MetaMQAP: A meta-server for the quality assessment of protein models

Background  

Computational models of protein structure are usually inaccurate and exhibit significant deviations from the true structure. The utility of models depends on the degree of these deviations. A number of predictive methods have been developed to discriminate between the globally incorrect and approximately correct models. However, only a few methods predict correctness of different parts of computational models. Several Model Quality Assessment Programs (MQAPs) have been developed to detect local inaccuracies in unrefined crystallographic models, but it is not known if they are useful for computational models, which usually exhibit different and much more severe errors.     

Probe-level linear model fitting and mixture modeling results in high accuracy detection of differential gene expression

Background  

The identification of differentially expressed genes (DEGs) from Affymetrix GeneChips arrays is currently done by first computing expression levels from the low-level probe intensities, then deriving significance by comparing these expression levels between conditions. The proposed PL-LM (Probe-Level Linear Model) method implements a linear model applied on the probe-level data to directly estimate the treatment effect. A finite mixture of Gaussian components is then used to identify DEGs using the coefficients estimated by the linear model. This approach can readily be applied to experimental design with or without replication.     

Extended charge banking model of dual path shocks for implantable cardioverter defibrillators

Background  

Single path defibrillation shock methods have been improved through the use of the Charge Banking Model of defibrillation, which predicts the response of the heart to shocks as a simple resistor-capacitor (RC) circuit. While dual path defibrillation configurations have significantly reduced defibrillation thresholds, improvements to dual path defibrillation techniques have been limited to experimental observations without a practical model to aid in improving dual path defibrillation techniques.     

Prediction of protein motions from amino acid sequence and its application to protein-protein interaction

Background  

Structural flexibility is an important characteristic of proteins because it is often associated with their function. The movement of a polypeptide segment in a protein can be broken down into two types of motions: internal and external ones. The former is deformation of the segment itself, but the latter involves only rotational and translational motions as a rigid body. Normal Model Analysis (NMA) can derive these two motions, but its application remains limited because it necessitates the gathering of complete structural information.     

Improving the quality of protein structure models by selecting from alignment alternatives

Background  

In the area of protein structure prediction, recently a lot of effort has gone into the development of Model Quality Assessment Programs (MQAPs). MQAPs distinguish high quality protein structure models from inferior models. Here, we propose a new method to use an MQAP to improve the quality of models. With a given target sequence and template structure, we construct a number of different alignments and corresponding models for the sequence. The quality of these models is scored with an MQAP and used to choose the most promising model. An SVM-based selection scheme is suggested for combining MQAP partial potentials, in order to optimize for improved model selection.     

A response to Yu et al. "A forward-backward fragment assembling algorithm for the identification of genomic amplification and deletion breakpoints using high-density single nucleotide polymorphism (SNP) array", BMC Bioinformatics 2007, 8: 145

Background  

Yu et al. (BMC Bioinformatics 2007,8: 145+) have recently compared the performance of several methods for the detection of genomic amplification and deletion breakpoints using data from high-density single nucleotide polymorphism arrays. One of the methods compared is our non-homogenous Hidden Markov Model approach. Our approach uses Markov Chain Monte Carlo for inference, but Yu et al. ran the sampler for a severely insufficient number of iterations for a Markov Chain Monte Carlo-based method. Moreover, they did not use the appropriate reference level for the non-altered state.     

Hepatic glucokinase promoter polymorphism is associated with hepatic insulin resistance in Asian Indians.

Background  

The role of glucokinase (GCK) in the pathogenesis of maturity-onset diabetes of the young is well established. However, its role in the common form of type 2 diabetes is far from convincing. We investigated the role of the G-to-A polymorphism in the hepatic GCK promoter on insulin sensitivity and beta cell function in 63 normotensive Asian Indians with normal glucose tolerance. As proposed by Matsuda and DeFronzo, hepatic insulin sensitivity (ISI_H) and total body insulin sensitivity (ISI_M) were estimated from the oral glucose tolerance test. Beta cell function was estimated using %B from the Homeostasis Model Assessment and insulingenic index (dI/dG).     

The A54T polymorphism at the intestinal fatty acid binding protein 2 is associated with insulin resistance in glucose tolerant Caucasians

Background  

An A54T polymorphism at the fatty acid binding protein 2 (FABP2) locus was found to be associated with insulin resistance in non-diabetic Pima Indians. To see whether this association is present in other populations, we performed a cross sectional study to examine the role of this polymorphism on insulin resistance in 55 healthy and normotensive Caucasian subjects with normal glucose tolerance. Insulin sensitivity (%S) and beta cell function (%B) were assessed using the Homeostasis Model Assessment (HOMA). Their genotypes were determined using a polymerase chain reaction-restriction fragment length polymorphism assay. The relationship between the genotypes and the phenotypes was examined.     

Sulfate but Not Thiosulfate Reduces Calculated and Measured Urinary Ionized Calcium and Supersaturation: Implications for the Treatment of Calcium Renal Stones

Background

Urinary sulfate (SO₄ ²⁻) and thiosulfate (S₂O₃ ²⁻) can potentially bind with calcium and decrease kidney stone risk. We modeled the effects of these species on the concentration of ionized calcium (iCa) and on supersaturation (SS) of calcium oxalate (CaOx) and calcium phosphate (CaP), and measured their in vitro effects on iCa and the upper limit of stability (ULM) of these salts.

Methods

Urine data from 4 different types of stone patients were obtained from the Mayo Nephrology Clinic (Model 1). A second data set was obtained from healthy controls and hypercalciuric stone formers in the literature who had been treated with sodium thiosulfate (STS) (Model 2). The Joint Expert Speciation System (JESS) was used to calculate iCa and SS. In Model 1, these parameters were calculated as a function of sulfate and thiosulfate concentrations. In Model 2, data from pre- and post STS urines were analyzed. ULM and iCa were determined in human urine as a function of sulfate and thiosulfate concentrations.

Results

Calculated iCa and SS values for all calcium salts decreased with increasing sulfate concentration. Thiosulfate had no effect on these parameters. In Model 2, calculated iCa and CaOx SS increased after STS treatment, but CaP SS decreased, perhaps due to a decrease in pH after STS treatment. In confirmatory in vitro experiments supplemental sulfate, but not thiosulfate, significantly increased the calcium needed to achieve the ULM of CaP and tended to increase the oxalate needed to reach the ULM of CaOx. Sulfate also significantly decreased iCa in human urine, while thiosulfate had no effect.

Conclusion

Increasing urinary sulfate could theoretically reduce CaOx and CaP stone risk. Although STS may reduce CaP stone risk by decreasing urinary pH, it might also paradoxically increase iCa and CaOx SS. As such, STS may not be a viable treatment option for stone disease.     

Longitudinal characterization of antimicrobial resistance genes in feces shed from cattle fed different subtherapeutic antibiotics

Background  

Environmental transmission of antimicrobial-resistant bacteria and resistance gene determinants originating from livestock is affected by their persistence in agricultural-related matrices. This study investigated the effects of administering subtherapeutic concentrations of antimicrobials to beef cattle on the abundance and persistence of resistance genes within the microbial community of fecal deposits. Cattle (three pens per treatment, 10 steers per pen) were administered chlortetracycline, chlortetracycline plus sulfamethazine, tylosin, or no antimicrobials (control). Model fecal deposits (n = 3) were prepared by mixing fresh feces from each pen into a single composite sample. Real-time PCR was used to measure concentrations of tet, sul and erm resistance genes in DNA extracted from composites over 175 days of environmental exposure in the field. The microbial communities were analyzed by quantification and denaturing gradient gel electrophoresis (DGGE) of PCR-amplified 16S-rRNA.     

Forward simulation of root’s ground penetrating radar signal: simulator development and validation

Background and aims

It remains unclear how the limiting factors (e.g., root size, root water content, spacing between roots, and soil water content) affect root investigation using ground penetrating radar (GPR). The objective of this study is to develop a theoretical forward simulation protocol of synthesizing root’s GPR signal and test the feasibility of our proposed simulation protocol in evaluating the impacts of limiting factors on GPR-based root detection and quantification.

Methods

The proposed forward simulation protocol was developed by integrating several existing numerical models, such as the Root Composition Model, the Root Dielectric Constant Model, the Root Electrical Conductivity Model, the Soil Dielectric Constant Model, the Soil Electrical Conductivity Model, and a newly-established model (Root Length-Biomass Model). Resolution and GPR index obtained from both field collected radargrams and corresponding simulations were compared to validate the accuracy of simulation.

Results

Simulated radargrams exhibit similar resolution with that of the in situ collected. The same trends of root radar signals against different levels of root size, root water content, interval between roots, root depth, and antenna frequency were observed on both in situ radargrams and simulated radargrams. Strong correlations (correlation coefficients ranging from 0.87 to 0.96) were found between GPR indices extracted from the simulated data and those from the field collected data.

Conclusions

Our proposed forward simulation is effective for assessing the impacts of limiting factors on root detection and quantification using GPR. This forward simulation protocol can be used to provide guidance for in situ GPR root investigation and can predict the accuracy of GPR-based root quantification under site-specific conditions.     

Iterative Bayesian Model Averaging: a method for the application of survival analysis to high-dimensional microarray data

Background  

Microarray technology is increasingly used to identify potential biomarkers for cancer prognostics and diagnostics. Previously, we have developed the iterative Bayesian Model Averaging (BMA) algorithm for use in classification. Here, we extend the iterative BMA algorithm for application to survival analysis on high-dimensional microarray data. The main goal in applying survival analysis to microarray data is to determine a highly predictive model of patients' time to event (such as death, relapse, or metastasis) using a small number of selected genes. Our multivariate procedure combines the effectiveness of multiple contending models by calculating the weighted average of their posterior probability distributions. Our results demonstrate that our iterative BMA algorithm for survival analysis achieves high prediction accuracy while consistently selecting a small and cost-effective number of predictor genes.     

Version control of pathway models using XML patches

Background  

Computational modelling has become an important tool in understanding biological systems such as signalling pathways. With an increase in size complexity of models comes a need for techniques to manage model versions and their relationship to one another. Model version control for pathway models shares some of the features of software version control but has a number of differences that warrant a specific solution.     

Telomere length determined by the fluorescence in situ hybridisation distinguishes malignant and benign cells in cytological specimens

Background

Telomeres are tandem repeats of TTAGGG at the end of eukaryotic chromosomes that play a key role in preventing chromosomal instability. The aim of the present study is to determine telomere length using fluorescence in situ hybridisation (FISH) on cytological specimens.

Methods

Aspiration samples (n = 41) were smeared on glass slides and used for FISH.

Results

Telomere signal intensity was significantly lower in positive cases (cases with malignancy, n = 25) as compared to negative cases (cases without malignancy, n = 16), and the same was observed for centromere intensity. The difference in DAPI intensity was not statistically significant. The ratio of telomere to centromere intensity did not show a significant difference between positive and negative cases. There was no statistical difference in the signal intensities of aspiration samples from ascites or pleural effusion (n = 23) and endoscopic ultrasound‐guided FNA samples from the pancreas (n = 18).

Conclusions

The present study revealed that telomere length can be used as an indicator to distinguish malignant and benign cells in cytological specimens. This novel approach may help improve diagnosis for cancer patients.     

Evaluation of the diagnostic performance of infrared imaging of the breast: a preliminary study

Background  

The study was conducted to investigate the diagnostic performance of infrared (IR) imaging of the breast using an interpretive model derived from a scoring system.     

Site-specific time heterogeneity of the substitution process and its impact on phylogenetic inference

Background  

Model violations constitute the major limitation in inferring accurate phylogenies. Characterizing properties of the data that are not being correctly handled by current models is therefore of prime importance. One of the properties of protein evolution is the variation of the relative rate of substitutions across sites and over time, the latter is the phenomenon called heterotachy. Its effect on phylogenetic inference has recently obtained considerable attention, which led to the development of new models of sequence evolution. However, thus far focus has been on the quantitative heterogeneity of the evolutionary process, thereby overlooking more qualitative variations.     

Past vegetation dynamics in the Yellowstone region highlight the vulnerability of mountain systems to climate change

Aim

Reconstruct the long‐term ecosystem dynamics of the region across an elevational gradient as they relate to climate and local controls. In particular, we (1) describe the dominant conifers' history; (2) assess changes in vegetation composition and distribution; and (3) note periods of abrupt change versus stability as means of better understanding vegetation responses to environmental variability.

Location

Greater Yellowstone Ecosystem (GYE; USA).

Time period

16.5 ka bp ‐present.

Major taxa studied

Juniperus, Picea, Abies, Pinus, Pseudotsuga.

Methods

The vegetation reconstruction was developed from 15 pollen records. Results were interpreted based on modern pollen–vegetation relationships estimated from a suite of regression‐based approaches.

Results

Calibrated pollen data suggest that late‐glacial vegetation, dominated by shrubs and Juniperus, lacks a modern counterpart in the area. Picea, Abies and Pinus expanded at 16 ka bp in association with postglacial warming and co‐occurred in mixed‐conifer parkland/forest after 12 ka bp . This association along with Pinus contorta forest, which was present after 9 ka bp , has persisted with little change at middle and high elevations to the present day. This stability contrasts with the dynamic history of plant communities at low elevations, where shifts between parkland, steppe and forest over the last 8,000 years were likely driven by variations in effective moisture and fire.

Main conclusions

The postglacial vegetation history of the GYE highlights the dynamic nature of mountain ecosystems and informs on their vulnerability to future climate change: (1) most of the conifers have been present in the area for >12,000 years and survived climate change by adjusting their elevational ranges; (2) some plant associations have exhibited stability over millennia as a result of nonclimatic controls; and (3) present‐day forest cover is elevationally more compressed than at any time in history, probably due to the legacy of the Medieval Climate Anomaly and the Little Ice Age.     

Effect of menstrual cycle phase and hormonal treatments on evaluation of tubal patency in baboons

Background

We evaluated whether menstrual cycle phase influences the assessment of tubal patency by hysterosalpingography (HSG) in baboons.

Methods

Retrospective analysis of baseline tubal patency studies and serum estradiol (E₂) and progesterone (P4) values obtained from female baboons used as models for development of non‐surgical permanent contraception in women. The main outcome measure was bilateral tubal patency (BTP) in relationship with estradiol level.

Results

Female baboons (n = 110) underwent a single (n = 81), two (n = 26), or three (n = 3) HSG examinations. In 33/142 (23%) HSG examinations, one or both tubes showed functional occlusion (FO). The median E₂ in studies with BTP (49 pg/mL) was significantly higher than in those studies with FO (32 pg/mL, P = .005). Among 18 animals with repeat examinations where serum E₂ changed from <60 to ≥ 60 pg/mL, 13 results changed from FO to BTP (P = .0001). No sets showed a change from BTP to FO with an increase in estradiol.

Conclusion

In baboons, functional occlusion of the fallopian tube is associated with low estradiol levels, supporting a role for estrogen‐mediated relaxation of the utero‐tubal junction.     

Studies of the role of steroid hormone in the regulation of oocyte maturation in cattle

Background  

The objective of this study was to investigate whether the steroid hormone(s) secreted from cumulus-oocyte complexes (COCs) is a prerequisite for bovine oocyte maturation and cumulus expansion using aminoglutethimide (AGT), a P450 cholesterol side-chain cleavage inhibitor.