Paleo-oncology: the role of ancient remains in the study of cancer

Paleo-oncology is the study of carcinomas and sarcomas in ancient human populations and their hominid precursors. These populations are informative concerning the possible influences on cancer of morphologic and functional evolution, diet, lifestyle, and other environmental factors. The prevalence of cancer in ancient populations might have differed from that in modern humans, because of substantial differences in tobacco and alcohol use, diet, life expectancy, and the availability of treatment. The available physical data concerning cancer in antiquity includes evidence of its existence in animal fossils and ancient humans and their precursors. The difficulties of paleo-oncologic research include a limited soft tissue record. In evaluating cancer in ancient remains, one must also deal with the problem of pseudopathology: whether an observed tissue change is all antemortem pathologic lesion or a postmortem artifact. Future archeological discoveries and the application of improved diagnostic techniques may enable paleo-oncology to make further contributions to our understanding of cancer.     

A comparison of phasing algorithms for trios and unrelated individuals

Knowledge of haplotype phase is valuable for many analysis methods in the study of disease, population, and evolutionary genetics. Considerable research effort has been devoted to the development of statistical and computational methods that infer haplotype phase from genotype data. Although a substantial number of such methods have been developed, they have focused principally on inference from unrelated individuals, and comparisons between methods have been rather limited. Here, we describe the extension of five leading algorithms for phase inference for handling father-mother-child trios. We performed a comprehensive assessment of the methods applied to both trios and to unrelated individuals, with a focus on genomic-scale problems, using both simulated data and data from the HapMap project. The most accurate algorithm was PHASE (v2.1). For this method, the percentages of genotypes whose phase was incorrectly inferred were 0.12%, 0.05%, and 0.16% for trios from simulated data, HapMap Centre d'Etude du Polymorphisme Humain (CEPH) trios, and HapMap Yoruban trios, respectively, and 5.2% and 5.9% for unrelated individuals in simulated data and the HapMap CEPH data, respectively. The other methods considered in this work had comparable but slightly worse error rates. The error rates for trios are similar to the levels of genotyping error and missing data expected. We thus conclude that all the methods considered will provide highly accurate estimates of haplotypes when applied to trio data sets. Running times differ substantially between methods. Although it is one of the slowest methods, PHASE (v2.1) was used to infer haplotypes for the 1 million-SNP HapMap data set. Finally, we evaluated methods of estimating the value of r(2) between a pair of SNPs and concluded that all methods estimated r(2) well when the estimated value was >or=0.8.     

Guía clínica de diagnóstico y tratamiento del prolactinoma y la hiperprolactinemia

ObjectiveTo provide practical and up to date recommendations for evaluation, differential diagnosis, and treatment of prolactinoma and hyperprolactinemia in various clinical settings.ParticipantsMembers of the Neuroendocrinology Working Group of the Spanish Society of Endocrinology.MethodsRecommendations were formulated according to the Grading of Recommendations, Assessment, Development, and Evaluation system (GRADE) to describe both the strength of recommendations and the quality of evidence. A systematic search was made in Medline (Pubmed) for each subject, and authors’ considerations were added in areas where the literature provided scarce evidence. Finally, recommendations were jointly discussed by the Working Group.ConclusionsThe document provides evidence-based practical and updated recommendations for diagnosis and management of hyperprolactinemia and prolactinoma, including drug-induced hyperprolactinemia, treatment options for prolactinoma (drugs, surgery, and radiotherapy), prolactinoma in pregnancy, adverse effects of dopaminergic agents, and drug-resistant and malignant prolactinomas.     

Enhanced Localization of Genetic Samples through Linkage-Disequilibrium Correction

Characterizing the spatial patterns of genetic diversity in human populations has a wide range of applications, from detecting genetic mutations associated with disease to inferring human history. Current approaches, including the widely used principal-component analysis, are not suited for the analysis of linked markers, and local and long-range linkage disequilibrium (LD) can dramatically reduce the accuracy of spatial localization when unaccounted for. To overcome this, we have introduced an approach that performs spatial localization of individuals on the basis of their genetic data and explicitly models LD among markers by using a multivariate normal distribution. By leveraging external reference panels, we derive closed-form solutions to the optimization procedure to achieve a computationally efficient method that can handle large data sets. We validate the method on empirical data from a large sample of European individuals from the POPRES data set, as well as on a large sample of individuals of Spanish ancestry. First, we show that by modeling LD, we achieve accuracy superior to that of existing methods. Importantly, whereas other methods show decreased performance when dense marker panels are used in the inference, our approach improves in accuracy as more markers become available. Second, we show that accurate localization of genetic data can be achieved with only a part of the genome, and this could potentially enable the spatial localization of admixed samples that have a fraction of their genome originating from a given continent. Finally, we demonstrate that our approach is resistant to distortions resulting from long-range LD regions; such distortions can dramatically bias the results when unaccounted for.     

Regulation of glycolysis and l-glycerol 3-phosphate concentration in rat epididymal adipose tissue in vitro. Role of phosphofructokinase

1. Attempts were made to define the role of phosphofructokinase in glycolytic control and the factors regulating the concentration of l-glycerol 3-phosphate in rat epididymal fat pads incubated in vitro. 2. Glycolysis rates were altered by anoxia or by additions of insulin, adrenaline or both to the incubation medium, and the changes in rate were related to changes in the steady-state concentrations of hexose phosphates, adenine nucleotides, l-glycerol 3-phosphate and citrate in the whole tissue. Measurements were also made of the lactate/pyruvate concentration ratio in the medium after incubation. 3. The mass-action ratios of phosphofructokinase, calculated from the whole-tissue concentrations of products and substrates, were less than 0.1% of the value of the ratio at pH7.4 at equilibrium. 4. Only in the presence of adrenaline could the observed stimulation of glycolytic flux be related to a possible activation of phosphofructokinase since, in this situation, the concentration of one substrate, fructose 6-phosphate, was not altered and the concentration of the other, ATP, was decreased. Increased glycolytic flux in the presence of insulin may be explained by an observed increase in the concentration of the substrate, fructose 6-phosphate. Under anaerobic conditions, glycolytic flux was decreased but this did not appear to be the result of inhibition of phosphofructokinase, since the concentrations of both substrates, fructose 6-phosphate and ATP, were decreased. The changes in glycolytic flux with insulin and anoxia may be secondary to changes in the rate of glucose uptake. 5. Changes in l-glycerol 3-phosphate concentration appear to be related both to changes in the concentration of dihydroxyacetone phosphate and to changes in the NADH/NAD(+) concentration ratio in the cytoplasm. They do not seem to be related directly to alterations in glycolytic rate.     

Detecting protein sequence conservation via metric embeddings

MOTIVATION: Comparing two protein databases is a fundamental task in biosequence annotation. Given two databases, one must find all pairs of proteins that align with high score under a biologically meaningful substitution score matrix, such as a BLOSUM matrix (Henikoff and Henikoff, 1992). Distance-based approaches to this problem map each peptide in the database to a point in a metric space, such that peptides aligning with higher scores are mapped to closer points. Many techniques exist to discover close pairs of points in a metric space efficiently, but the challenge in applying this work to proteomic comparison is to find a distance mapping that accurately encodes all the distinctions among residue pairs made by a proteomic score matrix. Buhler (2002) proposed one such mapping but found that it led to a relatively inefficient algorithm for protein-protein comparison. RESULTS: This work proposes a new distance mapping for peptides under the BLOSUM matrices that permits more efficient similarity search. We first propose a new distance function on peptides derived from a given score matrix. We then show how to map peptides to bit vectors such that the distance between any two peptides is closely approximated by the Hamming distance (i.e. number of mismatches) between their corresponding bit vectors. We combine these two results with the LSH-ALL-PAIRS-SIM algorithm of Buhler (2002) to produce an improved distance-based algorithm for proteomic comparison. An initial implementation of the improved algorithm exhibits sensitivity within 5% of that of the original LSH-ALL-PAIRS-SIM, while running up to eight times faster.     

In vivo anti-inflammatory effects of the M20 IL-1 Inhibitor: II. Effects on serum reactants

We have previously described an IL-1 Inhibitor derived from the M20 myelomoncytic cell line. This line also secretes several molecules of IL-1. We have shown that this factor is specific to IL-1in vitro, as well asin vivo. In vitro IL-1 induced proliferative responses of mouse thymocytes, human T cells and fibroblasts and IL-1 stimulated PGE₂ secretion from fibroblasts, were all inhibited by the M20 IL-1 Inhibitor.In vivo, the IL-1 Inhibitor reduced parameters of acute inflammation such as fever, leukocytosis and local inflammation. This study describes additional effects of the M20 IL-1 Inhibitor on inflammatory serum reactants. Levels of corticosterone and fibrinogen were increased by injection of IL-1, and decreased by the IL-1 Inhibitor. IL-1 reduced zinc and iron plasma levels and elevated copper plasma levels. The M20 IL-1 Inhibitor reversed these changes in a dose dependent manner. Similar effects produced by IL-6 and TNF were unaffected by the M20 IL-1 Inhibitor. Our results indicate that the M20 IL-1 Inhibitor acts specifically on IL-1 induced responsesin vivo. Therefore we conclude that this IL-1 Inhibitor has a great potential as an anti-inflammatory agent.Abbreviations IL-1 Interleukin 1 - IL-6 Interleukin 6 - IL-1ra Interleukin 1 receptor antagonist - TNF tumor necrosis factor