Additionally, vulnerable plaques were decreased and collagen fiber contents were observed to increase after miR-335-5p overexpression and Notch signaling inhibition.

Overexpression of miR-335-5p inhibited innate immune response of macrophage, reduced atherosclerotic vulnerable plaque formation, and promoted revascularization in ACS mice targeting JAG1 through Notch signaling.

Overexpression of miR-335-5p inhibited innate immune response of macrophage, reduced atherosclerotic vulnerable plaque formation, and promoted revascularization in ACS mice targeting JAG1 through Notch signaling.

Information on steroids derived from the adrenal glands, gonads, or fetoplacental unit is minimal in newborn foals.

To measure androgen concentrations in serum and determine their association with disease severity and outcome in hospitalized foals.

Hospitalized (n = 145) and healthy (n = 80) foals.

Prospective, multicenter, cross-sectional study. read more Foals of ≤3 days of age from 3 hospitals and horse farms were classified as healthy and hospitalized (septic, sick nonseptic, neonatal maladjustment syndrome [NMS]) based on physical exam, medical history, and laboratory findings. Serum androgen and plasma ACTH concentrations were measured with immunoassays. Data were analyzed by nonparametric methods and univariate analysis.

Serum dehydroepiandrosterone (DHEA), androstenedione, testosterone, and dihydrotestosterone (DHT) concentrations were higher upon admission in hospitalized foals (P <  .05), were associated with nonsurvival, decreased to 4.9-10.8%, 5.7-31%, and 30.8-62.8% admission values in healthyd play a role in or reflect a response to disorders such as sepsis or NMS in newborn foals.The indispensability of visual working memory (VWM) in human daily life suggests its importance in higher cognitive functions and neurological diseases. However, despite the extensive research efforts, most findings on the neural basis of VWM are limited to a unimodal context (either structure or function) and have low generalization. To address the above issues, this study proposed the usage of multimodal neuroimaging in combination with machine learning to reveal the neural mechanism of VWM across a large cohort (N = 547). Specifically, multimodal magnetic resonance imaging features extracted from voxel-wise amplitude of low-frequency fluctuations, gray matter volume, and fractional anisotropy were used to build an individual VWM capacity prediction model through a machine learning pipeline, including the steps of feature selection, relevance vector regression, cross-validation, and model fusion. The resulting model exhibited promising predictive performance on VWM (r = .402, p less then  .001), and identified features within the subcortical-cerebellum network, default mode network, motor network, corpus callosum, anterior corona radiata, and external capsule as significant predictors. The main results were then compared with those obtained on emotional regulation and fluid intelligence using the same pipeline, confirming the specificity of our findings. Moreover, the main results maintained well under different cross-validation regimes and preprocess strategies. These findings, while providing richer evidence for the importance of multimodality in understanding cognitive functions, offer a solid and general foundation for comprehensively understanding the VWM process from the top down.

Objectives Human biologists are increasingly interested in measuring and comparing physical activities in different societies. Sedentary behavior, which refers to time spent sitting or lying down while awake, is a large component of daily 24 hours movement patterns in humans and has been linked to poor health outcomes such as risk of all-cause and cardiovascular mortality, independently of physical activity. As such, it is important for researchers, with the aim of measuring human movement patterns, to most effectively use resources available to them to capture sedentary behavior.

This toolkit outlines objective (device-based) and subjective (self-report) methods for measuring sedentary behavior in free-living contexts, the benefits and drawbacks to each, as well as novel options for combined use to maximize scientific rigor. Throughout this toolkit, emphasis is placed on considerations for the use of these methods in various field conditions and in varying cultural contexts.

Objective measures such as inclinometers are the gold-standard for measuring total sedentary time but they typically cannot capture contextual information or determine which specific behaviors are taking place. Subjective measures such as questionnaires and 24 hours-recall methods can provide measurements of time spent in specific sedentary behaviors but are subject to measurement error and response bias.

We recommend that researchers use the method(s) that suit the research question; inclinometers are recommended for the measurement of total sedentary time, while self-report methods are recommended for measuring time spent in particular contexts of sedentary behavior.

We recommend that researchers use the method(s) that suit the research question; inclinometers are recommended for the measurement of total sedentary time, while self-report methods are recommended for measuring time spent in particular contexts of sedentary behavior.The acute rise in interstitial K+ that accompanies neural activity couples the energy demand of neurons to the metabolism of astrocytes. The effects of elevated K+ on astrocytes include activation of aerobic glycolysis, inhibition of mitochondrial respiration and the release of lactate. Using a genetically encoded FRET glucose sensor and a novel protocol based on 3-O-methylglucose trans-acceleration and numerical simulation of glucose dynamics, we report that extracellular K+ is also a potent and reversible modulator of the astrocytic glucose transporter GLUT1. In cultured mouse astrocytes, the stimulatory effect developed within seconds, engaged both the influx and efflux modes of the transporter, and was detected even at 1 mM incremental K+ . The modulation of GLUT1 explains how astrocytes are able to maintain their glucose pool in the face of strong glycolysis stimulation. We propose that the stimulation of GLUT1 by K+ supports the production of lactate by astrocytes and the timely delivery of glucose to active neurons.