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The Baeyer-Villiger oxidation of ketones is a crucial oxygen atom transfer (OAT) process used for ester production. Traditionally, Baeyer-Villiger oxidation is accomplished by thermally oxidizing the OAT from stoichiometric peroxides, which are often difficult to handle. Electrochemical methods hold promise for breaking the limitation of using water as the oxygen atom source. Nevertheless, existing demonstrations of electrochemical Baeyer-Villiger oxidation face the challenges of low selectivity. We report in this study a strategy to overcome this challenge. By employing a well-known water oxidation catalyst, Fe2O3, we achieved nearly perfect selectivity for the electrochemical Baeyer-Villiger oxidation of cyclohexanone. Mechanistic studies suggest that it is essential to produce surface hydroperoxo intermediates (M-OOH, where M represents a metal center) that promote the nucleophilic attack on ketone substrates. By confining the reactions to the catalyst surfaces, competing reactions (e.g., dehydrogenation, carboxylic acid cation rearrangements, and hydroxylation) are greatly limited, thereby offering high selectivity. The surface-initiated nature of the reaction is confirmed by kinetic studies and spectroelectrochemical characterizations. This discovery adds nucleophilic oxidation to the toolbox of electrochemical organic synthesis.
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Molecular Ir catalysts have emerged as an important class of model catalysts for understanding structure-activity relationships in water oxidation, a reaction that is central to renewable fuel synthesis. Prior efforts have mostly focused on controlling and elucidating the emergence of active species from prepared precursors. However, the development of efficient and stable molecular Ir catalysts also necessitates probing of reaction intermediates. To date, relatively little is known about the key intermediates in the cycles of the molecular Ir catalysts. Herein, we probed the catalytic cycle of a homogeneous Ir catalyst ("blue dimer") at a Au electrode/aqueous electrolyte interface by combining surface-enhanced infrared absorption spectroscopy (SEIRAS) with phase-sensitive detection (PSD). Cyclic voltammograms (CVs) from 1.4 to 1.7 VRHE (RHE = reversible hydrogen electrode) give rise to a band at â¼818 cm-1, whereas CVs from 1.4 to ≥1.85 VRHE generate an additional band at â¼1146 cm-1. Isotope labeling experiments indicate that the bands at â¼818 and â¼1146 cm-1 are attributable to oxo (IrVâO) and superoxo (IrIV-OOâ¢) moieties, respectively. This study establishes PSD-SEIRAS as a sensitive tool for probing water oxidation cycles at electrode/electrolyte interfaces and demonstrates that the relative abundance of two key intermediates can be tuned by the thermodynamic driving force of the reaction.
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Heterogeneous water oxidation catalysis is central to the development of renewable energy technologies. Recent research has suggested that the reaction mechanisms are sensitive to the hole density at the active sites. However, these previous results were obtained on catalysts of different materials featuring distinct active sites, making it difficult to discriminate between competing explanations. Here, a comparison study based on heterogenized dinuclear Ir catalysts (Ir-DHC), which feature the same type of active site on different supports, is reported. The prototypical reaction was water oxidation triggered by pulsed irradiation of suspensions containing a light sensitizer, Ru(bpy)32+, and a sacrificial electron scavenger, S2O82-. It was found that at relatively low temperatures (288-298 K), the water oxidation activities of Ir-DHC on indium tin oxide (ITO) and CeO2 supports were comparable within the studied range of fluences (62-151 mW cm-2). By contrast, at higher temperatures (310-323 K), Ir-DHC on ITO exhibited a ca. 100% higher water oxidation activity than on CeO2. The divergent activities were attributed to the distinct abilities of the supporting substrates in redistributing holes. The differences were only apparent at relatively high temperatures when hole redistribution to the active site became a limiting factor. These findings highlight the critical role of the supporting substrate in determining the turnover at active sites of heterogeneous catalysts.
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Various nonpharmaceutical interventions (NPIs) were implemented to alleviate the COVID-19 pandemic since its outbreak. The transmission dynamics of other respiratory infectious diseases, such as seasonal influenza, were also affected by these interventions. The drastic decline of seasonal influenza caused by such interventions would result in waning of population immunity and may trigger the seasonal influenza epidemic with the lift of restrictions during the post-pandemic era. We obtained weekly influenza laboratory confirmations from FluNet to analyse the resurgence patterns of seasonal influenza in China and the US. Our analysis showed that due to the impact of NPIs including travel restrictions between countries, the influenza resurgence was caused by influenza virus A in the US while by influenza virus B in China.
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COVID-19 , Gripe Humana , Humanos , Gripe Humana/epidemiología , Gripe Humana/prevención & control , Pandemias/prevención & control , COVID-19/epidemiología , China/epidemiología , Brotes de EnfermedadesRESUMEN
BACKGROUND: The high immune evasion ability of SARS-COV-2 Omicron variant surprised the world and appears to be far stronger than any previous variant. Previous to Omicron it has been difficult to assess and compare immune evasion ability of different variants, including the Beta and Delta variants, because of the relatively small numbers of reinfections and because of the problems in correctly identifying reinfections in the population. This has led to different claims appearing in the literature. Thus we find claims of both high and low immune evasion for the Beta variant. Some findings have suggested that the Beta variant has a higher immune evasion ability than the Delta variant in South Africa, and others that it has a lower ability. METHOD: In this brief report, we re-analyse a unique dataset of variant-specific reinfection data and a simple model to correct for the infection attack rates of different variants. RESULT: We find that a model with the Delta variant having an equal or higher immune evasion ability than Beta variant is compatible with the data. CONCLUSION: We conclude that the immune evasion ability of Beta variant is not stronger than Delta variant, and indeed, the immune evasion abilities of both variants are weak in South Africa.
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COVID-19 , Humanos , Sudáfrica/epidemiología , COVID-19/epidemiología , Evasión Inmune/genética , Reinfección , SARS-CoV-2/genéticaRESUMEN
BACKGROUND: The ongoing coronavirus 2019 (COVID-19) pandemic has emerged and caused multiple pandemic waves in the following six countries: India, Indonesia, Nepal, Malaysia, Bangladesh and Myanmar. Some of the countries have been much less studied in this devastating pandemic. This study aims to assess the impact of the Omicron variant in these six countries and estimate the infection fatality rate (IFR) and the reproduction number [Formula: see text] in these six South Asia, Southeast Asia and Oceania countries. METHODS: We propose a Susceptible-Vaccinated-Exposed-Infectious-Hospitalized-Death-Recovered model with a time-varying transmission rate [Formula: see text] to fit the multiple waves of the COVID-19 pandemic and to estimate the IFR and [Formula: see text] in the aforementioned six countries. The level of immune evasion and the intrinsic transmissibility advantage of the Omicron variant are also considered in this model. RESULTS: We fit our model to the reported deaths well. We estimate the IFR (in the range of 0.016 to 0.136%) and the reproduction number [Formula: see text] (in the range of 0 to 9) in the six countries. Multiple pandemic waves in each country were observed in our simulation results. CONCLUSIONS: The invasion of the Omicron variant caused the new pandemic waves in the six countries. The higher [Formula: see text] suggests the intrinsic transmissibility advantage of the Omicron variant. Our model simulation forecast implies that the Omicron pandemic wave may be mitigated due to the increasing immunized population and vaccine coverage.
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COVID-19 , Humanos , COVID-19/epidemiología , Pandemias , SARS-CoV-2 , Asia , OceaníaRESUMEN
In the context of infectious disease transmission, high heterogeneity in individual infectiousness indicates that a few index cases can generate large numbers of secondary cases, a phenomenon commonly known as superspreading. The potential of disease superspreading can be characterized by describing the distribution of secondary cases (of each seed case) as a negative binomial (NB) distribution with the dispersion parameter, k. Based on the feature of NB distribution, there must be a proportion of individuals with individual reproduction number of almost 0, which appears restricted and unrealistic. To overcome this limitation, we generalized the compound structure of a Poisson rate and included an additional parameter, and divided the reproduction number into independent and additive fixed and variable components. Then, the secondary cases followed a Delaporte distribution. We demonstrated that the Delaporte distribution was important for understanding the characteristics of disease transmission, which generated new insights distinct from the NB model. By using real-world dataset, the Delaporte distribution provides improvements in describing the distributions of COVID-19 and SARS cases compared to the NB distribution. The model selection yielded increasing statistical power with larger sample sizes as well as conservative type I error in detecting the improvement in fitting with the likelihood ratio (LR) test. Numerical simulation revealed that the control strategy-making process may benefit from monitoring the transmission characteristics under the Delaporte framework. Our findings highlighted that for the COVID-19 pandemic, population-wide interventions may control disease transmission on a general scale before recommending the high-risk-specific control strategies.
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COVID-19 , Enfermedades Transmisibles , COVID-19/epidemiología , Enfermedades Transmisibles/epidemiología , Humanos , Funciones de Verosimilitud , Modelos Estadísticos , Pandemias/prevención & controlRESUMEN
BACKGROUNDS: Brazil has suffered two waves of Coronavirus Disease 2019 (COVID-19). The second wave, coinciding with the spread of the Gamma variant, was more severe than the first wave. Studies have not yet reached a conclusion on some issues including the extent of reinfection, the infection fatality rate (IFR), the infection attack rate (IAR) and the effects of the vaccination campaign in Brazil, though it was reported that confirmed reinfection was at a low level. METHODS: We modify the classical Susceptible-Exposed-Infectious-Recovered (SEIR) model with additional class for severe cases, vaccination and time-varying transmission rates. We fit the model to the severe acute respiratory infection (SARI) deaths, which is a proxy of the COVID-19 deaths, in 20 Brazilian cities with the large number of death tolls. We evaluate the vaccination effect by a contrast of "with" vaccination actual scenario and "without" vaccination in a counterfactual scenario. We evaluate the model performance when the reinfection is absent in the model. RESULTS: In the 20 Brazilian cities, the model simulated death matched the reported deaths reasonably well. The effect of the vaccination varies across cities. The estimated median IFR is around 1.2%. CONCLUSION: Overall, through this modeling exercise, we conclude that the effects of vaccination campaigns vary across cites and the reinfection is not crucial for the second wave. The relatively high IFR could be due to the breakdown of medical system in many cities.
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COVID-19 , Brasil/epidemiología , COVID-19/epidemiología , COVID-19/prevención & control , Ciudades/epidemiología , Humanos , Reinfección , SARS-CoV-2 , VacunaciónRESUMEN
(1) Background: The coronavirus 2019 (COVID-19) pandemic has caused multiple waves of cases and deaths in the United States (US). The wild strain, the Alpha variant (B.1.1.7) and the Delta variant (B.1.617.2) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were the principal culprits behind these waves. To mitigate the pandemic, the vaccination campaign was started in January 2021. While the vaccine efficacy is less than 1, breakthrough infections were reported. This work aims to examine the effects of the vaccination across 50 US states and the District of Columbia. (2) Methods: Based on the classic Susceptible-Exposed-Infectious-Recovered (SEIR) model, we add a delay class between infectious and death, a death class and a vaccinated class. We compare two special cases of our new model to simulate the effects of the vaccination. The first case expounds the vaccinated individuals with full protection or not, compared to the second case where all vaccinated individuals have the same level of protection. (3) Results: Through fitting the two approaches to reported COVID-19 deaths in all 50 US states and the District of Columbia, we found that these two approaches are equivalent. We calculate that the death toll could be 1.67-3.33 fold in most states if the vaccine was not available. The median and mean infection fatality ratio are estimated to be approximately 0.6 and 0.7%. (4) Conclusions: The two approaches we compared were equivalent in evaluating the effectiveness of the vaccination campaign in the US. In addition, the effect of the vaccination campaign was significant, with a large number of deaths averted.