A calculator package for pharmacokinetic application

A calculator program package is given for the computation of the parameters of two different pharmacokinetic models: the 'one compartment open model' with first order absorption, and the 'two compartment open model' with rapid intravenous injection, using the peeling method. If parameters are known, simulation of these systems can be done for single and repetitive doses. The package includes an area under curve (AUC) program for the evaluation of clearance. The algorithms were applied for TI 58,59 and HP 97 calculators and they can be widely used in clinical practice.     

A calculator program to determine k and V from measured serum drug concentrations by a two point curve fitting method

A calculator program is presented which determines k and V from two drug levels or k from an assumed V and one drug level during maintenance dosing with any of four dosing schedules: intermittent, fixed interval; intermittent, two fixed intervals; intermittent, non-uniform dose, non-uniform interval; continuous intravenous infusion/sustained release. A loading dose and or one additional level taken before maintenance dosing begins can be taken into account for additional flexibility. Steady state concentrations are projected when dosage regimen and pharmacokinetic parameters are known.     

A technique for joint center analysis using a stored program calculator

For a long time in the study of joint kinematics, the instant center of rotation in plane motion was obtained through graphic drawings. Since then the study of joint kinematics has become three-dimensional involving the use of computers. For this paper a stored-program calculator has been used as it is a precise instrument and several films can be used even if their positions are very close to one another.

A movement is never perfectly plane, it was important to define a coefficient (in percentage) to qualify the more or less plane character of a movement.

We believe that an analytical location is a better way than using graphic drawings of I.C.R.:

1. (1) to smooth the raw coordinates;

2. (2) to calculate the plane motion coefficient in order to eliminate an X-Ray picture of a whole series of pictures for lack of plane character;

3. (3) to define in the results an error rectangle whose dimensions are linked to errors in the observation and then to pick out among the points of a body those with the smallest risk for error.

To probe this method the two radio-ulnaris joints have been studied. At present studies are being carried on to compare the I.C.R.'s behaviour of the lumbar spine during a motion of lateral inflexion both in the case of normal people and people with scoliosis.     

Mining genetic epidemiology data with Bayesian networks I: Bayesian networks and example application (plasma apoE levels)

MOTIVATION: The wealth of single nucleotide polymorphism (SNP) data within candidate genes and anticipated across the genome poses enormous analytical problems for studies of genotype-to-phenotype relationships, and modern data mining methods may be particularly well suited to meet the swelling challenges. In this paper, we introduce the method of Belief (Bayesian) networks to the domain of genotype-to-phenotype analyses and provide an example application. RESULTS: A Belief network is a graphical model of a probabilistic nature that represents a joint multivariate probability distribution and reflects conditional independences between variables. Given the data, optimal network topology can be estimated with the assistance of heuristic search algorithms and scoring criteria. Statistical significance of edge strengths can be evaluated using Bayesian methods and bootstrapping. As an example application, the method of Belief networks was applied to 20 SNPs in the apolipoprotein (apo) E gene and plasma apoE levels in a sample of 702 individuals from Jackson, MS. Plasma apoE level was the primary target variable. These analyses indicate that the edge between SNP 4075, coding for the well-known epsilon2 allele, and plasma apoE level was strong. Belief networks can effectively describe complex uncertain processes and can both learn from data and incorporate prior knowledge. AVAILABILITY: Various alternative and supplemental networks (not given in the text) as well as source code extensions, are available from the authors. SUPPLEMENTARY INFORMATION: http://bioinformatics.oxfordjournals.org.     

A program for predicting significant RNA secondary structures

We describe a program for the analysis of RNA secondary structure.There are two new features in this program. (i) To get vectorspeeds on a vector pipeline machine (such as Cray X-MP/24) wehave vectorized the secondary structure dynamic algorithm. (ii)The statistical significance of a locally ‘optimal’secondary structure is assessed by a Monte Carlo method. Theresults can be depicted graphically including profiles of thestability of local secondary structures and the distributionof the potentially significant secondary structures in the RNAmolecules. Interesting regions where both the potentially significantsecondary structures and ‘open’ structures (single-strandedcoils) occur can be identified by the plots mentioned above.Furthermore, the speed of the vectorized code allows repeatedMonte Carlo simulations with different overlapping window sizes.Thus, the optimal size of the significant secondary structureoccurring in the interesting region can be assessed by repeatingthe Monte Carlo simulation. The power of the program is demonstratedin the analysis of local secondary structures of human T-celllymphotrophic virus type III (HIV). Received on August 17, 1987; accepted on January 5, 1988     

High-throughput capillary electrophoresis method for plasma cysteinylglycine measurement: evidences for a clinical application

Summary. Increased levels in plasma homocysteine and cysteine, and more recently, decreased levels in cysteinylglycine have been indicated as a risk factor for vascular diseases. Most assays focused their attention only on homocysteine determination and when also other thiols were measured, analytical times drastically increased. By modifying our previous method for thiols detection, we set up a rapid capillary electrophoresis method for the selective quantification of plasma cysteinylglycine, cutting the analysis time of about 50%. Samples were treated with tri-n-butylphosphine as reducing agent, proteins were precipitated with trichloroacetic acid and released thiols were successively derivatized by the selective thiol laser-induced fluorescence-labeling agent 5-iodoacetamidofluorescein and separated by capillary electrophoresis. A baseline separation between peaks was obtained in about 2 min using 3 mmol/L sodium phosphate/2.5 mmol/L boric acid as electrolyte solution with 75 mmol/L N-methyl-D-glucamine at pH 11.25 in a 47 cm long capillary with a cartridge temperature of 45 °C. The method application was checked by measuring plasma Cys-Gly levels in a group of patients affected by retinal vein occlusion (RVO), an important cause of visual loss in the elderly. The low levels of Cys-Gly found in the RVO patients suggest that these small thiols may have importance in the disease development. Authors’ addresses: Dr. Angelo Zinellu, Dr. Ciriaco Carru, Department Biomedical Sciences, Chair of Clinical Biochemistry, University of Sassari, Viale San Pietro 43/B, 07100 Sassari, Italy     

A calculator program for least-squares parameter estimation according to the one-compartment kinetic model with zero-order input

A calculator program that performs a nonlinear least-squares fit to data conforming to the one-compartment model with zero-order input is described. The program, which is designed for the Hewlett-Packard HP-41 CV calculator, is based on the Gauss-Newton iterative algorithm as modified by Hartley. A subroutine for calculation of initial parameter estimates is incorporated into the program. Plasma concentration data relative to a single oral dose of a sustained-release theophylline formulation are used to demonstrate the practical application of the program.     

Mining genetic epidemiology data with Bayesian networks application to APOE gene variation and plasma lipid levels.

There is a critical need for data-mining methods that can identify SNPs that predict among individual variation in a phenotype of interest and reverse-engineer the biological network of relationships between SNPs, phenotypes, and other factors. This problem is both challenging and important in light of the large number of SNPs in many genes of interest and across the human genome. A potentially fruitful form of exploratory data analysis is the Bayesian or Belief network. A Bayesian or Belief network provides an analytic approach for identifying robust predictors of among-individual variation in a disease endpoints or risk factor levels. We have applied Belief networks to SNP variation in the human APOE gene and plasma apolipoprotein E levels from two samples: 702 African-Americans from Jackson, MS, and 854 non-Hispanic whites from Rochester, MN. Twenty variable sites in the APOE gene were genotyped in both samples. In Jackson, MS, SNPs 4036 and 4075 were identified to influence plasma apoE levels. In Rochester, MN, SNPs 3937 and 4075 were identified to influence plasma apoE levels. All three SNPs had been previously implicated in affecting measures of lipid and lipoprotein metabolism. Like all data-mining methods, Belief networks are meant to complement traditional hypothesis-driven methods of data analysis. These results document the utility of a Belief network approach for mining large scale genotype-phenotype association data.     

多水平贝叶斯模型预测森林土壤全氮

多水平贝叶斯方法阐明了预测中观测值、模型和参数的不确定性,被越来越多的生态学家所使用.应用多水平贝叶斯方法建立了北京八达岭地区森林土壤全氮模型,分析了模型参数及其不确定性,并对该区不同土壤层(A、B、C)全氮含量进行了预测.得到如下结论:(1)该区森林土壤全氮多水平贝叶斯模型为yi～N(β0j[i],k[j]+β1j[i],k[j]xi,σ2y).(2)对模型参数和其曲线不确定性分析表明,该模型能够很好的预测该区土壤全氮含量.(3)模型预测表明:土壤A层,随着海拔的增加,全氮含量递增.土壤B层,随着海拔的升高,植被类型0、1、2、3土壤全氮含量递增,而植被类型4土壤全氮含量出现递减现象.土壤C层,随着海拔的增加,植被类型0土壤全氮含量递增,而植被类型1、2、3、4土壤全氮含量均表现为递减.各植被类型土壤全氮含量都随着土层的深度而减少.     

MultiCoil: A program for predicting two-and three-stranded coiled coils

A new multidimensional scoring approach for identifying and distinguishing trimeric and dimeric coiled coils is implemented in the MultiCoil program. The program extends the two-stranded coiled-coil prediction program PairCoil to the identification of three-stranded coiled coils. The computations are based upon data gathered from a three-stranded coiled-coil database comprising 6,319 amino acid residues, as well as from the previously constructed two-stranded coiled-coil database. In addition to identifying coiled coils not predicted by the two-stranded database programs, MultiCoil accurately classifies the oligomerization states of known dimeric and trimeric coiled coils. Analysis of the MultiCoil scores provides insight into structural features of coiled coils, and yields estimates that 0.9% of all protein residues form three-stranded coiled coils and that 1.5% form two-stranded coiled coils. The MultiCoil program is available at http://theory.Ics.mit.edu/multicoil.     

A vector projection method for predicting the specificity of GalNAc-transferase

The specificity of UDP-Gal-NAc:polypeptide N-acetylgalactosaminytransferase (GalNAc-transferase) is consistent with the existence of an extended site composed of nine subsites, denoted by P₄, P₃, P₂, P₁, P₀, P₁′, P₂′, P₃′, and P₄′, where the acceptor at P₀ is being either Ser or Thr. To predict whether a peptide will react with the enzyme to form a Ser- or Thr-conjugated glycopeptide, a vector projection method is proposed which uses a training set of amino acid sequences surrounding 90 Ser and 106 Thr O-glycosylation sites extracted from the National Biomedical Research Foundation Protein Database. The model postulates independent interactions of the 9 amino acid moieties with their respective binding sites. The high ratio of correct predictions vs. total predictions for the data in both the training and the testing sets indicates that the method is self-consistent and efficient. It provides a rapid means for predicting O-glycosylation and designing effective inhibitors of GalNAc-transferase. © 1995 Wiley-Liss, Inc.     

A clinical method of estimating risk of drug induced delirium

A clinical research method for estimating risk of drug induced acute organic mental syndromes or delirium is described. The method was tested on two patient populations where delirium is expected to occur, and one population where mild organic mental syndromes occur. In two populations, post-cardiotomy and post-cataractectomy states, the drug risk number separated delirium from non-delirium subjects. Subjects with mild acute organic mental syndrome after electroconvulsive therapy also had a higher average drug risk number than comparison subjects.     

HPLC-APCI-MS for the determination of vitamin K(1) in human plasma: method and clinical application

A sensitive HPLC-APCI-MS method for the determination of vitamin K(1) (VK-1) in human plasma was established. Target ions at [M+H](+)m/z 451.5 for VK-1 and [M+H](+)m/z 331.4 for the I.S. (teprenone). Calibration curve was linear over the range of 0.3-1,000 ng/ml. The lower limit of quantification was 0.3 ng/ml. The intra- and inter-batch variability values were less than 8% and 15%, respectively. The C(max) was 210.1+/-86.7 ng/ml while the elimination half-life (t(1/2)) was 8.8+/-1.7h and time to the C(max) was 5.5+/-0.8h after administration of soft capsule containing 10mg VK-1.     

A simple method for predicting the functional differentiation of duplicate genes and its application to MIKC-type MADS-box genes

A simple statistical method for predicting the functional differentiation of duplicate genes was developed. This method is based on the premise that the extent of functional differentiation between duplicate genes is reflected in the difference in evolutionary rate because the functional change of genes is often caused by relaxation or intensification of functional constraints. With this idea in mind, we developed a window analysis of protein sequences to identify the protein regions in which the significant rate difference exists. We applied this method to MIKC-type MADS-box proteins that control flower development in plants. We examined 23 pairs of sequences of floral MADS-box proteins from petunia and found that the rate differences for 14 pairs are significant. The significant rate differences were observed mostly in the K domain, which is important for dimerization between MADS-box proteins. These results indicate that our statistical method may be useful for predicting protein regions that are likely to be functionally differentiated. These regions may be chosen for further experimental studies.     

A Bayesian analysis of the two-period crossover design for clinical trials

Statisticians have been critical of the use of the two-period crossover designs for clinical trials because the estimate of the treatment difference is biased when the carryover effects of the two treatments are not equal. In the standard approach, if the null hypothesis of equal carryover effects is not rejected, data from both periods are used to estimate and test for treatment differences; if the null hypothesis is rejected, data from the first period alone are used. A Bayesian analysis based on the Bayes factor against unequal carryover effects is given. Although this Bayesian approach avoids the "all-or-nothing" decision inherent in the standard approach, it recognizes that with small trials it is difficult to provide unequivocal evidence that the carryover effects of the two treatments are equal, and thus that the interpretation of the difference between treatment effects is highly dependent on a subjective assessment of the reality or not of equal carryover effects.