Explore the vast range of titles available.

In the human-computer interaction (HCI), electroencephalogram (EEG) access for automatic emotion recognition is an effective way for robot brains to perceive human behavior. In order to improve the accuracy of the emotion recognition, a method of EEG access for emotion recognition based on a deep hybrid network was proposed in this paper. Firstly, the collected EEG was decomposed into four frequency band signals, and the multiscale sample entropy (MSE) features of each frequency band were extracted. Secondly, the constructed 3D MSE feature matrices were fed into a deep hybrid network for autonomous learning. The deep hybrid network was composed of a continuous convolutional neural network (CNN) and hidden Markov models (HMMs). Lastly, HMMs trained with multiple observation sequences were used to replace the artificial neural network classifier in the CNN, and the emotion recognition task was completed by HMM classifiers. The proposed method was applied to the DEAP dataset for emotion recognition experiments, and the average accuracy could achieve 79.77% on arousal, 83.09% on valence, and 81.83% on dominance. Compared with the latest related methods, the accuracy was improved by 0.99% on valence and 14.58% on dominance, which verified the effectiveness of the proposed method.

Although PD-L1/PD-1 blockade therapy has been approved to treat many types of cancers, the majority of patients with solid tumors do not respond well, but the underlying reason remains unclear. Here, we studied ovarian cancer (OvCa), a tumor type generally resistant to current immunotherapies, to investigate PD-1-independent immunosuppression. We found that PD-L1 was not highly expressed in the tumor microenvironment (TME) of human OvCa. Instead, B7-H3, another checkpoint molecule, was highly expressed by both tumor cells and tumor-infiltrating antigen-presenting cells (APCs), which correlated with T-cell exhaustion in patients. Using ID8 OvCa mouse models, we found that B7-H3 expressed on tumor cells, but not host cells, had a dominant role in suppressing antitumor immunity. Therapeutically, B7-H3 blockade, but not PD-1 blockade, prolonged the survival of ID8 tumor-bearing mice. Collectively, our results demonstrate that tumor-expressed B7-H3 inhibits the function of CD8+ T cells and suggest that B7-H3 may be a target in patients who are not responsive to PD-L1/PD-1 inhibition, particularly OvCa patients.

Programmed cell death protein 1 (PD-1)/programmed death ligand 1 (PD-L1) pathway blockade has impressively benefited cancer patients with a wide spectrum of tumors. However, its efficacy in colorectal cancer (CRC) is modest, and only a small subset of patients benefits from approved checkpoint inhibitors. Newer checkpoints that target additional immunomodulatory pathways are becoming necessary to activate durable antitumor immune responses in patients with CRC. In this review, we evaluated the mRNA expression of all 10 reported B7 family members in human CRC by retrieving and analyzing the TCGA database and reviewed the current understanding of the top three B7 family checkpoint molecules (B7-H3, VISTA, and HHLA2) with the highest mRNA expression, introducing them as putative therapeutic targets in CRC.

In order to solve the problem that the emotion recognition rate of single-mode physiological signals is not high in the physiological signals based emotion recognition, in this paper, we propose a convolutional recurrent neural network based method for multi-modal physiological signal emotion recognition task. The method used convolutional neural network to learn the spatial representations of multi-channel EEG signals and the Long Short-term Memory network to learn the temporal representations of peripheral physiological signals (EOG, EMG, GSR, RSP, BVP, and TMP). The two representations are combined for emotion recognition and classification. In the two emotion dimensions of Arousal and Valence, our experiments conducted on the open source dataset DEAP shows that, this method achieve 89.68% and 89.19% average accuracy in the EEG emotion classification, 63.06% and 62.41% average accuracy in the peripheral physiological signal emotion classification, 93.06% and 91.95% average accuracy in the combined feature emotion classification. The experimental results show that the convolutional recurrent neural network based method that we proposed efficiently extract multi-modal physiological signal feature to improve the emotion recognition performance.

The consumption of cut roses (Rosa hybrida) has always ranked first in the world. However, it is vulnerable to rapid petal and leaf wilting due to leaf stomatal water loss, which seriously affects its ornamental quality and economic value. Stomatal movement, a key in plant physiological processes, is influenced by potassium and nitrate. Advancing comprehension of its physiological and molecular mechanism holds promise for preserving the freshness of cut roses. This study observed the impacts of different concentrations of KNO3 vase treatments on stomatal opening and water loss in cut rose ‘Carola’ leaves, as well as their transcriptional responses to KNO3. Water loss rates were influenced by KNO3 concentrations, with the 25 and 75 mmol/L treatments exhibiting the highest water loss rates. The stomatal aperture reached its widest value when treated with 75 mmol/L KNO3. Transcriptional sequencing analysis was performed to identify differentially expressed genes (DEGs) of which 5456 were up-regulated, and 6607 were down-regulated associated with photosynthesis, starch and sucrose metabolism, metabolic pathways, plant-pathogen interaction, plant hormone signal transduction, and related pathways. 246 DEGs were selected related to response to KNO3 treatment, of which gene ontology (GO) enrichment were nitrate and terpenoid metabolism, ion transport, and response to stimuli. Further heatmap analysis revealed that several genes related to nitrate transport a metabolism, K+ transport, vacuoles, and aquaporin were in close association with the response to KNO3 treatment. Weighted gene co-expression network analysis (WGCNA) revealed that hub genes, including LAX2, TSJT1, and SCPL34 were identified in turquoise, black, and darkgreen module. Transcription factors such as NAC021, CDF3, ERF053, ETR2, and ARF6 exhibited regulatory roles in the response to KNO3 treatment under light conditions. These findings provide valuable insights into the physiological and molecular mechanisms underlying the response of cut rose leaves to KNO3 treatment.

Heartbeat interval can be detected from ballistocardiogram (BCG) signals in a non-contact manner. Conventional methods achieved heartbeat detection from different perspectives, where template matching (TM) and deep learning (DL) were based on the similarity of neighboring heartbeat episodes and robust spatio-temporal characteristics, respectively, and thus, performed varied from case to case. Inspired by the above facts, we propose confidence analysis-based hybrid heartbeat detection using both TM and DL, and further explore the advantages of both methods in various scenarios. To be specific, the confidence of the heartbeat detection results was evaluated by the consistency of signal morphology and the variability of the detected heartbeat intervals, which could be formulated by the averaged correlation between each heartbeat episode and the detected template and the normalized standard deviation among detected heartbeat intervals, respectively, where the results with higher confidence were remained. In order to validate the effectiveness of the proposed hybrid method, we conducted experiments using practical clinical BCG dataset with 34 subjects including 924,235 heartbeats. Numerical results showed that the proposed hybrid method achieved an average absolute interval error of 20.73 ms, yielding a reduction of 29.28 ms and 10.13 ms compared to solo TM and DL methods, respectively. Besides, case study showed the robustness of heartbeat detection of TM and DL to individual differences and signal quality, respectively, and in turn, validated that the hybrid method could benefit from the complementary advantages of both methods, which demonstrated the superiority of the proposed hybrid method in practical BCG monitoring scenarios.

Epithelial‐mesenchymal transition (EMT) plays an important role in idiopathic pulmonary fibrosis (IPF). Astragaloside IV (ASV), a natural saponin from astragalus membranaceus, has shown anti‐fibrotic property in bleomycin (BLM)‐induced pulmonary fibrosis. The current study was undertaken to determine whether EMT was involved in the beneficial of ASV against BLM‐induced pulmonary fibrosis and to elucidate its potential mechanism. As expected, in BLM‐induced IPF, ASV exerted protective effects on pulmonary fibrosis and ASV significantly reversed BLM‐induced EMT. Intriguing, transforming growth factor‐β1 (TGF‐β1) was found to be up‐regulated, whereas Forkhead box O3a (FOXO3a) was hyperphosphorylated and less expressed. However, ASV treatment inhibited increased TGF‐β1 and activated FOXO3a in lung tissues. TGF‐β1 was administered to alveolar epithelial cells A549 to induce EMT in vitro. Meanwhile, stimulation with TGF‐β1‐activated phosphatidylinositol 3 kinase/protein kinase B (PI3K/Akt) pathway and induced FOXO3a hyperphosphorylated and down‐regulated. It was found that overexpression of FOXO3a leading to the suppression of TGF‐β1‐induced EMT. Moreover, ASV treatment, similar with the TGF‐β1 or PI3K/Akt inhibitor, reverted these cellular changes and inhibited EMT in A549 cells. Collectively, the results suggested that ASV significantly inhibited TGF‐β1/PI3K/Akt‐induced FOXO3a hyperphosphorylation and down‐regulation to reverse EMT during the progression of fibrosis.

The severe global warming issue currently threatens humans’ existence and development. Countries and international organizations have effectively implemented policies to reduce carbon emissions and investigate low-carbon growth strategies. Reducing carbon emissions is a hot topic that academics and government policy-making departments are concerned about.Through necessary condition analysis (NCA) and fuzzy set qualitative comparative analysis(fsQCA), this paper investigates local governments’ configuration linkage effect and path choice to improve carbon emission performance from six dimensions: energy consumption, industrial structure, technological innovation, government support, economic development, and demographic factors. The research findings include the following: (1) Individual condition does not represent necessary conditions for the government’s carbon performance. Among the two sets of second-order equivalence configurations(S and Q) (five high-level carbon performance configurations), those dominated by economic development or low energy consumption can produce high-level carbon performance. Therefore, the six antecedent conditions dimensions work together to explain how the government can create high levels of carbon performance. (2)According to the regional comparison, China’s eastern, central, and western regions exhibit similarities and differences in the driving forces behind high carbon emission performance. All three regions can demonstrate carbon emission performance when all the factors are combined. However, when constrained by the conditions of each region’s resource endowment, the eastern region emphasizes the advantage of economic and technological innovation, the central region favors government support and demographic factors, and the western region prefers upgrading industrial structure based on a specific level of economic development.

INTRODUCTION:Postendoscopic submucosal dissection (ESD) coagulation syndrome (PECS) prevention is one of the common postoperative complications of colorectal ESD. Considering the increasing incidence of PECS, it is critical to investigate various prevention methods. The objective of this study was to evaluate the efficacy of transrectal drainage tubes (TDTs) in PECS prevention in patients following colorectal ESD.METHODS:From July 2022 to July 2023, a multicenter, randomized controlled clinical trial was conducted in 3 hospitals in China. Patients with superficial colorectal lesions ≥20 mm who had undergone ESD for a single lesion were enrolled. Initially, 229 patients were included in the study and 5 were excluded. Two hundred twenty-four were randomly assigned to the TDT and non-TDT group in the end. This open-label study utilized a parallel design with a 1:1 allocation ratio, and endoscopists and patients were not blind to the randomization, and a 24 Fr drainage tube was inserted approximately 10-15 cm above the anus after the ESD under the endoscopy and tightly attached to a drainage bag. The TDTs were removed in 1-3 days following the ESD.RESULTS:A total of 229 eligible patients were enrolled in this study, and 5 patients were excluded. Ultimately, 224 patients were assigned to the TDT group (n = 112) and non-TDT group (n = 112). The median age for the patients was 63.45 years (IQR 57-71; 59 men [52.68%]) in the TDT group and 60.95 years (IQR 54-68; 60 men [53.57%]) in the non-TDT group. Intention-to-treat analysis showed patients in the TDT group had a lower incidence of PECS than patients in the non-TDT group (7 [6.25%] vs 20 [17.86%]; relative risk, 0.350; 95% confidence interval [CI], 0.154-0.795; P = 0.008). In the subgroup analysis, TDTs were found to prevent PECS in patients of the female gender (odd ratio, 0.097; 95% CI, 0.021-0.449; P = 0.001), tumor size <4 cm (odd ratio, 0.203; 95% CI, 0.056-0.728; P = 0.011), tumor located in the left-sided colorectum (odd ratio, 0. 339 95% CI, 0.120-0.957; P = 0.035), and shorter procedure time (<45 minutes) (odd ratio, 0.316; 95% CI, 0.113-0.879; P = 0.023). The tube fell off in 1 case (0.89%) accidentally ahead of time. No TDT-related complication was observed.DISCUSSION:The results from this randomized clinical study indicate that the application of TDTs effectively reduced the incidence of PECS in patients after colorectal ESD (chictr.org.cn Identifier: ChiCTR2200062164).

With the exacerbation of population aging, the health issues of middle-aged and older adults have increasingly become a focus of attention. The widespread use of the internet has created conditions for promoting the health of this demographic. However, little is known about the effects of information access in promoting the relationship between internet use and the health of middle-aged and older adults. This study aims to examine the relationship between internet use and multidimensional health in middle-aged and older adults, as well as the mediating effect of information access. Moreover, this study will explore the relationship between other dimensions of internet use (purposes and frequency) and health. Data were sourced from the China General Social Survey conducted in 2018. Health outcomes, including self-rated, physical, and mental health, were assessed using the 5-level self-rated health scale, the 5-level basic activities of daily living scale, and the 5-level depression scale, respectively. The ordinal logistic regression model was used to examine the relationship between internet use and health among middle-aged and older adults. Additionally, the Karlson-Holm-Breen decomposition method was used to examine the mediation effect of information access. To address endogeneity issues, the two-stage least squares approach was applied. In our sample, nearly half (n=3036, 46.3%) of the respondents use the internet. Regression analyses revealed that internet use was positively associated with self-rated health (odds ratio [OR] 1.55, 95% CI 1.39-1.74; P<.001), physical health (OR 1.39, 95% CI 1.25-1.56; P<.001), and mental health (OR 1.33, 95% CI 1.19-1.49; P<.001) of middle-aged and older adults. Various dimensions of internet use positively contribute to health. In addition, information access significantly mediated the relationship between internet use and self-rated health (β=.28, 95% CI 0.23-0.32), physical health (β=.40, 95% CI 0.35-0.45), and mental health (β=.16, 95% CI 0.11-0.20). Furthermore, there were significant differences in the relationship between internet use and health among advantaged and disadvantaged groups. The study showed that different dimensions of internet use are associated with better self-rated health, better physical health, and better mental health in middle-aged and older adults. Information access mediates the relationship between internet use and health. This result emphasizes the significance of promoting internet access as a means to enhance the health of middle-aged and older adults in China.