Banana leaves wastes (BL) were subjected to fungal treatment using Pleurotus ostreatus to produce edible mushrooms and biogas in the anaerobic digestion process. Effects of fungal treatment on mushrooms production, lignin degradation, trace elements compositions and biogas yield during the anaerobic digestion process were evaluated. Treatment with P.ostreatus for 36 d resulted in the production of 181 ± 19 g of edible mushrooms per 2 kg of BL with biological efficiency of 37 ± 4%. Lignin concentration in fungal treated BL decreased by 10% indicating an improvement on its digestibility. Important trace elements (Fe, Mn, Mo, Co and Ni) necessary for the improvement of the anaerobic digestion process were also significantly reduced (P  less then  0.05) during the fungal treatment process. The biogas yield for the fungal treated BL was 282 mL g-1 VS-1 of which this study suggests that could be improved through trace element supplementation during the anaerobic digestion process.RNA interference (RNAi) is mediated by an ∼21-nt double-stranded small interfering RNA (siRNA) and shows great promise in delineating gene functions and in developing therapeutics for human diseases. However, effective gene silencing usually requires the delivery of multiple siRNAs for a given gene, which is often technically challenging and time-consuming. In this study, by exploiting the type IIS restriction endonuclease-based synthetic biology methodology, we developed the fast assembly of multiplex siRNAs (FAMSi) system. In our proof-of-concept experiments, we demonstrated that multiple fragments containing three, four, or five siRNA sites targeting common Smad4 and/or BMPR-specific Smad1, Smad5, and Smad8 required for BMP9 signaling could be assembled efficiently. The constructed multiplex siRNAs effectively knocked down the expression of Smad4 and/or Smad1, Smad5, and Smad8 in mesenchymal stem cells (MSCs), and they inhibited all aspects of BMP9-induced osteogenic differentiation in bone marrow MSCs (BMSCs), including decreased expression of osteogenic regulators/markers, reduced osteogenic marker alkaline phosphatase (ALP) activity, and diminished in vitro matrix mineralization and in vivo ectopic bone formation. Collectively, we demonstrate that the engineered FAMSi system provides a fast-track platform for assembling multiplexed siRNAs in a single vector, and thus it may be a valuable tool to study gene functions or to develop novel siRNA-based therapeutics.We investigated whether microRNA-150 (miR-150)-based RNA interference (RNAi) ameliorates tubular injury and tubulointerstitial fibrosis. Mice injected with folic acid developed tubulointerstitial fibrosis at day 30. miR-150 levels were increased at day 7 and peaked at day 30. At day 30, protein levels of α-smooth muscle actin, fibronectin (FN), and collagen 1 (COL-1) were increased, while suppressor of cytokine signal 1 (SOCS1) was decreased. Kidneys manifested increased macrophage numbers and increased expression of potential mediators interferon-γ, interleukin-6, and tumor necrosis factor-α. Locked nucleic acid-anti-miR-150, started prior to or after tubular injury and administered twice weekly for 4 weeks, reversed renal inflammation and fibrosis. In HK-2 cells, co-culture with macrophages increased miR-150 expression and decreased SOCS1. Janus kinase (JAK) and signal transducer and activators of transcription (STAT) pathway-related proteins p-JAK1, p-JAK2, p-STAT1, p-STAT3, and pro-fibrotic genes encoding α-smooth muscle actin, FN, and COL-1 were all upregulated. The miR-150 antagonist reversed these transcriptional changes. Lastly, in renal biopsies from patients with chronic interstitial fibrosis, renal miR-150, and pro-fibrotic gene expression and macrophage numbers were increased, while SOCS1 expression was decreased. In conclusion, miR-150-based RNAi is as a potential novel therapeutic agent for tubulointerstitial fibrosis, suppressing the SOCS1/JAK/STAT pathway and reducing macrophage influx.Cancer is one of the most dangerous diseases to human health. The accurate prediction of anticancer peptides (ACPs) would be valuable for the development and design of novel anticancer agents. Current deep neural network models have obtained state-of-the-art prediction accuracy for the ACP classification task. However, based on existing studies, it remains unclear which deep learning architecture achieves the best performance. Thus, in this study, we first present a systematic exploration of three important deep learning architectures convolutional, recurrent, and convolutional-recurrent networks for distinguishing ACPs from non-ACPs. We find that the recurrent neural network with bidirectional long short-term memory cells is superior to other architectures. By utilizing the proposed model, we implement a sequence-based deep learning tool (DeepACP) to accurately predict the likelihood of a peptide exhibiting anticancer activity. The results indicate that DeepACP outperforms several existing methods and can be used as an effective tool for the prediction of anticancer peptides. Furthermore, we visualize and understand the deep learning model. We hope that our strategy can be extended to identify other types of peptides and may provide more assistance to the development of proteomics and new drugs.Recent studies have suggested that microRNA let-7i is a tumor suppressor in human cancers, including esophageal cancer, but its underlying mechanism is not yet fully understood. We investigated the role and mechanisms of let-7i in the progression of esophageal cancer. We first showed that let-7i was downregulated in esophageal cancer tissues and cells and then linked its low expression to cancer progression.  https://www.selleckchem.com/products/Eloxatin.html  Bioinformatic analysis predicted KDM5B as a target gene of let-7i, which was confirmed by a dual-luciferase reporter assay. Loss- and gain-of function approaches were adopted to examine the interactions of let-7i, KDM5B, SOX17, and GREB1 in vitro and in vivo. Overexpression of let-7i suppressed esophageal cancer cell proliferation and invasion and promoted apoptosis. Mechanistic investigation showed that let-7i targeted and inhibited KDM5B expression, whereas KDM5B enhanced H3K4me3 at the SOX17 promoter region. Overexpression of let-7i suppressed the expression of GREB1 in esophageal cancer cells by regulating the KDM5B/SOX17 axis in vivo and in vitro.