Predictive metabolomic signatures for safety assessment of three plastic nanoparticles using intestinal organoids.

Nanoplastic particles are pervasive environmental contaminants with potential health risks, while mouse intestinal organoids provide accurate in vitro models for studying these interactions. Metabolomics, especially through LC-MS, enables detailed cellular response studies, and there's a novel interest in comparing metabolic changes across nanoparticle species using gut organoids. This study used a mouse intestinal organoid combined with cell model to explore the differences in metabolites and toxicity mechanisms induced by exposure to three nanoplastics (PS, PTFE, and PMMA). The results showed that PS, PTFE, and PMMA exposure reduced mitochondrial membrane potential, intracellular ROS accumulation and oxidative stress, and inhibited the AKT/mTOR signaling pathway. Non-targeted metabolomics results confirmed that three types of nanoplastic particles regulate cellular status by regulating fatty acid metabolism, nucleotide metabolism, necroptosis and autophagy pathways. More importantly, these representative metabolites were further validated in model groups after mouse intestinal organoids and HCT116 cells were exposed to the respective NPs, indicating that organoid metabolomics results can be used to effectively predict toxicity. Untargeted metabolomics is sensitive enough to detect subtle metabolomic changes when functional cellular analysis shows no significant differences. Overall, our study reveals the underlying metabolic mechanism of NPs-induced intestinal organoid toxicity and provides new insights into the possible adverse consequences of NPs.

Safety assessment of Mpp75Aa1.1, a new ETX_MTX2 protein from Brevibacillus laterosporus that controls western corn rootworm.

The recently discovered insecticidal protein Mpp75Aa1.1 from Brevibacillus laterosporus is a member of the ETX_MTX family of beta-pore forming proteins (ß-PFPs) expressed in genetically modified (GM) maize to control western corn rootworm (WCR; Diabrotica virgifera virgifera LeConte). In this manuscript, bioinformatic analysis establishes that although Mpp75Aa1.1 shares varying degrees of similarity to members of the ETX_MTX2 protein family, it is unlikely to have any allergenic, toxic, or otherwise adverse biological effects. The safety of Mpp75Aa1.1 is further supported by a weight of evidence approach including evaluation of the history of safe use (HOSU) of ETX_MTX2 proteins and Breviballus laterosporus. Comparisons between purified Mpp75Aa1.1 protein and a poly-histidine-tagged (His-tagged) variant of the Mpp75Aa1.1 protein demonstrate that both forms of the protein are heat labile at temperatures at or above 55°C, degraded by gastrointestinal proteases within 0.5 min, and have no adverse effects in acute mouse oral toxicity studies at a dose level of 1920 or 2120 mg/kg body weight. These results support the use of His-tagged proteins as suitable surrogates for assessing the safety of their non-tagged parent proteins. Taken together, we report that Mpp75Aa1.1 is the first ETX-MTX2 insecticidal protein from B. laterosporus and displays a similar safety profile as typical Cry proteins from Bacillus thuringiensis.

Prediction of lymph node metastatic status in superficial esophageal squamous cell carcinoma using an assessment model combining clinical characteristics and pathologic results: A retrospective cohort study.

BACKGROUND: It is important to identify the risk of lymph node metastasis (LNM) in patients with superficial esophageal squamous carcinoma (SESC) who have received endoscopic resection (ER). We aimed to develop a risk-predicting model for metastasis of SESC to lymph nodes using clinicopathological features and pathological results. METHODS: Clinical data on 539 consecutive patients who underwent esophagectomy for SESC in our hospital were collected. Their post-surgical pathological results were assessed and analyzed. Multivariate logistic regression was used to identify all independent risk factors associated with LNM that then were incorporated into the prediction model. RESULTS: LNM was identified in 53 of 366 patients and 30 of 173 patients by positive histopathological results in the training and validation cohorts. The risk factors associated with LNM were large tumor size, poor tumor grade, deep invasion, and presence of angiolymphatic invasion. The model achieved good discriminatory ability of 0.80 (95%CI, 0.74-0.86) and 0.81 (95%CI, 0.75-0.86) in predicting LNM in the training and validation cohorts respectively. A LNM-predicting nomogram was formed with an area under curve of 0.80 (95% CI, 0.74-0.86), which had well-fitted calibration curves. CONCLUSIONS: A prediction model was constructed to generates 3 categories for estimated LNM risk in SESC patients. It provides a practical way of estimation of LNM risk in SESC patients who had received ER.