A signature combining brain functional connectivity with executive and motor function for general cognitive decline in Parkinson's disease.

Introduction: Cognitive decline is common in Parkinson's disease (PD). Reliance on neuropsychological testing alone can lead to delayed identification, and an objective and comprehensive approach is needed in clinical practice. We assessed brain functional connectivity during PD-MCI (mild cognitive impairment) and PD-NC (normal cognition) patients, and healthy controls (HC) completing the Stroop color-word test (SCWT) using functional near-infrared spectroscopy (fNIRS), and explored the predictive value of combining relevant brain function and behavioral information for general cognitive decline in PD.

Continuous Estimation of Swallowing Motion With EMG and MMG Signals.

Oropharyngeal dysphagia (OD) is a symptom of swallowing dysfunction that is associated with aspiration, severe respiratory complications, and even death. OD is a highly prevalent condition in populations including the elderly and patients with neurological diseases (e.g.

A Relationship Model between Optimized Exoskeleton Assistance and Gait Conditions Improves Multi-gait Human-in-the-Loop Optimization Performance.

Exoskeletons have been shown be able to reduce metabolic cost of human walking. Determining the suitable assistance is challenging due to individual variability in response and the need for tailored assistance across different gait conditions. Human-in-the-loop (HIL) optimization has been proposed to address this issue, but current implementations often suffer from prolonged optimization cycles.

Effect of Vest Load Carriage on Cardiometabolic Responses with Load Position, Load Mass, and Walking Conditions for Young Adults.

Carrying external loads, such as vest-borne systems, is common in occupations like firefighting and military service, yet the physiological impacts of load placement, mass, and walking conditions remain not fully understood. This study examined the effects of vest load carriage on metabolic rate and heart rate. Participants underwent three trials with varying load placements, masses (0-30 kg), and walking conditions (different speeds and inclines).

DeepQA: A Unified Transcriptome-Based Aging Clock Using Deep Neural Networks.

Understanding the complex biological process of aging is of great value, especially as it can help develop therapeutics to prolong healthy life. Predicting biological age from gene expression data has shown to be an effective means to quantify aging of a subject, and to identify molecular and cellular biomarkers of aging. A typical approach for estimating biological age, adopted by almost all existing aging clocks, is to train machine learning models only on healthy subjects, but to infer on both healthy and unhealthy subjects.

Decrease in walking ability with increased functional connectivity between multiple brain areas in Parkinson's disease: a functional near-infrared spectroscopy study.

Introduction: Gait disturbances significantly impact the mobility and quality of life of individuals with Parkinson's disease (PD). This study aims to delve into the cortical mechanisms underlying gait disorders in PD, specifically focusing on the prefrontal cortex (PFC), premotor cortex (PMC), and primary somatosensory cortex (PSC).

Objective: To compare the functional connectivity of the PFC, PMC, and PSC regions during walking between individuals with PD and healthy controls.

YoMo: Yoshimura Continuum Manipulator for MR Environment.

Origami robots have garnered attention due to their versatile deformation and potential applications, particularly for medical applications. In this article, we propose a Yoshimura continuum manipulator (YoMo) that can achieve accurate control of the tip position for the magnetic resonance (MR) environment. The YoMo made of a single piece of paper is cable-actuated to generate the bending and shortening deformation.

Engineering Bacterial Chitinases for Industrial Application: From Protein Engineering to Bacterial Strains Mutation! A Comprehensive Review of Physical, Molecular, and Computational Approaches.

Bacterial chitinases are integral in breaking down chitin, the natural polymer in crustacean and insect exoskeletons. Their increasing utilization across various sectors such as agriculture, waste management, biotechnology, food processing, and pharmaceutical industries highlights their significance as biocatalysts. The current review investigates various scientific strategies to maximize the efficiency and production of bacterial chitinases for industrial use.

Display of Bacterial Exochitanase on Spores Improved Enzyme Stability and Recyclability.

Chitin is the second most prevalent polysaccharide found in nature, following cellulose. Amino-oligosaccharides, the byproducts of chitin degradation, exhibit favorable biological properties and potential for various uses. Chitinases play a crucial function in the breakdown of chitin, and their exceptionally effective production has garnered significant interest.

SparseMorph: A weakly-supervised lightweight sparse transformer for mono- and multi-modal deformable image registration.

Purpose: Deformable image registration (DIR) is crucial for improving the precision of clinical diagnosis. Recent Transformer-based DIR methods have shown promising performance by capturing long-range dependencies. Nevertheless, these methods still grapple with high computational complexity.

A Knowledge-Driven Framework Discovers Brain ACtivation-Transition-Spectrum (ACTS) Features for Parkinson's Disease.

Dopaminergic treatment has proved effective to Parkinson's disease (PD), but the conventional treatment assessment is human-administered and prone to intra- and inter-assessor variability. In this paper, we propose a knowledge-driven framework and discover that brain ACtivation-Transition-Spectrum (ACTS) features achieve effective quantified assessments of dopaminergic therapy in PD. Firstly, brain activities of fifty-one PD patients during clinical walking tests under the OFF and ON states (without and with dopaminergic medication) were measured with functional near-infrared spectroscopy (fNIRS).

MatchMorph: A real-time pre- and intra-operative deformable image registration framework for MRI-guided surgery.

Purpose: The technological advancements in surgical robots compatible with magnetic resonance imaging (MRI) have created an indispensable demand for real-time deformable image registration (DIR) of pre- and intra-operative MRI, but there is a lack of relevant methods. Challenges arise from dimensionality mismatch, resolution discrepancy, non-rigid deformation and requirement for real-time registration.

Methods: In this paper, we propose a real-time DIR framework called MatchMorph, specifically designed for the registration of low-resolution local intraoperative MRI and high-resolution global preoperative MRI.

Active Neural Network Control for a Wearable Upper Limb Rehabilitation Exoskeleton Robot Driven by Pneumatic Artificial Muscles.

Pneumatic artificial muscle (PAM) has been widely used in rehabilitation and other fields as a flexible and safe actuator. In this paper, a PAM-actuated wearable exoskeleton robot is developed for upper limb rehabilitation. However, accurate modeling and control of the PAM are difficult due to complex hysteresis.

Denoising and Baseline Correction Methods for Raman Spectroscopy Based on Convolutional Autoencoder: A Unified Solution.

Preprocessing plays a key role in Raman spectral analysis. However, classical preprocessing algorithms often have issues with reducing Raman peak intensities and changing the peak shape when processing spectra. This paper introduces a unified solution for preprocessing based on a convolutional autoencoder to enhance Raman spectroscopy data.

Comparative Probiogenomics Analysis of Limosilactobacillus fermentum 3872.

Limosilactobacillus fermentum is an important member of the lactic acid bacteria group and holds immense potential for probiotic properties in human health and relevant industries. In this study, a comparative probiogenomic approach was applied to analyze the genome sequence of L. fermentum 3872, which was extracted from a commercially available yogurt sample, along with 20 different publicly available strains.

Balance Evaluation Based on Walking Experiments with Exoskeleton Interference.

The impairment of walking balance function seriously affects human health and will lead to a significantly increased risk of falling. It is important to assess and improve the walking balance of humans. However, existing evaluation methods for human walking balance are relatively subjective, and the selected metrics lack effectiveness and comprehensiveness.

A dynamic brain network decomposition method discovers effective brain hemodynamic sub-networks for Parkinson's disease.

Dopaminergic treatment is effective for Parkinson's disease (PD). Nevertheless, the conventional treatment assessment mainly focuses on human-administered behavior examination while the underlying functional improvements have not been well explored. This paper aims to investigate brain functional variations of PD patients after dopaminergic therapy.

Adaptive fuzzy control for tendon-sheath actuated bending-tip system with unknown friction for robotic flexible endoscope.

Introduction: The tendon-sheath actuated bending-tip system (TAB) has been widely applied to long-distance transmission scenes due to its high maneuverability, safety, and compliance, such as in exoskeleton robots, rescue robots, and surgical robots design. Due to the suitability of operation in a narrow or tortuous environment, TAB has demonstrated great application potential in the area of minimally invasive surgery. However, TAB involves highly non-linear behavior due to hysteresis, creepage, and non-linear friction existing on the tendon routing, which is an enormous challenge for accurate control.

Brain Temporal-Spectral Functional Variability Reveals Neural Improvements of DBS Treatment for Disorders of Consciousness.

Deep brain stimulation (DBS) is establishing itself as a promising treatment for disorders of consciousness (DOC). Measuring consciousness changes is crucial in the optimization of DBS therapy for DOC patients. However, conventional measures use subjective metrics that limit the investigations of treatment-induced neural improvements.

Subject-Specific Modeling of EEG-fNIRS Neurovascular Coupling by Task-Related Tensor Decomposition.

Neurovascular coupling (NVC) connects neural activity with hemodynamics and plays a vital role in sustaining brain function. Combining electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) is a promising way to explore the NVC. However, the high-order property of EEG data and variability of hemodynamic response function (HRF) across subjects have not been well considered in existing NVC studies.

Snapshot of the Probiotic Potential of DMKU-1042 Using a Comparative Probiogenomics Approach.

is a rapidly growing thermotolerant yeast that secretes a variety of lytic enzymes, utilizes different sugars, and produces ethanol. The probiotic potential of this yeast has not been well explored. To evaluate its probiotic potential, the yeast strain DMKU3-1042 was analyzed using next-generation sequencing technology.

Effective DBS treatment improves neural information transmission of patients with disorders of consciousness: an fNIRS study.

Deep brain stimulation (DBS) is a potential treatment that promotes the recovery of patients with disorders of consciousness (DOC). This study quantified the changes in consciousness and the neuromodulation effect of DBS on patients with DOC.Eleven patients were recruited for this study which consists of three conditions: 'Pre' (two days before DBS surgery), 'Post-On' (one month after surgery with stimulation), and 'Post-Off' (one month after surgery without stimulation).

fNIRS-based graph frequency analysis to identify mild cognitive impairment in Parkinson's disease.

Background: Early identification of mild cognitive impairment (MCI) is essential for its treatment and the prevention of dementia in Parkinson's disease (PD). Existing approaches are mostly based on neuropsychological assessments, while brain activation and connection have not been well considered.

New Method: This paper presents a neuroimaging-based graph frequency analysis method and the generated features to quantify the brain functional neurodegeneration and distinguish between PD-MCI patients and healthy controls.

Single-Channel sEMG-Based Estimation of Knee Joint Angle Using a Decomposition Algorithm With a State-Space Model.

Accurate human motion estimation is crucial for effective and safe human-robot interaction when using robotic devices for rehabilitation or performance enhancement. Although surface electromyography (sEMG) signals have been widely used to estimate human movements, conventional sEMG-based methods, which need sEMG signals measured from multiple relevant muscles, are usually subject to some limitations, including interference between sEMG sensors and wearable robots/environment, complicated calibration, as well as discomfort during long-term routine use. Few methods have been proposed to deal with these limitations by using single-channel sEMG (i.

High-Bandwidth Repetitive Trajectory Tracking Control of Piezoelectric Actuators via Phase-Hysteresis Hybrid Compensation and Feedforward-Feedback Combined Control.

Piezoelectric actuators (PEAs) are widely used in many nano-resolution manipulations. A PEA's hysteresis becomes the main factor limiting its motion accuracy. The distinctive feature of a PEA's hysteresis is the interdependence between the width of the hysteresis loop and the frequency or rate of the control voltage.