Background: The relationship between triglyceride-glucose index (TyG index) and the prevalence and prognosis of cardiovascular disease has been confirmed by former studies. However, it remains uncertain whether TyG index has a prognostic impact in patients with type 2 diabetes mellitus (T2DM) and non-ST-segment elevation acute coronary syndrome (NSTE-ACS) undergoing percutaneous coronary intervention (PCI). Methods: The study retrospectively enrolled 798 patients (mean age: 60.9 ± 8.3 years; 68.3% men) with T2DM and NSTE-ACS who underwent PCI at Beijing Anzhen Hospital from January to December 2015. TyG index was calculated as previously reported: ln [fasting TGs (mg/dL) * FBG (mg/dL)/2]. The primary endpoint was a composite of adverse events as follows: all-cause death, non-fatal myocardial infarction (MI) and ischemia-driven revascularization. Results: TyG index was significantly higher in patients with a primary endpoint event compared with those without. Multivariate Cox proportional hazards analysis showed that 1-unit increase of TyG index was independently associated with higher risk of primary endpoint, independent of other risk factors [hazard ratio (HR) 3.208 per 1-unit increase, 95% confidence interval (CI) 2.400-4.289, P < 0.001]. The addition of TyG index to a baseline risk model had an incremental effect on the predictive value for adverse prognosis [AUC: baseline risk model, 0.800 vs. baseline risk model + TyG index, 0.856, P for comparison < 0.001; category-free net reclassification improvement (NRI) 0.346, P < 0.001; integrated discrimination improvement (IDI) 0.087, P < 0.001]. Conclusions: Increased TyG index is a significant predictor of adverse prognosis in patients with T2DM and NSTE-ACS undergoing PCI. Further studies need to be performed to determine whether interventions for TyG index have a positive impact on improving clinical prognosis.

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Aim: The triglyceride-glucose index (TyG index) is proposed as a surrogate parameter for insulin resistance (IR) and, when elevated, is related to increased cardiovascular risks. Whether the TyG index is of great value in predicting adverse prognosis for individuals diagnosed with non-ST-segment elevation acute coronary syndrome (NSTE-ACS), who received elective percutaneous coronary intervention (PCI), and without recognized diabetes remains unclear. Methods: Overall, 1,510 subjects diagnosed with NSTE-ACS, who received elective PCI, and without recognized diabetes were enrolled in the current study. All participants received a routine follow-up after discharge. The TyG index was obtained from the following equation: napierian logarithmic (ln) [fasting triglyceride (TG, mg/dL)×fasting blood glucose (FBG, mg/dL)/2]. Adverse cardiovascular events included all-cause death, nonfatal myocardial infarction (MI), nonfatal ischemic stroke, and ischemia-driven revascularization, composite of which was defined as the primary endpoint. Results: Overall, 316 (20.9%) endpoint events were documented during a 48-month follow-up. Despite adjusting for confounding variates, the TyG index remains to be a significant risk predictor for the primary endpoint, with a hazard ratio (HR) [95% confidence interval (CI)] of 2.433 (1.853-3.196) ( P ＜0.001). A significant enhancement on the predictive performance for the primary endpoint emerged when adding the TyG index into a baseline model [area under the receiver-operating characteristic (ROC) curve (AUC), 0.835 for baseline model vs. 0.853 for baseline model＋TyG index, P ＜0.001; net reclassification improvement (NRI), 0.194, P ＜0.001; integrated discrimination improvement (IDI), 0.023, P =0.007]. Conclusions: The TyG index is an independent risk predictor for adverse cardiovascular events in nondiabetic subjects diagnosed with NSTE-ACS and who received elective PCI. Further prospective studies are needed to verify these findings.

Landslides cause a considerable amount of damage around the world every year. Landslide susceptibility assessments are useful for the mitigation of the associated potential risks to local economic development, land use planning, and decision makers. The main aim of this study was to present a novel hybrid approach of bagging (B)-based kernel logistic regression (KLR), named the BKLR model, for spatial prediction of landslides in the Shangnan County, China. We first selected 15 conditioning factors for landslide susceptibility modeling. Then, the prediction capability of all conditioning factors was evaluated using the least square support vector machine method. Model validation and comparison were performed based on the area under the receiver operating characteristic curve and several statistical-based indexes, including positive predictive rate, negative predictive rate, sensitivity, specificity, kappa index, and root mean square error. Results indicated that the BKLR ensemble model outperformed and outclassed the KLR and the benchmark support vector machine model. Our findings overall confirmed that a combination of the meta model with a decision tree classifier based on a functional algorithm can decrease the over-fitting and variance problems of data, which could enhance the prediction power of the landslide model. The resultant susceptibility maps could be useful for hazard mitigation in the study area and other similar landslide-prone areas.

An efficient and convenient copper-catalyzed method has been developed to achieve direct ortho-C-H/N-H annulation to synthesize phenanthridinones with arynes. This method highlights an emerging strategy to transform inert C-H bonds into versatile functional groups in organic synthesis and provides a new way to synthesize phenanthridinone alkaloids efficiently.

Composite structures are widely used due to their superior properties, such as low density, high strength, and high stiffness-to-weight ratio (Mallick, 1993, Fiber-Reinforced Composites: Materials, Manufacturing, and Design, Marcel Dekker, New York). However, the lack of methodologies for variation modeling and analysis of composite part assembly has imposed a significant constraint on developing dimensional control for composite assembly processes. This paper develops a modeling method to predict assembly deviation for compliant composite parts in a single-station assembly process. The approach is discussed in two steps: considering the part manufacturing error (PME) only and considering both the PME and the fixture position error (FPE). Finite element method (FEM) and homogenous coordinate transformation are used to reveal the impact of the PME and the FPE. The validity of the method is verified with two case studies on assembly deviation prediction of two composite laminated plates considering the PME only and both the PME and the FPE, respectively. The proposed method provides the basis for assembly deviation prediction in the multistation composite assembly.

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An efficient and environmentally benign Cu-mediated method was developed for direct cascade C-H/N-H annulation to construct polyheterocyclic indoloquinoline scaffolds. This method highlights an emerging strategy for transforming inert C-H bonds into versatile functional groups in organic synthesis and provides a new versatile approach for the efficient synthesis of indolo[3,2-c] and [2,3-c]quinoline alkaloids.