ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

Objective:To investigate gut microbiota differences between individuals with and without colorectal adenoma(CRA)and to identify gut microbes associated with CRA.Methods:This cross-sectional study analyzed the gut microbiota of 100 patients with CRA and 68 individuals without CRA(aged 40-75 years)who underwent colonoscopies between March 2021 and March 2022 at Tianjin Nankai Hospital.Fecal samples were sequenced for the V3-V4 region of the bacterial 16S rRNA gene using the Illumina NovaSeq platform.Results:Compared to the non-CRA group,the CRA group exhibited reduced relative abundances of identified and unidentified Lachnospiraceae,with increased Faecalibacterium and Streptococcus.In the non-CRA group,the relative abundances of Coprococcus,unidentified Clostridiaceae,and Clostridium were higher.LEfSe analysis revealed significant enrichment of Gammaproteobacteria,Proteobacteria,Enterobacteriales,and Faecalibacterium in the CRA group,while the non-CRA group was enriched for Moraxellaceae,Acinetobacter,and Anaerostipes.Conclusions:These findings suggest a discernible disparity in the gut microbiota structure between CRA patients and individuals without adenoma.The enrichment of potential pathogenic taxa,such as Faecalibacterium and Streptococcus,in the CRA group suggests a possible association with adenoma development.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

The classification of stoma skin barriers varies based on their specific features. The curvature design of convex skin barriers provides a secure and effective seal for patients with flat, retracted stomas or peristomal skin folds. The secure sealing ability of convex skin barriers is attributed to several critical structural components. Although convex skin barriers offer many clinical advantages, there is currently no unified standard for measuring their characteristics, resulting in confusion among healthcare professionals when selecting stoma care products. To address this issue, the 2021 International Stoma Care Expert Meeting proposed the Expert Consensus on Characteristics of Convex Skin Barriers and Clinical Application, which clearly defines five essential properties and clinical application guidelines for convex barriers. However, as most consensus contributors are from Europe and North America, its applicability in Chinese healthcare settings may be limited. Therefore, this paper provides a detailed interpretation of the five characteristics and clinical application statements of convex skin barriers, aiming to offer practical guidance to clinical nurses in selecting appropriate convex products and managing stoma-related complications.

Objective:To explore the clinical effects of sterilization of vas deferens by irrigation in clinic.Methods:Eighty-six male patients with voluntary sterilization were divided into control group(usual vasectomy,n=50)and observation group(sterilization of vas deferens by irrigation,n=36).The age,testicular volume,preoperative average concentration of spern,serum testosterone level,recovery duration evaluated by Artificial Obstruction Azoospermia(AOA)and degree of satisfaction were compared between the two groups of patients.Results:There were significant differences in recovery duration,degree of satisfaction between the two groups(P＜0.05).And there was no significant difference in age([32.0±5.5]years vs[31.0±6.3]years),testicular volume([16.0±4.8]mL vs[17.0±4.4]mL),preopera-tive average concentration of sperm([39.6±20.2]× 106/mL vs[40.2±22.6]× 106/mL)and levels of blood testosterone([4.3±0.8]ng/mL vs[4.4±0.8]ng/mL).There was significant difference in patency rate between the two sides of testicular ducts(91.7％vs 83.3％,P＜0.05).Conclusion:The method of sterilization of vas deferens by irrigation is worth popularizing in clinic.

Objective:In order to reduce the trauma associated with fetal cardiopulmonary bypass(F-CPB), Our team plans to develop a minimally invasive F-CPB through a small incision in the right axilla. The efficacy of this technique will be verified by using a big experimental animal model, thereby laying the foundation for fetal cardiac surgery supported by F-CPB in the future.Methods:Ten pregnant sheep were divided into F-CPB group(n=5) and control group(n=5). After fasting for 24 h, fetal lambs in the F-CPB group underwent a right axillary incision to establish F-CPB running for 1 h; The control group of fetal lambs only expose heart 1 h without F-CPB. Collect blood sample for laboratory test at the CPB vehicle before(T0), 30 min(T1), and 1 h after F-CPB running(T2) for the F-CPB group and through Superior Vena Cava before(T0), 30 min(T1), and 1 h after F-CPB running(T2) for the control group.Results:The blood routine indicators such as RBC, HCT, and Hb in the F-CPB group of fetal lambs decreased significantly during F-CPB, and their distribution showed significant statistical differences compared with the control group( P<0.05). There were no significant statistical differences in blood gas indicators such as pH, PO 2, PCO 2, and lactate concentration between the F-CPB group and the control group( P>0.05). There was no statistically significant difference in the concentration of cTnI in fetal lamb serum at each time point( P>0.05). There were significant statistical differences( P<0.05) in the distribution of fetal lamb Alb, γ-GGT, CK concentration and cholesterol concentration at various time points in the F-CPB group compared with the control group in liver function examination. In addition, the distribution of BUN in fetal lambs showed a significant difference between the two groups( P=0.006). Conclusion:A minimally invasive F-CPB via small incision in the right axilla is safe and feasible. The experimental animal model has demonstrated that this technique has minimal impact on the vital organ functions and internal environment of fetal lambs, thereby laying the foundation for clinical fetal cardiac surgery in the future.

ObjectiveUlcerative colitis is a prevalent immunoinflammatory disease. Th17/Treg cell imbalance and gut microbiota dysregulation are key factors in ulcerative colitis pathogenesis. The actin cytoskeleton contributes to regulating the proliferation, differentiation, and migration of Th17 and Treg cells. Wdr63, a gene containing the WD repeat domain, participates in the structure and functional modulation of actin cytoskeleton. Recent research indicates that WDR63 may serve as a regulator of cell migration and metastasis via actin polymerization inhibition. This article aims to explore the effect of Wdr63 deletion on Th17/Treg cells and ulcerative colitis. MethodsWe constructed Wdr63^-/- mice, induced colitis in mice using dextran sulfate sodium salt, collected colon tissue for histopathological staining, collected mesenteric lymph nodes for flow cytometry analysis, and collected healthy mouse feces for microbial diversity detection. ResultsCompared with wild-type colitis mice, Wdr63^-/- colitis mice had a more pronounced shortening of colonic tissue, higher scores on disease activity index and histological damage index, Treg cells decreased and Th17 cells increased in colonic tissue and mesenteric lymph nodes, a lower level of anti-inflammatory cytokine IL-10, and a higher level of pro-inflammatory cytokine IL-17A. In addition, WDR63 has shown positive effects on maintaining intestinal microbiota homeostasis. It maintains the balance of Bacteroidota and Firmicutes, promoting the formation of beneficial intestinal bacteria linked to immune inflammation. ConclusionWdr63 deletion aggravates ulcerative colitis in mice, WDR63 inhibits colonic inflammation likely by regulating Th17/Treg balance and maintains intestinal microbiota homeostasis.

Objective To explore the feasibility and corresponding implementation methods of constructing a sample resource bank based on individual-level data of completed clinical trials and using it to construct external controls for drug/device clinical trials.Methods Taking the pre-marketing clinical trial of transcatheter active valve replacement(TAVR)for the treatment of aortic valve stenosis as an example,the individual-level databases of multiple trials were standardized to form a sample bank.The original data of any trial in the sample bank were selected as the experimental group,and the remaining samples were selected as the control group.The potential confounding was handled by using the propensity score matching and stratification methods to clarify the process of constructing external controls based on the sample bank of individual-level data of clinical trials.Results This study included individual-level data of single-group trials of 4 TAVR devices,with a total of 569 subjects(59.2%male).The number of subjects in Trials 1 to 4 was 120,120,163,and 166,respectively.Propensity score matching enabled the matching of 113,117,125,and 147 subjects with comparable or similar characteristics from individual-level data from other trials,respectively,demonstrating a high matching success rate.The PS score distribution plot after stratification showed that the proportions of subjects in the experimental and control groups in strata 1 to 5 in scheme 1 were 4/103,11/103,22/92,32/87,and 51/64,respectively.For all constructed external controlled trials,a certain number of control samples with similar baseline characteristics to the experimental groups were distributed within each propensity score stratum.The results of the simulation test also reflected the potential differences between different devices in the 12-month all-cause mortality rate.Conclusions The sample bank constructed with individual-level data from clinical trials,as a high-quality data source,can serve as a source of external control for single-arm trials in the same field,and as a useful supplement to the external control scenario of real-world evidence to support drug and device development.At the same time,targeted research on research methods and bias control measures in related fields is also needed.

This study investigated the drug resistance and genetic relationships among strains co-existing in animals,the environ-ment,and the living quarters of employees at large-scale pig farms in certain regions of Shandong Province,to provide a scientific ba-sis for elucidating the transmission mechanisms of drug-resistant bacteria through bacterial traceability analysis.Samples were col-lected from two pig farms,and bacteria were isolated and purified.The species of the isolated strains were identified via 16S rRNA gene sequencing.Antimicrobial susceptibility testing was conducted with a VITEK-2 Compact system and the disk diffusion method for strains present in pigs,the environment,and living areas.Furthermore,whole-genome sequencing was performed on the Illumina Miniseq platform to annotate drug resistance genes,and multilocus sequence typing(MLST)and core genome single nucleotide poly-morphism(cgSNP)analyses were used to trace the resistant strains.Three species—Staphylococcus aureus,Pseudomonas aeruginosa,and Bacillus cereus—were isolated and cultured from animals,the environment,and employee living areas,and their distributions were analyzed.These strains exhibited diverse drug resistance spectra and genetic diversity.Additionally,the strains displayed highly consistent resistance profiles,resistance genes,ST types,and SNP loci in pig urine,soil both inside and outside the facility,human drinking water,and the cafeteria and dormitories.Our findings indicated a potential risk of transmission of opportunistic pathogens be-tween the pig farming area and the living quarters.Particular attention should be paid to the environmental transmission of methicillin-resistant Staphylococcus aureus.