Data collection, handling and fitting strategies to optimize accuracy and precision of oxygen uptake kinetics estimation from breath-by-breath measurements.

Phase 2 pulmonary oxygen uptake kinetics (ϕ2 τVO2P) reflect muscle oxygen consumption dynamics and are sensitive to changes in state of training or health. This study identified an unbiased method for data collection, handling and fitting to optimize VO2P kinetics estimation. A validated computational model of VO2P kinetics and a Monte Carlo approach simulated 2 x 10(5) moderate intensity transitions using a distribution of metabolic and circulatory parameters spanning normal health. Effects of averaging (interpolation, binning, stacking or separate fitting of up to 10 transitions) and fitting procedures (bi-exponential fitting, or ϕ2 isolation by time removal, statistical or derivative methods followed by mono-exponential fitting) on accuracy and precision of ϕ2 τVO2P estimation were assessed. The optimal strategy to maximize accuracy and precision of τVO2P estimation was 1-s interpolation of 4 bouts, ensemble averaged, with the first 20 s of exercise data removed. Contradictory to previous advice, we found optimal fitting procedures removed no more than 20 s of ϕ1 data. Averaging method was less critical: interpolation, bin averaging and stacking gave similar results, each with greater accuracy compared to analyzing repeated bouts separately. The optimal procedure resulted in ϕ2 τVO2P estimates for transitions from an unloaded or loaded baseline that averaged 1.97±2.08 and 1.04±2.30 s from true, but were within 2 s of true in only 47-62% of simulations. Optimized 95% confidence intervals for τVO2P ranged from 4.08-4.51 s, suggesting a minimally important difference of ~5 s to determine significant changes in τVO2P during interventional and comparative studies

Artificial intelligence in cancer imaging: Clinical challenges and applications

Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only its variegated forms with evolution of disease but also the need to take into account the individual condition of patients, their ability to receive treatment, and their responses to treatment. Challenges remain in the accurate detection, characterization, and monitoring of cancers despite improved technologies. Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises to make great strides in the qualitative interpretation of cancer imaging by expert clinicians, including volumetric delineation of tumors over time, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs. AI may automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions on whether or not to administer an intervention, and subsequent observation to a yet to be envisioned paradigm. Here, the authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types (lung, brain, breast, and prostate) to illustrate how common clinical problems are being addressed. Although most studies evaluating AI applications in oncology to date have not been vigorously validated for reproducibility and generalizability, the results do highlight increasingly concerted efforts in pushing AI technology to clinical use and to impact future directions in cancer care

The evolution of mammalian brain size

Relative brain size has long been considered a reflection of cognitive capacities and has played a fundamental role in developing core theories in the life sciences. Yet, the notion that relative brain size validly represents selection on brain size relies on the untested assumptions that brain-body allometry is restrained to a stable scaling relationship across species and that any deviation from this slope is due to selection on brain size. Using the largest fossil and extant dataset yet assembled, we find that shifts in allometric slope underpin major transitions in mammalian evolution and are often primarily characterized by marked changes in body size. Our results reveal that the largest-brained mammals achieved large relative brain sizes by highly divergent paths. These findings prompt a reevaluation of the traditional paradigm of relative brain size and open new opportunities to improve our understanding of the genetic and developmental mechanisms that influence brain size

Evaluation of a standard provision versus an autonomy promotive exercise referral programme: rationale and study design

Background The National Institute of Clinical Excellence in the UK has recommended that the effectiveness of ongoing exercise referral schemes to promote physical activity should be examined in research trials. Recent empirical evidence in health care and physical activity promotion contexts provides a foundation for testing the utility of a Self Determination Theory (SDT) -based exercise referral consultation. Methods/Design Design: An exploratory cluster randomised controlled trial comparing standard provision exercise on prescription with a Self Determination Theory-based (SDT) exercise on prescription intervention. Participants: 347 people referred to the Birmingham Exercise on Prescription scheme between November 2007 and July 2008. The 13 exercise on prescription sites in Birmingham were randomised to current practice (n=7) or to the SDT-based intervention (n=6). Outcomes measured at 3 and 6-months: Minutes of moderate or vigorous physical activity per week assessed using the 7-day Physical Activity Recall; physical health: blood pressure and weight; health status measured using the Dartmouth CO-OP charts; anxiety and depression measured by the Hospital Anxiety and Depression Scale and vitality measured by the subjective vitality score; motivation and processes of change: perceptions of autonomy support from the advisor, satisfaction of the needs for competence, autonomy, and relatedness via physical activity, and motivational regulations for exercise. Discussion This trial will determine whether an exercise referral programme based on Self Determination Theory increases physical activity and other health outcomes compared to a standard programme and will test the underlying SDT-based process model (perceived autonomy support, need satisfaction, motivation regulations, outcomes) via structural equation modelling. Trial registration The trial is registered as Current Controlled trials ISRCTN07682833

Changes in Weight, Waist Circumference and Compensatory Responses with Different Doses of Exercise among Sedentary, Overweight Postmenopausal Women

It has been suggested that exercise training results in compensatory mechanisms that attenuate weight loss. However, this has only been examined with large doses of exercise. The goal of this analysis was to examine actual weight loss compared to predicted weight loss (compensation) across different doses of exercise in a controlled trial of sedentary, overweight or obese postmenopausal women (n = 411).Participants were randomized to a non-exercise control (n = 94) or 1 of 3 exercise groups; exercise energy expenditure of 4 (n = 139), 8 (n = 85), or 12 (n = 93) kcal/kg/week (KKW). Training intensity was set at the heart rate associated with 50% of each woman's peak VO(2) and the intervention period was 6 months. All exercise was supervised. The main outcomes were actual weight loss, predicted weight loss (exercise energy expenditure/ 7700 kcal per kg), compensation (actual minus predicted weight loss) and waist circumference. The study sample had a mean (SD) age 57.2 (6.3) years, BMI of 31.7 (3.8) kg/m(2), and was 63.5% Caucasian. The adherence to the intervention was >99% in all exercise groups. The mean (95% CI) weight loss in the 4, 8 and 12 KKW groups was -1.4 (-2.0, -0.8), -2.1 (-2.9, -1.4) and -1.5 (-2.2, -0.8) kg, respectively. In the 4 and 8 KKW groups the actual weight loss closely matched the predicted weight loss of -1.0 and -2.0 kg, respectively, resulting in no significant compensation. In the 12 KKW group the actual weight loss was less than the predicted weight loss (-2.7 kg) resulting in 1.2 (0.5, 1.9) kg of compensation (P<0.05 compared to 4 and 8 KKW groups). All exercise groups had a significant reduction in waist circumference which was independent of changes in weight.In this study of previously sedentary, overweight or obese, postmenopausal women we observed no difference in the actual and predicted weight loss with 4 and 8 KKW of exercise (72 and 136 minutes respectively), while the 12 KKW (194 minutes) produced only about half of the predicted weight loss. However, all exercise groups had a significant reduction in waist circumference which was independent of changes in weight.(ClinicalTrials.gov) NCT00011193

‘You can’t stand on a corner and talk about it …’: Medicinal cannabis use, impression management and the analytical status of interviews

In this article, I examine how four medicinal cannabis users used impression management during in-depth, qualitative interviews to attend to self-presentational concerns. I examine the rhetorical strategies and narratives articulated by the participants while also attending to the role that I played in co-construction as the interviewer. Later I discuss how, although the participants’ accounts are occasioned by the interviews, they can still provide significant insights into the social worlds of the participants beyond the interviews. While discussions about whether to treat interviews as topic, resource or both are not new, I argue that we can treat interviews as both topic and resource because impression management is a product of the individual’s habitus and it and the accounts it produces are part of their social world

Evaporative evolution of a Na–Cl–NO(3)–K–Ca–SO(4)–Mg–Si brine at 95°C: Experiments and modeling relevant to Yucca Mountain, Nevada

A synthetic Topopah Spring Tuff water representative of one type of pore water at Yucca Mountain, NV was evaporated at 95°C in a series of experiments to determine the geochemical controls for brines that may form on, and possibly impact upon the long-term integrity of waste containers and drip shields at the designated high-level, nuclear-waste repository. Solution chemistry, condensed vapor chemistry, and precipitate mineralogy were used to identify important chemical divides and to validate geochemical calculations of evaporating water chemistry using a high temperature Pitzer thermodynamic database. The water evolved toward a complex "sulfate type" brine that contained about 45 mol % Na, 40 mol % Cl, 9 mol % NO(3), 5 mol % K, and less than 1 mol % each of SO(4), Ca, Mg, ∑CO(2)(aq), F, and Si. All measured ions in the condensed vapor phase were below detection limits. The mineral precipitates identified were halite, anhydrite, bassanite, niter, and nitratine. Trends in the solution composition and identification of CaSO(4 )solids suggest that fluorite, carbonate, sulfate, and magnesium-silicate precipitation control the aqueous solution composition of sulfate type waters by removing fluoride, calcium, and magnesium during the early stages of evaporation. In most cases, the high temperature Pitzer database, used by EQ3/6 geochemical code, sufficiently predicts water composition and mineral precipitation during evaporation. Predicted solution compositions are generally within a factor of 2 of the experimental values. The model predicts that sepiolite, bassanite, amorphous silica, calcite, halite, and brucite are the solubility controlling mineral phases

Two novel human cytomegalovirus NK cell evasion functions target MICA for lysosomal degradation

NKG2D plays a major role in controlling immune responses through the regulation of natural killer (NK) cells, αβ and γδ T-cell function. This activating receptor recognizes eight distinct ligands (the MHC Class I polypeptide-related sequences (MIC) A andB, and UL16-binding proteins (ULBP)1–6) induced by cellular stress to promote recognition cells perturbed by malignant transformation or microbial infection. Studies into human cytomegalovirus (HCMV) have aided both the identification and characterization of NKG2D ligands (NKG2DLs). HCMV immediate early (IE) gene up regulates NKGDLs, and we now describe the differential activation of ULBP2 and MICA/B by IE1 and IE2 respectively. Despite activation by IE functions, HCMV effectively suppressed cell surface expression of NKGDLs through both the early and late phases of infection. The immune evasion functions UL16, UL142, and microRNA(miR)-UL112 are known to target NKG2DLs. While infection with a UL16 deletion mutant caused the expected increase in MICB and ULBP2 cell surface expression, deletion of UL142 did not have a similar impact on its target, MICA. We therefore performed a systematic screen of the viral genome to search of addition functions that targeted MICA. US18 and US20 were identified as novel NK cell evasion functions capable of acting independently to promote MICA degradation by lysosomal degradation. The most dramatic effect on MICA expression was achieved when US18 and US20 acted in concert. US18 and US20 are the first members of the US12 gene family to have been assigned a function. The US12 family has 10 members encoded sequentially through US12–US21; a genetic arrangement, which is suggestive of an ‘accordion’ expansion of an ancestral gene in response to a selective pressure. This expansion must have be an ancient event as the whole family is conserved across simian cytomegaloviruses from old world monkeys. The evolutionary benefit bestowed by the combinatorial effect of US18 and US20 on MICA may have contributed to sustaining the US12 gene family

Signal Peptide-Dependent Inhibition of MHC Class I Heavy Chain Translation by Rhesus Cytomegalovirus

The US2-11 region of human and rhesus cytomegalovirus encodes a conserved family of glycoproteins that inhibit MHC-I assembly with viral peptides, thus preventing cytotoxic T cell recognition. Since HCMV lacking US2-11 is no longer able to block assembly and transport of MHC-I, we examined whether this is also observed for RhCMV lacking the corresponding region. Unexpectedly, recombinant RhCMV lacking US2-11 was still able to inhibit MHC-I expression in infected fibroblasts, suggesting the presence of an additional MHC-I evasion mechanism. Progressive deletion analysis of RhCMV-specific genomic regions revealed that MHC-I expression is fully restored upon additional deletion of rh178. The protein encoded by this RhCMV-specific open reading frame is anchored in the endoplasmic reticulum membrane. In the presence of rh178, RhCMV prevented MHC-I heavy chain (HC) expression, but did not inhibit mRNA transcription or association of HC mRNA with translating ribosomes. Proteasome inhibitors stabilized a HC degradation intermediate in the absence of rh178, but not in its presence, suggesting that rh178 prevents completion of HC translation. This interference was signal sequence-dependent since replacing the signal peptide with that of CD4 or murine HC rendered human HCs resistant to rh178. We have identified an inhibitor of antigen presentation encoded by rhesus cytomegalovirus unique in both its lack of homology to any other known protein and in its mechanism of action. By preventing signal sequence-dependent HC translocation, rh178 acts prior to US2, US3 and US11 which attack MHC-I proteins after protein synthesis is completed. Rh178 is the first viral protein known to interfere at this step of the MHC-I pathway, thus taking advantage of the conserved nature of HC leader peptides, and represents a new mechanism of translational interference

Climate change considerations are fundamental to management of deep‐sea resource extraction

Climate change manifestation in the ocean, through warming, oxygen loss, increasing acidification, and changing particulate organic carbon flux (one metric of altered food supply), is projected to affect most deep‐ocean ecosystems concomitantly with increasing direct human disturbance. Climate drivers will alter deep‐sea biodiversity and associated ecosystem services, and may interact with disturbance from resource extraction activities or even climate geoengineering. We suggest that to ensure the effective management of increasing use of the deep ocean (e.g., for bottom fishing, oil and gas extraction, and deep‐seabed mining), environmental management and developing regulations must consider climate change. Strategic planning, impact assessment and monitoring, spatial management, application of the precautionary approach, and full‐cost accounting of extraction activities should embrace climate consciousness. Coupled climate and biological modeling approaches applied in the water and on the seafloor can help accomplish this goal. For example, Earth‐System Model projections of climate‐change parameters at the seafloor reveal heterogeneity in projected climate hazard and time of emergence (beyond natural variability) in regions targeted for deep‐seabed mining. Models that combine climate‐induced changes in ocean circulation with particle tracking predict altered transport of early life stages (larvae) under climate change. Habitat suitability models can help assess the consequences of altered larval dispersal, predict climate refugia, and identify vulnerable regions for multiple species under climate change. Engaging the deep observing community can support the necessary data provisioning to mainstream climate into the development of environmental management plans. To illustrate this approach, we focus on deep‐seabed mining and the International Seabed Authority, whose mandates include regulation of all mineral‐related activities in international waters and protecting the marine environment from the harmful effects of mining. However, achieving deep‐ocean sustainability under the UN Sustainable Development Goals will require integration of climate consideration across all policy sectors.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2020 The Authors. Global Change Biology published by John Wiley & Sons Lt