Background Heterologous prime-boost with ChAdOx1 nCoV-19 vector vaccine (ChAd) and a messenger RNA vaccine (BNT or mRNA-1273) has been widely facilitating mass coronavirus disease 2019 (COVID-19) immunisation. This review aimed to synthesize immunogenicity and reactogenicity of heterologous immunisations with ChAd and BNT (mRNA-1273) vaccine compared with homologous ChAd or BNT (mRNA-1273) immunisation. Methods PubMed, Web of Science, and Embase databases were searched from inception to March 7, 2022. Immunogenicity involving serum antibodies against different SAS-CoV-2 fragments, neutralizing antibody, or spike-specific T cells response were compared. Any, local and systemic reactions were pooled by meta-analysis for comparison. Results Of 14,571 records identified, 13 studies (3024 participants) were included for analysis. Compared with homologous BNT/BNT vaccination, heterologous ChAd/BNT schedule probably induced noninferior anti-spike protein while higher neutralizing antibody and better T cells response. Heterologous ChAd/BNT (mRNA-1273) immunisation induced superior anti-spike protein and higher neutralizing antibody and better T cells response compared with homologous ChAd/ChAd vaccination. Heterologous ChAd/BNT (mRNA-1273) had similar risk of any reaction (RR = 1.30, 95% CI: 0.86−1.96) while higher risk of local reactions (RR = 1.65, 95% CI: 1.27−2.15) and systemic reactions (RR = 1.49, 95% CI: 1.17−1.90) compared with homologous ChAd/ChAd vaccination. There was a higher risk of local reactions (RR = 1.16, 95% CI: 1.03−1.31) in heterologous ChAd/BNT (mRNA-1273) vaccination compare with homologous BNT/BNT but a similar risk of any reaction (RR = 1.03, 95% CI: 0.79−1.34) and systemic reactions (RR = 0.89, 95% CI: 0.60−1.30). Conclusions Heterologous ChAd/BNT schedule induced at least comparable immunogenicity compared with homologous BNT/BNT and better immunogenicity compared with homologous ChAd/ChAd vaccination. The synthetical evidence supported the general application of heterologous prime-boost vaccination using ChAd and BNT COVID-19 vaccines. Graphical Abstract

Aptamers are emerging as promising molecular tools in cancer-targeted theranostics. Improving their in vivo stability has been a critical issue in promoting clinical translation, but such efforts could lead to more serious side effects resulting from prolonged retention in healthy organs. To address this problem, we developed an environment-responsive stabilization strategy for the selective enhancement of aptamer biostability in the tumor microenvironment (TME). Briefly, by means of the end extension of an ATP-responsive protection (ARP) module, the designed aptamer could be protected from nuclease degradation through the specific incorporation of ATP. Based on our in vivo results, this ARP-aptamer probe was effectively accumulated in tumors via aptamer-based molecular recognition. It showed selectively prolonged tumor retention time, but rapid digestion in healthy organs. Our strategy should provide a new paradigm for the development of organ-specific nucleic acid-based imaging and therapeutic agents.

Intentional islanding is an effective approach to avoid large-area blackouts and minimize outage losses through making full use of renewable energy sources. This paper proposes a novel strategy based on node electrical relevance and artificial bee colony algorithm. The node electrical relevance is defined with equivalent electrical distance and traditional line weight, which can reflect the electrical characteristics of power systems, differentiating the proposed strategy from most existing strategies which are based on graph theory. The artificial bee colony (ABC) algorithm employed has fewer control parameters, strong robustness, and high accuracy; therefore, more loads can be incorporated into islands and restored. The constraints of load priority, load controllability, line capacity, and stable operation requirements of power systems are considered to tally with the actual distribution networks. The strategy is tested using the IEEE 69-bus distribution system and compared with other strategies from the literature. The simulation results demonstrate that the proposed strategy is more feasible and efficient.

Chemically synthetic receptors that establish cells a new sense-and-respond capability to interact with outer worlds are highly desired, but rarely reported. In this work, we develop a membrane-anchored synthetic receptor (Ts-pHLIP-Pr) using DNA and peptide as the building block to equip cells with artificial signaling pathways. Upon sensing external pH stimuli, the Pr module can be translocated across the cell membrane via the conformation switch of pHLIP, enabling membrane-proximal recruitment of specific proteins to trigger downstream signaling cascades. Our experimental results demonstrate the capability of Ts-pHLIP-Pr for regulating PKCε-related signaling events upon responding to external pH reduction. With a modular feature, this receptor can be extended to elicit T cell activation through low-pH environment-induced directional movement of cytoplasmic ZAP70. Our work is expected to offer a new paradigm for intelligent synthetic biology and customized cell engineering.

We consider a nonzero-sum stochastic differential portfolio game problem in a continuous-time Markov regime switching environment when the price dynamics of the risky assets are governed by a Markov-modulated geometric Brownian motion (GBM). The market parameters, including the bank interest rate and the appreciation and volatility rates of the risky assets, switch over time according to a continuous-time Markov chain. We formulate the nonzero-sum stochastic differential portfolio game problem as two utility maximization problems of the sum process between two investors’ terminal wealth. We derive a pair of regime switching Hamilton-Jacobi-Bellman (HJB) equations and two systems of coupled HJB equations at different regimes. We obtain explicit optimal portfolio strategies and Feynman-Kac representations of the two value functions. Furthermore, we solve the system of coupled HJB equations explicitly in a special case where there are only two states in the Markov chain. Finally we provide comparative statics and numerical simulation analysis of optimal portfolio strategies and investigate the impact of regime switching on optimal portfolio strategies.