TBA method. The protein expression of nuclear factor E₂-associated factor 2 （Nrf2）/glutathione peroxidase 4 （GPX4） signaling pathway was detected by Western blot. ResultsCompared with those of the normal group， the contents of TC， LDL-C， TG， HDL-C， and MDA in the serum and the aortic vascular plaque deposition of the model group were significantly increased （P<0.01）， while the expression levels of SOD and GSH in serum， as well as Nrf2， solute carrier family 7 member 11 （SLC7A11）， and GPX4 in aorta were significantly decreased （P<0.01）. Mice in the model group appeared mitochondrial fragmentation and vacuolation in the aorta， volume atrophy， mitochondrial crista reduction， or a loose and disorganized form. Compared with those in the model group， the aortic vascular plaque deposition was significantly decreased in the low-dose， medium-dose， and high-dose groups of HLJDT and ATV group， and the contents of serum TC， LDL-C， TG， and MDA in serum were significantly decreased （P<0.05， P<0.01）. The contents of serum SOD and GSH and the expression levels of Nrf2， SLC7A11， and GPX4 in the aorta were increased （P<0.05， P<0.01）， and the symptoms of aortic mitochondrial vacuolation were alleviated. The number of cristae was increased， and they were ordered neatly. ConclusionHLJDT can reduce aortic vascular plaque deposition， decrease blood lipid and MDA expression， increase SOD and GSH expression， and ameliorate the pathological changes of ferroptosis， the mechanism of which is related to the Nrf2/GPX4 signaling pathway.

Objective:To investigate the distribution of health needs and healthcare workforce demands among potential service users in community health service institurions (CHSIs) and establish a comprehensive health needs profile for targeted service development.Methods:This is a cross-sectional study. A questionnaire survey (55 items for adults and 39 items for minors) was conducted among 564 residents aged 3-65 in Dapuqiao Subdistrict, Shanghai from March to May 2024. A health sketch model was developed, encompassing five dimensions (intake, basal metabolism, consumption, influencing factors, and somatosensory perception). Health issues were mapped to standardized healthcare services, and annual standardized workloads (SW) were calculated to quantify human resource demands. Results:Among 534 valid responses (94.68% response rate), 355 from the adults and 179 from minors, the top health issues for adults were irregular diet, nutritional imbalance, obesity, somatic fatigue, and disordered eating; for minors, they were nutritional imbalance, medication overuse, insufficient physical activity, picky eating, and anorexia. The total annual SW required to address these needs was 3 906 807.93. Among them, the total SW for each age group was as follows: the total annual SW demand for children aged between 3 and 5 years old was 24 108.90, for children aged between 6 and 11 years old was 141 355.70, for adolescents aged between 12 and 17 years old was 29 813.74, 223 475.50 for 18-24 year olds, 476 426.53 for 25-34 year olds, 1 221 105.84 for 35-44 year olds, 812 200.22 for 45-54 year olds; and 978 321.50 for 55-65 year olds. Workforce allocation analysis revealed a total demand for 139.84 standardized personnel, with rehabilitation therapists (38.16), general practitioners (35.69), and nurses (27.34) being the top three required roles.Conclusions:Health needs and workforce demands vary significantly across age groups. This study provides a data-driven framework for optimizing community health services through stratified health needs profiling and precision resource allocation. Future strategies should prioritize tailored interventions and workforce planning to bridge service gaps and enhance health outcomes.

Objective:To investigate the descrepancy between current supply and demand based on standardiized workload for rational human resource allocation in community health service centers.Methods:A retrospective study was conducted in Dapuqiao Community Health Service Center of Shanghai Huangpu District from January 1st to December 3lst 2023. The current status of demand and supply were analyzed using the 2023 data of the institution. The standardised workload was measured according to the potential basic medical and public health service needs based on the disease profile and population groups in the community. The discrepancy between the current supply and theoretical demand was analyzed.Results:A total of 36 634 patients paid 277 262 visits in outpatient clinics of Dapuqiao Community Health Service Center in 2023. There are total 161 employees in the center, 124 of whom are female (77.02%). The actual calibrated workload of basic medical care and public health service in the center calculated on fee-based medical service items in 2023 was 2 888 425.61 and 455 898.35, respectively; while the theoretically calibrated workload was 5 416 492.42 and 711 230.94, respectively. The center employed 131 medical and health workers currently, calibrated as 90.67 employees based on current demand, while it should be 183.74 calibrated on the theoretical demand, there was a certain discrepancy between the current staffing and the standard staffing based on the standardized workload calculation.Conclusion:At present, the actual standardized workload of basic medical and public health services in Dapuqiao Community Health Service Center still has room for improvement, but there is a certain gap between the current human resource allocation and the demand.

Objective:To develop and validate a machine learning (ML) noninvasive model based on routine laboratory parameters to preoperatively predict the microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC).Methods:A total of 629 HCC patients who underwent hepatectomy at the First Affiliated Hospital of Fujian Medical University between January 2019 and December 2023 were retrospectively enrolled in this study and were divided chronologically into a training set ( n=464) and internal validation set ( n=165). A cohort with 190 HCC patients from Fujian Provincial Hospital were used as an external validation set. Preoperatively demographic features, tumor size and routine laboratory data were collected. All patients were divided into MVI-positive or MVI-negative group. The Boruta algorithm and LASSO regression algorithm were used to screen out related features in the training set. Eight different ML algorithms including multivariate logistic regression, decision tree (DT), random forest (RF), extreme gradient boosting (XGboost), k-nearest neighbor (KNN), support vector machine (SVM), light gradient boosting machine (LGBM) and Naive Bayes were used to construct the prediction models. The predictive performances of these models on training and internal validation sets were evaluated by the receiver operating characteristic (ROC) curve with the area under the curve (AUC). The ML model with the highest AUC values was defined as the optimal model and its performance was further validated in the external validation set. The calibration curve showed that the probability value curve was close to the actual occurrence probability curve, and the DCA showed that it could be applied within the threshold probability range of 0.3-0.8 to obtain net benefits. Results:After screening, eight parameters including α-fetoprotein (AFP), protein induced by vitamin K absence Ⅱ (PIVKA-Ⅱ), tumor size, eosinophil count, neutrophil count, creatinine, ApoA1 and total bilirubin were finally selected for the construction of the preoperative prediction model for MVI in HCC. Among all the tested eight ML algorithms, XGboost obtained the optimal performance with an AUC of 0.820 in training set, an AUC of 0.803 in internal testing set and an AUC of 0.758 in external testing set. Further stratified analysis showed that the AUC for preoperatively predicting MVI by XGboost was 0.817 for HCC patients with positive hepatitis B surface antigen, 0.779 for male patients and 0.790 for elder patients. The calibration curves showed good agreement between observed and predicted values and the decision curve analysis curve showed relatively higher net benefits.Conclusions:We successfully established and verified a novel XGboost model based on eight routine laboratory parameters with relatively high and reliable predictive accuracy to preoperatively predict MVI in HCC.

Objective:To investigate the incidence and prothrombotic risk factors of postoperative venous thromboembolism(VTE) in Cushing′s disease and to further develop an assessment model to identify those at high risk of postoperative VTE events.Methods:A retrospective study was performed in 82 patients who were admitted to Huashan Hospital, Fudan University during January 2019 and January 2020 and diagnosed with Cushing′s disease. These patients underwent the evaluation about their clinical, hormonal, and coagulation parameters, as well as ultrasonography and pulmonary angio-CT when necessary. The least absolute shrinkage and selection operator(LASSO) regression analysis was used to screen independent risk factors, and a nomogram model for postsurgical VTE risk assessment in Cushing′s disease was initially established, and Bootstrap method was used for internal verification. Finally, the predictive model was evaluated for calibration and clinical applicability in the study cohort.Results:Nineteen patients(23.17%) developed VTE events, with 14 cases occurring after endoscopic transsphenoidal surgery. Compared to patients without VTE, those in the VTE group were older( P<0.001), had longer postoperative bed rest, higher rates of current infection, higher HbA 1C levels, and more severe glucose tolerance impairment(all P<0.05). Through LASSO regression analysis, two independent risk factors for postoperative VTE were identified: Age and current infection. Then a VTE risk assessment nomogram model was established to predict the patients at high risk of VTE. In the nomogram model for VTE risk assessment, the area under the receiver operating characteristic curve was 0.868(95% CI 0.787-0.949), with the calibration curve closely aligning with the ideal diagonal line and the clinical decision curve exceeding the two extreme curves. Conclusions:Advanced perioperative assessment needs to be taken to screen those with high VTE risks in patients diagnosed with Cushing′s disease. Additionally, during the perioperative period, patients with Cushing′s disease should undergo mandatory physical activity or prophylactic anticoagulant therapy.

We present a case of nephrogenic diabetes insipidus secondary to primary Sj?gren′s syndrome. At onset, the patient exhibited a urine output of up to 10 liter per day. Diagnostic evaluation and clinical features confirmed renal diabetes insipidus due to primary Sj?gren′s syndrome. A review of the literature indicates that primary Sj?gren′s syndrome can involve renal manifestations, including renal tubulointerstitial inflammation and impaired renal concentration ability. However, nephrogenic diabetes insipidus with such high urine output is uncommon. Management of this condition requires proactive control of the underlying disease, potassium supplementation, and urine management.