Biomedical applications of mRNA nanomedicine

As an attractive alternative to plasmid DNA, messenger RNA (mRNA) has recently emerged as a promising class of nucleic acid therapeutics for biomedical applications. Advances in addressing the inherent shortcomings of mRNA and in the development of nanoparticle-based delivery systems have prompted the development and clinical translation of mRNA-based medicines. In this review, we discuss the chemical modification strategies of mRNA to improve its stability, minimize immune responses, and enhance translational efficacy. We also highlight recent progress in nanoparticle-based mRNA delivery. Considerable attention is given to the increasingly widespread applications of mRNA nanomedicine in the biomedical fields of vaccination, protein-replacement therapy, gene editing, and cellular reprogramming and engineering.     

Regulation of Polymer Configurations Enables Green Solvent-Processed Large-Area Binary All-Polymer Solar Cells With Breakthrough Performance and High Efficiency Stretchability Factor

With the great potential of the all-polymer solar cells for large-area wearable devices, both large-area device efficiency and mechanical flexibility are very critical but attract limited attention. In this work, from the perspective of the polymer configurations, two types of terpolymer acceptors PYTX-A and PYTX-B (X = Cl or H) are developed. The configuration difference caused by the replacement of non-conjugated units results in distinct photovoltaic performance and mechanical flexibility. Benefiting from a good match between the intrinsically slow film-forming of the active materials and the technically slow film-forming of the blade-coating process, the toluene-processed large-area (1.21 cm²) binary device achieves a record efficiency of 14.70%. More importantly, a new parameter of efficiency stretchability factor (ESF) is proposed for the first time to comprehensively evaluate the overall device performance. PM6:PYTCl-A and PM6:PYTCl-B yield significantly higher ESF than PM6:PY-IT. Further blending with non-conjugated polymer donor PM6-A, the best ESF of 3.12% is achieved for PM6-A:PYTCl-A, which is among the highest comprehensive performances.     

The "new science" of wetland restoration

The intricate workings of natural wetlands are slowly yielding their secrets to scientists applying a number of experimental approaches.     

Effect of Elastic Energy due to Atomic Size Factor on Ordering and Decomposition Behaviour of Binary Solid Solutions

A theory recently developed by the present authors is applied to the study of the effect of elastic energy due to atomic size factor on the transformation behaviour of binary solid solutions. lt is found that elastic interaction energy (EIE), which is a part of the total elastic energy plays a key role in both ordering elastic interaction ordering (EIO) and spinodal decomposition. The present study gives a reasonable explanation to the historical dilemmas, "elastic energy paradox" and "atomic size factor paradox . By solving these confusing problems, the coexistence of ordering (EIO) and decomposition, which has been regarded as impossible by conventional theories. can be well understood. The mechanism is as follows: lowering of elastic energy demands EIO, and such an ordering provides a driving force for spinodal decomposition. Therefore, in alloys with large atomic size factor, spinodal decomposition is preceded and induced by ordering. Ordering and spinodal decomposition are thus closely related processes to each other     

Free energy perturbation approach for the rational engineering of the antibody for human hepatitis B virus

HzKR127 is the humanized monoclonal antibody effective for the neutralization of human hepatitis B virus. By means of the free energy perturbation (FEP) calculations based on molecular dynamic (MD) simulations, we examine the mutation-induced variations in the energetic and structural features associated with the interactions between HzKR127 and its antigen. N58A, Y96A, D97A, and D97A/Y102A mutants of HzKR127 are taken in account in this study for which the experimental data for relative efficacies with respect to the wild-type antibody are available. The results of the present MD-FEP simulation studies show that in order to enhance the affinity for the antigen, the engineering of HzKR127 should be made in such a way as to promote the dynamic stability of the overall protein conformation and that of the translational motion of the antigen in the antibody-antigen complex. The relative binding free energies of the four mutant antibodies obtained from MD-FEP calculations compare pretty well with the experimental mutagenesis data with the associated squared correlation coefficient of 0.96. This indicates that MD-FEP calculations may serve as a useful computational tool for rational antibody engineering. Discussed in detail are the differences in the structural features of antibody-antigen interactions between the wild-type and the mutant antibodies that are responsible for the change in binding affinities for the antigen.     

Credible sets for risk ratios in over-reported two-sample binomial data using the double-sampling scheme

We consider point and interval estimation for risk ratios based on two independent samples of binomial data subject to false positive misclassification. For such data it is well known that the model is unidentifiable. We consider incorporating training data obtained by using a double-sampling scheme to make the model identifiable. In this identifiable model, we propose a Bayesian method to make statistical inferences. In particular, we derive an easy-to-implement closed-form algorithm for drawing from the posterior distributions. The algorithm is illustrated using a real data example and further examined via Monte Carlo simulation studies.     

Development of a sequential robust–tolerance design model for a destructive quality characteristic

Robust design (RD) and tolerance design (TD) have received much attention from researchers and practitioners for more than two decades, and a number of methodologies for modeling and optimizing the RD and TD processes have been studied. However, there is ample room for improvement. Because most existing research considers RD and TD as separate research fields, the primary objective of this paper is to develop a sequential robust–tolerance design method to jointly determine the best factor settings and the closed-form solutions for the optimal specification limits. We then apply the proposed method to a destructive quality characteristic. Finally, a case study and sensitivity analyses are performed for verification purposes, and further studies are discussed.