Objective Analysis of the effects of relaxation training combined with exercise intervention in patients with colorectal cancer undergoing chemotherapy,aiming to provide reference for clinical nursing practice.Methods Using a convenience sampling method,80 colorectal cancer patients undergoing chemotherapy in the oncology ward of a tertiary A hospital in Changzhou,Jiangsu Province from November 2022 to November 2023 were selected as study subjects.Patients were divided into an experimental group and a control group using a random number table method,with 40 patients in each group.The experimental group received relaxation training combined with exercise interventionin addition to routine care provided to the control group.The control group received routine care.Differences in 6-minute walking distance,anxiety,depression and quality of life scores before and after six chemotherapy cycles were compared between the 2 groups.Results Finally,70 patients completed the intervention,with 35 patients in each group.After the intervention,there were differences in 6-minute walking distance,anxiety scores,depression scores,and overall health status scores between the 2 groups were all statistically significant(P＜0.001).Conclusion Relaxation training combined with exercise intervention can maintain exercise endurance in colorectal cancer patients undergoing chemotherapy and alleviate anxiety and depression to some extent,helping to improve patients' quality of life.

Objective:To explore the prognostic value of a combined model of baseline 18F-FDG PET/CT tumor metabolic parameters and clinical factors for predicting progression-free survival (PFS) in Hodgkin′s lymphoma (HL). Methods:From January 2014 to May 2023, 171 HL patients (102 males, 69 females; median age 40 years) who underwent 18F-FDG PET/CT before treatment at the First Affiliated Hospital of Nanjing Medical University and Nanjing Drum Tower Hospital were retrospectively collected. HL patients from the First Affiliated Hospital of Nanjing Medical University were classified as the training set (101 patients) and HL patients from Nanjing Drum Tower Hospital were classified as the validation set (70 patients). Clinical factors and tumor metabolic parameters associated with PFS were determined by multivariate Cox regression analysis, and then the combined model and the independent model of each factor were constructed respectively. The consistency index (C-index) and AUC were used to evaluate the predictive efficacy of models, and nomogram was constructed based on the optimal model, and calibration curves were used to assess the goodness of fit of the models. The differences in Kaplan-Meier survival curves of the high-risk and low-risk groups were compared using log-rank test. Results:The multivariate Cox regression analysis indicated that the independent prognostic factors associated with PFS were the Lugano staging (hazard ratio ( HR)=3.10, 95% CI: 1.17-8.23, P=0.023), total metabolic tumor volume (TMTV) ( HR=2.65, 95% CI: 1.23-5.74, P=0.014), and maximum distance between tumors ( Dmax) ( HR=2.23, 95% CI: 1.02-4.85, P=0.044). These factors were used to construct the combined model, with the highest prognostic efficacy of the C-index for the training and validation sets of 0.692 and 0.653, and the AUC of 0.732 and 0.697, respectively. The calibration curves demonstrated that the predictions made by the combined model were in high agreement with the actual results in both the training and validation sets. The Kaplan-Meier analysis revealed a significantly lower PFS rate in the high-risk group compared to the low-risk group both in training and validation sets ( χ2 values: 5.88 and 4.52, P values: 0.015 and 0.033). Conclusion:The combined model incorporating tumor metabolic parameters and clinical factors improves prognostic efficacy in predicting PFS in HL patients.

Objective:To explore the value of baseline 18F-FDG PET/CT metabolic parameters and related clinical factors in the prognostic assessment of patients with angioimmunoblastic T-cell lymphoma (AITL). Methods:From July 2013 to December 2023, 70 patients with AITL (44 males, 26 females, age (63.9±9.6) years) from Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University (32 cases) as well as the First Affiliated Hospital of Nanjing Medical University (38 cases) who were diagnosed pathologically and underwent PET/CT imaging prior to treatment were retrospectively analyzed. PET/CT metabolic parameters (calculated using the 41%SUV max threshold method) and related clinical factors were collected. The optimal cut-off values of metabolic parameters were determined by using the ROC curve analysis. Cox proportional risk regression models were used for prognostic analyses, prediction models were constructed and efficacies were assessed by calibration curves and time-dependent ROC curves. Results:With the follow-up of 19.0(10.0, 33.3) months, disease progression or recurrence occurred in 51 patients, and 28 patients died. ROC curves showed that the optimal cut-off values on diagnosing AITL of total metabolic tumor volume (TMTV), total lesion glycolysis (TLG), and SUV max were 767.1cm 3, 2159.6g and 13.0, respectively. TMTV (hazard ratio ( HR)=0.485, 95% CI: 0.252-0.935, P=0.031) and gender ( HR=0.441, 95% CI: 0.236-0.824, P=0.010) were independent risk factors for progression-free survival (PFS); TMTV ( HR=0.422, 95% CI: 0.178-0.997, P=0.049) and treatment regimen ( HR=0.346, 95% CI: 0.154-0.777, P=0.010) were independent risk factors for overall survival (OS). Time-dependent ROC curves indicated that the combined model of TMTV combining gender or treatment regimen had better prognostic results in predicting PFS (AUCs: 0.67-0.82) or OS (AUCs: 0.62-0.80) in patients with AITL. The calibration curve showed the predicted values of the combined models were in good consistency with the actual values. Conclusions:The metabolic parameter TMTV is an independent risk factor for PFS and OS in patients with AITL. The combined model of TMTV combining gender or treatment regimen can effectively improve the prognostic prediction efficacy of PFS or OS in patients with AITL.

Objective:To investigate the value of a cross-combination machine learning approach in constructing a PET radiomics score (RadScore) for predicting early treatment response and prognosis in patients with primary gastrointestinal diffuse large B-cell lymphoma (PGI-DLBCL).Methods:This retrospective cohort study was conducted on 108 patients (59 males and 49 females, age (55.6±12.1) years) diagnosed with PGI-DLBCL between November 2016 and December 2021 at Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University ( n=85) and West China Hospital, Sichuan University ( n=23). Patients were divided into a training set ( n=86) and a validation set ( n=22) with the ratio of 8∶2 using stratified random sampling method. Seven machine learning models were employed to generate 49 feature selection-classification candidates, and the optimal candidate was selected to construct the RadScore, with five-fold cross-validation applied to determine the best-performing model. Logistic regression analysis was performed to identify risk factors for early treatment response, and a radiomics nomogram was developed by integrating RadScore with clinical predictors. Survival results between different groups of RadScore was compared by log-rank test. Results:Nineteen predictive features were selected from 111 radiomic features to construct the RadScore. In the training set, lactate dehydrogenase (LDH) (odds ratio ( OR)=3.53, 95% CI: 1.21-10.31, P=0.021), intestinal involvement ( OR=3.04, 95% CI: 1.04-8.88, P=0.042), total lesion glycolysis (TLG; OR=6.73, 95% CI: 2.23-20.29, P<0.001) and RadScore ( OR=15.11, 95% CI: 3.95-57.80, P<0.001) were identified as independent risk factors for predicting early treatment response. The combined model integrating RadScore, LDH, intestinal involvement, and TLG demonstrated good discriminatory ability for early treatment response (AUC=0.860 in the training set; AUC=0.902 in the validation set). Significant differences were observed in progression-free survival (PFS) and overall survival (OS) between different RadScore groups ( χ2 values: 13.92 and 8.56, both P<0.01). Conclusions:The machine learning-based RadScore may effectively predict survival outcomes in patients with PGI-DLBCL. The combined model integrating RadScore, clinical factors, and metabolic indicators can predict early treatment response in PGI-DLBCL patients.

AIM:To investigate whether casein kinase 2(CK2)/calmodulin(CaM)/small-conductance Ca2+-activated K+channel type 2(SK2)signaling pathway mediates autophagy-induced sympathoexcitation in the paraventricu-lar nucleus(PVN)of rats with chronic heart failure(CHF).METHODS:We randomly divided 180 Wistar rats,aged 6 to 8 weeks,into 10 groups:sham+dimethyl sulfoxide(DMSO),sham+artificial cerebrospinal(aCSF),CHF+DMSO,CHF+aCSF,CHF+rapamycin(RAPA),CHF+3-methyladenine(3-MA),CHF+5,6-dichlorobenzimidazole riboside(DRB),CHF+calmidazolium chloride(CMDZ),CHF+N-cyclohexyl-N-[2-(3,5-dimethyl-1H-pyrazol-1-yl)-6-methyl-pyrimidin-4-yl]-amine(CyPPA),and CHF+apamin groups.We measured cardiac function,hemodynamic parameters,anatomic indicators,and sympathetic drive indicators(n=18).Western blot was used to examine the protein levels of mi-crotubule-associated protein 1 light chain 3-II(LC3-II)/LC3-I,beclin-1,P62,CK2α,SK2,and phosphorylated CaM.The number of SK2-positive neurons was measured using immunofluorescence staining.The NG108 cells were randomly divided into 6 groups:DMSO,aCSF,RAPA,3-MA,RAPA+DRB,and RAPA+CMDZ groups.Radioisotope 32P-ATP pro-tein kinase activity assays were used to detect CK2 activity in cultured NG108 cells.We used Western blot to examine the protein levels of CK2α,SK2,and phosphorylated CaM.RESULTS:Compared with CHF rats treated with vehicle,CHF rats treated with RAPA or apamin exhibited increased sympathetic drive indicators,but decreased left ventricular ejection fraction and fractional shortening(P<0.01).However,CHF symptoms,including sympathoexcitation,were attenuated by 3-MA,DRB,CMDZ or CyPPA infusion into the PVN(P<0.01).In CHF rats,RAPA infusion into the PVN induced CK2 activity,up-regulated LC3-II/LC3-I,beclin-1,CK2α,and phosphorylated CaM levels,but down-regulated P62 and SK2 expression,as well as the number of SK2-positive neurons(P<0.05 or P<0.01).In CHF rats,infusion of 3-MA or DRB into the PVN decreased CK2 activity,and down-regulated phosphorylated CaM level(P<0.01).Infusion of 3-MA,DRB or CMDZ into the PVN up-regulated SK2 expression and the number of SK2-positive neurons(P<0.01).In cultured NG108 cells,RAPA induced CK2 activation and up-regulated the expression of CK2α and the phosphorylation of CaM,but down-regulated SK2 expression(P<0.01).Treatment with RAPA increased the level of phosphorylated CaM and down-regulated SK2 expression in cultured NG108 cells(P<0.01),which was inhibited by DRB and CMDZ(P<0.05 or P<0.01).CONCLUSION:In rats with CHF,the CK2/CaM/SK2 signaling pathway in the PVN contributes to autophagy-induced sympathoexcitation.

AIM:To investigate whether casein kinase 2(CK2)/calmodulin(CaM)/small-conductance Ca2+-activated K+channel type 2(SK2)signaling pathway mediates autophagy-induced sympathoexcitation in the paraventricu-lar nucleus(PVN)of rats with chronic heart failure(CHF).METHODS:We randomly divided 180 Wistar rats,aged 6 to 8 weeks,into 10 groups:sham+dimethyl sulfoxide(DMSO),sham+artificial cerebrospinal(aCSF),CHF+DMSO,CHF+aCSF,CHF+rapamycin(RAPA),CHF+3-methyladenine(3-MA),CHF+5,6-dichlorobenzimidazole riboside(DRB),CHF+calmidazolium chloride(CMDZ),CHF+N-cyclohexyl-N-[2-(3,5-dimethyl-1H-pyrazol-1-yl)-6-methyl-pyrimidin-4-yl]-amine(CyPPA),and CHF+apamin groups.We measured cardiac function,hemodynamic parameters,anatomic indicators,and sympathetic drive indicators(n=18).Western blot was used to examine the protein levels of mi-crotubule-associated protein 1 light chain 3-II(LC3-II)/LC3-I,beclin-1,P62,CK2α,SK2,and phosphorylated CaM.The number of SK2-positive neurons was measured using immunofluorescence staining.The NG108 cells were randomly divided into 6 groups:DMSO,aCSF,RAPA,3-MA,RAPA+DRB,and RAPA+CMDZ groups.Radioisotope 32P-ATP pro-tein kinase activity assays were used to detect CK2 activity in cultured NG108 cells.We used Western blot to examine the protein levels of CK2α,SK2,and phosphorylated CaM.RESULTS:Compared with CHF rats treated with vehicle,CHF rats treated with RAPA or apamin exhibited increased sympathetic drive indicators,but decreased left ventricular ejection fraction and fractional shortening(P<0.01).However,CHF symptoms,including sympathoexcitation,were attenuated by 3-MA,DRB,CMDZ or CyPPA infusion into the PVN(P<0.01).In CHF rats,RAPA infusion into the PVN induced CK2 activity,up-regulated LC3-II/LC3-I,beclin-1,CK2α,and phosphorylated CaM levels,but down-regulated P62 and SK2 expression,as well as the number of SK2-positive neurons(P<0.05 or P<0.01).In CHF rats,infusion of 3-MA or DRB into the PVN decreased CK2 activity,and down-regulated phosphorylated CaM level(P<0.01).Infusion of 3-MA,DRB or CMDZ into the PVN up-regulated SK2 expression and the number of SK2-positive neurons(P<0.01).In cultured NG108 cells,RAPA induced CK2 activation and up-regulated the expression of CK2α and the phosphorylation of CaM,but down-regulated SK2 expression(P<0.01).Treatment with RAPA increased the level of phosphorylated CaM and down-regulated SK2 expression in cultured NG108 cells(P<0.01),which was inhibited by DRB and CMDZ(P<0.05 or P<0.01).CONCLUSION:In rats with CHF,the CK2/CaM/SK2 signaling pathway in the PVN contributes to autophagy-induced sympathoexcitation.

Objective Analysis of the effects of relaxation training combined with exercise intervention in patients with colorectal cancer undergoing chemotherapy,aiming to provide reference for clinical nursing practice.Methods Using a convenience sampling method,80 colorectal cancer patients undergoing chemotherapy in the oncology ward of a tertiary A hospital in Changzhou,Jiangsu Province from November 2022 to November 2023 were selected as study subjects.Patients were divided into an experimental group and a control group using a random number table method,with 40 patients in each group.The experimental group received relaxation training combined with exercise interventionin addition to routine care provided to the control group.The control group received routine care.Differences in 6-minute walking distance,anxiety,depression and quality of life scores before and after six chemotherapy cycles were compared between the 2 groups.Results Finally,70 patients completed the intervention,with 35 patients in each group.After the intervention,there were differences in 6-minute walking distance,anxiety scores,depression scores,and overall health status scores between the 2 groups were all statistically significant(P＜0.001).Conclusion Relaxation training combined with exercise intervention can maintain exercise endurance in colorectal cancer patients undergoing chemotherapy and alleviate anxiety and depression to some extent,helping to improve patients' quality of life.

Objective:To explore the prognostic value of a combined model of baseline 18F-FDG PET/CT tumor metabolic parameters and clinical factors for predicting progression-free survival (PFS) in Hodgkin′s lymphoma (HL). Methods:From January 2014 to May 2023, 171 HL patients (102 males, 69 females; median age 40 years) who underwent 18F-FDG PET/CT before treatment at the First Affiliated Hospital of Nanjing Medical University and Nanjing Drum Tower Hospital were retrospectively collected. HL patients from the First Affiliated Hospital of Nanjing Medical University were classified as the training set (101 patients) and HL patients from Nanjing Drum Tower Hospital were classified as the validation set (70 patients). Clinical factors and tumor metabolic parameters associated with PFS were determined by multivariate Cox regression analysis, and then the combined model and the independent model of each factor were constructed respectively. The consistency index (C-index) and AUC were used to evaluate the predictive efficacy of models, and nomogram was constructed based on the optimal model, and calibration curves were used to assess the goodness of fit of the models. The differences in Kaplan-Meier survival curves of the high-risk and low-risk groups were compared using log-rank test. Results:The multivariate Cox regression analysis indicated that the independent prognostic factors associated with PFS were the Lugano staging (hazard ratio ( HR)=3.10, 95% CI: 1.17-8.23, P=0.023), total metabolic tumor volume (TMTV) ( HR=2.65, 95% CI: 1.23-5.74, P=0.014), and maximum distance between tumors ( Dmax) ( HR=2.23, 95% CI: 1.02-4.85, P=0.044). These factors were used to construct the combined model, with the highest prognostic efficacy of the C-index for the training and validation sets of 0.692 and 0.653, and the AUC of 0.732 and 0.697, respectively. The calibration curves demonstrated that the predictions made by the combined model were in high agreement with the actual results in both the training and validation sets. The Kaplan-Meier analysis revealed a significantly lower PFS rate in the high-risk group compared to the low-risk group both in training and validation sets ( χ2 values: 5.88 and 4.52, P values: 0.015 and 0.033). Conclusion:The combined model incorporating tumor metabolic parameters and clinical factors improves prognostic efficacy in predicting PFS in HL patients.

Objective:To explore the value of baseline 18F-FDG PET/CT metabolic parameters and related clinical factors in the prognostic assessment of patients with angioimmunoblastic T-cell lymphoma (AITL). Methods:From July 2013 to December 2023, 70 patients with AITL (44 males, 26 females, age (63.9±9.6) years) from Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University (32 cases) as well as the First Affiliated Hospital of Nanjing Medical University (38 cases) who were diagnosed pathologically and underwent PET/CT imaging prior to treatment were retrospectively analyzed. PET/CT metabolic parameters (calculated using the 41%SUV max threshold method) and related clinical factors were collected. The optimal cut-off values of metabolic parameters were determined by using the ROC curve analysis. Cox proportional risk regression models were used for prognostic analyses, prediction models were constructed and efficacies were assessed by calibration curves and time-dependent ROC curves. Results:With the follow-up of 19.0(10.0, 33.3) months, disease progression or recurrence occurred in 51 patients, and 28 patients died. ROC curves showed that the optimal cut-off values on diagnosing AITL of total metabolic tumor volume (TMTV), total lesion glycolysis (TLG), and SUV max were 767.1cm 3, 2159.6g and 13.0, respectively. TMTV (hazard ratio ( HR)=0.485, 95% CI: 0.252-0.935, P=0.031) and gender ( HR=0.441, 95% CI: 0.236-0.824, P=0.010) were independent risk factors for progression-free survival (PFS); TMTV ( HR=0.422, 95% CI: 0.178-0.997, P=0.049) and treatment regimen ( HR=0.346, 95% CI: 0.154-0.777, P=0.010) were independent risk factors for overall survival (OS). Time-dependent ROC curves indicated that the combined model of TMTV combining gender or treatment regimen had better prognostic results in predicting PFS (AUCs: 0.67-0.82) or OS (AUCs: 0.62-0.80) in patients with AITL. The calibration curve showed the predicted values of the combined models were in good consistency with the actual values. Conclusions:The metabolic parameter TMTV is an independent risk factor for PFS and OS in patients with AITL. The combined model of TMTV combining gender or treatment regimen can effectively improve the prognostic prediction efficacy of PFS or OS in patients with AITL.

Objective:To investigate the value of a cross-combination machine learning approach in constructing a PET radiomics score (RadScore) for predicting early treatment response and prognosis in patients with primary gastrointestinal diffuse large B-cell lymphoma (PGI-DLBCL).Methods:This retrospective cohort study was conducted on 108 patients (59 males and 49 females, age (55.6±12.1) years) diagnosed with PGI-DLBCL between November 2016 and December 2021 at Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University ( n=85) and West China Hospital, Sichuan University ( n=23). Patients were divided into a training set ( n=86) and a validation set ( n=22) with the ratio of 8∶2 using stratified random sampling method. Seven machine learning models were employed to generate 49 feature selection-classification candidates, and the optimal candidate was selected to construct the RadScore, with five-fold cross-validation applied to determine the best-performing model. Logistic regression analysis was performed to identify risk factors for early treatment response, and a radiomics nomogram was developed by integrating RadScore with clinical predictors. Survival results between different groups of RadScore was compared by log-rank test. Results:Nineteen predictive features were selected from 111 radiomic features to construct the RadScore. In the training set, lactate dehydrogenase (LDH) (odds ratio ( OR)=3.53, 95% CI: 1.21-10.31, P=0.021), intestinal involvement ( OR=3.04, 95% CI: 1.04-8.88, P=0.042), total lesion glycolysis (TLG; OR=6.73, 95% CI: 2.23-20.29, P<0.001) and RadScore ( OR=15.11, 95% CI: 3.95-57.80, P<0.001) were identified as independent risk factors for predicting early treatment response. The combined model integrating RadScore, LDH, intestinal involvement, and TLG demonstrated good discriminatory ability for early treatment response (AUC=0.860 in the training set; AUC=0.902 in the validation set). Significant differences were observed in progression-free survival (PFS) and overall survival (OS) between different RadScore groups ( χ2 values: 13.92 and 8.56, both P<0.01). Conclusions:The machine learning-based RadScore may effectively predict survival outcomes in patients with PGI-DLBCL. The combined model integrating RadScore, clinical factors, and metabolic indicators can predict early treatment response in PGI-DLBCL patients.