To describe outcomes of people admitted to hospital with coronavirus disease 2019 (covid-19) in the United States, and the clinical and laboratory characteristics associated with severity of illness.
The degradation of cadmium sulfide (CdS)-based oil paints is a phenomenon potentially threatening the iconic painting The Scream (ca. 1910) by Edvard Munch (Munch Museum, Oslo) that is still poorly understood. Here, we provide evidence for the presence of cadmium sulfate and sulfites as alteration products of the original CdS-based paint and explore the external circumstances and internal factors causing this transformation. Macroscale in situ noninvasive spectroscopy studies of the painting in combination with synchrotron-radiation x-ray microspectroscopy investigations of a microsample and artificially aged mock-ups show that moisture and mobile chlorine compounds are key factors for promoting the oxidation of CdS, while light (photodegradation) plays a less important role. Furthermore, under exposure to humidity, parallel/secondary reactions involving dissolution, migration through the paint, and recrystallization of water-soluble phases of the paint are associated with the formation of cadmium sulfates.
Maintaining phenological synchrony with flowers is a key ecological challenge for pollinators that may be exacerbated by ongoing environmental change. Here, we show that bumble bee workers facing pollen scarcity damage leaves of flowerless plants and thereby accelerate flower production. Laboratory studies revealed that leaf-damaging behavior is strongly influenced by pollen availability and that bee-damaged plants flower significantly earlier than undamaged or mechanically damaged controls. Subsequent outdoor experiments showed that the intensity of damage inflicted varies with local flower availability; furthermore, workers from wild colonies of two additional bumble bee species were also observed to damage plant leaves. These findings elucidate a feature of bumble bee worker behavior that can influence the local availability of floral resources.
The detection ranges of broadband sounds produced by marine invertebrates are not known. To address this deficiency, a linear array of hydrophones was built in a shallow water area to experimentally investigate the propagation features of the sounds from various sizes of European spiny lobsters (Palinurus elephas), recorded between 0.5 and 100 m from the animals. The peak-to-peak source levels (SL, measured at one meter from the animals) varied significantly with body size, the largest spiny lobsters producing SL up to 167 dB re 1 µPa2. The sound propagation and its attenuation with the distance were quantified using the array. This permitted estimation of the detection ranges of spiny lobster sounds. Under the high ambient noise conditions recorded in this study, the sounds propagated between 5 and 410 m for the smallest and largest spiny lobsters, respectively. Considering lower ambient noise levels and different realistic propagation conditions, spiny lobster sounds can be detectable up to several kilometres away from the animals, with sounds from the largest individuals propagating over 3 km. Our results demonstrate that sounds produced by P. elephas can be utilized in passive acoustic programs to monitor and survey this vulnerable species at kilometre scale in coastal waters.
Coronavirus disease 2019 (COVID-19) is a global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Without approved antiviral therapeutics or vaccines to this ongoing global threat, type I and type III interferons (IFNs) are currently being evaluated for their efficacy. Both the role of IFNs and the use of recombinant IFNs in two related, highly pathogenic coronaviruses, SARS-CoV and MERS-CoV, have been controversial in terms of their protective effects in the host. In this review, we describe the recent progress in our understanding of both type I and type III IFN-mediated innate antiviral responses against human coronaviruses and discuss the potential use of IFNs as a treatment strategy for COVID-19.
Using Pacific benthic foraminiferal δ18O and Mg/Ca records, we derive a Cenozoic (66 Ma) global mean sea level (GMSL) estimate that records evolution from an ice-free Early Eocene to Quaternary bipolar ice sheets. These GMSL estimates are statistically similar to “backstripped” estimates from continental margins accounting for compaction, loading, and thermal subsidence. Peak warmth, elevated GMSL, high CO2, and ice-free “Hothouse” conditions (56 to 48 Ma) were followed by “Cool Greenhouse” (48 to 34 Ma) ice sheets (10 to 30 m changes). Continental-scale ice sheets (“Icehouse”) began ~34 Ma (>50 m changes), permanent East Antarctic ice sheets at 12.8 Ma, and bipolar glaciation at 2.5 Ma. The largest GMSL fall (27 to 20 ka; ~130 m) was followed by a >40 mm/yr rise (19 to 10 ka), a slowing (10 to 2 ka), and a stillstand until ~1900 CE, when rates began to rise. High long-term CO2 caused warm climates and high sea levels, with sea-level variability dominated by periodic Milankovitch cycles.
To detect possible SARS-CoV-2 RNA contamination of inanimate surfaces in areas at high risk of aerosol formation by patients with COVID-19.
Low-income countries have reduced health care system capacity and are therefore at risk of substantially higher COVID-19 case fatality rates than those currently seen in high-income countries. Handwashing is a key component of guidance to reduce transmission of the SARS-CoV-2 virus, responsible for the COVID-19 pandemic. Prior systematic reviews have indicated the effectiveness of handwashing to reduce transmission of respiratory viruses. In low-income countries, reduction of transmission is of paramount importance, but social distancing is challenged by high population densities and access to handwashing facilities with soap and water is limited.
To understand the epidemiology and burden of severe coronavirus disease 2019 (covid-19) during the first epidemic wave on the west coast of the United States.
There is ample evidence that morphological and social cues in a human face provide signals of human personality and behaviour. Previous studies have discovered associations between the features of artificial composite facial images and attributions of personality traits by human experts. We present new findings demonstrating the statistically significant prediction of a wider set of personality features (all the Big Five personality traits) for both men and women using real-life static facial images. Volunteer participants (N = 12,447) provided their face photographs (31,367 images) and completed a self-report measure of the Big Five traits. We trained a cascade of artificial neural networks (ANNs) on a large labelled dataset to predict self-reported Big Five scores. The highest correlations between observed and predicted personality scores were found for conscientiousness (0.360 for men and 0.335 for women) and the mean effect size was 0.243, exceeding the results obtained in prior studies using ‘selfies’. The findings strongly support the possibility of predicting multidimensional personality profiles from static facial images using ANNs trained on large labelled datasets. Future research could investigate the relative contribution of morphological features of the face and other characteristics of facial images to predicting personality.