YTHDF2 is a key m6A RNA modification"reader"that plays a crucial role in cell biological processes and tumor development.This review deeply explores the biological role of YTHDF2 and the advances in its application in tumors.The YTHDF2 structures are divided into mRNA procsomes and YTH domains,which recognize and bind m6A modified RNA molecules.It plays a biological role by promoting mRNA degradation,regu-lating cell signaling pathways and metabolism,and can regulate macrophage function and maintain an immunosup-pressive state in the tumor microenvironment.YTHDF2 has the potential to serve as diagnostic markers,therapeu-tic targets and prognostic evaluation biomarkers in different tumors,but currently relevant studies are insufficient in sample size,molecular mechanism and clinical application.In the future,research can be conducted on compre-hensive clinical research,in-depth analysis of molecular mechanisms,and research and development of optimized treatment strategies.

YTHDF2 is a key m6A RNA modification"reader"that plays a crucial role in cell biological processes and tumor development.This review deeply explores the biological role of YTHDF2 and the advances in its application in tumors.The YTHDF2 structures are divided into mRNA procsomes and YTH domains,which recognize and bind m6A modified RNA molecules.It plays a biological role by promoting mRNA degradation,regu-lating cell signaling pathways and metabolism,and can regulate macrophage function and maintain an immunosup-pressive state in the tumor microenvironment.YTHDF2 has the potential to serve as diagnostic markers,therapeu-tic targets and prognostic evaluation biomarkers in different tumors,but currently relevant studies are insufficient in sample size,molecular mechanism and clinical application.In the future,research can be conducted on compre-hensive clinical research,in-depth analysis of molecular mechanisms,and research and development of optimized treatment strategies.

Objective:To observe effectiveness of combining diffusion tensor imaging (DTI) with motor evoked potentials (MEPs) in evaluating the upper limb motor functioning of stroke survivors.Methods:Thirty-seven stroke survivors with upper limb motor dysfunction were selected. At the 4th, 12th and 24th week after their onset, each was were assessed using Fugl-Meyer Upper Limb (FMA-UE) scoring, the National Institutes of Health stroke scale (NIHSS), the modified Rankin Scale (mRS), the Barthel Index (BI) and hemiplegic hand function classification. DTI was also applied and MEPs were measured. The patients were divided into an MEP positive group and an MEP negative group according to the existence of the MEP waveform. The DTI and MEP parameters were correlated with the FMA-UE scores, linear regressions were evaluated and a receiver operating characteristics curve was prepared to estimate the utility of DTI in predicting hand function. The sensitivity and specificity of MEPs in predicting hand function recovery were evaluated.Results:The asymmetry index (FAa) of the average anisotropy score of the posterior limb of the internal capsule and the FAa of the cerebral peduncle were both significantly correlated with the FMA-UE scores at the 12th and 24th weeks. The best cut-off points for predicting functional recovery of a patient′s hand were 0.155 for the FAa of the posterior limb of the internal capsule and 0.145 for the cerebral peduncle. Among the 37 patients, the MEPs of 8 (the MEP positive group) could be extracted, and their hand functions recovered completely. The sensitivity of the MEPs in predicting the complete recovery of hand function was 80% with 100% specificity. The linear regression analysis showed 77% prediction accuracy for the FAa and MEPs of the cerebral peduncle for upper limb motor function at the 24th week after onset. In the MEP negative group, two patients completely recovered their hand function, with one′s FAa less than 0.145, and the other′s more than 0.145. When the MEP was negative, the sensitivity of DTI in predicting the recovery of hand function was 50% with 81.5% specificity.Conclusions:DTI combined with MEPs can be used as an index to evaluate the prognosis of upper limb motor function in stroke patients.

Objective:To observe effectiveness of combining diffusion tensor imaging (DTI) with motor evoked potentials (MEPs) in evaluating the upper limb motor functioning of stroke survivors.Methods:Thirty-seven stroke survivors with upper limb motor dysfunction were selected. At the 4th, 12th and 24th week after their onset, each was were assessed using Fugl-Meyer Upper Limb (FMA-UE) scoring, the National Institutes of Health stroke scale (NIHSS), the modified Rankin Scale (mRS), the Barthel Index (BI) and hemiplegic hand function classification. DTI was also applied and MEPs were measured. The patients were divided into an MEP positive group and an MEP negative group according to the existence of the MEP waveform. The DTI and MEP parameters were correlated with the FMA-UE scores, linear regressions were evaluated and a receiver operating characteristics curve was prepared to estimate the utility of DTI in predicting hand function. The sensitivity and specificity of MEPs in predicting hand function recovery were evaluated.Results:The asymmetry index (FAa) of the average anisotropy score of the posterior limb of the internal capsule and the FAa of the cerebral peduncle were both significantly correlated with the FMA-UE scores at the 12th and 24th weeks. The best cut-off points for predicting functional recovery of a patient′s hand were 0.155 for the FAa of the posterior limb of the internal capsule and 0.145 for the cerebral peduncle. Among the 37 patients, the MEPs of 8 (the MEP positive group) could be extracted, and their hand functions recovered completely. The sensitivity of the MEPs in predicting the complete recovery of hand function was 80% with 100% specificity. The linear regression analysis showed 77% prediction accuracy for the FAa and MEPs of the cerebral peduncle for upper limb motor function at the 24th week after onset. In the MEP negative group, two patients completely recovered their hand function, with one′s FAa less than 0.145, and the other′s more than 0.145. When the MEP was negative, the sensitivity of DTI in predicting the recovery of hand function was 50% with 81.5% specificity.Conclusions:DTI combined with MEPs can be used as an index to evaluate the prognosis of upper limb motor function in stroke patients.

Obejective　To investigate and compare the clinical efficacy of aroma massage with traditional massage in the treatment of chronic fatigue syndrome （CFS）. MethodsSeventy-two CFS patients were randomized into the aroma massage group and the traditional massage group， with 36 patients in each group. Both groups were treated with essential oil aromatherapy and massage were performed on the head， face， and abdomen stimultaneously. The aroma massage group used antifatigue oil， while the traditional massage group used placebo essential oil. The two groups were treated for 30 minutes each time， once every other day， three times a week， for a total of 4 weeks. The fatigue scale （FS-14） score， traditional Chinese medicine （TCM） syndrome score and patient satisfaction evaluation scale score before and after the treatment of the two groups were assessed to study the improvement of fatigue and other clinical symptoms of the patients as well as the changes of the TCM symptom scores， and to evaluate the clinical efficacy of the two groups. ResultsWith three drop-outs in the traditional massage group and two drop-outs in the aroma massage group， 33 cases in the traditional massage group and 34 cases in the aroma massage group were included in the outcome analysis. The FS-14 scores and TCM syndrome scores significantly decreased after treatment in both groups （P＜0.01）； compared to those in the traditional massage group （FS-14： 4.42±2.44； TCM syndrome score： 34.12±7.67）， the FS-14 score （3.06±2.37） and TCM syndrome score （28.79±5.62） in the aroma massage group were significantly lower （P＜0.05 or P＜0.01）. There was no significant difference in the satisfaction scores of the patients in the two groups after the treatment （P＞0.05）. The total effective rate of the aroma massage group was 94.12% （32/34）， which was significantly higher than 84.85% （28/33） of the traditional massage group （P＜0.05）. ConclusionBoth aromatherapy and traditional massage can improve the clinical symptoms of fatigue in CFS patients， and aromatherapy is more effective， which is easy to operate with high patient acceptance.

Objective To construct and validate a clinical prediction model for delayed extubation undergoing non-emergency major surgery based on the random forest algorithm.Methods Clinical data of 7 528 patients undergoing non-emergency major surgery under general anesthesia from January 2018 to De-cember 2022 were retrospectively collected.The patients were divided into two groups according to whether extubation was performed within 2 hours after surgery:non-delayed extubation group(≤2 hours)and de-layed extubation group(＞2 hours).All the patients were randomly divided into a training set and a valida-tion set in a ratio of 7 ∶ 3.The predictive factors for delayed extubation after surgery were screened through LASSO regression and Logistic regression.The random forest model was established and verified by random forest algorithm.Results There were 123 patients(1.6%)experienced delayed extubation after surgery.ASA physical status,department,intraoperative use of flurbiprofen ester,dexmedetomidine,glucocorticoid,hypocalcemia,severe anemia,intraoperative blood transfusion,and airway spasm were identified as inde-pendent predictive factors for delayed extubation.The area under curve(AUC)value of the random forest prediction model in the validation set was0.751(95%CI0.742-0.778),and the sensitivity was98.1%,and the specificity was 41.9%.Conclusion The predictive model of delayed extubation undergoing non-e-mergency major surgery based on random forest algorithm has a good predictive value,which may be helpful to prevent delayed extubation undergoing non-emergency major surgery.

Non-pharmaceutical interventions（NPIs）against the COVID-19 restricted the spread of respiratory infectious diseases.After the lifting of NPIs for the COVID-19 pandemic，a resurgence of respiratory syncytial virus（RSV）has been observed in multiple countries and regions globally，exhibiting epidemiological and clinical characteristics distinct from previous RSV epidemic during the pre-COVID-19 era.This resurgence poses new challenges for clinical management of RSV infection.This review elucidates the changes in epidemiological and clinical features of pediatric RSV epidemic after the lifting of NPIs，potential mechanisms underlying these changes，as well as advances in RSV prevention and control，aiming to enhance the understanding of pediatric RSV infection following the lifting of NPIs，and provides reference for further optimization of strategies in the prevention，control，and clinical management of pediatric RSV infection.

Objective:To compare the epidemiological and clinical characteristics of hospitalized children with respiratory syncytial virus (RSV) infection in Kunming among the pre-and post-COVID-19 era, and to establish a prediction model for severe RSV infection in children during the post-COVID-19 period.Methods:This was a retrospective study. Clinical and laboratory data were collected from 959 children hospitalized with RSV infection in the Department of Pulmonary and Critical Care Medicine at Kunming Children′s Hospital during January to December 2019 and January to December 2023. Patients admitted in 2019 were defined as the pre-COVID-19 group, while those admitted in 2023 were classified as the post-COVID-19 group. Epidemiological and clinical characteristics were compared between the two groups. Subsequently, comparison of the clinical severity among the two groups was performed based on propensity score matching (PSM). Furthermore, the subjects in the post-COVID-19 group were divided into severe and non-severe groups based on clinical severity. Chi-square test and Mann-Whitney U test were used for pairwise comparison between groups, and multivariate Logistic regression was applied for the identification of independent risk factors and construction of the prediction model. The receiver operating characteristic (ROC) curve and calibration curve were employed to evaluate the predictive performance of this model. Results:Among the 959 children hospitalized with RSV infection, there were 555 males and 404 females, with an onset age of 15.4 (7.3, 28.5) months. Of which, there were 331 cases in the pre-COVID-19 group and 628 cases in the post-COVID-19 group. The peak period of RSV hospitalization in the post-COVID-19 group were from May to October 2023, and the monthly number of inpatients for each of these months were as follows: 72 cases (11.5%), 98 cases (15.6%), 128 cases (20.4%), 101 cases (16.1%), 65 cases (10.4%), and 61 cases (9.7%), respectively. After PSM for general data, 267 cases were matched in each group. The proportion of wheezing in the post-COVID-19 group was lower than that in the pre-COVID-19 group (109 cases (40.8%) vs. 161 cases (60.3%), χ2=20.26, P<0.001), while the incidences of fever, tachypnea, seizures, severe case, neutrophil-to-lymphocyte ratio (NLR), C-reactive protein and interleukin-6 levels were all higher than those in the pre-COVID-19 group (146 cases (54.7%) vs. 119 cases (44.6%), 117 cases (43.8%) vs. 89 cases (33.3%), 37 cases (13.9%) vs. 14 cases (5.2%), 69 cases (25.8%) vs. 45 cases (16.9%), 3.6 (1.9, 6.4) vs. 2.3 (1.8, 4.6), 9.9 (7.1, 15.2) vs. 7.8 (4.5, 13.9) mg/L, 20.5 (15.7, 30.4) vs. 17.2 (11.0, 26.9) ng/L, χ2=5.46, 6.36, 11.47, 6.42, Z=4.13, 3.06, 2.96, all P<0.05). There were 252 cases and 107 cases with co-infection in the post-and pre-COVID-19 groups, respectively. The proportion of triple and quadruple infection in the post-COVID-19 group was higher than that in the pre-COVID-19 group (59 cases (23.4%) vs. 13 cases (12.1%), 30 cases (11.9%) vs. 5 cases (4.7%), χ2=5.94, 4.46, both P<0.05). Among the 252 cases with co-infection in post-COVID-19 group, the most prevalent pathogens involving in co-infections, in order, were Mycoplasma pneumoniae 56 cases (22.2%), Influenza A virus 53 cases (21.0%), Rhinovirus 48 cases (19.0%), Parainfluenza virus 35 cases (13.9%), and Adenovirus 28 cases (11.1%).The result of multivariate Logistic regression showed that age ( OR=0.70, 95% CI 0.62-0.78, P<0.001), underlying diseases ( OR=10.03, 95% CI 4.10-24.55, P<0.001), premature birth ( OR=6.78, 95% CI 3.53-13.04, P<0.001), NLR ( OR=1.85, 95% CI 1.09-3.15, P=0.023), and co-infection ( OR=1.28, 95% CI 1.18-1.38, P<0.001) were independently associated with the development of severe RSV infection in the post-COVID-19 group. The ROC curve of the prediction model integrating the above five factors indicated an area under the curve of 0.85 (95% CI 0.80-0.89, P<0.001), with an optimal cutoff of 0.21, a sensitivity of 0.83 and a specificity of 0.80. The calibration curve showed that the predicted probability in this model did not differ significantly from the actual probability ( P=0.319). Conclusions:In the post-COVID-19 era in Kunming, the peak in pediatric hospitalizations for RSV infection was from May to October, with declined incidence of wheezing and increased incidence of fever, tachypnea, seizures, severe cases, and rates of triple and quadruple co-infections. Age, underlying diseases, premature birth, NLR, and co-infection were identified as independent risk factors for severe RSV infection in the post-COVID-19 period. In this study, a risk prediction model for severe pediatric RSV infection was established, which had a good predictive performance.

T-cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domain(TIGIT)is a transmembrane glycoprotein expressed on the surface of immune cells.TIGIT expression is up-regulated in blad-der cancer and will have an important impact on bladder cancer development and poor prognosis.Immunotherapy that blocks TIGIT signaling is expected to improve the prognosis of bladder cancer.With further research,TIGIT is likely to become a target for bladder cancer diagnosis and treatment.This article reviews the structure,immuno-modulatory effect and the research progress of TIGIT in bladder cancer.

Objective To investigate the relationship between coronary artery plaque AI quantitative parameter and FFR-CT in coronary computed tomography angiography.Methods A total of 84 patients suspected of having CAD[52 males and 32 females,aged 27 to 81 years with a mean age of(58.1±11.9)years]were enrolled in this study.All patients underwent coronary computed tomography angiography.The CCTA data was processed using shukun(SK)software for labeling and analysis of the coronary arteries,as well as obtaining quantitative parameters of coronary artery plaque AI and corresponding FFR-CT values.The quantitative parameters included plaque length,total volume,minimum lumen area(MLA),minimal lumen degree(MLD),lipid composition volume and proportion,fibrous-lipid composition volume and proportion,fibrous composition volume and proportion,calcified composition volume and proportion.Coronary artery hemodynamic abnormality or myocardial ischemia was defined as an FFR-CT value≤0.8.Correlational analysis was performed to evaluate the association between AI plaque quantitative param-eters and FFR-CT values.Univariate and multivariate binary logistic regression analyses were conducted to identify independent risk factors for predicting FFR-CT≤0.8.The predictive performance of the model based on AI plaque quantitative parameters was assessed using receiver operating characteristic(ROC)curve analysis and calculation of the area under the curve(AUC).Sensitivities,specificities,diagnostic test accuracy rates were also calculated.Results The predominant symptoms observed in the cohort of 84 patients were chest pain(n=39,46.4%)and distress(n=27,32.1%).Spearman analysis results revealed a weak positive correlation between FFR-CT and MLA(r=0.49,P<0.0001),while weak negative correlations were found for plaque length,total volume,lipid composition volume,fibrous-lipid composition volume,fibrous composition volume,and calcified composition volume(r=-0.44,-0.56,-0.40,-0.36,-0.42,-0.40;all P<0.05).Additionally,MLD exhibited a moderate negative correlation with FFR-CT(r=-0.60,P<0.0001).In the univariate binary logistic regression analysis,several variables including plaque length,total volume,MLA,MLD,lipid composition volume,fibrous-lipid composition volume,fibrous composition volume,and calcified composition volume were found to be independently associated with FFR-CT≤0.8(All P<0.05).The adjusted multivariate binary logistic regression analysis model revealed that MLD was the sole independent predictor(OR=1.082,95%CI:1.034～1.133,P=0.001).The logistics re-gression model expression was logit(P)=0.079X1-4.052,where X1 represents the value of MLD and achieved a predictive accuracy of 85.2%.The ROC AUC of plaque length,total volume,MLA,MLD,lipid composition vol-ume,fibrous-lipid composition volume,fibrous composition volume and calcified composition volume were 0.796,0.886,0.711,0.754 and 0.698 respectively,and the coresponding sensitivities and specificities were 47.83%,73.91%,73.90%,52.17%,60.87%and 92.11%,73.68%,60.53%,84.21%,89.47%.The five in-dexes combined diagnostic model possessed the largest AUC of 0.906,and 73.91%,71.05%of sensitivity and specificity.Conclusion The AI quantitative parameters of coronary artery plaque exhibited varying degrees of correlation with FFR-CT,while MLD emerged as the sole independent predictor of FFR-CT≤0.8,demonstrating high diagnostic efficiency.