A Self-Collision Detection Algorithm of a Dual-Manipulator System Based on GJK and Deep Learning.

Self-collision detection is fundamental to the safe operation of multi-manipulator systems, especially when cooperating in highly dynamic working environments. Existing methods still face the problem that detection efficiency and accuracy cannot be achieved at the same time. In this paper, we introduce artificial intelligence technology into the control system. Based on the Gilbert-Johnson-Keerthi (GJK) algorithm, we generated a dataset and trained a deep neural network (DLNet) to improve the detection efficiency. By combining DLNet and the GJK algorithm, we propose a two-level self-collision detection algorithm (DLGJK algorithm) to solve real-time self-collision detection problems in a dual-manipulator system with fast-continuous and high-precision properties. First, the proposed algorithm uses DLNet to determine whether the current working state of the system has a risk of self-collision; since most of the working states in a system workspace do not have a self-collision risk, DLNet can effectively reduce the number of unnecessary detections and improve the detection efficiency. Then, for the working states with a risk of self-collision, we modeled precise colliders and applied the GJK algorithm for fine self-collision detection, which achieved detection accuracy. The experimental results showed that compared to that with the global use of the GJK algorithm for self-collision detection, the DLGJK algorithm can reduce the time expectation of a single detection in a system workspace by 97.7%. In the path planning of the manipulators, it could effectively reduce the number of unnecessary detections, improve the detection efficiency, and reduce system overhead. The proposed algorithm also has good scalability for a multi-manipulator system that can be split into dual-manipulator systems.

Comprehensive analysis of a novel signature incorporating lipid metabolism and immune-related genes for assessing prognosis and immune landscape in lung adenocarcinoma.

Background: As the crosstalk between metabolism and antitumor immunity continues to be unraveled, we aim to develop a prognostic gene signature that integrates lipid metabolism and immune features for patients with lung adenocarcinoma (LUAD). Methods: First, differentially expressed genes (DEGs) related to lipid metabolism in LUAD were detected, and subgroups of LUAD patients were identified via the unsupervised clustering method. Based on lipid metabolism and immune-related DEGs, variables were determined by the univariate Cox and LASSO regression, and a prognostic signature was established. The prognostic value of the signature was evaluated by the Kaplan-Meier method, time-dependent ROC, and univariate and multivariate analyses. Five independent GEO datasets were employed for external validation. Gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), and immune infiltration analysis were performed to investigate the underlying mechanisms. The sensitivity to common chemotherapeutic drugs was estimated based on the GDSC database. Finally, we selected PSMC1 involved in the signature, which has not been reported in LUAD, for further experimental validation. Results: LUAD patients with different lipid metabolism patterns exhibited significant differences in overall survival and immune infiltration levels. The prognostic signature incorporated 10 genes and stratified patients into high- and low-risk groups by median value splitting. The areas under the ROC curves were 0.69 (1-year), 0.72 (3-year), 0.74 (5-year), and 0.74 (10-year). The Kaplan-Meier survival analysis revealed a significantly poorer overall survival in the high-risk group in the TCGA cohort (p < 0.001). In addition, both univariate and multivariate Cox regression analyses indicated that the prognostic model was the individual factor affecting the overall survival of LUAD patients. Through GSEA and GSVA, we found that tumor progression and inflammatory and immune-related pathways were enriched in the high-risk group. Additionally, patients with high-risk scores showed higher sensitivity to chemotherapeutic drugs. The in vitro experiments further confirmed that PSMC1 could promote the proliferation and migration of LUAD cells. Conclusions: We developed and validated a novel signature incorporating both lipid metabolism and immune-related genes for all-stage LUAD patients. This signature can be applied not only for survival prediction but also for guiding personalized chemotherapy and immunotherapy regimens.

Identification of GGT5 as a Novel Prognostic Biomarker for Gastric Cancer and its Correlation With Immune Cell Infiltration.

Gastric cancer (GC) is a common malignant tumor of the digestive system. Recent studies revealed that high gamma-glutamyl-transferase 5 (GGT5) expression was associated with a poor prognosis of gastric cancer patients. In the present study, we aimed to confirm the expression and prognostic value of GGT5 and its correlation with immune cell infiltration in gastric cancer. First, we compared the differential expression of GGT5 between gastric cancer tissues and normal gastric mucosa in the cancer genome atlas (TCGA) and GEO NCBI databases using the most widely available data. Then, the Kaplan-Meier method, Cox regression, and univariate logistic regression were applied to explore the relationships between GGT5 and clinical characteristics. We also investigated the correlation of GGT5 with immune cell infiltration, immune-related genes, and immune checkpoint genes. Finally, we estimated enrichment of gene ontologies categories and relevant signaling pathways using GO annotations, KEGG, and GSEA pathway data. The results showed that GGT5 was upregulated in gastric cancer tissues compared to normal tissues. High GGT5 expression was significantly associated with T stage, histological type, and histologic grade (p < 0.05). Moreover, gastric cancer patients with high GGT5 expression showed worse 10-years overall survival (p = 0.008) and progression-free intervals (p = 0.006) than those with low GGT5 expression. Multivariate analysis suggested that high expression of GGT5 was an independent risk factor related to the worse overall survival of gastric cancer patients. A nomogram model for predicting the overall survival of GC was constructed and computationally validated. GGT5 expression was positively correlated with the infiltration of natural killer cells, macrophages, and dendritic cells but negatively correlated with Th17 infiltration. Additionally, we found that GGT5 was positively co-expressed with immune-related genes and immune checkpoint genes. Functional analysis revealed that differentially expressed genes relative to GGT5 were mainly involved in the biological processes of immune and inflammatory responses. In conclusion, GGT5 may serve as a promising prognostic biomarker and a potential immunological therapeutic target for GC, since it is associated with immune cell infiltration in the tumor microenvironment.

Identification of prognostic markers for hepatocellular carcinoma based on the epithelial-mesenchymal transition-related gene BIRC5.

BACKGROUND: The baculoviral IAP repeat containing 5 (BIRC5) related to epithelial-mesenchymal transition (EMT) plays a crucial role in the pathogenesis of hepatocellular carcinoma (HCC). However, it remains unclear whether BIRC5-related genes can be used as prognostic markers of HCC. METHODS: Kaplan-Meier (K-M) survival curve was used to assess the Overall Survival (OS) of high- and low-expression group divided by the median of BIRC5 expression. The differentially expressed genes (DEGs) between the two groups were screened using the limma package, and performed the functional enrichment analysis by the clusterProfiler package. WGCNA was used to analyze the relationship of the module and the clinical traits. The risk signature was constructed by univariate and multivariate Cox regression analyses and the enrichment analysis of genes in the risk signature was performed by the Intelligent pathway analysis (IPA). The immunophenoscore (IPS) and the tumor immune dysfunction and exclusion (TIDE) were used to estimate the clinical significance of the risk groups. RESULTS: BIRC5 was high-expressed in HCC samples and associated with a poor prognosis (p-value < 0.0001). WGCNA screened 180 module genes which were overlapped with the 241 DEGs, ultimately getting 33 candidate genes. After the Cox regression analyses, CENPA, CDCA8, EZH2, KIF20A, KPNA2, CCNB1, KIF18B and MCM4 were preserved and used to construct risk signature, followed by calculating the risk score. The patients in high-risk groups stratified by median of the risk score were associated with a poor prognosis. The risk score had high accuracy [the area under the curve (AUC) > 0.72] and was closely associated with clinicopathological characteristics of HCC patients. IPA suggested that the 8 genes were enriched in Cancer and Immunological disease related pathways. IPS and TIDE score indicated that the genes in low-risk group could cause an immune response, and patients in the low-risk group may be more sensitive to the immune checkpoint blockade (ICB) therapy. CONCLUSION: The risk score constructed by the 8 genes could not only predict the clinical outcome but also distinguish the cohort of ICB therapy in HCC, which exerted a vital value in treatment and prognosis of HCC.

The Effect of Long-Term Traditional Chinese Medicine Treatment on Survival Time of Colorectal Cancer Based on propensity Score Matching: A Retrospective Cohort Study.

OBJECTIVE: To explore the effect of long-term traditional Chinese medicine (TCM) treatment on survival time of colorectal cancer (hereinafter referred to as CRC). METHODS: Our clinical study included patients who were diagnosed with CRC clinically or pathologically. Patients were divided into TCM treatment group and control group according to whether the modified Anti-cancer Decoction II Formula was applied for more than six months. Propensity score matching (hereinafter referred to as PSM) was used to further balance the covariates between groups. One-year to six-year progression-free survival rates of the two groups and the median progression-free survival (mPFS), median overall survival (mOS) of the two groups before and after PSM were calculated respectively. Furthermore, 15 factors that may affect the mPFS in CRC were included in COX multivariate regression analysis to explore the prognostic factors related to CRC as well as to analyze the risk ratio of different subgroups. RESULTS: A total of 529 CRC patients were included in our study, 285 patients were in the TCM treatment group and 244 patients were in the control group. Before PSM, the mPFS and mOS in the TCM treatment group were 68 months and 75 months respectively, while mPFS and mOS in the control group were 40 months and 65 months respectively. After PSM, mPFS and mOS in the TCM treatment group were both 75 months, while mPFS and mOS in the control group were 28 months and 44 months respectively. One-year to six-year progression-free survival rates were 94.0%, 76.1%, 64.7%, 57.9%, 52.0%, 44.1% respectively in the TCM treatment group, and 78.6%, 61.4%, 51.7%, 40.8%, 33.0%, 29.1% respectively in the control group (p < 0.01). COX multivariate regression analysis indicated that surgery, chemotherapy and taking Chinese herbal decoction were protective factors for CRC recurrence and metastasis, while combining with intestinal obstruction, drinking history and family history were independent factors for CRC recurrence and metastasis. The results of subgroup analysis showed that the decoction of TCM could reduce the risk of recurrence and metastasis in each subgroup (p < 0.01). COX multivariate regression analysis indicated that surgery, chemotherapy and taking Chinese herbal decoction were protective factors for CRC recurrence and metastasis, while combining with intestinal obstruction, drinking history and family history were independent factors for CRC recurrence and metastasis. The results of subgroup analysis showed that the decoction of TCM could reduce the risk of recurrence and metastasis in each subgroup (. CONCLUSIONS: Long-term TCM treatment by the usage of the modified Anti-cancer Decoction II Formula not only has a positive effect on the survival time of CRC patients, but also helps reduce the risk of recurrence and metastasis of CRC, which can be flexibly applied in the whole process of CRC treatment.

Construction and application of a lung cancer stem cell model: antitumor drug screening and molecular mechanism of the inhibitory effects of sanguinarine.

Lung cancer is a neoplasm with a 5-year survival rate of less than 15 % and a leading cause of death worldwide, despite recent progress in treatment and diagnostic methods. Lung cancer stem-like cells (CSCs) are pivotal in lung cancer metastasis and drug resistance. This study aimed to develop lung CSCs that stably express stem cell properties through transfection to further screen traditional Chinese herbal compounds. Lung adenocarcinoma stem cells, which include various phenotypic subgroups, are normally characterized by high expression levels of pluripotent stem cell genes, particularly Nanog and OCT4. Plasmids containing Nanog and OCT4 were constructed and transfected into cells, and lung CSCs were identified not only in vitro using RT-PCR, Western blotting, plate cloning, sphere formation, drug resistance, and transwell migration but also in vivo using a nude mouse tumorigenicity assay. Subsequently, sanguinarine, which is derived from the whole leaves of the traditional Chinese medicine celandine, was identified through the high-throughput screening of a small-molecule compound library. Investigation of the molecular mechanisms of the effects of sanguinarine revealed that it significantly inhibited lung CSC proliferation, invasion, and apoptosis, possibly via downregulation of the Wnt/ß-catenin signaling pathway. Our results indicate that lung CSCs established by gene transfection may provide a stable and effective method of constructing CSCs to effectively screen potential antitumor drugs. Furthermore, these results suggest that sanguinarine may be a natural antitumor compound that targets lung CSCs, laying a foundation for further clinical study.