6:2 Cl-PFESA, a proposed safe alternative for PFOS, diminishes the gemcitabine effectiveness in the treatment of pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC)/pancreatic cancer, is a highly aggressive malignancy with poor prognosis. Gemcitabine-based chemotherapy remains the cornerstone of PDAC treatment. Nonetheless, the development of resistance to gemcitabine among patients is a major factor contributing to unfavorable prognostic outcomes. The resistance exhibited by tumors is modulated by a constellation of factors such as genetic mutations, tumor microenvironment transforms, environmental contaminants exposure. Currently, comprehension of the relationship between environmental pollutants and tumor drug resistance remains inadequate. Our study found that PFOS/6:2 Cl-PFESA exposure increases resistance to gemcitabine in PDAC. Subsequent in vivo trials confirmed that exposure to PFOS/6:2 Cl-PFESA reduces gemcitabine's efficacy in suppressing PDAC, with the inhibition rate decreasing from 79.5 % to 56.7 %/38.7 %, respectively. Integrative multi-omics sequencing and molecular biology analyses have identified the upregulation of ribonucleotide reductase catalytic subunit M1 (RRM1) as a critical factor in gemcitabine resistance. Subsequent research has demonstrated that exposure to PFOS and 6:2 Cl-PFESA results in the upregulation of the RRM1 pathway, consequently enhancing chemotherapy resistance. Remarkably, the influence exerted by 6:2 Cl-PFESA exceeds that of PFOS. Despite 6:2 Cl-PFESA being regarded as a safer substitute for PFOS, its pronounced effect on chemotherapeutic resistance in PDAC necessitates a thorough evaluation of its potential risks related to gastrointestinal toxicity.

SERPINE2 promotes liver cancer metastasis by inhibiting c-Cbl-mediated EGFR ubiquitination and degradation.

BACKGROUND: Liver cancer is a malignancy with high morbidity and mortality rates. Serpin family E member 2 (SERPINE2) has been reported to play a key role in the metastasis of many tumors. In this study, we aimed to investigate the potential mechanism of SERPINE2 in liver cancer metastasis. METHODS: The Cancer Genome Atlas database (TCGA), including DNA methylation and transcriptome sequencing data, was utilized to identify the crucial oncogene associated with DNA methylation and cancer progression in liver cancer. Data from the TCGA and RNA sequencing for 94 pairs of liver cancer tissues were used to explore the correlation between SERPINE2 expression and clinical parameters of patients. DNA methylation sequencing was used to detect the DNA methylation levels in liver cancer tissues and cells. RNA sequencing, cytokine assays, immunoprecipitation (IP) and mass spectrometry (MS) assays, protein stability assays, and ubiquitination assays were performed to explore the regulatory mechanism of SERPINE2 in liver cancer metastasis. Patient-derived xenografts and tumor organoid models were established to determine the role of SERPINE2 in the treatment of liver cancer using sorafenib. RESULTS: Based on the public database screening, SERPINE2 was identified as a tumor promoter regulated by DNA methylation. SERPINE2 expression was significantly higher in liver cancer tissues and was associated with the dismal prognosis in patients with liver cancer. SERPINE2 promoted liver cancer metastasis by enhancing cell pseudopodia formation, cell adhesion, cancer-associated fibroblast activation, extracellular matrix remodeling, and angiogenesis. IP/MS assays confirmed that SERPINE2 activated epidermal growth factor receptor (EGFR) and its downstream signaling pathways by interacting with EGFR. Mechanistically, SERPINE2 inhibited EGFR ubiquitination and maintained its protein stability by competing with the E3 ubiquitin ligase, c-Cbl. Additionally, EGFR was activated in liver cancer cells after sorafenib treatment, and SERPINE2 knockdown-induced EGFR downregulation significantly enhanced the therapeutic efficacy of sorafenib against liver cancer. Furthermore, we found that SERPINE2 knockdown also had a sensitizing effect on lenvatinib treatment. CONCLUSIONS: SERPINE2 promoted liver cancer metastasis by preventing EGFR degradation via c-Cbl-mediated ubiquitination, suggesting that inhibition of the SERPINE2-EGFR axis may be a potential target for liver cancer treatment.

Negentropy Spectrum Decomposition and Its Application in Compound Fault Diagnosis of Rolling Bearing.

The rolling bearings often suffer from compound fault in practice. Compared with single fault, compound fault contains multiple fault features that are coupled together and make it difficult to detect and extract all fault features by traditional methods such as Hilbert envelope demodulation, wavelet transform and empirical node decomposition (EMD). In order to realize the compound fault diagnosis of rolling bearings and improve the diagnostic accuracy, we developed negentropy spectrum decomposition (NSD), which is based on fast empirical wavelet transform (FEWT) and spectral negentropy, with cyclic extraction as the extraction method. The infogram is constructed by FEWT combined with spectral negentropy to select the best band center and bandwidth for band-pass filtering. The filtered signal is used as a new measured signal, and the fast empirical wavelet transform combined with spectral negentropy is used to filter the new measured signal again. This operation is repeated to achieve cyclic extraction, until the signal no longer contains obvious fault features. After obtaining the envelope of all extracted components, compound fault diagnosis of rolling bearings can be realized. The analysis of the simulation signal and the experimental signal shows that the method can realize the compound fault diagnosis of rolling bearings, which verifies the feasibility and effectiveness of the method. The method proposed in this paper can detect and extract all the fault features of compound fault completely, and it is more reliable for the diagnosis of compound fault. Therefore, the method has practical significance in rolling bearing compound fault diagnosis.

Application of a Predictive Growth Model of Pseudomonas spp. for Estimating Shelf Life of Fresh Agaricus bisporus.

For prediction of the shelf life of the mushroom Agaricus bisporus, the growth curve of the main spoilage microorganisms was studied under isothermal conditions at 2 to 22°C with a modified Gompertz model. The effect of temperature on the growth parameters for the main spoilage microorganisms was quantified and modeled using the square root model. Pseudomonas spp. were the main microorganisms causing A. bisporus decay, and the modified Gompertz model was useful for modelling the growth curve of Pseudomonas spp. All the bias factors values of the model were close to 1. By combining the modified Gompertz model with the square root model, a prediction model to estimate the shelf life of A. bisporus as a function of storage temperature was developed. The model was validated for A. bisporus stored at 6, 12, and 18°C, and adequate agreement was found between the experimental and predicted data.