Irritable bowel syndrome （IBS） is a functional bowel disorder characterized primarily by abdominal pain and altered defecation habits. In recent years， traditional Chinese medicine （TCM） has made progress in multiple aspects of IBS research and treatment， including syndrome distribution， development of TCM formulas， clinical efficacy evaluation， external therapies， and psychosocial regulation. However， it still faces challenges such as over-reliance on symptomatic manifestations rather than biomarkers for diagnostic criteria， and the lack of high-quality evidence-based data supporting the efficacy of TCM formulas in treating IBS. This paper proposed that TCM diagnosis and treatment of IBS should adhere to the strategy of integrating the holistic concept with syndrome differentiation and treatment， combining TCM external therapies such as acupuncture， moxibustion and acupoint application）， and emphasizing individualized diagnosis and treatment for psychosomatic abnormalities. Future research should integrate multi-omics technologies， artificial intelligence and other methods to deepen the understanding of the pathogenesis of IBS and the mechanisms of TCM formulas， so as to promote the standardization and internationalization of TCM in the diagnosis and treatment of IBS.

ObjectiveTo investigate the ability of clinically isolated， Helicobacter pylori （H. pylori）-specific gene polymerase chain reaction （PCR）-positive gastric， vaginal， and fecal Candida to release H. pylori. MethodsResuscitate 4 strains of H. pylori -specific 16S rDNA and ureA gene PCR-positive Candida strains isolated in laboratory from clinical sources， including 1 strain of gastric Candida， 1 strain of fecal Candida， 2 strains of vaginal Candida and the standard Candida albicans strain ATCC10231 （Ca10231）. The presence of H. pylori-specific ureA in the 5 strains of Candida isolates was confirmed by PCR. The aforementioned strains of Candida and H.pylori were inoculated into urea medium and cultured in a constant temperature incubator at 37 ℃. The color change of the medium was observed daily. A change in the medium's color from yellow to red indicated the presence of urease activity. Then， the five strains of Candida and H. pylori were co-incubated with the magnetic beads coated with H. pylori antibodies respectively. Scanning electron microscopy （SEM） was employed to observe the presence of bacilli adsorbed on the surface of the magnetic beads. PCR was used to detect the presence of H.pylori-specific 16S rDNA and ureA genes on magnetic beads. ResultsThe PCR analysis of the ureA gene in the four Candida isolates was positive， whereas the Ca10231 strain tested negative. Upon culturing the four Candida isolates on urea medium， the medium color changed from yellow to red which was determined to be urease positive， while the medium containing Ca10231 remained unchanged， which was urease negative. SEM revealed that bacilli could be observed on the surface of magnetic beads co-incubated with the 4 strains of Candida of clinical origin and H.pylori isolate. Specifically， PCR testing of the magnetic beads co-incubated with one vaginal Candida， one gastric Candida and H.pylori isolate showed positive results for the 16S rDNA and ureA genes of H. pylori； however， the PCR tests for the two genes were negative for the magnetic beads co-incubated with the other two Candida isolate. ConclusionThis study demonstrates that H. pylori-specific genes Candida can release H. pylori.

Based on plasma lipidomics combined with machine learning approaches, this study aimed to screen molecular biomarkers for the diagnosis of early-stage lung cancer in elderly patients and to evaluate their diagnostic performance.

A nodule in the right middle lobe of the lung was treated by a combination of cone-beam CT,three-dimensional registration for fusion imaging,and electromagnetic navigation bronchoscopy-guided thermal ablation.The procedure lasted for 90 min,with no significant bleeding observed under the bronchoscope.The total radiation dose during the operation was 384 mGy.The patient recovered well postoperatively,with only a small amount of blood in the sputum and no pneumothorax or other complications.A follow-up chest CT on the first day post operation showed that the ablation area completely covered the lesion,and the patient was discharged successfully.
Humans ; Bronchoscopy/methods* ; Catheter Ablation/methods* ; Cone-Beam Computed Tomography ; Electromagnetic Phenomena ; Imaging, Three-Dimensional ; Lung Neoplasms/diagnostic imaging* ; Tomography, X-Ray Computed

Objective:Based on the best evidence, formulate the review indicators to promote the initiation and establishment of maternal lactation and carry out clinical review, analyze the barriers and promoting factors of the clinical application of evidence, and formulate countermeasures.Methods:Evidence-based nursing research was used to identify clinical problems, build evidence-based group, systematically search, evaluate and synthesize evidence. On September 1,2023 to December 31 in Affiliated Hospital of Jiangsu University document and delivery of maternal investigation, in Ottawa research application mode as a guide, based on the evidence to review indicators and review method, clear clinical status and evidence gap, combined with the stakeholders interview, using content analysis to analyze barriers and promoting factors, to formulate action countermeasures.Results:In this study, 140 pregnant women were finally included for clinical review, aged from 22 to 42 (30.13 ± 3.69) years. A total of 23 pieces of best evidence were incorporated, leading to the establishment of 29 review indicators. Among these, 20 review indicators showed compliance rates below 60%. The main obstacles based on the results of review and interviews with stakeholders: the evidence content covered perinatal stages but lacked specificity and practical applicability; nurses had insufficient knowledge and faced increased workloads; pregnant/postpartum women lacked essential knowledge and skills, with delayed resolution of lactation issues; the practice environment lacked evidence-based implementation protocols, specialized assessment tools, and professional lactation consultant teams, etc. Promoting factors: the project team had rich experience in evidence transformation; the reform aligned with national policies, high engagement from departmental leaders, and standardized management systems for evidence-based projects in the nursing department; strong motivation among pregnant/postpartum women; the hospital was an infant-friendly hospital with talents needed for evidence transformation.Conclusions:There is a big gap between the clinical status and the evidence of promoting the initiation and establishment of lactation, so nursing staff should make full use of the promoting factors and formulate countermeasures according to the obstacle factors, so as to provide reference for promoting the initiation of lactation and the establishment of relevant evidence to clinical transformation.

Objective:To analyze the correlation of bone mineral density (BMD) , serum transforming growth factor β1 (TGF- β1) , and retinol-binding protein 4 (RBP4) with osteoporosis in gestational diabetes mellitus (GDM) . Methods:A total of 180 GDM patients admitted to Department of Gynecology, Second Hospital of Tianjin Medical University from Jan. 2022 to Jan. 2024 were included as the observation group, and 30 healthy pregnant women undergoing examination at the same time were included into the control group. BMD [stiffness index (SI) , broadband ultrasound attenuation (BUA) , speed of sound (SOS) ], serum TGF-β1, and RBP4 levels were compared between the two groups; GDM women with complicated with osteoporosis were included in the osteoporosis subgroup, and pregnant women without osteoporosis were included in the non-osteoporosis subgroup. BMD, serum TGF- β1 and RBP4 levels were compared between the two groups, and the relationship among bone mineral density and serum TGF- β1, RBP4 was analyzed by Pearson correlation. Receiver operating characteristic curve (ROC) curve was drawn to evaluate the diagnostic value of serum TGF- β1 and RBP4 levels in GDM complicated with osteoporosis. Results:The observation group had significantly higher levels of serum TGF- β1 and RBP4 than the control group, while lower BUA, SOS and SI ( t=99.04, 28.48, 4.10, 3.54, 6.29, P < 0.05) ; Among 180 pregnant women with GDM, 38 cases had osteoporosis and 142 cases did not have osteoporosis. The osteoporosis subgroup had significantly higher serum TGF- β1 and RBP4 levels than the other subgroup, while BMD indexes such as BUA, SOS and SI were significantly lower ( t=3.35, 3.48, 3.77, 2.85, 3.41, P < 0.05) ; Pearson correlation analysis showed that BMD indexes, such as BUA, SOS and SI, were significantly correlated with serum TGF- β1 and RBP4 in pregnant women with GDM ( r=-0.61, 0.58, -0.60, -0.58, -0.60, -0.63, P<0.05) ; The area under the curve (AUC) of TGF- β1, RBP4 and combined detection of GDM women with osteoporosis was 0.572, 0.653 and 0.659, respectively. Conclusions:In GDM women complicated with osteoporosis, the levels of serum TGF- β1 and RBP4 increase significantly, and BMD decreases significantly. Serum TGF- β1 and RBP4 in GDM women are closely related to BMD index, which can provide early diagnosis basis for GDM complicated with osteoporosis.

Objective In view of the potential threat of adverse drug reaction(ADR)to patients'health and the limitations of traditional monitoring methods,this study investigates the construction method of an ADR knowledge graph based on a knowledge-driven technology path to promote the intelligent upgrading of pharmacovigilance field.Methods In this study,an adverse drug reaction knowledge base was established,and the data within the knowledge base were preprocessed.The BERT-CRF model was utilized to identify and extract the relevant entities,relationships and attribute information,and knowledge alignment was carried out by combining the rule method and statistical method.The knowledge fusion data was stored in the Neo4j graph database to construct the knowledge graph.Results Based on the established knowledge base,this study explored the method of constructing knowledge graph of adverse drug reaction by knowledge-driven technology,laying the groundwork for data mining and the development of intelligent auxiliary system tools based on knowledge graph.Conclusions The study on the construction method of an ADR knowledge graph based on a knowledge-driven technology path provides a new perspective and technical path for the intelligent upgrading of pharmacovigilance field.It holds important theoretical and practical significance for improving drug safety,protecting patients'health,and promoting the healthy development of pharmaceutical industry.

Objective:To conduct a scoping review of studies related to social competence intervention in pediatric brain tumor survivors, aiming to identify the contents, outcome and effects of Social competence intervention and provide a reference for future.Methods:Based on the scope review research framework developed by Arksey and O′Malley, a systematic search was conducted in Web of Science, PubMed, Cochrane Library, Embase, China National Knowledge Infrastructure, VIP, Wanfang and China Biology Medicine disc until 30 July, 2024. The included studies were summarized and analyzed.Results:A total of 10 pieces of literature were included, including 5 quasi-experimental studies, 3 mixed-method studies, 1 randomize controlled trials, and 1 case study. The social competence intervention program included group social intervention, multimodal intervention, expressive art intervention, and peer intervention. Each program focused on training approximately 3-6 social skills. The intervention forms were all face-to-face interventions. The intervention duration was usually 8 weeks. Intervention had varying degrees of impact on social skills, clinical health outcomes, participation indicators and psychological status.Conclusions:Social competence interventions are safe and feasible for pediatric brain tumor survivors and demonstrate positive impacts on their social information processing abilities, social adaptation, and quality of life. Future research should actively explore and innovate new forms of social competence intervention based on China′s national conditions and cultural background, and develop comprehensive and personalized intervention plans.

Aim To investigate the protective effect of Vaccarin(Va)on epithelial-mesenchymal transition(EMT)in renal fibrosis model mice through regulating STAT3,and the underlying mechanism.Methods Left ureter ligation was used to establish a mouse model of unilateral ureteral obstruction(UUO);human kid-ney tubular epithelial(HK2)cells were induced to differentiate by transforming growth factor-β(TGF-β)in vitro.HE and Masson staining were used to observe the morphological changes of renal tissue;kits were used to detect the levels of BUN,Cr,IL-1β and IL-7 in mouse serum;CCK-8 was used to detect the effect of Va on the viability of HK2 cells;RT-PCR was used to detect the levels of inflammatory factors in HK2 cells;Western blot was used to detect the expression of STAT3,p-STAT3,E-cadherin,and α-SMA proteins in renal tissue and HK2 cells;to further investigate the regulation of Va on STAT3,JAK/STAT3 pathway acti-vator RO8191 was used to treat TGF-β-induced HK2 cells,and functional loss was detected.Results Va improved the pathological damage in UUO mice,inhibi-ted the levels of BUN,Cr and inflammatory factors;Va inhibited the phosphorylation of STAT3,upregulated E-cadherin,and downregulated α-SMA protein expres-sion;RO8191 counteracted the inhibitory effect of Va on the phosphorylation of STAT3.Conclusions Va inhibits the phosphorylation of STAT3 and the release of inflammatory factors,improves EMT,thus exerting an anti-renal fibrosis effect.

Objective To propose a dynamic early warning model based on machine learning methods and validate its predi-ctive efficacy so as to achieve precise assessment and early warning of mortality risk in patients with traumatic hypothermia.Methods Firstly,a total of 480 patients who met inclusion criteria were retrospectively selected from the eICU database and randomly divided into training and test sets at an 8∶2 ratio.Secondly,physiological parameters were extracted from these patients,and five machine learning algorithms including XGBoost,AdaBoost,LightGBM,logistic regression(LR)and random forest(RF)were employed respectively to develop dynamic mortality risk warning models for traumatic hypothermia patients,utilizing a 1-hour observation window.Thirdly,receiver operating characteristic curves(ROC)were plotted using the test set data and the effects of different warning windows on the model performance were analyzed by calculating the AUC.Finally,the interpretability of the models was analyzed using the SHapley Additive exPlanations(SHAP)algorithm to elucidate the contribution of each feature to predictive performance.Results The optimal warning window for the dynamic warning model constructed using the eICU database was 12 hours,and in case of 12-hour warning window the logistic regression model achieved the highest AUC of 0.935 and showed optimal predictive performance.The results of the interpretability analysis by the SHAP algorithm showed that body temperature was the feature that had the greatest impact on the model results,and its reduction was positively correlated with the increased risk of death.Conclusion The machine learning-based dynamic warning model for mortality risk in traumatic hypothermia patients enables real-time dynamic risk assessment,providing robust support for clinicians to identify the patient's condition changes at an early stage and references for the adjustment of clinical treatment programs.[Chinese Medical Equipment Journal,2025,46(3):9-14]