Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Oviposition responses of Anopheles gambiae s.s. (Diptera: Culicidae) and identification of volatiles from bacteria-containing solutions

In this study, a dual-choice oviposition bioassay was used to screen responses of gravid An. gambiae toward 17 bacterial species, previously isolated from Anopheles gambiae s.l. (Diptera: Culicidae) midguts or oviposition sites. The 10 isolates from oviposition sites have been identified by phylogenetic analyses of their 16S rRNA genes. Eight of the 10 isolates were gram-positive, out of which six belonged to the Bacilli class. Solid phase microextraction and gas chromatography coupled to mass spectrometry (GC-MS) were used to identify the volatiles emitted from the bacterial isolates. Aromatic and aliphatic alcohols, aliphatic ketones, alkylpyrazines, dimethyl oligosulfides, and indole were among the chemical compounds identified from the headspace above bacteria-containing saline. The mosquitoes laid significantly more eggs in six of the bacteria-containing solutions compared with the sterile solution. These six bacteria did not emit any compounds in common that could explain the positive oviposition response. Instead, the bacteria were grouped according to principal component analysis (PCA) based on the relative amounts of volatiles emitted. The PCA-plots facilitated the identification of 13 putative oviposition attractants for An. gambiae mosquitoe

Discovery of an oviposition attractant for gravid malaria vectors of the Anopheles gambiae species complex

Background New strategies are needed to manage malaria vector populations that resist insecticides and bite outdoors. This study describes a breakthrough in developing ‘attract and kill’ strategies targeting gravid females by identifying and evaluating an oviposition attractant for Anopheles gambiae s.l.. Methods Previously, the authors found that gravid An. gambiae s.s. females were two times more likely to lay eggs in lake water infused for six days with soil from a natural oviposition site in western Kenya compared to lake water alone or to the same but autoclaved infusion. Here, the volatile chemicals released from these substrates were analysed with a gas-chromatograph coupled to a mass-spectrometer (GC-MS). Furthermore, the behavioural responses of gravid females to one of the compounds identified were evaluated in dual choice egg-count bioassays, in dual-choice semi-field experiments with odour-baited traps and in field bioassays. Results One of the soil infusion volatiles was readily identified as the sesquiterpene alcohol cedrol. Its widespread presence in natural aquatic habitats in the study area was confirmed by analysing the chemical headspace of 116 water samples collected from different aquatic sites in the field and was therefore selected for evaluation in oviposition bioassays. Twice as many gravid females were attracted to cedrol-treated water than to water alone in two choice cage bioassays (odds ratio (OR) 1.84; 95% confidence interval (CI) 1.16-2.91) and in experiments conducted in large-screened cages with free-flying mosquitoes (OR 1.92; 95% CI 1.63-2.27). When tested in the field, wild malaria vector females were three times more likely to be collected in the traps baited with cedrol than in the traps containing water alone (OR 3.3; 95% CI 1.4-7.9). Conclusion Cedrol is the first compound confirmed as an oviposition attractant for gravid An. gambiae s.l.. This finding paves the way for developing new ‘attract and kill strategies’ for malaria vector control

Focus+context visualization techniques for displaying large lists with multiple points of interest on small tactile screens

Abstract. This paper presents a focus+context visualization and interaction technique for displaying large lists on handheld devices. This technique has been specifically designed to fit the constraints of small tactile screens. Thanks to its spiral layout, it provides a global view of large lists on a limited amount of screen real-estate. It has also been designed to allow direct interaction with fingers. This technique proposes an alternative to multi-focus visualization, called “augmented context”, where several objects of interest can be pointed up simultaneously. We propose two implementations of this approach that either use spatial or temporal composition. We conducted a controlled experiment that compares our approach to standard scrollable lists for a search task on a PDA phone. Results show that our technique significantly reduces the error rate (about 3.7 times lower) without loss of performance

Determining the Effect of Menu Element Size on Usability of Mobile Applications

As smartphones gain more and more prominence in the life of the public and are increasingly used for daily tasks, the usability of mobile applications accessed through smartphones becomes a growing concern. This two-part study looks at the usability of such applications, focusing on how the size of menu elements affects the usability of mobile applications. In the first study, users were asked to complete an online questionnaire regarding their preferences in relation to smartphone use and mobile applications. In the second study, a non-parametric t-test was used to identify how the size of menu elements affects the usability of mobile applications. Users were asked to complete a specific task navigating two different prototype mobile applications by clicking specific menu options and answering questionnaires to document their experiences. The results of this study found increased element size does increase user preference and overall usability. © 2013 Springer-Verlag Berlin Heidelberg