Ascorbate uptake enables tubular mitophagy to prevent septic AKI by PINK1-PARK2 axis.

Ascorbate (Vitamin C) has been proposed as a promising therapeutic agent against sepsis in clinical trials, but there is little experimental evidence on its anti-septic efficacy. We report that Toll-like receptor 4 (TLR4) activation by LPS stimuli augments ascorbate uptake in murine and human tubular cells through upregulation of two ascorbate transporters SVCT-1 and -2 mediated by Fn14/SCFFbxw7α cascade. Ascorbate restriction, or knockout of SVCT-1 and -2, the circumstance reminiscent to blockade of ascorbate uptake, endows tubular cells more vulnerable to the LPS-inducible apoptosis, whereas exogenous administration of ascorbate overrides the ruin execution, for which the PINK1-PARK2, rather than BNIP3-NIX axis is required. Ascorbate increases, while SVCT-1 and -2 knockout or ascorbate restriction dampens tubular mitophagy upon LPS stimuli. Treatment of endotoxemic mice with high-dose ascorbate confers mitophagy and substantial protection against mortality and septic acute kidney injury (AKI). Our work provides a rationale for clinical management of septic AKI with high doses of ascorbate.

A novel artificial intelligence protocol to investigate potential leads for diabetes mellitus.

Dipeptidyl peptidase-4 (DPP4) is highly participated in regulating diabetes mellitus (DM), and inhibitors of DPP4 may act as potential DM drugs. Therefore, we performed a novel artificial intelligence (AI) protocol to screen and validate the potential inhibitors from Traditional Chinese Medicine Database. The potent top 10 compounds were selected as candidates by Dock Score. In order to further screen the candidates, we used numbers of machine learning regression models containing support vector machines, bagging, random forest and other regression algorithms, as well as deep neural network models to predict the activity of the candidates. In addition, as a traditional method, 2D QSAR (multiple linear regression) and 3D QSAR methods are also applied. The AI methods got a better performance than the traditional 2D QSAR method. Moreover, we also built a framework composed of deep neural networks and transformer to predict the binding affinity of candidates and DPP4. Artificial intelligence methods and QSAR models illustrated the compound, 2007_4105, was a potent inhibitor. The 2007_4105 compound was finally validated by molecular dynamics simulations. Combining all the models and algorithms constructed and the results, Hypecoum leptocarpum might be a potential and effective medicine herb for the treatment of DM.

The Effect of Tartary Buckwheat Flavonoids in Inhibiting the Proliferation of MGC80-3 Cells during Seed Germination.

Tartary buckwheat (Fagopyrum tataricum (L.) Gaertn) is rich in functional compounds such as rutin, quercetin, d-chiro-inositol, dietary fiber, and essential amino acids. Electric field (EF) treatment before sprout germination results in physiological and chemical changes, and some alterations might lead to positive applications in plant seeds. MTT assay showed that the effect of total flavonoids on human gastric cancer cell line MGC80-3 was significantly changed after EF treatment for different germination days (3-7 days). Among them, the total flavonoids of tartary buckwheat (BWTF) on the third day had the most obvious inhibitory effect on MGC80-3 (p < 0.01). In addition, flow cytometry evidenced that different ratios of quercetin and rutin had effects on the proliferation of MGC80-3. The same content of quercetin and rutin had the best effect, reaching 6.18 ± 0.82%. The anti-cancer mechanism was mainly promoted by promoting the expression of apoptotic proteins. The expression of Bax/Bcl-2 and caspase-8 in MGC80-3 cells was mediated by BWTFs. This study has good research value for improving the biological and economic value of tartary buckwheat.

NF-κB-dependent transcriptional upregulation of cyclin D1 exerts cytoprotection against hypoxic injury upon EGFR activation.

Apoptosis of neural cells is one of the main pathological features in hypoxic/ischemic brain injury. Nuclear factor-κB (NF-κB) might be a potential therapeutic target for hypoxic/ischemic brain injury since NF-κB has been found to be inactivated after hypoxia exposure, yet the underlying molecular mechanisms of NF-κB inactivation are largely unknown. Here we report that epidermal growth factor receptor (EGFR) activation prevents neuron-like PC12 cells apoptosis in response to hypoxia via restoring NF-κB-dependent transcriptional upregulation of cyclin D1. Functionally, EGFR activation by EGF stimulation mitigates hypoxia-induced PC12 cells apoptosis in both dose- and time-dependent manner. Of note, EGFR activation elevates IKKß phosphorylation, increases IκBα ubiquitination, promotes P65 nuclear translocation and recruitment at cyclin D1 gene promoter as well as upregulates cyclin D1 expression. EGFR activation also abrogates the decrease of IKKß phosphorylation, reduction of IκBα ubiquitination, blockade of P65 nuclear translocation and recruitment at cyclin D1 gene promoter as well as downregulation of cyclin D1 expression induced by hypoxia. Furthermore, NF-κB-dependent upregulation of cyclin D1 is instrumental for the EGFR-mediated cytoprotection against hypoxic apoptosis. In addition, the dephosphorylation of EGFR induced by either EGF siRNA transfection or anti-HB-EGF neutralization antibody treatment enhances hypoxic cytotoxicity, which are attenuated by EGF administration. Our results highlight the essential role of NF-κB-dependent transcriptional upregulation of cyclin D1 in EGFR-mediated cytoprotective effects under hypoxic preconditioning and support further investigation of EGF in clinical trials of patients with hypoxic/ischemic brain injury.

A novel artificial intelligence protocol to investigate potential leads for Parkinson's disease.

Previous studies have shown that small molecule inhibitors of NLRP3 may be a potential treatment for Parkinson's disease (PD). NACHT, LRR and PYD domains-containing protein 3 (NLRP3), heat shock protein HSP 90-beta (HSP90AB1), caspase-1 (CASP1) and cellular tumor antigen p53 (TP53) have significant involvement in the pathogenesis pathway of PD. Molecular docking was used to screen the traditional Chinese medicine database TCM Database@Taiwan. Top traditional Chinese medicine (TCM) compounds with high affinities based on Dock Score were selected to form the drug-target interaction network to investigate potential candidates targeting NLRP3, HSP90AB1, CASP1, and TP53 proteins. Artificial intelligence model, 3D-Quantitative Structure-Activity Relationship (3D-QSAR) were constructed respectively utilizing training sets of inhibitors against the four proteins with known inhibitory activities (pIC50). The results showed that 2007_22057 (an indole derivative), 2007_22325 (a valine anhydride) and 2007_15317 (an indole derivative) might be a potential medicine formula for the treatment of PD. Then there are three candidate compounds identified by the result of molecular dynamics.

A novel artificial intelligence protocol for finding potential inhibitors of acute myeloid leukemia.

There is currently no effective treatment for acute myeloid leukemia, and surgery is also ineffective as an important treatment for most tumors. Rapidly developing artificial intelligence technology can be applied to different aspects of drug development, and it plays a key role in drug discovery. Based on network pharmacology and virtual screening, candidates were selected from the molecular database. Nine artificial intelligence algorithm models were used to further verify the candidates' potential. The 350 training results of the deep learning model showed higher credibility, and the R-square of the training set and test set of the optimal model reached 0.89 and 0.84, respectively. The random forest model has an R-square of 0.91 and a mean square error of only 0.003. The R-square of the Adaptive Boosting model and the Bagging model reached 0.92 and 0.88, respectively. Molecular dynamics simulation evaluated the stability of the ligand-protein complex and achieved good results. Artificial intelligence models had unearthed the promising candidates for STAT3 inhibitors, and the good performance of most models showed that they still had practical value on small data sets.

Reduced graphene oxide-Hemin-Au nanohybrids: Facile one-pot synthesis and enhanced electrocatalytic activity towards the reduction of hydrogen peroxide.

A facile and effective strategy is demonstrated for the synthesis of ternary reduced graphene oxide-Hemin-Au (rGO-H-Au) nanohybrids. The nanohybrids were synthesized through a one-pot in situ reduction of GO and HAuCl4 under alkaline conditions using GO, Hemin and HAuCl4 as the starting materials. The synthesis process can be finished within 1h in a solution phase, without adding any additional surfactant, stabilizing agent and toxic or harsh chemical reducing agents. The resulting nanohybrids were characterized by UV-vis spectroscopy, Raman spectroscopy, transmission electron microscopy (TEM), and so on. Electrochemical measurements showed that the rGO-H-Au nanohybrids exhibited good electrocatalytic activity for the reduction of hydrogen peroxide (H2O2). Based on this property, a simple and highly sensitive amperometric biosensor for H2O2 had been developed. The linear relationships were obtained from 0.1 µM to 40 µM and the detection limit was estimated to be 30 nM. The simple and sensitive sensing platform showed great promising applications in the pharmaceutical, clinical and industrial detection of H2O2.