This study employed the "disease-medicine-dose" pattern to mine the medication rules of traditional Chinese medicine(TCM) prescriptions containing Astragali Radix in ancient Chinese medical books, aiming to provide a scientific basis for the clinical application of Astragali Radix and the development of new medicines. The TCM prescriptions containing Astragali Radix were retrieved from databases such as Chinese Medical Dictionary and imported into Excel 2020 to construct the prescription library. Statical analysis were performed for the prescriptions regarding the indications, syndromes, medicine use frequency, herb effects, nature and taste, meridian tropism, dosage forms, and dose. SPSS statistics 26.0 and IBM SPSS Modeler 18.0 were used for association rules analysis and cluster analysis. A total of 2 297 prescriptions containing Astragali Radix were collected, involving 233 indications, among which sore and ulcer, consumptive disease, sweating disorder, and apoplexy had high frequency(>25), and their syndromes were mainly Qi and blood deficiency, Qi and blood deficiency, Yin and Yang deficiency, and Qi deficiency and collateral obstruction, respectively. In the prescriptions, 98 medicines were used with the frequency >25 and they mainly included Qi-tonifying medicines and blood-tonifying medicines. Glycyrrhizae Radix et Rhizoma, Angelicae Sinensis Radix, Ginseng Radix et Rhizoma, Atractylodis Macrocephalae Rhizoma, and Citri Reticulatae Pericarpium were frequently used. The medicines with high frequency mainly have warm or cold nature, and sweet, pungent, or bitter taste, with tropism to spleen, lung, heart, liver, and kidney meridians. In the treatment of sore and ulcer, Astragali Radix was mainly used with the dose of 3.73 g and combined with Glycyrrhizae Radix et Rhizoma to promote granulation and heal up sores. In the treatment of consumptive disease, Astragali Radix was mainly used with the dose of 37.30 g and combined with Ginseng Radix et Rhizoma to tonify deficiency and replenish Qi. In the treatment of sweating disorder, Astragali Radix was mainly used with the dose of 3.73 g and combined with Glycyrrhizae Radix et Rhizoma to consolidate exterior and stop sweating. In the treatment of apoplexy, Astragali Radix was mainly used with the dose of 7.46 g and combined with Glycyrrhizae Radix et Rhizoma to dispell wind and stop convulsions. Astragali Radix can be used in the treatment of multiple system diseases, with the effects of tonifying Qi and ascending Yang, consolidating exterior and stopping sweating, and expressing toxin and promoting granulation. According to the manifestations of different diseases, when combined with other medicines, Astragali Radix was endowed with the effects of promoting granulation and healing up sores, tonifying deficiency and Qi, consolidating exterior and stopping sweating, and dispelling wind and replenishing Qi. The findings provide a theoretical reference and a scientific basis for the clinical application of Astragali Radix and the development of new medicines.
Drugs, Chinese Herbal/history* ; Humans ; Medicine, Chinese Traditional/history* ; History, Ancient ; Astragalus Plant/chemistry* ; China ; Astragalus propinquus

Ultra performance liquid chromatography-quadrupole-time-of-flight-mass spectrometry/mass spectrometry(UPLC-Q-TOF-MS/MS), network pharmacology, and animal experiments were integrated o explore the blood glucose-lowering effects and mechanisms of Poria aqueous extract. Firstly, the active components of Poria aqueous extract were identified by UPLC-Q-TOF-MS/MS. Subsequently, network pharmacology was employed to predict the blood glucose-lowering components and mechanisms of Poria aqueous extract. Finally, a rat model of diabetes mellitus, 16S rDNA sequencing, and Western blot were employed to investigate the blood glucose-lowering effect and mechanism of Poria aqueous extract. A total of 39 triterpenoids were identified in the Poria aqueous extract, among them, 25-hydroxypachymic acid, 25α-hydroxytumulosic acid, 16α-hydroxytrametenolic acid, polyporenic acid C, and tumulosic acid may be the main active ingredients for treating diabetes. The Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis revealed that Poria might exert its therapeutic effects through multiple pathways such as NOD-like receptor signaling pathway, nuclear factor-kappa B(NF-κB) signaling pathway, and tumor necrosis factor(TNF) signaling pathway. The results of animal experiments demonstrated that Poria aqueous extract significantly reduced the levels of blood glucose and lipids and regulated the intestinal flora in diabetic rats. The main affected taxa included g＿Escherichia-Shigella, g＿Corynebacterium, g＿Prevotella＿9, g＿Prevotellaceae＿UCG-001, and g＿Bacteroidota＿unclassified. In addition, Poria aqueous extract lowered the levels of D-lactic acid and lipopolysaccharide, alleviated colonic mucosal damage, significantly down-regulated the protein levels of NOD-like receptor pyrin domain-containing protein 3(NLRP3), NF-κB, and TNF-α, and significantly up-regulated the protein levels of zonula occludens 1 and occludin in diabetic rates. Poria aqueous extract may play a role in treating diabetes mellitus by repairing the intestinal flora disturbance, protecting the intestinal barrier function, and inhibiting the NF-κB/NLRP3 signaling pathway. The results provide a scientific basis for clinical application and expansion of indications of Poria.
Animals ; Rats ; Network Pharmacology ; Tandem Mass Spectrometry ; Male ; Drugs, Chinese Herbal/pharmacology* ; Chromatography, High Pressure Liquid ; Blood Glucose/drug effects* ; Rats, Sprague-Dawley ; Hypoglycemic Agents/administration & dosage* ; Poria/chemistry* ; Diabetes Mellitus, Experimental/metabolism* ; NF-kappa B/genetics* ; Gastrointestinal Microbiome/drug effects* ; Humans

PURPOSE: The rate of complications among patients undergoing surgery has increased due to infection with SARS-CoV-2 and other variants of concern. However, Omicron has shown decreased pathogenicity, raising questions about the risk of postoperative complications among patients who are infected with this variant. This study aimed to investigate complications and related factors among patients with recent Omicron infection prior to undergoing orthopedic surgery. METHODS: A historical control study was conducted. Data were collected from all patients who underwent surgery during 2 distinct periods: (1) between Dec 12, 2022 and Jan 31, 2023 (COVID-19 positive group), (2) between Dec 12, 2021 and Jan 31, 2022 (COVID-19 negative control group). The patients were at least 18 years old. Patients who received conservative treatment after admission or had high-risk diseases or special circumstances (use of anticoagulants before surgery) were excluded from the study. The study outcomes were the total complication rate and related factors. Binary logistic regression analysis was used to identify related factors, and odds ratio (OR) and 95% confidence interval (CI) were calculated to assess the impact of COVID-19 infection on complications. RESULTS: In the analysis, a total of 847 patients who underwent surgery were included, with 275 of these patients testing positive for COVID-19 and 572 testing negative. The COVID-19-positive group had a significantly higher rate of total complications (11.27%) than the control group (4.90%, p < 0.001). After adjusting for relevant factors, the OR was 3.08 (95% CI: 1.45-6.53). Patients who were diagnosed with COVID-19 at 3-4 weeks (OR = 0.20 (95% CI: 0.06-0.59), p = 0.005), 5-6 weeks (OR = 0.16 (95% CI: 0.04-0.59), p = 0.010), or ≥7 weeks (OR = 0.26 (95% CI: 0.06-1.02), p = 0.069) prior to surgery had a lower risk of complications than those who were diagnosed at 0-2 weeks prior to surgery. Seven factors (age, indications for surgery, time of operation, time of COVID-19 diagnosis prior to surgery, C-reactive protein levels, alanine transaminase levels, and aspartate aminotransferase levels) were found to be associated with complications; thus, these factors were used to create a nomogram. CONCLUSION Omicron continues to be a significant factor in the incidence of postoperative complications among patients undergoing orthopedic surgery. By identifying the factors associated with these complications, we can determine the optimal surgical timing, provide more accurate prognostic information, and offer appropriate consultation for orthopedic surgery patients who have been infected with Omicron.
Humans ; COVID-19/complications* ; Male ; Female ; Middle Aged ; Postoperative Complications/epidemiology* ; SARS-CoV-2 ; Orthopedic Procedures/adverse effects* ; Aged ; Nomograms ; Adult ; Retrospective Studies ; Risk Factors

In recent years, with the increasing societal focus on drug quality and safety, quality issues have become a major challenge faced by the pharmaceutical industry, directly impacting consumer health and market trust. By combining multispectral imaging technology with machine learning, it is possible to achieve rapid, non-destructive, and precise detection of traditional Chinese medicine(TCM) preparations, thereby revolutionizing traditional detection methods and developing more convenient and automated solutions. This paper provides a comprehensive review of the current applications of rapid, non-destructive detection techniques based on machine learning algorithms in the field of TCM preparations. It analyzed the principles and advantages of commonly used rapid, non-destructive detection techniques, offering a reference for the application and promotion of these technologies in TCM preparation detection. Additionally, this paper explored various data preprocessing techniques, operational processes, and machine learning algorithms to enhance data utilization efficiency. Finally, it focused on the challenges of applying machine learning in TCM preparation detection and offered corresponding recommendations, providing guidance for the future integration of machine learning with rapid, non-destructive detection techniques in practical production.
Machine Learning ; Drugs, Chinese Herbal/analysis* ; Medicine, Chinese Traditional/methods* ; Humans ; Quality Control

The construction method and simulation parameter settings for the discrete element model of Jianwei Xiaoshi Granules, as the primary material of Jianwei Xiaoshi Tablets, are not yet clear. The accuracy of the simulation model significantly influences the dynamic response characteristics between granules. Therefore, it is necessary to calibrate the parameters to improve the accuracy of the simulation parameters. Using the repose angle of Jianwei Xiaoshi Granules as the response value, the response surface methodology was employed to optimize and calibrate the discrete element parameters. Physical experiments were conducted to determine the physical properties of Jianwei Xiaoshi Granules. Based on the Hertz-Mindlin with Johnson-Kendall-Roberts(JKR) V2 model and virtual simulation methods, a repose angle determination model was constructed in EDEM software. The repose angle was measured using image analysis and numerical fitting methods. The Plackett-Burman experiment was used to screen the initial parameters for significance in the discrete element simulation. The significant parameters were then subjected to a steepest ascent experiment to determine the optimal parameter range. Furthermore, based on the Box-Behnken experiment, a second-order regression equation between significant parameters and repose angle was established, with the repose angle of 37.64° in the physical experiment as the target value. The regression equation was optimized and solved. The significance screening experiment revealed that the granule-granule static friction coefficient, granule-granule rolling friction, and granule-steel plate rolling friction of Jianwei Xiaoshi Granules significantly influenced the simulated repose angle. The optimal parameter combination was found to be 0.330, 0.222, and 0.229. The simulation results with this optimal parameter combination showed that there was no significant difference between the simulated repose angle and the repose angle obtained in the physical experiment, with a relative error of 0.05%, which further validated the reliability of the calibrated discrete element parameters for Jianwei Xiaoshi Granules.
Drugs, Chinese Herbal/chemistry* ; Calibration ; Computer Simulation

Identification of critical material attributes(CMAs) is a key issue in the quality control of large-scale TCM products like Jianwei Xiaoshi Tablets. This study focuses on the granules of Jianwei Xiaoshi Tablets, using tablet tensile strength as the primary quality attribute. A method for identifying the CMAs and a design space for the granules were established, along with a predictive model for the granule CMAs based on Fourier transform near-infrared spectroscopy(FT-NIR). First, granules of Jianwei Xiaoshi Tablets with different properties were prepared using a partial factorial design method from the design of experiments(DOE). The powder properties of the granules were measured. An orthogonal partial least squares(OPLS) model was established to correlate the powder properties with tensile strength. Based on the characteristics of the comprehensive variables extracted by OPLS, the independent variables with the greatest explanatory power for tensile strength were identified. FT-NIR technology was then employed to establish a predictive model for the granule CMAs. The final CMAs identified were hygroscopicity, moisture content, D_(50), collapse angle, mass flow rate, and tapped density. The coefficients of determination of the prediction set(R■) and relative percentage deviation(RPD) of the prediction set for flowability, D_(50), and moisture content were 0.891, 0.994, and 0.998; and 2.97, 12.4, and 20.7, respectively. The established OPLS model clearly identified the impact of various factors on tensile strength, demonstrating good fit results. The model exhibited high prediction accuracy and can be used for the rapid and accurate determination of CMAs in granules of Jianwei Xiaoshi Tablets.
Drugs, Chinese Herbal/chemistry* ; Tablets/chemistry* ; Tensile Strength ; Quality Control ; Spectroscopy, Fourier Transform Infrared ; Spectroscopy, Near-Infrared

Abstract: Objective　To analyze the epidemiological characteristics (season, age, gender, mixed infection and clinical manifestations, etc.) of Mycoplasma pneumoniae (MP) infection in children in Hainan Province, so as to provide epidemiological evidence-based medical basis for the prevention and control of MP infection in children in Hainan Province. Methods　The serum IgM antibodies of MP, Legionella pneumophila, Chlamydia pneumoniae, adenovirus, respiratory syncytial virus (RSV), Q fever Rickettsia, parainfluenza virus, influenza A virus and influenza B virus in children with respiratory tract infections (RTIs) who were hospitalized in pediatrics of many hospitals in Hainan Province from March 2012 to February 2020 were detected by indirect immunofluorescence method. The positive serum MP-IgM antibody was defined as MP infection. The epidemiological and clinical data of MP infected cases were analyzed retrospectively. Results　From March, 2012 to February, 2020, a total of 35 731 qualified pediatric inpatients with RTIs in many hospitals in Hainan Province were tested for serum MP-IgM with the total positive rate of 39.12% (13 978/35 731). The yearly positive rates of MP-IgM from 2012 to 2020 were 48.39%, 56.23%, 56.62%, 47.04%, 29.71%, 24.14%, 47.55%, 36.84% and 24.46% respectively. The positive rates of MP-IgM in 2013 and 2014 were significantly higher than those in other years (P<0.05). The positive rate of MP-IgM in summer in Hainan Province was the highest (41.34%) and the lowest in winter (35.77%) (P<0.05). MP infection occurred in all age groups, the positive rate of MP-IgM in children of preschool (51.80%) was significantly higher than that in other age groups (P<0.01), and the positive rate of MP IgM in children of infancy (15.36%) was lower than that in other age groups (P<0.01). The positive rate of MP-IgM in female was 44.77%, which was significantly higher than that in male (35.83%) (P<0.05). MP infection combined with positive IgM of another pathogen accounted for 32.63% (4 561 cases), positive IgM of another two pathogens accounted for 1.26% (176 cases). MP infection was mostly found in pneumonia (68.73%), and the main clinical symptoms were cough (84.72%), fever (51.01%) and wheezing (3.16%). Conclusions　MP is an important pathogen of respiratory tract infection in children in Hainan Province, and infection is more common in children in early school age and early childhood. Mp-specific tests should be performed to identify the pathogen in children suspected of MP infection. In the high incidence season, health education should be strengthened in kindergartens, schools and other places to prevent respiratory tract infection.

Objective: To explore the epidemiological characteristic of a COVID-19 outbreak caused by 2019-nCoV Omicron variant BF.7 and other provinces imported in Shenzhen and analyze transmission chains and characteristics. Methods: Field epidemiological survey was conducted to identify the transmission chain, analyze the generation relationship among the cases. The 2019-nCoV nucleic acid positive samples were used for gene sequencing. Results: From 8 to 23 October, 2022, a total of 196 cases of COVID-19 were reported in Shenzhen, all the cases had epidemiological links. In the cases, 100 were men and 96 were women, with a median of age, M (Q₁, Q₃) was 33(25, 46) years. The outbreak was caused by traverlers initial cases infected with 2019-nCoV who returned to Shenzhen after traveling outside of Guangdong Province.There were four transmission chains, including the transmission in place of residence and neighbourhood, affecting 8 persons, transmission in social activity in the evening on 7 October, affecting 65 persons, transmission in work place on 8 October, affecting 48 persons, and transmission in a building near the work place, affecting 74 persons. The median of the incubation period of the infection, M (Q₁, Q₃) was 1.44 (1.11, 2.17) days. The incubation period of indoor exposure less than that of the outdoor exposure, M (Q₁, Q₃) was 1.38 (1.06, 1.84) and 1.95 (1.22, 2.99) days, respcetively (Wald χ²=10.27, P=0.001). With the increase of case generation, the number and probability of gene mutation increased. In the same transmission chain, the proportion of having 1-3 mutation sites was high in the cases in the first generation. Conclusions: The transmission chains were clear in this epidemic. The incubation period of Omicron variant BF.7 infection was shorter, the transmission speed was faster, and the gene mutation rate was higher. It is necessary to conduct prompt response and strict disease control when epidemic occurs.
Male ; Humans ; Female ; SARS-CoV-2 ; COVID-19/epidemiology* ; Disease Outbreaks ; Epidemics ; China/epidemiology*

This study aimed to characterize and identify the non-volatile components in Pogostemonis Herba by using ultra-perfor-mance liquid chromatography-quadrupole-time of flight-mass spectrometry(UPLC-Q-TOF-MS) combined with UNIFI and an in-house library. The chemical components in 50% methanol extract of Pogostemonis Herba were detected by UPLC-Q-TOF-MS in both positive and negative MS~E continuum modes. Then, the MS data were processed in UNIFI combined with an in-house library to automatically characterize the metabolites. Based on the multiple adduct ions, exact mass, diagnostic fragment ions, and peak intensity of compounds and the fragmentation pathways and retention behaviors of reference substances, the structures identified by UNIFI were further verified and those of the unidentified compounds were tentatively elucidated. A total of 120 compound structures were identified or tentatively identified, including flavonoids, phenylpropanoids, phenolic acids, terpenes, fatty acids, alkaloids, and phenylethanoid glycosides. Sixteen of them were accurately identified by comparison with reference substances, and 53 compounds were reported the first time for Pogostemonis Herba. This study systematically characterized and identified the non-volatile compounds in Pogostemonis Herba for the first time. The findings provide a scientific basis for revealing the pharmacodynamic material basis, establishing a quality control system, and developing products of Pogostemonis Herba.

ObjectiveTo compare the effects of ganirelix1， ganirelix2 and cetrorelix for preventing premature luteinizing hormone （LH） surges and on clinical outcomes in gonadotropin-releasing hormone antagonist （GnRH-ant） cycles. MethodsWe retrospectively analyzed 1434 GnRH-ant cycles of in vitro fertilization/intracytoplasmic sperm injection （IVF/ICSI） at the Reproductive Medical Center of The Third Affiliated Hospital of Sun Yat-sen University from October， 2019 to December， 2020， including 461 cycles with ganirelix 1 treatment （Group 1）， 741 cycles with ganirelix 2 treatment （Group 2） and 232 cycles with cetrorelix treatment （Group 3） . The baseline characteristics of the patients and the clinical outcomes of the three groups were compared. ResultsThere were no significantly differences found in age，body mass index and anti-Müllerian hormone among the three groups. There were no significant differences in number of oocytes， proportion of LH >10 U/L on human chorionic gonadotrophin （hCG） trigger day， incidence of moderate/severe ovarian hyperstimulation syndrome （OHSS）， mature oocytes， clinical pregnancy rate and live birth rate following fresh embryo transfer among the three groups （P > 0.05）. The early pregnancy loss rate of ganirelix 1 group was significantly higher than that of ganirelix 2 group （P < 0.05）. ConclusionThere were similar incidence of premature LH surge in hCG day， moderate/severe OHSS， clinical pregnancy rate and live birth rate in GnRH-ant protocols among the three antagonists. The ganirelix 1 group may have a higher risk of adverse pregnancy outcome following fresh transfer since the high early pregnancy loss rate of it.