Multi-Step Subway Passenger Flow Prediction under Large Events Using Website Data

An accurate and reliable forecasting method of the subway passenger flow provides the operators with more valuable reference to make decisions, especially in reducing energy consumption and controlling potential risks. However, due to the non-recurrence and inconsistency of large events (such as sports games, concerts or urban marathons), predicting passenger flow under large events has become a very challenging task. This paper proposes a method for extracting event-related information from websites and constructing a multi-step station-level passenger flow prediction model called DeepSPE (Deep Learning for Subway Passenger Flow Forecasting under Events). Experiments on the actual data set of the Beijing subway prove the superiority of the model and the effectiveness of website data in subway passenger flow forecasting under events

A Latent-Dirichlet-Allocation Based Extension for Domain Ontology of Enterprise’s Technological Innovation

This paper proposed a method for building enterprise's technological innovation domain ontology automatically from plain text corpus based on Latent Dirichlet Allocation (LDA). The proposed method consisted of four modules: 1) introducing the seed ontology for domain of enterprise's technological innovation, 2) using Natural Language Processing (NLP) technique to preprocess the collected textual data, 3) mining domain specific terms from document collections based on LDA, 4) obtaining the relationship between the terms through the defined relevant rules. The experiments have been carried out to demonstrate the effectiveness of this method and the results indicated that many terms in domain of enterprise's technological innovation and the semantic relations between terms are discovered. The proposed method is a process of continuously cycles and iterations, that is the obtained objective ontology can be re-iterated as initial seed ontology. The constant knowledge acquisition in the domain of enterprise's technological innovation to update and perfect the initial seed ontology

IL-10 plays a central regulatory role in the cytokines induced by hepatitis C virus core protein and polyinosinic acid:polycytodylic acid

Hepatitis C virus (HCV) can cause persistent infection and chronic liver disease, and viral factors are involved in HCV persistence. HCV core protein, a highly conserved viral protein, not only elicits an immunoresponse, but it also regulates it. In addition, HCV core protein interacts with toll-like receptors (TLRs) on monocytes, inducing them to produce cytokines. Polyinosinic acid:polycytodylic acid (polyI:C) is a synthetic analogue of double-stranded RNA that binds to TLR3 and can induce secretion of type I IFN from monocytes. Cytokine response against HCV is likely to affect the natural course of infection as well as HCV persistence. However, possible effects of cytokines induced by HCV core protein and polyI:C remain to be investigated. In this study, we isolated CD14+ monocytes from healthy donors, cultured them in the presence of HCV core protein and/or polyI:C, and characterized the induced cytokines, phenotypes and mechanisms. We demonstrated that HCV core protein- and polyI:C-stimulated CD14+ monocytes secreted tumor necrosis factor-α (TNF-α), interleukin (IL)-1β, IL-10, and type I interferon (IFN). Importantly, TNF-α and IL-1β regulated the secretion of IL-10, which then influenced the expression of signal transducer and activator of transcription 1 (STAT1) and interferon regulatory factor 1 (IRF1) and subsequently the production of type I IFN. Interestingly, type I IFN also regulated the production of IL-10, which in turn inhibited the nuclear factor (NF)-κB subunit, reducing TNF-α and IL-1β levels. Therefore, IL-10 appears to play a central role in regulating the production of cytokines induced by HCV core protein and polyI:C

HCV core protein inhibits polarization and activity of both M1 and M2 macrophages through the TLR2 signaling pathway

Hepatitis C virus (HCV) establishes persistent infection in most infected patients, and eventually causes chronic hepatitis, cirrhosis, and hepatocellular carcinoma in some patients. Monocytes and macrophages provide the first line of defense against pathogens, but their roles in HCV infection remains unclear. We have reported that HCV core protein (HCVc) manipulates human blood-derived dendritic cell development. In the present study, we tested whether HCVc affects human blood-derived monocyte differentiating into macrophages. Results showed that HCVc inhibits monocyte differentiation to either M1 or M2 macrophages through TLR2, associated with impaired STATs signaling pathway. Moreover, HCVc inhibits phagocytosis activity of M1 and M2 macrophages, M1 macrophage-induced autologous and allogeneic CD4+ T cell activation, but promotes M2 macrophage-induced autologous and allogeneic CD4+ T cell activation. In conclusion, HCVc inhibits monocyte-derived macrophage polarization via TLR2 signaling, leading to dysfunctions of both M1 and M2 macrophages in chronic HCV infected patients. This may contribute to the mechanism of HCV persistent infection, and suggest that blockade of HCVc might be a novel therapeutic approach to treating HCV infection

The role of the SGK3/TOPK signaling pathway in the transition from acute kidney injury to chronic kidney disease

Introduction: Profibrotic phenotype of renal tubular epithelial cells (TECs) featured with epithelial to mesenchymal transition (EMT) and profibrotic factors secretion, and aberrant accumulation of CD206+ M2 macrophages are the key points in the transition from acute kidney injury (AKI) to chronic kidney disease (CKD). Nevertheless, the underlying mechanisms involved remain incompletely understood. Serum and glucocorticoid-inducible kinase (SGK) is a serine/threonine protein kinase, required for intestinal nutrient transport and ion channels modulation. T-LAK-cell-originated protein kinase (TOPK) is a member of the mitogen activated protein kinase family, linked to cell cycle regulation. However, little is known about their roles in AKI-CKD transition.Methods: In this study, three models were constructed in C57BL/6 mice: low dose and multiple intraperitoneal injection of cisplatin, 5/6 nephrectomy and unilateral ureteral obstruction model. Rat renal tubular epithelial cells (NRK-52E) were dealt with cisplatin to induce profibrotic phenotype, while a mouse monocytic cell line (RAW264.7) were cultured with cisplatin or TGF-β1 to induce M1 or M2 macrophage polarization respectively. And co-cultured NRK-52E and RAW264.7 through transwell plate to explore the interaction between them. The expression of SGK3 and TOPK phosphorylation were detected by immunohistochemistry, immunofluorescence and western blot analysis.Results:In vivo, the expression of SGK3 and p-TOPK were gradually inhibited in TECs, but enhanced in CD206+ M2 macrophages. In vitro, SGK3 inhibition aggravated epithelial to mesenchymal transition through reducing the phosphorylation state of TOPK, and controlling TGF-β1 synthesis and secretion in TECs. However, SGK3/TOPK axis activation promoted CD206+ M2 macrophage polarization, which caused kidney fibrosis by mediating macrophage to myofibroblast transition (MMT). When co-cultured, the TGF-β1 from profibrotic TECs evoked CD206+ M2 macrophage polarization and MMT, which could be attenuated by SGK3/TOPK axis inhibition in macrophages. Conversely, SGK3/TOPK signaling pathway activation in TECs could reverse CD206+ M2 macrophages aggravated EMT.Discussion: We revealed for the first time that SGK3 regulated TOPK phosphorylation to mediate TECs profibrotic phenotype, macrophage plasticity and the crosstalk between TECs and macrophages during AKI-CKD transition. Our results demonstrated the inverse effect of SGK3/TOPK signaling pathway in profibrotic TECs and CD206+ M2 macrophages polarization during the AKI-CKD transition

Alleviation of DSS-induced colitis in mice by a new-isolated Lactobacillus acidophilus C4

IntroductionProbiotic is adjuvant therapy for traditional drug treatment of ulcerative colitis (UC). In the present study, Lactobacillus acidophilus C4 with high acid and bile salt resistance has been isolated and screened, and the beneficial effect of L. acidophilus C4 on Dextran Sulfate Sodium (DSS)-induced colitis in mice has been evaluated. Our data showed that oral administration of L. acidophilus C4 remarkably alleviated colitis symptoms in mice and minimized colon tissue damage.MethodsTo elucidate the underlying mechanism, we have investigated the levels of inflammatory cytokines and intestinal tight junction (TJ) related proteins (occludin and ZO-1) in colon tissue, as well as the intestinal microbiota and short-chain fatty acids (SCFAs) in feces.ResultsCompared to the DSS group, the inflammatory cytokines IL-1β, IL-6, and TNF-α in L. acidophilus C4 group were reduced, while the antioxidant enzymes superoxide dismutase (SOD), glutathione (GSH), and catalase (CAT) were found to be elevated. In addition, proteins linked to TJ were elevated after L. acidophilus C4 intervention. Further study revealed that L. acidophilus C4 reversed the decrease in intestinal microbiota diversity caused by colitis and promoted the levels of SCFAs.DiscussionThis study demonstrate that L. acidophilus C4 effectively alleviated DSS-induced colitis in mice by repairing the mucosal barrier and maintaining the intestinal microecological balance. L. acidophilus C4 could be of great potential for colitis therapy

Nucleated red blood cells as a novel biomarker in the diagnosis and prediction of sepsis severity in children

IntroductionSepsis is a vitally serious disease leading to high mortality. Nucleated red blood cells (NRBCs) are present in some noninfectious diseases, but the relationship between NRBCs and sepsis in children remains unknown. The purpose of this study was to compare the clinical characteristics and outcomes of sepsis with positive NRBCs and negative NRBCs in children, and to further explore whether the count of NRBCs has a relationship with the severity of sepsis.MethodsWe enrolled children with sepsis who were admitted to the Children’s Hospital of Chongqing Medical University between January 2020 and December 2022. The children’s clinical data, laboratory data and outcomes were recorded and analyzed.ResultsOne hundred and fifteen children met the inclusion criteria in our study. Compared to negative NRBCs patients, the C-reactive protein, alanine transaminase, urea nitrogen values, mortality rate and length of hospitalization were found to be significantly increased, while platelet counts, and hemoglobin were significantly decreased in sepsis patients with positive NRBC (P < 0.05). Receiver operating characteristic (ROC) curves analysis showed that the optimal cutoff value of the NRBC count in the diagnosis of severe sepsis was 3, with a sensitivity of 87.5% and specificity of 94.9%. The area under the ROC curve was 0.877 (95% CI: 0.798-0.957).DiscussionThese findings demonstrated that NRBC count has the potential to be a biomarker for the diagnosis of sepsis in children, especially an NRBC count greater than 3, which may predict the severity and poor prognosis in children suffering from sepsis

Ebullition was a major pathway of methane emissions from the aquaculture ponds in southeast China

Aquaculture ponds are hotspots of carbon cycling and important anthropogenic sources of the potent greenhouse gas methane (CH4). Despite the importance of CH4 ebullition in aquatic ecosystems, its magnitude and spatiotemporal variations in aquaculture ponds remain poorly understood. In this study, we determined the rates and spatiotemporal variations of ebullitive CH4 emissions from three mariculture ponds during the aquaculture period of two years at a subtropical estuary in southeast China. Our results showed that the mean ebullitive CH4 flux from the studied ponds was 14.9 mg CH4 m−2 h−1 during the aquaculture period and accounted for over 90% of the total CH4 emission, indicating the importance of ebullition as a major CH4 transport mechanism. Ebullitive CH4 emission demonstrated a clear seasonal pattern, with a peak value during the middle stage of aquaculture. Sediment temperature was found to be an important factor influencing the seasonal variations in CH4 ebullition. Ebullitive CH4 fluxes also exhibited considerable spatial variations within the ponds, with 49.7–71.8% of the whole pond CH4 ebullition being detected in the feeding zone where the large loading of sediment organic matter fueled CH4 production. Aquaculture ponds have much higher ebullitive CH4 effluxes than other aquatic ecosystems, which indicated the urgency to mitigate CH4 emission from aquaculture activities. Our findings highlighted that the importance of considering the large spatiotemporal variations in ebullitive CH4 flux in improving the accuracy of large-scale estimation of CH4 fluxes in aquatic ecosystems. Future studies should be conducted to characterize CH4 ebullitive fluxes over a greater number and diversity of aquaculture ponds and examine the mechanisms controlling CH4 ebullition in aquatic ecosystems

Improved ECA-ResTCN for Online Classroom Student Attention Recognition

With the rapid rise of online classrooms, monitoring student engagement is critical but challenging for educators. This work explores how artificial intelligence (AI) and big data techniques can automatically evaluate student concentration levels in online courses. We developed an end-to-end ResTCN model combining ResNet and temporal convolutional networks (TCN) to extract spatial and temporal video features. Further, we introduced a CutMix data augmentation method and an efficient channel attention (ECA) module to enhance model training. Evaluated on a public dataset of student videos, our approach achieved 63.28% accuracy in classifying student engagement, outperforming state-of-the-art methods. The contributions are a novel spatiotemporal neural architecture, data augmentation strategy, and attention mechanism tailored for the student engagement recognition task. This demonstrates the potential of AI in creating smart education systems