Purpose Pseudoexfoliation (PXF) is a unique form of glaucoma characterized by accumulation of exfoliative material in the eyes. Changes in tear profile in disease stages may give us insights into molecular mechanisms involved in causing glaucoma in the eye. Methods All patients were categorized into three main categories; pseudoexfoliation (PXF), pseudoexfoliation glaucoma (PXG) and cataract, which served as control. Cytokines, transforming growth factor β1 (TGFβ1), matrix metalloproteases (MMPs) and fibronectin (FN1) were assessed with multiplex bead assay, enzyme-linked immunosorbent assay (ELISA), gelatin zymography, and immunohistochemistry (IHC) respectively in different ocular tissues such as tears, tenon’s capsule, aqueous humor (AH) and serum samples of patients with PXF stages. Results We found that TGFβ1, MMP-9 and FN1 protein expression were upregulated in tears, tenon’s capsule and AH samples in PXG compared to PXF, though the MMP-9 protein activity was downregulated in PXG compared with control or PXF. We have also found that in PXG tears sample the fold change of TGF-α (Transforming Growth Factor-α), MDC (Macrophage Derived Chemokine), IL-8 (Interleukin-8), VEGF (Vascular Endothelial Growth Factor) were significantly downregulated and the levels of GM-CSF (Granulocyte Macrophage Colony Stimulating Factor), IP-10 (Interferon- γ produced protein-10) were significant upregulated. While in AH; IL-6 (Interleukin-6), IL-8, VEGF, IFN-a2 (Interferon- α2), GRO (Growth regulated alpha protein) levels were found lower and IL1a (Interleukin-1α) level was higher in PXG compared to PXF. And in serum; IFN-a2, Eotaxin, GM-CSF, Fractalkine, IL-10 (Interleukin-10), IL1Ra (Interleukin-1 receptor antagonist), IL-7 (Interleukin-7), IL-8, MIP1β (Macrophage Inflammatory Protein-1β), MCP-1 (Monocyte Chemoattractant Protein-1) levels were significantly upregulated and PDGF-AA (Platelet Derived Growth Factor-AA) level was downregulated in the patients with PXG compared to PXF. Conclusions Altered expression of these molecules in tears may therefore be used as a signal for onset of glaucoma or for identifying eyes at risk of developing glaucoma in PXF.

PurposeProstaglandin analogues (PGA’s) are the mainstay and first line of treatment in current glaucoma practise. Though latanoprost and bimatoprost are the most commonly used PGA’s with minimal side effects at lower concentrations like bimaotoprost 0.01%, direct comparison of their cytokine/MMP profile in tears has not been evaluated earlier. The study intends to ascribe PGA to the upregulation of MMPs, Cytokines and Chemokines mediating varied pathways to result in side effects of the drugs.MethodsTear sample collection was done from outer canthus of 30 eyes of 30 patients (primary open angle glaucoma (n = 26 and n’ = 20), normal tension glaucoma (n = 4 and n’ = 10), in latanoprost (n) 0.005% and bimatoprost (n’) 0.01% group respectively, with a mean age of 62±10.5 years) on >6 months of PGA use using Tear floTM Schirmer filter strip. Tear samples from 30 eyes of 30 cataract patients without drug treatment were used as the control. Gelatinolytic activity of MMP-9 and MMP-2 were examined by substrate gelatine zymography MMP-1 and TIMP-1 concentrations from tears samples with PGAs were evaluated by ELISA while cytokine concentration in the eluted tears was evaluated using a convenient bioplex kit assay (Milliplex MAP kit, HCYTMAG-60K-PX41, Millipore, Massachusetts, United States). The mean duration of use of PGA in both groups did not differ significantly (median 1.3 years in bimatoprost and 1.1 years in latanoprost eyes, p = 0.6).ResultsThe tear MMP-9 expression was higher in eyes receiving latanoprost while the MMP-2 expression was higher in eyes receiving bimatoprost with MMP1 protein levels being higher in the former. Latanoprost treated eyes had marginally elevated tear cytokines involved in tissue remodelling while bimatoprost eyes showed elevated cytokines regulating allergic pathways.ConclusionDifferential cytokine and MMP expression indicates differential signalling pathways mediating different cellular effects (evident as clinical and side effects) with the two drugs which can be explored further.

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Microvasculature change associated with tenacious Hyperglycemia are the hostile effects accompanying to diabetes mellitus. Diabetic Retinopathy (DR) is a progressive complication, which leads to retinal permeability, ischemia, neovascularization and macular edema. The pathology is characterized by variation in capillary diameter, size of microaneurysm, hemorrhage exudates. Thus it stimulates the growth of new abnormal blood vessels so as to nourish the eye muscles. But these newly grown blood vessels are subtle, and may get burst. Therefore it leads to leakage of blood, protein based particles named as exudates. Early determination of the DR signs will help the diabetic patient to eradicate austere vision damage. Medical image processing methods helps the ophthalmologists in easy diagnosis, and to estimate the severity of the pathology. Fuzzy based clustering methods are simple and effective methods that will classify the pathos. This work furnish an improved fuzzy clustering method with induced multi kernel and spatial constraint. Statistical evaluation is done to evaluate the performance of the proposed method.

Purpose Image classification is a fundamental form of digital image processing in which pixels are labeled into one of the object classes present in the image. Multispectral image classification is a challenging task due to complexities associated with the images captured by satellites. Accurate image classification is highly essential in remote sensing applications. However, existing machine learning and deep learning–based classification methods could not provide desired accuracy. The purpose of this paper is to classify the objects in the satellite image with greater accuracy. Design/methodology/approach This paper proposes a deep learning-based automated method for classifying multispectral images. The central issue of this work is that data sets collected from public databases are first divided into a number of patches and their features are extracted. The features extracted from patches are then concatenated before a classification method is used to classify the objects in the image. Findings The performance of proposed modified velocity-based colliding bodies optimization method is compared with existing methods in terms of type-1 measures such as sensitivity, specificity, accuracy, net present value, F1 Score and Matthews correlation coefficient and type 2 measures such as false discovery rate and false positive rate. The statistical results obtained from the proposed method show better performance than existing methods. Originality/value In this work, multispectral image classification accuracy is improved with an optimization algorithm called modified velocity-based colliding bodies optimization.

Retinalimagingisachallengingscreeningmethodfordetectionofretinalabnormalities.Diabetic Maculopathy(DM)isaconditionthatcanresultfromretinopathy.Regularscreeningisnecessaryfor diabeticmaculopathyinordertoidentifytheriskofvisionloss.Maculopathyisdamagetomacula,the keyregionresponsibleforhighsharpcolourvision.DiabeticRetinopathyandDiabeticMaculopathy needsregularobservationinordertoindicatevisualimpairmentrisk.Inthisarticle,theauthorfirst presentsabriefsummaryofdiabeticmaculopathyanditscauses.Then,anexhaustiveliteraturereview ofdifferentautomatedDMdiagnosissystemsoffered.Itisimportantforophthalmologiststohave anautomatedsystemwhichdetectsearlysymptomsofthediseaseandyieldsahighaccurateresult. AvitalassessmentoftheimageprocessingtechniquesusedforDMfeaturedetectionisprojectedin thispaper.VariousmethodshavebeenproposedtoidentifyandclassifyDMbasedonseveritylevel.

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