Objective:To evaluate the elastic characteristics of the pulmonary trunk and its distal branches in fetuses with tetralogy of Fallot（TOF）by Doppler echocardiography.Methods:A total of 42 fetuses with TOF（TOF group）and 84 gestational age-matched normal fetuses（control group）were prospectively collected from the Second Xiangya Hospital of Central South University from August 2022 to January 2023. The severity of TOF was classified into mild TOF（Z-score≥-2），moderate TOF（-40.05）. Conclusions:Fetuses with TOF present with increased MPA-PAS and decreased stiffness in the distal PA. Histological abnormalities of the pulmonary artery wall in fetuses with TOF have been observed during pregnancy.

Objective:To investigate the feasibility of the ultrasound "triangular method" in evaluating the morphology of the aortic arch in normal mid-to-late trimester fetuses，establish the gestational age-specific reference ranges for its morphological parameters，and to analyze their correlations with gestational age（GA）and cardiac valve annulus diameters.Methods:A prospective study was conducted on 317 normal singleton fetuses at 20-38 +6 weeks of gestation from the Second Xiangya Hospital of Central South University. Morphological parameters including arch length（a+b），arch width（w），arch height（h）and arch angle（θ）were measured using the "triangular method" in the aortic arch long-axis view. Arch tortuosity（a+b/w）and height-to-width ratio（h/w）were calculated. Linear regression was used to analyze correlations between arch length，width，height and GA，the reference intervals were established. Pearson correlation was applied to assess relationships between angle，tortuosity，height-to-width ratio and GA，cardiac valve annulus diameters（aortic，pulmonary，mitral，tricuspid）. Results:Aortic arch length，width and height showed strong positive correlations with GA（ r = 0.88，0.88，0.85；all P < 0.001）. The arch angle，tortuosity，and height-to-width ratio were independent of GA（all P > 0.05），with reference values of（69.2 ± 6.1）°，1.7 ± 0.1，and 0.7 ± 0.1，respectively. These parameters also showed no significant correlations with cardiac valve annulus diameters（all P > 0.05）. Conclusions:The ultrasound "triangular method" systematically quantifies fetal aortic arch morphology. The stability of arch angle，tortuosity and height-to-width ratio during mid-to-late gestation may provide a morphological benchmark for prenatal screening of aortic arch anomalies.

Objective:To evaluate the value of the proposed interpretable denoising deep learning model-grouped sharing convolutional attention-visual transformer（GSCAViT）for classifying normal fetal echocardiograms.Methods:A total of 2 501 images from 358 fetuses who underwent cardiac ultrasound examinations at Xiangya Second Hospital of Central South University from January to November 2024 were retrospectively analyzed. GSCAViT was constructed based on fetal echocardiograms from the three-vessel and trachea view，apical four-chamber view，long-axis view of the aortic arch，bicaval view，left ventricular outflow tract view，three-vessel view and right ventricular outflow tract view were compared with both baseline and improved models in the validation set to assess the performance of the classification echocardiography in terms of accuracy，precision，recall and F1-score. Its generalizability across test sets was assessed using the area under the ROC curve（AUC），sensitivity，specificity and F1-score. The impact of image features was interpreted using SHapley Additive exPlanations（SHAP）.The effectiveness of the GSCA module was compared through visual analysis，image parameter metrics and classification performance.Results:The GSCAViT model achieved classification performance for fetal echocardiograms second only to MaxViT，with an accuracy of 97.1%，precision of 97.1%，recall of 97.0%，and an F1-score of 97.0%. In the E10，E20 and E8 test sets，the AUCs of GSCAViT for the prediction of 7 types of fetal echocardiograms were 0.994，0.928 and 0.932，the sensitivities were 99.4%，81.3% and 72.9%，the specificities were 99.7%，96.8% and 94.8%，the F1-scores were 99.4%，81.3% and 67.6%，respectively. SHAP visualization indicated that the model could identify key structural features within the images. Images processed by the denoising-guided group-sharing convolutional attention module best captured and enhanced important regional features，achieving the highest contrast-to-noise ratio，peak signal-to-noise ratio and optimal classification performance，which demonstrated the module's effectiveness.Conclusions:The proposed GSCAViT model exhibits superior performance in classifying seven types of normal fetal echocardiograms compared to the baseline and some improved models. Furthermore，SHAP visualization enhances the interpretability of the classification results，and visual comparisons，image parameter analyses，as well as classification performance metrics confirming the effectiveness of the denoising-guided group-sharing convolutional attention module in the visual transformer model.

Gouty arthritis （GA） is an inflammatory disorder caused by monosodium urate （MSU） crystal deposition， accompanied by elevated oxidative stress and aberrant release of inflammatory cytokines， resulting in joint tissue damage and intense pain. Nuclear factor E₂-related factor 2 （Nrf2）， a key transcription factor regulating the antioxidant defence system， exerts cytoprotective effects through dissociation from Kelch-like ECH-associated protein 1 （Keap1） and activates downstream antioxidant response element （ARE）-mediated pathways. It can upregulate the expression of heme oxygenase-1 （HO-1）， NADH quinone oxidoreductase 1 （NQO1）， superoxide dismutase （SOD）， and glutathione transferase （GST） to preserve redox homeostasis. Moreover， Nrf2 can suppress activation of NOD-like receptor protein 3 （NLRP3） inflammasomes， reduce pro-inflammatory cytokine production and release， modulate nuclear factor-κB （NF-κB） transcriptional activity， regulate gut microbiota balance， enhance mitophagy， and inhibit apoptosis， so as to reduce joint inflammation and pain and promote body recovery. This review systematically examined recent advancements in traditional Chinese medicine （TCM） for GA prevention and treatment via regulating the Nrf2 signaling pathway. It delineated Nrf2's molecular mechanisms and its role in GA pathogenesis and elucidated how TCM intervenes in multiple pathways including Keap1/Nrf2/ARE， Nrf2/HO-1（NQO1）， and Nrf2/NF-κB/NLRP3 to exert therapeutic effects. The study demonstrated that TCM monomers and compounds effectively counteract oxidative damage， attenuate inflammatory responses， promote autophagy， and inhibit apoptosis via regulating the Nrf2 signaling pathway. These findings not only clarify the scientific basis of TCM in GA treatment but also offer strategic insights for developing novel Nrf2-targeted anti-gout drugs.

Diabetic kidney disease （DKD） stands as one of the most prevalent microvascular complications of diabetes，noted for its concealed onset and tendency to evolve into end-stage renal disease，profoundly impacting patients' life expectancy and quality of life. Epithelial-to-mesenchymal transition （EMT） is a central pathological process in the initiation and progression of DKD，facilitating disease advancement and renal fibrosis，thus representing a crucial focus of research into the pathological mechanisms of DKD. EMT is driven by the abnormal activation of signaling pathways，including transforming growth factor-β （TGF-β）/Smad，secreted glycoprotein/β-catenin，Notch，tumor necrosis factor-α （TNF-α）/nuclear factor-κB （NF-κB），and phosphatidylinositol-3-kinase/protein kinase B/mammalian target of rapamycin （PI3K/Akt/mTOR），leading to renal cellular injury and subsequently accelerating renal fibrosis and the progression of DKD. Traditional Chinese medicine （TCM），characterized by its multi-target and multi-pathway therapeutic approach，demonstrates unique advantages in addressing DKD and EMT. Recent research has shown that active ingredients in TCM，including glycosides，flavonoids，and polyphenols，as well as TCM formulas，can precisely target these relevant signaling pathways，effectively inhibiting cellular injury in DKD and intervening in the EMT process. These findings not only underscore the potential of TCM monomers and formulas in treating DKD and EMT but also pave new directions for research in this field within TCM. This paper systematically reviewed the signaling pathways associated with EMT and provided an in-depth analysis of the research achievements and underlying mechanisms of TCM monomers and formulas in treating DKD and intervening in EMT，aiming to offer new insights and directions for TCM in the treatment of DKD and research on EMT，thereby further promoting the modernization and development of TCM.

Diabetes is one of the major chronic non-communicable diseases in China. This article discusses the progress of diabetes prevention and control under the leadership of the government and how to integrate the National Diabetes Prevention and Control Center (DPCC) into the work of primary medical and health institutions in Yunnan Province, providing reference and experience for diabetes prevention and control efforts in the central and western regions of China.

Diabetes is one of the major chronic non-communicable diseases in China. This article discusses the progress of diabetes prevention and control under the leadership of the government and how to integrate the National Diabetes Prevention and Control Center (DPCC) into the work of primary medical and health institutions in Yunnan Province, providing reference and experience for diabetes prevention and control efforts in the central and western regions of China.

Objective:To evaluate the elastic characteristics of the pulmonary trunk and its distal branches in fetuses with tetralogy of Fallot（TOF）by Doppler echocardiography.Methods:A total of 42 fetuses with TOF（TOF group）and 84 gestational age-matched normal fetuses（control group）were prospectively collected from the Second Xiangya Hospital of Central South University from August 2022 to January 2023. The severity of TOF was classified into mild TOF（Z-score≥-2），moderate TOF（-40.05）. Conclusions:Fetuses with TOF present with increased MPA-PAS and decreased stiffness in the distal PA. Histological abnormalities of the pulmonary artery wall in fetuses with TOF have been observed during pregnancy.

Objective:To investigate the feasibility of the ultrasound "triangular method" in evaluating the morphology of the aortic arch in normal mid-to-late trimester fetuses，establish the gestational age-specific reference ranges for its morphological parameters，and to analyze their correlations with gestational age（GA）and cardiac valve annulus diameters.Methods:A prospective study was conducted on 317 normal singleton fetuses at 20-38 +6 weeks of gestation from the Second Xiangya Hospital of Central South University. Morphological parameters including arch length（a+b），arch width（w），arch height（h）and arch angle（θ）were measured using the "triangular method" in the aortic arch long-axis view. Arch tortuosity（a+b/w）and height-to-width ratio（h/w）were calculated. Linear regression was used to analyze correlations between arch length，width，height and GA，the reference intervals were established. Pearson correlation was applied to assess relationships between angle，tortuosity，height-to-width ratio and GA，cardiac valve annulus diameters（aortic，pulmonary，mitral，tricuspid）. Results:Aortic arch length，width and height showed strong positive correlations with GA（ r = 0.88，0.88，0.85；all P < 0.001）. The arch angle，tortuosity，and height-to-width ratio were independent of GA（all P > 0.05），with reference values of（69.2 ± 6.1）°，1.7 ± 0.1，and 0.7 ± 0.1，respectively. These parameters also showed no significant correlations with cardiac valve annulus diameters（all P > 0.05）. Conclusions:The ultrasound "triangular method" systematically quantifies fetal aortic arch morphology. The stability of arch angle，tortuosity and height-to-width ratio during mid-to-late gestation may provide a morphological benchmark for prenatal screening of aortic arch anomalies.

Objective:To evaluate the value of the proposed interpretable denoising deep learning model-grouped sharing convolutional attention-visual transformer（GSCAViT）for classifying normal fetal echocardiograms.Methods:A total of 2 501 images from 358 fetuses who underwent cardiac ultrasound examinations at Xiangya Second Hospital of Central South University from January to November 2024 were retrospectively analyzed. GSCAViT was constructed based on fetal echocardiograms from the three-vessel and trachea view，apical four-chamber view，long-axis view of the aortic arch，bicaval view，left ventricular outflow tract view，three-vessel view and right ventricular outflow tract view were compared with both baseline and improved models in the validation set to assess the performance of the classification echocardiography in terms of accuracy，precision，recall and F1-score. Its generalizability across test sets was assessed using the area under the ROC curve（AUC），sensitivity，specificity and F1-score. The impact of image features was interpreted using SHapley Additive exPlanations（SHAP）.The effectiveness of the GSCA module was compared through visual analysis，image parameter metrics and classification performance.Results:The GSCAViT model achieved classification performance for fetal echocardiograms second only to MaxViT，with an accuracy of 97.1%，precision of 97.1%，recall of 97.0%，and an F1-score of 97.0%. In the E10，E20 and E8 test sets，the AUCs of GSCAViT for the prediction of 7 types of fetal echocardiograms were 0.994，0.928 and 0.932，the sensitivities were 99.4%，81.3% and 72.9%，the specificities were 99.7%，96.8% and 94.8%，the F1-scores were 99.4%，81.3% and 67.6%，respectively. SHAP visualization indicated that the model could identify key structural features within the images. Images processed by the denoising-guided group-sharing convolutional attention module best captured and enhanced important regional features，achieving the highest contrast-to-noise ratio，peak signal-to-noise ratio and optimal classification performance，which demonstrated the module's effectiveness.Conclusions:The proposed GSCAViT model exhibits superior performance in classifying seven types of normal fetal echocardiograms compared to the baseline and some improved models. Furthermore，SHAP visualization enhances the interpretability of the classification results，and visual comparisons，image parameter analyses，as well as classification performance metrics confirming the effectiveness of the denoising-guided group-sharing convolutional attention module in the visual transformer model.