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It is very important to automatically detect violent behaviors in video surveillance scenarios, for instance, railway stations, gymnasiums and psychiatric centers. However, the previous detection methods usually extract descriptors around the spatiotemporal interesting points or extract statistic features in the motion regions, leading to limited abilities to effectively detect video-based violence activities. To address this issue, we propose a novel method to detect violence sequences. Firstly, the motion regions are segmented according to the distribution of optical flow fields. Secondly, in the motion regions, we propose to extract two kinds of low-level features to represent the appearance and dynamics for violent behaviors. The proposed low-level features are the Local Histogram of Oriented Gradient (LHOG) descriptor extracted from RGB images and the Local Histogram of Optical Flow (LHOF) descriptor extracted from optical flow images. Thirdly, the extracted features are coded using Bag of Words (BoW) model to eliminate redundant information and a specific-length vector is obtained for each video clip. At last, the video-level vectors are classified by Support Vector Machine (SVM). Experimental results on three challenging benchmark datasets demonstrate that the proposed detection approach is superior to the previous methods.

Observational studies have reported a correlation between Helicobacter pylori infection and colorectal cancer (CRC); however, the underlying cause has remained unclear. This research was aimed at determining whether there is a correlation between H. pylori infection and CRC by measuring the prevalence of H. pylori CagA antibodies and VacA antibodies. Using data from many genome-wide association studies (GWAS), we conducted a Mendelian randomization (MR) study with two sample GWAS. Then, we used bidirectional MR to evaluate the association between H. pylori infection and CRC for identifying causation. The most common method of analysis was the inverse variance-weighted technique. In addition, we performed supplementary analyses using the weighted median technique and MR-Egger regression. Horizontal pleiotropic outliers were identified and corrected using the MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) method. Genetically predicted anti- H. pylori IgG seropositivity was not causally associated with CRC [odds ratio (OR): 1.12; 95% confidence interval (CI): 0.98–1.27, P  = 0.08] and neither were H. pylori VacA antibody levels (OR = 0.96, 95% CI: 0.90–1.02, P  = 0.25) or H. pylori CagA antibody levels (OR = 1.00, 95% CI: 0.93–1.07, P  = 0.92). Furthermore, reverse MR analysis did not reveal evidence for a causal effect of CRC on H. pylori infection. The weighted median, the MR-Egger method, and MR-PRESSO yielded identical results. Using genetic data, MR analysis showed there was no evidence for a causal association between seroprevalence of H. pylori infection and CRC. The relationship between H. pylori infection and CRC requires further research.

Innate preference toward environmental conditions is crucial for animal survival. Although much is known about the neural processing of sensory information, how the aversive or attractive sensory stimulus is transformed through central brain neurons into avoidance or approaching behavior is largely unclear. Here we show that Drosophila larval light preference behavior is regulated by a disinhibitory mechanism. In the disinhibitory circuit, a pair of GABAergic neurons exerts tonic inhibition on one pair of contralateral projecting neurons that control larval reorientation behavior. When a larva enters the light area, the reorientation-controlling neurons are disinhibited to allow reorientation to occur as the upstream inhibitory neurons are repressed by light. When the larva exits the light area, the inhibition on the downstream neurons is restored to repress further reorientation and thus prevents the larva from re-entering the light area. We suggest that disinhibition may serve as a common neural mechanism for animal innate preference behavior. The reorientation response of Drosophila larva to light is an innate behaviour. Here the authors identify a pair of GABAergic neurons that mediate a disinhibitory mechanism that regulates the larval reorientation response.

This paper is devoted to investigating the problem of finite-time (FnT) adaptive cluster synchronization for heterogeneous fractional-order dynamic networks (FODNs) with community structure and co-competition interactions. By designing a suitable adaptive controller and using reduction to absurdity, some sufficient conditions are derived to ensure the considered heterogeneous FODNs can achieve cluster synchronization over a FnT interval. Meanwhile, the cluster-synchronized setting times (CSSTs) are evaluated effectively by means of the monotonicity of the Mittag-Leffler function. It is indicated that the estimated CSSTs are associated with the order of the derivation and the control parameters. Finally, numerical simulations are carried out to validate the effectiveness of our theoretical results.

Effective anti-tumor immunity critically depends on functional CD8 + T cells, yet in almost all solid tumors, these cells become dysfunctional, exhausted, or spatially excluded. This breakdown of immune surveillance arises not only from cell-intrinsic T cell exhaustion but also from multimodal communication among tumor, stromal, and immune cells within the tumor microenvironment (TME). This communication is mediated not only through direct receptor-ligand interactions but also through a suite of indirect mechanisms, such as metabolic competition, secretion of immunosuppressive metabolites and cytokines, extracellular vesicle exchange, and even mitochondrial transfer via tunneling nanotubes or membrane transfer through T cell trogocytosis. Together, these suppressive interactions impair CD8 + T cell metabolism, effector function, and persistence, thereby enabling tumor immune evasion. In this review, we summarize current understanding of how multimodal cell-cell communication, including immune checkpoints, metabolic reprogramming, and stromal crosstalk, cooperatively drive CD8 + T cell dysfunction. We also highlight emerging therapeutic strategies aimed at rewiring these suppressive networks, with emphasis on translational potential. A deeper understanding of the spatial, molecular, and metabolic context of CD8 + T cell suppression offers new avenues to enhance the efficacy of cancer immunotherapies.

T follicular helper (T FH ) cells are crucial for B cell-mediated humoral immunity 1 . Although transcription factors such as BCL6 drive the differentiation of T FH cells 2 , 3 , it is unclear whether and how post-transcriptional and metabolic programs enforce T FH cell programming. Here we show that the cytidine diphosphate (CDP)–ethanolamine pathway co-ordinates the expression and localization of CXCR5 with the responses of T FH cells and humoral immunity. Using in vivo CRISPR–Cas9 screening and functional validation in mice, we identify ETNK1, PCYT2, and SELENOI—enzymes in the CDP–ethanolamine pathway for de novo synthesis of phosphatidylethanolamine (PE)—as selective post-transcriptional regulators of T FH cell differentiation that act by promoting the surface expression and functional effects of CXCR5. T FH cells exhibit unique lipid metabolic programs and PE is distributed to the outer layer of the plasma membrane, where it colocalizes with CXCR5. De novo synthesis of PE through the CDP–ethanolamine pathway co-ordinates these events to prevent the internalization and degradation of CXCR5. Genetic deletion of Pcyt2 , but not of Pcyt1a  (which mediates the CDP–choline pathway), in activated T cells impairs the differentiation of T FH cells, and this is associated with reduced humoral immune responses. Surface levels of PE and CXCR5 expression on B cells also depend on Pcyt2 . Our results reveal that phospholipid metabolism orchestrates post-transcriptional mechanisms for T FH cell differentiation and humoral immunity, highlighting the metabolic control of context-dependent immune signalling and effector programs. Enzymes in the cytidine diphosphate–ethanolamine metabolic pathway, which promotes de novo synthesis of phosphatidylethanolamine, are shown to act as post-transcriptional mediators of the differentiation of T follicular helper (T FH ) cells, by regulating the chemokine receptor CXCR5.

[This corrects the article DOI: 10.3389/fimmu.2023.1159713.].

Herein, we developed a novel effervescence-assisted dual microextraction method, abbreviated as EM-LPSH, using lighter-than-water phosphonium-based ionic liquids (LPILs) and switchable hydrophilic/hydrophobic fatty acids (SHFAs). The EM-LPSH method was utilized for quick enrichment/extraction of polycyclic aromatic hydrocarbons (PAHs) in edible oils. Owing to lower density than water, LPILs used as the first extractant were floated on the upper layer of the aqueous phase, leading to a convenient separation/collection compared with traditional heavier-than-water imidazolium-based ionic liquids. Interestingly, SHFAs play triple functions: a dispersive solvent in the microextraction process, an acidic source in effervescent reaction, and the second extractant in dual microextraction, due to switchability from hydrophilicity to hydrophobicity. Consequently, the integration of LPILs with SHFAs greatly enhanced the extraction efficiency for PAHs owing to the quick dual microextraction process. Some important variables were rigorously optimized using a one-factor-at-a-time approach. Under optimized conditions, the EM-LPSH/HPLC-FLD method provided a wide linear range (0.07~0.63–200 μg kg−1), satisfactory recovery (80.12–103.27%), and low limit of detection (0.02–0.19 μg kg−1), as well as high intra-day and inter-day precision (0.03–6.55) for six PAHs in edible oils. By using certified reference material in olive oil samples (GBW10162), the recoveries ranged from 97.40 to 98.39%, demonstrating high accuracy and precision. According to the detected levels of PAHs in six unheated and heated oils, their edible safety was evaluated in detail. In short, the newly developed method is simple, convenient, and highly efficient, thereby showing great prospects for application in conventional monitoring of trace-level PAHs in edible oils.

By employing NH 2 -MIL-88 as a template, we synthesized the intermediate Fe@CN under high-temperature calcination and further fabricated the FeS 2 @CN nanocomposites in the presence of sulfur powder. Under varying temperatures (300–600 °C) and Fe@CN-to-S ratios (1:3–6), FeS 2 @CN 500-5 nanocomposites had the highest peroxidase-mimetic activity. Under optimized conditions (incubation temperature 40 °C; solution pH 4.0 and nanocomposite concentration 10 μg/mL; 652-nm absorption), the Michaelis-Menten constant ( K m ) of FeS 2 @CN was much lower than that of horseradish peroxidase (HRP), therefore demonstrating that it had a higher affinity for both chromogenic substrates than conventional HRP. The limits of detection for H 2 O 2 and glucose were 0.15 and 0.30 μmol/L, respectively, and the recoveries for glucose were 91.8–103% with RSDs <5.2%. The novelty of this study lies in (1) the FeS 2 @CN was confirmed to possess stronger enzyme-mimetic activity than its precursors (NH 2 -MIL-88 and Fe@CN); (2) the enhanced activity resulted from the unsaturated sites of N and S doping and the plentiful defects on the porous carbon surface; and (3) free radical trapping experiments evidenced that •OH played a major role in the catalytic reaction, while h + and •O 2 − simultaneously participated in the catalytic process. These convincing performance metrics lead us to postulate that the FeS 2 @CN-based colorimetric biosensor provides a promising approach for several real-world applications, such as point-of-care diagnosis and workplace health evaluations. Graphical abstract

Crystallization is important to the pharmaceutical, the chemical, and the materials fields, where the morphology of crystals is one of the key factors affecting the quality of crystallization. High-throughput screening based on microfluidic droplets is a potent technique to accelerate the discovery and development of new crystal morphologies with active pharmaceutical ingredients. However, massive crystal morphologies’ datum needs to be identified completely and accurately, which is time-consuming and labor-intensive. Therefore, effective morphologies’ detection and small-target tracking are essential for high-efficiency experiments. In this paper, a new improved algorithm YOLOv8 (YOLO-PBESW) for detecting indomethacin crystals with different morphologies is proposed. We enhanced its capability in detecting small targets through the integration of a high-resolution feature layer P2, and the adoption of a BiFPN structure. Additionally, in this paper, adding the EMA mechanism before the P2 detection head was implemented to improve network attention towards global features. Furthermore, we utilized SimSPPF to replace SPPF to mitigate computational costs and reduce inference time. Lastly, the CIoU loss function was substituted with WIoUv3 to improve detection performance. The experimental findings indicate that the enhanced YOLOv8 model attained advancements, achieving AP metrics of 93.3%, 77.6%, 80.2%, and 99.5% for crystal wire, crystal rod, crystal sheet, and jelly-like phases, respectively. The model also achieved a precision of 85.2%, a recall of 83.8%, and an F1 score of 84.5%, with a mAP of 87.6%. In terms of computational efficiency, the model’s dimensions and operational efficiency are reported as 5.46 MB, and it took 12.89 ms to process each image with a speed of 77.52 FPS. Compared with state-of-the-art lightweight small object detection models such as the FFCA-YOLO series, our proposed YOLO-PBESW model achieved improvements in detecting indomethacin crystal morphologies, particularly for crystal sheets and crystal rods. The model demonstrated AP values that exceeded L-FFCA-YOLO by 7.4% for crystal sheets and 3.9% for crystal rods, while also delivering a superior F1-score. Furthermore, YOLO-PBESW maintained a lower computational complexity, with parameters of only 11.8 GFLOPs and 2.65 M, and achieved a higher FPS. These outcomes collectively demonstrate that our method achieved a balance between precision and computational speed.