Non-linear relationship between sleep duration and blood pressure in children with short stature

BackgroundEvidence regarding the relationship between sleep duration and blood pressure is controversial. Therefore, the aim of this study was to investigate the relationship between sleep duration and blood pressure in children with short stature.MethodsA total of 1,085 participants with short stature were enrolled from the Affiliated Hospital of Jining Medical University in China. The variables involved in this study included sleep duration, anthropometric indicators and biochemical parameters. Sleep duration was evaluated in a face-to-face interview.ResultsThe average age of the 1,085 selected participants was 10.2 ± 3.5 years old, and approximately 763 (70.32%) of them were male. The results of adjusted linear regression showed that sleep duration was negatively associated with systolic blood pressure z scores (SBP-Z) and diastolic blood pressure z scores (DBP-Z) after adjusting for confounders (β −0.07, 95% CI −0.13, −0.01 P = 0.038; β −0.05, 95% CI −0.10, −0.01 P = 0.035, respectively). A nonlinear relationship was detected between sleep duration and blood pressure, including SBP-Z, DBP-Z and mean arterial pressure z scores (MAP-Z). The inflection point of the nonlinear relationship between sleep duration and SBP-Z is 10 h, and the inflection point of DBP-Z and MAP-Z is 8 h.ConclusionThis study revealed a nonlinear relationship between sleep duration and blood pressure in children with short stature. The findings suggest that the optimal sleep duration in children with short stature was 8–10 h, and sleep durations either too short or too long were associated with increased blood pressure levels

Distinct Topological Surface States on the Two Terminations of MnBi4_4Te7_7

The recent discovered intrinsic magnetic topological insulator MnBi2Te4 have been met with unusual success in hosting emergent phenomena such as the quantum anomalous Hall effect and the axion insulator states. However, the surface-bulk correspondence of the Mn-Bi-Te family, composed by the superlattice-like MnBi2Te4/(Bi2Te3)n (n = 0, 1, 2, 3 ...) layered structure, remains intriguing but elusive. Here, by using scanning tunneling microscopy (STM) and angle-resolved photoemission spectroscopy (ARPES) techniques, we unambiguously assign the two distinct surface states of MnBi4Te7 (n = 1) to the quintuple-layer (QL) Bi2Te3 termination and the septuple-layer (SL) MnBi2Te4 termination, respectively. A comparison of the experimental observations with theoretical calculations reveals the diverging topological behaviors, especially the hybridization effect between magnetic and nonmagnetic layers, on the two terminations: a gap on the QL termination originating from the topological surface states of the QL hybridizing with the bands of the beneath SL, and a gapless Dirac-cone band structure on the SL termination with time-reversal symmetry. The quasi-particle interference patterns further confirm the topological nature of the surface states for both terminations, continuing far above the Fermi energy. The QL termination carries a spin-helical Dirac state with hexagonal warping, while at the SL termination, a strongly canted helical state from the surface lies between a pair of Rashba-split states from its neighboring layer. Our work elucidates an unprecedented hybridization effect between the building blocks of the topological surface states, and also reveals the termination-dependent time-reversal symmetry breaking in a magnetic topological insulator, rendering an ideal platform to realize the half-integer quantum Hall effect and relevant quantum phenomena.Comment: 22 Pages, 4 Figure

An Adaptive Modeling Framework for Bearing Failure Prediction

Rolling element bearings are a common component in rotating equipment, a class of machines that is essential in a wide range of industries. Detecting and predicting bearing failures is then vital for reducing maintenance and production costs due to unplanned downtime. In previous literature, significant efforts have been devoted to building data-driven health models from historical bearing data. However, a common limitation is that these methods are typically tailored to specific failure instances and have limited ability to model bearing failures between repairs in the same system. In this paper, we propose a multi-state health model to predict bearing failures before they occur. The model employs a regression-based method to detect health state transition points and applies an exponential random coefficient model with a Bayesian updating process to estimate time-to-failure distributions. A model training framework is also introduced to make our proposed model applicable to more bearing instances in the same system setting. The proposed method has been tested on a publicly available bearing prognostics dataset. Case study results show that the proposed method provides accurate failure predictions across several system failures, and that the training approach can significantly reduce the time necessary to generate an effective, generalized model

Association between serum uric acid and triglyceride-glucose index in children and adolescents with short stature

Abstract The aim of this study was to explore the relationship between serum uric acid (SUA) and the triglyceride-glucose (TyG) index, which is a more effective indicator of insulin resistance. The study participants included 1700 children and adolescents with short stature who were recruited at the Affiliated Hospital of Jining Medical University in China between March 2013 and April 2021. A positive association between SUA levels and the TyG index was detected by univariate analysis (p < 0.001). Furthermore, a nonlinear relationship was detected between SUA and the TyG index, whose point was 6.55 mg/dL. There was a positive association between SUA and the TyG index when the SUA level was greater than 6.55 mg/dL (β 0.17, 95% CI: 0.07, 0.27; P < 0.001). However, we did not observe a significant relationship between SUA and the TyG index when the SUA level was less than 6.55 mg/dL (β 0.02, 95% CI: − 0.01, 0.05; P = 0.091). In addition, a stratified analysis was performed to appraise changes in this relationship for different sexes. The relationship between SUA and the TyG index in males and females is consistent with that in the general population, showing a nonlinear relationship. However, the inflection points of SUA level were significantly higher in males than in females, and the inflection points were approximately 6.72 and 5.88 mg/dL, respectively. This study revealed a nonlinear relationship between SUA and the TyG index in children with short stature. The nonlinear relationship remained in gender stratification analysis, but the inflection point of SUA level was higher in men. Further studies are needed to establish a causal relationship between SUA levels and the TyG index in children with short stature