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Open AccessArticle
Dietary Compound Chrysin Inhibits Retinal Neovascularization with Abnormal Capillaries in db/db Mice
Nutrients 2016, 8(12), 782; doi:10.3390/nu8120782 (registering DOI) -
Abstract
Diabetic retinopathy (DR) develops in a significant proportion of patients with chronic diabetes, characterized by retinal macular edema and abnormal retinal vessel outgrowth leading to vision loss. Chrysin, a naturally-occurring flavonoid found in herb and honeycomb, has anti-inflammatory, antioxidant, and anti-cancer properties. This
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Diabetic retinopathy (DR) develops in a significant proportion of patients with chronic diabetes, characterized by retinal macular edema and abnormal retinal vessel outgrowth leading to vision loss. Chrysin, a naturally-occurring flavonoid found in herb and honeycomb, has anti-inflammatory, antioxidant, and anti-cancer properties. This study sought to determine the protective effects of chrysin on retinal neovascularization with abnormal vessels and blood-retinal barrier (BRB) breakdown in 33 mM glucose-exposed human retinal endothelial cells and in db/db mouse eyes. High glucose caused retinal endothelial apoptotic injury, which was inhibited by submicromolar chrysin. This compound diminished the enhanced induction of HIF-1α, vascular endothelial growth factor (VEGF), and VEGF receptor-2 (VEGFR2) in high glucose-exposed retinal endothelial cells. Consistently, oral administration of 10 mg/kg chrysin reduced the induction of these proteins in db/db mouse eye tissues. In addition, chrysin restored the decrement of VE-cadherin and ZO-1 junction proteins and PECAM-1 in hyperglycemia-stimulated retinal endothelial cells and diabetic mouse retina, possibly maintaining tight cell-cell interactions of endothelial cells and pericytes. Anti-apoptotic chrysin reduced the up-regulation of Ang-1, Ang-2, and Tie-2 crucial to retinal capillary occlusion and BRB permeability. Furthermore, orally treating chrysin inhibited acellular capillary formation, neovascularization, and vascular leakage observed in diabetic retinas. These observations demonstrate, for the first time, that chrysin had a capability to encumber diabetes-associated retinal neovascularization with microvascular abnormalities and BRB breakdown. Full article
Open AccessArticle
Vitamin D Status and Efficacy of Vitamin D Supplementation in Atopic Dermatitis: A Systematic Review and Meta-Analysis
Nutrients 2016, 8(12), 789; doi:10.3390/nu8120789 (registering DOI) -
Abstract
Recent literature has highlighted the possible role of vitamin D in atopic dermatitis (AD), and that vitamin D supplementation might help to treat AD. This study determined the relationship between vitamin D level and AD, and assessed the efficacy of vitamin D supplementation.
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Recent literature has highlighted the possible role of vitamin D in atopic dermatitis (AD), and that vitamin D supplementation might help to treat AD. This study determined the relationship between vitamin D level and AD, and assessed the efficacy of vitamin D supplementation. We searched the MEDLINE, EMBASE, and Cochrane databases up to May 2015. Observational studies and randomized controlled trials were included based on the available data on the serum 25-hydroxyvitamin D (25(OH)D) level and quantified data available for severity assessed using the Scoring Atopic Dermatitis (SCORAD) index or Eczema Area and Severity Index (EASI) score. Compared with healthy controls, the serum 25(OH)D level was lower in the AD patients of all ages (standardized mean difference = −2.03 ng/mL; 95% confidence interval (CI) = −2.52 to −0.78), and predominantly in the pediatric AD patients (standardized mean difference = −3.03 ng/mL; 95% CI = −4.76 to −1.29). In addition, the SCORAD index and EASI score decreased after vitamin D supplementation (standardized mean difference = −5.85; 95% CI = −7.66 to −4.05). This meta-analysis showed that serum vitamin D level was lower in the AD patients and vitamin D supplementation could be a new therapeutic option for AD. Full article
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Open AccessReview
Polyphenols and DNA Damage: A Mixed Blessing
Nutrients 2016, 8(12), 785; doi:10.3390/nu8120785 (registering DOI) -
Abstract
Polyphenols are a very broad group of chemicals, widely distributed in plant foods, and endowed with antioxidant activity by virtue of their numerous phenol groups. They are widely studied as putative cancer-protective agents, potentially contributing to the cancer preventive properties of fruits and
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Polyphenols are a very broad group of chemicals, widely distributed in plant foods, and endowed with antioxidant activity by virtue of their numerous phenol groups. They are widely studied as putative cancer-protective agents, potentially contributing to the cancer preventive properties of fruits and vegetables. We review recent publications relating to human trials, animal experiments and cell culture, grouping them according to whether polyphenols are investigated in whole foods and drinks, in plant extracts, or as individual compounds. A variety of assays are in use to study genetic damage endpoints. Human trials, of which there are rather few, tend to show decreases in endogenous DNA damage and protection against DNA damage induced ex vivo in blood cells. Most animal experiments have investigated the effects of polyphenols (often at high doses) in combination with known DNA-damaging agents, and generally they show protection. High concentrations can themselves induce DNA damage, as demonstrated in numerous cell culture experiments; low concentrations, on the other hand, tend to decrease DNA damage. Full article
Open AccessArticle
Mapping Deforestation in North Korea Using Phenology-Based Multi-Index and Random Forest
Remote Sens. 2016, 8(12), 997; doi:10.3390/rs8120997 (registering DOI) -
Abstract
Phenology-based multi-index with the random forest (RF) algorithm can be used to overcome the shortcomings of traditional deforestation mapping that involves pixel-based classification, such as ISODATA or decision trees, and single images. The purpose of this study was to investigate methods to identify
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Phenology-based multi-index with the random forest (RF) algorithm can be used to overcome the shortcomings of traditional deforestation mapping that involves pixel-based classification, such as ISODATA or decision trees, and single images. The purpose of this study was to investigate methods to identify specific types of deforestation in North Korea, and to increase the accuracy of classification, using phenological characteristics extracted with multi-index and random forest algorithms. The mapping of deforestation area based on RF was carried out by merging phenology-based multi-indices (i.e., normalized difference vegetation index (NDVI), normalized difference water index (NDWI), and normalized difference soil index (NDSI)) derived from MODIS (Moderate Resolution Imaging Spectroradiometer) products and topographical variables. Our results showed overall classification accuracy of 89.38%, with corresponding kappa coefficients of 0.87. In particular, for forest and farm land categories with similar phenological characteristic (e.g., paddy, plateau vegetation, unstocked forest, hillside field), this approach improved the classification accuracy in comparison with pixel-based methods and other classes. The deforestation types were identified by incorporating point data from high-resolution imagery, outcomes of image classification, and slope data. Our study demonstrated that the proposed methodology could be used for deciding on the restoration priority and monitoring the expansion of deforestation areas. Full article
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Open AccessArticle
Bias Correction for Retrieval of Atmospheric Parameters from the Microwave Humidity and Temperature Sounder Onboard the Fengyun-3C Satellite
Atmosphere 2016, 7(12), 156; doi:10.3390/atmos7120156 (registering DOI) -
Abstract
The microwave humidity and temperature sounder (MWHTS) on the Fengyun (FY)-3C satellite measures the outgoing radiance from the Earth’s surface and atmospheric constituents. MWHTS, which makes measurements in the isolated oxygen absorption line near 118 GHz and the vicinity of the strong water
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The microwave humidity and temperature sounder (MWHTS) on the Fengyun (FY)-3C satellite measures the outgoing radiance from the Earth’s surface and atmospheric constituents. MWHTS, which makes measurements in the isolated oxygen absorption line near 118 GHz and the vicinity of the strong water vapor absorption line around 183 GHz, can provide fine vertical distribution structures of both atmospheric humidity and temperature. However, in order to obtain the accurate soundings of humidity and temperature by physical retrieval methods, the bias between the observed and simulated radiance calculated by the radiative transfer model from the background or first guess profiles must be corrected. In this study, two bias correction methods are developed through the correlation analysis between MWHTS measurements and air mass identified by the first guess profiles of the physical inversion; one is the linear regression correction (LRC), and the other is the neural network correction (NNC), representing the linear and nonlinear relationships between MWHTS measurements and air mass, respectively. The correction methods have been applied to MWHTS observed brightness temperatures over the geographic area (180° W–180° E, 60° S–60° N). The corrected results are evaluated by the probability density function of the differences between corrected observations and simulated values and the root mean square errors (RMSE) with respect to simulated observations. The numerical results show that the NNC method has better performance, especially in MWHTS Channels 1 and 7–9, whose peak weight function heights are close to the surface. In order to assess the effects of bias correction methods proposed in this study on the retrieval accuracy, a one-dimensional variational system was built and applied to the MWHTS brightness temperatures to estimate the atmospheric temperature and humidity profiles. The retrieval results also show that NNC has better performance. An indication of the stability and robustness of the NNC method is given, which suggests that the NNC method has promising application perspectives in the physical retrieval. Full article
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Open AccessArticle
A Three-Dimensional Movement Analysis of the Spike in Fistball
Sports 2016, 4(4), 55; doi:10.3390/sports4040055 (registering DOI) -
Abstract
Due to its relevancy to point scoring, the spike is considered as one of the most important skills in fistball. Biomechanical analyses of this sport are very rare. In the present study, we performed a three-dimensional kinematic analysis of the fistball spike, which
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Due to its relevancy to point scoring, the spike is considered as one of the most important skills in fistball. Biomechanical analyses of this sport are very rare. In the present study, we performed a three-dimensional kinematic analysis of the fistball spike, which helps to specify performance parameters on a descriptive level. Recorded by four synchronized cameras (120 Hz) and linked to the motion capture software Simi Motion® 5.0, three female fistball players of the second German league (24–26 years, 1.63–1.69 m) performed several spikes under standardized conditions. Results show that the segment velocities of the arm reached their maximum successively from proximal to distal, following the principle of temporal coordination of single impulses. The wrist shows maximum speed when the fist hits the ball. The elbow joint angle performs a rapid transition from a strong flexion to a (almost) full extension; however, the extension is completed after the moment of ball impact. In contrast, the shoulder joint angle increases almost linearly until the fistball contact and decreases afterward. The findings can be used to optimize the training of the spike. Full article
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Open AccessArticle
Retrieving XCO2 from GOSAT FTS over East Asia Using Simultaneous Aerosol Information from CAI
Remote Sens. 2016, 8(12), 994; doi:10.3390/rs8120994 (registering DOI) -
Abstract
In East Asia, where aerosol concentrations are persistently high throughout the year, most satellite CO2 retrieval algorithms screen out many measurements during quality control in order to reduce retrieval errors. To reduce the retrieval errors associated with aerosols, we have modified YCAR
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In East Asia, where aerosol concentrations are persistently high throughout the year, most satellite CO2 retrieval algorithms screen out many measurements during quality control in order to reduce retrieval errors. To reduce the retrieval errors associated with aerosols, we have modified YCAR (Yonsei Carbon Retrieval) algorithm to YCAR-CAI to retrieve XCO2 from GOSAT FTS measurements using aerosol retrievals from simultaneous Cloud and Aerosol Imager (CAI) measurements. The CAI aerosol algorithm provides aerosol type and optical depth information simultaneously for the same geometry and optical path as FTS. The YCAR-CAI XCO2 retrieval algorithm has been developed based on the optimal estimation method. The algorithm uses the VLIDORT V2.6 radiative transfer model to calculate radiances and Jacobian functions. The XCO2 results retrieved using the YCAR-CAI algorithm were evaluated by comparing them with ground-based TCCON measurements and current operational GOSAT XCO2 retrievals. The retrievals show a clear annual cycle, with an increasing trend of 2.02 to 2.39 ppm per year, which is higher than that measured at Mauna Loa, Hawaii. The YCAR-CAI results were validated against the Tsukuba and Saga TCCON sites and show an root mean square error of 2.25, a bias of −0.81 ppm, and a regression line closer to the linear identity function compared with other current algorithms. Even after post-screening, the YCAR-CAI algorithm provides a larger dataset of XCO2 compared with other retrieval algorithms by 21% to 67%, which could be substantially advantageous in validation and data analysis for the area of East Asia. Retrieval uncertainty indicates a 1.39 to 1.48 ppm at the TCCON sites. Using Carbon Tracker-Asia (CT-A) data, the sampling error was analyzed and was found to be between 0.32 and 0.36 ppm for each individual sounding. Full article
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Open AccessArticle
Inversion of Land Surface Temperature (LST) Using Terra ASTER Data: A Comparison of Three Algorithms
Remote Sens. 2016, 8(12), 993; doi:10.3390/rs8120993 (registering DOI) -
Abstract
Land Surface Temperature (LST) is an important measurement in studies related to the Earth surface’s processes. The Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) instrument onboard the Terra spacecraft is the currently available Thermal Infrared (TIR) imaging sensor with the highest spatial
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Land Surface Temperature (LST) is an important measurement in studies related to the Earth surface’s processes. The Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) instrument onboard the Terra spacecraft is the currently available Thermal Infrared (TIR) imaging sensor with the highest spatial resolution. This study involves the comparison of LSTs inverted from the sensor using the Split Window Algorithm (SWA), the Single Channel Algorithm (SCA) and the Planck function. This study has used the National Oceanic and Atmospheric Administration’s (NOAA) data to model and compare the results from the three algorithms. The data from the sensor have been processed by the Python programming language in a free and open source software package (QGIS) to enable users to make use of the algorithms. The study revealed that the three algorithms are suitable for LST inversion, whereby the Planck function showed the highest level of accuracy, the SWA had moderate level of accuracy and the SCA had the least accuracy. The algorithms produced results with Root Mean Square Errors (RMSE) of 2.29 K, 3.77 K and 2.88 K for the Planck function, the SCA and SWA respectively. Full article
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Open AccessArticle
Analysis of the Effects of Drought on Vegetation Cover in a Mediterranean Region through the Use of SPOT-VGT and TERRA-MODIS Long Time Series
Remote Sens. 2016, 8(12), 992; doi:10.3390/rs8120992 (registering DOI) -
Abstract
The analysis of vegetation dynamics and agricultural production is essential in semi-arid regions, in particular as a consequence of the frequent occurrence of periods of drought. In this paper, a multi-temporal series of the Normalized Difference of Vegetation Index (NDVI), derived from SPOT-VEGETATION
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The analysis of vegetation dynamics and agricultural production is essential in semi-arid regions, in particular as a consequence of the frequent occurrence of periods of drought. In this paper, a multi-temporal series of the Normalized Difference of Vegetation Index (NDVI), derived from SPOT-VEGETATION (between September 1998 and August 2013) and TERRA-MODIS satellite data (between September 2000 and August 2013), was used to analyze the vegetation dynamics over the central region of Tunisia in North Africa, which is characterized by a semi-arid climate. Products derived from these two satellite sensors are generally found to be coherent. Our analysis of land use and NDVI anomalies, based on the Vegetation Anomaly Index (VAI), reveals a strong level of agreement between estimations made with the two satellites, but also some discrepancies related to the spatial resolution of these two products. The vegetation’s behavior is also analyzed during years affected by drought through the use of the Windowed Fourier Transform (WFT). Discussions of the dynamics of annual agricultural areas show that there is a combined effect between climate and farmers’ behavior, leading to an increase in the prevalence of bare soils during dry years. Full article
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