A novel zebrafish model to provide mechanistic insights into the inflammatory events in carrageenan-induced abdominal edema

A suitable small animal model may help in the screening and evaluation of new drugs, especially those from natural products, which can be administered at lower dosages, fulfilling an urgent worldwide need. In this study, we explore whether zebrafish could be a model organism for carrageenan-induced abdominal edema. The research results showed that intraperitoneal (i.p.) administration of 1.5% λ-carrageenan in a volume of 20 µL significantly increased abdominal edema in adult zebrafish. Levels of the proinflammatory proteins tumor necrosis factor-α (TNF-α) and inducible nitric oxide synthase (iNOS) were increased in carrageenan-injected adult zebrafish during the development of abdominal edema. An associated enhancement was also observed in the leukocyte marker, myeloperoxidase (MPO). To support these results, we further observed that i.p. methylprednisolone (MP; 1 µg), a positive control, significantly inhibited carrageenan-induced inflammation 24 h after carrageenan administration. Furthermore, i.p. pretreatment with either an anti-TNF-α antibody (1∶5 dilution in a volume of 20 µL) or the iNOS-selective inhibitor aminoguanidine (AG; 1 µg) inhibited carrageenan-induced abdominal edema in adult zebrafish. This new animal model is uncomplicated, easy to develop, and involves a straightforward inducement of inflammatory edema for the evaluation of small volumes of drugs or test compounds.

Influence of miRNA in insulin signaling pathway and insulin resistance: micro-molecules with a major role in type-2 diabetes

The prevalence of type-2 diabetes (T2D) is increasing significantly throughout the globe since the last decade. This heterogeneous and multifactorial disease, also known as insulin resistance, is caused by the disruption of the insulin signaling pathway. In this review, we discuss the existence of various miRNAs involved in regulating the main protein cascades in the insulin signaling pathway that affect insulin resistance. The influence of miRNAs (miR-7, miR-124a, miR-9, miR-96, miR-15a/b, miR-34a, miR-195, miR-376, miR-103, miR-107, and miR-146) in insulin secretion and beta (β) cell development has been well discussed. Here, we highlight the role of miRNAs in different significant protein cascades within the insulin signaling pathway such as miR-320, miR-383, miR-181b with IGF-1, and its receptor (IGF1R); miR-128a, miR-96, miR-126 with insulin receptor substrate (IRS) proteins; miR-29, miR-384-5p, miR-1 with phosphatidylinositol 3-kinase (PI3K); miR-143, miR-145, miR-29, miR-383, miR-33a/b miR-21 with AKT/protein kinase B (PKB) and miR-133a/b, miR-223, miR-143 with glucose transporter 4 (GLUT4). Insulin resistance, obesity, and hyperlipidemia (high lipid levels in the blood) have a strong connection with T2D and several miRNAs influence these clinical outcomes such as miR-143, miR-103, and miR-107, miR-29a, and miR-27b. We also corroborate from previous evidence how these interactions are related to insulin resistance and T2D. The insights highlighted in this review will provide a better understanding on the impact of miRNA in the insulin signaling pathway and insulin resistance-associated diagnostics and therapeutics for T2D.

Understanding the conservation patterns and molecular phylogenetics of human death receptors family through computational biology

Human death receptors (TNFR1, FAS, DR3, DR4, DR5, DR6 and TNFBR), primarily from tumor necrosis receptor super family, play an essential role in the process of the extrinsic pathway of apoptosis. We performed conserved domain, amino acid residues analysis in which cysteine residues were found to be highly conserved for all the family members. Sixteen (16) highly conserved residues were observed in TNFR1, DR3 and TNFBR; and in case of Fas, only seven (7) residues are highly conserved. From molecular phylogenetics, we found that DR5 and DR4, TNFR1 and DR3 and TNFR1 and DR3 had the same point of origin. Alternatively, Fas was found to be distant from the rest of the death receptors. A network map was developed to explain these proteins are not only interlinked among themselves, but also interlinked with several other proteins. We have also observed from this system that scores of all the nodes ranges from 0.996 to 0.999.

Effect of Wnt3a on keratinocytes utilizing in vitro and bioinformatics analysis

Wingless-type (Wnt) signaling proteins participate in various cell developmental processes. A suppressive role of Wnt5a on keratinocyte growth has already been observed. However, the role of other Wnt proteins in proliferation and differentiation of keratinocytes remains unknown. Here, we investigated the effects of the Wnt ligand, Wnt3a, on proliferation and differentiation of keratinocytes. Keratinocytes from normal human skin were cultured and treated with recombinant Wnt3a alone or in combination with the inflammatory cytokine, tumor necrosis factor α (TNFα). Furthermore, using bioinformatics, we analyzed the biochemical parameters, molecular evolution, and protein–protein interaction network for the Wnt family. Application of recombinant Wnt3a showed an anti-proliferative effect on keratinocytes in a dose-dependent manner. After treatment with TNFα, Wnt3a still demonstrated an anti-proliferative effect on human keratinocytes. Exogenous treatment of Wnt3a was unable to alter mRNA expression of differentiation markers of keratinocytes, whereas an altered expression was observed in TNFα-stimulated keratinocytes. In silico phylogenetic, biochemical, and protein–protein interaction analysis showed several close relationships among the family members of the Wnt family. Moreover, a close phylogenetic and biochemical similarity was observed between Wnt3a and Wnt5a. Finally, we proposed a hypothetical mechanism to illustrate how the Wnt3a protein may inhibit the process of proliferation in keratinocytes, which would be useful for future researchers.

Sirtuins family--recent development as a drug target for aging, metabolism, and age related diseases

Silent information regulator 2 (Sir2) proteins, or sirtuins, are a family of proteins which influence several physiological responses and have implications for treating diseases of ageing. In this context, we have presented a summarized view on the discovery of Sir2 family proteins, the enzymatic activities, the role of sirtuins in aging, lifespan and onset of age-related symptoms. In addition, we have described the roles of mammalian sirtuins-with particular emphasis on their associations to aging, metabolism, and age related diseases with recent references. Current findings provide an understanding about mammalian sirtuins and their target diseases, small molecules discovery or drug discovery targeting sirtuin to tackle the serious diseases of aging.

miRNAs in insulin resistance and diabetes-associated pancreatic cancer: the 'minute and miracle' molecule moving as a monitor in the 'genomic galaxy'

The predominance of insulin resistance, T2D linked pancreatic cancer has increased throughout the world. The insulin/IGF signaling pathway related to insulin resistance, T2D and pancreatic cancer has been described. In this context, we have demonstrated the role of miRNAs in cancer progression and control of miRNAs in insulin/IGF signaling pathway, and pancreatic cancer. In this paper, an overview was depicted about the role of following miRNAs in pancreatic development and insulin secretion (miR-375, miR-7, miR-124a2, miR-195, miR-126, miR-9, miR-96, miR-34a); insulingrowth factor-1 receptor expression (miR-7, miR-139, miR-145, miR-1); the diabetes-associated pancreatic cancer pathway genes such as IRS, PI3K, AKT/PKB (miR-128a, miR-19a, miR-21, miR-29 a/b/c); mTOR protein regulation (miR- 99, miR-21, miR-126, and miR-146a) etc. At last, we have also explained the role of miRNAs in diagnostic marker (miR- 200, miR-21, miR-103, miR-107, and miR-155) and as a therapeutic modulator (miR-34, miR-21, miR-221, and miR-101) in pancreatic cancer.

DNA barcoding to map the microbial communities: current advances and future directions

During the last two decades, the DNA barcode development towards microbial community has increased dramatically. DNA barcode development is related to error-free and quick species identification which aid in understanding the microbial biodiversity, as well as the diseases related to microbial species. Here, we seek to evaluate the so-called barcoding initiatives for the microbial communities and the emerging trends in this field. In this paper, we describe the development of DNA marker-based DNA barcoding system, comparison between routine species identification and DNA barcode, and microbial biodiversity and DNA barcode for microbial communities. Two major topics, such as the molecular diversity of viruses and barcode for viruses have been discussed at the same time. We demonstrate the current status and the maker of DNA barcode for bacteria, algae, fungi, and protozoa. Furthermore, we argue about the promises, limitations, and present and future challenges of microbial barcode development.

Comparative bioinformatic analysis of the conserved domains, amino acid residues, and binding grooves of tumor necrosis factor

AIM

Comparative structural bioinformatic analysis of the conserved domains and amino acid residues, binding grooves of the tumor necrosis factor (TNF)α and β in order to elucidate structurebased inhibitor development was conducted.

METHODS

We carried out the bioinformatics study of TNF proteins at the Department of Bio-informatics (Galgotias University, India) between June and December 2012. TNFα and TNF-β functional protein sequences in FASTA format were obtained from the NCBI database for analysis. The online tool ClustalW from the European Bioinformatic Institute was used for multiple sequence alignment to record similarities. The Jmol server was used for 3D visualization of alpha helix, beta sheet and loops of TNF proteins. The PyMOL molecular visualization system was used to generate surface cavity and to identify binding grooves of TNF proteins.

RESULTS

This study showed highly conserved amino acids residues such as LYS11, PRO12, ALA14, HIS15, VAL50, PRO51, GLY54, LEU55, TYR56, LEU57, TYR59, SER60, GLN61, GLY122, VAL123, PHE124, PHE152, and GLY153 are consequent amino acids in TNF-β while residues such as ALA31, HIS32, SER77, GLN78, PHE166, and GLY167 are consequent amino acids in TNF-β. Surface cavity and binding grooves showed TNF-β with larger surface cavities than TNF-α with higher chances for drug development since small drug-like molecules can bind easily into the groove.

CONCLUSION

The results illustrate the structure of TNF proteins and the novel findings may guide future research on TNF and in the process of assisting the optimization of the pharmacological properties involving the two crucial proteins.

Evolution- and structure-based computational strategy reveals the impact of deleterious missense mutations on MODY 2 (maturity-onset diabetes of the young, type 2)

Heterozygous mutations in the central glycolytic enzyme glucokinase (GCK) can result in an autosomal dominant inherited disease, namely maturity-onset diabetes of the young, type 2 (MODY 2). MODY 2 is characterised by early onset: it usually appears before 25 years of age and presents as a mild form of hyperglycaemia. In recent years, the number of known GCK mutations has markedly increased. As a result, interpreting which mutations cause a disease or confer susceptibility to a disease and characterising these deleterious mutations can be a difficult task in large-scale analyses and may be impossible when using a structural perspective. The laborious and time-consuming nature of the experimental analysis led us to attempt to develop a cost-effective computational pipeline for diabetic research that is based on the fundamentals of protein biophysics and that facilitates our understanding of the relationship between phenotypic effects and evolutionary processes. In this study, we investigate missense mutations in the GCK gene by using a wide array of evolution- and structure-based computational methods, such as SIFT, PolyPhen2, PhD-SNP, SNAP, SNPs&GO, fathmm, and Align GVGD. Based on the computational prediction scores obtained using these methods, three mutations, namely E70K, A188T, and W257R, were identified as highly deleterious on the basis of their effects on protein structure and function. Using the evolutionary conservation predictors Consurf and Scorecons, we further demonstrated that most of the predicted deleterious mutations, including E70K, A188T, and W257R, occur in highly conserved regions of GCK. The effects of the mutations on protein stability were computed using PoPMusic 2.1, I-mutant 3.0, and Dmutant. We also conducted molecular dynamics (MD) simulation analysis through in silico modelling to investigate the conformational differences between the native and the mutant proteins and found that the identified deleterious mutations alter the stability, flexibility, and solvent-accessible surface area of the protein. Furthermore, the functional role of each SNP in GCK was identified and characterised using SNPeffect 4.0, F-SNP, and FASTSNP. We hope that the observed results aid in the identification of disease-associated mutations that affect protein structure and function. Our in silico findings provide a new perspective on the role of GCK mutations in MODY2 from an evolution-based structure-centric point of view. The computational architecture described in this paper can be used to predict the most appropriate disease phenotypes for large-genome sequencing projects and to provide individualised drug therapy for complex diseases such as diabetes.

Network analysis of transcription factors for nuclear reprogramming into induced pluripotent stem cell using bioinformatics

OBJECTIVE

Research related to induce pluripotent stem (iPS) cell generation has increased rapidly in recent years. Six transcription factors, namely OCT4, SOX2, C-MYC, KLF4, NANOG, and LIN28 have been widely used for iPS cell generation. As there is a lack of data on intra- and inter-networking among these six different transcription factors, the objective of this study is to analyze the intra- and inter-networks between them using bioinformatics.

MATERIALS AND METHODS

In this computational biology study, we used AminoNet, MATLAB to examine networking between the six different transcription factors. The directed network was constructed using MATLAB programming and the distance between nodes was estimated using a phylogram. The protein-protein interactions between the nuclear reprogramming factors was performed using the software STRING.

RESULTS

The relationship between C-MYC and NANOG was depicted using a phylogenetic tree and the sequence analysis showed OCT4, C-MYC, NANOG, and SOX2 together share a common evolutionary origin.

CONCLUSION

This study has shown an innovative rapid method for the analysis of intra and inter-networking among nuclear reprogramming factors. Data presented may aid researchers to understand the complex regulatory networks involving iPS cell generation.

Computational analysis of C-reactive protein for assessment of molecular dynamics and interaction properties

Serum C-reactive protein (CRP) is used as a marker of inflammation in several diseases including autoimmune disease and cardiovascular disease. CRP, a member of the pentraxin family, is comprised of five identical subunits. CRP has diverse ligand-binding properties which depend upon different structural states of CRP. However, little is known about the molecular dynamics and interaction properties of CRP. In this study, we used SAPS, SCRATCH protein predictor, PDBsum, ConSurf, ProtScale, Drawhca, ASAView, SCide and SRide server and performed comprehensive analyses of molecular dynamics, protein-protein and residue-residue interactions of CRP. We used 1GNH.pdb file for the crystal structure of human CRP which generated two pentamers (ABCDE and FGHIJ). The number of residues involved in residue-residue interactions between A-B, B-C, C-D, D-E, F-G, G-H, H-I, I-J, A-E and F-J subunits were 12, 11, 10, 11, 12, 11, 10, 11, 10 and 10, respectively. Fifteen antiparallel β sheets were involved in β-sheet topology, and five β hairpins were involved in forming the secondary structure. Analysis of hydrophobic segment distribution revealed deviations in surface hydrophobicity at different cavities present in CRP. Approximately 33 % of all residues were involved in the stabilization centers. We show that the bioinformatics tools can provide a rapid method to predict molecular dynamics and interaction properties of CRP. Our prediction of molecular dynamics and interaction properties of CRP combined with the modeling data based on the known 3D structure of CRP is helpful in designing stable forms of CRP mutants for structure-function studies of CRP and may facilitate in silico drug design for therapeutic targeting of CRP.

Predicting the impact of deleterious mutations in the protein kinase domain of FGFR2 in the context of function, structure, and pathogenesis--a bioinformatics approach

Fibroblast growth factor receptor 2 (FGFR2) controls a wide range of biological functions by regulating the cellular proliferation, survival, migration and differentiation. A growing body of preclinical data demonstrated that deregulation of the FGFR signalling through genetic modification was observed in various types of cancers. However, the extent to which genetic modifications interfere with gene regulation and their involvement in cancer susceptibility remains largely unknown. In this work, we performed in silico profiling of harmful non-synonymous single nucleotide polymorphisms (SNPs) in the protein kinase domain of FGFR2. Tolerance index, position-specific independent count score, change in free energy score (ΔΔG), Eris and FoldX indicated that seven mutations were found to be deleterious and may alter the protein function and structure. Furthermore, based on physico-chemical properties, two mutations K659N and R747H were found to be most deleterious in protein kinase domain and taken for further structural analysis. Docking study showed a complete loss of binding affinity followed by interference in hydrogen bonding and surrounding residues due to K659N and R747H mutations. In order to elucidate the mechanism behind the impact of mutation that can generate a ripple effect throughout the protein structure and ultimately affect the function, in-depth molecular dynamics simulation and principal component analysis were performed. The obtained results indicate that K659N and R747H mutations have a distinct effect on the dynamic behaviour of FGFR2 protein. Our strategy may be helpful for understanding SNP effects on proteins with function and their role in human genetic diseases and for the development of novel pharmacological strategies.

In silico discrimination of nsSNPs in hTERT gene by means of local DNA sequence context and regularity

Understanding and predicting the significance of novel genetic variants revealed by DNA sequencing is a major challenge to integrate and interpret in medical genetics with medical practice. Recent studies have afforded significant advances in characterization and predicting the association of single nucleotide polymorphisms in human TERT with various disorders, but the results remain inconclusive. In this context, a comparative study between disease causing and novel mutations in hTERT gene was performed computationally. Out of 59 missense mutations, five variants were predicted to be less stable with the most deleterious effect on hTERT gene by in silico tools, in which two mutations (L584W and M970T) were not previously reported to be involved in any of the human disorders. To get insight into the structural and functional impact due to the mutation, docking study and interaction analysis was performed followed by 6 ns molecular dynamics simulation. These results may provide new perspectives for the targeted drug discovery in the coming future.

Extrapolating the effect of deleterious nsSNPs in the binding adaptability of flavopiridol with CDK7 protein: a molecular dynamics approach

Background

Recent reports suggest the role of nonsynonymous single nucleotide polymorphisms (nsSNPs) in cyclin-dependent kinase 7 (CDK7) gene associated with defect in the DNA repair mechanism that may contribute to cancer risk. Among the various inhibitors developed so far, flavopiridol proved to be a potential antitumor drug in the phase-III clinical trial for chronic lymphocytic leukemia. Here, we described a theoretical assessment for the discovery of new drugs or drug targets in CDK7 protein owing to the changes caused by deleterious nsSNPs.

Methods

Three nsSNPs (I63R, H135R, and T285M) were predicted to have functional impact on protein function by SIFT, PolyPhen2, I-Mutant3, PANTHER, SNPs&GO, PhD-SNP, and screening for non-acceptable polymorphisms (SNAP). Furthermore, we analyzed the native and proposed mutant models in atomic level 10 ns simulation using the molecular dynamics (MD) approach. Finally, with the aid of Autodock 4.0 and PatchDock, we analyzed the binding efficacy of flavopiridol with CDK7 protein with respect to the deleterious mutations.

Results

By comparing the results of all seven prediction tools, three nsSNPs (I63R, H135R, and T285M) were predicted to have functional impact on the protein function. The results of protein stability analysis inferred that I63R and H135R exhibited less deviation in root mean square deviation in comparison with the native and T285M protein. The flexibility of all the three mutant models of CDK7 protein is diverse in comparison with the native protein. Following to that, docking study revealed the change in the active site residues and decrease in the binding affinity of flavopiridol with mutant proteins.

Conclusion

This theoretical approach is entirely based on computational methods, which has the ability to identify the disease-related SNPs in complex disorders by contrasting their costs and capabilities with those of the experimental methods. The identification of disease related SNPs by computational methods has the potential to create personalized tools for the diagnosis, prognosis, and treatment of diseases.

Lay abstract

Cell cycle regulatory protein, CDK7, is linked with DNA repair mechanism which can contribute to cancer risk. The main aim of this study is to extrapolate the relationship between the nsSNPs and their effects in drug-binding capability. In this work, we propose a new methodology which (1) efficiently identified the deleterious nsSNPs that tend to have functional effect on protein function upon mutation by computational tools, (2) analyze d the native protein and proposed mutant models in atomic level using MD approach, and (3) investigated the protein-ligand interactions to analyze the binding ability by docking analysis. This theoretical approach is entirely based on computational methods, which has the ability to identify the disease-related SNPs in complex disorders by contrasting their costs and capabilities with those of the experimental methods. Overall, this approach has the potential to create personalized tools for the diagnosis, prognosis, and treatment of diseases.

Quantitative microscopy approach for shape-based erythrocytes characterization in anaemia

Anaemia is one of the most common diseases in the world population. Primarily anaemia is identified based on haemoglobin level; and then microscopically examination of peripheral blood smear is required for characterizing and confirmation of anaemic stages. In conventional approach, experts visually characterize abnormality present in the erythrocytes under light microscope, and this evaluation process is subjective in nature and error prone. In this study, we have proposed a methodology using machine learning techniques for characterizing erythrocytes in anaemia associated with anaemia using microscopic images of peripheral blood smears. First, peripheral blood smear images are preprocessed based on grey world assumption technique and geometric mean filter for reducing unevenness of background illumination and noise reduction. Then erythrocyte cells are segmented using marker-controlled watershed segmentation technique. The erythrocytes in anaemia, such as, tear drop, echinocyte, acanthocyte, elliptocyte, sickle cells and normal erythrocytes cells have been characterized and classified based on their morphological changes. Optimal subset of features, ranked by information gain measure provides highest classification performance using logistic regression classifier in comparison with other standard classifiers.

Can computational biology improve the phylogenetic analysis of insulin?

Using computational biology, we have depicted the insulin phylogenetics. We have also analyzed the sequence alignment and sequence logos formation for both the insulin chain A and B for three groups namely, the mammalian group, vertebrates group and fish group. We have also analyzed cladograms of insulin for the mammalian group. In accordance with that path lengths, matrix for distance analysis, matching representation of nodes of the cladogram and dissimilarity between two nodes have been performed for both of the A and B chains of the mammalian group. Our results show that 12 amino acid residues (GlyA1, IleA2, ValA3, TyrA19, CysA20, AsnA21, LeuB6, GlyB8, LeuB11, ValB12, GlyB23 and PheB24) are highly conserved for all groups and among them some (GlyA1, IleA2, ValA3);(TyrA19, CysA20, AsnA21) are continuous. This study shows a rapid method to calculate the amino acid sequences in terms of evolutionary conservation rates as well as molecular phylogenetics.

Retraction Notice: Zebrafish Caspase-3: Molecular Cloning, Characterization, Crystallization and Phylogenetic Analysis

Title:

“Zebrafish Caspase-3: Molecular Cloning, Characterization, Crystallization and Phylogenetic Analysis; Protein & Peptide Letters, vol.13, no. 6; Pp.633-640”

Authors:

Chiranjib Chakraborty, Shyam S. Nandi, Surajit Sinha and V. K. Gera

Stem cells in the light of evolution

All organisms depend on stem cells for their survival. As a result, stem cells may be a prerequisite for the evolution of specific characteristics in organisms that include regeneration, multicellularity and coloniality. Stem cells have attracted the attention of biologists and medical scientists for a long time. These provide materials for regenerative medicine. We review in this paper, the link between modern stem cell research and early studies in ancient organisms. It also outlines details on stem cells in the light of evolution with an emphasis on their regeneration potential, coloniality and multicellularity. The information provided might be of use to molecular biologists, medical scientists and developmental biologists who are engaged in integrated research involving the stem cells.

Detection of damaging nsSNPs on human caspase-cascades related to apoptotic signalling pathway

In tumorigenesis, cancer genetics and the related mutations have been the main topic of study these days. Caspases have been found to be actively involved in the process of apoptosis. Malfunction of apoptosis is one of the causes for cancerous tumors and different caspase mutations are related to that process. It has been found that two groups of caspases involved in this process apoptosis which are initiator caspases and executioner caspases. SNPs have been extensively studied over the last decade, due to their association with a number of genetic diseases. Human SNPs have always been a source of information related to the complex changes associated with their origin. SNPs which can change the resulting amino acid i.e., nonsynonymous SNPs (nsSNPs) are of prime concern these days because of their direct relation with the disease or the respective individual. In this study our focus is not only to detect the nsSNPs available in the human caspase data but to further evaluate the potentially damaging nsSNPs. Using the computational approach we have been able to obtain almost seventy eight nsSNPs, among these few of the nsSNPs seem to have serious consequences, as they have been cross verified from a variety of SNP prediction tools. The functional as well as structural impact of the nsSNPs is determined and discussed. Our predicted nsSNPs on human caspases may be associated with cancer risk.

Automated Diagnosis of Oral Cancer Using Higher Order Spectra Features and Local Binary Pattern: A Comparative Study

In the field of quantitative microscopy, textural information plays a significant role very often in tissue characterization and diagnosis, in addition to morphology and intensity. The objective of this work is to improve the classification accuracy based on textural features for the development of a computer assisted screening of oral sub-mucous fibrosis (OSF). In fact, the approach introduced is used to grade the histopathological tissue sections into normal, OSF without dysplasia (OSFWD) and OSF with dysplasia (OSFD), which would help the oral onco-pathologists to screen the subjects rapidly. The main objective of this work is to evaluate the use of Higher Order Spectra (HOS) features and Local Binary Pattern (LBP) features extracted from the epithelial layer in classifying normal, OSFWD and OSFD. For this purpose, we extracted twenty three HOS features and nine LBP features and fed them to a Support Vector Machine (SVM) for automated diagnosis. One hundred and fifty eight images (90 normal, 42 OSFWD and 26 OSFD images) were used for analysis. LBP features provide a good sensitivity of 82.85% and specificity of 87.84%, and the HOS features provide higher values of sensitivity (94.07%) and specificity (93.33%) using SVM classifier. The proposed system, can be used as an adjunct tool by the onco-pathologists to cross-check their diagnosis.

Effect of caffeine, norfloxacin and nimesulide on heartbeat and VEGF expression of zebrafish larvae

The use of pharmaceuticals during pregnancy may causes abnormalities to the embryo. Sometime the drug also effect to the new born if the drug transferred through lactation. We have used zebrafish model to see the effect of some pharmaceuticals on embryos and larvae. Three drugs, caffeine, norfloxacin and nimesulide, were used for this study to see the effect mainly the hatching rate of eggs, heart beat rate and the vascular endothelial growth factor (VEGF) expression of the larvae. VEGF is an important signaling protein that involved generating the new blood vessels during embryonic development. We have used 10, 20, 50, 100 microg ml(-1) concentrations of all the drugs to see the effect. No significant mortality or malformations were observed in zebrafish embryos. Hatching was stared from 60 hr. In control group, 91% hatching rate was observed. Lowest hatching rate was observed using highest concentration of norfloxacin (100 microg ml(-1)) and nimesulide (100 microg ml(-1)) i.e. 55 and 56% respectively. In control group, 110 to 115 heart beat rate was counted per minute. Significantly higher heart beat was observed in caffeine treated group which is 125 to 140 min(-1) Lower heart beat was noted in nimesulide treated group which is 100 min(-1). We have tried to observe the possible effect of VEGF of the larvae by these three drugs. Expression of VEGF was very low in caffeine treated group. Almost no VGF expression was observe in 100 microg ml(-1) caffeine treated group. These studies suggest that there is a possibility that high dosage of caffeine can harm the unborn baby or new born babies, if the mothers use caffeine.

Effects of propofol on proliferation and anti-apoptosis of neuroblastoma SH-SY5Y cell line: new insights into neuroprotection

Recently, it has been suggested that anesthetic agents may have neuroprotective potency. The notion that anesthetic agents can offer neuroprotection remains controversial. Propofol, which is a short-acting intravenous anesthetic agent, may have potential as a neuroprotective agent. In this study, we tried to determine whether propofol affected the viability of human neuroblastoma SH-SY5Y cells by using the MTT assay. Surprisingly, our results showed that propofol at a dose of 1-10 μM could improve cell proliferation. However, at higher doses (200 μM), propofol appears to be cytotoxic. On the other hand, propofol could up-regulate the expression of key proteins involved in neuroprotection including B-cell lymphoma 2 at a dose range of 1-10 μM, activation of phospho-serine/threonine protein kinase at a dose range of 0.5-10 μM, and activation of phospho-extracellular signal-regulated kinases at a dose range of 5-10 μM. Similarly, we demonstrate that propofol (10 μM) could elevate protein levels of heat shock protein 90 and heat shock protein 70. Therefore, we choose to utilize a 10 μM concentration of propofol to assess neuroprotective activities in our studies. In the following experiments, we used dynorphin A to generate cytotoxic effects on SH-SY5Y cells. Our data indicate that propofol (10 μM) could inhibit the cytotoxicity in SH-SY5Y cells induced by dynorphin A. Furthermore, propofol (10 μM) could decrease the expression of the p-P38 protein as well. These data together suggest that propofol may have the potential to act as a neuroprotective agent against various neurologic diseases. However, further delineation of the precise neuroprotective effects of propofol will need to be examined.

Landscape mapping of functional proteins in insulin signal transduction and insulin resistance: a network-based protein-protein interaction analysis

The type 2 diabetes has increased rapidly in recent years throughout the world. The insulin signal transduction mechanism gets disrupted sometimes and it's known as insulin-resistance. It is one of the primary causes associated with type-2 diabetes. The signaling mechanisms involved several proteins that include 7 major functional proteins such as INS, INSR, IRS1, IRS2, PIK3CA, Akt2, and GLUT4. Using these 7 principal proteins, multiple sequences alignment has been created. The scores between sequences also have been developed. We have constructed a phylogenetic tree and modified it with node and distance. Besides, we have generated sequence logos and ultimately developed the protein-protein interaction network. The small insulin signal transduction protein arrangement shows complex network between the functional proteins.

A hypothetical relationship between the nuclear reprogramming factors for induced pluripotent stem (iPS) cells generation--bioinformatic and algorithmic approach

A hypothetical evolutionary relationship was generated between the nuclear reprogramming factors for induced pluripotent stem (iPS) cells generation. Utilizing bioinformatics techniques, sequence analyses and phylogenetic tree algorithms, a comparative study has been performed to understand the evolutionary relationship of human nuclear reprogramming factors of induced pluripotent stem cells (iPSCs) generation. Among the total six nuclear reprogramming factors, the four reprogramming factors (SOX2, C-MYC, KLF4, and LIN28) have significant evolutionary origin. Our study shows SOX2 and C-MYC have evolutionary relationship and common point of origin. Likewise, KLF4 and LIN28 are having evolutionary relationship and have common point of origin. Based on these evidences, we propose that our study may be a great help to the future researchers to understand the mechanism(s) as well as pathway of nuclear reprogramming process.

A special report on India's biotech scenario: advancement in biopharmaceutical and health care sectors

India's biotechnology industry has been growing towards new heights in conjunction with the recent economic outburst. The country has the potential to revolutionize biopharmaceutical and healthcare sectors. In this review, we have highlighted the achievements of India's biotechnology industry, especially biopharmaceutical and healthcare sectors that include therapeutics, diagnostics, stem cell research, human healthcare related bioinformatics and animal health care. We have also described regulatory mechanisms involved in India's health care biotech including manpower development.

Zebrafish: a complete animal model for in vivo drug discovery and development

In last few years, the use of zebrafish (Danio rerio) in scientific research is growing very rapidly. Initially, it was a popular as a model of vertebrate development because zebrafish embryos are transparent and also develop rapidly. Presently, the research using zebrafish is expanding into other areas such as pharmacology, clinical research as a diseases model and interestingly in drug discovery. The use of zebrafish in pharmaceutical research and discovery and drug development is mainly screening of lead compounds, target identification, target validation, morpholino oligonucleotide screens, assay development for drug discovery, physiology based drug discovery, quantitative structure-activity relationship (QSAR) and structure -activity relationships (SAR) study and drug toxicity study. In this paper, we have described properly all the areas of drug discovery where zebrafish is used as a tool. We are hopeful that the use of these techniques or methods will make the zebrafish a prominent model in drug discovery and development research in the forthcoming years.

Decorin-mediated inhibition of proliferation and migration of the human trophoblast via different tyrosine kinase receptors

Decorin (DCN), a decidua-derived TGFbeta-binding proteoglycan, negatively regulates proliferation, migration, and invasiveness of human extravillous trophoblast (EVT) cells in a TGFbeta-independent manner. The present study examined underlying mechanisms, in particular possible roles of epidermal growth factor receptor (EGFR), IGF receptor (IGFR)-I, and vascular endothelial growth factor receptor (VEGFR)-2. EVT cell sprouting from first-trimester chorionic villus explants in the presence or absence of TGFbeta-neutralizing antibody was inhibited with DCN, suggesting its negative regulatory role in situ. Inhibition of migration of the human EVT cell line HTR-8/SVneo in transwells undercoated with fibronectin was stronger when cells were briefly preincubated with DCN at 4 C (known to retard dissociation of receptor-ligand complex) than at 37 C, suggesting possible DCN action by cell membrane binding. Pretreatment of cells with an IGFR-I blocking agent, but not two EGFR blocking agents or a VEGFR blocking agent, significantly abrogated migration inhibitory effects of DCN, suggesting the involvement of IGFR-I but not EGFR or VEGFR in migration inhibition by DCN. On the other hand, pretreatment with either of the EGFR blocking agents, or the VEGFR blocking agent but not the IGFR-I blocking agent, blocked proliferation inhibitory effects of DCN, indicating the roles of EGFR and VEGFR, but not IGFR-I in antiproliferative action of DCN. EVT cells expressed EGFR, IGFR-I, and VEGFR-2. IGFR-I and VEGF-R2 were phosphorylated in the presence of their natural ligands as well as DCN, and these events were blocked by pretreatment with respective receptor blocking agents indicating DCN-mediated activation of these receptors. In conclusion, DCN effects on EVT cells are mediated selectively by multiple tyrosine kinase receptors.