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As an indispensable part of the vehicle environment perception task, road traffic marking detection plays a vital role in correctly understanding the current traffic situation. However, the existing traffic marking detection algorithms still have some limitations. Taking lane detection as an example, the current detection methods mainly focus on the location information detection of lane lines, and they only judge the overall attribute of each detected lane line instance, thus lacking more fine-grained dynamic detection of lane line attributes. In order to meet the needs of intelligent vehicles for the dynamic attribute detection of lane lines and more perfect road environment information in urban road environment, this paper constructs a fine-grained attribute detection method for lane lines, which uses pixel-level attribute sequence points to describe the complete attribute distribution of lane lines and then matches the detection results of the lane lines. Realizing the attribute judgment of different segment positions of lane instances is called the fine-grained attribute detection of lane lines (Lane-FGA). In addition, in view of the lack of annotation information in the current open-source lane data set, this paper constructs a lane data set with both lane instance information and fine-grained attribute information by combining manual annotation and intelligent annotation. At the same time, a cyclic iterative attribute inference algorithm is designed to solve the difficult problem of lane attribute labeling in areas without visual cues such as occlusion and damage. In the end, the average accuracy of the proposed algorithm reaches 97% on various types of lane attribute detection.
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Hydroxytyrosol (HT), a plant-derived phenolic compound, is recognized for its potent antioxidant capabilities alongside a spectrum of pharmacological benefits, including anti-inflammatory, anti-cancer, anti-bacterial, and anti-viral properties. These attributes have propelled HT into the spotlight as a premier nutraceutical and food additive, heralding a new era in health and wellness applications. Traditional methods for HT production, encompassing physico-chemical techniques and plant extraction, are increasingly being supplanted by biotechnological approaches. These modern methodologies offer several advantages, notably environmental sustainability, safety, and cost-effectiveness, which align with current demands for green and efficient production processes. This review delves into the biosynthetic pathways of HT, highlighting the enzymatic steps involved and the pivotal role of genetic and metabolic engineering in enhancing HT yield. It also surveys the latest progress in the biotechnological synthesis of HT, examining innovative strategies that leverage both genetically modified and non-modified organisms. Furthermore, this review explores the burgeoning potential of HT as a nutraceutical, underscoring its diverse applications and the implications for human health. Through a detailed examination of both the biosynthesis and biotechnological advances in HT production, this review contributes valuable insights to the field, charting a course towards the sustainable and scalable production of this multifaceted compound.
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Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related mortality worldwide. Increasing evidence suggests that long noncoding RNAs play crucial roles in lung cancer pathogenesis. We previously identified a novel lncRNA, LINC070974, which is associated with tumor cell proliferation. In the present study, we find that knockdown of LINC070974 inhibits cell proliferation, migration and invasion as well as tumor formation both in vitro and in nude mice. LINC070974 silencing also improves cisplatin efficacy in A549/DDP cells. The function of LINC070974 may depend on its interaction with YBX1. Knockdown of LINC070974 reduces the recruitment of YBX1 to the CCND1 promoter and delays tumor progression through its coregulatory genes, which are mainly involved in the p53 signaling pathway. We utilize nebulized inhalation to deliver siRNAs targeting LINC070974 and find that LINC070974 significantly prevents tumor metastasis and growth in lung tissues. These findings reveal the role of LINC070974 in lung cancer and suggest a promising therapeutic approach involving siRNA inhalation.
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BACKGROUND: To date, because of the difficulty in obtaining normal parathyroid gland samples in human or in animal models, our understanding of this last-discovered organ remains limited. METHODS: In the present study, we performed a single-cell transcriptome analysis of six normal parathyroid and eight parathyroid adenoma samples using 10 × Genomics platform. FINDINGS: We have provided a detailed expression atlas of parathyroid endocrine cells. Interestingly, we found an exceptional high expression levels of CD4 and CD226 in parathyroid endocrine cells, which were even higher than those in lymphocytes. This unusual expression of lymphocyte markers in parathyroid endocrine cells was associated with the depletion of CD4 T cells in normal parathyroid glands. Moreover, CD4 and CD226 expression in endocrine cells was significantly decreased in parathyroid adenomas, which was associated with a significant increase in Treg counts. Finally, along the developmental trajectory, we discovered the loss of POMC, ART5, and CES1 expression as the earliest signature of parathyroid hyperplasia. INTERPRETATION: We propose that the loss of CD4 and CD226 expression in parathyroid endocrine cells, coupled with an elevated number of Treg cells, could be linked to the pathogenesis of parathyroid adenoma. Our data also offer valuable information for understanding the noncanonical function of CD4 molecule. FUNDING: This work was supported by the National Key R&D Program of China (2022YFA0806100), National Natural Science Foundation of China (82130025, 82270922, 31970636, 32211530422), Shandong Provincial Natural Science Foundation of China (ZR2020ZD14), Innovation Team of Jinan (2021GXRC048) and the Outstanding University Driven by Talents Program and Academic Promotion Program of Shandong First Medical University (2019LJ007).