The Asp-His-His and Asp-His-His-associated (DHH/DHHA1) domain-containing phosphodiesterases (PDEs) that catalyze degradation of cyclic di-adenosine monophosphate (c-di-AMP) could be subdivided into two subfamilies based on the final product [5'-phosphadenylyl-adenosine (5'-pApA) or AMP]. In a previous study, we revealed that Rv2837c, a stand-alone DHH/DHHA1 PDE, employs a 5'-pApA internal flipping mechanism to produce AMPs. However, why the membrane-bound DHH/DHHA1 PDE can only degrade c-di-AMP to 5'-pApA remains obscure. Here, we report the crystal structure of the DHH/DHHA1 domain of GdpP (GdpP-C), and structures in complex with c-di-AMP, cyclic di-guanosine monophosphate (c-di-GMP), and 5'-pApA. Structural analysis reveals that GdpP-C binds nucleotide substrates quite differently from how Rv2837c does in terms of substrate-binding position. Accordingly, the nucleotide-binding site of the DHH/DHHA1 PDEs is organized into three (C, G, and R) subsites. For GdpP-C, in the C and G sites c-di-AMP binds and degrades into 5'-pApA, and its G site determines nucleotide specificity. To further degrade into AMPs, 5'-pApA must slide into the C and R sites for flipping and hydrolysis as in Rv2837c. Subsequent mutagenesis and enzymatic studies of GdpP-C and Rv2837c uncover the complete flipping process and reveal a unified catalytic mechanism for members of both DHH/DHHA1 PDE subfamilies.

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Accelerating the photogenerated carrier separation of semiconductor photocatalysts is still a big challenge to developing highly effective hydrogen evolution reaction (HER) systems. Here, a novel ternary photocatalytic system of Cu 2 ZnSnS 4 nanocrystals/Ag clusters/conducting polyaniline (CZTS/Ag/PANI) was successfully synthesized via a facile solvothermal and hydrothermal method for the first time. PANI, serving as the support, efficiently prevents the aggregating of the Cu 2 ZnSnS 4 and Ag clusters, so CZTS nanocrystals (30−50 nm) and Ag clusters (2−5 nm) disperse equally in macromolecule PANI. PANI with an extended πconjugated electron system and Ag clusters with a plasmon resonance effect are used as sensitizers/cocatalysts to enhance the light absorption and electrical conductivity and excite the separation of photogenerated electron and hole pairs. As expected, the CZTS/Ag/PANI heterostructured photocatalyst exhibits significantly enhanced photocatalytic activity for hydrogen evolution from water splitting in the presence of visible light. The optimal hydrogen evolution rate over CZTS/Ag/ PANI with the apparent quantum yield (AQE) ∼ 30.5% at 450 nm is 859.6 μmol h −1 , which is also higher than previously reported for CZTS-based photocatalysts. Recycling experiments confirm that the CZTS/Ag/PANI composite exhibits remarkably stable photocatalytic performance and can be reused in four successive cycles. This research indicates that the application of Ag nanoclusters and the PANI semiconductor as a cocatalyst can provide a new approach to designing and synthesizing stable and high efficiency CZTS-based visible-light-induced photocatalysts.

The equipment in railway station is complicated and diverse, and the health status assessment and prediction of equipment is crucial to the safe and stable operation of stations. Graph Neural Networks (GNNs) effectively combine graph data with deep learning technology, which has stronger data and knowledge representation capability and can efficiently handle some non-Euclidean spatial data problems with irregular station equipment associated network structure. Based on this, this paper takes the automatic gate machine and X-ray security checker as an example and proposes a health status assessment and prediction scheme for railway passenger station equipment based on Graph Long Short-Term Memory (G-LSTM) neural network. This paper first analyzes the main factors affecting the health status of passenger station equipment, as well as the correlation between the equipment. Then, the initial graph network structure of the passenger station equipment is constructed, and the G-LSTM model is used to evaluate and predict the health status of the passenger station equipment. Finally, this paper takes the automatic gate machine and X-ray security checker of a high-speed railway station in Beijing as an example to verify the proposed method. The experimental results show that all evaluation metrics perform well, indicating that the G-LSTM model has high accuracy in assessing and predicting the health status of automatic gate machine and X-ray security checker. This paper realizes the health status assessment and prediction of railway passenger station equipment, which can provide some reference for the Prognostics and Health Management (PHM) of equipment in railway stations.

4-1BB (CD137, TNFSF9) is a promising co-stimulatory signaling mediator of T cells and NK cells, and agonistic monoclonal antibodies targeting 4-1BB are under clinical investigations aiming to observe sufficient and prolonged anti-tumor efficacy. However, these trials have resulted in limited efficacy or safety, and different bispecific approaches are being explored to improve the profiles. BH3120, a bivalent bispecific antibody generated by Pentambody(TM) platform targeting 4-1BB and PD-L1 simultaneously, demonstrates strong and prolonged antitumor efficacy as monotherapy in in vivo studies, and favorable safety profiles up to 200mg/kg/dose in non-human primates. Moreover, combination of BH3120 with an immune checkpoint inhibitor shows synergistically enhanced anti-tumor efficacy. Supported by these results, IND enabling studies of BH3120 are on-going and clinical evaluations are planned from later in 2022. Citation Format: Jiangcheng Xu, Yang Liu, Jing Wang, Fei Fan, Haitao Gu, Lanxin Zhang, Jun Wang, Ding Song, Ailong Guo, Hongjuan Zhang, Kaixuan Su, Jiaojiao Su, Lijuan Li, Jingmei Cai, Aihong Zhang, Jiawang Liu, Kyoungwoo Lee. BH3120: A novel bispecific antibody targeting 4-1BB and PD-L1 with well balanced efficacy and safety profiles [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5605.