Patterned nanofiber air filters with high optical transparency, robust mechanical strength, and effective PM_(2.5) capture capability

PM_(2.5), due to its small particle size, strong activity, ease of the attachment of toxic substances and long residence time in the atmosphere, has a great impact on human health and daily production. In this work, we have presented patterned nanofiber air filters with high optical transparency, robust mechanical strength and effective PM_(2.5) capture capability. Here, to fabricate a transparency air filter by a facile electrospinning method, we chose three kinds of patterned wire meshes with micro-structures as negative receiver substrates and directly electrospun polymer fibers onto the supporting meshes. Compared with randomly oriented nanofibers (named “RO NFs” in this paper) and commercially available facemasks, the patterned air filters showed great mechanical properties, and the water contact angles on their surfaces were about 122–143° (the water contact angle for RO NFs was 81°). In addition, the patterned nanofibers exhibited high porosity (>80%), and their mean pore size was about 0.5838–0.8686 μm (the mean pore size of RO NFs was 0.4374 μm). The results indicate that the transparent patterned air filters have the best PM_(2.5) filtration efficiency of 99.99% at a high transmittance of ∼69% under simulated haze pollution

Patterned nanofiber air filters with high optical transparency, robust mechanical strength, and effective PM_(2.5) capture capability

PM_(2.5), due to its small particle size, strong activity, ease of the attachment of toxic substances and long residence time in the atmosphere, has a great impact on human health and daily production. In this work, we have presented patterned nanofiber air filters with high optical transparency, robust mechanical strength and effective PM_(2.5) capture capability. Here, to fabricate a transparency air filter by a facile electrospinning method, we chose three kinds of patterned wire meshes with micro-structures as negative receiver substrates and directly electrospun polymer fibers onto the supporting meshes. Compared with randomly oriented nanofibers (named “RO NFs” in this paper) and commercially available facemasks, the patterned air filters showed great mechanical properties, and the water contact angles on their surfaces were about 122–143° (the water contact angle for RO NFs was 81°). In addition, the patterned nanofibers exhibited high porosity (>80%), and their mean pore size was about 0.5838–0.8686 μm (the mean pore size of RO NFs was 0.4374 μm). The results indicate that the transparent patterned air filters have the best PM_(2.5) filtration efficiency of 99.99% at a high transmittance of ∼69% under simulated haze pollution

Study on perception threshold for whole-body vibration

When people stay in the vibrating environment for a long time, the body may produce a series of physiological and psychological diseases. In order to evaluate the impact of vibration on the human body, the establishment of evaluation method or evaluation system is necessary. At present, most countries usually evaluate whole-body vibration based on the international standard ISO 2631-1 “Mechanical vibration and shock-Evaluation of human exposure to whole-body vibration-Part 1: General requirements”. In this paper, the experiments of perception threshold of whole-body vibration were taken as the breakthrough point of evaluation method, and 12 subjects participated in the experiments. Through the experiments, comparing the provisions of ISO 2631-1, we get some different conclusions about the distribution law of perception thresholds. This also provides some data support for further experimental research

Monitoring marine pollution for carbon neutrality through a deep learning method with multi-source data fusion

IntroductionMarine pollution can have a significant impact on the blue carbon, which finally affect the ocean’s ability to sequester carbon and contribute to achieving carbon neutrality. Marine pollution is a complex problem that requires a great deal of time and effort to measure. Existing machine learning algorithms cannot effectively solve the detection time problem and provide limited accuracy. Moreover, marine pollution can come from a variety of sources. However, most of the existing research focused on a single ocean indicator to analyze marine pollution. In this study, two indicators, marine organisms and debris, are used to create a more complete picture of the extent and impact of pollution in the ocean.MethodsTo effectively recognize different marine objects in the complex marine environment, we propose an integrated data fusion approach where deep convolutional neural networks (CNNs) are combined to conduct underwater object recognition. Through this multi-source data fusion approach, the accuracy of object recognition is significantly improved. After feature extraction, four machine and deep learning classifiers’ performances are used to train on features extracted with deep CNNs.ResultsThe results show that VGG-16 achieves better performance than other feature extractors when detecting marine organisms. When detecting marine debris, AlexNet outperforms other deep CNNs. The results also show that the LSTM classifier with VGG-16 for detecting marine organisms outperforms other deep learning models.DiscussionFor detecting marine debris, the best performance was observed with the AlexNet extractor, which obtained the best classification result with an LSTM. This information can be used to develop policies and practices aimed at reducing pollution and protecting marine environments for future generations

High-performance chiral all-optical logic gate based on topological edge states of valley photonic crystal

For all-optical communication and information processing, it is necessary to develop all-optical logic gates based on photonic structures that can directly perform logic operations. All-optical logic gates have been demonstrated based on conventional waveguides and interferometry, as well as photonic crystal structures. Nonetheless, any defects in those structures will introduce high scattering loss, which compromises the fidelity and contrast ratio of the information process. Based on the spin-valley locking effect that can achieve defect-immune unidirectional transmission of topological edge states in valley photonic crystals (VPCs), we propose a high-performance all-optical logic OR gate based on a VPC structure. By tuning the working bandwidth of the two input channels, we prevent interference between the two channels to achieve a stable and high-fidelity output. The transmittance of both channels is higher than 0.8, and a high contrast ratio of 28.8 dB is achieved. Moreover, the chirality of the logic gate originated from the spin-valley locking effect allows using different circularly polarized light as inputs, representing "1" or "0", which is highly desired in quantum computing. The device's footprint is small, allowing high-density on-chip integration. In addition, this design can be experimentally fabricated using current nanofabrication techniques and will have potential applications in optical communication, information processing, and quantum computing.Comment: 10 pages, 6 figure

Correlation and combining ability analysis of physiological traits and some agronomic traits in maize

Combining ability information on the physiological traits in maize (Zea mays L) and the relationship between physi¬ological traits and biomass, grain yield (GY) and yield components (YC) can help maize breeders design experi¬ments for improving inbred lines and/or developing hybrids with improved GY or YC (GYYC). A six-parent diallel experiment (Griffing method 3) was conducted for combining ability and correlation analyses. The objectives of this study were to 1) study the correlation between physiological traits and biomass at seedling stage; 2) study which physiological traits at seedling stage have significant correlation with biomasses at both seedling and later growth stages and GYYCs; 3) evaluate combining ability of the physiological traits that are significantly correlated with either GY or one of the YCs. Results showed plant heights at 20 day, 40 day, and leaf area were highly corre¬lated with both dry weights of shoots and roots. All chlorophyll-related organelles were significantly correlated with only dry weights of shoots. However, dry matter at seedling stage seemed not to be related to dry matter in later growth stages. Five physiological traits (stomatal conductance, transpiration rate, net photosynthetic rate, two quantum yield related traits) at seedling stage were identified to greatly impact dry matter at later growth stages. Results also showed that 13 out of 35 physiological traits studied were significantly correlated with GYYCs. Differ¬ent germplasms for improving GYYCs could be used based on both correlation between the 13 traits and GYYCs and combining ability effects of each line for the 13 selected traits

Gut microbial biomarkers for the treatment response in first-episode, drug-naive schizophrenia: a 24-week follow-up study

Preclinical studies have shown that the gut microbiota can play a role in schizophrenia (SCH) pathogenesis via the gut-brain axis. However, its role in the antipsychotic treatment response is unclear. Here, we present a 24-week follow-up study to identify gut microbial biomarkers for SCH diagnosis and treatment response, using a sample of 107 first-episode, drug-naive SCH patients, and 107 healthy controls (HCs). We collected biological samples at baseline (all participants) and follow-up time points after risperidone treatment (SCH patients). Treatment response was assessed using the Positive and Negative Symptoms Scale total (PANSS-T) score. False discovery rate was used to correct for multiple testing. We found that SCH patients showed lower alpha-diversity (the Shannon and Simpson\u27s indices) compared to HCs at baseline (p = 1.21 x 10(-9), 1.23 x 10(-8), respectively). We also found a significant difference in beta-diversity between SCH patients and HCs (p = 0.001). At baseline, using microbes that showed different abundance between patients and controls as predictors, a prediction model can distinguish patients from HCs with an area under the curve (AUC) of 0.867. In SCH patients, after 24 weeks of risperidone treatment, we observed an increase of alpha-diversity toward the basal level of HCs. At the genus level, we observed decreased abundance of Lachnoclostridium (p = 0.019) and increased abundance Romboutsia (p = 0.067). Moreover, the treatment response in SCH patients was significantly associated with the basal levels of Lachnoclostridium and Romboutsia (p = 0.005 and 0.006, respectively). Our results suggest that SCH patients may present characteristic microbiota, and certain microbiota biomarkers may predict treatment response in this patient population

Clinical characteristics and genetic analysis of pediatric patients with sodium channel gene mutation-related childhood epilepsy: a review of 94 patients

ObjectiveThis study aimed to examine the clinical and gene-mutation characteristics of pediatric patients with sodium channel gene mutation-related childhood epilepsy and to provide a basis for precision treatment and genetic counseling.MethodsThe clinical data from 94 patients with sodium channel gene mutation-related childhood epilepsy who were treated at Hunan Children's Hospital from August 2012 to December 2022 were retrospectively evaluated, and the clinical characteristics, gene variants, treatment, and follow-up status were analyzed and summarized.ResultsOur 94 pediatric patients with sodium channel gene variant-related childhood epilepsy comprised 37 girls and 57 boys. The age of disease onset ranged from 1 day to 3 years. We observed seven different sodium channel gene variants, and 55, 14, 9, 6, 6, 2, and 2 patients had SCNlA, SCN2A, SCN8A, SCN9A, SCN1B, SCN11A, and SCN3A variants, respectively. We noted that 52 were reported variants and 42 were novel variants. Among all gene types, SCN1A, SCN2A, and SCN8A variants were associated with an earlier disease onset age. With the exception of the SCN1B, the other six genes were associated with clustering seizures. Except for variants SCN3A and SCN11A, some patients with other variants had status epilepticus (SE). The main diagnosis of children with SCN1A variants was Dravet syndrome (DS) (72.7%), whereas patients with SCN2A and SCN8A variants were mainly diagnosed with various types of epileptic encephalopathy, accounting for 85.7% (12 of 14) and 88.9% (8 of 9) respectively. A total of five cases of sudden unexpected death in epilepsy (SUDEP) occurred in patients with SCN1A, SCN2A, and SCN8A variants. The proportion of benign epilepsy in patients with SCN9A, SCN11A, and SCN1B variants was relatively high, and the epilepsy control rate was higher than the rate of other variant types.ConclusionSodium channel gene variants involve different epileptic syndromes, and the treatment responses also vary. We herein reported 42 novel variants, and we are also the first ever to report two patients with SCN11A variants, thereby increasing the gene spectrum and phenotypic profile of sodium channel dysfunction. We provide a basis for precision treatment and prognostic assessment

The Modulatory Properties of Astragalus membranaceus Treatment on Triple-Negative Breast Cancer: An Integrated Pharmacological Method.

Background: Studies have shown that the natural products of Astragalus membranaceus (AM) can effectively interfere with a variety of cancers, but their mechanism of action on breast cancer remains unclear. Triple-negative breast cancer (TNBC) is associated with a severely poor prognosis due to its invasive phenotype and lack of biomarker-driven-targeted therapies. In this study, the potential mechanism of the target composition acting on TNBC was explored by integrated pharmacological models and in vitro experiments. Materials and Methods: Based on the Gene Expression Omnibus (GEO) database and the relational database of Traditional Chinese Medicines (TCMs), the drug and target components were initially screened to construct a common network module, and multiattribute analysis was then used to characterize the network and obtain key drug-target information. Furthermore, network topology analysis was used to characterize the betweenness and closeness of key hubs in the network. Molecular docking was used to evaluate the affinity between compounds and targets and obtain accurate combination models. Finally, in vitro experiments verified the key component targets. The cell counting kit-8 (CCK-8) assay, invasion assay, and flow cytometric analysis were used to assess cell viability, invasiveness, and apoptosis, respectively, after Astragalus polysaccharides (APS) intervention. We also performed western blot analysis of key proteins to probe the mechanisms of correlated signaling pathways. Results: We constructed "compound-target" (339 nodes and 695 edges) and "compound-disease" (414 nodes and 6458 edges) networks using interaction data. Topology analysis and molecular docking were used as secondary screens to identify key hubs of the network. Finally, the key component APS and biomarkers PIK3CG, AKT, and BCL2 were identified. The in vitro experimental results confirmed that APS can effectively inhibit TNBC cell activity, reduce invasion, promote apoptosis, and then counteract TNBC symptoms in a dose-dependent manner, most likely by inhibiting the PIK3CG/AKT/BCL2 pathway. Conclusion: This study provides a rational approach to discovering compounds with a polypharmacology-based therapeutic value. Our data established that APS intervenes with TNBC cell invasion, proliferation, and apoptosis via the PIK3CG/AKT/BCL2 pathway and could thus offer a promising therapeutic strategy for TNBC