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PubMed2001

Pattern recognition in flow cytometry.

BACKGROUND: Analytical flow cytometry (AFC), by quantifying sometimes more than 10 optical parameters on cells at rates of approximately 10(3) cells/s, rapidly generates vast quantities of multidimensional data, which provides a considerable challenge for data analysis. We review the application of multivariate data analysis and pattern recognition techniques to flow cytometry. METHODS: Approaches were divided into two broad types depending on whether the aim was identification or clustering. Multivariate statistical approaches, supervised artificial neural networks (ANNs), problems of overlapping character distributions, unbounded data sets, missing parameters, scaling up, and estimating proportions of different types of cells comprised the first category. Classic clustering methods, fuzzy clustering, and unsupervised ANNs comprised the second category. We demonstrate the state of the art by using AFC data on marine phytoplankton populations. RESULTS AND CONCLUSIONS: Information held within the large quantities of data generated by AFC was tractable using ANNs, but for field studies the problem of obtaining suitable training data needs to be resolved, and coping with an almost infinite number of cell categories needs further research.

Flow Cytometry↗
PubMed1994

[Assessment of a multimicrotest system for biochemical identification of enterobacteria (MMT E1) in a controlled epidemiological experiment. I].

Comparative evaluation of a system of multimicrotests for biochemical identification of enterobacteria (MMT E1) developed at the ALLERGEN Research and Production Amalgamation and of tube tests for the same purpose in a controlled epidemiologic experiment has shown that the suggested system meets the requirements to such diagnostic preparations by all the major qualitative parameters (compatibility and reproducibility of the test results). Practical use of MMT E1 system will simplify and facilitate the process of enterobacteria identification.

Bacteriological Techniques↗
PubMed2004

Towards in vivo aorta material identification and stress estimation.

This paper addresses the problem of constructing a mechanical model for the abdominal aorta and calibrating its parameters to in vivo measurable data. The aorta is modeled as a pseudoelastic, thick-walled, orthotropic, residually stressed cylindrical tube, subjected to an internal pressure. The model parameters are determined by stating a minimization problem for the model pressure and computing the optimal solution by a minimization algorithm. The data used in this study is in vivo pressure-diameter data for the abdominal aorta of a 24-year-old man. The results show that the axial, circumferential and radial stresses have magnitudes in the span 0 to 180 kPa. Furthermore, the results show that it is possible to determine model parameters directly from in vivo measurable data. In particular, the parameters describing the residual stress distribution can be obtained without interventional procedures.

Adult↗
PubMed1998

Identification of human joint mechanical properties from single trial data.

A method is presented for estimating the time-varying compliance parameters of the elbow-joint from a single movement. The method separates by frequency the perturbed from the voluntary response, then determines the parameters by exponentially weighted least squares. The tracking performance of the method is established by simulation and by a calibrated mechanical joint. Experimental results are presented on time-varying posture and slow movement.

Adult↗
PubMed2004

A self-tuning method for one-chip SNP identification.

Current methods for interpreting oligonucleotide-based SNP-detection microarrays, SNP chips, are based on statistics and require extensive parameter tuning as well as extremely high-resolution images of the chip being processed. We present a method, based on a simple data-classification technique called nearest-neighbors that, on haploid organisms, produces results comparable to the published results of the leading statistical methods and requires very little in the way of parameter tuning. Furthermore, it can interpret SNP chips using lower-resolution scanners of the type more typically used in current microarray experiments. Along with our algorithm, we present the results of a SNP-detection experiment where, when independently applying this algorithm to six identical SARS SNP chips, we correctly identify all 24 SNPs in a particular strain of the SARS virus, with between 6 and 13 false positives across the six experiments.

Algorithms↗
PubMed1988

[Cardiac and extracardiac parameters as principles in differential therapeutic considerations for decreasing pre- and afterload].

A differential therapy of congestive heart failure requires the identification of the different stages of myocardial damage consequent to the underlying heart disease and the individual adaptive response to it. Because of their different load dependence, it is important to recognize the independent contribution of systolic and diastolic dysfunction in congestive heart failure. The vertical displacement of the diastolic pressure-volume loop is associated with a reduced therapeutic range. Reducing preload may limit the degree of diastolic filling necessary to fill a noncompliant heart and limit active myocardial stretch. The final outcome of any disorder is either to comprise cardiac filling, emptying, or both. When the end-stage is reached, only modification of excessive neurohormonal responses to heart failure remains. Efforts are necessary to avoid substances able to support the maladaptation. The rational use of vasodilator therapy in congestive heart failure is based on the concept that peripheral circulatory mechanisms overshoot, and may thereby act to exacerbate the heart failure. As important as it is to modify late neurohormonal responses, it is even more important to intervene at an earlier stage to reduce the degree of irreversible myocardial damage. Further studies have to prove the potential benefits of ACE-inhibitors in patients with mild heart failure in order to prevent or delay the progress of the disease.

Blood Pressure↗
PubMed1981

[Possible identification of electroencephalographic changes caused by hereditary and process factors in schizophrenia].

A comparative study of the quantitative differences of EEG parameters in the pairs of mono- and dizygotic twins suffering from schizophrenia has shown that the magnitudes of some parameters were substantially lower in the monozygotic twins than in the dizygotic ones. Examinations of healthy relatives of the schizophrenic twins revealed an increased frequency of the same signs (in the magnitude and direction), as in the patients. Less distinct in the mono- dizygotic pairs were differences between the reactive changes of the biopotentials and the latter's spatio-temporal organization inside the pairs. In the monozygotic pairs, these changes and organization were disturbed to a greater degree in the twin partner with a more rapid progress of the disease.

Cerebral Cortex↗
PubMed1979

Lp(a) phenotypes, other lipoprotein parameters, and a family history of coronary heart disease in middle-aged males.

In a study of 95 presumably healthy, 40-42-year old males from Northen Sweden, the Lp(a) phenotype distribution differed between those who had, and those who did not have one or more close relatives (parent or sib) with coronary heart disease. In the former group, 60% of the males were Lp(a+), as opposed to 28% in the latter group. Thus, in the homogeneous population sample studied, analysis of the normal inherited Lp(a) variation permitted the identification of distinct subpopulations, with respect to familial occurrence of coronary heart disease. None of a series of other parameters distinguished such sub-populations. The results reported are in agreement with our previous finding of a close association between phenotype Lp(a+) and risk of contracting coronary heart disease.

Adult↗
PubMed2004

Neuroendocrine differentiation in pure type mammary mucinous carcinoma is associated with favorable histologic and immunohistochemical parameters.

Mucinous carcinoma of the breast is a specific good prognostic type malignancy occurring in elderly patients. Neuroendocrine differentiation has long been described in mucinous carcinoma, but the significance of such finding is uncertain. We evaluated the neuroendocrine differentiation profiles of 38 cases of pure mucinous carcinoma and compared the clinicopathological differences between those with and those without neuroendocrine differentiation. The parameters assessed included patients' age, tumor size, nuclear grade, axillary lymph node status at time of diagnosis, percentage area of intratumoral mucin, and the expression of estrogen and progesterone receptors, cerbB2 oncoprotein, and three neuroendocrine markers, namely neurone-specific enolase, chromogranin, and synaptophysin by immunohistochemistry. Patients' outcome and follow-up period were also documented. Of the 38 cases of pure mucinous carcinoma, 28, 11 and six cases showed positive staining for 1, 2 and 3 of the neuroendocrine markers. For all the groups with variable neuroendocrine differentiation and compared to those without such differentiation, they all showed older patients' age, higher proportion of tumors with lower nuclear grade, lower incidence of axillary lymph node metastasis, a higher progesterone receptor, and lower cerbB2 oncoprotein expression. No difference was detected between tumor size, intratumoral mucinous area, and estrogen receptor status. In all, 37 patients did not have distant metastases or local recurrences at the end of follow-up period, while one patient with coexisting high-grade ductal carcinoma in situ at time of diagnosis died of breast carcinoma. Our findings suggest that the identification of neuroendocrine differentiation in pure mucinous carcinoma is associated with more favorable histologic and immunohistochemical parameters.

Adenocarcinoma, Mucinous↗
PubMed2001

Autoantibodies associated with rheumatic diseases.

The identification of circulating autoantibodies contributes to the correct diagnosis as well as to the follow-up of rheumatic diseases. Some autoantibodies are even included in diagnostic and classification criteria for these types of autoimmune diseases. There are several relatively specific screening and identification methods for the measurement of autoantibodies available. The type of assay crucially influences the diagnostic value of the parameters. In general, routine laboratories should prefer enzyme immunoassays (ELISA) using well characterized antigens, although ELISA tests tend to produce more false-positive and true weakly positive results, which reduce their positive predictive value. Therefore one should be aware that laboratory results can only be properly interpreted when there is a correlation with the clinical situation and when the limitations of the technologies used for autoantibody identification have been taken into consideration. A diagnostic algorithm consisting of screening and identification steps should be established by each laboratory in order to create a rational, evidence-based and cost-effective basis for the diagnosis of rheumatic diseases.

Antibodies, Antinuclear↗
PubMed2002

Protein identification by MALDI-TOF-MS peptide mapping: a new strategy.

A new strategy for identifying proteins by MALDI-TOF-MS peptide mapping is reported. In contrast to current approaches, the strategy does not rely on a good relative or absolute mass accuracy as the criterion that discriminates false positive results. The protein sequence database is first searched for all proteins that match a minimum five of the submitted masses within the maximum expected relative errors when the default or externally determined calibration constants are used, for instance, +/-500 ppm. Typically, this search retrieves many thousand candidate sequences. Assuming initially that each of these is the correct protein, the relative errors of the matching peptide masses are calculated for each candidate sequence. Linear regression analysis is then performed of the calculated relative errors as a function of m/z for each candidate sequence, and the standard deviation to the regression is used to distinguish the correct sequence among the candidates. We show that this parameter is independent of whether the mass spectrometric data were internally or externally calibrated. The result is a search engine that renders internal spectrum calibration unnecessary and adapts to the quality of the raw data without user interference. This is made possible by a dynamic scoring algorithm, which takes into account the number of matching peptide masses, the percentage of the protein's sequence covered by these peptides and, as new parameter, the determined standard deviation. The lower the standard deviation, the less cleavage peptides are required for identification and vice versa. Performance of the new strategy is demonstrated and discussed. All necessary computing has been implemented in a computer program, free access to which is provided in the Internet.

Algorithms↗
PubMed2004

Metabolic control analysis under uncertainty: framework development and case studies.

Information about the enzyme kinetics in a metabolic network will enable understanding of the function of the network and quantitative prediction of the network responses to genetic and environmental perturbations. Despite recent advances in experimental techniques, such information is limited and existing experimental data show extensive variation and they are based on in vitro experiments. In this article, we present a computational framework based on the well-established (log)linear formalism of metabolic control analysis. The framework employs a Monte Carlo sampling procedure to simulate the uncertainty in the kinetic data and applies statistical tools for the identification of the rate-limiting steps in metabolic networks. We applied the proposed framework to a branched biosynthetic pathway and the yeast glycolysis pathway. Analysis of the results allowed us to interpret and predict the responses of metabolic networks to genetic and environmental changes, and to gain insights on how uncertainty in the kinetic mechanisms and kinetic parameters propagate into the uncertainty in predicting network responses. Some of the practical applications of the proposed approach include the identification of drug targets for metabolic diseases and the guidance for design strategies in metabolic engineering for the purposeful manipulation of the metabolism of industrial organisms.

Algorithms↗
PubMed2006

Characterization of the methanolic extract of hops using capillary electrophoresis-electrospray ionization-mass spectrometry.

Hops are used almost exclusively for bitterness and flavor by brewers. We propose the first analytical application of CZE coupled to ESI-MS for the separation and structural elucidation of organic compounds in the methanolic extracts of hops, and different extraction procedures of the plant material have been carried out. The proposed method permits the identification of hop polyphenols (flavonoids glycosides and chalcones), bitter acids (alpha-acids and beta-acids), and their oxidation products. The optimization of CZE parameters (pH, concentration, and type of buffer) and ESI-MS parameters (nature and flow rate of the sheath liquid, nebulizer pressure, drying gas flow rate, temperature, and compound stability) have permitted the development of a rapid, simple, direct, and straightforward CZE-ESI-MS method for the identification of components of methanolic extracts from different hops used in the brewing process.

Acids↗
PubMed2004

Prediction of elasticity constants in small biomaterial samples such as bone. A comparison between classical optimization techniques and identification with artificial neural networks.

Measuring the elasticity constants of biological materials often sets important constraints, such as the limited size or the irregular geometry of the samples. In this paper, the identification approach as applied to the specific problem of accurately retrieving the material properties of small bone samples from a measured displacement field is discussed. The identification procedure can be formulated as an optimization problem with the goal of minimizing the difference between computed and measured displacements by searching for an appropriate set of material parameters using dedicated algorithms. Alternatively, the backcalculation of the material properties from displacement maps can be implemented using artificial neural networks. In a practical situation, however, measurement errors strongly affect the identification results, calling for robust optimization approaches in order accurately to retrieve the material properties from error-polluted sample deformation maps. Using a simple model problem, the performances of both classical and neural network driven optimization are compared. When performed before the collection of experimental data, this evaluation can be very helpful in pinpointing potential problems with the envisaged experiments such as the need for a sufficient signal-to-noise ratio, particularly important when working with small tissue samples such as specimens cut from rodent bones or single bone trabeculae.

Algorithms↗
PubMed1995

Use of Presumpto Plates to identify anaerobic bacteria.

Identification of anaerobic bacteria requires special media and growth conditions that contribute to a higher cost per identification than that for aerobic isolates. Newer rapid methods streamline the identification process, but confirmation to the species level is often difficult. The Presumpto Plate method for the identification of commonly encountered anaerobes consists of three quadrant plates, each containing four conventional media, that result in the generation of 21 test parameters: growth on Lombard-Dowell medium; production of indole, indole derivative, catalase, lecithinase, and lipase; proteolysis of milk, H2S, and esculin; growth on 20% bile; precipitate on bile; DNase, glucose, casein, starch, and gelatin hydrolysis; and fermentation of lactose, mannitol, and rhamnose. Identification charts were developed by using the results from 2,300 anaerobic isolates. Because conventional media were used, there was a high degree of agreement between the Presumpto Plate method and the reference method when testing commonly encountered anaerobes. The Presumpto Plate method is as accurate as commercially available enzyme systems for the identification of many anaerobic species but is less expensive to perform.

Bacteria, Anaerobic↗
PubMed1980

Effective treatment of hormonally-unresponsive metastatic carcinoma of the prostate with adriamycin and cyclophosphamide: methods of documenting tumor response and progression.

Combination chemotherapy with Adriamycin and cyclophosphamide was administered to 22 men with progressive tumor following hormonal treatment for metastatic carcinoma of the prostate. Objective partial response was documented in 7 patients (32%); an additional four (18%) had stable disease for a minimum of four months, and 11 (50%) were non-responders. Patients with partial response had a median survival of 14 months and lived significantly longer than those with no response (median five months); survival of men with stable disease approximated that of partial responders. Serial utilization of multiple staging procedures during chemotherapy demonstrated that although no single test allowed identification of all patients with objective tumor response or progression, improvement in median of five parameters could be documented in responding patients. In patients adequately studied at the time of disease progression, deterioration in a median of six tests was found. Serum acid phosphatase radionuclide bone scan, and plasma carcinoembryonic antigen were the most sensitive procedures which detected both objective tumor response and progression. Toxicity of chemotherapy was acceptable except in patients with prior radiation therapy. Administration of Adriamycin and cyclophosphamide was associated with clinical benefit in half of our patients with hormone-resistant prostatic cancer. Tumor response and progression can best be objectively assessed if several staging procedures are serially employed during treatment.

Aged↗
PubMed1992

Human cerebrospinal fluid protein database: edition 1992.

Two-dimensional electrophoresis maps of human cerebrospinal fluid proteins are presented in the form of labeled images. 931 protein spots are identified in spinal fluid from a normal volunteer. Distinct spots that represent variants of the same protein, especially posttranslational modifications, are estimated to reduce the 931 different spots to < 200 different proteins. 248 spots of 29 protein groups have been identified and are indicated on enlargements of specific gel regions. The distribution of protein abundance, mass, charge and shape characteristics of these normal 931 spinal fluid spots are graphically profiled. Analysis of the shape parameter "vertical height: width ratio" reveals that a ratio > 3.5 correlates with glycoproteins, enabling their identification simply by image analysis. Proteins that are not present on the normal map, but appear in spinal fluid in patients with schizophrenia and Creutzfeldt-Jakob disease are illustrated on additional maps.

Cerebrospinal Fluid Proteins↗
PubMed2003

Fluorescence activated cell sorting reveals heterogeneous and cell non-autonomous osteoprogenitor differentiation in fetal rat calvaria cell populations.

Identification of osteoblast progenitors, with defined developmental capacity, would facilitate studies on a variety of parameters of bone development. We used expression of alkaline phosphatase (ALP) and the parathyroid hormone/parathyroid hormone-related protein receptor (PTH1R) as osteoblast markers in dual-color fluorescence activated cell sorting (FACS) to fractionate rat calvaria (RC) cells into ALP(-)PTH1R(-), ALP(+)PTH1R(-), ALP(-)PTH1R(+), and ALP(+)PTH1R(+) populations. These fractionated populations were seeded clonally (n = 96) or over a range of cell densities ( approximately 150-8,500 cell/cm(2); n = 3). Our results indicate that colony forming unit-osteoblast (CFU-O)/bone nodule-forming cells are found in all fractions, but the frequency of CFU-O and total mineralized area is different across fractions. Analysis of these differences suggests that ALP(-)PTH1R(-), ALP(-)PTH1R(+), ALP(+)PTH1R(-), and ALP(+)PTH1R(+) cell populations are separated in order of increasing bone formation capacity. Dexamethasone (dex) differentially increased the CFU-O number in the four fractions, with the largest stimulation in the ALP(-) cell populations. However, there was no significant difference in the number or size distribution of CFU-F (fibroblast) colonies that formed in vehicle versus dex. Finally, both cell autonomous and cell non-autonomous (i.e., inhibitory/stimulatory effects of cell neighbors) differentiation of osteoprogenitors was seen. Only the ALP(-)PTH1R(-) population was capable of forming nodules at the clonal level, at approximately 3- or 12-times the predicted frequency of unfractionated populations in dex or vehicle, respectively. These data suggest that osteoprogenitors can be significantly enriched by fractionation of RC populations, that assay conditions modify the osteoprogenitor frequencies observed and that fractionation of osteogenic populations is useful for interrogation of their developmental status and osteogenic capacity.

Alkaline Phosphatase↗