The key link to colorectal cancer progression is that epigenetic derangements promote reprogramming of glucose metabolism.Based on many studies on the relationship between spleen being the origin of acquired constitution and epigenetics,spleen qi dispersing essence and glucose metabolism,combined with the extensive experience of traditional Chinese medicine in the treatment of colorectal cancer and the accumulation of researches on glucose metabolism,it is believed that the"epigenetic-reprogramming of glucose metabolism"pathology of colorectal cancer is the microscopic essence of the key pathogenesis of"dysfunction of spleen transforming essences".The"promoting spleen and dispersing essences"method means that"promoting spleen"to reverse epigenetic derangements and"dispersing essences"to regulate reprogramming of glucose metabolism was put forward to treat colorectal cancer.Look forward to enrich the scientific connotation of the pathogenesis of"dysfunction of spleen transforming essences",new ideas and potential empirical basis for traditional Chinese medicine intervention in colorectal cancer were provided.

Objective To establish a prediction model for the occurrence of non-occupational carbon monoxide poisoning events in Beijing, and to provide scientific basis and theoretical support for the prevention and warning of poisoning events. Methods Based on the monitoring data of non-occupational carbon monoxide poisoning events in Beijing from 2016 to 2024, the seasonal ARIMA model and seasonal index model were established to analyze the data and predict the occurrence of events. Results Between 2016 and 2024, a total of 436 cases of non-occupational carbon monoxide poisoning were reported in Beijing, showing a downward trend. The established SARIMA model and seasonal index model were SARIMA (1,0,0) (1,1,0) 12, Yt = (-0.0339t+5.8863) × St, and the average relative errors were 65.42% and 29.19%, respectively. In terms of months, the SARIMA model had better predictive performance during April and summer (June to August), while the seasonal index model was superior in other months. By combining the two models, the predicted number of events in 2025 was as follows: 3, 2, 2, 3, 1, 5, 2, 7, 1, 1, 1, and 2. Conclusion The seasonal index model has the best prediction effect on the non-occupational carbon monoxide poisoning events in Beijing throughout the year, and the number of summer events predicted by SARIMA model is closer to the actual values. The two models can be combined to predict the trend of non-occupational carbon monoxide poisoning, which provides a scientific basis for the prevention and control of carbon monoxide poisoning in the future.

Objective To investigate the value of predicting microsatellite instability(MSI)status in endometrial cancer based on whole-tumor apparent diffusion coefficient(ADC)histogram.Methods The data of 131 endometrial cancer patients who underwent preoperative MRI examination and were confirmed by pathology were retrospectively analyzed.According to the pathological immu-nohistochemical results,they were divided into microsatellite stability(MSS)group(103 cases)and MSI group(28 cases).The whole-tumor volume of interest(VOI)was outlined using ITK-SNAP software,and ADC histogram analysis was performed using uAI Research Portal software.The t-test or Mann-Whitney U-test were used to compare the differences between the two groups,and multifactorial logistic regression analysis was used to screen independent predictors for the above parameters with differences.The area under the curve(AUC),sensitivity and specificity were calculated using the receiver operating characteristic(ROC)curve.Results The ADC histogram parameters that were statistically significant between groups were ADC10th,ADC90th,ADCmaximum,ADCmedian,ADCmean,ADCrange,ADCinterquartile range,ADCuniformity,ADCvariance,ADCenergy,ADCentropy,ADCtotal energy,ADCroot mean square,ADCmean absolute deviation,ADCrobust mean absolute deviation,all the above parameters were significantly smaller in the MSI group than in the MSS group.Further multifactorial logistic regression analysis results showed that ADCmedian[odds ratio(OR)=1.019,P=0.020]and ADCroot mean square(OR=0.977,P=0.005)were independent predictors of the MSI status in endometrial cancer.The results of ROC curve showed that the AUC of ADCmedian and ADCroot mean square for predicting MSI status were 0.699 and 0.731,respectively,and the AUC of combining the two parameters to predict MSI status was 0.760,with a sensitivity of 57.14%and a specificity of 86.41%.Conclusion The parameters of ADCmedian and ADCroot mean square based on whole-tumor ADC histogram can be used to predict the MSI status of endometrial cancer,and the combined use of these two parameters helps to improve the efficacy of predicting MSI.

Objective To investigate the consistency and diagnostic efficacy of 1.5T and 3.0T MRI in the kidney clear cell likeli-hood score(ccLS)v2.0.Methods A retrospective collection was conducted on the data of 176 pathologically confirmed small renal mass(SRM).Two radiologists independently scored the MRI images using the ccLS v2.0.The Kappa test was used to assess inter-observer consistency,and receiver operating characteristic(ROC)curves were plotted to analyze the diagnostic efficacy.The area under the curve(AUC),sensitivity,specificity,positive predictive value(PPV),and negative predictive value(NP V)were calculated.Results The inter-observer consistency for ccLS v2.0 score was good for 1.5T MRI and excellent for 3.0T MRI(Kappa values were 0.754 and 0.836,respectively).On 1.5T MRI examination,a ccLS≥4 points was identified as the optimal threshold,with AUC of 0.935 and 0.923 for the two radiologists,sensitivities of 92.45％and 88.68％,and specificities of 88.00％and 92.00％,respec-tively.For 3.0T MRI examination,using the same threshold,the AUC were 0.933 and 0.901,with sensitivities of 91.43％and 90.00％,and specificities of 78.57％and 78.57％for both radiologists.Conclusion The ccLS v2.0 demonstrates good consistency across high and low field intensity MRI,and a threshold of ccLS≥4 pionts provides high diagnostic efficacy for clear cell renal cell carcinoma(ccRCC).

[Purpose]To analyze the incidence and mortality of liver cancer in Fusui County of Guangxi Zhuang Autonomous Region in 2019 and the trend of change from 201 1 to 2019.[Meth-ods]Based on the incidence and mortality data of liver cancer in Fusui County from 2011 to 2019,the crude incidence rate,crude mortality rate,age-standardized rate by Chinese standard population(ASIRC/ASMRC),age-standardized rate by world standard population(ASMRW/ASM-RW),disability-adjusted life years(DALY),years of life lost(YLL),years of lived with disability(YLD)were calculated.The Joinpoint linear regression model was used to calculate the average annual percentage change(AAPC)of the ASIRC/ASMRC and DALY rate of liver cancer in Fusui County from 2011 to 2019.[Results]In 2019,there were 345 new cases and 298 deaths of liver cancer in Fusui County,accounting for 28.49％and 35.86％of all new cases and death cases of malignant tumors in Fusui County,respectively.The crude incidence rate,ASIRC and ASIRW were 74.71/105,67.55/105 and 65.63/105,respectively;the crude mortality rate,ASMRC and ASMRW were 64.53/105,58.78/105 and 56.88/105,respectively.In 2019,ASIRC/ASMRC of men were higher than those of women(105.32/105 and 95.67/105 for men;27.26/105 and 19.11/105 for women).The peak incidence and mortality rates were in the 65～69 and 80～84 age groups,re-spectively.The incidence rate of liver cancer in Fusui County declined from 82.50/105 in 2011 to 67.55/105 in 2019,with an AAPC of-3.01％(P=0.024),but the mortality rate did not have sig-nificant changes(AAPC=-1.44％,P=0.224).The rate of DALY decreased from 14.51/105 to 10.36/105,with an AAPC of-2.82％(P=0.050).[Conclusion]The incidence rate and DALY rate of liv-er cancer in Fusui County showed an overall decreasing trend from 2011 to 2019,but still re-mained at a high level.It is necessary to further strengthen the prevention,screening and early treatment of liver cancer in this region,especially for men and the elderly.

The key link to colorectal cancer progression is that epigenetic derangements promote reprogramming of glucose metabolism.Based on many studies on the relationship between spleen being the origin of acquired constitution and epigenetics,spleen qi dispersing essence and glucose metabolism,combined with the extensive experience of traditional Chinese medicine in the treatment of colorectal cancer and the accumulation of researches on glucose metabolism,it is believed that the"epigenetic-reprogramming of glucose metabolism"pathology of colorectal cancer is the microscopic essence of the key pathogenesis of"dysfunction of spleen transforming essences".The"promoting spleen and dispersing essences"method means that"promoting spleen"to reverse epigenetic derangements and"dispersing essences"to regulate reprogramming of glucose metabolism was put forward to treat colorectal cancer.Look forward to enrich the scientific connotation of the pathogenesis of"dysfunction of spleen transforming essences",new ideas and potential empirical basis for traditional Chinese medicine intervention in colorectal cancer were provided.

[Purpose]To analyze the incidence and mortality of liver cancer in Fusui County of Guangxi Zhuang Autonomous Region in 2019 and the trend of change from 201 1 to 2019.[Meth-ods]Based on the incidence and mortality data of liver cancer in Fusui County from 2011 to 2019,the crude incidence rate,crude mortality rate,age-standardized rate by Chinese standard population(ASIRC/ASMRC),age-standardized rate by world standard population(ASMRW/ASM-RW),disability-adjusted life years(DALY),years of life lost(YLL),years of lived with disability(YLD)were calculated.The Joinpoint linear regression model was used to calculate the average annual percentage change(AAPC)of the ASIRC/ASMRC and DALY rate of liver cancer in Fusui County from 2011 to 2019.[Results]In 2019,there were 345 new cases and 298 deaths of liver cancer in Fusui County,accounting for 28.49％and 35.86％of all new cases and death cases of malignant tumors in Fusui County,respectively.The crude incidence rate,ASIRC and ASIRW were 74.71/105,67.55/105 and 65.63/105,respectively;the crude mortality rate,ASMRC and ASMRW were 64.53/105,58.78/105 and 56.88/105,respectively.In 2019,ASIRC/ASMRC of men were higher than those of women(105.32/105 and 95.67/105 for men;27.26/105 and 19.11/105 for women).The peak incidence and mortality rates were in the 65～69 and 80～84 age groups,re-spectively.The incidence rate of liver cancer in Fusui County declined from 82.50/105 in 2011 to 67.55/105 in 2019,with an AAPC of-3.01％(P=0.024),but the mortality rate did not have sig-nificant changes(AAPC=-1.44％,P=0.224).The rate of DALY decreased from 14.51/105 to 10.36/105,with an AAPC of-2.82％(P=0.050).[Conclusion]The incidence rate and DALY rate of liv-er cancer in Fusui County showed an overall decreasing trend from 2011 to 2019,but still re-mained at a high level.It is necessary to further strengthen the prevention,screening and early treatment of liver cancer in this region,especially for men and the elderly.

Objective To investigate the consistency and diagnostic efficacy of 1.5T and 3.0T MRI in the kidney clear cell likeli-hood score(ccLS)v2.0.Methods A retrospective collection was conducted on the data of 176 pathologically confirmed small renal mass(SRM).Two radiologists independently scored the MRI images using the ccLS v2.0.The Kappa test was used to assess inter-observer consistency,and receiver operating characteristic(ROC)curves were plotted to analyze the diagnostic efficacy.The area under the curve(AUC),sensitivity,specificity,positive predictive value(PPV),and negative predictive value(NP V)were calculated.Results The inter-observer consistency for ccLS v2.0 score was good for 1.5T MRI and excellent for 3.0T MRI(Kappa values were 0.754 and 0.836,respectively).On 1.5T MRI examination,a ccLS≥4 points was identified as the optimal threshold,with AUC of 0.935 and 0.923 for the two radiologists,sensitivities of 92.45％and 88.68％,and specificities of 88.00％and 92.00％,respec-tively.For 3.0T MRI examination,using the same threshold,the AUC were 0.933 and 0.901,with sensitivities of 91.43％and 90.00％,and specificities of 78.57％and 78.57％for both radiologists.Conclusion The ccLS v2.0 demonstrates good consistency across high and low field intensity MRI,and a threshold of ccLS≥4 pionts provides high diagnostic efficacy for clear cell renal cell carcinoma(ccRCC).

Objective To investigate the value of predicting microsatellite instability(MSI)status in endometrial cancer based on whole-tumor apparent diffusion coefficient(ADC)histogram.Methods The data of 131 endometrial cancer patients who underwent preoperative MRI examination and were confirmed by pathology were retrospectively analyzed.According to the pathological immu-nohistochemical results,they were divided into microsatellite stability(MSS)group(103 cases)and MSI group(28 cases).The whole-tumor volume of interest(VOI)was outlined using ITK-SNAP software,and ADC histogram analysis was performed using uAI Research Portal software.The t-test or Mann-Whitney U-test were used to compare the differences between the two groups,and multifactorial logistic regression analysis was used to screen independent predictors for the above parameters with differences.The area under the curve(AUC),sensitivity and specificity were calculated using the receiver operating characteristic(ROC)curve.Results The ADC histogram parameters that were statistically significant between groups were ADC10th,ADC90th,ADCmaximum,ADCmedian,ADCmean,ADCrange,ADCinterquartile range,ADCuniformity,ADCvariance,ADCenergy,ADCentropy,ADCtotal energy,ADCroot mean square,ADCmean absolute deviation,ADCrobust mean absolute deviation,all the above parameters were significantly smaller in the MSI group than in the MSS group.Further multifactorial logistic regression analysis results showed that ADCmedian[odds ratio(OR)=1.019,P=0.020]and ADCroot mean square(OR=0.977,P=0.005)were independent predictors of the MSI status in endometrial cancer.The results of ROC curve showed that the AUC of ADCmedian and ADCroot mean square for predicting MSI status were 0.699 and 0.731,respectively,and the AUC of combining the two parameters to predict MSI status was 0.760,with a sensitivity of 57.14%and a specificity of 86.41%.Conclusion The parameters of ADCmedian and ADCroot mean square based on whole-tumor ADC histogram can be used to predict the MSI status of endometrial cancer,and the combined use of these two parameters helps to improve the efficacy of predicting MSI.

Objective To explore the comparative study of constructing prediction models for muscle invasive of bladder cancer based on different machine learning algorithms combined with MRI radiomic.Methods A total of 187 bladder cancer patients who underwent MRI examination and were confirmed by pathology were retrospectively selected.Patients were randomly divided into a training set and a test set in a 7∶3 ratio.The patients were divided into muscle invasive bladder cancer(MIBC)group and non-muscle invasive bladder cancer(NMIBC)group according to the surgical pathology results.Tumor volume of interest(VOI)was outlined on the images of T2 WI,diffusion weighted imaging(DWI),and apparent diffusion coefficient(ADC),and the radiomic features were extracted by A.K software,and dimensionality reduction was performed using the maximum relevance minimum redundancy(mRMR)algorithm combined with least absolute shrinkage and selection operator(LASSO).Six machine learning algorithms,including K-nearest neighbor(KNN),decision tree(DT),support vector machine(SVM),logistic regression(LR),random forest(RF),and explainable boosting machine(EBM)were used to construct the radiomic model and calculate the corresponding area under the curve(AUC),accuracy,sensitivity,and specificity,respectively.Results Six machine learning algorithms,including KNN,DT,SVM,LR,RF,and EBM were used to construct the radiomic model,and the AUC values for predicting MIBC in the training set were 0.863,0.838,0.853,0.866,0.977,0.997,and in the test set were 0.748,0.833,0.860,0.868,0.870,0.900.Among them,the MRI radiomic model constructed based on EBM had the highest predictive efficacy for MIBC,with AUC values,accuracy,sensitivity and specificity of 0.997,0.977,0.957 and 0.981 in the training set,and 0.900,0.877,0.800,and 0.894 in the test set,respectively.Conclusion Multiple machine learning algorithms combined with MRI radiomic to construct models have good predictive efficacy for MIBC,and the model constructed based on EBM shows the highest predictive value.