Adaptive Point-Line Fusion: A Targetless LiDAR-Camera Calibration Method with Scheme Selection for Autonomous Driving.

Accurate calibration between LiDAR and camera sensors is crucial for autonomous driving systems to perceive and understand the environment effectively. Typically, LiDAR-camera extrinsic calibration requires feature alignment and overlapping fields of view. Aligning features from different modalities can be challenging due to noise influence. Therefore, this paper proposes a targetless extrinsic calibration method for monocular cameras and LiDAR sensors that have a non-overlapping field of view. The proposed solution uses pose transformation to establish data association across different modalities. This conversion turns the calibration problem into an optimization problem within a visual SLAM system without requiring overlapping views. To improve performance, line features serve as constraints in visual SLAM. Accurate positions of line segments are obtained by utilizing an extended photometric error optimization method. Moreover, a strategy is proposed for selecting appropriate calibration methods from among several alternative optimization schemes. This adaptive calibration method selection strategy ensures robust calibration performance in urban autonomous driving scenarios with varying lighting and environmental textures while avoiding failures and excessive bias that may result from relying on a single approach.

Forecasting China carbon price using an error-corrected secondary decomposition hybrid model integrated fuzzy dispersion entropy and deep learning paradigm.

Forecasting China's carbon price accurately can encourage investors and manufacturing industries to take quantitative investments and emission reduction decisions effectively. The inspiration for this paper is developing an error-corrected carbon price forecasting model integrated fuzzy dispersion entropy and deep learning paradigm, named ICEEMDAN-FDE-VMD-PSO-LSTM-EC. Initially, the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) is used to primary decompose the original carbon price. Subsequently, the fuzzy dispersion entropy (FDE) is conducted to identify the high-complexity signals. Thirdly, the variational mode decomposition (VMD) and deep learning paradigm of particle swarm optimized long short-term memory (PSO-LSTM) models are employed to secondary decompose the high-complexity signals and perform out-of-sample forecasting. Finally, the error-corrected (EC) method is conducted to re-modify and strengthen the above-predicted accuracy. The results conclude that the forecasting performance of ICEEMDAN-type secondary decomposition models is significantly better than the primary decomposition models, the deep learning PSO-LSTM-type models have superiority in forecasting China carbon price, and the EC method for improving the forecasting accuracy has been proved. Noteworthy, the proposed model presents the best forecasting accuracy, with the forecasting errors RMSE, MAE, MAPE, and Pearson's correlation are 0.0877, 0.0407, 0.0009, and 0.9998, respectively. Especially, the long-term forecasting ability for 750 consecutive trading prices is outstanding. Those conclusions contribute to judging the carbon price characteristics and formulating market regulations.

GSTM3 enhances radiosensitivity of nasopharyngeal carcinoma by promoting radiation-induced ferroptosis through USP14/FASN axis and GPX4.

BACKGROUND: Radiotherapy is a critical treatment modality for nasopharyngeal carcinoma (NPC). However, the mechanisms underlying radiation resistance and tumour recurrence in NPC remain incompletely understood. METHODS: Oxidised lipids were assessed through targeted metabolomics. Ferroptosis levels were evaluated using cell viability, clonogenic survival, lipid peroxidation, and transmission electron microscopy. We investigated the biological functions of glutathione S-transferase mu 3 (GSTM3) in cell lines and xenograft tumours. Co-immunoprecipitation, mass spectrometry, and immunofluorescence were conducted to explore the molecular mechanisms involving GSTM3. Immunohistochemistry was performed to investigate the clinical characteristics of GSTM3. RESULTS: Ionising radiation (IR) promoted lipid peroxidation and induced ferroptosis in NPC cells. GSTM3 was upregulated following IR exposure and correlated with IR-induced ferroptosis, enhancing NPC radiosensitivity in vitro and in vivo. Mechanistically, GSTM3 stabilised ubiquitin-specific peptidase 14 (USP14), thereby inhibiting the ubiquitination and subsequent degradation of fatty acid synthase (FASN). Additionally, GSTM3 interacted with glutathione peroxidase 4 (GPX4) and suppressed GPX4 expression. Combining IR treatment with ferroptosis inducers synergistically improved NPC radiosensitivity and suppressed tumour growth. Notably, a decrease in GSTM3 abundance predicted tumour relapse and poor prognosis. CONCLUSIONS: Our findings elucidate the pivotal role of GSTM3 in IR-induced ferroptosis, offering strategies for the treatment of radiation-resistant or recurrent NPC.

Senescence-Related lncRNA Signature Predicts Prognosis, Response to Immunotherapy and Chemotherapy in Skin Cutaneous Melanoma.

Skin cutaneous melanoma (SKCM) is a highly malignant and aggressive cancer. Previous studies have shown that cellular senescence is a promising therapeutic strategy to limit melanoma cell progression. However, models to predict the prognosis of melanoma based on senescence-related lncRNAs and the efficacy of immune checkpoint therapy remain undefined. In this study, we developed a predictive signature consisting of four senescence-related lncRNAs (AC009495.2, U62317.1, AATBC, MIR205HG), and we then classified patients into high- and low-risk groups. GSEA (Gene set enrichment analysis) showed different activation of immune-related pathways in two groups. In addition, there were significant differences between the scores of tumor immune microenvironment, tumor burden mutation, immune checkpoint expression, and chemotherapeutic drug sensitivity between the two groups of patients. It provides new insights to guide more personalized treatment for patients with SKCM.

Poria cocos Polysaccharide Ameliorated Antibiotic-Associated Diarrhea in Mice via Regulating the Homeostasis of the Gut Microbiota and Intestinal Mucosal Barrier.

Poria cocos polysaccharides (PCP) have been validated for several biological activities, including antitumor, anti-inflammatory, antioxidant, immunomodulatory, hepatoprotective and modulation on gut microbiota. In this research, we aim to demonstrate the potential prebiotic effects and the therapeutic efficacies of PCP in the treatment of antibiotic-associated diarrhea (AAD), and confirm the beneficial effects of PCP on gut dysbiosis. Antibiotic-associated diarrhea mice models were established by treating them with broad-spectrum antibiotics in drinking water for seven days. Mice in two groups treated with probiotics and polysaccharide were given Bifico capsules (4.2 g/kg/d) and PCP (250 mg/kg/d) for seven days using intragastric gavage, respectively. To observe the regulatory effects of PCP on gut microbiota and intestinal mucosal barrier, we conducted the following experiments: intestinal flora analysis (16S rDNA sequencing), histology (H&E staining) and tight junction proteins (immunofluorescence staining). The levels of mRNA expression of receptors associated with inflammation and gut metabolism were assessed by real-time reverse transcription-polymerase chain reaction (RT-PCR). The study revealed that PCP can comprehensively improve the clinical symptoms of AAD mice, including fecal traits, mental state, hair quality, etc., similar to the effect of probiotics. Based on histology observation, PCP significantly improved the substantial structure of the intestine of AAD mice by increasing the expression levels of colonic tight junction protein zonula-occludens 1 (ZO-1) and its mRNA. Moreover, PCP not only increased the abundance of gut microbiota, but also increased the diversity of gut microbiota in AAD mice, including alpha diversity and beta diversity. Further analysis found that PCP can modulate seven characteristic species of intestinal flora in AAD mice, including Parabacteroides_distasonis, Akkermansia_muciniphila, Clostridium_saccharolyticum, Ruminoc-occus_gnavus, Lactobacillus_salivarius, Salmonella_enterica and Mucispirillum_schaedleri. Finally, enrichment analysis predicted that PCP may affect intestinal mucosal barrier function, host immune response and metabolic function by regulating the microbiota. RT-PCR experiments showed that PCP can participate in immunomodulatory and modulation on metabolic by regulating the mRNA expression of forkhead-box protein 3 (FOXP3) and G protein-coupled receptor 41 (GPR41). These results indicated that Poria cocos polysaccharide may ameliorate antibiotic-associated diarrhea in mice by regulating the homeostasis of the gut microbiota and intestinal mucosal barrier. In addition, polysaccharide-derived changes in intestinal microbiota were involved in the immunomodulatory activities and modulation of the metabolism.

CYLD deficiency enhances metabolic reprogramming and tumor progression in nasopharyngeal carcinoma via PFKFB3.

Aberrant cancer metabolism contributes to cell proliferation and tumor progression. However, the contribution of enhanced glycolysis, observed during cancer metabolism, to the pathogenesis and progression of nasopharyngeal carcinoma (NPC) remains unclear. CYLD, an NF-κB inhibitor, is frequently deficient in NPC. Here, we investigated the role of CYLD in the metabolic reprogramming of NPC and found that restoration of CYLD expression suppressed glycolysis in NPC cells. Mechanistic dissection showed that CYLD stabilized p53 and facilitated its nuclear translocation, thereby enhancing p53 activity by removing K63-linked and K48-linked ubiquitin chains of p53, which can bind to the PFKFB3 promoter and inhibit its transcription. Additionally, CYLD interacted with FZR1 to promote APC/C-FZR1 E3 ligase activity, which further ubiquitinated and degraded PFKFB3 via the 26S proteasomal system. Furthermore, clinical tissue array analysis indicated that low expression of CYLD was correlated with high expression of PFKFB3 and poor prognosis among patients with NPC. In conclusion, CYLD suppressed PFKFB3 expression via two factors, namely, p53 and FZR1, to inhibit glycolysis and delay tumor growth and progression in NPC. CYLD is a biomarker indicating poor prognosis of patients with NPC.

Protein tyrosine phosphatase receptor type D gene promotes radiosensitivity via STAT3 dephosphorylation in nasopharyngeal carcinoma.

Radiotherapy is essential to the treatment of nasopharyngeal carcinoma (NPC) and acquired or innate resistance to this therapeutic modality is a major clinical problem. However, the underlying molecular mechanisms in the radiation resistance in NPC are not fully understood. Here, we reanalyzed the microarray data from public databases and identified the protein tyrosine phosphatase receptor type D (PTPRD) as a candidate gene. We found that PTPRD was downregulated in clinical NPC tissues and NPC cell lines with its promoter hypermethylated. Functional assays revealed that PTPRD overexpression sensitized NPC to radiation in vitro and in vivo. Importantly, miR-454-3p directly targets PTPRD to inhibit its expression and biological effect. Interestingly, mechanistic analyses indicate that PTPRD directly dephosphorylates STAT3 to enhance Autophagy-Related 5 (ATG5) transcription, resulting in triggering radiation-induced autophagy. The immunohistochemical staining of 107 NPC revealed that low PTPRD and high p-STAT3 levels predicted poor clinical outcome. Overall, we showed that PTPRD promotes radiosensitivity by triggering radiation-induced autophagy via the dephosphorylation of STAT3, thus providing a potentially useful predictive biomarker for NPC radiosensitivity and drug target for NPC radiosensitization.