Objective:To explore the chain mediating effect of self-esteem and emotional resilience on the relationship between cyberbullying and depression of college students.Methods:From March to October 2023, a total of 346 college students were measured using Chinese version of Delaware bullying victimization scale-student, self esteem scale, adolescents' emotional resilience questionnaire, and patient health questionnaire-9, adopting a longitudinal tracking design with a total of 2 sessions and a 6-month interval between each session. SPSS 25.0 software was used for common method bias, descriptive statistical analysis, correlation analysis and mediating effect test.Results:(1) The results showed that cyberbullying T1 (4.54±1.60) was significantly and negatively correlated with self-esteem T2 (27.85±4.43) ( r=-0.152, P<0.01), while not significantly correlated with emotional resilience T2 (40.50±9.55) ( r=-0.093, P>0.05).Self-esteem T2 was significantly and positively correlated with emotional resilience T2( r=0.583, P<0.01), while negatively correlated with depression T2 ( r=-0.425, P<0.01). Emotional resilience T2 was significantly and negatively correlated with depression T2 ( r=-0.479, P<0.01).(2) Self-esteem and emotional resilience fully mediated the relationship between cyberbullying and depression. The mediating effect was consisted of two pathways including mediating effect of self-esteem and the chain mediating effect of self-esteem and emotional resilience, with effect value of 0.024 and 0.021 respectively. Conclusion:Cyberbullying can indirectly affect depression through the mediation of self-esteem and chain mediating effect of self-esteem and emotional resilience.

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.

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.

Objective:To explore the correlation between metabolic syndrome (MS), serum high-sensitivity C-reactive protein (hs-CRP) levels, their combination and the risk of digestive system malignancies.Methods:A prospective cohort study was conducted in the participants from the Kailuan cohort who took health examination in July 2006. Anthropometric parameters, epidemiological information, and laboratory test results were collected. Incidence and mortality of digestive system malignant tumors were collected through biennial health examinations and questionnaires. The follow-up period ended on December 31, 2021.According to MS status and hs-CRP levels (hs-CRP≤3 or >3 mg/L), the cohort was divided into 4 groups, induding MS -hs-CRP -, MS -hs-CRP +, MS + hs-CRP -, and MS + hs-CRP + group. Chi-squared test, one analysis of variance, and the Kruskal-Wallis H test were used for inter-group comparison among groups. Kaplan-Meier method was used to calculate the cumulative incidence of digestive system malignant tumors, and log-rank test was performed to compare the cumulative incidence among groups. Multivariable Cox proportional hazards regression models were used to evaluate the effects of MS and hs-CRP levels on the overall risk of digestive system malignant tumors, as well as the effects of their combination on the risk of digestive system malignant tumors of different site, and relevant confounding factors were adjusted.A sensitivity analysis was conducted by excluding individuals diagnosed with digestive system malignancies within one year of follow-up, as well as those taking antihypertensive, antidiabetic, or lipid-lowering medications. Results:A total of 92 916 participants were included in this study. Among them, 57 933 cases were in the MS -hs-CRP - group, 10 949 cases in the MS -hs-CRP + group, 18 412 cases in the MS + hs-CRP - group, and 5 622 cases in the MS + hs-CRP + group.The median follow-up period was 15.01 years (14.66 to 15.20 years). By the end of follow-up, these were 1 992 cases of new-onset digestive system malignant tumors. The cumulative incidence rates of digestive system malignant tumors of MS -hs-CRP -, MS -hs-CRP +, MS + hs-CRP -, and MS + hs-CRP + groups were 2.0%(1 164/57 933), 2.3%(249/10 949), 2.4%(440/18 412), and 2.5%(139/5 622), respectively. The difference in the cumulative incidence among the 4 groups was statistically significant ( χ2=14.09, P=0.003).The results of multivariate Cox analysis showed that, after hs-CRP level and other confounding factors were adjusted, the risk of developing digestive system malignant tumors in participants with MS was 21.4% higher than that in those without MS ( HR=1.214 (95% confidence interval (95% CI): 1.086 to 1.340), P<0.001). After MS status and other confounding factors were adjusted, the risk of developing digestive system malignant tumors in participants with high hs-CRP level (>3 mg/L) was 17.2% higher than those with low hs-CRP level (≤3 mg/L) ( HR=1.172 (95% CI: 1.042 to 1.303), P=0.008). After relevant confounding factors were adjusted, the risks of developing digestive system malignant tumors in the MS -hs-CRP +, MS + hs-CRP -, and MS + hs-CRP + groups increased by 17.2%, 21.4%, and 35.9%, respectively, as compared with that of the MS -hs-CRP - group ( HR=1.172 (95% CI: 1.017 to 1.399), P=0.028; HR=1.214 (95% CI: 1.074 to 1.356), P=0.002; HR=1.359 (95% CI: 1.135 to 1.635), P=0.001). Among the 4 groups, the overall risk of developing digestive system malignant tumors of MS + hs-CRP + group was the highest. After relevant confounding factors were adjusted, the risks of colorectal cancer, liver cancer, and pancreatic cancer of the MS + hs-CRP + group increased by 46.2%, 35.7%, and 88.3%, respectively, as compared with those of the MS -hs-CRP - group ( HR=1.462 (95% CI: 1.088 to 1.956), HR=1.357 (95% CI: 1.132 to 2.089), HR=1.883 (95% CI: 1.052 to 3.342)), suggesting that MS combined with high hs-CRP was a significant risk factor for increased incidences of colorectal cancer, liver cancer, and pancreatic cancer ( P=0.012, 0.016 and 0.033). After participants diagnosed with new digestive system malignancies within one year of follow-up and those taking antihypertensive, antidiabetic, or lipid-lowering medications (108 cases, 10 680 cases, 2 344 cases, 906 cases) were excluded, the results of sensitivity analysis indicated the increased risk of digestive system malignant tumors in the MS -hs-CRP +, MS + hs-CRP -, and MS + hs-CRP + groups were 12.1%, 21.4%, 28.7%; 18.2%, 21.4%, 24.8%; 16.4%, 21.4%, 32.2%; 17.3%, 20.4%, 35.8%. Among the 3 groups, the increased risk of developing digestive system malignant tumors of MS + hs-CRP + group was the highest. Conclusion:MS and hs-CRP >3 mg/L are both independent risk factors for developing digestive system malignant tumors, and their combination further increases the risk of developing digestive system malignant tumors.

Objective To compare the effectiveness of the heart rate variability threshold(HRVT),muscle oxygenation threshold(MOT),and their combined threshold(COMT)in predicting the ventila-tory threshold(VT)and lactate threshold(LT).Methods Twenty male athletes at or above the nation-al level were recruited to perform an incremental exercise test to determine VT and LT,during which gas exchange,muscle oxygenation,and heart rate variability were collected.The HRVT,MOT,and COMT methods were then applied,and their predictive validity was evaluated by comparing the correla-tions and agreements between heart rate(HR)and power output(PO)at VT and LT.Results For HR,VT1 showed strong correlation and agreement with MOT1(r=0.958,ICC=0.944)and COMT1(r=0.957,ICC=0.951),with COMT1 having the smallest mean bias(1.4 bpm)and the narrowest limits of agreement(LOA)(-5.4 to 8.2 bpm).Moreover,VT2 demonstrated the highest correlation and agree-ment with COMT2(r=0.985,ICC=0.982),with a mean bias of-0.7 bpm and LOA of-5.0 to 3.7 bpm.Meanwhile,LT showed high correlation and good agreement with COMT2(r=0.884,ICC=0.754)and MOT2(r=0.886,ICC=0.738),with mean biases of-6.8 bpm and-7.3 bpm,and LOA of-17.5 to 3.8 bpm and-17.9 to 3.2 bpm,respectively.For PO,VT1 had the best correlation and agreement with MOT1(r=0.836,ICC=0.808),with a mean bias of-0.2 W and LOA of-11.7 to 11.3 W.VT2 performed best correlation and agreement with COMT2(r=0.910,ICC=0.900),with a mean bias of 2.3 W and LOA of-8.9 to 13.5 W.In LT prediction,MOT2(r=0.736,ICC=0.692)outperformed COMT2(r=0.635,ICC=0.618),with mean biases of-2.6 W and 0.2 W,and LOA of-26.0 to 20.7 W and-26.6 to 27.1 W,respectively.Conclusion All three indicators—HRVT,MOT,and COMT—demonstrates high validity in predicting VT and LT.MOT1 performs best for predicting PO at VT1,while COMT2 shows the highest consistency for predicting both HR and PO at VT2.Howev-er,for LT prediction,MOT2 is more advantageous for predicting PO,whereas COMT2 is more accu-rate for predicting HR.Therefore,method selection should be tailored to the specific threshold type and measurement target.

Objective:To investigate the predictive value of different obesity indicators for colorectal cancer (CRC) risk in different gender populations.Methods:This observational study was conducted within the Kailuan Study (Registration Number: ChiCTR-TNC-11001489). From July 2006 to October 2007, a total of 101,510 employed and retired individuals underwent health examinations, including gastrointestinal disease screening, hematological tests, and questionnaires, at Kailuan General Hospital and its 10 affiliated hospitals. After excluding those with incomplete data, 93,606 participants were included in this study and divided into male (74 852) and female (18 754) groups. CRC incidence was collected through physical examinations and questionnaires every two years. Each participant's follow-up period began at the time of the questionnaire and ended upon CRC diagnosis, death, or December 31, 2021. Body Mass Index (BMI), waist circumference, waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) were quartiled (Q1, Q2, Q3, Q4), with Q1 serving as the control group. After adjusting for traditional risk factors such as age, total cholesterol, triglycerides, diabetes, hypertension, smoking status, alcohol consumption, and physical exercise, Cox regression models were used to calculate the correlations between BMI, waist circumference, WHR, WHtR, and CRC incidence in both male and female populations.Results:The age of all patients was (51±12) years, BMI was (25.06±3.49) kg/m 2, waist circumference was (86.94±9.97) cm, hip circumference was (97.30±8.81) cm, WHR was 0.89±0.07, and WHtR was 0.52±0.06.Female participants had significantly lower BMI, waist circumference, WHR, and WHtR compared to males, with statistically significant differences (all P<0.05). The mean follow-up duration for all participants was 15.01 (14.10±2.66) years, during which 718 CRC cases were identified, including 626 males (0.83%) and 92 females (0.49%). Cox proportional hazards models for males showed that CRC risk increased with waist circumference from Q3 (HR=1.43, 95%CI: 1.13-1.79, P=0.003) to Q4 (HR=1.45,95%CI: 1.14-1.82, P=0.002). Similarly, CRC risk increased with WHR from Q3 (HR=1.22, 95%CI: 1.01-1.53, P=0.007) to Q4 (HR=1.43, 95%CI: 1.14-1.79, P=0.002) and with WHtR from Q3 (HR=1.37, 95%CI: 1.08-1.74, P=0.009) to Q4 (HR=1.68, 95%CI: 1.33-2.12, P<0.001). For females, CRC risk increased with waist circumference from Q2 (HR=2.37, 95%CI: 1.20-4.67, P=0.012) to Q3 (HR=2.42, 95%CI: 1.21-4.84, P=0.013) but decreased in Q4 ( HR=2.08, 95%CI: 1.02-4.25, P=0.043). CRC risk increased significantly with WHR from Q2 (HR=2.20, 95%CI: 1.11-4.39, P=0.024) to Q3 (HR=2.89, 95%CI: 1.48-5.67, P=0.002) in females but was not statistically significant in Q4 ( P=0.074). Among females, CRC risk also increased significantly with WHtR in Q2 (HR=2.30, 95% CI: 1.16-4.56, P=0.017) and Q4 (HR=2.64, 95%CI: 1.32-5.29, P=0.006). There were no statistically significant differences in CRC risk associated with BMI in either male or female populations (both P>0.05). Conclusion:Waist circumference, WHR, and WHtR were better predictors of CRC risk than BMI in both male and female populations.

Objective:To explore the chain mediating effect of self-esteem and emotional resilience on the relationship between cyberbullying and depression of college students.Methods:From March to October 2023, a total of 346 college students were measured using Chinese version of Delaware bullying victimization scale-student, self esteem scale, adolescents' emotional resilience questionnaire, and patient health questionnaire-9, adopting a longitudinal tracking design with a total of 2 sessions and a 6-month interval between each session. SPSS 25.0 software was used for common method bias, descriptive statistical analysis, correlation analysis and mediating effect test.Results:(1) The results showed that cyberbullying T1 (4.54±1.60) was significantly and negatively correlated with self-esteem T2 (27.85±4.43) ( r=-0.152, P<0.01), while not significantly correlated with emotional resilience T2 (40.50±9.55) ( r=-0.093, P>0.05).Self-esteem T2 was significantly and positively correlated with emotional resilience T2( r=0.583, P<0.01), while negatively correlated with depression T2 ( r=-0.425, P<0.01). Emotional resilience T2 was significantly and negatively correlated with depression T2 ( r=-0.479, P<0.01).(2) Self-esteem and emotional resilience fully mediated the relationship between cyberbullying and depression. The mediating effect was consisted of two pathways including mediating effect of self-esteem and the chain mediating effect of self-esteem and emotional resilience, with effect value of 0.024 and 0.021 respectively. Conclusion:Cyberbullying can indirectly affect depression through the mediation of self-esteem and chain mediating effect of self-esteem and emotional resilience.

Objective:To investigate exercise fear condition and its influencing factors in patients with coronary heart dis-ease(CHD)involving in phase Ⅱ cardiac rehabilitation after percutaneous coronary intervention(PCI).Methods:Conven-ience sampling was performed among cardiac rehabilitation patients from a Shanxi grade-A tertiary hospital between Janu-ary 2023 and June 2023.General data questionnaire,Tampa Scale for Kinesiophobia-Short Version for Heart patients(TSK-SV H),the Multidimensional Scale of Perceived Social Support(MSPSS)and the Post Percutaneous Coronary In-tervention Health Literacy Scale(PPCIHLS)were used for assessment.Pearson and Spearman rank correlation analyses were applied to investigate the relationships between social support factors and health literacy factors with patients'fear of exercise;multivariate linear regression models and quantile regression models were used to analyze the influencing factors of fear of exercise.Results:Among the 118 patients,average TSK-SV H score was(33.78±3.79)points;10.2％patients showed significant fear.The correlation analysis showed that PPCIHLS score was negatively correlated with TSK-SV H score(r=-0.423,P＜0.001).Results from multivariate regression analysis indicated that health literacy,cardiac func-tion class and drinking status affected the average score of exercise fear(P＜0.05 all).The quantile regression model pro-vided additional insights,showing that the impact of factors such as living situation,drinking status,cardiac function class and health literacy on exercise fear varied across different quantiles.Notably,cardiac function class had a consistently posi-tive effect on TSK-SV H score at various quantiles.Conclusion:Improving health literacy and tailored rehabilitation plans are vital to reduce exercise fear and improve cardiac rehabilitation effect.

Objective To compare the effectiveness of the heart rate variability threshold(HRVT),muscle oxygenation threshold(MOT),and their combined threshold(COMT)in predicting the ventila-tory threshold(VT)and lactate threshold(LT).Methods Twenty male athletes at or above the nation-al level were recruited to perform an incremental exercise test to determine VT and LT,during which gas exchange,muscle oxygenation,and heart rate variability were collected.The HRVT,MOT,and COMT methods were then applied,and their predictive validity was evaluated by comparing the correla-tions and agreements between heart rate(HR)and power output(PO)at VT and LT.Results For HR,VT1 showed strong correlation and agreement with MOT1(r=0.958,ICC=0.944)and COMT1(r=0.957,ICC=0.951),with COMT1 having the smallest mean bias(1.4 bpm)and the narrowest limits of agreement(LOA)(-5.4 to 8.2 bpm).Moreover,VT2 demonstrated the highest correlation and agree-ment with COMT2(r=0.985,ICC=0.982),with a mean bias of-0.7 bpm and LOA of-5.0 to 3.7 bpm.Meanwhile,LT showed high correlation and good agreement with COMT2(r=0.884,ICC=0.754)and MOT2(r=0.886,ICC=0.738),with mean biases of-6.8 bpm and-7.3 bpm,and LOA of-17.5 to 3.8 bpm and-17.9 to 3.2 bpm,respectively.For PO,VT1 had the best correlation and agreement with MOT1(r=0.836,ICC=0.808),with a mean bias of-0.2 W and LOA of-11.7 to 11.3 W.VT2 performed best correlation and agreement with COMT2(r=0.910,ICC=0.900),with a mean bias of 2.3 W and LOA of-8.9 to 13.5 W.In LT prediction,MOT2(r=0.736,ICC=0.692)outperformed COMT2(r=0.635,ICC=0.618),with mean biases of-2.6 W and 0.2 W,and LOA of-26.0 to 20.7 W and-26.6 to 27.1 W,respectively.Conclusion All three indicators—HRVT,MOT,and COMT—demonstrates high validity in predicting VT and LT.MOT1 performs best for predicting PO at VT1,while COMT2 shows the highest consistency for predicting both HR and PO at VT2.Howev-er,for LT prediction,MOT2 is more advantageous for predicting PO,whereas COMT2 is more accu-rate for predicting HR.Therefore,method selection should be tailored to the specific threshold type and measurement target.

Objective:To investigate the predictive value of different obesity indicators for colorectal cancer (CRC) risk in different gender populations.Methods:This observational study was conducted within the Kailuan Study (Registration Number: ChiCTR-TNC-11001489). From July 2006 to October 2007, a total of 101,510 employed and retired individuals underwent health examinations, including gastrointestinal disease screening, hematological tests, and questionnaires, at Kailuan General Hospital and its 10 affiliated hospitals. After excluding those with incomplete data, 93,606 participants were included in this study and divided into male (74 852) and female (18 754) groups. CRC incidence was collected through physical examinations and questionnaires every two years. Each participant's follow-up period began at the time of the questionnaire and ended upon CRC diagnosis, death, or December 31, 2021. Body Mass Index (BMI), waist circumference, waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) were quartiled (Q1, Q2, Q3, Q4), with Q1 serving as the control group. After adjusting for traditional risk factors such as age, total cholesterol, triglycerides, diabetes, hypertension, smoking status, alcohol consumption, and physical exercise, Cox regression models were used to calculate the correlations between BMI, waist circumference, WHR, WHtR, and CRC incidence in both male and female populations.Results:The age of all patients was (51±12) years, BMI was (25.06±3.49) kg/m 2, waist circumference was (86.94±9.97) cm, hip circumference was (97.30±8.81) cm, WHR was 0.89±0.07, and WHtR was 0.52±0.06.Female participants had significantly lower BMI, waist circumference, WHR, and WHtR compared to males, with statistically significant differences (all P<0.05). The mean follow-up duration for all participants was 15.01 (14.10±2.66) years, during which 718 CRC cases were identified, including 626 males (0.83%) and 92 females (0.49%). Cox proportional hazards models for males showed that CRC risk increased with waist circumference from Q3 (HR=1.43, 95%CI: 1.13-1.79, P=0.003) to Q4 (HR=1.45,95%CI: 1.14-1.82, P=0.002). Similarly, CRC risk increased with WHR from Q3 (HR=1.22, 95%CI: 1.01-1.53, P=0.007) to Q4 (HR=1.43, 95%CI: 1.14-1.79, P=0.002) and with WHtR from Q3 (HR=1.37, 95%CI: 1.08-1.74, P=0.009) to Q4 (HR=1.68, 95%CI: 1.33-2.12, P<0.001). For females, CRC risk increased with waist circumference from Q2 (HR=2.37, 95%CI: 1.20-4.67, P=0.012) to Q3 (HR=2.42, 95%CI: 1.21-4.84, P=0.013) but decreased in Q4 ( HR=2.08, 95%CI: 1.02-4.25, P=0.043). CRC risk increased significantly with WHR from Q2 (HR=2.20, 95%CI: 1.11-4.39, P=0.024) to Q3 (HR=2.89, 95%CI: 1.48-5.67, P=0.002) in females but was not statistically significant in Q4 ( P=0.074). Among females, CRC risk also increased significantly with WHtR in Q2 (HR=2.30, 95% CI: 1.16-4.56, P=0.017) and Q4 (HR=2.64, 95%CI: 1.32-5.29, P=0.006). There were no statistically significant differences in CRC risk associated with BMI in either male or female populations (both P>0.05). Conclusion:Waist circumference, WHR, and WHtR were better predictors of CRC risk than BMI in both male and female populations.