Associations between prenatal exposure to per- and polyfluoroalkyl substances and plasma immune molecules in three-year-old children in China.

BACKGROUND: Many studies have reported that prenatal exposure to Per- and Polyfluoroalkyl Substances (PFASs) can disrupt immune function. However, little is known about the effects of PFASs on immune molecules. The study analyzed the association between prenatal exposure to mixed and single PFASs and plasma immune molecules in three-year-old children. METHODS: Ten PFASs were measured in umbilical cord serum, while peripheral blood samples were collected at age three to measure immune molecules. Associations between exposure to individual and combined PFASs and immune molecules were analyzed using Generalized Linear Models and Weighted Quantile Sum (WQS) regression. RESULTS: (1) Interleukin-4 (IL-4) increased by 23.85% (95% CI:2.99,48.94) with each doubling of Perfluorooctanoic Acid (PFOA), and Interleukin-6 (IL-6) increased by 39.07% (95%CI:4.06,85.86) with Perfluorotridecanoic Acid (PFTrDA). Elevated PFOA and Perfluorononanoic Acid (PFNA) were correlated with increases of 34.06% (95% CI: 6.41, 70.28) and 24.41% (95% CI: 0.99, 53.27) in Eotaxin-3, respectively. Additionally, the doubling of Perfluorohexane Sulfonic Acid (PFHxS) was associated with a 9.51% decrease in Periostin (95% CI: -17.84, -0.33). (2) The WQS analysis revealed that mixed PFASs were associated with increased IL-6 (ß = 0.37, 95%CI:0.04,0.69), mainly driven by PFTrDA, PFNA, and 8:2 Chlorinated Perfluoroethyl Sulfonamide (8:2 Cl-PFESA). Moreover, mixed PFASs were linked to an increase in Eotaxin-3 (ß = 0.32, 95% CI: 0.09,0.55), primarily influenced by PFOA, PFTrDA, and Perfluorododecanoic Acid (PFDoDA). CONCLUSIONS: Prenatal PFASs exposure significantly alters the levels of immune molecules in three-year-old children, highlighting the importance of understanding environmental impacts on early immune development.

Corrigendum: Dynamic evolution of left ventricular strain and microvascular perfusion assessed by speckle tracking echocardiography and myocardial contrast echocardiography in diabetic rats: effect of dapagliflozin.

[This corrects the article DOI: 10.3389/fcvm.2023.1109946.].

Railway track settlement patterns and control measures for multi-tunnel construction underneath a station track group: a case study.

This paper is based on the proximity engineering project of the Baishiyi tunnel group passing under the Chongqing West Station track group. Considering the train load and the spatial relationship of the tunnel and track groups, the settlement patterns, horizontal displacement, and differential settlement of the tunnel-strata-tracks system during the excavation process are studied through theoretical calculations and numerical simulation methods. The results indicate that the tunnel vault, strata, and track settlement deformation patterns are similar. Throughout the tunnel construction process, the tracks underwent uplift, settlement, and eventually stabilized. The settlement trough formed by the excavation of the three tunnels below the track group has an impact range of 25-145 m. Between 35 and 75 m, the differential settlement of the double track gradually increases with excavation. As the tunnel face reaches 75 m, the track differential settlement gradually converges and tends to stabilize. To minimize the impact of underpass tunnel construction on track groups, it is recommended to use a combination of full-section hole grouting and surface reinforcement grouting for ground reinforcement. Additionally, optimizing the construction parameters, including the step length and primary support closure time, and strengthening the locking anchor can further reduce the impact.

An Intersubject Brain-Computer Interface Based on Domain-Adversarial Training of Convolutional Neural Network for Online Attention Decoding.

Attention decoding plays a vital role in daily life, where electroencephalography (EEG) has been widely involved. However, training a universally effective model for everyone is impractical due to substantial interindividual variability in EEG signals. To tackle the above challenge, we propose an end-to-end brain-computer interface (BCI) framework, including temporal and spatial one-dimensional (1D) convolutional neural network and domain-adversarial training strategy, namely DA-TSnet. Specifically, DA-TSnet extracts temporal and spatial features of EEG, while it is jointly supervised by task loss and domain loss. During training, DA-TSnet aims to maximize the domain loss while simultaneously minimizing the task loss. We conduct an offline analysis, simulate online experiments on a self-collected dataset of 85 subjects, and real online experiments on 22 subjects. Main results: DA-TSnet achieves a leave-one-subject-out (LOSO) cross-validation (CV) classification accuracy of 89.40% ± 9.96%, outperforming several state-of-the-art attention EEG decoding methods. In simulated online experiments, DA-TSnet achieves an outstanding accuracy of 88.07% ± 11.22%. In real online experiments, it achieves an average accuracy surpassing 86%. Significance: An end-to-end network framework does not rely on elaborate preprocessing and feature extraction steps, which saves time and human workload. Moreover, our framework utilizes domain-adversarial training neural network (DANN) to tackle the challenge posed by the high interindividual variability in EEG signals, which has significant reference value for handling other EEG signal decoding issues. Last, the performance of the DA-TSnet framework in offline and online experiments underscores its potential to facilitate more reliable applications.

Construction and enhancement of government capacity for international communication and promotion of Chinese Wushu.

BACKGROUND: In the process of international communication in Chinese Wushu (ICCW), the government controls the orientation, scale, pace. However, the ICCW currently lacks a standardised government capacity structural system, and a detailed study of framework construction may be required to ensure the smooth development of the ICCW. OBJECTIVES: This study aims to clarify these elements and construct a framework for a governmental capacity system for ICCW. METHODS: For this purpose, an expert interview outline was designed, and in-depth interviews were conducted with 61 experts. Using grounded theory in the qualitative research method, NVivo 12 software was used to conduct a three-level coding analysis of the interview text for data processing and analysis. RESULTS: We extracted 58 opening codes and 11 tree nodes and categorised them into three core categories: supply side government capacity, environment-side government capacity, and demand-side government capacity, accounting for 62.36 %, 24.76 %, and 12.86 % of the total, respectively, which jointly constructed the framework structure system of the governmental capacity system for the ICCW. CONCLUSIONS: This study found that these three-dimensional government capacities have synergistic effects and that multiple measures work together. The government should ensure the supply side's direct promotion effect; the environmental side's indirect influencing effect; and the demand side's internal driving effect to promote ICCW. Meanwhile, a closed-loop systematic study of communication processes should be conducted in combination with communication organisations and individuals.

The Association between Prenatal Exposure to Per- and Polyfluoroalkyl Substances and Respiratory Tract Infections in Preschool Children: A Wuhan Cohort Study.

This study investigates the association between prenatal exposure to per- and polyfluoroalkyl substances (PFASs) and the incidence and frequency of respiratory tract infections (RTIs) in preschool children. We selected 527 mother-infant pairs from Wuhan Healthy Baby Cohort (WHBC), China. Ten PFASs were measured in umbilical cord serum, and we collected data on common RTIs in preschool children aged 4 years through a questionnaire. Associations of single PFASs with the incidence and frequency of RTIs were analyzed via Logistic regression and Poisson regression, while the collective effect was assessed by weighted quantile sum (WQS) regression. Furthermore, stratified and interaction analyses were performed to evaluate if there were sex-specific associations. We found a positive correlation between perfluorododecanoic acid (PFDoDA) and the incidence of tonsillitis, with several PFASs also showing positive associations with its frequency. Moreover, perfluorotridecanoic acid (PFTrDA) showed a positive link with the frequency of common cold. The results of WQS regression revealed that after adjusting for other covariates, PFASs mixture showed a positive association with the incidence of tonsillitis, the frequency of common cold, and episodes. In particular, perfluoroundecanoic acid (PFUnDA), PFDoDA, PFTrDA, perfluorodecanoic acid (PFDA) and 8:2 chlorinated polyfluorinated ether sulfonic acid (8:2 Cl-PFESA) had the most significant impact on this combined effect. The results suggest that both single and mixed exposures to PFASs may cause RTIs in preschool children. However, there was no statistically significant interaction between different PFASs and sex.

An EEG-based attention recognition method: fusion of time domain, frequency domain, and non-linear dynamics features.

Introduction: Attention is a complex cognitive function of human brain that plays a vital role in our daily lives. Electroencephalogram (EEG) is used to measure and analyze attention due to its high temporal resolution. Although several attention recognition brain-computer interfaces (BCIs) have been proposed, there is a scarcity of studies with a sufficient number of subjects, valid paradigms, and reliable recognition analysis across subjects. Methods: In this study, we proposed a novel attention paradigm and feature fusion method to extract features, which fused time domain features, frequency domain features and nonlinear dynamics features. We then constructed an attention recognition framework for 85 subjects. Results and discussion: We achieved an intra-subject average classification accuracy of 85.05% ± 6.87% and an inter-subject average classification accuracy of 81.60% ± 9.93%, respectively. We further explored the neural patterns in attention recognition, where attention states showed less activation than non-attention states in the prefrontal and occipital areas in α, ß and θ bands. The research explores, for the first time, the fusion of time domain features, frequency domain features and nonlinear dynamics features for attention recognition, providing a new understanding of attention recognition.

A study of transverse maxillomandibular discrepancy and dental compensation in early mixed dentition with skeletal Class III malocclusion without posterior crossbite.

OBJECTIVE: To evaluate transverse maxillomandibular discrepancy and dental compensation in first molar areas in 7- to 9-year-old children with skeletal Class III malocclusion without posterior crossbite using cone-beam computed tomography (CBCT). METHODS: The sample of this retrospective study consisted of 60 children (7 to 9 years old), who were divided into the skeletal Class III malocclusion group (study group, skeletal Class III malocclusion without posterior crossbite, N = 31) and the Class I occlusion group (control group, Class I occlusion with one or two impacted teeth, N = 30). CBCT data were obtained from the database of the Department of Radiology of Hospital of Stomatology, Shandong University. For three-dimensional reconstruction of the head, the dental arch width, basal bone width, and buccolingual inclination angle were measured using MIMICS 21.0 software. Independent-sample t tests were used to compare the two groups. RESULTS: The mean age of the children was 8.18±0.83years. The width of the maxillary basal bone was significantly smaller in the skeletal Class III malocclusion group (59.75 ± 3.14 mm) than in the Class I occlusion group (62.39 ± 3.01 mm) (P < 0.01). The mandibular basal bone width was significantly larger in the skeletal Class III malocclusion group (60.00 ± 2.56 mm) than in the Class I occlusion group (58.19 ± 2.42 mm) (P < 0.01). The difference in the width of the maxillary and mandibular bases in the skeletal Class III malocclusion group (-0.25 ± 1.73 mm) was significantly different from that in the Class I occlusion group (4.20 ± 1.25 mm) (P < 0.01). However, there was no significant difference in the upper or lower dental arch width between the two groups (P > 0.05). The buccal inclination of the maxillary molars in the skeletal Class III malocclusion group (31.4° ± 8.9°) was significantly higher than that in the Class I occlusion group (17.64° ± 7.3°) (P < 0.01), as was the lingual inclination angle of mandibular molars (45.24° ± 8.3° vs. 37.96° ± 10.18°; P < 0.01). CONCLUSION: Transverse maxillary and mandibular discrepancies in the posterior area and transverse dental compensation were found in the early mixed dentition of patients with skeletal Class III malocclusion without posterior crossbite. This suggests that even in the absence of posterior crossbite, maxillary expansion can be attempted to correct the maxillomandibular transverse discrepancy.

Risk factors associated with left atrial appendage thrombosis in patients with non-valvular atrial fibrillation by transesophageal echocardiography.

PURPOSE: This study investigated possible mechanism of left atrial appendage (LAA) thrombosis and constructed a model to evaluate the future risk of LAA thrombosis and spontaneous echo contrast (SEC) in non-valvular atrial fibrillation (NVAF) patients. METHODS: This retrospective study included 2591 patients diagnosed with NVAF. Patients were divided based on the presence of transesophageal echocardiography (TEE) into a thrombus group, SEC group, and control group. General, biochemical, and echocardiography data of the three groups were analyzed. The variables independently associated with LAA thrombosis and SEC were determined by the logistic regression analysis. A nomogram was constituted based on the regression analysis and the discriminatory ability was analyzed by receiver operating characteristic (ROC) curve. RESULTS: LAA thrombosis and SEC were present in 110 (4.2%) patients and 103 (3.9%) patients, respectively. AF type (OR = 1.857), previous stroke (OR = 1.924), fibrinogen (OR = 1.636), diameters of the left atria (OR = 1.094), left ventricular ejection fraction (OR = 0.938), and LAA maximum caliber (OR = 1.238) resulted as independent risk factors for LAA thrombosis and SEC. The area under curve of the nomogram established by multivariate logistic regression was 0.824. Conclusions; Through the study, 6 independent risk factors related to the LAA thrombosis and SEC were found, and an effective nomogram was constructed to predict the LAA thrombosis and SEC in NVAF patients.

STGATE: Spatial-temporal graph attention network with a transformer encoder for EEG-based emotion recognition.

Electroencephalogram (EEG) is a crucial and widely utilized technique in neuroscience research. In this paper, we introduce a novel graph neural network called the spatial-temporal graph attention network with a transformer encoder (STGATE) to learn graph representations of emotion EEG signals and improve emotion recognition performance. In STGATE, a transformer-encoder is applied for capturing time-frequency features which are fed into a spatial-temporal graph attention for emotion classification. Using a dynamic adjacency matrix, the proposed STGATE adaptively learns intrinsic connections between different EEG channels. To evaluate the cross-subject emotion recognition performance, leave-one-subject-out experiments are carried out on three public emotion recognition datasets, i.e., SEED, SEED-IV, and DREAMER. The proposed STGATE model achieved a state-of-the-art EEG-based emotion recognition performance accuracy of 90.37% in SEED, 76.43% in SEED-IV, and 76.35% in DREAMER dataset, respectively. The experiments demonstrated the effectiveness of the proposed STGATE model for cross-subject EEG emotion recognition and its potential for graph-based neuroscience research.

A novel semi-supervised meta learning method for subject-transfer brain-computer interface.

The brain-computer interface (BCI) provides a direct communication pathway between the human brain and external devices. However, the models trained for existing subjects perform poorly on new subjects, which is termed the subject calibration problem. In this paper, we propose a semi-supervised meta learning (SSML) method for subject-transfer calibration. The proposed SSML learns a model-agnostic meta learner with existing subjects and then fine-tunes the meta learner in a semi-supervised learning manner, i.e. using a few labelled samples and many unlabelled samples of the target subject for calibration. It is significant for BCI applications in which labelled data are scarce or expensive while unlabelled data are readily available. Three different BCI paradigms are tested: event-related potential detection, emotion recognition and sleep staging. The SSML achieved classification accuracies of 0.95, 0.89 and 0.83 in the benchmark datasets of three paradigms. The runtime complexity of SSML grows linearly as the number of samples of target subject increases so that is possible to apply it in real-time systems. This study is the first attempt to apply semi-supervised model-agnostic meta learning methodology for subject calibration. The experimental results demonstrated the effectiveness and potential of the SSML method for subject-transfer BCI applications.

Dynamic evolution of left ventricular strain and microvascular perfusion assessed by speckle tracking echocardiography and myocardial contrast echocardiography in diabetic rats: Effect of dapagliflozin.

Background: This experimental study aimed to determine the dynamic changes in myocardial strain and microvascular perfusion in diabetic rats by comprehensive echocardiography while evaluating the effect of dapagliflozin (DAPA). Materials and methods: Male Sprague-Dawley rats (n = 128) were randomly divided into four groups based on the presence or absence of a high-fat diet and streptozotocin-induced diabetes with or without DAPA treatment (n = 32/group). Serial conventional ultrasound, two-dimensional speckle tracking echocardiography (2D-STE) and myocardial contrast echocardiography (MCE) were performed at 2, 4, 6, and 8 weeks, and left ventricular global longitudinal strain (GLS), myocardial blood flow velocity (MBFV), myocardial blood flow (MBF), and myocardial blood volume (MBV) were determined. All animals were sacrificed immediately after the last echo measurement for histopathological assessment. Results: Despite similar conventional Doppler-echo indexes among the groups at 2, 4, 6, and 8 weeks (p > 0.05), left ventricular GLS, MBFV, MBF, and MBV were decreased at 8 weeks in diabetic rats (p < 0.05) as detected by both 2D-STE and MCE. These indexes were significantly improved at 6 and 8 weeks after treatment with DAPA for diabetic rats (p < 0.05), reaching similar values observed in non-diabetic controls. DAPA treatment was associated with increased myocardial vacuolization and microvessel density and reduced interstitial fibrosis in diabetic rats. Conclusions: Combined 2D-STE and MCE is sensitive for detecting left ventricular deformity and impaired microvascular perfusion in prediabetes and the early stage of diabetes mellitus. DAPA exerts a beneficial effect on protecting myocardial perfusion in diabetic rats.

Identification of genetic susceptibility in preterm newborns with bronchopulmonary dysplasia by whole-exome sequencing: BIVM gene may play a role.

Bronchopulmonary dysplasia (BPD) is a common chronic respiratory disease in preterm infants caused by multifactorial etiology. Genetic factors are involved in the occurrence of BPD, but studies have found that candidate genes have poor reproducibility and are influenced by ethnic heterogeneity; therefore, more exploration is still needed. We performed whole-exon sequencing in 34 preterm infants with BPD and 32 non-BPD control neonates. The data were analyzed and interpreted by Fisher difference comparison, PLINK and eQTL association analysis, KEGG and GO enrichment analysis, STRING tool, Cytoscape software, ProtParam tool, HOPE online software, and GEOR2 analysis on NCBI GEO dataset. BPD has a highly heterogeneity in different populations, and we found 35 genes overlapped with previous whole-exon sequencing studies, such as APOB gene. Arterial and epithelial cell development and energy metabolism pathways affect BPD. In this study, 24 key genes were identified, and BIVM rs3825519 mutation leads to prolonged assisted ventilation in patients with BPD. A novel DDAH1 mutation site (NM_012137: exon1: c.89 T > G: p.L30R) was found in 9 BPD patients. CONCLUSION: BIVM gene rs3825519 mutation may play a role in the pathogenesis of BPD by affecting cilia movement, and the DDAH1 and APOB genes mutations may have a pathogenic role in BPD. WHAT IS KNOWN: • Genetic factors are involved in the occurrence of bronchopulmonary dysplasia. • The candidate genes have poor reproducibility and are influenced by ethnic heterogeneity, therefore, more exploration is still needed. WHAT IS NEW: • We identified the role of susceptible SNPs in BPD in Shenzhen, China, and identified 24 key genes that influence the pathogenesis of BPD, and also found 35 genes overlapped with previous whole exon sequencing studies, such as APOB gene. • We found that BIVM and DDAH1 genes may play a pathogenic role in the pathogenesis of BPD.

A Potential Prognosis Indicator Based on P300 Brain-Computer Interface for Patients with Disorder of Consciousness.

For patients with disorders of consciousness, such as unresponsive wakefulness syndrome (UWS) patients and minimally conscious state (MCS) patients, their long treatment cycle and high cost commonly put a heavy burden on the patient's family and society. Therefore, it is vital to accurately diagnose and predict consciousness recovery for such patients. In this paper, we explored the role of the P300 signal based on an audiovisual BCI in the classification and prognosis prediction of patients with disorders of consciousness. This experiment included 18 patients: 10 UWS patients and 8 MCS- patients. At the three-month follow-up, we defined patients with an improved prognosis (from UWS to MCS-, from UWS to MCS+, or from MCS- to MCS+) as "improved patients" and those who stayed in UWS/MCS as "not improved patients". First, we compared and analyzed different types of patients, and the results showed that the P300 detection accuracy rate of "improved" patients was significantly higher than that of "not improved" patients. Furthermore, the P300 detection accuracy of traumatic brain injury (TBI) patients was significantly higher than that of non-traumatic brain injury (NTBI, including acquired brain injury and cerebrovascular disease) patients. We also found that there was a positive linear correlation between P300 detection accuracy and CRS-R score, and patients with higher P300 detection accuracy were likely to achieve higher CRS-R scores. In addition, we found that the patients with higher P300 detection accuracies tend to have better prognosis in this audiovisual BCI. These findings indicate that the detection accuracy of P300 is significantly correlated with the level of consciousness, etiology, and prognosis of patients. P300 can be used to represent the preservation level of consciousness in clinical neurophysiology and predict the possibility of recovery in patients with disorders of consciousness.

Terahertz spectroscopic detection of amino acid molecules under magnetic field.

Terahertz (THz) waves can cover the characteristic spectra of substances such as plasma, organisms, and biomolecules, whereas THz photons have low energy and do not damage biological tissues. Therefore, its absorption characteristics in the THz region can be used to characterize the internal structure of biomolecules. In this study, we designed a microfluidic chip and combined it with THz technology. The spectral intensity in descending order was found to be deionized water, phenylalanine, histidine, glycine and glutamic acid by observing the THz wave transmission in the range of 0.1-1.0 THz, comparing the frequency domain spectra of four amino acid solutions with volume fraction of 2% and deionized water. It is inferred that different molecular structures of amino acids resulted in different numbers of hydrogen bonds formed between them and water molecules, leading to different degrees of absorption of THz waves. In addition, magnetic fields parallel to the THz wave transmission were used to study the variation of different amino acids with magnetic field intensity. It is found that increasing the magnetic field strength decrease the transmission of THz waves. This is because under the action of the magnetic field, on the one hand, the hydrogen bonds formed by water molecules are strengthened and the absorption of THz waves is enhanced; on the other hand, amino acid molecules aggregate and the radius of molecular clusters increases, thus blocking the transmission of THz waves. Finally, we also calculated the electric conductivity of the solutions to prove the accuracy of the experimental results from a theoretical point of view.

Value Analysis of Neoadjuvant Radiotherapy for Breast Cancer after Modified Radical Mastectomy Based on Data Mining.

Over the last two generations, there has been a surge of interest in nonmutilating treatment for women with early breast cancer. Neoadjuvant radiation therapy, which is progressively being provided to breast cancer patients, could be used to decrease tumor burden while also providing an ability to examine treatment response. This paper aims to explore the effects of the initiation time of radiotherapy after modified adjuvant radical mastectomy on the prognosis of breast cancer. The EMR data can be used to mine hidden rules, which are of great significance for treatment and prognosis analysis. In collaboration with breast cancer, the appropriate prediction model and visualization method are selected and a visual analysis system for breast cancer group and treatment plan based on electronic medical record is constructed. Patients with multiple dimensions are reduced and clustered to form patient groups. The differences of characteristics among patient groups are intuitively displayed by using Nightingale diagram, word cloud, and time axis visualization methods. The support vector machine (SVM) model is used to predict the treatment scheme. The radiotherapy time after modified radical surgery in the two groups was within 15 weeks (observation group) and 15 weeks (routine group), respectively. The incidence of complications, local recurrence rate, progression-free survival, and quality of life scores of patients in the routine group and observation group were compared. The total incidence of complications differed significantly between the observation and routine groups. The physical function, material function, psychological function, and social function of the observation group were significantly higher than the routine group (P < 0.05). Radiotherapy within 15 weeks after modified radical mastectomy for breast cancer can not only reduce the local recurrence rate but also prolong the progression-free survival of patients, and the incidence of complications will not increase, which will greatly help improve the quality of life of patients.

Terahertz spectral properties of glucose and two disaccharides in solid and liquid states.

The vibrational and rotational frequencies of most biological macromolecules fall within the terahertz (THz) band; therefore, the THz wave has a strong ability to distinguish substances. Saccharides are important organic substances and the main source of life-sustaining activities. In this study, the spectral characteristics of D-glucose, α-lactose hydrate, and ß-maltose hydrate were measured in the solid state through THz time-domain spectroscopy in the frequency range of 0.1-2.5 THz. The crystal configurations of these three saccharides were then simulated using solid-state density functional theory, and the experimental results were found to be in good agreement with the simulation results. Furthermore, the spectral characteristics of the three saccharides in solutions were measured. Each saccharide was found to have unique spectral characteristics, and a correlation existed between the THz absorption spectra of the same substance in the solid state and aqueous solution.

Fusion of EEG-Based Activation, Spatial, and Connection Patterns for Fear Emotion Recognition.

At present, emotion recognition based on electroencephalograms (EEGs) has attracted much more attention. Current studies of affective brain-computer interfaces (BCIs) focus on the recognition of happiness and sadness using brain activation patterns. Fear recognition involving brain activities in different spatial distributions and different brain functional networks has been scarcely investigated. In this study, we propose a multifeature fusion method combining energy activation, spatial distribution, and brain functional connection network (BFCN) features for fear emotion recognition. The affective brain pattern was identified by not only the power activation features of differential entropy (DE) but also the spatial distribution features of the common spatial pattern (CSP) and the EEG phase synchronization features of phase lock value (PLV). A total of 15 healthy subjects took part in the experiment, and the average accuracy rate was 85.00% ± 8.13%. The experimental results showed that the fear emotions of subjects were fully stimulated and effectively identified. The proposed fusion method on fear recognition was thus validated and is of great significance to the development of effective emotional BCI systems.

[Research progress on the relationship between lncRNA and the pathogenesis of allergic rhinitis].

Long non-coding RNA（lncRNA） belongs to the category of non-coding RNA, which length exceeds 200 nucleotides and can hardly encode the expression of proteins. Based on the data from several clinical researches, it is considered that lncRNA not only plays the biological role in epigenetics, transcriptional and post-transcriptional levels, but also abnormally expresses in inflammatory response and the related diseases. In recent years, with the intensive study of gene expression regulation of allergic rhinitis（AR）, it has been found that a variety of non-coding RNA, including lncRNA, have close relationship with the occurrence and development of AR. This review mainly summarized the biological function, immunomodulatory effect of lncRNA and the relationship between the lncRNA and the pathogenesis of AR, providing new thoughts and strategies for the further research, prevention as well as the treatment of AR.

Advances in P300 brain-computer interface spellers: toward paradigm design and performance evaluation.

A brain-computer interface (BCI) is a non-muscular communication technology that provides an information exchange channel for our brains and external devices. During the decades, BCI has made noticeable progress and has been applied in many fields. One of the most traditional BCI applications is the BCI speller. This article primarily discusses the progress of research into P300 BCI spellers and reviews four types of P300 spellers: single-modal P300 spellers, P300 spellers based on multiple brain patterns, P300 spellers with multisensory stimuli, and P300 spellers with multiple intelligent techniques. For each type of P300 speller, we further review several representative P300 spellers, including their design principles, paradigms, algorithms, experimental performance, and corresponding advantages. We particularly emphasized the paradigm design ideas, including the overall layout, individual symbol shapes and stimulus forms. Furthermore, several important issues and research guidance for the P300 speller were identified. We hope that this review can assist researchers in learning the new ideas of these novel P300 spellers and enhance their practical application capability.