IntroductionCritically ill patients can develop acute respiratory failure requiring endotracheal intubation. Swallowing dysfunction after liberation from mechanical ventilation, also known as post-extubation dysphagia, is common and deleterious among patients without neurologic disease. However, the risk factors associated with the development of post-extubation dysphagia and its effect on hospital lengthofstay in critically ill patients with neurologic disorders remains relatively unexplored.MethodsWe conducted a retrospective, observational cohort study from 2008 to 2010 of patients with neurologic impairment who required mechanical ventilation and subsequently received a bedside swallow evaluation (BSE) by a speech-language pathologist.ResultsA BSE was performed after mechanical ventilation in 25% (630/2,484) of all patients. In the 184 patients with neurologic impairment, post-extubation dysphagia was present in 93% (171/184), and was classified as mild, moderate, or severe in 34% (62/184), 26% (48/184), and 33% (61/184), respectively. In univariate analyses, statistically significant risk factors for moderate/severe dysphagia included longer durations of mechanical ventilation and the presence of a tracheostomy. In multivariate analysis, adjusting for age, tracheostomy, cerebrovascular disease, and severity of illness, mechanical ventilation for >7 days remained independently associated with moderate/severe dysphagia (adjusted odds ratio = 4.48 (95%confidence interval = 2.14 to 9.81), P<0.01). The presence of moderate/severe dysphagia was also significantly associated with prolonged hospital lengthofstay, discharge status, and surgical placement of feeding tubes. When adjusting for age, severity of illness, and tracheostomy, patients with moderate/severe dysphagia stayed in the hospital 4.32 days longer after their initial BSE than patients with none/mild dysphagia (95% confidence interval = 3.04 to 5.60 days, P <0.01).ConclusionIn a cohort of critically ill patients with neurologic impairment, longer duration of mechanical ventilation is independently associated with post-extubation dysphagia, and the development of post-extubation dysphagia is independently associated with a longer hospital length of stay after the initial BSE.

Understanding intent is an important aspect of communication among people and is an essential component of the human cognitive system. This capability is particularly relevant for situations that involve collaboration among agents or detection of situations that can pose a threat. In this paper, we propose an approach that allows a robot to detect intentions of others based on experience acquired through its own sensory-motor capabilities, then using this experience while taking the perspective of the agent whose intent should be recognized. Our method uses a novel formulation of Hidden Markov Models designed to model a robot's experience and interaction with the world. The robot's capability to observe and analyze the current scene employs a novel vision-based technique for target detection and tracking, using a non-parametric recursive modeling approach. We validate this architecture with a physically embedded robot, detecting the intent of several people performing various activities.

Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

Recent evidence suggests that stochasticism is important for generating cell type diversity. We have identified a novel stochastic fate choice as part of the mechanism by which Delta/Notch (Dl/N) signaling specifies R7 fate in the Drosophila eye. The equivalence of R1/R6/R7 precursors is normally broken by the activation of N, which specifies the R7 fate. The orphan nuclear hormone receptor Seven-up (Svp) is necessary and sufficient to direct R1/R6/R7 precursors to adopt the R1/R6 fate. A simple model, therefore, is that N represses Svp, which otherwise prevents adoption of the R7 fate. However, we have found that R1/R6s lacking svp stochastically adopt either the R7 or the R8 fate with equal likelihood. We show that N specifies the R7 fate by a novel branched pathway: N represses Svp expression, thereby exposing an underlying stochastic choice between the R7 and R8 fates, and then tips this choice towards the R7 fate.

No abstract