Severe COVID-19 and Retina: Are There Any Retinal Manifestations?

2021 ◽  
Author(s):  
Medine Gündogan ◽  
Soner Kiliç ◽  
Sertan Göktas ◽  
Esra Vural ◽  
Muhammed Rasit Sirem ◽  
...  
Keyword(s):  
Near Infrared ◽  
Fundus Autofluorescence ◽  
Fundus Photography ◽  
Systemic Diseases ◽  
Infrared Reflectance ◽  
Cotton Wool ◽  
Near Infrared Reflectance ◽  
Cotton Wool Spots ◽  
The Mean ◽  
Oct Imaging

Abstract Purpose To investigate whether there are retinal lesions associated with severe COVID-19. Methods We studied 232 symptomatic subjects aged 18 – 65 years who had severe COVID-19 and had received treatment. The evaluations included ophthalmological examinations, optical coherence tomography (OCT), imaging modalities with near infrared reflectance (NIR), fundus autofluorescence (FAF), and fundus photography (FP). Results The mean age of the patients was 49 years, and 67.6% of them were men. There were no findings of microhemorrhage, cotton wool spots (CWS), vitritis, or retinitis in the examination and imaging. Conclusions This study indicates that retinal involvement as a complication associated with COVID-19 is questionable, although some reports have demonstrated a relationship that may occur secondary to existing systemic diseases.

scholarly journals Diagnostic ability of confocal near-infrared reflectance fundus imaging to detect retrograde microcystic maculopathy from chiasm compression. A comparative study with OCT findings

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0253323
Author(s):  
Mário L. R. Monteiro ◽  
Rafael M. Sousa ◽  
Rafael B. Araújo ◽  
Daniel Ferraz ◽  
Mohammad A. Sadiq ◽  
...  
Keyword(s):  
Optic Atrophy ◽  
Near Infrared ◽  
Screening Method ◽  
Fundus Photography ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance ◽  
Chiasmal Compression ◽  
Fundus Imaging ◽  
Cell Layers ◽  
Level Of Agreement

Purpose To evaluate the ability of confocal near-infrared reflectance (NIR) to diagnose retrograde microcystic maculopathy (RMM) in eyes with temporal visual field (VF) loss and optic atrophy from chiasmal compression. To compare NIR findings with optical coherence tomography (OCT) findings in the same group of patients. Methods Thirty-four eyes (26 patients) with temporal VF loss from chiasmal compression and 41 healthy eyes (22 controls) underwent NIR fundus photography, and macular OCT scanning. VF loss was estimated and retinal layers thickness were measured on OCT. Two examiners blinded to the diagnosis randomly examined NIR images for the presence of hyporeflective abnormality (HA) and OCT scans for the presence of microcystic macular abnormalities (MMA). The total average and hemi-macular HA area and number of microcysts were determined. The groups were compared and the level of agreement was estimated. Results The OCT-measured macular retinal nerve fiber and ganglion cell layers were thinner and the inner nuclear layer was thicker in patients compared to controls. HA and MMA were detected in 22 and 12 patient eyes, respectively, and in 0 controls (p<0.001, both comparisons). HA was significantly more frequent than MMA in patients with optic atrophy, and agreement between HA and MMA (both total and hemi-macular) was fair (kappa range: 0.24–0.29). The mean HA area was significantly greater in the nasal than temporal hemi-macula. A re-analysis of the 14 eyes with discrepant findings allowed to confirm RMM in 20 eyes (20/34) indicating that OCT detected RMM in 12 and missed it in 8 eyes. On the other hand, NIR correctly detected 18 out of 20 eyes, overcalled 4 and missed 2. Conclusions RMM is a frequent finding in eyes with severe VF loss from long-standing chiasmal compression. NIR photography appears to be more sensitive than OCT for detecting RMM and may be useful as screening method for its presence.

scholarly journals Nutritional evaluation of Jambo forage using near infrared reflectance spectroscopy and comparison with wet chemistry analysis

2012 ◽  
Vol 40 (1-2) ◽  
pp. 46-50
Author(s):  
ZH Khandaker ◽  
ABM Khaleduzzaman
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Reflectance Spectroscopy ◽  
Infrared Reflectance ◽  
Mean Square ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Nutritional Evaluation ◽  
Wet Chemistry ◽  
The Mean

A study was undertaken for the nutritional evaluation of Jambo forage by using Near Infrared Reflectance Spectroscopy (NIRS) and compare with the values obtained from wet chemistry analysis. Near infra-red reflectance spectrum of ground forage samples were obtained in duplicate (scanningnumber 32, resolution 8) with an FT-NIRS (Bruker, MPA, Germany) systems monochromator (700-2400 nm) using a Qurtz cup sampling device. For the development of local calibration equations, multivariate analysis was performed by a commercial analysis program Optical User Software (OPUS) and OpusLab to relate the spectral data and corresponding concentration values for each nutrient component of forage. The108 Jambo forage samples were collected from 108 cultivated experimental plots and groundthrough 2.0 mm screen for analysis the proximate components (Moisture, CP, CF, NFE and ash). The value for each component was placed into calibration group for NIRS equation development. The root mean square error of estimation (RMSEE) for the determination of CP, CF, NFE and total ash of Jambo forage was 0.33, 0.51, 1.14 and 0.39% respectively with correlation coefficient (r2) of 79.18, 82.04, 87.92 and 84.37 respectively. After cross validation, the root mean square error cross validation (RMSECV) for the CP, CF, NFE and total ash of Jambo forage were 0.37, 0.58, 1.41 and 0.48% respectively with correlation coefficient (r2) of 72.42, 73.85, 78.87 and 73.78 respectively. The mean predicted values of CP, CF, NFE and total ash by NIRS are close to the mean laboratory values determined by wet chemistry analysis. It can be concluded that NIRS could potentially be used to predict the nutritional quality of Jambo forage.DOI: http://dx.doi.org/10.3329/bjas.v40i1-2.10790Bang. J. Anim. Sci. 2011. 40 (1-2): 46-50

scholarly journals Predicting quality, texture and chemical content of yam (Dioscorea alata L.) tubers using near infrared spectroscopy

2021 ◽  
pp. 096703352110075
Author(s):  
Adou Emmanuel Ehounou ◽  
Denis Cornet ◽  
Lucienne Desfontaines ◽  
Carine Marie-Magdeleine ◽  
Erick Maledon ◽  
...  
Keyword(s):  
High Throughput ◽  
Dry Matter ◽  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
Infrared Reflectance ◽  
Quality Traits ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Infrared Reflectance Spectroscopy ◽  
Texture Attributes

Despite the importance of yam ( Dioscorea spp.) tuber quality traits, and more precisely texture attributes, high-throughput screening methods for varietal selection are still lacking. This study sets out to define the profile of good quality pounded yam and provide screening tools based on predictive models using near infrared reflectance spectroscopy. Seventy-four out of 216 studied samples proved to be moldable, i.e. suitable for pounded yam. While samples with low dry matter (<25%), high sugar (>4%) and high protein (>6%) contents, low hardness (<5 N), high springiness (>0.5) and high cohesiveness (>0.5) grouped mostly non-moldable genotypes, the opposite was not true. This outline definition of a desirable chemotype may allow breeders to choose screening thresholds to support their choice. Moreover, traditional near infrared reflectance spectroscopy quantitative prediction models provided good prediction for chemical aspects (R2 > 0.85 for dry matter, starch, protein and sugar content), but not for texture attributes (R2 < 0.58). Conversely, convolutional neural network classification models enabled good qualitative prediction for all texture parameters but hardness (i.e. an accuracy of 80, 95, 100 and 55%, respectively, for moldability, cohesiveness, springiness and hardness). This study demonstrated the usefulness of near infrared reflectance spectroscopy as a high-throughput way of phenotyping pounded yam quality. Altogether, these results allow for an efficient screening toolbox for quality traits in yams.

scholarly journals Climate predicts both visible and near‐infrared reflectance in butterflies

2021 ◽  
Author(s):  
Changku Kang ◽  
Sehyeok Im ◽  
Won Young Lee ◽  
Yunji Choi ◽  
Devi Stuart‐Fox ◽  
...  
Keyword(s):  
Near Infrared ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance
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