Chinese hamster ovary (CHO) cells are the most established and versatile mammalian expression system for the large-scale production of recombinant therapeutic proteins, owing to their genetic stability, adaptability to serum-free suspension culture, and ability to perform human-like post-translational modifications. More than 70% of biologics approved by the U.S. Food and Drug Administration rely on CHO-based production platforms, underscoring their central role in modern biopharmaceutical manufacturing. Despite these advantages, CHO systems continue to face three persistent bottlenecks that limit their potential for high-yield, reproducible, and cost-efficient production: excessive metabolic burden during high-density culture, heterogeneity of glycosylation patterns, and progressive loss of long-term expression stability. This review provides an integrated analysis of recent advances addressing these challenges and proposes a forward-looking framework for constructing intelligent and sustainable CHO cell factories. In terms of metabolic regulation, excessive lactate and ammonia accumulation disrupts energy balance and reduces recombinant protein synthesis efficiency. Optimization of culture parameters such as temperature, pH, dissolved oxygen, osmolarity, and glucose feeding can effectively alleviate metabolic stress, while supplementation with modulators including sodium butyrate, baicalein, and S-adenosylmethionine promotes specific productivity (qP) by modulating apoptosis and chromatin structure. Furthermore, genetic engineering strategies—such as overexpression of MPC1/2, HSP27, and SIRT6 or knockout of Bax, Apaf1, and IGF-1R—have demonstrated significant improvements in cell viability and product yield. The combination of multi-omics metabolic modeling with artificial intelligence (AI)-based prediction offers new opportunities for building self-regulating CHO systems capable of dynamic adaptation to environmental stress. Regarding glycosylation uniformity, which determines therapeutic efficacy and immunogenicity, gene editing-based glycoengineering (e.g., FUT8 knockdown or ST6Gal1 overexpression) has enabled the humanization of CHO glycan profiles, minimizing non-human sugar residues and enhancing drug stability. Process-level strategies such as galactose or manganese co-feeding and fine control of temperature or osmolarity further allow rational regulation of glycosyltransferase activity. Additionally, in vitro chemoenzymatic remodeling provides a complementary route to construct human-type glycans with defined structures, though industrial applications remain constrained by cost and scalability. The integration of model-driven process design and AI feedback control is expected to enable real-time prediction and correction of glycosylation deviations, ensuring batch-to-batch consistency in continuous biomanufacturing. Long-term expression stability, another critical challenge, is often impaired by promoter silencing, chromatin condensation, and random genomic integration. Molecular optimization—such as the use of improved promoters (CMV, EF-1α, or CHO endogenous promoters), Kozak and signal peptide refinement, and incorporation of chromatin-opening elements (UCOE, MAR, STAR)—helps maintain durable transcriptional activity, while site-specific integration systems including Cre/loxP, Flp/FRT, φC31, and CRISPR/Cas9 can enable single-copy, position-independent gene insertion at genomic safe-harbor loci, ensuring stable, predictable expression. Collectively, this review highlights a paradigm shift in CHO system optimization driven by the convergence of genome editing, synthetic biology, and artificial intelligence. The transition from empirical optimization to rational, data-driven design will facilitate the development of programmable CHO platforms capable of autonomous regulation of metabolic flux, glycosylation fidelity, and transcriptional activity. Such intelligent cell factories are expected to accelerate the transformation from laboratory-scale research to industrial-scale, high-consistency, and economically sustainable biopharmaceutical manufacturing, thereby supporting the next generation of efficient and customizable biologics manufacturing.

Chinese hamster ovary (CHO) cells are the most established and versatile mammalian expression system for the large-scale production of recombinant therapeutic proteins, owing to their genetic stability, adaptability to serum-free suspension culture, and ability to perform human-like post-translational modifications. More than 70% of biologics approved by the U.S. Food and Drug Administration rely on CHO-based production platforms, underscoring their central role in modern biopharmaceutical manufacturing. Despite these advantages, CHO systems continue to face three persistent bottlenecks that limit their potential for high-yield, reproducible, and cost-efficient production: excessive metabolic burden during high-density culture, heterogeneity of glycosylation patterns, and progressive loss of long-term expression stability. This review provides an integrated analysis of recent advances addressing these challenges and proposes a forward-looking framework for constructing intelligent and sustainable CHO cell factories. In terms of metabolic regulation, excessive lactate and ammonia accumulation disrupts energy balance and reduces recombinant protein synthesis efficiency. Optimization of culture parameters such as temperature, pH, dissolved oxygen, osmolarity, and glucose feeding can effectively alleviate metabolic stress, while supplementation with modulators including sodium butyrate, baicalein, and S-adenosylmethionine promotes specific productivity (qP) by modulating apoptosis and chromatin structure. Furthermore, genetic engineering strategies—such as overexpression of MPC1/2, HSP27, and SIRT6 or knockout of Bax, Apaf1, and IGF-1R—have demonstrated significant improvements in cell viability and product yield. The combination of multi-omics metabolic modeling with artificial intelligence (AI)-based prediction offers new opportunities for building self-regulating CHO systems capable of dynamic adaptation to environmental stress. Regarding glycosylation uniformity, which determines therapeutic efficacy and immunogenicity, gene editing-based glycoengineering (e.g., FUT8 knockdown or ST6Gal1 overexpression) has enabled the humanization of CHO glycan profiles, minimizing non-human sugar residues and enhancing drug stability. Process-level strategies such as galactose or manganese co-feeding and fine control of temperature or osmolarity further allow rational regulation of glycosyltransferase activity. Additionally, in vitro chemoenzymatic remodeling provides a complementary route to construct human-type glycans with defined structures, though industrial applications remain constrained by cost and scalability. The integration of model-driven process design and AI feedback control is expected to enable real-time prediction and correction of glycosylation deviations, ensuring batch-to-batch consistency in continuous biomanufacturing. Long-term expression stability, another critical challenge, is often impaired by promoter silencing, chromatin condensation, and random genomic integration. Molecular optimization—such as the use of improved promoters (CMV, EF-1α, or CHO endogenous promoters), Kozak and signal peptide refinement, and incorporation of chromatin-opening elements (UCOE, MAR, STAR)—helps maintain durable transcriptional activity, while site-specific integration systems including Cre/loxP, Flp/FRT, φC31, and CRISPR/Cas9 can enable single-copy, position-independent gene insertion at genomic safe-harbor loci, ensuring stable, predictable expression. Collectively, this review highlights a paradigm shift in CHO system optimization driven by the convergence of genome editing, synthetic biology, and artificial intelligence. The transition from empirical optimization to rational, data-driven design will facilitate the development of programmable CHO platforms capable of autonomous regulation of metabolic flux, glycosylation fidelity, and transcriptional activity. Such intelligent cell factories are expected to accelerate the transformation from laboratory-scale research to industrial-scale, high-consistency, and economically sustainable biopharmaceutical manufacturing, thereby supporting the next generation of efficient and customizable biologics manufacturing.

ObjectivePost-ischemic acute inflammation and the subsequent persistent dysregulation of the immune microenvironment represent major pathological drivers that aggravate neuronal injury and severely restrict functional recovery following ischemic stroke. Although current reperfusion therapies partially restore blood flow, they fail to effectively modulate the secondary inflammatory cascade and oxidative stress, which remain critical barriers to neurological restoration. To address this challenge, this study aimed to engineer and systematically evaluate a biomimetic nanosystem composed of transforming growth factor-β1 (TGF-β1)-loaded platelet membrane-camouflaged lipid nanoparticles (PLP). This nanosystem was designed to achieve dual lesion-targeted delivery and immune microenvironment remodeling. By verifying its spatiotemporal accumulation, anti-inflammatory activity, and neuroprotective efficacy, we sought to establish an integrated therapeutic strategy that simultaneously enables lesion targeting, immune regulation, and functional recovery after ischemic injury. MethodsThe physicochemical properties of PLP, including hydrodynamic particle size, zeta potential, structural stability, and morphology, were characterized using dynamic light scattering, zeta potential analysis, and transmission electron microscopy. The preservation of platelet membrane-derived adhesion and immunoregulatory proteins was confirmed by SDS-PAGE through comparative analysis of protein band profiles between PLP and native platelet membranes. The in vitro biological activities of PLP were evaluated using two complementary cellular models. LPS-induced M1-polarized RAW264.7 macrophages were employed to assess inflammatory modulation, while oxygen glucose deprivation/reperfusion (OGD/R)-induced BV2 microglial cells and SH-SY5Y neuronal cells were utilized to investigate neuroinflammatory regulation and neuronal protection. For in vivo validation, a transient middle cerebral artery occlusion (tMCAO) mouse model was established to mimic ischemia-reperfusion injury. The spatiotemporal biodistribution and lesion-targeting capability of the PLP were monitored through live fluorescence imaging. Therapeutic efficacy was comprehensively evaluated by triphenyltetrazolium chloride (TTC) staining, glial fibrillary acidic protein (GFAP) immunofluorescence analysis, body weight monitoring, and neurological severity score (NSS) assessment. ResultsPLP nanoparticles displayed a uniform spherical morphology, nanoscale particle size distribution, and stable negative surface charge, indicating favorable colloidal stability and circulation potential. SDS-PAGE results confirmed the effective retention of key platelet membrane proteins associated with endothelial adhesion, immune evasion, and inflammatory regulation, demonstrating the successful biomimetic construction. Optimal therapeutic concentrations were determined in OGD/R-induced BV2 cells, where PLP exhibited excellent cytocompatibility and anti-inflammatory activity.In vitro experiments demonstrated that PLP significantly inhibited the polarization of RAW264.7 macrophages toward the pro-inflammatory M1 phenotype and markedly reduced neuronal apoptosis under ischemia-reperfusion conditions. In vivo fluorescence imaging revealed that PLP rapidly accumulated in the ischemic brain hemisphere and maintained prolonged retention for up to 7 d, suggesting enhanced lesion-specific targeting and sustained drug release. Compared with control group, PLP treatment significantly reduced cerebral infarct volume, attenuated reactive astrogliosis, improved weight recovery, and accelerated neurological functional restoration, as reflected by significantly improved NSS scores. ConclusionThis study establishes a multifunctional biomimetic nanoplatform that integrates platelet membrane-mediated active targeting with the anti-inflammatory, antioxidative, and neuroprotective properties of TGF-β1. The PLP system enables rapid lesion homing and long-term retention while synergistically regulating the post-stroke inflammatory microenvironment by suppressing pro-inflammatory immune activation, reducing neuronal apoptosis, and limiting excessive astrocyte reactivity. Importantly, this study proposes a conceptually therapeutic paradigm that combines targeted delivery with immune microenvironment remodeling to achieve comprehensive neurovascular protection. These findings provide strong experimental evidence supporting the translational potential of biomimetic nanotherapeutics as next-generation precision interventions for ischemic stroke.

Objective To quantitatively assess the exposure-response association between exposure to heatwave and sudden death, estimate the attributable excess deaths, and identify potential vulnerable subgroups. Methods A time-stratified case-crossover study was conducted among residents who died from sudden death in Jiangsu Province, China between 2015 and 2021. Heatwave events in Jiangsu Province, defined using varying relative temperature thresholds and durations, were identified using temperature data from the China Meteorological Administration Land Data Assimilation System (CLDAS V2.0). Individual heatwave exposure was assessed based on each subject's residential address. The exposure-response association between heatwave and sudden death was evaluated using conditional logistic regression model combined with a Distributed Lag Nonlinear Model(DLNM). Heatwave-attributable excess deaths were estimated. Stratified analyses by sex and age were performed to assess potential effect modifications. Results Under all definitions, exposure to heatwave was significantly associated with an increased risk of sudden death, and the risk increased with the intensity of heatwave. Using the P95_3d definition (temperature exceeding the 95th percentile for ≥3 consecutive days), heatwave was significantlyassociated with a 56% increased risk of sudden death (95% CI: 31%, 86%). The population-attributable fraction of sudden death due to heatwave exposure was 1.45% (95% CI: 0.97%, 1.90%). Stratified analyses indicated no statistically significant differences in the association between heatwave exposure and sudden death across age or sex subgroups. Conclusion Heatwave exposure was associated with an increased risk of sudden death. Reducing heatwave exposure during summer may help lower the occurrence of sudden death.

OBJECTIVE: To investigate the current status of clinical genetics specialization development and the diagnostic and therapeutic capabilities for hereditary diseases across medical institutions in Shanghai, and to assess the necessity and feasibility of establishing training bases for clinical genetics specialists. METHODS: By employing a cross-sectional survey design, the Clinical Genetics Committee of Shanghai Medical Association has conducted questionnaire surveys from March to April 2025 across 54 healthcare institutions in Shanghai (including 33 tertiary hospitals and 21 secondary hospitals). The survey involved administrative departments and medical personnel from 15 clinical specialties. The survey has covered current genetic disease diagnosis and treatment practices, relevant and specialised disease types, genetic department establishment, testing capabilities, personnel teams, and training requirements. RESULTS: The results revealed that 78.0% of clinical departments surveyed had treated patients with hereditary disorders. Shanghai possesses diagnostic and therapeutic expertise for over 95% of hereditary diseases listed in its rare disease catalogue, reflecting both the practical clinical demand for such conditions and the city's overall diagnostic and therapeutic strengths in this field. Nevertheless, significant disparities exist in the development of genetics departments across different tiers of healthcare institutions. Resources for genetic testing capabilities (including molecular, cellular, and biochemical testing) are also unevenly distributed across different tiers of hospitals. The survey further revealed that only 26.0% of departments believe that their current physician structure fully meets the diagnostic and treatment demands. Over 90% of departments consider standard training for clinical genetic specialists necessary, with 74.0% expressing willingness to participate in establishing training bases. Based on above findings and thorough deliberation, the Clinical Genetics Committee of the Shanghai Medical Association proposes advancing specialist training and discipline development through establishing a standard training system. The committee has drafted a three-year training protocol featuring a "joint training"-centered model, recommending a pilot-first, dynamically optimized strategy for steadily advancing training base development. CONCLUSION Shanghai faces substantial demand for genetic disease diagnosis and treatment, yet exhibits shortcomings in clinical genetics specialization development, resource allocation, and talent pipeline cultivation. To establish a standard training system holds significant practical importance and is underpinned by a broad demand.
Humans ; China ; Surveys and Questionnaires ; Genetic Diseases, Inborn/genetics* ; Cross-Sectional Studies ; Genetics, Medical/education* ; Genetic Testing

BACKGROUND:Patellar tendonitis can present as tendon degeneration that fails to heal due to tissue overload and incomplete recovery.Patellar tendonitis is a predisposition to high jumping and its pathogenesis has not been clearly defined.OBJECTIVE:To explore the stress-strain relationship of patellar tendon in the take-off technique of high jump through the finite element model with accurate human anatomical structure,so as to provide ideas for the prevention and rehabilitation of patellar tendinitis.METHODS:Based on the CT and MRI imaging data of the lower extremity(including the knee and ankle)of one subject(22 years old,183 cm height,70 kg body mass),a three-dimensional finite element model of the lower extremity was reconstructed using medical imaging software,reverse engineering software and modeling software.The plantar pressure of the take-off leg was collected in eight subjects by gait testing system,and the technical action of high jump take-off was collected by motion capture system.The captured data were imported into human sports biomechanics software for analysis,and kinematic and kinetic data were obtained as the boundary conditions of finite element model for finite element simulation analysis.RESULTS AND CONCLUSION:The force borne by the patellar tendon reached 3.29 times of its own body mass when the subjects took off.In the take-off stage,the peak values of normal equivalent stress,strain and shear stress of the patellar tendon were 127.76 MPa,0.81 and 37.69 MPa,respectively,which were in the nonlinear region of the stress-strain curve,and the peak values were distributed in the proximal and posterior parts of patellar tendon.To conclude,the high patellar tendon force,strain and shear stress caused by the load of 3.29 times its own body mass during take-off are related to the induction of patellar tendinitis.

BACKGROUND:Patellar tendonitis can present as tendon degeneration that fails to heal due to tissue overload and incomplete recovery.Patellar tendonitis is a predisposition to high jumping and its pathogenesis has not been clearly defined.OBJECTIVE:To explore the stress-strain relationship of patellar tendon in the take-off technique of high jump through the finite element model with accurate human anatomical structure,so as to provide ideas for the prevention and rehabilitation of patellar tendinitis.METHODS:Based on the CT and MRI imaging data of the lower extremity(including the knee and ankle)of one subject(22 years old,183 cm height,70 kg body mass),a three-dimensional finite element model of the lower extremity was reconstructed using medical imaging software,reverse engineering software and modeling software.The plantar pressure of the take-off leg was collected in eight subjects by gait testing system,and the technical action of high jump take-off was collected by motion capture system.The captured data were imported into human sports biomechanics software for analysis,and kinematic and kinetic data were obtained as the boundary conditions of finite element model for finite element simulation analysis.RESULTS AND CONCLUSION:The force borne by the patellar tendon reached 3.29 times of its own body mass when the subjects took off.In the take-off stage,the peak values of normal equivalent stress,strain and shear stress of the patellar tendon were 127.76 MPa,0.81 and 37.69 MPa,respectively,which were in the nonlinear region of the stress-strain curve,and the peak values were distributed in the proximal and posterior parts of patellar tendon.To conclude,the high patellar tendon force,strain and shear stress caused by the load of 3.29 times its own body mass during take-off are related to the induction of patellar tendinitis.

Objective To compare the efficacy and safety of video-assisted thoracoscopic surgery (VATS) thymectomy for the treatment of thymoma through subxiphoid uniportal approach using double sternum retractors, and subxiphoid and subcostal arch approach. Methods We retrospectively analyzed the clinical data of the patients diagnosed with thymoma who underwent VATS thymectomy from June 2023 to June 2024 in West China Hospital. Patients were categorized based on the surgical approach into two groups: a subxiphoid uniportal VATS thymectomy (SUVT) group and a subxiphoid and subcostal arch VATS thymectomy (SASAT) group. Comparisons were made between the two groups regarding surgical duration, intraoperative blood loss, postoperative drainage, thymoma size and location, and postoperative pain assessed using the visual analogue scale (VAS). Results The SUVT group consisted of 20 patients, including 11 males and 9 females, with an average age of (51.5±14.3) years. The SASAT group comprised 40 patients, including 26 males and 14 females, with an average age of (50.0±13.0) years. Compared to the SASAT group, the SUVT group had significantly larger thymomas [ (5.9±2.7) cm vs. (4.2±2.1) cm, P=0.010] and a higher proportion of neoplasms located in the superior mediastinum (30.0% vs. 2.5%, P=0.007). Additionally, the VAS pain scores on postoperative days 3, 7, and 30 were significantly lower in the SUVT group compared to the SASAT group (P<0.05). There were no statistical differences between the two groups in demographic characteristics, operative time, intraoperative blood loss, duration and volume of postoperative drainage, length of postoperative hospital stay, or the VAS pain score on the first postoperative day. Conclusion SUVT using double sternum retractors significantly reduces postoperative pain and provides superior efficacy in the resection of larger thymomas or those situated in the superior mediastinum.

ObjectiveTo clarify whether epigallocatechin gallate （EGCG） is involved in the clearance of amyloid β-protein （Aβ） and autophagy induction by microglia， so as to explore the potential mechanisms of EGCG in the prevention and treatment of Alzheimer's disease （AD）. MethodsSix-month-old APP/PS1 mice were randomly divided into model and EGCG groups， with some additional wild type （WT） mice as the control group， each group consisting of 15 mice. The EGCG group received continuous gavage administration［5 mg/（kg·d）］ for 8 weeks， followed by the open field test and Y-maze to assess the learning and memory abilities of the mice. Thioflavin-S staining was used to evaluate the content and distribution of amyloid β-protein （Aβ）in the brain parenchyma of the mice， and immunofluorescence was employed to detect the expression levels of Aβ_1-42， glial fibrillary acidic protein （GFAP）， and ionized calcium-binding adapter molecule 1 （Iba1） in the hippocampal tissue of the mice. Additionally， N9 mouse microglial cells were induced with 20 µmol/L Aβ_1-42， and the cell viability was measured after treatment with different concentrations of EGCG （5 µmol/L， 10 µmol/L， 20 µmol/L）. Western blotting was used to detect the levels of Aβ_1-42， low density lipoprotein receptor-related protein 1（LRP1）， receptor for advanced glycation endproducts （RAGE）， amyloid precursor protein （APP）， insulin degrading enzyme （IDE）， neprilysin （NEP）， microtubule associated protein 1 hydrogen chain 3（LC3）-Ⅱ/LC3-Ⅰ， phosphatidylinositol 3-hydroxy kinase（PI3K）， p-PI3K， protein kinase B （AKT）， p-AKT， mammalian target of rapamycin （mTOR）， p-mTOR， and histone deacetylase 6（HDAC6）. Finally， through the co-culture of microglial cells and neuronal SH-SY5Y cells， cell viability and Caspase-3 levels were measured to verify the protective effect of EGCG-mediated Aβ clearance on neurons. ResultsEGCG increased the activity time and frequency of APP/PS1 mice in the central area of the open field （P<0.05）， and enhanced the percentage of alternation in the Y-maze test （P<0.01）； EGCG reduced Aβ deposition in the hippocampal tissue of APP/PS1 mice and increased the number of microglia； in vitro experiments showed that EGCG improved the survival rate of Aβ-induced N9 cells （P<0.01）， upregulated RAGE activity （P<0.05）， and promoted the internalization and phagocytosis of Aβ （P<0.01）. ECGC activated microglial autophagy by downregulating the level of HDAC6 （P<0.05）， inhibiting the phosphorylation of PI3K， AKT， mTOR （P<0.001）， and increasing the LC3-Ⅱ/LC3-I ratio （P<0.001）； EGCG improved the survival rate of SH-SY5Y cells （P<0.05） and reduced the activity of Caspase-3 （P<0.01） by clearing Aβ_1-42 through microglia， and had a protective effect on neurons. ConclusionEGCG activates microglial autophagy to clear Aβ by targeting and inhibiting the HDAC6-PI3K/AKT/mTOR axis.

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.