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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Prognostic value analysis of cholesterol and cholesterol homeostasis related genes in breast cancer by Mendelian randomization and multi-omics machine learning.

Introduction: The high incidence of breast cancer (BC) prompted us to explore more factors that might affect its occurrence, development, treatment, and also recurrence. Dysregulation of cholesterol metabolism has been widely observed in BC; however, the detailed role of how cholesterol metabolism affects chemo-sensitivity, and immune response, as well as the clinical outcome of BC is unknown. Methods: With Mendelian randomization (MR) analysis, the potential causal relationship between genetic variants of cholesterol and BC risk was assessed first. Then we analyzed 73 cholesterol homeostasis-related genes (CHGs) in BC samples and their expression patterns in the TCGA cohort with consensus clustering analysis, aiming to figure out the relationship between cholesterol homeostasis and BC prognosis. Based on the CHG analysis, we established a CAG_score used for predicting therapeutic response and overall survival (OS) of BC patients. Furthermore, a machine learning method was adopted to accurately predict the prognosis of BC patients by comparing multi-omics differences of different risk groups. Results: We observed that the alterations in plasma cholesterol appear to be correlative with the venture of BC (MR Egger, OR: 0.54, 95% CI: 0.35-0.84, p<0.006). The expression patterns of CHGs were classified into two distinct groups(C1 and C2). Notably, the C1 group exhibited a favorable prognosis characterized by a suppressed immune response and enhanced cholesterol metabolism in comparison to the C2 group. In addition, high CHG score were accompanied by high performance of tumor angiogenesis genes. Interestingly, the expression of vascular genes (CDH5, CLDN5, TIE1, JAM2, TEK) is lower in patients with high expression of CHGs, which means that these patients have poorer vascular stability. The CAG_score exhibits robust predictive capability for the immune microenvironment characteristics and prognosis of patients(AUC=0.79). It can also optimize the administration of various first-line drugs, including AKT inhibitors VIII Imatinib, Crizotinib, Saracatinib, Erlotinib, Dasatinib, Rapamycin, Roscovitine and Shikonin in BC patients. Finally, we employed machine learning techniques to construct a multi-omics prediction model(Risklight),with an area under the feature curve (AUC) of up to 0.89. Conclusion: With the help of CAG_score and Risklight, we reveal the signature of cholesterol homeostasis-related genes for angiogenesis, immune responses, and the therapeutic response in breast cancer, which contributes to precision medicine and improved prognosis of BC.

Novel immune checkpoint-related gene model to predict prognosis and treatment responsiveness in low-grade gliomas.

Recently, studies have shown that immune checkpoint-related genes (ICGs) are instrumental in maintaining immune homeostasis and can be regarded as potential therapeutic targets. However, the prognostic applications of ICGs require further elucidation in low-grade glioma (LGG) cases. In the present study, a unique prognostic gene signature in LGG has been identified and validated as well based on ICGs as a means of facilitating clinical decision-making. The RNA-seq data as well as corresponding clinical data of LGG samples have been retrieved utilizing the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. ICG-defined non-negative matrix factorization (NMF) clustering was performed to categorize patients with LGG into two molecular subtypes with different prognoses, clinical traits, and immune microenvironments. In the TCGA database, a signature integrating 8 genes has been developed utilizing the LASSO Cox method and validated in the GEO database. The signature developed is superior to other well-recognized signatures in terms of predicting the survival probability of patients with LGG. This 8-gene signature was then subsequently applied to categorize patients into high- and low-risk groups, and differences between them in terms of gene alteration frequency were observed. There were remarkable variations in IDH1 (91% and 64%) across low-as well as high-risk groups. Additionally, various analyses like function enrichment, tumor immune microenvironment, and chemotherapy drug sensitivity revealed significant variations across high- and low-risk populations. Overall, this 8-gene signature may function as a useful tool for prognosis and immunotherapy outcome predictions among LGG patients.

The pan-cancer multi-omics landscape of key genes of sialylation combined with RNA-sequencing validation.

BACKGROUND: Sialylation, the process of salivary acid glycan synthesis, plays a pivotal function in tumor growth, immune escape, tumor metastasis, and resistance to drugs. However, the association between sialylation and prognosis, tumor microenvironment (TME), and treatment response in a variety of cancers remains unclear. METHODS: A comprehensive survey of the expression profile, prognostic value, and genetic and epigenetic alterations of sialylation-related genes was performed in pan-cancer. Subsequently, the single-sample gene set enrichment analysis (ssGSEA) algorithm was used to compute sialylation pathway scores in pan-cancer. Correlations of sialylation pathway scores with clinical features, prognosis, and TME were evaluated using multiple algorithms. Finally, the efficacy of the sialylation pathway score in determining the effect of immunotherapy was evaluated. The expression of sialylation-related genes were verified by RNA-sequencing. RESULTS: Significant differences were observed in sialylation-related genes expression between tumors and adjacent normal tissues for most cancer types. Sialylation pathway scores differed according to the type of tumor, where the poor prognosis was correlated with high sialylation pathway scores in uveal melanoma (UVM) and pancreatic adenocarcinoma (PAAD). In addition, sialylation pathway scores were positively associated with the ImmuneScore, StromalScore and immune-related pathways. Moreover, the level of immune cells infiltration was higher in tumors with higher sialylation pathway scores. Finally, patients with high sialylation pathway scores were more sensitive to immunotherapy. CONCLUSION: Sialylation-related genes are essential in pan-cancer. The sialylation pathway score may be used as a biomarker in oncology patients.

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.

Acetyl-cinobufagin suppresses triple-negative breast cancer progression by inhibiting the STAT3 pathway.

BACKGROUND: The incidence of breast cancer (BC) worldwide has increased substantially in recent years. Epithelial-mesenchymal transition (EMT) refers to a crucial event impacting tumor heterogeneity. Although cinobufagin acts as an effective anticancer agent, the clinical use of cinobufagin is limited due to its strong toxicity. Acetyl-cinobufagin, a pre-drug of cinobufagin, was developed and prepared with greater efficacy and lower toxicity. METHODS: A heterograft mouse model using triple negative breast cancer (TNBC) cell lines, was used to evaluate the potency of acetyl-cinobufagin. Signal transducer and stimulator of transcription 3 (STAT3)/EMT involvement was investigated by gene knockout experiments using siRNA and Western blot analysis. RESULTS: Acetyl-cinobufagin inhibited proliferation, migration, and cell cycle S/G2 transition and promoted apoptosis in TNBC cells in vitro. In general, IL6 triggered the phosphorylation of the transcription factor STAT3 thereby activating the STAT3 pathway and inducing EMT. Mechanistically, acetyl-cinobufagin suppressed the phosphorylation of the transcription factor STAT3 and blocked the interleukin (IL6)-triggered translocation of STAT3 to the cell nucleus. In addition, acetyl-cinobufagin suppressed EMT in TNBC by inhibiting the STAT3 pathway. Experiments in an animal model of breast cancer clearly showed that acetyl-cinobufagin was able to reduce tumor growth. CONCLUSIONS: The findings of this study support the potential clinical use of acetyl-cinobufagin as a STAT3 inhibitor in TNBC adjuvant therapy.

Establishment and validation of a ubiquitination-related gene signature associated with prognosis in pancreatic duct adenocarcinoma.

Background: Patients with pancreatic duct adenocarcinoma (PDAC) have varied prognoses that depend on numerous variables. However, additional research is required to uncover the latent impact of ubiquitination-related genes (URGs) on determining PDAC patients' prognoses. Methods: The URGs clusters were discovered via consensus clustering, and the prognostic differentially expressed genes (DEGs) across clusters were utilized to develop a signature using a least absolute shrinkage and selection operator (LASSO) regression analysis of data from TCGA-PAAD. Verification analyses were conducted across TCGA-PAAD, GSE57495 and ICGC-PACA-AU to show the robustness of the signature. RT-qPCR was used to verify the expression of risk genes. Lastly, we formulated a nomogram to improve the clinical efficacy of our predictive tool. Results: The URGs signature, comprised of three genes, was developed and was shown to be highly correlated with the prognoses of PAAD patients. The nomogram was established by combining the URGs signature with clinicopathological characteristics. We discovered that the URGs signature was remarkably superior than other individual predictors (age, grade, T stage, et al). Also, the immune microenvironment analysis indicated that ESTIMATEscore, ImmuneScores, and StromalScores were elevated in the low-risk group. The immune cells that infiltrated the tissues were different between the two groups, as did the expression of immune-related genes. Conclusion: The URGs signature could act as the biomarker of prognosis and selecting appropriate therapeutic drugs for PDAC patients.

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.

Dual antitumor immunomodulatory effects of PARP inhibitor on the tumor microenvironment: A counterbalance between anti-tumor and pro-tumor.

Poly (ADP-ribose)-polymerases (PARPs) play an essential role in the maintenance of genome integrity, DNA repair, and apoptosis. PARP inhibitors (PARPi) exert antitumor effects via synthetic lethality and PARP trapping. PARPi impact the antitumor immune response by modulating the tumor microenvironment, and their effect has dual properties of promoting and inhibiting the antitumor immune response. PARPi promote M1 macrophage polarization, antigen presentation by dendritic cells, infiltration of B and T cells and their killing capacity and inhibit tumor angiogenesis. PARPi can also inhibit the activation and function of immune cells by upregulating PD-L1. In this review, we summarize the dual immunomodulatory effects and possible underlying mechanisms of PARPi, providing a basis for the design of combination regimens for clinical treatment and the identification of populations who may benefit from these therapies.

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.

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.