Non-invasive single-cell biomechanical analysis using live-imaging datasets

The physiological state of a cell is governed by a multitude of processes and can be described by a combination of mechanical, spatial and temporal properties. Quantifying cell dynamics at multiple scales is essential for comprehensive studies of cellular function, and remains a challenge for traditional end-point assays. We introduce an efficient, non-invasive computational tool that takes time-lapse images as input to automatically detect, segment and analyze unlabeled live cells; the program then outputs kinematic cellular shape and migration parameters, while simultaneously measuring cellular stiffness and viscosity. We demonstrate the capabilities of the program by testing it on human mesenchymal stem cells (huMSCs) induced to differentiate towards the osteoblastic (huOB) lineage, and T-lymphocyte cells (T cells) of naïve and stimulated phenotypes. The program detected relative cellular stiffness differences in huMSCs and huOBs that were comparable to those obtained with studies that utilize atomic force microscopy; it further distinguished naïve from stimulated T cells, based on characteristics necessary to invoke an immune response. In summary, we introduce an integrated tool to decipher spatiotemporal and intracellular dynamics of cells, providing a new and alternative approach for cell characterization

Trabecular bone volume and osteoprotegerin expression in uremic rats given high calcium

Calcium (Ca)-containing phosphate binders have been recommended for the treatment of hyperphosphatemia in children with chronic kidney disease. To study the effects of high Ca levels on trabecular bone volume (BV) and osteoprotegerin (OPG) expression in uremic young rats, a model of marked overcorrection of secondary hyperparathyroidism was created by providing a diet of high Ca to 5/6 nephrectomized young rats (Nx-Ca) for 4 weeks. The results of chondrocyte proliferation and apoptosis, osteoclastic activity, OPG expression and BV were compared among intact rats given the control diet, intact rats given a high Ca diet and 5/6 nephrectomized rats given the control diet (Nx-Control) and the high Ca diet (Nx-Ca). Ionized Ca levels were higher and parathyroid hormone levels were lower in Nx-Ca rats than in the other groups. Final weight, final length and final tibial length of Nx-Ca rats were significantly less than those of the other groups, although the length gain did not differ among the groups. The hypertrophic zone width was markedly enlarged in Nx-Ca rats. Chondrocyte proliferation rates did not differ among the groups, whereas osteoclastic activity was decreased in Nx-Ca rats compared with the Nx-Control animals. The OPG expression and BV were increased in Nx-Ca rats compared with the Nx-Control rats. Increased BV should improve bone strength, whereas disturbance of osteoclastogenesis interferes with bone remodeling. Bone quality has yet to be determined in high Ca-fed uremic young rats

Prescribing practices of primary-care veterinary practitioners in dogs diagnosed with bacterial pyoderma

Concern has been raised regarding the potential contributions of veterinary antimicrobial use to increasing levels of resistance in bacteria critically important to human health. Canine pyoderma is a frequent, often recurrent diagnosis in pet dogs, usually attributable to secondary bacterial infection of the skin. Lesions can range in severity based on the location, total area and depth of tissue affected and antimicrobial therapy is recommended for resolution. This study aimed to describe patient signalment, disease characteristics and treatment prescribed in a large number of UK, primary-care canine pyoderma cases and to estimate pyoderma prevalence in the UK vet-visiting canine population

An Analysis of Solution Properties of the Graph Coloring Problem

This paper concerns the analysis of solution properties of the Graph Coloring Problem. For this purpose, we introduce a property based on the notion of representative sets which are sets of vertices that are always colored the same in a set of solutions. Experimental results on well-studied DIMACS graphs show that many of them contain such sets and give interesting information about the diversity of the solutions. We also show how such an analysis may be used to improve a tabu search algorithm

Gene expression analyses in breast cancer epidemiology: the Norwegian Women and Cancer postgenome cohort study

Introduction The introduction of high-throughput technologies, also called -omics technologies, into epidemiology has raised the need for high-quality observational studies to reduce several sources of error and bias. Methods The Norwegian Women and Cancer (NOWAC) postgenome cohort study consists of approximately 50,000 women born between 1943 and 1957 who gave blood samples between 2003 and 2006 and filled out a two-page questionnaire. Blood was collected in such a way that RNA is preserved and can be used for gene expression analyses. The women are part of the NOWAC study consisting of 172,471 women 30 to 70 years of age at recruitment from 1991 to 2006 who answered one to three questionnaires on diet, medication use, and lifestyle. In collaboration with the Norwegian Breast Cancer Group, every NOWAC participant born between 1943 and 1957 who is admitted to a collaborating hospital for a diagnostic biopsy or for surgery of breast cancer will be asked to donate a tumor biopsy and two blood samples. In parallel, at least three controls are approached for each breast cancer case in order to obtain blood samples from at least two controls per case. The controls are drawn at random from NOWAC matched by time of follow-up and age. In addition, 400 normal breast tissues as well as blood samples will be collected among healthy women participating at the Norwegian Mammography Screening program at the Breast Imaging Center at the University Hospital of North-Norway, Tromsø. Results The NOWAC postgenome cohort offers a unique opportunity (a) to study blood-derived gene expression profiles as a diagnostic test for breast cancer in a nested case-control design with adjustment for confounding factors related to different exposures, (b) to improve the reliability and accuracy of this approach by adjusting for an individual's genotype (for example, variants in genes coding for hormone and drug-metabolizing and detoxifying enzymes), (c) to study gene expression profiles from peripheral blood as surrogate tissue to biomonitor defined exposure (for example, hormone) and its association with disease risk (that is, breast cancer), and (d) to study gene variants (single nucleotide polymorphisms and copy number variations) and environmental exposure (endogenous and exogenous hormones) and their influence on the incidence of different molecular subtypes of breast cancer. Conclusion The NOWAC postgenome cohort combining a valid epidemiological approach with richness of biological samples should make an important contribution to the study of the etiology and system biology of breast cancer

Bayesian estimation of genetic parameters for multivariate threshold and continuous phenotypes and molecular genetic data in simulated horse populations using Gibbs sampling

<p>Abstract</p> <p>Background</p> <p>Requirements for successful implementation of multivariate animal threshold models including phenotypic and genotypic information are not known yet. Here simulated horse data were used to investigate the properties of multivariate estimators of genetic parameters for categorical, continuous and molecular genetic data in the context of important radiological health traits using mixed linear-threshold animal models via Gibbs sampling. The simulated pedigree comprised 7 generations and 40000 animals per generation. Additive genetic values, residuals and fixed effects for one continuous trait and liabilities of four binary traits were simulated, resembling situations encountered in the Warmblood horse. Quantitative trait locus (QTL) effects and genetic marker information were simulated for one of the liabilities. Different scenarios with respect to recombination rate between genetic markers and QTL and polymorphism information content of genetic markers were studied. For each scenario ten replicates were sampled from the simulated population, and within each replicate six different datasets differing in number and distribution of animals with trait records and availability of genetic marker information were generated. (Co)Variance components were estimated using a Bayesian mixed linear-threshold animal model via Gibbs sampling. Residual variances were fixed to zero and a proper prior was used for the genetic covariance matrix.</p> <p>Results</p> <p>Effective sample sizes (ESS) and biases of genetic parameters differed significantly between datasets. Bias of heritability estimates was -6% to +6% for the continuous trait, -6% to +10% for the binary traits of moderate heritability, and -21% to +25% for the binary traits of low heritability. Additive genetic correlations were mostly underestimated between the continuous trait and binary traits of low heritability, under- or overestimated between the continuous trait and binary traits of moderate heritability, and overestimated between two binary traits. Use of trait information on two subsequent generations of animals increased ESS and reduced bias of parameter estimates more than mere increase of the number of informative animals from one generation. Consideration of genotype information as a fixed effect in the model resulted in overestimation of polygenic heritability of the QTL trait, but increased accuracy of estimated additive genetic correlations of the QTL trait.</p> <p>Conclusion</p> <p>Combined use of phenotype and genotype information on parents and offspring will help to identify agonistic and antagonistic genetic correlations between traits of interests, facilitating design of effective multiple trait selection schemes.</p

Expression of Telomerase and Telomere Length Are Unaffected by either Age or Limb Regeneration in Danio rerio

BACKGROUND:The zebrafish is an increasingly popular model for studying many aspects of biology. Recently, ztert, the zebrafish homolog of the mammalian telomerase gene has been cloned and sequenced. In contrast to humans, it has been shown that the zebrafish maintains telomerase activity for much of its adult life and has remarkable regenerative capacity. To date, there has been no longitudinal study to assess whether this retention of telomerase activity equates to the retention of chromosome telomere length through adulthood. METHODOLOGY/PRINCIPAL FINDINGS:We have systematically analyzed individual organs of zebrafish with regard to both telomere length and telomerase activity at various time points in its adult life. Heart, gills, kidney, spleen, liver, and intestine were evaluated at 3 months, 6 months, 9 months, and 2 years of age by Southern blot analysis. We found that telomeres do not appreciably shorten throughout the lifespan of the zebrafish in any organ. In addition, there was little difference in telomere lengths between organs. Even when cells were under the highest pressure to divide after fin-clipping experiments, telomere length was unaffected. All aged (2 year old) tissues examined also expressed active amounts of telomerase activity as assessed by TRAP assay. CONCLUSIONS/SIGNIFICANCE:In contrast to several other species including humans, the retention of lifelong telomerase and telomeres, as we have reported here, would be necessary in the zebrafish to maintain its tremendous regenerative capacity. The ongoing study of the zebrafish's ability to maintain telomerase activity may be helpful in unraveling the complexity involved in the maintenance (or lack thereof) of telomeres in other species such the mouse or human

Amino Acid Similarity Accounts for T Cell Cross-Reactivity and for “Holes” in the T Cell Repertoire

Background: Cytotoxic T cell (CTL) cross-reactivity is believed to play a pivotal role in generating immune responses but the extent and mechanisms of CTL cross-reactivity remain largely unknown. Several studies suggest that CTL clones can recognize highly diverse peptides, some sharing no obvious sequence identity. The emerging realization in the field is that T cell receptors (TcR) recognize multiple distinct ligands. Principal Findings: First, we analyzed peptide scans of the HIV epitope SLFNTVATL (SFL9) and found that TCR specificity is position dependent and that biochemically similar amino acid substitutions do not drastically affect recognition. Inspired by this, we developed a general model of TCR peptide recognition using amino acid similarity matrices and found that such a model was able to predict the cross-reactivity of a diverse set of CTL epitopes. With this model, we were able to demonstrate that seemingly distinct T cell epitopes, i.e., ones with low sequence identity, are in fact more biochemically similar than expected. Additionally, an analysis of HIV immunogenicity data with our model showed that CTLs have the tendency to respond mostly to peptides that do not resemble self-antigens. Conclusions: T cell cross-reactivity can thus, to an extent greater than earlier appreciated, be explained by amino acid similarity. The results presented in this paper will help resolving some of the long-lasting discussions in the field of T cel

Co-prescription of medication for bipolar disorder and diabetes mellitus : a nationwide population based study with focus on gender differences

BackgroundStudies have shown a correlation between bipolar disorder and diabetes mellitus. It is unclear if this correlation is a part of common pathophysiological pathways, or if medication for bipolar disorder has negative effects on blood sugar regulation.MethodsThe Norwegian prescription database was analyzed. Prescriptions for lithium, lamotrigine, carbamazepine and valproate were used as proxies for bipolar disorder. Prescriptions for insulin and oral anti-diabetic agents were used as proxies for diabetes mellitus. We explored the association between medication for bipolar disorder and diabetes medication by logistic regressionResultsWe found a strong association between concomitant use of medication to treat diabetes mellitus and mood stabilizers for the treatment of bipolar disorder. Females had a 30% higher risk compared to men of being treated for both disorders. Persons using oral anti-diabetic agents had higher odds of receiving valproate than either lithium or lamotrigine. Use of insulin as monotherapy seemed to have lower odds than oral anti-diabetic agents of co-prescription of mood stabilizers, compared to the general population.ConclusionsThis study showed a strong association between the use of mood stabilizers and anti-diabetic agents. The association was stronger among women than men

Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method

<p>Abstract</p> <p>Background</p> <p>Antigen presenting cells (APCs) sample the extra cellular space and present peptides from here to T helper cells, which can be activated if the peptides are of foreign origin. The peptides are presented on the surface of the cells in complex with major histocompatibility class II (MHC II) molecules. Identification of peptides that bind MHC II molecules is thus a key step in rational vaccine design and developing methods for accurate prediction of the peptide:MHC interactions play a central role in epitope discovery. The MHC class II binding groove is open at both ends making the correct alignment of a peptide in the binding groove a crucial part of identifying the core of an MHC class II binding motif. Here, we present a novel stabilization matrix alignment method, SMM-align, that allows for direct prediction of peptide:MHC binding affinities. The predictive performance of the method is validated on a large MHC class II benchmark data set covering 14 HLA-DR (human MHC) and three mouse H2-IA alleles.</p> <p>Results</p> <p>The predictive performance of the SMM-align method was demonstrated to be superior to that of the Gibbs sampler, TEPITOPE, SVRMHC, and MHCpred methods. Cross validation between peptide data set obtained from different sources demonstrated that direct incorporation of peptide length potentially results in over-fitting of the binding prediction method. Focusing on amino terminal peptide flanking residues (PFR), we demonstrate a consistent gain in predictive performance by favoring binding registers with a minimum PFR length of two amino acids. Visualizing the binding motif as obtained by the SMM-align and TEPITOPE methods highlights a series of fundamental discrepancies between the two predicted motifs. For the DRB1*1302 allele for instance, the TEPITOPE method favors basic amino acids at most anchor positions, whereas the SMM-align method identifies a preference for hydrophobic or neutral amino acids at the anchors.</p> <p>Conclusion</p> <p>The SMM-align method was shown to outperform other state of the art MHC class II prediction methods. The method predicts quantitative peptide:MHC binding affinity values, making it ideally suited for rational epitope discovery. The method has been trained and evaluated on the, to our knowledge, largest benchmark data set publicly available and covers the nine HLA-DR supertypes suggested as well as three mouse H2-IA allele. Both the peptide benchmark data set, and SMM-align prediction method (<it>NetMHCII</it>) are made publicly available.</p