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At least 181 records · Page 10Linked to original sources
PubMed2003

Effects of positive end-expiratory pressure increments can be predicted by computer simulation based on a physiological profile in acute respiratory failure.

OBJECTIVE: We examined whether computer simulation predicts airway pressures after increments of positive end-expiratory pressure (PEEP) in acute respiratory failure. DESIGN AND SETTING: Prospective, nonrandomized comparative trial in an intensive care unit of a university hospital. PATIENTS: Twelve consecutive acute respiratory failure patients. INTERVENTIONS. PEEP increments from 0 to 2.5, 5, 7.5, 10, and 15 cm H(2)O. MEASUREMENTS AND RESULTS: A physiological profile comprising values for compliance, respiratory resistance and CO(2 )elimination as a function of tidal volume was established from a recording of ordinary breaths prior to increments of PEEP. Airway pressures and CO(2 )elimination were measured 30 s after resetting, pressures also after 10 min. Values from simulation of the resetting, based on the profile, were compared to measured values. The profiles indicated vast differences in physiology between the 12 subjects. Errors of simulation of airway pressures were nonsignificant or trivial up to PEEP levels of 10 cm H(2)O (95% of errors <3 cm H(2)O). After 10 min plateau pressure averaged 1.5 cm H(2)O lower than 30 s after resetting. At increments to PEEP 7.5, 10, and 15, CO(2 )elimination fell by on average 4%, 8%, and 11%, respectively. As tidal volume and respiratory rate was unchanged this was not predicted. CONCLUSIONS: On the basis of a simple lung model, simulation predicted effects of moderate increments of PEEP on airway pressures in patients with complex physiology.

Acute Disease↗
PubMed2003

An analysis of the Candida albicans genome database for soluble secreted proteins using computer-based prediction algorithms.

We sought to identify all genes in the Candida albicans genome database whose deduced proteins would likely be soluble secreted proteins (the secretome). While certain C. albicans secretory proteins have been studied in detail, more data on the entire secretome is needed. One approach to rapidly predict the functions of an entire proteome is to utilize genomic database information and prediction algorithms. Thus, we used a set of prediction algorithms to computationally define a potential C. albicans secretome. We first assembled a validation set of 47 C. albicans proteins that are known to be secreted and 47 that are known not to be secreted. The presence or absence of an N-terminal signal peptide was correctly predicted by SignalP version 2.0 in 47 of 47 known secreted proteins and in 47 of 47 known non-secreted proteins. When all 6165 C. albicans ORFs from CandidaDB were analysed with SignalP, 495 ORFs were predicted to encode proteins with N-terminal signal peptides. In the set of 495 deduced proteins with N-terminal signal peptides, 350 were predicted to have no transmembrane domains (or a single transmembrane domain at the extreme N-terminus) and 300 of these were predicted not to be GPI-anchored. TargetP was used to eliminate proteins with mitochondrial targeting signals, and the final computationally-predicted C. albicans secretome was estimated to consist of up to 283 ORFs. The C. albicans secretome database is available at http://info.med.yale.edu/intmed/infdis/candida/

Algorithms↗
PubMed1987

Small bowel obstruction: computer-assisted prediction of strangulation at presentation.

A multivariate computer analysis has been performed on the presenting data of patients with simple small bowel obstruction that settled with conservative treatment (n = 120) and of patients with viable strangulation small bowel obstruction (n = 38) and non-viable strangulation small bowel obstruction (n = 39) found at operation. Initially only 66 per cent of patients with viable strangulation and 46 per cent of those with non-viable strangulation had been treated by immediate surgery after resuscitation. The remainder had been treated conservatively for a median of 3.8 and 2.2 days respectively before undergoing surgery. The computer predicted on the basis of presenting symptoms and signs that 82 per cent of patients with viable strangulation and 97 per cent of those with non-viable strangulation had or would develop strangulation and should have undergone immediate surgery. We advocate that the computer can assist in the management of patients with small bowel obstruction.

Constriction, Pathologic↗
PubMed1992

[Computer-aided prediction of optimal composition of multicomponent mobile phase in high performance liquid chromatography].

This paper proposed a systematic optimizing method for the composition of multicomponent mobile phase in high performance liquid chromatography. A new chromatographic response function (CRF) has been constructed according to the fundamental retention equation and rule of peak width at half-height, and the optimal composition of multicomponent mobile phase can be automatically predicted by a computer with CRF. This paper improved the known complex method, therefore, the optimal mobile phase composition in the global area may be found by means of this modified complex method. The optimal separation conditions of four vitamins and three nitrophenols were determined by use of the optimizing method reported in this paper. The results predicted by the computer were verified by the experimental data obtained in HPLC using ternary mobile phase.

Chromatography, High Pressure Liquid↗
PubMedDate not supplied

Computer aided prediction of biological activity spectra: evaluating versus known and predicting of new activities for thiazole derivatives.

Computer aided prediction of biological activity spectra by the computer program PASS was applied to a set of 89 new thiazole derivatives. Experimentally tested activities (NSAID, local anaesthetic and antioxidant) coincide with the experiment in 70.8% cases, that exceeds significantly the random guess-work (approximately 0.1%). Therefore, computer aided prediction using the Prediction of Activity Spectra for Substances (PASS) system (http://www.ibmh.msk.su/PASS) provides a reliable basis for planning of synthesis and experimental study for new compounds. New psychotropic activities are predicted for some compounds from the series under study. In particular, 7, 44 and 55 compounds likely have anxiolytic, anticonvulsant and cognition enhancer effects, respectively. Most of these compounds have the estimated values of probability to be active (Pa) less than 60%. Therefore, if their activity will be confirmed by the experiment, they might occur to be New Chemical Entities.

Anesthetics, Local↗
PubMed1999

Quantitative drug interactions prediction system (Q-DIPS): a computer-based prediction and management support system for drug metabolism interactions.

OBJECTIVE: Drug biotransformation and interactions are a major source of variability in the response to drugs. The superfamily of cytochromes P450 plays a key role in this phenomenon but, because of the complexity of interactions between drugs and isozymes, it becomes more and more difficult for clinicians to master the knowledge required to predict the occurrence of such drug interactions. To predict and help manage the occurrence of cytochrome P450-dependent interactions, we developed an original computer application: Q-DIPS (quantitative drug interactions prediction system). METHODS: A multidisciplinary work team was created, associating clinical pharmacologists, pharmacists and a computer scientist. Major steps of investigation were: (1) the creation of a database to collect qualitative and quantitative data describing substrates, inhibitors and inducers of specific cytochrome P450 isozymes, with quality assessments; (2) the development of multi-access to these data and (3) their incorporation into extrapolation systems allowing the prediction of in vivo drug interactions on the basis of in vitro data. As an example, prediction and validation studies of CYP3A4 inhibition by ketoconazole and fluconazole will be discussed. RESULTS: Q-DIPS gives up-to-date information, in dynamic tables, describing which specific P450 isozymes metabolise a given drug, as well as which drugs may inhibit or induce a given isozyme. To better answer common clinical questions and help to rapidly evaluate the risk of interactions, it is possible to obtain an overview of substances causing interactions with a specific drug or to focus on drugs taken by a patient ("clinical case"). For each question, key references, relevant quantitative data and quality indices are easily accessible. Two modules allowing input with commercial names and the anatomical therapeutic chemical classification were also included. On the basis of enzymatic and pharmacokinetic data generated in vitro or collected in vivo, the extrapolation module integrates quantitative models to predict the impact of a treatment on enzymatic activities. The simplest model predicted a strong but fluctuating inhibition of CYP3A4 by ketoconazole, whereas the impact of fluconazole was lower. Validations with published in vivo data suggested an appropriate prediction of the risk. CONCLUSION: The current Q-DIPS prototype shows promising potential for helping to improve the management of drug interactions involving metabolism. Validation of extrapolation techniques need to be completed, in view of including important factors such as intrahepatocyte drug accumulation, contribution of metabolites to inhibition as well as in vitro non-specific binding to microsomal proteins. The final goal will be to help select the most judicious clinical studies to be performed so as to avoid useless, expensive and unethical investigations in man.

Antifungal Agents↗
PubMed2000

The first positive: computing positive predictive value at the extremes.

Computing the positive predictive value (PPV) of a wellknown test for a relatively common disease is a straight-forward exercise. However, in the case of a new test for a rare disorder; the extreme numbers involved-the very low prevalence of the disorder and the lack of previous false-positive results--make it difficult to compute the PPV. As new genetic tests become available in the next decade, more and more clinicians will have to answer questions about PPVs in cases with extreme prevalence, sensitivity, and specificity. This paper presents some tools for thinking about these calculations. First, a standard PPV calculation with rough estimates of the prevalence, sensitivity, and specificity is reviewed. The "zero numerator" problem posed by not having seen any false-positive results is then discussed, and a Bayesian approach to this problem is described. The Bayesian approach requires specification of a prior distribution that describes the initial uncertainty about the false-positive rate. This prior distribution is updated as new evidence is obtained, and the updated expected false-positive rate is used to calculate PPVs. The Bayesian approach provides appropriate and defensible PPVs and can be used to estimate failure rates for other rare events as well.

Bayes Theorem↗
PubMed1996

Single-photon emission computed tomography gallium imaging versus computed tomography: predictive value in patients undergoing high-dose chemotherapy and autologous stem-cell transplantation for non-Hodgkin's lymphoma.

PURPOSE: To evaluate the predictive value of computed tomography (CT) scanning and single-photon emission computed tomography (SPECT) gallium (Ga) scanning in the disease-free survival of patients receiving high-dose chemotherapy and autologous stem-cell transplantation for non-Hodgkin's lymphoma (NHL). PATIENTS AND METHODS: One hundred forty-three patients undergoing transplant for NHL underwent CT scanning of chest, abdomen, and pelvis, and a SPECT Ga scan before transplantation and at day + 100 after transplant. The failure-free survival (FFS) by scan result was analyzed. RESULTS: In the diffuse aggressive lymphoma patients, the 1-year FFS for patients having a positive SPECT Ga scan at day + 100 was 15% compared with a 3-year FFS of 47% for those with a negative scan (P < .001). Patients with a positive CT scan at day + 100 had a 36% 3-year FFS, and those with a negative CT scan had a 39% 3-year FFS (P = not significant [NS]). An analysis of the combination of CT scan and SPECT Ga scan results at day + 100 posttransplant demonstrated a 3-year FFS of 14% if they were both abnormal; if the CT was positive and Ga was negative, the 3-year FFS was 68%; positive Ga with a negative CT was 25%; and both negative was 34% (P = .0015). For the patients with follicular NHL, those with a positive SPECT Ga at day + 100 had a 14% 1-year FFS compared with those with a negative scan, who had a 45% 3-year FFS (P < .001). In the follicular NHL patients, the 3-year FFS of those with a positive CT was 17% compared with a 64% 3-year FFS for patients with a negative CT scan (P < .001). CONCLUSION: The use of SPECT Ga scan at day + 100 posttransplant for evaluation of disease activity in patients with diffuse aggressive NHL was highly predictive of eventual outcome and was more predictive than the CT scan results. However, for patients with follicular NHL, the addition of SPECT Ga scanning to CT scanning did not add substantially to the evaluation of transplant outcome.

Adolescent↗
PubMed2001

Promoter prediction in the human genome.

Computational prediction of eukaryotic poIII promoters has been one of the most elusive problems despite considerable effort devoted to the study. Researchers have looked for various types of signals around the transcriptional start site (TSS), viz. oligo-nucleotide statistics, potential binding sites for core factors, clusters of binding sites, proximity to CpG islands etc. The proximity of CpG islands to gene starts is now a well established fact, although until recently, it was based on very little genomic data. In this work we explore the possibility of enhancing the promoter prediction accuracy by combining CpG island information with a few other, biologically motivated, seemingly independent signals, that cover most of the known knowledge. We benchmarked the method on a much larger genomic datasets compared to previous studies. We were able to improve slightly upon current prediction accuracy. Furthermore, we observe that CpG islands are the most dominant signals and the other signals do not improve the prediction. This suggests that the computational prediction of promoters for genes with no associated CpG-island (typically having tissue-specific expression) looking only at the immediate neighborhood of the TSS may not even be possible. We suggest some biological experiments and studies to better understand the biology of transcription.

Binding Sites↗
PubMed2003

ETOPE: Evolutionary test of predicted exons.

Since a large number of computationally predicted exons are not supported by existing sequence (e.g. ESTs) or experimental (e.g. expression analysis) data they need to be validated by other methods. ETOPE is designed to test computational predictions by using signals that have not been included in any current computational prediction method. The test is based on the ratio of non-synonymous to synonymous substitution rates between sequences from different genomes. It has been previously shown, by empirical data and computer simulation, to be a powerful criterion for identifying protein-coding regions. The ETOPE is available at http://nekrut.uchicago.edu/etope/.

Amino Acid Substitution↗
PubMed1986

Computer-automated prediction of the mutagenicity of benzidine, 4,4"-diaminoterphenyl, 4-dimethylaminoazobenzene and 4-cyanodimethylaniline: comparison with the results of the Second UKEMS Collaborative Study.

There was agreement between the experimental results, obtained in the course of the Second UKEMS Collaborative Study, for the mutagenicity in Salmonella typhimurium of benzidine, 4,4"-diaminoterphenyl, 4-dimethylaminoazobenzene and 4-cyanodimethylaniline and the mutagenicity predicted by CASE (Computer Automated Structure Evaluation), a recently developed artificial intelligence system.

Aniline Compounds↗
PubMed2006

Aspects of large-scale chromatin structures in mouse liver nuclei can be predicted from the DNA sequence.

The large amount of non-coding DNA present in mammalian genomes suggests that some of it may play a structural or functional role. We provide evidence that it is possible to predict computationally, from the DNA sequence, loci in mouse liver nuclei that possess distinctive nucleosome arrays. We tested the hypothesis that a 100 kb region of DNA possessing a strong, in-phase, dinucleosome period oscillation in the motif period-10 non-T, A/T, G, should generate a nucleosome array with a nucleosome repeat that is one-half of the dinucleosome oscillation period value, as computed by Fourier analysis of the sequence. Ten loci with short repeats, that would be readily distinguishable from the pervasive bulk repeat, were predicted computationally and then tested experimentally. We estimated experimentally that less than 20% of the chromatin in mouse liver nuclei has a nucleosome repeat length that is 15 bp, or more, shorter than the bulk repeat value of 195 +/- bp. All 10 computational predictions were confirmed experimentally with high statistical significance. Nucleosome repeats as short as 172 +/- 5 bp were observed for the first time in mouse liver chromatin. These findings may be useful for identifying distinctive chromatin structures computationally from the DNA sequence.

Animals↗
PubMed2002

Can pre-operative computed tomography predict resectability of ovarian carcinoma at primary laparotomy?

OBJECTIVE: To assess the ability of computed tomography in predicting whether suspected ovarian cancer could be fully excised at primary laparotomy. DESIGN: Retrospective analysis of patient notes and pre-operative computed tomography scans. Setting A UK NHS cancer centre. POPULATION: Seventy-seven women who underwent laparotomy for an ovarian tumour and who had had a pre-operative computed tomography scan. METHODS: Women who had a computed tomography scan before laparotomy for an ovarian tumour were identified. Analysis was undertaken to determine the accuracy of computed tomography in predicting malignancy, stage and residual disease. The computed tomography parameters significantly associated with residual disease were determined by a chi2 analysis. These parameters, in addition to age and CA125, were used to generate a predictive model. This model was further refined by stepwise logistic regression and a clinical scoring index was generated. MAIN OUTCOME MEASURES: To identify those computed tomography parameters significantly associated with residual disease and to use these with CA125 and age to generate a useful clinical scoring index to predict residual disease in suspected ovarian cancer. RESULTS: Seventy-seven women underwent a laparotomy for an ovarian tumour and had a pre-operative computed tomography scan. Fifty-one of these women had malignant disease and twenty-five of these women had residual disease remaining. The sensitivity of computed tomography in predicting malignancy was 90% with a specificity of 85% and the overall accuracy of computed tomography for predicting stage of disease was 73% (37/51). The overall sensitivity of computed tomography in predicting residual disease was 88%, the specificity was 92% and the positive predictive value was 85%. The parameters on computed tomography that were significantly (P < 0.05) associated with residual disease were ascites, omental cake, mesenteric disease, paracolic gutter deposits, diaphragmatic deposits and pleural effusion. The predictive model generated was more accurate than computed tomography alone (sensitivity 88%, specificity 98%, positive predictive value 95%). Using stepwise logistic regression enabled the predictive model to be simplified to include mesenteric disease, omental cake, age and CA125 without any change in sensitivity or specificity and this model was used to generate a scoring index. CONCLUSION: This study shows that prediction of resectability by computed tomography is excellent and is further improved by the generation of a predictive model, which can be used to generate a simple scoring index. This scoring system now needs to be tested prospectively to ensure that its performance remains as good in an independent sample population.

Adult↗
PubMed1998

Computer aided prediction and control of shrinkage porosity in titanium dental castings.

OBJECTIVES: The main objectives were to investigate the possibility and reliability of quantitative prediction and control of the concentrated shrinkage porosity (macroporosity) in titanium dental castings by means of a numerical simulation technique; and finally to optimize the filling and feeding system design for dental castings. METHODS: A commercial software, MAGMASOFT (Giessereitechnologie GmbH, Germany), was employed to simulate the mold filling and solidification process, and predict the shrinkage tendency in a sample dental casting, two simplified tooth crowns with a connector bar between them. The numerically predicted shrinkages were compared with the experimental results. The experiments were carried out on a centrifugal casting machine. The same geometric and processing parameters of the casting as in the simulations were strictly controlled. RESULTS: The computer predicted shrinkage porosity coincided with the performed experiments, demonstrating the reliability of the numerical model and the thermal physical data chosen for the calculations. Based on the above numerical model, several filling and feeding systems for the same casting were numerically simulated and compared. Finally an optimized design for this sample casting was proposed, and porosity-free castings were obtained. SIGNIFICANCE: It was expected that the numerical simulation technique could be further developed for dental laboratories to aid the real dental casting design.

Computer Simulation↗
PubMed1987

Computer-assisted predictions of signal peptidase processing sites.

Computer programs are presented which incorporate 2 different algorithms for predicting the site of signal peptide cleavage for eukaryotic preproteins. These programs can be used to identify sites of signal peptidase cleavage of putative preproteins to facilitate the design and interpretation of signal peptide mutagenesis experiments, and to engineer artificial prepolypeptides.

Amino Acids↗
PubMed2006

Challenges in validating CFD-derived inhaled aerosol deposition predictions.

Computational fluid dynamic (CFD) techniques have provided unprecedented opportunity for investigating inhaled particle deposition in realistic human airway geometries. Several recent articles describing local aerosol deposition predictions based upon "validated" CFD models have highlighted the challenges in validating local aerosol deposition predictions. These challenges include: (1) defining what is meant by validation; (2) defining appropriate experimental data for validation; and (3) determining when the agreement is not fortuitous. The term validation has numerous meanings, depending on the field and context in which it is used. For example, in computer programming it means the code executes as intended, to the experimentalist it means predicted results agree with matched experimental measurements, and to the risk assessor it implies that predictions using new parameters can be trusted. Based on the current literature it is not clear that a consensus exists for what constitutes a validated CFD model. It is also not clear what types of experimental data are needed or how closely the CFD input values and experimental conditions should be matched (similar or identical airway geometries, entrance airflow, or aerosol profiles) to validate CFD derived predictions. Due to the complexity of CFD computer codes and the multiplicity of deposition mechanisms, it is possible that total aerosol deposition may be accurately predicted and the resulting local particle deposition patterns are incorrect, or vice versa. Specific examples and suggestions for several challenges to experimentalists and modelers are presented.

Aerosols↗
PubMed2002

The effect of thermodynamic data on computer model predictions of uranium speciation in natural water systems.

Computer models have found widespread application in order to help elucidate and predict changes in environmental systems. One such application is the prediction of trace metal speciation in aqueous systems. This is achieved by solving a set of non-linear equations involving equilibrium constants for all the components in the system, within mass and charge balance constraints. In this study a comparison of the predicted uranium speciation from two computer programs, WHAM and PHREEQCI, is used to illustrate the effect variations in thermodynamic data can have on the models produced. Using the original thermodynamic data provided with the models, WHAM predicted the UO2(2+) ion as the major species (84%) while PHREEQCI predicted UO2(HPO4)2(2-) as the major species (86%). Substituting uranium data from the Nuclear Energy Agency Thermochemical Database project (NEA-TDB) into both programs produced similar results from each program, with UO2F+ predicted to dominate (68%) in a groundwater sample. Natural water samples often contain humic substances. The possible interaction of such substances with uranium was also modelled. The WHAM program includes a discreet site electrostatic humic substance model, however in order to use the PHREEQCI program to model humic substance interactions, a 'model fulvic acid' dataset was added to the program. These models predicted 85 to 98% uranium-humic substance species at neutral pH. This indicates that humic substances do need to be taken into account when modelling uranium speciation in natural water samples.

Computer Simulation↗
PubMedDate not supplied

Evidence for obstructive and restrictive lung pathology among tetra-ethyl lead handlers and petrol tanker fillers at a petrochemical industry in Nigeria.

Described here is a computer predicted and computer measured pulmonary function in a randomly selected population sample of 111 men. These consisted of 36 primary school teachers (control), 35 Tetra-ethyl Lead handlers (TEL) and 40 Tanker Loaders (TL) at a petrochemical industry in Warri, Delta State, Nigeria. Productive cough and headache were commoner among the TL (45%, 38%) and the TEL handlers (43%, 31%). TEL handlers were 5 times likely to develop insomnia and other sleep disturbances than the control group. TL were more than 3 1/2 times more likely to develop nervousness than the control group. Measured FEF25-75% was significantly lower than its predicted value among the TEL handlers (56%) and TL (55%) when compared with the control group (36%) (P < 0.05 respectively). Although there were distinct reductions in the measured values of FEF75-85% among the TEL handlers (41%) and the TL (40%) compared to the control group (28%), this difference did not reach a level of significance when the TEL or the TL were compared individually to the control group. Predicted and measured forced mid expiratory flow time (FMFT) was not significantly varied among the cases and the control. There was statistically significant disparities (P < 0.005) in the values of predicted and measured maximum voluntary ventilation (litres) of the TEL handlers (47%) and of the TL (46%) compared with that of the control group (29%). The data suggest obstruction of the big and small airways of those occupationally exposed at a petrochemical factory in Nigeria especially the tetra-ethyl lead handlers and the tanker loaders. This data also suggests that pulmonary impairment may lead to an increased respiratory absorption of lead in its organic form. Efforts should be made to ascertain the degree of impairment and to treat the affected workers.

Adult↗