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With the development of urbanization, underground commercial buildings (UCB) are facing severe challenges in fire safety management due to their unique structure and environmental characteristics. This study constructed a fire casualty risk assessment model that combines fuzzy fault tree analysis (FFTA) and Bayesian network (BN), aiming to quantitatively analyze the dynamic risk of casualties caused by fires in UCB. Fault tree analysis (FTA) is used to comprehensively identify the key risk factors leading to fire casualties in UCB, involving 55 basic events, and the occurrence probability of basic events was calculated via a fuzzy set. The FTA model was transformed into a BN structure via conversion rules and was optimized. The optimized BN model can dynamically analyze the specific fire evolution process and quantify the impacts of different emergency response measures on fire control, evacuation, and casualties. Innovatively, from the post-incident (a historical case study) and pre-incident (two potentially different fire scenarios) perspectives, various emergency plans were scientifically evaluated, providing reasonable suggestions and decision support for emergency management. The results indicate that the model can effectively guide the formulation of fire prevention and control strategies and emergency response work of UCB and provide an innovative tool for improving the safety of UCB and reducing fire accidents and casualties.

Abstract Liposarcoma (LPS) is the second most common kind of soft tissue sarcoma, and a heterogeneous malignant tumor derived from adipose tissue. Up to now, the prognostic value of BAG1 or BAG2 in LPS has not been defined yet. Expression profiling data of LPS patients were collected from TCGA and GEO database. Survival curves were plotted to verify the outcome differences of patients based on BAG1 or BAG2 expression. Univariate and multivariate Cox regression models were used to analyze the prognostic ability of BAG1 or BAG2. Chaperone’s regulators BAG1 and BAG2 were identified as prognostic biomarkers for LPS patients, which exhibited distinct expression patterns and survival outcome prediction performances. Patients with high BAG2 expression and/or low BAG1 expression had worse prognosis. Enrichment analysis showed that BAG1 was involved in negative regulation of TGF-β signaling. Low expression of BAG1 was associated with high abundance of regulatory T cells (Tregs). The 2-gene signature model further confirmed the improved risk assessment performance of BAG1 and BAG2: high risk patients displayed poor prognosis. BAG1 and BAG2 are supposed to be potential prognostic biomarkers for LPS and have impacts on liposarcomagenesis and immune infiltration in distinctive manners, which may function as potential therapy targets (BAG1 agonists/BAG2 inhibitors) for LPS.

Abstract Exercise enhances synaptic plasticity and alleviates depression symptoms, but the mechanism through which exercise improves high-fat diet-induced depression remains unclear. In this study, 6-week-old male C57BL/6J mice were administered a high-fat diet (HFD, 60% kcal from fat) to a HFD model for 8 weeks. The RUN group also received 1 h of daily treadmill exercise in combination with the HFD. Depressive-like behaviors were evaluated by behavioral assessments for all groups. The key mediator of the effect of exercise on high-fat diet-induced depressive-like behaviors was detected by RNA-seq. The morphology and function of the neurons were evaluated via Nissl staining, Golgi staining, electron microscopy and electrophysiological experiments. The results showed that exercise attenuated high-fat diet-induced depressive-like behavior and reversed hippocampal gene expression changes. RNA-seq revealed Wnt5a, which was a key mediator of the effect of exercise on high-fat diet-induced depressive-like behaviors. Further work revealed that exercise significantly activated neuronal autophagy in the hippocampal CA1 region via the Wnt5a/CamkII signaling pathway, which enhanced synaptic plasticity to alleviate HFD-induced depressive-like behavior. However, the Wnt5a inhibitor Box5 suppressed the ameliorative effects of exercise. Therefore, this work highlights the critical role of Wnt5a, which is necessary for exercise to improve high-fat diet-induced depression.

Abstract Pathogenic allele silencing is a promising treatment for genetic hereditary diseases. Here, we develop an RNA-cleaving tool, TaqTth-hpRNA, consisting of a small, chimeric TaqTth, and a hairpin RNA guiding probe. With a minimal flanking sequence-motif requirement, in vitro and in vivo studies show TaqTth-hpRNA cleaves RNA efficiently and specifically. In an Alzheimer’s disease model, we demonstrate silencing of mutant APP swe mRNA without altering the wild-type APP mRNA. Notably, due to the compact size of TaqTth, we are able to combine with APOE2 overexpression in a single AAV vector, which results in stronger inhibition of pathologies.

Abstract Climate and environmental changes threaten human mental health, but the impacts of specific environmental conditions on neuropsychiatric disorders remain largely unclear. Here, we show the impact of a humid heat environment on the brain and the gut microbiota using a conditioned housing male mouse model. We demonstrate that a humid heat environment can cause anxiety-like behaviour in male mice. Microbial 16 S rRNA sequencing analysis reveals that a humid heat environment caused gut microbiota dysbiosis (e.g., decreased abundance of Lactobacillus murinus), and metabolomics reveals an increase in serum levels of secondary bile acids (e.g., lithocholic acid). Moreover, increased neuroinflammation is indicated by the elevated expression of proinflammatory cytokines in the serum and cortex, activated PI3K/AKT/NF-κB signalling and a microglial response in the cortex. Strikingly, transplantation of the microbiota from mice reared in a humid heat environment readily recapitulates these abnormalities in germ-free mice, and these abnormalities are markedly reversed by Lactobacillus murinus administration. Human samples collected during the humid heat season also show a decrease in Lactobacillus murinus abundance and an increase in the serum lithocholic acid concentration. In conclusion, gut microbiota dysbiosis induced by a humid heat environment drives the progression of anxiety disorders by impairing bile acid metabolism and enhancing neuroinflammation, and probiotic administration is a potential therapeutic strategy for these disorders.

Groundwater vulnerability to nitrate assessment serves as a measure of potential groundwater nitrate pollution in a target area. This study applies the DRASTIC-LU framework, nitrate distribution data, and three machine learning models (RF, XGB, SVM) to classify nitrate levels (exceeding 10 mg/L as nitrogen) in Chongqing, China. Model evaluation uses accuracy and F1 score metrics, with RF achieving the highest accuracy (92.9%), kappa (0.857), and AUC (0.948) on test dataset. Furthermore, the SHAP interpreter revealed that aquifer conductivity, lithology, agricultural activities, areas with high-intensity development, and groundwater recharge are the most influential indicators of groundwater vulnerability. The final groundwater vulnerability level distribution map, with a resolution of 1 km × 1 km, reveals that high and extremely high vulnerability levels are concentrated in areas with high-intensity urban development and karst trough valleys in the southeastern, northeastern, and central urban areas. This work represents the first attempt of using machine learning models for groundwater vulnerability assessment in the Chongqing region. It provides theoretical support for the construction layout of groundwater monitoring stations and the prevention and control of groundwater pollution in the future. HIGHLIGHTS Predicting groundwater nitrate vulnerability in Chongqing region using DRASTIC-LU framework and machine learning models.; Random Forest outperforms other machine learning approaches.; Aquifer conductivity, lithology, agricultural activities and areas with high-intensity development predictors were most influential explanatory factors.; Distribution of groundwater nitrate vulnerability map at 1 km resolution.; Groundwater nitrate vulnerability map reveal the high vulnerability levels distributed karst trough valleys in the southeastern, northeastern, and central urban areas.;

Highlights This review provides a comprehensive summary associated with recent progress in the preparation and application of microgels. The characteristics and applications of microgels and microgel-based scaffolds for cell culture and delivery are elaborated with an emphasis on the advantages of these carriers in cell therapy. This review expounds on the ongoing and foreseeable applications and current limitations of microgels and their aggregate in the field of biomedical engineering. Through stimulating innovative ideas, the present review paves new avenues for expanding the application of microgels in cell delivery techniques.

Abstract Background This study investigates the therapeutic mechanisms of dendrobine, a primary bioactive compound in Dendrobium nobile, for Metabolic Associated Fatty Liver Disease (MASLD) management. Utilizing network pharmacology combined with experimental validation, the clinical effectiveness of dendrobine in MASLD treatment was assessed and analyzed. Results The study demonstrates significant improvement in liver function among MASLD patients treated with Dendrobium nobile. Network pharmacology identified key targets such as Peroxisome Proliferator-Activated Receptor Gamma (PPARG), Interleukin 6 (IL6), Tumor Necrosis Factor (TNF), Interleukin 1 Beta (IL1B), and AKT Serine/Threonine Kinase 1 (AKT1), with molecular docking confirming their interactions. Additionally, dendrobine significantly reduced ALT and AST levels in palmitic acid-treated HepG2 cells, indicating hepatoprotective properties and amelioration of oxidative stress through decreased Malondialdehyde (MDA) levels and increased Superoxide Dismutase (SOD) levels. Conclusion Dendrobine mitigates liver damage in MASLD through modulating inflammatory and immune responses and affecting lipid metabolism, potentially by downregulating inflammatory mediators like TNF, IL6, IL1B, and inhibiting AKT1 and Signal Transducer and Activator of Transcription 3 (STAT3). This study provides a theoretical basis for the application of dendrobine in MASLD treatment, highlighting its potential as a therapeutic agent.

Abstract Background Concurrent chemoradiation is the standard treatment for advanced cervical cancer. However some patients still have a poor prognosis, and currently, there is no effective treatment for recurrence. In recent years, 125I seed implantation therapy has emerged as a treatment for advanced malignant tumors including surgically unresectable tumors, residual tumors after surgical resection, and metastatic tumors. However, the use of 125I seeds implantation in primary advanced cervical cancer has not been reported. In this study, we present a case of stage IIIB cervical cancer in a patient who had poor response to radiotherapy and chemotherapy. Subsequently, a radical hysterectomy was performed, and 125I radioactive seeds were successfully implanted during the surgery. This effectively controlled the lesions that were resistant to radiotherapy and had the potential to improve the prognosis. Case presentation A 56-year-old woman was diagnosed with stage IIIB (FIGO 2009) IIIC1r (FIGO 2018) squamous carcinoma of the cervix. After receiving 4 cycles of platinum-based chemotherapy and 30 rounds of radiotherapy, she underwent a radical hysterectomy. The localized cervical lesions were reduced, but there was no reduction in the size of the enlarged pelvic lymph nodes. Therefore, 125I seed implantation was performed under direct surgical vision for the right paracervical lesion and the enlarged pelvic lymph nodes on the right side. During the 18-month follow-up period, the enlarged lymph nodes subsided without any signs of recurrence or metastasis. Conclusion Intraoperative implantation of 125I seeds in lesions that are difficult to control with radiotherapy or in sites at high risk of recurrence is a feasible and effective treatment option for patients with advanced squamous cervical cancer, and it may contribute to improved survival.

Abstract Scintillating fibre detectors combine sub-mm resolution particle tracking, precise measurements of the particle stopping power and sub-ns time resolution. Typically, fibres are read out with silicon photomultipliers (SiPM). Hence, if fibres with a few hundred $$\upmu $$ μ m diameter are used, either they are grouped together and coupled with a single SiPM, losing spatial resolution, or a very large number of electronic channels is required. In this article we propose and provide a first demonstration of a novel configuration which allows each individual scintillating fibre to be read out regardless of the size of its diameter, by imaging them with Single-Photon Avalanche Diode (SPAD) array sensors. Differently from SiPMs, SPAD array sensors provide single-photon detection with single-pixel spatial resolution. In addition, O(us) or faster coincidence of detected photons allows to obtain noise-free images. Such a concept can be particularly advantageous if adopted as a neutrino active target, where scintillating fibres alternated along orthogonal directions can provide isotropic, high-resolution tracking in a dense material and reconstruct the kinematics of low-momentum protons (down to 150 MeV/c), crucial for an accurate characterisation of the neutrino-nucleus cross section. In this work the tracking capabilities of a bundle of scintillating fibres coupled to SwissSPAD2 is demonstrated. The impact of such detector configuration in GeV-neutrino experiments is studied with simulations and reported. Finally, future plans, including the development of a new SPAD array sensor optimised for neutrino detection, are discussed.

Respiratory infectious diseases can cause public health emergencies, threatening human well-being, social operation, and economic development. Clarifying the transmission mechanism of respiratory infectious diseases is essential for control measures. We review the main research findings on the transmission mechanism of respiratory infectious diseases in recent decades. The source characteristics of respiratory infectious diseases, the airborne transmission mechanism, the exposure of susceptible persons, and the infection risk assessment methods are discussed. Given that the dynamic scenario of respiratory infectious disease transmission has attracted wide attention in recent years, we summarize the effects of human movement on indoor airflow, pathogen diffusion, and human exposure. Considering the everyday use of facemasks, the effects of facemasks on source characteristics and infection risk are also discussed. Finally, future research prospects are proposed. The transmission mechanism of infectious diseases can be comprehensively explored by delving into patients' pathological characteristics and personnel protection measures. This exploration can be facilitated by establishing a multi-pose manikin database, enabling personalized and refined evaluations. Interdisciplinary cooperation will play a pivotal role in fostering a holistic understanding. Furthermore, it is crucial to account for the impact of individuals' activity patterns on disease transmission dynamics. This review is expected to reference public health emergency management.

The conversion of agricultural lands, termed “nonagriculturalization,” poses profound threats to food security and ecological stability. Remote sensing image change detection offers an invaluable tool for monitoring this phenomenon. However, most change detection techniques prioritize image comparison over exploiting accumulated vector datasets. Additionally, many current methods are not readily applicable in practical scenarios due to inadequate model generalization capabilities and a scarcity of samples, resulting in a continued reliance on manual intervention for nonagriculturalization detection. In response, this article introduces a novel change detection approach for nonagriculturalization based on the vector data and contrastive learning. Initially, the boundary-constrained simple noniterative clustering algorithm is applied to segment two-phase images under vector data guidance. Samples are then generated using an adaptive cropping method. For early phase image samples, a collaborative validation-based sample annotation framework is employed to optimize and annotate the samples, with the purified high-quality samples serving as the training set for subsequent classification. For later-phase image samples, only those within the cropland vector polygons are retained for prediction. Building on this, a semi-supervised cross-domain contrastive learning framework is proposed for remote sensing scene classification. Ultimately, by integrating nonagriculturalization rules and postprocessing techniques, areas undergoing nonagriculturalization are further detected. Validating our methodology on Wuxi and Yangzhou datasets yielded precision rates of 91.57% and 89.21%, with recall rates of 93.68% and 90.51%, respectively. These outcomes affirm the effectiveness of our method in nonagriculturalization detection, offering robust technical support for research in this domain.

A producing-fibrinolytic enzyme strain was isolated with high yield. The strain was identified as Bacillus amyloliquefaciens. B. amyloliquefaciens GUTU06 fibrinolytic enzyme was purified by acetone precipitation and reverse micelle. Acetone precipitation condition and reverse micelle condition were examined. Results showed that the total reverse micelle extraction efficiency was 64.49 % ± 1.6 %. The purification fold of the entire process reached 13.38. The optimum pH of purified enzyme is 5, and the optimum temperature is 45 °C. Fe3+ and K+ can enhance the fibrinolytic activity of the enzyme. Compared to commercial fibrinolytic enzymes such as urokinase and lumbrukinase, GUTU06 fibrinolytic enzymes have a lower pH optimal range and higher temperature stability. The molecular weight of the enzyme was approximately 28 kDa. Reverse micelle extraction with cetyl trimethylammonium bromide as a surfactant combined with acetone precipitation is suitable for separating and purifying fibrinolytic enzymes and a promising technique for obtaining active proteins.

General anesthesia leads to a loss of consciousness and an unrousable state in patients. Although general anesthetics are widely used in clinical practice, their underlying mechanisms remain elusive. The potential involvement of nonneuronal cells is unknown. Microglia are important immune cells in the central nervous system (CNS) that play critical roles in CNS function and dysfunction. We unintentionally observed delayed anesthesia induction and early anesthesia emergence in microglia-depleted mice. We found that microglial depletion differentially regulates neuronal activities by suppressing the neuronal network of anesthesia-activated brain regions and activating emergence-activated brain regions. Thus, microglia facilitate and stabilize the anesthesia status. This influence is not mediated by dendritic spine plasticity. Instead, it relies on the activation of microglial P2Y12 and subsequent calcium influx, which facilitates the general anesthesia response. Together, we elucidate the regulatory role of microglia in general anesthesia, extending our knowledge of how nonneuronal cells modulate neuronal activities.

Abstract The advancement of microfluidics has enabled numerous discoveries and technologies in life sciences. However, due to the lack of industry standards and configurability, the design and fabrication of microfluidic devices require highly skilled technicians. The diversity of microfluidic devices discourages biologists and chemists from applying this technique in their laboratories. Modular microfluidics, which integrates the standardized microfluidic modules into a whole, complex platform, brings the capability of configurability to conventional microfluidics. The exciting features, including portability, on-site deployability, and high customization motivate us to review the state-of-the-art modular microfluidics and discuss future perspectives. In this review, we first introduce the working mechanisms of the basic microfluidic modules and evaluate their feasibility as modular microfluidic components. Next, we explain the connection approaches among these microfluidic modules, and summarize the advantages of modular microfluidics over integrated microfluidics in biological applications. Finally, we discuss the challenge and future perspectives of modular microfluidics.

Abstract Soil and water assessment tool (SWAT) model was used to calculate the runoff, nitrogen and phosphorus emissions in the Dagu River Basin from 2002 to 2012 and provided preliminary suggestions on environmental protection measures. Calibration on hydrological watershed parameters was obtained from data obtained from multiple representative stations. Cluster analysis was used to group all stations, and the parameters of different representative stations were applied to the entire geographical area to reflect the hydrological conditions of the basin. Additionally, the spatiotemporal changes and pollution source characteristics of nitrogen and phosphorus were analyzed. Anthropogenic sources—chemical fertilizer loss and livestock breeding—accounted for 49.9–29.6% of total nitrogen (TN) and 41.4% and 40.3% of total phosphorus (TP), respectively. Non-point sources accounted for 85.8% of the TN and 89.4% of the TP. Six landscape management practices were set up to evaluate the reduction effect on non-point source pollution loads, and comprehensive measures were proposed to reduce TN (TP) by ~ 70%. According to water quality model, the response relationship between river control and nutrient distribution in Jiaozhou Bay is calculated. Based on the findings, we propose an optimal control scheme for non-point source pollution in the Dagu River Basin and other similar basins.

Abstract Background Compound–protein interaction site and binding affinity predictions are crucial for drug discovery and drug design. In recent years, many deep learning-based methods have been proposed for predications related to compound–protein interaction. For protein inputs, how to make use of protein primary sequence and tertiary structure information has impact on prediction results. Results In this study, we propose a deep learning model based on a multi-objective neural network, which involves a multi-objective neural network for compound–protein interaction site and binding affinity prediction. We used several kinds of self-supervised protein embeddings to enrich our protein inputs and used convolutional neural networks to extract features from them. Our results demonstrate that our model had improvements in terms of interaction site prediction and affinity prediction compared to previous models. In a case study, our model could better predict binding sites, which also showed its effectiveness. Conclusion These results suggest that our model could be a helpful tool for compound–protein related predictions.

Abstract Background Esophageal squamous cell carcinoma (ESCC) remains one of the most lethal cancers worldwide accompany with an extremely poor prognosis. Therefore, this study aims to screen for new molecules affecting ESCC and explore their mechanisms of action to provide ideas for targeted therapies for ESCC. Methods Firstly, we screened out the membrane protein SCARA5 by high-throughput sequencing of the ESCC patient tissues, and RT-qPCR and WB were used to verify the differential expression of SCARA5 in esophageal cell lines, and IHC analyzed the expression localization of SCARA5 in ESCC tissue. Then, flow cytometry, wound healing assay, Transwell assay and CCK-8 assay were used to explore the effects of SCARA5 on cell cycle, migration and invasion as well as cell proliferation activity of esophageal squamous carcinoma cells. Meanwhile, transmission electron microscopy was used to detect changes in cellular mitochondrial morphology, and flow cytometry were used to detect changes in intracellular reactive oxygen metabolism, and immunofluorescence and flow cytometry were used to detect changes in intracellular Fe2+. Mechanistically, co-immunoprecipitation was used to detect whether SCARA5 binds to ferritin light chain, and ferroptosis-related protein expression was detected by WB. Finally, the tumor xenograft model was applied to validation the role of SCARA5 tumor growth inhibition in vivo. Results We found that SCARA5 was aberrantly decreased in ESCC tissues and cell lines. Furthermore, we confirmed that SCARA5 suppressed the cell cycle, metastasis and invasion of ESCC cells. Meanwhile, we also found that overexpression of SCARA5 caused changes in mitochondrial morphology, accumulation of intracellular reactive oxygen species and increased intracellular Fe2+ in ESCC cells, which induced ferroptosis in ESCC cells. Mechanically, we validated that SCARA5 combined with ferritin light chain and increased intracellular Fe2+. As well as, overexpression SCARA5 induced ferroptosis by increasing ferritin light chain in nude mice subcutaneous tumors and inhibited the growth of nude mice subcutaneous tumors. Conclusion Collectively, our findings demonstrated that SCARA5 suppressed the proliferation and metastasis of ESCC by triggering ferroptosis through combining with ferritin light chain.

Influenza A, the most common subtype, induces 3 to 5 million severe infections and 250,000 to 500,000 deaths each year. Vaccination is traditionally considered to be the best way to prevent influenza A. Yet because the Influenza A virus (IAV) is highly susceptible to antigenic drift and Antigenic shift, and because of the lag in vaccine production, this poses a significant challenge to vaccine effectiveness. Additionally, much information about the resistance of antiviral drugs, such as Oseltamivir and Baloxavir, has been reported. Therefore, the search for alternative therapies in the treatment of influenza is warranted. Recent studies have found that regulating the gut microbiota (GM) can promote the immune effects of anti-IAV via the gut-lung axis. This includes promoting IAV clearance in the early stages of infection and reducing inflammatory damage in the later stages. In this review, we first review the specific alterations in GM observed in human as well as animal models regarding IAV infection. Then we analyzed the effect of GM on host immunity against IAV, including innate immunity and subsequent adaptive immunity. Finally, our study also summarizes the effects of therapies using probiotics, prebiotics, or herbal medicine in influenza A on intestinal microecological composition and their immunomodulatory effects against IAV.

Background: Dietary intervention is the preferred approach for the prevention and clinical management of gout. Nevertheless, the existing evidence regarding the influence of specific foods on gout is insufficient. Methods: We used two-sample Mendelian randomization for genetic prediction to analyze the relationship between the intake of more than a dozen daily food items, such as pork, beef, cheese, and poultry, and dietary macronutrient intake (fat, protein, carbohydrates, and sugar) and the risk of developing gout and elevating the serum uric acid level. Inverse-variance weighted MR analyses were used as the main evaluation method, and the reliability of the results was tested by a sensitivity analysis. Results: Cheese intake was associated with lower serum uric acid levels, and tea intake (OR = 0.523, [95%CI: 0.348~0.784], p = 0.002), coffee intake (OR = 0.449, [95%CI: 0.229~0.882], p = 0.020), and dried fruit intake (OR = 0.533, [95%CI: 0.286~0.992], p = 0.047) showed a preventive effect on the risk of gouty attacks. In contrast, non-oily fish intake (β = 1.08, [95%CI: 0.24~1.92], p = 0.012) and sugar intake (β = 0.34, [95%CI: 0.03~0.64], p = 0.030) were risk factors for elevated serum uric acid levels, and alcohol intake frequency (OR = 1.422, [95%CI: 1.079~1.873], p = 0.012) was a risk factors for gout predisposition. Conclusions: These results will significantly contribute to the formulation and refinement of nutritional strategies tailored to patients afflicted with gout.

Abstract Background Gout is a common disease with high incidence due to unhealthy diet and living habits. Simiao Powder, as a classic formula consisted of four common herbs, has been widely used in clinical practice since ancient times to prevent and treat gout. However, the pharmacological mechanism of Simiao Powder is still unclear. Methods Based on network pharmacology, Simiao Powder active compounds were identified in TCMSP, ETCM and BATMAN database, used to establish a network of interaction between potential targets of Simiao Powder and known therapeutic targets of gout. Subsequently, the key potential targets are being used for protein–protein interaction, GO enrichment analysis and KEGG pathway enrichment analysis through several authoritative open databases. Molecular docking through AutoDockTools software can verify interaction between molecules. Finally, to validate the predicted results, in vivo experiments based on hyperuricemic-gout mice model were designed and treated with Simiao powder and allopurinol. Serum levels of uric acid (UA), creatinine (Cr), blood urea nitrogen (BUN) and xanthine oxidase (XOD) were determined using a customized assay kit while the expression of PPAR-γ, PTGS1, IL-6 and Bcl2 mRNA were analyzed through qRT-PCR. Results Disease-target-compound network was visualized basing on the 20 bioactive compounds and the 19 potential targets using Cytoscape software. The results of PPI analysis, GO enrichment and KEGG pathway enrichment analysis indicate that the potential mechanism of Simiao Powder in treating gout may be achieved by regulating immune and inflammatory reactions, improving metabolism and endocrine. The results of molecular docking show that most of the targets and components have good binding activity. In vivo experiments revealed that Simiao powder can decreased serum UA and XOD levels in hyperuricemic-gout mice, and improved renal function. Furthermore, Simiao powder certainly regulates the expression of PPAR-γ, PTGS1, IL-6 and Bcl2 mRNA in ankle tissue in hyperuricemic-gout mice. Conclusion Collectively, this research predicted a multiple compounds, targets, and pathways model mechanism of Simiao Powder in the prevention and treatment of gout, providing new ideas and methods for in-depth research, via vivo experiments.

Pedestrian detection has always been a difficult and hot spot in computer vision research. At the same time, pedestrian detection technology plays an important role in many applications, such as intelligent transportation and security monitoring. In complex scenes, pedestrian detection often faces some challenges, such as low detection accuracy and misdetection due to small target sizes and scale variations. To solve these problems, this paper proposes a pedestrian detection network PT-YOLO based on the YOLOv5. The pedestrian detection network PT-YOLO consists of the YOLOv5 network, the squeeze-and-excitation module (SE), the weighted bi-directional feature pyramid module (BiFPN), the coordinate convolution (coordconv) module and the wise intersection over union loss function (WIoU). The SE module in the backbone allows it to focus on the important features of pedestrians and improves accuracy. The weighted BiFPN module enhances the fusion of multi-scale pedestrian features and information transfer, which can improve fusion efficiency. The prediction head design uses the WIoU loss function to reduce the regression error. The coordconv module allows the network to better perceive the location information in the feature map. The experimental results show that the pedestrian detection network PT-YOLO is more accurate compared with other target detection methods in pedestrian detection and can effectively accomplish the task of pedestrian detection in complex scenes.

Abstract N6‐methyladenosine (m6A) is the most common methylation modification in mammalian messenger RNA (mRNA) and noncoding RNAs. m6A modification plays a role in the regulation of gene expression and deregulation of m6A methylation has been implicated in many human diseases. Recent publications suggest that exploitation of this methylation process may possess utility against acute lung injury (ALI). ALI and its more severe form, acute respiratory distress syndrome (ARDS) are acute, inflammatory clinical syndromes characterized by poor oxygenation and diffuse pulmonary infiltrates. This syndrome is associated with microvascular endothelial dysfunction, subsequent pulmonary hypertension and may ultimately lead to mortality without rigorous and acute clinical intervention. Over the years, many attempts have been made to detect novel therapeutic avenues for research without much success. The urgency for the discovery of novel therapeutic agents has become more pronounced recently given the current pandemic infection of coronavirus disease 2019 (COVID‐2019), still ongoing at the time that this review is being written. We review the current landscape of literature regarding ALI and ARDS etiology, pathophysiology, and therapeutics and present a potential role of m6A methylation. Additionally, we will establish the axiomatic principles of m6A methylation to provide a framework. In conclusion, METTL3, or methyltransferase‐like 3, the selective RNA methyltransferase for m6A, is a hub of proinflammatory gene expression regulation in ALI, and using a modern drug discovery strategy will identify new and effective ALI drug candidates targeting METTTL3.

Vibrio cholerae (V. cholerae), one of the most important bacterial pathogens in history, is a gram-negative motile bacterium that causes fatal pandemic disease in humans via oral ingestion of contaminated water or food. This process involves the coordinated actions of numerous regulatory factors. The MerR family regulators, which are widespread in prokaryotes, have been reported to be associated with pathogenicity. However, the role of the MerR family regulators in V. cholerae virulence remains unknown. Our study systematically investigated the influence of MerR family regulators on intestinal colonization of V. cholerae within the host. Among the five MerR family regulators, MlrA was found to significantly promote the colonization capacity of V. cholerae in infant mice. Furthermore, we revealed that MlrA increases bacterial intestinal colonization by directly enhancing the expression of tcpA, which encodes one of the most important virulence factors in V. cholerae, by binding to its promoter region. In addition, we revealed that during infection, mlrA is activated by anaerobic signals in the small intestine of the host through Fnr. In summary, our findings reveal a MlrA-mediated virulence regulation pathway that enables V. cholerae to sense environmental signals at the infection site to precisely activate virulence gene expression, thus providing useful insights into the pathogenic mechanisms of V. cholerae.

This paper describes a method to fabricate the 3D microfluidic channel using the free-standing, phase-change gallium mold. Three approaches to prepare the free-standing gallium molds are described. The solid metal framework is strong enough to stand against the gravity. After casting, the embedded gallium molds are melted from solid to liquid and then extracted from the encasing elastomer to form the 3D microfluidic channel due to the phase change property. Since this method is compatible with many encasing materials (e.g., elastomers, gels, resins, ceramics), the encasing materials will bring novel functionalities to the microfluidic chip. Two proof-of-concept experiments have been demonstrated. Firstly, a soft, sticky, on-skin microfluidic cooler is developed based on this method to deliver the focused, minimal invasive cooling power at arbitrary skins of human body with temperature control. Secondly, an ultra-stretchable viscoelastic microchannel with the ultra-soft base is fabricated to continuously tune the viscoelastic particle focusing with a large dynamic range. This proposed technique suggests the new possibilities for the development of lab-on-a-chip applications.

The basic density (ρ), kinematic viscosity (v) and surface tension (γ) data of the 1,2-propanediol (1,2-PPD) (1) + 1,2-propane diamine (1,2-PDA) (2) binary system at T = (293.15, 298.15, 303.15, 308.15, 313.15 and 318.15) K were reported under atmospheric pressure (889 hectopascals in Hohhot, China). After that, the absolute viscosity (η), excess volume (VmE), viscosity deviation (Δη), surface tension difference (Δ γ), apparent molar volume (Vφ,1 and Vφ,2), partial molar volume (V1¯ and V2¯), isothermal expansion coefficient (αp) and excess Gibbs free energy (ΔG*E) of the binary system were further calculated. Meanwhile, the Redlich-Kister (R-K) equations were fitted to VmE, Δ η, and Δ γ values, and the corresponding equation coefficients were obtained to estimate the errors between the experimental and calculated values. Finally, the binary system was characterized by FTIR, UV-vis, FLS, 1H NMR, Raman spectroscopic techniques, and the bond energy and bond length between molecules were calculated by Gaussian 09 software to discuss the intermolecular interaction between 1,2-PPD and 1,2-PDA. The results show that hydrogen bonding interaction does exist among molecules in the form of -OH···N-. Herein, the work provides a basis for engineering design and also provides fundamental data for the application of the binary system.

The bacterium Vibrio cholerae can colonize the human intestine and cause cholera, but spends much of its life cycle in seawater. Here, Liu et al. identify a fructose uptake system that is important for the growth of the bacteria in seawater, where fructose concentrations are low.

This study explores the use of Cu dopant to improve the optoelectronic properties and stability of CsPbX3 perovskites for blue-light-emitting diode material. The addition of Cu causes the metal octahedron of orthorhombic CsPbBr3 to shrink, which relaxes the lattice strain from the distortion and twisting of the [PbX6] octahedron and reduces energy from Jahn–Teller effects. A crystal orbital Hamilton population (COHP) analysis reveals that the Cu-Br bond in the [CuX6] octahedron has a higher integrated projected COHP (IpCOHP), and the strong hybridization between the Cu-3d and Br-4p bond enhances the bond interaction and the whole crystalline lattice. The addition of Cu dopants in CsPbBr3 perovskites results in a stronger framework that suppresses intrinsic defects like Br vacancies, leading to enhanced photoluminescence (PL) performance. Additionally, the Cu-3d orbitals contribute to the valence band and increase the band gap, resulting in a blue shift of the luminescence from Cu-doped CsPbBr3. These findings indicate that Cu dopants significantly improve the luminescence efficiency and the stability of CsPbBr3 perovskites, making them suitable for blue light LED applications.

As a form of social public opinion, network public opinion has the characteristics of high degree of social concern, fast transmission speed and wide range of influence, which often breaks out suddenly and makes people unprepared. Because the earthquake disasters are directly related to people’s life and property, the earthquake emergency is very easy to cause network public opinion, in which there are many kinds of rumors. If not handled in time or improperly, it will bring more serious social impact. Taking“Sanya earthquake”topic as an example, we will analyze the main types of construction subject of“Sanya earthquake”topic, and the main content, public emotion and communication area of its public opinion. Opinion and suggestions on emergency management of public opinion in earthquake emergencies and the guidance of public opinion will be discussed.

Abstract The efficient induction and long-term persistence of pathogen-specific memory CD8 T cells are pivotal to rapidly curb the reinfection. Recent studies indicated that long-noncoding RNAs expression is highly cell- and stage-specific during T cell development and differentiation, suggesting their potential roles in T cell programs. However, the key lncRNAs playing crucial roles in memory CD8 T cell establishment remain to be clarified. Through CD8 T cell subsets profiling of lncRNAs, this study found a key lncRNA-Snhg1 with the conserved naivehi-effectorlo-memoryhi expression pattern in CD8 T cells of both mice and human, that can promote memory formation while impeding effector CD8 in acute viral infection. Further, Snhg1 was found interacting with the conserved vesicle trafficking protein Vps13D to promote IL-7Rα membrane location specifically. With the deep mechanism probing, the results show Snhg1-Vps13D regulated IL-7 signaling with its dual effects in memory CD8 generation, which not just because of the sustaining role of STAT5-BCL-2 axis for memory survival, but more through the STAT3-TCF1-Blimp1 axis for transcriptional launch program of memory differentiation. Moreover, we performed further study with finding a similar high-low-high expression pattern of human SNHG1/VPS13D/IL7R/TCF7 in CD8 T cell subsets from PBMC samples of the convalescent COVID-19 patients. The central role of Snhg1-Vps13D-IL-7R-TCF1 axis in memory CD8 establishment makes it a potential target for improving the vaccination effects to control the ongoing pandemic.

Abstract The effect of dislocation-RE atoms interactions on the creep behaviour has been studied via creep testing and HAADF-STEM analysis of two extruded alloys; Mg–0.5Ce and Mg–2Gd (wt%). Almost no Ce atoms are detected in the Mg matrix due to the low solid solubility and faster diffusion rate in as-extruded condition. However, Gd solute segregations are observed along dislocations and hexagonal dislocation patterns. Such segregations can not only pin the dislocation motion and enhance the creep strengthening via dislocation patterns, but also lead to dynamic precipitation. Thus, combing with the stress exponent values, the transition of creep mechanism between Mg–0.5Ce alloys and Mg–2Gd alloys has been found and dislocation-Gd atoms interactions are determined to be the main factor for superior creep resistance of Mg–2Gd alloys.

Feature selection is a process of choosing a subset of relevant features so that the quality of predictive models can be improved. An extensive body of work exists on information-theoretic feature selection, based on maximizing Mutual Information (MI) between subsets of features and class labels. The current methods use a lower order approximation, by treating the joint entropy as a summation of several single variable entropies. This leads to locally optimal selections and misses correlated (multi-way) non-local feature combinations. In this article we present a higher order MI-based approximation technique called Higher Order Feature Selection (HOFS) implemented in R software. Instead of producing a single list of features, our method produces a ranked collection of feature subsets that maximizes MI, giving better comprehension (feature ranking) as to which features work best together when selected, due to their underlying interdependence. We demonstrate that the proposed method performs better than existing feature selection approaches while keeping similar running times and computational complexity.

Cytotoxic CD8+ T cells are the main focus of efforts to understand anti-tumor immunity and immunotherapy. The adoptive transfer of tumor-reactive cytotoxic CD8+ T lymphocytes expanded and differentiated in vitro has long been considered the primary strategy in adaptive anti-tumor immunity, however, the majority of the transferred tumor antigen-specific CD8+ T cells differentiated into CD39+CD69+ exhausted progenies, limiting its effects in repressing tumor growth. Contrarily, less attention has been addressed to the role of CD4+ T cells during tumorigenesis. Using a mouse model of metastatic melanoma, we found that transferring tumor-specific CD4+ T cells into recipients induces substantial regression of the established metastatic tumors. Notably, in vitro activated CD4+ T cells developed into cytotoxic CD4- T cells in vivo and get exhausted gradually. The blockade of PD-L1 signaling resulted in an expansion of tumor specific CD4+ T cells, which could better control the established metastatic melanoma. Moreover, the tumor-specific memory CD4+ T cell can prevent mice from tumor metastasis, and the tumor-specific effector CD4+ T cells can also mitigate the established metastatic tumor. Overall, our findings suggest a novel mechanism of CD4+ T cells in curtailing tumor metastasis and confirm their therapeutic role in combination with PD-L1 blockade in cancer immunotherapy. Hence, a better understanding of cytotoxic CD4- T cell-mediated tumor regression could provide an alternative choice for patients exhibiting suboptimal or no response to CD8+ T cell-based immunotherapies.

This paper collected the continuous gravity observation data from Qiongzhong seismic station since 2009. After processing the raw data with sudden jumps，steps and error data，we calculated and analyzed the characteristics of the gravity tide data from Qiongzhong seismic station，the characteristics of the M2 wave tide factor and the spectrum characteristics of the observation data of typical events. The results show that the continuous gravity observation data of Qiongzhong seismic station include not only long-period signals such as solid tide and zero drift，but also high-frequency signals such as earthquakes and typhoons. For the recorded strong earthquakes above 7.0，the frequency of seismic signals is mainly distributed within 0.3 Hz; the disturbance signal caused by the typhoon is mainly distributed in the 0.1—0.4 Hz frequency band; at the same time，the original continuous gravity data of Qiongzhong seismic station and its M2 wave tide factor have no obvious precursory anomalie since 2009.

Abstract This letter is a retrospective analysis of our team's research for the Defense Advanced Research Projects Agency Explainable Artificial Intelligence project. Our initial approach was to use salience maps, English sentences, and lists of feature names to explain the behavior of deep‐learning‐based discriminative systems, with particular focus on visual question answering systems. We found that presenting static explanations along with answers led to limited positive effects. By exploring various combinations of machine and human explanation production and consumption, we evolved a notion of explanation as an interactive process that takes place usually between humans and artificial intelligence systems but sometimes within the software system. We realized that by interacting via explanations people could task and adapt machine learning (ML) agents. We added affordances for editing explanations and modified the ML system to act in accordance with the edits to produce an interpretable interface to the agent. Through this interface, editing an explanation can adapt a system's performance to new, modified purposes. This deep tasking, wherein the agent knows its objective and the explanation for that objective, will be critical to enable higher levels of autonomy.

Archidendron clypearia (A. clypearia), a Fabaceae family member, is widely used as an anti-inflammatory herbal medicine; however, its antibacterial and antidiabetic properties have not been extensively investigated. This study aimed to systematically analyze the antibacterial and antidiabetic components of A. clypearia by utilizing a combination of analytical methods. First, ten different polarity extracts were analyzed through ultra-performance liquid chromatography (UPLC), and their antibacterial and antidiabetic activities were evaluated. Then the spectrum–effect relationship between the biological activity and UPLC chromatograms was analyzed by partial least squares regression and gray relational analysis, followed by corresponding validation using isolated components. Finally, network pharmacology and molecular docking were implemented to predict the main antibacterial target components of A. clypearia and the enzyme inhibition active sites of α-amylase and α-glucosidase. P15, P16, and P20 were found to be the antibacterial and antidiabetic active components. The inhibitory effect of 7-O-galloyltricetiflavan (P15) on six bacterial species may be mediated through the lipid and atherosclerosis pathway, prostate cancer, adherens junctions, and targets such as SRC, MAPK1, and AKT1. The molecular docking results revealed that 7-O-galloyltricetiflavan and 7,4′-di-O-galloyltricetiflavan (P16/P20) can bind to α-amylase and α-glucosidase pockets with binding energies lower than −6 kcal/mol. Our study provides guidance for the development of antibacterial and antidiabetic products based on A. clypearia and can be used as a reference for the evaluation of bioactivity of other herbs.

The development of new techniques for the detection of microRNAs (miRNAs) is highly desirable. Herein, a new crystalline three-component covalent organic framework (COF) termed EB-TAPB-TFP COF was synthesized under solvothermal conditions utilizing 1,3,5-triformylphloroglucinol, 1,3,5-tris(4-aminophenyl)benzene and ethidium bromide as monomers. Interestingly, EB-TAPB-TFP COF can be self-exfoliated into two-dimensional nanosheets (NSs) in an aqueous medium. The obtained EB-TAPB-TFP NSs exhibited a remarkable fluorescence intensity enhancement in the presence of a DNA-miRNA heteroduplex when compared to the presence of single-stranded DNA and other phosphate-based small molecules, making it promising in the detection of miRNA without tagging any fluorescent marker. Moreover, the EB-TAPB-TFP NSs can also be used as sensing material for the detection of a DNA-miRNA heteroduplex using the quartz crystal microbalance technique, which is in good agreement with the fluorescence sensing result. The exploration of COF-based sensors in this work demonstrates a new pathway for the selective detection of miRNAs.

Probiotics have the functions of inhibiting pathogen infection and maintaining gastrointestinal homeostasis. The aim of this study was to investigate the preventive effect of Lactobacillus casei T1 (L. casei T1) isolated from kurut against the gastric inflammation and gut microbiota alteration induced by Helicobacter pylori (H. pylori) infection. The results showed that L. casei T1 and its supernatant had a potent inhibitory effect on H. pylori growth in vitro. L. casei T1 adhered to GES-1 cells, down-regulated the expression of MUC5AC, IL-6, IL-8 and TNF-α in GES-1 cells induced by H. pylori. This followed by in vivo studies demonstrated that L. casei T1 pretreatment alleviated gastric inflammation and prevent gut microbiota alteration caused by H. pylori infection. These results demonstrated that L. casei T1 have a preventive effect against H. pylori infection and it can be served as a further development and utilization of probiotic.

Abstract Background Coumarins play roles in many biological processes. Angelica decursiva is one of the major sources of coumarins in China. Due to increasing demand for coumarins in the marketplace, traditional extraction from plants is now considered economically insufficient and unsustainable. Microbial synthesis is a promising strategy for scalable production of coumarins. However, the biosynthetic pathway of coumarin remains poorly understood, and even more, the genes associated with this process have not been characterized in A. decursiva. Results RNA-seq was employed to elucidate the umbelliferone biosynthetic pathway. The results indicated that three enzymes, phenylalanine ammonia-lyase (PAL), 4-Coumarate: Coenzyme A Ligase (4CL), and p-coumaroyl CoA 2'-hydroxylase (C2’H) were involved in umbelliferone biosynthesis. Using the cloned genes, we generated a synthetic biology based microbial cell factory that produces coumarins from tyrosine utilizing Rhodotorula glutinis tyrosine ammonia lyase (RgTAL) to bypass cinnamic acid 4-hydroxylase (C4H). With metabolic engineering strategies, we deleted prephenate dehydratase (pheA), anthranilate synthase (trpE) and transcriptional regulatory protein (tyrR) and overexpressed six related genes involved in tyrosine biosynthesis, to drive the carbon flux from tyrosine. To overcome the limitation of 4CL, a virtual screening and site-specific mutagenesis-based protein engineering approach was applied. In addition, induction/culture conditions and different ions were employed to further improve the yield of umbelliferone. Finally, a yield of 356.59 mg/L umbelliferone was obtained. Conclusions The current study elucidated the umbelliferone biosynthesis pathway in A. decursiva. The results also demonstrated the feasibility of integrating gene mining with synthetic biology techniques to produce natural compounds.

Enterohemorrhagic Escherichia coli (EHEC) O157:H7 (O157) is a major foodborne pathogen that causes severe illness in humans worldwide. The genome of O157 contains 177 genomic islands known as O islands (OIs), including Shiga toxin-converting phages (OI-45 and OI-93) and the locus for enterocyte effacement (LEE) pathogenicity island (OI-148). However, most genes in OIs are uncharacterized and code for unknown functions. In this study, we demonstrated, for the first time, that OI-9 encodes a novel transcriptional activator, Z0346 (named OvrB), which is required for bacterial adherence to host cells and LEE gene expression in O157. OvrB directly binds to the promoter region of LEE1 and activates the transcription of ler (encoding a master regulator of LEE genes), which in turn activates LEE1–5 genes to promote O157 adherence. Furthermore, mouse oral infection assays showed that OvrB promotes O157 colonization in the mouse intestine. Finally, OvrB is shown to be a widespread transcriptional activator of virulence genes in other enterohemorrhagic and enteropathogenic Escherichia coli serotypes. Our work significantly expands the understanding of bacterial virulence control and provides new evidence suggesting that horizontally transferred regulator genes mediate LEE gene expression.

Surface-enhanced Raman scattering (SERS) detection requires dense hotspots and a uniform distribution of analytes to obtain a stable signal with good repeatability. However, due to the coffee-ring effect on the hydrophilic substrate, and the difficulty of droplet manipulation on the superhydrophobic substrate, few substrates can ensure that the analytes are evenly distributed. In this work, we develop a method that can efficiently enrich plasmonic hotspots for SERS measurement on the superhydrophobic concave dome array (SCDA). The SCDA is formed by spraying hydrophobic silica nanoparticles onto a polydimethylsiloxane (PDMS) slab with a concave dome array that can physically confine the droplets and overcome the coffee-ring effect. During droplet evaporation, the SCDA is driven by a horizontal spinner, and the droplets spin on the SCDA, enabling the plasmonic nanoparticles to become closely packed to form the SERS hotspots. The limit of detection (LOD) of the dynamic-enriched SERS hotspots for crystal violet and methylene blue can reach up to 10−11 M. Moreover, the LOD for melamine in milk can reach 5 × 10−7 M, which is lower than the safety threshold defined by the Food and Drug Administration (FDA). Based on this SERS platform, an effective, low-cost, and simple method for SERS detection in analytical chemistry and food safety is highly expected.

Background/Aims: Gastric cancer (GC) is a common malignancy with a global incidence that ranks fourth among all tumor types. Epithelial-to-mesenchymal transition (EMT) is a tumor biological process with a role in GC cell metastasis. Long non-coding RNAs (lncRNAs) and microRNAs possess important regulatory functions at the cellular level and in diverse pathophysiological processes. This study was conducted to investigate whether lncRNA RP11-789C1.1 regulates EMT in GC by mediating the miR-5003/E-cadherin pathway. Methods: RP11-789C1.1 and miR-5003 expression was detected in GC specimens and cell lines by quantitative real-time PCR. Western blotting and immunohistochemistry were performed to detect EMT markers in GC. Cell Counting Kit 8 assays were carried out to explore cell proliferation. Wound healing and Transwell assays were conducted to determine the migration and invasion of GC cells. To clarify the correlation between RP11-789C1.1, miR-5003, and E-cadherin, dual-luciferase reporter assays were applied. Results: LncRNA RP11-789C1.1 was significantly down-regulated in GC patients and cell lines, along with the concomitant up-regulation of miR-5003. Silencing RP11-789C1.1 and over-expressing miR-5003 significantly promoted the tumor behavior of GC cells. Dual-luciferase reporter assays confirmed that miR-5003 was the target of both RP11-789C1.1 and E-cadherin. Furthermore, at both the mRNA and protein level, silencing RP11-789C1.1 remarkably reduced the expression of E-cadherin and promoted EMT, which were reversed by knocking down miR-5003. Conclusions: LncRNA RP11-789C1.1 inhibited EMT in GC through the RP11-789C1.1/miR-5003/E-cadherin axis, which could be a promising therapeutic target for GC.

Follicular helper T cells (TFH cells), known as the primary “helpers” of the germinal center (GC) reaction, promote the humoral immune response to defend against various pathogens. Under conditions of infection by different types of pathogens, many shared transcription factors (TFs), such as Bcl-6, TCF-1, and Maf, are selectively enriched in pathogen-specific TFH cells, orchestrating TFH cell differentiation and function. In addition, TFH cells also coexpress environmentally associated TFs as their conventional T cell counterparts (such as T-bet, GATA-3, or ROR-γt, which are expressed in Th1, Th2, or Th17 cells, respectively). These features likely indicate both the lineage-specificity and environmental adaption of the TFH cell responses. However, the extent to which the TFH cell response relies on these environmentally specific TFs is not completely understood. Here, we found that T-bet was specifically expressed in Type I TFH cells but not Type II TFH cells. While dispensable for the early fate commitment of TFH cells, T-bet was essential for the maintenance of differentiated TFH cells, promoting their proliferation, and inhibiting their apoptosis during acute viral infection. Microarray analysis showed both similarities and differences in transcriptome dependency on T-bet in TFH and TH1 cells, suggesting the distinctive role of T-bet in TFH cells. Collectively, our findings reveal an important and specific supporting role for T-bet in type I TFH cell response, which can help us gain a deeper understanding of TFH cell subsets.

Road extraction in rural areas is one of the most fundamental tasks in the practical application of remote sensing. In recent years, sample-driven methods have achieved state-of-the-art performance in road extraction tasks. However, sample-driven methods are prohibitively expensive and laborious, especially when dealing with rural roads with irregular curvature changes, narrow widths, and diverse materials. The template matching method can overcome these difficulties to some extent and achieve impressive road extraction results. This method also has the advantage of the vectorization of road extraction results, but the automation is limited. Straight line sequences can be substituted for curves, and the use of the color space can increase the recognition of roads and nonroads. A model-driven-to-sample-driven road extraction method for rural areas with a much higher degree of automation than existing template matching methods is proposed in this study. Without prior samples, on the basis of the geometric characteristics of narrow and long roads and using the advantages of straight lines instead of curved lines, the road center point extraction model is established through length constraints and gray mean contrast constraints of line sequences, and the extraction of some rural roads is completed through topological connection analysis. In addition, we take the extracted road center point and manual input data as local samples, use the improved line segment histogram to determine the local road direction, and use the panchromatic and hue, saturation, value (HSV) space interactive matching model as the matching measure to complete the road tracking extraction. Experimental results show that, for different types of data and scenarios on the premise, the accuracy and recall rate of the evaluation indicators reach more than 98%, and, compared with other methods, the automation of this algorithm has increased by more than 40%.

Follicular helper CD4+ T (TFH) cells are critical for optimal B-cell-mediated humoral immunity by initiating, fueling, and sustaining germinal center reactions. The differentiation of TFH cells relies on multiple intrinsic and extrinsic factors; however, the details by which these factors are integrated to coordinate TFH differentiation are largely unknown. In this study, using a mouse model of acute lymphocytic choriomeningitis virus (LCMV) viral infection, we demonstrate that mTOR complex 2 (mTORC2) kinase integrates TCR signaling and ICOS-mediated co-stimulation to promote late differentiation and functional maturation of virus-specific TFH cells. Specifically, mTORC2 functions to maintain TFH lineage specifications, including phenotypes, migratory characteristics, and functional properties. Thus, our results highlight the importance of mTORC2 in guarding TFH phenotypic and functional maturation.