OBJECTIVE To explore a synergistic medication strategy integrating stage-specific modifications of Bushen huoxue decoction with hormone replacement therapy （HRT） for premature ovarian insufficiency （POI）. METHODS The connotation of Academician Tong Xiaolin’s “state-target differentiation and treatment” theory and the disease stage characteristics of POI were summarized. The latent stage， subclinical stage， clinical stage and exhaustion stage of POI were classified into corresponding core pathogenesis “states” and key objective indicator “targets”. Taking Bushen huoxue decoction as the basic prescription， its staged modification scheme and its sequential combination with HRT were analyzed. RESULTS & CONCLUSIONS The four stages of POI correspond to four pathogenic states respectively： kidney yin deficiency， kidney deficiency and blood stasis， heart-kidney disharmony， and deficiency of both yin and yang. Follicle-stimulating hormone （FSH）， anti-Müllerian hormone （AMH）， antral follicle count （AFC） and Kupperman score were taken as the evaluation targets of staging. Combined with the “state-target” characteristics of each stage， a medication principle based on Bushen huoxue decoction with syndrome differentiation modification and stage-adjusted administration was established： traditional Chinese medicine dominates in the latent stage， a sequential collaborative regimen is adopted in the subclinical stage， HRT is dominant supplemented by traditional Chinese medicine in the clinical stage， and integrated traditional Chinese and Western medicine is applied to consolidate the root cause in the exhaustion stage.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

Poly(lactic-co-glycolide)(PLGA)is a key excipient in long-acting sustained-release preparations,and its degradation properties directly affect the drug release behavior.In this study,PLGA microspheres were prepared by microfluidic techniques,and the morphology changes of the microspheres were observed by scanning electron microscopy(SEM).In alkaline environment,due to the accelerated hydrolysis of ester bonds,the surface of the microspheres was rapidly dissolved and eroded,and the degradation rate was significantly higher than that in acidic environment.High temperature accelerated the degradation of PLGA microspheres.Under neutral and alkaline conditions,the microspheres showed aggregation and adhesion.Under acidic conditions,the microspheres gradually decomposed into irregular fragments.The high ionic strength further promoted the surface corrosion of the microspheres,especially under extreme pH conditions.Simultaneously,PLGA microspheres encapsulating coumarin were prepared to simulate the microsphere formulation.The release rate of coumarin after degradation of the microspheres under different conditions was observed by measuring the absorbance with ultraviolet-visible spectrophotometry.The results were consistent with those of the blank microspheres.This study revealed that the degradation of PLGA microspheres was significantly pH-dependent,temperature sensitive and ion strength responsive.These findings not only helped to understand and optimize the long-term stability and controlled release performance of drug-carrying microspheres,but also provided a theoretical basis for further improvement of PLGA-based drug carrier design.

Objective To study the damage effect of high-voltage electric shock on skin based on metabolomics,analyze its metabolic differences,and explore its injury mechanism.Methods A total of 16 SPF C57BL/6J male mice were divided into the electric shock group(head skin received electric shock treatment)and control group(head skin received electric shock acoustic-optical stimulation),and the skin appearance after treatment of mice in the two groups was observed.The histopathological changes caused by electric shock were analyzed by HE staining,EVG staining and Masson staining.GC-MS and LC-MS metabonomics were used to analyze the changes of skin metabolism spectrum and tissue metabolites after electric shock exposure,and the differential metabolites were analyzed.The obtained differential metabolites were combined and KEGG enrichment analysis was conducted.Results After high-voltage electric shock,the skin of mice could be damaged to the dermis,and the epidermis was partially thickened,lifted and separated.The structure of skin appendages in the dermis was destroyed,with a large number of inflammatory cells infiltrating and obvious swelling,accompanied by congestion,which led to severe skin inflammatory reaction and impaired skin barrier function.Metabonomics analysis suggested that the metabolites changed after electric shock exposure.KEGG enrichment analysis showed that electric shock significantly affected the central carbon metabolism pathway of cancer,pentose phosphate pathway,purine metabolism,glycine,serine and threonine metabolism processes,amino acid tRNA biosynthesis mechanism,glycerophospholipid metabolism pathway,pyrimidine metabolism pattern,glycolysis/gluconeogenesis,alanine metabolism process,glucagon signal pathway and so on.Conclusion High voltage electric shock can cause deep skin damage,disturb its energy metabolism and amino acid metabolism,and seriously interfere with its antioxidant and DNA repair system functions.

Objective:To observe the efficacy of plasma beam combined with intense pulsed light on facial burn scars and its impact on scar score and pain level.Method:This study was a prospective study,and a random number table method was used to divided 92 patients with facial burn scars who were admitted to Maoming People's Hospital from March 2024 to August 2024 into control group(received intense pulsed light treatment,46 cases)and study group(received plasma beam treatment in addition to the control group,46 cases).The efficacy,related scale scores,scar recovery and incidence of adverse reaction rates between two groups were compaerd.Result:Compared with control group after treatment,the clinical total effective rate and the chinese version of the simplified burn health scale(BSHS-B)score of the study group were higher,while vancouver scar scale(VSS),visual analogue scale(VAS)scores,scar thickness,and scar blood flow perfusion were lower(P＜0.05).There was no significant difference in the incidence of adverse reaction rates between the two groups(P＞0.05).Conclusion:Plasma beam combined with intense pulsed light on facial burn scars,can improve clinical efficacy,improve scar thickness and blood flow perfusion,alleviate scar itching and pain,and has good safety in treating facial burn scar patients.

Depressive disorder is a kind of mental disorder characterized by persistent and significant depressed mood, with complex etiology and high recurrence rate. At present, more precise and effective diagnostic and therapeutic approaches are still required. Increasing evidence suggests that hypoxia inducible factor-1 (HIF-1) and related pathways are involved in regulating the development and recovery of depression. HIF-1 enhances neuroplasticity, mitigates neuroinflammatory responses, alleviates oxidative stress, and modulates brain energy metabolism by influencing specific molecules associated with depression. This paper reviews pertinent domestic and international studies, examine the potential mechanisms of HIF-1 in the pathogenesis and progression of depression, and explore antidepressant treatment strategies targeting the HIF-1 signaling pathway. This article provides novel insights into elucidating the pathogenesis of depression and developing innovative therapeutic approaches.

Depressive disorder is a kind of mental disorder characterized by persistent and significant depressed mood, with complex etiology and high recurrence rate. At present, more precise and effective diagnostic and therapeutic approaches are still required. Increasing evidence suggests that hypoxia inducible factor-1 (HIF-1) and related pathways are involved in regulating the development and recovery of depression. HIF-1 enhances neuroplasticity, mitigates neuroinflammatory responses, alleviates oxidative stress, and modulates brain energy metabolism by influencing specific molecules associated with depression. This paper reviews pertinent domestic and international studies, examine the potential mechanisms of HIF-1 in the pathogenesis and progression of depression, and explore antidepressant treatment strategies targeting the HIF-1 signaling pathway. This article provides novel insights into elucidating the pathogenesis of depression and developing innovative therapeutic approaches.

Objective:To investigate the application value of risk prediction model for acute kidney injury (AKI) after donation of cardiac death (DCD) liver transplantation based on machine learning algorithm.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 001 pairs of DCD liver transplant donors and recipients at five hospitals, including The First Affiliated Hospital of Zhejiang University School of Medicine et al, in the Chinese Liver Transplan-tation Registry from January 2015 to December 2023 were collected. Of the donors, there were 825 males and 176 females. Of the recipients, there were 806 males and 195 females, aged 52 (range, 18-75)years. There were 281 recipients included using oversampling technique, and all 1 282 recipients were divided to the training set of 897 recipients and the validation set of 385 recipients by a ratio of 7∶3 using computer-generated random numbers. Seven prediction models, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbors (KNN), and Categorical Boosting (CatBoost), were constructed for AKI after liver transplantation based on machine learning algorithm. Observation indicators: (1) comparison of clinicopathological characteristics between recipients with and without AKI and donors; (2) follow-up and survival of recipients with and without AKI; (3) construction and validation of nomogram prediction model of AKI after liver transplantation; (4) construction and validation of machine learning prediction model of AKI after liver transplantation. 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, and comparison among groups was conducted using the Kruskal-Wallis H test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. Kaplan-Meier method was used to calculate survival rates and plot survival curves. Logistic regression model was performed for univariate and multivariate analyses. The receiver operating characteristic (ROC) curve was plotted to calculate area under curve (AUC) and 95% confidence interval ( CI). The performance of prediction model was evaluated using DeLong test, accuracy, sensitivity, specificity. The calibration curve was plotted to evaluate the performance of predicted probability and actual probability. The interpretability analysis of machine learning algorithm and SHapley Additive exPlanations was used to explain the model decision separately. Results:(1) Comparison of clinicopathological characteristics between recipients with and without AKI and donors. Of 1 001 recipients, there were 360 cases with AKI and 641 cases without AKI after liver transplantation. There were significant differences in body mass index (BMI), hepatic encepha-lopathy, hepatitis B surfact antigen (HBsAg), hepatorenal syndrome (HRS) and donor diabetes, donor blood urea nitrogen, donor alanine aminotransferase, donor aspartate aminotransferase, mass of graft, volume of blood loss during liver transplantation, warm ischema time of donor liver, and operation time between recipients with and without AKI ( Z=-4.337, χ2=9.751, 9.088, H=11.142, χ2=5.286, Z=-3.360, -2.539, -3.084, -1.730, -3.497, -1.996, -2.644, P<0.05). (2) Follow-up and survival of recipients with and without AKI. All the 1 001 recipients received follow-up. The recipients with AKI after liver transplantation were followed up for 18.6(range, 0-102.3)months, and recipients without AKI after liver transplantation were followed up for 31.9(range, 0.1-105.5)months. The 1-, 3-, and 5-year overall survival rates were 72.1%, 63.5%, and 59.3% of recipients with AKI, versus 86.7%, 76.7%, and 72.5% of recipients without AKI, respectively, showing a significant difference in overall survival between them ( χ2=26.028, P<0.05). (3) Construction and validation of nomogram predic-tion model of AKI after liver transplantation. Results of multivariate analysis showed that recipient BMI, recipient creatinine, recipient HBsAg, recipient HRS, donor blood urea nitrogen, donor crea-tinine, anhepatic phase and volume of blood loss during liver transplantation were independent risk factors for AKI of recipients after liver transplantation ( odds ratio=1.113, 0.998, 0.605, 1.580, 1.047, 0.998, 1.006, 1.157, 95% CI as 1.070-1.157, 0.996-1.000, 0.450-0.812, 1.021-2.070, 1.021-1.074, 0.996-0.999, 1.000-1.012, 1.045-1.281, P<0.05). The nomogram prediction model of AKI after liver transplantation was constructed based on the results of multivariate analysis. Results of ROC curve showed that the AUC of 0.666 (95% CI as 0.637-0.696). (4) Construction and validation of machine learning prediction model of AKI after liver transplantation. Based on the Lasso regression analysis, seven machine learning algorithm prediction models, including RF, XGBoost, SVM, LR, DT, KNN, and CatBoost, were constructed, with ROC curves of the validation set plotted. The AUC of above models were 0.863, 0.841, 0.721, 0.637, 0.620, 0.708, 0.731, accuracies were 0.764, 0.782, 0.701, 0.592, 0.605, 0.605, 0.681, sensitivities were 0.764, 0.789, 0.719, 0.588, 0.694, 0.694, 0.704, specificities were 0.763, 0.774, 0.683, 0.597, 0.511, 0.511, 0.656, respectively. Delong test showed that the RF model with the highest AUC of 0.863(95% CI as 0.828-0.899). Calibration curve analysis showed the predicted probability closest to the actual probability of RF model, indicating the model with a good validation value. Further sorting of SHAP of different clinical factors based on RF model showed that recipient BMI, donor blood urea nitrogen, volume of blood loss during liver transplantation, donor age had large effects on the output outcomes. Conclusion:The nomogram prediction model and seven machine learning algorithm prediction models for AKI after DCD liver transplantation are constructed, and the RF model based on machine learning has a better predictive performance.

Objective To investigate the effects of ischemia time and storage periods on RNA quality in fresh-frozen breast cancer(BC)and esophageal cancer(EC)tissue samples in order to establish evidence-based protocols for biobank sample management.Methods The tumor(T)and paired normal(N)tissue samples from 6 cases of BC and 6 cases of EC were collected and cryopreserved in Biobank,Shantou Central Hospital.Mirror paraffin-embedded tissues were simultaneously prepared into sections for morphological analysis.The samples were divided into two groups of<15 min and 15-30 min according to ischemia time,and RNA quality was analyzed at 4 storage periods of 8-10 months(T1),14-16 months(T2),26-28 months(T3)and 38-40 months(T4).Results In 96 analyzed samples,93.8%(90/96)exhibited high quality(RIN≥6),with 89.6%(43/48)in BC and 97.9%(47/48)in EC.Significant differences in RIN were observed between BC group and EC group(8.050 vs.8.600,P=0.009).In EC group,RIN value was significantly negatively correlated with RNA yield(P<0.001).Moreover,RIN values of tumor-normal pairs exhibited markedly significant differences(7.550 vs.9.000,P<0.001).In contrast,no significant difference was detected in BC group(8.200 vs.7.700,P=0.348).Statistical analysis showed that RIN value was positively correlated with 28S/18S(P<0.001),but had no correlation with tumor content(P=0.676)and necrotic content(P=0.055).Neither ischemia time(<15 min vs.15-30 min:8.200 vs.8.300,P=0.932)nor storage periods(T1-T4:8.400,7.700,8.450,8.600,P=0.163)compromised RNA quality.Conclusion Organ origin and tissue type could influence RNA quality of fresh-frozen tissue samples.However,limited ischemia time(≤30 min)and long-term storage period(38-40 months)do not adversely affect RNA quality in fresh-frozen breast cancer and esophageal cancer tissue samples.

This study was aimed at identifying the pathogenic bacteria responsible for the death of a young tiger at the Fujian Meihua Mountain South China Tiger Breeding Research Institute.Tissue samples from the lungs,liver,and intestines of the deceased tiger were collected,and the bacteria were cultured inasterile environment.The bacterial strains were characterized according to their morphological and molecular biological properties,including assessment of virulence genes and antibiotic resistance genes,mouse lethality tests,and antibiotic susceptibility evaluations.A predominant bacterial strain isolated from the liver of the deceased tiger was identified as enterotoxigenic Escherichia coli(ETEC)strain Tiger22513F.Phylogenetic analysis of the 16S rRNA gene revealed that the Tiger22513F strain exhibited close genetic similarity to the reference strain ETEC(MF919609.1),with 99.9%nucleotide similarity,and resided on the same evolutionary branch.The Tiger22513F strain contained 11 antibiotic resistance genes(tetA,sul1,sul3,cmlA,floR,blaTEM,blaSHV,blaCMY-2,qnrA,qnrS,and qnrD)along with five virulence genes(VT1,fyuA,tsh,iucD,and ST).Mouse lethality tests indicated significant pathogenicity toward mice,affecting primarily the lungs,liver,and intestines.Antibiotic susceptibility testing demonstrated that this strain exhibited resistance to various classes of beta-lactam antibiotics,as well as quinolones and aminoglycosides.This investigation successfully isolated a multi-drug resistant enterotoxigenic Escherichia coli strain with pronounced pathogenicity from the liver of a deceased tiger;thus providing valuable scientific insights for clinical diagnosis,as well as prevention and control measures,against ETEC infections in South China tigers.