Temperature-Responsive Multilayer Films Based on Block Copolymer-Coated Silica Nanoparticles for Long-Term Release of Favipiravir

Using surface-initiated atom-transfer radical polymerization, temperature-responsive block polymers were functionalized on the surface of silica nanocapsules (SNCs) by a "grafting from" technique. Favipiravir, a potential medicine candidate for the treatment of coronavirus disease (COVID-19), was encapsulated in polymer-coated SNCs and further incorporated into welldefined films by layer-by-layer self-assembly. The multilayer films composed of polymer-coated SNCs and poly(methacrylic acid) (PMAA) homopolymers exhibited swelling/deswelling behaviors under the trigger of a temperature stimulus. For the first time, the impact of steric hindrance on the assembling behavior, swelling/ deswelling transition, and delivering capacity of nanocapsule-based multilayer films was investigated. SNCs with coronae of higher steric hindrance resulted in a larger layering distance during film growth. Moreover, the difference in the sustained release rates of the drug indicated their diverse diffusion coefficients and intermolecular interactions within the multilayer films, due to the presence of a methyl spacer at the amino group of nanocapsule coronae and weaker ionic pairing between SNC coronae and PMAA homopolymers. The profile of drug release from the films was dependent on the temperature value of the surrounding environment. At 37 and 40 degrees C, the films were able to efficiently entrap favipiravir, with as low as 50% released in 80 days, whereas a faster favipiravir release was triggered by exposure to a lower temperature value at 25 degrees C. This work demonstrates the first proof-of-concept platform of temperature-responsive SNC-incorporated multilayered films with a well-defined internal structure and a sustained release profile for on-demand in vitro drug delivery.

Modeling heterogeneous multi-attribute emergency decision-making with Dempster-Shafer theory

Conventional multi-attribute decision-making (MADM) methods, with regard to different attributes, typically require decision-makers (DMs) to use a unified information expression to evaluate the performance of various alternatives. This does not properly reflect the heterogeneity among attributes. This paper presents a novel heterogeneous multi-attribute decision-making approach based on Dempster-Shafer theory (DST). A humancentric heterogeneous multi-attribute emergency decision-making framework is constructed based on Dempster-Shafer structures. The term "human-centric" is emphasized here as the proposed framework encompasses aspects specific to human judgments, specifications, or evaluations. Considering the differences in DM backgrounds and preferences, our framework incorporates a heterogeneous decision environment. DST allows DMs to express decision information in a manner closely consistent with human cognition. A series of parameters capture the subjective attitudes of DMs in our framework, the embodiments of which are manifold: (1) they reveal the sensitivity of DMs to alternative ranks in the process of basic probability assignment generation from decision information;(2) they reflect the tolerance of DMs to uncertainty in the process of weight calculation from belief entropy;and (3) they facilitate analysis of DMs in the decision process based on belief intervals. The proposed approach is demonstrated on a emergency decision-making application for medical supplier selection in the context of COVID-19.

Driving Forces of Changes in Air Quality during the COVID-19 Lockdown Period in the Yangtze River Delta Region, China

During the COVID-19 lockdown period (from January 23 to February 29, 2020), ambient PM2.5 concentrations in the Yangtze River Delta (YRD) region were observed to be much lower, while the maximum daily 8 h average (MDA8) O-3 concentrations became much higher compared to those before the lockdown (from January 1 to 22, 2020). Here, we show that emission reduction is the major driving force for the PM2.5 change, contributing to a PM2.5 decrease by 37% to 55% in the four YRD major cities (i.e., Shanghai, Hangzhou, Nanjing, and Hefei), but the MDA8 O-3 increase is driven by both emission reduction (29%-52%) and variation in meteorological conditions (17%-49%). Among all pollutants, reduction in emissions mainly of primary PM contributes to a PM2.5 decrease by 28% to 46%, and NOx emission reduction contributes 7% to 10%. Although NOx emission reduction dominates the MDA8 O-3 increase (38%-59%), volatile organic compounds (VOCs) emission reduction lead to a 5% to 9% MDA8 O-3 decrease. Increased O-3 promotes secondary aerosol formation and partially offsets the decrease of PM2.5 caused by the primary PM emission reductions. The results demonstrate that more coordinated air pollution control strategies are needed in YRD.