1.Construction of a renal rehabilitation, diagnosis and quality control information platform
Ying SHI ; Xiaomeng SUN ; Jun CHENG ; Di CHEN ; Yifan TIAN ; Yingchun MA ; Xinxin WANG ; Haiyan YE
Chinese Journal of Rehabilitation Theory and Practice 2026;32(4):488-496
ObjectiveTo develop a full-process data platform of renal rehabilitation, diagnosis and quality control information. MethodsA hierarchical architectural design was proposed, adhering to clinical pathway models and standardized data protocols. The platform comprehensively covered assessment, intervention, follow-up and quality control for maintenance hemodialysis (MHD) patients. By integrating multidisciplinary resources and standardizing rehabilitation workflows, it delivered standardized and intelligent rehabilitation services. ResultsThe platform achieved standardized and intelligent management of rehabilitation services, effectively improved the physiological function, psychological state and quality of life convenience for MHD patients, while significantly reduced the economic and care burden on patients' families and society. ConclusionThe rehabilitation service model based on a full-process data platform may provide scientific and systematic support for MHD patients.
2.Association of liver fibrosis markers and inflammation markers with the risk of gallstones in patients with metabolic dysfunction-associated fatty liver disease
Shuai ZHANG ; Shoulu JIN ; Wanqing LI ; Xijing SHI ; Hao LIANG ; Hao DONG ; Dailong LU ; Ying ZHU ; Xiaoxing XIANG ; Jun LIU
Journal of Clinical Hepatology 2026;42(3):579-585
ObjectiveTo investigate the association of liver fibrosis scores and inflammation markers with gallstones in patients with metabolic dysfunction-associated fatty liver disease (MAFLD), as well as the mediating role of liver fibrosis scores in the relationship between inflammation markers and gallstones. MethodsA total of 14 567 patients who received physical examination and were diagnosed with MAFLD in Subei People’s Hospital from January 2014 to June 2023 were enrolled in this study, and according to the results of abdominal color Doppler ultrasound, they were divided into gallstone group with 1 724 patients and non-gallstone group with 12 843 patients. Related clinical data were collected from all patients, including demographic data, medical history, family history, physical examination, Color Doppler ultrasound, and biochemical parameters. The biomarkers associated with metabolic disorders and insulin resistance included triglyceride-glucose index (TyG), TyG-body mass index (BMI) index, atherogenic index of plasma (AIP), and non-high-density lipoprotein cholesterol-to-high-density lipoprotein cholesterol ratio (NHHR); the biomarkers associated with inflammation and nutritional status included neutrophil-to-lymphocyte ratio (NLR), neutrophil percentage-to-albumin ratio (NPAR), and monocyte-to-lymphocyte ratio (MLR); the biomarkers for assessing liver fibrosis degree and liver function included albumin-bilirubin (ALBI) score, NAFLD fibrosis score (NFS), fibrosis-4 (FIB-4) index, and aspartate aminotransferase-to-platelet ratio index (APRI). The independent-samples t test was used for comparison of normally distributed continuous data between two groups, while the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups; the chi-square test was used for comparison of categorical data between two groups. Multivariate Logistic regression analysis, restricted cubic spline analysis, and mediating effect analysis were used to assess the association of liver fibrosis markers and inflammation markers with the risk of gallstones. ResultsThe prevalence rate of gallstones was 11.8% among the MAFLD patients. There were significant differences between the gallstone group and the non-gallstone group in sex, age, smoking history, diabetes, hypertension, lymphocytes, platelets, glucose, albumin, serum uric acid, alanine aminotransferase, aspartate aminotransferase, red blood cell, NLR, NPAR, MLR, NFS, FIB-4 index, and ALBI score (all P<0.05). The multivariate Logistic regression analysis showed that NLR (odds ratio [OR]=1.091, 95% confidence interval [CI]: 1.028 — 1.160, P<0.05), NPAR (OR=1.073, 95%CI: 1.042 — 1.105, P<0.05), MLR (OR=1.142, 95%CI: 1.057 — 1.232, P<0.05), NFS (OR=1.239, 95%CI: 1.190 — 1.291, P<0.05), and FIB-4 index (OR=1.326, 95%CI: 1.241 — 1.417, P<0.05) were influencing factors for the prevalence rate of gallstones. The restricted cubic spline analysis showed a significant non-linear association between NFS/FIB-4 index and the risk of gallstone (non-linear P<0.05). The mediating effect analysis further showed that the association of NLR, MLR, and NPAR with gallstones was partially mediated by NFS or FIB-4 index, with a mediating effect accounting for 36.79%、28.09%、29.67% and 18.31%、17.70、11.57%, respectively. ConclusionNFS and FIB-4 index have a non-linear association with the prevalence rate of gallstones in MAFLD patients, and they also mediate the association of NLR, NPAR, and MLR with the risk of gallstone.
3.Empirical study of input, output, outcome and impact of community-based rehabilitation stations
Xiayao CHEN ; Ying DONG ; Xue DONG ; Zhongxiang MI ; Jun CHENG ; Aimin ZHANG ; Didi LU ; Jun WANG ; Jude LIU ; Qianmo AN ; Hui GUO ; Xiaochen LIU ; Zefeng YU
Chinese Journal of Rehabilitation Theory and Practice 2026;32(1):83-89
ObjectiveTo investigate the present situation of input, output, outcome and impact of all registered community-based rehabilitation stations in Inner Mongolia in China, and analyze how the input predict the output, outcome and impact. MethodsFrom March 1st to April 30th, 2025, a questionnaire survey was conducted on all registered community-based rehabilitation stations in Inner Mongolia, covering four dimensions: input, output, outcome and impact. A total of 1 365 questionnaires were distributed. The input included four items: laws and policies, human resources, equipment and facilities, and rehabilitation information management. The output included two items: technical paths and benefits/effectiveness. The outcome included three items: coverage rates, rehabilitation interventions and functional results. The impact included two items: health and sustainability. Each item contained several questions, all of which were described in a positive way. Each question was scored from one to five. A lower score indicated that the situation of the community-based rehabilitation station was more in line with the content described in the question. Regression analysis was performed using the total score of each item of input dimension as independent variables, and the total scores of the output, outcome and impact dimensions as dependent variables. ResultsA total of 1 262 valid questionnaires were collected. The mean values of input, output, outcome and impact of community-based rehabilitation stations were 1.827 to 1.904, with coefficient of variation of 45.892% to 49.239%. The regression analysis showed that, rehabilitation information management, human resources, and laws and policies significantly predicted the output dimension (R² = 0.910, P < 0.001). Meanwhile, all four items in the input dimension predicted both the outcome (R² = 0.850, P < 0.001) and impact dimensions (R² = 0.833, P < 0.001). ConclusionInput, output, outcome and impact of the community-based rehabilitation stations in Inner Mongolia were generally in line with the content of the questions, although some imbalances were observed. Additionally, the input of community-based rehabilitation stations could significantly predict their output, outcome and impact.
4.Correlation between liver fibrosis degree and carotid plaque in patients with lean metabolic dysfunction-associated fatty liver disease
Shuai ZHANG ; Shoulu JIN ; Wanqing LI ; Xijing SHI ; Hao LIANG ; Hao DONG ; Dailong LU ; Ying ZHU ; Xiaoxing XIANG ; Jun LIU
Journal of Clinical Hepatology 2026;42(2):319-325
ObjectiveTo investigate the association between noninvasive liver fibrosis markers and carotid plaque (CP) in patients with lean metabolic dysfunction-associated fatty liver disease (MAFLD), and to provide a basis for screening high-risk populations. MethodsA total of 957 patients with lean MAFLD who underwent physical examination in Subei People’s Hospital from January 2021 to June 2023 was enrolled as the observation cohort, with the presence or absence of CP as the outcome, and fibrosis-4 (FIB-4) index and nonalcoholic fatty liver disease fibrosis score (NFS) were used to assess liver fibrosis degree. The independent-samples t test was used for comparison of normally distributed continuous data between two groups, and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups; the chi-square test was used for comparison of categorical data between two groups. The multivariate logistic regression analysis, the restricted cubic spline analysis, the receiver operating characteristic curve, and the mediation effect analysis were used to investigate the association between liver fibrosis degree and CP. ResultsThe prevalence rate of CP was 36.6% in the lean MAFLD population. Compared with the non-CP group(n=607), the CP group (n=350) had a significantly higher proportion of male patients, a significantly higher proportion of patients with smoking/diabetes/hypertension, and significantly higher levels of age, creatinine, blood urea nitrogen, triglycerides, fasting blood glucose, aspartate aminotransferase, aspartate aminotransferase/alanine aminotransferase ratio, NFS, and FIB-4 index, as well as significantly lower levels of platelet count and albumin (all P<0.05). The multivariate logistic regression analysis showed that after adjustment for confounding factors, FIB-4 index (odds ratio[OR]=2.979, 95% confidence interval[CI]:2.141 — 4.219, P<0.001) and NFS (OR=1.747, 95%CI: 1.499 — 2.046, P<0.001) were positively correlated with CP. Both FIB-4 index and NFS had a good value in predicting CP. Hypertension had a significant indirect effect on the prevalence rate of CP through its impact on liver fibrosis markers, and its mediating effect accounted for 39.5% — 40.8% of the total effect (P<0.001). ConclusionIn patients with lean MAFLD, NFS and FIB-4 index are significantly positively correlated with the prevalence rate of CP, and they can be used as potential epidemiological predictive indicators. Liver fibrosis markers may play a mediating role in the association between hypertension and CP. Interventions targeting hypertension and liver fibrosis markers may help to prevent and delay the progression of CP.
5.Xuefu Zhuyutang Ameliorates Metabolic-associated Fatty Liver Disease via AMPK Signaling Pathway
Ming HAN ; Ying ZHANG ; Lingya KONG ; Jun DAI ; Ting ZHANG ; Zhihong MA
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(11):1-12
ObjectiveTo investigate the therapeutic mechanism of Xuefu Zhuyutang (XFZYT) for metabolic-associated fatty liver disease (MAFLD) through integrated network pharmacology and animal experiments. MethodsNetwork pharmacology was utilized to predict the core components, key therapeutic targets, and signaling pathways of XFZYT in the treatment of MAFLD. For animal experiments, a rat model of MAFLD was established by feeding a high-cholesterol diet for 4 weeks. Intervention was then administered with low-dose (2 g·kg-1) and high-dose (4 g·kg-1) XFZYT for 2 weeks. Biochemical assays were performed to measure the serum levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL), and low-density lipoprotein (LDL). In addition, the activities of superoxide dismutase (SOD) and catalase (CAT) and levels of malondialdehyde (MDA) and glutathione (GSH) in the serum were measured. The same way was adopted to measure the levels of TC and TG in the liver tissue. Enzyme-linked immunosorbent assay (ELISA) was employed to quantify the serum levels of interleukin (IL)-6, IL-1β, and tumor necrosis factor-alpha (TNF-α). Histopathological evaluations included hematoxylin and eosin (HE) staining for liver tissue morphology, Oil Red O staining for lipid deposition, and dihydroethidium (DHE) probe staining for reactive oxygen species (ROS) levels. Western blot analysis was conducted to assess the protein levels of AMP-activated protein kinase (AMPK), phosphorylated (p)-AMPK, nuclear factor erythroid 2-related factor 2 (Nrf2), heme oxygenase-1 (HO-1), nuclear factor-kappa B (NF-κB), and p-NF-κB in the liver tissue. Untargeted metabolomics analysis of the serum was performed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). ResultsNetwork pharmacology analysis predicted 155 potential targets of XFZYT for MAFLD treatment, with core targets including signal transducer and activator of transcription 3 (STAT3), protein kinase B1 (Akt1), TNF, and IL-6. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment primarily implicated the AMPK signaling pathway. Animal experiments demonstrated that compared with the normal group, the model group exhibited dyslipidemia, hepatic function impairment, pronounced hepatic lipid deposition, and inflammatory manifestations, with elevated serum levels of AST, ALT, TC, TG, LDL, and MDA (P<0.05), reduced HDL and GSH levels plus decreased SOD and CAT activities (P<0.05), downregulated protein levels of Nrf2, HO-1, and p-AMPK (P<0.05), and upregulated protein level of p-NF-κB (P<0.05) in the liver tissue. Compared with the model group, XFZYT intervention groups showed significant amelioration of dyslipidemia and hepatic function impairment, markedly reduced hepatic lipid deposition and inflammatory cell infiltration, decreased serum levels of AST, ALT, TC, TG, LDL, and MDA (P<0.05), increased HDL and GSH levels plus enhanced SOD and CAT activities (P<0.05), upregulated protein levels of Nrf2, HO-1, and p-AMPK (P<0.05), and downregulated protein level of p-NF-κB (P<0.05). Serum metabolomics revealed 511 differentially expressed metabolites (231 upregulated and 280 downregulated) between normal and model groups, while XFZYT groups versus model group showed 94 differential metabolites (51 upregulated and 43 downregulated). Among them, 11 metabolites displayed the most significant alterations, with enriched pathways including glycerolipid metabolism, cholesterol metabolism, and insulin resistance, multiple of which demonstrated AMPK association. ConclusionXFZYT alleviates MAFLD by regulating the AMPK signaling pathway and associated metabolic networks.
6.Aging-related dysregulation of glucose metabolism:crossroads of cancer and neurodegenerative diseases
Huan LIU ; Shaopeng ZENG ; Jun CHEN ; Linqian HE ; Ying YANG ; Jing ZHANG
Chinese Journal of Tissue Engineering Research 2026;30(6):1527-1538
BACKGROUND:Epidemiological studies indicate that individuals with neurodegenerative diseases exhibit a comparatively lower risk of developing the majority of cancers.Although the precise mechanisms underlying this inverse correlation remain unclear,it is noteworthy that aberrant glucose metabolism,a pathological factor common to both conditions,may significantly contribute to this association.OBJECTIVE:To review the potential relationship between cancers and neurodegenerative diseases in glucose metabolism.METHODS:PubMed was searched for relevant literature using the search terms of"cancer,neurodegenerative diseases,Alzheimer's disease,Parkinson's disease,metabolic reprogramming,glucose metabolism,aerobic glycolysis,neuroprotection,aging,"and 136 articles were finally included for analysis.RESULTS AND CONCLUSION:Cancer and neurodegenerative diseases exhibit a profound pathological correlation at the level of glucose metabolism imbalance associated with aging.Cancer cells promote uncontrolled proliferation,invasion,and metastasis through the persistent activation of aerobic glycolysis,whereas neurodegenerative diseases are characterized by a reduction in aerobic glycolysis.Restoring aerobic glycolysis may confer neuroprotective effects and delay disease progression.The key nodes of glucose metabolism demonstrate a bidirectional regulatory pattern:metabolic regulators,which are significantly upregulated or aberrantly activated in cancer,are inhibited or functionally inactivated in neurodegenerative diseases.Mitochondria play a crucial role in mediating the aging process through the regulation of reactive oxygen species homeostasis and mitochondrial autophagy.They establish regulatory networks that connect cancer and neurodegenerative diseases,and maintaining their functional homeostasis is of paramount importance for disease prevention and treatment.
7.Aging-related dysregulation of glucose metabolism:crossroads of cancer and neurodegenerative diseases
Huan LIU ; Shaopeng ZENG ; Jun CHEN ; Linqian HE ; Ying YANG ; Jing ZHANG
Chinese Journal of Tissue Engineering Research 2026;30(6):1527-1538
BACKGROUND:Epidemiological studies indicate that individuals with neurodegenerative diseases exhibit a comparatively lower risk of developing the majority of cancers.Although the precise mechanisms underlying this inverse correlation remain unclear,it is noteworthy that aberrant glucose metabolism,a pathological factor common to both conditions,may significantly contribute to this association.OBJECTIVE:To review the potential relationship between cancers and neurodegenerative diseases in glucose metabolism.METHODS:PubMed was searched for relevant literature using the search terms of"cancer,neurodegenerative diseases,Alzheimer's disease,Parkinson's disease,metabolic reprogramming,glucose metabolism,aerobic glycolysis,neuroprotection,aging,"and 136 articles were finally included for analysis.RESULTS AND CONCLUSION:Cancer and neurodegenerative diseases exhibit a profound pathological correlation at the level of glucose metabolism imbalance associated with aging.Cancer cells promote uncontrolled proliferation,invasion,and metastasis through the persistent activation of aerobic glycolysis,whereas neurodegenerative diseases are characterized by a reduction in aerobic glycolysis.Restoring aerobic glycolysis may confer neuroprotective effects and delay disease progression.The key nodes of glucose metabolism demonstrate a bidirectional regulatory pattern:metabolic regulators,which are significantly upregulated or aberrantly activated in cancer,are inhibited or functionally inactivated in neurodegenerative diseases.Mitochondria play a crucial role in mediating the aging process through the regulation of reactive oxygen species homeostasis and mitochondrial autophagy.They establish regulatory networks that connect cancer and neurodegenerative diseases,and maintaining their functional homeostasis is of paramount importance for disease prevention and treatment.
8.Ameliorative effect of baicalin nanomedicine on hydrogen peroxide-induced senescence of human umbilical vein vascular endothelial cells
Xinhe MO ; Youqiong WAN ; Sibu WANG ; Qin MA ; Jun ZHANG ; Ying CHEN
Journal of China Pharmaceutical University 2025;56(1):110-118
To investigate the effect of baicalin (BAI)-loaded cross-linked lipoic acid nanocapsules (BAI@cLANCs) against hydrogen peroxide (H2O2)-induced senescence in human umbilical vein endothelial cells (HUVECs), this study examined the toxicity of BAI@cLANCs on HUVECs by MTT method. The cell nuclear staining, SA-β-gal staining, and MTT methods were used to assess the optimal concentration of H2O2-induced senescence in HUVECs. The cellular uptake of BAI@cLANCs was evaluated using fluorescence microscopy imaging and flow cytometry. The proportion of cellular senescence was determined by SA-β-gal staining. The level of reactive oxygen species (ROS) in senescent cells was detected by fluorescence microscopy imaging and multifunctional microplate reader. The content of malondialdehyde (MDA) in cells was detected by lipid oxidation detection kit, and the cell cycle was analyzed by flow cytometry with propidium iodide staining. The results showed that BAI@cLANCs had no significant effect on the growth of HUVECs in the range of BAI at 2.80−112 mmol/L. 200 μmol/L and 25 minutes were the ideal conditions for H2O2-induced senescence of HUVECs. cLANCs as drug delivery carriers significantly enhanced the uptake efficiency of BAI in HUVECs. Compared with the normal group, the H2O2 model group showed decreased cell viability, increased positive SA-β-gal staining rate, increased ROS and MDA content, as well as increased percentage of cells blocked in S phase and decreased cells entering G2/M phase. Compared with the H2O2 model group, BAI, cLANCs, BAI + cLANCs, and BAI@cLANCs groups showed increased cell viability, decreased positive SA-β-gal staining rate, decreased ROS and MDA content, decreased percentage of S-phase cells, and increased cells entering G2/M phase, with the best anti-aging effect in the BAI@cLANCs group. In summary, the results above showed that both BAI and cLANCs have anti-aging properties. With cLANCs as drug carriers, the anti-aging benefits of BAI@cLANCs are synergistic and can effectively delay H2O2-induced senescence of HUVECs.
9.Exploration and Practice of Artificial Intelligence Empowering Case-based Teaching in Biochemistry and Molecular Biology
Ying-Lu HU ; Yi-Chen LIN ; Jun-Ming GUO ; Xiao-Dan MENG
Progress in Biochemistry and Biophysics 2025;52(8):2173-2184
In recent years, the deep integration of artificial intelligence (AI) into medical education has created new opportunities for teaching Biochemistry and Molecular Biology, while also offering innovative solutions to the pedagogical challenges associated with protein structure and function. Focusing on the case of anaplastic lymphoma kinase (ALK) gene mutations in non-small-cell lung cancer (NSCLC), this study integrates AI into case-based learning (CBL) to develop an AI-CBL hybrid teaching model. This model features an intelligent case-generation system that dynamically constructs ALK mutation scenarios using real-world clinical data, closely linking molecular biology concepts with clinical applications. It incorporates AI-powered protein structure prediction tools to accurately visualize the three-dimensional structures of both wild-type and mutant ALK proteins, dynamically simulating functional abnormalities resulting from conformational changes. Additionally, a virtual simulation platform replicates the ALK gene detection workflow, bridging theoretical knowledge with practical skills. As a result, a multidimensional teaching system is established—driven by clinical cases and integrating molecular structural analysis with experimental validation. Teaching outcomes indicate that the three-dimensional visualization, dynamic interactivity, and intelligent analytical capabilities provided by AI significantly enhance students’ understanding of molecular mechanisms, classroom engagement, and capacity for innovative research. This model establishes a coherent training pathway linking “fundamental theory-scientific research thinking-clinical practice”, offering an effective approach to addressing teaching challenges and advancing the intelligent transformation of medical education.
10.Diagnostic Techniques and Risk Prediction for Cardiovascular-kidney-metabolic (CKM) Syndrome
Song HOU ; Lin-Shan ZHANG ; Xiu-Qin HONG ; Chi ZHANG ; Ying LIU ; Cai-Li ZHANG ; Yan ZHU ; Hai-Jun LIN ; Fu ZHANG ; Yu-Xiang YANG
Progress in Biochemistry and Biophysics 2025;52(10):2585-2601
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.

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