LAG3 is the most promising immune checkpoint next to PD-1 and CTLA-4. High LAG3 and FGL1 expression boosts tumor growth by inhibiting the immune microenvironment. This review comprises four sections ...presenting the structure/expression, interaction, biological effects, and clinical application of LAG3/FGL1. D1 and D2 of LAG3 and FD of FGL1 are the LAG3-FGL1 interaction domains. LAG3 accumulates on the surface of lymphocytes in various tumors, but is also found in the cytoplasm in non-small cell lung cancer (NSCLC) cells. FGL1 is found in the cytoplasm in NSCLC cells and on the surface of breast cancer cells. The LAG3-FGL1 interaction mechanism remains unclear, and the intracellular signals require elucidation. LAG3/FGL1 activity is associated with immune cell infiltration, proliferation, and secretion. Cytokine production is enhanced when LAG3/FGL1 are co-expressed with PD-1. IMP321 and relatlimab are promising monoclonal antibodies targeting LAG3 in melanoma. The clinical use of anti-FGL1 antibodies has not been reported. Finally, high FGL1 and LAG3 expression induces EGFR-TKI and gefitinib resistance, and anti-PD-1 therapy resistance, respectively. We present a comprehensive overview of the role of LAG3/FGL1 in cancer, suggesting novel anti-tumor therapy strategies.
Cross-species transmission of viruses from wildlife animal reservoirs poses a marked threat to human and animal health
. Bats have been recognized as one of the most important reservoirs for emerging ...viruses and the transmission of a coronavirus that originated in bats to humans via intermediate hosts was responsible for the high-impact emerging zoonosis, severe acute respiratory syndrome (SARS)
. Here we provide virological, epidemiological, evolutionary and experimental evidence that a novel HKU2-related bat coronavirus, swine acute diarrhoea syndrome coronavirus (SADS-CoV), is the aetiological agent that was responsible for a large-scale outbreak of fatal disease in pigs in China that has caused the death of 24,693 piglets across four farms. Notably, the outbreak began in Guangdong province in the vicinity of the origin of the SARS pandemic. Furthermore, we identified SADS-related CoVs with 96-98% sequence identity in 9.8% (58 out of 591) of anal swabs collected from bats in Guangdong province during 2013-2016, predominantly in horseshoe bats (Rhinolophus spp.) that are known reservoirs of SARS-related CoVs. We found that there were striking similarities between the SADS and SARS outbreaks in geographical, temporal, ecological and aetiological settings. This study highlights the importance of identifying coronavirus diversity and distribution in bats to mitigate future outbreaks that could threaten livestock, public health and economic growth.
•Identify and analyze Cco-evolved interaction network in allosteryic regulation and energy transduction of AKIII identified.•Interaction network analysis of the R- and T-states of AKIII reveals ...rearrangement.•Interfacial interaction network is key for conducting allosteric energy transduction.•Mutations verified key residues of the co-evolved network of energy transduction.
Understanding co-evolved interaction network involved in allosteric regulation of kinase is of fundamental interest. Here, with aspartokinase III (AKIII) from E. coli as a model system the rearrangement of side-chain interactions upon inhibitor binding are identified by comparing amino acid interaction networks for both the R- and T-states of AKIII. Steered molecular dynamics simulation is then applied to study the dynamic conformational change and the energy transduction process, which is followed by identification of co-evolved interaction network involved in the allosteric regulation. To verify the co-evolved allo-network, mutations of AKIII are examined and modulation of the allosteric regulation is demonstrated by site-directed mutagenesis of the key residues. As illustrated, this study proposes a strategy to identify the co-evolved interaction network that drives the allosteric process. The key feature of the strategy is that key residues involved in the energy transfer pathway can be quickly determined by co-evolutionary analysis of the interfacial interactions of motifs.
Electrical contact to low-dimensional (low-D) materials is a key to their electronic applications. Traditional metal contacts to low-D semiconductors typically create gap states that can pin the ...Fermi level (E F). However, low-D metals possessing a limited density of states at E F can enable gate-tunable work functions and contact barriers. Moreover, a seamless contact with native bonds at the interface, without localized interfacial states, can serve as an optimal electrode. To realize such a seamless contact, one needs to develop atomically precise heterojunctions from the atom up. Here, we demonstrate an all-carbon staircase contact to ultranarrow armchair graphene nanoribbons (aGNRs). The coherent heterostructures of width-variable aGNRs, consisting of 7, 14, 21, and up to 56 carbon atoms across the width, are synthesized by a surface-assisted self-assembly process with a single molecular precursor. The aGNRs exhibit characteristic vibrational modes in Raman spectroscopy. A combined scanning tunneling microscopy and density functional theory study reveals the native covalent-bond nature and quasi-metallic contact characteristics of the interfaces. Our electronic measurements of such seamless GNR staircase constitute a promising first step toward making low resistance contacts.
•A spark-based parallel dynamic programming (SPDP) method is proposed.•A spark-based parallel particle swarm optimization (SPPSO) method is proposed.•Simulation experiments of the two methods are ...performed on the cloud computing.•The parallel performance of SPDP and SPPSO are investigated.•Results verify the performance of DP is better than PSO via parallel cloud computing.
The joint optimal operation of a large-scale reservoir system is a complex optimization problem with high-dimensional, multi-stage, and nonlinear features. As the number of reservoirs and discrete states increase, the runtime of optimal operation model increases exponentially, leading to the phenomenon of “curse of dimensionality”. Traditional multi-core parallel computing can improve the efficiency to a certain extent, but it is difficult to expand and break through the hardware limitation, which is not suitable for the optimization of the large-scale reservoir system and its refined management. Different from the current literature about reservoir operations that focus on the comparisons of dynamic programming (DP) with particle swarm optimization (PSO) algorithm in serial mode, this paper pays emphasis on a comparison study of parallel DP with parallel PSO via cloud computing. This study proposes the spark-based parallel dynamic programming (SPDP) and spark-based parallel particle swarm optimization (SPPSO) methods via cloud computing. Taking the cascade eight-reservoir system in the Yuanshui basin in China as an example, simulation experiments are carried out for the comparison between SPDP and SPPSO in terms of parallel performance, precision, efficiency, and stability. The results are as follows: (1) The parallel performance of SPDP in the cloud environment is better than SPPSO. (2) Under the same runtime, the precision of SPDP is generally higher than that of SPPSO. (3) Setting the same precision, the runtime of SPPSO is on average 255.18% longer than SPDP, and it does not reach the precision of SPDP. (4) SPPSO has a fast convergence speed and the ability to jump out of the local optimal solution, but its precision increases by 0.41%, while the runtime increases by 229.55% with the increase of iterations. DP solves more accurately and efficiently than PSO via parallel cloud computing, which ensures the global search capability of the algorithm. Moreover, cloud computing is flexible, economical, and safe, with high practical value and application prospects.
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•Propose a coordinated optimization framework for hydro-PV hybrid systems.•Develop a multi-objective optimization model for long-term complementary operation.•Design a parallel ...GFM-MOEA algorithm to search Pareto optimal solutions.•Propose a novel SMAA-FOS model for robust decision-making.•Make a risk-informed complementary operation strategy with higher reliabilities.
Hydropower system is a crucial support for the integration of various renewable energy sources. The integration of dispatchable hydropower and non-dispatchable photovoltaic (PV) power is promising to achieve efficient resource use. This paper proposes a coordinated optimization framework for the long-term complementary operation of large-scale hydro-PV hybrid systems. A multi-objective optimization model is established that simultaneously optimizes the economic benefit and operational safety of the hybrid system, i.e., the quantity and quality of the joint power output. The proposed model decouples hydropower and PV power in time scales to maintain calculation accuracy and reduce problem dimensions. A parallel generic front modeling-based multi-objective evolutionary algorithm (GFM-MOEA) is designed to produce a well-converged and well-distributed set of Pareto optimal solutions. Also, we develop a novel robust decision-making model to evaluate, rank and select the Pareto optimal solutions, which allows potential uncertainties in input data to be considered. The proposed framework is applied to the Longyangxia hydro-PV hybrid power system, which is the largest hydro-PV power plant in the world. Several numerical experiments are conducted to examine the hydrological effect on multi-objective optimization as well as the effect of uncertainty levels on robust decision-making. The results show that: (1) a clear competing relationship exists between total generated power and stability of the joint power output; (2) hydropower can compensate for the PV power, mainly when the solar radiation is limited while the abundant water resource is available due to rainfalls; (3) hydrological regimes have significant impacts on the multi-objective optimization results and the complementary effect; (4) the robust decision-making model enhances the reliability of the risk-informed complementary operation strategy by measuring the robustness and uncertainty of the decision.
The L-tryptophan (Trp) biosynthesis pathway is highly regulated at multiple levels. The three types of regulations identified so far, namely repression, attenuation, and feedback inhibition have ...greatly impacted our understanding and engineering of cellular metabolism. In this study, feed-forward regulation is discovered as a novel regulation of this pathway and explored for engineering Escherichia coli for more efficient Trp biosynthesis. Specifically, indole glycerol phosphate synthase (IGPS) of the multifunctional enzyme TrpC from E. coli is found to be feed-forward inhibited by anthranilate noncompetitively. Surprisingly, IGPS of TrpC from both Saccharomyces cerevisiae and Aspergillus niger was found to be feed-forward activated, for which the glutamine aminotransferase domain is essential. The anthranilate binding site of IGPS from E. coli is identified and mutated, resulting in more tolerant variants for improved Trp biosynthesis. Furthermore, expressing the anthranilate-activated TrpC from A. niger in a previously engineered Trp producing E. coli strain S028 made the strain more robust in growth and more efficient in Trp production in bioreactor. It not only increased the Trp concentration from 19 to 29 g/L within 42 h, but also improved the maximum Trp yield from 0.15 to 0.18 g/g in simple fed-batch fermentations, setting a new level to rationally designed Trp producing strains. The findings are of fundamental interest for understanding and re-designing dynamics and control of metabolic pathways in general and provide a novel target and solution to engineering of E. coli for efficient Trp production particularly.
•Discovery of a novel feed-forward regulation in tryptophan biosynthesis.•IGPS in the multifunctional enzyme TrpC can be inhibited or activated by anthranilate.•Anthranilate-activated TrpC significantly increases Trp productivity and yield.•Multiplicity experimentally observed for the first time and overcome by proper design.
Phosphoserine aminotransferase (SerC) from Escherichia coli (E. coli) MG1655 is engineered to catalyze the deamination of homoserine to 4‐hydroxy‐2‐ketobutyrate, a key reaction in producing ...1,3‐propanediol (1,3‐PDO) from glucose in a novel glycerol‐independent metabolic pathway. To this end, a computation‐based rational approach is used to change the substrate specificity of SerC from l‐phosphoserine to l‐homoserine. In this approach, molecular dynamics simulations and virtual screening are combined to predict mutation sites. The enzyme activity of the best mutant, SerCR42W/R77W, is successfully improved by 4.2‐fold in comparison to the wild type when l‐homoserine is used as the substrate, while its activity toward the natural substrate l‐phosphoserine is completely deactivated. To validate the effects of the mutant on 1,3‐PDO production, the “homoserine to 1,3‐PDO” pathway is constructed in E. coli by coexpression of SerCR42W/R77W with pyruvate decarboxylase and alcohol dehydrogenase. The resulting mutant strain achieves the production of 3.03 g L−1 1,3‐PDO in fed‐batch fermentation, which is 13‐fold higher than the wild‐type strain and represents an important step forward to realize the promise of the glycerol‐independent synthetic pathway for 1,3‐PDO production from glucose.
1,3‐Propanediol (1,3‐PDO) is an important chemical compound with many applications in polymers and cosmetics industries. In this study, the authors use a computation‐based rational approach to change the substrate specificity of phosphoserine aminotransferase from l‐phosphoserine to l‐homoserine, achieving the production of 3.03 g l−1 1,3‐PDO in fed‐batch fermentation. This study represents an important step forward to realize the potential of the glycerol‐independent synthetic pathway for 1,3‐PDO production from glucose.
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