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At least 145 records · Page 8Linked to original sources

PubMed1999

Individual-based prediction of the size of the supporting zones in the permanent dentition. A comparison of the Moyers method with a unitary prediction value.

The aims of this individual-based study were 1. to assess the actual space requirements of the permanent canines and premolars, 2. to test the reliability of the Moyers method in predicting a space deficiency at the 75% confidence level and 3. to try to find a reliable unitary prediction value (= unitary value) as a possible substitute for the calculated Moyers values. Dental cast measurements were taken of the permanent dentition of 100 females and 100 males. The average sum of the widths of the maxillary and mandibular permanent canines and premolars was 20.8 mm (17.3 to 24.3 mm). The Moyers method could predict a maxillary space deficiency in 77.5% and a mandibular space deficiency in 65.5% of the subjects. The unitary value of 22.0 mm made it possible to predict a space deficiency in 83.5% of the subjects. The unitary value thus had a higher confidence level (83.5%) than the 75% level stated by Moyers and might thus substitute the calculated Moyers values. Furthermore, the unitary value is easy and quick to handle.

Bicuspid↗

PubMed2020

Harsh Parenting Predicts Novel HPA Receptor Gene Methylation and NR3C1 Methylation Predicts Cortisol Daily Slope in Middle Childhood.

Adverse experiences in childhood are associated with altered hypothalamic-pituitary-adrenal (HPA) axis function and negative health outcomes throughout life. It is now commonly accepted that abuse and neglect can alter epigenetic regulation of HPA genes. Accumulated evidence suggests harsh parenting practices such as spanking are also strong predictors of negative health outcomes. We predicted harsh parenting at 2.5 years old would predict HPA gene DNA methylation similarly to abuse and neglect, and cortisol output at 8.5 years old. Saliva samples were collected three times a day across 3 days to estimate cortisol diurnal slopes. Methylation was quantified using the Illumina Infinium MethylationEPIC array BeadChip (850 K) with DNA collected from buccal cells. We used principal components analysis to compute a summary statistic for CpG sites across candidate genes. The first and second components were used as outcome variables in mixed linear regression analyses with harsh parenting as a predictor variable. We found harsh parenting significantly predicted methylation of several HPA axis genes, including novel gene associations with AVPRB1, CRHR1, CRHR2, and MC2R (FDR corrected p < 0.05). Further, we found NR3C1 methylation predicted a steeper diurnal cortisol slope. Our results extend the current literature by demonstrating harsh parenting may influence DNA methylation similarly to more extreme early life experiences such as abuse and neglect. Further, we show NR3C1 methylation is associated with diurnal HPA function. Elucidating the molecular consequences of harsh parenting on health can inform best parenting practices and provide potential treatment targets for common complex disorders.

Child↗

PubMed1998

Predictive respiratory complication quotient predicts pulmonary complications in thoracic surgical patients.

BACKGROUND: This study was designed to develop an accurate preoperative index of prediction of outcome and hospital charges after lung resection with standard available pulmonary tests in a tertiary cancer center. METHODS: Sixty-one consecutive patients undergoing pulmonary resections were evaluated. All patients underwent spirometry, carbon monoxide diffusion capacity, split lung function testing, and room air blood gas analysis at rest and after a 2-minute step climb. The thoracic prospective data base and patient charts were reviewed for length of hospitalization, postoperative length of stay, and complications requiring therapy. Logistic regression analysis of the preoperative data, operation and postoperative outcome was used to develop a new postoperative predictive index: the predictive respiratory complication quotient (PRQ). We describe the design of the equation for the probability of serious pulmonary complications, hospital stay, and hospital charges based on PRQ. RESULTS: Ten of 12 patients with a PRQ less than 2,200 suffered serious pulmonary complications of pneumonia, respiratory insufficiency, hypoxemia, and death. Forty-nine patients with a PRQ more than 2,200 did not experience any pulmonary complications. Postoperative length of stay and hospital charges correlated with the PRQ. CONCLUSIONS: A construct such as the PRQ may provide a better prediction of outcome than its individual parts. We identified an important underlying relationship between intensive care unit stay, hospital stay and charges, and our index. A PRQ of less than 2,200 was associated with an increased risk of pulmonary complications and mortality.

Algorithms↗

PubMed2001

Prediction of internal standards in reversed-phase liquid chromatography. 1. Initial study on predicting internal standards for use with neutral samples based on linear solvation energy relationships.

This paper describes the results of an initial study on the application of linear solvation energy relationships (LSERs) to the prediction of internal standard compounds in reversed-phase liquid chromatographic (RPLC) method development. Six neutral samples are separated on an Inertsil ODS(3) column by either acetonitrile-water or methanol-water mobile phases under either isocratic or linear gradient conditions. After the separation conditions are optimized, the desired positions for internal standard candidates are selected based on the "open windows" of the chromatograms. The compounds with the desired retention range are then predicted based on LSERs from a database consisting of more than 700 compounds with defined physicochemical properties. The prediction requires the use of LSER coefficients under the separation conditions for each sample. They are determined a priori by performing multivariable linear regression on the retention of 20 reference solutes against their physicochemical properties. It can be concluded from the study that LSER is an excellent approach to the selection of internal standard compounds for RPLC under either isocratic or gradient elution. The average prediction error is usually within 10%, but no more than 20%. Finally, LSER approach is fast and systematic, and will save a significant amount of time and resources during RPLC method development.

Chromatography, Liquid↗

PubMed2002

Prediction of internal standards in reversed-phase liquid chromatography. II. Selectivity optimization and internal standard prediction for the quantitation of estradiol and levonorgestrel in a transdermal drug delivery formulation based on the linear solvation energy relationships.

This paper describes the results of selectivity optimization and internal standard prediction for the quantitation of estradiol and levonorgestrel in transdermal patches by reversed-phase liquid chromatography (RPLC) based on the linear solvation energy relationships (LSERs). The patch samples are prepared by swelling with acetonitrile (ACN) and the separation is performed by Zorbax Eclipse XDB ODS columns. A proper retention range is first determined with a binary mobile phase of ACN and water based on the general resolution equation. The interference to estradiol from a levonorgestrel impurity is then eliminated by a ternary mobile phase of acetonitrile-methanol-water with a composition predicted by LSERs. When the resolution is optimized and the "open window" in the chromatogram for an internal standard is selected, LSERs are used to predict the candidate compounds to be evaluated as the internal standard. The approach described in this study can be used, in general, to considerably improve the efficiency of RPLC method development, particularly for neutral samples. Finally, the LSER approach for the selectivity optimization is compared with a statistical response surface methodology (RSM) based on a central composite design (CCD) in terms of the effectiveness and number of experiments. It is concluded that, although the predicted mobile phase composition to achieve the desired selectivity is about the same, the LSER approach is more efficient and fewer experiments are required.

Chromatography, Liquid↗

PubMed1988

Creatinine clearance prediction in spinal cord injury patients: comparison of 6 prediction equations.

The renal function of spinal cord injury patients frequently is overestimated by 3 commonly used equations to predict creatinine clearance. Overestimation of creatinine clearance may result in aminoglycoside overdosage and resultant nephrotoxicity. Three newer prediction equations have been developed from creatinine clearances measured in neurologically abnormal patients. These 6 equations were tested in 77 male and 9 female spinal cord injury patients (48 quadriplegics and 38 paraplegics, including 38 with acute and 48 with chronic injuries). The equation developed by Sawyer and Hutchins was superior to 2 other equations developed in spinal cord injury patients and 3 equations developed in neurologically normal patients. However, creatinine clearances predicted by this equation were within 30 ml. per minute of measured creatinine clearances in only two-thirds of the spinal cord injury patients. Errors ranged from overestimation by 95 ml. per minute (151 per cent) to underestimation by 106 ml. per minute (45 per cent). The potential for large errors in creatinine clearance prediction necessitates measurement of creatinine clearance as soon as possible when renal excreted and toxic pharmaceuticals are administered to spinal cord injury patients.

Adult↗

PubMed1987

Theoretical, computer-assisted prediction versus SRK prediction of postoperative refraction after intraocular lens implantation.

The postoperative refraction prediction was evaluated in 99 patients with a 19.0-diopter standard power anterior chamber lens using a theoretical, computer-assisted method based on Gaussian optics and an empirical intraocular lens calculation method based on the SRK formula. Both the theoretical and the empirical predictions accorded with the observed values in the near emmetropia region. In the prediction of ametropia, the SRK method showed a tendency to predict refractions that were lower than the actual values in hyperopic eyes and higher than the actual values in myopic eyes. The bias of the SRK method may be due to the use of an erroneous refraction factor that converts the ametropia to the deviation in implant power from the emmetropia power. By introducing an individual refraction factor, the accuracy of the SRK method approached that of the theoretical method.

Aged↗

PubMed1991

New joint prediction algorithm (Q7-JASEP) improves the prediction of protein secondary structure.

The classical problem of secondary structure prediction is approached by a new joint algorithm (Q7-JASEP) that combines the best aspects of six different methods. The algorithm includes the statistical methods of Chou-Fasman, Nagano, and Burgess-Ponnuswamy-Scheraga, the homology method of Nishikawa, the information theory method of Garnier-Osgurthope-Robson, and the artificial neural network approach of Qian-Sejnowski. Steps in the algorithm are (i) optimizing each individual method with respect to its correlation coefficient (Q7) for assigning a structural type from the predictive score of the method, (ii) weighting each method, (iii) combining the scores from different methods, and (iv) comparing the scores for alpha-helix, beta-strand, and coil conformational states to assign the secondary structure at each residue position. The present application to 45 globular proteins demonstrates good predictive power in cross-validation testing (with average correlation coefficients per test protein of Q7, alpha = 0.41, Q7, beta = 0.47, Q7,c = 0.41 for alpha-helix, beta-strand, and coil conformations). By the criterion of correlation coefficient (Q7) for each type of secondary structure, Q7-JASEP performs better than any of the component methods. When all protein classes are included for training and testing (by cross-validation), the results here equal the best in the literature, by the Q7 criterion. More generally, the basic algorithm can be applied to any protein class and to any type of structure/sequence or function/sequence correlation for which multiple predictive methods exist.

Algorithms↗

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↗

PubMed2006

Reliable prediction of Drosha processing sites improves microRNA gene prediction.

MOTIVATION: Mature microRNAs (miRNAs) are processed from long hairpin transcripts. Even though it is only the first of several steps, the initial Drosha processing defines the mature product and is characteristic for all miRNA genes. Methods that can separate between true and false processing sites are therefore essential to miRNA gene discovery. RESULTS: We present a classifier that predicts 5' Drosha processing sites in hairpins that are candidate miRNAs. The classifier, called Microprocessor SVM, correctly predicts the processing site for 50% of known human 5' miRNAs, and 90% of its predictions are within two nucleotides of the true site. Another classifier that is trained on the output from the Microprocessor SVM outperforms existing methods for prediction of unconserved miRNAs. Reanalysis of characteristics and supporting evidence for a set of newly annotated miRNAs shows that some miRNAs may be misannotated. This suggests that expressed hairpins should not be annotated as miRNAs until they are verified to be Drosha and Dicer substrates. AVAILABILITY: The classifiers are publicly available at https://demo1.interagon.com/miRNA/

Artificial Intelligence↗

PubMed2001

Statistical prediction of single-stranded regions in RNA secondary structure and application to predicting effective antisense target sites and beyond.

Single-stranded regions in RNA secondary structure are important for RNA-RNA and RNA-protein interactions. We present a probability profile approach for the prediction of these regions based on a statistical algorithm for sampling RNA secondary structures. For the prediction of phylogenetically-determined single-stranded regions in secondary structures of representative RNA sequences, the probability profile offers substantial improvement over the minimum free energy structure. In designing antisense oligonucleotides, a practical problem is how to select a secondary structure for the target mRNA from the optimal structure(s) and many suboptimal structures with similar free energies. By summarizing the information from a statistical sample of probable secondary structures in a single plot, the probability profile not only presents a solution to this dilemma, but also reveals 'well-determined' single-stranded regions through the assignment of probabilities as measures of confidence in predictions. In antisense application to the rabbit beta-globin mRNA, a significant correlation between hybridization potential predicted by the probability profile and the degree of inhibition of in vitro translation suggests that the probability profile approach is valuable for the identification of effective antisense target sites. Coupling computational design with DNA-RNA array technique provides a rational, efficient framework for antisense oligonucleotide screening. This framework has the potential for high-throughput applications to functional genomics and drug target validation.

Algorithms↗

PubMed2002

A predictive fatigue model--I: Predicting the effect of stimulation frequency and pattern on fatigue.

Previously we developed a mathematical force- and fatigue-model system that could predict fatigue produced by a wide range of frequencies and pulse patterns. However, the models tended to overestimate the forces produced by higher frequency trains. This paper presents modifications to our previously developed force- and fatigue-model system to improve the accuracy in predicting forces during repetitive activation of human skeletal muscle. By comparing the predictions produced by the modified force and fatigue models to those by our previous models, the modification appears to be successful. The current force- and fatigue-model system accounts for about 93% variance in experimental data produced by fatigue protocols consisting of trains with a wide range of frequencies and pulse patterns. In addition, the present models successfully predict the effect of stimulation frequency and pulse pattern on muscle fatigue. The success of our current force- and fatigue-model system suggests its potential use in helping to identify the optimal activation pattern to use during the clinical application of functional electrical stimulation.

Algorithms↗

PubMed2005

Prediction and verification of microRNA targets by MovingTargets, a highly adaptable prediction method.

BACKGROUND: MicroRNAs (miRNAs) mediate a form of translational regulation in animals. Hundreds of animal miRNAs have been identified, but only a few of their targets are known. Prediction of miRNA targets for translational regulation is challenging, since the interaction with the target mRNA usually occurs via incomplete and interrupted base pairing. Moreover, the rules that govern such interactions are incompletely defined. RESULTS: MovingTargets is a software program that allows a researcher to predict a set of miRNA targets that satisfy an adjustable set of biological constraints. We used MovingTargets to identify a high-likelihood set of 83 miRNA targets in Drosophila, all of which adhere to strict biological constraints. We tested and verified 3 of these predictions in cultured cells, including a target for the Drosophila let-7 homolog. In addition, we utilized the flexibility of MovingTargets by relaxing the biological constraints to identify and validate miRNAs targeting tramtrack, a gene also known to be subject to translational control dependent on the RNA binding protein Musashi. CONCLUSION: MovingTargets is a flexible tool for the accurate prediction of miRNA targets in Drosophila. MovingTargets can be used to conduct a genome-wide search of miRNA targets using all Drosophila miRNAs and potential targets, or it can be used to conduct a focused search for miRNAs targeting a specific gene. In addition, the values for a set of biological constraints used to define a miRNA target are adjustable, allowing the software to incorporate the rules used to characterize a miRNA target as these rules are experimentally determined and interpreted.

3' Untranslated Regions↗

PubMed2006

Prediction of depression in European general practice attendees: the PREDICT study.

BACKGROUND: Prevention of depression must address multiple risk factors. Estimating overall risk across a range of putative risk factors is fundamental to prevention of depression. However, we lack reliable and valid methods of risk estimation. This protocol paper introduces PREDICT, an international research study to address this risk estimation. METHODS/DESIGN: This is a prospective study in which consecutive general practice attendees in six European countries are recruited and followed up after six and 12 months. Prevalence of depression is assessed at baseline and each follow-up point. Consecutive attendees between April 2003 and September 2004 who were aged 18 to 75 were asked to take part. The possibility of a depressive episode was assessed using the Depression Section of the Composite International Diagnostic Interview. A selection of presumed risk factors was based on our previous work and a systematic review of the literature. It was necessary to evaluate the test-retest reliability of a number of risk factor questions that were developed specifically, or adapted, for the PREDICT study. In a separate reliability study conducted between January and November 2003, consecutive general practice attendees in the six participating European countries completed the risk factor items on two occasions, two weeks apart. The overall response rate at entry to the study was 69%. We exceeded our expected recruitment rate, achieving a total of 10,048 people in all. Reliability coefficients were generally good to excellent. DISCUSSION: Response rate to follow-up in all countries was uniformly high, which suggests that prediction will be based on almost a full cohort. The results of our reliability analysis are encouraging and suggest that data collected during the course of PREDICT will have a satisfactory level of stability. The development of a multi-factor risk score for depression will lay the foundation for future research on risk reduction in primary care. Our data will also provide the necessary evidence base on which to develop and evaluate interventions to reduce the prevalence of depression.

Adolescent↗

PubMed1975

The prediction and predictability of speech in schizophrenic patients.

Previous research suggests, though by no means consistently, that schizophrenic patients may be less able than normals to predict the speech of other people, and that schizophrenic speech is less predictable than normal speech. The present experiment tests these two suggestions and also a third possibility, that the difference between schizophrenic and normal speech is less marked for schizophrenics asked to make the predictions than for normals. Twelve schizophrenic patients recently admitted to hospital, and twelve comparable, psychiatrically normal, orthopaedic patients, were asked to predict both schizophrenic and normal speech, using Cloze Procedure, under both fourth-word and fifth-word deletion. The first hypothesis was upheld, but the second and third received only very limited support. The findings are discussed in the light of previous work, and suggestions are made for future research.

Adolescent↗

PubMed1985

Prediction of antigenic sites in follicle-stimulating hormones: difference profiles enhance antigenicity prediction methods.

A method of predicting antigenic sites in proteins using only the information provided by primary structure has been reported. The basis of this method is that hydrophilic regions of a polypeptide should contain antigenic sites, since hydrophobic sites should be buried and inaccessible. However, if the antigen is homologous with a naturally occurring polypeptide in the immunized animal, the immune system may not recognize the predicted antigenic site as non-self. Therefore, a modification of the prediction scheme has been developed which can simultaneously examine a protein and its homolog. This method would predict as epitopes those sites that are hydrophilic (accessible) and unrelated to the host homolog (non-self). A computer program has been developed to compare polypeptides and generate difference profiles for antigenic sites. The method has been used to distinguish the antigenic determinants of ovine and human FSH.

Animals↗

PubMed2005

Causal and predictive-value judgments, but not predictions, are based on cue-outcome contingency.

In three experiments, we show that people respond differently when they make predictions as opposed to when they are asked to estimate the causal or the predictive value of cues: Their response to each of those three questions is based on different sets of information. More specifically, we show that prediction judgments depend on the probability of the outcome given the cue, whereas causal and predictive-value judgments depend on the cue-outcome contingency. Although these results might seem problematic for most associative models in their present form, they can be explained by explicitly assuming the existence of postacquisition processes that modulate participants' responses in a flexible way.

Adult↗

PubMed2002

Pre-mRNA secondary structure prediction aids splice site prediction.

Accurate splice site prediction is a critical component of any computational approach to gene prediction in higher organisms. Existing approaches generally use sequence-based models that capture local dependencies among nucleotides in a small window around the splice site. We present evidence that computationally predicted secondary structure of moderate length pre-mRNA subsequencies contains information that can be exploited to improve acceptor splice site prediction beyond that possible with conventional sequence-based approaches. Both decision tree and support vector machine classifiers, using folding energy and structure metrics characterizing helix formation near the splice site, achieve a 5-10% reduction in error rate with a human data set. Based on our data, we hypothesize that acceptors preferentially exhibit short helices at the splice site.

Computer Simulation↗