Diabetic peripheral neuropathy (DPN) is one of the common chronic complications of diabetes, presenting with neuropathic pain, sensory abnormalities, and sensory loss, and may lead to foot infections, ulcers, or amputation in severe cases. Its pathogenesis remains unclear, with challenge in early diagnosis and limited treatment efficacy. Emerging evidences suggest that DPN involves in not only the peripheral nervous system but also the central nervous system (CNS). With advances in imaging technologies, multimodal MRI has become a key tool to investigate CNS involvement in DPN. This review summarizes the structural, functional, metabolic, and perfusion-related CNS changes in DPN patients based on structural MRI, functional MRI, MR spectroscopy, and perfusion-weighted imaging, aiming to help early detection, clinical subtyping, and personalized treatment of DPN.

Objective To construct and validate a predictive model for gastric precancerous le-sions based on urea breath test,serum pepsinogen(PG)and gastrin-17(G-17).Methods Partici-pants who underwent endoscopic screening for upper gastrointestinal tumors were retrospectively en-rolled as study subjects.Using random function,all participants were divided into training cohort of 2,788 cases(comprising 1,290 cases in precancerous lesion group and 1,498 cases in control group)and validation cohort of 1,194 cases(comprising 581 cases in precancerous lesion group and 613 cases in control group)at a ratio of 7 to 3.A simple model was established based on urea breath test,PG and G-17.Clinical data between the precancerous lesion group and the control group in the training cohort were compared.A predictive model for gastric precancerous lesions was constructed u-sing multifactorial Logistic regression analysis,and a scoring model for gastric precancerous lesions(the complete model)was developed based on this predictive model.The complete model,the simple model,the new ABC method,and the Li's score were all included in the validation cohort to compare the predictive performance of the four models.Results Multifactorial Logistic regression analysis indicated that male,smoking,positive Helicobacter pylori(Hp)infection,PG Ⅱ ≥10.19 μg/L,the ratio of PG Ⅰ to PG Ⅱ(PGR)≤11.87,and G-17 ≥3.82 pmol/L were independent risk factors for gastric precancerous lesions(P＜0.05).A predictive model for gastric precancerous lesions was constructed based on these risk factors,and the complete model was established based on the predic-tive model.The total score ranged from 0 to 12(with 6 to 12 indicating a high-risk population for gastric precancerous lesions and 0 to 5 indicating a low-risk population).When the complete model,the simple model,the new ABC method,and the Li's score were included in the validation cohort for comparison,the predictive values of the complete model and the simple model were similar.Both models demonstrated higher sensitivity,specificity,positive predictive value,negative predictive value,and accuracy compared to the new ABC method and the Li's score.Furthermore,the diag-nostic value of the simple model in the high-sensitivity region was slightly superior to that of the com-plete model.Conclusion The simple model constructed based on the urea breath test,PG and G-17 exhibits favorable predictive efficacy,calibration,and clinical utility,and is of positive signifi-cance for the early identification of patients with gastric precancerous lesions.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective This study aims to explore the application value of spectral CT and perfusion CT parameters in the pathological classification and prognostic assessment of lung cancer.Methods A total of 94 lung cancer patients confirmed by pathology at Shanghai Chest Hospital from January 2023 to November 2024 were included in the study,including 49 cases of lung adenocarcinoma(LUAD),30 cases of lung squamous cell carci-noma(LUSC),and 15 cases of small cell lung cancer(SCLC).All patients underwent spectral CT combined with perfusion scanning using a 256-slice Revolution Apex from GE.Two radiologists independently measured the spectral and perfusion parameters of the three groups of images,including spectral curve slope(K),iodine concentration in the lesion area(ICL),effective atomic number(Zeff),surface permeability(PS),and perfusion index(PI),and established a lung cancer pathological subtype discrimination prediction model based on spectral CT radiomics features.All subjects were randomly divided into a training group and a validation group at a ratio of 3∶1.The discrimination efficacy of the spectral discrimination model between different pathological subtypes and the discrimination efficacy of arterial and venous phase images were compared in multiple dimensions.The performance of the model was evaluated using the receiver operating characteristic(ROC)curve.Results Statistical analysis showed that the spectral curve slope,ICL,NIC,and Zeff of LUAD patients were significantly higher than those of LUSC and SCLC patients(P<0.05),while there were no significant differences in these parameters between LUSC and SCLC patients(P>0.05).Among the perfusion CT parameters,surface permeability(PS)showed significant differences among the three groups(P<0.05),while blood volume(BV),blood flow(BF),perfusion index(PI),time to peak(TTP),and mean transit time(MTT)did not show statistical differences.The multi-factor logistic regression model based on spectral parameters showed strong discriminatory performance:the area under the curve(AUC)of the LUAD and LUSC discrimination model was 0.806/0.77(training group/test group)in the arterial phase and 0.867/0.9(training group/test group)in the venous phase;the AUC of the LUAD and SCLC discrimination model was 0.885/0.883(training group/test group)in the arterial phase and 0.851/0.776(training group/test group)in the venous phase.Conclusion This study indicates that the multi-dimensional functional metabolic analysis indicators of spectral and perfusion CT imaging have significant value in the differential diagnosis of lung cancer pathological subtypes.The diagnostic model constructed by combining multiple spectral parameters can significantly improve the discrimination efficacy of lung adenocarcinoma,squamous cell carcinoma,and small cell lung cancer,providing precise imaging evidence for the formulation of individualized treatment plans.

Objective This study aims to explore the application value of spectral CT and perfusion CT parameters in the pathological classification and prognostic assessment of lung cancer.Methods A total of 94 lung cancer patients confirmed by pathology at Shanghai Chest Hospital from January 2023 to November 2024 were included in the study,including 49 cases of lung adenocarcinoma(LUAD),30 cases of lung squamous cell carci-noma(LUSC),and 15 cases of small cell lung cancer(SCLC).All patients underwent spectral CT combined with perfusion scanning using a 256-slice Revolution Apex from GE.Two radiologists independently measured the spectral and perfusion parameters of the three groups of images,including spectral curve slope(K),iodine concentration in the lesion area(ICL),effective atomic number(Zeff),surface permeability(PS),and perfusion index(PI),and established a lung cancer pathological subtype discrimination prediction model based on spectral CT radiomics features.All subjects were randomly divided into a training group and a validation group at a ratio of 3∶1.The discrimination efficacy of the spectral discrimination model between different pathological subtypes and the discrimination efficacy of arterial and venous phase images were compared in multiple dimensions.The performance of the model was evaluated using the receiver operating characteristic(ROC)curve.Results Statistical analysis showed that the spectral curve slope,ICL,NIC,and Zeff of LUAD patients were significantly higher than those of LUSC and SCLC patients(P<0.05),while there were no significant differences in these parameters between LUSC and SCLC patients(P>0.05).Among the perfusion CT parameters,surface permeability(PS)showed significant differences among the three groups(P<0.05),while blood volume(BV),blood flow(BF),perfusion index(PI),time to peak(TTP),and mean transit time(MTT)did not show statistical differences.The multi-factor logistic regression model based on spectral parameters showed strong discriminatory performance:the area under the curve(AUC)of the LUAD and LUSC discrimination model was 0.806/0.77(training group/test group)in the arterial phase and 0.867/0.9(training group/test group)in the venous phase;the AUC of the LUAD and SCLC discrimination model was 0.885/0.883(training group/test group)in the arterial phase and 0.851/0.776(training group/test group)in the venous phase.Conclusion This study indicates that the multi-dimensional functional metabolic analysis indicators of spectral and perfusion CT imaging have significant value in the differential diagnosis of lung cancer pathological subtypes.The diagnostic model constructed by combining multiple spectral parameters can significantly improve the discrimination efficacy of lung adenocarcinoma,squamous cell carcinoma,and small cell lung cancer,providing precise imaging evidence for the formulation of individualized treatment plans.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Diabetic peripheral neuropathy (DPN) is one of the common chronic complications of diabetes, presenting with neuropathic pain, sensory abnormalities, and sensory loss, and may lead to foot infections, ulcers, or amputation in severe cases. Its pathogenesis remains unclear, with challenge in early diagnosis and limited treatment efficacy. Emerging evidences suggest that DPN involves in not only the peripheral nervous system but also the central nervous system (CNS). With advances in imaging technologies, multimodal MRI has become a key tool to investigate CNS involvement in DPN. This review summarizes the structural, functional, metabolic, and perfusion-related CNS changes in DPN patients based on structural MRI, functional MRI, MR spectroscopy, and perfusion-weighted imaging, aiming to help early detection, clinical subtyping, and personalized treatment of DPN.

Objective:We aimed to develop a novel visualized model based on nomogram to predict postoperative overall survival.Methods:This was a multicenter, retrospective, observational cohort study, including participants with histologically confirmed gastric and colorectal cancer who underwent radical surgery from 11 medical centers in China from August 1, 2015 to June 30, 2018. Baseline characteristics, histopathological data and nutritional status, as assessed using Nutrition Risk Screening 2002 (NRS 2002) score and the scored Patient-Generated Subjective Global Assessment, were collected. The least absolute shrinkage and selection operator regression and Cox regression were used to identify variables to be included in the predictive model. Internal and external validations were performed.Results:There were 681 and 127 patients in the training and validation cohorts, respectively. A total of 188 deaths were observed over a median follow-up period of 59 (range: 58 to 60) months. Two independent predictors of NRS 2002 and Tumor-Node-Metastasis (TNM) stage were identified and incorporated into the prediction nomogram model together with the factor of age. The model's concordance index for 1-, 3- and 5-year overall survival was 0.696, 0.724, and 0.738 in the training cohort and 0.801, 0.812, and 0.793 in the validation cohort, respectively.Conclusions:In this study, a new nomogram prediction model based on NRS 2002 score was developed and validated for predicting the overall postoperative survival of patients with gastric colorectal cancer. This model has good differentiation, calibration and clinical practicability in predicting the long-term survival rate of patients with gastrointestinal cancer after radical surgery.

Objective:To predict the possible targets and signaling pathways of Jiangtang Xiaoke Granules in the treatment of diabetes mellitus (DM) using computer network pharmacology and molecular docking technology.Methods:The active components and targets of Jiangtang Xiaoke Granules were collected by ETCM; the targets of DM were searched from the databases of DisGeNET and GeneCards, and the intersections of the two were taken to draw a Venny diagram; String database was used for gene transformation and network interaction analysis; the network diagram was constructed with Cytoscape3.6.0; the predicted results were supported by molecular docking technology; GO and KEGG analysis was performed through Metascape database.Results:A total of 128 active components of Jiangtang Xiaoke Granules were screened, with 607 corresponding targets, 1 240 DM related targets, and 53 core targets. Molecular docking showed that the active components had good binding energy with the core targets. GO analysis yielded 46 functional items and KEGG analysis yielded 15 pathways.Conclusion:Jiangtang Xiaoke Granules regulate glucose homeostasis by participating in a variety of biological processes through multiple components, and multiple targets, including affecting lipids and atherosclerosis, Alzheimer disease, AMPK signaling pathway, Apelin signaling pathway, and glucagon signaling pathway.

In order to curb the excessive growth of medical expenses, the United States has initiated payment reform of diagnosis-related groups (DRG) since 1983, and developed a series of complementary measures to address issues such as overcoding and declining healthcare service quality which were exposed during the reform. The authors discussed the implementation of DRG payment reform in the United States, namely the case-mix specialization of medical institutions and the reduction of costs, as well as the relationship between the two. On this basis, the authors suggested that when implementing reforms to the medical insurance payment system in China, it is imperative to avoid such loopholes as overcoding by medical institutions and excessive pursuit of efficiency at the expense of quality control, as well as the decline of comprehensive rescue capability and quality of care incurred by the exacerbated specialization.