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Ciprofloxacin (CIP), an important emerging contaminant, has been frequently detected in water, and its efficient removal has become an issue of great concern. In this study, a nanocomposite material nZVI/PA was synthesized by impregnating nanoscale zero-valent iron (nZVI) inside a millimeter-sized porous host (polystyrene-based anion exchange resin (PA)) for CIP removal. The nZVI/PA composite was characterized by field emission scanning electron microscopy coupled with energy-dispersive X-ray, transmission electron microscopy, X-ray diffraction, as well as X-ray photoelectron spectroscopy, and it was confirmed that nZVI was uniformly dispersed in PA with a small particle size. Furthermore, several key factors were investigated including initial solution pH, initial CIP concentration, co-existing ions, organic ligands, and dissolved oxygen. The experimental results indicated that the nZVI/PA composites exhibited a high removal efficiency for CIP under the conditions of initial pH 5.0, and initial CIP concentration 50 mg L−1 at 25 °C, with the maximum removal rate of CIP reaching 98.5%. Moreover, the nZVI/PA composites exhibited high efficiency even after five cycles. Furthermore, quenching tests and electron spin resonance (ESR) confirmed that CIP degradation was attributed to hydroxyl (·OH) and superoxide radicals (⋅O2−). Finally, the main degradation products of CIP were analyzed, and degradation pathways including the hydroxylation of the quinolone ring, the cleavage of the piperazine ring, and defluorination were proposed. These results are valuable for evaluating the practical application of nZVI/PA composites for the removal of CIP and other fluoroquinolone antibiotics.

Due to low efficiency and the material choice limitations of traditional evaporation systems to treat acid wastewater, humidification and dehumidification (HDH) as the core process was applied in the treatment and reduction of wastewater with organic acid pollutant concentrations. The forecasting of pH changes and COD reduction is important for the system’s design. Therefore, a study of the pollutant removal efficiency with different parameters, such as the reaction temperature, air quantity, and flow rate was conducted with ASPEN modeling. In this article, ASPEN modeling was used to simulate the water and acid material transformation in HDH system. The process was composed of blocks, such as RadFrac, heater and split. The analysis was taken with different air quantities, tower diameters, heat loads and flow rates. The analysis indicated that the pH of the maleic acid wastewater changed from 3.0 to 5.7. The relationship between inlet quantity, air quantity, inlet heat and the clean water yield was also shown in the modeling results. Based on these studies, we determined that the model can help engineers solve the key problems of HDH systems, such as heat balance calculation, equipment selection, and the prediction of incoming and outgoing evaporation materials.

Single-trial electroencephalogram detection has been widely applied in brain-computer interface (BCI) systems. Moreover, an individual generalized model is significant for applying the dynamic visual target detection BCI system in real life because of the time jitter of the detection latency, the dynamics and complexity of visual background. Hence, we developed an unsupervised multi-source domain adaptation network (P3-MSDA) for dynamic visual target detection. In this network, a P3 map-clustering method was proposed for source domain selection. The adversarial domain adaptation was conducted for domain alignment to eliminate individual differences, and prediction probabilities were ranked and returned to guide the input of target samples for imbalanced data classification. The results showed that individuals with a strong P3 map selected by the proposed P3 map-clustering method perform best on the source domain. Compared with existing schemes, the proposed P3-MSDA network achieved the highest classification accuracy and F1 score using five labeled individuals with a strong P3 map as the source domain. These findings can have a significant meaning in building an individual generalized model for dynamic visual target detection.

Objective To assess the awareness, attitude and barriers of colorectal cancer screening among high-risk populations in China.Design A cross-sectional study was employed.Setting This study was conducted in nine hospitals in Hunan province, China.Participants Individuals with a high-risk for colorectal cancer were interviewed using a pretested structured questionnaire.Primary and secondary outcome measures Knowledge, attitude towards colorectal cancer screening, sociodemographic factors associated with screening knowledge and behaviour and barriers of colorectal cancer screening.Results This study included 684 participants. The mean knowledge score was 11.86/24 (SD 4.84). But over 70% of them held a positive attitude towards screening. Only 13.3% had undergone colorectal cancer screening. Independent factors related to knowledge were education level of college or above, working as a white collar, higher income, having health insurance, having seen a doctor in the past year and with a high perceived risk (p

Abstract Background Splice sites prediction has been a long-standing problem in bioinformatics. Although many computational approaches developed for splice site prediction have achieved satisfactory accuracy, further improvement in predictive accuracy is significant, for it is contributing to predict gene structure more accurately. Determining a proper window size before prediction is necessary. Overly long window size may introduce some irrelevant features, which would reduce predictive accuracy, while the use of short window size with maximum information may performs better in terms of predictive accuracy and time cost. Furthermore, the number of false splice sites following the GT–AG rule far exceeds that of true splice sites, accurate and rapid prediction of splice sites using imbalanced large samples has always been a challenge. Therefore, based on the short window size and imbalanced large samples, we developed a new computational method named chi-square decision table (χ2-DT) for donor splice site prediction. Results Using a short window size of 11 bp, χ2-DT extracts the improved positional features and compositional features based on chi-square test, then introduces features one by one based on information gain, and constructs a balanced decision table aimed at implementing imbalanced pattern classification. With a 2000:271,132 (true sites:false sites) training set, χ2-DT achieves the highest independent test accuracy (93.34%) when compared with three classifiers (random forest, artificial neural network, and relaxed variable kernel density estimator) and takes a short computation time (89 s). χ2-DT also exhibits good independent test accuracy (92.40%), when validated with BG-570 mutated sequences with frameshift errors (nucleotide insertions and deletions). Moreover, χ2-DT is compared with the long-window size-based methods and the short-window size-based methods, and is found to perform better than all of them in terms of predictive accuracy. Conclusions Based on short window size and imbalanced large samples, the proposed method not only achieves higher predictive accuracy than some existing methods, but also has high computational speed and good robustness against nucleotide insertions and deletions. Reviewers This article was reviewed by Ryan McGinty, Ph.D. and Dirk Walther.

Biometric identity authentication technology is widely used in the field of information security. As a new biological method, electroencephalography (EEG) is gradually applied in biometric recognition, because scientists believe that practicability and portability are the development direction of EEG identity authentication. This work investigates the feasibility of using resting state EEG signals recorded by single-channel portable device for identity authentication. Single-channel EEG classification are effectively improved by using mixed-method in three feature domains (i.e., time, frequency, and time-frequency), feature selection (Rayleigh quotient) and classifier design (ensemble classifier). We invited 46 subjects to participate in the EEG identity authentication experiment. Experimental results show that the open-eyed resting state is an ideal authentication method, and the average classification accuracy of the authentication algorithm can reach 95.48% in 2 seconds, validating that the new method of processing single-channel EEG signals is especially useful in extrapolating EEG identity authentication to realistic field contexts.

The gut microbiome is a unique marker for cetaceans’ health status, and the microbiome composition of their skin wounds can indicate a potential infection from their habitat. Our study provides the first comparative analysis of the microbial communities from gut regions and skin wounds of an individual Indo-Pacific finless porpoise (Neophocaena phocaenoides). Microbial richness increased from the foregut to the hindgut with variation in the composition of microbes. Fusobacteria (67.51% ± 5.10%), Firmicutes (22.00% ± 2.60%), and Proteobacteria (10.47% ± 5.49%) were the dominant phyla in the gastrointestinal tract, while Proteobacteria (76.11% ± 0.54%), Firmicutes (22.00% ± 2.60%), and Bacteroidetes (10.13% ± 0.49%) were the dominant phyla in the skin wounds. The genera Photobacterium, Actinobacillus, Vibrio, Erysipelothrix, Tenacibaculum, and Psychrobacter, considered potential pathogens for mammals, were identified in the gut and skin wounds of the stranded Indo-Pacific finless porpoise. A comparison of the gut microbiome in the Indo-Pacific finless porpoise and other cetaceans revealed a possible species-specific gut microbiome in the Indo-Pacific finless porpoise. There was a significant difference between the skin wound microbiomes in terrestrial and marine mammals, probably due to habitat-specific differences. Our results show potential species specificity in the microbiome structure and a potential threat posed by environmental pathogens to cetaceans.

Molecular ferroelectrics have promising potential as next-generation flexible electronic materials by the advantage of flexibility, structural tunability, and easy processability. However, an obstacle in expanding their promising applications is effectively raising the ferroelectric transition temperature (Tc) necessary for practical applications, especially under high-temperature operating conditions. Herein, taking the advantage of a hydroxyl group that could form stronger hydrogen bonds to insert/tune host–guest and guest–guest interactions, we employed the 3-hydroxypyrrolidine cation to construct two new enantiomeric hexagonal perovskite ferroelectrics, (R)-3-OH-(C4H9N)[CdCl3] and (S)-3-OH-(C4H9N)[CdCl3]. Both of them undergo a ferroelectric phase transition from C2221 to P21 with a high Tc of 350 K, which is 110 K and 47 K higher than that of their parent compound (C4H10N)[CdCl3] (240 K) and F-substituted analogues (R/S)-3-F-(C4H9N)[CdCl3] (303 K), respectively. These findings well demonstrate that, besides the F-substitution strategy, an OH-substitution strategy provides an important and practical way in designing high-Tc ferroelectrics.

Study Objectives: This study aims to identify the characteristic sleep disturbances that affect behavioral problems in children with autism spectrum disorder (ASD), providing a potential direction for sleep and behavioral intervention in ASD.Methods: The data of 513 children with ASD and 246 typically developing (TD) children aged between 2 and 5 years old were collected. The behavior performance of preschool children was assessed using the Child Behavior Checklist for 1.5–5.0 years old. The Children's Sleep Habits Questionnaire (CSHQ) was used to measure the sleep status of the children, and the Social Responsiveness Scale was used to measure the severity of disorder. Linear regression analysis was performed to examine the effects of sleep disturbances on behavioral problems, and independent-sample t-test was performed to compare the mean of the samples.Results: Compared to TD children, children with ASD had longer sleep onset delay and more night awakenings. The parasomnias score (a subscale of the CSHQ) was significantly associated with the internalizing (β = 0.113, P = 0.010), externalizing (β = 0.128, P = 0.006), and total problems (β = 0.143, P = 0.001) of children with ASD, while this association was not significant in TD children. “Bed wetting” and “restless and moves a lot” (two items in the CSHQ under parasomnia) significantly only affected the overall behavioral score in children with ASD (P < 0.05).Conclusion: Parasomnias, especially bed wetting and restlessness, are specifically associated with the behavioral problems of children with ASD rather than TD children.

Background It is essential to investigate the experiences behind why adolescents start and continue to self-harm in order to develop targeted treatment and prevent future self-harming behaviours. Aims The aims of this study are to understand the motivations for initiating and repeating nonfatal self-harm, the different methods used between first-time and repeated self-harm and the reasons that adolescents do not seek help from health services. Methods Adolescents with repeated nonfatal self-harm experiences were recruited to participate in individual, semi-structured qualitative interviews. The interviews were analysed with interpretative phenomenological analysis. Results We found that nonfatal self-harm among adolescents occurred comparatively early and was often triggered by specific reasons. However, the subsequent nonfatal self-harm could be causeless, with repeated self-harm becoming a maladaptive coping strategy to handle daily pressure and negative emotions. The choice of tools used was related to the ease of accessibility, the life-threatening risk and the size of the scars. Adolescents often concealed their scars on purpose, which made early identification insufficient. Peer influence, such as online chat groups encouraging self-harm by discussing and sharing self-harm pictures, could also lead to increased self-harm. The results also included participants’ opinions on how to stop nonfatal self-harm and their dissatisfaction with the current healthcare services. Conclusions The current study provides important implications both for early identification and interventions for adolescents who engage in repeated nonfatal self-harm, and for individualising treatment planning that benefits them. It is also worthwhile to further investigate how peer influence and social media may affect self-harm in adolescents.

Emotion recognition plays an important part in human-computer interaction (HCI). Currently, the main challenge in electroencephalogram (EEG)-based emotion recognition is the non-stationarity of EEG signals, which causes performance of the trained model decreasing over time. In this paper, we propose a two-level domain adaptation neural network (TDANN) to construct a transfer model for EEG-based emotion recognition. Specifically, deep features from the topological graph, which preserve topological information from EEG signals, are extracted using a deep neural network. These features are then passed through TDANN for two-level domain confusion. The first level uses the maximum mean discrepancy (MMD) to reduce the distribution discrepancy of deep features between source domain and target domain, and the second uses the domain adversarial neural network (DANN) to force the deep features closer to their corresponding class centers. We evaluated the domain-transfer performance of the model on both our self-built data set and the public data set SEED. In the cross-day transfer experiment, the ability to accurately discriminate joy from other emotions was high: sadness (84%), anger (87.04%), and fear (85.32%) on the self-built data set. The accuracy reached 74.93% on the SEED data set. In the cross-subject transfer experiment, the ability to accurately discriminate joy from other emotions was equally high: sadness (83.79%), anger (84.13%), and fear (81.72%) on the self-built data set. The average accuracy reached 87.9% on the SEED data set, which was higher than WGAN-DA. The experimental results demonstrate that the proposed TDANN can effectively handle the domain transfer problem in EEG-based emotion recognition.

The prediction and control of vortex-induced vibration (VIV) is one of the key problems for riser design. The effect of platform heave motion on VIV of deep sea top-tensioned riser (TTR) is presented by means of numerical simulation and experiment in this research. First, the heave motion was modeled as a parametric excitation, and the governing equation of VIV of riser considering the parametric excitation was established. Then, the dynamic response of TTR was calculated numerically by the finite difference method based on the Van der Pol wake-oscillator model. Finally, a validation experiment was carried out at the towing tank of Tianjin university. The results show that the VIV response at the bottom of riser is significantly increased due to the platform heave motion, especially in the situation of low current velocity. The larger amplitude and the higher frequency of the platform heave motion with the greater influence are generated on VIV of TTR. In particular, the value of 0.5 times, 1 time, or other multiples of the platform heave frequency will be included in the vibration frequency component of TTR when the platform heave amplitude is large and the frequency is high.

China Earthquake Parameter Zoning (2016) has increased the seismic fortification intensity in Chengdu from VII to VIII. It is necessary to conduct in-depth discussion on the impact of the seismic performance of the built underground station structure. In this paper, a stratum-structure finite element model is established with a Chengdu subway station as an example. The model boundary adopts viscoelastic boundary, and the ground motion is input in the form of equivalent nodal force. The equivalent linearization method is used to consider the nonlinearity of soil materials. The time-history analysis of seismic fortification intensity of VII and VIII degrees is carried out, respectively. By comparing the calculation results of the two seismic fortification intensity ground motion conditions, it is concluded that the connection between the side wall and the floor is the weakest position of the station structure under the action of the earthquake; the seismic fortification intensity is increased from VII to VIII to the internal force of the structure. It has a relatively large impact, especially the most obvious impact on the bending moment. The results of the verification of the seismic time-history analysis show that the increase of fortification intensity will have a more obvious impact on the structural deformation, and the structural design of the station can meet the safety performance requirements of VII and VIII degrees of seismic fortification. The research has certain reference significance for the seismic safety evaluation of the built underground station structure in Chengdu area.

The VersaPlex™ 27PY System is an STR multiplex from Promega offering co-amplification of 27 loci. This six-dye multiplex was designed for casework samples and includes loci that meet database requirements for the US (CODIS), Europe (ESS) and China (Chinese National Database). The 23 autosomal loci include the D6S1043 locus because of its high level of discrimination power, especially in Asian populations. The multiplex also includes two rapidly-mutating Y-STRs that can provide useful genetic information for forensic samples. In this article we describe the developmental validation experiments performed on the VersaPlex™ 27PY System that were designed to meet SWGDAM requirements. Changes in the performance of the multiplex are documented in response to reaction variables including PCR inhibitors, reaction volume, cycle number, annealing temperature, and magnesium concentration. The sensitivity, specificity, precision, and reproducibility of the VersaPlex™ 27PY System were also evaluated. The results of the experiments demonstrate the capabilities of the VersaPlex™ 27PY System as a tool for forensic laboratories.

Skeletal diseases caused by excessive activation of osteoclasts seriously affect elderly’s health. Therefore, inhibiting excessive activation of osteoclasts become effective therapeutic strategy for osteoporosis. Celery, a traditional and popular Chinese vegetable with high nutritional value, is rich in flavonoids which have a variety of pharmacological activities. The present study aimed to determine the pharmacological effect of total flavonoids of celery (TFC) on osteoclastogenesis, and to explore the molecular mechanisms. Results showed that TFC inhibited osteoclast differentiation and bone resorption without significant toxic and side effect. Furthermore, the results of western blot analysis and qPCR indicated that TFC inhibited the degradation of IκBα, phosphorylation of NF-κB and p38, and subsequently attenuated the expression levels of osteoclast-specific genes. The results of this study may have a positive impact on the application of TFC as functional food ingredients, which has potential preventive and therapeutic effects on osteoclast-related diseases.

Coronin 2A (CORO2A) is a novel component of the N-CoR (nuclear receptor co-repressor) complex. Abnormal CORO2A expression is associated with carcinogenesis. We used databases from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), and analyzed CORO2A expression and gene regulation networks in breast cancer. Expression was analyzed using GEO and TCGA database and further validated in breast cancer samples collected in our clinic. The prognostic value of CORO2A was explored by using the Kaplan–Meier survival analysis and Cox proportional hazards regression analysis. LinkedOmics was used to identify coexpressed genes associated with CORO2A. After analyzing the intersection of coexpressed genes correlated with CORO2A and differentially expressed genes after CORO2A silencing, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of the intersecting genes were conducted by using FunRich software. Transwell assays were performed in breast cancer cells to determine the effect of CORO2A on cell migration. MTS, colony formation, and cell cycle distribution assays were performed in breast cancer cells to determine the effect of CORO2A on cell proliferation. Gene enrichment analysis was employed to explore the target networks of transcription factors and miRNAs. We found that CORO2A was upregulated and that the elevated expression of CORO2A was associated with poor overall survival (OS) and relapse-free survival (RFS) in TNBC patients. Further bioinformatics analysis of public sequencing data and our own RNA-Seq data revealed that CORO2A was probably involved in the epithelial-to-mesenchymal transition process and might have a significant effect on the migration of breast cancer cells, which might be mediated via pathways involving several miRNAs and MYC transcription factors. Functionally, the knockdown of CORO2A inhibited cell migration, decreased viability, and colony formation and induced cell cycle arrest in the G0/G1 phase in breast cancer cells. These results demonstrate that bioinformatics-based analysis efficiently reveals information about CORO2A expression and its potential regulatory networks in breast cancer, laying a foundation for further mechanistic research on the role of CORO2A in carcinogenesis. Moreover, CORO2A promotes the migration and proliferation of breast cancer cells and may have an important function in breast cancer progression. CORO2A is a potential prognostic predictor for TNBC patients. Targeting CORO2A may provide promising therapy strategies for breast cancer treatment.

High-frequency electroencephalography (EEG) signals play an important role in research on human emotions. However, the different network patterns under different emotional states in the high gamma band (50–80 Hz) remain unclear. In this paper, we investigate different emotional states using functional network analysis on various frequency bands. We constructed multiple functional networks on different frequency bands and performed functional network analysis and time–frequency analysis on these frequency bands to determine the significant features that represent different emotional states. Furthermore, we verified the effectiveness of these features by using them in emotion recognition. Our experimental results revealed that the network connections in the high gamma band with significant differences among the positive, neutral, and negative emotional states were much denser than the network connections in the other frequency bands. The connections mainly occurred in the left prefrontal, left temporal, parietal, and occipital regions. Moreover, long-distance connections with significant differences among the emotional states were observed in the high frequency bands, particularly in the high gamma band. Additionally, high gamma band fusion features derived from the global efficiency, network connections, and differential entropies achieved the highest classification accuracies for both our dataset and the public dataset. These results are consistent with literature and provide further evidence that high gamma band EEG signals are more sensitive and effective than the EEG signals in other frequency bands in studying human affective perception.

BACKGROUND:Depression is one of the most common mental disorders, profoundly impacting an individual's performance and quality of life. Due to their unique working conditions, nursing is counted among the occupational groups at high risk for developing depression. Because of the shortage of nursing resources in China, Chinese nurses suffer from heavy daily workloads more than those in many other countries. Therefore, this study aimed to evaluate the overall prevalence of depressive symptoms and analyse the potential risk factors of depressive symptoms in Chinese nurses. METHODS:A systematic literature search in PubMed, EMBASE, Web of Science, the Chinese BioMedical Literature Database (CBM), the China National Knowledge Infrastructure (CNKI), and the Weipu and Wanfang databases up to Dec 31st, 2019 was performed regarding the prevalence of depressive symptoms in Chinese nurses. Eligibility assessment and data extraction were performed independently by 2 researchers, and meta-analysis was used to synthesize the data. Heterogeneity was evaluated using Cochran's Q test and quantified using the I2 statistic. To explore the potential source of heterogeneity, subgroup analyses were also performed. In addition, both funnel plot and Egger's tests were adopted to assess publication bias. RESULTS:A total of 102 studies published from 1996 to 2019 covering 22 provinces were included for further analysis. The total number of participants was 52,592, with a range of 46 to 7205 per study. The overall prevalence of depressive symptoms in Chinese nurses was 43.83% (95%CI: 40.26%-47.42%), and 31.12% (95%CI: 27.30%-35.07%) were classified as mild degrees of depressive symptoms. The prevalence of depressive symptoms may be significantly affected by region, province or municipality and department marital status. Moreover, an increasing trend in the prevalence of depressive symptoms was observed in recent years. CONCLUSION:The results presented a high prevalence of depressive symptoms among Chinese nurses, which suggests interventional programmes by health decision-makers to improving the mental state of nurses is needed urgently, especially in nurses with high risk factors for depressive symptoms. Furthermore, the nationwide investigation of depressive symptoms prevalence should be performed with a standard diagnostic tool, which may be more useful for policy makers and planners.

PurposeThe purpose of this study was to construct a multi-center cross-sectional study to predict self-regulated learning (SRL) levels of Chinese medical undergraduates.MethodsWe selected medical undergraduates by random sampling from five universities in mainland China. The classical regression methods (logistic regression and Lasso regression) and machine learning model were combined to identify the most significant predictors of SRL levels. Nomograms were built based on multivariable models. The accuracy, discrimination, and generalization of our nomograms were evaluated by the receiver operating characteristic curves (ROC) and the calibration curves and a high quality external validation.ResultsThere were 2052 medical undergraduates from five universities in mainland China initially. The nomograms constructed based on the non-overfitting multivariable models were verified by internal validation (C-index: learning motivation: 0.736; learning strategy: 0.744) and external validation (C-index: learning motivation: 0.986; learning strategy: 1.000), showing decent prediction accuracy, discrimination, and generalization.ConclusionComprehensive nomograms constructed in this study were useful and convenient tools to evaluate the SRL levels of undergraduate medical students in China.

Background: Increasing evidence supports that the immune infiltration of tumours is associated with prognosis. Here, we sought to assess the relevance of the cellular composition of the immune infiltrate to survival after platinum-based chemotherapy amongst patients with high-grade serous ovarian cancer and evaluate these effects by molecular subtype. Methods: We searched publicly available databases and identified 13 studies with more than 2000 patients. We estimated the proportions of 22 immune cell subsets by using a computational approach (CIBERSORT). Then, we investigated the associations between each immune cell subset and progression-free survival (PFS) and overall survival (OS), with cellular proportions modelled as quartiles. Findings: A high fraction of M1 [hazard ratio (HR) = 0.92, 95% confidence interval (CI) = 0.86–0.99] and M0 (HR = 0.93, 95% CI = 0.87–0.99) macrophages emerged as the most closely associated with favourable OS. Neutrophils were associated with poor OS (HR = 1.06, 95% CI = 1.00–1.13) and PFS (HR = 1.10, 95% CI = 1.02–1.13). Amongst the immunoreactive tumours, the M0 macrophages and the CD8+ T cells were associated with improved OS, whereas the M2 macrophages conferred worse OS. Interestingly, PD-1 was associated with good OS (HR=0.89, 95% CI = 0.80–1.00) and PFS (HR=0.89, 95% CI = 0.79–1.01) in this subtype. Four subgroups of tumours with distinct survival patterns were identified using immune cell proportions with unsupervised clustering. Interpretation: Further investigations of the quantitative cellular immune infiltrations in tumours may contribute to therapeutic advances. Keywords: Tumour-immune infiltration, Platinum, High grade serous ovarian cancer, Overall survival, Progression-free survival

Object detection in remote-sensing images (RSIs) is always a vibrant research topic in the remote-sensing community. Recently, deep-convolutional-neural-network (CNN)-based methods, including region-CNN-based and You-Only-Look-Once-based methods, have become the de-facto standard for RSI object detection. CNNs are good at local feature extraction but they have limitations in capturing global features. However, the attention-based transformer can obtain the relationships of RSI at a long distance. Therefore, the Transformer for Remote-Sensing Object detection (TRD) is investigated in this study. Specifically, the proposed TRD is a combination of a CNN and a multiple-layer Transformer with encoders and decoders. To detect objects from RSIs, a modified Transformer is designed to aggregate features of global spatial positions on multiple scales and model the interactions between pairwise instances. Then, due to the fact that the source data set (e.g., ImageNet) and the target data set (i.e., RSI data set) are quite different, to reduce the difference between the data sets, the TRD with the transferring CNN (T-TRD) based on the attention mechanism is proposed to adjust the pre-trained model for better RSI object detection. Because the training of the Transformer always needs abundant, well-annotated training samples, and the number of training samples for RSI object detection is usually limited, in order to avoid overfitting, data augmentation is combined with a Transformer to improve the detection performance of RSI. The proposed T-TRD with data augmentation (T-TRD-DA) is tested on the two widely-used data sets (i.e., NWPU VHR-10 and DIOR) and the experimental results reveal that the proposed models provide competitive results (i.e., centuple mean average precision of 87.9 and 66.8 with at most 5.9 and 2.4 higher than the comparison methods on the NWPU VHR-10 and the DIOR data sets, respectively) compared to the competitive benchmark methods, which shows that the Transformer-based method opens a new window for RSI object detection.

Retinoid-related orphan receptor alpha (RORα) is involved in tumor development. However, the mechanisms underlying RORα inhibiting epithelial-to-mesenchymal transition (EMT) and invasion are poorly understood in gastric cancer (GC). This study revealed that the decreased expression of RORα is associated with GC development, progression, and prognosis. RORα suppressed cell proliferation, EMT, and invasion in GC cells through inhibition of the Wnt/β-catenin pathway. RORα overexpression resulted in the decreased Wnt1 expression and the increased RORα interaction with β-catenin, which could lead to the decreased intranuclear β-catenin and p-β-catenin levels, concomitant with downregulated T-cell factor-4 (TCF-4) expression and the promoter activity of c-Myc. The inhibition of Wnt/β-catenin pathway was coupled with the reduced expression of Axin, c-Myc, and c-Jun. RORα downregulated vimentin and Snail and upregulated E-cadherin protein levels in vitro and in vivo. Inversely, knockdown of RORα attenuated its inhibitory effects on Wnt/β-catenin pathway and its downstream gene expression, facilitating cell proliferation, EMT, migration, and invasion in GC cells. Therefore, RORα could play a crucial role in repressing GC cell proliferation, EMT, and invasion via downregulating Wnt/β-catenin pathway.

Immunogenicity of hepatitis B vaccine between 20 μg with 3-dose schedule and 60 μg with 2-dose regimens was compared 2 years after primary immunization. A total of 353 healthy adults aged 18–25 years were enrolled in the study and randomly assigned (1: 1: 1) into 3 vaccine groups: A (20 μg, 0–1–6 month), B (60 μg, 0–1 month) and C (60 μg, 0–2 month). Serum samples were collected at 1 month after a series vaccination and 12 months, 24 months after the first-dose. The GMC level of anti-HBs antibody was measured using Chemiluminescent Microparticle ImmunoAssay (CMIA). There were 59, 45 and 55 vaccinees available to follow-up with 2 year later in vaccine groups A, B and C, respectively. No significant differences existed in sex ratio, age and body mass index (BMI) among vaccinees at month 24 and the corresponding participants at baseline in each group (P > 0.05). The seroprotection rates in group A, B and C were 98.31%, 88.37% and 85.19%, respectively (P = 0.014), reflecting the fact that the rate of group A was significantly higher than that in group C (P = 0.026). Also, the GMC level of anti-HBs antibody in group A was significantly higher than those of other two groups (427.46 mIU/ml vs. 89.74 mIU/ml, 89.80 mIU/ml, respectively; all P < 0.01). This data suggested that the standard 20 μg (0–1–6 month) regimen of hepatitis B vaccine should be recommended as a priority on the premise of complete compliance in adults.

Abstract Background The electroencephalogram (EEG) signal represents a subject’s specific brain activity patterns and is considered as an ideal biometric given its superior invisibility, non-clonality, and non-coercion. In order to enhance its applicability in identity authentication, a novel EEG-based identity authentication method is proposed based on self- or non-self-face rapid serial visual presentation. Results In contrast to previous studies that extracted EEG features from rest state or motor imagery, the designed paradigm could obtain a distinct and stable biometric trait with a lower time cost. Channel selection was applied to select specific channels for each user to enhance system portability and improve discriminability between users and imposters. Two different imposter scenarios were designed to test system security, which demonstrate the capability of anti-deception. Fifteen users and thirty imposters participated in the experiment. The mean authentication accuracy values for the two scenarios were 91.31 and 91.61%, with 6 s time cost, which illustrated the precision and real-time capability of the system. Furthermore, in order to estimate the repeatability and stability of our paradigm, another data acquisition session is conducted for each user. Using the classification models generated from the previous sessions, a mean false rejected rate of 7.27% has been achieved, which demonstrates the robustness of our paradigm. Conclusions Experimental results reveal that the proposed paradigm and methods are effective for EEG-based identity authentication.

With the spread of camera-equipped devices, massive images and videos are recorded on construction sites daily, and the ever-increasing volume of digital images has inspired scholars to visually capture the actual status of construction sites from them. Three-dimensional (3D) reconstruction is the key to connecting the Building Information Model and the project schedule to daily construction images, which enables managers to compare as-planned with as-built status and detect deviations and therefore monitor project progress. Many scholars have carried out extensive research and produced a variety of intricate methods. However, few studies comprehensively summarize the existing technologies and introduce the homogeneity and differences of these technologies. Researchers cannot clearly identify the relationship between various methods to solve the difficulties. Therefore, this paper focuses on the general technical path of various methods and sorts out a comprehensive research map, to provide reference for researchers in the selection of research methods and paths. This is followed by identifying gaps in knowledge and highlighting future research directions. Finally, key findings are summarized.

Background/Aims: Neurotensin (NTS), an intestinal hormone, is profoundly implicated in cancer progression through binding its primary receptor NTSR1. The conserved Wnt/β-Catenin pathway regulates cell proliferation and differentiation via activation of the β-catenin/T-cell factor (TCF) complex and subsequent modulation of a set of target genes. In this study, we aimed to uncover the potential connection between NTS/NTSR1 signaling and Wnt/β-Catenin pathway. Methods: Genetic silencing, pharmacological inhibition and gain-of-function studies as well as bioinformatic analysis were performed to uncover the link between NTS/ NTSR1 signaling and Wnt/β-Catenin pathway. Two inhibitors were used in vivo to evaluate the efficiency of targeting NTS/NTSR1 signaling or Wnt/β-Catenin pathway. Results: We found that NTS/NTSR1 induced the activation of mitogen-activated protein kinase (MAPK) and the NF-κB pathway, which further promoted the expression of Wnt proteins, including Wnt1, Wnt3a and Wnt5a. Meanwhile, the mRNA and protein expression levels of NTSR1 were increased by the Wnt pathway activator Wnt3a and decreased by the Wnt inhibitor iCRT3 in glioblastoma cells. Furthermore, pharmacological inhibition of NTS/NTSR1 or Wnt/β-Catenin signaling suppressed tumor growth in vitro and in vivo. Conclusion: These results reveal a positive feedback loop between NTS/NTSR1 and Wnt/β-Catenin signaling in glioblastoma cells that might be important for tumor development and provide potential therapeutic targets for glioblastoma.

Purpose: Early detection and management of coronary heart disease (CHD) are embedded into many community health service and primary care practices in western countries. The Framingham CHD risk score has been used to predict CHD and mortality for nearly 20 years, and it has predicted CHD event risk accurately in multiethnic populations. The aim of this study was to access the effect of a 6-month community-based intervention on CHD risk in individuals at high risk. Methods: A randomized controlled trial of individuals with a high 10-year CHD risk were recruited from two communities in China. Individuals in the intervention group (n = 53) received a 3-month group education and a 3-month coaching session. Physical examination and self-report questionnaires were used to collect both pre- and postintervention data on blood pressure, glucose, cholesterol, body mass index, smoking, depression, and health-related quality of life (HRQoL). Results: A total of 102 participants (85.0%) completed the 6-month study. Compared with the usual care group, the intervention group had a 5 mmHg greater reduction in systolic blood pressure (t = 2.01, p = .047), larger declines in glucose (t = −2.49, p = .015), cholesterol (t = −2.44, p = .017), body mass index (t = −2.58, p = .011), and depression (t = −2.05, p = .043), and better reports of HRQoL (t = 3.36, p = .001). No significant group differences in smoking behaviors were reported. Conclusion: A 6-month community-based intervention in a CHD high-risk population improved disease-related risk factors, depression, and HRQoL. Results provide preliminary evidence for primary prevention of cardiovascular disease risk in a community high-risk population. Keywords: coronary heart disease, intervention study, primary prevention

Over the centuries, people have used healing mud (peloids) to draw toxins out of the body, boost the immune system, cure psoriasis, acne, depression, and hair loss. The beauty industry has used mud-clay masks, body wraps, soaps, and baths. The useful properties of mud were established empirically. The most popular healing-mud spars are known in the Dead Sea in Israel, Baden-Baden in Germany, Calistoga in California, Budapest in Hungary, Akhtala and Kumisi in Georgia, Paratunka in Kamchatka, Wudalianchi in China.

Objective To study the characteristics and diagnosis of limb-girdle muscular dystrophy type 2D (LGMD2D). Methods The clinical characteristics, EMG, muscle MRI and muscle pathological studies of 2 female patients in a family with LGMD2D were analyzed. Genetic analysis was used in the diagnosis of this disease. The cases were reported along with related literatures review. Results The onset of the proband and her younger sister occurred at 3 years old with progressive proximal muscle weakness of four limbs as the main clinical manifestation. The serum creatine kinase (CK) was significantly high (> 50 × 10 3 U/L). EMG showed myogenic damage. Muscle MRI indicated partial muscle atrophy, fatness or fiber edema. Muscle pathological examination of the proband's younger sister revealed skeletal muscle necrosis and focal regeneration, partial striated muscle disappearance, and the muscle fibers in different sizes. Sequencing of all 10 coding exons of the SGCA gene in 2 patients revealed the same mutation: a c.262delT (p.Phe88SerfsX123) frameshift mutation in exon 3 and a c.409G > A (p.Glu137Lys) missense mutation in exon 5. Their mother was a carrier of SGCA gene c.409G > A (p.Glu137Lys) mutation. c.409G > A (p.Glu137Lys) is a mutation already found, and c.262delT (p.Phe88SerfsX123) is a novel mutation. The proband's father did not take the genetic test for some reason. Conclusions In case of a female with Duchenne muscular dystrophy (DMD).like symptom, if she has been excluded from the DMD gene carrier, pedigree analysis and genetic analysis involving limb . girdle muscular dystrophy (LGMD) should be conducted to facilitate the diagnosis of the LGMD and its subtypes. DOI: 10.3969/j.issn.1672-6731.2017.08.010

Objectives: To evaluate the persistence of protection from hepatitis B (HB) vaccination among adolescents immunized with a primary series of HB vaccine as infants, and the immune response to booster doses. Methods: Healthy adolescents aged 15–17 y vaccinated with HB vaccine only at birth were enrolled. Baseline serum hepatitis B surface antigen (HBsAg), antibody against hepatitis B surface antigen (anti-HBs) and antibody against hepatitis B core antigen (anti-HBc) were detected by Enzyme-Linked Immunosorbent Assay (ELISA) and anti-HBs level was measured using Chemiluminescent Microparticle Immunoassay (CMIA). The rate of HBV infection was calculated. The seroprotection rate of anti-HBs (≥ 10 mIU/ml) and GMC level were used to evaluate the persistence of immunity from HB vaccination. Those with anti-HBs < 10 mIU/ml were immunized with booster doses of HB vaccine and the anamnestic response was assessed. Results: Of 180 adolescents who received a primary series of HB vaccinations as infants, 3 (1.7%) had HBV infection and 74 (41.1%) had anti-HBs ≥ 10 mIU/ml with a GMC of 145.11 mIU/ml. The remaining 103 (57.2%) with anti-HBs < 10 mIU/ml received a booster dose of 20 μg HB vaccine and achieved the seroprotection rate of 84% (84/100) and a GMC of 875.19 mIU/ml at one month post-booster. An additional dose of 60 μg HB vaccine was administered to the 16 adolescents with anti-HBs < 10 mIU/ml after the first booster. All of them obtained anti-HBs seroprotection with a GMC of 271.02 mIU/ml at 1.5 months after an additional dose. Conclusions: Vaccine-induced immunity persisted for up to 15–17 y in 89.3% (158/177) of participants after a primary HB vaccination in infancy. Administering a booster dose of 20μg HB vaccine elicited an anamnestic immune responses in the majority of individuals with baseline anti-HBs

Abstract Dysregulated long noncoding RNAs (lncRNAs) are potential markers of several tumor prognoses. This study aimed to develop a lncRNA expression signature that can predict chemotherapeutic sensitivity for patients with advanced stage and high-grade serous ovarian cancer (HGS-OvCa) treated with platinum-based chemotherapy. The lncRNA expression profiles of 258 HGS-OvCa patients from The Cancer Genome Atlas were analyzed. Results revealed that an eight-lncRNA signature was significantly associated with chemosensitivity in the multivariate logistic regression model, which can accurately predict the chemosensitivity of patients [Area under curve (AUC) = 0.83]. The association of a chemosensitivity predictor with molecular subtypes indicated the excellent prognosis performance of this marker in differentiated, mesenchymal, and immunoreactive subtypes (AUC > 0.8). The significant correlation between ZFAS1 expression and chemosensitivity was confirmed in 233 HGS-OvCa patients from the Gene Expression Omnibus datasets (GSE9891, GSE63885, and GSE51373). In vitro experiments demonstrated that the ZFAS1 expression was upregulated by cisplatin in A2008, HeyA8, and HeyC2 cell lines. This finding suggested that ZFAS1 may participate in platinum resistance. Therefore, the evaluation of the eight-lncRNA signature may be clinically implicated in the selection of platinum-resistant HGS-OvCa patients. The role of ZFAS1 in platinum resistance should be further investigated.

Oleanolic acid (OA) has recently become a research hotspot in the treatment of many human diseases, especially osteoporosis and arthritis. However, the mechanisms are not elucidated completely. We aimed to elucidate the target and the mechanism via which OA inhibited osteoclast differentiation. We used TRAP staining and toluidine blue dye to test OA effect on osteoclastogenesis and bone resorption respectively. We detected the expression level of osteoclast differentiation related genes, estrogen receptor alpha (ERα) and miR-503. We blocked ERα with its specific blocker, methylpiperidino pyrazole (MPP). We antagonized the function of miR-503 with antagomir-503-5p. RT-PCR and ELISA kits were used to investigate the effects of OA on miR-503 formation and maturation-relevant enzymes Dicer and Drosha at gene and protein levels. The data suggested that OA inhibited osteoclastogenesis and bone resorption. OA upregulated ERα and miR-503 expression levels, inhibited RANK expression. MPP significantly attenuated the OA effect including inhibiting osteoclastogenesis, inhibiting bone resorption and up-regulating miR-503 expression. It showed that ERα was the target of OA and OA up-regulated miR-503 expression through ERα. Antagomir-503-5p inhibited the function of miR-503 and attenuated the inhibition of OA on osteoclastogenesis, suggesting that OA inhibited osteoclast by up-regulating miR-503 expression. In addition, OA up-regulated miR-503 by up-regulating Dicer expression. In conclusion, OA inhibits RANKL-induced osteoclastogenesis via ERα/miR-503/RANK signaling pathway in RAW264.7 cells.

BackgroundThe purpose of this study is to develop an effective but concise long non-coding RNA (lncRNA) expression signature that can predict response to neoadjuvant chemotherapy for breast cancer (BC) patients.MethodslncRNA expression profiling in 1102 BC patients from Gene Expression Omnibus datasets was analyzed using lncRNA-mining approach. The association between lncRNA signature and pathological complete response (pCR) was analyzed using logistic regression model in the training set (GSE25066, n = 488). Validation was performed in independent testing datasets, GSE20194, GSE20271, GSE22093, and GSE23988 (n = 614). Bonferroni method was employed for multiple testing corrections. Cell proliferation assay and Western blot assay were performed to evaluate the cell viability and protein expression level, respectively.ResultsThree lncRNAs (AK291479, U79293, and BC032585) have been identified to be significantly associated with pCR in the training dataset (Bonferroni p-value < 0.05). Expression signature with these lncRNAs was predictive of pCR in the training (AUC = 0.74) and testing (AUC = 0.72) datasets. Weighted gene co-expression network analysis and gene functional annotation suggest that the three lncRNAs were involved in cell cycle process. To confirm the functional significance of the identified lncRNAs, BC032585 was selectively silenced using RNA interference. Knockdown of BC032585 lncRNA significantly promoted cell resistance to multiple anticancer-drugs through upregulating MDR1 expression in breast cancer cells.ConclusionThese results suggest that lncRNAs such as BC032585 might be involved in chemotherapeutic response in breast cancer patients, and the three-lncRNA signature identified in the present study may serve as a useful biomarker for the selection of responsive breast cancer patients in neoadjuvant chemotherapy.

Background: Critical thinking (CT) is an essential competence for medical students. Family socioeconomic status (family SES) and general self-efficacy (GSE) play crucial roles in the development of CT. However, the association among family SES, GSE, and CT in Chinese medical students has yet to be fully investigated.Objectives: To investigate the role of family SES and GSE in the development of CT in Chinese medical students.Methods: 1,338 medical students were recruited using multistage stratified cluster sampling from three institutions in China. The Chinese critical thinking disposition inventory (CTDI-CV), General Self-Efficacy Scale (GSES), and a self-made inventory assessing family SES were administered to collect data. The relationship between CT and family SES as well as GSE was evaluated by structural equation modeling.Results: Students of higher family SES obtained higher CTDI-CV and GSES scores. A positive correlation was found between family SES and CT (r = 0.101–0.141, p < 0.05 or p < 0.01), as well as between family SES and GSE (r = 0.111–0.129, p < 0.01). Moreover, GSE was moderately correlated with CT (r = 0.418, p < 0.01). The model of partial mediate effect of GSE showed the best fit index with X2 = 29.698, df = 9 and X2/df = 3.300, NFI = 0.990, IFI = 0.993, TLI = 0.984, CFI = 0.993, RMSEA = 0.041.Conclusion: Family SES has a positive albeit limited influence on GSE and CT in Chinese medical students. GSE mediates the effect of family SES on CT and plays a larger role. Enhancing medical student’ GSE maybe an efficacious way to improve medical students’ CT.

Sulforaphane has been reported to possibly improve core symptoms associated with autism spectrum disorders from mostly small size studies. Here we present results of a larger randomized clinical trial (N = 108) in China. There were no significant changes in caregiver rated scales between sulforaphane and placebo groups. However, clinician rated scales showed a significant improvement in the sulforaphane group, and one third of participants showed at least a 30% decrease in score by 12 weeks treatment. The effects of sulforaphane were seen across the full range of intelligence and greater in participants over 10 years. Sulforaphane was safe and well-tolerated even for young children. The inconsistent results between caregiver and clinician rated scales suggest more clinical trials are needed to confirm our findings.

In recent years, research on decoding brain activity based on functional magnetic resonance imaging (fMRI) has made eye-catching achievements. However, constraint-free natural image reconstruction from brain activity remains a challenge, as specifying brain activity for all possible images is impractical. The problem was often simplified by using semantic prior information or just reconstructing simple images, including digitals and letters. Without semantic prior information, we present a novel method to reconstruct natural images from the fMRI signals of human visual cortex based on the computation model of convolutional neural network (CNN). First, we extracted the unit output of viewed natural images in each layer of a pre-trained CNN as CNN features. Second, we transformed image reconstruction from fMRI signals into the problem of CNN feature visualization by training a sparse linear regression to map from the fMRI patterns to CNN features. By iteratively optimization to find the matched image, whose CNN unit features become most similar to those predicted from the brain activity, we finally achieved the promising results for the challenging constraint-free natural image reconstruction. The semantic prior information of the stimuli was not used when training decoding model, and any category of images (not constraint by the training set) could be reconstructed theoretically. We found that the reconstructed images resembled the natural stimuli, especially in position and shape. The experimental results suggest that hierarchical visual features may be an effective tool to express the human visual processing.

Viscous sputum specimens usually cannot undergo automated extraction, and thus, a pre-homogenization process is desirable before isolating nucleic acids for real-time reverse transcription PCR. In this study, we compared three preprocessing methods [preprocessing with normal saline (NS), dithiothreitol (DTT), and proteinase K (PK)] of sputum specimens on the extraction and detection of influenza A virus (IAV) nucleic acids. Based on the experimental results of 217 specimens, we found that DTT and PK could be used to improve the homogenization effects of sputum and increase the positive rates by 5.53–6.91% higher than that of the NS group. Comparison of 49 positive specimens in all of the three groups demonstrated that the threshold cycle values of the DTT group and PK group were significantly lower and their nucleic acid concentration and A260/A280 ratio within 1.8–2.0 were higher than those of the NS group. Thus, sputum homogenization before nucleic acid extraction is essential for the accurate diagnosis of IAV infection.

Background/purpose: To evaluate the effects of attribution retraining on the perceived career barriers of undergraduate nursing students and to foster positive attributional styles. Methods: Ninety-four undergraduate nursing students were recruited and randomly divided into two groups: the attribution retraining group and the control group. All students were assessed by the perceived career barriers inventory before and after the eight-week study. Results: Attribution retraining significantly influenced the students' perceived career barriers. The mean scores of vocational knowledge, professional knowledge, and social ability of the experimental group were significantly reduced compared to the control group (p

The application of electroencephalogram (EEG) generated by human viewing images is a new thrust in image retrieval technology. A P300 component in the EEG is induced when the subjects see their point of interest in a target image under the rapid serial visual presentation (RSVP) experimental paradigm. We detected the single-trial P300 component to determine whether a subject was interested in an image. In practice, the latency and amplitude of the P300 component may vary in relation to different experimental parameters, such as target probability and stimulus semantics. Thus, we proposed a novel method, Target Recognition using Image Complexity Priori (TRICP) algorithm, in which the image information is introduced in the calculation of the interest score in the RSVP paradigm. The method combines information from the image and EEG to enhance the accuracy of single-trial P300 detection on the basis of traditional single-trial P300 detection algorithm. We defined an image complexity parameter based on the features of the different layers of a convolution neural network (CNN). We used the TRICP algorithm to compute for the complexity of an image to quantify the effect of different complexity images on the P300 components and training specialty classifier according to the image complexity. We compared TRICP with the HDCA algorithm. Results show that TRICP is significantly higher than the HDCA algorithm (Wilcoxon Sign Rank Test, p

In this study, a target analytical approach using high-performance liquid chromatography−tandem mass spectrometry (HPLC−MS/MS) was developed to simultaneously determine six isothiazolinones containing 2-Methylisothiazol-3(2H)-one (MI), 5-Chloro-2-methyl-4-isothiazolin-3-one (CMI), 1,2-benzisothiazolin-3-one (BIT), 2-Octyl-3(2H)-isothiazolinone (OIT), Dichlorooctylisothiazolinone (DCOIT), and 2-methyl-1,2-benzisothiazolin-3-one (MBIT) in water-based adhesive used for food contact materials. The main factors affecting extraction efficiency such as extraction method, extraction time, extraction solvent, and solid−liquid ratio have been evaluated by using real adhesive samples. Multiple-reaction monitoring (MRM) was used for the qualitative and quantitative analyses of targeted isothiazolinones. This method was demonstrated as an effective and reliable technique for detecting multiple isothiazolinones with satisfactory recoveries (81.5~107.3%), and the limits of detection (LOD) and quantification (LOQ) were obtained at a low level. This method was validated and applied to the determination of six isothiazolinones in commercial water-based adhesives. The present results revealed that these adhesives contained a combination of isothiazolinones (BIT, MI, CMI, and MBIT) with the concentration ranging from 2.27 to 123.5 mg/kg. To our knowledge, it is the first time it has been reported that MBIT was detected in water-based adhesives used for food contact materials, which requires a further investigation for its migration to food and the risk to human health.

Electroencephalogram (EEG) signals, which originate from neurons in the brain, have drawn considerable interests in identity authentication. In this paper, a face image-based rapid serial visual presentation (RSVP) paradigm for identity authentication is proposed. This paradigm combines two kinds of biometric trait, face and EEG, together to evoke more specific and stable traits for authentication. The event-related potential (ERP) components induced by self-face and non-self-face (including familiar and not familiar) are investigated, and significant differences are found among different situations. On the basis of this, an authentication method based on Hierarchical Discriminant Component Analysis (HDCA) and Genetic Algorithm (GA) is proposed to build subject-specific model with optimized fewer channels. The accuracy and stability over time are evaluated to demonstrate the effectiveness and robustness of our method. The averaged authentication accuracy of 94.26% within 6 s can be achieved by our proposed method. For a 30-day averaged time interval, our method can still reach the averaged accuracy of 88.88%. Experimental results show that our proposed framework for EEG-based identity authentication is effective, robust, and stable over time.

Background: Epidemiological studies have shown that hyperuricemia is associated with all-cause and cardiovascular mortality in chronic kidney disease (CKD) and hemodialysis patients. Our study investigated the influence of serum uric acid (UA) levels on survival in peritoneal dialysis (PD) patients. Methods: This was a retrospective study involving 156 subjects who had undergone PD. The patient demographics, etiology of ESRD, comorbid conditions and other laboratory parameters were collected. The subjects were divided into three groups according to their serum UA concentrations (group 1, the lowest quartile; group 2, the middle quartiles; group 3, the highest quartile). The risk of death was calculated using a multivariate Cox regression model. Results: There were 41 deaths during a follow-up period of 31.3±17.5 months. Compared with group 2, which had a mortality rate of 5.7 per 1000 person-months, the mortality rates were higher in group 1 (14.3 per 1000 person-months, p0.05) for group 1 and 2.96 (95% CI 1.29-6.80, p=0.01) for group 3. Conclusions: In PD patients, a higher serum UA level is related to increased mortality and is an independent risk factor for all-cause mortality. Uric acid levels and all-cause mortality in peritoneal dialysis patients.

The maximal information coefficient (MIC) captures dependences between paired variables, including both functional and non-functional relationships. In this paper, we develop a new method, ChiMIC, to calculate the MIC values. The ChiMIC algorithm uses the chi-square test to terminate grid optimization and then removes the restriction of maximal grid size limitation of original ApproxMaxMI algorithm. Computational experiments show that ChiMIC algorithm can maintain same MIC values for noiseless functional relationships, but gives much smaller MIC values for independent variables. For noise functional relationship, the ChiMIC algorithm can reach the optimal partition much faster. Furthermore, the MCN values based on MIC calculated by ChiMIC can capture the complexity of functional relationships in a better way, and the statistical powers of MIC calculated by ChiMIC are higher than those calculated by ApproxMaxMI. Moreover, the computational costs of ChiMIC are much less than those of ApproxMaxMI. We apply the MIC values tofeature selection and obtain better classification accuracy using features selected by the MIC values from ChiMIC.

Objective To explore the clinicopathological features of angiocentric glioma. Methods The clinical manifestations, radiologic and histopathological features and immunohistochemical results were analyzed in one case of angiocentric glioma, with reviewing of the related literatures. Results The patient was a 12-year-old girl with a 2-year history of instability of right hand and 1-year history of onset of syncope associated with twitching limbs. Magnetic resonance imaging (MRI) examination showed T1-hypointense and T2-hyperintense lesions in the left temporal-parietal lobe without obvious enhancement. Morphologically, the tumor was of diffuse growth pattern, with no boundary with normal brain tissue. The tumor was formed by monomorphous bipolar spindle cells arranged in fascicles and pseudorosettes surrounding blood vessels. Tumor cells were well-differentiated, but showed an infiltrating biological behavior. No mitosis was apparent. Microvascular proliferation and necrosis were absent. Immunohistochemically, tumor cells were reactive for glial fibrillary acidic protein (GFAP), nestin and EMA, and the latter showed an characteristic 'dot-like' pattern. Tumor cells were negative for cytokeratin (CK), E-cadherin, synaptophysin (Syn), neurofilament (NF), NeuN and P53. Ki⁃67 labelling index was less than 1%. Conclusion Angiocentric glioma has both the features of ependymoma and diffuse astrocytoma. Its diagnosis mainly depends on histopathologic analysis and immunohistochemical staining.DOI：10.3969/j.issn.1672⁃6731.2011.06.004

Strain DCS523 was isolated from the branch tissue of Daphniphyllum longeracemosum and determined to be a Penicillium sp. according to the ITS sequence analysis. The extracts from the PDA solid fermentation media of Penicillium sp. DCS523 were purified to give two new chroman derivatives as well as six known compounds. Based on their spectral data the new compounds were identified as (Z)-6-acetyl- 3-(1,2-dihydroxypropylidene)-5-hydroxy-8-methylchroman-2-one (1) and 6-acetyl-2α,5- dihydroxy-2-(2-hydroxypropyl)- 3α,8-dimethylchroman (2), respectively.

The strain T1BF was isolated from the old bast tissue of Taxus yunnanensis and determined to be a member of Talaromyces. The extracts from the solid fermentation of Talaromycessp. T1BF were purified and obtained three azaphilones, including a new one. They were identified on the basis of spectral data as 6α-hydroxy-7β-methyl-8-oxo-3-((E)- prop-1-en-1-yl)-5,6,7,8-tetrahydro-1H-isochromen-7-yl-4'-hydroxy-2'-methoxy-6'-methyl- benzoate, named as kasanosin C (1), entonaemin A (2) and (+)-mitorubrin (3).

Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods.

In order to grasp the water quality change trend and predict the future water quality characteristics of the bicarbonate mineral water in WUDALIANCHI, using the measured data from 2008 to 2016 of north drink spring in WUDALIANCHI as the predicted sample, carbon dioxide, total soluble solids, strontium and metasilicic acid which can divide mineral water type as analysis factor, the BP neural network combination forecast model was contructed. The results showed that the BP neural network combination forecast model was obviously more precise and better than grey system model, its average relative error was controlled within 5%. The results indicated that the BP neural network combination forecast model can effectively predict the change trend of water quality of bicarbonate mineral water in WUDALIANCHI.

The electroencephalogram (EEG) signal represents a subject’s specific brain activity patterns and is considered as an ideal biometric given its superior forgery prevention. However, the accuracy and stability of the current EEG-based person authentication systems are still unsatisfactory in practical application. In this paper, a multi-task EEG-based person authentication system combining eye blinking is proposed, which can achieve high precision and robustness. Firstly, we design a novel EEG-based biometric evoked paradigm using self- or non-self-face rapid serial visual presentation (RSVP). The designed paradigm could obtain a distinct and stable biometric trait from EEG with a lower time cost. Secondly, the event-related potential (ERP) features and morphological features are extracted from EEG signals and eye blinking signals, respectively. Thirdly, convolutional neural network and back propagation neural network are severally designed to gain the score estimation of EEG features and eye blinking features. Finally, a score fusion technology based on least square method is proposed to get the final estimation score. The performance of multi-task authentication system is improved significantly compared to the system using EEG only, with an increasing average accuracy from 92.4% to 97.6%. Moreover, open-set authentication tests for additional imposters and permanence tests for users are conducted to simulate the practical scenarios, which have never been employed in previous EEG-based person authentication systems. A mean false accepted rate (FAR) of 3.90% and a mean false rejected rate (FRR) of 3.87% are accomplished in open-set authentication tests and permanence tests, respectively, which illustrate the open-set authentication and permanence capability of our systems.

Constitutive activation of the transcription factor nuclear factor-κB (NF-κB) is involved in tumorigenesis and chemo-resistance. As the key regulator of NF-κB, IKKβ is a major therapeutic target for various cancers. Trichothecin (TCN) is a metabolite isolated from an endophytic fungus of the herbal plant Maytenus hookeri Loes. In this study, we evaluated the anti-tumor activity of TCN and found that TCN markedly inhibits the growth of cancer cells with constitutively activated NF-κB. TCN induces G0/G1 cell cycle arrest and apoptosis in cancer cells, activating pro-apoptotic proteins, including caspase-3, -8 and PARP-1, and decreasing the expression of anti-apoptotic proteins Bcl-2, Bcl-xL, and survivin. Reporter activity assay and target genes expression analysis illustrated that TCN works as a potent inhibitor of the NF-κB signaling pathway. TCN inhibits the phosphorylation and degradation of IκBα and blocks the nuclear translocation of p65, and thus inhibits the expression of NF-κB target genes XIAP, cyclin D1, and Bcl-xL. Though TCN does not directly interfere with IKKβ kinase, it suppresses the phosphorylation of IKKβ. Overexpression of constitutively activated IKKβ aborted TCN induced cancer cell apoptosis, whereas knockdown of endogenous IKKβ with siRNA sensitized cancer cells toward apoptosis induced by TCN. Moreover, TCN showed a markedly weaker effect on normal cells. These findings suggest that TCN may be a potential therapeutic candidate for cancer treatment, targeting NF-κB signaling.