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1.
Bioact Mater ; 26: 413-424, 2023 Aug.
Article in English | MEDLINE | ID: mdl-36969106

ABSTRACT

Bone bionics and structural engineering have sparked a broad interest in optimizing artificial scaffolds for better bone regeneration. However, the mechanism behind scaffold pore morphology-regulated bone regeneration remains unclear, making the structure design of scaffolds for bone repair challenging. To address this issue, we have carefully assessed diverse cell behaviors of bone mesenchymal stem cells (BMSCs) on the ß-tricalcium phosphate (ß-TCP) scaffolds with three representative pore morphologies (i.e., cross column, diamond, and gyroid pore unit, respectively). Among the scaffolds, BMSCs on the ß-TCP scaffold with diamond pore unit (designated as D-scaffold) demonstrated enhanced cytoskeletal forces, elongated nucleus, faster cell mobility, and better osteogenic differentiation potential (for example, the alkaline phosphatase expression level in D-scaffold were 1.5-2 times higher than other groups). RNA-sequencing analysis and signaling pathway intervention revealed that Ras homolog gene family A (RhoA)/Rho-associated kinase-2 (ROCK2) has in-depth participated in the pore morphology-mediated BMSCs behaviors, indicating an important role of mechanical signaling transduction in scaffold-cell interactions. Finally, femoral condyle defect repair results showed that D-scaffold could effectively promote endogenous bone regeneration, of which the osteogenesis rate was 1.2-1.8 times higher than the other groups. Overall, this work provides insights into pore morphology-mediated bone regeneration mechanisms for developing novel bioadaptive scaffold designs.

2.
Front Oncol ; 12: 840950, 2022.
Article in English | MEDLINE | ID: mdl-35359369

ABSTRACT

Background: This study determined the predictive value of CRMP4 promoter methylation in prostate tissues collected by core needle biopsies for a postoperative upgrade of Gleason Score (GS) to ≥8 in patients with low-risk PCa. Method: A retrospective analysis of the clinical data was conducted from 631 patients diagnosed with low-risk PCa by core needle biopsy at multiple centers and then underwent Radical Prostatectomy (RP) from 2014-2019. Specimens were collected by core needle biopsy to detect CRMP4 promoter methylation. The pathologic factors correlated with the postoperative GS upgrade to ≥8 were analyzed by logistic regression. The cut-off value for CRMP4 promoter methylation in the prostate tissues collected by core needle biopsy was estimated from the ROC curve in patients with a postoperative GS upgrade to ≥8. Result: Multivariate logistic regression showed that prostate volume, number of positive cores, and CRMP4 promoter methylation were predictive factors for a GS upgrade to ≥8 (OR: 0.94, 95% CI: 0.91-0.98, P=0.003; OR: 3.16, 95% CI: 1.81-5.53, P<0.001; and OR: 1.43, 95% CI: 1.32-1.55, P<0.001, respectively). The positive predictive rate was 85.2%, the negative predictive rate was 99.3%, and the overall predictive rate was 97.9%. When the CRMP4 promoter methylation rate was >18.00%, the low-risk PCa patients were more likely to escalate to high-risk patients. The predictive sensitivity and specificity were 86.9% and 98.8%, respectively. The area under the ROC curve (AUC) was 0.929 (95% CI: 0.883-0.976; P<0.001). The biochemical recurrence (BCR)-free survival, progression-free survival (PFS), and cancer-specific survival (CSS) were worse in patients with CRMP4 methylation >18.0% and postoperative GS upgrade to ≥8 than in patients without an upgrade (P ≤ 0.002). Conclusion: A CRMP4 promoter methylation rate >18.00% in prostate cancer tissues indicated that patients were more likely to escalate from low-to-high risk after undergoing an RP. We recommend determining CRMP4 promoter methylation before RP for low-risk PCa patients.

3.
J Mater Chem B ; 9(16): 3573-3583, 2021 04 28.
Article in English | MEDLINE | ID: mdl-33909742

ABSTRACT

The regenerative repair of large bone defects is a major problem in orthopedics and clinical medicine. The key problem is the lack of ability of existing bone graft materials to promote osteogenesis and angiogenesis. Previous studies have shown that the osteogenic or angiogenic abilities of these materials could be significantly improved by adding miRNA or small-molecule drugs to bone graft materials; however, the synergistic effect arising from this combination is not clear. Therefore, we proposed to construct a dual drug delivery system that could simultaneously achieve the co-encapsulation and co-delivery of miRNA and small-molecule drugs to explore the effect of a dual drug delivery system on bone repair. In this study, we constructed dual-sized pore structure calcium-silicon nanospheres (DPNPs) and achieved the co-encapsulation of miR-210, angiogenic gene drugs, and simvastatin (Siv), a small-molecule osteogenic drug, through metal-ion coordination and physical adsorption. In vitro and in vivo osteogenic and angiogenic experiments showed that the dual drug delivery system (Siv/DPNP/miR-210) exhibited better properties than those of the individual unloaded and single drug-loaded systems and could significantly accelerate the process of bone repair, which provides a novel strategy for the regeneration and repair of bone defects.


Subject(s)
Bone Regeneration/drug effects , Drug Delivery Systems , MicroRNAs/metabolism , Simvastatin/pharmacology , Tissue Scaffolds/chemistry , Animals , Calcium/chemistry , Cells, Cultured , Humans , Mice , MicroRNAs/genetics , Nanoparticles/chemistry , Osteogenesis/drug effects , Particle Size , Porosity , Silicon/chemistry , Simvastatin/chemistry , Surface Properties
4.
Ann Noninvasive Electrocardiol ; 21(1): 69-81, 2016 Jan.
Article in English | MEDLINE | ID: mdl-25940734

ABSTRACT

AIMS: Research related to type 2 diabetes mellitus (DM) and parameters of electrocardiography (ECG) was limited. Patients with and without DM (NDM) were randomly enrolled in a study to exploit the influence of DM on planar QRS and T vectors derived from the Virtual Holter process. METHODS: A total of 216 (NDM) and 127 DM patients were consecutively and randomly recruited. We selected a 1-minute length of ECG, which was scheduled for analysis at 4 AM. After a series of calculating algorisms, we received the virtual planar vector parameters. RESULTS: Patients with DM were elderly (65.61 ± 12.08 vs 59.41 ± 16.86 years, P < 0.001); higher morbidity of hypertension (76.38% vs 58.14%, P < 0.001) and coronary artery disease (44.09% vs 32.41%, P = 0.03); thicker interventricular septum (10.92 ± 1.77 vs 10.08 ± 1.96 mm, P < 0.001) and left ventricular posterior wall (9.84 ± 1.38 vs 9.39 ± 1.66 mm, P = 0.03); higher lipid levels and average heart rate (66.67 ± 12.04 vs 61.87 ± 13.36 bpm, P < 0.01); higher angle of horizontal QRS vector (HQRSA, -2.87 ± 48.48 vs -19.00 ± 40.18 degrees, P < 0.01); lower maximal magnitude of horizontal T vector (HTV, 2.33 ± 1.47 vs 2.88 ± 1.89 mm, P = 0.01) and maximal magnitude of right side T vector (2.77 ± 1.55 vs 3.27 ± 1.92 mm, P = 0.03), and no difference in angle of frontal QRS-T vector (FQRSTA, 32.77 ± 54.20 vs 28.39 ± 52.87 degrees, P = 0.74) compared with patients having NDM. After adjusting for confounding factors, DM was significantly effective on FQRSTA (regression coefficient -40.0, 95%CI -66.4 to -13.6, P < 0.01), HQRSA (regression coefficient 22.6, 95%CI 2.5 to 42.8, P = 0.03), and HTV (regression coefficient 0.9, 95%CI 0.2 to 1.7, P = 0.01). Confounding factors included: sex, 2-hour postprandial blood glucose, smoking, triglyceride, apolipoprotein A, creatinine, left ventricular ejection fraction, and average heart rate. CONCLUSIONS: The risk factors of DM and lipid metabolism abnormality particularly apolipoprotein A significantly modified parameters of virtual planar QRS and T vector, including frontal QRS-T angle.


Subject(s)
Diabetes Mellitus, Type 2/complications , Diabetic Cardiomyopathies/diagnosis , Electrocardiography, Ambulatory , Aged , Apoprotein(a)/blood , Diabetes Mellitus, Type 2/physiopathology , Diabetic Cardiomyopathies/physiopathology , Female , Humans , Lipid Metabolism , Male , Middle Aged , Random Allocation , Risk Factors
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