RESUMO
BACKGROUND: Seasonal influenza remains a global public health concern. A messenger RNA (mRNA)-based quadrivalent seasonal influenza vaccine, mRNA-1010, was investigated in a 3-part, first-in-human, phase 1/2 clinical trial. METHODS: In Parts 1-3 of this stratified, observer-blind study, adults aged ≥18 years old were randomly assigned to receive a single dose (6.25 µg to 200 µg) of mRNA-1010 or placebo (Part 1) or an active comparator (Afluria; Parts 2-3). Primary study objectives were assessment of safety, reactogenicity, and humoral immunogenicity of mRNA-1010, placebo (Part 1), or active comparator (Parts 2-3). Exploratory endpoints included assessment of cellular immunogenicity (Part 1) and antigenic breadth against vaccine heterologous (A/H3N2) strains (Parts 1-2). RESULTS: In all study parts, solicited adverse reactions were reported more frequently for mRNA-1010 than placebo or Afluria and most were grade 1 or 2 in severity. No vaccine-related serious adverse events or deaths were reported. In Parts 1-2, a single dose of mRNA-1010 (25 µg to 200 µg) elicited robust Day 29 hemagglutination inhibition (HAI) titers that persisted through 6 months. In Part 3, lower doses of mRNA-1010 (6.25 µg to 25 µg) elicited Day 29 HAI titers that were higher or comparable to Afluria for influenza A strains. Compared with Afluria, mRNA-1010 (50 µg) elicited broader A/H3N2 antibody responses (Part 2). mRNA-1010 induced greater T-cell responses than placebo at Day 8 that were sustained or stronger at Day 29 (Part 1). CONCLUSIONS: Data support the continued development of mRNA-1010 as a seasonal influenza vaccine. CLINICALTRIALS.GOV IDENTIFIER: NCT04956575 (https://clinicaltrials.gov/study/NCT04956575).
RESUMO
BACKGROUND: The mRNA-1345 vaccine demonstrated efficacy against RSV disease with acceptable safety in adults ≥60 years in the ConquerRSV trial. Here, humoral immunogenicity results from the trial are presented. METHODS: This phase 2/3 trial randomly assigned adults (≥60 years) to mRNA-1345 50-µg encoding prefusion F (preF) glycoprotein (n = 17,793) vaccine or placebo (n = 17,748). RSV-A and RSV-B neutralizing antibody (nAb) and preF binding antibody (bAb) levels at baseline and day 29 post-vaccination were assessed in a per-protocol immunogenicity subset ([PPIS]; mRNA-1345, n = 1515; placebo, n = 333). RESULTS: Day 29 nAb geometric mean titers (GMTs) increased 8.4-fold against RSV-A and 5.1-fold against RSV-B from baseline. Seroresponses (4-fold rise from baseline) in the mRNA-1345 groups were 74.2% and 56.5% for RSV-A and RSV-B, respectively. Baseline GMTs were lower among participants who met the seroresponse criteria than those who did not. mRNA-1345 induced preF bAbs at day 29, with a pattern similar to nAbs. Day 29 antibody responses across demographic and risk subgroups were generally consistent with the overall PPIS. CONCLUSION: mRNA-1345 enhanced RSV-A and RSV-B nAbs and preF bAbs in adults (≥60 years) across various subgroups, including those at risk for severe disease, consistent with its demonstrated efficacy in the prevention of RSV disease.
RESUMO
Wearable devices, such as data gloves and electronic skins, can perceive human instructions, behaviors and even emotions by tracking a hand's motion, with the help of knowledge learning. The shape or position single-mode sensor in such devices often lacks comprehensive information to perceive interactive gestures. Meanwhile, the limited computing power of wearable applications restricts the multimode fusion of different sensing data and the deployment of deep learning networks. We propose a perceptive fusion electronic skin (PFES) with a bioinspired hierarchical structure that utilizes the magnetization state of a magnetostrictive alloy film to be sensitive to external strain or magnetic field. Installed at the joints of a hand, the PFES realizes perception of curvature (joint shape) and magnetism (joint position) information by mapping corresponding signals to the two-directional continuous distribution such that the two edges represent the contributions of curvature radius and magnetic field, respectively. By autonomously selecting knowledge closer to the user's hand movement characteristics, the reinforced knowledge distillation method is developed to learn and compress a teacher model for rapid deployment on wearable devices. The PFES integrating the autonomous learning algorithm can fuse curvature-magnetism dual information, ultimately achieving human machine interaction with gesture recognition and haptic feedback for cross-space perception and manipulation.