Generative adversarial network-based deep learning approach in classification of retinal conditions with optical coherence tomography images.

Purpose: To determine whether a deep learning approach using generative adversarial networks (GANs) is beneficial for the classification of retinal conditions with Optical coherence tomography (OCT) images.

Methods: Our study utilized 84,452 retinal OCT images obtained from a publicly available dataset (Kermany Dataset). Employing GAN, synthetic OCT images are produced to balance classes of retinal disorders.

Ma's bamboo-based medicinal moxibustion therapy of low back pain in lumbar disc herniation: study protocol for a randomized controlled trial.

Background: Lumbar disc herniation (LDH) is a common and frequently occurring disease in clinics. Low back pain and sciatica are the presenting symptoms of LDH. To some extent, it can be considered that measures with the capability to improve low back pain or sciatica have the potential to treat LDH.

Using machine learning to determine the correlation between physiological and environmental parameters and the induction of acute mountain sickness.

Background: Recent studies on acute mountain sickness (AMS) have used fixed-location and fixed-time measurements of environmental and physiological variable to determine the influence of AMS-associated factors in the human body. This study aims to measure, in real time, environmental conditions and physiological variables of participants in high-altitude regions to develop an AMS risk evaluation model to forecast prospective development of AMS so its onset can be prevented.

Results: Thirty-two participants were recruited, namely 25 men and 7 women, and they hiked from Cuifeng Mountain Forest Park parking lot (altitude: 2300 m) to Wuling (altitude: 3275 m).

General deep learning model for detecting diabetic retinopathy.

Background: Doctors can detect symptoms of diabetic retinopathy (DR) early by using retinal ophthalmoscopy, and they can improve diagnostic efficiency with the assistance of deep learning to select treatments and support personnel workflow. Conventionally, most deep learning methods for DR diagnosis categorize retinal ophthalmoscopy images into training and validation data sets according to the 80/20 rule, and they use the synthetic minority oversampling technique (SMOTE) in data processing (e.g.

[Exploration on effect mechanism of Miao medicinal acupuncture therapy in treatment of knee osteoarthritis based on TRPV ion channel].

Objective: To observe the effect of Miao medicinal acupuncture therapy on transient receptor potential vanilloid (TRPV) channel in knee joint synovial tissue of the rabbits with knee osteoarthritis (KOA) model and to explore the mechanism of Miao medicinal acupuncture therapy in treatment of KOA.

Methods: Of 34 New Zealand male rabbits, 6 rabbits were selected randomly as the normal group. KOA model was established in the rest rabbits by injecting a mixture of papain and L-cysteine in right knee joints.

Lemnalol Modulates the Electrophysiological Characteristics and Calcium Homeostasis of Atrial Myocytes.

Sepsis, an inflammatory response to infection provoked by lipopolysaccharide (LPS), is associated with high mortality, as well as ischemic stroke and new-onset atrial arrhythmia. Severe bacterial infections causing sepsis always result in profound physiological changes, including fever, hypotension, arrhythmia, necrosis of tissue, systemic multi-organ dysfunction and finally death. LPS challenge-induced inflammatory responses during sepsis may increase the likelihood of the arrhythmogenesis.

Wireless Stimulus-on-Device Design for Novel P300 Hybrid Brain-Computer Interface Applications.

Improving the independent living ability of people who have suffered spinal cord injuries (SCIs) is essential for their quality of life. Brain-computer interfaces (BCIs) provide promising solutions for people with high-level SCIs. This paper proposes a novel and practical P300-based hybrid stimulus-on-device (SoD) BCI architecture for wireless networking applications.

Systematic node management mechanism using ZigBee-based real-time vital sign information monitoring system to manage large numbers of patients.

Background: Local hospitals must deal with large numbers of patients during mass casualty incidents, and the wireless sensor networks (WSNs) can help in these situations by monitoring vital signs. Conventional ZigBee nodes can obtain the ID of a device by assigning a unique 16-bit short address or by burning firmware into an IC. These methods tend to complicate node management and lack portability.

Excavatolide B Modulates the Electrophysiological Characteristics and Calcium Homeostasis of Atrial Myocytes.

Severe bacterial infections caused by sepsis always result in profound physiological changes, including fever, hypotension, arrhythmia, necrosis of tissue, systemic multi-organ dysfunction, and finally death. The lipopolysaccharide (LPS) provokes an inflammatory response under sepsis, which may increase propensity to arrhythmogenesis. Excavatolide B (EXCB) possesses potent anti-inflammatory effects.

Epigallocatechin-3-gallate modulates arrhythmogenic activity and calcium homeostasis of left atrium.

Background: Atrial fibrillation (AF) is the commonest sustained arrhythmia, and increases the risk of stroke, heart failure, and mortality. Calcium (Ca) overload and oxidative stress are thought to participate in the pathogenesis of AF. Epigallocatechin-3-gallate (EGCG) has an antioxidative effect and been shown to be beneficial in promoting cardiovascular health.