Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

The Expert Consensus on Clinical Application of Qinbaohong Zhike Oral Liquid in Treatment of Acute Bronchitis and Acute Attack of Chronic Bronchitis （GS/CACM 337-2023） was released by the China Association of Chinese Medicine on December 13^th， 2023. This expert consensus was developed by experts in methodology， pharmacy， and Chinese medicine in strict accordance with the development requirements of the China Association of Chinese Medicine （CACM） and based on the latest medical evidence and the clinical medication experience of well-known experts in the fields of respiratory medicine （pulmonary diseases） and pediatrics. This expert consensus defines the application of Qinbaohong Zhike oral liquid in the treatment of cough and excessive sputum caused by phlegm-heat obstructing lung， acute bronchitis， and acute attack of chronic bronchitis from the aspects of applicable populations， efficacy evaluation， usage， dosage， drug combination， and safety. It is expected to guide the rational drug use in medical and health institutions， give full play to the unique value of Qinbaohong Zhike oral liquid， and vigorously promote the inheritance and innovation of Chinese patent medicines.

AIM: To explore the risk factors associated with diabetic retinopathy(DR)based on ultra-widefield swept-source optical coherence tomography angiography(UWF-SS-OCTA), and to establish a clinical prediction model.METHODS:A total of 235 patients(235 eyes)with type 2 diabetes mellitus who were treated in the Affiliated Hospital of Xuzhou Medical University from July to November 2024 were selected as the research objects. According to the presence or absence of DR, they were divided into 120 cases(120 eyes)in non-DR group(NDR group)and 115 cases(115 eyes)in non-proliferative DR group(NPDR group). Data on general characteristics, laboratory tests, and OCTA results were collected for both groups. Univariate analysis was employed to identify DR-related risk factors. Logistic regression analysis was conducted to analyze these risk factors and to establish a DR prediction model. The efficacy of the model was evaluated using the receiver operating characteristic(ROC)curve, calibration curve, and decision curve analysis(DCA).RESULTS: The duration of diabetes, fasting blood glucose, blood urea nitrogen(BUN), history of hypertension, and the choroidal vascular index(CVI)were found to be statistically significant in the model(all P<0.05). Specifically, the duration of diabetes, fasting blood glucose, BUN, and history of hypertension were identified as risk factors for DR among diabetic patients, while CVI was recognized as a protective factor. The area under the curve for the model predicting the probability of DR was 0.898(0.859-0.938), with a diagnostic threshold of 0.438. The corresponding sensitivity and specificity were 87.8% and 78.3%, respectively, indicating that the model possesses high predictive value for the occurrence of DR.CONCLUSION: The duration of diabetes, fasting blood glucose, BUN, history of hypertension, and CVI are significantly correlated with DR. The established prediction model demonstrates a substantial screening capability for DR.

ObjectiveTo analyze the impact of maternal postpartum depression (PPD) at 2 months postpartum on caregiving for infants aged2 to 24 months, and to provide a scientific basis for future maternal and infant healthcare services. MethodsBased on the Shanghai Maternal-Child Pairs Cohort, 1 060 mother-child pairs were selected from those fully participating in follow-up visits at 2, 6, 12, and 24 months postpartum. Pregnancy and childbirth-related information was collected using standardized questionnaire surveys and hospital obstetric and maternity records. The Edinburgh postpartum depression scale was used to assess the maternal postpartum depressive symptoms at 2 months postpartum. At 2, 6, 12, and 24 months postpartum, questionnaire survey was used to evaluate the maternal responsiveness in caregiving and the provision of early learning opportunities for infants. Scores for responsive caregiving and early learning opportunities at 2, 6, 12, and 24 months were grouped based on the 25th percentile (P₂₅) of total scores. The mixed-effects model was used to analyze the longitudinal impact of maternal postpartum depression at 2 months on the caregiving of 2 to 24-month-old infants. ResultsThe longitudinal results from the mixed-effects model did not show an impact of maternal PPD on infant responsive caregiving within 12 months and early learning opportunities within24 months. However, cross-sectional analysis revealed that, compared to the non-PPD group, the risk of low responsive caregiving at 2 months in the PPD group was 93% higher (OR=1.931, 95%CI: 1.113‒3.364, P=0.019). The risks for low provision of early learning opportunities at2 months and 24 months increased by 59% (OR=1.589, 95%CI: 1.082‒2.324, P=0.017) and 60% (OR=1.598, 95%CI:1.120‒2.279, P=0.010), respectively. ConclusionMaternal postpartum depression increases the risk of low responsive caregiving at 2 months, but its long-term effects warrant further research.

To explore the inhibitory effect of ginkgolide B (GB) on MH7A human fibroblast-like synoviocytes (FLS) and its potential mechanism. Firstly, 20 μg/L tumor necrosis factor-α (TNF-α) was pretreated with MH7A to establish a cell model of arthritis. After incubation of MH7A cells with various concentrations of GB, CCK-8 assay, Transwell assay, and flow cytometry (FCM) were separately used to detect cell viability, cell invasion, and cell apoptosis rate and cell cycle; Real-time quantitative PCR and Western blot assay were performed to detect the apoptosis- and cycle-related gene transcriptions and protein expressions, respectively. The results showed that compared with the control group, GB dose- and time-dependently suppressed cell viability to a greater extent; GB significantly reduced cell invasive ability and increased cell apoptosis rate and proportion of G0/G1 phase in MH7A cells, along with increased transcription levels of Bcl-2-associated X protein (Bax) and p21 mRNA and decreased transcription levels of Bcl-2, myeloid cell leukemia 1(Mcl-1), protein kinase B (PKB; AKT), IP3K, Cyclin D1 and cyclin-dependent kinase 4 (CDK4) mRNA; GB remarkably increased expression levels of Bax, p21, and cleaved-Caspase 3 protein and decreased expression levels of Bcl-2, Mcl-1, p-AKT, p-PI3K, Cyclin D1, and CDK4 protein, with decreased ratios of p-PI3K/PI3K, p-AKT/AKT, and Bcl-2/Bax. In conclusion, GB blocks the G1-to-S cell cycle transition, suppresses cell viability and cell invasion and induces cell apoptosis of MH7A human RA-FLS via suppressing the PI3K/AKT signaling pathway.

Objective: To investigate the correlation between sleep fragmentation and body composition/blood pressure in female students of middle school, so as to provide theoretical guidance for preventing health risks associated with sleep fragmentation. Methods: From September 2022 to December 2023, 505 female students aged 12-15 years in Nanyang City were selected through stratified cluster random sampling and conducted Pittsburgh Sleep Quality Index(PSQI) survey. Participants were divided into Q 1- Q 4 groups based on sleep fragmentation index (SFI) quartiles. Body composition and blood pressure measurements were measured by adopting body composition analyzer and traditional mercury sphygmomanometer, and data were analyzed using χ 2 tests and linear regression. Results: Significant intergroup differences for Q 1- Q 4 were observed with increasing SFI levels for body mass index(BMI), fat percentage, muscle mass, bone mass, trunk fat percentage, systolic blood pressure, diastolic blood pressure, and PSQI total scores ( F =15.25,7.33,8.38,5.97,11.24,16.85,6.87,15.73, all P <0.05). SFI showed positive correlations with BMI, fat percentage, trunk fat percentage, and blood pressure( β =0.37,0.45,0.34,0.42,0.38), but negative correlations with muscle mass and bone mass( β =-0.35,-0.48) (all P <0.05). The χ 2 trend test revealed a significant increase in hypertension detection rates with elevated SFI ( χ 2=42.75, P <0.05). The χ 2 testing demonstrated statistically significant differences in hypertension incidence among different quartiles groups ( χ 2=14.16, P <0.05). After adjusting the significance level, hypertension incidence differences remained significant between Q 1and Q 4 ( χ 2=10.77), Q 2 and Q 4 groups ( χ 2=6.28) (both P <0.008 3). Conclusions Sleep fragmentation correlates significantly with body composition and blood pressure indicators in female students of middle school. Implementing sleep fragmentation interventions is essential for safeguarding female students health in middle school.

Houpo Sanwutang， included in the Catalogue of Ancient Classical Prescriptions （Second Batch）， was first recorded in the Synopsis of Golden Chamber written by ZHANG Zhongjing from the Eastern Han dynasty and was modified by successive generations of medical experts. A total of 37 pieces of effective data involving 37 ancient Chinese medical books were retrieved from different databases. Through literature mining， statistical analysis， and data processing， combined with modern articles， this study employed bibliometrics to investigate the historical origin， composition， decoction methods， clinical application， and other key information. The results showed that the medicinal origin of Houpo Sanwutang was clearly documented in classic books. Based on the conversion of the measurements from the Han Dynasty， it is recommended that 110.4 g Magnolia Officinalis Cortex， 55.2 g Rhei Radix et Rhizoma， and 72 g Aurantii Fructus Immaturus should be taken. Magnolia Officinalis Cortex and Aurantii Fructus Immaturus should be decocted with 2 400 mL water first， and 1 000 mL should be taken from the decocted liquid. Following this， Rhei Radix et Rhizoma should be added for further decoction， and then 600 mL should be taken from the decocted liquid. A single dose of administration is 200 mL， and the medication can be stopped when patients restore smooth bowel movement. Houpo Sanwutang has the effect of moving Qi， relieving stuffiness and fullness， removing food stagnation， and regulating bowels. It can be used in treating abdominal distending pain， guarding， constipation， and other diseases with the pathogenesis of stagnated heat and stagnated Qi in the stomach. The above results provide reference for the future development and research of Houpo Sanwutang.

Three carboline fluorescent probes F1-F3 were designed and synthesized, based on lead compound JYJ-19, an antifungal compound discovered previously by our group. The antifungal activity in vitro results showed that compound F1 had moderate antifungal activity (MIC₈₀ = 32 μg·mL^-1). The stokes shift of F1 is 70 nm. The fluorescent probe F1 has good optical properties and can be used for fluorescence imaging research. Subcellular localization experiments results showed that F1 was enriched in the mitochondria of fungal cells. The detection of intracellular reactive oxygen species levels shows that JYJ-19 enhances intracellular reactive oxygen species levels. The above results indicated that carboline compounds could exert antifungal effects by acting on fungal mitochondria.

Objective To explore the eradication rate of human papillomavirus(HPV)and gestational outcome of patients with high-grade squamous intraepithelial disease of the cervix(HSIL)after loop electrosurgical excision procedure(LEEP)by transvaginal dissection of the vesicorectal form the cervix.Methods A total of 53 patients treated with LEEP by transvaginal dissection of the vesicorectal form the cervix in Obstetrics and Gynecology Hospital,Fudan University from Jan to Dec,2019 were investigated.Clinical information of cervical cytological examination,HPV test and cervical biopsy under colposcopy were followed up for 6,12 and 24 months post-LEEP were collected.HPV infection in these 53 patients were compared before and after LEEP surgery.The rate of successful fertility of the cohort,the HPV conversion rate of patients with hysterectomy and LEEP done were compared.The association between the pathological type and positive surgical margin and the association between HPV infection type and positive surgical margin were analyzed.Results HPV infection rate of was 94.3%(50/53)and the proportion of HPV16 and/or 18 infection was 75.5%(40/53).Mono-HPV infection rate(69.8%,37/53)was significantly higher than mixed HPV infection rate(22.7%,13/53).Thirty-eight patients(71.7%)were found with positive surgical margin in previous LEEP operation.Fifteen patients had recurrence(28.3%)and 40 patients(75.5%)successfully delivered baby after surgery.Postoperative pathology was mainly HSIL,accounting for 66%(30/53),and 28.3%patients(15/53)had no pathological change.Forty cases had satisfying fertility-conservative operation outcome with negative surgical margin,and 38 patients eradicated HPV infection after LEEP,which took up 95%of patients with satisfying fertility-conservative operation.There was no significant difference of positive resection margin rate in between groups of HPV16/18 infection and other types.Five cases had successful delivery(12.5%,5/40)with 1 case of vaginal delivery and 4 cases of cesarean section.Among these 5 cases,3 cases undertook preventive cervical cerclage,with 1 case of vaginal delivery and 2 cases of cesarean sections.Conclusion HPV eradication rate and surgical outcome could be significantly improved by LEEP with transvaginal dissection of the vesicorectal from the cervix,which satisfied the fertility preservation of females at reproductive age.

BACKGROUND:The combination of machine learning and medical metal materials can make up for the inefficiency and high cost of traditional experiments and computational simulations,and quickly and accurately predict the characteristics of metal materials by analyzing large amounts of data,optimize material design and performance,and improve the safety and efficiency of medical applications. OBJECTIVE:To summarize the research progress and shortcomings of machine learning in the characteristics of medical materials. METHODS:The first author searched CNKI,PubMed,X-MOL,and Web of Science databases by computer to search all relevant articles from January 2013 to April 2023.The Chinese search terms were"machine learning of medical metal materials,medical titanium alloy,medical magnesium alloy,medical metal material properties".The English search terms were"machine learning medical metal materials,medical stainless steel alloy,medical cobalt-chromium alloy,medical titanium alloy,medical magnesium alloy".Finally,70 relevant articles were included for a summary. RESULTS AND CONCLUSION:(1)The introduction of machine learning as a material design methodology has opened up new paradigms for material science research as the accessibility of large amounts of data generated by traditional experimental and computational simulation methods increases.(2)The machine learning workflow is divided into four main parts:data collection and preprocessing,feature engineering,model selection and training,and model evaluation,each of which is indispensable.(3)Medical metal materials are categorized into:stainless steel co-base alloys,cobalt-chromium alloys,titanium alloys,and magnesium alloys.For stainless steel co-base alloy,machine learning predicts its mechanical properties,to improve the generalization ability of machine learning.For cobalt-chromium alloy,machine learning predicts its mechanical properties,and it can conclude that cobalt-chromium alloy is the optimal material for hip implants.For titanium alloy,machine learning predicts its mechanical properties,and it can select the implant with the best mechanical properties.For magnesium alloy,machine learning predicts its corrosion resistance and mechanical properties;the ensemble model can accurately predict the mechanical properties of magnesium alloys,and the random forest model can predict the optimal elemental contents of magnesium alloys as vascular stents.(4)Machine learning has deficiencies in the field of medical materials.For example,the model is relatively lagging;the data failed to be standardized,and the generalization is low.To solve such problems,we should make full use of deep learning and segmentation algorithm technology,use unified standard data,and improve the model to increase the generalization ability.