Objective To investigate the characteristics of changes in pain-anxiety-depression-fatigue symptom clusters and their possible associated factors in adolescents with acute lymphoblastic leukemia(ALL)during early chemotherapy.Methods A prospective longitudinal study was conducted from Nov 2019 to Oct 2021,enrolling newly diagnosed adolescent ALL patients from 5 tertiary or pediatric specialty hospitals in Shanghai,Zhejiang Province,Sichuan Province,Anhui Province and Guangdong Province.Patient-reported pain,anxiety,depression,and fatigue were collected at five time points within the first nine weeks of chemotherapy using the PROMIS Pediatric-25 instrument.Latent profile analysis(LPA)and latent transition analysis(LTA)were applied to explore the latent classes of symptom clusters,their transition probabilities over time,and possible risk or protective factors associated with class membership.Results A total of 134 ALL cases were enrolled,and symptom clusters at all the 5 time points(T1-T5)were consistently classified into three groups of mild,moderate and severe symptoms.The severe symptoms group accounted for the largest proportion at each time point(54.5%,59.7%,66.4%,49.3%,and 47.0%,respectively),while the mild and moderate symptoms groups showed an initial decline followed by an increase.Among participants,40.2%maintained the same symptom status,and 77.4%experienced at least one episode of severe symptom status during the trajectory.Religious affiliation(T5)and family monthly income>5 000 Yuan(T2,T4 and T5)served as protective factors against severe symptoms.Higher baseline fatigue(T1)was associated with membership in the severe symptoms group at subsequent time points.Conclusion Pain-anxiety-depression-fatigue symptoms in adolescents with ALL during early chemotherapy can be categorized into mild,moderate and severe symptoms with dynamic transitions over time.Higher baseline fatigue was associated with increased risk of severe symptoms,whereas higher family income and religious affiliation appeared protective effects.

AIM To investigate the clinical effects of Yifei Tongluo Decoction combined with azithromycin on patients with childern severe Mycoplasma pneumoniae pneumonia due to Toxic Heat Blocking Lung.METHODS One hundred and fifty-six patients were randomly assigned into control group(78 cases)for 7-day administration of azithromycin,and observation group(78 cases)for 7-day administration of both Yifei Tongluo Decoction and azithromycin.The changes in clinical effects,disappearance time of local symptoms,mycoplasmas,pulmonary imaging score,Toxic Heat Blocking Lung score,pulmonary function indices(PEF,VPTEF,MMF,TPTEF),inflammatory factors(sB7-H3,Cgp-39,sICAM-1,CCL5),immune function indices(RBC-C3bR,RBC-ICR,CD3+,CD4+)and safety indices were detected.RESULTS The observation group demonstrated higher total effective rate than the control group(P＜0.05),along with shorter disappearance time of local symptoms(P＜0.05).After the treatment,the two groups displayed decreased mycoplasmas,pulmonary imaging score,Toxic Heat Blocking Lung score,inflammatory factors,RBC-ICR(P＜0.05),and increased pulmonary function indices,RBC-C3bR,CD3+,CD4+(P＜0.05),especially for the observation group(P＜0.05).No obvious difference in incidence of adverse reactions was found between the two groups(P＞0.05).CONCLUSION For the patients with childern severe Mycoplasma pneumoniae pneumonia due to Toxic Heat Blocking Lung,Yifei Tongluo Decoction combined with azithromycin can safely and effectively alleviate clinical symptoms,improve pulmonary functions,and reduce body inflammatory responses.

Objective:To construct a risk prediction model of postoperative severe bradyarrhythmia for patients with valvular heart disease and verify the predictive efficacy of the model.Methods:A total of 636 patients undergoing heart valve surgery in Nanjing First Hospital between June 2023 and March 2024 were retrospectively selected.Ac-cording to the need for permanent pacemaker implantation after the surgery,the patients were divided into severe bradyarrhythmia group(n=80)and non-severe bradyarrhythmia group(n=556),then univariate and multivariate Logistic regression analysis were conducted to analyze the influencing factors of postoperative severe bradyarrhyth-mia in patients with valvular heart disease.R software was used to draw a nomogram prediction model for postoper-ative severe bradyarrhythmia in patients with valvular heart disease,and to verify the predictive effect of the model.Results:The incidence of postoperative severe bradyarrhythmia in patients with valvular heart disease was 12.6％in this study.Multivariate Logistic regression analysis showed that BMI＞28kg/m2(OR=2.094,95％CI 1.047～4.189,P=0.037),preoperative conduction block(OR=6.507,95％CI 2.909～14.552,P＜0.001),tricuspid valve surgery(OR=1.831,95％CI 1.094～3.063,P=0.021)and low cardiac output after surgery(OR=3.186,95％CI 1.310～7.751,P=0.011)were independent risk factors of postoperative severe bradyarrhythmia in these patients,while NYHA class Ⅲ～Ⅳ was its independent protective factor(OR=0.328,95％CI 0.194～0.555,P＜0.001).The nomogram model was constructed based on the influencing factors.H-L test in model group showed that x2=3.667,P=0.886,AUC under ROC curve was 0.744(95％CI 0.685～0.803),H-L test in validation group showed that x2=9.314,P=0.316,AUC under ROC was 0.718(95％CI 0.618～0.818),and the accuracy was 72.0％.Conclusion:The independent predictors for postoperative severe bradyarrhythmia in patients with val-vular heart disease include BMI,preoperative conduction block,NYHA class,tricuspid valve surgery and low cardi-ac output after surgery.A prediction model based on the above-mentioned risk factors may have good performance in predicting postoperative severe bradyarrhythmia in this population.

Objective:To construct a risk prediction model of postoperative severe bradyarrhythmia for patients with valvular heart disease and verify the predictive efficacy of the model.Methods:A total of 636 patients undergoing heart valve surgery in Nanjing First Hospital between June 2023 and March 2024 were retrospectively selected.Ac-cording to the need for permanent pacemaker implantation after the surgery,the patients were divided into severe bradyarrhythmia group(n=80)and non-severe bradyarrhythmia group(n=556),then univariate and multivariate Logistic regression analysis were conducted to analyze the influencing factors of postoperative severe bradyarrhyth-mia in patients with valvular heart disease.R software was used to draw a nomogram prediction model for postoper-ative severe bradyarrhythmia in patients with valvular heart disease,and to verify the predictive effect of the model.Results:The incidence of postoperative severe bradyarrhythmia in patients with valvular heart disease was 12.6％in this study.Multivariate Logistic regression analysis showed that BMI＞28kg/m2(OR=2.094,95％CI 1.047～4.189,P=0.037),preoperative conduction block(OR=6.507,95％CI 2.909～14.552,P＜0.001),tricuspid valve surgery(OR=1.831,95％CI 1.094～3.063,P=0.021)and low cardiac output after surgery(OR=3.186,95％CI 1.310～7.751,P=0.011)were independent risk factors of postoperative severe bradyarrhythmia in these patients,while NYHA class Ⅲ～Ⅳ was its independent protective factor(OR=0.328,95％CI 0.194～0.555,P＜0.001).The nomogram model was constructed based on the influencing factors.H-L test in model group showed that x2=3.667,P=0.886,AUC under ROC curve was 0.744(95％CI 0.685～0.803),H-L test in validation group showed that x2=9.314,P=0.316,AUC under ROC was 0.718(95％CI 0.618～0.818),and the accuracy was 72.0％.Conclusion:The independent predictors for postoperative severe bradyarrhythmia in patients with val-vular heart disease include BMI,preoperative conduction block,NYHA class,tricuspid valve surgery and low cardi-ac output after surgery.A prediction model based on the above-mentioned risk factors may have good performance in predicting postoperative severe bradyarrhythmia in this population.

Objective:To observe the application effect of hyperbaric oxygen combined with task oriented training in hemiplegic patients after cerebral infarction.Methods:106 hemiplegic patients after cerebral infarction admitted to Xinglin Hospital of Xiamen from March 2022 to June 2024 were prospectively selected and randomly divided into control group(received task oriented training,n=53)and observation group(received hyperbaric oxygen combined with task oriented training,n=53).Berg balance scale(BBS),clinical spasticity index(CSI),national institute of health stroke Scale(NIHSS),motor function[fugl-meyer motor function assessment scale(FMA),motor assessment scale(MAS)],walking ability[functional ambulation category(FAC),6-minute walking distance(6MWD)],quality of life and self-care ability[quality of life scale for stroke(SS-QOL),activity of daily living(ADL)]before intervention and 8 weeks after intervention were compared between the two groups.Result:Compared with control group 8 weeks after intervention,the observation group had higher BBS,FMA,MAS,FAC,SS-QOL,ADL scores,and 6MWD,while had lower NIHSS and CSI scores(P＜0.05).Conclusion:Hyperbaric oxygen combined with task oriented training in hemiplegic patients after cerebral infarction,can effectively improve patients' motor function,balance ability,and self-care ability,enhance their quality of life,and reduce neurological damage.

Objective:To observe the application effect of hyperbaric oxygen combined with task oriented training in hemiplegic patients after cerebral infarction.Methods:106 hemiplegic patients after cerebral infarction admitted to Xinglin Hospital of Xiamen from March 2022 to June 2024 were prospectively selected and randomly divided into control group(received task oriented training,n=53)and observation group(received hyperbaric oxygen combined with task oriented training,n=53).Berg balance scale(BBS),clinical spasticity index(CSI),national institute of health stroke Scale(NIHSS),motor function[fugl-meyer motor function assessment scale(FMA),motor assessment scale(MAS)],walking ability[functional ambulation category(FAC),6-minute walking distance(6MWD)],quality of life and self-care ability[quality of life scale for stroke(SS-QOL),activity of daily living(ADL)]before intervention and 8 weeks after intervention were compared between the two groups.Result:Compared with control group 8 weeks after intervention,the observation group had higher BBS,FMA,MAS,FAC,SS-QOL,ADL scores,and 6MWD,while had lower NIHSS and CSI scores(P＜0.05).Conclusion:Hyperbaric oxygen combined with task oriented training in hemiplegic patients after cerebral infarction,can effectively improve patients' motor function,balance ability,and self-care ability,enhance their quality of life,and reduce neurological damage.

Objective To investigate the characteristics of changes in pain-anxiety-depression-fatigue symptom clusters and their possible associated factors in adolescents with acute lymphoblastic leukemia(ALL)during early chemotherapy.Methods A prospective longitudinal study was conducted from Nov 2019 to Oct 2021,enrolling newly diagnosed adolescent ALL patients from 5 tertiary or pediatric specialty hospitals in Shanghai,Zhejiang Province,Sichuan Province,Anhui Province and Guangdong Province.Patient-reported pain,anxiety,depression,and fatigue were collected at five time points within the first nine weeks of chemotherapy using the PROMIS Pediatric-25 instrument.Latent profile analysis(LPA)and latent transition analysis(LTA)were applied to explore the latent classes of symptom clusters,their transition probabilities over time,and possible risk or protective factors associated with class membership.Results A total of 134 ALL cases were enrolled,and symptom clusters at all the 5 time points(T1-T5)were consistently classified into three groups of mild,moderate and severe symptoms.The severe symptoms group accounted for the largest proportion at each time point(54.5%,59.7%,66.4%,49.3%,and 47.0%,respectively),while the mild and moderate symptoms groups showed an initial decline followed by an increase.Among participants,40.2%maintained the same symptom status,and 77.4%experienced at least one episode of severe symptom status during the trajectory.Religious affiliation(T5)and family monthly income>5 000 Yuan(T2,T4 and T5)served as protective factors against severe symptoms.Higher baseline fatigue(T1)was associated with membership in the severe symptoms group at subsequent time points.Conclusion Pain-anxiety-depression-fatigue symptoms in adolescents with ALL during early chemotherapy can be categorized into mild,moderate and severe symptoms with dynamic transitions over time.Higher baseline fatigue was associated with increased risk of severe symptoms,whereas higher family income and religious affiliation appeared protective effects.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Aim To explore the compatibility and po-tential mechanism of effective components of Biejia-Ezhu against triple negative breast cancer(TNBC)and verify it by experiments.Methods Effective compo-nents and targets of Biejia-Ezhu were obtained by TC-MSP and Swiss Target Prediction.Disease targets of TNBC were obtained from OMMI and GeneCards data-bases.The PPI network was constructed using STRING database.GO and KEGG path enrichment analysis was performed using DAVID database.Cytoscape3.9.1 software was used to construct the"drug-component-target-disease"network,screen key targets and compo-nents for molecular docking,and further verify the com-patibility of key components and targets in vitro.Re-sults ① A total of 71 effective components were iden-tified in the Biejia-Ezhu drug pair.There were 146 drug targets associated with the disease.A total of 113 signaling pathways were identified by KEGG analysis.The 71 potential active components of Biejia-Ezhu mainly acted on key targets such as mTORC1,ULK1,TNF,EGFR,ESR1,STAT3,HIF1A,and PTGS2.Mo-lecular docking results showed that glycine and curcu-min were the key active components of Biejia-Ezhu,and both had strong docking activity against key target proteins mTORC1 and ULK1.②The results of in vitro experiment showed that glycine combined with curcu-min significantly inhibited the proliferation and clonal formation ability of TNBC cells(P＜0.05),up-regula-ted the expression of autophagy marker LC3 Ⅱ/Ⅰ,down-regulated the expression of EGFR,down-regula-ted the expression of pathway protein mTORC1,p-mTOR,p-ULK1,and promoted the expression of path-way protein ULK1(P＜0.05).Conclusion The key component of Biejia-Ezhu against triple-negative breast cancer is glycine-curcumin,the mechanism of which may be related to the regulation of the mTORC1/ULK1 signaling pathway to promote autophagy.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.