The Development of LLMs for Embodied Navigation

In recent years, the rapid advancement of Large Language Models (LLMs) such as the Generative Pre-trained Transformer (GPT) has attracted increasing attention due to their potential in a variety of practical applications. The application of LLMs with Embodied Intelligence has emerged as a significant area of focus. Among the myriad applications of LLMs, navigation tasks are particularly noteworthy because they demand a deep understanding of the environment and quick, accurate decision-making. LLMs can augment embodied intelligence systems with sophisticated environmental perception and decision-making support, leveraging their robust language and image-processing capabilities. This article offers an exhaustive summary of the symbiosis between LLMs and embodied intelligence with a focus on navigation. It reviews state-of-the-art models, research methodologies, and assesses the advantages and disadvantages of existing embodied navigation models and datasets. Finally, the article elucidates the role of LLMs in embodied intelligence, based on current research, and forecasts future directions in the field. A comprehensive list of studies in this survey is available at https://github.com/Rongtao-Xu/Awesome-LLM-E

Regulation of Wnt Singaling Pathway by Poly (ADP-Ribose) Glycohydrolase (PARG) Silencing Suppresses Lung Cancer in Mice Induced by Benzo(a)pyrene Inhalation Exposure

Benzo(a)pyrene (BaP) is a polycyclic aromatic hydrocarbon that specifically causes cancer and is widely distributed in the environment. Poly (ADP-ribosylation), as a key post-translational modification in BaP-induced carcinogenesis, is mainly catalyzed by poly (ADP-ribose) glycohydrolase (PARG) in eukaryotic organisms. Previously, it is found that PARG silencing can counteract BaP-induced carcinogenesis in vitro, but the mechanism remained unclear. In this study, we further examined this process in vivo by using heterozygous PARG knockout mice (PARG+/−). Wild-type and PARG+/− mice were individually treated with 0 or 10 μg/m3 BaP for 90 or 180 days by dynamic inhalation exposure. Pathological analysis of lung tissues showed that, with extended exposure time, carcinogenesis and injury in the lungs of WT mice was progressively worse; however, the injury was minimal and carcinogenesis was not detected in the lungs of PARG+/− mice. These results indicate that PARG gene silencing protects mice against lung cancer induced by BaP inhalation exposure. Furthermore, as the exposure time was extended, the protein phosphorylation level was down-regulated in WT mice, but up-regulated in PARG+/− mice. The relative expression of Wnt2b and Wnt5b mRNA in WT mice were significantly higher than those in the control group, but there was no significant difference in PARG+/− mice. Meanwhile, the relative expression of Wnt2b and Wnt5b proteins, as assessed by immunohistochemistry and Western blot analysis, was significantly up-regulated by BaP in WT mice; while in PARG+/− mice it was not statistically affected. Our work provides initial evidence that PARG silencing suppresses BaP induced lung cancer and stabilizes the expression of Wnt ligands, PARG gene and Wnt ligands may provide new options for the diagnosis and treatment of lung cancer

Separate pathways for biliary excretion of sulfobromophthalein and bilirubin in rats

Digitized by Kansas Correctional Industrie

An optimal design of cluster spacing intervals for staged fracturing in horizontal shale gas wells based on the optimal SRVs

When horizontal well staged cluster fracturing is applied in shale gas reservoirs, the cluster spacing is essential to fracturing performance. If the cluster spacing is too small, the stimulated area between major fractures will be overlapped, and the efficiency of fracturing stimulation will be decreased. If the cluster spacing is too large, the area between major fractures cannot be stimulated completely and reservoir recovery extent will be adversely impacted. At present, cluster spacing design is mainly based on the static model with the potential reservoir stimulation area as the target, and there is no cluster spacing design method in accordance with the actual fracturing process and targets dynamic stimulated reservoir volume (SRV). In this paper, a dynamic SRV calculation model for cluster fracture propagation was established by analyzing the coupling mechanisms among fracture propagation, fracturing fluid loss and stress. Then, the cluster spacing was optimized to reach the target of the optimal SRVs. This model was applied for validation on site in the Jiaoshiba shale gasfield in the Fuling area of the Sichuan Basin. The key geological engineering parameters influencing the optimal cluster spacing intervals were analyzed. The reference charts for the optimal cluster spacing design were prepared based on the geological characteristics of south and north blocks in the Jiaoshiba shale gasfield. It is concluded that the cluster spacing optimal design method proposed in this paper is of great significance in overcoming the blindness in current cluster perforation design and guiding the optimal design of volume fracturing in shale gas reservoirs. Keywords: Shale gas, Horizontal well, Staged fracturing, Cluster spacing, Reservoir, Stimulated reservoir volume (SRV), Mathematical model, Optimal method, Sichuan basin, Jiaoshiba shale gasfiel

The effects of low-dose Nepsilon-(carboxymethyl)lysine (CML) and Nepsilon-(carboxyethyl)lysine (CEL), two main glycation free adducts considered as potential uremic toxins, on endothelial progenitor cell function

<p>Abstract</p> <p>Background</p> <p>Patients with chronic kidney disease (CKD) are at high risk of cardiovascular disease (CVD). Endothelial progenitor cell (EPCs) dysfunction plays a key role in this pathogenesis. Uremic retention toxins have been reported to be in associated with EPC dysfunction. Advanced glycation end-products (AGEs) free adducts, including Nepsilon-(carboxymethyl)lysine (CML) and Nepsilon-(carboxyethyl)lysine (CEL), are formed by physiological proteolysis of AGEs and released into plasma for urinary excretion. They are retained in CKD patients and are considered to be potential uremic toxins. Though AGEs have been demonstrated to impair EPC function in various ways, the effect of AGE free adducts on EPC function has not been studied. Thus, we examined the role of CML and CEL in the regulation of growth-factor-dependent function in cultured human EPCs and the mechanisms by which they may affect EPC function.</p> <p>Methods</p> <p>Late outgrowth EPCs were incubated with different concentrations of CML or CEL for up to 72 hours. Cell proliferation was determined using WST-1 and BrdU assays. Cell apoptosis was tested with annexin V staining. Migration and tube formation assays were used to evaluate EPC function.</p> <p>Results</p> <p>Though CML and CEL were determined to have anti-proliferative effects on EPCs, cells treated with concentrations of CML and CEL in the range found in CKD patients had no observable impairment on migration or tube formation. CML and CEL did not induce EPC apoptosis. The reduced growth response was accompanied by significantly less phosphorylation of mitogen-activated protein kinases (MAPKs).</p> <p>Conclusions</p> <p>Our study revealed that CML and CEL at uremic concentrations have low biological toxicity when separately tested. The biologic effects of AGE free adducts on the cardiovascular system merit further study.</p

ERp29 controls invasion and metastasis of gastric carcinoma by inhibition of epithelial-mesenchymal transition via PI3K/Aktsignaling pathway

Abstract Background Gastric cancer (GC) accounts for the fourth most occurring malignancy and the third major cause of cancer death. Identifying novel molecular signaling pathways participating in gastric tumorigenesis and progression is pivotal for rational design of targeted therapies to improve advanced GC outcome. Recently, the endoplasmic reticulum (ER) protein 29 (ERp29) has been shown to inversely associate with primary tumor development and function as a tumor suppressor in breast cancer. However, the role of ERp29 in GC patients’ prognosis and its function in GC progression is unknown. Methods Clinical importance of ERp29 in the prognosis of GC patients was assessed by examining its expression in 148 GC tumor samples and correlation with clinicopathological characteristics and survival of the patients. The function and underlying mechanisms of ERp29 in GC growth, invasion and metastasis were explored both in vitro and in vivo. Results Downregulation of ERp29 was commonly found in GC tissues and highly correlated with more aggressive phenotypes and poorer prognosis. Functional assays demonstrated that knockdown of ERp29 increased GC cell migration and invasion and promoted metastasis. Conversely, ectopic overexpression of ERp29 produced opposite effects. Mechanistic studies revealed that loss of ERp29 induced an epithelial-to-mesenchymal transition (EMT) in the GC cells through activation of PI3K/Akt pathway signaling. Conclusion These findings suggest that downregulation of ERp29 is probably one of the key molecular mechanisms responsible for the development and progression of GC

Oxidative carbonylation of methanol to dimethyl carbonate over Cu/AC catalysts prepared by microwave irradiation: Effect of La and Zr promoters

384-391Copper catalysts with a loading of 16.7 wt%, supported on activated carbon (AC) with the addtion of La or Zr, have been prepared by microwave heating methods and tested for the oxidative carbonylation of methanol to dimethyl carbonate (DMC). X-ray diffraction (XRD, temperature-programmed reduction (TPR), XPS), and scanning electron micrographs (SEM) have been carried out to examine the bulk and surface properties of the carbon-supported copper catalysts. It is found that the addition of La or Zr promoters favours the auto-reduction of copper precursors to metallic copper and leads to smaller and even nanoparticle-size Cu distributed on the surface of the carbon support which exhibt promising space-time yield of DMC of 480.2 and 585.2 mg·g-1·h-1, respectively. Meanwhile, the selectivity of DMC reached 95.7 and 90.3% and higher conversion of CH3OH of approximately4.0 and 4.7% have been achieved surprisingly, even after five sets of relevant experiments. The improved catalytic performance of Cu/AC with the addition of La or Zr in the DMC synthesis is due to the presence of more metallic copper, more evenly distributed over the surface of the carbon support, with a significantly reduced particle size as compared with no La or Zr promoter

The Development of a Prediction Model Based on Random Survival Forest for the Postoperative Prognosis of Pancreatic Cancer: A SEER-Based Study

Accurate prediction for the prognosis of patients with pancreatic cancer (PC) is a emerge task nowadays. We aimed to develop survival models for postoperative PC patients, based on a novel algorithm, random survival forest (RSF), traditional Cox regression and neural networks (Deepsurv), using the Surveillance, Epidemiology, and End Results Program (SEER) database. A total of 3988 patients were included in this study. Eight clinicopathological features were selected using least absolute shrinkage and selection operator (LASSO) regression analysis and were utilized to develop the RSF model. The model was evaluated based on three dimensions: discrimination, calibration, and clinical benefit. It found that the RSF model predicted the cancer-specific survival (CSS) of the postoperative PC patients with a c-index of 0.723, which was higher than the models built by Cox regression (0.670) and Deepsurv (0.700). The Brier scores at 1, 3, and 5 years (0.188, 0.177, and 0.131) of the RSF model demonstrated the model&rsquo;s favorable calibration and the decision curve analysis illustrated the model&rsquo;s value of clinical implement. Moreover, the roles of the key variables were visualized in the Shapley Additive Explanations plotting. Lastly, the prediction model demonstrates value in risk stratification and individual prognosis. In this study, a high-performance prediction model for PC postoperative prognosis was developed, based on RSF The model presented significant strengths in the risk stratification and individual prognosis prediction