Search

Background: Cofilin is a member of the actin depolymerizing factor (ADF)/cofilin family, which regulates actin dynamics. Increasing evidence suggests that mitochondrial translocation of cofilin appears necessary for the regulation of apoptosis. Results: We report that allyl isothiocyanate (AITC) potently induces mitochondria injury and apoptosis. These events were accompanied by a loss of polymerized filamentous actin (F-actin) and increase in unpolymerized globular actin (G-actin). AITC also induces dephosphorylation of cofilin through activation of PP1 and PP2A. Only dephosphorylated cofilin binds to G-actin and translocates to mitochondria during AITC-mediated apoptosis. Mechanistic study revealed that interruption of ROCK1/PTEN/PI3K signaling pathway plays a critical role in AITC-mediated dephosphorylation and mitochondrial translocation of cofilin and apoptosis. Our in vivo study also showed that AITC-mediated inhibition of tumor growth of mouse leukemia xenograft model is in association with dephosphorylation of cofilin. Conclusions: These findings support a model in which induction of apoptosis by AITC stems primarily from activation of ROCK1 and PTEN, and inactivation of PI3K, leading in turn to activation of PP1 and PP2A, resulting in dephosphorylation of cofilin, which binds to G-actin and translocates to mitochondria, culminating in the dysfunction of mitochondria, release of cytochrome c and apoptosis. [ABSTRACT FROM AUTHOR]

Our aim was to develop a machine learning-based predictor for early mortality and severe intraventricular hemorrhage (IVH) in very-low birth weight (VLBW) preterm infants in Taiwan. We collected retrospective data from VLBW infants, dividing them into two cohorts: one for model development and internal validation (Cohort 1, 2016–2021), and another for external validation (Cohort 2, 2022). Primary outcomes included early mortality, severe IVH, and early poor outcomes (a combination of both). Data preprocessing involved 23 variables, with the top four predictors identified as gestational age, birth body weight, 5-min Apgar score, and endotracheal tube ventilation. Six machine learning algorithms were employed. Among 7471 infants analyzed, the selected predictors consistently performed well across all outcomes. Logistic regression and neural network models showed the highest predictive performance (AUC 0.81–0.90 in both internal and external validation) and were well-calibrated, confirmed by calibration plots and the lowest two mean Brier scores (0.0685 and 0.0691). We developed a robust machine learning-based outcome predictor using only four accessible variables, offering valuable prognostic information for parents and aiding healthcare providers in decision-making. [ABSTRACT FROM AUTHOR]

The purpose of this study was to explore the effects of virtual reality (VR) application on creative performance and immersion, evaluated through electroencephalography brain wave data to achieve accurate and robust results. In this study, 72 middle school teachers were recruited as participants, and a non‐randomized control‐group pre‐test–post‐test design was employed. The experimental group received VR‐based design instruction, and the control group received lecture‐based design training. Our results revealed that VR significantly affects immersion, especially with regard to attention. Additionally, VR had a positive effect on the feasibility of the creative process, although its effects on variety and novelty were inconclusive. VR was significantly correlated with theta, beta, and gamma brain wave activity. VR also increased attention‐related and meditation‐related brain wave activity and desynchronized alpha waves. Practitioner notes: What is already known about this topic VR is used in many areas.VR in education is getting more important day after day. What this paper adds VR significantly affects immersion, especially with regard to attention.VR had a positive effect on the feasibility of the creative process, although its effects on variety and novelty were inconclusive.VR was significantly correlated with theta, beta, and gamma brain wave activity.VR also increased attention‐related and meditation‐related brain wave activity and desynchronized alpha waves. Implications for practice and/or policy User lack of familiarity with VR may also have influenced the results; more VR learning materials should be provided for learners.In addition to using a larger sample, future studies should focus on creative novelty when developing VR content to improve creative processes and outcomes.Familiarizing learners with the use of VR could effectively reduce the cognitive load, as well as contribute to the stimulation of creative brain waves. [ABSTRACT FROM AUTHOR]

Bronchopulmonary dysplasia (BPD) has been a critical morbidity in preterm infants. To improve our definition and prediction of BPD is challenging yet indispensable. We aimed to apply machine learning (ML) to investigate effective models by using the recently-proposed and data-driven definition to predict late respiratory support modalities at 36 weeks' post menstrual age (PMA). We collected data on very-low-birth-weight infants born between 2016 and 2019 from the Taiwan Neonatal Network database. Twenty-four attributes associated with their early life and seven ML algorithms were used in our analysis. The target outcomes were overall mortality, death before 36 weeks' PMA, and severity of BPD under the new definition, which served as a proxy for respiratory support modalities. Of the 4103 infants initially considered, 3200 were deemed eligible. The logistic regression algorithm yielded the highest area under the receiver operating characteristic curve (AUROC). After attribute selection, the AUROC of the simplified models remain favorable (e.g., 0.801 when predicting no BPD, 0.850 when predicting grade 3 BPD or death before 36 weeks' PMA, and 0.881 when predicting overall mortality). By using ML, we developed models to predict late respiratory support. Estimators were developed for clinical application after being simplified through attribute selection. [ABSTRACT FROM AUTHOR]

Both evaluating students' design works and also understanding their cognition in the industrial design process are equally important for students' learning. This study used the design activities and design competencies required by the industrial design process as items to develop an "Industrial Design Self-Efficacy and Anxiety Scale" that can be used to help teachers better understand students' learning from a psychological perspective. In this study, 285 industrial-design college students were recruited and item analysis, exploratory factor analysis, confirmatory factor analysis, and reliability analysis were used to construct a scale with good reliability and validity. Analyses of the background variables revealed that (1) the self-efficacy of male students in model prototyping was significantly better than that of female students; (2) the level of anxiety regarding model prototyping was significantly higher among senior students than among freshmen students; (3) students scoring higher for self-evaluation also scored higher for self-efficacy in problem solving, information collecting, and model prototyping; and (4) students with abundant maker-space experience scored significantly higher for self-efficacy in problem solving, information collecting, and model prototyping than those with less experience. Finally, the practical use of the proposed scale is discussed. [ABSTRACT FROM AUTHOR]

Introduction: This study aimed to explore the relationship between the trajectories of body weight (BW) z -scores at birth, discharge, and 6 months corrected age (CA) and neurodevelopmental outcomes at 24 months CA., Methods: Conducted as a population-based retrospective cohort study across 21 hospitals in Taiwan, we recruited 3,334 very-low-birth-weight (VLBW) infants born between 2012 and 2017 at 23-32 weeks of gestation. Neurodevelopmental outcomes were assessed at 24 months CA. Instances of neurodevelopmental impairment (NDI) were defined by the presence of at least one of the following criteria: cerebral palsy, severe hearing loss, profound vision impairment, or cognitive impairment. Group-based trajectory modeling was employed to identify distinct BW z-score trajectory groups. Multivariable logistic regression was used to assess the associations between these trajectories, postnatal comorbidity, and neurodevelopmental impairments., Results: The analysis identified three distinct trajectory groups: high-climbing, mid-declining, and low-declining. Significant associations were found between neurodevelopmental impairments and both cystic periventricular leukomalacia (cPVL) [with an adjusted odds ratio (aOR) of 3.59; p  < 0.001] and belonging to the low-declining group (aOR: 2.59; p  < 0.001)., Discussion: The study demonstrated that a low-declining pattern in body weight trajectory from birth to 6 months CA, along with cPVL, was associated with neurodevelopmental impairments at 24 months CA. These findings highlight the importance of early weight trajectory and specific health conditions in predicting later neurodevelopmental outcomes in VLBW infants., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 Wang, Chen, Su, Yang, Chu, Lin, Chang, Lin, Lin, Lin and Taiwan Premature Infant Follow-up Network.)

Health education is the teaching by healthcare professionals of healthcare-related knowledge and skills to students in order that these students learn to help patients self-manage their disease and maintain health. This article introduces a new strategy in health education known as the learning portfolio and presents the theoretical basis and function of the learning portfolio and the current application of this approach in academic and health education. The learning portfolio is a learner-centric approach that collects evidence related to an individual's learning process systematically. This approach helps educators understand learner needs and conditions, while allowing the learner to observe his / her learning process in a manner that promotes self-reflection, continual inspection, and behavioral modification throughout the learning process. The results enhance the motivation of learners and strengthen their care confidence in accomplishing learning tasks.

Synthesis of crystalline barium stronium titanate (Ba(0.6)Sr(0.4)TiO(3)) nanoparticles and subsequent formation of thin films have been carried out. The crystalline products were confirmed by X-ray diffractometry. Uniform Ba(0.6)Sr(0.4)TiO(3) thin films were formed by using electrophoretic deposition method (EPD) under a 0.3 to 5 V dc bias for 10 min to 1 h. Ba(0.6)Sr(0.4)TiO(3) nanoparticles having an average crystallite size of 20 to 50 nm, and Ba(0.6)Sr(0.4)TiO(3) thin films with thickness of 150 nm to 4 mum were obtained. A scanning electron microscope (SEM) and transmission electron microscope (TEM) were used to characterize the morphologies of nanoparticles and thin films. The results show that the EPD process route is a rapid, cost-effective alternative for forming Ba(0.6)Sr(0.4)TiO(3) thin films.