An H5N1-based matrix protein 2 ectodomain tetrameric peptide vaccine provides cross-protection against lethal infection with H7N9 influenza virus

published_or_final_versio

Chemical characterization of PM2.5 from a southern coastal city of China:applications of modeling and chemical tracers in demonstrationof regional transport

An intensive sampling campaign of airborne fine particles (PM2.5) was conducted at Sanya, a coastal city in Southern China, from January to February 2012. Chemical analyses and mass reconstruction were used identify potential pollution sources and investigate atmospheric reaction mechanisms. A thermodynamic model indicated that low ammonia and high relative humidity caused the aerosols be acidic and that drove heterogeneous reactions which led to the formation of secondary inorganic aerosol. Relationships among neutralization ratios, free acidity, and air-mass trajectories suggest that the atmosphere at Sanya was impacted by both local and regional emissions. Three major transport pathways were identified, and flow from the northeast (from South China) typically brought the most polluted air to Sanya. A case study confirmed strong impact from South China (e.g., Pearl River Delta region) (contributed 76.8% to EC, and then this result can be extended to primary pollutants) when the northeast winds were dominant. The Weather Research Forecasting Black carbon model and trace organic markers were used to apportion local pollution versus regional contributions. Results of the study offer new insights into the atmospheric conditions and air pollution at this coastal city

Modeling, Oscillation Analysis and Distributed Stabilization Control of Autonomous PV-based Microgrids

Driven by rising energy demand and the goal of carbon neutrality, renewable energy generations (REGs), especially photovoltaic (PV) generations, are widely used in the urban power energy systems. While the intelligent control of microgrids (MG) brings economic and efficient operation, its potential stability problem cannot be ignored. To date, most of the research on modeling, analyzing and enhancing the stability of MG usually assume the DC-link as an ideal voltage source. However, this practice of ignoring the dynamics of DC-link may omit the latent oscillation phenomena of autonomous PV-based MG. First, this paper establishes a complete dynamic model of autonomous PV-based MG including PV panels and DC-link. Different from previous conclusions of idealizing DC-link dynamics, participation factor analysis finds the potential impact of DC-link dynamics on system dynamic performance, and different influence factors including critical control parameters and non-linear V-I output characteristic of PV array are considered to further reveal oscillation mechanisms. Second, based on the average consensus algorithm, a distributed stabilization controller with strong robustness is proposed to enhance stability of the PV-based MG, which does not affect the steady-state performance of the system. Finally, the correctness of all theoretical analysis and the effectiveness of the proposed controller are verified by time domain simulation and hardware-in-loop tests.10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 51907031

Engineering a BCR-ABL-activated caspase for the selective elimination of leukemic cells.

Increased understanding of the precise molecular mechanisms involved in cell survival and cell death signaling pathways offers the promise of harnessing these molecules to eliminate cancer cells without damaging normal cells. Tyrosine kinase oncoproteins promote the genesis of leukemias through both increased cell proliferation and inhibition of apoptotic cell death. Although tyrosine kinase inhibitors, such as the BCR-ABL inhibitor imatinib, have demonstrated remarkable efficacy in the clinic, drug-resistant leukemias emerge in some patients because of either the acquisition of point mutations or amplification of the tyrosine kinase, resulting in a poor long-term prognosis. Here, we exploit the molecular mechanisms of caspase activation and tyrosine kinase/adaptor protein signaling to forge a unique approach for selectively killing leukemic cells through the forcible induction of apoptosis. We have engineered caspase variants that can directly be activated in response to BCR-ABL. Because we harness, rather than inhibit, the activity of leukemogenic kinases to kill transformed cells, this approach selectively eliminates leukemic cells regardless of drug-resistant mutations

Phosphatidylinositol Transfer Protein-α in platelets is inconsequential for thrombosis yet is utilized for tumor metastasis

Platelets are increasingly recognized for their contributions to tumor metastasis. Here, we show that the phosphoinositide signaling modulated by phosphatidylinositol transfer protein type α (PITPα), a protein which shuttles phosphatidylinositol between organelles, is essential for platelet-mediated tumor metastasis. PITPα-deficient platelets have reduced intracellular pools of phosphoinositides and an 80% reduction in IP3 generation upon platelet activation. Unexpectedly, mice lacking platelet PITPα form thrombi normally at sites of intravascular injuries. However, following intravenous injection of tumor cells, mice lacking PITPα develop fewer lung metastases due to a reduction of fibrin formation surrounding the tumor cells, rendering the metastases susceptible to mucosal immunity. These findings demonstrate that platelet PITPα-mediated phosphoinositide signaling is inconsequential for in vivo hemostasis, yet is critical for in vivo dissemination. Moreover, this demonstrates that signaling pathways within platelets may be segregated into pathways that are essential for thrombosis formation and pathways that are important for non-hemostatic functions

Short-Term Wind Power Prediction Based on Data Decomposition and Combined Deep Neural Network

A hybrid short-term wind power prediction model based on data decomposition and combined deep neural network is proposed with the inclusion of the characteristics of fluctuation and randomness of nonlinear signals, such as wind speed and wind power. Firstly, the variational mode decomposition (VMD) is used to decompose the wind speed and wind power sequences in the input data to reduce the noise in the original signal. Secondly, the decomposed wind speed and wind power sub-sequences are reconstructed into new data sets with other related features as the input of the combined deep neural network, and the input data are further studied for the implied features by convolutional neural network (CNN), which should be passed into the long and short-term memory neural network (LSTM) as input for prediction. At the same time, the improved particle swarm optimization algorithm (IPSO) is adopted to optimize the parameters of each prediction model. By superimposing each predicted sub-sequence, the predicting wind power could be obtained. Simulations based on a short-term power prediction in different months with huge weather differences is carried out for a wind farm in Guangdong, China. The simulated results validate that the proposed model has a high prediction accuracy and generalization ability.Guangdong-Guangxi Joint Foundation of China: Research on Distributed Optimal Control of Renewable Multi-microgrids based on the Integration of Multi-Agent Dynamic Game and Prediction Mechanism [Project Number 2021A1515410009]

Electricity trading based on distribution locational marginal price

Department of Finance and Education of Guangdong Province; Education Department of Guangdong Province; Brunel University Londo

An M2e-based multiple antigenic peptide vaccine protects mice from lethal challenge with divergent H5N1 influenza viruses

<p>Abstract</p> <p>Background</p> <p>A growing concern has raised regarding the pandemic potential of the highly pathogenic avian influenza (HPAI) H5N1 viruses. Consequently, there is an urgent need to develop an effective and safe vaccine against the divergent H5N1 influenza viruses. In the present study, we designed a tetra-branched multiple antigenic peptide (MAP)-based vaccine, designated M2e-MAP, which contains the sequence overlapping the highly conserved extracellular domain of matrix protein 2 (M2e) of a HPAI H5N1 virus, and investigated its immune responses and cross-protection against different clades of H5N1 viruses.</p> <p>Results</p> <p>Our results showed that M2e-MAP vaccine induced strong M2e-specific IgG antibody responses following 3-dose immunization of mice with M2e-MAP in the presence of Freunds' or aluminium (alum) adjuvant. M2e-MAP vaccination limited viral replication and attenuated histopathological damage in the challenged mouse lungs. The M2e-MAP-based vaccine protected immunized mice against both clade1: VN/1194 and clade2.3.4: SZ/406H H5N1 virus challenge, being able to counteract weight lost and elevate survival rate following lethal challenge of H5N1 viruses.</p> <p>Conclusions</p> <p>These results suggest that M2e-MAP presenting M2e of H5N1 virus has a great potential to be developed into an effective subunit vaccine for the prevention of infection by a broad spectrum of HPAI H5N1 viruses.</p