Objective : To explore the causal relationship between 46 phenotypes ( including 15 seropositive case- control phenotypes and 31 quantitative antibody-measurement phenotypes) and ulcerative colitis( UC) using two- sample bidirectional Mendelian randomization( TSMR) . Methods: Single nucleotide polymorphisms ( SNPs) sig- nificantly associated with the relative abundance of the 46 antibody sera were extracted as instrumental variables ac- cording to preset thresholds . Summary statistics for UC were obtained from the OPEN GWAS database ( n = 47 745) . MR-Egger regression , weighted median method ( WME) , inverse variance weighting ( IVW) , the simple mode method (SM) , and weighted multitude method (WM) were used to estimate the causal relationship between antibody levels and UC , primarily using the IVW method . The results were assessed according to the effect indica- tor dominance ratios (OR) and 95% confidence intervals (CI) . Sensitivity analysis , heterogeneity test , gene plei- otropy test , and outlier test (MR-PRESSO) were combined to verify the stability and reliability of the results , and the causal association study was performed again using reverse Mendelian randomization(MR) . Results : IVW re- sults showed that Epstein-Barr( EB) virus EA-D antibody levels ( OR = 0. 806 , 95% CI = 0. 693 - 0. 939 , P < 0. 01) , Epstein-Barr virus EBNA-1 antibody levels ( OR = 1 . 870% , 95% CI = 1 . 480 - 2. 360 , P < 0. 000 1) , Anti-polyomavirus 2 IgG seropositivity (OR = 0. 570 , 95% CI = 0. 435 - 0. 746 , P < 0. 000 1) were associated with UC . The inverse MR analysis revealed a causal effect on anti-polyomavirus 2 IgG seropositivity , and none of the a- bove revealed genetic pleiotropy or significant heterogeneity of IVs . Conclusion EB virus EBNA-1 antibody levels are positively associated with the risk of UC , while EB virus EA-D antibody levels and anti-polyomavirus 2 IgG se- ropositivity are negatively associated with the risk of UC , indicating that they are protective factors for UC .

Objective To compare the consistency of voice parameters collected by commonly used smart-phone brands in China and professional recording equipment,and to study whether smartphones can be used for voice research.Methods A total of 67 normal subjects were selected for voice recording using six different smart-phone brands(via the"Active Health"screening APP from the National Key Research and Development Program)and professional recording equipment.Acoustic voice parameters such as fundamental frequency parameters,fre-quency variation parameters,amplitude variation parameters,formant parameters,and energy parameters were ex-tracted from the vowels/a/,/i/,and/u/.A one-way ANOVA test and Tukey's HSD post-hoc comparisons were conducted on the independent variables.Results There were no significant differences between smartphones and professional recording equipment in terms of fundamental frequency parameters such as median F0,mean F0,max F0 and min F0;frequency parameters such as jitter local,jitter local absolute,jitter rap,jitter ppq5,and jitter ddp;amplitude parameters such as shimmer local,shimmer local dB,shimmer apq3,shimmer apq5,shimmer apq11,and shimmer dda;and formant parameters such as F1,F2,F3,and F4.However,significant differences were found in energy parameters such as mean energy(F=31.171,P＜0.001),max energy(F=34.193,P＜0.001),and min energy(F=5.453,P＜0.001)between smartphones and professional recording equipment.Conclusion The smartphones using the"Active Health"screening app from the National Key Research and Development Program can replace professional recording equipment for voice research.However,caution should be exercised when selec-ting energy-related acoustic parameters.

Objective To compare the consistency of voice parameters collected by commonly used smart-phone brands in China and professional recording equipment,and to study whether smartphones can be used for voice research.Methods A total of 67 normal subjects were selected for voice recording using six different smart-phone brands(via the"Active Health"screening APP from the National Key Research and Development Program)and professional recording equipment.Acoustic voice parameters such as fundamental frequency parameters,fre-quency variation parameters,amplitude variation parameters,formant parameters,and energy parameters were ex-tracted from the vowels/a/,/i/,and/u/.A one-way ANOVA test and Tukey's HSD post-hoc comparisons were conducted on the independent variables.Results There were no significant differences between smartphones and professional recording equipment in terms of fundamental frequency parameters such as median F0,mean F0,max F0 and min F0;frequency parameters such as jitter local,jitter local absolute,jitter rap,jitter ppq5,and jitter ddp;amplitude parameters such as shimmer local,shimmer local dB,shimmer apq3,shimmer apq5,shimmer apq11,and shimmer dda;and formant parameters such as F1,F2,F3,and F4.However,significant differences were found in energy parameters such as mean energy(F=31.171,P＜0.001),max energy(F=34.193,P＜0.001),and min energy(F=5.453,P＜0.001)between smartphones and professional recording equipment.Conclusion The smartphones using the"Active Health"screening app from the National Key Research and Development Program can replace professional recording equipment for voice research.However,caution should be exercised when selec-ting energy-related acoustic parameters.

Objective To investigate the incidence of moderate to severe cancer-related fatigue in bone tumor chemotherapy patients and its influence factors were analyzed.Methods Totally 265 bone tumor chemotherapy patients who received chemotherapy for the first time in our hospital from January 2021 to June 2023 were selected as the research subjects by convenience sampling method.A general information survey Hamilton anxiety scale,Hamilton depression scale,simplified coping style questionnaire and the Piper fatigue scale revised(PFS-R)were used to investigate the cancer-related fatigue status of bone tumor chemotherapy patients,and the logistic regression analysis was used to analyze its influencing factors.Results Totally 239 patients completed the study.Among 239 bone tumor chemotherapy patients,154 cases had moderate to severe cancer-related fatigue,the incidence rate was 64.44%.The Logistic regression analysis showed that daily sleep time<5 hours,low body weight,and high anxiety and depression scores were risk factors for moderate to severe cancer-related fatigue in bone tumor chemotherapy patients,while active coping strategies was protective factors(all P<0.05).Conclusion The incidence of moderate to severe cancer-related fatigue in bone tumor chemotherapy patients is relatively high.Preintervention is needed for patients with low body weight,short sleep time,anxiety,depression,and negative coping strategies to reduce the occurrence of moderate to severe cancer-related fatigue in patients.

Objective To investigate the incidence of moderate to severe cancer-related fatigue in bone tumor chemotherapy patients and its influence factors were analyzed.Methods Totally 265 bone tumor chemotherapy patients who received chemotherapy for the first time in our hospital from January 2021 to June 2023 were selected as the research subjects by convenience sampling method.A general information survey Hamilton anxiety scale,Hamilton depression scale,simplified coping style questionnaire and the Piper fatigue scale revised(PFS-R)were used to investigate the cancer-related fatigue status of bone tumor chemotherapy patients,and the logistic regression analysis was used to analyze its influencing factors.Results Totally 239 patients completed the study.Among 239 bone tumor chemotherapy patients,154 cases had moderate to severe cancer-related fatigue,the incidence rate was 64.44%.The Logistic regression analysis showed that daily sleep time<5 hours,low body weight,and high anxiety and depression scores were risk factors for moderate to severe cancer-related fatigue in bone tumor chemotherapy patients,while active coping strategies was protective factors(all P<0.05).Conclusion The incidence of moderate to severe cancer-related fatigue in bone tumor chemotherapy patients is relatively high.Preintervention is needed for patients with low body weight,short sleep time,anxiety,depression,and negative coping strategies to reduce the occurrence of moderate to severe cancer-related fatigue in patients.