Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Ferroptosis is an iron-dependent cell death caused by phospholipid peroxidation damage of polyunsaturated fatty acids on cell membranes and involves several pathways, including the iron homeostasis regulatory pathway, the cystine glutamate reverse transporter (system Xc) pathway and the voltage-dependent anion channel (VDAC) pathway. Ferroptosis is involved in the development of several diseases (e. g. myocardial infarction, stroke, cancer and degenerative diseases). The ubiquitination is an important post-translational modification of various protein molecules in the organism. Studies have shown that regulating the ubiquitination of ferroptosis pathway-related molecules can control cellular ferroptosis. Targeting the ubiquitination of ferroptosis pathway-related molecules can effectively promote or inhibit ferroptosis, which is expected to be a new strategy for the treatment of cancer or cardiovascular diseases. In this paper we review the progress of the ferroptosis pathways and the ubiquitination modification of ferroptosis-related molecules.

Humans ; Proto-Oncogene Proteins p21(ras)/genetics* ; Prognosis ; Biomarkers, Tumor/genetics* ; Mutation/genetics* ; Colorectal Neoplasms/genetics* ; Proto-Oncogene Proteins B-raf/metabolism*

OBJECTIVE: To explore the mechanism of electroacupuncture (EA) in promoting recovery of the facial function with the involvement of autophagy, glial cell line-derived neurotrophic factor (GDNF), and phosphatidylinositol-3-kinase (PI3K)/mammalian target of rapamycin (mTOR) signaling pathway. METHODS: Seventy-two male Sprague-Dawley rats were randomly allocated into the control, sham-operated, facial nerve injury (FNI), EA, EA+3-methyladenine (3-MA), and EA+GDNF antagonist groups using a random number table, with 12 rats in each group. An FNI rat model was established with facial nerve crushing method. EA intervention was conducted at Dicang (ST 4), Jiache (ST 6), Yifeng (SJ 17), and Hegu (LI 4) acupoints for 2 weeks. The Simone's 10-Point Scale was utilized to monitor the recovery of facial function. The histopathological evaluation of facial nerves was performed using hematoxylin-eosin (HE) staining. The levels of Beclin-1, light chain 3 (LC3), and P62 were detected by immunohistochemistry (IHC), immunofluorescence, and reverse transcription-polymerase chain reaction, respectively. Additionally, IHC was also used to detect the levels of GDNF, Rai, PI3K, and mTOR. RESULTS: The facial functional scores were significantly increased in the EA group than the FNI group (P<0.05 or P<0.01). HE staining showed nerve axons and myelin sheaths, which were destroyed immediately after the injury, were recovered with EA treatment. The expressions of Beclin-1 and LC3 were significantly elevated and the expression of P62 was markedly reduced in FNI rats (P<0.01); however, EA treatment reversed these abnormal changes (P<0.01). Meanwhile, EA stimulation significantly increased the levels of GDNF, Rai, PI3K, and mTOR (P<0.01). After exogenous administration with autophagy inhibitor 3-MA or GDNF antagonist, the repair effect of EA on facial function was attenuated (P<0.05 or P<0.01). CONCLUSIONS EA could promote the recovery of facial function and repair the facial nerve damages in a rat model of FNI. EA may exert this neuroreparative effect through mediating the release of GDNF, activating the PI3K/mTOR signaling pathway, and further regulating the autophagy of facial nerves.
Rats ; Male ; Animals ; Rats, Sprague-Dawley ; Electroacupuncture ; Phosphatidylinositol 3-Kinase/metabolism* ; Facial Nerve Injuries/therapy* ; Phosphatidylinositol 3-Kinases/metabolism* ; Beclin-1 ; Glial Cell Line-Derived Neurotrophic Factor ; Signal Transduction ; TOR Serine-Threonine Kinases/metabolism* ; Autophagy ; Mammals/metabolism*

Objective To develop an intelligent model for differential diagnosis of atrioventricular nodal re-entrant tachycardia(AVNRT)and atrioventricular re-entrant tachycardia(AVRT)using 12-lead wearable electrocardiogram devices.Methods A total of 356 samples of 12-lead supraventricular tachycardia(SVT)electrocardiograms recorded by wearable devices were randomly divided into training and validation sets using 5-fold cross validation to establish the intelligent classification model,and 101 patients with the diagnosis of SVT undergoing electrophysiological studies and radiofrequency ablation from October,2021 to March,2023 were selected as the testing set.The changes in electrocardiogram parameters before and during induced tachycardia were compared.Based on multiscale deep neural network,an intelligent diagnosis model for classifying SVT mechanisms was constructed and validated.The 3-lead electrocardiogram signals from Ⅱ,Ⅲ,and V1 were extracted to build new classification models,whose diagnostic efficacy was compared with that of the 12-lead model.Results Of the 101 patients with SVT in the testing set,68 were diagnosed with AVNRT and 33 were diagnosed with AVRT by electrophysiological study.The pre-trained model achieved a high area under the precision-recall curve(0.9492)and F1 score(0.8195)for identifying AVNRT in the validation set.The total F1 scores of the lead Ⅱ,Ⅲ,V1,3-lead and 12-lead intelligent diagnostic models in the testing set were 0.5597,0.6061,0.3419,0.6003 and 0.6136,respectively.Compared with the 12-lead classification model,the lead-Ⅲ model had a net reclassification index improvement of-0.029(P=0.878)and an integrated discrimination index improvement of-0.005(P=0.965).Conclusion The intelligent diagnostic model based on multiscale deep neural network using wearable electrocardiogram devices has an acceptable accuracy for classifying SVT mechanisms.

Objective To develop an intelligent model for differential diagnosis of atrioventricular nodal re-entrant tachycardia(AVNRT)and atrioventricular re-entrant tachycardia(AVRT)using 12-lead wearable electrocardiogram devices.Methods A total of 356 samples of 12-lead supraventricular tachycardia(SVT)electrocardiograms recorded by wearable devices were randomly divided into training and validation sets using 5-fold cross validation to establish the intelligent classification model,and 101 patients with the diagnosis of SVT undergoing electrophysiological studies and radiofrequency ablation from October,2021 to March,2023 were selected as the testing set.The changes in electrocardiogram parameters before and during induced tachycardia were compared.Based on multiscale deep neural network,an intelligent diagnosis model for classifying SVT mechanisms was constructed and validated.The 3-lead electrocardiogram signals from Ⅱ,Ⅲ,and V1 were extracted to build new classification models,whose diagnostic efficacy was compared with that of the 12-lead model.Results Of the 101 patients with SVT in the testing set,68 were diagnosed with AVNRT and 33 were diagnosed with AVRT by electrophysiological study.The pre-trained model achieved a high area under the precision-recall curve(0.9492)and F1 score(0.8195)for identifying AVNRT in the validation set.The total F1 scores of the lead Ⅱ,Ⅲ,V1,3-lead and 12-lead intelligent diagnostic models in the testing set were 0.5597,0.6061,0.3419,0.6003 and 0.6136,respectively.Compared with the 12-lead classification model,the lead-Ⅲ model had a net reclassification index improvement of-0.029(P=0.878)and an integrated discrimination index improvement of-0.005(P=0.965).Conclusion The intelligent diagnostic model based on multiscale deep neural network using wearable electrocardiogram devices has an acceptable accuracy for classifying SVT mechanisms.

Objective To investigate the incidence rate,clinical characteristics,and prognosis of neonatal stroke in Shenzhen,China.Methods Led by Shenzhen Children's Hospital,the Shenzhen Neonatal Data Collaboration Network organized 21 institutions to collect 36 cases of neonatal stroke from January 2020 to December 2022.The incidence,clinical characteristics,treatment,and prognosis of neonatal stroke in Shenzhen were analyzed.Results The incidence rate of neonatal stroke in 21 hospitals from 2020 to 2022 was 1/15 137,1/6 060,and 1/7 704,respectively.Ischemic stroke accounted for 75％(27/36);boys accounted for 64％(23/36).Among the 36 neonates,31(86％)had disease onset within 3 days after birth,and 19(53％)had convulsion as the initial presentation.Cerebral MRI showed that 22 neonates(61％)had left cerebral infarction and 13(36％)had basal ganglia infarction.Magnetic resonance angiography was performed for 12 neonates,among whom 9(75％)had involvement of the middle cerebral artery.Electroencephalography was performed for 29 neonates,with sharp waves in 21 neonates(72％)and seizures in 10 neonates(34％).Symptomatic/supportive treatment varied across different hospitals.Neonatal Behavioral Neurological Assessment was performed for 12 neonates(33％,12/36),with a mean score of(32±4)points.The prognosis of 27 neonates was followed up to around 12 months of age,with 44％(12/27)of the neonates having a good prognosis.Conclusions Ischemic stroke is the main type of neonatal stroke,often with convulsions as the initial presentation,involvement of the middle cerebral artery,sharp waves on electroencephalography,and a relatively low neurodevelopment score.Symptomatic/supportive treatment is the main treatment method,and some neonates tend to have a poor prognosis.

Objective:To detect the expression of L-type amino acid transporter 1(LAT1)in non-Hodgkin's lymphoma(NHL)tissues,and analyze its effect on clinicopathological characteristics and prognosis of patients.Methods:A total of 92 NHL patients who were treated in our hospital from January 2017 to April 2019 were collected.The expression of LAT1 in NHL tissue was detected by immunohistochemistry and compared between patients with different pathological features(including sex,Ann Arbor stage,extranodal infiltration,Ki-67).The risk factors affecting mortality were analyzed using univariate and multivariate Cox proportional hazards regression.Receiver operating characteristic(ROC)curve was used to detect the predictive value of percentage of LAT1-positive cells in NHL tissue for patient mortality,and analyzing the effect of percentage of LAT1-positive cells on survival rate.Results:LAT1 was positively expressed in NHL tissue.The high expression rate of LAT1 in Ann Arbor stage Ⅲ and Ⅳ groups were higher than that in Ann Arbor stage Ⅰ group,that in extranodal infiltration group was higher than non-extranodal infiltration group,and that in Ki-67 positive expression group was higher than Ki-67 negative expression group(all P＜0.05).The remission rate after 3 courses of treatment in high-LAT1 expression group was 70.7％,which was lower than 91.2％in low-LAT1 expression group(P＜0.05).Ann Arbor stage Ⅲ and Ⅳ,extranodal invasion,Ki-67 positive expression and increased expression of LAT1(LAT1-positive cell percentage score ≥ 2)were risk factors for mortality.The cut-off value of percentage of LAT1-positive cells for predicting NHL death was 45.6％,and the area under the ROC curve was 0.905(95％CI:0.897-0.924).The 3-year survival rate of high-LAT1 level group(the percentage of LAT1-positive cells ≥ 45.6％)was 50.00％,which was lower than 78.26％of low-LAT1 level group(P＜0.05).Conclusion:The expression level of LAT1 in NHL tissue increases,which affects Ann Arbor stage and extranodal infiltration of patients.LAT1 is a risk factor for death.

Background/Aims: Cholestatic liver diseases including primary biliary cholangitis (PBC) are associated with active hepatic fibrogenesis, which ultimately progresses to cirrhosis. Activated hepatic stellate cells (HSCs) are the main fibrogenic effectors in response to cholangiocyte damage. JCAD regulates cell proliferation and malignant transformation in nonalcoholic steatoheaptitis-associated hepatocellular carcinoma (NASH-HCC). However, its participation in cholestatic fibrosis has not been explored yet. Methods: Serial sections of liver tissue of PBC patients were stained with immunofluorescence. Hepatic fibrosis was induced by bile duct ligation (BDL) in wild-type (WT), global JCAD knockout mice (JCAD-KO) and HSC-specific JCAD knockout mice (HSC-JCAD-KO), and evaluated by histopathology and biochemical tests. In situ-activated HSCs isolated from BDL mice were used to determine effects of JCAD on HSC activation. Results: In consistence with staining of liver sections from PBC patients, immunofluorescent staining revealed that JCAD expression was identified in smooth muscle α-actin (α-SMA)-positive fibroblast-like cells and was significantly up-regulated in WT mice with BDL. JCAD deficiency remarkably ameliorated BDL-induced hepatic injury and fibrosis, as documented by liver hydroxyproline content, when compared to WT mice with BDL. Histopathologically, collagen deposition was dramatically reduced in both JCAD-KO and HSC-JCAD-KO mice compared to WT mice, as visualized by Trichrome staining and semi-quantitative scores. Moreover, JCAD deprivation significantly attenuated in situ HSC activation and reduced expression of fibrotic genes after BDL. Conclusions JCAD deficiency effectively suppressed hepatic fibrosis induced by BDL in mice, and the underlying mechanisms are largely through suppressed Hippo-YAP signaling activity in HSCs.

OBJECTIVE: To observe the effects of auricular thumbtack needle on breast feeding and lactation function in primiparous women with cesarean section, and to explore its mechanism of action from the perspective of lactation-related gene expression. METHODS: One hundred cases of primiparous women with cesarean section were randomly divided into an observation group (50 cases, 3 cases dropped off) and a control group (50 cases, 2 cases were eliminated). The patients in the control group were treated with routine obstetric care. Based on the treatment of the control group, the patients in the observation group were treated with auricular thumbtack needle at Neifenmi (CO₁₈), Xiong (AH₁₀), Xiongzhui (AH₁₁), Shenmen (TF₄), and Jiaogan (AH_6a), etc., with one side of auricular point selected, only once for a total of 3 d. The lactation initiation time, lactation adequacy rate at postpartum 72 h, exclusive breastfeeding rate at postpartum 42 d, and breastfeeding score after treatment were compared between the two groups. Real-time quantitative PCR and Western blot method were used to detect the mRNA and protein expression levels of TDP-43, Btn1A1 and XDH. RESULTS: After treatment, the lactation initiation time in the observation group was earlier than that in the control group (P<0.01), and breastfeeding score in the observation group was higher than that in the control group (P<0.01). The lactation adequacy rate at postpartum 72 h was 63.8% (30/47) in the observation group, which was higher than 41.7% (20/48) in the control group (P<0.05). The exclusive breastfeeding rate at postpartum 42 d was 72.3% (34/47) in the observation group, which was higher than 47.9% (23/48) in the control group (P<0.05). The mRNA and protein expression levels of TDP-43 and Btn1A1 in breast milk in the observation group were higher than those in the control group (P<0.01), while there was no statistically significant difference in mRNA and protein expression of XDH in breast milk between the two groups (P>0.05). CONCLUSION The auricular thumbtack needle in addition to routine care could promote lactation initiation, improve lactation adequacy rate and exclusive breastfeeding rate in primiparous women with cesarean section, and the action mechanism may be related to up-regulation of TDP-43 and Btn1A1 expression.
Pregnancy ; Humans ; Female ; Breast Feeding ; Cesarean Section ; Lactation ; Milk, Human ; DNA-Binding Proteins