Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Data Analytics”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,477 records · Page 82Linked to original sources
PubMed2002

Integrated acquisition of analytical and biopharmaceutical screening data for beta-adrenergic-drugs employing diversified macrocycle supported potentiometric detection in HPLC systems.

Potentiometric detection with poly(vinyl chloride) (PVC) based liquid membrane electrode coatings is presented for a series of eighteen beta-adrenoceptor binding drugs (five agonists and thirteen antagonists) in cation exchange-HPLC and RP-HPLC systems. Incorporation of lipophilic cation-exchanger tetrakis(p-chlorophenyl)borate (TCPB) alone or in combination with trioctylated alpha-cyclodextrin into the polymeric liquid membrane gives very sensitive responses for racemic forms of bufuralol, propranolol, carazolol, clenbuterol, mabuterol, cimaterol, bisoprolol, oxprenolol, alprenolol, tertatolol, and bevantolol, especially in the cation-exchange HPLC system applying acetonitrile -- 40 mM phosphoric acid (15: 85, v/v, pH* = 2.35) as the mobile phase. In both applied orthogonal HPLC modes we observed that use of TCPB containing electrodes (no addition of neutral macrocyclic ionophores) gives more than five fold improvement in limit of detection down to 10(-7) M for mabuterol, bufuralol, alprenolol and tertatolol in comparison with UV detection. These results suggest that potentiometric detection, especially in RP-HPLC employing hybrid polymer-silica packings, can be considered as the promising alternative in the high-throughput drug abuse or doping control procedures of investigated beta-adrenergic agonists and beta-adrenolytics in humans and animals. The quantitative structure - potentiometric response relationships were developed for a set of eighteen beta-adrenenergic drugs and a set of PVC based electrodes using TCPB alone or in admixture with trioctylated alpha-cyclodextrin, dibenzo-18-crown-6 or calix[6]arene hexaethylacetate ester. A multiple linear regression model based on computationally derived set of molecular descriptors was used to predict detection limits of beta-blocking agents and beta-adrenergic agonists from their molecular structure in the developed potentiometric detectors. Principal components analysis (PCA) of data considering determined potentiometric detection limits revealed that it can be used to establish a reliable pharmacological classification of compounds with beta-adrenoceptor activity, especially for the differentiation of cardioselective and non-cardioselective beta1-antagonists.

Adrenergic beta-Agonists↗
PubMed1983

Ion-pair partition chromatography of mefenamic acid with tetraalkylammonium cations: development of analytical method from extraction data.

The ion-pair partition properties of mefenamic acid with the methyl, ethyl, n-propyl, and n-butyl homologs of tetraalkylammonium cation were studied in relation to a model of an assay procedure for acidic drugs. Variables studied included identity and concentration of pairing ion and composition of extracting solvents. Resulting data were used to develop a partition chromatographic assay procedure. Standard recoveries averaged 99.01 +/- 0.82%. Assays of commercial capsules were reproducible.

Capsules↗
PubMed1983

Food composition tables--analytical problems in the collection of data.

The range of techniques available to analytical chemists is increasing steadily. Some of the recently introduced techniques are being applied to the analysis of foods in connection with the continual updating of food composition tables. These new procedures enable the analyst to provide results which give either, more information than was previously possible or, more analyses for a particular level of expenditure. The above developments and their associated problems are discussed along with some of the other problems found in the particular field of work.

Ascorbic Acid↗
PubMed2005

Anomalous nucleation far from equilibrium.

We present precision Monte Carlo data and analytic arguments for an asymmetric exclusion process, involving two species of particles driven in opposite directions on a 2xL lattice. To resolve a stark discrepancy between earlier simulation data and an analytic conjecture, we argue that the presence of a single macroscopic cluster is an intermediate stage of a complex nucleation process: in smaller systems, this cluster is destabilized while larger systems form multiple clusters. Both limits lead to exponential cluster size distributions, controlled by very different length scales.

Journal Article↗
PubMed2005

Analyzing multi-response data using forcing functions.

INTRODUCTION: Two analytic strategies can be taken to the analysis of multi-response data: a multivariate output model can be fit to all the response components simultaneously (SIM), or each response component can be fit separately to a univariate output model, conditioning in some way on the non-modeled components, the so-called forcing function approach (FFA). Focusing on a special case of multi-response model corresponding to a (pharmacokinetic) physiological f low model (PFM), the aims of this study are to (i) provide an algorithm for applying FFA to multi-response data from a PFM; (ii) examine the performance of FFA vs. SIM under optimal conditions for both, and in the presence of model misspecification; (iii) make recommendations regarding the use of FFA for multi-response data analysis. METHODS: The basic PFM we use (variants of the basic model are used for simulation) has four homogenous compartments among which drug distributes. All are sampled arterial blood (A), non-eliminating tissue (N), eliminating tissue (E), and venous blood (V), which is also the drug dosing site. Parameters are blood f low rates to E and N, volumes of distribution of A, E, N, and V, elimination rate constant from E, and observation error variances. Observations from a generic individual under various study designs and parameter values are simulated. Using data-analytic models (DAM) both the same as, and different than the data simulation model (DSM), SIM fits the PFM to all data simultaneously; FFA first fits each type of response (one per tissue) separately, approximating the tissue's input by linearly interpolating the observed concentrations from the donor tissue(s), estimates the identifiable parameter combinations for the response type, and then solves the simultaneous equations linking these across tissues, to obtain the primary model parameters of interest. This simulation and analysis steps are repeated to generate reliable performance statistics. Performances are compared with respect to parameter estimation error (when DAM and DSM are identical), and interpolated prediction error (when DAM and DSM are/are-not identical). The ability of SIM and FFA to identify the correct analytic model is also examined by comparing their failure rates in rejecting the wrong DAM. RESULTS: The parameter estimation errors with FFA are generally about two times greater than those with SIM when the DAM is identical to the DSM. The prediction errors of FFA are about ten times greater than those of SIM when the DAM is identical to the DSM, and are about three times greater when the two are different. However, SIM fails to identify the correct model twice as often as FFA. CONCLUSIONS: Despite its greater convenience for model building, and its clear advantages for model identification, FFA's final parameter estimates cannot be trusted when the multi-response system being modeled involves feedback. The size of the ratio of the two FFA residuals (obtained from the response-specific fits and from predictions made with the final FFA parameters) can, however, be used to indicate when FFA's final estimates may be trustworthy.

Algorithms↗
PubMed2005

Pre-analytical factors and measurement uncertainty.

Pre-analytical factors are an important source of variation or errors in clinical laboratory measurements. Based on the new accreditation standards, medical and laboratory professions now seek to develop tools to deal systematically with these diverse factors. Several obvious pre-analytical uncertainty components were estimated in pragmatic experiments and combined with data on analytical variation and literature knowledge on biological variation, to estimate the measurement uncertainty of most common chemical and haematological examinations in clinical laboratories. The main aim was to assess quality specifications for regional laboratory services. The expanded measurement uncertainties (level of confidence 95%) of serum cholesterol, albumin and potassium remained within 13-16%. The major uncertainty component for cholesterol was biological variation, whereas those for albumin and potassium were sample collection and pretreatment. The measurement uncertainties for serum free thyroxin, thyrotropin and C-reactive protein, 20%, 42% and 125% respectively, were largely due to their biological variation. The measurement uncertainties of basic erythrocyte parameters (erythrocyte count and mean corpuscular volume, blood haemoglobin concentration) were less than 10%. Larger measurement uncertainties were obtained for thrombocyte and leukocyte counts, 24 and 31%, respectively, and for the reticulocyte fraction, 41%.

Adult↗
PubMed1990

Quality goals for hormone testing.

Estimates of intra-individual biological variation in normal subjects have been made for 17 hormones commonly measured for diagnostic purposes and the results have been compared with state-of-the-art analytical imprecision data. The implications of using these results for setting goals for analytical performance are discussed.

Adult↗
PubMed2004

Phytoestrogens and prostate cancer risk.

BACKGROUND: Phytoestrogens are natural plant substances. The four main classes are isoflavones, flavonoids, coumestans, and lignans. Phytoestrogens have anti-carcinogenic potential. For evaluation of the effect of phytoestrogens on prostate cancer risk, we reviewed analytical epidemiological data. METHODS: Up to now, there are few studies that have assessed the direct relation between the individual dietary intake of soy products and other nutrients with phytoestrogens and the risk of prostate cancer. We decided to review analytical epidemiological studies providing data on (a) dietary soy intake or flavonoids intake, (b) urinary excretion of isoflavones or lignans, or (c) blood measurements of isoflavones or lignans. Soy is used as a marker for isoflavone intake. RESULTS: Overall, the results of these studies do not show protective effects. Only four of these studies are prospective, and none of them found statistically significant prostate cancer reductions. Two prospective studies measured flavonoid intake and one reported a preventive effect on prostate cancer for the assumption of myricetin. One study assessed enterolactone concentrations in three different countries and showed no reduction in prostate cancer occurrence. CONCLUSION: Few studies showed protective effect between phytoestrogen intake and prostate cancer risk.

Age Distribution↗
PubMed2000

Stoichiometry, kinetic and binding analysis of the interaction between epidermal growth factor (EGF) and the extracellular domain of the EGF receptor.

The kinetics, binding equilibria and stoichiometry of the interaction between epidermal growth factor and the soluble extracellular domain of the epidermal growth factor receptor (sEGFR), produced in CHO cells using a bioreactor, have been studied by three methods: analytical ultracentrifugation, biosensor analysis using surface plasmon resonance detection (BIAcore 2000) and fluorescence anisotropy. These studies were performed with an sEGFR preparation purified in the absence of detergent using a mild two step chromatographic procedure employing anion exchange and size exclusion HPLC. The fluorescence anisotropy and analytical ultracentrifugation data indicated a 1:1 molar binding ratio between EGF and the sEGFR. Analytical ultracentrifugation further indicated that the complex comprised 2EGF:2sEGFR, consistent with the model proposed recently by Lemmon et al. (1997). Global analysis of the BIAcore binding data showed that a simple Langmuirian interaction does not adequately describe the EGF:sEGFR interaction and that more complex interaction mechanisms are operative. Furthermore, analysis of solution binding data using either fluorescence anisotropy or the biosensor, to determine directly the concentration of free sEGFR in solution competition experiments, yielded Scatchard plots which were biphasic and Hill coefficients of less than unity. Taken together our data indicate that in solution there are two sEGFR populations; one which binds EGF with a KD of 2-20 nM and the other with a KD of 400-550 nM.

Amino Acid Sequence↗
PubMed2002

Analytical differentiation of the differential-absorption-lidar data distorted by noise.

A method of analytical differentiation is developed for processing differential absorption lidar (DIAL) data. The method is based on simple analytical transformation of the DIAL on and off signal ratio. The derivatives consequently are found for either individual data points or local zones of the measurement range. The method makes possible the separation of local zones of interest and the separate investigation of these. The smoothing level is established by the selected value of the exponent in a transformation formula rather than by the selection of the resolution range. The method does not require the calculation of local signal increments. This reduces significantly the high-frequency noise in the measured concentration. The method is general and can be used for different experimental data, including inelastic (Raman) lidar data. The processing technique is practical and does not require a determination of the solution for a large set of algebraic equations. It is based on the simple repetition of the same type of calculations with different constants. The method can easily be implemented for practical computations.

Journal Article↗
PubMed2003

Separation of individual-level and cluster-level covariate effects in regression analysis of correlated data.

The focus of this paper is regression analysis of clustered data. Although the presence of intracluster correlation (the tendency for items within a cluster to respond alike) is typically viewed as an obstacle to good inference, the complex structure of clustered data offers significant analytic advantages over independent data. One key advantage is the ability to separate effects at the individual (or item-specific) level and the group (or cluster-specific) level. We review different approaches for the separation of individual-level and cluster-level effects on response, their appropriate interpretation and give recommendations for model fitting based on the intent of the data analyst. Unlike many earlier papers on this topic, we place particular emphasis on the interpretation of the cluster-level covariate effect. The main ideas of the paper are highlighted in an analysis of the relationship between birth weight and IQ using sibling data from a large birth cohort study.

Birth Weight↗
PubMed2004

HIV patients in the HCUP database: a study of hospital utilization and costs.

This study examines the utilization of hospital care by HIV patients in all hospitals in eight states (California, Colorado, Florida, Kansas, New Jersey, New York, Pennsylvania, and South Carolina), and examines the cost of hospital care for HIV patients in six of these states (California, Colorado, Kansas, New Jersey, New York, and South Carolina). The eight states in the sample account for more than 52% of all persons living with AIDS in the United States; the six states account for 39%. The unit of observation in both studies is a hospital admission by a patient with HIV. Hospital data were obtained from the Healthcare Cost and Utilization Project (HCUP), State Inpatient Database (SID), which is maintained by the Agency for Healthcare Research and Quality (AHRQ). The HCUP contains hospital discharge data and is a federal/state/industry partnership to build a multistate health care data system. Using multivariate analytic techniques and data from 2000, results indicate that cost and length of a hospital stay vary significantly across states after accounting for a patient's gender, insurance type, race, age, and number of diagnoses, as well as the teaching status and ownership category of the hospital.

Adult↗