Bioactivity Profile of Polyunsaturated Fattyacid extracts from Sardinella longiceps and Sardinella fimbriata – A comparative study

The oceans have proved to be an interminable source of new and effective drugs. Innumerable studies have proved that specific compounds isolated from marine organisms have great nutritional and pharmaceutical value. Polyunsaturated fattyacids (PUFA) in general are known for their dietary benefits in preventing and curing several critical ailments including Coronary heart disease (CHD) and cancers of various kinds. Eicosapentaenoic Acid (EPA) and Docosahexaenoic Acid (DHA) are two PUFA which are entirely marine in origin – and small Clupeoid fishes like sardines are known to be excellent sources of these two compounds. In this study, we selected two widely available Sardine species in the west coast, Sardinella longiceps and Sardinella fimbriata, for a comparative analysis of their bioactive properties. Both these sardines are known to be rich in EPA and DHA, however considerable seasonal variation in its PUFA content was expected and these variations studied. An extraction procedure to isolate PUFA at high purity levels was identified and the extracts obtained thus were studied for anti-bacterial, anti-diabetic and anti-cancerous properties.Samples of both the sardines were collected from landing centre, measured and their gut content analysed in four different months of the year – viz. June, September, December and March. The fish samples were analyzed for fattyacid using FAME method using gas chromatography to identify the full range of fattyacids and their respective concentration in each of the samples. The fattyacids were expressed in mg/g meat and later converted to percentage values against total fatty acids and total PUFA content. Fattyacids during winter season (Dec-Mar) were found to be generally higher than spawning season (June-Sept). PUFA dominated the profiles of both species and average PUFA content was also higher during winter. However, it was found that S. longiceps had proportionately higher EPA as compared to S. fimbriata which was DHA rich. Percentage of EPA and DHA also varied across months for both species – the spawning season seemed to show higher EPA content in S. longiceps and higher DHA content in S. fimbriata. Gut content analysis indicate that adult S. fimbriata is partial to zooplanktons which are DHA rich while adult S. longiceps feed mainly on EPA rich phytoplankton. Juveniles of both species, found mainly in winter, had a gut content showing more mixed diet. This difference in the feeding pattern reflect clearly in their PUFA profile – adult S. longiceps, which dominate the catch during the spawn season, feeding mostly on phytoplankton is concentrated with EPA while the juveniles which are found mostly in the winter season has slightly less EPA proportion as compared to adults. The same is true for S. fimbriata adults that are caught mostly in the spawning season; being rich in DHA as they feed mainly on zooplankton while the juveniles caught during winter season has a relatively lower concentration of DHA in their total PUFA.Various extraction procedures are known to obtain PUFA from fish oil. However, most of them do not give high purity and do not use materials indicated as safe. PUFA extracts have to be edible and should not have harmful substances for applying on mice and human subjects. Some PUFA extraction procedures, though pure and non-toxic, might induce cis-trans conversions during the extraction process. This conversion destroys the benefits of PUFA and at times is harmful to human body. A method free from these limitations has been standardized for this study. Gas Chromatography was performed on the extracts thus made to ensure that it is substantially pure. EPA: DHA ratios for both samples were derived - for S. longiceps this ratio was 3:2, while it was 3:8 for S. fimbriata.Eight common strains of gram positive and gram negative bacterial strains were subjected to the PUFA extracts from both species dissolved in acetone solution using Agar Well Diffusion method. The activity was studied against an acetone control. At the end of incubation period, zones of inhibition were measured to estimate the activity. Minimum inhibitory concentration for each of the active combinations was calculated by keeping p < 0.01 as significant. Four of the bacteria including multi-resistant Staphylococcus aureus were shown to be inhibited by the fish extracts. It was also found that the extracts from S. fimbriata were better than the one from S. longiceps in annihilating harmful bacteria.Four groups of mice subjects were studied to evaluate the antidiabetic properties of the PUFA extracts. Three groups were induced diabetes by administration of alloxan tetra hydrate. One group without diabetes was kept as control and another with diabetes was kept as diabetic control. For two diabetic groups, a prescribed amount of fish extracts were fed from each of the extracts. The biochemical parameters like serum glucose, total cholesterol, LDL & HDL cholesterol, triglycerides, urea and creatinine were sampled from all four groups at regular intervals of 7 days for a period of 28 days. It was found that groups fed with fish extracts had marked improvement in the levels of total LDL & HDL cholesterol, triglycerides and creatinine. Groups fed with extracts from S. fimbriata seem to have fared better as compared to S. longiceps. However, both groups did not show any marked improvement in blood glucose levels or levels of urea.Cell lines of MCF-7 (Breast Cancer) and DU-145 (Prostate Cancer) were used to analyse the cytotoxicity of the PUFA extracts. Both cell lines were subjected to MTT Assay and later the plates were read using an ELISA reader at a wavelength of 570nm. It was found that both extracts had significant cytotoxic effects against both cell lines and a peak cytotoxicity of 85-90% was apparent. IC50 values were calculated from the graphs and it was found that S. longiceps extracts had a slightly lower IC50 value indicating that it is toxic even at a lower concentration as compared to extracts from S. fimbriata.This study summarizes the bioactivity profile of PUFA extracts and provides recommendation for dietary intake; fish based nutritional industry and indigenous pharmaceutical industry. Possible future directions of this study are also elaborated.

Influence of collagen content on the texture andstorage quality of fish mince basedproducts

Objectives of the present study are to find out the proximate composition of 20 commercially important tropical fish species on the west coast of India. To determine the collagen content in these commercially important fish species and fractionation of collagen into acid soluble collagen (ASC) and hot water soluble (insoluble) collagen (ISC). To classify fishes according to its collagen content and To study the different storage characteristics in the mince based product—surimi, from different species of fishes. The researcher tries to find out a suitable collagen source to incorporate in surimi. and studies the different storage qualities in the mince based product, surimi at different levels of collagen in different species of fishes. The optimum collagen level to get desirable texture and storage quality for mince based product. The researcher aims to develop some products from surimi with desirable level of collagen. And compare the products prepared from surimi of lesser collagen content fish containing desirable level of collagen with surimi prepared with high collagen content fish without collagen. This study gains in importance as there is littleinformation on the collagen content of different species of fishes in India. So far no attempt was made to classify fishes according to its collagen content.

Reply to "Comment on 'Nature and entropy content of the ordering transitions in RCo2'"

In the previous Comment, Forker and co-workers claim that perturbed angular correlation (PAC) data leave no alternative to the conclusion that the spontaneous magnetization of PrCo2 and NdCo2 undergoes a discontinuous, first-order phase transition at TC. We show here that their claim is in clear contradiction with a wealth of experimental evidence, including our own. Finally, we propose a possible origin for the disagreement between their interpretation of the PAC results and the literature on this subject.

Web Presence Of The Engineering College Libraries In Kerala: An Analysis Of Content

Websites of academic institutions are the prime source of information about the institution. Libraries, being the main provider of information for the academics, need to be represented in the respective homepages with due importance. Keeping this in mind, this study is an attempt to understand and analyze the presence and presentation of libraries of Engineering Colleges (EC) in Kerala in their respective websites. On the basis of the reviewed literature and an observation of libraries of nationally important institutions imparting technical education in India, a set of criteria were developed for analyzing the websites/web pages. Based on this an extensive survcy of the websites of ECs were done. The collected data was then analyzed using Microsoft Excel. The library websites were then ranked on the basis of this analysis. It was observed that majority of the websites of ECs in Kerala have least representation of their respective libraries. Another important observation is that even the highest scoring libraries satisfy only half of the criteria listed for analysis.

Content Based Image Retrieval Using Low Level Features of Automatically Extracted Regions of Interest

This paper proposes a region based image retrieval system using the local colour and texture features of image sub regions. The regions of interest (ROI) are roughly identified by segmenting the image into fixed partitions, finding the edge map and applying morphological dilation. The colour and texture features of the ROIs are computed from the histograms of the quantized HSV colour space and Gray Level co- occurrence matrix (GLCM) respectively. Each ROI of the query image is compared with same number of ROIs of the target image that are arranged in the descending order of white pixel density in the regions, using Euclidean distance measure for similarity computation. Preliminary experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods.

classification and content based retrieval of digital mammograms and placental sonograms

Image processing has been a challenging and multidisciplinary research area since decades with continuing improvements in its various branches especially Medical Imaging. The healthcare industry was very much benefited with the advances in Image Processing techniques for the efficient management of large volumes of clinical data. The popularity and growth of Image Processing field attracts researchers from many disciplines including Computer Science and Medical Science due to its applicability to the real world. In the meantime, Computer Science is becoming an important driving force for the further development of Medical Sciences. The objective of this study is to make use of the basic concepts in Medical Image Processing and develop methods and tools for clinicians’ assistance. This work is motivated from clinical applications of digital mammograms and placental sonograms, and uses real medical images for proposing a method intended to assist radiologists in the diagnostic process. The study consists of two domains of Pattern recognition, Classification and Content Based Retrieval. Mammogram images of breast cancer patients and placental images are used for this study. Cancer is a disaster to human race. The accuracy in characterizing images using simplified user friendly Computer Aided Diagnosis techniques helps radiologists in detecting cancers at an early stage. Breast cancer which accounts for the major cause of cancer death in women can be fully cured if detected at an early stage. Studies relating to placental characteristics and abnormalities are important in foetal monitoring. The diagnostic variability in sonographic examination of placenta can be overlooked by detailed placental texture analysis by focusing on placental grading. The work aims on early breast cancer detection and placental maturity analysis. This dissertation is a stepping stone in combing various application domains of healthcare and technology.

Content Based Image Retrieval System for Malayalam Handwritten Characters

Content Based Image Retrieval is one of the prominent areas in Computer Vision and Image Processing. Recognition of handwritten characters has been a popular area of research for many years and still remains an open problem. The proposed system uses visual image queries for retrieving similar images from database of Malayalam handwritten characters. Local Binary Pattern (LBP) descriptors of the query images are extracted and those features are compared with the features of the images in database for retrieving desired characters. This system with local binary pattern gives excellent retrieval performance

Content-Based Image Retrieval of Axial Brain Slices Using a Novel LBP with a Ternary Encoding

Retrieval of similar anatomical structures of brain MR images across patients would help the expert in diagnosis of diseases. In this paper, modified local binary pattern with ternary encoding called modified local ternary pattern (MOD-LTP) is introduced, which is more discriminant and less sensitive to noise in near-uniform regions, to locate slices belonging to the same level from the brain MR image database. The ternary encoding depends on a threshold, which is a user-specified one or calculated locally, based on the variance of the pixel intensities in each window. The variancebased local threshold makes the MOD-LTP more robust to noise and global illumination changes. The retrieval performance is shown to improve by taking region-based moment features of MODLTP and iteratively reweighting the moment features of MOD-LTP based on the user’s feedback. The average rank obtained using iterated and weighted moment features of MOD-LTP with a local variance-based threshold, is one to two times better than rotational invariant LBP (Unay, D., Ekin, A. and Jasinschi, R.S. (2010) Local structure-based region-of-interest retrieval in brain MR images. IEEE Trans. Inf. Technol. Biomed., 14, 897–903.) in retrieving the first 10 relevant images

Content Based Image Retrieval of Brain MR Images across Different Classes

Magnetic Resonance Imaging play a vital role in the decision-diagnosis process of brain MR images. For an accurate diagnosis of brain related problems, the experts mostly compares both T1 and T2 weighted images as the information presented in these two images are complementary. In this paper, rotational and translational invariant form of Local binary Pattern (LBP) with additional gray scale information is used to retrieve similar slices of T1 weighted images from T2 weighted images or vice versa. The incorporation of additional gray scale information on LBP can extract more local texture information. The accuracy of retrieval can be improved by extracting moment features of LBP and reweighting the features based on users’ feedback. Here retrieval is done in a single subject scenario where similar images of a particular subject at a particular level are retrieved, and multiple subjects scenario where relevant images at a particular level across the subjects are retrieved

Content Based Video Retrieval using SURF Descriptor

This paper presents a Robust Content Based Video Retrieval (CBVR) system. This system retrieves similar videos based on a local feature descriptor called SURF (Speeded Up Robust Feature). The higher dimensionality of SURF like feature descriptors causes huge storage consumption during indexing of video information. To achieve a dimensionality reduction on the SURF feature descriptor, this system employs a stochastic dimensionality reduction method and thus provides a model data for the videos. On retrieval, the model data of the test clip is classified to its similar videos using a minimum distance classifier. The performance of this system is evaluated using two different minimum distance classifiers during the retrieval stage. The experimental analyses performed on the system shows that the system has a retrieval performance of 78%. This system also analyses the performance efficiency of the low dimensional SURF descriptor.

The Effect of SIFT Features as Content Descriptors in the Context of Automatic Writer Identification in Malayalam Language

The span of writer identification extends to broad domes like digital rights administration, forensic expert decisionmaking systems, and document analysis systems and so on. As the success rate of a writer identification scheme is highly dependent on the features extracted from the documents, the phase of feature extraction and therefore selection is highly significant for writer identification schemes. In this paper, the writer identification in Malayalam language is sought for by utilizing feature extraction technique such as Scale Invariant Features Transform (SIFT).The schemes are tested on a test bed of 280 writers and performance evaluated

SUBKAVYA: KATHYA KE VIBHINNA AYAM (POETRY OF SURDAS-DIFFERENT DIMENSIONS OF POETIC CONTENT)

HINDI

Content aggregation on knowledge bases using graph clustering

Recently, research projects such as PADLR and SWAP have developed tools like Edutella or Bibster, which are targeted at establishing peer-to-peer knowledge management (P2PKM) systems. In such a system, it is necessary to obtain provide brief semantic descriptions of peers, so that routing algorithms or matchmaking processes can make decisions about which communities peers should belong to, or to which peers a given query should be forwarded. This paper proposes the use of graph clustering techniques on knowledge bases for that purpose. Using this clustering, we can show that our strategy requires up to 58% fewer queries than the baselines to yield full recall in a bibliographic P2PKM scenario.

The Audiomomma Music Recommendation System

We design and implement a system that recommends musicians to listeners. The basic idea is to keep track of what artists a user listens to, to find other users with similar tastes, and to recommend other artists that these similar listeners enjoy. The system utilizes a client-server architecture, a web-based interface, and an SQL database to store and process information. We describe Audiomomma-0.3, a proof-of-concept implementation of the above ideas.