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Biomedical subjects

T E Hanson

Publications and source records attributed to T E Hanson.

12 recordsLinked to original sources
PubMed2005

Predicting the probability of abortion in dairy cows: a hierarchical Bayesian logistic-survival model using sequential pregnancy data.

Although abortion contributes substantially to poor reproductive health of dairy herds, little is known about the predictability of abortion based on age, previous abortion or gravidity (number of previous pregnancies). A poor understanding of effects of maternal factors on abortion risk exists, in part, because of methodological difficulties related to non-independence of multiple pregnancies of the same cow in analysis of fetal survival data. We prospectively examined sequential pregnancies to investigate relationships between fetal survival and putative dam risk factors for 2991 abortions from 24,706 pregnancies of 13,145 cows in nine California dairy herds. Relative risks and predicted probabilities of abortion (PPA) were estimated using a previously described hierarchical Bayesian logistic-survival model generalized to incorporate longitudinal data of multiple pregnancies from a single cow. The PPA increased with increasing dam age at conception, with increasing number of previous abortions, and if the previous pregnancy was aborted >60 days in gestation. The PPA decreased with increasing gravidity and with increasing number of days open. For cows that aborted, the median time to fetal death decreased slightly as gravidity increased. The study considers several methodological issues faced in epidemiologic investigations of fetal health, including multi-modal hazard functions, extensive censoring and non-independence of multiple pregnancies. The model improves our ability to predict bovine abortion and to characterize fetal survival, which have important applications to herd health management.

Abortion, Veterinary↗
PubMed2001

A ribulose-1,5-bisphosphate carboxylase/oxygenase (RubisCO)-like protein from Chlorobium tepidum that is involved with sulfur metabolism and the response to oxidative stress.

A gene encoding a product with substantial similarity to ribulose-1,5-bisphosphate carboxylase/oxygenase (RubisCO) was identified in the preliminary genome sequence of the green sulfur bacterium Chlorobium tepidum. A highly similar gene was subsequently isolated and sequenced from Chlorobium limicola f.sp. thiosulfatophilum strain Tassajara. Analysis of these amino acid sequences indicated that they lacked several conserved RubisCO active site residues. The Chlorobium RubisCO-like proteins are most closely related to deduced sequences in Bacillus subtilis and Archaeoglobus fulgidus, which also lack some typical RubisCO active site residues. When the C. tepidum gene encoding the RubisCO-like protein was disrupted, the resulting mutant strain displayed a pleiotropic phenotype with defects in photopigment content, photoautotrophic growth and carbon fixation rates, and sulfur metabolism. Most important, the mutant strain showed substantially enhanced accumulation of two oxidative stress proteins. These results indicated that the C. tepidum RubisCO-like protein might be involved in oxidative stress responses and/or sulfur metabolism. This protein might be an evolutional link to bona fide RubisCO and could serve as an important tool to analyze how the RubisCO active site developed.

Amino Acid Sequence↗
PubMed2001

Application of Bayesian inference to characterize risks associated with low doses of low-LET radiation.

Improved risk characterization for stochastic biological effects of low doses of low-LET radiation is important for protecting nuclear workers and the public from harm from radiation exposure. Here we present a Bayesian approach to characterize risks of stochastic effects from low doses of low-LET radiation. The stochastic effect considered is neoplastic transformation of cells because it relates closely to cancer induction. We have used a published model of neoplastic transformation called NEOTRANS1. It is based on two different classes of cellular sensitivity for asynchronous, exponentially growing populations (in vitro). One sensitivity class is the hypersensitive cell; the other is the resistant cell. NEOTRANS1 includes the effects of genomic damage accumulation, DNA repair during cell cycle arrest, and DNA misrepair (non-lethal repair errors). The model-associated differential equations are solved for conditions of in vitro irradiation at a fixed rate. Previously published solutions apply only to high dose rates and were incorrectly assumed to apply to only high-LET radiation. Solutions provided here apply to any fixed dose rate and to both high- and low-LET radiations. Markov chain Monte Carlo methods are used to carry out the Bayesian inference of the low-dose risk for neoplastic transformation of aneuploid C3H 10T1/2 cells for X-ray doses from 0 to 1000 mGy. We have assumed that for this low-dose range only the hypersensitive fraction of the cells are affected. Our results indicate that the initial slope of the risk vs dose relationship for neoplastic transformation is as follows: (1) directly proportional to the fraction, f1, of hypersensitive cells; (2) directly proportional to the radiosensitivity of the genomic target; and (3) inversely proportional to the rate at which hypersensitive cells with radiation-induced damage are committed to undergo correct repair of genomic damage. Further, our results indicate that very fast molecular events are associated with the commitment of cells to the correct repair pathway. Results also indicate a relatively large probability for misrepair that leads to genomic instability. Our results are consistent with the view that for very low doses, dose rate is not an important variable for characterizing low-LET radiation risks so long as age-related changes in sensitivity do not occur during irradiation.

Animals↗
PubMed2000

Log-linear and logistic modeling of dependence among diagnostic tests.

We developed log-linear and logistic-modeling approaches to investigate dependence among diagnostic tests. To illustrate the approaches, we used published data for swine toxoplasmosis, bovine paratuberculosis, and swine brucellosis. These diseases were selected because each animal's true disease status was known, at least five tests were used, and the serologic tests had been previously shown to have moderate-to-high pairwise dependence in test sensitivities (and sometimes in test specificities). Log-linear and logistic modeling yielded similar results for swine toxoplasmosis and swine brucellosis. However, logistic modeling could not be used to investigate test dependence for bovine paratuberculosis because of quasi-separation in the data attributable to two fecal-based tests having specificities of 100%. Findings from our modeling indicated that 3 (modified agglutination, enzyme-linked immunosorbent assay (ELISA), latex agglutination) of 5 serologic tests for toxoplasmosis and 2 (rivanol and particle concentration fluorescence immunoassay) of 6 serologic tests for brucellosis were adequate for diagnosis. For bovine paratuberculosis, both fecal-based tests (Herrold's egg-yolk culture and radiometric culture) and 1 (ELISA) of 3 serologic tests were necessary in serial and parallel testing schemes.

Animals↗
PubMed1996

Methanotrophic bacteria.

Methane-utilizing bacteria (methanotrophs) are a diverse group of gram-negative bacteria that are related to other members of the Proteobacteria. These bacteria are classified into three groups based on the pathways used for assimilation of formaldehyde, the major source of cell carbon, and other physiological and morphological features. The type I and type X methanotrophs are found within the gamma subdivision of the Proteobacteria and employ the ribulose monophosphate pathway for formaldehyde assimilation, whereas type II methanotrophs, which employ the serine pathway for formaldehyde assimilation, form a coherent cluster within the beta subdivision of the Proteobacteria. Methanotrophic bacteria are ubiquitous. The growth of type II bacteria appears to be favored in environments that contain relatively high levels of methane, low levels of dissolved oxygen, and limiting concentrations of combined nitrogen and/or copper. Type I methanotrophs appear to be dominant in environments in which methane is limiting and combined nitrogen and copper levels are relatively high. These bacteria serve as biofilters for the oxidation of methane produced in anaerobic environments, and when oxygen is present in soils, atmospheric methane is oxidized. Their activities in nature are greatly influenced by agricultural practices and other human activities. Recent evidence indicates that naturally occurring, uncultured methanotrophs represent new genera. Methanotrophs that are capable of oxidizing methane at atmospheric levels exhibit methane oxidation kinetics different from those of methanotrophs available in pure cultures. A limited number of methanotrophs have the genetic capacity to synthesize a soluble methane monooxygenase which catalyzes the rapid oxidation of environmental pollutants including trichloroethylene.

Base Sequence↗
PubMed1968

Metabolism of D-fructose in Aerobacter aerogenes: analysis of mutants lacking D-fructose 6-phosphate kinase and D-fructose 1,6-diphosphatase.

The relative significance of the pathways for the conversion of d-fructose to d-fructose 1,6-diphosphate via d-fructose 1-phosphate or d-fructose 6-phosphate in Aerobacter aerogenes PRL-R3 was assessed by observing growth patterns of mutants lacking either d-fructose 6-phosphate kinase or d-fructose 1,6-diphosphatase. The mutant lacking d-fructose 6-phosphate kinase grew well on d-fructose or glycerol but not on d-glucose, whereas the mutant lacking d-fructose 1,6-diphosphatase grew on d-glucose but not on d-fructose or glycerol. The data indicate that the pathway of d-fructose metabolism is primarily through d-fructose 1-phosphate rather than d-fructose 6-phosphate.

Enterobacter↗