Search

MYB transcription factors are major actors regulating plant development and adaptability. Brassica napus is a staple oil crop and is hampered by lodging and diseases. Here, four B. napus MYB69 (BnMYB69s) genes were cloned and functionally characterized. They were dominantly expressed in stems during lignification. BnMYB69 RNA interference (BnMYB69i) plants showed considerable changes in morphology, anatomy, metabolism and gene expression. Stem diameter, leaves, roots and total biomass were distinctly larger, but plant height was significantly reduced. Contents of lignin, cellulose and protopectin in stems were significantly reduced, accompanied with decrease in bending resistance and Sclerotinia sclerotiorum resistance. Anatomical detection observed perturbation in vascular and fiber differentiation in stems, but promotion in parenchyma growth, accompanied with changes in cell size and cell number. In shoots, contents of IAA, shikimates and proanthocyanidin were reduced, while contents of ABA, BL and leaf chlorophyll were increased. qRT-PCR revealed changes in multiple pathways of primary and secondary metabolisms. IAA treatment could recover many phenotypes and metabolisms of BnMYB69i plants. However, roots showed trends opposite to shoots in most cases, and BnMYB69i phenotypes were light-sensitive. Conclusively, BnMYB69s might be light-regulated positive regulators of shikimates-related metabolisms, and exert profound influences on various internal and external plant traits.

Large pre-trained code generation models, such as OpenAI Codex, can generate syntax- and function-correct code, making the coding of programmers more productive and our pursuit of artificial general intelligence closer. In this paper, we introduce CodeGeeX, a multilingual model with 13 billion parameters for code generation. CodeGeeX is pre-trained on 850 billion tokens of 23 programming languages as of June 2022. Our extensive experiments suggest that CodeGeeX outperforms multilingual code models of similar scale for both the tasks of code generation and translation on HumanEval-X. Building upon HumanEval (Python only), we develop the HumanEval-X benchmark for evaluating multilingual models by hand-writing the solutions in C++, Java, JavaScript, and Go. In addition, we build CodeGeeX-based extensions on Visual Studio Code, JetBrains, and Cloud Studio, generating 4.7 billion tokens for tens of thousands of active users per week. Our user study demonstrates that CodeGeeX can help to increase coding efficiency for 83.4% of its users. Finally, CodeGeeX is publicly accessible and in Sep. 2022, we open-sourced its code, model weights (the version of 850B tokens), API, extensions, and HumanEval-X at https://github.com/THUDM/CodeGeeX.

The production of protein by alkali-solution and acid-isolation method will lead to the increase of salt in the feed liquid and affect its quality. In order to simplify the production of protein by the alkali acid precipitation process and obtain protein with high content and quality, the cation exchange resin was used to separate the walnut dreg protein. The desalination rate, protein content and recovery rate were used as indicators. Single factor experiments and response surface method were used to optimize the time used to isolate the protein from the cation exchange resin, the speed and temperature of the water bath shaker. Our results showed that the optimal time was determined at 62 min; the optimal speed of the water bath shaker was 120 rpm, and the optimal temperature was 49 °C. Under these conditions, the optimal protein recovery was 95.22% and the optimal protein content was 78.12%.

We introduce GLM-130B, a bilingual (English and Chinese) pre-trained language model with 130 billion parameters. It is an attempt to open-source a 100B-scale model at least as good as GPT-3 and unveil how models of such a scale can be successfully pre-trained. Over the course of this effort, we face numerous unexpected technical and engineering challenges, particularly on loss spikes and disconvergence. In this paper, we introduce the training process of GLM-130B including its design choices, training strategies for both efficiency and stability, and engineering efforts. The resultant GLM-130B model offers significant outperformance over GPT-3 175B on a wide range of popular English benchmarks while the performance advantage is not observed in OPT-175B and BLOOM-176B. It also consistently and significantly outperforms ERNIE TITAN 3.0 260B -- the largest Chinese language model -- across related benchmarks. Finally, we leverage a unique scaling property of GLM-130B to reach INT4 quantization, without quantization aware training and with almost no performance loss, making it the first among 100B-scale models. More importantly, the property allows its effective inference on 4$\times$RTX 3090 (24G) or 8$\times$RTX 2080 Ti (11G) GPUs, the most ever affordable GPUs required for using 100B-scale models. The GLM-130B model weights are publicly accessible and its code, training logs, related toolkit, and lessons learned are open-sourced at https://github.com/THUDM/GLM-130B ., Comment: 47 pages

Porous silicon nanoparticles are an promising platform for drug delivery due to their high surface area and biodegradability. However, conventional drug loading methods like physical adsorption always result in premature drug release. This thesis develops a novel strategy to use stimulus-cleavable linker to tether small molecule drug doxorubicin to the surface of porous silicon nanoparticles through covalent bonding, and linker cleavage only occurs in the presence of corresponding stimulus to enable drug release. The utilisation of stimuli-cleavable linkers was confirmed to realise stimuli-responsive drug release behaviour on porous silicon nanoparticles.

Recently, great effort has been devoted to the search for two-dimensional (2D) ferromagnetic materials with inherent strong Dzyaloshinskii--Moriya interaction (DMI). Here, through a first-principles approach, we systematically investigate the effect of biaxial strain on the DMI, the Heisenberg exchange interaction, and the magnetic anisotropy energy (MAE) of Janus Cr$_{2}$X$_{3}$Y$_{3}$ (X, Y = Cl, Br, I, X $\neq$ Y) monolayers. Both DMI and MAE can be significantly enhanced by tensile strain, while a reversal of the chirality of DMI in Cr$_{2}$Cl$_{3}$Br$_{3}$ and a switch of MAE from off-plane to in-plane in Cr$_{2}$I$_{3}$Cl$_{3}$ are induced by a compressive strain of $2\%$. Microscopically, DMI and MAE are associated mainly with the large spin--orbit coupling of the heavy nonmagnetic halogen atoms rather than that of the magnetic Cr atoms. In particular, the peculiar magnetic transition of Cr$_{2}$I$_{3}$Cl$_{3}$ is explained by competition between direct exchange and superexchange interactions. Micromagnetic simulations show that a small external magnetic field of 65~mT stabilizes a skyrmion with a diameter of 9.8~nm in the Cr$_2$I$_3$Cl$_3$ monolayer. Our results will provide guidance for further research on DMI and skyrmions in 2D Janus materials, as well as a basis for the potential applications in spintronic devices., Comment: 8 pages, 5 figures