Water-Capture Filter Paper Separator Realizing Ambient Li-Air Battery.

Lithium-air battery (LAB) is regarded as one of the most promising energy storage systems. However, the challenges arising from the lithium metal anode have significantly impeded the progress of LAB development. In this study, cellulose-based filter paper (FP) is utilized as a separator for ambient Li-air batteries to suppress dendrite growth and prevent H2O crossover. Thermogravimetric analysis and molecular spectrum reveal that FP enables ambient Li-air battery operation due to its surface functional groups derived from cellulose. The oxygen-enriched surface of cellulose not only enhances ion conductivity but also captures water and confines solvent molecules, thereby mitigating anode corrosion and side reactions. Compared with commercial glassfiber (GF) separator, this cellulose-based FP separator is cheaper, renewable, and environmentally friendly. Moreover, it requires less electrolyte while achieving prolonged and stable cycle life under real air environment conditions. This work presents a novel approach to realizing practical Li-air batteries by capturing water on the separator's surface. It also provides insights into the exploration and design of separators for enabling practical Li-air batteries toward their commercialization.

Emerging Roles of B56 Phosphorylation and Binding Motif in PP2A-B56 Holoenzyme Biological Function.

Protein serine/threonine phosphatase 2A (PP2A) regulates diverse cellular processes via the formation of ~100 heterotrimeric holoenzymes. However, a scarcity of knowledge on substrate recognition by various PP2A holoenzymes has greatly prevented the deciphering of PP2A function in phosphorylation-mediated signaling in eukaryotes. The review summarized the contribution of B56 phosphorylation to PP2A-B56 function and proposed strategies for intervening B56 phosphorylation to treat diseases associated with PP2A-B56 dysfunction; it especially analyzed recent advancements in LxxIxEx B56-binding motifs that provide the molecular details of PP2A-B56 binding specificity and, on this basis, explored the emerging role of PP2A-B56 in the mitosis process, virus attack, and cancer development through LxxIxE motif-mediated PP2A-B56 targeting. This review provides theoretical support for discriminatingly targeting specific PP2A holoenzymes to guide PP2A activity against specific pathogenic drivers.

Construction of an Immunophenoscore-Related Signature for Evaluating Prognosis and Immunotherapy Sensitivity in Ovarian Cancer.

Ovarian cancer (OC) is the deadliest gynecological malignancy in the world, and immunotherapy is emerging as a promising treatment. Immunophenoscore (IPS) is a robust biomarker distinguishing sensitive responders from immunotherapy. In this study, we aimed to construct a prognostic model for predicting overall survival (OS) and identifying patients who would benefit from immunotherapy. First, we combined The Cancer Genome Atlas (TCGA) and The Cancer Immune Atlas (TCIA) data sets and incorporated 229 OC samples into a training cohort. The validation cohort included 240 OC samples from the Gene Expression Omnibus (GEO) cohort. The training cohort was divided into high- and low-IPS subgroups to obtain differentially expressed genes (DEGs). DEGs with OS were identified by Univariate Cox regression analysis. The least absolute shrinkage and selection operator (LASSO) Cox regression was used to construct the prognostic model. Then, immune and mutation analyses were performed to explore the relationship between the model and the tumor microenvironment (TME) and tumor mutation burden (TMB). Eighty-three DEGs were obtained between the high-and low-IPS subgroups, where 17 DEGs were associated with OS. The five essential genes were selected to establish the prognostic model, which showed high accuracy for predicting OS and could be an independent survival indicator. OC samples that were divided by risk scores showed distinguished immune status, TME, TMB, immunotherapy response, and chemotherapy sensitivity. Similar results were validated in the GEO cohort. We developed an immunophenoscore-related signature associated with the TME to predict OS and response to immunotherapy in OC.

Chronic exposure to ampicillin alters lung microbial composition in laboratory rat.

PURPOSE: High-throughput sequencing technologies have revealed that the lungs contain a variety of low biomass microbiota associated with various lung diseases. Rat model is an important tool to understand the possible causal relationship between pulmonary microbiota and diseases. Antibiotic exposure can alter the microbiota, however, a direct influence of long-term ampicillin exposure on commensal bacteria of healthy lungs has not been investigated, which could be useful in the study of the relation between microbiome and long-term lung diseases, especially in animal model-making of lung diseases. METHODS: The rats were aerosolized ampicillin of different concentrations for five months, and then the effect on the lung microbiota was investigated using 16S rRNA gene sequencing. RESULTS: The ampicillin treatment by a certain concentration (LA5, 0.2 ml of 5 mg/ml ampicillin) administration leads to profound changes in the rat lung microbiota but not in the low critical ampicillin concentration (LA01 and LA1, 0.1 and 1 mg/ml ampicillin), when compared to the untreated group (LC). The genus Acidobacteria_Gp16 dominated the ampicillin treated lung microbiota while the genera Brucella, Acinetobacter, Acidobacteria_Gp14, Sphingomonas, and Tumebacillus dominated the untreated lung microbiota. The predicted KEGG pathway analysis profile revealed some difference in the ampicillin treated group. CONCLUSIONS: The study demonstrated the effects of different concentrations of ampicillin treatment on lung microbiota of rats in a relatively long term. It could serve as a basis for the clinical use of antibiotic and the use of ampicillin to control certain bacteria in the animal model-making of respiratory diseases such as chronic obstructive pulmonary disease.

Risk cognition, agricultural cooperatives training, and farmers' pesticide overuse: Evidence from Shandong Province, China.

Introduction: Pesticides are widely and excessively used in the world. Reducing pesticide overuse is an important measure to protect the environment and human health. Methods: Based on the survey data of 518 farmers in Shandong Province, China, using the Logit model to empirically test the effect of risk cognition on farmers' pesticide overuse behavior and the moderating effect of cooperatives training on the effect of risk cognition on farmers' pesticide overuse behavior. Results and discussion: We found that 21.24% of farmers overused pesticides. The three dimensions of risk cognition have significant negative effects on farmers' behavior of excessive pesticide use, among which the human health risk cognition has the largest impact (0.74), followed by food safety risk cognition (0.68) and ecological environment risk cognition (0.63). Cooperatives training has a positive moderating effect on the relationship between risk cognition and pesticide overuse behavior, that is, when risk cognition matches farmers participating in cooperatives training, the effect on reducing pesticide overuse is more significant. Years of education, planting scale and detection frequency of pesticide residues have significant effects on farmers' pesticide overuse. Conclusions: The government should help farmers reduce pesticide overuse by improving risk cognition, developing agricultural cooperatives and perfecting guarantee conditions.

Projection optical engine design based on tri-color LEDs and digital light processing technology.

Digital light processing (DLP) is currently a cutting-edge technology for desktop projection optical engines. Due to the passive luminescence characteristics, the DLP projection engine needs a few specific illumination optical components for light collimation, homogenization, and color combination, together with a projection lens matching the DLP chip and magnifying the image. In this paper, we propose a design approach that first splits the DLP projection optical engine into individual components for separate design, and then integrates them into a whole system for further verification. For the first step, the collimating lens group is designed for light collection, and the dichroic mirrors are used to fold the light path based on tri-color LED light sources. For the second step, a fly-eye lens and the corresponding relay lens group are designed to achieve uniform illumination on the DMD chip. The third step is to optimize the projection lens group for high-resolution projection display. Based on the design and simulation, the optical efficiency is 63.4% and the uniformity reaches 94.9% on the projection screen. The modulation transfer function (MTF) of the projection lens is higher than 0.4 at 66 lines for the distance of 500∼1500mm, and the distortion is lower than 1%. Simulation results show that the total luminous flux is estimated to reach 224.15 lm when the powers of tri-color LEDs are 21 W, 15.5 W, and 25 W, respectively. A projector prototype is built and tested for further verification, which provides a luminous flux of 220.43 lm and uniformity of 90.22%, respectively. The proposed design, demonstrated by both simulation and experiment, exhibits high feasibility and application potential in state-of-the-art commercial projector design.

Comparison of Methods for the Estimation of the Maximum Oxygen Uptake of Men Drug Addicts.

Background: Maximum oxygen uptake (VO2max) is an important respiratory physiological index of the aerobic endurance of the body, especially for special groups such as drug addicts, and it is an important indicator for assessing the cardiopulmonary function and formulating exercise prescriptions. Although the cardiopulmonary exercise test (CPX) is a classic method to directly measure VO2max, this method is limited by factors such as cumbersome operating procedures and expensive equipment, resulting in its relatively low applicability. Recently, many studies have begun to focus on the estimation of VO2max in different groups of people, but few studies have focused on drug addicts. Methods: Fifteen chemically synthesized drug addicts (such as amphetamines) and Fifteen plant-derived drug addicts (such as heroin) were recruited at the Chongqing Compulsory Isolation and Drug Rehabilitation Center in China. First, the VO2max of subjects was directly measured through the CPX. Second, after subjects were fully rested, they were required to complete the 30-s high-leg raise, 1,000-m walk, and 3-min step experiment. Finally, SPSS 21.0 software was used to perform the correlation and linear regression analysis to verify the estimated effectiveness. Results: (1) Regardless of chemically synthesized or natural plant-derived drug addicts, the years of drug use and walking time of 1,000 m were significantly negatively correlated with VO2max (chemically synthesized: P < 0.01 and natural plant-derived: P < 0.05), the number of 30-s high-leg raises was a significantly positive correlation with VO2max (P < 0.05 and P < 0.01), and the 3-min step index was significantly positively correlated with VO2max (P < 0.01 and P < 0.01). (2) Regression analysis shows that the 30-s high-leg lift, 1,000-m walking, and 3-min step experiment could effectively estimate the VO2max of chemically synthesized and natural plant-derived drug addicts. (3) Multiple linear regression constructed by the years of drug use combined with the step index has the highest estimated accuracy for the VO2max of chemically synthesized drug addicts (96.48%), while the unary regression equation established by a single step index has the highest prediction accuracy for the VO2max of natural plant-derived addicts (94.30%). Conclusion: The indirect measurement method could effectively estimate the VO2max of drug addicts, but different measurement methods have certain differences in the estimation accuracy of VO2max of different drug addicts. In the future, the physical characteristics of drug users can be fully considered, combined with more cutting-edge science and technology, to make the estimation accuracy of VO2max closer to the real level.

The Effect of Physical Activity on Drug Cravings of Drug Addicts With AIDS: The Dual Mediating Effect of Internal Inhibition.

BACKGROUND: As a global infectious disease, Acquired Immune Deficiency Syndrome (AIDS) poses a serious threat to the safety and health of the society. In recent years, the proportion of drug addicts infected with HIV has been increased, and drug addicts became one of the main carriers of the spread of AIDS, which has attracted worldwide attention. It has been reported that physical activity has positive effects on improving the inhibitory function of drug addicts and reducing their drug craving, but the mechanism of the internal inhibition remains to be further explored. METHOD: The drug addicts in an AIDS treatment center in Chongqing were investigated by means of a Physical Activity Rating Scale (PARS - 3), Internal Inhibition Scale and Drug Craving Scale, and a structural equation model was established. RESULTS: (1) There is no gender difference in the internal inhibition and drug craving of drug addicts with AIDS, and there are significant differences across the types and years of drug abuse. (2) The amount of physical activity in drug addicts with AIDS is positively correlated with the intrinsic inhibition, while the internal inhibition is negatively correlated with the drug craving, and the physical exercise amount is negatively correlated with the drug craving. The years of drug abuse were negatively correlated with internal inhibition and positively correlated with drug craving. (3) Internal inhibition plays a partly mediatory role between the physical activity amount and the craving for drugs, and internal inhibition plays a partly mediatory role between the number of years of drug abuse and the craving for drugs, which indicates that internal inhibition has a dual mediating effect. CONCLUSION: Actively participate in physical activity, especially high-intensity physical activity, can effectively enhance the internal inhibition of drug addicts with AIDS and reduce their drug craving. Meanwhile, the difference in the drug-taking years among addicts should be paid attention to, and the physical activity prescription should be formulated according to the actual situation.

CNN Training with Twenty Samples for Crack Detection via Data Augmentation.

The excellent generalization ability of deep learning methods, e.g., convolutional neural networks (CNNs), depends on a large amount of training data, which is difficult to obtain in industrial practices. Data augmentation is regarded commonly as an effective strategy to address this problem. In this paper, we attempt to construct a crack detector based on CNN with twenty images via a two-stage data augmentation method. In detail, nine data augmentation methods are compared for crack detection in the model training, respectively. As a result, the rotation method outperforms these methods for augmentation, and by an in-depth exploration of the rotation method, the performance of the detector is further improved. Furthermore, data augmentation is also applied in the inference process to improve the recall of trained models. The identical object has more chances to be detected in the series of augmented images. This trick is essentially a performance-resource trade-off. For more improvement with limited resources, the greedy algorithm is adopted for searching a better combination of data augmentation. The results show that the crack detectors trained on the small dataset are significantly improved via the proposed two-stage data augmentation. Specifically, using 20 images for training, recall in detecting the cracks achieves 96% and Fext(0.8), which is a variant of F-score for crack detection, achieves 91.18%.

An Experimental Study of Step Test Index Combined With Heart Rate Variability in Estimating Maximum Oxygen Uptake in Women With Drug Use Disorder.

BACKGROUND: Maximal oxygen uptake (VO2max), a vital physiological indicator, has been widely used in many fields. In recent years, the measurement method of VO2max has been widely explored in various populations, but few studies have been conducted for women drug abusers. For the importance of VO2max in the formulation of aerobic exercise intensity for drug users, the present study estimated VO2max using the step test index combined with heart rate variability in women with drug use disorder. METHODS: Forty women methamphetamine (MA) users without cardiovascular disease and dyskinesia participated in a cardiopulmonary exercise test (CPX) and a 3-minute step test. Each of them performed a heart rate variability (HRV) monitoring test after the step test, and VO2max was estimated by step test index and HRV. RESULTS: (1) The step test index had a significant positive correlation with VO2max. The standard deviation of normal-to-normal interval (SDNN) had a significant positive correlation with VO2max and a significant positive correlation with the step test index; (2) the R-square values of the estimated VO2max by step test index and post-SDNN for overall MA users were 0.29 and 0.22, with an accuracy of 93.19 and 92.85%, respectively; (3) the R-square values of the estimated VO2max by step test index and post-SDNN in group I were 0.27 and 0.36, respectively, with an accuracy of 94.04 and 93.99%. The R-square value of the estimated VO2max by step test index in group II was 0.44, with an accuracy of 92.65%, however, post-SDNN cannot adequately estimate the VO2max in group II; and (4) there was no significant difference in VO2max obtained by CPX, step test index, or post-SDNN, regardless of overall or grouping variable analysis. CONCLUSION: The 3-minute step test combined with HRV can estimate the VO2max of women MA users to a certain extent, but the size and the coverage of the sample size should be further considered. In the future, more methods, such as machine learning or artificial neural networks, should be used.

MICAL-L2 potentiates Cdc42-dependent EGFR stability and promotes gastric cancer cell migration.

Enhanced migration potential is a common characteristic of cancer cells induced by mechanisms that are incompletely defined. The present study was designed to investigate relationship of a new discovered cytoskeleton regulator MICAL-L2 and the endogenous epidermal growth factor receptor (EGFR) signalling pathways in gastric cancer cell migration. Increased expression of MICAL-L2 in gastric cancer cells up-regulated EGFR protein level, accompanied by the increase of cell migration, whereas silencing MICAL-L2 down-regulated EGFR and inhibited cell migration. Expression of MICAL-L2 was also shown positively correlated with the activation of HSP27/cytoskeleton and HSP27/ß-catenin signalling pathways that provide key mechanisms controlling cell migration. The up-regulating effect of MICAL-L2 on EGFR is mediated through a transcription-independent mechanism that involves inhibiting EGFR protein degradation in lysosome. Further analysis indicated that Cdc42 activation contributed in maintaining the effect of MICAL-L2 on EGFR stability. Furthermore analysis of clinic specimens revealed increased expression of MICAL-L2 in carcinoma tissues and a positive correlation between MICAL-L2 and EGFR expression levels. The above results indicate that MICAL-L2 potentiates gastric cell migration via inhibiting EGFR degradation in lysosome via a Cdc42-dependent manner that leads to the activation of EGFR/HSP27 signalling pathways.

NEDD9 Facilitates Hypoxia-Induced Gastric Cancer Cell Migration via MICAL1 Related Rac1 Activation.

Aims and Hypothesis: NEDD9 is highly expressed in gastric cancer and has a significant involvement in its pathogenesis. However, the mechanism behind hypoxia-promoted cancer cell migration and its regulation because of NEDD9 is still unknown. The aim of this study is to investigate the involvement of NEDD9 in gastric cancer cell migration under hypoxia and explore the underlying potential molecular mechanisms. METHODS: Cell motility was measured by wound healing and transwell assay. NEDD9 and MICAL1 expressions were examined by western blot analysis. Interaction between NEDD9 and MICAL1 was assessed by immunohistochemistry and co-immunoprecipitation assay, respectively. Cells were transfected with plasmids or siRNA to upregulate or downregulate the expression of NEDD9 and MICAL1. Rac1, Cdc42, and RhoA activation was assessed by pulldown assay. RESULTS: The mRNA and protein level of NEDD9 increased as a result of hypoxia in gastric cancer cell lines BGC-823 and SGC-7901 while decreased levels of NEDD9 caused reduced cell migratory potential in response to hypoxia. Hypoxia also caused the enhancement of MICAL1 expression. Furthermore, it was revealed that there is a positive correlation between NEDD9 and MICAL1 protein while hypoxia played role in increasing their interaction. Under hypoxic conditions, silencing of NEDD9 caused reduction in the stability of MICAL1 protein, while depletion of MICAL1 also inhibited the migration of NEDD9-overexpressing gastric cancer cells. In addition, silencing of NEDD9 or MICAL1 expression reversed the increased GTP forms of Rac1 and Cdc42 in hypoxic cells. However, only the upregulation of Rac1-GTP level was observed in gastric cancer cells that were already overexpressed by MICAL1. CONCLUSION: In all, it is concluded that MICAL1 is regulated by NEDD9 that facilitates hypoxia-induced gastric cancer cell migration via Rac1-dependent manner.

Adaptive Fifth-Degree Cubature Information Filter for Multi-Sensor Bearings-Only Tracking.

Standard Bayesian filtering algorithms only work well when the statistical properties of system noises are exactly known. However, this assumption is not always plausible in real target tracking applications. In this paper, we present a new estimation approach named adaptive fifth-degree cubature information filter (AFCIF) for multi-sensor bearings-only tracking (BOT) under the condition that the process noise follows zero-mean Gaussian distribution with unknown covariance. The novel algorithm is based on the fifth-degree cubature Kalman filter and it is constructed within the information filtering framework. With a sensor selection strategy developed using observability theory and a recursive process noise covariance estimation procedure derived using the covariance matching principle, the proposed filtering algorithm demonstrates better estimation accuracy and filtering stability. Simulation results validate the superiority of the AFCIF.