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Response of nonlocal thermoelastic nanobeams supported by Pasternak foundations to the effect of generalized fractional theory with three-phase lags
Transformer based spatially resolved prediction of mechanical properties in wire arc additive manufacturing
Environmental risk assessment based on multiscale spatial recurrent neural network algorithm for IoT agriculture area
Experimental and CFD analysis of flow impediments and encrustation in ureteral stents using in vitro urinary tract model
MDDC: An R and Python package for adverse event identification in pharmacovigilance data
Effect of breast milk olfactory experience on physiological indicators in very low birth weight infants: a randomized clinical trial
Triglyceride-glycated hemoglobin index as a superior predictor of type 2 diabetes risk in a large-scale retrospective cohort study
Abstract Early detection of individuals at elevated risk for type 2 diabetes (T2D) is critical for effective prevention strategies. We developed a novel metabolic marker, the triglyceride-glycated hemoglobin index (TyH-i), which integrates lipid and glycemic parameters to improve T2D risk prediction. This study sought to evaluate the relationship between TyH-i and T2D risk and to examine its predictive performance with the triglyceride-glucose index (TyG-i). A large-scale retrospective cohort study was conducted using data from 15,464 Japanese adults without T2D at baseline. The TyH-i was calculated as Ln[glycated hemoglobin index (%)×triglycerides (mg/dL)/2], and its association with incident T2D was assessed using Cox proportional hazards models and smooth curve fitting and cubic spline functions. The predictive performance of the TyH-i was compared with the TyG-i using receiver operating characteristic curves. Over a median follow-up of 5.39 years, 373 participants developed T2D. After accounting for confounders, the TyH-i was significantly associated with T2D risk (HR: 1.55, 95% CI: 1.22–1.97, P = 0.00031). Additionally, a J-shaped relationship between the TyH-i and incident T2D was identified. A significant positive correlation was identified between TyH-i and T2D only when TyH-i levels were above 4.92 (HR: 1.73, 95%CI: 1.35–2.23, P < 0.0001). Furthermore, TyH-i and TyG-i possess comparable discriminatory ability in predicting incident T2D (AUC: 0.751 vs. 0.750, P = 0.8873). Moreover, TyH-i yielded lower Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) values than TyG-i (AIC: 3211.60 vs. 3211.91; BIC: 3226.89 vs. 3227.20), indicating a more parsimonious model with better overall model fit. The TyH-i is a novel and effective predictor of T2D risk, exhibiting a non-linear relationship with T2D. Furthermore, TyH-i and TyG-i exhibit comparable discriminatory abilities in predicting incident T2D. These results highlight the potential of TyH-i as a valuable instrument for T2D risk stratification, particularly in individuals with elevated TyH-i levels.
Spider predatory aggressiveness exhibits diverse personality and plasticity associations and complex neurophysiological mechanisms
The ER-associated degradation adaptor SEL1L is dispensable for ER homeostasis and the differentiation of spermatogenic cells
Clinical and functional outcomes of masquelet technique for treating Fracture-related Infections(FRIs) in shoulder girdle
The audiological phenotype of patients with a variant in MYH9 and MYH14 genes
A temporal and spatial analysis of incidence and mortality of lip, oral cavity, and pharyngeal cancer in a Northeastern Brazilian state
Nutational resonance modes in antiferromagnetic materials
Abstract The Landau–Lifshitz–Gilbert (LLG) equation is well-established to describe the spin dynamics of magnetic materials. This first-order differential equation is based on the assumption that the spin angular momenta and corresponding magnetic moments are always parallel. While this assumption is largely unproblematic, both theoretical considerations and experimental results have indicated that the two may become separated on ultrafast timescales, giving rise to inertial dynamics along with a modified spin wave dispersion. Here, we apply linear spin wave theory to the inertial LLG equation to compute the eigenmodes of the altermagnetic materials SmErFeO3 and $$\alpha$$ -Fe2O3. We find the largest influence of nutation on the magnetic resonances in the case of hematite, which exhibits both a sizeable shift of the resonance frequencies as compared to the inertia-free case and additional nutational resonances that are in a similar order of magnitude to the materials’ higher-frequency precessional exchange modes. While the realistic magnitude of the inertial parameter remains an open question, we hope that our quantitative analysis provides the starting point for further experimental investigations.