Deep Charge: A Deep Learning Model of Electron Density from One-Shot Density Functional Theory Calculation

Electron charge density is a fundamental physical quantity, determining various properties of matter. In this study, we have proposed a deep-learning model for accurate charge density prediction. Our model naturally preserves physical symmetries and can be effectively trained from one-shot density functional theory calculation toward high accuracy. It captures detailed atomic environment information, ensuring accurate predictions of charge density across bulk, surface, molecules, and amorphous structures. This implementation exhibits excellent scalability and provides efficient analyses of material properties in large-scale condensed matter systems

2-Cyano-N,N-dimethyl­acetamide

In the crystal structure of the title compound, C5H8N2O, mol­ecules are linked by weak C—H⋯O hydrogen bonds, forming a three-dimensional network

Molecular Cloning, Expression Profile and 5′ Regulatory Region Analysis of Two Chemosensory Protein Genes from the Diamondback Moth, Plutella xylostella

Chemosensory proteins play an important role in transporting chemical compounds to their receptors on dendrite membranes. In this study, two full-length cDNA codings for chemosensory proteins of Plutella xylostella (Lepidoptera: Plutellidae) were obtained by RACE-PCR. PxylCSP3 and Pxyl-CSP4, with GenBank accession numbers ABM92663 and ABM92664, respectively, were cloned and sequenced. The gene sequences both consisted of three exons and two introns. RT-PCR analysis showed that Pxyl-CSP3 and Pxyl-CSP4 had different expression patterns in the examined developmental stages, but were expressed in all larval stages. Phylogenetic analysis indicated that lepidopteran insects consist of three branches, and Pxyl-CSP3 and Pxyl-CSP4 belong to different branches. The 5′regulatory regions of Pxyl-CSP3 and Pxyl-CSP4 were isolated and analyzed, and the results consist of not only the core promoter sequences (TATA-box), but also several transcriptional elements (BR-C Z4, Hb, Dfd, CF2-II, etc.). This study provides clues to better understanding the various physiological functions of CSPs in P. xylostella and other insects

Graphene-Based Nanostructures in Electrocatalytic Oxygen Reduction

Application of graphene-type materials in electrocatalysis is a topic of growing scientific and technological interest. A tremendous amount of research has been carried out in the field of oxygen electroreduction, particularly with respect to potential applications in the fuel cell research also with use of graphene-type catalytic components. This work addresses fundamental aspects and potential applications of graphene structures in the oxygen reduction electrocatalysis. Special attention will be paid to creation of catalytically active sites by using non-metallic heteroatoms as dopants, formation of hierarchical nanostructured electrocatalysts, their long-term stability, and application as supports for dispersed metals (activating interactions)

The association between ATM D1853N polymorphism and breast cancer susceptibility: a meta-analysis

BACKGROUND: Emerging evidence suggests that ataxia telangiectasia-mutated (ATM) is involved in numerous damage repair signaling pathways and cell-cycle checkpoints. Heterozygous carriers of ATM-mutations have an increased risk for the development of breast cancer. The purpose of this study is to evaluate the association between ATM exon39 5557G > A (D1853N, rs1801516) polymorphism and breast cancer susceptibility with the use of a meta-analysis. METHODS: By searching PubMed and Embase databases, a total of 9 epidemiological studies with 4,191 cases and 3,780 controls were identified. Crude odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) for ATM D1853N polymorphism and breast cancer risk were calculated using fixed- or random-effects model based on the degree of heterogeneity among studies. RESULTS: No significant association between the ATM D1853N polymorphism and breast cancer risk was observed in overall analysis (GA versus GG: OR = 1.18; 95% CI, 0.90-1.53; AA versus GG: OR = 0.77; 95% CI, 0.58-1.03; dominant model: OR = 1.16; 95% CI, 0.89-1.51; and recessive model: OR = 0.78; 95% CI, 0.59-1.04, respectively). CONCLUSION: Our results indicate that ATM D1853N polymorphism is not a risk factor for developing breast cancer

Effective components screening and anti-myocardial infarction mechanism study of the Chinese medicine NSLF6 based on "system to system" mode

<p>Abstract</p> <p>Background</p> <p><it>Shuanglong </it>formula (SLF), a Chinese medicine composed of <it>panax ginseng </it>and <it>salvia miltiorrhiza </it>exhibited significant effect in the treatment of myocardial infarction (MI) in clinical. Because of the complex nature and lack of stringent quality control, it's difficult to explain the action mechanism of SLF.</p> <p>Method</p> <p>In this study, we present a "system to system" (S2S) mode. Based on this mode, SLF was simplified successively through bioactivity-guided screening to achieve an optimized minimal phytochemical composition (new formula NSLF6) while maintaining its curative effect for MI.</p> <p>Results</p> <p>Pharmacological test combining with the study of systems biology show that NSLF6 has activity for treatment MI through synergistic therapeutic efficacies between total ginsenosides and total salvianolic acids via promoting cardiac cell regeneration and myocardial angiogenesis, antagonistic myocardial cell oxidative damage.</p> <p>Conclusions</p> <p>The present S2S mode may be an effective way for the discovery of new composite drugs from traditional medicines.</p

Stomatal responses of terrestrial plants to global change

Quantifying the stomatal responses of plants to global change factors is crucial for modeling terrestrial carbon and water cycles. Here we synthesize worldwide experimental data to show that stomatal conductance (gs) decreases with elevated carbon dioxide (CO2), warming, decreased precipitation, and tropospheric ozone pollution, but increases with increased precipitation and nitrogen (N) deposition. These responses vary with treatment magnitude, plant attributes (ambient gs, vegetation biomes, and plant functional types), and climate. All two-factor combinations (except warming + N deposition) significantly reduce gs, and their individual effects are commonly additive but tend to be antagonistic as the effect sizes increased. We further show that rising CO2 and warming would dominate the future change of plant gs across biomes. The results of our meta-analysis provide a foundation for understanding and predicting plant gs across biomes and guiding manipulative experiment designs in a real world where global change factors do not occur in isolation