Abstract： In the hot strip rolling control system, the temperature distribution and deformation resistance are the main parameters affecting prediction of rolling force. In order to improve the model prediction preci...Abstract： In the hot strip rolling control system, the temperature distribution and deformation resistance are the main parameters affecting prediction of rolling force. In order to improve the model prediction precision, an optimiza- tion algorithm based on objective function was put forward, in which the penalty function index was adopted. During the adaptation process, the temperature distribution and deformation resistance were taken as the optimized parame ters, and the Nelder-Mead simplex algorithm was used to search the optimal solution of the objective function. Fur thermore, the temperature adaptation and force adaptation were solved simultaneously. Application results show that the method can improve the accuracy of the rolling force model obviously, and it can meet the demand of the indus trial production and has a good application prospect.展开更多
There are multiple biases in using observational studies to examine treatment effects such as those from prevalent drug users, immortal time and drug indications. We used renin angiotensin system(RAS) inhibitors and s...There are multiple biases in using observational studies to examine treatment effects such as those from prevalent drug users, immortal time and drug indications. We used renin angiotensin system(RAS) inhibitors and statins as reference drugs with proven efficacies in randomized clinical trials(RCTs) and examined their effectiveness in the prospective Hong Kong Diabetes Registry using adjustment methods proposed in the literature. Using time-dependent exposures to drug treatments yielded greatly inflated hazard ratios(HR) regarding the treatment effects of these drugs for cardiovascular disease(CVD) in type 2 diabetes. These errors were probably due to changing indications to use these drugs during follow up periods, especially at the time of drug commencement making time-dependent analysis extremely problematic. Using time-fixed analysis with exclusion of immortal time and adjustment for confounders at baseline and/or during follow-up periods, the HR of RAS inhibitors for CVD was comparable to that in RCT. The result supported the use of the Registry for performing pharmacoepidemiological analysis which revealed an attenuated low low-density lipoprotein cholesterol related cancer risk with RAS inhibitors. On the other hand, time-fixed analysis with including immortal time and adjustment for confounders at baseline and/or during follow-up periods, the HR of statins for CVD was similar to that in the RCT. Our results highlight the complexity and difficulty in removing these biases. We call for validations of the methods to cope with immortal time and drug use indications before applying them to particular research questions, so to avoid making erroneous conclusions.展开更多
Introduction:This study aimed to investigate the correlation between various plasma metabolites and the likelihood of developing diabetic nephropathy(DN)and construct a diagnostic model for DN in Chinese patients with...Introduction:This study aimed to investigate the correlation between various plasma metabolites and the likelihood of developing diabetic nephropathy(DN)and construct a diagnostic model for DN in Chinese patients with type 2 diabetes mellitus(T2DM).Methods:A cross-sectional investigation was conducted in a hospital setting.Based on medical data,a total of 743 patients from a tertiary hospital were selected and categorized into two groups:the diabetic nephropathy group(DN group)and the non-diabetic nephropathy group(non-DN group).Plasma levels of metabolites,including amino acids and acylcarnitines,were determined using a laser counter measurement system(LC-MS).Subsequently,partial least-squares regression was used to assess the significance of these metabolites.Receiver operating characteristic(ROC)curves were generated for factors that ranked highest in terms of relevance.Model performance was assessed using the curve(AUC).Results:Of the 743 patients with T2DM admitted to the hospital,145 had DN.Compared with the non-DN group,the DN group exhibited elevated systolic blood pressure(P=0.001),high-density lipoprotein cholesterol(P=0.01),and low-density lipoprotein cholesterol(P=0.042).Additionally,the DN group had a higher prevalence of stroke patients(P<0.001)and diabetic retinopathy patients(P<0.001).Finally,a risk model that included citrulline,leucine,tyrosine,valine,propionylcarnitine(C3),and palmitoylcarnitine(C16)was developed.This model achieved an AUC of 0.709,with a 95%confidence interval(CI)ranging from 0.626 to 0.793.Conclusions:A diagnostic model consisting of six plasma metabolites to assess the risk of DN in Chinese patients with T2DM may provide clues for future research.展开更多
基金Sponsored by National Natural Science Foundation of China(51074051)The Fundamental Research Funds for the CentralUniversities of China(N110307001)
文摘Abstract： In the hot strip rolling control system, the temperature distribution and deformation resistance are the main parameters affecting prediction of rolling force. In order to improve the model prediction precision, an optimiza- tion algorithm based on objective function was put forward, in which the penalty function index was adopted. During the adaptation process, the temperature distribution and deformation resistance were taken as the optimized parame ters, and the Nelder-Mead simplex algorithm was used to search the optimal solution of the objective function. Fur thermore, the temperature adaptation and force adaptation were solved simultaneously. Application results show that the method can improve the accuracy of the rolling force model obviously, and it can meet the demand of the indus trial production and has a good application prospect.
文摘There are multiple biases in using observational studies to examine treatment effects such as those from prevalent drug users, immortal time and drug indications. We used renin angiotensin system(RAS) inhibitors and statins as reference drugs with proven efficacies in randomized clinical trials(RCTs) and examined their effectiveness in the prospective Hong Kong Diabetes Registry using adjustment methods proposed in the literature. Using time-dependent exposures to drug treatments yielded greatly inflated hazard ratios(HR) regarding the treatment effects of these drugs for cardiovascular disease(CVD) in type 2 diabetes. These errors were probably due to changing indications to use these drugs during follow up periods, especially at the time of drug commencement making time-dependent analysis extremely problematic. Using time-fixed analysis with exclusion of immortal time and adjustment for confounders at baseline and/or during follow-up periods, the HR of RAS inhibitors for CVD was comparable to that in RCT. The result supported the use of the Registry for performing pharmacoepidemiological analysis which revealed an attenuated low low-density lipoprotein cholesterol related cancer risk with RAS inhibitors. On the other hand, time-fixed analysis with including immortal time and adjustment for confounders at baseline and/or during follow-up periods, the HR of statins for CVD was similar to that in the RCT. Our results highlight the complexity and difficulty in removing these biases. We call for validations of the methods to cope with immortal time and drug use indications before applying them to particular research questions, so to avoid making erroneous conclusions.
基金Funding for this project was provided by the Project for the National Key Research and Development Program of China(2021YFA1301202)the National Natural Science Foundation of China(82273676)the Liaoning Province Scientific and Technological Project(2021JH2/10300039).
文摘Introduction:This study aimed to investigate the correlation between various plasma metabolites and the likelihood of developing diabetic nephropathy(DN)and construct a diagnostic model for DN in Chinese patients with type 2 diabetes mellitus(T2DM).Methods:A cross-sectional investigation was conducted in a hospital setting.Based on medical data,a total of 743 patients from a tertiary hospital were selected and categorized into two groups:the diabetic nephropathy group(DN group)and the non-diabetic nephropathy group(non-DN group).Plasma levels of metabolites,including amino acids and acylcarnitines,were determined using a laser counter measurement system(LC-MS).Subsequently,partial least-squares regression was used to assess the significance of these metabolites.Receiver operating characteristic(ROC)curves were generated for factors that ranked highest in terms of relevance.Model performance was assessed using the curve(AUC).Results:Of the 743 patients with T2DM admitted to the hospital,145 had DN.Compared with the non-DN group,the DN group exhibited elevated systolic blood pressure(P=0.001),high-density lipoprotein cholesterol(P=0.01),and low-density lipoprotein cholesterol(P=0.042).Additionally,the DN group had a higher prevalence of stroke patients(P<0.001)and diabetic retinopathy patients(P<0.001).Finally,a risk model that included citrulline,leucine,tyrosine,valine,propionylcarnitine(C3),and palmitoylcarnitine(C16)was developed.This model achieved an AUC of 0.709,with a 95%confidence interval(CI)ranging from 0.626 to 0.793.Conclusions:A diagnostic model consisting of six plasma metabolites to assess the risk of DN in Chinese patients with T2DM may provide clues for future research.
