Background/Aims: Lenvatinib resistance remains a critical barrier in advanced hepatocellular carcinoma (HCC) therapy. However, the underlying mechanisms and strategies for reversing resistance remain incompletely understood. Methods: Integrated transcriptomics of lenvatinib-resistant patient tumors and an acquired-resistance murine model identified a novel macrophage subpopulation. Functional validation employed CRISPR-SAM screening, conditioned medium (CM) assays, subcutaneous/orthotopic xenografts, patient-derived organoids (PDOs), and patient-derived xenografts (PDXs). Mechanistic studies included ChIP-qPCR, co-immunoprecipitation, and pharmacologic targeting. Clinical relevance was assessed in a retrospective cohort. Results: Resistant HCC exhibited significant enrichment of a COLEC12high TAM subset , which correlated with poor survival and treatment response. These TAMs secreted neuregulin-1 (NRG1) , activating HER2/HER3-AKT signaling in tumor cells to drive cancer stemness and lenvatinib resistance. Mechanistically, in TAMs COLEC12 sequestered STAT1 in the cytoplasm, preventing its phosphorylation, and thereby derepressing STAT3-mediated NRG1 transcription. Depletion of NRG1 reversed the stemness phenotypes and resensitized tumors to lenvatinib both in vitro and in vivo. Clinically, high NRG1 expression predicted an inferior lenvatinib response and shorter survival. Crucially, the bispecific anti-HER2/HER3 antibody zenocutuzumab restored lenvatinib efficacy in PDOs, PDXs, and murine models. Conclusions Our work establishes the COLEC12high TAM/NRG1 axis as a master regulator of therapeutic resistance and identifies NRG1 as a predictive biomarker, providing a clinically actionable strategy to overcome lenvatinib resistance in HCC.

Background: Advances in intensive care have markedly improved survival after severe brain injury, leading to a growing population of patients with prolonged disorders of consciousness (pDOC). Current management of pDOC remains largely supportive, and evidence-based neuromodulatory interventions are limited; moreover, existing guidelines provide insufficiently explicit recommendations regarding mechanisms of action and objective biomarkers of treatment response. Transcutaneous auricular vagus nerve stimulation (taVNS) has emerged as a potential noninvasive intervention; however, its modulatory effects on brain function in pDOC are not yet well characterized, and the paucity of integrative mechanistic evidence has constrained its translation into routine clinical practice. Objectives: Within a multimodal assessment framework, this study aims to systematically elucidate the neurobiological mechanisms by which taVNS modulates brain function and autonomic activity in patients with pDOC, and to evaluate its clinical potential to enhance levels of consciousness. Methods: In this randomized controlled trial, 60 patients with vegetative state/minimally conscious state will be enrolled and randomly allocated to a taVNS group, a transcutaneous nonauricular vagus nerve stimulation group (sham), or a control group (n = 20 per group) for a 4-week intervention. The primary outcome will be changes in the Coma Recovery Scale-Revised scores from baseline to weeks 1, 2, and 4 of treatment. Secondary outcomes will include functional brain activity assessed by electroencephalography and functional near-infrared spectroscopy, as well as autonomic modulation indexed by heart rate variability. Functional prognosis will be evaluated using the Glasgow Outcome Scale-Extended at the end of treatment and at a 6-month follow-up. Safety will be assessed by continuous monitoring and documentation of adverse events throughout the study period. Results and discussion: By integrating electroencephalography–functional near-infrared spectroscopy with heart rate variability, this study will characterize the effects of taVNS on functional brain networks and consciousness recovery in pDOC across complementary behavioral, electrophysiological, hemodynamic, and autonomic domains, while interrogating potential sources of clinical and neurobiological heterogeneity. The findings are expected to provide a mechanistic and evidence-based foundation for the mechanism-driven clinical implementation of taVNS and the optimization of stimulation protocols in pDOC. Clinical trial registration: International Traditional Medicine Clinical Trial Registry, ITMCTR20250021041, https://itmctr.ccebtcm.org.cn.

ObjectiveObesity, a global chronic metabolic disease, is closely associated with disruptions in lipid metabolism and gut microbiota. Current intervention strategies still have limitations in terms of safety and microecological regulation, necessitating the exploration of novel natural regulatory approaches. Based on the early pathological characteristics of obesity, this study innovatively employs a rectal delivery method alongside a high-fat diet (HFD)-induced obesity model to systematically evaluate the inhibitory effects, safety, and gut microbiota regulation mechanisms of leek-derived and konjac-derived extracellular vesicles on obesity development. By simulating early clinical intervention scenarios, this study aims to explore the preventive potential of plant-derived extracellular vesicles during the initial stages of obesity onset. MethodsExtracellular vesicles from leek and konjac were isolated using ultracentrifugation combined with density gradient centrifugation. Their nanoscale properties were characterized by dynamic light scattering (DLS), transmission electron microscopy (TEM), and nanoparticle tracking analysis (NTA). Male C57BL/6J mice were randomly divided into four groups: normal control (NC), high-fat diet (HFD), leek-derived extracellular vesicles (LEVs), and konjac-derived extracellular vesicles (KEVs). Beginning simultaneously with HFD feeding, mice in the intervention groups received 20 g/L vesicles rectally every 3 d for 4 weeks. Body mass and body composition were monitored throughout. At endpoint, mouse serum, adipose tissue, and colonic contents were collected. Serum biochemical indices (lipid profile, liver and kidney function, cardiac markers) were assessed to evaluate safety and metabolic efficacy, while 16S rRNA sequencing was employed to analyze gut microbial structure and diversity. ResultsDLS, NTA, and TEM confirmed that both LEVs and KEVs exhibited typical cup-shaped nanostructures with average particle sizes of approximately 284 nm and 223 nm, respectively. LEVs and KEVs treatment significantly suppressed HFD-induced weight gain and elevation of body-fat percentage (P<0.05), and reduced accumulation of abdominal white and epididymal adipose tissue. Serological analyses showed that both vesicles lowered total cholesterol, triglycerides and LDL-cholesterol, and ameliorated liver enzyme profiles (ALT, AST), demonstrating lipid-metabolic regulation and hepatoprotective effects. No hepatic, renal or cardiac dysfunction was observed, indicating favorable safety. Gut microbiota analyses revealed that vesicle intervention partially restored HFD-depleted microbial diversity and reshaped community structure. Notably, LEVs markedly increased the relative abundance of the beneficial taxon Lachnospiraceae at the family level, which is known for producing short-chain fatty acids and enhancing intestinal barrier function. Furthermore, Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) functional prediction suggested that LEVs and KEVs modulated gut microbial functions through distinct mechanisms: LEVs downregulated pathways related to ribosomes and DNA replication while enhancing xenobiotic degradation, whereas KEVs tended to upregulate energy metabolism and protein synthesis toward healthy levels. ConclusionRectally administered LEVs and KEVs exhibit excellent safety and pronounced metabolic benefits during the early phase of obesity, suppressing weight gain, correcting lipid dysregulation, and exerting effects via modulation of gut microbial composition and function. This study provides systematic experimental evidence supporting plant-derived exosome-like vesicles as an early intervention strategy against obesity.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

OBJECTIVE: To explore the genetic etiology of 46 Chinese pedigrees affected with Hereditary multiple exostoses (HME) and provide genetic counseling and reproductive intervention. METHODS: Whole-exome sequencing and Sanger sequencing were carried out on 87 patients from the 46 pedigrees to analyze the variants of EXT1 and EXT2 genes. Pathogenicity of the variants was assessed based on the guidelines from the American College of Medical Genetics and Genomics and Association for Molecular Pathology (ACMG/AMP). Prenatal diagnosis and preimplantation genetic testing (PGT) were provided for couples with identified pathogenic mutations. This study was approved by the Medical Ethics Committee of the hospital (Ethics No.: LL-SC-SG-2014-010). RESULTS: In total 17 and 22 pathogenic variants were respectively identified in the EXT1 and EXT2 genes, among which 5 EXT1 and 12 EXT2 variants were unreported previously. Three patients with no family history were found to harbor de novo variants of the EXT1 gene. Twenty nine couples had opted for PGT or underwent prenatal diagnosis following natural conception, and 17 healthy babies were born. CONCLUSION This study has clarified the genetic etiology of 45 HME pedigrees and identified 17 novel variants, which has enriched the mutational spectrum of the EXT1 and EXT2 genes. Reproductive intervention through PGT and prenatal diagnosis have prevented the recurrence of HME in these families.
Humans ; Female ; Male ; Pedigree ; Exostoses, Multiple Hereditary/diagnosis* ; N-Acetylglucosaminyltransferases/genetics* ; Adult ; Exostosin 1 ; Asian People/genetics* ; Genetic Testing ; Exostosin 2 ; Mutation ; China ; Prenatal Diagnosis ; Pregnancy ; Genetic Counseling ; Preimplantation Diagnosis ; Exome Sequencing ; East Asian People

ObjectiveTo investigate the effect of repetitive peripheral magnetic stimulation (rPMS) combined with upper limb intelligent robotic training on muscle tension, motor function and cortical excitability in children with unilateral spastic cerebral palsy (USCP). MethodsFrom March, 2023 to December, 2024, 90 children with USCP admitted to Children's Hospital of Soochow University were selected and randomly divided into control group (n = 30), rPMS group (n = 30) and combined group (n = 30). The control group received conventional occupational therapy. The rPMS group received rPMS intervention followed by conventional occupational therapy. The combined group received rPMS followed by upper limb intelligent robot training, for four weeks. Before and after treatment, muscle tension of biceps brachii was assessed using the modified Ashworth Scale (MAS); upper limb motor function was evaluated using the Fugl-Meyer Assessment-Upper Extremity (FMA-UE) and upper limb intelligent parameters; and cortical excitability was measured using transcranial magnetic stimulation (TMS), including resting motor threshold (RMT) and motor-evoked potential (MEP) amplitude of the affected hemisphere. ResultsAfter treatment, MAS grades improved in all groups (|Z| > 3.523, P < 0.001), and the improvement in the combined group was superior to that in the control group (P < 0.05). Significant intra-group (F > 65.21, P < 0.001), inter-group (F > 17.94, P < 0.001) and interaction effects (F > 5.36, P < 0.01) were observed in FMA-UE scores, upper limb intelligent parameters and TMS parameters. Post Hoc analysis showed that the combined group demonstrated significantly greater improvements in FMA-UE scores, upper limb intelligent parameters, and TMS parameters compared with both the control and rPMS groups (all P < 0.01). Except for FMA-UE scores, the rPMS group showed significantly greater improvements than the control group in upper limb intelligent parameters (mechanical feedback, trajectory, and range of motion) and TMS parameters (RMT and MEP amplitude) (P < 0.05). ConclusionrPMS combined with upper limb intelligent robotic training can reduce upper limb muscle tension, improve motor function, and enhance cortical excitability in children with USCP.

ObjectiveObesity, a global chronic metabolic disease, is closely associated with disruptions in lipid metabolism and gut microbiota. Current intervention strategies still have limitations in terms of safety and microecological regulation, necessitating the exploration of novel natural regulatory approaches. Based on the early pathological characteristics of obesity, this study innovatively employs a rectal delivery method alongside a high-fat diet (HFD)-induced obesity model to systematically evaluate the inhibitory effects, safety, and gut microbiota regulation mechanisms of leek-derived and konjac-derived extracellular vesicles on obesity development. By simulating early clinical intervention scenarios, this study aims to explore the preventive potential of plant-derived extracellular vesicles during the initial stages of obesity onset. MethodsExtracellular vesicles from leek and konjac were isolated using ultracentrifugation combined with density gradient centrifugation. Their nanoscale properties were characterized by dynamic light scattering (DLS), transmission electron microscopy (TEM), and nanoparticle tracking analysis (NTA). Male C57BL/6J mice were randomly divided into four groups: normal control (NC), high-fat diet (HFD), leek-derived extracellular vesicles (LEVs), and konjac-derived extracellular vesicles (KEVs). Beginning simultaneously with HFD feeding, mice in the intervention groups received 20 g/L vesicles rectally every 3 d for 4 weeks. Body mass and body composition were monitored throughout. At endpoint, mouse serum, adipose tissue, and colonic contents were collected. Serum biochemical indices (lipid profile, liver and kidney function, cardiac markers) were assessed to evaluate safety and metabolic efficacy, while 16S rRNA sequencing was employed to analyze gut microbial structure and diversity. ResultsDLS, NTA, and TEM confirmed that both LEVs and KEVs exhibited typical cup-shaped nanostructures with average particle sizes of approximately 284 nm and 223 nm, respectively. LEVs and KEVs treatment significantly suppressed HFD-induced weight gain and elevation of body-fat percentage (P<0.05), and reduced accumulation of abdominal white and epididymal adipose tissue. Serological analyses showed that both vesicles lowered total cholesterol, triglycerides and LDL-cholesterol, and ameliorated liver enzyme profiles (ALT, AST), demonstrating lipid-metabolic regulation and hepatoprotective effects. No hepatic, renal or cardiac dysfunction was observed, indicating favorable safety. Gut microbiota analyses revealed that vesicle intervention partially restored HFD-depleted microbial diversity and reshaped community structure. Notably, LEVs markedly increased the relative abundance of the beneficial taxon Lachnospiraceae at the family level, which is known for producing short-chain fatty acids and enhancing intestinal barrier function. Furthermore, Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) functional prediction suggested that LEVs and KEVs modulated gut microbial functions through distinct mechanisms: LEVs downregulated pathways related to ribosomes and DNA replication while enhancing xenobiotic degradation, whereas KEVs tended to upregulate energy metabolism and protein synthesis toward healthy levels. ConclusionRectally administered LEVs and KEVs exhibit excellent safety and pronounced metabolic benefits during the early phase of obesity, suppressing weight gain, correcting lipid dysregulation, and exerting effects via modulation of gut microbial composition and function. This study provides systematic experimental evidence supporting plant-derived exosome-like vesicles as an early intervention strategy against obesity.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveTo investigate whether modified Taohe Chengqitang （JTCT） treats liver fibrosis by inhibiting hepatic sinusoidal capillarization， and to verify whether its specific mechanism is related to the Homologous genes responsible for the notches along the edges of Drosophila wings（Notch） signaling pathway and endothelial nitric oxide synthase （eNOS） signaling pathway. MethodsFifty C57BL/6 mice were randomized into 5 groups： Control， model （5 mL·kg^-1·3 d^-1）， low-dose JTCT， medium-dose JTCT， and high-dose JTCT （JTCT-L，JTCT-M，JTCT-H）. Except the control group， the other groups were intraperitoneally injected with 20% carbon tetrachloride （CCl₄） olive oil solution every 3 days for 4 weeks to induce liver fibrosis. Meanwhile， JTCT-L， JTCT-M， and JTCT-H groups were administrated with JTCT by gavage at doses of 16.6， 33.3， and 66.6 g·kg^-1·d^-1， respectively， for 4 consecutive weeks （the control and model groups received equal volumes of normal saline by gavage）. Primary liver sinusoidal endothelial cells （LSECs） were isolated from rat livers through in situ perfusion of collagenase， Percoll density gradient centrifugation， and selective removal of Kupffer cells. After verification of cell phenotype， LSECs were used for experiments. For cells at the logarithmic growth phase， the small interfering RNA（siRNA） kit was used to knock down the expression of soluble guanylate cyclase （sGC） through transient transfection. Subsequently， the Notch agonist Jagged-1 was applied. Cell counting kit-8 （CCK-8） was used to examine the cytotoxicity of JTCT on LSECs. Real-time PCR and Western blot were employed to measure the expression of molecules in the Notch and eNOS signaling pathways at mRNA and protein levels， respectively. Intracellular Ca²⁺ was labeled with the fluorescent probe Fluo-4 acetoxymethyl ester（Fluo-4/AM）. ResultsThe animal experiment showed that compared with the control group， the model group exhibited hepatic steatosis， inflammatory cell infiltration， hepatocyte degeneration and necrosis， lobular structural disorder， and fibrous tissue hyperplasia in the mouse liver tissue， significantly elevated serum levels of hydroxyproline （Hyp）， alanine transaminase （ALT）， and aspartate transaminase （AST） （P<0.01）， significantly upregulated expression levels of Notch1， Hes family bHLH transcription factor 1（Hes1）， Cluster of Differentiation 31（CD31）， and von Willebrand factor（vWF） （P<0.01）， and significantly downregulated phosphorylate（p）-eNOS/eNOS ratio and sGC expression （P<0.01）. Compared with the model group， all the JTCT groups showed significantly reduced serum Hyp， ALT， and AST levels （P<0.01）， downregulated expression of Notch1， Hes1， CD31， and vWF （P<0.05， P<0.01）， and upregulated p-eNOS/eNOS ratio and sGC expression （P<0.05， P<0.01） in the liver tissue， with the JTCT-H group showing the most significant changes （P<0.01）. The cell experiment showed that compared with the LSEC-1day group， the LSEC-5day group exhibited significantly increased expression of Notch1， Hes1， CD31， and vWF （P<0.01）， significantly decreased p-eNOS/eNOS ratio and sGC expression （P<0.01）， and elevated intracellular Ca²⁺ concentration （P<0.01）. Compared with the LSEC-5day group， the JTCT group showed decreased expression of Notch1， Hes1， CD31， and vWF （P<0.01）， significantly increased p-eNOS/eNOS ratio （P<0.01）， and significantly reduced intracellular Ca²⁺ concentration （P<0.01）. No significant differences were observed in the expression of Notch1， Hes1， eNOS， p-eNOS， CD31， vWF， sGC， or intracellular Ca²⁺ concentration between the Jagged1 group and the Jagged1+JTCT group. Compared with the LSEC-5day group， the sGC knockout group （sGC-KO） showed significantly increased expression of CD31 and vWF （P<0.01）. There was no significant difference in CD31 or vWF expression between the sGC-KO group and the sGC-KO+JTCT group. ConclusionJTCT inhibits the activation of the Notch signaling pathway and restores the activity of the eNOS signaling pathway to suppress sinusoidal capillarization of LSECs， thereby treating liver fibrosis.

Objective: To examine the relationship between self-management behaviors and time perspective among patients with comorbid diabetes, so as to provide the evidence for improving self-management behaviors among patients with comorbid diabetes. Methods: The patients with comorbid diabetes who were registered in the chronic disease health management system of Minhang District, Shanghai Municipality in 2021, followed up regularly, and lived in Meilong Town were recruited. Demographic information and family history of diabetes were collected through questionnaire surveys. Time perspective and self-management behaviors were assessed using the Zimbardo Time Perspective Inventory and Diabetes Self-Management Behavior Scale, respectively. The relationship between self-management behaviors and time perspective was analyzed using a multivariable ordinal logistic regression model. Results: A total of 907 patients with comorbid diabetes were enrolled, including 472 males (52.04%) and 435 females (47.96%). There were 652 cases aged 65 years and above, accounting for 71.89%. In terms of the types of time perspective, 280 patients were future-oriented (30.87%), 236 were balanced (26.02%), 162 were sensation-seeking (17.86%), 123 were fatalistic (13.56%), and 106 were negative (11.69%). In terms of the self-management behaviors, 46 patients were good (5.07%), 643 were moderate (70.89%), and 218 were poor (24.04%). Multivariable ordinal logistic regression analysis showed that after adjusting for age, gender, educational level, marital status, occupation status, monthly income, and family history of diabetes, the patients with comorbid diabetes who had a future-oriented time perspective had better self-management behaviors (OR=1.874, 95%CI: 1.204-2.915). Conclusion The self-management behaviors among patients with comorbid diabetes are moderate to poor, and patients with a future-oriented time perspective can better engage in self-management behaviors.