A Probabilistic Adaptive Cerebral Cortex Segmentation Algorithm for Magnetic Resonance Human Head Scan Images

The total efficiency of Magnetic Resonance Imaging (MRI) results in the need for human involvement in order to appropriately detect information contained in the image. Currently, there has been a surge in interest in automated algorithms that can more precisely divide medical image structures into substructures than prior attempts. Instant segregation of cerebral cortex width from MRI scanned images is difficult due to noise, Intensity Non-Uniformity (INU), Partial Volume Effects (PVE), MRI's low resolution, and the very complicated architecture of the cortical folds. In this paper, a Probabilistic Adaptive Cerebral Cortex Segmentation (PACCS) approach is proposed for segmenting brain areas of T1 weighted MRI of human head images. Skull Stripping (SS), Brain Hemisphere Segmentation (BHS) and CCS are the three primary processes in the suggested technique. In step 1, Non-Brain Cells (NBC) is eliminated by a Contour-Based Two-Stage Brain Extraction Method (CTS-BEM). Step 2 details a basic BHS technique for Curve Fitting (CF) detection in MRI human head images. The left and right hemispheres are divided using the discovered Mid-Sagittal Plane (MSP). At last, to enhance a probabilistic CCS structure with adjustments such as prior facts change to remove segmentation bias; the creation of express direct extent training; and a segmentation version based on a regionally various Gaussian Mixture Model- Hidden Markov Random Field – Expectation Maximization (GMM-HMRF-EM). The underlying partial extent categorization and its interplay with found image intensities are represented as a spatially correlated HMRF within the GMM-HMRF-EM method. The proposed GMM-HMRF method estimates HMRF parameters using the EM technique. Finally, the outcomes of segmentation are evaluated in terms of precision, recall, specificity, Jaccard Similarity (JS), and Dice Similarity (DS). The proposed method works better and more consistently than the present locally Varying MRF (LV-MRF), according to the experimental findings obtained by using the suggested GMM-HMRF-EM methodology to 18 individuals' brain images

Prevalence of pre-diabetes in adolescents aged 11-17 years with high risk factors

Background: Obesity is a rising global epidemic in children which leads to pre-diabetes and overt diabetes. Identification at early stage helps in early intervention. This study was undertaken to study the prevalence of pre-diabetes in urban school going adolescents aged 11-17 years with high risk factors.Methods: This was a prospective cross-sectional study conducted in Chennai, India between December 2011 and November 2012. Overweight or obese adolescents in the age group 11-17 years, either with family history of diabetes or acanthosis nigricans or both were included. After obtaining informed consent from parents, history was obtained in pre-tested questionnaire.Results: 148 adolescents were enrolled in the study (n=148), 71.62% were females, mean weight was 59.54±10.44 kg, mean height was 150.92±8.62 cm, mean BMI was 26.19±3.23 and mean blood glucose was 82.1 mg/dl. 60.81% of subjects were overweight and others obese. Girls had statistically significant higher mean weight and mean BMI than boys. 78.37% had acanthosis nigricans, 47.29% had family history of diabetes, 12.16% had pre-diabetes and the mean blood glucose in pre-diabetics was 104.9 mg/dl. Pre-diabetes was higher in adolescents with family history of diabetes (p=0.038).Conclusions: Recognition of risk of type 2 diabetes in the asymptomatic pre-diabetes phase needs to be emphasized and targeted screening of high risk children for pre-diabetes seems to be justified. The morbidity and mortality of youth onset type 2 diabetes can be reduced only by early detection and treatment

Risk factors and mortality profile of post neonatal deaths; 1 month to 1 year, in a rural medical college hospital, South India

Background: Infant mortality is the most important indicator which reflect country growth standards and development. This study was aimed to assess the risk factors and clinical profile of post neonatal deaths, admitted in PICU, government Villupuram medical college.Methods: A retrospective analysis was done on post neonatal mortality data by pediatric department of government Villupuram medical college, Mundiyambakkam from January 2019 to December 2020, referral and LAMA patients were excluded from study. Data was analyzed using SPSS 18.0Results: Overall post neonatal mortality was 7.3%. Mortality amongst boys were 28 (41.1%) and girls were 40 (58.8%). Mortality of female babies were higher than male babies.Among the 68 post neonatal deaths, maximum number of mortalities was seen in 1-3 months (61.9%), maximum within 24 hours of hospital stay (54.4%), 37 cases (54.4%) were referred from GHPHC and private practitioners of the nearby districts, 28 babies (41.1%) had previous admissions, 22 babies had SNCU admissions and 6 babies had pediatric admissions. Three most common causes of mortality were bronchopneumonia, sepsis and acute CNS infections. Congenital malformations and heart disease along with failure to thrive are other causes of morbidity.Conclusions: Analysis reflects the disease occurrence, treatment modalities and quality of treatment available. Treatment at primary level can prevent postnatal deaths from infections. The preventive and primary health care system should be strengthened. All special newborn care units (SNCU) discharged babies should have both community and district early intervention centre (DEIC) follow up, immunization practices, explaining danger signs to the parents, improving the quality of life has got great impact on the post neonatal outcome

Automatic Leather Species Identification using Machine Learning Techniques

Content: Identification and classification of leather species becomes valuable and necessary due to concerns regarding consumer protection, product counterfeiting, and dispute settlement in the leather industry. Identification and classification of leather into species is carried out by histological examination or molecular analysis based on DNA. Manual method requires expertise, training and experience, and due to involvement of human judgment disputes are inevitable thus a need to automate the leather species identification. In the present investigation, an attempt has been made to automate leather species identification using machine learning techniques. A novel non-destructive leather species identification algorithm is proposed for the identification of cow, buffalo, goat and sheep leathers. Hair pore pattern was segmented efficiently using k-means clustering algorithm Significant features representing the unique characteristics of each species such as no.of hair pores, pore density, percent porosity, shape of the pores etc., were extracted. The generated features were used for training the Random forest classifier. Experimental results on the leather species image library database achieved an accuracy of 87 % using random forest as classifier, confirming the potentials of using the proposed system for automatic leather species classification. Take-Away: Novel technique to identify leather species Non destructive method Machine learning algorithms to automate leather species identificatio

In vitro antioxidant and cytotoxicity studies of Curcuma

Abstract: Curcuma amada Roxb, of Zingiberaceae is an important active spice used in traditional system of medicine. They also used in the manufacture of pickles, chutney, salad and jam. Phosphomolybdenam method was used to measure the total antioxidant capacity (TAC) of C. amada ethanolic rhizome extract (CAEREt). The free radical scavenging capacity of CAEREt was also carried out by ABTS and DPPH methods. The cytotoxicity effect of CAEREt was determined by Trypan blue dye exclusion method and MTT assay using two different cell lines such as Dalton Lyphoma Ascites (DLA) and Human Cervical Cancer Cell Line (HeLa). The results showed that the rhizome extract of C. amada rich in phytocompounds and have exhibited better antioxidant and cytotoxicity properties

Psychopharmacological activities of acorus calamus roots in rat and mice models

Acorus calamus (Araceae) is commonly known in India as sweet flag and has been used in traditional medicine as a remedy for pain, convulsion, inflammation, and ulcer. In the present work, the methanolic extract of Acorus calamus roots (MEAC) was assessed for different psychopharmacological activities in rats and mice by evaluation of general, exploratory behaviour, phenobarbitone sodium-induced sleeping time and muscle relaxant activity. The extract at doses 100 mg/kg and above exhibited a reduction in spontaneous activity and a decrease in exploratory behavioural pattern was observed. Also a significant reduction in muscle relaxant activity and potentiated phenobarbitone sodium-induced sleeping time in mice was noted in MEAC treated groups. From our study, the results indicates that MEAC appears to have effects on alteration in general behavior pattern, evident from the spontaneous activity, sound, touch and pain responses of the MEAC treated groups.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Evolution of a domain conserved in microtubule-associated proteins of eukaryotes

The microtubule network, the major organelle of the eukaryotic cytoskeleton, is involved in cell division and differentiation but also with many other cellular functions. In plants, microtubules seem to be involved in the ordered deposition of cellulose microfibrils by a so far unknown mechanism. Microtubule-associated proteins (MAP) typically contain various domains targeting or binding proteins with different functions to microtubules. Here we have investigated a proposed microtubule-targeting domain, TPX2, first identified in the Kinesin-like protein 2 in Xenopus. A TPX2 containing microtubule binding protein, PttMAP20, has been recently identified in poplar tissues undergoing xylogenesis. Furthermore, the herbicide 2,6-dichlorobenzonitrile (DCB), which is a known inhibitor of cellulose synthesis, was shown to bind specifically to PttMAP20. It is thus possible that PttMAP20 may have a role in coupling cellulose biosynthesis and the microtubular networks in poplar secondary cell walls. In order to get more insight into the occurrence, evolution and potential functions of TPX2-containing proteins we have carried out bioinformatic analysis for all genes so far found to encode TPX2 domains with special reference to poplar PttMAP20 and its putative orthologs in other plants

Applications of Geospatial Technology in the Management of Cultural Heritage Sites – Potentials and Challenges for the Indian region

Cultural heritage management can be defined as all the processes in understanding (through knowing and identifying), conserving and managing various expressions of cultural heritage. These expressions could be intangible like traditional skills, crafts, folklore, rituals, etc. or tangible like objects or places. Objects including artefacts, murals and sculptures are defined as movable cultural property, while structures, monuments, precincts, water bodies and canals are called sites and also termed as immovable cultural property. Emerging technologies and scientific developments are increasingly being used in the management of these different expressions of cultural heritage. For example, heritage object databases that link source, provenance and current location are proving useful in museum contexts, predictive technologies are being used to fill in partially missing sections of murals/ inscriptions or aid virtual reconstruction of object remains or even something as basic as mapping indigenous processional routes. However, the expression of cultural heritage as immovable cultural property or heritage sites appears to render itself most to analysis through various techniques available under the large umbrella of geospatial technology. This is because of the nature of such heritage – structures are necessarily built in particular geographical and cultural settings, presumably based on appropriate site selection in order to suitably locate them and their components, and the initially planned layout and subsequent additions would have a spatial spread – these factors combined with the locational permanence of the structures relative to movable property make built heritage welldisposed for geospatial analysis. This review article therefore explores the use and applicability of geospatial technology for the management of built cultural heritage, including its context and environment

Amniotic membrane as a scaffold in wound healing and diabetic foot ulcer: an experimental technique and recommendations

Background: Human amniotic membrane has been used clinically in a variety of applications for over the past 100 years and produced a significant amount of data in multiple areas of medicine. Its clinical usage ranges from wound coverage for burn victims to healing of the conjunctiva after pterygium repair. The amniotic membrane natural properties provide an easy to use, safe option for various medical applications. There is need to develop a method for storage of amniotic membrane which can retain the biological properties and as well have long shelf life too.Methods: The experimental technique was standardized for cryopreservation of amniotic membrane. For this, amniotic membrane was obtained from mothers who had delivered through caesarean section with their consent.Results: The standardized protocol for cryopreservation of amniotic membrane was found to be safe and preserved amniotic membrane is expected to have long shelf life.  Conclusions: The advantages associated with amniotic membrane such as easily available, inexpensive, non-immunogenic and antimicrobial, anti-inflammatory properties make it a suitable graft to be used in wound healing and diabetic foot ulcers