81 research outputs found

    Pronounced zonal heterogeneity in Eocene southern high-latitude sea surface temperatures

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    Paleoclimate studies suggest that increased global warmth during the Eocene epoch was greatly amplified at high latitudes, a state that climate models cannot fully reproduce. However, proxy estimates of Eocene near-Antarctic sea surface temperatures (SSTs) have produced widely divergent results at similar latitudes, with SSTs above 20 °C in the southwest Pacific contrasting with SSTs between 5 and 15 °C in the South Atlantic. Validation of this zonal temperature difference has been impeded by uncertainties inherent to the individual paleotemperature proxies applied at these sites. Here, we present multiproxy data from Seymour Island, near the Antarctic Peninsula, that provides well-constrained evidence for annual SSTs of 10–17 °C (1σ SD) during the middle and late Eocene. Comparison of the same paleotemperature proxy at Seymour Island and at the East Tasman Plateau indicate the presence of a large and consistent middle-to-late Eocene SST gradient of ∌7 °C between these two sites located at similar paleolatitudes. Intermediate-complexity climate model simulations suggest that enhanced oceanic heat transport in the South Pacific, driven by deep-water formation in the Ross Sea, was largely responsible for the observed SST gradient. These results indicate that very warm SSTs, in excess of 18 °C, did not extend uniformly across the Eocene southern high latitudes, and suggest that thermohaline circulation may partially control the distribution of high-latitude ocean temperatures in greenhouse climates. The pronounced zonal SST heterogeneity evident in the Eocene cautions against inferring past meridional temperature gradients using spatially limited data within given latitudinal bands

    Peaks and Troughs of Three-Dimensional Vestibulo-ocular Reflex in Humans

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    The three-dimensional vestibulo-ocular reflex (3D VOR) ideally generates compensatory ocular rotations not only with a magnitude equal and opposite to the head rotation but also about an axis that is collinear with the head rotation axis. Vestibulo-ocular responses only partially fulfill this ideal behavior. Because animal studies have shown that vestibular stimulation about particular axes may lead to suboptimal compensatory responses, we investigated in healthy subjects the peaks and troughs in 3D VOR stabilization in terms of gain and alignment of the 3D vestibulo-ocular response. Six healthy upright sitting subjects underwent whole body small amplitude sinusoidal and constant acceleration transients delivered by a six-degree-of-freedom motion platform. Subjects were oscillated about the vertical axis and about axes in the horizontal plane varying between roll and pitch at increments of 22.5° in azimuth. Transients were delivered in yaw, roll, and pitch and in the vertical canal planes. Eye movements were recorded in with 3D search coils. Eye coil signals were converted to rotation vectors, from which we calculated gain and misalignment. During horizontal axis stimulation, systematic deviations were found. In the light, misalignment of the 3D VOR had a maximum misalignment at about 45°. These deviations in misalignment can be explained by vector summation of the eye rotation components with a low gain for torsion and high gain for vertical. In the dark and in response to transients, gain of all components had lower values. Misalignment in darkness and for transients had different peaks and troughs than in the light: its minimum was during pitch axis stimulation and its maximum during roll axis stimulation. We show that the relatively large misalignment for roll in darkness is due to a horizontal eye movement component that is only present in darkness. In combination with the relatively low torsion gain, this horizontal component has a relative large effect on the alignment of the eye rotation axis with respect to the head rotation axis

    Lymphovascular invasion quantification could improve risk prediction of lymph node metastases in patients with submucosal (T1b) esophageal adenocarcinoma

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    AIM: To quantify lymphovascular invasion (LVI) and to assess the prognostic value in patients with pT1b esophageal adenocarcinoma. METHODS: In this nationwide, retrospective cohort study, patients were included if they were treated with surgery or endoscopic resection for pT1b esophageal adenocarcinoma. Primary endpoint was the presence of metastases, lymph node metastases, or distant metastases, in surgical resection specimens or during follow‐up. A prediction model to identify risk factors for metastases was developed and internally validated. RESULTS: 248 patients were included. LVI was distributed as follows: no LVI (n = 196; 79.0%), 1 LVI focus (n = 16; 6.5%), 2–3 LVI foci (n = 21; 8.5%) and ≄4 LVI foci (n = 15; 6.0%). Seventy‐eight patients had metastases. The risk of metastases was increased for tumors with 2–3 LVI foci [subdistribution hazard ratio (SHR) 3.39, 95% confidence interval (CI) 2.10–5.47] and ≄4 LVI foci (SHR 3.81, 95% CI 2.37–6.10). The prediction model demonstrated a good discriminative ability (c‐statistic 0.81). CONCLUSION: The risk of metastases is higher when more LVI foci are present. Quantification of LVI could be useful for a more precise risk estimation of metastases. This model needs to be externally validated before implementation into clinical practice

    Individual risk calculator to predict lymph node metastases in patients with submucosal (T1b) esophageal adenocarcinoma:a multicenter cohort study

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    Background Lymph node metastasis (LNM) is possible after endoscopic resection of early esophageal adenocarcinoma (EAC). This study aimed to develop and internally validate a prediction model that estimates the individual risk of metastases in patients with pT1b EAC. Methods A nationwide, retrospective, multicenter cohort study was conducted in patients with pT1b EAC treated with endoscopic resection and/or surgery between 1989 and 2016. The primary end point was presence of LNM in surgical resection specimens or detection of metastases during follow-up. All resection specimens were histologically reassessed by specialist gastrointestinal pathologists. Subdistribution hazard regression analysis was used to develop the prediction model. The discriminative ability of this model was assessed using the c-statistic. Results 248 patients with pT1b EAC were included. Metastases were seen in 78 patients, and the 5-year cumulative incidence was 30.9 % (95 % confidence interval [CI] 25.1 %-36.8 %). The risk of metastases increased with submucosal invasion depth (subdistribution hazard ratio [SHR] 1.08, 95 %CI 1.02-1.14, for every increase of 500 ÎŒm), lymphovascular invasion (SHR 2.95, 95 %CI 1.95-4.45), and for larger tumors (SHR 1.23, 95 %CI 1.10-1.37, for every increase of 10 mm). The model demonstrated good discriminative ability (c-statistic 0.81, 95 %CI 0.75-0.86). Conclusions A third of patients with pT1b EAC experienced metastases within 5 years. The probability of developing post-resection metastases was estimated with a personalized predicted risk score incorporating tumor invasion depth, tumor size, and lymphovascular invasion. This model requires external validation before implementation into clinical practice

    A walking programme and a supervised exercise class versus usual physiotherapy for chronic low back pain: a single-blinded randomised controlled trial. (The Supervised Walking In comparison to Fitness Training for Back Pain (SWIFT) Trial)

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    BACKGROUND: Chronic low back pain (CLBP) is a persistent disabling condition with rising significant healthcare, social and economic costs. Current research supports the use of exercise-based treatment approaches that encourage people with CLBP to assume a physically active role in their recovery. While international clinical guidelines and systematic reviews for CLBP support supervised group exercise as an attractive first-line option for treating large numbers of CLBP patients at low cost, barriers to their delivery include space and time restrictions in healthcare settings and poor patient attendance. The European Clinical Guidelines have identified the need for research in the use of brief/minimal contact self-activation interventions that encourage participation in physical activity for CLBP. Walking may be an ideally suited form of individualized exercise prescription as it is easy to do, requires no special skills or facilities, and is achievable by virtually all ages with little risk of injury, but its effectiveness for LBP is unproven. METHODS AND DESIGN: This study will be an assessor-blinded randomized controlled trial that will investigate the difference in clinical effectiveness and costs of an individualized walking programme and a supervised general exercise programme compared to usual physiotherapy, which will act as the control group, in people with chronic low back pain. A sample of 246 patients will be recruited in Dublin, Ireland through acute general hospital outpatient physiotherapy departments that provide treatment for people with CLBP. Patients will be randomly allocated to one of the three groups in a concealed manner. The main outcomes will be functional disability, pain, quality of life, fear avoidance, back beliefs, physical activity, satisfaction and costs, which will be evaluated at baseline, and 3, 6 and 12 months [follow-up by pre-paid postage]. Qualitative telephone interviews and focus groups will be embedded in the research design to obtain feedback about participants' experiences of the interventions and trial participation, and to inform interpretation of the quantitative data. Planned analysis will be by intention to treat (quantitative data) and thematic analysis (qualitative data) DISCUSSION: The trial will evaluate the effectiveness of a walking programme and a supervised general exercise programme compared to usual physiotherapy in people with CLBP. TRIAL REGISTRATION: Current controlled trial ISRCTN1759209

    Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: a modelling study

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    Background: The risk of severe COVID-19 if an individual becomes infected is known to be higher in older individuals and those with underlying health conditions. Understanding the number of individuals at increased risk of severe COVID-19 and how this varies between countries should inform the design of possible strategies to shield or vaccinate those at highest risk. Methods: We estimated the number of individuals at increased risk of severe disease (defined as those with at least one condition listed as “at increased risk of severe COVID-19” in current guidelines) by age (5-year age groups), sex, and country for 188 countries using prevalence data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 and UN population estimates for 2020. The list of underlying conditions relevant to COVID-19 was determined by mapping the conditions listed in GBD 2017 to those listed in guidelines published by WHO and public health agencies in the UK and the USA. We analysed data from two large multimorbidity studies to determine appropriate adjustment factors for clustering and multimorbidity. To help interpretation of the degree of risk among those at increased risk, we also estimated the number of individuals at high risk (defined as those that would require hospital admission if infected) using age-specific infection–hospitalisation ratios for COVID-19 estimated for mainland China and making adjustments to reflect country-specific differences in the prevalence of underlying conditions and frailty. We assumed males were twice at likely as females to be at high risk. We also calculated the number of individuals without an underlying condition that could be considered at increased risk because of their age, using minimum ages from 50 to 70 years. We generated uncertainty intervals (UIs) for our estimates by running low and high scenarios using the lower and upper 95% confidence limits for country population size, disease prevalences, multimorbidity fractions, and infection–hospitalisation ratios, and plausible low and high estimates for the degree of clustering, informed by multimorbidity studies. Findings: We estimated that 1·7 billion (UI 1·0–2·4) people, comprising 22% (UI 15–28) of the global population, have at least one underlying condition that puts them at increased risk of severe COVID-19 if infected (ranging from <5% of those younger than 20 years to >66% of those aged 70 years or older). We estimated that 349 million (186–787) people (4% [3–9] of the global population) are at high risk of severe COVID-19 and would require hospital admission if infected (ranging from <1% of those younger than 20 years to approximately 20% of those aged 70 years or older). We estimated 6% (3–12) of males to be at high risk compared with 3% (2–7) of females. The share of the population at increased risk was highest in countries with older populations, African countries with high HIV/AIDS prevalence, and small island nations with high diabetes prevalence. Estimates of the number of individuals at increased risk were most sensitive to the prevalence of chronic kidney disease, diabetes, cardiovascular disease, and chronic respiratory disease. Interpretation: About one in five individuals worldwide could be at increased risk of severe COVID-19, should they become infected, due to underlying health conditions, but this risk varies considerably by age. Our estimates are uncertain, and focus on underlying conditions rather than other risk factors such as ethnicity, socioeconomic deprivation, and obesity, but provide a starting point for considering the number of individuals that might need to be shielded or vaccinated as the global pandemic unfolds. Funding: UK Department for International Development, Wellcome Trust, Health Data Research UK, Medical Research Council, and National Institute for Health Research

    An expanded evaluation of protein function prediction methods shows an improvement in accuracy

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    Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent. Keywords: Protein function prediction, Disease gene prioritizationpublishedVersio

    An Expanded Evaluation of Protein Function Prediction Methods Shows an Improvement In Accuracy

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    Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent
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