134 research outputs found

    Doyne lecture 2016:intraocular health and the many faces of inflammation

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    Dogma for reasons of immune privilege including sequestration (sic) of ocular antigen, lack of lymphatic and immune competent cells in the vital tissues of the eye has long evaporated. Maintaining tissue and cellular health to preserve vision requires active immune responses to prevent damage and respond to danger. A priori the eye must contain immune competent cells, undergo immune surveillance to ensure homoeostasis as well as an ability to promote inflammation. By interrogating immune responses in non-infectious uveitis and compare with age-related macular degeneration (AMD), new concepts of intraocular immune health emerge. The role of macrophage polarisation in the two disorders is a tractable start. TNF-alpha regulation of macrophage responses in uveitis has a pivotal role, supported via experimental evidence and validated by recent trial data. Contrast this with the slow, insidious degeneration in atrophic AMD or in neovasular AMD, with the compelling genetic association with innate immunity and complement, highlights an ability to attenuate pathogenic immune responses and despite known inflammasome activation. Yolk sac-derived microglia maintains tissue immune health. The result of immune cell activation is environmentally dependent, for example, on retinal cell bioenergetics status, autophagy and oxidative stress, and alterations that skew interaction between macrophages and retinal pigment epithelium (RPE). For example, dead RPE eliciting macrophage VEGF secretion but exogenous IL-4 liberates an anti-angiogenic macrophage sFLT-1 response. Impaired autophagy or oxidative stress drives inflammasome activation, increases cytotoxicity, and accentuation of neovascular responses, yet exogenous inflammasome-derived cytokines, such as IL-18 and IL-33, attenuate responses

    f(R) theories

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    Over the past decade, f(R) theories have been extensively studied as one of the simplest modifications to General Relativity. In this article we review various applications of f(R) theories to cosmology and gravity - such as inflation, dark energy, local gravity constraints, cosmological perturbations, and spherically symmetric solutions in weak and strong gravitational backgrounds. We present a number of ways to distinguish those theories from General Relativity observationally and experimentally. We also discuss the extension to other modified gravity theories such as Brans-Dicke theory and Gauss-Bonnet gravity, and address models that can satisfy both cosmological and local gravity constraints.Comment: 156 pages, 14 figures, Invited review article in Living Reviews in Relativity, Published version, Comments are welcom

    The Spatial and Temporal Construction of Confidence in the Visual Scene

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    Human subjects can report many items of a cluttered field a few hundred milliseconds after stimulus presentation. This memory decays rapidly and after a second only 3 or 4 items can be stored in working memory. Here we compared the dynamics of objective performance with a measure of subjective report and we observed that 1) Objective performance beyond explicit subjective reports (blindsight) was significantly more pronounced within a short temporal interval and within specific locations of the visual field which were robust across sessions 2) High confidence errors (false beliefs) were largely confined to a small spatial window neighboring the cue. The size of this window did not change in time 3) Subjective confidence showed a moderate but consistent decrease with time, independent of all other experimental factors. Our study allowed us to asses quantitatively the temporal and spatial access to an objective response and to subjective reports

    Bright light in elderly subjects with nonseasonal major depressive disorder: a double blind randomised clinical trial using early morning bright blue light comparing dim red light treatment

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    <p>Abstract</p> <p>Background</p> <p>Depression frequently occurs in the elderly. Its cause is largely unknown, but several studies point to disturbances of biological rhythmicity. In both normal aging, and depression, the functioning of the suprachiasmatic nucleus (SCN) is impaired, as evidenced by an increased prevalence of day-night rhythm perturbations, such as sleeping disorders. Moreover, the inhibitory SCN neurons on the hypothalamus-pituitary adrenocortical axis (HPA-axis) have decreased activity and HPA-activity is enhanced, when compared to non-depressed elderly. Using bright light therapy (BLT) the SCN can be stimulated. In addition, the beneficial effects of BLT on seasonal depression are well accepted. BLT is a potentially safe, nonexpensive and well accepted treatment option. But the current literature on BLT for depression is inconclusive.</p> <p>Methods/Design</p> <p>This study aims to show whether BLT can reduce non-seasonal major depression in elderly patients. Randomized double blind placebo controlled trial in 126 subjects of 60 years and older with a diagnosis of major depressive disorder (MDD, DSM-IV/SCID-I). Subjects are recruited through referrals of psychiatric outpatient clinics and from case finding from databases of general practitioners and old-people homes in the Amsterdam region. After inclusion subjects are randomly allocated to the active (bright blue light) vs. placebo (dim red light) condition using two Philips Bright Light Energy boxes type HF 3304 per subject, from which the light bulbs have been covered with bright blue- or dim red light- permitting filters. Patients will be stratified by use of antidepressants. Prior to treatment a one-week period without light treatment will be used. At three time points several endocrinological, psychophysiological, psychometrically, neuropsychological measures are performed: just before the start of light therapy, after completion of three weeks therapy period, and three weeks thereafter.</p> <p>Discussion</p> <p>If BLT reduces nonseasonal depression in elderly patients, then additional lightning may easily be implemented in the homes of patients to serve as add-on treatment to antidepressants or as a stand-alone treatment in elderly depressed patients. In addition, if our data support the role of a dysfunctional biological clock in depressed elderly subjects, such a finding may guide further development of novel chronobiological oriented treatment strategies.</p> <p>Trial registration</p> <p>ClinicalTrials.gov identifier: NCT00332670</p

    Accelerated discovery of two crystal structure types in a complex inorganic phase field

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    The discovery of new materials is hampered by the lack of efficient approaches to the exploration of both the large number of possible elemental compositions for such materials, and of the candidate structures at each composition1. For example, the discovery of inorganic extended solid structures has relied on knowledge of crystal chemistry coupled with time-consuming materials synthesis with systematically varied elemental ratios2,3. Computational methods have been developed to guide synthesis by predicting structures at specific compositions4,5,6 and predicting compositions for known crystal structures7,8, with notable successes9,10. However, the challenge of finding qualitatively new, experimentally realizable compounds, with crystal structures where the unit cell and the atom positions within it differ from known structures, remains for compositionally complex systems. Many valuable properties arise from substitution into known crystal structures, but materials discovery using this approach alone risks both missing best-in-class performance and attempting design with incomplete knowledge8,11. Here we report the experimental discovery of two structure types by computational identification of the region of a complex inorganic phase field that contains them. This is achieved by computing probe structures that capture the chemical and structural diversity of the system and whose energies can be ranked against combinations of currently known materials. Subsequent experimental exploration of the lowest-energy regions of the computed phase diagram affords two materials with previously unreported crystal structures featuring unusual structural motifs. This approach will accelerate the systematic discovery of new materials in complex compositional spaces by efficiently guiding synthesis and enhancing the predictive power of the computational tools through expansion of the knowledge base underpinning them

    Reproductive Ecology and Severe Pollen Limitation in the Polychromic Tundra Plant, Parrya nudicaulis (Brassicaceae)

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    Pollen limitation is predicted to be particularly severe in tundra habitats. Numerous reproductive patterns associated with alpine and arctic species, particularly mechanisms associated with reproductive assurance, are suggested to be driven by high levels of pollen limitation. We studied the reproductive ecology of Parrya nudicaulis, a species with relatively large sexual reproductive investment and a wide range of floral pigmentation, in tundra habitats in interior montane Alaska to estimate the degree of pollen limitation. The plants are self-compatible and strongly protandrous, setting almost no seed in the absence of pollinators. Supplemental hand pollinations within pollinator exclusion cages indicated no cage effect on seed production. Floral visitation rates were low in both years of study and particularly infrequent in 2010. A diversity of insects visited P. nudicaulis, though syrphid and muscid flies composed the majority of all visits. Pollen-ovule ratios and levels of heterozygosity are consistent with a mixed mating system. Pollen limitation was severe; hand pollinations increased seed production per plant five-fold. Seed-to-ovule ratios remained low following hand pollinations, indicating resource limitation is likely to also be responsible for curtailing seed set. We suggest that pollen limitation in P. nudicaulis may be the result of selection favoring an overproduction of ovules as a bet-hedging strategy in this environmental context of highly variable pollen receipt

    Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

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    Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations

    Variation in Structure and Process of Care in Traumatic Brain Injury: Provider Profiles of European Neurotrauma Centers Participating in the CENTER-TBI Study.

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    INTRODUCTION: The strength of evidence underpinning care and treatment recommendations in traumatic brain injury (TBI) is low. Comparative effectiveness research (CER) has been proposed as a framework to provide evidence for optimal care for TBI patients. The first step in CER is to map the existing variation. The aim of current study is to quantify variation in general structural and process characteristics among centers participating in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. METHODS: We designed a set of 11 provider profiling questionnaires with 321 questions about various aspects of TBI care, chosen based on literature and expert opinion. After pilot testing, questionnaires were disseminated to 71 centers from 20 countries participating in the CENTER-TBI study. Reliability of questionnaires was estimated by calculating a concordance rate among 5% duplicate questions. RESULTS: All 71 centers completed the questionnaires. Median concordance rate among duplicate questions was 0.85. The majority of centers were academic hospitals (n = 65, 92%), designated as a level I trauma center (n = 48, 68%) and situated in an urban location (n = 70, 99%). The availability of facilities for neuro-trauma care varied across centers; e.g. 40 (57%) had a dedicated neuro-intensive care unit (ICU), 36 (51%) had an in-hospital rehabilitation unit and the organization of the ICU was closed in 64% (n = 45) of the centers. In addition, we found wide variation in processes of care, such as the ICU admission policy and intracranial pressure monitoring policy among centers. CONCLUSION: Even among high-volume, specialized neurotrauma centers there is substantial variation in structures and processes of TBI care. This variation provides an opportunity to study effectiveness of specific aspects of TBI care and to identify best practices with CER approaches
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