A scoping review was performed to systematically search and summarize the clinical research in the treatment of dysmenorrhea with oral Chinese patent medicines. The oral Chinese patent medicines for treating dysmenorrhea in three major drug lists, guidelines, and textbooks were screened, and the relevant clinical trials were retrieved from eight Chinese and English databases. The key information of the included trials was extracted and visually analyzed. A total of 50 Chinese patent medicines were included, among which oral Chinese patent medicines for the dysmenorrhea patients with the syndrome of Qi stagnation and blood stasis accounted for the highest proportion, and the average daily cost varied greatly among Chinese patent medicines. A total of 150 articles were included, involving 22 Chinese patent medicines, among which Guizhi Fuling Capsules/Pills, Sanjie Zhentong Capsules, and Dan'e Fukang Soft Extract were the most frequently studied. These articles mainly reported randomized controlled trial(RCT), which mainly focused on the comparison of the intervention effect between Chinese patent medicines combined with western medicine and western medicine alone, and the sample size was generally 51-100 cases. The high-frequency outcome indicators belonged to nine domains such as effective rate, adverse reactions, and laboratory examinations. This study showed that oral Chinese patent medicines had advantages in the treatment of dysmenorrhea, and the annual number of related clinical trials showed an overall growing trend. However, there were still problems such as insufficient safety information and vague description of traditional Chinese medicine(TCM) syndromes types in the instructions of Chinese patent medicines. The available clinical research had shortcomings such as uneven distribution of Chinese patent medicines, limited research scale, poor methodological rigor, and insufficient standardization of outcome indicators. In the future, it is necessary to deepen the development of high-quality clinical research and improve the contents of the instructions to ensure the effectiveness and safety of the clinical application of oral Chinese patent medicines in the treatment of dysmenorrhea.
Dysmenorrhea/drug therapy* ; Humans ; Drugs, Chinese Herbal/administration & dosage* ; Female ; Administration, Oral ; Nonprescription Drugs/administration & dosage*

The differences in chemical quality characteristics between Xinjiang Rehmannia glutinosa and R. glutinosa were analyzed to provide a theoretical basis for the introduction and quality control of R. glutinosa. In this study, the high performance liquid chromatography(HPLC) fingerprints of 6 batches of Xinjiang R. glutinosa and 10 batches of R. glutinosa samples were established. The content of iridoid glycosides, phenylethanoid glycosides, monosaccharides, oligosaccharides, and polysaccharides in Xinjiang R. glutinosa and R. glutinosa was determined by high performance liquid chromatography-diode array detection(HPLC-DAD), high performance liquid chromatography-evaporative light scattering detection(HPLC-ELSD), and ultraviolet-visible spectroscopy(UV-Vis). The determination results were analyzed with by chemical pattern recognition and entropy weight TOPSIS method. The results showed that there were 19 common peaks in the HPLC fingerprints of the 16 batches of R. glutinosa, and catalpol, aucubin, rehmannioside D, rehmannioside A, hydroxytyrosol, leonuride, salidroside, cistanoside A, and verbascoside were identified. Hierarchical cluster analysis(HCA) and principal component analysis(PCA) showed that Qinyang R. glutinosa, Mengzhou R. glutinosa, and Xinjiang R. glutinosa were grouped into three different categories, and eight common components causing the chemical quality difference between Xinjiang R. glutinosa and R. glutinosa in Mengzhou and Qinyang of Henan province were screened out by orthogonal partial least squares discriminant analysis(OPLS-DA). The results of content determination showed that there were glucose, sucrose, raffinose, stachyose, polysaccharides, and nine glycosides in Xinjiang R. glutinosa and R. glutinosa samples, and the content of catalpol, rehmannioside A, leonuride, cistanoside A, verbascoside, sucrose, and glucose was significantly different between Xinjiang R. glutinosa and R. glutinosa. The analysis with entropy weight TOPSIS method showed that the comprehensive quality of R. glutinosa in Mengzhou and Qinyang of Henan province was better than that of Xinjiang R. glutinosa. In conclusion, the types of main chemical components of R. glutinosa and Xinjiang R. glutinosa were the same, but their content was different. The chemical quality of R. glutinosa was better than Xinjiang R. glutinosa, and other components in R. glutinosa from two producing areas and their effects need further study.
Rehmannia/classification* ; Drugs, Chinese Herbal/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Quality Control

Nanoparticle delivery systems have good application prospects in the field of precision therapy, but the preparation process of nanomaterial has problems such as short in vivo circulation time, easy recognition, and clearance by the immune system in the body. In recent years, biomimetic nanoparticle delivery systems mediated by natural cell membranes have become a research hotspot to address these issues. The natural membrane biomimetic nanoparticle delivery system cleverly integrates the advantages of natural biofilm "autologous" and "artificial" functional carriers by using endogenous cell membranes to modify the surface of nanocarriers, endowing them with characteristics such as tumor targeting, low immunogenicity, and long blood circulation. Currently, biomimetic nanoparticle delivery systems have been used in the treatment of malignant tumors, cardiovascular diseases, bacterial infections, and other diseases. This paper analyzes the development status and current research hotspots of natural cell membrane camouflaged biomimetic nanoparticle delivery systems mainly reviews the latest research progress of red blood cell membrane camouflaged biomimetic nanoparticle delivery systems in the field of disease treatment in recent years. It focuses on exploring the advantages, future development prospects, and limitations of biomimetic nanoparticle delivery systems based on red blood cell membrane camouflage in improving drug delivery, to provide a reference for the in-depth research and development of this system.

OBJECTIVE: CRISPR-Cas protects bacteria from exogenous DNA invasion and is associated with bacterial biofilm formation and pathogenicity. METHODS: We analyzed the type I-F CRISPR-Cas system of Legionella pneumophila WX48, including Cas1, Cas2-Cas3, Csy1, Csy2, Csy3, and Cas6f, along with downstream CRISPR arrays. We explored the effects of the CRISPR-Cas system on the in vitro growth, biofilm-forming ability, and pathogenicity of L. pneumophila through constructing gene deletion mutants. RESULTS: The type I-F CRISPR-Cas system did not affect the in vitro growth of wild-type or mutant strains. The biofilm formation and intracellular proliferation of the mutant strains were weaker than those of the wild type owing to the regulation of type IV pili and Dot/Icm type IV secretion systems. In particular, Cas6f deletion strongly inhibited these processes. CONCLUSION The type I-F CRISPR-Cas system may reduce biofilm formation and intracellular proliferation in L. pneumophila.
Legionella pneumophila/pathogenicity* ; CRISPR-Cas Systems ; Biofilms/growth & development* ; Phenotype ; Bacterial Proteins/metabolism* ; Gene Deletion

Objective:To establish and evaluated a logistic regression model for predicting the acute biliary pancreatitis (ABP) based on liver-injury related indexes.Methods:Clinical data of 210 patients diagnosed with acute pancreatitis (AP) at the Affiliated Hospital of Jiangnan University from October 2020 to December 2022 were retrospectively analyzed, including 113 males and 97 females, with a median age of 52 years (range, 43 to 58). Among these, 88 were diagnosed with ABP and 122 with acute non-biliary pancreatitis (ANBP). Additionally, a test cohort was created using data from 101 AP patients diagnosed between January and December 2023, including 60 males and 41 females, with a median age of 53 years (range, 43 to 63). Based on the original dataset, univariate and multivariate logistic regression analyses were conducted to identify the factors influencing ABP. A prediction probability formula (Pre) was then established based on the multivariate results. The effectiveness of each indicator in predicting ABP was evaluated using the receiver operating characteristic (ROC) curve. The ROC curve analysis determined the optimal cutoff value of Pre, which was subsequently used to diagnose ABP and ANBP in the test cohort.Results:Multivariate logistic regression analysis showed the factors influencing ABP include direct bilirubin (DBIL), alanine aminotransferase (ALT), aspartate aminotransferase (AST), cholinesterase (CHE), and fibrinogen (FIB). Based on the multivariate analysis results, the prediction probability formula (Pre) for ABP was established as follows: P=1/{1+ exp[-(4.807+ 0.134×DBIL-1.859×AST/ALT-0.0003×CHE-0.387×FIB)]}. ROC curve analysis revealed that the area under the curve (AUC) for Pre in predicting ABP was 0.858, with an optimal cutoff value of 0.56, at which the sensitivity was 69.3% and the specificity was 91.0%. Using the cutoff value of 0.56 for Pre, ABP was diagnosed when Pre≥0.56 and ANBP was diagnosed when Pre<0.56. This criterion was applied to diagnose patients in the test cohort, where the sensitivity and specificity of Pre for diagnosing ABP were 86.1% and 92.3%, respectively.Conclusion:The logistic regression model based on liver injury-related indicators is a valuable tool for clinically assessing the incidence of ABP.

Objective:To analyze the changes of serum metabolites in patients with acute pancreatitis (AP) by non-targeted metabolomics method.Methods:Serum samples and clinical data of 15 AP patients hospitalized in the Affiliated Hospital of Jiangnan University from August to September 2024 were collected and included in the AP group, including 9 males and 6 females, aged (55.4±15.3) years. The serum and clinical data of 25 patients with colon polyps in the same hospital during the same period of time were collected, including 15 males and 10 females, aged (61.2±11.5) years, and were included in the control group. Serum metabolomic detection was performed using the ultra-high performance liquid chromatography tandem Fourier transform mass spectrometer. The modeling method was orthogonal partial least square discriminant analysis, and principal component analysis was performed on the data matrix to screen the differential metabolites in serum of AP patients. The Kyoto Encyclopedia database of Genes and Genomes was used to annotate differential metabolites, and the pathway of differential metabolite enrichment was analyzed by software.Results:The principal component analysis showed that the contribution ratio of the first principal component was 15.1%, the proportion of the second principal component was 10.8%, and the total proportion of the two was 25.9%. In principal component analysis, two groups of samples can be clearly distinguished and show obvious clustering characteristics. According to the analysis of OPLS-DA model, there were significant differences in serum metabolic profiles between AP group and control group. There were 683 differentially expressed metabolites between the two groups, with 367 differentially expressed metabolites up-regulated compared with the control group and 316 differentially expressed metabolites down-regulated compared with the control group. It is mainly Phosphatidic Acid (Lte4/8: 0) (+ 218%), Omeprazole Sulphone (-38%), and 2-(Propylthio) Nicotinic Acid (2-propyl thionicotinic acid) (-58%), Gein (salicyricetin) (-47%) and so on. Pathway enrichment analysis showed that the differential metabolites in AP patients were mainly concentrated in citric acid cycle, arginine biosynthesis and glycerophospholipid metabolism pathways.Conclusion:Serum metabolites in AP patients change significantly, including citric acid cycle, arginine biosynthesis, glycerophospholipid metabolism.

Objective:To establish and evaluated a logistic regression model for predicting the acute biliary pancreatitis (ABP) based on liver-injury related indexes.Methods:Clinical data of 210 patients diagnosed with acute pancreatitis (AP) at the Affiliated Hospital of Jiangnan University from October 2020 to December 2022 were retrospectively analyzed, including 113 males and 97 females, with a median age of 52 years (range, 43 to 58). Among these, 88 were diagnosed with ABP and 122 with acute non-biliary pancreatitis (ANBP). Additionally, a test cohort was created using data from 101 AP patients diagnosed between January and December 2023, including 60 males and 41 females, with a median age of 53 years (range, 43 to 63). Based on the original dataset, univariate and multivariate logistic regression analyses were conducted to identify the factors influencing ABP. A prediction probability formula (Pre) was then established based on the multivariate results. The effectiveness of each indicator in predicting ABP was evaluated using the receiver operating characteristic (ROC) curve. The ROC curve analysis determined the optimal cutoff value of Pre, which was subsequently used to diagnose ABP and ANBP in the test cohort.Results:Multivariate logistic regression analysis showed the factors influencing ABP include direct bilirubin (DBIL), alanine aminotransferase (ALT), aspartate aminotransferase (AST), cholinesterase (CHE), and fibrinogen (FIB). Based on the multivariate analysis results, the prediction probability formula (Pre) for ABP was established as follows: P=1/{1+ exp[-(4.807+ 0.134×DBIL-1.859×AST/ALT-0.0003×CHE-0.387×FIB)]}. ROC curve analysis revealed that the area under the curve (AUC) for Pre in predicting ABP was 0.858, with an optimal cutoff value of 0.56, at which the sensitivity was 69.3% and the specificity was 91.0%. Using the cutoff value of 0.56 for Pre, ABP was diagnosed when Pre≥0.56 and ANBP was diagnosed when Pre<0.56. This criterion was applied to diagnose patients in the test cohort, where the sensitivity and specificity of Pre for diagnosing ABP were 86.1% and 92.3%, respectively.Conclusion:The logistic regression model based on liver injury-related indicators is a valuable tool for clinically assessing the incidence of ABP.

Objective:To analyze the changes of serum metabolites in patients with acute pancreatitis (AP) by non-targeted metabolomics method.Methods:Serum samples and clinical data of 15 AP patients hospitalized in the Affiliated Hospital of Jiangnan University from August to September 2024 were collected and included in the AP group, including 9 males and 6 females, aged (55.4±15.3) years. The serum and clinical data of 25 patients with colon polyps in the same hospital during the same period of time were collected, including 15 males and 10 females, aged (61.2±11.5) years, and were included in the control group. Serum metabolomic detection was performed using the ultra-high performance liquid chromatography tandem Fourier transform mass spectrometer. The modeling method was orthogonal partial least square discriminant analysis, and principal component analysis was performed on the data matrix to screen the differential metabolites in serum of AP patients. The Kyoto Encyclopedia database of Genes and Genomes was used to annotate differential metabolites, and the pathway of differential metabolite enrichment was analyzed by software.Results:The principal component analysis showed that the contribution ratio of the first principal component was 15.1%, the proportion of the second principal component was 10.8%, and the total proportion of the two was 25.9%. In principal component analysis, two groups of samples can be clearly distinguished and show obvious clustering characteristics. According to the analysis of OPLS-DA model, there were significant differences in serum metabolic profiles between AP group and control group. There were 683 differentially expressed metabolites between the two groups, with 367 differentially expressed metabolites up-regulated compared with the control group and 316 differentially expressed metabolites down-regulated compared with the control group. It is mainly Phosphatidic Acid (Lte4/8: 0) (+ 218%), Omeprazole Sulphone (-38%), and 2-(Propylthio) Nicotinic Acid (2-propyl thionicotinic acid) (-58%), Gein (salicyricetin) (-47%) and so on. Pathway enrichment analysis showed that the differential metabolites in AP patients were mainly concentrated in citric acid cycle, arginine biosynthesis and glycerophospholipid metabolism pathways.Conclusion:Serum metabolites in AP patients change significantly, including citric acid cycle, arginine biosynthesis, glycerophospholipid metabolism.

The current status of exoskeletons was introduced in enhancing individual soldier's battlefield rescue capabilities,promoting the integrated use of battlefield rescue equipment,protecting medical personnel on the battlefield and assisting injured soldiers in rehabilitation training.The challenges of exoskeletons faced in human-machine interaction,power supply endurance,heavy overall structure,restricted movement and high cost were analyzed when applied to medical service support,and some suggestions were proposed accordingly including enhancing technology research and development,integrated application,communication and cooperation and personnel training.References were provided for the application of exoskeletons in China's medical service support.[Chinese Medical Equipment Journal,2024,45(3):71-75]