Histone variant H2BE controls activity-dependent gene expression and homeostatic scaling.

A cell's ability to respond and adapt to environmental stimuli relies in part on transcriptional programs controlled by histone proteins. Histones affect transcription through numerous mechanisms including through replacement with variant forms that carry out specific functions. We recently identified the first widely expressed H2B histone variant, H2BE and found that it promotes transcription and is critical for neuronal function and long-term memory.

Performance of a Novel Electronic Nose for the Detection of Volatile Organic Compounds Relating to Starvation or Human Decomposition Post-Mass Disaster.

There has been a recent increase in the frequency of mass disaster events. Following these events, the rapid location of victims is paramount. Currently, the most reliable search method is scent detection dogs, which use their sense of smell to locate victims accurately and efficiently.

Lactate Suppresses Growth of Esophageal Adenocarcinoma Patient-Derived Organoids through Alterations in Tumor NADH/NAD+ Redox State.

Barrett's esophagus (BE) is a common precancerous lesion that can progress to esophageal adenocarcinoma (EAC). There are significant alterations in the esophageal microbiome in the progression from healthy esophagus to BE to EAC, including an increased abundance of a variety of lactate-producing bacteria and an increase of lactate in the tumor microenvironment, as predicted by metabolic modeling. The role of bacterial lactate in EAC is unknown.

An automated system for polymer wear debris analysis in total disc arthroplasty using convolution neural network.

Polymer wear debris is one of the major concerns in total joint replacements due to wear-induced biological reactions which can lead to osteolysis and joint failure. The wear-induced biological reactions depend on the wear volume, shape and size of the wear debris and their volumetric concentration. The study of wear particles is crucial in analysing the failure modes of the total joint replacements to ensure improved designs and materials are introduced for the next generation of devices.

Visceral Adiposity Independently Predicts Time to Flare in Inflammatory Bowel Disease but Body Mass Index Does Not.

Background: Obesity is associated with progression of inflammatory bowel disease (IBD). Visceral adiposity may be a more meaningful measure of obesity compared with traditional measures such as body mass index (BMI). This study compared visceral adiposity vs BMI as predictors of time to IBD flare among patients with Crohn's disease and ulcerative colitis.

Spatiotemporal Compliance Control for a Wearable Lower Limb Rehabilitation Robot.

Compliance control is crucial for physical human-robot interaction, which can enhance the safety and comfort of robot-assisted rehabilitation. In this study, we designed a spatiotemporal compliance control strategy for a new self-designed wearable lower limb rehabilitation robot (WLLRR), allowing the users to regulate the spatiotemporal characteristics of their motion. The high-level trajectory planner consists of a trajectory generator, an interaction torque estimator, and a gait speed adaptive regulator, which can provide spatial and temporal compliance for the WLLRR.

The use of novel electronic nose technology to locate missing persons for criminal investigations.

The search for missing persons is a major challenge for investigations involving presumed deceased individuals. Currently, the most effective tool is the use of cadaver-detection dogs; however, they are limited by their cost, limited operation times, and lack of granular information reported to the handler. Thus, there is a need for discrete, real-time detection methods that provide searchers explicit information as to whether human-decomposition volatiles are present.

Human Mpox Virus Proctitis With Persistent Rectal Ulcers on Sigmoidoscopy.

The 2022 Mpox outbreak has caused public health concerns worldwide. Mpox infection often manifests as papular skin lesions; other systemic complications have also been reported. We present the case of a 35-year-old man with HIV who presented with rectal pain and hematochezia and was found to have severe ulceration and exudate on sigmoidoscopy consistent with Mpox proctitis.

Sleep Apnea Detection Using Multi-Error-Reduction Classification System with Multiple Bio-Signals.

Introduction: Obstructive sleep apnea (OSA) can cause serious health problems such as hypertension or cardiovascular disease. The manual detection of apnea is a time-consuming task, and automatic diagnosis is much more desirable. The contribution of this work is to detect OSA using a multi-error-reduction (MER) classification system with multi-domain features from bio-signals.

Inertial Sensor Estimation of Initial and Terminal Contact during In-Field Running.

Given the popularity of running-based sports and the rapid development of Micro-electromechanical systems (MEMS), portable wireless sensors can provide in-field monitoring and analysis of running gait parameters during exercise. This paper proposed an intelligent analysis system from wireless micro-Inertial Measurement Unit (IMU) data to estimate contact time (CT) and flight time (FT) during running based on gyroscope and accelerometer sensors in a single location (ankle). Furthermore, a pre-processing system that detected the running period was introduced to analyse and enhance CT and FT detection accuracy and reduce noise.

Matlab Open Source Code: Noise-Assisted Multivariate Empirical Mode Decomposition Based Causal Decomposition for Causality Inference of Bivariate Time Series.

Causality inference has arrested much attention in academic studies. Currently, multiple methods such as Granger causality, Convergent Cross Mapping (CCM), and Noise-assisted Multivariate Empirical Mode Decomposition (NA-MEMD) are introduced to solve the problem. Motivated by the researchers who uploaded the open-source code for causality inference, we hereby present the Matlab code of NA-MEMD Causal Decomposition to help users implement the algorithm in multiple scenarios.

Design of Electronic Nose Detection System for Apple Quality Grading Based on Computational Fluid Dynamics Simulation and K-Nearest Neighbor Support Vector Machine.

Apples are one of the most widely planted fruits in the world, with an extremely high annual production. Several issues should be addressed to avoid the damaging of samples during the quality grading process of apples (e.g.

Noise-assisted Multivariate Empirical Mode Decomposition based Causal Decomposition for Detecting Upper Limb Movement in EEG-EMG Hybrid Brain Computer Interface.

EEG-EMG based hybrid Brain Computer Interface (hBCI) utilizes the brain-muscle physiological system to interpret and identify motor behaviors, and transmit human intelligence to automated machines in AI applications such as neurorehabilitations and brain-like intelligence. The study introduces a hBCI method for motor behaviors, where multiple time series of the brain neuromuscular network are introduced to indicate brain-muscle causal interactions, and features are extracted based on Relative Causal Strengths (RCSs) derived by Noise-assisted Multivariate Empirical Mode Decomposition (NA-MEMD) based Causal Decomposition. The complex process in brain neuromuscular interactions is specifically investigated towards a monitoring task of upper limb movement, whose 63-channel EEGs and 2-channel EMGs are composed of data inputs.

Nonparametric Modelling Based Model Predictive Control for Human Heart Rate Regulation during Treadmill Exercise.

This paper applies a kernel-based nonparametric modelling method to estimate the heart rate response during treadmill exercise and proposes a model predictive control (MPC) method to perform heart rate control for an automated treadmill system. This kernel-based method introduces a kernel regularisation term, which brings prior information to the model estimation phase. By adding this prior information, the experimental protocol can be significantly simplified and only a small amount of model training experiments are needed.

Relationship Between Body Composition and Death in Patients with COVID-19 Differs Based on the Presence of Gastrointestinal Symptoms.

Background: Patients with SARS-CoV-2 who present with gastrointestinal symptoms have a milder clinical course than those who do not. Risk factors for severe COVID-19 disease include increased adiposity and sarcopenia.

Aims: To determine whether body composition risk factors are associated with worse outcomes among patients with gastrointestinal symptoms.

A Hybrid Arm-Hand Rehabilitation Robot With EMG-Based Admittance Controller.

Reach-and-grasp is one of the most fundamental activities in daily life, while few rehabilitation robots provide integrated and active training of the arm and hand for patients after stroke to improve their mobility. In this study, a novel hybrid arm-hand rehabilitation robot (HAHRR) was built for the reach-and-grasp task. This hybrid structure consisted of a cable-driven module for three-dimensional arm motion and an exoskeleton for hand motion, which enabled assistance of the arm and hand simultaneously.

The effect of consecutive ambient air pollution on the hospital admission from chronic obstructive pulmonary disease in the Chengdu region, China.

Hospitalisation risks for chronic obstructive pulmonary disease (COPD) have been attributed to ambient air pollution worldwide. However, a rise in COPD hospitalisations may indicate a considerable increase in fatality rate in public health. The current study focuses on the association between consecutive ambient air pollution (CAAP) and COPD hospitalisation to offer predictable early guidance towards estimates of COPD hospital admissions in the event of consecutive exposure to air pollution.

Human Motion Intent Description Based on Bumpless Switching Mechanism for Rehabilitation Robot.

This paper aims to improve the performance of an electromyography (EMG) decoder based on a switching mechanism in controlling a rehabilitation robot for assisting human-robot cooperation arm movements. For a complex arm movement, the major difficulty of the EMG decoder modeling is to decode EMG signals with high accuracy in real-time. Our recent study presented a switching mechanism for carving up a complex task into simple subtasks and trained different submodels with low nonlinearity.

Noise-assisted multivariate empirical mode decomposition based causal decomposition for brain-physiological network in bivariate and multiscale time series.

Noise-assisted multivariate empirical mode decomposition (NA-MEMD) based causal decomposition depicts a cause and effect relationship that is not based on the term of prediction, but rather on the phase dependence of time series. Here, we present the NA-MEMD based causal decomposition approach according to the covariation and power views traced to Hume and Kant:cause-effect interaction is first acquired, and the presence of a candidate cause and of the effect is then computed from the sensory input somehow.Based on the definition of NA-MEMD based causal decomposition, we show such causal relation is a phase relation where the candidate causes are not merely followed by effects, but rather produce effects.

Ultrasound volume projection image quality selection by ranking from convolutional RankNet.

Periodic inspection and assessment are important for scoliosis patients. 3D ultrasound imaging has become an important means of scoliosis assessment as it is a real-time, cost-effective and radiation-free imaging technique. With the generation of a 3D ultrasound volume projection spine image using our Scolioscan system, a series of 2D coronal ultrasound images are produced at different depths with different qualities.

One-Shot Neural Architecture Search: Maximising Diversity to Overcome Catastrophic Forgetting.

One-shot neural architecture search (NAS) has recently become mainstream in the NAS community because it significantly improves computational efficiency through weight sharing. However, the supernet training paradigm in one-shot NAS introduces catastrophic forgetting, where each step of the training can deteriorate the performance of other architectures that contain partially-shared weights with current architecture. To overcome this problem of catastrophic forgetting, we formulate supernet training for one-shot NAS as a constrained continual learning optimization problem such that learning the current architecture does not degrade the validation accuracy of previous architectures.

Association Between Consecutive Ambient Air Pollution and Chronic Obstructive Pulmonary Disease Hospitalization: Time Series Study During 2015-2017 in Chengdu China.

This paper investigates the association between consecutive ambient air pollution and Chronic Obstructive Pulmonary Disease (COPD) hospitalization in Chengdu China. The three-year (2015-2017) time series data for both ambient air pollutant concentrations and COPD hospitalizations in Chengdu are approved for the study. The big data statistic analysis shows that Air Quality Index (AQI) exceeded the lighted air polluted level in Chengdu region are mainly attributed to particulate matters (i.

A Per-sample Digitized Algorithm for Automatically Detecting Apnea and Hypopnea Events from Airflow and Oximetry.

Sleep apnea is a common sleep disorder that can significantly decrease the quality of life. An accurate and early diagnosis of sleep apnea is required before getting proper treatment. A reliable automated detection of sleep apnea can overcome the problems of manual diagnosis (scoring) due to variability in recording and scoring criteria (for example across Europe) and to inter-scorer variability.

Automatic Segmentation of 3D Ultrasound Spine Curvature Using Convolutional Neural Network.

Scoliosis is a 3D spinal deformation where the spine takes a lateral curvature, which generates an angle in a coronal plane. For periodic detection of scoliosis, safe and economic imaging modality is needed as continuous exposure to radiative imaging may cause cancer. 3D ultrasound imaging is a cost-effective and radiation-free imaging modality which gives volume projection image.