Objective: To investigate the current status of benefit finding among young and middle-aged patients with type 2 diabetes mellitus (T2DM) and analyze its influencing factors, so as to provide a reference for improving the level of benefit finding in this population. Methods: From November 2022 to May 2023, young and middle-aged patients with T2DM aged 18-59 years hospitalized in the endocrinology departments of 2 tertiary hospitals in Hengyang City, Hunan Province were selected as survey subjects by a convenience sampling method. Basic demographic information was collected using a general questionnaire survey. Benefit finding, resourcefulness, and stigma were evaluated using the Benefit Finding Scale, the Chinese Version of the Resourcefulness Scale, and the Type 2 Diabetes Stigma Assessment Scale, respectively. A multiple linear regression model was used to analyze the influencing factors of benefit finding among young and middle-aged patients with T2DM. Results: A total of 305 young and middle-aged patients with T2DM were investigated, including 222 males (72.79%) and 83 females (27.21%). There were 231 cases aged 45-59 years, accounting for 75.74%. The scores for benefit finding, resourcefulness, and stigma were (42.86±6.06), (75.12±11.30), and (41.20±10.10), respectively. Multiple linear regression analysis showed that young and middle-aged patients with T2DM who were male (β′=0.088), aged 18-<45 years (β′=0.083), absence of diabetes complications (β′=0.124), and had higher resourcefulness scores (β′=0.679) had higher levels of benefit finding, while patients with higher stigma scores (β′=-0.097) had lower levels of benefit finding. Conclusion The level of benefit finding among young and middle-aged patients with T2DM was moderate, and was related to gender, age, diabetes complications, resourcefulness, and stigma.

Background and aims:Noninvasive assessments play a crucial role in ruling out high-risk esophageal varices(HREV)in cirrhotic patients.However,the value of sound touch elastography(STE)in predicting HREV has not been comprehensively investigated.Therefore,this study aimed to establish prediction models based on liver and spleen stiffness measurements obtained by STE and provide assessment strategies and cutoff values tailored for different clinical situations.Methods:This prospective study included cirrhotic patients who underwent esophagogastroduodeno-scopy(EGD).Liver and spleen stiffness measurements by STE were performed within six months of EGD examination.Various prediction models and their corresponding cutoff values were established for different clinical situations,incorporating spleen diameter and laboratory parameters.Results:A total of 154 cirrhotic patients were included in the study and stratified into training(n=119)and validation(n=35)sets.Multivariable analysis revealed platelet,spleen diameter and spleen stiffness measurement as independent predictors of HREV.The model incorporating spleen stiffness measurement,platelet,and spleen diameter demonstrated superior performance in predicting HREV,yielding an area under the receiver operating characteristic curve(AUC)of 0.878 and 0.853 in the training set and validation set,respectively.Application of this model for screening cirrhotic patients could avoid EGDs in 39.7％(27/68)and 35.3％(6/17)of patients in the training and validation sets,respectively.Conclusions:Liver and spleen stiffness measurements obtained through STE are valuable for predicting HREV in cirrhotic patients.The developed prediction models and their corresponding cutoff values provide tailored solutions for various clinical situations,thereby effectively reducing the need for un-necessary endoscopies.

The elimination of biofilms is a crucial step in controlling hospital-acquired infections.Once biofilms colonize luminal instruments,it is difficult to remove them using traditional disinfection methods.Conventional disinfection approaches now face a series of challenges,including microbial resistance,corrosiveness,cytotoxicity,residual disinfection byproducts,and environmental pollution.Therefore,developing novel disinfection technologies specifically targeting biofilm removal is vitally important.New disinfection technologies,such as slightly acidic electrolyzed water,plasma technology,surface modification techniques,nanomaterial-based disinfection,bacteriophage disinfection,and enzymatic disinfection,are constantly emerging.These technologies exhibit excellent performance against biofilms by leveraging the synergistic effects of multiple mechanisms,including the reactive oxygen species(ROS)burst,photocatalytic oxidation,physical disruption,and biological targeting.This review summarizes the characteristics,underlying mechanisms,and potential application scenarios of these novel disinfection technologies,with a particular focus on their effects against biofilms formed by common pathogenic bacteria on surfaces in hospital settings.It aims to provide a reference basis for the practical application and translation of these disinfection technologies and the development of new disinfection strategies.

OBJECTIVE To evaluate the effect of antimicrobial stewardship scientific(AMS)of antimicrobial agents on special antibiotics so as to provide evidence-based bases for reasonable use of antibiotics.METHODS A retro-spective survey was conducted for the status of use of special antibiotics in Zhongnan Hospital,Wuhan University.The utilization rate of intravenous infusion of antibiotics,antimicrobials use density(AUD)of special grade antibi-otics,defined daily doses(DDDs),etiological submission rate of microorganisms before use of antibiotics and drug resistance rates of major gram-negative bacteria to special grade antibiotics were observed and compared be-fore and after the AMS was carried out.RESULTS There were no significant differences in gender,severity of dis-ease and spectrum of infectious diseases before and after the AMS was carried out.The utilization rate of intrave-nous infusion of antibiotics was(55.64±1.63)％among the hospitalized patients after the AMS was carried out,the AUD of special grade antibiotics was 2.08±0.57,and the DDDs was 2406.53±292.16,showing generally downward trends(P＜0.05).The drug resistance rates of Acinetobacter baumannii strains to cefepime and imi-penem were 89.15％and 90.21％,respectively,showing upward trends(P＜0.05).CONCLUSION The AUD and DDDs of the special grade antibiotics can be remarkably reduced through powerful means such as carrying out AMS,setting up AMS task group for special grade antibiotics,developing guidance documents for scientific use of special antibiotics,taking full advantage of reasonable drug administration surveillance system,implementing closed-loop management of the special antibiotics,and completing early warning mechanisms for bacterial drug re-sistance as well as information construction to boost management.

Chemiluminescence,as a self-luminous phenomenon that does not require light,heat,acoustic,electric and magnetic excitation,has been widely used in the fields of analytical chemistry,cold light source and bio-imaging because of its advantages including high sensitivity,wide linear range,simple equipment and fast detection speed compared with other analytical techniques.Carbon dots(CDs)are a class of nanomaterials with excellent photoluminescence properties and high biocompatibility.CDs are stable,easy to prepare and abundant in types,and researchers have introduced many types of CDs into different chemiluminescence systems.In this paper,the applications of CDs in common chemiluminescence systems and the possible mechanisms of action were discussed,and the research progresses on the application of CDs in different chemiluminescence detection fields in recent years were summarized.Finally,the development trend of CDs in chemiluminescence was analyzed.

Objective:To investigate the inpact of thyroid cancer-derived cancer-associated fibroblasts(CAF) autophagy on papillary thyroid cancer(PTC).Methods:CAF and normal fibroblasts were isolated from cancerous and adjacent normal thyroid tissues from four PTC patients. Expressions of fibroblast activation protein(FAP) and α-smooth muscle actin in cells were assessed. Conditioned medium of CAF and normal fibroblasts were prepared and used to culture PTC cells. The effects of CAF and normal fibroblasts on survival, proliferation, migration, invasion and iodine uptake of PTC cells were evaluated through cell proliferation assay, cell scratch assay, cell invasion assay, and cell iodine uptake assay. The autophagy level of CAF was also evaluated. Autophagy inhibition and activation were used to regulate the autophagy of CAF, and then their effects on PTC cell proliferation, migration and invasion were further evaluated. The in vivo effect of CAF autophagy on PTC xenograft tumor growth was evaluated.Results:CAF exhibited higher FAP expression and basal autophagy levels. PTC cells co-cultured with CAF-conditioned media showed enhanced proliferation, migration, invasion, and reduced iodine uptake. Autophagy inhibition reduced these effects, while autophagy activation further promoted them. In vivo, inhibiting CAF autophagy suppressed tumor growth.Conclusions:CAF promotes PTC cell malignancy through autophagy activation, enhancing proliferation, migration, and invasion while reducing iodine uptake.

Objective:To explore the value of ultrasound imaging characteristics combined with clinical indicators in assessing the prognosis of patients with pancreatic ductal adenocarcinoma (PDAC).Methods:A retrospective analysis was conducted for patients who underwent pancreatic contrast-enhanced ultrasound (CEUS) from September 2017 to October 2023 at Peking Union Medical College Hospital and were diagnosed with PDAC based on pathological findings. Various parameters were recorded, including CA19-9 levels, tumor size, location, morphologic features, echogenicity, presence of internal cystic components, dilatation of the main pancreatic duct, peripheral vascular invasion, CEUS characteristics, presence or absence of liver metastasis, and treatment methods. In April 2024, patient survival information was obtained through telephone follow-up or review of medical records. Based on the results of the cox regression model analysis, a nomogram model of the risk of death was developed. The receiver operating characteristic (ROC) curves were applied to evaluate the predictive efficacy of the model. The calibration curves were plotted to evaluate the accuracy of the model, and clinical decision curves were used to evaluate the clinical benefit of the model.Results:This study included a total of 207 patients with PDAC. As of April 2024, 71 patients were alive and 136 died, with a median survival time of 14 months (95% CI: 12 -17). Multivariate analysis confirmed that the elevated CA19-9 ( HR=1.689, 95% CI: 1.102-2.588), tumor size >4 cm ( HR=1.641, 95% CI: 1.159-2.322), taller-than-wide shapes ( HR=1.450, 95% CI: 1.019-2.065), incomplete hypo-enhancement ( HR=1.618, 95% CI: 1.100-2.380), and liver metastasis ( HR=1.687, 95% CI: 1.175-2.423) were independent risk factors for survival in patients with PDAC. A nomogram model was further constructed for 6-month, 12-month and 3-year survival of patients with PDAC. The areas under the ROC curve were 0.679, 0.705 and 0.815, respectively. The calibration curves suggested that the model was more accurate, and the clinical decision curves showed that the model had a better clinical benefit. Conclusion:The combined use of ultrasound imaging characteristics and clinical indicators could effectively predict the prognosis of PDAC patients. Specifically, tumor size >4 cm, taller-than-wide shapes, incomplete hypo-enhancement, elevated CA19-9, and the presence of liver metastasis are correlated with poorer survival outcomes. The nomogram model constructed on the basis of these factors can be used to assess the survival of patients with PDAC.

Objective To observe the value of multi-sequence magnetic resonance imaging(MRI)radiomics in predicting the efficacy of concurrent chemoradiotherapy(CCRT)in locally advanced cervical squamous cell carcinoma(CSCC)patients.Methods Clinical data of 100 CSCC patients underwent CCRT treatment were selected.In order to better validate the performance of the model,patients were randomly divided into the training set(70 cases)and the validation set(30 cases)in a 7∶3 ratio.According to the efficacy criteria for solid tumors,patients were divided into the complete response(CR)group(n=16)and the partial response(PR)group(n=14).Examination images of cross-sectional DWI,T2WI and enhanced T1WI were collected from all patients before treatment.ITK-SNAP software package combined with three sequences were used to outline ROI,and the open source software PyRadiomics was used to extract image omics features.For MRI omics features,the minimum redundancy maximum correlation(mRMR)algorithm was used to analyze and screen out the first 30 main features,and then the minimum absolute contraction and selection method(Lasso)based on 10-fold cross-validation was used to reduce dimensionality to screen the non-zero coefficient features.According to the weighting coefficient of Lasso-Logistic regression model in the training set,patient omics labels were calculated.Logistic regression analysis was used to construct a prediction model based on DWI,T2WI and T1WI sequence prediction models and multiple sequenomics labels.Receiver operating characteristic(ROC)curves evaluated the predictive value of each omics model for CCRT treatment in patients with locally advanced CSCC.Results There were 38 cases in the CR group and 32 cases in the PR group in the training set.There were 16 cases in the CR group and 14 cases in the PR group in the validation set.There were no significant differences in patient age,FIGO stage,differentiation degree,maximum lesion diameter and menstrual status between the CR group and the PR group in the training and validation sets.A total of 851 imaging features were extracted from the ROI target area.After the first 30 features were retained by mRMR algorithm,3 CR-related features were selected from the 851 imaging omics features of each individual sequence by Lasso algorithm and 10-fold cross-validation.Eight CR related features were selected from 2 553 features after the combination of the three sequences.ROC curve results showed that in the training set and validation set,the AUC of multiple sequences combined to predict the therapeutic effect of CCRT in patients with locally advanced CSCC was 0.971 and 0.946,respectively,which was higher than that of T1WI,T2WI and DWI single sequence prediction(training set Z=2.683,2.046,2.817,P＜0.05;verification set Z=2.075,2.117,2.005,P＜0.05).Conclusion The multi sequence MRI radiomics model has high predictive value for the efficacy of CCRT treatment in locally advanced CSCC patients.

Artificial intelligence(AI)has demonstrated great potential in the diagnosis and treatment of pancreatic cancer.It plays an important role in medical imaging analysis,pathological slide recognition,drug efficacy and prognosis prediction,as well as new drug development by leveraging deep learning algorithms.Despite challenges such as data acquisition and model interpretability,advancements in technology and data sharing are expected to further enhance its role in early screening,personalized treatment,and innovative drug discovery for pancreatic cancer,ultimately improving patient outcomes.

Objective To explore the predictive value of serum levels of CXC chemokine ligand 4(CXCL4),CXC receptor 3 chemokine(CXCR3)for postoperative cerebral vasospasm(CVS)in patients with ruptured intracranial aneurysms.Methods The clinical data of 106 patients with intracranial aneurysms rupture who under went craniotomy and clipping surgery at the Central Hospital of Enshi Tujia and Miao Autonomous Prefecture from October 2020 to December 2022 were collected.The incidence of CVS was observed.Serum CXCL4 and CXCR3 levels were compared at 1,3,7 days after surgery between patients without CVS and patients with CVS.Spearman correlation coefficient was used to analyze the relationship between serum CXCL4,CXCR3 levels and CVS degree.ROC curve was used to analyze the value of serum CXCL4 and CXCR3 levels in predicting postoperative CVS.Results Among 106 patients with ruptured intracranial aneurysms,a total of 38 cases(35.85%)developed CVS after surgery,and 68 cases(64.15%)did not develop CVS.There was no statistically obvious difference in preoperative serum levels of CXCL4 and CXCR3 between the CVS group and the non CVS group(t=0.104,0.141,all P>0.05).The serum levels of CXCL4 and CXCR3 in the non CVS group were lower than those before surgery 1,3,and 7 day after surgery,and the differences were statistically significant(q=14.867,17.525,24.384;16.274,20.251,34.237,all P<0.05).Compated with preoperative levels,the levels of serum CXCL4 and CXCR3 in the CVS group decreased on postoperative 1 and 7 days,and the differences were statistically significant(q=9.486,4.858;10.760,9.104,all P<0.05).Compared with the mild CVS group,the serum levels of CXCL4 and CXCR3 in the moderate and severe CVS groups were obviously increased(q=2.982,5.992;2.961,3.465),and the serum levels of CXCL4 and CXCR3 in the severe CVS group were higher than those in the moderate CVS group(q=3.564,4.036),and the differences were statistically significant(all P<0.05),respectively.Spearman results showed that serum levels of CXCL4 and CXCR3 were positively correlated with the severity of CVS(r=0.491,0.483,all P<0.05).The ROC curve results showed that the AUC of CXCL4 and CXCR3 combined in predicting postoperative CVS in patients with intracranial ruptured aneurysms was higher than that of CXCL4,CXCR3 alone,and the differences were statistically significant(Z=2.937,2.750,all P<0.05).Conclusion The serum levels of CXCL4 and CXCR3 in ruptured intracranial aneurysms patients with postoperative CVS are obviously elevated,and the combined detection of the two can effectively predict the occurrence of CVS.