STUDIES ON THE PHYSIOLOGICAL AND BIOCHEMICAL ASPECTS OF OSMOREGULATION IN TWO INTERTIDAL BIVALVE MOLLUSCS

Division of Marine Biology, Microbiology and Biochemistry, School of Marine Sciences, Cochin University of Science and Technology

Physiological and Genetic Diversity Studies on Regeneration of Santalum Album L.

S. album L. is the source of highly priced and fragrant heartwood which on steam distillation yields on an average 57 per cent oil of high perfumery value. Global demand for sandalwood is about 5000-6000 tons/year and that of oil is 100 tons/year. Heartwood of sandal is estimated to fetch up to Rs. 3.7 million/ton and wood oil Rs.70,000-100,000/ kg in the international market. Sandal heartwood prices have increased from Rs. 365/ton in 1900 to Rs. 6.5 lakhs/ton in 1999-2000 and to Rs. 37 lakhs/ton in 2007. Substantial decline in sandalwood production has occurred from 3176 tons/year during 1960-‘ 65 to 1500 tons/year in 1997-98, and to 500 tons/year in 2007.Depletion of sandal resources is attributed to several factors, both natural and anthropogenic. Low seed setting, poor seed germination, seedling mortality, lack of haustorial connection with host plant roots, recurrent annual fires in natural sandal forests, lopping of trees for fodder, excessive grazing, hacking, encroachments, seedling diseases and spread of sandal spike disease are the major problems facing sandal. While these factors hinder sandal regeneration in forest areas, the situation is accelerated by human activities of chronic overexploitation and illicit felling.Deterioration of natural sandal populations due to illicit felling, encroachments and diseases has an adverse effect on genetic diversity of the species. The loss of genetic diversity has aggravated during recent years due to extensive logging, changing landuse patterns and poor natural regeneration. The consequent genetic erosion is of serious concern affecting tree improvement programme in sandal. Conservation as well as mass propagation are the two strategies to be given due importance. To initiate any conservation programme, precise knowledge of the factors influencing regeneration and survival of the species is essential. Hence, the present study was undertaken with the objective of investigating the autotrophic and parasitic phase of sandal seedlings growth, the effects of shade on morphology, chlorophyll concentration and chlorophyll fluorescence of sandal seedlings, genetic diversity in sandal seed stands using ISSR markers, and the diversity of fungal isolates causing sandal seedling wilt using RAPD markers. All these factors directly influence regeneration and survival of sandal seedlings in natural forests and plantations.

Synthesis, characterization and kinetic studies on complex formed between amantadine hydrochloride and sodium molybdate at physiological pH

The title reaction was undertaken to establish the interaction between amantadine and molybdate at physiological pH. Identical FTIR spectra, TG-DTA curves and CHN data of the complexes formed from three solutions at pH 1.5, 7.4 and 8.0 indicate that the same complex was formed at all the three pHs. The FTIR spectrum shows shift in peaks corresponding to primary amino group of the drug due to coordination to molybdate. An octahedral geometry is assigned to the complex. The kinetics of the complexation has been studied at low concentrations of the reactants using UV-visible spectrophotometry. At pH 7.4, the initial rate varies linearly with [molybdate]. A plot of initial rate versus [drug] is linear passing through origin. These results indicate that the drug and molybdate react at pH 7.4 even at low concentrations. At pH 1.5, the rate increases linearly with increase in [drug] but decreases with [molybdate]. The effect of pH and ionic strength on the rate of the reaction has also been studied. A suitable mechanism has been proposed for the reaction. Reaction between the drug and molybdate even at low concentrations and the fact that the amino group of amantadine required to be free for its function as antiviral, is bound to molybdate in the complex suggests that simultaneous administration of the drug and molybdate supplements should be avoided.

Physiological effects of copper (II) on sunetta scripta L.

In India industrial pollution has become a subject of increasing concern.Incidents of industrial pollution have been reported from many parts of the country. Cochin, the collection site of the present study, being the industrial capital of Kerela is also a harbour, is vulnerable to pollution by trace metal contaminants. In the recent times, pollutants of greatest concern in the aquatic environment are those which are persistent such as toxic heavy metals and the chlorinated hydrocarbons which include insecticides and pesticides.The animals collected from the clam bed situated on the northern side af Cochin bermouth are subject to wide fluctuations in salinity both seasonal and tidal. also; salinity is considered as an important parameter influencing the.-physiological functioning of an organism. Hence, the salinity tolerance of the animal is worked out. Considering the potential vulnerability of Cochin backwaters to heavy metal pollution, the impact of heavy metal copper (II) on the bivalve Sunetta sripta was conceived. Static bioassays were conducted for the determination of the sublethal concentrations of the metal as a preliminary step towards the toxicity studies. Oxygen consumption and filtration rate which are considered as reliable sublethal toxicity indices were employed for investigating the toxic effects of the metal. Bioaccumulation, a physiological phenomenon which can be of importance from the public health point of view, and also in the assessment of environmental quality is also dealt with.

Development of a Biometric Personal Authentication System Based on Fingerprint and Speech

Biometrics deals with the physiological and behavioral characteristics of an individual to establish identity. Fingerprint based authentication is the most advanced biometric authentication technology. The minutiae based fingerprint identification method offer reasonable identification rate. The feature minutiae map consists of about 70-100 minutia points and matching accuracy is dropping down while the size of database is growing up. Hence it is inevitable to make the size of the fingerprint feature code to be as smaller as possible so that identification may be much easier. In this research, a novel global singularity based fingerprint representation is proposed. Fingerprint baseline, which is the line between distal and intermediate phalangeal joint line in the fingerprint, is taken as the reference line. A polygon is formed with the singularities and the fingerprint baseline. The feature vectors are the polygonal angle, sides, area, type and the ridge counts in between the singularities. 100% recognition rate is achieved in this method. The method is compared with the conventional minutiae based recognition method in terms of computation time, receiver operator characteristics (ROC) and the feature vector length. Speech is a behavioural biometric modality and can be used for identification of a speaker. In this work, MFCC of text dependant speeches are computed and clustered using k-means algorithm. A backpropagation based Artificial Neural Network is trained to identify the clustered speech code. The performance of the neural network classifier is compared with the VQ based Euclidean minimum classifier. Biometric systems that use a single modality are usually affected by problems like noisy sensor data, non-universality and/or lack of distinctiveness of the biometric trait, unacceptable error rates, and spoof attacks. Multifinger feature level fusion based fingerprint recognition is developed and the performances are measured in terms of the ROC curve. Score level fusion of fingerprint and speech based recognition system is done and 100% accuracy is achieved for a considerable range of matching threshold

Physiological Effects Of Some Heavy Metals On Perna Viridis (Linnaeus)

No serious attempt has so far been made in India to make use of the ‘Mussel watch’ concept as a useful tool for pollution monitoring of the marine and estuarine environment. The recently conducted 'National seminar on mussel watch’ by the Cochin University of Science and Technology (13-14 Feb, 1986) discussed the technical aspects related to mussel watch programme and the application of sentinel organism concept to the coastal areas of India. It is well known that the biological and physiological characteristics of the organism inhabiting tropical waters such as those prevailing in India, and the ecological as well as the environmental characteristics of temperate areas, where mussel watch programmes are already in existence differ greatly. So it is essential to adopt the techniques and standards developed for temperate species to the situations and conditions in India. In this context it is a prerequisite to collect information on physiology and other biological indices of stress of possible sentinel organisms like P.viridis. In consideration of the above, P. viridis which is a potential sentinel organism, is selected for the present study

“Reconstruction of Gene Regulatory Network from Expression Profile of Plasma RNA Data of Colorectal Cancer Patients using Soft Computing Techniques”

Microarray data analysis is one of data mining tool which is used to extract meaningful information hidden in biological data. One of the major focuses on microarray data analysis is the reconstruction of gene regulatory network that may be used to provide a broader understanding on the functioning of complex cellular systems. Since cancer is a genetic disease arising from the abnormal gene function, the identification of cancerous genes and the regulatory pathways they control will provide a better platform for understanding the tumor formation and development. The major focus of this thesis is to understand the regulation of genes responsible for the development of cancer, particularly colorectal cancer by analyzing the microarray expression data. In this thesis, four computational algorithms namely fuzzy logic algorithm, modified genetic algorithm, dynamic neural fuzzy network and Takagi Sugeno Kang-type recurrent neural fuzzy network are used to extract cancer specific gene regulatory network from plasma RNA dataset of colorectal cancer patients. Plasma RNA is highly attractive for cancer analysis since it requires a collection of small amount of blood and it can be obtained at any time in repetitive fashion allowing the analysis of disease progression and treatment response.

Cooperative Caching Framework for Mobile Cloud Computing

Due to the advancement in mobile devices and wireless networks mobile cloud computing, which combines mobile computing and cloud computing has gained momentum since 2009. The characteristics of mobile devices and wireless network makes the implementation of mobile cloud computing more complicated than for fixed clouds. This section lists some of the major issues in Mobile Cloud Computing. One of the key issues in mobile cloud computing is the end to end delay in servicing a request. Data caching is one of the techniques widely used in wired and wireless networks to improve data access efficiency. In this paper we explore the possibility of a cooperative caching approach to enhance data access efficiency in mobile cloud computing. The proposed approach is based on cloudlets, one of the architecture designed for mobile cloud computing.

Biochemical and physiological characteristics of actinomycetes isolated from high altitude shola soils of tropical Montane forest

Actinomycetes are gram-positive, free-living, saprophytic bacteria widely distributed in soil, water and colonizing plants showing marked chemical and morphological diversity. They are potential source of many bioactive compounds, which have diverse clinical effects and important applications in human medicine. In the present work, we have studied some of the physiological and biochemical characteristics of 36 actinomycete strains isolated from the shola soils of tropical montane forest; a relatively unexplored biodiversity hotspot. Ability of actinomycetes isolates to ferment and produce acids from various carbohydrate sources such as innositol, mannose, sorbitol, galactose, mannitol, xylose, rhamnose, arabinose, lactose and fructose were studied. Almost all the carbon compounds were utilized by one or other actinomycete isolates. The most preferred carbon sources were found to be xylose (94.44%) followed by fructose and mannose (91.66%). Only 41.76% of the isolates were able to ferment lactose. The ability of actinomycetes isolates to decompose protein and amino acid differ considerably. 72.22% of the isolates were able to decompose milk protein casein and 61.11% of the isolates decompose tyrosine. Only 8.33% of the strains were able to decompose amino acid hypoxanthine and none of them were able to decompose amino acid xanthine. Potential of the actinomycetes isolates to reduce esculin, urea and hippurate and to resist lysozyme was also checked. 91.66% of the isolates showed ability to decompose esculin and 63.88% of the isolates had the capacity to produce urease and to decompose urea. Only 25% of the isolate were able to decompose hippurate and 94.44% showed lysozyme resistance

Computing median and antimedian sets in median graphs

The median (antimedian) set of a profile π = (u1, . . . , uk) of vertices of a graphG is the set of vertices x that minimize (maximize) the remoteness i d(x,ui ). Two algorithms for median graphs G of complexity O(nidim(G)) are designed, where n is the order and idim(G) the isometric dimension of G. The first algorithm computes median sets of profiles and will be in practice often faster than the other algorithm which in addition computes antimedian sets and remoteness functions and works in all partial cubes

Soft Computing Approach for Optimization of siRNA Efficiency Prediction for Post-transcriptional Gene Silencing

Post-transcriptional gene silencing by RNA interference is mediated by small interfering RNA called siRNA. This gene silencing mechanism can be exploited therapeutically to a wide variety of disease-associated targets, especially in AIDS, neurodegenerative diseases, cholesterol and cancer on mice with the hope of extending these approaches to treat humans. Over the recent past, a significant amount of work has been undertaken to understand the gene silencing mediated by exogenous siRNA. The design of efficient exogenous siRNA sequences is challenging because of many issues related to siRNA. While designing efficient siRNA, target mRNAs must be selected such that their corresponding siRNAs are likely to be efficient against that target and unlikely to accidentally silence other transcripts due to sequence similarity. So before doing gene silencing by siRNAs, it is essential to analyze their off-target effects in addition to their inhibition efficiency against a particular target. Hence designing exogenous siRNA with good knock-down efficiency and target specificity is an area of concern to be addressed. Some methods have been developed already by considering both inhibition efficiency and off-target possibility of siRNA against agene. Out of these methods, only a few have achieved good inhibition efficiency, specificity and sensitivity. The main focus of this thesis is to develop computational methods to optimize the efficiency of siRNA in terms of “inhibition capacity and off-target possibility” against target mRNAs with improved efficacy, which may be useful in the area of gene silencing and drug design for tumor development. This study aims to investigate the currently available siRNA prediction approaches and to devise a better computational approach to tackle the problem of siRNA efficacy by inhibition capacity and off-target possibility. The strength and limitations of the available approaches are investigated and taken into consideration for making improved solution. Thus the approaches proposed in this study extend some of the good scoring previous state of the art techniques by incorporating machine learning and statistical approaches and thermodynamic features like whole stacking energy to improve the prediction accuracy, inhibition efficiency, sensitivity and specificity. Here, we propose one Support Vector Machine (SVM) model, and two Artificial Neural Network (ANN) models for siRNA efficiency prediction. In SVM model, the classification property is used to classify whether the siRNA is efficient or inefficient in silencing a target gene. The first ANNmodel, named siRNA Designer, is used for optimizing the inhibition efficiency of siRNA against target genes. The second ANN model, named Optimized siRNA Designer, OpsiD, produces efficient siRNAs with high inhibition efficiency to degrade target genes with improved sensitivity-specificity, and identifies the off-target knockdown possibility of siRNA against non-target genes. The models are trained and tested against a large data set of siRNA sequences. The validations are conducted using Pearson Correlation Coefficient, Mathews Correlation Coefficient, Receiver Operating Characteristic analysis, Accuracy of prediction, Sensitivity and Specificity. It is found that the approach, OpsiD, is capable of predicting the inhibition capacity of siRNA against a target mRNA with improved results over the state of the art techniques. Also we are able to understand the influence of whole stacking energy on efficiency of siRNA. The model is further improved by including the ability to identify the “off-target possibility” of predicted siRNA on non-target genes. Thus the proposed model, OpsiD, can predict optimized siRNA by considering both “inhibition efficiency on target genes and off-target possibility on non-target genes”, with improved inhibition efficiency, specificity and sensitivity. Since we have taken efforts to optimize the siRNA efficacy in terms of “inhibition efficiency and offtarget possibility”, we hope that the risk of “off-target effect” while doing gene silencing in various bioinformatics fields can be overcome to a great extent. These findings may provide new insights into cancer diagnosis, prognosis and therapy by gene silencing. The approach may be found useful for designing exogenous siRNA for therapeutic applications and gene silencing techniques in different areas of bioinformatics.