Microstructure design of advanced magnesium-air battery anodes

Metal-air battery is an environmental friendly energy storage system with unique open structure.Magnesium(Mg)and its alloys have been extensively attempted as anodes for air batteries due to high theoretical energy density,low cost,and recyclability.However,the study on Mg-air battery(MAB)is still at the laboratory level currently,mainly owing to the low anodic efficiency caused by the poor corrosion resistance.In order to reduce corrosion losses and achieve optimal utilization efficiency of Mg anode,the design strategies are reviewed from microstructure perspectives.Firstly,the corrosion behaviors have been discussed,especially the negative difference effect derived by hydrogen evolution.Special attention is given to the effect of anode micro-structures on the MAB,which includes grain size,grain orientation,second phases,crystal structure,twins,and dislocations.For further improvement,the discharge performance,long period stacking ordered phase and its enhancing effect are considered.Meanwhile,given the current debates over Mg dendrites,the potential risk,the impact on discharge,and the elimination strategies are discussed.Microstructure control and single crystal would be promising ways for MAB anode.

Three Kinds of Discrete Formulae for the Caputo Fractional Derivative

In this paper,three kinds of discrete formulae for the Caputo fractional derivative are studied,including the modified L1 discretisation forα∈(O,1),and L2 discretisation and L2C discretisation forα∈(1,2).The truncation error estimates and the properties of the coeffcients of all these discretisations are analysed in more detail.Finally,the theoretical analyses areverifiedby thenumerical examples.

A zwitterionic polymer-inspired material mediated efficient CRISPR-Cas9 gene editing

The typeⅡ prokaryotic CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 (CRISPR/Cas9) adaptive immune system is a cutting-edge genome-editing toolbox.However,its applications are still limited by its inefficient transduction.Herein,we present a novel gene vector,the zwitterionic polymer-inspired material with branched structure (ZEBRA) for efficient CRISPR/Cas9 delivery.Polo-like kinase 1 (PLK1) acts as a master regulator of mitosis and overexpresses in multiple tumor cells.The Cas9 and single guide sgRNA (sgRNA)-encoded plasmid was transduced to knockout Plk1 gene,which was expected to inhibit the expression of PLK1.Our studies demonstrated that ZEBRA enabled to transduce the CRISPR/Cas9 system with large size into the cells efficiently.The transduction with ZEBRA was cell line dependent,which showed~10-fold higher in CD44-positive cancer cell lines compared with CD44-negative ones.Furthermore,ZEBRA induced highlevel expression of Cas9 proteins by the delivery of CRISPR/Cas9 and efficient gene editing of Plk1 gene,and inhibited the tumor cell growth significantly.This zwitterionic polymerinspired material is an effective and targeted gene delivery vector and further studies are required to explore its potential in gene delivery applications.

Increased 5-hydroxymethylcytosine is a favorable prognostic factor of Helicobacter pylori-negative gastric cancer patients

BACKGROUND Most gastric cancer(GC)patients are diagnosed at middle or late stage because the symptoms in early stage are obscure,which causes higher mortality rates of GC.Helicobacter pylori(H.pylori)was identified as a class I carcinogen and leads to aberrant DNA methylation/hydroxymethylation.5-hydroxymethylcytosine(5-hmC)plays complex roles in gene regulation of tumorigenesis and can be considered as an activating epigenetic mark of hydroxymethylation.AIM To explore the association between 5-hmC levels and the progression and prognosis of GC patients with or without H.pylori infection.METHODS A retrospective cohort study was conducted to estimate the predicted value of 5-hmC level in the progression and prognosis of GC patients with different H.pylori infection status.A total of 144 GC patients were recruited.RESULTS The levels of 5-hmC were significantly decreased in tumor tissues(0.076±0.048)compared with the matched control tissues(0.110±0.057,P=0.001).A high level of 5-hmC was an independent significant favorable predictor of overall survival in GC patients(hazard ratio=0.61,95% confidence interval:0.38-0.98,P=0.040),the H.pylori-negative GC subgroup(hazard ratio=0.30,95% confidence interval:0.13-0.68,P=0.004)and the GC patients with TNM stage Ⅰ or Ⅱ(hazard ratio=0.32,95% confidence interval:0.13-0.77,P=0.011).CONCLUSION Increased 5-hmC is a favorable prognostic factor in GC,especially for H.pylori-negative subgroups.

Ailanthone ameliorates pulmonary fibrosis by suppressing JUN-dependent MEOX1 activation

Pulmonary fibrosis poses a significant health threat with very limited therapeutic options available.In this study,we reported the enhanced expression of mesenchymal homobox 1(MEOX1)in pulmonary fibrosis patients,especially in their fibroblasts and endothelial cells,and confirmed MEOX1 as a central orchestrator in the activation of profibrotic genes.By high-throughput screening,we identified Ailanthone(AIL)from a natural compound library as the first small molecule capable of directly targeting and suppressing MEOX1.AIL demonstrated the ability to inhibit both the activation of fibroblasts and endothelial-to-mesenchymal transition of endothelial cells when challenged by transforming growth factor-b1(TGF-b1).In an animal model of bleomycin-induced pulmonary fibrosis,AIL effectively mitigated the fibrotic process and restored respiratory functions.Mechanistically,AIL acted as a suppressor of MEOX1 by disrupting the interaction between the transcription factor JUN and the promoter of MEOX1,thereby inhibiting MEOX1 expression and activity.In summary,our findings pinpointed MEOX1 as a cell-specific and clinically translatable target in fibrosis.Moreover,we demonstrated the potent anti-fibrotic effect of AIL in pulmonary fibrosis,specifically through the suppression of JUN-dependent MEOX1 activation.

SnS_(2) nanosheets decorated SnO_(2) hollow multishelled nanostructures for enhanced sensing of triethylamine gas

Highly sensitive,fast and low-temperature detection of triethylamine(TEA)gas based on SnO_(2) is attractive yet remains challenging.Herein,SnS_(2) nanosheets(NSs)/SnO_(2) hollow multishelled structures(HoMSs)-based sensors are designed by the synthesis of SnO_(2) HoMSs,followed by in situ sulfuration with thioacetamide.By varying the thioacetamide levels,Sn S_(2)/SnO_(2) heterostructures with different SnS_(2) contents were obtained and their TEA gas sensing performances were investigated.

SS-Pro:a simplified siamese contrastive learning approach for protein surface representation

Protein surface serves as an important representation of protein structure,revealing how protein interacts with other biomolecules to perform its functions.This forms the basis for pharmaceutical and fundamental biological research[1].Datadriven deep learning methods in protein surface representation face challenges of label scarcity,since labeled data are typically obtained through wet lab experiments.

Experimental quantum secret sharing based on phase encoding of coherent states

Quantum secret sharing(QSS)is one of the basic communication primitives in future quantum networks which addresses part of the basic cryptographic tasks of multiparty communication and computation.Nevertheless,it is a challenge to provide a practical QSS protocol with security against general attacks.A QSS protocol that balances security and practicality is still lacking.Here,we propose a QSS protocol with simple phase encoding of coherent states among three parties.Removing the requirement of impractical entangled resources and the need for phase randomization,our protocol can be implemented with accessible technology.We provide the finite-key analysis against coherent attacks and implement a proof-of-principle experiment to demonstrate our scheme’s feasibility.Our scheme achieves a key rate of 85.3 bps under a 35 d B channel loss.Combined with security against general attacks and accessible technology,our protocol is a promising candidate for practical multiparty quantum communication networks.

Supertough spontaneously self-healing polymer based on septuple dynamic bonds integrated in one chemical group

The development of spontaneously self-healing materials with excellent mechanical properties remains a formidable challenge despite the extensive interest in such materials.This is because the self-healing and mechanical properties of a material are usually optimized via contradictory routes.The present study demonstrated a supertough spontaneously self-healing polymer,Fe-(2,6-diacetylpyridine dioxime)-urethane-based polyurethane(Fe-PPOU)based on septuple dynamic bonds integrated in one chemical group.A synergistic effect was induced by the presence of multiple dynamic crosslinking points,which comprised the integrated dynamic interactions,and the hidden lengths of the folded polymeric chains in Fe-PPOU.Thus,the mechanical and self-healing properties of the polymer were simultaneously optimized.Fe-PPOU demonstrated the highest reported toughness(139.8 MJ m^(-3))among all the room-temperature spontaneously self-healing polymers with a nearly 100%healing rate.Fe-PPOU exhibited instant(30 s)self-healing to reach a strength of 1.6 MPa that was higher than the original strength of numerous recently reported self-healing polymers.

4-Axis printing microfibrous tubular scaffold and tracheal cartilage application

Long-segment defects remain a major problem in clinical treatment of tubular tissue reconstruction.The design of tubular scaffold with desired structure and functional properties suitable for tubular tissue regeneration remains a great challenge in regenerative medicine.Here,we present a reliable method to rapidly fabricate tissueengineered tubular scaffold with hierarchical structure via 4-axis printing system.The fabrication process can be adapted to various biomaterials including hydrogels,thermoplastic materials and thermosetting materials.Using polycaprolactone(PCL)as an example,we successfully fabricated the scaffolds with tunable tubular architecture,controllable mesh structure,radial elasticity,good flexibility,and luminal patency.As a preliminary demonstration of the applications of this technology,we prepared a hybrid tubular scaffold via the combination of the 4-axis printed elastic poly(glycerol sebacate)(PGS)bio-spring and electrospun gelatin nanofibers.The scaffolds seeded with chondrocytes formed tubular mature cartilage-like tissue both via in vitro culture and subcutaneous implantation in the nude mouse,which showed great potential for tracheal cartilage reconstruction.

Prediction of pandemic risk for animal-origin coronavirus using a deep learning method

Background:Coronaviruses can be isolated from bats,civets,pangolins,birds and other wild animals.As an animalorigin pathogen,coronavirus can cross species barrier and cause pandemic in humans.In this study,a deep learning model for early prediction of pandemic risk was proposed based on the sequences of viral genomes.Methods:A total of 3257 genomes were downloaded from the Coronavirus Genome Resource Library.We present a deep learning model of cross-species coronavirus infection that combines a bidirectional gated recurrent unit network with a one-dimensional convolution.The genome sequence of animal-origin coronavirus was directly input to extract features and predict pandemic risk.The best performances were explored with the use of pre-trained DNA vector and attention mechanism.The area under the receiver operating characteristic curve(AUROC)and the area under precision-recall curve(AUPR)were used to evaluate the predictive models.Results:The six specifc models achieved good performances for the corresponding virus groups(1 for AUROC and 1 for AUPR).The general model with pre-training vector and attention mechanism provided excellent predictions for all virus groups(1 for AUROC and 1 for AUPR)while those without pre-training vector or attention mechanism had obvi‑ously reduction of performance(about 5–25%).Re-training experiments showed that the general model has good capabilities of transfer learning(average for six groups:0.968 for AUROC and 0.942 for AUPR)and should give reason‑able prediction for potential pathogen of next pandemic.The artifcial negative data with the replacement of the coding region of the spike protein were also predicted correctly(100%accuracy).With the application of the Python programming language,an easy-to-use tool was created to implements our predictor.Conclusions:Robust deep learning model with pre-training vector and attention mechanism mastered the features from the whole genomes of animal-origin coronaviruses and could predict the risk of cross-species infection for early warning of next pandemic.