The antioxidant protein ZmPrx5 contributes resistance to maize stalk rot

Maize(Zea mays L.)stalk rot is a devastating disease worldwide,causing severe yield losses.Although previous studies have focused on the genetic dissection of maize resistance to stalk rot,the mechanisms of resistance remain largely unknown.We used a comparative proteomics approach to identify candidate proteins associated with stalk rot resistance.Statistical analyses revealed 763 proteins differentially accumulated between Fusarium graminearum and mock-inoculated plants.Among them,the antioxidant protein ZmPrx5,which was up-accumulated in diseased plants,was selected for further study.ZmPrx5 transcripts were present in root,stalk,leaf,ear,and reproductive tissues.The expression of ZmPrx5 in three inbred lines increased significantly upon F.graminearum infection.ZmPrx5 was localized in the cytoplasm.Compared to control plants,maize plants overexpressing ZmPrx5 showed increased resistance to F.graminearum infection,and ZmPrx5 mutant plants were more susceptible than wild-type plants.Defense-associated pathways including plant–pathogen interactions,phenylalanine metabolism,and benzoxazinoid and flavonoid biosynthesis were suppressed in ZmPrx5 homozygous mutant plants compared with wild-type plants.We suggest that ZmPrx5 positively regulates resistance against stalk rot in maize,likely through defense-oriented transcriptome reprogramming.These results lay a foundation for further research on the roles of Prx5 subfamily proteins in resistance to plant fungal diseases,and provide a potential genetic resource for breeding disease-resistance maize lines.

Prediction of Salinity Variations in a Tidal Estuary Using Artificial Neural Network and Three-Dimensional Hydrodynamic Models

The simulation of salinity at different locations of a tidal river using physically-based hydrodynamic models is quite cumbersome because it requires many types of data, such as hydrological and hydraulic time series at boundaries, river geometry, and adjusted coefficients. Therefore, an artificial neural network (ANN) technique using a back-propagation neural network (BPNN) and a radial basis function neural network (RBFNN) is adopted as an effective alternative in salinity simulation studies. The present study focuses on comparing the performance of BPNN, RBFNN, and three-dimensional hydrodynamic models as applied to a tidal estuarine system. The observed salinity data sets collected from 18 to 22 May, 16 to 22 October, and 26 to 30 October 2002 (totaling 4320 data points) were used for BPNN and RBFNN model training and for hydrodynamic model calibration. The data sets collected from 30 May to 2 June and 11 to 15 November 2002 (totaling 2592 data points) were adopted for BPNN and RBFNN model verification and for hydrodynamic model verification. The results revealed that the ANN (BPNN and RBFNN) models were capable of predicting the nonlinear time series behavior of salinity to the multiple forcing signals of water stages at different stations and freshwater input at upstream boundaries. The salinity predicted by the ANN models was better than that predicted by the physically based hydrodynamic model. This study suggests that BPNN and RBFNN models are easy-to-use modeling tools for simulating the salinity variation in a tidal estuarine system.

Baicalin induces ferroptosis in bladder cancer cells by downregulating FTH1

Ferroptosis is a non-apoptotic regulated cell death caused by iron accumulation and subsequent lipid peroxidation.Currently,the therapeutic role of ferroptosis on cancer is gaining increasing interest.Baicalin an active component in Scutellaria baicalensis Georgi with anticancer potential various cancer types;however,the effects of baicalein on bladder cancer and the underlying molecular mechanisms remain largely unknown.In the study,we investigated the effect of baicalin on bladder cancer cells5637 and KU-19-19.As a result,we show baicalin exerted its anticancer activity by inducing apoptosis and cell death in bladder cancer cells.Subsequently,we for the first time demonstrate baicalin-induced ferroptotic cell death in vitro and in vivo,accompanied by reactive oxygen species(ROS) accumulation and intracellular chelate iron enrichment.The ferroptosis inhibitor deferoxamine but not necrostatin-1,chloroquine(CQ),N-acetyl-L-cysteine,L-glutathione reduced,or carbobenzoxy-valyl-alanyl-aspartyl-[O-methyl]-fluoromethylketone(Z-VAD-FMK) rescued baicalin-induced cell death,indicating ferroptosis contributed to baicalin-induced cell death.Mechanistically,we show that ferritin heavy chain1(FTH1) was a key determinant for baicalin-induced ferroptosis.Overexpression of FTH1 abrogated the anticancer effects of baicalin in both 5637 and KU19-19 cells.Taken together,our data for the first time suggest that the natural product baicalin exerts its anticancer activity by inducing FTH1-dependent ferroptosis,which will hopefully provide a prospective compound for bladder cancer treatment.

Curcumenol triggered ferroptosis in lung cancer cells via lncRNA H19/miR-19b-3p/FTH1 axis

Curcumenol,an effective ingredient of Wenyujin,has been reported that exerted its antitumor potential in a few cancer types.However,the effect and molecular mechanism of curcumenol in lung cancer are largely unknown.Here,we found that curcumenol induced cell death and suppressed cell proliferation in lung cancer cells.Next,we demonstrated that ferroptosis was the predominant method that contributed to curcumenol-induced cell death of lung cancer in vitro and vivo for the first time.Subsequently,using RNA sequencing,we found that the long non-coding RNA H19(lncRNA H19)was significantly downregulated in lung cancer cells treated with curcumenol,when compared to untreated controls.Overexpression of lncRNA H19 eliminated the anticancer effect of curcumenol,while lncRNA H19 knockdown promoted ferroptosis induced by curcumenol treatment.Mechanistically,we showed that lncRNA H19 functioned as a competing endogenous RNA to bind to miR-19b-3p,thereby enhanced the transcription activity of its endogenous target,ferritin heavy chain 1(FTH1),a marker of ferroptosis.In conclusion,our data show that the natural product curcumenol exerted its antitumor effects on lung cancer by triggering ferroptosis,and the lncRNA H19/miR-19b-3p/FTH1 axis plays an essential role in curcumenol-induced ferroptotic cell death.Therefore,our findings will hopefully provide a valuable drug for treating lung cancer patients.

Segregation Behavior and Evolution Mechanism of Iron-Rich Phases in Molten Magnesium Alloys

A new method has been proposed to prepare Mg-A1-Si master alloys by utilizing scrap AI-Si-Fe alloys with higher Fe levels, which aims to segregate Fe from AI-Si-Fe alloys by Mg melt. The segregation be- haviors, microstructure morphology and evolution mechanism of iron-rich phases in Mg-A1-Si alloy melts were studied, after AI-14Si-4Fe （wt%） alloys were added and dissolved completely. In the Mg-A1-Si alloys, iron has very little solubility and tends to combine with other elements to form intermetallic phases, which grow into a deposition layer due to the higher density. During the cooling and solidifying process of Mg-A1-Si melts, the needle-like AlsSiFe phase in AI-14Si-4Fe alloy evolved into blocky AI5Fe2 and Al0.7Fe3Si0.3 phases. Besides, the Fe levels of the Mg-AI-Si master alloys were reduced to 0.017 wt% from nominal content of 0.164 wt%. Based on the above results, this work carried out a semi-quantitative phase- compositions analysis for the deposition layer by relative intensity ratio （RIR） method, and evolution mechanism of the iron-rich phases had also been discussed. This study has paved a new way to regen- erate the scrap AI-Si-Fe alloys, which has a great significance of promoting the recycling of aluminum resources.

Deep simulated annealing for the discovery of novel dental anesthetics with local anesthesia and anti-inflammatory properties

Multifunctional therapeutics have emerged as a solution to the constraints imposed by drugs with singular or insufficient therapeutic effects.The primary challenge is to integrate diverse pharmacophores within a single-molecule framework.To address this,we introduced DeepSA,a novel edit-based generative framework that utilizes deep simulated annealing for the modification of articaine,a wellknown local anesthetic.DeepSA integrates deep neural networks into metaheuristics,effectively constraining molecular space during compound generation.This framework employs a sophisticated objective function that accounts for scaffold preservation,anti-inflammatory properties,and covalent constraints.Through a sequence of local editing to navigate the molecular space,DeepSA successfully identified AT-17,a derivative exhibiting potent analgesic properties and significant anti-inflammatory activity in various animal models.Mechanistic insights into AT-17 revealed its dual mode of action:selective inhibition of NaV1.7 and 1.8 channels,contributing to its prolonged local anesthetic effects,and suppression of inflammatory mediators via modulation of the NLRP3 inflammasome pathway.These findings not only highlight the efficacy of AT-17 as a multifunctional drug candidate but also highlight the potential of DeepSA in facilitating AI-enhanced drug discovery,particularly within stringent chemical constraints.