Parkinson's disease （PD） is a chronic progressive neurodegenerative disorder primarily characterized by motor dysfunction. The main pathological features include the loss of dopaminergic neurons in the substantia nigra， abnormal aggregation of alpha-Synuclein （α-Syn）， and the formation of Lewy bodies. However， the exact mechanisms remain unclear. In recent years， the PD incidence has gradually increased， while current treatment methods are limited to symptom alleviation， incapable of halting disease progression， and prone to adverse effects， thus making it urgent to search for medicines effective for PD. Modern research indicates that the Kelch-like ECH-associated protein 1 （Keap1）/nuclear factor E₂ related factor 2 （Nrf2）/antioxidant response element （ARE） signaling pathway is closely related to oxidative stress， neuroinflammation， apoptosis， ferroptosis， and mitochondrial dysfunction， playing a crucial role in the pathophysiological development of PD. A large number of studies have further confirmed that traditional Chinese medicine （TCM） can regulate diseases through a holistic view of Syndrome differentiation and microscopic molecular pathways. With unique advantages， such as multiple targets， multiple pathways， and fewer adverse reactions， TCM provides a new strategy for PD treatment. This article elucidates the mechanism of the Keap1/Nrf2/ARE signaling pathway in the occurrence and development of PD， while summarizing the latest research on PD intervention by TCM monomers， active ingredients， and compounds， as well as acupuncture via the precise targeted regulation of the Keap1/Nrf2/ARE pathway， aiming to provide a reference for clinical medicine development to prevent and treat PD.

OBJECTIVE To systematically compare mature experiences of comprehensive drug value assessment in typical countries/regions and to provide decision-making references for China to establish a scientific and standardized comprehensive drug value assessment system for medical-insured drugs. METHODS The literature analysis was used to systematically review drug value assessment frameworks in 11 representative countries/regions， namely the UK， Canada， Italy， Australia， Germany， France， South Korea， Japan， the United States， as well as Taiwan （China） and Hong Kong （China）. Comparisons were made across three dimensions： assessment entities， value dimension， and application of results. RESULTS &CONCLUSIONS In most countries/regions， independent technical assessment institutions have been established as part of the drug value evaluation system， with the involvement of multiple stakeholders （e.g.， the UK， Canada）. The mainstream drug value assessment frameworks have generally transcended the traditional core dimensions of safety， efficacy， and cost-effectiveness， exhibiting two major trends： the continuous expansion of assessment dimensions and stricter evidence requirements. Assessment outcomes are closely integrated with payment policies， ranging from providing technical advice for decision-making （e.g.， Italy， France） to directly determining reimbursement eligibility （e.g.， the UK， Germany）. The following recommendations are proposed for China： first， establish an evaluation mechanism featuring multi-stakeholder participation and separation of evaluation from decision-making. Second， develop a comprehensive evaluation framework integrating clinical， economic， patient， and societal value， emphasizing quantitative indicator exploration and real-world evidence application. Third， promote direct linkage between value-based tiering outcomes and medical insurance reimbursement decisions or access negotiations to balance patient benefits， fund sustainability， and industrial innovation.

ObjectiveTo analyze the epidemiological characteristics of 8 major respiratory pathogens in influenza-like illness (ILI) cases with acute respiratory infections at fever clinics in Huangpu District, Shanghai from 2015 to 2024, and to provide a scientific basis for the prevention and treatment of respiratory diseases. MethodsA retrospective study was conducted in Huangpu District. Individuals meeting the case definition of ILI from 2015 to 2024 was registered. Their nasopharyngeal swabs were collected for pathogen detection. A total of 8 respiratory viruses were tested, including Influenza A virus (Flu A), Influenza B virus (Flu B), adenovirus (ADV), enterovirus/human rhinovirus (EV/HRV), human parainfluenza virus (HPIV), human coronavirus (HCoV), respiratory syncytial virus (RSV), and human metapneumovirus (HMPV). ResultsFrom 2015 to 2019, a total of 344 ILI cases were tested, of which 192 out of 344 cases (55.81%) were tested positive for single respiratory pathogen. From 2023 to 2024, 1 557 ILI cases were tested, with 572 out of 1 557 cases (36.74%) being positive for single pathogen. From 2023 to 2024, the positive rate of single pathogen in ILI cases was significantly lower than that in 2015‒2019 (χ²=42.66, P<0.001). Specifically, the positive rate of Flu A (χ²=74.43, P<0.001) decreased, while that of HPIV (χ²=8.66, P=0.003) increased, both with statistically significant differences. According to the seasonal pattern, the epidemic intensity of Flu A decreased in summer, while that of HPIV increased in summer and autumn. Demographic results showed statistically significant differences in the positive rates of EV/HRV between genders (χ²=22.38, P<0.001), with males exhibiting a higher positive rate than females. No statistically significant differences were identified in the positive rates of single pathogen among different age groups (χ²=4.42, P=0.110). Nevertheless, statistically significant differences were noted when comparing the positive rates of EV/HRV, Flu A, Flu B and HPIV across different age groups (P<0.05). EV/HRV was more commonly detected in the 15‒<25 age group (10.93%), while Flu A and HPIV had the highest positive rates in the ≥60 age group (21.24% and 4.77%). Flu B had the highest positive rate in the 25‒<60 age group (11.26%). 52.63% of cases with co-infections occurred during winter, with the primary pathogens involved being EV/HRV (9 cases) and HCoV (6 cases). The most prevalent combination of co-infection was Flu A with EV/HRV. ConclusionThe prevalence of respiratory pathogens among ILI cases from 2023 to 2024 exhibited notable fluctuations compared to that from 2015 to 2019. Therefore, influenza surveillance should be strengthened, and attention should also be paid to the prevalence of respiratory pathogens such as HPIV. These findings have profound implications for future research, surveillance, vaccine planning, and public health policy making.

Objective: To analyze the change trends in the body shape indicators and proportions of students in Harbin from 2010 to 2024, and to investigate ergonomic compatibility of functional dimensions of school desks and chairs with current student shape indicators, so as to provide a reference for revising furniture standards of desks and chairs. Methods: Between September and November of both 2010 and 2024, a combination of convenience sampling and stratified cluster random sampling was conducted across three districts in Harbin, yielding samples of 6 590 and 6 252 students, respectively. Anthropometric shape indicators cluding height, sitting height, crus length, and thigh length-and their proportional changes were compared over the 15-year period. The 2024 data were compared with current standard functional dimensions of school furniture. The statistical analysis incorporated t-test and Mann-Whitney U- test. Results: From 2010 to 2024, average height increased by 1.8 cm for boys and 1.5 cm for girls; sitting height increased by 1.5 cm for both genders; crus length increased by 0.3 cm for boys and 0.4 cm for girls; and thigh length increased by 0.5 cm for both genders. The ratios of sitting height to height, and sitting height to leg length increased by less than 0.1 . The difference between desk chair height and 1/3 sitting height ranged from 0.4-0.8 cm. Among students matched with size 0 desks and chairs, 22.0% had a desk to chair height difference less than 0, indicating that the desk to chair height difference might be insufficient for taller students. The differences between seat height and fibular height ranged from -1.4 to 1.1 cm; and the differences between seat depth and buttock popliteal length ranged from -9.8 to 3.4 cm. Among obese students, the differences between seat width and 1/2 hip circumference ranged from -20.5 to -8.7 cm, while it ranged from -12.2 to -3.8 cm among non obese students. Conclusion Current furniture standards basically satisfy hygienic requirements; however, in the case of exceptionally tall and obese students, ergonomic accommodations such as adaptive seating allocation or personalized adjustments are recommended to meet hygienic requirements.

Objective:To investigate the prognostic factors for esophageal cancer after radical resection and the application value of machine learning prediction model.Methods:The retrospective cohort study was conducted. The clinicopatholigical data of 406 esophageal cancer patients who were admitted to Qilu Hospital of Shandong University from January 2018 to March 2022 were collected. There were 357 males and 49 females, aged (64±8)years. All patients underwent radical resection of esophageal cancer. The 406 patients were randomly divided into a training set of 285 cases and a validation set of 121 cases at a 7∶3 ratio based on a random number table. The training set was used to construct prediction model, and the validation set was used to validate prediction model. Patients were divided into high-risk group and low-risk group based on risk scores. Observation indicators: (1) follow-up of patients and analysis of influencing factors for prognosis; (2) construction and validation of machine learning prediction models. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Comparison of ordinal data between groups was conducted using the rank sum test. The Kaplan-Meier method was used to calculate survival rate and plot survival curve, and the Log-rank test was used for survival analysis. The Cox proportional hazard regression model was used for univariate and multivariate analyses. Independent influencing factors were included, and data processing, machine learning model construction, and visualization were performed using R packages including random survival forest (RSF), gradient boosting machine (GBM), least absolute shrinkage and selection operator Cox regression (LASSO-Cox), Cox proportional hazards model boosting (CoxBoost), survival support vector machine (survivalsvm), extreme gradient boosting (XGBoost), supervised principal component analysis (SuperPC), and Cox partial least squares regression (plsRcox). Receiver operating characteristic (ROC) curves were drawn, and sensitivity, specificity, and area under the curve (AUC) were calculated. The Delong test was used to assess the differences in AUC among different models in the training set, and the time-dependent ROC was used to compare the predictive performance of different models. Calibration curves were used to evaluate model accuracy, and decision curve analysis (DCA) was used to evaluate overall net benefit. Results:(1) Follow-up of patients and analysis of influencing factors for prognosis. All 406 patients were followed up postoperatively for 28(range, 6-36)months, with 1- and 3-year overall survival rate of 86.5% and 40.9%, respectively. The 285 patients in the training set were followed up postoperatively for 30(range, 6-36)months, with 1- and 3-year overall survival rate of 85.1% and 35.5%, respectively. The 121 patients in the validation set were followed up postoperatively for 25(range, 6-36)months, with 1- and 3-year overall survival rate of 87.0% and 43.2%, respectively. There was no significant difference in postoperative overall survival rate between the training set and the validation set ( χ2=3.20, P>0.05). Results of multivariate analysis showed that left thoracic surgical approach, preopera-tive neutrophil count, vascular invasion, perineural invasion, pathological T2-4 stage, pathological N2-3 stage, and postoperative pneumonia were independent risk factors affecting postoperative survival of 285 patients in the training set ( hazard ratio=1.466, 1.037, 1.482, 1.549, 5.268, 7.727, 22.202, 2.539, 2.686, 1.425, 95% confidence interval as 1.026-2.096, 1.003-1.073, 1.008-2.179, 1.105-2.170, 1.201-23.099, 1.833-32.576, 4.734-104.128, 1.577-4.087, 1.631-4.422, 1.018-1.994, P<0.05). (2) Construction and validation of machine learning prediction models. Independent risk factors affecting postoperative survival were included to construct RSF, GBM, LASSO-Cox, CoxBoost, survivalsvm, XGBoost, SuperPC, and plsRcox machine learning prediction models. Results of Delong test showed that there were significant differences in the AUC of RSF and GBM from the other six models ( P<0.05). Results of time-dependent ROC curve showed that all 8 machine learning predic-tion models had good discriminative ability in the training cohort, among which the RSF machine learning prediction model had the best predictive performance. Results of calibration curve showed that the RSF machine learning prediction model fitted well for predicting postoperative 1-, 2-, and 3-year overall survival in the training cohort, with high consistency with actual results. Results of decision curve analysis showed that within a threshold range of 0-0.80, the RSF machine learning prediction model provided a better overall net benefit. Further analysis showed that in the validation set, the AUC of RSF machine learning prediction model for postoperative 1-, 2-, and 3-year survival prediction were 0.786 (95% confidence interval as 0.609-0.962), 0.774 (95% confidence interval as 0.676-0.873), and 0.750 (95% confidence interval as 0.652-0.848), respectively. Results of calibration curve showed that the RSF machine learning prediction model fitted well for predicting postopera-tive 1-, 2-, and 3-year overall survival in the validation set, with high consistency with actual results. In the training set, the optimal cutoff value of the RSF machine learning prediction model risk score was 11.7. Patients with risk score ≥11.7 were classified as the high-risk group, and those with risk score <11.7 as the low-risk group. The median survival times of the two groups were 18.0 months and >36.0 months, respectively, showing a significant difference between them ( χ2=73.30, P<0.05). In the validation set, the optimal cutoff value of the RSF machine learning prediction model risk score was 11.7. Patients with risk score ≥11.7 were classified as the high-risk group, and those with risk score<11.7 as the low-risk group. The median survival times of the two groups were 17.0 months and>36.0 months for the high-risk and low-risk groups, respectively, showing a significant difference between them ( χ2=35.20, P<0.05). Conclusions:Left thoracic surgical approach, preoperative neutrophil count, vascular invasion, perineural invasion, pathological T2-4 stage, pathological N2-3 stage, and postoperative pneumonia are independent risk factors affecting survival of esophageal cancer patients after radical resection. The RSF machine learning prediction model constructed based on these factors can effectively distinguish the survival prognosis of high-risk and low-risk patients.

AIM:To evaluate the pharmacokinet-ics(PK)and pharmacodynamics(PD)of two recom-binant human insulin injection by euglycemic clamp technology in healthy male subjects after a single subcutaneous injection.METHODS:We con-ducted a randomized,open-label,single dose,two period,crossover study.A total of 24 healthy male subjects were enrolled and randomized to receive single subcutaneous doses(0.2 U/kg)of the investi-gational products every period.The PK and PD characteristics were assessed by euglycemic clamp up to 14 hours after dosing.RESULTS:Euglycemic clamp technique was successfully established.C-peptide levels detected at each time point before and after administration indicated that endoge-nous insulin secretion was inhibited in the two groups after administration.The geometric mean ratio of Cmax and AUC0-tand 90％confidence interval(CI)of test preparation and reference preparation under fasting condition were in the range of 80.00％-125.00％.CONCLUSION:The human insulin produced by KP Biotech demonstrated similarity to the reference preparation Humulin? in PK and PD characteristics in healthy Chinese subjects.

This study aimed to identify mutations in the human insulin receptor gene (INSR) and investigate their role in the pathogenesis of severe insulin resistance syndrome. Sanger sequencing of the INSR gene was performed on a patient clinically suspected of having type A insulin resistance syndrome admitted to the Department of Endocrinology, the First Medical Center of Chinese PLA General Hospital. Upon identifying mutations, relevant exons were sequenced in her first-degree relatives. Additionally, control groups consisting of individuals with type 2 diabetes and those with normal glucose tolerance were screened for the mutation detected in the patient. Functional predictions of the INSR protein were made using MutationTaster, SIFT, and PolyPhen2 software. A previously unreported heterozygous missense mutation, c.3652G/A (Asp1218Asn), in exon 20 was identified in both the proband and her father. This mutation was not present in any of the control individuals. Multiple prediction tools indicate that this mutation likely disrupts gene/protein structure or function. The c.3652G/A (Asp1218Asn) heterozygous mutation in INSR is a novel variant that plays a significant role in the pathogenesis of severe insulin resistance in this Chinese family.

Objective:To investigate the value of Sequential Organ Failure (SOFA) score and its dynamics (ΔSOFA) in predicting mortality in hematology care unit (HCU) .Methods:A retrospective clinical study was conducted on 79 critically ill hematologic patients admitted to the Center for Critical Care Medicine, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences, between May and June 2024. SOFA scores and ΔSOFA were calculated within 2 days before and after HCU admission. The predictive value of SOFA and ΔSOFA in mortality was assessed using receiver operating characteristic (ROC) curve analysis.Results:Among the 79 patients, the HCU mortality rate was 54.4%. The SOFA scores on days 1–3 (D1, D2, and D3) and ΔSOFA on day 1 (ΔD_1) of all patients, leukemia patients and hematopoietic stem cell transplantation (HSCT) patients were significantly higher in the death group compared with the non-death group (all P<0.05). ROC curve analysis revealed that the D_1, D_2, D_3 scores, and ΔD_1 significantly predicted mortality ( P<0.001), with areas under the curve (AUCs) of 0.786, 0.866, 0.901, and 0.843, respectively. The sensitivity values were 74.36%, 57.89%, 62.85%, and 86.84%, while specificity values were 70%, 100%, 100%, and 67.65%, respectively. In the HSCT group, the D_-1, D_1, D_2, D_ 3, scores and ΔD_1 were predictive of HCU mortality, with AUCs of 0.833, 0.794, 0.871, 0.846, and 0.795, respectively. Sensitivity values for these scores were 100%, 85.71%, 71.43%, 57.14%, and 57.14%, while specificity values were 73.33%, 70.59%, 91.33%, 100%, and 100%, respectively. In the leukemia group, the D_1, D_2, D_3 scores, and ΔD_1 were predictive of HCU mortality, with AUCs of 0.760, 0.829, 0.846, and 0.756, respectively. Sensitivity values were 71.43%, 78.57%, 53.85%, and 71.43%, while specificity values were 76.19%, 78.95%, 100%, and 63.16%, respectively. For all patients, the D_3 score exhibited the highest specificity, while the ΔD_1 demonstrated the highest sensitivity. For patients in both the HSCT and leukemia groups, the sensitivity and specificity values of the D_1 and D_3 scores exceeded those of the ΔD_1. Conclusion:For patients with hematologic critical illness, including leukemia and those undergoing HSCT hospitalized in the HCU, D_1, D_2, D_ 3 scores and ΔD_1 are significantly associated with HCU mortality.

Infectious keratitis (IK) is a leading cause of blindness worldwide, primarily resulting from improper contact lens use, trauma, and a compromised immune response. The pathogenic microorganisms responsible for IK include bacteria, fungi, viruses, and Acanthamoeba. This review examines standard therapeutic agents for treating IK, including broad-spectrum empiric antibiotics for bacterial keratitis (BK), antifungals such as voriconazole and natamycin for fungal infections, and antiviral nucleoside analogues for viral keratitis (VK). Additionally, this review discusses therapeutic agents, such as polyhexamethylene biguanide (PHMB), for the treatment of Acanthamoeba keratitis (AK). The review also addresses emerging drugs and the challenges associated with their clinical application, including anti-biofilm agents that combat drug resistance and nuclear factor kappa-B (NF-κB) pathway-targeted therapies to mitigate inflammation. Furthermore, methods of Photodynamic Antimicrobial Therapy (PDAT) are explored. This review underscores the importance of integrating novel and traditional therapies to tackle drug resistance and enhance drug delivery, with the goal of advancing treatment strategies for IK.

Objective To analyze the effectiveness of reasonable control measures for prophylactic use of antibiotics in urinary system lithotripsy. Methods By antimicrobial stewardship, strengthening special comments on antibiotics and information notification on rational use of antibiotics, adding and improving the pre-review rules for antibiotics prescriptions, conducting in-depth clinical training and consultation by clinical pharmacists, strengthening innovation in rational use of drugs, and taking various measures to actively improve rational use of prophylactic antibiotics of lithotripsy in urology department, the changes of indexes related to antibiotics in urology department from 2019 to 2022 were analyzed. Results After active and reasonable control, Antibiotics Use Density in urology department decreased year by year. The utilization rate of antibiotics in inpatients decreased from 94.27% in 2019 to 77.47% in 2022. Various rate of microbial inspection reached the standard in 2022. The imipenem and cilastatin sodium for injection ranking of prophylactic use of antibiotics consumption DDDs for urinary system lithotripsy decreased from the 4th place in 2019 to the 8th place in 2022. The ranking of the urology department on carbapenem consumption DDDs in the whole hospital decreased from the 8th place in 2019 to the 12th place in 2022. At the same time, the incidence of urinary tract lithotripsy postoperative infection showed a decreasing trend year by year, from 0.84% in 2019 to 0.49% in 2022. Conclusion Positive control measures can promote the rational use of prophylactic antibiotics for urinary system lithotripsy.