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PubMed2005

Propagation of population PK and PD information using a Bayesian approach: dealing with non-exchangeability.

The aim of this work is to implement a conservative prior that safeguards against population non-exchangeability of prior and data likelihood, in the framework of population pharmacokinetic/pharmacodynamic analysis, incorporating multi-level hierarchical modelling. Three different exercises were performed: (i) we investigated the use of parametric priors in the multilevel hierarchical modelling framework; (ii) we assessed the average performance of the multilevel hierarchical model compared to the standard mixed effect model, considering also some interesting extreme cases and (iii) we implemented an application with a small Proof of Principle (PoP) study, which demonstrates the propagation of information across PD studies using multilevel modelling. Fitting with the 4-level model and informative parametric priors performed similar to a meta-analysis of the test datasets combined with the datasets that the priors came from, demonstrating that parametric priors can be used alternatively to meta-analysis. Further, the 4-level model gave posterior distributions which had larger uncertainty but at the same time were unbiased, compared to the 3-level model, and therefore implements a more conservative prior in a formal way, which is appropriate when the prior and the test populations are not exchangeable. For the application with the PoP study, the statistical power of detecting the difference in potency between two drugs, when inter-study variability was present, was greater when an extra level in the hierarchical model to account for it, was used. In conclusion, by applying the prior one hierarchical level above the level of the parameters of interest, we implemented a more conservative prior, compared to applying the prior directly on the parameters of interest. The approach is equivalent to Bayesian individualization, offers a safeguard against bias from the prior and also avoids the danger of the data being overwhelmed by a strong prior.

Bayes Theorem↗

PubMed2005

Propagation of population pharmacokinetic information using a Bayesian approach: comparison with meta-analysis.

We investigated the propagation of population pharmacokinetic information across clinical studies by applying Bayesian techniques. The aim was to summarize the population pharmacokinetic estimates of a study in appropriate statistical distributions in order to use them as Bayesian priors in consequent population pharmacokinetic analyses. Various data sets of simulated and real clinical data were fitted with WinBUGS, with and without informative priors. The posterior estimates of fittings with non-informative priors were used to build parametric informative priors and the whole procedure was carried on in a consecutive manner. The posterior distributions of the fittings with informative priors where compared to those of the meta-analysis fittings of the respective combinations of data sets. Good agreement was found, for the simulated and experimental datasets when the populations were exchangeable, with the posterior distribution from the fittings with the prior to be nearly identical to the ones estimated with meta-analysis. However, when populations were not exchangeble an alternative parametric form for the prior, the natural conjugate prior, had to be used in order to have consistent results. In conclusion, the results of a population pharmacokinetic analysis may be summarized in Bayesian prior distributions that can be used consecutively with other analyses. The procedure is an alternative to meta-analysis and gives comparable results. It has the advantage that it is faster than the meta-analysis, due to the large datasets used with the latter and can be performed when the data included in the prior are not actually available.

Administration, Oral↗

PubMed2007

Evaluation of uncertainty parameters estimated by different population PK software and methods.

The uncertainty associated with parameter estimations is essential for population model building, evaluation, and simulation. Summarized by the standard error (SE), its estimation is sometimes questionable. Herein, we evaluate SEs provided by different non linear mixed-effect estimation methods associated with their estimation performances. Methods based on maximum likelihood (FO and FOCE in NONMEM, nlme in Splus, and SAEM in MONOLIX) and Bayesian theory (WinBUGS) were evaluated on datasets obtained by simulations of a one-compartment PK model using 9 different designs. Bootstrap techniques were applied to FO, FOCE, and nlme. We compared SE estimations, parameter estimations, convergence, and computation time. Regarding SE estimations, methods provided concordant results for fixed effects. On random effects, SAEM and WinBUGS, tended respectively to under or over-estimate them. With sparse data, FO provided biased estimations of SE and discordant results between bootstrapped and original datasets. Regarding parameter estimations, FO showed a systematic bias on fixed and random effects. WinBUGS provided biased estimations, but only with sparse data. SAEM and WinBUGS converged systematically while FOCE failed in half of the cases. Applying bootstrap with FOCE yielded CPU times too large for routine application and bootstrap with nlme resulted in frequent crashes. In conclusion, FO provided bias on parameter estimations and on SE estimations of random effects. Methods like FOCE provided unbiased results but convergence was the biggest issue. Bootstrap did not improve SEs for FOCE methods, except when confidence interval of random effects is needed. WinBUGS gave consistent results but required long computation times. SAEM was in-between, showing few under-estimated SE but unbiased parameter estimations.

Bayes Theorem↗

PubMed2005

An investigation into the ability to define transmembrane protein spans using the biophysical properties of amino acid residues.

A key question associated with topology predictions for membrane proteins is whether there is sufficient variation in the biophysical properties of residues at the membrane interface to enable identification of TM spans in a robust and efficient manner using relatively simple methods of analysis. Here, a test for the homogeneity of multinomial populations is used to identify statistical differences between the residue compositions of windows within datasets of aligned non-homologous TM alpha-helices. Using this approach, the accuracy and robustness of the predicted boundaries for datasets of uncleaved signal (US) sequences and stop transfer sequences (ST) is tested. The validity of the 21 residue length, which is generally assumed for TM spans in membrane protein topology prediction is also investigated and it is suggested that ST sequences may be better represented by a length of 22 residues.

Amino Acid Sequence↗

PubMed2004

Comparative map and trait viewer (CMTV): an integrated bioinformatic tool to construct consensus maps and compare QTL and functional genomics data across genomes and experiments.

In the past few decades, a wealth of genomic data has been produced in a wide variety of species using a diverse array of functional and molecular marker approaches. In order to unlock the full potential of the information contained in these independent experiments, researchers need efficient and intuitive means to identify common genomic regions and genes involved in the expression of target phenotypic traits across diverse conditions. To address this need, we have developed a Comparative Map and Trait Viewer (CMTV) tool that can be used to construct dynamic aggregations of a variety of types of genomic datasets. By algorithmically determining correspondences between sets of objects on multiple genomic maps, the CMTV can display syntenic regions across taxa, combine maps from separate experiments into a consensus map, or project data from different maps into a common coordinate framework using dynamic coordinate translations between source and target maps. We present a case study that illustrates the utility of the tool for managing large and varied datasets by integrating data collected by CIMMYT in maize drought tolerance research with data from public sources. This example will focus on one of the visualization features for Quantitative Trait Locus (QTL) data, using likelihood ratio (LR) files produced by generic QTL analysis software and displaying the data in a unique visual manner across different combinations of traits, environments and crosses. Once a genomic region of interest has been identified, the CMTV can search and display additional QTLs meeting a particular threshold for that region, or other functional data such as sets of differentially expressed genes located in the region; it thus provides an easily used means for organizing and manipulating data sets that have been dynamically integrated under the focus of the researcher's specific hypothesis.

Adaptation, Physiological↗

PubMed2006

Assessment of differential item functioning for demographic comparisons in the MOS SF-36 health survey.

OBJECTIVE: To investigate whether items of the Medical Outcomes Study (MOS) 36-Item Short-Form Health Status Survey (SF-36) exhibited differential item functioning (DIF) with respect to age, education, race, and gender. METHODS: The data for this study come from two large national datasets, the MOS and the 1990 National Survey of Functional Health Status (NSFHS). We used logistic regression to identify items exhibiting DIF. RESULTS: We found DIF to be most problematic for age comparisons. Items flagged for age DIF were vigorous activities, bend/kneel/stoop, bathing or dressing, limited in kind of work, health in general, get sick easier than others, expect health to get worse, felt calm and peaceful, and all four vitality items. Items flagged for education DIF include vigorous activities, health in general, health is excellent, felt calm and peaceful, and been a happy person. Vigorous activities, walk more than a mile, health in general, and expect health to get worse were identified as DIF when comparing African-Americans with whites. No items were identified for gender DIF. CONCLUSIONS: We found several consistent patterns of DIF using two national datasets with different population characteristics. In the current study, the effect of DIF rarely transferred to the scale level. Further research is needed to corroborate these results and determine qualitatively why DIF may occur for these specific items.

Adolescent↗

PubMed2006

Phylogenetic relationships of Steinernema Travassos, 1927 (Nematoda: Cephalobina: Steinernematidae) based on nuclear, mitochondrial and morphological data.

Entomopathogenic nematodes of the genus Steinernema are lethal parasites of insects that are used as biological control agents of several lepidopteran, dipteran and coleopteran pests. Phylogenetic relationships among 25 Steinernema species were estimated using nucleotide sequences from three genes and 22 morphological characters. Parsimony analysis of 28S (LSU) sequences yielded a well-resolved phylogenetic hypothesis with reliable bootstrap support for 13 clades. Parsimony analysis of mitochondrial DNA sequences (12S rDNA and cox 1 genes) yielded phylogenetic trees with a lower consistency index than for LSU sequences, and with fewer reliably supported clades. Combined phylogenetic analysis of the 3-gene dataset by parsimony and Bayesian methods yielded well-resolved and highly similar trees. Bayesian posterior probabilities were high for most clades; bootstrap (parsimony) support was reliable for approximately half of the internal nodes. Parsimony analysis of the morphological dataset yielded a poorly resolved tree, whereas total evidence analysis (molecular plus morphological data) yielded a phylogenetic hypothesis consistent with, but less resolved than trees inferred from combined molecular data. Parsimony mapping of morphological characters on the 3-gene trees showed that most structural features of steinernematids are highly homoplastic. The distribution of nematode foraging strategies on these trees predicts that S. hermaphroditum, S. diaprepesi and S. longicaudum (US isolate) have cruise forager behaviours.

Amino Acid Sequence↗

PubMed2006

Classification of breast masses in mammograms using genetic programming and feature selection.

Mammography is a widely used screening tool and is the gold standard for the early detection of breast cancer. The classification of breast masses into the benign and malignant categories is an important problem in the area of computer-aided diagnosis of breast cancer. A small dataset of 57 breast mass images, each with 22 features computed, was used in this investigation; the same dataset has been previously used in other studies. The extracted features relate to edge-sharpness, shape, and texture. The novelty of this paper is the adaptation and application of the classification technique called genetic programming (GP), which possesses feature selection implicitly. To refine the pool of features available to the GP classifier, we used feature-selection methods, including the introduction of three statistical measures--Student's t test, Kolmogorov-Smirnov test, and Kullback-Leibler divergence. Both the training and test accuracies obtained were high: above 99.5% for training and typically above 98% for test experiments. A leave-one-out experiment showed 97.3% success in the classification of benign masses and 95.0% success in the classification of malignant tumors. A shape feature known as fractional concavity was found to be the most important among those tested, since it was automatically selected by the GP classifier in almost every experiment.

Algorithms↗

PubMed2025

Expression and prognosis of CXCL13 in uterine corpus endometrial carcinoma based on bioinformatics analysis.

OBJECTIVE: The biological significance of the chemokine ligand C-X-C motif chemokine ligand 13 (CXCL13) may play a significant role in the pathogenesis of uterine corpus endometrial carcinoma (UCEC). This study aims to identify and verify CXCL13 with predictive value for prognosis in UCEC. METHODS: CXCL13 mRNA expression differences were analyzed using R software in three independent datasets: one each from The Cancer Genome Atlas (TCGA) and two from the Gene Expression Omnibus (GEO), namely GSE17025 and GSE106191. The correlation between CXCL13 expression and prognosis was evaluated by Kaplan-Meier analysis. Univariate and multivariate Cox analyses were utilized to construct a prognostic nomogram. Tumor Immune Estimation Resource (TIMER) and the Tumor and Immune System Interaction Database (TISIDB) were employed to assess the relationship between CXCL13 and tumor immune infiltration. Coexpressed genes with CXCL13 were identified by the Spearman correlation analysis. A CXCL13 protein-protein interaction (PPI) network was constructed with the STRING website tool and hub genes were screened out. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) analyses were performed with the "clusterProfiler" R package. Gene set enrichment analysis (GSEA) was used to identify underlying biological mechanisms. A drug-gene interaction network was constructed in the Comparative Toxicogenomics Database (CTD). RESULTS: High CXCL13 mRNA expression were validated in UCEC in the above three independent datasets. High CXCL13 expression was associated with favorable prognosis in UCEC. A nomogram for predicting the 1-, 3-, and 5-year survival probability in UCEC was construct based on CXCL13 expression and other clinical parameters. The use of Spearman correlation indicated certain correlation between CXCL13 and immune cells and immune checkpoint (ICP) genes. Seven hub genes were upregulated in UCEC, namely CXCL9, IFNG, CXCL10, CXCL11, GBP5, CCL18, and GZMB. The expression and prognostic relevance of CXCL9, IFNG, GBP5, and GZMB were in accordance with CXCL13. The main biological processes enriched were cytokine-cytokine receptor interaction and chemokine signaling pathway. CONCLUSIONS: The above comprehensive analyses suggest that CXCL13 may serve as a potential prognostic biomarker for UCEC, specifically for early-stage UCEC.

CXCL13↗

PubMed2026

Multi-cohort integration and machine learning identify CPVL as a novel oncogenic driver in gastric cancer.

BACKGROUND: Gastric cancer (GC) remains a leading cause of cancer-related mortality worldwide, and the prognosis of advanced GC remains poor. Systematic identification of robust biomarkers through multi-cohort integration and computational prioritization may facilitate the discovery of novel therapeutic targets. AIM: To identify key genes associated with gastric cancer progression through integrative multi-omics analysis and to elucidate the biological functions and molecular mechanisms of the top-prioritized candidate gene. METHODS: Comprehensive bioinformatics analyses integrating The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Gene Expression Omnibus (GEO) datasets were performed using differential expression analysis, weighted gene co-expression network analysis (WGCNA), Cox regression, and eight machine-learning algorithms to systematically identify and prioritize GC-associated hub genes. Among the identified candidates, CPVL was selected for further validation based on its diagnostic and prognostic performance. CPVL expression and clinical relevance were validated by independent datasets and immunohistochemistry. Lentiviral constructs were used to overexpress or silence CPVL in GC cell lines. Functional assays were performed, including CCK-8, colony formation, EdU incorporation, and flow cytometry, to assess cell proliferation and cell-cycle distribution. Western blotting and JAK2 inhibitor (AZD1480) rescue experiments were performed to elucidate the underlying mechanisms, and a nude mouse xenograft model was used to evaluate tumorigenicity in vivo. RESULTS: Multi-cohort screening identified five hub genes (CPVL, AADAC, BCAT1, CPXM1, and FBN1). Among them, CPVL exhibited the highest diagnostic accuracy (AUC = 0.895) and the strongest correlation with poor overall survival, and was therefore selected for mechanistic investigation. CPVL expression was markedly upregulated in GC tissues and cell lines. Functional assays demonstrated that CPVL promotes GC cell proliferation and accelerates G1/S-phase transition. Mechanistically, CPVL activated the JAK2/STAT3 signaling pathway, upregulating Cyclin D1 and CDK4 while downregulating p27. Treatment with the JAK2 inhibitor AZD1480 partially reversed these effects. In vivo, CPVL knockdown significantly inhibited tumor growth. CONCLUSION: Through systematic multi-cohort integration and machine-learning prioritization, CPVL was identified as a novel oncogenic driver in gastric cancer. CPVL promotes tumor growth via activation of the JAK2/STAT3 pathway and regulation of the Cyclin D1/CDK4/p27 axis, highlighting its potential as a diagnostic biomarker and therapeutic target.

Biomarker↗

PubMed2026

ONT-only genome assembly of a Korean male individual using a semen sample.

BACKGROUND: Long-read sequencing has enabled the generation of high-quality human genome assemblies, but many previous assemblies were based on blood-derived DNA and often relied on limited data types from a single sequencing strategy. OBJECTIVE: This study aimed to generate high-quality phased genome assemblies of a Korean individual using multiple independent long-read datasets produced from a single sequencing platform and to evaluate their utility for chromosome-scale assembly and variant detection. METHODS: Genomic DNA was extracted from a semen sample of a Korean male. Long-read, ultra-long-read, and chromatin conformation capture sequencing data were generated using Oxford Nanopore Technologies. These datasets were integrated to construct phased genome assemblies, followed by correction of noticeable phasing errors and assessment of assembly continuity, chromosomal representation, telomeric repeat recovery, and variant detection performance. RESULTS: The final phased assemblies spanned approximately 2.9 Gb and represented 23 pairs of chromosomes with an NG50 of 150 Mb. Telomeric repeats were detected at 36 and 37 of the 48 chromosomal ends in the two assemblies, indicating high end-to-end completeness. In addition, we successfully identified structural variants, including small variants. These results demonstrate that combining multiple Oxford Nanopore data types can produce highly continuous and informative phased human genome assemblies. CONCLUSIONS: We generated high-quality phased genome assemblies of a Korean individual using Oxford Nanopore long-read sequencing data derived from semen DNA. This publicly available genome resource will support broader applications of long-read sequencing in human genomics and variant analysis.

Humans↗

PubMed2025

Quantitative trait loci for Globodera pallida resistance derived from wild potato species Solanum gourlayi.

Globodera pallida is a major pest that is responsible for huge losses in potato yields worldwide. Expanding the gene pool of cultivated potatoes with clones resistant to this pest is made possible by searching for resistance genes in wild Solanum species. The aim of this study was to identify quantitative trait loci (QTLs) for potato resistance to Globodera pallida derived from Solanum gourlayi. A resistant diploid potato clone, Sg 2/7 (Solanum gourlayi, accession CGN17592), was crossed with a susceptible potato hybrid clone, DW 94-4235, to generate an F1 mapping population. All clones were tested for nematode resistance using G. pallida, pathotypes Pa2 and Pa3, in 2 or 3 years (2017-2019), respectively. Diversity Array Technology (DArTseq) was used for genotyping and genetic map construction. QTLs for nematode resistance were identified on potato chromosomes II, IV, V, VI, VII, X, XI, and XII, explaining from 10.1 to 21.5% of phenotypic variance. The most significant QTL for resistance to G. pallida pathotype Pa2 was identified on chromosome XII, explaining 20.9% of the phenotypic variance in the dataset from 2017. The most significant QTL for resistance to the G. pallida Pa3 pathotype was identified on chromosome VI, with a CAPS marker Exp928 in its peak, explaining 21.5% of the phenotypic variance in the dataset from 2017. The novel QTLs for resistance to S. gourlayi may be useful for breeding resistant potato cultivars, further studies of candidate genes, and host responses of potato to G. pallida infection.

Quantitative Trait Loci↗

PubMed1996

Three-dimensional reconstruction of intracranial vessels from biplane projection views.

The three-dimensional (3D) reconstruction of intracerebral vessels from two-dimensional (2D) projection views is an important clinical problem that, so far, has eluded solution. This report describes a new approach that uses projection images to build arterial trees progressively from an underlying 3D network, using a new method to pair shadow images on widely separated projection views. As a test of our general methodology, we have reconstructed a middle cerebral arterial tree from two projection views of a magnetic resonance dataset and have tested the accuracy of reconstruction against the original 3D dataset. This report describes the general approach to 3D vascular reconstruction and the computer program used to perform the final reconstruction step. The results suggest that accurate, 3D reconstruction of intracranial vessels is indeed possible from as few as two projection views.

Cerebral Arteries↗

PubMed1995

The application of the WLF equation to predict lag time as a function of temperature for three psychrotrophic bacteria.

Many mathematical models for microbial growth rates or lag times have been proposed. Most of these models either predict well, but are empirical and offer no insight into mechanism or they reflect mechanism but are too complex or do not fit the data adequately. The Williams-Landel-Ferry (WLF) equation (used by polymer chemists) is empirical, but shows some relation to first principles, and hence may offer some insight into mechanism. This model also has only three parameters and therefore a fairly simple form. The WLF equation was fit to lag times derived from three datasets previously developed in our laboratory. The fits obtained with the WLF equation were as good as the best fits obtained with other models (e.g Arrhenius, Davey, response surface and square root). The WLF model was able to account for 98 to 99% of the variance in the three datasets, indicating a very good fit overall. The parameter estimates of the WLF model were not as highly correlated as those of some of the other models. Many of the models, including the WLF equation did not predict well at very long lag times. Weighted least squares non-linear regression improved the fit for these long lag times.

Listeria monocytogenes↗

PubMed1992

The selection of portal aperture using interactively displayed Beam's Eye Sections.

Portal apertures are often defined by wax-pencil lines drawn on simulator films. The simulator-film images suffer degradation due to X ray absorption and scatter in tissues proximal to and distal to the intended target volume. We describe a method for avoiding the degradation by using a 3-D dataset to produce high-contrast section images with a user-defined orientation. The calculation of these Beam's Eye Section (BES) images requires a set of medium-to high-resolution transverse section data (the 3-D dataset), as well as a medium- to high-performance computer workstation. These CT-like section images, providing more contrast and detail than a projection (that is, a simulator or Digitally Reconstructed Radiograph [DRR]) image, should allow for more accurate selection of portal apertures. The BES image plane is oriented perpendicular to the central axis of a user-selected beam. Once the user has created a beam, the system allows the user to step along that beam with a new BES image produced at each step. Contours manually drawn on these BES images are ultimately projected onto a DRR image. The outermost segments of these sometimes crisscrossing contours (the union of all projected areas) accurately defines the portal aperture needed to encompass the target at all levels.

Computer Simulation↗

PubMed1996

Collimator-related radiation dose for different cobalt machines and linear accelerators.

PURPOSE: In previous publications (12, 13) measurements are described of the dose outside the primary beam (the peripheral dose (PD)) for 60Co gamma radiation to 25 MV photons. Comparison with data published by other investigators for different treatment machines, showed good agreement. This can only be explained when the contribution to the PD of radiation leaking through and scattering from the collimator does not differ considerably between treatment machines from different manufactures, and it is the purpose of this article to investigate whether this assumption is valid. METHODS AND MATERIALS: A request was sent out to all radiotherapy departments in The Netherlands and one in Belgium to measure the dose outside the primary beam for as many machines as possible. The following geometry was given: field sizes of 10 x 10 cm2 and 20 x 20 cm2 at distances of 30 and 50 cm, for collimator angles 0 degrees and 90 degrees at the standard source surface distance. This, therefore, resulted in a dataset of eight measurements per photon energy. RESULTS: Data were collected for four cobalt machines and 37 linear accelerators, from seven different manufacturers. All together 56 datasets were collected for 12 different photon energies. Although the variation of the leakage radiation dose is small, there can be differences of about 50% in the collimator scatter dose between collimator angles of 0 degrees and 90 degrees, depending on the collimator design or on the design of the flattening filter. For dual energy machines with a large gap between the low and the high energy, the values for the high energy are higher by about 40%. Old cobalt machines show higher leakage radiation dose than modern ones. CONCLUSION: Although there is no large variation in leakage radiation dose between different makes of accelerators, some show higher collimator scatter dose than others. The magnitude of the leakage radiation dose is well within regulatory limits. As the PD not only consists of a contribution from collimator-related radiation, but also of patient scatter, the differences are negligible when estimating the peripheral dose for an individual patient.

Cobalt↗

PubMed1995

A quantitative structure-activity relationship for the eye irritation potential of neutral organic chemicals.

Quantitative structure-activity relationships (QSARs) have been derived relating eye irritation data of a set of neutral organic chemicals to log(octanol-water partition coefficient), the minor principal inertial axes (Ry and Rz) and dipole moment. Datasets were analysed using principal components analysis; plots of the first 2 principal components of the above parameters showed that the analysis was able to discriminate well between the irritant and non-irritant chemicals in the dataset. The derived QSAR could be useful for the prediction of the eye irritation potential of new or untested chemicals within this category.

Animal Testing Alternatives↗

PubMed1995

Tracking of cerebral vessels in MR angiography after highpass filtering.

Maximum intensity projection (MIP), the commonly used technique for calculating MR-angiograms from three-dimensional (3D) datasets, often fails to visualize small vessels due to superposition of background signal. An improved vascular depiction can be reached by application of a connectivity algorithm, but a very good delimitation of vessel signals from signals of stationary tissue is required for this technique. Results of intracranial vessel tracking could be improved by a 3D interpolation and a preceding highpass filtering of the 3D image dataset.

Cerebral Arteries↗