Potential impact of annual vaccination with reformulated COVID-19 vaccines: Lessons from the US COVID-19 scenario modeling hub.

BACKGROUND: Coronavirus Disease 2019 (COVID-19) continues to cause significant hospitalizations and deaths in the United States. Its continued burden and the impact of annually reformulated vaccines remain unclear. Here, we present projections of COVID-19 hospitalizations and deaths in the United States for the next 2 years under 2 plausible assumptions about immune escape (20% per year and 50% per year) and 3 possible CDC recommendations for the use of annually reformulated vaccines (no recommendation, vaccination for those aged 65 years and over, vaccination for all eligible age groups based on FDA approval). METHODS AND FINDINGS: The COVID-19 Scenario Modeling Hub solicited projections of COVID-19 hospitalization and deaths between April 15, 2023 and April 15, 2025 under 6 scenarios representing the intersection of considered levels of immune escape and vaccination. Annually reformulated vaccines are assumed to be 65% effective against symptomatic infection with strains circulating on June 15 of each year and to become available on September 1. Age- and state-specific coverage in recommended groups was assumed to match that seen for the first (fall 2021) COVID-19 booster. State and national projections from 8 modeling teams were ensembled to produce projections for each scenario and expected reductions in disease outcomes due to vaccination over the projection period. From April 15, 2023 to April 15, 2025, COVID-19 is projected to cause annual epidemics peaking November to January. In the most pessimistic scenario (high immune escape, no vaccination recommendation), we project 2.1 million (90% projection interval (PI) [1,438,000, 4,270,000]) hospitalizations and 209,000 (90% PI [139,000, 461,000]) deaths, exceeding pre-pandemic mortality of influenza and pneumonia. In high immune escape scenarios, vaccination of those aged 65+ results in 230,000 (95% confidence interval (CI) [104,000, 355,000]) fewer hospitalizations and 33,000 (95% CI [12,000, 54,000]) fewer deaths, while vaccination of all eligible individuals results in 431,000 (95% CI: 264,000-598,000) fewer hospitalizations and 49,000 (95% CI [29,000, 69,000]) fewer deaths. CONCLUSIONS: COVID-19 is projected to be a significant public health threat over the coming 2 years. Broad vaccination has the potential to substantially reduce the burden of this disease, saving tens of thousands of lives each year.

Advanced Nanocarbons Toward two-Electron Oxygen Electrode Reactions for H2O2 Production and Integrated Energy Conversion.

Hydrogen peroxide (H2O2) plays a pivotal role in advancing sustainable technologies due to its eco-friendly oxidizing capability. The electrochemical two-electron (2e-) oxygen reduction reaction and water oxidation reaction present an environmentally green method for H2O2 production. Over the past three years, significant progress is made in the field of carbon-based metal-free electrochemical catalysts (C-MFECs) for low-cost and efficient production of H2O2 (H2O2EP). This article offers a focused and comprehensive review of designing C-MFECs for H2O2EP, exploring the construction of dual-doping configurations, heteroatom-defect coupling sites, and strategic dopant positioning to enhance H2O2EP efficiency; innovative structural tuning that improves interfacial reactant concentration and promote the timely release of H2O2; modulation of electrolyte and electrode interfaces to support the 2e- pathways; and the application of C-MFECs in reactors and integrated energy systems. Finally, the current challenges and future directions in this burgeoning field are discussed.

A Molecular Rheology Dynamics Study on 3D Printing of Liquid Crystal Elastomers.

This work presents a rheological study of a biocompatible and biodegradable liquid crystal elastomer (LCE) ink for three dimensional (3D) printing. These materials have shown that their structural variations have an effect on morphology, mechanical properties, alignment, and their impact on cell response. Within the last decade LCEs are extensively studied as potential printing materials for soft robotics applications, due to the actuation properties that are produced when liquid crystal (LC) moieties are induced through external stimuli. This report utilizes experiments and coarse-grained molecular dynamics to study the macroscopic rheology of LCEs in nonlinear shear flow. Results from the shear flow simulations are in line with the outcomes of these experimental investigations. This work believes the insights from these results can be used to design and print new material with desirable properties necessary for targeted applications.

Leveraging advances in data-driven deep learning methods for hybrid epidemic modeling.

Mathematical modeling of epidemic dynamics is crucial to understand its underlying mechanisms, quantify important parameters, and make predictions that facilitate more informed decision-making. There are three major types of models: mechanistic models including the SEIR-type paradigm, alternative data-driven (DD) approaches, and hybrid models that combine mechanistic models with DD approaches. In this paper, we summarize our work in the COVID-19 Scenario Modeling Hub (SMH) for more than 12 rounds since early 2021 for informed decision support. We emphasize the importance of deep learning techniques for epidemic modeling via a flexible DD framework that substantially complements the mechanistic paradigm to evaluate various future epidemic scenarios. We start with a traditional curve-fitting approach to model cumulative COVID-19 based on the underlying SEIR-type mechanisms. Hospitalizations and deaths are modeled as binomial processes of cases and hospitalization, respectively. We further formulate two types of deep learning models based on multivariate long short term memory (LSTM) to address the challenges of more traditional DD models. The first LSTM is structurally similar to the curve fitting approach and assumes that hospitalizations and deaths are binomial processes of cases. Instead of using a predefined exponential curve, LSTM relies on the underlying data to identify the most appropriate functions, and is capable of capturing both long-term and short-term epidemic behaviors. We then relax the assumption of dependent inputs among cases, hospitalizations, and death. Another type of LSTM that handles all input time series as parallel signals, the independent multivariate LSTM, is developed. Independent multivariate LSTM can incorporate a wide range of data sources beyond traditional case-based epidemiological surveillance. The DD framework unleashes its potential in big data era with previously neglected heterogeneous surveillance data sources, such as syndromic, environment, genomic, serologic, infoveillance, and mobility data. DD approaches, especially LSTM, complement and integrate with the mechanistic modeling paradigm, provide a feasible alternative approach to model today's complex socio-epidemiological systems, and further leverage our ability to explore different scenarios for more informed decision-making during health emergencies.

Systematic review with expert consensus on use of extracorporeal hemoadsorption in septic shock: An Indian perspective.

BACKGROUND: Septic shock is a severe form of sepsis characterised by deterioration in circulatory and cellular-metabolic parameters. Despite standard therapy, the outcomes are poor. Newer adjuvant therapy, such as CytoSorb® extracorporeal haemoadsorption device, has been investigated and shown promising outcome. However, there is a lack of some guidance to make clinical decisions on the use of CytoSorb® haemoadsorption as an adjuvant therapy in septic shock in Indian Setting. Therefore, this expert consensus was formulated. AIM: To formulate/establish specific consensus statements on the use of CytoSorb® haemoadsorption treatment based on the best available evidence and contextualised to the Indian scenario. METHODS: We performed a comprehensive literature on CytoSorb® haemoadsorption in sepsis, septic shock in PubMed selecting papers published between January 2011 and March 2023 2021 in English language. The statements for a consensus document were developed based on the summarised literature analysis and identification of knowledge gaps. Using a modified Delphi approach combining evidence appraisal and expert opinion, the following topics related to CytoSorb® in septic shock were addressed: need for adjuvant therapy, initiation timeline, need for Interleukin -6 levels, duration of therapy, change of adsorbers, safety, prerequisite condition, efficacy endpoints and management flowchart. Eleven expert members from critical care, emergency medicine, and the intensive care participated and voted on nine statements and one open-ended question. RESULTS: Eleven expert members from critical care, emergency medicine, and the intensive care participated and voted on nine statements and one open-ended question. All 11 experts in the consensus group (100%) participated in the first, second and third round of voting. After three iterative voting rounds and adapting two statements, consensus was achieved on nine statements out of nine statements. The consensus expert panel also recognised the necessity to form an association or society that can keep a registry regarding the use of CytoSorb® for all indications in the open-ended question (Q10) focusing on "future recommendations for CytoSorb® therapy". CONCLUSION: This Indian perspective consensus statement supports and provides guidance on the use of CytoSorb® haemoadsorption as an adjuvant treatment in patients with septic shock to achieve optimal outcomes.