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PubMed2006

Parallelization of multicategory support vector machines (PMC-SVM) for classifying microarray data.

BACKGROUND: Multicategory Support Vector Machines (MC-SVM) are powerful classification systems with excellent performance in a variety of data classification problems. Since the process of generating models in traditional multicategory support vector machines for large datasets is very computationally intensive, there is a need to improve the performance using high performance computing techniques. RESULTS: In this paper, Parallel Multicategory Support Vector Machines (PMC-SVM) have been developed based on the sequential minimum optimization-type decomposition method for support vector machines (SMO-SVM). It was implemented in parallel using MPI and C++ libraries and executed on both shared memory supercomputer and Linux cluster for multicategory classification of microarray data. PMC-SVM has been analyzed and evaluated using four microarray datasets with multiple diagnostic categories, such as different cancer types and normal tissue types. CONCLUSION: The experiments show that the PMC-SVM can significantly improve the performance of classification of microarray data without loss of accuracy, compared with previous work.

Algorithms↗

PubMed2006

Gene expression patterns that predict sensitivity to epidermal growth factor receptor tyrosine kinase inhibitors in lung cancer cell lines and human lung tumors.

BACKGROUND: Increased focus surrounds identifying patients with advanced non-small cell lung cancer (NSCLC) who will benefit from treatment with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKI). EGFR mutation, gene copy number, coexpression of ErbB proteins and ligands, and epithelial to mesenchymal transition markers all correlate with EGFR TKI sensitivity, and while prediction of sensitivity using any one of the markers does identify responders, individual markers do not encompass all potential responders due to high levels of inter-patient and inter-tumor variability. We hypothesized that a multivariate predictor of EGFR TKI sensitivity based on gene expression data would offer a clinically useful method of accounting for the increased variability inherent in predicting response to EGFR TKI and for elucidation of mechanisms of aberrant EGFR signalling. Furthermore, we anticipated that this methodology would result in improved predictions compared to single parameters alone both in vitro and in vivo. RESULTS: Gene expression data derived from cell lines that demonstrate differential sensitivity to EGFR TKI, such as erlotinib, were used to generate models for a priori prediction of response. The gene expression signature of EGFR TKI sensitivity displays significant biological relevance in lung cancer biology in that pertinent signalling molecules and downstream effector molecules are present in the signature. Diagonal linear discriminant analysis using this gene signature was highly effective in classifying out-of-sample cancer cell lines by sensitivity to EGFR inhibition, and was more accurate than classifying by mutational status alone. Using the same predictor, we classified human lung adenocarcinomas and captured the majority of tumors with high levels of EGFR activation as well as those harbouring activating mutations in the kinase domain. We have demonstrated that predictive models of EGFR TKI sensitivity can classify both out-of-sample cell lines and lung adenocarcinomas. CONCLUSION: These data suggest that multivariate predictors of response to EGFR TKI have potential for clinical use and likely provide a robust and accurate predictor of EGFR TKI sensitivity that is not achieved with single biomarkers or clinical characteristics in non-small cell lung cancers.

Adenocarcinoma↗

PubMed2005

Individual patient data meta-analysis : Cervical stitch (cerclage) for preventing pregnancy loss in women.

BACKGROUND: Cervical cerclage is a surgical procedure involving suturing the cervix with a purse type stitch to keep it closed during pregnancy. This procedure has been used widely in the management of pregnancies considered at high risk of preterm delivery. Several observational studies into the efficacy of cervical cerclage have claimed high rates of successful pregnancy outcome in women with a poor obstetric history attributed to cervical incompetence. However, a recent aggregate data Cochrane review found no such conclusive evidence from seven included randomised studies. Current data suggests that cervical cerclage is likely to benefit women considered to be 'at very high risk' of a second trimester miscarriage due to a cervical factor, however identifying such women remains elusive and many women may be treated unnecessarily. Undertaking an individual patient data (IPD) meta-analysis of the studies will allow us to investigate whether treatment is more effective in particular subgroups. Such an analysis will also provide a more powerful analysis of the predictors of preterm delivery and pregnancy loss, including ultrasound measurement of cervical length, and will allow a more complete analysis of 'time to event' outcomes. METHODS/DESIGN: The analysis will include data from randomised trials comparing the intervention of elective cerclage versus no cerclage or bedrest to prevent miscarriage or pre-term labour. A specific list of data will be requested for each trial, including demographic and obstetric history data. The primary outcomes of interest will be neonatal mortality/morbidity. Attention will also be given to secondary outcomes such as time from randomisation to delivery, preterm delivery before 32 weeks and maternal morbidity. An intention to treat analysis will be performed, with attention paid to assessing clinical and statistical heterogeneity. Multilevel models with patients and trials as the two levels will be explored to investigate treatment effect on various outcomes. Patient-level covariates will be incorporated into the models in an attempt to account for statistical heterogeneity as well as to investigate interactions with treatment effect. DISCUSSION: Predictive models generated from our analysis should lead to more effective counselling of women at risk and a more cost effective use of cerclage.

Journal Article↗

PubMed2006

How golden is silence? Teaching undergraduates the power and limits of RNA interference.

It is hard and getting harder to strike a satisfying balance in teaching. Time dedicated to student-generated models or ideas is often sacrificed in an effort to "get through the syllabus." I describe a series of RNA interference (RNAi) experiments for undergraduate students that simultaneously explores fundamental concepts in gene regulation, develops cutting-edge laboratory skills, and embraces student-directed learning. Students design a small interfering RNA (siRNA) against luciferase, add it to cells expressing this gene, and then quantitatively assess the siRNA's effect on both intended and unintended targets, using a luciferase assay and a DNA microarray. Because both RNAi and microarray technologies are relatively new, with no clear consensus on their analysis or limitations, students are encouraged to explore different approaches to the design of their reagents and interpretations of their data. The ability to creatively formulate a hypothesis-driven experimental approach to a scientific question and to critically evaluate collected data is stressed. Equally important, this experiment emphasizes how modern scientific ideas emerge, are debated, tested, and decided.

Educational Measurement↗

PubMed2003

Of different minds: an accessible identity model of justice reasoning.

An accessible identity model (AIM) of justice reasoning is introduced to explain when people become concerned about justice and how they define what is fair or unfair once justice concerns are activated. This model has two core propositions: (a) People are most likely to think about justice and fairness when self-relevant values and goals are highly accessible or activated, and (b) how people define fairness depends on which aspect of the self (i.e., material, social, or personal and moral) dominates the working self-concept. A review of the literature indicates that this general model provides an integrative account for when and how people become concerned about both procedural and distributive justice, and provides a cogent explanation for known effects and results previously thought to be anomalies. Finally, the model generates novel hypotheses about how identity threat may lead to motivated perceptions of fairness or unfairness.

Adaptation, Psychological↗

PubMed2005

Lidocaine excites both pre- and postsynaptic neurons of reconstructed respiratory pattern generator in Lymnaea stagnalis.

Lidocaine causes both inhibition and excitation in the central nervous system, including the respiratory pattern. The excitation induced by an excessive dose of local anesthetic is thought to be the result of an initial blockade of an inhibitory pathway in the cerebral cortex. To clarify the effect of lidocaine on the pre- and postsynaptic neurons of an inhibitory synapse, a cultured soma-soma respiratory pattern generator model consisting of two neurons from the snail Lymnaea stagnalis were reconstructed in vitro. First we investigated the effects of lidocaine on single presynaptic (RPeD1) or postsynaptic (VD4) neurons. While RPeD1 and VD4 were simultaneously recorded, the number of action potentials, the membrane potential, and the wavelength of the action potential were compared before and after lidocaine (0.01, 0.1, and 1 mM) administration. Lidocaine increased the number of action potentials and the wavelength of a single action potential, and it depolarized the resting membrane potential in both RPeD1 and VD4 neurons in a dose-dependent manner. Furthermore, lidocaine decreased outward potassium currents. In soma-soma pairs, RPeD1 excitation and VD4 suppression occurred in 0.01 mM lidocaine, whereas both RPeD1 and VD4 neurons were excited by 0.1 and 1 mM lidocaine. In conclusion, lidocaine causes a reduction in synaptic transmission and general neuronal excitation in both presynaptic and postsynaptic neurons.

Action Potentials↗

PubMed2003

Use of the Internet to optimize self-management of type 1 diabetes: preliminary experience with DiasNet.

Six patients with type 1 diabetes participated in a pilot trial. Their median age was 36 years (range 29-61) and the median duration of diabetes was 10 years (range 3-29). They were asked to enter, from their home or work PC, blood glucose values, insulin doses and a food diary. From the data entered, a computer model generated a simulation of the blood glucose concentration for the data collection period. It could then suggest alternative insulin doses (or regimes), or meal sizes, to reduce the risk of hypo- and hyperglycaemia. During a six-month study, patients entered a median of five sets of data (range two to eight). Feedback from participants revealed that while the system was helpful, difficulties with data entry hindered its use. Information gained from this exercise is shaping further development of the system.

Adult↗

PubMed1995

Computer planning of stereotactic iodine-125 seed brachytherapy for recurrent malignant gliomas.

At St Thomas' Hospital, we have developed a computer program on a Titan graphics supercomputer to plan the stereotactic implantation of iodine-125 seeds for the palliative treatment of recurrent malignant gliomas. Use of the Gill-Thomas-Cosman relocatable frame allows planning and surgery to be carried out at different hospitals on different days. Stereotactic computed tomography (CT) and positron emission tomography (PET) scans are performed and the images transferred to the planning computer. The head, tumour and frame fiducials are outlined on the relevant images, and a three-dimensional model generated. Structures which could interfere with the surgery or radiotherapy, such as major vessels, shunt tubing etc., can also be outlined and included in the display. Catheter target and entry points are set using a three-dimensional cursor controlled by a set of dials attached to the computer. The program calculates and displays the radiation dose distribution within the target volume for various catheter and seed arrangements. The CT co-ordinates of the fiducial rods are used to convert catheter co-ordinates from CT space to frame space and to calculate the catheter insertion angles and depths. The surgically implanted catheters are after-loaded the next day and the seeds left in place for between 4 and 6 days, giving a nominal dose of 50 Gy to the edge of the target volume. 25 patients have been treated so far.

Brachytherapy↗

PubMed2003

Simulation of drug use and urine screening patterns.

Urine drug screens are used extensively in substance-abuse treatment, especially methadone maintenance treatment programs, as well as criminal-justice and clinical research settings. While positive urinalysis generally indicates drug use, no information is provided about the context or pattern of use. A computer generated model was created to examine the influence of drug use patterns and drug screen schedules upon urine test results. The results indicate that (1) when urine testing is performed at a rate of eight times per year, the probability of testing positive in a given month is little better than 50-50 even for daily use, (2) infrequent drug use is difficult to detect regardless of drug testing frequency, and (3) the benefits of more frequent drug testing are greatest with moderate drug use. The data presented provide a guide for clinicians to match drug screen schedules to frequency or pattern of suspected drug use.

Appointments and Schedules↗

PubMed2004

Polarization of transmission scattering simulated by using a multiple-facets model.

A Mueller matrix for scattering by a rough plane surface of a glass hemisphere was simulated by using a micro-facet model. The algorithms are formulated in vector representation in terms of the input and output directions. The single-facet scattering simulation used the results of the Kirchhoff integral for medium rough surfaces with exponential height distribution. Scatterings by two or more facets were also simulated. For a fixed angle between the incident and the detection directions, the transmission scattering and its polarization properties were symmetric when plotted against the off-specular incident angle. The single-facet model generated no depolarization or polarization change. When double-facet scattering was included, polarizations were changed appreciably while depolarization was still very small. Depolarization increased appreciably when scattering by higher orders was included. The simulated results that include all orders of scattering fit excellently to the measured scattering transmittance and its polarization and depolarization.

Journal Article↗

PubMed2004

Evaluation of visible and near-infrared spectroscopy as a tool for assessing fiber fineness during mechanical preparation of dew-retted flax.

Flax fiber must be mechanically prepared to improve fineness and homogeneity of the sliver before chemical processing and wet-spinning. The changes in fiber characteristics are monitored by an airflow method, which is labor intensive and requires 90 minutes to process one sample. This investigation was carried out to develop robust visible and near-infrared calibrations that can be used as a rapid tool for quality assessment of input fibers and changes in fineness at the doubling (blending), first, second, third, and fourth drawing frames, and at the roving stage. The partial least squares (PLS) and principal component regression (PCR) methods were employed to generate models from different segments of the spectra (400-1100, 1100-1700, 1100-2498, 1700-2498, and 400-2498 nm) and a calibration set consisting of 462 samples obtained from the six processing stages. The calibrations were successfully validated with an independent set of 97 samples, and standard errors of prediction of 2.32 and 2.62 dtex were achieved with the best PLS (400-2498 nm) and PCR (1100-2498 nm) models, respectively. An optimized PLS model of the visible-near-infrared (vis-NIR) spectra explained 97% of the variation (R(2) = 0.97) in the sample set with a standard error of calibration (SEC) of 2.45 dtex and a standard error of cross-validation (SECV) of 2.51 dtex R(2) = 0.96). The mean error of the reference airflow method was 1.56 dtex, which is more accurate than the NIR calibration. The improvement in fiber fineness of the validation set obtained from the six production lines was predicted with an error range of -6.47 to +7.19 dtex for input fibers, -1.44 to +5.77 dtex for blended fibers at the doubling, and -4.72 to +3.59 dtex at the drawing frame stages. This level of precision is adequate for wet-spinners to monitor fiber fineness of input fibers and during the preparation of fibers. The advantage of visNIR spectroscopy is the potential capability of the technique to assess fineness and other important quality characteristics of a fiber sample simultaneously in less than 30 minutes; the disadvantages are the expensive instrumentation and the expertise required for operating the instrument compared to the reference method. These factors need to be considered by the industry before installing an off-line NIR system for predicting quality parameters of input materials and changes in fiber characteristics during mechanical processing.

Flax↗

PubMed2006

Analysis of the effect of particle size on polymorphic quantitation by Raman spectroscopy.

Raman spectroscopy has been widely used to monitor various aspects of the crystallization process. Although it has long been known that particle size can influence Raman signal, relatively little research has been conducted in this area, in particular for mixtures of organic materials. The aim of this study was to investigate the effect of particle size on quantification of polymorphic mixtures. Several sets of calibration samples containing different particle size fractions were prepared and Raman spectra were collected with different probes. Calibration models were built using both univariate and multivariate analysis. It was found that, for a single component system, Raman intensity decreased with increasing particle size. For mixtures, calibration models generated from the same particle size distribution as the sample yielded relatively good predictions of the actual sample composition. However, if the particle sizes of the calibration and unknown samples were different, prediction errors resulted. For extreme differences in particle sizes, prediction errors of up to 20% were observed. Prediction errors could be minimized by changing the sampling optics employed.

Journal Article↗

PubMed1999

Recovery of cellulase by HPMC-salt precipitation: analysis by statistical experimental design.

Production of industrial enzymes including cellulases requires minimum cost with the downstream processing. The objective of this work was to analyze the precipitation of cellulases by ammonium sulfate in the presence of hydroxypropyl(methylcellulose) as a co-precipitant through the use of statistical experimental design. The model generated with the experimental results showed that high protein recovery can be achieved at high levels of temperature, aging times, and rate of salt-solution addition, and at a low mixing level. The results also allowed the observation that activity recovery was improved at high levels of temperature, rate of salt addition and mixing level, and a low level of aging time.

Journal Article↗

PubMed2005

Simulation and robotics studies of salamander locomotion: applying neurobiological principles to the control of locomotion in robots.

This article presents a project that aims at understanding the neural circuitry controlling salamander locomotion, and developing an amphibious salamander-like robot capable of replicating its bimodal locomotion, namely swimming and terrestrial walking. The controllers of the robot are central pattern generator models inspired by the salamander's locomotion control network. The goal of the project is twofold: (1) to use robots as tools for gaining a better understanding of locomotion control in vertebrates and (2) to develop new robot and control technologies for developing agile and adaptive outdoor robots. The article has four parts. We first describe the motivations behind the project. We then present neuromechanical simulation studies of locomotion control in salamanders. This is followed by a description of the current stage of the robotic developments. We conclude the article with a discussion on the usefulness of robots in neuroscience research with a special focus on locomotion control.

Animals↗

PubMed2004

Pharmacokinetic profile of intramuscular fulvestrant in advanced breast cancer.

OBJECTIVE: To characterise the pharmacokinetics of a long-acting formulation of fulvestrant following intramuscular administration of single and multiple doses. STUDY DESIGN: Pharmacokinetic investigations of single and multiple doses of fulvestrant were conducted within two global phase III efficacy studies that compared intramuscular fulvestrant with oral anastrozole in postmenopausal women with hormone-sensitive advanced breast cancer (study 0020, conducted in Europe, Australia and South Africa, and study 0021, conducted in North America). METHODS: Patients received once-monthly intramuscular injections of fulvestrant 250 mg (1 x 5 mL for < or =21 months in study 0020; 2 x 2.5 mL for < or =30 months in study 0021). Serial blood samples were collected for the first 28 days after the initial dose and immediately prior to all subsequent monthly doses. Plasma fulvestrant concentrations were determined by high-performance liquid chromatography-tandem mass spectrometry. PATIENTS: Twenty-six (study 0020) and 193 (study 0021) postmenopausal women, comprising the pharmacokinetic subgroups of the phase III efficacy trials, were studied. Patients had shown disease progression or recurrence following previous hormonal therapy for advanced disease or had relapsed after adjuvant endocrine therapy with a nonsteroidal antiestrogen. OUTCOME MEASURES AND RESULTS: For single-dose fulvestrant 250 mg, area under the concentration-time curve from time zero to 28 days (AUC(28)), maximum observed plasma concentration (C(max)), minimum observed plasma concentration at 28 days (C(min)) and time to maximum plasma concentration (t(max)) were determined. For multiple-dose fulvestrant 250 mg once monthly, steady-state trough concentrations (C(trough)) were determined. Plasma fulvestrant concentrations reached a peak at a median of 7 days (range 2-8 days) postdose, and declined biexponentially with a slower phase commencing approximately 2-3 weeks postdose. Intersubject variability in C(max) and AUC(28) was approximately 6-fold and 4-fold, respectively. Mean parameters for single-dose fulvestrant were: AUC(28), 148 microg. day/L; C(max), 8.2 microg/L; C(min), 2.6 microg/L; t(max), 7.0 days. Geometric mean C(trough) increased from 2.57 to 6.15 microg/L (study 0020) and from 2.38 to 6.52 microg/L (study 0021) over the first 6 months, reaching steady-state concentrations of approximately 6-7 microg/L (study 0020) or 9 microg/L (study 0021). Preliminary pharmacokinetic analysis, using a naive pooled data approach, suggests that observed single- and multiple-dose plasma profiles can be adequately described with a two-compartment kinetic model. Model-generated steady-state AUC(28) values were approximately 300 microg. day/L. CONCLUSIONS: The intramuscular formulation of fulvestrant displays predictable kinetics and approximately 2-fold accumulation on administration once monthly. At the proposed therapeutic dosage (250 mg once monthly), plasma fulvestrant concentrations are maintained within a narrow range throughout the administration interval, thus ensuring stable systemic drug exposure during long-term treatment.

Adult↗

PubMed2004

Artificial neural networks for the prediction of response to interferon plus ribavirin treatment in patients with chronic hepatitis C.

Combined therapy using Interferon alfa (IFN) and Ribavirin (RIB) represents the standard treatment in patients with chronic hepatitis C. However, the percentage of responders to this regimen is still low, while its cost and side effects are elevated. Therefore, the possibility to predict patient's response to the above treatment is of paramount importance. The progress in the field of informatics and its large use for decision making has led to the development of novel techniques related to the so-called Artificial Intelligence, even including artificial neural networks (ANNs). In chronic viral hepatitis data are lacking. By means of an artificial neural network (ANN), 300 patients treated with IFN plus RIB were retrospectively analyzed with the aim to predict the response to the treatment. One hundred patients resulted responders and 200 non-responders at the end of treatment and during the follow up. For evaluating the prediction of treatment response, six ANNs with 16 neurons of input, an hidden layer with 7 neurons and an output layer with one neuron were utilized. The ANN model generated a positive predictive value (i.e. posterior probability of treatment response) ranging from 57% to 75% while the negative one (i.e. posterior probability of no response to treatment) was comprised between 52% and 71%. The highest level of diagnostic accuracy was 70%. In conclusion, ANNs appear to be a promising tool in the prediction of treatment response in patients with chronic hepatitis C. However, additional prospective studies are necessary to ultimately validate this predictive method.

Adolescent↗

PubMed2006

Patterns of early adherence to the antidepressant citalopram among older primary care patients: the prospect study.

OBJECTIVE: Our purpose was to determine the personal characteristics associated with different patterns of adherence to the antidepressant citalopram in a primary care trial of depression management. METHOD: The study sample consisted of 228 adults aged 60 years and older recruited from primary care settings and who participated in a depression intervention. The intervention consisted of services of trained care managers, who offered recommendations to physicians following a clinical algorithm and helped patients with treatment adherence. Adherence to the antidepressant citalopram was measured using pill counts. We employed the latent class model to classify patients according to the pattern of adherence to citalopram over time. We examined the association of sociodemographic characteristics, depression status, cognitive status, and medical comorbidity with the resulting classes of adherence. RESULTS: The latent class model generated three classes of adherence: known to be adherent, unknown adherence, and known to be nonadherent. Participants who were white were more likely to be in the known to be adherent class than in the known to be nonadherent class (odds ratio (OR) = 10.38, 95% confidence interval (CI) [3.47, 31.12]). Married participants were less likely to be in the unknown adherence class than the known to be nonadherent class (OR = 0.28, 95% CI [0.09, 0.85]). No associations between age, gender, education level, depression status, cognitive status, or medical comorbidity and classes of adherence were found. CONCLUSIONS: We found stronger relationships between ethnicity and marital status with patterns of adherence to citalopram than we did other personal characteristics. Identification of a subgroup of patients at particularly high risk of nonadherence is important for the development of adherence interventions.

Aged↗

PubMed2003

Making tissue engineering scaffolds work. Review: the application of solid freeform fabrication technology to the production of tissue engineering scaffolds.

Tissue engineering is a new and exciting technique which has the potential to create tissues and organs de novo. It involves the in vitro seeding and attachment of human cells onto a scaffold. These cells then proliferate, migrate and differentiate into the specific tissue while secreting the extracellular matrix components required to create the tissue. It is evident, therefore, that the choice of scaffold is crucial to enable the cells to behave in the required manner to produce tissues and organs of the desired shape and size. Current scaffolds, made by conventional scaffold fabrication techniques, are generally foams of synthetic polymers. The cells do not necessarily recognise such surfaces, and most importantly cells cannot migrate more than 500 microm from the surface. The lack of oxygen and nutrient supply governs this depth. Solid freeform fabrication (SFF) uses layer-manufacturing strategies to create physical objects directly from computer-generated models. It can improve current scaffold design by controlling scaffold parameters such as pore size, porosity and pore distribution, as well as incorporating an artificial vascular system, thereby increasing the mass transport of oxygen and nutrients into the interior of the scaffold and supporting cellular growth in that region. Several SFF systems have produced tissue engineering scaffolds with this concept in mind which will be the main focus of this review. We are developing scaffolds from collagen and with an internal vascular architecture using SFF. Collagen has major advantages as it provides a favourable surface for cellular attachment. The vascular system allows for the supply of nutrients and oxygen throughout the scaffold. The future of tissue engineering scaffolds is intertwined with SFF technologies.

Biocompatible Materials↗