Basic research for identification and classification of organophosphorus pesticides in water based on ultraviolet-visible spectroscopy information.

In this study, the goal was to develop a method for detecting and classifying organophosphorus pesticides (OPPs) in bodies of water. Sixty-five samples with different concentrations were prepared for each of the organophosphorus pesticides, namely chlorpyrifos, acephate, parathion-methyl, trichlorphon, dichlorvos, profenofos, malathion, dimethoate, fenthion, and phoxim, respectively. Firstly, the spectral data of all the samples was obtained using a UV-visible spectrometer. Secondly, five preprocessing methods, six manifold learning methods, and five machine learning algorithms were utilized to build detection models for identifying OPPs in water bodies. The findings indicate that the accuracy of machine learning models trained on data preprocessed using convolutional smoothing + first-order derivatives (SG + FD) outperforms that of models trained on data preprocessed using other methods. The backpropagation neural network (BPNN) model exhibited the highest accuracy rate at 99.95%, followed by the support vector machine (SVM) and convolutional neural network (CNN) models, both at 99.92%. The extreme learning machine (ELM) and K-nearest neighbors (KNN) models demonstrated accuracy rates of 99.84% and 99.81%, respectively. Following the application of a manifold learning algorithm to the full-wavelength data set for the purpose of dimensionality reduction, the data was then visualized in the first three dimensions. The results demonstrate that the t-distributed domain embedding (t-SNE) algorithm is superior, exhibiting dense clustering of similar clusters and clear classification of dissimilar ones. SG + FD-t-SNE-SVM ranks highest among the feature extraction models in terms of performance. The feature extraction dimension was set to 4, and the average classification accuracy was 99.98%, which slightly improved the prediction performance over the full-wavelength model. As shown in this study, the ultraviolet-visible (UV-visible) spectroscopy system combined with the t-SNE and SVM algorithms can effectively identify and classify OPPs in waterbodies.

Hydrogen gas promotes apoptosis of lung adenocarcinoma A549 cells through X-linked inhibitor of apoptosis and baculoviral inhibitor of apoptosis protein repeat-containing 3.

Objective: Lung cancer is currently the cancer with the highest incidence and death toll worldwide. Hydrogen gas has been found to affect a variety of diseases; however, the effect of hydrogen gas on patients with lung cancer has not been reported. Therefore, we determined the effect of hydrogen gas on apoptosis of lung adenocarcinoma in vivo and in vitro. Materials and Methods: A549 cells in the logarithmic phase were treated with 20%, 40%, or 60% hydrogen gas. Cell apoptosis was evaluated by flow cytometry. The A549 cell suspension was inoculated into 15 nude mice. The mice were randomly divided into control, hydrogenation (inhalation of 60% hydrogen gas), and cisplatin groups (intraperitoneal injection of cisplatin [4 mg/kg]). After 3 weeks, the tumor tissue was removed and measured. We identified differentially expressed genes by transcriptional profiling. The levels of X-linked inhibitor of apoptosis (XIAP), baculoviral inhibitor of apoptosis protein repeat-containing 3 (BIRC3), and BCL2-associated X and apoptosis regulator (BAX) protein expression were detected by Western blotting and immunohistochemistry. Results: Compared with the control group, the apoptosis rates in the 20%, 40%, and 60% hydrogen gas groups were significantly increased (P < 0.01). The levels of XIAP and BIRC3 protein expression were clearly decreased in the hydrogen gas group compared to the control group. Moreover, cisplatin and hydrogen gas reduced the tumor volume in nude mice (P < 0.01). Transcriptome sequencing showed that XIAP, BIRC2, BIRC3, BAX, PIK3CD, and ATM were related to apoptosis. Hydrogen gas further decreased the levels of XIAP and BIRC3 expression than in nude mice (P < 0.01). Conclusion: Hydrogen gas promoted apoptosis of A549 cells by reducing the expression of XIAP and BIRC3 protein.

Suppression of autophagy facilitates hydrogen gas-mediated lung cancer cell apoptosis.

Our previous study found that hydrogen gas (H2) could efficiently inhibit lung cancer progression; however, the underlying mechanisms still remains to be elucidated. The present study aimed to explore the roles of H2 in lung cancer cell autophagy, and reveal the effects of autophagy on H2-mediated lung cancer cell apoptosis and the underlying mechanisms. The expression levels of proteins associated with cell apoptosis and autophagy were detected using western blot analysis. Cell autophagy was inhibited by 3-methyladenine treatment or Beclin1 downregulation, while rapamycin was used to induce autophagy. Cell growth and apoptosis were detected using the Cell Counting Kit-8 and flow cytometry assays, respectively. The results demonstrated that cell apoptosis and autophagy were significantly enhanced in the A549 and H1975 lung cancer cell lines treated with H2. However, autophagy enhancement weakened H2 roles in promoting cell apoptosis and vice versa. In addition, it was found that H2 treatment induced marked decreases in the protein expression levels of phosphorylated STAT3 and Bcl2, and overexpression of STAT3 abolished H2 roles in promoting cell apoptosis and autophagy. Overall, the present study revealed that H2 can promote lung cancer cell apoptosis and autophagy via inhibiting the activation of STAT3/Bcl2 signaling and suppression of autophagy can enhance H2 roles in promoting lung cancer cell apoptosis.

Hydrogen gas represses the progression of lung cancer via down-regulating CD47.

Hydrogen gas (H2) has been identified to play an anti-tumor role in several kinds of cancers, but the molecular mechanisms remain largely unknown. In our previous study, our project group found that H2 could decrease the expression of CD47 in lung cancer A549 cells via the next-generation sequencing, indicating that CD47 might be involved in H2-mediated lung cancer repression. Therefore, the present study aimed to explore the effects of CD47 on H2-induced lung cancer repression. Western blotting and real-time PCR (RT-PCR) assays were used to detect the levels of proteins and mRNAs, respectively. Cell proliferation, invasion, migration and apoptosis were detected by using the cell counting kit-8 (CCK-8), Transwell chambers, wound healing and flow cytometry assays, respectively. The results showed that H2 treatment caused decreases in the expression levels of CD47 and cell division control protein 42 (CDC42) in a dose-dependent manner. Up-regulation of CD47 abolished H2 roles in promoting lung cancer cell apoptosis and repressing cell growth, invasion and migration in both A549 and H1975 cell lines. However, knockdown of CD47 enhanced H2 role in lung cancer inhibition. Moreover, we also observed that H2 treatment induced obvious inhibitions in the expression levels of CDC42 and CD47 in mice tumor tissues, as well as reinforced macrophage-mediated phagocytosis in A549 and H1975 cells. In conclusion, the current study reveals that H2 inhibits the progression of lung cancer via down-regulating CD47, which might be a potent method for lung cancer treatment.

PYCR1 promotes the progression of non-small-cell lung cancer under the negative regulation of miR-488.

PYCR1 is over-expressed in non-small-cell lung cancer (NSCLC) and its high expression accelerates the progression of NSCLC. However, the underlying mechanisms of PYCR1 in NSCLC progression remain poorly understood. Our study determined the mechanisms of PYCR1 in promotion of the occurrence and development of NSCLC in vitro and in vivo. Firstly, the expression patterns of PYCR1 in NSCLC tissues and cells were determined by RT-PCR, western blot and immunohistochemistry. Then, the effects of PYCR1 on cell proliferation and apoptosis were evaluated by CCK-8 and flow cytomery assays. Finally, we explored the up-regulatory microRNAs (miRs) of PYCR1 and determined if MAPK pathway involved in this process. PYCR1 expression was elevated in NSCLC tissue samples and cells, and the high expression of PYCR1 closely associated with patients' advanced clinical process and poor outcome. Up-regulation of PYCR1 significantly increased the expression of p38 and promoted its nuclear accumulation. Besides, PYCR1 expression was negatively regulated by miR-488, and up-regulation of miR-488 significantly inhibited cell proliferation and tumorigenesis and increased cell apoptosis, and decreased p38 expression and its nuclear accumulation, whereas up-regulation of PYCR1 rescued these results induced by miR-488 over-expression. Collectively, these data suggest the mechanism of PYCR1 in promotion of NSCLC progression. PYCR1 is negatively regulated by miR-488 and then promotes the occurrence and development of NSCLC and activates p38 MAPK pathway.