In-fusion cloning technology,as a revolutionary and efficient molecular biology tool,has been applied in multiple research fields such as basic biology,biotechnology,and biomedicine.In this article,we introduce a teaching reform project suitable for undergraduate students in the course of"Molecular Bi-ology Laboratory",which utilizes in-Fusion cloning technology to construct a prokaryotic expression vector for alkaline phosphatase mutant genes.Through specific teaching cases,we systematically explored the design and implementation of experimental projects,and focused on analyzing the key and difficult points of the teaching content.Our teaching practice has found that the implementation of this educational re-form project has achieved very good results in enhancing students' core biological literacy,bioinformatics skills,research thinking,and innovation abilities.At the same time,the application of this technology can significantly improve the quality of experimental teaching,providing new ideas and practical refer-ences for promoting the reform and innovation of National First-Class Courses.

In-fusion cloning technology,as a revolutionary and efficient molecular biology tool,has been applied in multiple research fields such as basic biology,biotechnology,and biomedicine.In this article,we introduce a teaching reform project suitable for undergraduate students in the course of"Molecular Bi-ology Laboratory",which utilizes in-Fusion cloning technology to construct a prokaryotic expression vector for alkaline phosphatase mutant genes.Through specific teaching cases,we systematically explored the design and implementation of experimental projects,and focused on analyzing the key and difficult points of the teaching content.Our teaching practice has found that the implementation of this educational re-form project has achieved very good results in enhancing students' core biological literacy,bioinformatics skills,research thinking,and innovation abilities.At the same time,the application of this technology can significantly improve the quality of experimental teaching,providing new ideas and practical refer-ences for promoting the reform and innovation of National First-Class Courses.

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.

Liposomes serve as critical carriers for drugs and vaccines, with their biological effects influenced by their size. The microfluidic method, renowned for its precise control, reproducibility, and scalability, has been widely employed for liposome preparation. Although some studies have explored factors affecting liposomal size in microfluidic processes, most focus on small-sized liposomes, predominantly through experimental data analysis. However, the production of larger liposomes, which are equally significant, remains underexplored. In this work, we thoroughly investigate multiple variables influencing liposome size during microfluidic preparation and develop a machine learning (ML) model capable of accurately predicting liposomal size. Experimental validation was conducted using a staggered herringbone micromixer (SHM) chip. Our findings reveal that most investigated variables significantly influence liposomal size, often interrelating in complex ways. We evaluated the predictive performance of several widely-used ML algorithms, including ensemble methods, through cross-validation (CV) for both liposome size and polydispersity index (PDI). A standalone dataset was experimentally validated to assess the accuracy of the ML predictions, with results indicating that ensemble algorithms provided the most reliable predictions. Specifically, gradient boosting was selected for size prediction, while random forest was employed for PDI prediction. We successfully produced uniform large (600 nm) and small (100 nm) liposomes using the optimised experimental conditions derived from the ML models. In conclusion, this study presents a robust methodology that enables precise control over liposome size distribution, offering valuable insights for medicinal research applications.

This study employed 16S r RNA gene high-throughput sequencing and metabolomics to explore the mechanism of Angelicae Dahuricae Radix polysaccharides(RP) in the treatment of ulcerative colitis(UC). A mouse model of UC was induced with 2. 5% dextran sulfate sodium. The therapeutic effects of RP on UC in mice were evaluated based on changes in body weight, disease activity index( DAI), and colon length, as well as pathological changes. RT-qPCR was performed to assess the m RNA levels of interleukin(IL)-6, IL-1β, tumor necrosis factor(TNF)-α, myeloperoxidase(MPO), mucin 2(Muc2), Occludin, Claudin2, and ZO-1 in the mouse colon tissue. ELISA was employed to measure the expression of IL-1β and TNF-α in the colon tissue. The intestinal permeability of mice was evaluated by the fluorescent dye permeability assay. Immunohistochemistry was employed to detect the expression of Muc2 and occludin in the colon tissue. Changes in gut microbiota and metabolites were analyzed by 16S r RNA sequencing and ultra-high-performance liquid chromatography coupled with quadrupole-orbitrap mass spectrometry( UPLC-Q-Exactive Plus Orbitrap MS), respectively. The results indicated that low-dose RP alleviated general symptoms, reduced colonic inflammation and intestinal permeability, and promoted Muc2 secretion and tight junction protein expression in UC mice. In addition, low-dose RP increased gut microbiota diversity in UC mice and decreased the relative abundance of harmful bacteria such as Ochrobactrum and Streptococcus. Twenty-seven differential metabolites were identified in feces, and low-dose RP restored the levels of disturbed metabolites. Notably, arginine and proline metabolism were the most significantly altered amino acid metabolic pathways following lowdose RP intervention. In conclusion, RP can ameliorate general symptoms, inhibit colonic inflammation, and maintain intestinal mucosal barrier integrity in UC mice by modulating gut microbiota composition and arginine and proline metabolism.
Animals ; Gastrointestinal Microbiome/drug effects* ; Colitis, Ulcerative/genetics* ; Mice ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Polysaccharides/administration & dosage* ; Angelica/chemistry* ; Humans ; Colon/metabolism* ; Disease Models, Animal ; Mucin-2/metabolism* ; Tumor Necrosis Factor-alpha/metabolism*

AIM To evaluate the quality of Croci Stigma from different producing areas.METHODS The analysis was performed on a 25 ℃ thermostatic Waters Acquity UPLC HSS T3 column(2.1 mm× 100 mm,1.8μm),with the mobile phase comprising of 0.1％phosphoric acid-acetonitrile flowing at 0.35 mL/min in a gradient elution manner,and the detection wavelengths were set at 254,440 nm.The UPLC fingerprints were established,after which orthogonal partial least squares discriminant analysis was performed,picrocrocin,crocin-Ⅰ,crocin-Ⅱ,crocin-Ⅲ,crocin-Ⅳ contents and chromaticity values(L*,a*,b*,E*ab)were determined,Pearson correlation analysis was adopted in the investigation of correlations between chromaticity values and internal constituent contents.RESULTS There were 14 common peaks in the fingerprints for 22 batches of medicinal materials with the similarities of more than 0.98.Various batches of medicinal materials were clustered into 2 types,7 quality difference components were screened.crocin-Ⅰ content in medicinal materials from different producing areas demonstrated significant differences(P＜0.05);the redder the color of medicinal material,the higher the contents of crocins.Picrocrocin,crocin-Ⅰ,crocin-Ⅱ,crocin-Ⅳ contents displayed highly significant correlations with colorimetric values(P＜0.01),while crocin-Ⅲ content exhibited no significant correlation with the latter(P＞0.05).CONCLUSION This accurate and reliable method can provide references for the quality control and color-quality relationship elucidation of Croci Stigma.

OBJECTIVE: Acupuncture therapies are known for their effectiveness in treating a variety of gastric diseases, although the mechanisms underlying these effects are not fully understood. This study tested the effectiveness of electroacupuncture (EA) at acupoints Zhongwan (RN12) and Weishu (BL21) for managing gastric motility disorder (GMD) and investigated the underlying mechanisms involved. METHODS: A GMD model was used to evaluate the impact of EA on various aspects of gastric function including the amplitude of gastric motility, electrogastrogram, food intake, and the rate of gastric emptying. Immunofluorescence techniques were used to explore the activation of spinal neurons by EA, specifically examining the presence of cholera toxin B subunit (CTB)-positive neurons and fibers emanating from acupoints RN12 and BL21. The stimulation of γ-aminobutyric acid (GABA)-ergic neurons in the spinal dorsal horn, the inhibition of sympathetic preganglionic neurons in the spinal lateral horn, and their collective effects on the activity of sympathetic nerves were examined. RESULTS: EA at RN12 and BL21 significantly improved gastric motility compromised by GMD. Notably, EA activated spinal neurons, with CTB-positive neurons and fibers from RN12 and BL21 being detectable in both the dorsal root ganglia and the spinal dorsal horn. Further analysis revealed that EA at these acupoints not only stimulated GABAergic neurons in the spinal dorsal horn but also suppressed sympathetic preganglionic neurons in the spinal lateral horn, effectively reducing excessive activity of sympathetic nerves triggered by GMD. CONCLUSION EA treatment at RN12 and BL21 effectively enhances gastric motility in a GMD model. The therapeutic efficacy of this approach is attributed to the activation of spinal neurons and the modulation of the spinal GABAergic-sympathetic pathway, providing a neurobiological foundation for the role of acupuncture in treating gastric disorders. Please cite this article as: Zhang MT, Liang YF, Dai Q, Gao HR, Wang H, Chen L, Huang S, Wang XY, Shen GM. A spinal neural circuit for electroacupuncture that regulates gastric functional disorders. J Integr Med. 2025; 23(1): 56-65.
Electroacupuncture ; Animals ; Male ; Acupuncture Points ; Stomach Diseases/physiopathology* ; Rats, Sprague-Dawley ; Gastrointestinal Motility ; Rats ; Gastric Emptying ; Neurons ; Spinal Cord ; Stomach/physiopathology*

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

AIM To evaluate the quality of Croci Stigma from different producing areas.METHODS The analysis was performed on a 25 ℃ thermostatic Waters Acquity UPLC HSS T3 column(2.1 mm× 100 mm,1.8μm),with the mobile phase comprising of 0.1％phosphoric acid-acetonitrile flowing at 0.35 mL/min in a gradient elution manner,and the detection wavelengths were set at 254,440 nm.The UPLC fingerprints were established,after which orthogonal partial least squares discriminant analysis was performed,picrocrocin,crocin-Ⅰ,crocin-Ⅱ,crocin-Ⅲ,crocin-Ⅳ contents and chromaticity values(L*,a*,b*,E*ab)were determined,Pearson correlation analysis was adopted in the investigation of correlations between chromaticity values and internal constituent contents.RESULTS There were 14 common peaks in the fingerprints for 22 batches of medicinal materials with the similarities of more than 0.98.Various batches of medicinal materials were clustered into 2 types,7 quality difference components were screened.crocin-Ⅰ content in medicinal materials from different producing areas demonstrated significant differences(P＜0.05);the redder the color of medicinal material,the higher the contents of crocins.Picrocrocin,crocin-Ⅰ,crocin-Ⅱ,crocin-Ⅳ contents displayed highly significant correlations with colorimetric values(P＜0.01),while crocin-Ⅲ content exhibited no significant correlation with the latter(P＞0.05).CONCLUSION This accurate and reliable method can provide references for the quality control and color-quality relationship elucidation of Croci Stigma.

Liposomes serve as critical carriers for drugs and vaccines,with their biological effects influenced by their size.The microfluidic method,renowned for its precise control,reproducibility,and scalability,has been widely employed for liposome preparation.Although some studies have explored factors affecting liposomal size in microfluidic processes,most focus on small-sized liposomes,predominantly through experimental data analysis.However,the production of larger liposomes,which are equally significant,remains underexplored.In this work,we thoroughly investigate multiple variables influencing liposome size during microfluidic preparation and develop a machine learning(ML)model capable of accurately predicting liposomal size.Experimental validation was conducted using a staggered herringbone micromixer(SHM)chip.Our findings reveal that most investigated variables significantly influence liposomal size,often interrelating in complex ways.We evaluated the predictive performance of several widely-used ML algorithms,including ensemble methods,through cross-validation(CV)for both lipo-some size and polydispersity index(PDI).A standalone dataset was experimentally validated to assess the accuracy of the ML predictions,with results indicating that ensemble algorithms provided the most reliable predictions.Specifically,gradient boosting was selected for size prediction,while random forest was employed for PDI prediction.We successfully produced uniform large(600 nm)and small(100 nm)liposomes using the optimised experimental conditions derived from the ML models.In conclusion,this study presents a robust methodology that enables precise control over liposome size distribution,of-fering valuable insights for medicinal research applications.