Broadly conserved roles of TMEM131 family proteins in intracellular collagen assembly and secretory cargo trafficking.

Collagen is the most abundant protein in animals. Its dysregulation contributes to aging and many human disorders, including pathological tissue fibrosis in major organs. How premature collagen proteins in the endoplasmic reticulum (ER) assemble and route for secretion remains molecularly undefined. From an RNA interference screen, we identified an uncharacterized Caenorhabditis elegans gene tmem-131, deficiency of which impairs collagen production and activates ER stress response. We find that amino termini of human TMEM131 contain bacterial PapD chaperone-like domains, which recruit premature collagen monomers for proper assembly and secretion. Carboxy termini of TMEM131 interact with TRAPPC8, a component of the TRAPP tethering complex, to drive collagen cargo trafficking from ER to the Golgi. We provide evidence that previously undescribed roles of TMEM131 in collagen recruitment and secretion are evolutionarily conserved in C. elegans, Drosophila, and humans

Maternal ambient air pollution exposure with spatial-temporal variations and preterm birth risk assessment during 2013-2017 in Zhejiang Province, China.

Preterm birth (PTB) can give rise to significant neonatal morbidity and mortality, as well as children's long-term health defects. Many studies have illustrated the associations between ambient air pollution exposure during gestational periods and PTB risks, but most of them only focused on one single air pollutant, such as PM2.5. In this population-based environmental-epidemiology study, we recruited 6275 pregnant mothers in Zhejiang Province, China, and evaluated their gestational exposures to various air pollutants during 2013-2017. Time-to-event logistic regressions were performed to estimate risk associations after adjusting all confounders, and Quasi-AQI model and PCA-GLM analysis were applied to resolve the collinearity issues in multi-pollutant regression models. It was found that gestational exposure to ambient air pollutants was significantly associated with the occurrence of PTB, and SO2 was the largest contributor with a proportion of 29.4%. Three new variables, prime factor (a combination of PM2.5, PM10, SO2, and NO2), carbon factor (CO), and ozone factor (O3), were generated by PCA integration, contributing 63.4%, 17.1%, and 19.5% to PTB risks, respectively. The first and third trimester was the most crucial exposure window, suggesting the pregnant mothers better to avoid severe air pollution exposures during these sensitive periods

Discovery and excavation of lichen bioactive natural products

Lichen natural products are a tremendous source of new bioactive chemical entities for drug discovery. The ability to survive in harsh conditions can be directly correlated with the production of some unique lichen metabolites. Despite the potential applications, these unique metabolites have been underutilized by pharmaceutical and agrochemical industries due to their slow growth, low biomass availability, and technical challenges involved in their artificial cultivation. At the same time, DNA sequence data have revealed that the number of encoded biosynthetic gene clusters in a lichen is much higher than in natural products, and the majority of them are silent or poorly expressed. To meet these challenges, the one strain many compounds (OSMAC) strategy, as a comprehensive and powerful tool, has been developed to stimulate the activation of silent or cryptic biosynthetic gene clusters and exploit interesting lichen compounds for industrial applications. Furthermore, the development of molecular network techniques, modern bioinformatics, and genetic tools is opening up a new opportunity for the mining, modification, and production of lichen metabolites, rather than merely using traditional separation and purification techniques to obtain small amounts of chemical compounds. Heterologous expressed lichen-derived biosynthetic gene clusters in a cultivatable host offer a promising means for a sustainable supply of specialized metabolites. In this review, we summarized the known lichen bioactive metabolites and highlighted the application of OSMAC, molecular network, and genome mining-based strategies in lichen-forming fungi for the discovery of new cryptic lichen compounds

Repetitive transcranial magnetic stimulation for treatment of limb spasticity following multiple sclerosis: a systematic review and meta-analysis

Pilot trials have suggested that repetitive transcranial magnetic stimulation (rTMS) may reduce limb spasticity in multiple sclerosis (MS). We carried out the current meta-analysis to synthesize currently available evidence regarding such correlation. Up to November 2022, five international electronic databases (Cochrane CENTRAL, PubMed, Embase, Web of Science, and CINAHL) and four Chinese electronic databases (CBM, CNKI, WanFang Data, and VIP) were systematically searched to identify randomized trials comparing active rTMS and sham stimulation in patients with MS-related spasticity. Two reviewers independently selected studies and extracted data on study design, quality, clinical outcomes, and time points measured. The primary outcome was clinical spasticity relief after intervention. Secondary outcomes included spasticity at the follow-up visit 2 weeks later and post-treatment fatigue. Of 831 titles found, we included 8 studies (181 participants) in the quantitative analysis. Pooled analyses showed that rTMS therapy was associated with significant spasticity relief in the early post-intervention period [standardized mean differences (SMD): -0.67; 95%CI: -1.12 to -0.21], but there was insufficient evidence for rTMS in reducing spasticity at the follow-up visit 2 weeks later (SMD: -0.17; 95%CI: -0.52 to 0.17) and fatigue (SMD: -0.26; 95%CI: -0.84 to 0.31). This evidence supports the recommendations to treat MS-related spasticity with rTMS, but underlines the need for further large randomized trials

A study on MEMS oscillators‘ frequency drift of temperature

The frequency output of oscillators is subject to a series of factors, such as working temperature, humidity, shock and vibration. Most of these factors are related to the manufacturing processes and packaging techniques employed in the semiconductor industry. Among the above factors, the influence of temperature is the most direct and most significant. And the effect of temperature on the frequency output of the oscillator is also called oscillators‘ frequency drift of temperature. This project aims to study frequency drift of two types of oscillators influenced by temperature, namely Quarts oscillators and MEMS oscillators. Firstly, the report states two types of oscillators‘ strength and weakness respectively. And then, referring to some industrial standards, the report also deceives and performs a series of tests to obtain data about the behavior of oscillators in different temperature. The experimental results show that the curve of the frequency-temperature of OCXO is approximately a horizontal line. And the curve of MEMS oscillator 1 looks like a capital letter M with relative small amplitude, and the curve of MEMS oscillator 2 is close to a slowly decreasing line. While the curve of crystal oscillator is a sine curve with steep rise at the end. According to the diagram, a conclusion that MEMS oscillators‘ frequency drift of temperature is less than that of crystal oscillators can be drawn naturally

Optical and Magnetic Properties of Ni Doped ZnS Diluted Magnetic Semiconductors Synthesized by Hydrothermal Method

Diluted magnetic semiconductors Zn1-xNixS with different consistency ratio (x = 0, 0.01, 0.03, 0.05, and 0.07) were successfully synthesized by hydrothermal method using ethylenediamine as a modifier. The influence of Ni doping concentration on the microstructure, morphology, and optical and magnetic properties of undoped and Ni doped ZnS nanocrystals was characterized by X-ray diffraction (XRD), high-resolution transmission electron microscopy (HRTEM), X-ray energy dispersive spectrometry (XEDS), ultraviolet-visible spectroscopy (UV-vis), Fourier transform infrared spectroscopy (FT-IR), photoluminescence spectra (PL), and the vibrating sample magnetometer (VSM), respectively. The experiment results show the substitution of Ni2+ on Zn2+ sites without changing the hexagonal wurtzite structure of ZnS and generate single-phase Zn1-xNixS with good crystallization. The lattice constant causes distortion and decreases with the increase of Ni2+ doped concentration. The appearance of the samples is one-dimensional well-dispersed nanorods. UV-vis spectra reveal the band gap of all Zn1-xNixS samples greater than that of bulk ZnS (3.67 eV), and blue shift phenomenon occurs. The photoluminescence spectra of undoped and doped samples possess the broad blue emission band in the range of 400–650 nm; the PL intensities of Zn1-xNixS nanorods increase with the increase of Ni content comparing to pure ZnS and reach maximum for x = 0.03. Magnetic measurements indicated that the undoped ZnS samples are superparamagnetic, whereas the doped samples exhibit ferromagnetism

Fault Diagnosis of Rotating Machinery Based on Improved Self-Supervised Learning Method and Very Few Labeled Samples

Convolution neural network (CNN)-based fault diagnosis methods have been widely adopted to obtain representative features and used to classify fault modes due to their prominent feature extraction capability. However, a large number of labeled samples are required to support the algorithm of CNNs, and, in the case of a limited amount of labeled samples, this may lead to overfitting. In this article, a novel ResNet-based method is developed to achieve fault diagnoses for machines with very few samples. To be specific, data transformation combinations (DTCs) are designed based on mutual information. It is worth noting that the selected DTC, which can complete the training process of the 1-D ResNet quickly without increasing the amount of training data, can be randomly used for any batch training data. Meanwhile, a self-supervised learning method called 1-D SimCLR is adopted to obtain an effective feature encoder, which can be optimized with very few unlabeled samples. Then, a fault diagnosis model named DTC-SimCLR is constructed by combining the selected data transformation combination, the obtained feature encoder and a fully-connected layer-based classifier. In DTC-SimCLR, the parameters of the feature encoder are fixed, and the classifier is trained with very few labeled samples. Two machine fault datasets from a cutting tooth and a bearing are conducted to evaluate the performance of DTC-SimCLR. Testing results show that DTC-SimCLR has superior performance and diagnostic accuracy with very few samples

Overview on the development and critical issues of water jet guided laser machining technology

There was no established literature or documentation regarding this due to the competition for the market and confidentiality issues. This article reviews the current status of waterjet guided laser (WJGL) processing. This paper addresses the state-of-the-art development and knowledge in WJGL technology. The paper attempts to support researchers as well as practical engineers who are considering this non-traditional manufacturing method for application in their field. The topic is developed following the history of the water-jet guided laser technology. It outlines the primary aspects of industrial use, their relevant applications, and the variety of laser beam sources available. Here the principle, machine configuration and benefits of the WJGL technology are elaborated. The formation process of water jet, optical characteristics of water, the influence of different factors on the stability of jet are discussed. In this paper different aspect of laser-waterjet coupling like coupling unit, parameters, loss, propagation modes and speckle etc. are discussed. The major factors which affect transmission efficiency are wavelength of laser, focal position and numerical aperture. After giving some more details on the operating principle and its realization, the following sections WJGL-matter interaction, modeling of material removal, laser induced bubble and breakdown are presented. In this paper an attempt is made to present a literature survey on waterjet guided laser technology