ObjectiveTo analyze the processing mechanism underlying the enhanced effect of invigorating spleen and stopping diarrhea of soil-fried Atractylodis Macrocephalae Rhizoma（AMR） by analyzing the changes of microstructure， chemical composition and anti-ulcerative colitis（UC） activity before and after soil stir-frying. MethodsThe microstructure and elemental composition of AMR before and after soil stir-frying were analyzed by scanning electron microscopy-energy dispersive spectroscopy（SEM-EDS）， to investigate the differences in microstructure and the underlying causes. Ultra-high performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS） coupled with UNIFI 1.9.2 natural product analysis platform were used to analyze and identify the chemical constituents in raw and soil-fried products， and multivariate statistical methods including principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA） were used to explore the differences and sources of chemical constituents between them. A dextran sulfate sodium（DSS）-induced UC mouse model was established. The method of disease activity index（DAI） was used to evaluate the severity of intestinal inflammation. Hematoxylin-eosin（HE） staining was used to observe the pathological changes of colon tissue， enzyme-linked immunosorbent assay（ELISA） was used to detect the levels of inflammatory factors， Real-time quantitative polymerase chain reaction（Real-time PCR） and Western blot were used to analyze the expressions of key genes and proteins involved in the intestinal mucosal barrier. The 16S rRNA sequencing was used to evaluate the diversity of intestinal flora， headspace gas chromatography-mass spectrometry（HS-GC-MS） was used to explore the levels of short-chain fatty acids（SCFAs） in feces. Base on the above findings， this paper investigated the effects of raw and soil-fried AMR on the biological， chemical， mechanical and immune barriers of model animals， and the differences in pharmacological effects and underlying mechanisms from the perspective of regulating the intestinal mucosal barrier in UC mice. ResultsSEM observation revealed numerous hearth soil particles on the surface of soil-fried AMR， accompanied by bubble-like bulges. At the same time， there were many cracks and folds on the surface of the hearth soil. EDS analysis revealed that the contents of Si， Al， Mg and Ca in soil-fried AMR were significantly higher than those of raw products， and these elements constituted the primary components of hearth soil. UPLC-Q-TOF-MS combined with database comparison was used to identify the chemical constituents of raw and soil-fried AMR. In positive ion mode， a total of 132 components were identified， primarily comprising three categories of terpenoids， polyphenols and amino acids. In negative ion mode， a total of 40 components were identified， primarily polyphenolic and glycoside compounds. Among them， the contents of sesquiterpenes and polyphenolic acids were changed significantly before and after processing. Soil-fried AMR could reduce the DAI score of UC mice， alleviate the shortening of colon length， reduce the levels of pro-inflammatory factors such as interleukin（IL）-17， IL-18， γ-interferon（IFN-γ） and tumor necrosis factor（TNF）-α in serum， increase the levels of anti-inflammatory factors such as secretory immunoglobulin A（sIgA）， IL-10， IL-4 and transforming growth factor-β（TGF-β） in serum， increase the expressions of key genes and proteins of intestinal mucosal barrier such as tight junction protein-1（ZO-1）， Occludin， Claudin-1 and mucin 2（MUC2） in colonic mucosa， and improve the disorders of intestinal flora diversity and the levels of SCFAs（P<0.05， P<0.01）. The raw and stir-fried products of AMR also exhibited the aforementioned effects， but they were weaker than the soil-fried products. Additionally， the auxiliary material hearth soil also had a certain pharmacodynamic effect. ConclusionSoil-fried AMR can enhance the protective effect on intestinal mucosal barrier in UC mice. These changes or heating-induced alterations in the microscopic structure and chemical composition of AMR may be attributed to the dual effects of adsorption of hearth soil.

ObjectiveTo analyze the processing mechanism underlying the enhanced effect of invigorating spleen and stopping diarrhea of soil-fried Atractylodis Macrocephalae Rhizoma（AMR） by analyzing the changes of microstructure， chemical composition and anti-ulcerative colitis（UC） activity before and after soil stir-frying. MethodsThe microstructure and elemental composition of AMR before and after soil stir-frying were analyzed by scanning electron microscopy-energy dispersive spectroscopy（SEM-EDS）， to investigate the differences in microstructure and the underlying causes. Ultra-high performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS） coupled with UNIFI 1.9.2 natural product analysis platform were used to analyze and identify the chemical constituents in raw and soil-fried products， and multivariate statistical methods including principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA） were used to explore the differences and sources of chemical constituents between them. A dextran sulfate sodium（DSS）-induced UC mouse model was established. The method of disease activity index（DAI） was used to evaluate the severity of intestinal inflammation. Hematoxylin-eosin（HE） staining was used to observe the pathological changes of colon tissue， enzyme-linked immunosorbent assay（ELISA） was used to detect the levels of inflammatory factors， Real-time quantitative polymerase chain reaction（Real-time PCR） and Western blot were used to analyze the expressions of key genes and proteins involved in the intestinal mucosal barrier. The 16S rRNA sequencing was used to evaluate the diversity of intestinal flora， headspace gas chromatography-mass spectrometry（HS-GC-MS） was used to explore the levels of short-chain fatty acids（SCFAs） in feces. Base on the above findings， this paper investigated the effects of raw and soil-fried AMR on the biological， chemical， mechanical and immune barriers of model animals， and the differences in pharmacological effects and underlying mechanisms from the perspective of regulating the intestinal mucosal barrier in UC mice. ResultsSEM observation revealed numerous hearth soil particles on the surface of soil-fried AMR， accompanied by bubble-like bulges. At the same time， there were many cracks and folds on the surface of the hearth soil. EDS analysis revealed that the contents of Si， Al， Mg and Ca in soil-fried AMR were significantly higher than those of raw products， and these elements constituted the primary components of hearth soil. UPLC-Q-TOF-MS combined with database comparison was used to identify the chemical constituents of raw and soil-fried AMR. In positive ion mode， a total of 132 components were identified， primarily comprising three categories of terpenoids， polyphenols and amino acids. In negative ion mode， a total of 40 components were identified， primarily polyphenolic and glycoside compounds. Among them， the contents of sesquiterpenes and polyphenolic acids were changed significantly before and after processing. Soil-fried AMR could reduce the DAI score of UC mice， alleviate the shortening of colon length， reduce the levels of pro-inflammatory factors such as interleukin（IL）-17， IL-18， γ-interferon（IFN-γ） and tumor necrosis factor（TNF）-α in serum， increase the levels of anti-inflammatory factors such as secretory immunoglobulin A（sIgA）， IL-10， IL-4 and transforming growth factor-β（TGF-β） in serum， increase the expressions of key genes and proteins of intestinal mucosal barrier such as tight junction protein-1（ZO-1）， Occludin， Claudin-1 and mucin 2（MUC2） in colonic mucosa， and improve the disorders of intestinal flora diversity and the levels of SCFAs（P<0.05， P<0.01）. The raw and stir-fried products of AMR also exhibited the aforementioned effects， but they were weaker than the soil-fried products. Additionally， the auxiliary material hearth soil also had a certain pharmacodynamic effect. ConclusionSoil-fried AMR can enhance the protective effect on intestinal mucosal barrier in UC mice. These changes or heating-induced alterations in the microscopic structure and chemical composition of AMR may be attributed to the dual effects of adsorption of hearth soil.

Objective: To develop a prediction model for mild cognitive impairment (MCI) risk among the elderly, so as to provide a tool for MCI early screening. Methods : From July 2022 to September 2024, a multi-stage stratified random cluster sampling method was used to recruit permanent residents aged ≥65 years from the Xinjiang Uygur Autonomous Region as study participants. Data on sociodemographic characteristics, nutritional status, body composition indices, bone mineral density, and handgrip strength were collected through questionnaires and physical examinations. Sarcopenia was defined based on appendicular skeletal muscle index and handgrip strength. MCI was assessed using the Mini-Mental State Examination, with adjustments for educational level. Participants were randomly divided into a training set and a validation set in a 7∶3 ratio. LASSO regression and multivariable logistic regression models were employed to screen for predictors and construct an MCI risk prediction model. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Results: A total of 1 641 participants were surveyed, including 755 males (46.01%) and 886 females (53.99%). The majority of participants were aged 65-<75 years, comprising 1 154 individuals (70.32%). MCI was detected in 517 participants, corresponding to a detection rate of 31.51%. Resultsfrom LASSO regression and multivariate logistic regression analysis showed that residence (rural, OR = 2.323, 95% CI: 1.682-3.210), age (75-<85 years, OR = 1.405, 95% CI: 1.019-1.937; ≥85 years, OR = 3.655, 95% CI: 1.696-7.875), educational level (primary school, OR = 0.341, 95% CI: 0.247-0.472; junior high school, OR = 0.255, 95% CI: 0.160-0.408; high school, OR = 0.286, 95% CI: 0.154-0.531; bachelor's degree or above, OR = 0.120, 95% CI: 0.041-0.351), history of alcohol consumption (yes, OR = 3.216, 95% CI: 2.164-4.779), risk of malnutrition (yes, OR = 1.464, 95% CI: 1.064-2.014), sarcopenia (yes, OR = 3.197, 95% CI: 2.332-4.385), and waist-to-hip ratio (abnormal, OR = 1.540, 95% CI: 1.159-2.048) were identified as predictive factors for MCI among the elderly. In the training set, the area under the ROC curve, sensitivity, and specificity were 0.788, 0.719, and 0.712, respectively. In the validation set, the corresponding values were 0.784, 0.913, and 0.542, respectively. DCA demonstrated that the model provided a higher clinical net benefit for predicting MCI risk when the risk threshold probability ranged from 0.124 to 0.764. Conclusion The prediction model developed in this study demonstrates good discriminative ability and clinical utility, indicating its substantial value for predicting the MCI risk among the elderly.

ObjectiveTo explore the mechanism of action of Paeoniae Radix Rubra and Aconiti Lateralis Radix Praeparata （CSFZ） in the treatment of acute-on-chronic liver failure （ACLF） through network pharmacology， molecular docking， and animal experiments. MethodsNetwork pharmacology was used to identify potential targets and related signaling pathways for the treatment of ACLF with CSFZ. Molecular docking was used to examine the binding activity of the core components with corresponding key targets. An ACLF rat model was established by subcutaneous and tail vein injections of bovine serum albumin combined with lipopolysaccharide （LPS） + D-galactosamine （D-GalN） intraperitoneal injection. A normal control group （NC）， a model group， a CSFZ group （CSFZ， 5.85 g·kg^-1）， and a hepatocyte growth-promoting granule group （HGFG， 4.05 g·kg^-1） were set up in this study. Pathological changes in rat liver tissue were observed using hematoxylin and eosin （HE） and Masson staining. Enzyme-linked immunosorbent assay （ELISA） was used to detect the expression levels of interleukin-6 （IL-6）， B-cell lymphoma-2 （Bcl-2）， Caspase-3， and albumin （ALB）. Real-time quantitative polymerase chain reaction （Real-time PCR） and Western blot were used to measure the mRNA and protein expression levels of phosphoinositide 3-kinase （PI3K）， protein kinase B （Akt）， phosphorylated PI3K （p-PI3K）， and phosphorylated Akt （p-Akt）. ResultsNetwork pharmacology screening identified 49 active ingredients of CSFZ， 103 action targets， and 3 317 targets related to ACLF. Among these， 74 targets overlapped with CSFZ drug targets. Key nodes in the protein-protein interaction （PPI） network included Akt1， tumor necrosis factor （TNF）， IL-6， Bcl-2， and Caspase-3. Gene Ontology （GO） functional analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analysis identified multiple signaling pathways， with the PI3K/Akt signaling pathway being the most frequent. Molecular docking showed that the core components of the drug exhibited good binding activity with the corresponding key targets. Animal experiments confirmed that CSFZ significantly improved liver tissue pathological damage in ACLF rats， reduced the release of inflammatory factors and liver cell apoptosis， and upregulated the expression levels of the PI3K/Akt signaling pathway. ConclusionThrough network pharmacology， molecular docking， and in vivo experiments， this study confirms the effect of CSFZ in reducing liver cell inflammatory damage and inhibiting liver cell apoptosis. The specific mechanism may be related to its involvement in regulating the PI3K/Akt signaling pathway.

Brain’s neural activities encompass both periodic rhythmic oscillations and aperiodic neural fluctuations. Rhythmic oscillations manifest as spectral peaks of neural signals, directly reflecting the synchronized activities of neural populations and closely tied to cognitive and behavioral states. In contrast, aperiodic fluctuations exhibit a power-law decaying spectral trend, revealing the multiscale dynamics of brain neural activity. In recent years, researchers have made notable progress in studying brain aperiodic dynamics. These studies demonstrate that aperiodic activity holds significant physiological relevance, correlating with various physiological states such as external stimuli, drug induction, sleep states, and aging. Aperiodic activity serves as a reflection of the brain’s sensory capacity, consciousness level, and cognitive ability. In clinical research, the aperiodic exponent has emerged as a significant potential biomarker, capable of reflecting the progression and trends of brain diseases while being intricately intertwined with the excitation-inhibition balance of neural system. The physiological mechanisms underlying aperiodic dynamics span multiple neural scales, with activities at the levels of individual neurons, neuronal ensembles, and neural networks collectively influencing the frequency, oscillatory patterns, and spatiotemporal characteristics of aperiodic signals. Aperiodic dynamics currently boasts broad application prospects. It not only provides a novel perspective for investigating brain neural dynamics but also holds immense potential as a neural marker in neuromodulation or brain-computer interface technologies. This paper summarizes methods for extracting characteristic parameters of aperiodic activity, analyzes its physiological relevance and potential as a biomarker in brain diseases, summarizes its physiological mechanisms, and based on these findings, elaborates on the research prospects of aperiodic dynamics.

Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

Alzheimer’s disease (AD) is a prevalent neurodegenerative condition characterized by progressive cognitive decline and memory loss. As the incidence of AD continues to rise annually, researchers have shown keen interest in the active components found in natural plants and their neuroprotective effects against AD. Quercetin, a flavonol widely present in fruits and vegetables, has multiple biological effects including anticancer, anti-inflammatory, and antioxidant. Oxidative stress plays a central role in the pathogenesis of AD, and the antioxidant properties of quercetin are essential for its neuroprotective function. Quercetin can modulate multiple signaling pathways related to AD, such as Nrf2-ARE, JNK, p38 MAPK, PON2, PI3K/Akt, and PKC, all of which are closely related to oxidative stress. Furthermore, quercetin is capable of inhibiting the aggregation of β‑amyloid protein (Aβ) and the phosphorylation of tau protein, as well as the activity of β‑secretase 1 and acetylcholinesterase, thus slowing down the progression of the disease.The review also provides insights into the pharmacokinetic properties of quercetin, including its absorption, metabolism, and excretion, as well as its bioavailability challenges and clinical applications. To improve the bioavailability and enhance the targeting of quercetin, the potential of quercetin nanomedicine delivery systems in the treatment of AD is also discussed. In summary, the multifaceted mechanisms of quercetin against AD provide a new perspective for drug development. However, translating these findings into clinical practice requires overcoming current limitations and ongoing research. In this way, its therapeutic potential in the treatment of AD can be fully utilized.

Background: In acute and chronic renal inflammatory diseases, the activation of inflammatory cells is involved in the defect of erythropoietin (EPO) production. Ras guanine nucleotide-releasing protein-4 (RasGRP4) promotes renal inflammatory injury in type 2 diabetes mellitus (T2DM). Our study aimed to investigate the role and mechanism of RasGRP4 in the production of renal EPO in diabetes. Methods: The degree of tissue injury was observed by pathological staining. Inflammatory cell infiltration was analyzed by immunohistochemical staining. Serum EPO levels were detected by enzyme-linked immunosorbent assay, and EPO production and renal interstitial fibrosis were analyzed by immunofluorescence. Quantitative real-time polymerase chain reaction and Western blotting were used to detect the expression of key inflammatory factors and the activation of signaling pathways. In vitro, the interaction between peripheral blood mononuclear cells (PBMCs) and C3H10T1/2 cells was investigated via cell coculture experiments. Results: RasGRP4 decreased the expression of hypoxia-inducible factor 2-alpha (HIF2A) via the ubiquitination–proteasome degradation pathway and promoted myofibroblastic transformation by activating critical inflammatory pathways, consequently reducing the production of EPO in T2DM mice. Conclusion RasGRP4 participates in the production of renal EPO in diabetic mice by affecting the secretion of proinflammatory cytokines in PBMCs, degrading HIF2A, and promoting the myofibroblastic transformation of C3H10T1/2 cells.

ObjectiveTo investigate the value of Fried Frailty Phenotype （FFP）， liver frailty index （LFI）， and Short Physical Performance Battery （SPPB） in predicting 2-year all-cause mortality and decompensation events in patients with liver cirrhosis. MethodsA total of 277 patients with liver cirrhosis who were hospitalized in Beijing Friendship Hospital， Capital Medical University， from December 2020 to December 2021 were enrolled， and FFP， LFI， and SPPB were used to assess the state of frailty. Based on the scores of each tool， these patients were divided into frail and non-frail groups. These three tools were compared in terms of consistency and independent predictive performance. The primary endpoints were 2-year all-cause mortality rate and composite endpoints （death+decompensation events）， and the Cox regression analysis， the receiver operating characteristic （ROC） curve， net reclassification index （NRI）， and integrated discrimination improvement （IDI） index were used to analyze the predictive value of the three tools. Normally distributed continuous data were compared between two groups using the independent samples t-test， while non-normally distributed continuous data were compared using the Mann-Whitney U test. Categorical data were compared between groups using the chi-square test or Fisher’s exact test. The agreement among different frailty tools was evaluated using Cohen’s Kappa statistic. The Kaplan-Meier survival curve was plotted， and a survival analysis was performed using the log-rank test. ResultsThe prevalence rate of frailty assessed by FFP， LFI， and SPPB was 37.2%， 22.4%， and 20.2%， respectively， with a moderate consistency between FFP and LFI/SPPB （κ=0.57， 95% confidence interval ［CI］： 0.47 — 0.67； κ=0.51， 95%CI： 0.41 — 0.62） and a relatively high consistency between LFI and SPPB （κ=0.87， 95%CI： 0.80 — 0.94）. Compared with the non-frailty group， the frailty group had significantly higher all-cause mortality rate and incidence rate of composite endpoints （P0.001）. After multivariate adjustment， FFP， LFI， and SPPB had a hazard ratio of 2.42（95%CI： 1.51 — 5.11）， 2.21（95%CI： 1.11 — 4.42）， and 2.21（95%CI： 1.14 — 4.30）， respectively， in predicting all-cause mortality， as well as a hazard ratio of 2.51（95%CI： 1.61 — 3.91）， 2.40（95%CI： 1.51 — 3.80）， and 2.20（95%CI： 1.39 — 3.47）， respectively， in predicting composite endpoints. Compared with Child-Pugh score， FFP had a significantly greater area under the ROC curve （AUC） in predicting all-cause mortality （0.79 vs 0.69， P=0.032） and composite endpoints （0.75 vs 0.68， P=0.044）. Frailty assessment tools combined with Child-Pugh score significantly improved the performance in predicting all-cause mortality and composite endpoints， with an AUC of 0.81 — 0.82 and 0.77 — 0.78， respectively （P0.05）. NRI and IDI analyses further confirmed the improvement of the combined model in classification （all P0.001）. ConclusionFFP， LFI， and SPPB can independently predict adverse outcomes in patients with liver cirrhosis， among which FFP has the best predictive performance， and the combination of frailty assessment tools with Child-Pugh score can significantly enhance the accuracy of prognostic evaluation.

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.