Sangjuyin， as a pungent and cooling agent with precise therapeutic effect， is a classic pungent formula for cooling relief of the epidermis， which is highly respected by medical practitioners. This formula is from the Wenbing Tiaobian written by WU Jutong in the Qing dynasty， on the basis of which subsequent medical practitioners have made additions and subtractions to apply it. The authors used the bibliometric method to systematically organize the medical books from the Qing dynasty and the Republic of China and modern literature to analyze the composition， concoction， decoction， efficacy， and previous and modern application of Sangjuyin. After examination， the drug base of this formula is basically clear. Armeniacae Semen Amarum is the dried mature seeds of Armeniaca vulgaris， family Rosaceae. Forsythiae Fructus is the dried fruit of Forsythia suspensa， family Mulleinaceae. Menthae Haplocalycis Herba is the dried above-ground part of Mentha haplocalyx， family Labiatae. Mori Folium is the dried leaves of Morus alba， family Moraceae. Chrysanthemi Flos is the dried head of Chrysanthemum morifolium， family Asteraceae. Platycodonis Radix is the dried root of Eryngium grandiflorum， family Eryngium. Glycyrrhizae Radix et Rhizoma is the dried root and rhizome of Glycyrrhiza uralensis of the Leguminosae family， and Phragmitis Rhizoma is the fresh or dried rhizome of Phragmites communis of the Gramineae family. It is recommended that the eight drugs be used in raw form as medicine. The dosage and method of decoction were converted into a modern single dosage of 7.46 g Armeniacae Semen Amarum， 5.60 g Forsythiae Fructus， 2.98 g Menthae Haplocalycis Herba， 9.33 g Mori Folium， 3.73 g Chrysanthemi Flos， 7.46 g Platycodonis Radix， 2.98 g Glycyrrhizae Radix et Rhizoma， and 11.19 g Phragmitis Rhizoma， with 400 mL water added， and the solution was boiled to obtain 200 mL， taken twice a day. Sangjuyin has the efficacy of dispersing wind and clearing heat， promoting lung and relieving cough， and it is used for treating the initial onset of wind-warmth and the evidence of evil spirits in the lungs and collaterals. Modern research has shown that Sangjuyin is often used in the treatment of cough， pneumonia， rhinitis， and other respiratory diseases， and the results of this study provide a reference for the later development of Sangjuyin.

ObjectiveTo evaluate the clinical efficacy and safety of acupuncture in treating severe Bell's palsy and to explore its potential mechanism by investigating the effect on serum levels of glial cell line-derived neurotrophic factor （GDNF） and nerve growth factor （NGF）. MethodsA randomized， subject-blinded， sham-acupuncture controlled trial was conducted. A total of 130 patients with severe Bell's palsy were randomly allocated into a treatment group or a control group at a 1∶1 ratio. Both groups received conventional western medicine. In addition， the treatment group received acupuncture， while the control group received sham acupuncture， with each session lasting 30 minutes. The treatment course lasted 8 weeks for both groups， followed by a follow-up assessment at week 12. The primary outcome was the proportion of patients achieving House-Brackmann （H-B） grade Ⅱ or lower at week 8. Secondary outcomes included Sunnybrook facial grading system scores at week 0， 4， 8， and 12， the time to satisfactory recovery（the time required to achieve H-B grade≤Ⅱ）， distribution of H-B grades and facial disability index （FDI） scores including the physical function subscale （FDIP） and social/well-being function subscale （FDIS） scores at week 0， 4， 8， and 12， and serum GDNF and NGF levels at week 0， 4， and 8. Adverse events and participants' self-assessments of treatment efficacy were also recorded. ResultsA total of 122 participants completed the study， including 62 in the treatment group and 60 in the control group. An intention-to-treat （ITT） analysis was performed， and missing data were handled using the last observation carried forward （LOCF） method. The proportion of patients achieving H-B grade ≤grade Ⅱ at week 8 was 78.5% （51/65） in the treatment group， significantly higher than 49.2% （32/65） in the control group （P＜0.05）. The Sunnybrook scores， FDIP and FDIS scores increased， while H-B grades decreased at week 4， 8， and 12 in both groups compared to week 0； moreover， improvements in all outcome measures were significantly greater in the treatment group than in the control group （P＜0.05）. The median time to satisfactory recovery was 6 weeks （95%CI： 5.697-6.303） in the treatment group， significantly shorter than 12 weeks （95%CI： 8.314-15.686） in the control group （P＜0.05）. Serum levels of GDNF and NGF were significantly higher in the treatment group at weeks 4 and 8 （P＜0.05）. No serious acupuncture-related adverse events occurred in either group. Adverse events were reported in 5 patients （7.69%） in the treatment group and 4 patients （6.15%） in the control group， with no statistically significant difference between groups （P＞0.05）. Patients' self-assessment of treatment efficacy after 8 weeks treatment was significantly better in the treatment group （P＜0.05）. ConclusionAcupuncture can effectively improve facial nerve function and shorten recovery time in patients with severe Bell's palsy， with a favorable safety profile. The therapeutic mechanism may be associated with the upregulation of serum GDNF and NGF levels.

ObjectiveTo systematically characterize the in vitro chemical constituents of Entada phaseoloides and its absorbed prototype compounds and metabolites in a neuropathic pain （NP） model， thereby elucidating the potential pharmacological material basis underlying its analgesic activity. MethodsUltra-high-performance liquid chromatography coupled with quadrupole-Orbitrap high-resolution mass spectrometry （UHPLC-Q-Orbitrap HRMS） was used to analyze the constituents of the 80% methanol extract of E. phaseoloides. Thirty-six mice were divided into a blank group， low-， medium-， and high-dose E. phaseoloides extract groups （25， 50， and 100 mg·kg^-1， respectively）， an aspirin group （400 mg·kg^-1）， and a morphine group （10 mg·kg^-1）， with six mice in each group. The tail-flick threshold was measured. Twenty-four mice were randomly divided into a blank group and low-， medium-， and high-dose E. phaseoloides extract groups （25， 50， and 100 mg·kg^-1， respectively）， with six mice in each group， and motor coordination was evaluated. A spinal nerve ligation （SNL） model was established in mice. Twenty-four mice were randomly divided into a sham-operated （Sham） group， an SNL group， an SNL + E. phaseoloides extract group （750 mg·kg^-1）， and an SNL + pregabalin group （20 mg·kg^-1）， with 6 mice in each group. Mechanical allodynia and thermal hyperalgesia were evaluated. Behavioral assessments were combined to determine the optimal onset time of the analgesic effect， and plasma samples were collected at this time point. Absorbed components and metabolites were systematically identified based on accurate mass， MS/MS fragmentation patterns， retention time， and comparisons with literature data and reference standards. Meanwhile， network pharmacology， target similarity analysis， and molecular docking validation were integrated to evaluate the potential effects of absorbed components on disease intervention. ResultsCompared with the blank group， the high-dose E. phaseoloides extract group and morphine group showed significantly increased pain response thresholds （P<0.01）， without affecting motor coordination in normal mice. Compared with the Sham group， the SNL group exhibited significantly decreased thresholds for mechanical allodynia and thermal hyperalgesia （P<0.01）. Compared with the SNL group， the SNL + E. phaseoloides extract group and SNL + pregabalin group showed significantly increased thresholds for mechanical allodynia and thermal hyperalgesia （P<0.01）. The analgesic effect of E. phaseoloides was most significant at 2 h after administration. A total of 70 constituents were identified in vitro， and 22 prototype compounds and 29 metabolites were detected in plasma. The targets of the absorbed components were mainly enriched in biological processes associated with pain signal perception and transmission and showed a high degree of overlap with disease genes related to neuropathic pain. In addition， multiple components exhibited strong binding energies with core pain-related targets. Based on integrated analysis of in vitro content， plasma exposure levels， and target associations， ketanthamide A-β-D-pyranoside and ketengzide were identified as the most representative pharmacologically active substances responsible for the analgesic effect. ConclusionThis study systematically elucidates the material basis of E. phaseoloides intervention in neuropathic pain from three aspects， including chemical constituent characteristics， in vivo behavioral characteristics， and potential targets， providing important theoretical foundations and experimental support for further studies on its pharmacological mechanism and analgesic drug development.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6％of the isolates were Gram-negative bacteria and 17.4％were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)％and(94.0±0.1)％,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P＜0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9％.The prevalence of penicillin-resistant S.pneumoniae was 1.4％.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8％and 41.3％,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7％,20.8％,9.4％,29.8％,and 73.3％,respectively.The prevalence of β-lactamase was 96.1％in Moraxella catarrhalis and 60.0％in Haemophilus influenzae.The H.influenzae isolates from children(＜18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P＜0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.

Objective To compare and find an optimal model for predicting the risk of DKD occurrence in patients with type 2 diabetes mellitus(T2DM).Methods A total of 2005 patients with T2DM were enrolled in this study from The Second Hospital of Shijiazhuang City during December 2017 to December 2022.All the subjects were divided into a training set(n=1403)and a validation set(n=602)according to the ratio of 3∶1 by simple random sampling.With the occurrence of DKD as the outcome variablein the training set,important feature variables were screened by LASSO regression.Six different machine learning models were established according to the feature variables,thenthe optimal model was determined by comparison,and anonlinerisk predictor for DKD occurrence was constructed in patients with T2DM.Results Taking the occurrence of DKD as the outcome variable in the training set,the results of LASSO regression analysis showed that the optimal value of the model was 10-fold cross validation lambda.1se=0.01662473,and 15 characteristic variables with nonzero coefficient were screened out to be related to the occurrence of DKD.The data included sex,age,family history of DM,DM duration,LDL-C,HbA1c,WBC,PDW,Scr,urine α1-microglobulin,urine β2-microglobulin,urine microalbumin,hypertension,hypokalemia,and DR.In the training set and validation set,the prediction performance of XGBoost model was better than that of other models(AUC=0.872,0.893,95%CI 0.853～0.891,0.865～0.921),the sensitivity was 0.779,0.863,and the specificity was 0.721,0.758,respectively.The F1 scores were 0.774 and 0.787.DCA analysis showed that the XGBoost model had a greater net benefit and threshold probability.According to the XGBoost model,the online predictor of DKD risk in T2DM patients was laid out,and two patients were selected for application,the results showed that the predictive value of the model was 0.185 in non-DKD patients,and the predictive value was 0.510 in DKD patients.Conclusions The XGBoost model is the best model for predicting the occurrence of DKD in T2DM patients,and an online predictor was successfully built.

Objective To compare and find an optimal model for predicting the risk of DKD occurrence in patients with type 2 diabetes mellitus(T2DM).Methods A total of 2005 patients with T2DM were enrolled in this study from The Second Hospital of Shijiazhuang City during December 2017 to December 2022.All the subjects were divided into a training set(n=1403)and a validation set(n=602)according to the ratio of 3∶1 by simple random sampling.With the occurrence of DKD as the outcome variablein the training set,important feature variables were screened by LASSO regression.Six different machine learning models were established according to the feature variables,thenthe optimal model was determined by comparison,and anonlinerisk predictor for DKD occurrence was constructed in patients with T2DM.Results Taking the occurrence of DKD as the outcome variable in the training set,the results of LASSO regression analysis showed that the optimal value of the model was 10-fold cross validation lambda.1se=0.01662473,and 15 characteristic variables with nonzero coefficient were screened out to be related to the occurrence of DKD.The data included sex,age,family history of DM,DM duration,LDL-C,HbA1c,WBC,PDW,Scr,urine α1-microglobulin,urine β2-microglobulin,urine microalbumin,hypertension,hypokalemia,and DR.In the training set and validation set,the prediction performance of XGBoost model was better than that of other models(AUC=0.872,0.893,95%CI 0.853～0.891,0.865～0.921),the sensitivity was 0.779,0.863,and the specificity was 0.721,0.758,respectively.The F1 scores were 0.774 and 0.787.DCA analysis showed that the XGBoost model had a greater net benefit and threshold probability.According to the XGBoost model,the online predictor of DKD risk in T2DM patients was laid out,and two patients were selected for application,the results showed that the predictive value of the model was 0.185 in non-DKD patients,and the predictive value was 0.510 in DKD patients.Conclusions The XGBoost model is the best model for predicting the occurrence of DKD in T2DM patients,and an online predictor was successfully built.

Objective::To evaluate the diagnostic efficacy and clinical application of the Obstetrical Chinese Disseminated Intravascular Coagulation (DIC) Scoring System (OCDSS).Methods::This study is a retrospective study that collected 1063 cases from Wuhan Union Hospital, Yichang Central People’s Hospital, and the Central Hospital of Enshi Tujia and Miao Autonomous Prefecture between July 2017 and June 2024. These cases were divided into DIC and non-DIC groups based on score standard. Diagnosis of DIC, the rate of hysterectomy, neonatal mortality, and severe asphyxia are the main outcome measures. All the laboratory indicators are all determined by clinical laboratory department of the hospital. Data were expressed as mean ± standard deviation or median (interquartile range) and frequencies. Independent sample t-test or non-parametric test were used to compare measurement data, while the chi-square test was used for count data. Receiver operating characteristic (ROC) curve and area under curve (AUC) were used to test the predictive accuracy. Using univariate and multivariate logistic regression analysis to study the high-risk factors. P < 0.050 indicates a statistical significance. Results::Of 1063 participants in this study, 29 participants (2.73%) were diagnosed with obstetrical DIC by OCDSS score standard, and all the participants were diagnosed as DIC with underlying disease. When the Takao, Clark, and Erez score standard is the "gold standard", the OCDSS score standard always shows good sensitivity and specificity, with all the AUC over 0.75. OCDSS score standard also has better predictive of hysterectomy (68.18%, 91.07%, 0.872), severe neonatal asphyxia and death (79.17%, 75.07%, 0.842) than the other three score standards. All the indicators included in the OCDSS score standard contributed to the DIC diagnosis (all the P < 0.001). The indicators in the DIC group were more abnormal than the non-DIC group (all the P < 0.001). Conclusion::OCDSS is a first score standard, especially for pregnancies, it considers the underlying disease, clinical symptoms, and laboratory results. This score system shared a good diagnosis performance for DIC in the Chinese population and may help clinicians make timely decisions.

Objective:To address the critical issue of missing dynamic border molding information in edentulous direct digital impression technology, this study explores innovative digital solutions and conducts preliminary application validation.Methods:Based on the myostatic line theory, a methodology was established: intraoral scanner (IOS) high-frequency video was utilized to dynamically capture functional molding data of soft tissues, integrated with a self-developed mobility gradient recognition algorithm to achieve dynamic threshold segmentation between the muscle dynamic zone and myostatic zone, termed "optical digital molding technology". Ten edentulous patients with well-fitting complete dentures, treated at the Department of Prosthodontics, Peking University School and Hospital of Stomatology from January 2024 to December 2024, were enrolled. The standard deviation between the muscle static line (generated by mobility gradient algorithm with thresholds of 0.3-0.7 mm) and the denture border curve was analyzed to optimize the dynamic threshold, followed by single-case clinical validation.Results:Among the mobility thresholds of 0.3-0.7 mm, the 0.5 mm threshold yielded the smallest standard deviation between the myostatic line and denture border. Clinical validation demonstrated that dentures designed with this threshold exhibited no displacement during dynamic functional tests, with marginal sealing meeting clinical standards.Conclusions:The optical digital border molding technique for edentulous soft tissue boundaries translates the myostatic line theory into quantifiable parameters for the first time. Based on data from 10 cases, a mobility threshold of 0.5 mm is recommended for clinical application.