Evaluating operational AVHRR sea surface temperature data at the coastline using surfers

Sea surface temperature (SST) is an essential climate variable that can be measured routinely from Earth Observation (EO) with high temporal and spatial coverage. To evaluate its suitability for an application, it is critical to know the accuracy and precision (performance) of the EO SST data. This requires comparisons with co-located and concomitant in situ data. Owing to a relatively large network of in situ platforms there is a good understanding of the performance of EO SST data in the open ocean. However, at the coastline this performance is not well known, impeded by a lack of in situ data. Here, we used in situ SST measurements collected by a group of surfers over a three year period in the coastal waters of the UK and Ireland, to improve our understanding of the performance of EO SST data at the coastline. At two beaches near the city of Plymouth, UK, the in situ SST measurements collected by the surfers were compared with in situ SST collected from two autonomous buoys located ∼7 km and ∼33 km from the coastline, and showed good agreement, with discrepancies consistent with the spatial separation of the sites. The in situ SST measurements collected by the surfers around the coastline, and those collected offshore by the two autonomous buoys, were used to evaluate the performance of operational Advanced Very High Resolution Radiometer (AVHRR) EO SST data. Results indicate: (i) a significant reduction in the performance of AVHRR at retrieving SST at the coastline, with root mean square errors in the range of 1.0 to 2.0 °C depending on the temporal difference between match-ups, significantly higher than those at the two offshore stations (0.4 to 0.6 °C); (ii) a systematic negative bias in the AVHRR retrievals of approximately 1 °C at the coastline, not observed at the two offshore stations; and (iii) an increase in the root mean square error at the coastline when the temporal difference between match-ups exceeded three hours. Harnessing new solutions to improve in situ sampling coverage at the coastline, such as tagging surfers with sensors, can improve our understanding of the performance of EO SST data in coastal regions, helping inform users interested in EO SST products for coastal applications. Yet, validating EO SST products using in situ SST data at the coastline is challenged by difficulties reconciling the two measurements, which are provided at different spatial scales in a dynamic and complex environment

Clearance kinetics and matrix binding partners of the receptor for advanced glycation end products

Elucidating the sites and mechanisms of sRAGE action in the healthy state is vital to better understand the biological importance of the receptor for advanced glycation end products (RAGE). Previous studies in animal models of disease have demonstrated that exogenous sRAGE has an anti-inflammatory effect, which has been reasoned to arise from sequestration of pro-inflammatory ligands away from membrane-bound RAGE isoforms. We show here that sRAGE exhibits in vitro binding with high affinity and reversibly to extracellular matrix components collagen I, collagen IV, and laminin. Soluble RAGE administered intratracheally, intravenously, or intraperitoneally, does not distribute in a specific fashion to any healthy mouse tissue, suggesting against the existence of accessible sRAGE sinks and receptors in the healthy mouse. Intratracheal administration is the only effective means of delivering exogenous sRAGE to the lung, the organ in which RAGE is most highly expressed; clearance of sRAGE from lung does not differ appreciably from that of albumin. Copyright: © 2014 Milutinovic et al

The economic potential of bioenergy for climate change mitigation with special attention given to implications for the land system

Biomass from cellulosic bioenergy crops is expected to play a substantial role in future energy systems, especially if climate policy aims at stabilizing greenhouse gas concentration at low levels. However, the potential of bioenergy for climate change mitigation remains unclear due to large uncertainties about future agricultural yield improvements and land availability for biomass plantations. This letter, by applying a modelling framework with detailed economic representation of the land and energy sector, explores the cost-effective contribution of bioenergy to a low-carbon transition, paying special attention to implications for the land system. In this modelling framework, bioenergy competes directly with other energy technology options on the basis of costs, including implicit costs due to biophysical constraints on land and water availability. As a result, we find that bioenergy from specialized grassy and woody bioenergy crops, such as Miscanthus or poplar, can contribute approximately 100 EJ in 2055 and up to 300 EJ of primary energy in 2095. Protecting natural forests decreases biomass availability for energy production in the medium, but not in the long run. Reducing the land available for agricultural use can partially be compensated for by means of higher rates of technological change in agriculture. In addition, our trade-off analysis indicates that forest protection combined with large-scale cultivation of dedicated bioenergy is likely to affect bioenergy potentials, but also to increase global food prices and increase water scarcity. Therefore, integrated policies for energy, land use and water management are needed.EC/FP7/265104/EU/Visions Of LANd use Transitions in Europe/VOLANTEEC/FP7/265170/EU/Enhancing Robustness and Model Integration for The Assessment of Global Environmental Change/ERMITAG

Association of nutritional intake with clinical and imaging activity in pediatric multiple sclerosis.

BACKGROUND: Understanding nutritions role in multiple sclerosis (MS) can guide recommendations and intervention-based studies. OBJECTIVE: Evaluate the association between nutrition and pediatric-onset MS outcomes. METHODS: Prospective longitudinal multicenter study conducted as part of the US Network of Pediatric MS centers. Predictors were collected using a food screener estimating intake of various dietary food groups (e.g. dairy and fruits) and additional calculated indices (e.g. Healthy Eating Index (HEI)). Outcomes included time-from-enrollment to clinical relapse, new magnetic resonance imaging (MRI) T2 lesions, and Expanded Disability Status Scale (EDSS) increase. RESULTS: 353 children with MS were enrolled (mean ± SD age 15.4 ± 2.9, follow-up 3.9 ± 2.6 years). Multivariable analysis demonstrated that increased dairy by 50% of recommended intake was associated with increased relapse risk by 41% (adjusted hazard ratio (HR) 1.41, 95% CI 1.07-1.86), and risk of T2 progression by 40% (1.40, 1.12-1.74). Increased intake of fruit or vegetable above recommended, and every five-point HEI increase decreased relapse risk by 25% (0.75, 0.60-0.95), 45% (0.55, 0.32-0.96), and 15% (0.84, 0.74-0.96), respectively. No associations were found with EDSS. CONCLUSION: This work supports the influence of dietary intake on MS course, particularly with dairy intake. Future prospective study is required to establish causation

Association Between Sun Exposure and Risk of Relapse in Pediatric-Onset Multiple Sclerosis.

BACKGROUND AND OBJECTIVES: Low sun and ultraviolet radiation (UVR) exposures have been associated with increased risk of developing pediatric-onset multiple sclerosis (MS); however, their effect on disease course has not been well characterized. We primarily investigated whether there was an association between time spent in the sun in early childhood and risk of relapse in pediatric MS. We secondarily investigated the effect of sun exposure during more recent periods on risk of relapse. METHODS: We conducted a multicenter cohort study of participants with pediatric-onset MS recruited from 18 pediatric MS clinics across the United States between November 1, 2011, and July 1, 2017. Relapses were identified prospectively after study enrollment; relapses preceding study enrollment were entered retrospectively. Time spent in the sun at various periods of life was measured using a detailed environmental questionnaire, and ambient UVR exposure was determined using zip codes. Multivariable Cox regression models were used to assess the association between time spent in the sun and UVR dose at specific periods of life and the risk of relapse. Models were adjusted for demographic, clinical, and sun exposure-related characteristics. RESULTS: In our cohort of 334 children with MS, 206 (62%) experienced at least one relapse from disease onset to the end of the follow-up period. After adjustment, ≥30 minutes of daily sun exposure during the first summer of life was associated with a lower risk of relapse compared with <30 minutes (adjusted hazard ratio [aHR] 0.67, CI 0.48-0.92, p = 0.01). Greater time spent in the sun during the second trimester of pregnancy was also associated with reduced risk of relapse (aHR 0.68, CI 0.48-0.97, p = 0.04). UVR dose and time spent in the sun later in life were not significantly associated with relapse risk. DISCUSSION: In this large cohort study of children with MS, greater early childhood and prenatal sun exposure time was associated with lower risk of relapse. Further investigation of sun exposure at other periods is needed to better characterize its impact on disease course and guide potential future interventions

Three foci at the science-policy interface for systemic Sustainable Development Goal acceleration

The integrated and indivisible nature of the SDGs is facing implementation challenges due to the silo approaches. We present the three interconnected foci (SDG interactions, modeling, and tools) at the science-policy interface to address these challenges. Accounting for them will support accelerated SDG progress, operationalizing the integration and indivisibility principles.</p

Association of Brain Age, Lesion Volume, and Functional Outcome in Patients With Stroke

Background and Objectives: Functional outcomes after stroke are strongly related to focal injury measures. However, the role of global brain health is less clear. In this study, we examined the impact of brain age, a measure of neurobiological aging derived from whole-brain structural neuroimaging, on poststroke outcomes, with a focus on sensorimotor performance. We hypothesized that more lesion damage would result in older brain age, which would in turn be associated with poorer outcomes. Related, we expected that brain age would mediate the relationship between lesion damage and outcomes. Finally, we hypothesized that structural brain resilience, which we define in the context of stroke as younger brain age given matched lesion damage, would differentiate people with good vs poor outcomes. Methods: We conducted a cross-sectional observational study using a multisite dataset of 3-dimensional brain structural MRIs and clinical measures from the ENIGMA Stroke Recovery. Brain age was calculated from 77 neuroanatomical features using a ridge regression model trained and validated on 4,314 healthy controls. We performed a 3-step mediation analysis with robust mixedeffects linear regression models to examine relationships between brain age, lesion damage, and stroke outcomes. We used propensity score matching and logistic regression to examine whether brain resilience predicts good vs poor outcomes in patients with matched lesion damage.Results: We examined 963 patients across 38 cohorts. Greater lesion damage was associated with older brain age (β = 0.21; 95% CI 0.04 0.38, p = 0.015), which in turn was associated with poorer outcomes, both in the sensorimotor domain (β = −0.28; 95% CI −0.41 to −0.15, p < 0.001) and across multiple domains of function (β = −0.14; 95% CI −0.22 to −0.06, p < 0.001). Brain age mediated 15% of the impact of lesion damage on sensorimotor performance (95% CI 3%–58%, p = 0.01). Greater brain resilience explained why people have better outcomes, given matched lesion damage (odds ratio 1.04, 95% CI 1.01–1.08, p = 0.004). Discussion: We provide evidence that younger brain age is associated with superior poststroke outcomes and modifies the impact of focal damage. The inclusion of imaging-based assessments of brain age and brain resilience may improve the prediction of poststroke outcomes compared with focal injury measures alone, opening new possibilities for potential therapeutic targets

Brain aging in specific phobia: An ENIGMA-anxiety mega-analysis

Introduction Specific phobia (SPH) is a prevalent anxiety disorder and may involve advanced biological aging. However, brain age research in psychiatry has primarily examined mood and psychotic disorders. This mega-analysis investigated brain aging in SPH participants within the ENIGMA-Anxiety Working Group. Methods 3D brain structural MRI scans from 17 international samples (600 SPH individuals, of whom 504 formally diagnosed and 96 questionnaire-based cases; 1,134 controls; age range: 22-75 years) were processed with FreeSurfer. Brain age was estimated from 77 subcortical and cortical regions with a publicly available ENIGMA brain age model. The brain-predicted age difference (brain-PAD) was calculated as brain age minus chronological age. Linear mixed-effect models examined group differences in brain-PAD and moderation by age. Results No significant group difference in brain-PAD manifested (βdiagnosis (SE)=0.37 years (0.43), p=0.39). A negative diagnosis-by-age interaction was identified, which was most pronounced in formally diagnosed SPH (βdiagnosis-by-age=-0.08 (0.03), pFDR=0.02). This interaction remained significant when excluding participants with anxiety comorbidities, depressive comorbidities, and medication use. Post-hoc analyses revealed a group difference for formal SPH diagnosis in younger participants (22-35 years; βdiagnosis=1.20 (0.60), p<0.05, mixed-effects d (95% confidence interval)=0.14 (0.00-0.28)), but not older participants (36-75 years; βdiagnosis=0.07 (0.65), p=0.91). Conclusions Brain aging did not relate to SPH in the full sample. However, a diagnosis-by-age interaction was observed across analyses, and was strongest in formally diagnosed SPH. Post-hoc analyses showed a subtle advanced brain aging in young adults with formally diagnosed SPH. Taken together, these findings indicate the importance of clinical severity, impairment and persistence, and may suggest a slightly earlier end to maturational processes or subtle decline of brain structure in SPH

Association of Brain Age, Lesion Volume, and Functional Outcome in Patients With Stroke

BACKGROUND AND OBJECTIVES: Functional outcomes after stroke are strongly related to focal injury measures. However, the role of global brain health is less clear. In this study, we examined the impact of brain age, a measure of neurobiological aging derived from whole-brain structural neuroimaging, on poststroke outcomes, with a focus on sensorimotor performance. We hypothesized that more lesion damage would result in older brain age, which would in turn be associated with poorer outcomes. Related, we expected that brain age would mediate the relationship between lesion damage and outcomes. Finally, we hypothesized that structural brain resilience, which we define in the context of stroke as younger brain age given matched lesion damage, would differentiate people with good vs poor outcomes. METHODS: We conducted a cross-sectional observational study using a multisite dataset of 3-dimensional brain structural MRIs and clinical measures from the ENIGMA Stroke Recovery. Brain age was calculated from 77 neuroanatomical features using a ridge regression model trained and validated on 4,314 healthy controls. We performed a 3-step mediation analysis with robust mixed-effects linear regression models to examine relationships between brain age, lesion damage, and stroke outcomes. We used propensity score matching and logistic regression to examine whether brain resilience predicts good vs poor outcomes in patients with matched lesion damage. RESULTS: We examined 963 patients across 38 cohorts. Greater lesion damage was associated with older brain age (β = 0.21; 95% CI 0.04-0.38, DISCUSSION: We provide evidence that younger brain age is associated with superior poststroke outcomes and modifies the impact of focal damage. The inclusion of imaging-based assessments of brain age and brain resilience may improve the prediction of poststroke outcomes compared with focal injury measures alone, opening new possibilities for potential therapeutic targets