The Protective Effects of Bushen Daozhuo Granule on Chronic Non-bacterial Prostatitis

Background: Chronic non-bacterial prostatitis (CNP), one of the most common chronic diseases in urology, leads to pain in the prostate and dysuria, critically affecting the physical or mental health of patients. However, there are no standard treatment approaches for the treatment of CNP in the clinic. Although the clinical application of Bushen Daozhuo granule (BSDZG) offers hope to CNP patients in China, the mechanisms of BSDZG in treating CNP are still not entirely clear. Hence, we aimed to investigate the novel therapeutic mechanisms of BSDZG on CNP.Methods: In this study, we first assayed the prostate index of rats and then determined the anti-inflammatory and anti-apoptotic effects of BSDZG on CNP in vivo and in vitro by employing ELISA kits and TUNEL staining. Next, we investigated whether the anti-inflammatory and anti-apoptotic mechanisms of BSDZG on prostate protein-induced rats and lipopolysaccharide (LPS) induced RWPE-1 cells were related to the AKT, p38 MAPK, and NF-κB pathways with the help of Western blot. Finally, the influence of BSDZG on the interaction between the p38 MAPK and NF-κB pathway in LPS-induced RWPE-1 cells was explored by adopting dehydrocorydaline (DHC, p38 MAPK activator) with the help of ELISA kits and Western blot.Results:In vivo, BSDZG effectively reduced the prostate index. In vivo and in vitro, BSDZG dramatically declined the level of two pro-inflammatory cytokines, TNF-α and IL-1β, as well as the apoptosis rate. Moreover, in vivo and in vitro, BSDZG memorably upregulated the expression level of p-AKT, and substantially downregulated the expression level of p-p38 MAPK and NF-κB2. The activation of p38 MAPK significantly reversed the moderation effects of BSDZG on the level of TNF-α and IL-1β, as well as the expression level of p-p38 MAPK and NF-κB2 in vitro.Conclusion: To sum up, the in vivo and in vitro therapeutic mechanisms of BSDZG on CNP were reflected as the anti-inflammation and anti-apoptosis that was formed by inhibiting the level of pro-inflammatory cytokines, TNF-α and IL-1β, to regulate the AKT, p38 MAPK, and NF-κB pathways, and the anti-inflammatory effect of BSDZG was realized by suppressing the p38 MAPK pathway to inhibit the downstream NF-κB pathway

Drug Side-Effect Prediction Via Random Walk on the Signed Heterogeneous Drug Network

Drug side-effects have become a major public health concern as they are the underlying cause of over a million serious injuries and deaths each year. Therefore, it is of critical importance to detect side-effects as early as possible. Existing computational methods mainly utilize the drug chemical profile and the drug biological profile to predict the side-effects of a drug. In the utilized drug biological profile information, they only focus on drug–target interactions and neglect the modes of action of drugs on target proteins. In this paper, we develop a new method for predicting potential side-effects of drugs based on more comprehensive drug information in which the modes of action of drugs on target proteins are integrated. Drug information of multiple types is modeled as a signed heterogeneous information network. We propose a signed heterogeneous information network embedding framework for learning drug embeddings and predicting side-effects of drugs. We use two bias random walk procedures to obtain drug sequences and train a Skip-gram model to learn drug embeddings. We experimentally demonstrate the performance of the proposed method by comparison with state-of-the-art methods. Furthermore, the results of a case study support our hypothesis that modes of action of drugs on target proteins are meaningful in side-effect prediction

Adverse Drug Reaction Predictions Using Stacking Deep Heterogeneous Information Network Embedding Approach

Inferring potential adverse drug reactions is an important and challenging task for the drug discovery and healthcare industry. Many previous studies in computational pharmacology have proposed utilizing multi-source drug information to predict drug side effects have and achieved initial success. However, most of the prediction methods mainly rely on direct similarities inferred from drug information and cannot fully utilize the drug information about the impact of protein–protein interactions (PPI) on potential drug targets. Moreover, most of the methods are designed for specific tasks. In this work, we propose a novel heterogeneous network embedding approach for learning drug representations called SDHINE, which integrates PPI information into drug embeddings and is generic for different adverse drug reaction (ADR) prediction tasks. To integrate heterogeneous drug information and learn drug representations, we first design different meta-path-based proximities to calculate drug similarities, especially target propagation meta-path-based proximity based on PPI network, and then construct a semi-supervised stacking deep neural network model that is jointly optimized by the defined meta-path proximities. Extensive experiments with three state-of-the-art network embedding methods on three ADR prediction tasks demonstrate the effectiveness of the SDHINE model. Furthermore, we compare the drug representations in terms of drug differentiation by mapping the representations into 2D space; the results show that the performance of our approach is superior to that of the comparison methods

Biosynthesis and Roles of Salicylic Acid in Balancing Stress Response and Growth in Plants

Salicylic acid (SA) is an important plant hormone with a critical role in plant defense against pathogen infection. Despite extensive research over the past 30 year or so, SA biosynthesis and its complex roles in plant defense are still not fully understood. Even though earlier biochemical studies suggested that plants synthesize SA from cinnamate produced by phenylalanine ammonia lyase (PAL), genetic analysis has indicated that in Arabidopsis, the bulk of SA is synthesized from isochorismate (IC) produced by IC synthase (ICS). Recent studies have further established the enzymes responsible for the conversion of IC to SA in Arabidopsis. However, it remains unclear whether other plants also rely on the ICS pathway for SA biosynthesis. SA induces defense genes against biotrophic pathogens, but represses genes involved in growth for balancing defense and growth to a great extent through crosstalk with the growth-promoting plant hormone auxin. Important progress has been made recently in understanding how SA attenuates plant growth by regulating the biosynthesis, transport, and signaling of auxin. In this review, we summarize recent progress in the biosynthesis and the broad roles of SA in regulating plant growth during defense responses. Further understanding of SA production and its regulation of both defense and growth will be critical for developing better knowledge to improve the disease resistance and fitness of crops

Highly Enhanced Visible-Light-Driven Photoelectrochemical Performance of ZnO-Modified In2S3 Nanosheet Arrays by Atomic Layer Deposition

Abstract Photoanodes based on In2S3/ZnO heterojunction nanosheet arrays (NSAs) have been fabricated by atomic layer deposition of ZnO over In2S3 NSAs, which were in situ grown on fluorine-doped tin oxide glasses via a facile solvothermal process. The as-prepared photoanodes show dramatically enhanced performance for photoelectrochemical (PEC) water splitting, compared to single semiconductor counterparts. The optical and PEC properties of In2S3/ZnO NSAs have been optimized by modulating the thickness of the ZnO overlayer. After pairing with ZnO, the NSAs exhibit a broadened absorption range and an increased light absorptance over a wide wavelength region of 250–850 nm. The optimized sample of In2S3/ZnO-50 NSAs shows a photocurrent density of 1.642 mA cm−2 (1.5 V vs. RHE) and an incident photon-to-current efficiency of 27.64% at 380 nm (1.23 V vs. RHE), which are 70 and 116 times higher than those of the pristine In2S3 NSAs, respectively. A detailed energy band edge analysis reveals the type-II band alignment of the In2S3/ZnO heterojunction, which enables efficient separation and collection of photogenerated carriers, especially with the assistance of positive bias potential, and then results in the significantly increased PEC activity

Self-Assembly of Polyoxovanadate-Containing Fluorosurfactants

Two novel polyoxovanadate (POV)-containing fluorosurfactants, each with two hydrophobic fluorinated “tails” and one nanosized, hydrophilic, rigid POV “head group”, are synthesized for the first time. They self-assemble into spherical, bilayer vesicles in acetonitrile/water mixed solvents, as evidenced by systemic studies using laser light scattering (LLS) and electron microscopy techniques. The vesicle sizes demonstrate dynamic change over different solvent compositions mainly as a result of the solvent swelling of the fluorocarbon chains, although the charge number on the POVs changes over the solvent polarity as well