Notes

Molecular trafficking involving germs decides the form involving stomach microbial local community.
Comparisons proved that wearing the exoskeleton caused a negligible deviation of gait, and that the soft exoskeleton could reduce metabolic cost during walking. The research results are expected to be beneficial for lightweight soft exoskeletons and integration with exosuits that provide assistive forces through the wearer's entire gait.
Whole-cell biosensors are a powerful and easy-to-use screening tool for the fast and sensitive detection of chemical compounds, such as antibiotics. β-Lactams still represent one of the most important antibiotic groups in therapeutic use. They interfere with late stages of the bacterial cell wall biosynthesis and result in irreversible perturbations of cell division and growth, ultimately leading to cell lysis. In order to simplify the detection of these antibiotics from solutions, solid media or directly from producing organisms, we aimed at developing a novel heterologous whole-cell biosensor in
, based on the β-lactam-induced regulatory system BlaR1/BlaI from
.

The BlaR1/BlaI system was heterologously expressed in
and combined with the
operon of
under control of the BlaR1/BlaI target promoter to measure the output of the biosensor. A combination of codon adaptation, constitutive expression of
and
and the allelic replacement of
increased the inducer spectrum and dynamic range of this highly sensitive for a broad spectrum of β-lactams from all four chemical classes. Therefore, it increases the detectable spectrum of compounds with respect to previous biosensor designs. Our biosensor can readily be applied for identifying β-lactams in liquid or on solid media, as well as for identifying potential β-lactam producers.
Mental health challenges are a leading health concern for youth globally, requiring a comprehensive approach incorporating promotion, prevention and treatment within a healthy public policy framework. However, the broad enactment of this vision has yet to be realized. Further, mental health
evidence specific to youth is still emerging and has not yet focused at a policy level. This is a critical gap, as policy is a key mental health promotion lever that can alter the social and structural conditions that contribute to shaping youth mental health outcomes for
youth, across the full spectrum of need. Responsive to this research and intervention priority, our prototype study intervention-the Agenda Gap-is comprised of an innovative, multi-media engagement intervention, developed in collaboration with youth. This intervention aims to equip youth and build capacity for them to lead meaningful policy change reflective of the mental health needs of diverse communities of youth, including those who experienceks, for whom, and in what context.

This study is unique in its "upstream" focus on youth-engaged policymaking as a tool for improving the social and structural conditions that influence youth mental health across socioecological levels. Through the implementation and testing of the Agenda Gap intervention with diverse youth, this study will contribute to the evidence base on youth-engaged policymaking as a novel and innovative, mental health promotion strategy.
This study is unique in its "upstream" focus on youth-engaged policymaking as a tool for improving the social and structural conditions that influence youth mental health across socioecological levels. Through the implementation and testing of the Agenda Gap intervention with diverse youth, this study will contribute to the evidence base on youth-engaged policymaking as a novel and innovative, mental health promotion strategy.
The Eating Disorder Quality of Life (ED-QOL) scale is a 25-item self-report measure that assesses health-related quality of life (HRQoL) of eating-disorder patients. Although the ED-QOL is one of the most widely used questionnaires in many countries, no prior research has addressed the psychometric properties of the Japanese translation of the ED-QOL. Therefore, the aim of the present study was to assess its reliability and validity.

A total of 99 Japanese female eating disorder patients and 469 female healthy university undergraduate students completed the Japanese translation of the ED-QOL in addition to the Eating Attitudes Test-26 (EAT-26) and Eating Disorder Inventory-2 (EDI-2). The patient group consisted of 37 patients with anorexia nervosa restricting type (AN-R), 35 patients with binge-eating/purge type (AN-BP), and 27 patients with bulimia nervosa (BN). We performed confirmatory factor analyses on the ED-QOL subscales both for Japanese eating disorder patients and for healthy university undergragarded as reliable, valid, and functional for female eating-disorder patients and female healthy university undergraduate students.
Based on this study, the Japanese translation of the ED-QOL can be regarded as reliable, valid, and functional for female eating-disorder patients and female healthy university undergraduate students.Osteoarthritis (OA) is a common chronic articular degenerative disease, and characterized by articular cartilage degradation, synovial inflammation/immunity, and subchondral bone lesion, etc. The disease affects 2-6% of the population around the world, and its prevalence rises with age and exceeds 40% in people over 70. Recently, increasing interest has been devoted to the treatment or prevention of OA by herbal medicines. In this paper, the herbal compounds with anti-OA activities were reviewed, and the cheminformatics tools were used to predict their drug-likeness properties and pharmacokinetic parameters. A total of 43 herbal compounds were analyzed, which mainly target the damaged joints (e.g. cartilage, subchondral bone, and synovium, etc.) and circulatory system to improve the pathogenesis of OA. Through cheminformatics analysis, over half of these compounds have good drug-likeness properties, and the pharmacokinetic behavior of these components still needs to be further optimized, which is conducive to the enhancement in their drug-likeness properties. Most of the compounds can be an alternative and valuable source for anti-OA drug discovery, which may be worthy of further investigation and development.
(Labill.) Benth, one of the traditional Chinese herbal medicines, has been used for treatment of nephritis, osteoporosis, rheumatism, and menopausal syndrome. The aim of this study was to illuminate the therapeutic effect and mechanism of
aqueous extract (GATE) in the treatment of nephrotic syndrome (NS).

UHPLC-DAD-MS/MS was used to analyze the chemical profile of GATE. Adriamycin (ADR)-induced NS mouse model and network pharmacology methods were conducted to explore the protective effect and mechanism of GATE on NS treatment.

GATE administration significantly ameliorated symptoms of proteinuria and hyperlipidemia in NS mice, as evidenced by reduced excretion of urine protein and albumin, and decreased plasma levels of total cholesterol and triglyceride. Decreased blood urea nitrogen (BUN) and creatinine levels in NS mice suggested that GATE could prevent renal function decline caused by ADR. GATE treatment also inhibited ADR-induced pathological lesions of renal tissues as indicated by periodic acihrough modulating oxidative stress and inflammation, suggesting the potential application of GATE or its derivatives in the prevention and treatment of NS and other related kidney diseases.EEG pattern recognition is an important part of motor imagery- (MI-) based brain computer interface (BCI) system. Traditional EEG pattern recognition algorithm usually includes two steps, namely, feature extraction and feature classification. In feature extraction, common spatial pattern (CSP) is one of the most frequently used algorithms. However, in order to extract the optimal CSP features, prior knowledge and complex parameter adjustment are often required. Convolutional neural network (CNN) is one of the most popular deep learning models at present. Within CNN, feature learning and pattern classification are carried out simultaneously during the procedure of iterative updating of network parameters; thus, it can remove the complicated manual feature engineering. In this paper, we propose a novel deep learning methodology which can be used for spatial-frequency feature learning and classification of motor imagery EEG. Specifically, a multilayer CNN model is designed according to the spatial-frequency characteristics of MI EEG signals. An experimental study is carried out on two MI EEG datasets (BCI competition III dataset IVa and a self-collected right index finger MI dataset) to validate the effectiveness of our algorithm in comparison with several closely related competing methods. Superior classification performance indicates that our proposed method is a promising pattern recognition algorithm for MI-based BCI system.
Earth Observation 'EO' remote sensing technology development enables original insights into vegetation function and health at ever finer temporal, spectral and spatial resolution. Research sites equipped with monitoring infrastructure such as flux towers operate at a key bridging scale between satellite platform measurements and on-the-ground leaf-level processes.

This paper presents the technical details of the design and operation of a proximal observation system 'THEMS' that generates unattended long-term high quality thermal and hyperspectral images of a forest canopy on a short (sub-daily) timescale. The primary purpose of the system is to measure canopy temperature, spectral reflectance and radiance coincident with a highly instrumented flux tower site for benchmarking purposes. Basic system capability is demonstrated through low level data product descriptions of the high-resolution multi-angular imagery and ancillary data streams. The system has been successfully operational for more than 2years with little to no intervention.

These data can then be used to derive remotely sensed proxies of canopy and ecosystem function to study temporal forest dynamics over a wide range of wavelengths, spatial scales (individual trees to canopy), and temporal scales (minutes to multiple years). The multi-purpose system is intended to provide unprecedented spatio-temporal ecophysiological insight and to underpin upscaling of remotely sensed dynamic ecosystem water, CO
, and energy exchange processes.
These data can then be used to derive remotely sensed proxies of canopy and ecosystem function to study temporal forest dynamics over a wide range of wavelengths, spatial scales (individual trees to canopy), and temporal scales (minutes to multiple years). The multi-purpose system is intended to provide unprecedented spatio-temporal ecophysiological insight and to underpin upscaling of remotely sensed dynamic ecosystem water, CO2, and energy exchange processes.
Timely and accurate estimates of canopy chlorophyll (Chl) a and b content are crucial for crop growth monitoring and agricultural management. Crop canopy reflectance depends on many factors, which can be divided into the following categories (i) leaf effects (e.g., leaf pigments), (ii) canopy effects (e.g., Leaf Area Index [LAI]), and (iii) soil background reflectance (e.g., soil reflectance). The estimation of leaf variables, such as Chl contents, from reflectance at the canopy scale is usually less accurate than that at the leaf scale. In this study, we propose a Visible and Near-infrared (NIR) Angle Index (VNAI) to estimate the Chl content of soybean canopy, and soybean canopy Chl maps are produced using visible and NIR unmanned aerial vehicle (UAV) remote sensing images. The VNAI is insensitive to LAI and can be used for the multi-stage estimation of crop canopy Chl content.

Eleven previously used vegetation indices (VIs) (e.g., Pigment-specific Normalized Difference Index) were selected for performance comparison.
Homepage: