Objective: To develop a quality appraisal tool for case reports in traditional Chinese medicine (TCM) based on their characteristics. [Methods]: An extensive literature search was conducted in Chinese Biomedical Literature Database (CBM), China National Knowledge Infrastructure (CNKI), and China Science and Technology Journal Database (CSTJ), focusing on expert consensus statements and checklists for TCM case reports. Relevant items were extracted, and a Delphi method involving 34 experts was used in two rounds to rate each item on a 5-point Likert scale. Items were screened based on measures of central tendency and coordination (including total score, mean score, percentage of items rated as unimportant, and coefficient of variation). The weighted average method was used to determine item weights and construct the appraisal tool. Internal consistency was assessed using Cronbach’s α coefficient. The finalized tool was pilot-tested by two reviewers independently appraising 20 case reports, with an additional four reviewers evaluating 5 of these cases to compare inter-rater consistency. Results: A total of 9 513 articles were retrieved, and 96 items from 25 articles were extracted. After two rounds of the Delphi method, 27 items across 10 domains were retained. The Cronbach’s α coefficient was 0.72 in the first round (acceptable range), and 0.96 in the second round, indicating strong internal consistency. The tool was piloted by six reviewers, achieving a kappa value of 0.663 and a Kendall’s coefficient of concordance of 0.845, demonstrating high consistency among reviewers. Conclusion The developed TCM case report quality appraisal tool, consisting of 27 items in 10 domains, offers a scientific and reliable means of assessing the quality of TCM case reports. The tool showed high consistency and practical utility, and its application is expected to enhance the standardization, scientific rigor, and evidence quality of TCM case reports, facilitating the integration of traditional medical knowledge with modern evidence-based standards.

Local anesthetics (LAs), such as articaine (AT), exhibit limited efficacy in inflammatory environments, which constitutes a significant limitation in their clinical application within oral medicine. In our prior research, we developed AT-17, which demonstrated effective properties in chronic inflammatory conditions and appears to function as a novel oral LA that could address this challenge. In the present study, we further elucidated the beneficial effects of AT-17 in acute inflammation, particularly in oral acute inflammation, where mitochondrial-related apoptosis played a crucial role. Our findings indicated that AT-17 effectively inhibited lipopolysaccharide (LPS)-induced nerve cell apoptosis by ameliorating mitochondrial dysfunction in vitro. This process involved the inhibition of mitochondrial reactive oxygen species (mtROS) production and the subsequent activation of the NRF2 pathway. Most notably, improvements in mitochondria-related apoptosis were key contributors to AT-17's inhibition of voltage-gated sodium channels. Additionally, AT-17 was shown to reduce mtROS production in nerve cells through the Na⁺/NCLX/ETC signaling axis. In conclusion, we have developed a novel local anesthetic that exhibits pronounced anesthetic functionality under inflammatory conditions by enhancing mitochondria-related apoptosis. This advancement holds considerable promise for future drug development and deepening our understanding of the underlying mechanisms of action.

Objective:To establish a set of artificial intelligence (AI) verification rules for blood routine analysis.Methods:Blood routine analysis data of 18 474 hospitalized patients from the First Hospital of Jilin University during August 1st to 31st, 2019, were collected as training group for establishment of the AI verification rules,and the corresponding patient age, microscopic examination results, and clinical diagnosis information were collected. 92 laboratory parameters, including blood analysis report parameters, research parameters and alarm information, were used as candidate conditions for AI audit rules; manual verification combining microscopy was considered as standard, marked whether it was passed or blocked. Using decision tree algorithm, AI audit rules are initially established through high-intensity, multi-round and five-fold cross-validation and AI verification rules were optimized by setting important mandatory cases. The performance of AI verification rules was evaluated by comparing the false negative rate, precision rate, recall rate, F1 score, and pass rate with that of the current autoverification rules using Chi-square test. Another cohort of blood routine analysis data of 12 475 hospitalized patients in the First Hospital of Jilin University during November 1sr to 31st, 2023, were collected as validation group for validation of AI verification rules, which underwent simulated verification via the preliminary AI rules, thus performance of AI rules were analyzed by the above indicators. Results:AI verification rules consist of 15 rules and 17 parameters and do distinguish numeric and morphological abnormalities. Compared with auto-verification rules, the true positive rate, the false positive rate, the true negative rate, the false negative rate, the pass rate, the accuracy, the precision rate, the recall rate and F1 score of AI rules in training group were 22.7%, 1.6%, 74.5%, 1.3%, 75.7%, 97.2%, 93.5%, 94.7%, 94.1, respectively.All of them were better than auto-verification rules, and the difference was statistically significant ( P<0.001), and with no important case missed. In validation group, the true positive rate, the false positive rate, the true negative rate, the false negative rate, the pass rate, the accuracy, the precision rate, the recall rate and F1 score were 19.2%, 8.2%, 70.1%, 2.5%, 72.6%, 89.2%, 70.0%, 88.3%, 78.1, respectively, Compared with the auto-verification rules, The false negative rate was lower, the false positive rate and the recall rate were slightly higher, and the difference was statistically significant ( P<0.001). Conclusion:A set of the AI verification rules are established and verified by using decision tree algorithm of machine learning, which can identify, intercept and prompt abnormal results stably, and is moresimple, highly efficient and more accurate in the report of blood analysis test results compared with auto-vefication.

Objective To investigate the clinical efficacy of mitral valve repair technique in the treatment of rheumatic mitral valve lesions. Methods The clinical data of patients diagnosed with rheumatic mitral valve lesions and undergoing mitral valve repair under extracorporeal circulation in our department from 2021 to 2022 were retrospectively analyzed. Results A total of 100 patients were collected, including 78 females and 22 males with an average age of 52 years. There were no secondary open heart or death in the whole group. Extracorporeal circulation time was 136.3±33.1 min, aortic cross-clamping time was 107.6±27.5 min, ventilator use time was 12.9±5.9 h, ICU stay was 2.6±1.4 d, and vasoactive medication use was 823.4±584.4 mg. Before and after the surgery, there were statistical differences in the left ventricular end diastolic diameter, left atrial end systolic diameter, effective mitral valve orifice area, shortening rate of left ventricular short axis, mitral E-peak blood flow velocity, mean mitral transvalvular pressure difference, mitral pressure half-time, and cardiac function graded by New York Heart Association (P＜0.05). While there was no statistical difference in left ventricular ejection fraction or left ventricular end-diastolic volume (P>0.05). Conclusion Overall repair of rheumatic mitral valve lesions can significantly improve the cardiac function and hemodynamics of the patients, and is a good choice for patients with rheumatic mitral valve lesions.

Objective To evaluate the efficacy and safety of brexpiprazole in treating acute schizophrenia.Methods Patients with schizophrenia were randomly divided into treatment group and control group.The treatment group was given brexpiprozole 2-4 mg·d-1 orally and the control group was given aripiprazole 10-20 mg·d-1orally,both were treated for 6 weeks.Clinical efficacy of the two groups,the response rate at endpoint,the changes from baseline to endpoint of Positive and Negative Syndrome Scale(PANSS),Clinical Global Impression-Improvement(CGI-S),Personal and Social Performance scale(PSP),PANSS Positive syndrome subscale,PANSS negative syndrome subscale were compared.The incidence of treatment-related adverse events in two groups were compared.Results There were 184 patients in treatment group and 186 patients in control group.After treatment,the response rates of treatment group and control group were 79.50％(140 cases/184 cases)and 82.40％(150 cases/186 cases),the scores of CGI-I of treatment group and control group were(2.00±1.20)and(1.90±1.01),with no significant difference(all P＞0.05).From baseline to Week 6,the mean change of PANSS total score wese(-30.70±16.96)points in treatment group and(-32.20±17.00)points in control group,with no significant difference(P＞0.05).The changes of CGI-S scores in treatment group and control group were(-2.00±1.27)and(-1.90±1.22)points,PSP scores were(18.80±14.77)and(19.20±14.55)points,PANSS positive syndrome scores were(-10.30±5.93)and(-10.80±5.81)points,PANSS negative syndrome scores were(-6.80±5.98)and(-7.30±5.15)points,with no significant difference(P＞0.05).There was no significant difference in the incidence of treatment-related adverse events between the two group(69.00％vs.64.50％,P＞0.05).Conclusion The non-inferiority of Brexpiprazole to aripiprazole was established,with comparable efficacy and acceptability.

OBJECTIVES: To investigate the risk factors for neonatal asphyxia in Hubei Enshi Tujia and Miao Autonomous Prefecture and establish a nomogram model for predicting the risk of neonatal asphyxia. METHODS: A retrospective study was conducted with 613 cases of neonatal asphyxia treated in 20 cooperative hospitals in Enshi Tujia and Miao Autonomous Prefecture from January to December 2019 as the asphyxia group, and 988 randomly selected non-asphyxia neonates born and admitted to the neonatology department of these hospitals during the same period as the control group. Univariate and multivariate analyses were used to identify risk factors for neonatal asphyxia. R software (4.2.2) was used to establish a nomogram model. Receiver operator characteristic curve, calibration curve, and decision curve analysis were used to assess the discrimination, calibration, and clinical usefulness of the model for predicting the risk of neonatal asphyxia, respectively. RESULTS: Multivariate logistic regression analysis showed that minority (Tujia), male sex, premature birth, congenital malformations, abnormal fetal position, intrauterine distress, maternal occupation as a farmer, education level below high school, fewer than 9 prenatal check-ups, threatened abortion, abnormal umbilical cord, abnormal amniotic fluid, placenta previa, abruptio placentae, emergency caesarean section, and assisted delivery were independent risk factors for neonatal asphyxia (P<0.05). The area under the curve of the model for predicting the risk of neonatal asphyxia based on these risk factors was 0.748 (95%CI: 0.723-0.772). The calibration curve indicated high accuracy of the model for predicting the risk of neonatal asphyxia. The decision curve analysis showed that the model could provide a higher net benefit for neonates at risk of asphyxia. CONCLUSIONS The risk factors for neonatal asphyxia in Hubei Enshi Tujia and Miao Autonomous Prefecture are multifactorial, and the nomogram model based on these factors has good value in predicting the risk of neonatal asphyxia, which can help clinicians identify neonates at high risk of asphyxia early, and reduce the incidence of neonatal asphyxia.
Infant, Newborn ; Humans ; Male ; Pregnancy ; Female ; Nomograms ; Retrospective Studies ; Cesarean Section ; Risk Factors ; Asphyxia Neonatorum/etiology*

Objective:To explore the current status of surgery for portal hypertension to grasp current status and future development of surgery in China.Methods:This study is jointly sponsored by China Hepatobiliary & Pancreatic Specialist Alliance & Portal Hypertension Alliance in China (CHESS).Comprehensive surveying is conducted for basic domestic situations of surgery for portal hypertension, including case load, surgical approaches, management of postoperative complications, primary effects, existing confusion and obstacles, liver transplantation(LT), laparoscopic procedures and transjugular intrahepatic portosystemic shunt(TIPS), etc.Results:A total of 8 512 cases of portal hypertension surgery are performed at 378 hospitals nationwide in 2021.Splenectomy plus devascularization predominated(53.0%)and laparoscopy accounted for 76.1%.Primary goal is preventing rebleeding(67.0%) and 72.8% of hospitals used preventive anticoagulants after conventional surgery.And 80.7% of teams believe that the formation of postoperative portal vein thrombosis is a surgical dilemma and 65.3% of hospitals practiced both laparoscopy and TIPS.The major reasons for patients with portal hypertension not receiving LT are due to a lack of qualifications for LT(69.3%)and economic factors(69.0%).Conclusions:Surgery is an integral part of management of portal hypertension in China.However, it is imperative to further standardize the grasp of surgical indications, the handling of surgical operation and the management of postoperative complications.Moreover, prospective, multi-center randomized controlled clinical studies should be performed.

The last essential enzyme in the biosynthetic pathway of trilobatin, phloretin-4'-O glycosyltransferase (P4'-OGT), catalyzes the conversion of trilobatin to phloretin in vitro. However, only a few P4'-OGTs have been found in plants. This study used Malus domestica phloretin-4'-O glycosyltransferase (MdPh-4'-OGT) as a query to identify and clone two UDP-glucuronosyltransferase (UGT) genes, designated UGT74L2 and UGT74L3, from the transcriptome of Andrographis paniculata. According to a phylogenetic tree analysis, UGT74L2 and UGT74L3 belonged to the UGT74 family, which has been linked to several activities in other species. The in vitro enzymatic reaction demonstrated that UGT74L2 could particularly catalyze the formation of trilobatin from phloretin, but UGT74L3 had no effects. By using Ni-NTA affinity chromatography to extract the soluble UGT74L2 recombinant protein, the enzymatic kinetics of the activity was investigated using phloretin as the substrate. The results showed that the optimal temperature and pH for UGT74L2 enzymatic reaction were 40 ℃ and 8.0 (Tris-HCl system), respectively. Three metal ions (Ca²⁺, Mn²⁺ and Co²⁺) showed inhibitory effect on the activity of UGT74L2, while Mg²⁺ could improve the activity of UGT74L2. Other tested metal ions have no significant effect on UGT74L2. The results of enzymatic kinetic parameters that the K_m value was 29.84 μmol·L^-1, the k_cat was 0.02 s^-1, and the k_cat·K_m^-1 was 572.6 mol^-1·s^-1. By homology modeling, molecular docking and mutation experiments, we found that multiple amino acids residues around the substrate binding pocket play quite an important role during catalytic process, In summary, we identified a novel P4'-OGT gene from medicinal plant Andrographis paniculata and provided a new efficient catalyst to synthesize trilobatin. Meanwhile, this study provides a reference for mining new efficient glycosylation modules from plants.

Objective: To analyze the course of disease and epidemiological parameters of COVID-19 and provide evidence for making prevention and control strategies. Methods: To display the distribution of course of disease of the infectors who had close contacts with COVID-19 cases from January 1 to March 15, 2020 in Guangdong Provincial, the models of Lognormal, Weibull and gamma distribution were applied. A descriptive analysis was conducted on the basic characteristics and epidemiological parameters of course of disease. Results: In total, 515 of 11 580 close contacts were infected, with an attack rate about 4.4%, including 449 confirmed cases and 66 asymptomatic cases. Lognormal distribution was fitting best for latent period, incubation period, pre-symptomatic infection period of confirmed cases and infection period of asymptomatic cases; Gamma distribution was fitting best for infectious period and clinical symptom period of confirmed cases; Weibull distribution was fitting best for latent period of asymptomatic cases. The latent period, incubation period, pre-symptomatic infection period, infectious period and clinical symptoms period of confirmed cases were 4.50 (95%CI:3.86-5.13) days, 5.12 (95%CI:4.63-5.62) days, 0.87 (95%CI:0.67-1.07) days, 11.89 (95%CI:9.81-13.98) days and 22.00 (95%CI:21.24-22.77) days, respectively. The latent period and infectious period of asymptomatic cases were 8.88 (95%CI:6.89-10.86) days and 6.18 (95%CI:1.89-10.47) days, respectively. Conclusion: The estimated course of COVID-19 and related epidemiological parameters are similar to the existing data.
COVID-19 ; Cohort Studies ; Contact Tracing ; Humans ; Incidence ; Prospective Studies

OBJECTIVE: To develop a method for R-peak detection of ECG data from wearable devices to allow accurate estimation of the physiological parameters including heart rate and heart rate variability. METHODS: A fully convolutional neural network was applied to predict the R-peak heatmap of ECG data and locate the R-peak positions. The heartbeat-aware (HA) module was introduced to enable the model to learn to predict the heartbeat number and R-peak heatmap simultaneously, thereby improving the capability of the model for extraction of the global context. The R-R interval estimated by the predicted heartbeat number was adopted to calculate the minimum horizontal distance for peak positioning. To achieve real-time R-peak detection on mobile devices, the deep separable convolution was adopted to reduce the number of parameters and the computational complexity of the model. RESULTS: The proposed model was trained only with ECG data from wearable devices. At a tolerance window interval of 150 ms, the proposed method achieved R peak detection sensitivities of 100% for both wearable device ECG dataset and a public dataset (i.e. LUDB), and the true positivity rates exceeded 99.9%. As for the ECG signal of a 10 s duration, the CPU time of the proposed method for R-peak detection was about 23.2 ms. CONCLUSION The proposed method has good performance for R-peak detection of both wearable device ECG data and routine ECG data and also allows real-time R-peak detection of the ECG data.
Algorithms ; Electrocardiography ; Heart Rate ; Neural Networks, Computer ; Signal Processing, Computer-Assisted ; Wearable Electronic Devices