Objective: To investigate the objective characteristics of tongue manifestation in different stages of damp-heat syndrome in diabetic kidney disease (DKD). Methods: A cross-sectional study enrolled 134 patients with DKD G3-5 stages who met the diagnostic criteria for damp-heat syndrome in DKD. The patients were treated at Dongzhimen Hospital, Beijing University of Chinese Medicine, from May 2023 to January 2024. The patients were divided into three groups: DKD G3, DKD G4, and DKD G5 stage, with 53, 33, and 48 patients in each group, respectively. Clinical general data (gender, age, and body mass index) and damp-heat syndrome scores were collected from the patients. The YZAI-02 traditional Chinese medicine (TCM) AI Tongue Image Acquisition Device was used to capture tongue images from these patients. The accompanying AI Open Platform for TCM Tongue Diagnosis of the device was used to analyze and extract tongue manifestation features, including objective data on tongue color, tongue quality, coating color, and coating texture. Clinical data and objective tongue manifestation characteristics were compared among patients with DKD G3-5 based on their DKD damp-heat syndrome status. Results: No statistically significant difference in gender or body mass index was observed among the three patient groups. The DKD G3 stage group had the highest age (P<0.05). The DKD G3 stage group had a lower score for symptoms of poor appetite and anorexia(P<0.05) than the DKD G5 group. No statistically significant difference was observed in damp-heat syndrome scores among the three groups. Compared with the DKD G5 stage group, the DKD G3 stage group showed a decreased proportion of pale color at the tip and edges of the tongue (P<0.05). The DKD G4 stage group exhibited an increased proportion of crimson at the root of the tongue, a decreased proportion of thick white tongue coating at the root, a decreased proportion of pale color at the tip and edges of the tongue, an increased hue value (indicating color tone) of the tongue color in the middle, an increased brightness value (indicating color lightness) of the tongue coating color in the middle, and an increased thickness of the tongue coating (P<0.05). No statistically significant difference was observed in other tongue color proportions, color chroma values, body characteristics, coating color proportions, coating color chroma values, and coating texture characteristics among the three groups. Conclusion Tongue features differ in different stages of DKD damp-heat syndrome in multiple dimensions, enabling the inference that during the DKD G5 stage, the degree of qi and blood deficiency in the kidneys, heart, lungs, liver, gallbladder, spleen, and stomach is prominent. Dampness is more likely to accumulate in the lower jiao, particularly in the kidneys, whereas heat evil in the spleen and stomach is the most severe. These insights provide novel ideas for the clinical treatment of DKD.

Methods: Seventy-five patients with atlas fracture were included from January 2015 to December 2020. Based on the anatomy of the fracture line, atlas fractures were divided into three types. Each type was divided into two subtypes according to the fracture displacement. Unweighted Cohen kappa coefficients were applied to evaluate the reliability and reproducibility. Results: According to the new classification, 17 cases of type A1, 12 of type A2, seven of type B1, 13 of type B2, 12 of type C1, and 14 of type C2 were identified. The K-values of the interobserver and intraobserver reliability were 0.846 and 0.912, respectively, for the new classification. The K-values of interobserver reliability for types A, B, and C were 0.843, 0.799, and 0.898, respectively. The K-values of intraobserver reliability for types A, B, and C were 0.888, 0.910, and 0.935, respectively. The mean K-values of the interobserver and intraobserver reliability for subtypes were 0.687 and 0.829, respectively. Conclusions The new classification of atlas fractures can cover nearly all atlas fractures. This system is the first to evaluate the severity of fractures based on the C1 articular facet and fracture displacement and strengthen the anatomy ring of the atlas. It is concise, easy to remember, reliable, and reproducible.

Methods: Seventy-five patients with atlas fracture were included from January 2015 to December 2020. Based on the anatomy of the fracture line, atlas fractures were divided into three types. Each type was divided into two subtypes according to the fracture displacement. Unweighted Cohen kappa coefficients were applied to evaluate the reliability and reproducibility. Results: According to the new classification, 17 cases of type A1, 12 of type A2, seven of type B1, 13 of type B2, 12 of type C1, and 14 of type C2 were identified. The K-values of the interobserver and intraobserver reliability were 0.846 and 0.912, respectively, for the new classification. The K-values of interobserver reliability for types A, B, and C were 0.843, 0.799, and 0.898, respectively. The K-values of intraobserver reliability for types A, B, and C were 0.888, 0.910, and 0.935, respectively. The mean K-values of the interobserver and intraobserver reliability for subtypes were 0.687 and 0.829, respectively. Conclusions The new classification of atlas fractures can cover nearly all atlas fractures. This system is the first to evaluate the severity of fractures based on the C1 articular facet and fracture displacement and strengthen the anatomy ring of the atlas. It is concise, easy to remember, reliable, and reproducible.

Methods: Seventy-five patients with atlas fracture were included from January 2015 to December 2020. Based on the anatomy of the fracture line, atlas fractures were divided into three types. Each type was divided into two subtypes according to the fracture displacement. Unweighted Cohen kappa coefficients were applied to evaluate the reliability and reproducibility. Results: According to the new classification, 17 cases of type A1, 12 of type A2, seven of type B1, 13 of type B2, 12 of type C1, and 14 of type C2 were identified. The K-values of the interobserver and intraobserver reliability were 0.846 and 0.912, respectively, for the new classification. The K-values of interobserver reliability for types A, B, and C were 0.843, 0.799, and 0.898, respectively. The K-values of intraobserver reliability for types A, B, and C were 0.888, 0.910, and 0.935, respectively. The mean K-values of the interobserver and intraobserver reliability for subtypes were 0.687 and 0.829, respectively. Conclusions The new classification of atlas fractures can cover nearly all atlas fractures. This system is the first to evaluate the severity of fractures based on the C1 articular facet and fracture displacement and strengthen the anatomy ring of the atlas. It is concise, easy to remember, reliable, and reproducible.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Objective To explore clinical effect of modified Chinese-way technique under shoulder arthroscopy in treating massive rotator cuff tears.Methods From January 2019 to June 2022,22 patients with massive rotator cuff tears who underwent arthroscopic rotator cuff repair with improved Chinese-way technique,including 10 males and 12 females,aged from 46 to 76 years old with an average of(64.14±7.45)years old;the courses of disease ranged from 5 to 14 months with an average of(8.32±2.42)months;19 patients were complete repaired,and 3 patients were partial repaired.Visual analogue scale(VAS)and University of California at Los Angeles(UCLA)scale were used to evaluate pain and function of shoulder joint preopera-tively and 1 year postoperatively.Postoperative complications,the integrity of reconstructed tissue structure and the size of sub-acromial space were observed.Results All patients were followed up from 12 to 34 months with an average of(17.14±5.93)months.Re-tear were occurred in 4 patients during MRI follow-up,but clinical symptoms of patients were improved significant-ly and they were satisfied with the treatment,the others were no complications such as incision infection,peripheral nerve in-jury,loosening and falling off of internal fixation anchors.Preoperative and 1 year after operation VAS were(8.05±1.12)and(1.82±1.50),UCLA scores were(7.45±1.65)and(31.41±2.87)respectively,and the difference was statistically significant(P＜0.05).Conclusion The modified Chinese-way technique under shoulder arthroscopy for the massive rotator cuff tear could relieve pain obviously and recovery postoperative function well,with satisfactory curative effect.

Objective To explore the predictive value of soluble fms-like tyrosine kinase-1(sFlt-1)and leukotriene B4(LTB4)in patients with intracranial aneurysms for cerebral vasospasm(CVS)after interventional embolization.Methods A total of 98 patients with intracranial aneurysms admitted to our hospital from January 2019 to September 2023 were regarded as the observation group,and were divided into the CVS group(32 cases)and the non CVS group(66 cases)according to whether CVS occurred or not within 3 to 5 days after surgery;102 healthy examinees in our hospital were selected as the control group.Enzyme-linked immunosorbent assay was used to detect serum levels of sFlt-1 and LTB4;the influencing factors for CVS after interventional embolization of intracranial aneurysms were analyzed by Logistic regression analysis;the predictive value of serum sFlt-1 and LTB4 levels for the occurrence of CVS after interventional embolization of intracranial aneurysms was analyzed by receiver operating characteristic(ROC)curve.Results The serum levels of sFlt-1 and LTB4 of patients in the observation group were obviously higher than those in the control group,and the differences were statistically significant(P<0.05).The serum levels of sFlt-1 and LTB4,and the proportions of patients with postoperative blood pressure fluctuation range≥30 mmHg and Hunt-Hess grade Ⅲ in the CVS group were obviously higher than those in the non CVS group,and the differences were statistically significant(P<0.05).SFlt-1(OR:2.985;95%CI:1.684 to 5.291)and LTB4(OR:2.868;95%CI:1.581 to 5.204)were the independent risk factors for CVS after interventional embolization of intracranial aneurysms(P<0.05).The area under the curve(AUC)of sFlt-1 and LTB4 alone and in combination for predicting the occurrence of CVS after interventional embolization of intracranial aneurysms were 0.839,0.825,and 0.915,respectively,with sensitivity of 84.44%,87.59%,and 81.36%,and specificity of 74.26%,75.87%,and 90.98%,respectively.The AUC of the combination of the two was higher than those of sFlt-1 and LTB4 alone,and the differences were statistically significant(Z=2.150,2.546,P<0.05).Conclusion The serum levels of sFlt-1 and LTB4 in patients with CVS after interventional embolization of intracranial aneurysms are increased,and the combination of the two can serve as the important indicators for predicting CVS.

Objective To explore the risk factors related to afterload mismatch(AM)after transcatheter mitral valve repair(MitraClip).Methods This was a retrospective cohort study.48 patients hospitalized in the Department of Cardiovascular Medicine,the First Affiliated Hospital of Sun Yat-sen University from December 2021 to December 2023,who underwent MitraClip due to severe mitral regurgitation(MR)were included.Preoperative clinical data,laboratory tests,and preoperative and postoperative color Doppler echocardiographic examination results of surgical patients were collected.AM was defined as the left ventricular ejection fraction(LVEF)decreased by 15％or more after surgery compared with the one before(dLVEF≤-15％).Patients were divided into AM group and non-AM group according to whether afterload mismatch occurred.Univariate and multivariate logistic regression were used to analyze the risk factors of postoperative AM.Results Among 48 patients who underwent MitraClip,14 of them(29.2％)developed afterload-mismatched.For those without AM,their overall LVEF was improved after the operation;for patients in both AM group and non-AM group,their overall left ventricular end-diastolic diameter(LVEDd),left ventricular end-diastolic diameter volume index(LVEDVi)was reduced compared with the preoperative ones.Univariate regression analysis showed that C-reactive protein levels(OR 1.98,95％CI 1.02-3.83),platelets(OR 2.22,95％CI 1.08-4.53),systemic immune inflammation index(OR 1.96,95％CI 1.03-3.71)were associated with an increased risk of AM in patients undergoing MitraClip(all P＜0.05),while those with larger right atrial diameter(OR 0.35,95％CI 0.13-0.93)or moderate to severe tricuspid regurgitation(OR 0.19,95％CI 0.05-0.81)were less likely to develop into AM(both P＜0.05),which is still satisfied after adjustment.Conclusions For patients who underwent MitraClip,C-reactive protein levels,platelets and systemic immune inflammation index(SII)are associated with an increased risk of afterload mismatched,while those with larger right atrial diameter or moderate to severe tricuspid regurgitation were less likely to develop into AM.

Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8％(62 219/261 893),and gram-negative bacteria 76.2％(199 674/261 893).The most common species were E.coli(46.7％),E.faecium(10.4％),K.pneumoniae(9.8％),E.faecalis(8.7％),P.mirabilis(3.5％),P.aeruginosa(3.4％),SS.agalactiae(2.6％),and E.cloacae(2.1％).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2％,52.8％and 37.0％,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7％,18.5％,16.4％,and 40.3％,respectively.Lower than 10％of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90％of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was＜2％.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.

Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7％)and Enterococcus faecalis(41.5％).The strains were mainly isolated from urinary tract specimens(46.9％±2.6％),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6％).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1％and 1.3％,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7％in 2015 to 3.4％in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3％.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.