Effects of Auto-Titrating Mandibular Advancement Device on Autonomic Nervous System in Obstructive Sleep Apnea.

One prior study revealed that a newly developed auto-titrating mandibular advancement device (AMAD) could potentially enhance polysomnographic outcomes in individuals with obstructive sleep apnea (OSA). However, evidence regarding its impact on autonomic nervous system dysregulation in OSA remains limited. In this study, we aimed to compare the effects of conventional mandibular advancement devices (MADs) and AMDA on autonomic function.

A Longitudinal Study Investigating Whether Chronic Rhinosinusitis Influences the Subsequent Risk of Developing Dementia.

Numerous studies have explored the association between chronic rhinosinusitis (CRS) and cognitive decline. However, whether CRS is an independent risk factor for the development of dementia remains unclear. Thus, this retrospective cohort study sought to examine the potential association between CRS and increased incidence and risk of dementia by utilizing a representative population-based cohort dataset.

Knockdown of E2F4 suppresses the growth of ovarian cancer cells through the cell cycle pathway.

Ovarian cancer remains one of the major causes of death from gynecologic cancer in developed countries. The E2F family has been shown to have a central role in the control of cell proliferation, differentiation, and cell cycle progression in various types of cancer. Despite advances in cancer research, the carcinogenic role of E2F transcription factor 4 (E2F4) in ovarian cancer remains unclear.

Two-Stage Latent Dynamics Modeling and Filtering for Characterizing Individual Walking and Running Patterns with Smartphone Sensors.

Recently, data from built-in sensors in smartphones have been readily available, and analyzing data for various types of health information from smartphone users has become a popular health care application area. Among relevant issues in the area, one of the most prominent topics is analyzing the characteristics of human movements. In this paper, we focus on characterizing the human movements of walking and running based on a novel machine learning approach.

LSTM-Guided Coaching Assistant for Table Tennis Practice.

Recently, wearable devices have become a prominent health care application domain by incorporating a growing number of sensors and adopting smart machine learning technologies. One closely related topic is the strategy of combining the wearable device technology with skill assessment, which can be used in wearable device apps for coaching and/or personal training. Particularly pertinent to skill assessment based on high-dimensional time series data from wearable sensors is classifying whether a player is an expert or a beginner, which skills the player is exercising, and extracting some low-dimensional representations useful for coaching.

Extraction of natural colorant from purple sweet potato and dyeing of fabrics with silver nanoparticles for augmented antibacterial activity against skin pathogens.

The main objective of this study was to extract natural colorant from purple sweet potato powder (PSPP) via a water bath and ultrasound water bath using acidified ethanol (A. EtOH) as the extraction solvent. When optimizing the colorant extraction conditions of the solvents, acidified ethanol with ultrasound yielded a high extraction capacity and color intensity at pH2, temperature of 80°C, 20mL of A.

Comparison of Computer Vision and Photogrammetric Approaches for Epipolar Resampling of Image Sequence.

Epipolar resampling is the procedure of eliminating vertical disparity between stereo images. Due to its importance, many methods have been developed in the computer vision and photogrammetry field. However, we argue that epipolar resampling of image sequences, instead of a single pair, has not been studied thoroughly.

Large Protein Dynamics Described by Hierarchical-Component Mode Synthesis.

Protein dynamics has played a pivotal role in understanding the biological function of protein. For investigation of such dynamics, normal-mode analysis (NMA) has been broadly employed with atomistic model and/or coarse-grained models such as elastic network model (ENM). For large protein complexes, NMA with even ENM encounters the expensive computational process such as diagonalization of Hessian (stiffness) matrix.