Role of arterial stiffness and endothelial dysfunction on lower limb performance in older adults with type 2 diabetes: A cross-sectional study

AimTo verify whether arterial stiffness and endothelial dysfunction influence lower limb muscle strength and gait speed in older adults with type 2 diabetes mellitus (T2DM).MethodsCross-sectional study including seventy-eight older adults with T2DM (aged 67 ± 6 years and 42 % male). Arterial stiffness was assessed using pulse wave velocity (PWV), while endothelial function was measured by flow-mediated dilation (FMD). Lower limb muscle strength and gait speed were assessed using the 30-second chair stand test (30s-CST) and 10-Meter Walk Test, respectively.ResultsBoth PWV (m/s) and FMD (%) were univariately associated with number of repetitions in 30s-CST and gait speed (P < 0.05). After control for age, sex and body mass index, PWV remained associated with repetitions in 30s-CST (95 % CI: ?0.494 to ?0.054; P = 0.015) and gait speed (95 % CI: ?0.039 to ?0.002; P = 0.031). After adjustments for control variables, T2DM duration and glycemic control, FMD was associated with repetitions in 30s-CST (95 % CI: 0.008 to 0.324; P = 0.039) and gait speed (95 % CI: 0.011 to 0.038; P = 0.001).ConclusionIn older adults with T2DM, both arterial stiffness and endothelial dysfunction are associated with decreased leg muscle strength and slower gait speed.     

Gender difference in association between diabetes mellitus and all-cause mortality in atrial fibrillation patients

ObjectiveThere may be gender difference in correlation of diabetes mellitus (DM) and cardiovascular events. We attempt to investigate whether there is gender-heterogeneity in one-year outcomes of atrial fibrillation (AF) patients with DM or not.MethodsPatients who were diagnosed with AF admitted to the emergency departments in the Chinese AF Multicenter Registry study were enrolled. Basic demographics information, initial Blood Pressure and heart rate, medical histories, and treatments of each patient were collected. Follow-up was carried out with a mean duration of one year. The primary endpoint was all-cause mortality and systemic embolism.ResultsA total of 2016 patients were selected from September 2008 and April 2011. All-cause mortality was significantly higher in male AF patients with DM than those without (21.8 % & 13.6 %, P = 0.014). Cox regression analysis showed that there was an interaction between gender and DM for one-year all-cause mortality (P = 0.049). DM was significantly associated with one-year all-cause mortality regardless of univariate analysis (HR = 1.436, 95%CI:1.079–1.911, P = 0.013) or multivariate analysis (HR = 1.418, 95%CI: 1.059–1.899, P = 0.019). For male patients with AF, DM was significantly associated with one-year all-cause mortality (P = 0.048), but not for female patients with AF (P = 0.362).ConclusionDM was independently associated with one-year all-cause mortality in the entire cohort of AF patients. This association was found mainly in male patients with AF, but not in female patients. DM management programs may need to reflect gender difference.     

Deep learning with biopsy whole slide images for pretreatment prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer：A multicenter study

IntroductionPredicting pathological complete response (pCR) for patients receiving neoadjuvant chemotherapy (NAC) is crucial in establishing individualized treatment. Whole-slide images (WSIs) of tumor tissues reflect the histopathologic information of the tumor, which is important for therapeutic response effectiveness. In this study, we aimed to investigate whether predictive information for pCR could be detected from WSIs.Materials and methodsWe retrospectively collected data from four cohorts of 874 patients diagnosed with biopsy-proven breast cancer. A deep learning pathological model (DLPM) was constructed to predict pCR using biopsy WSIs in the primary cohort, and it was then validated in three external cohorts. The DLPM could generate a deep learning pathological score (DLPs) for each patient; stromal tumor-infiltrating lymphocytes (TILs) were selected for comparison with DLPs.ResultsThe WSI feature-based DLPM showed good predictive performance with the highest area under the curve (AUC) of 0.72 among the cohorts. Alternatively, the combination of the DLPM and clinical characteristics offered a better prediction performance (AUC >0.70) in all cohorts. We also evaluated the performance of DLPM in three different breast subtypes with the best prediction for the triple-negative breast cancer (TNBC) subtype (AUC: 0.73). Moreover, DLPM combined with clinical characteristics and stromal TILs achieved the highest AUC in the primary cohort (AUC: 0.82) and validation cohort 1 (AUC: 0.80).ConclusionOur study suggested that WSIs integrated with deep learning could potentially predict pCR to NAC in breast cancer. The predictive performance will be improved by combining clinical characteristics. DLPs from DLPM can provide more information compared to stromal TILs for pCR prediction.     

A highly tumor-targeted nanoparticle of podophyllotoxin penetrated tumor core and regressed multidrug resistant tumors

Podophyllotoxin (PPT) exhibited significant activity against P-glycoprotein mediated multidrug resistant (MDR) tumor cell lines; however, due to its poor solubility and high toxicity, PPT cannot be dosed systemically, preventing its clinical use for MDR cancer. We developed a nanoparticle dosage form of PPT by covalently conjugating PPT and polyethylene glycol (PEG) with acetylated carboxymethyl cellulose (CMC-Ac) using one-pot esterification chemistry. The polymer conjugates self-assembled into nanoparticles (NPs) of variable sizes (20–120 nm) depending on the PPT-to-PEG molar ratio (2–20). The conjugate with a low PPT/PEG molar ratio of 2 yielded NPs with a mean diameter of 20 nm and released PPT at ∼5%/day in serum, while conjugates with increased PPT/PEG ratios (5 and 20) produced bigger particles (30 nm and 120 nm respectively) that displayed slower drug release (∼2.5%/day and ∼1%/day respectively). The 20 nm particles exhibited 2- to 5-fold enhanced cell killing potency and 5- to 20-fold increased tumor delivery compared to the larger NPs. The biodistribution of the 20 nm PPT-NPs was highly selective to the tumor with 8-fold higher accumulation than all other examined tissues, while the larger PPT-NPs (30 and 120 nm) exhibited increased liver uptake. Within the tumor, >90% of the 20 nm PPT-NPs penetrated to the hypovascular core, while the larger particles were largely restricted in the hypervascular periphery. The 20 nm PPT-NPs displayed significantly improved efficacy against MDR tumors in mice compared to the larger PPT-NPs, native PPT and the standard taxane chemotherapies, with minimal toxicity.