Hyperglycemic and Hyperlipidemic Conditions Alter Cardiac Cell Biomechanical Properties

Currently, many diabetic cardiomyopathy (DC) studies focus on either in vitro molecular pathways or in vivo whole-heart properties such as ejection fraction. However, as DC is primarily a disease caused by changes in structural and functional properties, such studies may not precisely identify the influence of hyperglycemia or hyperlipidemia in producing specific cellular changes, such as increased myocardial stiffness or diastolic dysfunction. To address this need, we developed an in vitro approach to examine how structural and functional properties may change as a result of a diabetic environment. Particle-tracking microrheology was used to characterize the biomechanical properties of cardiac myocytes and fibroblasts under hyperglycemia or hyperlipidemic conditions. We showed that myocytes, but not fibroblasts, exhibited increased stiffness under diabetic conditions. Hyperlipidemia, but not hyperglycemia, led to increased cFos expression. Although direct application of reactive oxygen species had only limited effects that altered myocyte properties, the antioxidant N-acetylcysteine had broader effects in limiting glucose or fatty-acid alterations. Changes consistent with clinical DC alterations occur in cells cultured in elevated glucose or fatty acids. However, the individual roles of glucose, reactive oxygen species, and fatty acids are varied, suggesting multiple pathway involvement.     

Cardiomyocyte Antihypertrophic Effect of Adipose Tissue Conditioned Medium from Rats and Its Abrogation by Obesity is Mediated by the Leptin to Adiponectin Ratio

White adipocytes are known to function as endocrine organs by secreting a plethora of bioactive adipokines which can regulate cardiac function including the development of hypertrophy. We determined whether adipose tissue conditioned medium (ATCM) generated from the epididymal regions of normal rats can affect the hypertrophic response of cultured rat ventricular myocytes to endothelin-1 (ET-1) administration. Myocytes were treated with ET-1 (10 nM) for 24 hours in the absence or presence of increasing ATCM concentrations. ATCM supressed the hypertrophic response to ET-1 in a concentration-dependent manner, an effect enhanced by the leptin receptor antagonist and attenuated by an antibody against the adiponectin AdipoR1 receptor. Antihypertrophic effects were also observed with ATCM generated from perirenal-derived adipose tissue. However, this effect was absent in ATCM from adipose tissue harvested from corpulent JCR:LA-cp rats. Detailed analyses of adipokine content in ATCM from normal and corpulent rats revealed no differences in the majority of products assayed, although a significant increase in leptin concentrations concomitant with decreased adiponectin levels was observed, resulting in a 11 fold increase in the leptin to adiponectin ratio in ATCM from JCR:LA-cp. The antihypertrophic effect of ATCM was associated with increased phosphorylation of AMP-activated protein kinase (AMPK), an effect abrogated by the AdipoR1 antibody. Moreover, the antihypertrophic effect of ATCM was mimicked by an AMPK activator. There was no effect of ET-1 on mitogen-activated protein kinase (MAPK) activities 24 hour after its addition either in the presence or absence of ATCM. Our study suggests that adipose tissue from healthy subjects exerts antihypertrophic effects via an adiponectin–dependent pathway which is impaired in obesity, most likely due to adipocyte remodelling resulting in enhanced leptin and reduced adiponectin levels.     

Epitope analysis and molecular modeling reveal the topography of the C-terminal peptide of the beta-subunit of human chorionic gonadotropin.

Human chorionic gonadotropin (hCG) belongs to a family of heterodimeric glycoprotein hormones that share a common alpha-subunit and a hormone-specific beta-subunit. Among the gonadotropin beta-subunits, greater than 85% homology exists between lutropin (hLH)beta and hCGbeta in their first 114 amino acid residues. However, unlike hLHbeta, hCGbeta contains a 31-amino acid hydrophilic stretch at its carboxyl end (CTPbeta: C-terminal peptide). Although the crystal structure of deglycosylated hCG has been solved, the topography of CTPbeta remains unknown. In this study, we have attempted to define the topology of CTPbeta using mAb probes. We investigated three epitopes on hCGalpha, which are hidden in the hCGalphabeta dimer. However, these epitopes are not hidden in hLH, which has a similar subunit interface to that of hCG, but lacks CTPbeta. This suggested that these epitopes are not masked at the subunit interface of hLH or hCG. Hence, we hypothesized that, in the case of hCG, these epitopes are masked by the CTPbeta. Consistent with this view, several treatments of hCG that removed CTPbeta unmasked these epitopes and enhanced their reactivity with the corresponding mAbs. In order to localise the position of CTPbeta on the alpha-subunit, we used an epitope-mapping strategy [N. Venkatesh & G. S. Murthy (1997) J. Immunol. Methods 202, 173-182] based on differential susceptibility of epitopes to covalent modifications. This enabled us to predict the possible topography of CTPbeta. Further, we were also able to build a model of CTPbeta, completely independently of the epitope-mapping studies, using a homology-based modeling approach [S. Krishnaswamy, I. Lakshminarayanan & S. Bhattacharya (1995) Protein Sci. 4 (Suppl. 2), 86-97]. Results obtained from these two different approaches (epitope analysis and homology modeling) agree with each other and indicate that portions of CTPbeta are in contact with hCGalpha in the native hCG dimer.     

Aspergillosis in desert locust (Schistocerka gregaria Forsk)

Fatal Aspergillus flavus infection of Desert Locust at Field Station for Investigations on Locusts, Bikaner, India, has been described. The infection appeared in the form of pinkish to brownish black patches with hardening of the affected regions, paralysis and twichings of the legs. The fungus was demonstrated in the lesions and was isolated from the diseased parts as well as from the air, floor and walls of the breeding cabin. The cool and humid conditions of the cabin favoured growth of the fungus and the air blasts helped in dissemination of its spores in the air which predisposed the disease. The infection appeared exogenous with the fungus gaining access through surface and invading the deeper tissues. It has often been observed at the Field Station for Investigations on Locusts, Bikaner, India, that the mortility rate of Desert Locust (Schistocerca gregaria Forst) at times increased to a frustating level preventing the building of a good laboratory stock (5). All the diseased and dying insects showed similar features. Sporadic deaths occured throughout the year and were preceeded by similar signs and symtoms. On 12th May 1975 following a two day dust storm about 40% of the insects in a breeding cabin developed these features and ultimately died. This paper describes investigations under taken at our end to study aetiopathogenesis of this disease.     

A conceptual review on systems biology in health and diseases: from biological networks to modern therapeutics

Human physiology is an ensemble of various biological processes spanning from intracellular molecular interactions to the whole body phenotypic response. Systems biology endures to decipher these multi-scale biological networks and bridge the link between genotype to phenotype. The structure and dynamic properties of these networks are responsible for controlling and deciding the phenotypic state of a cell. Several cells and various tissues coordinate together to generate an organ level response which further regulates the ultimate physiological state. The overall network embeds a hierarchical regulatory structure, which when unusually perturbed can lead to undesirable physiological state termed as disease. Here, we treat a disease diagnosis problem analogous to a fault diagnosis problem in engineering systems. Accordingly we review the application of engineering methodologies to address human diseases from systems biological perspective. The review highlights potential networks and modeling approaches used for analyzing human diseases. The application of such analysis is illustrated in the case of cancer and diabetes. We put forth a concept of cell-to-human framework comprising of five modules (data mining, networking, modeling, experimental and validation) for addressing human physiology and diseases based on a paradigm of system level analysis. The review overtly emphasizes on the importance of multi-scale biological networks and subsequent modeling and analysis for drug target identification and designing efficient therapies.     

Is Demography Destiny? Application of Machine Learning Techniques to Accurately Predict Population Health Outcomes from a Minimal Demographic Dataset

For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC) from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD) outcomes (four NCDs and two major clinical risk factors), based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88) and those excluded from the development for use as a completely separated validation sample (median correlation 0.85), demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease.     

BiNChE: A web tool and library for chemical enrichment analysis based on the ChEBI ontology

Background

Ontology-based enrichment analysis aids in the interpretation and understanding of large-scale biological data. Ontologies are hierarchies of biologically relevant groupings. Using ontology annotations, which link ontology classes to biological entities, enrichment analysis methods assess whether there is a significant over or under representation of entities for ontology classes. While many tools exist that run enrichment analysis for protein sets annotated with the Gene Ontology, there are only a few that can be used for small molecules enrichment analysis.

Results

We describe BiNChE, an enrichment analysis tool for small molecules based on the ChEBI Ontology. BiNChE displays an interactive graph that can be exported as a high-resolution image or in network formats. The tool provides plain, weighted and fragment analysis based on either the ChEBI Role Ontology or the ChEBI Structural Ontology.

Conclusions

BiNChE aids in the exploration of large sets of small molecules produced within Metabolomics or other Systems Biology research contexts. The open-source tool provides easy and highly interactive web access to enrichment analysis with the ChEBI ontology tool and is additionally available as a standalone library.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0486-3) contains supplementary material, which is available to authorized users.