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Background and Objective Coronavirus disease 2019 is a novel disease caused by the severe acute respiratory syndrome coronavirus (SARS-CoV)-2 virus. It was first detected in December 2019 and has since been declared a pandemic causing millions of deaths worldwide. Therefore, there is an urgent need to develop effective therapeutics against coronavirus disease 2019. A critical step in the crosstalk between the virus and the host cell is the binding of the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein to the peptidase domain of the angiotensin-converting enzyme 2 (ACE2) receptor present on the surface of host cells. Methods An in silico approach was employed to design a 13-amino acid peptide inhibitor (13AApi) against the RBD of the SARS-CoV-2 spike protein. Its binding specificity for RBD was confirmed by molecular docking using pyDockWEB, ClusPro 2.0, and HDOCK web servers. The stability of 13AApi and the SARS-CoV-2 spike protein complex was determined by molecular dynamics simulation using the GROMACS program while the physicochemical and ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of 13AApi were determined using the ExPASy tool and pkCSM server. Finally, in vitro validation of the inhibitory activity of 13AApi against the spike protein was performed by an enzyme-linked immunosorbent assay. Results In silico analyses indicated that the 13AApi could bind to the RBD of the SARS-CoV-2 spike protein at the ACE2 binding site with high affinity. In vitro experiments validated the in silico findings, showing that 13AApi could significantly block the RBD of the SARS-CoV-2 spike protein. Conclusions Blockage of binding of the SARS-CoV-2 spike protein with ACE2 in the presence of the 13AApi may prevent virus entry into host cells. Therefore, the 13AApi can be utilized as a promising therapeutic agent to combat coronavirus disease 2019. Supplementary Information The online version contains supplementary material available at 10.1007/s40268-021-00357-0.

In cancer, the activating transcription factor 2 (ATF2) has pleiotropic functions in cellular responses to growth stimuli, damage, or inflammation. Due to only limited studies, the significance of ATF2 in colorectal cancer (CRC) is not well understood. We report that low ATF2 levels correlated with worse prognosis and tumor aggressiveness in CRC patients. NanoString gene expression and ChIP analysis confirmed trophoblast cell surface antigen 2 (TROP2) as a novel inhibitory ATF2 target gene. This inverse correlation was further observed in primary human tumor tissues. Immunostainings revealed that high intratumoral heterogeneity for ATF2 and TROP2 expression was sustained also in liver metastasis. Mechanistically, our in vitro data of CRISPR/Cas9-generated ATF2 knockout (KO) clones revealed that high TROP2 levels were critical for cell de-adhesion and increased cell migration without triggering EMT. TROP2 was enriched in filopodia and displaced Paxillin from adherens junctions. In vivo imaging, micro-computer tomography, and immunostainings verified that an ATF2KO/TROP2high status triggered tumor invasiveness in in vivo mouse and chicken xenograft models. In silico analysis provided direct support that ATF2low/TROP2high expression status defined high-risk CRC patients. Finally, our data demonstrate that ATF2 acts as a tumor suppressor by inhibiting the cancer driver TROP2. Therapeutic TROP2 targeting might prevent particularly the first steps in metastasis, i.e., the de-adhesion and invasion of colon cancer cells.

Objective of the study: The present study tries to explore the variation in criminal cases of crimes against children in West Bengal vis-à-vis India during the period 2006 to 2017. Methodology: This is mainly a descriptive study, which uses secondary information collected from the official records of the National Crime Records Bureau from 2006-2017 of India and West Bengal. The present study considers only the crimes against children that are punishable under IPC. Linear regression is carried out to explore the crime against children which is increasing over the years. Findings: The data shows that all sorts of crime against children are increasing over time and that more than 90 percent of crimes against children are committed by known people. Implications: There should be awareness programmes by the Government of India and the respective State Governments to teach the parents and the teachers of schools about how to prepare the children against any move committed against them and how to treat the children if such mis-happenings are already committed. The NGOs and mass medias also have their specific roles in order to stem violence against children. Limitations: Firstly, the study was based on secondary data. Hence, sometimes it was not specific to researcher’s needs. Secondly, National Crime Records Bureau provides history of crime upto 2017 and afterwards no further records regarding crimes were updated. So, the present situation of overall crime against children in India was not known.

Lipoxygenases (LOX) are a family lipid oxygenating enzymes that can generate bioactive lipids of clinical relevance from polyunsaturated fatty acids. Most LOXs display a Ca

Lipoxygenases (LOXs) are a family of enzymes that can oxygenate polyunsaturated fatty acids. As a member of the family, 15-lipoxygenase-1 (15-LOX-1) specifically metabolizes arachidonic acid and linoleic acid. 15-LOX-1 can affect physiological and pathophysiological events via regulation of the protein-lipid interactome, alterations in intracellular redox state and production of lipid metabolites that are involved in the induction and resolution of inflammation. Although several studies have shown that 15-LOX-1 has an antitumorigenic role in many different cancer models, including breast cancer, the role of the protein in cancer drug resistance has not been established yet. In this study, we, for the first time, aimed to show the potential role of 15-LOX-1 in acquired doxorubicin (DOX) resistance in MCF7 and HeLa cancer cell lines. Our results show that ALOX15 was transcriptionally downregulated in DOX-resistant cells compared with their drug-sensitive counterparts. Moreover, overexpression of ALOX15 in the drug-resistant cells resulted in resensitization of those cells to DOX in a cell-dependent manner. 15-LOX-1 expression could induce apoptosis by activating PPAR gamma and enhance the accumulation of DOX in drug-resistant MCF7 cells by altering cellular motility properties, and membrane dynamics. However, HeLa DOX cells did not show any of these effects but were susceptible to cell death when treated with 13(S)-HODE. These results underline the role and importance of 15-LOX-1 in cancer drug resistance, and points to novel mechanisms as a therapeutic approach to overcome cancer drug resistance.

Bacterial endotoxin-induced sepsis causes 30–40% of the deaths in the intensive care unit (ICU) globally, for which there is no pharmacotherapy. Lipopolysaccharide (LPS), a bacterial endotoxin, stimulates the Toll-like receptor (TLR)-4 signalling pathways to upregulate the expression of various inflammatory mediators. Here, we show that the TIRAP and c-Jun protein signalling complex forms in macrophages in response to LPS stimulation, which increases the AP1 transcriptional activity, thereby amplifying the expression of inflammatory mediators. Using a computer-aided molecular docking platform, we identified gefitinib as a putative inhibitor of the TIRAP-c-Jun signalling complex. Further, we demonstrated the ability of gefitinib to inhibit the interaction of TIRAP-c-Jun with in vitro experiments and with a mouse model of sepsis. Importantly, pre-treatment with gefitinib increased the survival of the mice that received a lethal dose of LPS compared to that of the controls. These findings verify the ability of gefitinib to directly disrupt the interaction of TIRAP and c-Jun, thereby inhibiting a major inflammatory response that is often observed in patients experiencing sepsis.

We report the surface modification of chitosan/poly(ethylene glycol) (chitosan/PEG) hydrogel materials via layer-by-layer (LbL) technique using stimuli-responsive polymers. Water-soluble complexes of Tannic Acid (TA) and a broad-spectrum antibiotic, Ciprofloxacin (Cipro) were prepared and co-assembled at the surface of Chitosan/PEG hydrogels with poly(N-vinyl caprolactam) (PVCL). Compared to the bare hydrogels, the surface spreading and proliferation of human fibroblasts were significantly enhanced on precast hydrogels coated with TA-Cipro/PVCL multilayers. LbL coating also provided enhanced Cipro release from the hydrogel surface at 37 °C compared to bare hydrogels. TA-Cipro/PVCL coated hydrogels showed antibacterial activity through chitosan and temperature-induced release of Cipro from multilayers. Chitosan and Cipro showed a coordinated antibacterial effect on Eschericia coli and Bacillus cereus, reducing their minimum inhibitory concentration (MIC). This effect was more pronounced on B. cereus. LbL modification of chitosan-based hydrogels using stimuli responsive polymers can be advantageous for bringing multiple functionalities to these materials without sacrificing their intrinsic properties such as antibacterial activity and biocompatibility. Such LbL-coated hydrogels hold promise in wound treatment as they may promote fibroblast proliferation and skin tissue regeneration.

Deregulation of metabolic pathways has increasingly been appreciated as a major driver of cancer in recent years. The principal cancer-associated alterations in metabolism include abnormal uptake of glucose and amino acids and the preferential use of metabolic pathways for the production of biomass and nicotinamide adenine dinucleotide phosphate (NADPH). Aldo-keto reductases (AKRs) are NADPH dependent cytosolic enzymes that can catalyze the reduction of carbonyl groups to primary and secondary alcohols using electrons from NADPH. Aldose reductase, also known as AKR1B1, catalyzes the conversion of excess glucose to sorbitol and has been studied extensively for its role in a number of diabetic pathologies. In recent years, however, high expression of the AKR1B and AKR1C family of enzymes has been strongly associated with worse outcomes in different cancer types. This review provides an overview of the catalysis-dependent and independent data emerging on the molecular mechanisms of the functions of AKRBs in different tumor models with an emphasis of the role of these enzymes in chemoresistance, inflammation, oxidative stress and epithelial-to-mesenchymal transition.

Tropical cyclones are natural phenomena occurring in coastal tropical regions that cause damage to life and property. Hence, a study of their evolution is necessary to prevent loss of life and property. In this paper, we present a cloud intensity classification technique for tropical cyclones based on feature extraction and pattern recognition, over the Bay of Bengal and Arabian Sea basins (latitudes 5° N–22° N and longitudes 52° E–100° E). Images of ten cyclones (2013 to 2018) are collected from the TC archive of Marine Meteorology Division of the US Naval Research Laboratory. A novel set of features is used for this purpose using some geometric properties of the cyclone structure. These features are fed to five machine learning classifiers: Naive Bayes, Support Vector Machine, Logistic Model Tree, Random Tree and Random Forest. The Random Forest classifier used here for classification task outperforms other classifiers with an accuracy of 86.66%. It is also observed that the root mean square error of the Random Forest classifier maximum sustained wind speed is 9.84 knots. Results indicate that the proposed feature extraction technique and machine learning classifiers are feasible for the tropical cyclone intensity classification from infrared images.

Background The nutritional and immunization status of children can play an important role in determining their future health status of a particular country. The aim of the present study is to investigate the nutritional and immunization status of under-five children in India and Bangladesh, and to find the difference in the status between these two countries. Methods We have used the National Family Health Survey data, 2015–2016 of India and Bangladesh Demographic Health Survey, 2017–2018 datasets. The sample sizes are 222,418, among them 8759 and 8759 children for India and Bangladesh respectively. The nutritional status of under-five children is measured by standard anthropometric indicators of height-for-age (HAZ) and weight-for-age (WAZ). Regarding child immunization status, only BCG, DPT, polio and measles vaccinations are considered for the present study. Multiple binary logistic model has been used for analysing the data. Results This study reveals that the prevalence of stunting and underweight of under-five children in India are higher than Bangladeshi children. Secondary and higher educated mothers are more likely of having normal HAZ and WAZ children than up to primary educated mothers for both countries. Chances of having normal HAZ and WAZ are higher among non-poor category for both countries. The present study also shows that immunization status of Bangladeshi children is better than Indian children except measles. Religion of mother also shows influence on immunization status of children in India whereas Bangladesh shows no significant results regarding religion. Mother’s educational attainment and wealth index show influence on immunization status among children for both countries. Conclusions The study concludes that a remarkable number of under-five children are suffering from under nutrition for both countries, however Bangladeshi children have better nutritional and immunization status compared to Indian children. Higher wealth index, better educational attainment and lower unemployment of Bangladeshi mothers may be the causes for better nutritional and immunization status of children. Mother’s socio-economic factors have significant impact on determining the child’s health status. Our findings can help to government of Indian and Bangladesh for taking health policy to improve under-five children nutritional and immunization status.

Deregulation of metabolic pathways has increasingly been appreciated as a major driver of cancer in recent years. The principal cancer-associated alterations in metabolism include abnormal uptake of glucose and amino acids and the preferential use of metabolic pathways for the production of biomass and nicotinamide adenine dinucleotide phosphate (NADPH). Aldo-keto reductases (AKRs) are NADPH dependent cytosolic enzymes that can catalyze the reduction of carbonyl groups to primary and secondary alcohols using electrons from NADPH. Aldose reductase, also known as AKR1B1, catalyzes the conversion of excess glucose to sorbitol and has been studied extensively for its role in a number of diabetic pathologies. In recent years, however, high expression of the AKR1B and AKR1C family of enzymes has been strongly associated with worse outcomes in different cancer types. This review provides an overview of the catalysis-dependent and independent data emerging on the molecular mechanisms of the functions of AKRBs in different tumor models with an emphasis of the role of these enzymes in chemoresistance, inflammation, oxidative stress and epithelial-to-mesenchymal transition.

Classification of tropical cyclone (TC) using cloud pattern is an evolving area of research. The classification result may use for intensity detection of a TC to mitigate the damage. TC classification using image processing technique is a stimulating task due to complexity of the problem. This paper attempted to classify TC images using a modified local binary pattern (LBP). The LBP of an image describes its local structure in an easy and efficient manner. The proposed blocked LBP (B-LBP) is an improvised approach to generate central pixels form an input image. The input image is distributed into 3 × 3 identical blocks and the central pixels of each block are used to construct a new image pattern. This new image further analyzed by histogram and box plot to classify images. This paper shows a significant improvement in result toward classification. The B-LBP approach can improve the performance of the intensity prediction through classification with 91% accuracy.

In this paper, we present a retina abnormality classification framework for diabetic retinopathy and age related macular degeneration using content based image retrieval. This is performed in two phases, namely, feature extraction and pattern recognition. In the first phase, image pre-processing and Otsu multi-level thresholding is applied to retina fundus images to extract eleven low level spatial and statistical features. The second phase consists of machine learning based classification with these features using four machine learning classifiers, namely, Naive Bayes classifier, support vector machine, K-nearest neighbour classifier and random forest classifier. It is found that random forest classifier outperforms all the other classifiers for the detection of both bright and dark lesion classes and achieves 94.8% and 95.1% accuracy, respectively with ROC area 0.977 and 0.98, respectively.

Proteinase-activated receptor 2 (PAR-2) is a G protein-coupled receptor activated by both trypsin and a specific agonist peptide, SLIGKV-NH2. It has been linked to various pathologies, including pain and inflammation. Several peptide and peptidomimetic agonizts for PAR-2 have been developed exhibiting high potency and efficacy. However, the number of PAR-2 antagonists is smaller. We screened the Food and Drug Administration library of approved compounds to retrieve novel antagonists for repositioning in the PAR-2 structure. The most efficacious compound bicalutamide bound to the PAR-2 binding groove near the extracellular domain as observed in the in silico studies. Further, it showed reduced Ca2+ release in trypsin activated cells in a dose-dependent manner. Hence, bicalutamide is a novel and potent PAR-2 antagonist which could be therapeutically useful in blocking multiple pathways diverging from PAR-2 signaling. Further, the novel scaffold of bicalutamide represents a new molecular structure for PAR-2 antagonism and can serve as a basis for further drug development.

We report the preparation of ultrathin coatings of zwitterionic block copolymer micelles and a comparison of their protein adsorption, adhesiveness, and antibacterial properties. Zwitterionic block copolymer micelles were obtained through pH-induced self-assembly of poly[3-dimethyl(methacryloyloxyethyl)ammonium propanesulfonate- b-2-(diisopropylamino)ethyl methacrylate] (βPDMA- b-PDPA) at pH 7.5. βPDMA- b-PDPA micelles with zwitterionic βPDMA-corona and pH-responsive PDPA-core were then used as building blocks to prepare layer-by-layer (LbL) assembled multilayer films together with hyaluronic acid (HA), tannic acid (TA), or poly(sodium 4-styrenesulfonate) (PSS). Protein adsorption tests showed that 3-layer βPDMA- b-PDPA micelles/HA films were the most effective to reduce the adhesion of BSA, lysozyme, ferritin, and casein. In contrast, βPDMA- b-PDPA micelles/TA films were the most attractive surfaces for protein adsorption. Bacterial antiadhesive tests against a model Gram-negative bacterium, Escherichia coli, and a model Gram-positive bacterium, Staphylococcus aureus, were in good agreement with the protein adsorption properties of the films. The differences in the antiadhesive properties between these three different film systems are discussed within the context of chemical nature and the functional chemical groups of the polyanions, layer number, and surface morphology of the films. Multilayers were found to lose their antiadhesiveness in the long term. However, by taking advantage of the pH-responsive hydrophobic micellar cores, we show that an antibacterial agent could be loaded into the micelles and multilayers could exhibit antibacterial activity in the long term especially at moderately acidic conditions. In contrast to antiadhesive properties, no significant differences were recorded in the antibacterial properties between the different film types.

Tropical cyclones (TC) prediction and intensity detection is one of the most emerging fields of research. Starting from Dvorak technique many approaches are used by meteorologist towards the TC intensity prediction and estimation. In this paper we have proposed an image processing based approach to categorise the cyclone intensity by using feature vector. The feature vector of a TC constructed using mean, variance, density and decentricity. Further, this vector converges to a distinct weight value by random weight genetic algorithm. Finally weight values under each intensity scale are used to find the intensity of a test image. This approach can be used in cyclone intensity detection technique. This paper focuses on estimate the intensity of tropical cyclones from satellite images over the Bay of Bengal.

Orthopedic implants have shown major success in clinics after successful orthopedic surgeries. However, they are also associated with several drawbacks such as local and systemic immune reaction in the body and improper integration of the bone with the implants. Osteoconductivity is a property of orthopedic implants that promotes bone cell adhesion and bone tissue integration on implant surfaces. This study presents use of a biodegradable cationic polyester, poly(4-hydroxy-L-proline ester) (PHPE) together with Tannic Acid (TA) as building blocks in construction of layer-by-layer (LbL) films to impart osteoconductive properties to multilayer films. Water-soluble complexes of PHPE and TA (PHPE-TA) were prepared at pH 4 and then LbL deposited at the surface without using a polymer counterpart. Multilayers were then cross-linked using NaIO4 to enhance their stability under physiological conditions. Potential of multilayers as an osteoconductive coating were assessed by (i) osteoblast-like cell adhesion; (ii) determination of collagen deposition by cells and (iii) the determination of extracellular matrix (ECM) mineralization and the results were compared to control substrates, i.e. cell culture plate well surface and collagen-coated substrates. PHPE-TA multilayers were found to be adhesive for SaOS-2 osteoblast-like cells and promoted collagen-rich nodule formation and mineralization of the ECM without causing cytotoxicity. PHPE-TA multilayers promoted higher alkaline phosphatase (ALP) activity and mineralization of the ECM, compared to collagen-coated surfaces. Importantly, PHPE-TA multilayers exhibited osteoconductive behavior without need for incorporation of bioactive natural polymers like collagen and hyaluronic acid or calcium phosphate ceramics into the multilayer films. Such LbL films are promising to modify the surfaces of orthopedic implants to impart osteoconductive properties to a surface.

AKR1B1 and AKR1B10, members of the aldo-keto reductase family of enzymes that participate in the polyol pathway of aldehyde metabolism, are aberrantly expressed in colon cancer. We previously showed that high expression of AKR1B1 (AKR1B1HIGH) was associated with enhanced motility, inflammation and poor clinical outcome in colon cancer patients. Using publicly available datasets and ex vivo gene expression analysis (n = 51, Ankara cohort), we have validated our previous in silico finding that AKR1B1HIGH was associated with worse overall survival (OS) compared with patients with low expression of AKR1B1 (AKR1B1LOW) samples. A combined signature of AKR1B1HIGH and AKR1B10LOW was significantly associated with worse recurrence-free survival (RFS) in microsatellite stable (MSS) patients and in patients with distal colon tumors as well as a higher mesenchymal signature when compared with AKR1B1LOW/AKR1B10HIGH tumors. When the patients were stratified according to consensus molecular subtypes (CMS), AKR1B1HIGH/AKR1B10LOW samples were primarily classified as CMS4 with predominantly mesenchymal characteristics while AKR1B1LOW/AKR1B10HIGH samples were primarily classified as CMS3 which is associated with metabolic deregulation. Reverse Phase Protein Array carried out using protein samples from the Ankara cohort indicated that AKR1B1HIGH/AKR1B10LOW tumors showed aberrant activation of metabolic pathways. Western blot analysis of AKR1B1HIGH/AKR1B10LOW colon cancer cell lines also suggested aberrant activation of nutrient-sensing pathways. Collectively, our data suggest that the AKR1B1HIGH/AKR1B10LOW signature may be predictive of poor prognosis, aberrant activation of metabolic pathways, and can be considered as a novel biomarker for colon cancer prognostication.

Intestinal epithelial cells are derived from stem cells at the crypts that undergo differentiation into transit‐amplifying cells, which in turn form terminally differentiated enterocytes as these cells reach the villus. Extensive alterations in both transcriptional and translational programs occur during differentiation, which can induce the activation of cellular stress responses such as ER stress‐related unfolded protein response (UPR) and autophagy, particularly in the cells that are already committed to becoming absorptive cells. Using an epithelial cell model of enterocyte differentiation, we report a mechanistic study connecting enterocyte differentiation to UPR and autophagy. We report that differentiated colon epithelial cells showed increased cytosolic Ca2+ levels and activation of all three pathways of UPR: inositol‐requiring enzyme 1 (IRE1), protein kinase RNA‐like ER kinase, and activating transcription factor 6 (ATF6) compared to the undifferentiated cells. Enhanced UPR in the differentiated cells was accompanied by the induction of autophagy as evidenced by increased ratio of light chain 3 II/I, upregulation of Beclin‐1, and downregulation of p62. We show for the first time that mechanistically, the upregulation of hepatocyte nuclear factor 4α (HNF4α) during differentiation led to increased promoter binding and transcriptional upregulation of two major proteins of UPR: X‐box binding protein‐1 and ATF6, implicating HNF4α as a key regulator of UPR response during differentiation. Integrating wet‐lab with in silico analyses, the present study links differentiation to cellular stress responses, and highlights the importance of transcription factor signaling and cross‐talk between the cellular events in the regulation of intestinal cell differentiation. TÜBİTAK. Grant Numbers: 114S937, 113S985 Bilecik Şeyh Edebali University Scientific Research Fund. Grant Number: 2018‐01.BŞEÜ.12‐01

This review focuses on exosomes derived from various cancer cells. The review discusses the possibility of differentiating macrophages in alternatively activated anti-inflammatory pro-tumorigenic M2 macrophage phenotypes and classically activated pro-inflammatory, anti-tumorigenic M1 macrophage phenotypes in the tumor microenvironment (TME). The review is divided into two main parts, as follows: (1) role of exosomes in alternatively activating M2-like macrophages-breast cancer-derived exosomes, hepatocellular carcinoma (HCC) cell-derived exosomes, lung cancer-derived exosomes, prostate cancer-derived exosomes, Oral squamous cell carcinoma (OSCC)—derived exosomes, epithelial ovarian cancer (EOC)—derived exosomes, Glioblastoma (GBM) cell-derived exosomes, and colorectal cancer-derived exosomes, (2) role of exosomes in classically activating M1-like macrophages, oral squamous cell carcinoma-derived exosomes, breast cancer-derived exosomes, Pancreatic-cancer derived modified exosomes, and colorectal cancer-derived exosomes, and (3) exosomes and antibody-dependent cellular cytotoxicity (ADCC). This review addresses the following subjects: (1) crosstalk between cancer-derived exosomes and recipient macrophages, (2) the role of cancer-derived exosome payload(s) in modulating macrophage fate of differentiation, and (3) intracellular signaling mechanisms in macrophages regarding the exosome’s payload(s) upon its uptake and regulation of the TME. Under the electron microscope, nanoscale exosomes appear as specialized membranous vesicles that emerge from the endocytic cellular compartments. Exosomes harbor proteins, growth factors, cytokines, lipids, miRNA, mRNA, and DNAs. Exosomes are released by many cell types, including reticulocytes, dendritic cells, B-lymphocytes, platelets, mast cells, and tumor cells. It is becoming clear that exosomes can impinge upon signal transduction pathways, serve as a mediator of signaling crosstalk, thereby regulating cell-to-cell wireless communications. Based on the vesicular cargo, the molecular constituents, the exosomes have the potential to change the fate of macrophage phenotypes, either M1, classically activated macrophages, or M2, alternatively activated macrophages. In this review, we discuss and describe the ability of tumor-derived exosomes in the mechanism of macrophage activation and polarization.

This research is an effort to assist the ophthalmologists in the primary prediction of retina diseases due to Diabetic Retinopathy and Age related Macular Degeneration. Case Based Reasoning is a paradigm that solves problems by using past experiences similar to the medical diagnosis process. In this paper, Case Based Reasoning is used to develop a computer aided diagnosis system to detect the retina abnormalities. The proposed system contains candidate lesion (both bright and dark) detection by processing the macula centric retina fundus images followed by feature set selection and classification. The lesion detection is done by Otsu multilevel segmentation followed by optic disc and blood vessel tree elimination. Each region of candidate lesions is evaluated in terms of the selected feature set. Case Based Reasoning based classification is implemented using K-Nearest Neighbour algorithm to predict the class type of each region. The KNN classifier outperforms Naive Bayes classifier and achieves 92.6% of average accuracy with an ROC of 0.952 in lesion classification.

Tropical Cyclone image processing is an attractive area of research among researchers. Satellite images of tropical cyclones are required sufficient preprocessing to perform further experiments. These satellite images are captured by Mateosat-7, which are huge in size due to large area covered by Mateosat-7 (40°E to 120°E and 20°S to 20°N). Most of the portion of a captured image is not relevant and which is required to locate tropical cyclone from the entire image. This paper focuses on to locate region of interest of an image by finding center gravity and distance between center of gravity and other significant points of an image. Here a distinctive iterative method has proposed by calculating center of gravity and average distance between relevant points using Euclidean and Manhattan distance metrics.