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In situ depot gel is a type of polymeric long-acting injectable (pLAI) drug delivery system; compared to microsphere technology, its preparation process is simpler and more conducive to industrialization. To ensure the chemical stability of peptide ACTY116, we avoided the use of harsh conditions such as high temperatures, high shear mixing, or homogenization; maintaining a water-free and oxygen-free environment was also critical to prevent hydrolysis and oxidation. Molecular dynamics (MDs) simulations were employed to assess the stability mechanism between ACTY116 and the pLAI system. The initial structure of ACTY116 with an alpha helix conformation was constructed using SYBYL-X, and the copolymer PLGA was generated by AMBER 16; results showed that PLGA-based in situ depot gel improved conformational stability of ACTY116 through hydrogen bonds formed between peptide ACTY116 and the components of the pLAI formulation, while PLGA (Poly(DL-lactide-co-glycolide)) also created steric hindrance and shielding effects to prevent conformational changes. As a result, the chemical and conformational stability and in vivo long-acting characteristics of ACTY116 ensure its enhanced efficacy. In summary, we successfully achieved our objective of developing a highly stable peptide-loaded long-acting injectable (LAI) in situ depot gel formulation that is stable for at least 3 months under harsh conditions (40 °C, above body temperature), elucidating the underlying stabilisation mechanism, and the high stability of the ACTY116 pLAI formulation creates favourable conditions for its in vivo pharmacological activity lasting for weeks or even months. [ABSTRACT FROM AUTHOR]

Mevalonate kinase (MevK) is an important enzyme in the mevalonate pathway that catalyzes the phosphorylation of mevalonate into phosphomevalonate and is involved in juvenile hormone biosynthesis. Herein, we present a structure model of MevK from the red flour beetle Tribolium castaneum (TcMevK), which adopts a compact α/β conformation that can be divided into two parts: an N-terminal domain and a C-terminal domain. A narrow, deep cavity accommodating the substrate and cofactor was observed at the junction between the two domains of TcMevK. Computational simulation combined with site-directed mutagenesis and biochemical analyses allowed us to define the binding mode of TcMevK to cofactors and substrates. Moreover, TcMevK showed optimal enzyme activity at pH 8.0 and an optimal temperature of 40 °C for mevalonate as the substrate. The expression profiles and RNA interference of TcMevK indicated its critical role in controlling juvenile hormone biosynthesis, as well as its participation in the production of other terpenoids in T. castaneum. These findings improve our understanding of the structural and biochemical features of insect Mevk and provide a structural basis for the design of MevK inhibitors. [ABSTRACT FROM AUTHOR]

[Objective] A lightweight SE-PPM algorithm (SAPMDSNet) was proposed to solve the problems of slow speed, misclassification and difficulty in feature extraction in traditional positive and subgroup classification of natural state tobacco leaves. [Method] Based on the lightweight ShuffleNetV2 net-work, the training speed of the network model was accelerated by reducing the network convolution depth and evolving the activation function. Then, the channel attention SE module was introduced to enhance the haracteristic differences between channels, improve the representation ability of the network model and a-void the group misclassification caused by the regionalization. Finally, the pyramid pooling module PPM was embedded to integrate the exposure characters and global information by aggregating context information, and the in-house tobacco leaf data set was used and compared with other models. [Result] The SAPMDSNet network model achieved relatively high classification results with accuracy of 91.09% and FLOPs of 151.70 M. Compared with the original ShuffleNetV2 model and the lightweight GhostNet model, the FLOPs were slightly increased by 2.65% and 2.84%, and the accuracy was increased by 2.72% and 21.13 %, respectively. MobileNetV2, DenseNet and SqueezeNet achieved recognition accuracies of 87.02%, 89.53% and 87.60%, which were close to the proposed model, but their FLOPs were significantly higher. [Conclusion] The constructed SAPMDSNet network model improved the classification accuracy of positive and sub-group tobacco leaves in natural state with better overall performance, which provides a new method for primary screening of tobacco leaves. [ABSTRACT FROM AUTHOR]

Regulating the structural and interfacial properties of transition metal phosphides (TMPs) by coupling carbon-based materials with large surface areas to enhance hydrogen evolution reaction (HER) performance presents significant progress for water splitting technology. Herein, we constructed a composite substrate of a three-dimensional porous graphene oxide matrix (3D-GO) embedded in nickel foam (NF) to grow a Co2P electrocatalyst. Well-defined gladiolus-like Co2P nanowire arrays tightly anchored on the substrate show enhanced electrochemical characteristics for the hydrogen evolution reaction (HER) based on the promoting roles of 3D porous reduced GO (3D-rGO) derived from 3D-GO, which promotes the dispersion of active components, improves the rate of electron transfer, and facilitates the transport of water molecules. As a result, the obtained Co2P@3D-rGO/NF electrode exhibits superior HER activity in 1.0 M KOH media, achieving overpotentials of 36.5 and 264.7 mV at current densities of 10 and 100 mA cm−2, respectively. The electrode also has a low Tafel slope of 55.5 mV dec−1, a large electrochemical surface area, and small charge-transfer resistance, further revealing its mechanism of high intrinsic activity. Moreover, the electrode exhibits excellent HER stability and durability without surface morphology and chemical state changes. [ABSTRACT FROM AUTHOR]