Sleep Diplomacy: an Approach to Boosting global brain health

Sleep diplomacy highlights the urgent need to address the widespread issue of sleep deprivation and its detrimental effects on overall health, particularly brain health and healthy ageing. By providing practical advice on sleep hygiene, healthy schedules, and light exposure, sleep diplomacy aims to promote a comprehensive approach to well-being. Despite the well-established importance of sleep for optimal cognitive function, emotional regulation, and physical abilities, it is often neglected in public and medical recommendations. Our proposed concept of sleep diplomacy also offers practical recommendations to address sleep issues in various settings and populations

Adaptation, Transformation and Resilience in Healthcare Comment on “Government Actions and Their Relation to Resilience in Healthcare During the COVID-19 Pandemic in New South Wales, Australia and Ontario, Canada”

Adaptive capacity is a critical component of building resilience in healthcare (RiH). Adaptive capacity comprises the ability of a system to cope with and adapt to disturbances. However, “shocks,” such as the current coronavirus disease 2019 (COVID-19) pandemic, can potentially exceed critical adaptation thresholds and lead to systemic collapse. To effectively manage healthcare systems during periods of crises, both adaptive and transformative changes are necessary. This commentary discusses adaptation and transformation as two complementary, integral components of resilience and applies them to healthcare. We treat resilience as an emergent property of complex systems that accounts for multiple, often disparately distinct regimes in which multiple processes (eg, adaptation, recovery) are subsumed and operate. We argue that Convergence Mental Health and other transdisciplinary paradigms such as Brain Capital and One Health can facilitate resilience planning and management in healthcare systems

Affective Computing for Late-Life Mood and Cognitive Disorders

Affective computing (also referred to as artificial emotion intelligence or emotion AI) is the study and development of systems and devices that can recognize, interpret, process, and simulate emotion or other affective phenomena. With the rapid growth in the aging population around the world, affective computing has immense potential to benefit the treatment and care of late-life mood and cognitive disorders. For late-life depression, affective computing ranging from vocal biomarkers to facial expressions to social media behavioral analysis can be used to address inadequacies of current screening and diagnostic approaches, mitigate loneliness and isolation, provide more personalized treatment approaches, and detect risk of suicide. Similarly, for Alzheimer\u27s disease, eye movement analysis, vocal biomarkers, and driving and behavior can provide objective biomarkers for early identification and monitoring, allow more comprehensive understanding of daily life and disease fluctuations, and facilitate an understanding of behavioral and psychological symptoms such as agitation. To optimize the utility of affective computing while mitigating potential risks and ensure responsible development, ethical development of affective computing applications for late-life mood and cognitive disorders is needed

Large scale variation in the rate of germ-line de novo mutation, base composition, divergence and diversity in humans

It has long been suspected that the rate of mutation varies across the human genome at a large scale based on the divergence between humans and other species. However, it is now possible to directly investigate this question using the large number of de novo mutations (DNMs) that have been discovered in humans through the sequencing of trios. We investi- gate a number of questions pertaining to the distribution of mutations using more than 130,000 DNMs from three large datasets. We demonstrate that the amount and pattern of variation differs between datasets at the 1MB and 100KB scales probably as a consequence of differences in sequencing technology and processing. In particular, datasets show differ- ent patterns of correlation to genomic variables such as replication time. Never-the-less there are many commonalities between datasets, which likely represent true patterns. We show that there is variation in the mutation rate at the 100KB, 1MB and 10MB scale that can- not be explained by variation at smaller scales, however the level of this variation is modest at large scales–at the 1MB scale we infer that ~90% of regions have a mutation rate within 50% of the mean. Different types of mutation show similar levels of variation and appear to vary in concert which suggests the pattern of mutation is relatively constant across the genome. We demonstrate that variation in the mutation rate does not generate large-scale variation in GC-content, and hence that mutation bias does not maintain the isochore struc- ture of the human genome. We find that genomic features explain less than 40% of the explainable variance in the rate of DNM. As expected the rate of divergence between spe- cies is correlated to the rate of DNM. However, the correlations are weaker than expected if all the variation in divergence was due to variation in the mutation rate. We provide evidence that this is due the effect of biased gene conversion on the probability that a mutation will become fixed. In contrast to divergence, we find that most of the variation in diversity can be explained by variation in the mutation rate. Finally, we show that the correlation between divergence and DNM density declines as increasingly divergent species are considered

Nonlinear bias correction for satellite data assimilation using Taylor series polynomials

Output from a high-resolution ensemble data assimilation system is used to assess the ability of an innovative nonlinear bias correction (BC) method that uses a Taylor series polynomial expansion of the observation-minus background departures to remove linear and nonlinear conditional biases from all-sky satellite infrared brightness temperatures. Univariate and multivariate experiments were performed in which the satellite zenith angle and variables sensitive to clouds and water vapor were used as the BC predictors. The results showed that even though the bias of the entire observation departure distribution is equal to zero regardless of the order of the Taylor series expansion, there are often large conditional biases that vary as a nonlinear function of the BC predictor. The linear 1st order term had the largest impact on the entire distribution as measured by reductions in variance; however, large conditional biases often remained in the distribution when plotted as a function of the predictor. These conditional biases were typically reduced to near zero when the nonlinear 2nd and 3rd order terms were used. The univariate results showed that variables sensitive to the cloud top height are effective BC predictors especially when higher order Taylor series terms are used. Comparison of the statistics for clear-sky and cloudy-sky observations revealed that nonlinear departures are more important for cloudy-sky observations as signified by the much larger impact of the 2nd and 3rd order terms on the conditional biases. Together, these results indicate that the nonlinear BC method is able to effectively remove the bias from all-sky infrared observation departures

Virus Replication as a Phenotypic Version of Polynucleotide Evolution

In this paper we revisit and adapt to viral evolution an approach based on the theory of branching process advanced by Demetrius, Schuster and Sigmund ("Polynucleotide evolution and branching processes", Bull. Math. Biol. 46 (1985) 239-262), in their study of polynucleotide evolution. By taking into account beneficial effects we obtain a non-trivial multivariate generalization of their single-type branching process model. Perturbative techniques allows us to obtain analytical asymptotic expressions for the main global parameters of the model which lead to the following rigorous results: (i) a new criterion for "no sure extinction", (ii) a generalization and proof, for this particular class of models, of the lethal mutagenesis criterion proposed by Bull, Sanju\'an and Wilke ("Theory of lethal mutagenesis for viruses", J. Virology 18 (2007) 2930-2939), (iii) a new proposal for the notion of relaxation time with a quantitative prescription for its evaluation, (iv) the quantitative description of the evolution of the expected values in in four distinct "stages": extinction threshold, lethal mutagenesis, stationary "equilibrium" and transient. Finally, based on these quantitative results we are able to draw some qualitative conclusions.Comment: 23 pages, 1 figure, 2 tables. arXiv admin note: substantial text overlap with arXiv:1110.336

Transmission of Staphylococcus aureus between health-care workers, the environment, and patients in an intensive care unit: a longitudinal cohort study based on whole-genome sequencing

Background: Health-care workers have been implicated in nosocomial outbreaks of Staphylococcus aureus, but the dearth of evidence from non-outbreak situations means that routine health-care worker screening and S aureus eradication are controversial. We aimed to determine how often S aureus is transmitted from health-care workers or the environment to patients in an intensive care unit (ICU) and a high-dependency unit (HDU) where standard infection control measures were in place. Methods: In this longitudinal cohort study, we systematically sampled health-care workers, the environment, and patients over 14 months at the ICU and HDU of the Royal Sussex County Hospital, Brighton, England. Nasal swabs were taken from health-care workers every 4 weeks, bed spaces were sampled monthly, and screening swabs were obtained from patients at admission to the ICU or HDU, weekly thereafter, and at discharge. Isolates were cultured and their whole genome sequenced, and we used the threshold of 40 single-nucleotide variants (SNVs) or fewer to define subtypes and infer recent transmission. Findings: Between Oct 31, 2011, and Dec 23, 2012, we sampled 198 health-care workers, 40 environmental locations, and 1854 patients; 1819 isolates were sequenced. Median nasal carriage rate of S aureus in health-care workers at 4-weekly timepoints was 36·9% (IQR 35·7–37·3), and 115 (58%) health-care workers had S aureus detected at least once during the study. S aureus was identified in 8–50% of environmental samples. 605 genetically distinct subtypes were identified (median SNV difference 273, IQR 162–399) at a rate of 38 (IQR 34–42) per 4-weekly cycle. Only 25 instances of transmission to patients (seven from health-care workers, two from the environment, and 16 from other patients) were detected. Interpretation: In the presence of standard infection control measures, health-care workers were infrequently sources of transmission to patients. S aureus epidemiology in the ICU and HDU is characterised by continuous ingress of distinct subtypes rather than transmission of genetically related strains. Funding: UK Medical Research Council, Wellcome Trust, Biotechnology and Biological Sciences Research Council, UK National Institute for Health Research, and Public Health England

Comprehensive analysis of the base composition around the transcription start site in Metazoa

BACKGROUND: The transcription start site of a metazoan gene remains poorly understood, mostly because there is no clear signal present in all genes. Now that several sequenced metazoan genomes have been annotated, we have been able to compare the base composition around the transcription start site for all annotated genes across multiple genomes. RESULTS: The most prominent feature in the base compositions is a significant local variation in G+C content over a large region around the transcription start site. The change is present in all animal phyla but the extent of variation is different between distinct classes of vertebrates, and the shape of the variation is completely different between vertebrates and arthropods. Furthermore, the height of the variation correlates with CpG frequencies in vertebrates but not in invertebrates and it also correlates with gene expression, especially in mammals. We also detect GC and AT skews in all clades (where %G is not equal to %C or %A is not equal to %T respectively) but these occur in a more confined region around the transcription start site and in the coding region. CONCLUSIONS: The dramatic changes in nucleotide composition in humans are a consequence of CpG nucleotide frequencies and of gene expression, the changes in Fugu could point to primordial CpG islands, and the changes in the fly are of a totally different kind and unrelated to dinucleotide frequencies

The SR-BI Partner PDZK1 Facilitates Hepatitis C Virus Entry

Entry of hepatitis C virus (HCV) into hepatocytes is a multi-step process that involves a number of different host cell factors. Following initial engagement with glycosaminoglycans and the low-density lipoprotein receptor, it is thought that HCV entry proceeds via interactions with the tetraspanin CD81, scavenger receptor class B type I (SR-BI), and the tight-junction proteins claudin-1 (CLDN1) and occludin (OCLN), culminating in clathrin-dependent endocytosis of HCV particles and their pH-dependent fusion with endosomal membranes. Physiologically, SR-BI is the major receptor for high-density lipoproteins (HDL) in the liver, where its expression is primarily controlled at the post-transcriptional level by its interaction with the scaffold protein PDZK1. However, the importance of interaction with PDZK1 to the involvement of SR-BI in HCV entry is unclear. Here we demonstrate that stable shRNA-knockdown of PDZK1 expression in human hepatoma cells significantly reduces their susceptibility to HCV infection, and that this effect can be reversed by overexpression of full length PDZK1 but not the first PDZ domain of PDZK1 alone. Furthermore, we found that overexpression of a green fluorescent protein chimera of the cytoplasmic carboxy-terminus of SR-BI (amino acids 479–509) in Huh-7 cells resulted in its interaction with PDZK1 and a reduced susceptibility to HCV infection. In contrast a similar chimera lacking the final amino acid of SR-BI (amino acids 479–508) failed to interact with PDZK1 and did not inhibit HCV infection. Taken together these results indicate an indirect involvement of PDZK1 in HCV entry via its ability to interact with SR-BI and enhance its activity as an HCV entry factor