An Unsupervised Deep Learning-Based Model Using Multiomics Data to Predict Prognosis of Patients with Stomach Adenocarcinoma.

Methods: Patients (363 in total) with stomach adenocarcinoma from The Cancer Genome Atlas (TCGA) cohort were included. An autoencoder was constructed to integrate the RNA sequencing, miRNA sequencing, and methylation data. The features of the bottleneck layer were used to perform the k-means clustering algorithm to obtain different subgroups for evaluating the prognosis-related risk of stomach adenocarcinoma. The model's robustness was verified using a 10-fold cross-validation (CV). Survival was analyzed by the Kaplan-Meier method. Univariate and multivariate Cox regression was used to estimate hazard risk. The model was validated in three independent cohorts with different endpoints. Results: The patients were divided into low-risk and high-risk groups according to the k-means clustering algorithm. The high-risk group had a significantly higher risk of poor survival (log-rank P value = 2.80e - 06; adjusted hazard ratio = 2.386, 95% confidence interval: 1.607~3.543), a concordance index (C-index) of 0.714, and a Brier score of 0.184. The model performed well both in the 10-fold CV procedure and three independent cohorts from the Gene Expression Omnibus (GEO) repository. Conclusions: A robust and generalizable model based on the autoencoder was proposed to integrate multiomics data and predict the prognosis of patients with stomach adenocarcinoma. The model demonstrates better performance than two alternative approaches on prognosis prediction. The results might provide the grounds for further exploring the potential biomarkers to predict the prognosis of patients with stomach adenocarcinoma.

Toxicokinetics and systematic responses of differently sized indium tin oxide (ITO) particles in mice via oropharyngeal aspiration exposure.

Indium tin oxide (ITO) is an important semiconductor material, because of increasing commercial products consumption and potentially exposed workers worldwide. So, urgently we need to assess and manage potential health risks of ITO. Although the Occupational Exposure Limit (OEL) has been established for ITO exposure, there is still a lack of distinguishing the risks of exposure to particles of different sizes. Therefore, obtaining toxicological data of small-sized particles will help to improve its risk assessment data. Important questions raised in quantitative risk assessments for ITO particles are whether biodistribution of ITO particles is affected by particle size and to what extent systematic adverse responses is subsequently initiated. In order to determine whether this toxicological paradigm for size is relevant in ITO toxic effect, we performed comparative studies on the toxicokinetics and sub-acute toxicity test of ITO in mice. The results indicate both sized-ITO resided in the lung tissue and slowly excreted from the mice, and the smaller size of ITO being cleared more slowly. Only a little ITO was transferred to other organs, especially with higher blood flow. Two type of ITO which deposit in the lung mainly impacts respiratory system and may injure liver or kidney. After sub-acute exposure to ITO, inflammation featured by neutrophils infiltration and fibrosis with both dose and size effects have been observed. Our findings revealed toxicokinetics and dose-dependent pulmonary toxicity in mice via oropharyngeal aspiration exposure, also replenish in vivo risk assessment of ITO. Collectively, these data indicate that under the current OEL, there are potential toxic effects after exposure to the ITO particles. The observed size-dependent biodistribution patterns and toxic effect might be important for approaching the hazard potential of small-sized ITO in an occupational environment.

The Toxicity Of Metallic Nanoparticles On Liver: The Subcellular Damages, Mechanisms, And Outcomes.

Metallic nanoparticles (MNPs) are new engineering materials with broad prospects for biomedical applications; thus, their biosafety has drawn great concern. The liver is the main detoxification organ of vertebrates. However, many issues concerning the interactions between MNPs and biological systems (cells and tissues) are unclear, particularly the toxic effects of MNPs on hepatocytes and other liver cells. Numerous researchers have shown that some MNPs can induce decreased cell survival rate, production of reactive oxygen species (ROS), mitochondrial damage, DNA strand breaks, and even autophagy, pyroptosis, apoptosis, or other forms of cell death. Our review focuses on the recent researches on the liver toxicity of MNPs and its mechanisms at cellular and subcellular levels to provide a scientific basis for the subsequent hepatotoxicity studies of MNPs.