Pan-cancer analysis of NUP155 and validation of its role in breast cancer cell proliferation, migration, and apoptosis.

NUP155 is reported to be correlated with tumor development. However, the role of NUP155 in tumor physiology and the tumor immune microenvironment (TIME) has not been previously examined. This study comprehensively investigated the expression, immunological function, and prognostic significance of NUP155 in different cancer types. Bioinformatics analysis revealed that NUP155 was upregulated in 26 types of cancer. Additionally, NUP155 upregulation was strongly correlated with advanced pathological or clinical stages and poor prognosis in several cancers. Furthermore, NUP155 was significantly and positively correlated with DNA methylation, tumor mutational burden, microsatellite instability, and stemness score in most cancers. Additionally, NUP155 was also found to be involved in TIME and closely associated with tumor infiltrating immune cells and immunoregulation-related genes. Functional enrichment analysis revealed a strong correlation between NUP155 and immunomodulatory pathways, especially antigen processing and presentation. The role of NUP155 in breast cancer has not been examined. This study, for the first time, demonstrated that NUP155 was upregulated in breast invasive carcinoma (BRCA) cells and revealed its oncogenic role in BRCA using molecular biology experiments. Thus, our study highlights the potential value of NUP155 as a biomarker in the assessment of prognostic prediction, tumor microenvironment and immunotherapeutic response in pan-cancer.

Fusobacterium nucleatum promotes the early occurrence of esophageal cancer through upregulation of IL-32/PRTN3 expression.

Previous studies have shown that gastrointestinal microbiome is associated with the development of esophageal cancer, but the relationship and molecular mechanism between esophageal microbiota and the early development of esophageal cancer remain unclear. Here, we found that Lactobacillus, Escherichia-Shigella, Rikenellaceae-RC9-gut-group, Morganella, and Fusobacterium were more abundant in early-stage esophageal cancer (EEC) tissues compared with normal esophageal tissues. The abundance of bacteria such as Prevotella, Fusobacterium, Porphyromonas, Actinobacillus, and Neisseria in advanced esophageal cancer (AEC) was higher than that in EEC. Then, we further verified that Fusobacterium nucleatum (Fn) was enriched in EEC tissues and that its abundance increased with the progression of esophageal cancer by FISH and RT-PCR. Next, we demonstrated that Fn promoted the proliferation of esophageal squamous cell carcinoma (ESCC) in vitro and in vivo. Finally, we confirmed that Fn promoted ESCC proliferation by upregulating the expression of interleukin (IL)-32/proteinase 3 (PRTN3) and then activating the PI3K/AKT signaling pathway. In conclusion, Fn promoted the early development of ESCC by upregulating the expression of IL-32/PRTN3 and thereby activating the PI3K/AKT signaling pathway. A better understanding of the molecular mechanism of Fn in early esophageal cancer may contribute to the development of early screening markers to diagnose ESCC and provide new targets for treatment.

Virtual Reality Rehabilitation Versus Conventional Physical Therapy for Improving Balance and Gait in Parkinson's Disease Patients: A Randomized Controlled Trial.

BACKGROUND The aim of this study was to investigate the effect of virtual reality (VR) technology on balance and gait in patients with Parkinson's disease (PD). MATERIAL AND METHODS The study design was a single-blinded, randomized, controlled study. Twenty-eight patients with PD were randomly divided into the experimental group (n=14) and the control group (n=14). The experimental group received VR training, and the control group received conventional physical therapy. Patients performed 45 minutes per session, 5 days a week, for 12 weeks. Individuals were assessed pre- and post-rehabilitation with the Berg Balance Scale (BBS), Timed Up and Go Test (TUGT), Third Part of Unified Parkinson's Disease Rating Scale (UPDRS3), and Functional Gait Assessment (FGA). RESULTS After treatment, BBS, TUGT, and FGA scores had improved significantly in both groups (P<0.05). However, there was no significant difference in the UPDRS3 between the pre- and post-rehabilitation data of the control group (P>0.05). VR training resulted in significantly better performance compared with the conventional physical therapy group (P<0.05). CONCLUSIONS The results of this study indicate that 12 weeks of VR rehabilitation resulted in a greater improvement in the balance and gait of individuals with PD when compared to conventional physical therapy.

Revealing Water Stress by the Thermal Power Industry in China Based on a High Spatial Resolution Water Withdrawal and Consumption Inventory.

This study reveals the spatial distribution of water withdrawal and consumption by thermal power generation and the associated water stress at catchment level in China based on a high-resolution geodatabase of electric generating units and power plants. We identified three groups of regions where the baseline water stress exerted by thermal power generation is comparatively significant: (1) the Hai River Basin/East Yellow River Basin in the north; (2) some arid catchments in Xinjiang Autonomous Region in the northwest; and (3) the coastal city clusters in the Yangtze River Delta, Pearly River Delta, and Zhejiang Province. Groundwater stress is also detected singularly in a few aquifers mainly in the Hai River Basin and the lower reaches of the Yellow River Basin. As China accelerates its pace of coal mining and coal-fired power generation in the arid northwest regions, the energy/water priorities in catchments under high water stress are noteworthy. We conclude that promotion of advanced water-efficient technologies in the energy industry and more systematic analysis of the water stress of thermal power capacity expansion in water scarce regions in inland China are needed. More comprehensive and transparent data monitoring and reporting are essential to facilitate such water stress assessment.

Amino Acid Residues in the Putative Transmembrane Domain 11 of Human Organic Anion Transporting Polypeptide 1B1 Dictate Transporter Substrate Binding, Stability, and Trafficking.

Organic anion transporting polypeptides (OATPs, gene symbol SLCO) are membrane proteins that mediate the sodium-independent transport of a wide range of endogenous and exogenous compounds. Due to their broad substrate specificity, wide tissue distribution, and involvement in drug-drug interactions, OATPs have been considered as key players in drug absorption, distribution, and excretion. Transmembrane domains (TMs) are crucial structural features involved in proper functions of many transporters. According to computer-based modeling and previous studies of our laboratory and others, TM11 of OATP1B1 may face the substrate interaction pocket and thus play an important role in the transport function of the protein. Alanine-scanning of the transmembrane domain identified seven critical amino acid residues within the region. Further analysis revealed that alanine substitution of these residues resulted in reduced protein stability, which led to significantly decreased protein expression on the plasma membrane. In addition, all mutants exhibited an altered Km for ES uptake (either high affinity or low affinity component, or both), though Km for taurocholate transport only changed in R580A, G584A, and F591A. These results suggested that critical residues in TM11 not only affect protein stability of the transporter, but its interaction with substrates as well. The identification of seven essential residues out of 21 TM amino acids highlighted the importance of this transmembrane domain in the proper function of OATP1B1.

Genetic polymorphisms in VDR, ESR1 and ESR2 genes may contribute to susceptibility to Parkinson's disease: a meta-analysis.

We conducted this meta-analysis of relevant case-control studies to investigate the relationships between genetic polymorphisms in VDR, ESR1 and ESR2 genes to the susceptibility of Parkinson's disease (PD). A search on electronic databases without any language restrictions was conducted: MEDLINE (1966-2013), the Cochrane Library Database (Issue 12, 2013), EMBASE (1980-2013), CINAHL (1982-2013), Web of Science (1945-2013) and the Chinese Biomedical Database (1982-2013). Meta-analysis was performed using the STATA statistical software. Crude odds ratio (OR) with their 95% confidence interval (95% CI) was calculated. Fourteen case-control studies with a total of 3,689 PD patients and 4,627 healthy subjects were included in our meta-analysis. The results of our meta-analysis demonstrated that the VDR genetic polymorphisms might be closely related to increased risks of PD (allele model: OR = 1.18, 95% CI 1.09-1.29, P < 0.001; dominant model: OR = 1.37, 95% CI 1.16-1.63, P < 0.001; respectively), especially for the polymorphisms rs7976091 and rs10735810. Our findings also illustrated that ESR1 genetic polymorphisms might increase the risk of PD (allele model: OR = 1.56, 95% CI 1.17-2.07, P = 0.002; recessive model: OR = 1.93, 95 % CI 1.33-2.80, P < 0.001; homozygous model: OR = 1.35, 95% CI 1.02-1.79, P = 0.038; heterozygous model: OR = 2.04, 95% CI 1.36-3.07, P = 0.001; respectively), especially for the polymorphisms rs2234693 and rs9340799. Furthermore, we found significant correlations of ESR2 genetic polymorphisms with the risk of PD (allele model: OR = 1.78, 95% CI 1.19-2.67, P = 0.005; recessive model: OR = 1.93, 95% CI 1.15-3.27, P = 0.014; homozygous model: OR = 1.77, 95% CI 1.09-2.89, P = 0.022; heterozygous model: OR = 1.88, 95% CI 1.08-3.27, P = 0.025; respectively), especially for the rs1256049 polymorphism. Our meta-analysis suggests that genetic polymorphisms in VDR, ESR1 and ESR2 genes may contribute to increased risks for PD.

Development of a biomarker signature associated with anoikis to predict prognosis and immunotherapy response in melanoma.

Skin cutaneous melanoma (SKCM) is malignant cancer known for its high aggressiveness and unfavorable prognosis, particularly in advanced tumors. Anoikis is a specific pattern of programmed cell death associated with tumor regeneration, migration, and metastasis. Nevertheless, limited research has been conducted to investigate the function of anoikis in SKCM. Anoikis-related genes (ARGs) were extracted from Genecards to identify SKCM subtypes and to explore the immune microenvironment between the different subtypes. Prognostic models of SKCM were developed by LASSO COX regression analysis. Subsequently, the predictive value of risk scores in SKCM and the association with immunotherapy were further explored. Finally, the expression of 6 ARGs involved in the model construction was detected by immunohistochemistry and PCR. This study identified 20 ARGs significantly associated with SKCM prognosis and performed disease subtype analysis of samples based on these genes, different subtypes exhibited significantly different clinical features and tumor immune microenvironment (TIME) landscapes. The risk score prognostic model was generated by further screening and identification of the six ARGs. The model exhibited a high degree of sensitivity and specificity to predict the prognosis of individuals with SKCM. These high- and low-risk populations showed different immune statuses and drug sensitivity. Further immunohistochemical and PCR experiments identified significant differential expression of the six ARGs in tumor and normal samples. Anoikis-based features may serve as novel prognostic biomarkers for SKCM and may provide important new insights for survival prediction and individualized treatment development.

Intelligent control of self-driving vehicles based on adaptive sampling supervised actor-critic and human driving experience.

Due to the complexity of the driving environment and the dynamics of the behavior of traffic participants, self-driving in dense traffic flow is very challenging. Traditional methods usually rely on predefined rules, which are difficult to adapt to various driving scenarios. Deep reinforcement learning (DRL) shows advantages over rule-based methods in complex self-driving environments, demonstrating the great potential of intelligent decision-making. However, one of the problems of DRL is the inefficiency of exploration; typically, it requires a lot of trial and error to learn the optimal policy, which leads to its slow learning rate and makes it difficult for the agent to learn well-performing decision-making policies in self-driving scenarios. Inspired by the outstanding performance of supervised learning in classification tasks, we propose a self-driving intelligent control method that combines human driving experience and adaptive sampling supervised actor-critic algorithm. Unlike traditional DRL, we modified the learning process of the policy network by combining supervised learning and DRL and adding human driving experience to the learning samples to better guide the self-driving vehicle to learn the optimal policy through human driving experience and real-time human guidance. In addition, in order to make the agent learn more efficiently, we introduced real-time human guidance in its learning process, and an adaptive balanced sampling method was designed for improving the sampling performance. We also designed the reward function in detail for different evaluation indexes such as traffic efficiency, which further guides the agent to learn the self-driving intelligent control policy in a better way. The experimental results show that the method is able to control vehicles in complex traffic environments for self-driving tasks and exhibits better performance than other DRL methods.

Multi-View Time-Series Hypergraph Neural Network for Action Recognition.

Recently, action recognition has attracted considerable attention in the field of computer vision. In dynamic circumstances and complicated backgrounds, there are some problems, such as object occlusion, insufficient light, and weak correlation of human body joints, resulting in skeleton-based human action recognition accuracy being very low. To address this issue, we propose a Multi-View Time-Series Hypergraph Neural Network (MV-TSHGNN) method. The framework is composed of two main parts: the construction of a multi-view time-series hypergraph structure and the learning process of multi-view time-series hypergraph convolutions. Specifically, given the multi-view video sequence frames, we first extract the joint features of actions from different views. Then, limb components and adjacent joints spatial hypergraphs based on the joints of different views at the same time are constructed respectively, temporal hypergraphs are constructed joints of the same view at continuous times, which are established high-order semantic relationships and cooperatively generate complementary action features. After that, we design a multi-view time-series hypergraph neural network to efficiently learn the features of spatial and temporal hypergraphs, and effectively improve the accuracy of skeleton-based action recognition. To evaluate the effectiveness and efficiency of MV-TSHGNN, we conduct experiments on NTU RGB+D, NTU RGB+D 120 and imitating traffic police gestures datasets. The experimental results indicate that our proposed method model achieves the new state-of-the-art performance.

A high-performance room-temperature NH3 gas sensor based on WO3/TiO2 nanocrystals decorated with Pt NPs.

In this work, a high-performance room-temperature ammonia (NH3) gas sensor based on Pt-modified WO3-TiO2 nanocrystals was synthesized via a two-step hydrothermal method. The structural properties were characterized by scanning electron microscopy, transmission electron microscopy, X-ray diffraction, and X-ray photoelectron spectroscopy. The 10 at% Pt@WO3-TiO2 nanocrystals present the highest NH3 sensing performance at room temperature. Compared with the nanocrystals without Pt modification, the sensitivity of the Pt@WO3-TiO2 sensor is tenfold higher, with the lowest concentration threshold reaching the 75 ppb level. The response is approximately 92.28 to 50 ppm, and response and recovery times are 23 s and 8 s, respectively. The improved sensing was attributed to a synergetic mechanism involving the space charge layer effect and Pt metal sensitization, enhancing the electron transfer efficiency, oxygen vacancy and specific surface area. This study is expected to guide the development of high-performance room-temperature ammonia sensors for clinical breath testing.

Pan-cancer Multi-omics Analysis Reveals HMGN1 as a Potential Prognostic and Immune Infiltration-associated Biomarker.

BACKGROUND: The High Mobility Group Nucleosomal Binding Domain 1 Gene (HMGN1) is crucial for epigenetic regulation. However, the specific function of HMGN1 in cancer development is unclear. METHODS: Raw data on HMGN1 expression were procured from Genotype-Tissue Expression (GTEx), the University of Alabama- Birmingham CANcer data analysis Portal (UALCAN), and The Cancer Genome Atlas (TCGA). Thereafter, the pan-cancer analysis was implemented to understand the HMGN1 expression patterns, prognostic value, and immunological features. Furthermore, the Gene Set Enrichment Analysis (GSEA) was executed via R language. In addition, the relationship between HMGN1 and the sensitivity of antitumor drugs was also determined. Finally, real-time PCR (RT-PCR) experiments were carried out. RESULTS: Pan-cancer analysis revealed that HMGN1 was upregulated in several solid tumors and was associated with pathological staging and poor prognosis. In addition, HMGN1 was found to be involved in regulating the tumor microenvironment. The GSEA enrichment analysis indicated that HMGN1 assisted in the regulation of oncogenic processes, especially metabolic and immune pathways. Furthermore, HMGN1 expression was linked to microsatellite instability (MSI) and tumor mutational burden (TMB) across diverse tumor types. RT-PCR assays indicated that HMGN1 was overexpressed in the gastric and breast cancer cell lines and tissues. CONCLUSION: This study highlighted the potential of HMGN1 as a biomarker for pan- - cancer analysis.

Humidity-tolerant and highly sensitive gas sensor for hydrogen sulfide based on WO3 nanocubes modified with CeO2.

The influence of ambient humidity on the gas-sensing characteristics of metal oxide semiconductors has been one of the greatest obstacles for gas-sensing applications. In this paper, the pure WO3 and CeO2-modified WO3 nanocubes were prepared by a simple hydrothermal method, and their gas-sensing characteristics in dry and humid atmospheres were investigated. The results show that CeO2/WO3 demonstrated excellent gas-sensing properties toward H2S with high sensitivity and high selectivity at 115 °C. Noteworthy, the humidity independence of the CeO2/WO3 increased compared to the WO3. The response retentions over the whole humidity range of the CeO2/WO3-6 and CeO2/WO3-15 sensors were 70.3, and 76%, respectively, which were much higher than the WO3 sensor (17.9%). The gas-sensing mechanism of CeO2-modified WO3 is discussed based on the gas sensitivity properties. The obtained results provide a promising route to enhance the anti-humidity properties of metal oxide semiconductor gas sensors.

Causal relationship between atrial fibrillation/warfarin and cutaneous melanoma: a two-sample Mendelian randomization study.

Purpose: In recent years, the relationship between malignant tumors and atrial fibrillation has attracted more and more attention. Atrial fibrillation can also cause a series of adverse events, such as the risk of thromboembolism. Also, Warfarin is often used here. But, the relationship between cutaneous melanoma and atrial fibrillation, and between cutaneous melanoma and warfarin is still unclear. Therefore, we used a two-sample Mendelian randomization to assess the causal relationship between atrial fibrillation/warfarin and cutaneous melanoma (cM). Methods: Firstly, atrial fibrillation (ukb-b-11550; nCase = 3,518, nControl = 459,415) and warfarin (ukb-b-13248; nCase = 4,623, nControl = 458,310) as exposures, with genome-wide association studies (GWAS) data from the United Kingdom Biobank. And cM (ieu-b-4969; nCase = 3,751, nControl = 372,016) as outcome, with GWAS data from the IEU Open GWAS project. Subsequently, single-nucleotide polymorphisms (SNPs) were filtered from GWAS studies using quality control measures. In addition, two-sample Mendelian randomization (MR) analysis was performed to explore the causal relationship between atrial fibrillation or warfarin and cM and used inverse variance weighting (IVW) as the primary analytical method. Finally, relevant heterogeneity and sensitivity analysis were performed to ensure the accuracy of the results. Results: A causal relationship between atrial fibrillation and cutaneous melanoma was observed, and between warfarin and cutaneous melanoma. Conclusion: The atrial fibrillation may play a causal role in the development of cutaneous melanoma, but the mechanism and the causal relationship between warfarin and cutaneous melanoma needs to be further elucidated.

A pan-cancer multi-omics analysis of lactylation genes associated with tumor microenvironment and cancer development.

Background: Lactylation is a significant post-translational modification bridging the gap between cancer epigenetics and metabolic reprogramming. However, the association between lactylation and prognosis, tumor microenvironment (TME), and response to drug therapy in various cancers remains unclear. Methods: First, the expression, prognostic value, and genetic and epigenetic alterations of lactylation genes were systematically explored in a pan-cancer manner. Lactylation scores were derived for each tumor using the single-sample gene set enrichment analysis (ssGSEA) algorithm. The correlation of lactylation scores with clinical features, prognosis, and TME was assessed by integrating multiple computational methods. In addition, GSE135222 data was used to assess the efficacy of lactylation scores in predicting immunotherapy outcomes. The expression of lactylation genes in breast cancers and gliomas were verified by RNA-sequencing. Results: Lactylation genes were significantly upregulated in most cancer types. CREBBP and EP300 exhibited high mutation rates in pan-cancer analysis. The prognostic impact of the lactylation score varied by tumor type, and lactylation score was a protective factor for KIRC, ACC, READ, LGG, and UVM, and a risk factor for CHOL, DLBC, LAML, and OV. In addition, a high lactylation score was associated with cold TME. The infiltration levels of CD8+ T, γδT, natural killer T cell (NKT), and NK cells were lower in tumors with higher lactylation scores. Finally, immunotherapy efficacy was worse in patients with high lactylation scores than other types. Conclusion: Lactylation genes are involved in malignancy formation. Lactylation score serves as a promising biomarker for predicting patient prognosis and immunotherapy efficacy.

Deep pan-cancer analysis and multi-omics evidence reveal that ALG3 inhibits CD8+ T cell infiltration by suppressing chemokine secretion and is associated with 5-fluorouracil sensitivity.

BACKGROUND: α-1,3-mannosyltransferase (ALG3) holds significance as a key member within the mannosyltransferase family. Nevertheless, the exact function of ALG3 in cancer remains ambiguous. Consequently, the current research aimed to examine the function and potential mechanisms of ALG3 in various types of cancer. METHODS: Deep pan-cancer analyses were conducted to investigate the expression patterns, prognostic value, genetic variations, single-cell omics, immunology, and drug responses associated with ALG3. Subsequently, in vitro experiments were executed to ascertain the biological role of ALG3 in breast cancer. Moreover, the link between ALG3 and CD8+ T cells was verified using immunofluorescence. Lastly, the association between ALG3 and chemokines was assessed using qRT-PCR and ELISA. RESULTS: Deep pan-cancer analysis demonstrated a heightened expression of ALG3 in the majority of tumors based on multi-omics evidence. ALG3 emerges as a diagnostic and prognostic biomarker across diverse cancer types. In addition, ALG3 participates in regulating the tumor immune microenvironment. Elevated levels of ALG3 were closely linked to the infiltration of bone marrow-derived suppressor cells (MDSC) and CD8+ T cells. According to in vitro experiments, ALG3 promotes proliferation and migration of breast cancer cells. Moreover, ALG3 inhibited CD8+ T cell infiltration by suppressing chemokine secretion. Finally, the inhibition of ALG3 enhanced the responsiveness of breast cancer cells to 5-fluorouracil treatment. CONCLUSION: ALG3 shows potential as both a prognostic indicator and immune infiltration biomarker across various types of cancer. Inhibition of ALG3 may represent a promising therapeutic strategy for tumor treatment.

Identification of CREB5 as a prognostic and immunotherapeutic biomarker in glioma through multi-omics pan-cancer analysis.

BACKGROUND: The functional relevance of cyclic adenosine monophosphate (cAMP)-response element-binding protein 5 (CREB5) in cancers remains elusive, despite its significance as a member of the CREB family. The current research aims to explore the role of CREB5 in multiple cancers. METHODS: Pan-cancer analysis was performed to explore the expression patterns, prognostic value, mutational landscape as well as single-cell omic, immunologic, and drug sensitivity profiles of CREB5. Furthermore, we incorporated five distinct machine learning algorithms and determined that the least absolute shrinkage and selection operator-COX (LASSO-COX) algorithm, which exhibited the highest C index, was the optimal selection. Subsequently, we constructed a prognostic model centered around CREB5-associated genes. To elucidate the biological function of CREB5 in glioma cells, several assays including cell counting kit-8 (CCK-8), wound healing, transwell, flow cytometric were performed. RESULTS: CREB5 was overexpressed in pan-cancer and was linked to unfavorable prognosis, particularly in glioma. Furthermore, genetic alterations were determined in various types of cancer, and modifications in the CREB5 gene were linked to the prognosis. The single-cell omics and enrichment analyses showed that CREB5 was predominantly expressed in malignant glioma cells and was critically involved in the regulation of various oncogenic processes. Elevated levels of CREB5 were strongly linked with the infiltration of cancer-associated fibroblasts and the Th1 subset of CD4+ T cells. The validated CREB5-associated prognostic model reliably predicted the prognosis and drug response of glioma patients. The in vitro experiments showed that CREB5 promoted glioma cell proliferation, invasion, migration, and gap phase 2/mitotic (G2/M) phase arrest and recruited M2 macrophages into glioma cells. CONCLUSION: CREB5 has the potential to act as an oncogene and a biological marker in multiple cancers, particularly glioma.

Wnt dose escalation during the exit from pluripotency identifies tranilast as a regulator of cardiac mesoderm.

Wnt signaling is a critical determinant of cell lineage development. This study used Wnt dose-dependent induction programs to gain insights into molecular regulation of stem cell differentiation. We performed single-cell RNA sequencing of hiPSCs responding to a dose escalation protocol with Wnt agonist CHIR-99021 during the exit from pluripotency to identify cell types and genetic activity driven by Wnt stimulation. Results of activated gene sets and cell types were used to build a multiple regression model that predicts the efficiency of cardiomyocyte differentiation. Cross-referencing Wnt-associated gene expression profiles to the Connectivity Map database, we identified the small-molecule drug, tranilast. We found that tranilast synergistically activates Wnt signaling to promote cardiac lineage differentiation, which we validate by in vitro analysis of hiPSC differentiation and in vivo analysis of developing quail embryos. Our study provides an integrated workflow that links experimental datasets, prediction models, and small-molecule databases to identify drug-like compounds that control cell differentiation.

Identification of a novel reactive oxygen species (ROS)-related genes model combined with RT-qPCR experiments for prognosis and immunotherapy in gastric cancer.

Reactive oxygen species play a crucial role in the prognosis and tumor microenvironment (TME) of malignant tumors. An ROS-related signature was constructed in gastric cancer (GC) samples from TCGA database. ROS-related genes were obtained from the Molecular Signatures Database. Consensus clustering was used to establish distinct ROS-related subtypes related to different survival and immune cell infiltration patterns. Sequentially, prognostic genes were identified in the ROS-related subtypes, which were used to identify a stable ROS-related signature that predicted the prognosis of GC. Correlation analysis revealed the significance of immune cell iniltration, immunotherapy, and drug sensitivity in gastric cancers with different risks. The putative molecular mechanisms of the different gastric cancer risks were revealed by functional enrichment analysis. A robust nomogram was established to predict the outcome of each gastric cancer. Finally, we verified the expression of the genes involved in the model using RT-qPCR. In conclusion, the ROS-related signature in this study is a novel and stable biomarker associated with TME and immunotherapy responses.

Research and implementation of variable-domain fuzzy PID intelligent control method based on Q-Learning for self-driving in complex scenarios.

In the control of the self-driving vehicles, PID controllers are widely used due to their simple structure and good stability. However, in complex self-driving scenarios such as curvature curves, car following, overtaking, etc., it is necessary to ensure the stable control accuracy of the vehicles. Some researchers used fuzzy PID to dynamically change the parameters of PID to ensure that the vehicle control remains in a stable state. It is difficult to ensure the control effect of the fuzzy controller when the size of the domain is not selected properly. This paper designs a variable-domain fuzzy PID intelligent control method based on Q-Learning to make the system robust and adaptable, which is dynamically changed the size of the domain to further ensure the control effect of the vehicle. The variable-domain fuzzy PID algorithm based on Q-Learning takes the error and the error rate of change as input and uses the Q-Learning method to learn the scaling factor online so as to achieve online PID parameters adjustment. The proposed method is verified on the Panosim simulation platform.The experiment shows that the accuracy is improved by 15% compared with the traditional fuzzy PID, which reflects the effectiveness of the algorithm.

Aflatoxin B1-induced early developmental hepatotoxicity in larvae zebrafish.

Aflatoxin B1 (AFB1) is a ubiquitous mycotoxin that causes oxidative damage in various organs. At present, the research studies on AFB1 are primarily focused on its effects on the terrestrial environment and animals. However, its toxicity mechanism in aquatic environments and aquatic animals has not been largely explored. Thus, in this study, zebrafish was used as a model to study the toxicity mechanism of AFB1 on the liver of developing larvae. The results showed that AFB1 exposure inhibited liver development and promoted fat accumulation in the liver. Transcriptome sequencing analysis showed that AFB1 affected liver redox metabolism and oxidoreductase activity. KEGG analysis showed that AFB1 inhibited the expression of gsto1, gpx4a, mgst3a, and idh1 in the glutathione metabolizing enzyme gene pathway, resulting in hepatic oxidative stress. At the same time, AFB1 also inhibited the expression of acox1, acsl1b, pparα, fabp2, and cpt1 genes in peroxidase and PPAR metabolic pathways, inducing hepatic steatosis and lipid droplet accumulation. Antioxidant N-Acetyl-l-cysteine (NAC) preconditioning up-regulated gsto1, gpx4a and idh1 genes, and improved the AFB1-induced lipid droplet accumulation in the liver. In summary, AFB1 induced hepatic oxidative stress and steatosis, resulting in abnormal liver fat metabolism and accumulation of cellular lipid droplets. NAC could be used as a potential preventative drug to improve AFB1-induced fat accumulation.