Genomic selection (GS) is a promising breeding strategy by which the phenotypes of plant individuals are usually predicted based on genome-wide markers of genotypes. In this study, we present a deep ...learning method, named DeepGS, to predict phenotypes from genotypes. Using a deep convolutional neural network, DeepGS uses hidden variables that jointly represent features in genotypes when making predictions; it also employs convolution, sampling and dropout strategies to reduce the complexity of high-dimensional genotypic data. We used a large GS dataset to train DeepGS and compared its performance with other methods. The experimental results indicate that DeepGS can be used as a complement to the commonly used RR-BLUP in the prediction of phenotypes from genotypes. The complementarity between DeepGS and RR-BLUP can be utilized using an ensemble learning approach for more accurately selecting individuals with high phenotypic values, even for the absence of outlier individuals and subsets of genotypic markers. The source codes of DeepGS and the ensemble learning approach have been packaged into Docker images for facilitating their applications in different GS programs.
The quantum-level interplay between geometry, topology and correlation is at the forefront of fundamental physics1-15. Kagome magnets are predicted to support intrinsic Chern quantum phases owing to ...their unusual lattice geometry and breaking of time-reversal symmetry14,15. However, quantum materials hosting ideal spinorbit-coupled kagome lattices with strong out-of-plane magnetization are lacking16-21. Here, using scanning tunnelling microscopy, we identify a new topological kagome magnet, TbMn6Sn6, that is close to satisfying these criteria. We visualize its effectively defect-free, purely manganese-based ferromagnetic kagome lattice with atomic resolution. Remarkably, its electronic state shows distinct Landau quantization on application of a magnetic field, and the quantized Landau fan structure features spin-polarized Dirac dispersion with a large Chern gap. We further demonstrate the bulk-boundary correspondence between the Chern gap and the topological edge state, as well as the Berry curvature field correspondence of Chern gapped Dirac fermions. Our results point to the realization of a quantum-limit Chern phase in TbMn6Sn6, and may enable the observation of topological quantum phenomena in the RMn6Sn6 (where R is a rare earth element) family with a variety of magnetic structures. Our visualization ofthe magnetic bulk-boundary-Berry correspondence covering real space and momentum space demonstrates a proof-of-principle method for revealing topological magnets.
Resin content of composites is a dominant factor of macroscopic properties and essential to study. Taking carbon fiber/poly (ether ether ketone) (CF/PEEK) composites molded by various means as ...examples, a method for resin content calculation obtained along with thermogravimetric analysis (TGA) for thermal properties analyzation was introduced. According to results of resin mass contents, TGA curves and differential thermogravimetric analysis (DTG) curves were divided to four stages, including non-decomposition stage of 25–500 °C, rapid decomposition stage of 500–600 °C, transitional stage of 600–700 °C and the stable stage of 700–800 °C. And resin contents were accurate obtained from the transitional stage and stable stage. Results tested by acid digestion method, ignition loss method and TGA methods were compared and it was proved that the TGA method was suitable for resin fraction calculation with a slight difference below 3% compared to results from the other two methods. By comparing results of different composites, we found that TGA methods can also be applied to other composites including reinforcements not disintegrate such as graphite, carbon nanotubes and matrix of thermosetting and thermoplastic decompose under inert gas in testing condition.
•TGA curves including PEEK matrix and CF/PEEK composites can be applied for resin content calculation.•The slow decomposition stage and stable stage of TGA curves (600 ºC-800 °C) are suitable for resin content study.•TGA method is available and accurate based on the uniformity of composites composed of decomposable thermosetting and thermoplastic polymers and non-decomposable or little-decomposable reinforcements, such as, CF, carbon nanotubes, graphite and some inorganic substance under inert atmosphere in the testing scope.
Epstein-Barr virus (EBV)-associated epithelial cancers, including nasopharyngeal carcinoma (NPC) and approximately 10% of gastric cancers, termed EBVaGC, represent 80% of all EBV-related ...malignancies. However, the exact role of EBV in epithelial cancers remains elusive. Here, we report that EBV functions in vasculogenic mimicry (VM). Epithelial cancer cells infected with EBV develop tumor vascular networks that correlate with tumor growth, which is different from endothelial-derived angiogenic vessels and is VEGF-independent. Mechanistically, activation of the PI3K/AKT/mTOR/HIF-1α signaling cascade, which is partly mediated by LMP2A, is responsible for EBV-induced VM formation. Both xenografts and clinical samples of NPC and EBVaGC exhibit VM histologically, which are correlated with AKT and HIF-1α activation. Furthermore, although anti-VEGF monotherapy shows limited effects, potent synergistic antitumor activities are achieved by combination therapy with VEGF and HIF-1α-targeted agents. Our findings suggest that EBV creates plasticity in epithelial cells to express endothelial phenotype and provides a novel EBV-targeted antitumor strategy.
In this study, all-inorganic perovskite quantum dots (QDs) for pure blue emission are explored for full-color displays. We prepared CsPbBr
and Cs
NdCl
QDs via hot injection methods and mixed in ...various ratios at room temperature for color blending. Nd-doped CsPb(Cl/Br)
QDs showed a blueshift in emission, and the photoluminescence quantum yields (PLQY, Φ
) were lower in the 460-470 nm range due to surface halogen and Cs vacancies. To address this, we introduced a silane molecule, APTMS, via a ligand exchange process, effectively repairing these vacancies and enhancing Nd doping into the lattice. This modification promotes the PLQY to 94% at 466 nm. Furthermore, combining these QDs with 1Benzothieno3,2-b1benzothiophene (BTBT), a conjugated small-molecule semiconductor, in a composite film reduced PLQY loss caused by FRET in solid-state QD films. This approach achieved a wide color gamut of 124% National Television System Committee (NTSC), using a UV LED backlight and RGB perovskite QDs in a BTBT-based organic matrix as the color conversion layer. Significantly, the photostability of this composite was enhanced when used as a color conversion layer (CCL) under blue-LED excitation.
Abstract
In ordinary materials, electrons conduct both electricity and heat, where their charge-entropy relations observe the Mott formula and the Wiedemann-Franz law. In topological quantum ...materials, the transverse motion of relativistic electrons can be strongly affected by the quantum field arising around the topological fermions, where a simple model description of their charge-entropy relations remains elusive. Here we report the topological charge-entropy scaling in the kagome Chern magnet TbMn
6
Sn
6
, featuring pristine Mn kagome lattices with strong out-of-plane magnetization. Through both electric and thermoelectric transports, we observe quantum oscillations with a nontrivial Berry phase, a large Fermi velocity and two-dimensionality, supporting the existence of Dirac fermions in the magnetic kagome lattice. This quantum magnet further exhibits large anomalous Hall, anomalous Nernst, and anomalous thermal Hall effects, all of which persist to above room temperature. Remarkably, we show that the charge-entropy scaling relations of these anomalous transverse transports can be ubiquitously described by the Berry curvature field effects in a Chern-gapped Dirac model. Our work points to a model kagome Chern magnet for the proof-of-principle elaboration of the topological charge-entropy scaling.
Glucosamine-6-phosphate N-acetyltransferase (GNA1) is the key enzyme that causes overproduction of N-acetylglucosamine in Bacillus subtilis. Previously, we increased GlcNAc production by promoting ...the expression of GNA1 from Caenorhabditis elegans (CeGNA1) in an engineered B. subtilis strain BSGN12. In this strain overflow metabolism to by-products acetoin and acetate had been blocked by mutations, however pyruvate accumulated as an overflow metabolite. Although overexpression of CeGNA1 drove carbon flux from pyruvate to the GlcNAc synthesis pathway and decreased pyruvate accumulation, the residual pyruvate reduced the intracellular pH, resulting in inhibited CeGNA1 activity and limited GlcNAc production.
In this study, we attempted to further overcome pyruvate overflow by enzyme engineering and host engineering for enhanced GlcNAc production. To this end, the key enzyme CeGNA1 was evolved through error-prone PCR under pyruvate stress to enhance its catalytic activity. Then, the urease from Bacillus paralicheniformis was expressed intracellularly to neutralize the intracellular pH, making it more robust in growth and more efficient in GlcNAc production. It was found that the activity of mutant CeGNA1 increased by 11.5% at pH 6.5-7.5, with the catalytic efficiency increasing by 27.5% to 1.25 s
µM
. Modulated expression of urease increased the intracellular pH from 6.0 to 6.8. The final engineered strain BSGN13 overcame pyruvate overflow, produced 25.6 g/L GlcNAc with a yield of 0.43 g GlcNAc/g glucose in a shake flask fermentation and produced 82.5 g/L GlcNAc with a yield of 0.39 g GlcNAc/g glucose by fed-batch fermentation, which was 1.7- and 1.2-times, respectively, of the yield achieved previously.
This study highlights a strategy that combines pathway enzyme engineering and host engineering to resolve overflow metabolism in B. subtilis for the overproduction of GlcNAc. By means of modulated expression of urease reduced pyruvate burden, conferred bacterial survival fitness, and enhanced GlcNAc production, all of which improved our understanding of co-regulation of cell growth and metabolism to construct more efficient B. subtilis cell factories.
Abstract
Itinerant kagome lattice magnets exhibit many novel correlated and topological quantum electronic states with broken time-reversal symmetry. Superconductivity, however, has not been observed ...in this class of materials, presenting a roadblock in a promising path toward topological superconductivity. Here, we report that novel superconductivity can emerge at the interface of kagome Chern magnet TbMn
6
Sn
6
and metal heterostructures when elemental metallic thin films are deposited on either the top (001) surface or the side surfaces. Superconductivity is also successfully induced and systematically studied by using various types of metallic tips on different TbMn
6
Sn
6
surfaces in point-contact measurements. The anisotropy of the superconducting upper critical field suggests that the emergent superconductivity is quasi-two-dimensional. Remarkably, the interface superconductor couples to the magnetic order of the kagome metal and exhibits a hysteretic magnetoresistance in the superconducting states. Taking into account the spin-orbit coupling, the observed interface superconductivity can be a surprising and more realistic realization of the
p
-wave topological superconductors theoretically proposed for two-dimensional semiconductors proximity-coupled to
s
-wave superconductors and insulating ferromagnets. Our findings of robust superconductivity in topological-Chern-magnet/metal heterostructures offer a new direction for investigating spin-triplet pairing and topological superconductivity.
Utilizing large-scale epigenomics data, deep learning tools can predict the regulatory activity of genomic sequences, annotate non-coding genetic variants, and uncover mechanisms behind complex ...traits. However, these tools primarily rely on human or mouse data for training, limiting their performance when applied to other species. Furthermore, the limited exploration of many species, particularly in the case of livestock, has led to a scarcity of comprehensive and high-quality epigenetic data, posing challenges in developing reliable deep learning models for decoding their non-coding genomes. The cross-species prediction of the regulatory genome can be achieved by leveraging publicly available data from extensively studied organisms and making use of the conserved DNA binding preferences of transcription factors within the same tissue. In this study, we introduced DeepSATA, a novel deep learning-based sequence analyzer that incorporates the transcription factor binding affinity for the cross-species prediction of chromatin accessibility. By applying DeepSATA to analyze the genomes of pigs, chickens, cattle, humans, and mice, we demonstrated its ability to improve the prediction accuracy of chromatin accessibility and achieve reliable cross-species predictions in animals. Additionally, we showcased its effectiveness in analyzing pig genetic variants associated with economic traits and in increasing the accuracy of genomic predictions. Overall, our study presents a valuable tool to explore the epigenomic landscape of various species and pinpoint regulatory deoxyribonucleic acid (DNA) variants associated with complex traits.
Cyclin-dependent kinase inhibitor p16
(p16) primarily functions as a negative regulator of the retinoblastoma protein (Rb) -E2F pathway, thus plays critical role in cell cycle progression, cellular ...senescence and apoptosis. In this study, we showed that the methylation of Arg 138 and the phosphorylation of Ser 140 on p16 were critical for the control of cell proliferation and apoptosis. Compared to wild type p16, mutant p16R138K possessed improved function in preventing cell proliferation and inducing apoptosis, while the Ser 140 mutation (p16S140A) exhibited the opposite alteration. We also demonstrated that H
O
was able to induce the phosphorylation of p16, which facilitated the interaction between CDK4 (Cyclin-dependent protein kinase) and p16, in 293T (human emborynic kidney) cells. Furthermore, the elevated arginine methylation in p16S140A mutant and increased serine phosphorylation in p16R138K mutant suggest that a antagonizing mechanism coordinating Arg 138 methylation and Ser 140 phosphorylation to regulates p16 function as well as cellular apoptosis and senescence. These findings will therefore contribute to therapeutic treatment for p16-related gene therapy by providing theoretical and experimental evidence.
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