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Abstract This 2-year, 28-day study examined whether adolescents felt greater fatigue and emotional distress the same day and the day after air quality was worse. We linked objective daily air quality measurements to daily self-reports from 422 Mexican–American adolescents in Los Angeles County, California from 2009 to 2011 (50% girls, M Age = 15 years). A robust, within-subject analysis of 9696 observations revealed that adolescents with ongoing physical complaints reported greater fatigue and emotional distress on days that the air contained higher levels of nitrogen dioxide (NO2) and carbon monoxide (CO). Regardless of physical complaints, adolescents on average also reported greater fatigue the day after NO2 levels were higher. The same-day and next-day associations between air pollution and distress were mediated via daily increases in fatigue. Results were robust when controlling for day of the week, and daily temperature and humidity. Sulfur dioxide (SO2), ozone (O3), PM2.5 and PM10 were not related to daily fatigue or distress.

Abstract Nuclear cataract (NC) is a priority ocular disease of blindness and vision impairment globally. Early intervention and cataract surgery can improve the vision and life quality of NC patients. Anterior segment coherence tomography (AS-OCT) imaging is a non-invasive way to capture the NC opacity objectively and quantitatively. Recent clinical research has shown that there exists a strong opacity correlation relationship between NC severity levels and the mean density on AS-OCT images. In this paper, we present an effective NC classification framework on AS-OCT images, based on feature extraction and feature importance analysis. Motivated by previous clinical knowledge, our method extracts the clinical global–local features, and then applies Pearson’s correlation coefficient and recursive feature elimination methods to analyze the feature importance. Finally, an ensemble logistic regression is employed to distinguish NC, which considers different optimization methods’ characteristics. A dataset with 11,442 AS-OCT images is collected to evaluate the method. The results show that the proposed method achieves 86.96% accuracy and 88.70% macro-sensitivity, respectively. The performance comparison analysis also demonstrates that the global–local feature extraction method improves about 2% accuracy than the single region-based feature extraction method.

Abstract Notch ligands are expression changes in a great many malignancies including gastric cancer (GC) frequently. The prognostic value of each Notch ligands in GC patients remains lack of large sample data results. In present research, we researched the prognostic value of Notch ligands in GC patients in order to fill the shortage areas. We used an online database ( http://kmplot.com/analysis/index.php?p=service&cancer=gastric ) to identify the relationship between mRNA expression of each Notch ligand and overall survival (OS) in GC. We analyze the relevance of overall survival and clinical data which includes gender, Lauren's classification, differentiation, clinical stage and treatment. The study found that high DLL1, DLL3, DLL4 and JAG2 mRNA expression were tied to worse OS in all GC patients followed up for 10 years. There is no significant relevance to the expression of JAG1 mRNA and OS in patients with GC. We also did a survey of each Notch ligands in different clinical and pathological features present different prognosis. The information will help to better understand the biology of gastric cancer heterogeneity, provide more accurate prognostic evaluation tools and provide new targets for targeted drug development besides.

Summary The natural flavonoids luteolin and luteoloside have anti‐bacterial, anti‐inflammatory, anti‐oxidant, anti‐tumour, hypolipidemic, cholesterol lowering and neuroprotective effects, but their poor water solubility limits their application in industrial production and the pharmaceutical industry. In this study, luteolin‐7‐O‐β‐(6″‐O‐succinyl)‐d‐glucoside, a new compound that was prepared by succinyl glycosylation of luteolin by the organic solvent tolerant bacterium Bacillus amyloliquefaciens FJ18 in an 8.0% DMSO (v/v) system, was obtained and identified. Its greater water solubility (2293 times that of luteolin and 12 232 times that of luteoloside) provides the solution to the application problems of luteolin and luteoloside. The conversion rate of luteolin (1.0 g l−1) was almost 100% at 24 h, while the yield of luteolin‐7‐O‐β‐(6″‐O‐succinyl)‐d‐glucoside reached 76.2%. In experiments involving the oxygen glucose deprivation/reoxygenation injury model of mouse hippocampal neuron cells, the cell viability was significantly improved with luteolin‐7‐O‐β‐(6″‐O‐succinyl)‐d‐glucoside dosing, and the expressions of the anti‐oxidant enzyme HO‐1 in the nucleus increased, providing a neuroprotective effect for ischemic cerebral cells. The availability of biosynthetic luteolin‐7‐O‐β‐(6″‐O‐succinyl)‐d‐glucoside, which is expected to replace luteolin and luteoloside, would effectively expand the clinical application value of luteolin derivatives.

ABSTRACT: Objectives: We aimed to determine the breakpoint of cycloserine (CS) susceptibility in MGIT and to describe the molecular characteristics of CS-resistant Mycobacterium tuberculosis (MTB) isolates. Methods: A total of 124 MTB isolates were recruited in our analysis. Minimum inhibitory concentration (MIC) was determined using the MGIT system. The mutations of MTB isolates within alr, ddl, ald, and cycA, potentially conferring CS resistance were analyzed by the whole-genome sequencing. Results: In vitro drug susceptibility testing of isolates with doubling concentrations of CS revealed that the modal MIC values was 4 mg/L for MGIT, accounting for 35.5% (44/124) of isolates tested. Seven isolates harbored mutations conferring CS resistance, consisting of five with alr mutations and two with ald mutations. On the basis of the MIC distributions of wild-type and resistotype populations, we proposed a tentative epidemiologic cut-off value of 16 mg/l. The proportion of CS resistance in extensively drug-resistant TB was significantly higher than that of multidrug-resistant TB. Conclusion: In conclusion, we propose critical concentration for MGIT 960 to properly diagnose CS-resistant MTB and demonstrate that mutations in alr and ald genes are the major mechanism conferring CS resistance in clinical isolates.

Currently, Chinese herbal feed additives (CHFA) are commonly utilized in domestic pig farms. However, their impact on the sperm quality and reproductive capacity of imported breeding boars has yet to be thoroughly explored. In this study, the effect of CHFA on the sperm quality and reproductive capacity of the imported Duroc boars was investigated. Sixteen boars were randomly divided into control group and experimental (CHFA treated) group and fed normal or CHFA-levels containing diets, respectively. The sperm quality and reproductive hormone levels were periodically tested, and the reproductive capacity with breeding sows were evaluated. The results showed that the CHFA treated group boars significantly improved sperm volume, sperm concentration, and motility and reduced the sperm abnormalities. Furthermore, the serum levels of reproductive hormone such as follicle-stimulating hormone (FSH), luteinizing hormone (LH), and testosterone (T) in the CHFA treated group were significantly higher than those in the control group. Although there was no significant difference in the initial birth weight of piglets between the two groups, the CHFA treated group had a significantly higher average number of piglets born, the average number of piglets born alive, the number of piglets weaned at 28 days, and the weaning weight compared to the control group. These findings suggest that CHFA can significantly improve the sperm quality of breeding boars and enhance their reproductive hormone levels as well as the reproductive capacity, providing direct evidence for the further application of CHFA in the management of breeding boars in China.

Microcrack damage repair and microbial contamination prevention are two major challenges for anti-corrosion coatings on the surfaces of underwater installations. In this study, water-triggered self-healing microcapsules were combined with low-surface-energy fluoropolymers to prepare a bifunctional anti-corrosion coating with underwater self-healing and bio-fouling properties. The results showed that the prepared microcapsules had good mechanical, thermal, and environmental stability, with an average diameter of 153 μm and an encapsulation rate of 66.7%. When the microcapsule content in the coating was 8 wt%, the microcapsule dispersion performance and healing barrier effect of the composite coating were optimal, and the repair efficiency reached 81.6%. Furthermore, compared with the coating without microcapsules or graft fluoropolymers (PFG), the sample denoted as PFG18/4/IPDI-MC/ER showed the largest surface water contact angle and had the best protein inhibition rate of 87% when using bovine hemoglobin to detect the protein adsorption concentration on the coating surface.

Spiking neural networks (SNNs) have recently demonstrated outstanding performance in a variety of high-level tasks, such as image classification. However, advancements in the field of low-level assignments, such as image reconstruction, are rare. This may be due to the lack of promising image encoding techniques and corresponding neuromorphic devices designed specifically for SNN-based low-level vision problems. This paper begins by proposing a simple yet effective undistorted weighted-encoding-decoding technique, which primarily consists of an Undistorted Weighted-Encoding (UWE) and an Undistorted Weighted-Decoding (UWD). The former aims to convert a gray image into spike sequences for effective SNN learning, while the latter converts spike sequences back into images. Then, we design a new SNN training strategy, known as Independent-Temporal Backpropagation (ITBP) to avoid complex loss propagation in spatial and temporal dimensions, and experiments show that ITBP is superior to Spatio-Temporal Backpropagation (STBP). Finally, a so-called Virtual Temporal SNN (VTSNN) is formulated by incorporating the above-mentioned approaches into U-net network architecture, fully utilizing the potent multiscale representation capability. Experimental results on several commonly used datasets such as MNIST, F-MNIST, and CIFAR10 demonstrate that the proposed method produces competitive noise-removal performance extremely which is superior to the existing work. Compared to ANN with the same architecture, VTSNN has a greater chance of achieving superiority while consuming ~1/274 of the energy. Specifically, using the given encoding-decoding strategy, a simple neuromorphic circuit could be easily constructed to maximize this low-carbon strategy.

There are increasing epilepsy patients suffering from the pain of seizure onsets, and effective prediction of seizures could improve their quality of life. To obtain high sensitivity for epileptic seizure prediction, current studies generally need complex feature extraction operations, which heavily depends on the artificial experience (or domain knowledge) and is highly subjective. To address these issues, in this paper we propose an end-to-end epileptic seizure prediction approach based on the long short-term memory network (LSTM). In the new method, only the gamma band of raw electroencephalography (EEG) signals is extracted as network input directly for seizure prediction, thus avoiding subjective and expensive feature design process. Despite its simplicity, the proposed method achieves the mean sensitivity of 91.76% and false prediction rate (FPR) of 0.29/h on Children’s Hospital Boston-MIT (CHB-MIT) scalp EEG Database, respectively, when identifying the preictal stage from the EEG signals. Furthermore, different from traditional methods that only consider the classification of preictal and interictal EEG, we introduce the postictal stage as an extra class in the proposed method. As a result, the performance of seizure prediction is further improved, obtaining a higher sensitivity of 92.17% and a low FPR of 0.27/h. The mean warning time is 44.46 min, which suggests that sufficient time is reserved for patients to take intervention measures by this prediction method.

The widespread use of pharmaceuticals and personal care products (PPCPs) in many fields has brought convenience to human lives but has also caused unavoidable environmental pollution issues. In particular, the resistance gene problem resulting from accumulating antibiotics that cannot be fully absorbed by biological individuals has been a concern; thus, it is urgent to find efficient technologies to boost the degradation efficiency of antibiotics in the environment. Here, an ε-MnO2 catalyst was prepared by a novel droplet-interface-drying method and utilized as a Fenton-like catalyst for efficiently degrading ciprofloxacin (CIP). The ε-MnO2 shell was formed preferentially at the gas–liquid interface and then continued to decompose into ε-MnO2 with abundant O vacancies in the air-insulated microcavity. The XPS result confirms that this particular preparation method can regulate the content of O vacancies in the material. Compared with ε-MnO2 samples obtained by the direct drying method (ε-MnO2-B), the catalytic performance of ε-MnO2 prepared by the droplet-interface-drying method (ε-MnO2-P) is significantly improved. By activating peroxymonosulfate (PMS) with the ε-MnO2-P catalyst, the CIP degradation efficiency can reach 84.1%. The detection and analysis of reactive oxygen species (ROS) in the ε-MnO2-P/PMS oxidation system confirms that ·OH, SO4·− and 1O2 are the main ROS for CIP degradation. This study highlights the creation of miniature hypoxic space to regulate the content of O vacancies in ε-MnO2, providing a new idea for the synthesis of other O-vacancy-rich materials.