Radical-Chain Hydrosilylation of Alkenes Enabled by Triplet Energy Transfer.

Development of mild, robust and metal-free catalytic approach for the hydrosilylation of alkenes is critical to the advancement of modern organosilicon chemistry given their powerful capacity in the construction of various C-Si bonds. Herein, we wish to disclose a visible light-triggered organophotocatalytic strategy, which proceeds via a triplet energy transfer (EnT)-enabled radical chain pathway. Notably, this redox-neutral protocol is capable of accommodating a broad spectrum of electron-deficient and -rich alkenes with excellent functional group compatibility. Electron-deficient alkenes are more reactive and the reaction could be finished within a couple of minutes even in PBS solution with extremely low concentration, which suggests its click-like potential in organic synthesis. The preparative power of the transformations has been further highlighted in a number of complex settings, including the late-stage functionalization and scale-up experiments. Furthermore, although only highly reactive (TMS)3SiH is suitable hydrosilane substrate, our studies revealed the great reactivity and versatility of (TMS)3Si- group in diverse C-Si and Si-Si bond cleavage-based transformations, enabling the rapid introduction of diverse functional groups and the facile construction of valuable quaternary silicon architectures.

Survival prediction in patients with colon adenocarcinoma via multi-omics data integration using a deep learning algorithm.

This study proposed a deep learning (DL) algorithm to predict survival in patients with colon adenocarcinoma (COAD) based on multi-omics integration. The survival-sensitive model was constructed using an autoencoder for DL implementation based on The Cancer Genome Atlas (TCGA) data of patients with COAD. The autoencoder framework was compared to PCA, NMF, t-SNE, and univariable Cox-PH model for identifying survival-related features. The prognostic robustness of the inferred survival risk groups was validated using three independent confirmation cohorts. Differential expression analysis, Pearson's correlation analysis, construction of miRNA-target gene network, and function enrichment analysis were performed. Two risk groups with significant survival differences were identified in TCGA set using the autoencoder-based model (log-rank p-value = 5.51e-07). The autoencoder framework showed superior performance compared to PCA, NMF, t-SNE, and the univariable Cox-PH model based on the C-index, log-rank p-value, and Brier score. The robustness of the classification model was successfully verified in three independent validation sets. There were 1271 differentially expressed genes, 10 differentially expressed miRNAs, and 12 hypermethylated genes between the survival risk groups. Among these, miR-133b and its target genes (GNB4, PTPRZ1, RUNX1T1, EPHA7, GPM6A, BICC1, and ADAMTS5) were used to construct a network. These genes were significantly enriched in ECM-receptor interaction, focal adhesion, PI3K-Akt signaling pathway, and glucose metabolism-related pathways. The risk subgroups obtained through a multi-omics data integration pipeline using the DL algorithm had good robustness. miR-133b and its target genes could be potential diagnostic markers. The results would assist in elucidating the possible pathogenesis of COAD.

Corilagin protects the acute lung injury by ameliorating the apoptosis pathway.

This study elucidates the protective effect of corilagin in acute lung injury rat model. Lung injury induced by ischemia/reperfusion (I/R) model was established by isolating the lungs from the rats. Ischemia was produced for the duration of 1h and thereafter reperfusion was done for 90min in isolated lung in presence and absence of corilagin (20 and 40mg/ml). Effect of corilagin was evaluated by estimating the pulmonary vein oxygen partial pressure (PaO2), airway compliance and tidal volume. Moreover the level of oxidative stress parameter, pro inflammatory parameters, phosphorylation of JNK and apoptosis rate was estimated in lung tissues. There was significant increase in the PaO2, airway compliance and tidal volume in corilagin treated group than I/R group. Treatment with corilagin significantly increases the activity of superoxide dismutase (SOD) and level of adenosine triphosphate (ATP) and decreases the level of MDA in the tissue homogenate of I/R induced lung injury model. Whereas expressions of proinflammatory gene such as tumor necrosis factor α, interlukin-6, IL-1ß and cycloxygenase -2 (COX-2) was found to be reduced in corilagin treated group than I/R group. Posphorylation of JNK and apoptotic rate was also found to be decreased in corilagin treated group than I/R group. Present report concludes that treatment with corilagin attenuates the lung injury in ex vivo I/R induced lung injury rat model by decreasing oxidative stress, pro-inflammatory mediators and its anti apoptotic activity.