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PubMed1978

Street heroin potency and deaths from overdose in San Antonio.

Disagreement over the mechanism of death in so-called heroin overdose has been noted in the medical literature for more than a decade. We studied the relationship between the potency of street heroin and the frequency of heroin overdose deaths in San Antonio in order to test the "pharmacologic overdose" hypothesis. We found a small, nonsignificant correlation (r=+.13) between monthly mean heroin dose and monthly number of heroin overdose deaths over a 5-year period. This low correlation contradicts findings of previous studies in Washington, D.C. and Atlanta, conducted over shorter periods of time, in which high positive correlations were found. The low correlation does not support the pharmacologic overdose hypothesis. Since there were confounding variables, the data do not refute the hypothesis. These variables include the use of alcohol and other depressants, hidden suicide, and reduced opioid drug tolerance due to institutional treatment.

Drug Packaging↗

PubMed2005

[Sportsman's hernia--a plea for conservative therapeutical approach].

Sportsmen often suffer prolonged inguinal pain which can become a serious debilitating condition. In most cases the pain originates from a musculoskeletal problem. However, for some patients it has been suggested that the etiology is a weakness of the inguinal canal. This syndrome was termed "sportsman's hernia" although a hernia can not be found on physical examination. Imaging findings were found to be inconclusive regarding the alleged hidden hernia. Various types of operations, based on the variable theories regarding the pathophysiological process, have been developed for the treatment of this syndrome. Some surgeons focus on the external elements of the inguinal canal, and repair the external oblique fascia or enforce the groin with the rectus abdominis. Other surgeons perform an inguinal hernia repair procedure, either with sutures, synthetic mesh, or laparoscopically. Some researchers believe that the problem is in the lower abdominal muscles, or is caused by nerve entrapment, and treat it accordingly. There are no controlled comparative data on the results of the various surgical approaches, and there is no evidence that surgical treatment is more beneficial than conservative treatment. We recommend to operate only if conservative therapy, with prolonged rest, fails. During the operation the inguinal canal should be thoroughly explored, and will be enforced only if a hernia, or a definite weakness of the canal's floor, are found. Similarly, the release of a nerve should be performed only when the exploration reveals clear evidence of entrapment.

Athletic Injuries↗

PubMed2004

Hypervariable genes--experimental error or hidden dynamics.

In a homogeneous group of samples, not all genes of high variability stem from experimental errors in microarray experiments. These expression variations can be attributed to many factors including natural biological oscillations or metabolic processes. The behavior of these genes can tease out important clues about naturally occurring dynamic processes in the organism or experimental system under study. We developed a statistical procedure for the selection of genes with high variability denoted hypervariable (HV) genes. After the exclusion of low expressed genes and a stabilizing log-transformation, the majority of genes have comparable residual variability. Based on an F-test, HV genes are selected as having a statistically significant difference from the majority of variability stabilized genes measured by the 'reference group'. A novel F-test clustering technique, further noted as 'F-means clustering', groups HV genes with similar variability patterns, presumably from their participation in a common dynamic biological process. F-means clustering establishes, for the first time, groups of co-expressed HV genes and is illustrated with microarray data from patients with juvenile rheumatoid arthritis and healthy controls.

Adolescent↗

PubMed1979

Capping of variable antigen on Trypanosoma brucei, and its immunological and biological significance.

Pathogenic trypanosomes undergo antigenic variation, whereby the glycoprotein molecules constituting the cell coat are changed, the parasite thus evading the host's immune response. On application of homologous antiserum in indirect immunofluorescence to a given variable antigen type of Trypanosoma brucei, the surface variable antigen moves to the flagellar pocket region, which overlies the Golgi apparatus. This redistribution, or capping, is temperature-dependent, occurring at 37 degrees C but not at 0-4 degree C. Patching does not occur at either temperature. Immediately after capping no homologous or heterologous variable antigen, or host plasma or blood cell antigens, can be detected by immunofluorescence on the cell surface outside the cap; only trypanosome membrane common antigens can be found. It seems unlikely for two reasons that this antibody-induced redistribution is relevant to antigenic variation. Capping of the coat requires the indirect, rather than the direct, immunofluorescent method; a single layer of antibody, in nature, would appear to be ineffective. Also, capping of variable antigen of one type is followed within 3 h by appearance of antigen of the same, and not another, type. The necessity for 2 antibody layers is usually thought of as meaning that the individual molecules of the cell surface antigen are spaced further apart than the binding sites of an individual antibody molecule, so that the necessary cross-linked lattice cannot be formed, but on T. brucei the surface variable antigen molecules are very closely packed. It is proposed that one layer of antibody is ineffective for steric reasons; the dimensions of the exposed face of each variable antigen molecule may not permit the binding of more than one molecule of immunoglobulin, or perhaps the antigen molecules are so closely packed that most of the antigenic determinants are hidden from antibodies. To test this hypothesis, an attempt was made to cap variable antigen on trypanosomes transforming in vitro from the bloodstream to the procyclic (insect midgut) stage; such forms have a much less densely packed surface coat. Patching was observed, indicative of lattice formation, but these trypanosomes did not survive the in vitro manipulation long enough to permit any possible capping. T. brucei differs structurally from most other eukaryotic cells. It has no detectable microfilaments under the plasma membrane, except at the desmosomes in the region of flagellar binding, and it also has a pellicular cortex of microtubules. Capping of its surface antigen would appear then to differ from that on mammalian cells, either in the cellular components involved or in that specialized areas of the plasma membrane are involved.

Animals↗

PubMed1998

Neural networks as "software sensors" in enzyme engineering.

Industrial applications of enzyme technology are rapidly increasing. On-line control of enzyme production processes, however, is difficult owing to the uncertainties typical of biological systems and to the lack of suitable on-line sensors for key process variables and quality attributes. We demonstrate that well-trained feedforward backpropagation neural networks with one hidden layer can be employed to overcome such problems with no need for a priori knowledge of the relationships of the process variables involved. Neural network programs were written in Microsoft Visual C++ for Windows and implemented in a personal computer. The goodness of fit of the trained neural network to the reference data was determined by the coefficient of determination, R2. Case studies of beta-galactosidase, glucoamylase, lipase, and xylanase production processes will be used as examples.

Algorithms↗

PubMedDate not supplied

Longitudinal study of the presence of hidden 19S IgM rheumatoid factor in juvenile rheumatoid arthritis.

Complement-fixing hidden 19S IgM rheumatoid factor (RF), i.e., 19S IgM RF that can be detected in the IgM-containing fraction by the hemolytic assay after separation of the serum by acid gel filtration, was evaluated serially (3 or more evaluations) over a 4-year period in 26 children with juvenile rheumatoid arthritis (JRA) correlating its presence with disease activity. Six children with continually active disease had consistently elevated hidden RF titers (26 evaluations), and the titers of 4 children with inactive disease remained insignificant (12 evaluations). Sixteen children had disease with variable activity over this period. Of these, 11 (43 evaluations) demonstrated positive correlation between disease activity and hidden RF titers. Five patients (8/20 evaluations) did not show correlation of disease activity with hidden RF titers. Thus, the presence of hidden RF correlated with disease activity in 93 of 101 evaluations. When hidden RF titers and the erythrocyte sedimentation rate were determined simultaneously on 40 occasions, the presence of hidden 19S IgM RF correlated significantly better (p less than 0.001) with disease activity.

Arthritis, Juvenile↗

PubMed2007

Application of artificial neural network coupling particle swarm optimization algorithm to biocatalytic production of GABA.

The biotransformation of L-sodium glutamate (L-MSG) to gamma-aminobutyric acid (GABA) catalyzed by the cells of Lactobacillus brevis with higher glutamate decarboxylase activity was investigated. The results showed that pH, temperature, and FeSO(4) x 7H(2)O concentration had significantly positive effect on GABA yield. The individual and interactive effects of pH, temperature, and FeSO(4) x 7H(2)O concentration were further optimized in terms of GABA yield. In the present work, an artificial neural network (ANN) and response surface methodology (RSM) models were developed, which incorporated pH, temperature, and FeSO(4) x 7H(2)O concentration as input variables, and GABA yield as output variable. The optimized ANN topology included four neurons in the hidden layer and the best network architecture was 3-4-1. The trained ANN gave total root-mean square error (sigma) equal to 1.84 for GABA yield while the RSM gave sigma equal to 2.63. The results demonstrated a slightly higher prediction accuracy of ANN compared to RSM. The modeled maximum GABA yield was identified by applying particle swarm optimization algorithm to the ANN model developed. The modeled maximum GABA yield reached 91 mM under the following optimal conditions: 25 mL Na(2)HPO(4)-citric acid buffer (100 mM, pH 4.23), 120 mM L-MSG, 0.83 g/L FeSO(4) x 7H(2)O, 10 microM PLP, the resting cells obtained from a 60-h culture broth, 2.68 g dry cell weight (DCW)/L, and without agitation at 40 degrees C for 5 h. The previous high value of GABA yield that was observed was 81.8 mM. The optimized conditions allowed GABA yield to be increased from 81.8 to 90.57 mM after verification experiments test.

Algorithms↗

PubMed2006

Artificial neural network for the joint modelling of discrete cause-specific hazards.

OBJECTIVE: Artificial neural network (ANN) based regression methods have been introduced for modelling censored survival data to account for complex prognostic patterns. In the framework of ANN extensions of generalized linear models for survival data, PLANN is a partial logistic ANN, suitable for smoothed discrete hazard estimation as a function of time and covariates. An extension of PLANN for competing risks analysis (PLANNCR) is now proposed for discrete or grouped survival times, resorting to the multinomial likelihood. METHODS AND MATERIALS: PLANNCR is built by assigning input nodes to the explanatory variables with the time interval treated as an ordinal variable. The logistic function is used as activation for the hidden nodes of the network, whereas the softmax, which corresponds to the canonical link of generalized linear models for polytomous regression, is adopted for multiple output nodes, to provide a smoothed estimation of discrete conditional event probabilities for each event. The Kullback-Leibler distance is used as error function for the target vectors, amounting to half of the deviance of a multinomial logistic regression model. PLANNCR can jointly model non-linear, non-proportional and non-additive effects on cause-specific hazards (CSHs). The degree of smoothing is modulated by the number of hidden nodes and penalization of the error function (weight decay). Model optimisation is achieved by quasi-Newton algorithms, while non-linear cross-validation (NCV) and the Network Information Criterion (NIC) were adopted for model selection. PLANNCR was applied to data on 1793 women with primary invasive breast cancer, histologically N-, who underwent surgery at the Milan Cancer Institute between 1981 and 1986. RESULTS: Differential effects of covariates and time on the shape of the CSH for the three main failure causes, namely intra-breast tumor recurrences, distant metastases and contralateral breast cancer, have been enlightened. CONCLUSIONS: PLANNCR can be suitably adopted in an exploratory framework for a thorough evaluation of the disease dynamics in the presence of competing risks.

Adult↗

PubMed1997

Cardiac risk stratification in renal transplantation using a form of artificial intelligence.

The purpose of this study was to determine if an expert network, a form of artificial intelligence, could effectively stratify cardiac risk in candidates for renal transplant. Input into the expert network consisted of clinical risk factors and thallium-201 stress test data. Clinical risk factor screening alone identified 95 of 189 patients as high risk. These 95 patients underwent thallium-201 stress testing, and 53 had either reversible or fixed defects. The other 42 patients were classified as low risk. This algorithm made up the "expert system," and during the 4-year follow-up period had a sensitivity of 82%, specificity of 77%, and accuracy of 78%. An artificial neural network was added to the expert system, creating an expert network. Input into the neural network consisted of both clinical variables and thallium-201 stress test data. There were 5 hidden nodes and the output (end point) was cardiac death. The expert network increased the specificity of the expert system alone from 77% to 90% (p < 0.001), the accuracy from 78% to 89% (p < 0.005), and maintained the overall sensitivity at 88%. An expert network based on clinical risk factor screening and thallium-201 stress testing had an accuracy of 89% in predicting the 4-year cardiac mortality among 189 renal transplant candidates.

Adult↗

PubMed1996

Relationship between alcohol withdrawal seizures and temporal lobe white matter volume deficits.

A previous magnetic resonance imaging study from our laboratory reported significant temporal lobe volume deficits in cortical gray matter, white matter, and anterior hippocampus in chronic alcoholic men relative to controls. In the present study, we reexamined these data and asked whether withdrawal seizure history was predictive of either the hippocampal or the extrahippocampal volume deficits. A review of the medical charts indicated that 11 alcoholics had experienced one or more alcohol-related seizures and 35 were seizure-free; no patient had a seizure disorder unrelated to alcohol. The two alcoholic groups did not differ significantly in age, education, alcohol consumption variables, premorbid intelligence, Memory Quotient, Trail Making, or detection of hidden figures. Although each alcoholic group showed significant bilateral volume deficits of the anterior hippocampus and frontal-parietal and temporal gray matter, relative to controls, the seizure group had significantly smaller temporal lobe white matter volumes than either the control or the seizure-free groups; the latter two groups did not differ from each other. Both alcoholic groups, however, had white matter volume deficits in the frontal-parietal region. Thus, the seizure group accounted for the white matter volume deficits in the temporal lobe previously reported in the full sample of alcoholics. It seems, then, that reduced white matter volume in the temporal lobes may be either a risk factor for or sequela of alcohol withdrawal seizures.

Adult↗

PubMed2006

Alcohol use and abuse in training conscripts of the Hellenic navy.

OBJECTIVES: Alcohol abuse and addiction are big current problems of the developed world having multivariate causality and multiple effects. Alcohol abuse in young people is a matter of central importance due to its wide range long lasting effects, especially so in Greece where the problem has only recently started growing. The Hellenic Navy is interested in the complications of alcohol abuse in training conscripts. Because young conscripts will be placed in demanding positions, but also because in Greece the military service is obligatory and represents an important period for the socialization of young men. METHODS: In the present study, levels of alcohol use and abuse were measured in a sample of 650 male training conscripts of the Hellenic Navy. The tools used are: (a) two questionnaires measuring frequency and quantity of alcohol consumption and psychosocial variables, (b) the CAGE test, which is a questionnaire measuring hidden alcoholism. RESULTS: 38,1% conscripts were characterized problematic drinkers according the adolescents criteria. Additional psychological complications were related to alcohol use. Using the stricter criterion for adults (plus psychological complications) 8.9% were found to be problematic drinkers. The use of CAGE questionnaire which is measuring hidden alcoholism, identified 16% of the total sample as hidden alcoholics. DISCUSSION: The findings regarding unregular levels of alcohol use and abuse are presented as well as their relation to psychosocial complications and to demographic characteristics. The results are discussed in the light of Creek and international bibliography.

Journal Article↗

PubMed2006

Application of data mining to predict the dosage of vancomycin as an outcome variable in a teaching hospital population.

OBJECTIVE: Data mining is a process used to extract potentially valuable information hidden in large volumes of raw data. The aim of this study was to explore the possibility of using easy to implement and effective supervised learning techniques to predict the dosage of vancomycin. METHODS: To reach this goal, we considered the prediction of the dosage of vancomycin as a classification problem. We chose the C4.5 decision tree technique for the dosage prediction process and supplied it with a boosting technique to enhance its performance. RESULTS: The potential predictor variables were collected from 833 patients with methicillin-resistant Staphylococcus aureus, or penicillin intolerance who were being treated with vancomycin and undergoing therapeutic drug monitoring (TDM) after attainment of steady state blood concentrations. Attributes tested as potential predictors included age, sex, weight, serum creatinine concentration, dosing interval, and variables from 1-compartment model kinetics such as Kd, Vd, and t(1/2). CONCLUSIONS: The results showed that the proposed method can utilize a variety of parameters to predict the dosage of vancomycin in the population used and that it performs well over a range of patient ages and renal function. The method may offer an alternative to existing methods used to support decision-making in clinical practice.

Adolescent↗

PubMed1987

A cell that dies during wild-type C. elegans development can function as a neuron in a ced-3 mutant.

Mutations in the C. elegans gene ced-3 prevent almost all programmed cell deaths, so that in a ced-3 mutant there are many extra cells. We show that the pharyngeal neuron M4 is essential for feeding in wild-type worms, but in a ced-3 mutant, one of the extra cells, probably MSpaaaaap (the sister of M4), can sometimes take over M4's function. The function of MSpaaaaap, unlike that of M4, is variable and subnormal. One possible explanation is that its fate, being hidden by death and not subject to selection, has drifted randomly during evolution. We suggest that such cells may play roles in the evolution of cell lineage analogous to those played by pseudogenes in the evolution of genomes.

Animals↗

PubMed2006

Directional multiscale modeling of images using the contourlet transform.

The contourlet transform is a new two-dimensional extension of the wavelet transform using multiscale and directional filter banks. The contourlet expansion is composed of basis images oriented at various directions in multiple scales, with flexible aspect ratios. Given this rich set of basis images, the contourlet transform effectively captures smooth contours that are the dominant feature in natural images. We begin with a detailed study on the statistics of the contourlet coefficients of natural images: using histograms to estimate the marginal and joint distributions and mutual information to measure the dependencies between coefficients. This study reveals the highly non-Gaussian marginal statistics and strong interlocation, interscale, and interdirection dependencies of contourlet coefficients. We also find that conditioned on the magnitudes of their generalized neighborhood coefficients, contourlet coefficients can be approximately modeled as Gaussian random variables. Based on these findings, we model contourlet coefficients using a hidden Markov tree (HMT) model with Gaussian mixtures that can capture all interscale, interdirection, and interlocation dependencies. We present experimental results using this model in image denoising and texture retrieval applications. In denoising, the contourlet HMT outperforms other wavelet methods in terms of visual quality, especially around edges. In texture retrieval, it shows improvements in performance for various oriented textures.

Algorithms↗

PubMed2005

Deterministic convergence of an online gradient method for BP neural networks.

Online gradient methods are widely used for training feedforward neural networks. We prove in this paper a convergence theorem for an online gradient method with variable step size for backward propagation (BP) neural networks with a hidden layer. Unlike most of the convergence results that are of probabilistic and nonmonotone nature, the convergence result that we establish here has a deterministic and monotone nature.

Algorithms↗

PubMed2005

A probabilistic model of face mapping with local transformations and its application to person recognition.

This paper proposes a new measure of "distance" between faces. This measure involves the estimation of the set of possible transformations between face images of the same person. The global transformation, which is assumed to be too complex for direct modeling, is approximated by a patchwork of local transformations, under a constraint imposing consistency between neighboring local transformations. The proposed system of local transformations and neighboring constraints is embedded within the probabilistic framework of a two-dimensional hidden Markov model. More specifically, we model two types of intraclass variabilities involving variations in facial expressions and illumination, respectively. The performance of the resulting method is assessed on a large data set consisting of four face databases. In particular, it is shown to outperform a leading approach to face recognition, namely, the Bayesian intra/extrapersonal classifier.

Algorithms↗

PubMed1990

Mitochondrial DNA polymorphism reveals hidden heterogeneity within some Asian populations.

Use of data on mtDNA morph distributions from six Asian populations has shown that the observed number of different mtDNA morphs is too large when compared with the number expected on the basis of the observed gene diversity in the mtDNA genome. This excess number of morphs mainly occurs through an excess of rare morphs, and this discrepancy is more pronounced in a pooled sample of five Asian populations. It is suggested that this discrepancy is probably due to internal heterogeneity in each of the anthropologically defined populations. This analysis demonstrates the utility that population data for a single locus, such as the mtDNA genome, have for detecting hidden heterogeneity in populations, provided that the locus has substantial genetic variability, so that many variant alleles can be detected.

Asia↗

PubMed1988

Three-dimensional reconstruction of cells from serial sections and whole-cell mounts using multilevel contouring of stereo micrographs.

A comprehensive computer-graphics-based system (STERECON) is described for tracing and digitizing contours from individual or stereopair electron micrographs. The contours are drawn in parallel planes within the micrographs. Provision is also made for tracing and digitizing in full three-dimensional (3-D) coordinates in any direction along linear structures such as cytoskeletal elements. The stereopair micrographs are viewed in combination with the contours being traced on a graphics terminal monitor. This is done either by projecting original electron micrograph (EM) negatives onto a screen and optically combining these images with contour lines being drawn on the monitor, or by first digitizing the images and displaying them directly on the monitor along with the contour lines. Prior image digitization allows computer enhancement of the structures to be contoured. Correction and alignment routines are included to deal with variable section thickness, section distortion and mass loss, variations in photography in the electron microscope, and terminal screen curvature when combining projected images with contour lines on the monitor. The STERECON system organizes and displays the digitized data from successive sections as a 3-D reconstruction. Reconstructions can be viewed in any orientation as contour stacks with hidden lines removed; as wire-frame models; or as shaded, solid models with variable lighting, transparency, and reflectivity. Volumes and surface areas of the reconstructed objects can be determined. Particular attention was paid to making the system convenient for the biological user. Users are given a choice of three different stereo-viewing methods.

Animals↗