Ficus hirta Vahl. alleviate LPS induced apoptosis via down-regulating of miR-411 in orange-spotted grouper (Epinephelus coioides) spleen cell.

Ficus hirta Vahl. (FhV) has been shown to have antimicrobial and antiviral efficacy. To further ascertain the pharmacological properties of FhV., and to search for alternatives to antibiotics. An in vitro experiment was carried out to evaluate what influence FhV. would have on LPS-induced apoptosis. In this study, Fas, an apoptosis receptor, was cloned, which included a 5'-UTR of 39 bp, an ORF of 951 bp, a protein of 316 amino acids, and a 3'-UTR of 845 bp. EcFas was most strongly expressed in the spleen tissue of orange-spotted groupers. In addition, the apoptosis of fish spleen cells induced by LPS was concentration-dependent. Interestingly, appropriate concentrations of FhV. alleviated LPS-induced apoptosis. Inhibition of miR-411 further decreased the inhibitory effect of Fas on apoptosis, which reduced Bcl-2 expression and mitochondrial membrane potential, enhanced the protein expression of Bax and Fas. More importantly, the FhV. could activate miR-411 to improve this effect. In addition, luciferase reporter assays showed that miR-411 binds to Fas 3'-UTR to inhibit Fas expression. These findings provide evidence that FhV. alleviates LPS-induced apoptosis by activating miR-411 to inhibit Fas expression and, therefore, provided possible strategies for bacterial infections in fish.

Applications of Nanoparticle-Antibody Conjugates in Immunoassays and Tumor Imaging.

Modern diagnostic technologies rely on both in vitro and in vivo modalities to provide a complete understanding of the clinical state of a patient. Nanoparticle-antibody conjugates have emerged as promising systems to confer increased sensitivity and accuracy for in vitro diagnostics (e.g., immunoassays). Meanwhile, in vivo applications have benefited from the targeting ability of nanoparticle-antibody conjugates, as well as payload flexibility and tailored biodistribution. This review provides an encompassing overview of nanoparticle-antibody conjugates, from chemistry to applications in medical immunoassays and tumor imaging, highlighting the underlying principles and unique features of relevant preclinical applications employing commonly used imaging modalities (e.g., optical/photoacoustics, positron-emission tomography, magnetic resonance imaging, X-ray computed tomography).

AdipoRs- a potential therapeutic target for fibrotic disorders.

Introduction: Fibrotic disorders are a leading cause of morbidity and mortality; hence effective treatments are still vigorously sought. AdipoRs (AdipoR1 and Adipo2) are responsible for the antifibrotic effects of adiponectin (APN). APN exerts antifibrotic effects by binding to its receptors. APN concentration and AdipoR expression are closely associated with fibrotic disorders. Decreased AdipoR expression may reduce APN-AdipoR signaling, while the upregulation of AdipoR expression may restore the anti-fibrotic effects of APN. Loss of APN signaling exacerbates fibrosis in vivo and in vitro. Areas covered: We assess the relationship between APN and fibrotic disorders, the structure of receptors for APN and the pathways accounting for APN or its analogs blocking fibrotic disorders. This article also discusses designed APN products and their therapeutic prospects for fibrotic disorders. Expert opinion: AdipoRs have a critical role in blocking fibrosis. The development of small-molecule agonists toward this target represents a valid drug development pathway.

Discovery of CDK4 inhibitors by convolutional neural networks.

Aim: Descriptors of molecules are important in the discovery of lead compounds. Most of these descriptors are used to represent molecular structures, although structural formulas are the most intuitive representation. Convolutional neural networks (ConvNets) are effective for managing intuitive information. Results/methodology: Convolutional neural networks (ConvNets) based on two-dimensional structural formulas were used for the preliminary screening of CDK4 inhibitors. After supervised learning of our homemade dataset, our models screened out ten approved drugs, including indocyanine green and candesartan cilexetil, with IC50 values of 2.0 and 5.2 µM, respectively. Conclusion: Depending only on intuitive information, the developed method was shown to be feasible, thus providing a new method of lead compound discovery.