A novel approach for ASD recognition based on graph attention networks.

Early detection and diagnosis of Autism Spectrum Disorder (ASD) can significantly improve the quality of life for affected individuals. Identifying ASD based on brain functional connectivity (FC) poses a challenge due to the high heterogeneity of subjects' fMRI data in different sites. Meanwhile, deep learning algorithms show efficacy in ASD identification but lack interpretability. In this paper, a novel approach for ASD recognition is proposed based on graph attention networks. Specifically, we treat the region of interest (ROI) of the subjects as node, conduct wavelet decomposition of the BOLD signal in each ROI, extract wavelet features, and utilize them along with the mean and variance of the BOLD signal as node features, and the optimized FC matrix as the adjacency matrix, respectively. We then employ the self-attention mechanism to capture long-range dependencies among features. To enhance interpretability, the node-selection pooling layers are designed to determine the importance of ROI for prediction. The proposed framework are applied to fMRI data of children (younger than 12 years old) from the Autism Brain Imaging Data Exchange datasets. Promising results demonstrate superior performance compared to recent similar studies. The obtained ROI detection results exhibit high correspondence with previous studies and offer good interpretability.

Upregulation of circRNA_0023685 promotes gastric cancer progression via a circRNA-miRNA-mRNA interaction network.

Circular RNAs (circRNAs) have been extensively studied for their critical roles as noncoding RNAs (ncRNAs) in gastric cancer (GC). In this study, we focused on the expression, function and molecular mechanism of circRNA_0023685 in gastric cancer (GC) to provide new ways for the diagnosis and treatment of GC. Firstly, a novel differentially expressed circRNA, circRNA_0023685, was identified, and its differential expression in GC plasma, tissue, and cell lines was further verified by RT-qPCR. Next, circRNA_0023685 was verified to promote the proliferation, migration and apoptosis of GC cells in vitro. CircRNA_0023685 was also proved to enhance the growth of GC tumors in xenograft models. Finally, for excavating the mechanism to promote GC, downstream microRNAs (miRNAs) and mRNAs were screened by bioinformatics analyses. After intersecting the target genes and genes enriched in GO analysis, a circRNA competing endogenous RNAs (ceRNAs) network was built. A protein-protein interaction (PPI) network was then constructed to find the candidate gene, APP. Our study confirmed that the highly expressed circRNA_0023685 could promote GC, which provided a new clinical diagnostic biomarker and therapeutic target for GC.

One amino acid drives the lipid droplet targeting sequence of a new noncoding RNA-encoded protein to mitochondrion.

Over the past decade, the majority of the mammalian genome considered to be noncoding has been revealed to be able to produce proteins. Many RNA molecules, mis-annotated as noncoding, actually are predicted to code for proteins. Some of those proteins have been identified and verified to play critical roles in multiple biological processes. The lipid droplet (LD) is a unique cellular organelle bound with a phospholipid monolayer membrane, and is closely associated with cellular lipid metabolism and metabolic disorders. However, it is still unclear how a protein targets to LDs. Here we identified a new protein on LDs, LDANP2, which is encoded by noncoding RNA, through a proteomics-based strategy. The key sequence for its localization on LDs, Truncation 3, is predicted to form an amphipathic helix. Surprisingly, the deletion of the first amino acid in Truncation 3 resulted in mitochondrial localization. How the types of amino acids would determine the LD or mitochondrial localizations of the protein was studied. The findings introduce a useful strategy to mine for new proteins and would provide clues to the understanding of how a protein would find its right organelle, with phospholipid monolayer or bilayer membrane.

Protein sample preparation for tissue distribution study.

PURPOSE: The distribution and expression level of a protein among animal tissues is indicative of its possible roles. It is important to establish a generally applicable method to prepare protein samples with high-quality and achieve near 100% recovery of proteins from animal tissues. EXPERIMENTAL DESIGN: During preparation, to sufficiently dissolve and maintain stability of almost all proteins from tissues, as well as to avoid most contaminations affecting protein detection, 2×SDS Sample Buffer, sonication and trichloroacetic acid precipitation are applied. RESULTS: Here we provide a relatively simple, reproducible, and broadly applicable method for studying protein distribution in most tissues, in which the issues resulting from protein degradation and modification during sample preparation and assay interference by other cellular components like neutral lipids and glycogen could be overcome. Furthermore, this method represents the protein content by equal wet tissue mass, which is a better means to present the expression level of a protein in various tissues. High-quality protein samples from almost all tissues could be prepared. CONCLUSIONS AND CLINICAL RELEVANCE: The samples produced are amenable to tissue distribution analysis by Western blotting and for silver/Coomassie staining, proteomics, and other protein analyses, which would contribute to potential biomarkers or treatments for a disease.

P2X1 enhances leukemogenesis through PBX3-BCAT1 pathways.

How bone marrow niches regulate leukemogenic activities of leukemia-initiating cells (LICs) is unclear. The present study revealed that the metabolic niche component, ATP, efficiently induced ion influx in LICs through its ligand-gated ion channel, P2X1. P2X1 deletion impaired LIC self-renewal capacities and resulted in an approximately 8-fold decrease in functional LIC numbers in a murine acute myeloid leukemia (AML) model without affecting normal hematopoiesis. P2X1 phosphorylation at specific sites of S387 and T389 was essential for sustaining its promoting effects on leukemia development. ATP-P2X1-mediated signaling upregulated the PBX3 level to transactivate BCAT1 to maintain LIC fates. P2X1 knockdown inhibited the proliferation of both human AML cell lines and primary cells. The P2X1 antagonist sufficiently suppressed AML cell proliferation. These results provided a unique perspective on how metabolic niche factor ATP fine-tunes LIC activities, which may benefit the development of strategies for targeting LICs or other cancer stem cells.

Supervised and Semisupervised Manifold Embedded Knowledge Transfer in Motor Imagery-Based BCI.

A long calibration procedure limits the use in practice for a motor imagery (MI)-based brain-computer interface (BCI) system. To tackle this problem, we consider supervised and semisupervised transfer learning. However, it is a challenge for them to cope with high intersession/subject variability in the MI electroencephalographic (EEG) signals. Based on the framework of unsupervised manifold embedded knowledge transfer (MEKT), we propose a supervised MEKT algorithm (sMEKT) and a semisupervised MEKT algorithm (ssMEKT), respectively. sMEKT only has limited labelled samples from a target subject and abundant labelled samples from multiple source subjects. Compared to sMEKT, ssMEKT adds comparably more unlabelled samples from the target subject. After performing Riemannian alignment (RA) and tangent space mapping (TSM), both sMEKT and ssMEKT execute domain adaptation to shorten the differences among subjects. During domain adaptation, to make use of the available samples, two algorithms preserve the source domain discriminability, and ssMEKT preserves the geometric structure embedded in the labelled and unlabelled target domains. Moreover, to obtain a subject-specific classifier, sMEKT minimizes the joint probability distribution shift between the labelled target and source domains, whereas ssMEKT performs the joint probability distribution shift minimization between the unlabelled target domain and all labelled domains. Experimental results on two publicly available MI datasets demonstrate that our algorithms outperform the six competing algorithms, where the sizes of labelled and unlabelled target domains are variable. Especially for the target subjects with 10 labelled samples and 270/190 unlabelled samples, ssMEKT shows 5.27% and 2.69% increase in average accuracy on the two abovementioned datasets compared to the previous best semisupervised transfer learning algorithm (RA-regularized common spatial patterns-weighted adaptation regularization, RA-RCSP-wAR), respectively. Therefore, our algorithms can effectively reduce the need of labelled samples for the target subject, which is of importance for the MI-based BCI application.

Hydraulic constraints determine the distribution of heteromorphic leaves along plant vertical height.

As an interesting and important trait of some drought-tolerant species, heteromorphic leaves are distributed differentially along plant vertical heights. However, the underpinning mechanism for the formation of heteromorphic leaves remains unclear. We hypothesize that heteromorphic leaves are caused by the hydraulic constraints possibly due to the compensation of the changes in functional traits in response to water transport capacity or the reduction of ineffective water loss. In this study, differences in water transport capacity, morphological traits, anatomical structures, and cellular water relations among three typical types of heteromorphic leaves (i.e., lanceolate, ovate, and broad-ovate) of Populus euphratica Oliv. (a dominant species of desert riparian forest in Central and West Asia) and their relationships were analyzed in order to explore the forming mechanism of heteromorphic leaves. The results showed that the lanceolate, ovate, and broad-ovate leaves were growing in the lower, intermediate, and higher positions from the ground, respectively. Morphological traits, anatomical structures, cellular water relations, and water transport capacity significantly varied among the three types of heteromorphic leaves (P< 0.01). Drought stress in broad-ovate leaves was significantly higher than that in ovate and lanceolate leaves (P< 0.01). Water transport capacity has significant correlations with morphological traits, anatomical structures, and cellular water relations (R 2 ≥ 0.30; P< 0.01). Our results indicated that heteromorphic leaves were used as an important adaptive strategy for P. euphratica to alleviate the increase of hydraulic constraints along vertical heights.

Selective Cross-Subject Transfer Learning Based on Riemannian Tangent Space for Motor Imagery Brain-Computer Interface.

A motor imagery (MI) brain-computer interface (BCI) plays an important role in the neurological rehabilitation training for stroke patients. Electroencephalogram (EEG)-based MI BCI has high temporal resolution, which is convenient for real-time BCI control. Therefore, we focus on EEG-based MI BCI in this paper. The identification of MI EEG signals is always quite challenging. Due to high inter-session/subject variability, each subject should spend long and tedious calibration time in collecting amounts of labeled samples for a subject-specific model. To cope with this problem, we present a supervised selective cross-subject transfer learning (sSCSTL) approach which simultaneously makes use of the labeled samples from target and source subjects based on Riemannian tangent space. Since the covariance matrices representing the multi-channel EEG signals belong to the smooth Riemannian manifold, we perform the Riemannian alignment to make the covariance matrices from different subjects close to each other. Then, all aligned covariance matrices are converted into the Riemannian tangent space features to train a classifier in the Euclidean space. To investigate the role of unlabeled samples, we further propose semi-supervised and unsupervised versions which utilize the total samples and unlabeled samples from target subject, respectively. Sequential forward floating search (SFFS) method is executed for source selection. All our proposed algorithms transfer the labeled samples from most suitable source subjects into the feature space of target subject. Experimental results on two publicly available MI datasets demonstrated that our algorithms outperformed several state-of-the-art algorithms using small number of the labeled samples from target subject, especially for good target subjects.

Function of the P2X7 receptor in hematopoiesis and leukemogenesis.

Adenosine triphosphate (ATP) accumulates at tissue injury and inflammation sites. The P2X7 receptor is an ATP-gated ion channel known for its cytotoxic activity. However, P2X7 receptors also play important roles in the growth of cancer and the immune regulation. Functional P2X7 receptor is widely expressed in murine and human hematopoietic stem cells and their lineages, including monocytes, macrophages, mast cells, and B or T lymphocytes, and participates in various physiological and pathologic activities. Therefore, it is not surprising that the P2X7 receptor is important for the normal hematopoiesis and leukemogenesis. Here, we summarize the biological functions of P2X7 receptor during both normal hematopoiesis and leukemogenesis. In particular, we found that ATP levels are dramatically increased in the leukemic bone marrow niche and the fates of leukemia-initiating cells of acute myeloid leukemia are tightly controlled by P2X7 expression and ATP-P2X7-mediated signaling pathways. These findings strongly indicate that the P2X7 receptor may be considered a potential biomarker of hematological malignancies in bone marrow niches, and its antagonists may be useful for the leukemia treatment in addition to the traditional chemotherapy.

A Review on Signal Processing Approaches to Reduce Calibration Time in EEG-Based Brain-Computer Interface.

In an electroencephalogram- (EEG-) based brain-computer interface (BCI), a subject can directly communicate with an electronic device using his EEG signals in a safe and convenient way. However, the sensitivity to noise/artifact and the non-stationarity of EEG signals result in high inter-subject/session variability. Therefore, each subject usually spends long and tedious calibration time in building a subject-specific classifier. To solve this problem, we review existing signal processing approaches, including transfer learning (TL), semi-supervised learning (SSL), and a combination of TL and SSL. Cross-subject TL can transfer amounts of labeled samples from different source subjects for the target subject. Moreover, Cross-session/task/device TL can reduce the calibration time of the subject for the target session, task, or device by importing the labeled samples from the source sessions, tasks, or devices. SSL simultaneously utilizes the labeled and unlabeled samples from the target subject. The combination of TL and SSL can take advantage of each other. For each kind of signal processing approaches, we introduce their concepts and representative methods. The experimental results show that TL, SSL, and their combination can obtain good classification performance by effectively utilizing the samples available. In the end, we draw a conclusion and point to research directions in the future.

Regulation PP2Ac methylation ameliorating autophagy dysfunction caused by Mn is associated with mTORC1/ULK1 pathway.

Manganese (Mn) exposure leads to autophagy dysfunction and causes neurodegenerative diseases such as Parkinson's syndrome and Alzheimer's disease. However, the mechanism of neurotoxicity of Mn has been less clear. The methylation of the protein phosphatase 2A catalytic subunit determines the dephosphorylation activity of protein phosphatase and plays an important role in autophagy regulation. In this investigation, we established a model of Mn (0-2000 µmol/L) exposure to N2a cells for 12 h, used the PPME-1 inhibitor ABL-127, and constructed an LCMT1-overexpressing N2a cell line. We also regulated the PP2Ac methylation level and explored the effect of PP2Ac methylation on Mn-induced (0-1000 µmol/L) N2a cellular autophagy. Our results showed that Mn > 500 µmol/L induced N2a cell damage and increased oxidative stress. Moreover, Mn modulated autophagy in N2a cells by downregulating PP2Ac methylation, which regulated mTORC1 signaling pathway activation. Both ABL-127 and LCMT1 overexpression can upregulate PP2Ac methylation in parallel with ameliorating N2a cell abnormal autophagy induced by Mn, Briefly, the upregulation of PP2Ac methylation can ameliorate the autophagy disorder of N2a by Mn and effectively alleviate Mn-induced cytotoxicity and oxidative stress, indicating that regulation of autophagy is a protective strategy against Mn-induced neurotoxicity.

Person image generation through graph-based and appearance-decomposed generative adversarial network.

Due to the sophisticated entanglements for non-rigid deformation, generating person images from source pose to target pose is a challenging work. In this paper, we present a novel framework to generate person images with shape consistency and appearance consistency. The proposed framework leverages the graph network to infer the global relationship of source pose and target pose in a graph for better pose transfer. Moreover, we decompose the source image into different attributes (e.g., hair, clothes, pants and shoes) and combine them with the pose coding through operation method to generate a more realistic person image. We adopt an alternate updating strategy to promote mutual guidance between pose modules and appearance modules for better person image quality. Qualitative and quantitative experiments were carried out on the DeepFashion dateset. The efficacy of the presented framework are verified.

Methionine-Mediated Protein Phosphatase 2A Catalytic Subunit (PP2Ac) Methylation Ameliorates the Tauopathy Induced by Manganese in Cell and Animal Models.

The molecular mechanism of Alzheimer-like cognitive impairment induced by manganese (Mn) exposure has not yet been fully clarified, and there are currently no effective interventions to treat neurodegenerative lesions related to manganism. Protein phosphatase 2 A (PP2A) is a major tau phosphatase and was recently identified as a potential therapeutic target molecule for neurodegenerative diseases; its activity is directed by the methylation status of the catalytic C subunit. Methionine is an essential amino acid, and its downstream metabolite S-adenosylmethionine (SAM) participates in transmethylation pathways as a methyl donor. In this study, the neurotoxic mechanism of Mn and the protective effect of methionine were evaluated in Mn-exposed cell and rat models. We show that Mn-induced neurotoxicity is characterized by PP2Ac demethylation accompanied by abnormally decreased LCMT-1 and increased PME-1, which are associated with tau hyperphosphorylation and spatial learning and memory deficits, and that the poor availability of SAM in the hippocampus is likely to determine the loss of PP2Ac methylation. Importantly, maintenance of local SAM levels through continuous supplementation with exogenous methionine, or through specific inhibition of PP2Ac demethylation by ABL127 administration in vitro, can effectively prevent tau hyperphosphorylation to reduce cellular oxidative stress, apoptosis, damage to cell viability, and rat memory deficits in cell or animal Mn exposure models. In conclusion, our data suggest that SAM and PP2Ac methylation may be novel targets for the treatment of Mn poisoning and neurotoxic mechanism-related tauopathies.

Time-weighted average of fine particulate matter exposure and cause-specific mortality in China: a nationwide analysis.

BACKGROUND: Most previous assessments of the hazardous effects attributable to fine particulate matter (PM2·5) exposure have used ambient PM2·5 as an exposure metric, resulting in substantial bias in effect estimates. We did a study to examine the association between cause-specific mortality and the time-weighted average of PM2·5 exposure after accounting for indoor exposure in 267 cities in China. METHODS: We did a nationwide study, using Laser Egg air quality monitors in 36 cities to obtain data for indoor PM2·5 concentrations from 18 484 anonymised households between Nov 1, 2015 and July 2, 2018. We developed and validated a nationwide indoor PM2·5 prediction model for a further 302 cities by retrieving raw records of hourly concentrations from residents' air sensors; the model was used to predict indoor PM2·5 during 2013 to 2018. Daily ambient PM2·5 concentration data were estimated by averaging hourly ambient PM2·5 concentrations obtained from China's National Urban Air Quality Real-time Publishing Platform. Daily numbers of deaths from all non-accidental causes were obtained from 324 cities from the Disease Surveillance Point System of China between Jan 1, 2013, to Dec 31, 2017, and calculated for 267 cities that had an average daily mortality above three, and data for PM2·5 concentrations and meteorological information for at least 1 year between 2013 and 2017. We used distributed lag non-linear models to estimate city-specific associations between cause-specific mortality and reconstructed PM2·5 exposure by considering indoor PM2·5 exposure. We combined the city-specific effect estimates at the national level using a random effects meta-analysis. FINDINGS: 13 972 records of daily indoor PM2·5 concentrations for 36 cities, extracted from 47 459 183 raw records from the sensors were included for modelling indoor PM2·5 levels. The nationwide indoor PM2·5 concentration was 40 µg/m3 (SD 21) between 2013 and 2017, which was approximately 20% lower than the ambient PM2·5 concentration of 50 µg/m3 (42). An increase of 10 µg/m3 in time-averaged PM2·5 exposure concentrations was associated with increased daily mortality estimates of 0·44% (95% CI 0·33-0·54) for total non-accidental causes, 0·50% (0·37-0·63) for cardiovascular diseases, 0·46% (0·28-0·63) for coronary heart disease, 0·49% (0·32-0·66) for stroke, 0·59% (0·39-0·79) for respiratory diseases, and 0·69% (0·45-0·92) for chronic obstructive pulmonary disease, respectively. Compared with previous estimations based on ambient PM2·5, our estimates approximately doubled the size of the effects related to PM2·5. INTERPRETATION: This nationwide study revealed a higher mortality risk attributed to time-averaged indoor and ambient PM2·5 exposure compared with the risk associated with ambient PM2·5 exposure alone, which indicates that caution should be exercised when using ambient PM2·5 as a surrogate for PM2·5 exposure. FUNDING: National Natural Science Foundation of China (Youth Program) and the Fundamental Research Project of Beihang University.

Inactivation of antibiotic-resistant bacteria and antibiotic resistance genes by electrochemical oxidation/electro-Fenton process.

Antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in the environment are of great concern due to their potential risk to human health. The effluents from wastewater treatment plants and livestock production are major sources of ARB and ARGs. Chlorination, UV irradiation, and ozone disinfection cannot remove ARGs completely. In this study, the potential of electrochemical oxidation and electro-Fenton processes as alternative treatment technologies for inactivation of ARB and ARGs in both intracellular and extracellular forms was evaluated. Results showed that the electrochemical oxidation process was effective for the inactivation of selected ARB but not for the removal of intracellular ARGs or extracellular ARGs. The electro-Fenton process was more effective for the removal of both intracellular and extracellular ARGs. The removal efficiency after 120 min of electro-Fenton treatment under 21.42 mA/cm2 was 3.8 logs for intracellular tetA, 4.1 logs for intracellular ampC, 5.2 logs for extracellular tetA, and 4.8 logs for extracellular ampC, respectively in the presence of 1.0 mmol/L Fe2+. It is suggested that electrochemical oxidation is an effective disinfection method for ARB and the electro-Fenton process is a promising technology for the removal of both intracellular and extracellular ARGs in wastewater.

[Expression, purification and functional assessment of asprosin inclusion body].

OBJECTIVE: The obtain purified recombinant asprosin and test its functions. METHODS: The recombinant plasmid of pET-22b-asprosin was constructed and transformed into competent E.coli BL (DE3) strain. After IPTG-induced expression, asprosin inclusion body was renatured by gradient urea and purified by Ni-NTA affinity chromatography column followed by removal of endotoxin to obtain recombinant asprosin for use in cells and animals experiments. C57 mice were injected intraperitoneally with the recombinant asprosin and blood glucose was detected using a blood glucose meter. Alamar Blue assay was used to evaluate of the effect of the recombinant asprosin on the viability of MIHA cells, and cellular glycogen content was detected using the anthrone method. RESULTS: At the absorbance at 600 nm of 0.8, induction of the recombinant host bacteria with 1 mmol/L IPTG at 37 ℃ for 4 h optimally induced the expression of asprosin inclusion body. After purification and endotoxin removal, the purity of the recombinant asprosin exceeded 95% with the content of endotoxin below 1 EU/mg. In C57 mice, intraperitoneal injection with recombinant asprosin significantly increased blood glucose level, which reached the peak level at 60 min following the injection (P=0.021) and recovered the normal level at 120 min (P=0.03). Treatment with the recombinant asprosin for 24 h did not cause obvious adverse effect on the viability of MIHA cells but significantly lowered glycogen content in the cells (P < 0.05). CONCLUSIONS: We successfully obtained recombinant asprosin using a prokaryotic expression system. The recombinant asprosin can decrease glycogen content in MIHA cells and increase blood glucose level in mice.

Systemic toxicity evaluation of novel tobacco products in Caenorhabditis elegans.

Under strictly Framework Convention on Tobacco Control, novel tobacco products are going to be promising alterations to consumers and manufactures. Even though the novel tobacco products have been considered less harmful than traditional tobaccos, there is a few knowledges about the subsequent substances during consume and their impacts to the consumers due to short introduction into the market. Thus, the present study aims to investigate the adverse effects of novel tobacco products on Caenorhabditis elegans(C. elegans) and to provide relevant references for novel tobacco products toxicity research and assessment. C. elegans individuals at L4 stage were exposed to different kinds of novel tobacco products, including electronic cigarettes liquid (e-liquid), the extract of e-cig aerosol (e-aerosol), mint and black tea flavor snus. After specific exposure time, the multiple toxic endpoints of C. elegans were measured, including acute toxicity, locomotion behavior, body length, and life-span. The oxidative stress was tested too. According to acute toxicity assays, the half lethal dose of four novel tobacco products calculated from theoretical nicotine concentration, ranked as follows e-liquid (0.29 mg/ml) > the extract of e-cig aerosol (0.43 mg/ml) > mint flavor snus (1.20 mg/ml) > black tea flavor snus (1.50 mg/ml). The equivalent lethal rate 5%~20% of four novel tobacco products were applied to following experiments. These novel tobacco products damaged nematode's locomotion including head thrashing and body bending, the damage was most evident in two flavors of snus. The similar trends were found in reproductive performance investigation. At tested concentrations, the retardation development of C. elegans was found throughout all stages with peak blockage at adulthood. Life-span tests showed that novel tobacco products at 5% lethal rate seemed no significant effect on affected the life-span of nematodes, with snus shortened the lifespan of C. elegans at 20% lethal rate. Imaging stress response indicted four types of tobacco productions causing stress response in C. elegans. Exposed to either 5% or 20% lethal levels (5% and 20%), the percentages of worms with DAF-16 redistribution among all groups varied, with higher frequencies in both snus. Summary, novel tobacco products caused multiple adverse impacts to C. elegans, including acute toxicity, locomotion behavior disruption, brood size reduction, development retardation, and life-span reduction. The toxicity was associated with both the feature and concentration of tobacco products, and oxidative stress was the main mechanism.

Improved Transductive Support Vector Machine for a Small Labelled Set in Motor Imagery-Based Brain-Computer Interface.

Long and tedious calibration time hinders the development of motor imagery- (MI-) based brain-computer interface (BCI). To tackle this problem, we use a limited labelled set and a relatively large unlabelled set from the same subject for training based on the transductive support vector machine (TSVM) framework. We first introduce an improved TSVM (ITSVM) method, in which a comprehensive feature of each sample consists of its common spatial patterns (CSP) feature and its geometric feature. Moreover, we use the concave-convex procedure (CCCP) to solve the optimization problem of TSVM under a new balancing constraint that can address the unknown distribution of the unlabelled set by considering various possible distributions. In addition, we propose an improved self-training TSVM (IST-TSVM) method that can iteratively perform CSP feature extraction and ITSVM classification using an expanded labelled set. Extensive experimental results on dataset IV-a from BCI competition III and dataset II-a from BCI competition IV show that our algorithms outperform the other competing algorithms, where the sizes and distributions of the labelled sets are variable. In particular, IST-TSVM provides average accuracies of 63.25% and 69.43% with the abovementioned two datasets, respectively, where only four positive labelled samples and sixteen negative labelled samples are used. Therefore, our algorithms can provide an alternative way to reduce the calibration time.

Vasoactive intestinal peptide stabilizes intestinal immune homeostasis through maintaining interleukin-10 expression in regulatory B cells.

Rationale: Immune dysfunction is thought to play an important role in the pathogenesis of inflammatory bowel disease (IBD), including ulcerative colitis (UC) and Crohn's disease (CD). However, the underlying mechanism requires further investigation. Vasoactive intestinal peptide (VIP) has immune regulatory functions, but its role in immune regulatory activities in the intestinal mucosa is not fully understood. This study aims to elucidate the role of VIP in the regulation of regulatory B cell (Breg) function in the intestine. Methods: Peripheral blood samples were collected from UC patients and healthy control (HC) subjects. Bregs were isolated from these samples and their immune regulatory function was analyzed. A murine colitis model was established to test the role of VIP in inhibiting inflammation in the intestine. Results: Serum IL-10 and VIP levels were lower in IgE+ (≥0.35 IU/mL) UC patients than that in HC subjects. The immune suppressive function of Bregs isolated from IgE+ UC patients was impaired. IL-10 mRNA decayed spontaneously in Bregs, which was reversed by VIP added to the culture. Tristetraprolin (TTP) bound IL-10 mRNA to speed its decay, which was blocked by VIP in the culture. Administration of VIP efficiently inhibited experimental colitis. Conclusions: Insufficient VIP levels in the microenvironment speeds IL-10 mRNA decay to cause Breg dysfunction. Administration of VIP can inhibit experimental colitis, suggesting the translational potential of VIP in the treatment of IgE+ UC.

Microbial functional diversity and carbon use feedback in soils as affected by heavy metals.

Soil microorganisms are an important indicator of soil fertility and health. However, our state of knowledge about soil microbial activities, community compositions and carbon use patterns under metal contaminations is still poor. This study aimed to evaluate the influences of heavy metals (Cd and Pb) on soil microorganisms by investigating the microbial community composition and carbon use preferences. Metal pollution was approached both singly and jointly with low (25 and 2500 mg kg-1) and high (50 and 5000 mg kg-1) concentrations of Cd and Pb, respectively, in an artificially contaminated soil. In a laboratory incubation experiment, bio-available and potentially bio-available metal concentrations, selected soil properties (pH, electrical conductivity, total organic carbon and total nitrogen), and microbial parameters (microbial activity as basal respiration, microbial biomass carbon (MBC) and microbial functional groups) were determined at two sampling occasions (7 and 49 days). Metal contamination had no effect on the selected soil properties, while it significantly inhibited both microbial activity and MBC formation. Contaminated soils had higher microbial quotient (qCO2), suggesting there was higher energy demand with less microbially immobilized carbon as MBC. Notably, the efficiency of microbial carbon use was repressed as the metal concentration increased, yet no difference was observed between metal types (p > 0.05). Based on the microbial phospholipid fatty acids (PLFA) analysis, total PLFAs decreased significantly under metal stress at the end of incubation. Heavy metals had a greater negative influence on the fungal population than bacteria with respective 5-35 and 8-32% fall in abundances. The contaminant-driven (metal concentrations and types) variation of soil PLFA biomarkers demonstrated that the heavy metals led to the alteration of soil microbial community compositions and their activities, which consequently had an adverse impact on soil microbial carbon immobilization.