Direct imaging of liquid domains in membranes by cryo-electron tomography.

Images of micrometer-scale domains in lipid bilayers have provided the gold standard of model-free evidence to understand the domains' shapes, sizes, and distributions. Corresponding techniques to directly and quantitatively assess smaller (nanoscale and submicron) liquid domains have been limited. Researchers commonly seek to correlate activities of membrane proteins with attributes of the domains in which they reside; doing so hinges on identification and characterization of membrane domains. Although some features of membrane domains can be probed by indirect methods, these methods are often constrained by the limitation that data must be analyzed in the context of models that require multiple assumptions or parameters. Here, we address this challenge by developing and testing two methods of identifying submicron domains in biomimetic membranes. Both methods leverage cryo-electron tomograms of ternary membranes under vitrified, hydrated conditions. The first method is optimized for probe-free applications: Domains are directly distinguished from the surrounding membrane by their thickness. This technique quantitatively and accurately measures area fractions of domains, in excellent agreement with known phase diagrams. The second method is optimized for applications in which a single label is deployed for imaging membranes by both high-resolution cryo-electron tomography and diffraction-limited optical microscopy. For this method, we test a panel of probes, find that a trimeric mCherry label performs best, and specify criteria for developing future high-performance, dual-use probes. These developments have led to direct and quantitative imaging of submicron membrane domains in vitrified, hydrated vesicles.

Decreasing measles burden by optimizing campaign timing.

Measles remains a major contributor to preventable child mortality, and bridging gaps in measles immunity is a fundamental challenge to global health. In high-burden settings, mass vaccination campaigns are conducted to increase access to vaccine and address this issue. Ensuring that campaigns are optimally effective is a crucial step toward measles elimination; however, the relationship between campaign impact and disease dynamics is poorly understood. Here, we study measles in Pakistan, and we demonstrate that campaign timing can be tuned to optimally interact with local transmission seasonality and recent incidence history. We develop a mechanistic modeling approach to optimize timing in general high-burden settings, and we find that in Pakistan, hundreds of thousands of infections can be averted with no change in campaign cost.

Policy Review and Modeling Analysis of Mitigation Measures for Coronavirus Disease Epidemic Control, Health System, and Disease Burden, South Korea.

We reviewed the timeline of key policies for control of the coronavirus disease epidemic and determined their impact on the epidemic and hospital burden in South Korea. Using a discrete stochastic transmission model, we estimated that multilevel policies, including extensive testing, contact tracing, and quarantine, reduced contact rates by 90% and rapidly decreased the epidemic in Daegu and nationwide during February‒March 2020. Absence of these prompt responses could have resulted in a >10-fold increase in infections, hospitalizations, and deaths by May 15, 2020, relative to the status quo. The model suggests that reallocation of persons who have mild or asymptomatic cases to community treatment centers helped avoid overwhelming hospital capacity and enabled healthcare workers to provide care for more severely and critically ill patients in hospital beds and negative-pressure intensive care units. As small outbreaks continue to occur, contact tracing and maintenance of hospital capacity are needed.

Sculpting Fano Resonances To Control Photonic-Plasmonic Hybridization.

Hybrid photonic-plasmonic systems have tremendous potential as versatile platforms for the study and control of nanoscale light-matter interactions since their respective components have either high-quality factors or low mode volumes. Individual metallic nanoparticles deposited on optical microresonators provide an excellent example where ultrahigh-quality optical whispering-gallery modes can be combined with nanoscopic plasmonic mode volumes to maximize the system's photonic performance. Such optimization, however, is difficult in practice because of the inability to easily measure and tune critical system parameters. In this Letter, we present a general and practical method to determine the coupling strength and tailor the degree of hybridization in composite optical microresonator-plasmonic nanoparticle systems based on experimentally measured absorption spectra. Specifically, we use thermal annealing to control the detuning between a metal nanoparticle's localized surface plasmon resonance and the whispering-gallery modes of an optical microresonator cavity. We demonstrate the ability to sculpt Fano resonance lineshapes in the absorption spectrum and infer system parameters critical to elucidating the underlying photonic-plasmonic hybridization. We show that including decoherence processes is necessary to capture the evolution of the lineshapes. As a result, thermal annealing allows us to directly tune the degree of hybridization and various hybrid mode quantities such as the quality factor and mode volume and ultimately maximize the Purcell factor to be 104.

Characterizing Localized Surface Plasmons Using Electron Energy-Loss Spectroscopy.

Electron energy-loss spectroscopy (EELS) offers a window to view nanoscale properties and processes. When performed in a scanning transmission electron microscope, EELS can simultaneously render images of nanoscale objects with subnanometer spatial resolution and correlate them with spectroscopic information at a spectral resolution of ∼10-100 meV. Consequently, EELS is a near-perfect tool for understanding the optical and electronic properties of individual plasmonic metal nanoparticles and few-nanoparticle assemblies, which are significant in a wide range of fields. This review presents an overview of basic plasmonics and EELS theory and highlights several recent noteworthy experiments involving the interrogation of plasmonic metal nanoparticle systems using electron beams.

STEM/EELS Imaging of Magnetic Hybridization in Symmetric and Symmetry-Broken Plasmon Oligomer Dimers and All-Magnetic Fano Interference.

Negative-index metamaterials composed of magnetic plasmon oligomers are actively being investigated for their potential role in optical cloaking, superlensing, and nanolithography applications. A significant improvement to their practicality lies in the ability to function at multiple distinct wavelengths in the visible part of spectrum. Here we utilize the nanometer spatial-resolving power of electron energy-loss spectroscopy to conclusively demonstrate hybridization of magnetic plasmons in oligomer dimers that can achieve this goal. We also show that breaking the dimer's symmetry can induce all-magnetic Fano interferences based solely on the interplay of bright and dark magnetic modes, allowing us to further tailor the system's optical responses. These features are engineered through the design of the oligomer's underlying nanoparticle elements as elongated Ag nanodisks with spectrally isolated long-axis plasmon resonances. The resulting magnetic plasmon oligomers and their hybridized assemblies establish a new design paradigm for optical metamaterials with rich functionality.

Depletion with Cyclodextrin Reveals Two Populations of Cholesterol in Model Lipid Membranes.

Recent results provide evidence that cholesterol is highly accessible for removal from both cell and model membranes above a threshold concentration that varies with membrane composition. Here we measured the rate at which methyl-ß-cyclodextrin depletes cholesterol from a supported lipid bilayer as a function of cholesterol mole fraction. We formed supported bilayers from two-component mixtures of cholesterol and a PC (phosphatidylcholine) lipid, and we directly visualized the rate of decrease in area of the bilayers with fluorescence microscopy. Our technique yields the accessibility of cholesterol over a wide range of concentrations (30-66 mol %) for many individual bilayers, enabling fast acquisition of replicate data. We found that the bilayers contain two populations of cholesterol, one with low surface accessibility and the other with high accessibility. A larger fraction of the total membrane cholesterol appears in the more accessible population when the acyl chains of the PC-lipid tails are more unsaturated. Our findings are most consistent with the predictions of the condensed-complex and cholesterol bilayer domain models of cholesterol-phospholipid interactions in lipid membranes.

Estimating the Impact of Vaccination Campaigns on Measles Transmission in Somalia.

Somalia is a complex and fragile setting with a demonstrated potential for disruptive, high-burden measles outbreaks. In response, since 2018, Somalian authorities have partnered with UNICEF and the WHO to implement measles vaccination campaigns across the country. In this paper, we create a Somalia-specific model of measles transmission based on a comprehensive epidemiological dataset including case-based surveillance, vaccine registries, and serological surveys. We use this model to assess the impact of these campaign interventions on Somalian's measles susceptibility, showing, for example, that across the roughly 10 million doses delivered, 1 of every 5 immunized a susceptible child. Finally, we use the model to explore a counter-factual epidemiology without the 2019-2020 campaigns, and we estimate that those interventions prevented over 10,000 deaths.

Population-Level Risk Factors Related to Measles Case Fatality: A Conceptual Framework Based on Expert Consultation and Literature Review.

A better understanding of population-level factors related to measles case fatality is needed to estimate measles mortality burden and impact of interventions such as vaccination. This study aimed to develop a conceptual framework of mechanisms associated with measles case fatality ratios (CFRs) and assess the scope of evidence available for related indicators. Using expert consultation, we developed a conceptual framework of mechanisms associated with measles CFR and identified population-level indicators potentially associated with each mechanism. We conducted a literature review by searching PubMed on 31 October 2021 to determine the scope of evidence for the expert-identified indicators. Studies were included if they contained evidence of an association between an indicator and CFR and were excluded if they were from non-human studies or reported non-original data. Included studies were assessed for study quality. Expert consultation identified five mechanisms in a conceptual framework of factors related to measles CFR. We identified 3772 studies for review and found 49 studies showing at least one significant association with CFR for 15 indicators (average household size, educational attainment, first- and second-dose coverage of measles-containing vaccine, human immunodeficiency virus prevalence, level of health care available, stunting prevalence, surrounding conflict, travel time to major city or settlement, travel time to nearest health care facility, under-five mortality rate, underweight prevalence, vitamin A deficiency prevalence, vitamin A treatment, and general malnutrition) and only non-significant associations for five indicators (antibiotic use for measles-related pneumonia, malaria prevalence, percent living in urban settings, pneumococcal conjugate vaccination coverage, vitamin A supplementation). Our study used expert consultation and a literature review to provide additional insights and a summary of the available evidence of these underlying mechanisms and indicators that could inform future measles CFR estimations.

Slight reduction in SARS-CoV-2 exposure viral load due to masking results in a significant reduction in transmission with widespread implementation.

Masks are a vital tool for limiting SARS-CoV-2 spread in the population. Here we utilize a mathematical model to assess the impact of masking on transmission within individual transmission pairs and at the population level. Our model quantitatively links mask efficacy to reductions in viral load and subsequent transmission risk. Our results reinforce that the use of masks by both a potential transmitter and exposed person substantially reduces the probability of successful transmission, even if masks only lower exposure viral load by ~ 50%. Slight increases in mask adherence and/or efficacy above current levels would reduce the effective reproductive number (Re) substantially below 1, particularly if implemented comprehensively in potential super-spreader environments. Our model predicts that moderately efficacious masks will also lower exposure viral load tenfold among people who get infected despite masking, potentially limiting infection severity. Because peak viral load tends to occur pre-symptomatically, we also identify that antiviral therapy targeting symptomatic individuals is unlikely to impact transmission risk. Instead, antiviral therapy would only lower Re if dosed as post-exposure prophylaxis and if given to ~ 50% of newly infected people within 3 days of an exposure. These results highlight the primacy of masking relative to other biomedical interventions under consideration for limiting the extent of the COVID-19 pandemic prior to widespread implementation of a vaccine. To confirm this prediction, we used a regression model of King County, Washington data and simulated the counterfactual scenario without mask wearing to estimate that in the absence of additional interventions, mask wearing decreased Re from 1.3-1.5 to ~ 1.0 between June and September 2020.

Impact of COVID-19-related disruptions to measles, meningococcal A, and yellow fever vaccination in 10 countries.

Background: Childhood immunisation services have been disrupted by the COVID-19 pandemic. WHO recommends considering outbreak risk using epidemiological criteria when deciding whether to conduct preventive vaccination campaigns during the pandemic. Methods: We used two to three models per infection to estimate the health impact of 50% reduced routine vaccination coverage in 2020 and delay of campaign vaccination from 2020 to 2021 for measles vaccination in Bangladesh, Chad, Ethiopia, Kenya, Nigeria, and South Sudan, for meningococcal A vaccination in Burkina Faso, Chad, Niger, and Nigeria, and for yellow fever vaccination in the Democratic Republic of Congo, Ghana, and Nigeria. Our counterfactual comparative scenario was sustaining immunisation services at coverage projections made prior to COVID-19 (i.e. without any disruption). Results: Reduced routine vaccination coverage in 2020 without catch-up vaccination may lead to an increase in measles and yellow fever disease burden in the modelled countries. Delaying planned campaigns in Ethiopia and Nigeria by a year may significantly increase the risk of measles outbreaks (both countries did complete their supplementary immunisation activities (SIAs) planned for 2020). For yellow fever vaccination, delay in campaigns leads to a potential disease burden rise of >1 death per 100,000 people per year until the campaigns are implemented. For meningococcal A vaccination, short-term disruptions in 2020 are unlikely to have a significant impact due to the persistence of direct and indirect benefits from past introductory campaigns of the 1- to 29-year-old population, bolstered by inclusion of the vaccine into the routine immunisation schedule accompanied by further catch-up campaigns. Conclusions: The impact of COVID-19-related disruption to vaccination programs varies between infections and countries. Planning and implementation of campaigns should consider country and infection-specific epidemiological factors and local immunity gaps worsened by the COVID-19 pandemic when prioritising vaccines and strategies for catch-up vaccination. Funding: Bill and Melinda Gates Foundation and Gavi, the Vaccine Alliance.

Intensive Care Unit Capacity and Its Associated Risk Factors During the COVID-19 Surge in the Republic of Korea: Analysis Using Nationwide Health Claims Data.

OBJECTIVE: To identify risk factors for intensive care unit (ICU) admission and mechanical ventilator usage among confirmed coronavirus disease (COVID-19) patients and estimate the effects of mitigation efforts on ICU capacity in Korea. PATIENTS AND METHODS: Data on profiles and medical history of all confirmed COVID-19 patients in the past 1 year were extracted from the Korean National Health Insurance System's claims database to assess risk factors for ICU admission and ventilator use. We used a time-series epidemic model to estimate the ICU census in Daegu from the reported hospital data. FINDINGS: Multivariate regression analysis revealed male sex, old age, and residing in Daegu city as significant risk factors for ICU admission. The number of patients requiring ICU admission exceeded the bed capacity across all Daegu hospitals before March 9, 2020, and therefore, critically ill patients were transferred to nearby hospitals outside Daegu. This finding was consistent with our prediction that the ICU census in Daegu would peak on March 16, 2020, at 160 through mitigation efforts, without which it would have reached 300 by late March 2020. CONCLUSION: Older age and male sex were risk factors for ICU admission. In addition, the geographic location of the hospital seems to contribute to the severity of the COVID-19 patients admitted to the ICU and to the ICU capacity.

Comment on "Long-term measles-induced immunomodulation increases overall childhood infectious disease mortality".

Mina et al (Reports, 8 May 2015, p. 694) used population-level statistical analysis to argue that measles infection results in a 2- to 3-year immunomodulation, implicating measles in substantially more child mortality than previously thought. We show, using both simulation and data from Iceland, that the statistical approach used may be confounded by the 2-year periodicity of measles incidence in the areas studied.

Charge-tunable quantum plasmons in colloidal semiconductor nanocrystals.

Nanomaterials exhibiting plasmonic optical responses are impacting sensing, information processing, catalysis, solar, and photonics technologies. Recent advances have expanded the portfolio of plasmonic nanostructures into doped semiconductor nanocrystals, which allow dynamic manipulation of carrier densities. Once interpreted as intraband single-electron transitions, the infrared absorption of doped semiconductor nanocrystals is now commonly attributed to localized surface plasmon resonances and analyzed using the classical Drude model to determine carrier densities. Here, we show that the experimental plasmon resonance energies of photodoped ZnO nanocrystals with controlled sizes and carrier densities diverge from classical Drude model predictions at small sizes, revealing quantum plasmons in these nanocrystals. A Lorentz oscillator model more adequately describes the data and illustrates a closer link between plasmon resonances and single-electron transitions in semiconductors than in metals, highlighting a fundamental contrast between these two classes of plasmonic materials.