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In semantic segmentation, the efficient representation of multi-scale context is of paramount importance. Inspired by the remarkable performance of Vision Transformers (ViT) in image classification, subsequent researchers have proposed some Semantic Segmentation ViTs, most of which have achieved impressive results. However, these models often struggle to effectively utilizing multi-scale context, disregarding intra-image semantic context, and neglecting the global context of training data, i.e., the semantic relationships among pixels across different images. In this paper, we introduce the Sliding Window Dilated Attention and combine it with the Spatial Pyramid Pooling (SPP) to form a novel decoder called Sliding window dilated attention spatial pyramid pooling(SwinASPP). By adjusting the sliding window dilation rates, this decoder is capable of capturing multi-scale contextual information from different granularities. Additionally, we propose the Semantic Attention Block, which integrates semantic attention operations into the encoder. And adopt our proposed supervised pixel-wise contrastive learning algorithm, we shift the current training strategy to inter-image for semantic segmentation. Our experiments demonstrate that these methods lead to performance improvements on the SanJiangYuan MouseHole dataset and Cityscapes.

Rodent infestation has become one of the important factors in grassland degradation on the Qinghai–Tibet Plateau, one of the hindrances to ecological and environmental protection, and a threat to the balance and development of the ecosystem in the Sanjiangyuan region. Based on the need for the scientific planning for ecological protection, this paper designs a method for detecting rodent infestation in plateau scenarios. Firstly, data were collected and annotated, and a dataset of plateau rodent distribution in the Qinghai region was constructed. The collected data include videos captured through drone-based field surveys, which were processed using OpenCV and annotated with LabelMe. The dataset is categorized into four specific types: ungobbled rat holes, gobbled rat holes, rocks, and cow dung. This categorization allows the model to effectively differentiate between rodent-related features and other environmental elements, which is crucial for the segmentation task. Secondly, the latest segmentation algorithm provided by YOLO v8 is improved to design a segmentation algorithm that can accurately detect the distribution of rodent infestation in the plateau scene. The specific improvements are as follows: firstly, the Contextual Transformer module is introduced in YOLO v8 to improve the global modeling capability; secondly, the DRConv dynamic region-aware convolution is introduced in YOLO v8 to improve the convolutional representation capability; thirdly, the attention mechanism is incorporated in the backbone of YOLO v8 to enhance the feature extraction capability of the network capability. A comparison test with the original algorithm on the plateau rodent distribution dataset showed that the new algorithm improved the detection accuracy from 77.9% to 82.74% and MIoU from 67.65% to 72.69% on the plateau rodent distribution dataset. The accuracy of the evaluation of plateau rodent damage levels has been greatly improved.

Maintaining a harmonious balance between grassland ecology and local economic development necessitates effective management of livestock resources. Traditional approaches have proven inefficient, highlighting an urgent need for intelligent solutions. Accurate identification of livestock targets is pivotal for precise livestock farming management. However, the You Only Look Once version 8 (YOLOv8) model exhibits limitations in accuracy when confronted with complex backgrounds and densely clustered targets. To address these challenges, this study proposes an optimized CCS-YOLOv8 (Comprehensive Contextual Sensing YOLOv8) model. First, we curated a comprehensive livestock detection dataset encompassing the Qinghai region. Second, the YOLOv8n model underwent three key enhancements: (1) incorporating a Convolutional Block Attention Module (CBAM) to accentuate salient image information, thereby boosting feature representational power; (2) integrating a Content-Aware ReAssembly of FEatures (CARAFE) operator to mitigate irrelevant interference, improving the integrity and accuracy of feature extraction; and (3) introducing a dedicated small object detection layer to capture finer livestock details, enhancing the recognition of smaller targets. Experimental results on our dataset demonstrate the CCS-YOLOv8 model’s superior performance, achieving 84.1% precision, 82.2% recall, 84.4% mAP@0.5, 60.3% mAP@0.75, 53.6% mAP@0.5:0.95, and 83.1% F1-score. These metrics reflect substantial improvements of 1.1%, 7.9%, 5.8%, 6.6%, 4.8%, and 4.7%, respectively, over the baseline model. Compared to mainstream object detection models, CCS-YOLOv8 strikes an optimal balance between accuracy and real-time processing capability. Its robustness is further validated on the VisDrone2019 dataset. The CCS-YOLOv8 model enables rapid and accurate identification of livestock age groups and species, effectively overcoming the challenges posed by complex grassland backgrounds and densely clustered targets. It offers a novel strategy for precise livestock population management and overgrazing prevention, aligning seamlessly with the demands of modern precision livestock farming. Moreover, it promotes local environmental conservation and fosters sustainable development within the livestock industry.

Abstract Background RNA‐binding protein Quaking‐5 (QKI‐5), a major isoform of QKIs, inhibits tumor progression in non‐small cell lung cancer (NSCLC). However, the underlying molecular mechanisms of QKI‐5 in the cell cycle of NSCLC are still largely unknown. Methods MTT, flow cytometry, and colony formation assays were used to investigate cellular phenotypic changes. Mice xenograft model was used to evaluate the antitumor activities of QKI‐5. Co‐immunoprecipitation, RNA immunoprecipitation (RIP), and RIP sequencing were used to investigate protein–protein interaction and protein–mRNA interaction. Results The QKI‐5 expression was downregulated in NSCLC tissues compared with that in paired normal adjacent lung tissues. Overexpression of QKI‐5 inhibited NSCLC cell proliferative and colony forming ability. In addition, QKI‐5 induced cell cycle arrest at G0/G1 phase through upregulating p21Waf1/Cip1 (p21) expression and downregulating cyclin D1, cyclin‐dependent kinase 4 (CDK4), and CDK6 expressions. Further analyses showed that QKI‐5 interacts with p21 protein and CDK4, CDK6 mRNAs, suggesting a critical function of QKI‐5 in cell cycle regulation. In agreement with in vitro study, the mouse xenograft models validated tumor suppressive functions of QKI‐5 in vivo through altering cell cycle G1‐phase‐associated proteins. Moreover, we demonstrated that QKI‐5 is a direct target of miR‐31. The QKI‐5 expression was anticorrelated with the miR‐31 expression in NSCLC patient samples. Conclusion Our results suggest that the miR‐31/QKI‐5/p21‐CDK4–CDK6 axis might have critical functions in the progression of NSCLC, and targeting this axis could serve as a potential therapeutic strategy for NSCLC.

Background: Our recent study found that QKI-5 regulated miRNA, miR-196b-5p, promotes non-small cell lung cancer (NSCLC) progression by directly targeting GATA6, TSPAN12 and FAS. However, the biological functions of miR-196b-5p in NSCLC progression and metastasis still remain elusive. Methods: Cell proliferation, migration, colony formation, cell cycle assays were used to investigate cellular phenotypic changes. Quantitative real-time PCR (qRT-PCR) and western blot analyses were used to measure expressions of relative gene and protein. Interaction between QKI-5 and miR-196b-5p was determined by RNA immunoprecipitation (RIP) assay. Luciferase reporter assay was used to determine direct binding between miR-196b-5p and NFKBIA 3′-UTR. ELISA assay was used to measure secreted IL6 proteins. Mice xenograft model was used to assess the functions of NFKBIA on in vivo tumor growth. Results: We demonstrated that the miR-196b-5p facilitates lung cancer cell proliferation, migration, colony formation, and cell cycle by directly targeting NFKBIA, a negative regulator of NFκB signaling. Knocking down NFKBIA increases IL6 mediated phosphorylation of signal transducer and activator of transcription 3 (STAT3) to promote lung cancer cell growth by activating NFκB signaling. The expression of NFKBIA was significantly downregulated in NSCLC tissue samples, and was negatively correlated with the expression miR-196b-5p. In addition, we found that downregulated QKI-5 expression was associated with the elevated miR-224 expression in NSCLC. Conclusions: Our findings indicated that the miR-224/QKI-5/miR-196b-5p/NFKBIA signaling pathway might play important functions in the progression of NSCLC, and suggested that targeting this pathway might be an effective therapeutic strategy in treating NSCLC.

Abstract Background Breast cancer is the most prevalent cancer among women worldwide. WZ35, an analog of curcumin, has been demonstrated to remarkably improve the pharmacokinetic profiles in vivo compared with curcumin. WZ35 exhibits promising antitumor activity in gastric cancer, HCC, colon cancer. However, antitumor effects of WZ35 in breast cancer and its underlying molecular mechanisms remain unclear. Methods CCK8, Flow cytometry and transwell assays were used to measure cell proliferation, cell cycle arrest, apoptosis, cell migration and invasion. We constructed xenograft mouse model and lung metastasis model to assess the antitumor activities of WZ35 in vivo. To explore the underlying molecular mechanisms of WZ35, we performed a series of overexpression and knockdown experiments. The cellular oxygen consumption rates (OCRs) was measured to assess mitochondrial dysfunction. Results We found that treatment of breast cancer cells with WZ35 exerts stronger anti-tumor activities than curcumin both in vitro and in vivo. Mechanistically, our research showed that WZ35 induced reactive oxygen species (ROS) generation and subsequent YAP mediated JNK activation in breast cancer cells. Abrogation of ROS production markedly attenuated WZ35 induced anti-tumor activities as well as YAP and JNK activation. In addition, ROS mediated YAP and JNK activation induced mitochondrial dysfunction in breast cancer cells. Conclusion Our study showed that novel anti-cancer mechanisms of WZ35 in breast cancer cells and ROS-YAP-JNK pathway might be a potential therapeutic target for the treatment of breast cancer patients.

Lung cancer is the leading cause of cancer-related deaths worldwide and non-small cell lung cancer (NSCLC) accounts for more than 80% of all lung cancer cases. Recent advancements in diagnostic tools, surgical treatments, chemotherapies, and molecular targeted therapies that improved the therapeutic efficacy in NSCLC. However, the 5-years relative survival rate of NSCLC is only about 20% due to the inadequate screening methods and late onset of clinical symptoms. Dysregulation of microRNAs (miRNAs) was frequently observed in NSCLC and closely associated with NSCLC development, progression, and metastasis through regulating their target genes. In this review, we provide an updated overview of aberrant miRNA signature in NSCLC, and discuss the possibility of miRNAs becoming a diagnostic and therapeutic tool. We also discuss the possible causes of dysregulated miRNAs in NSCLC.