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PubMed2002

Conformational analysis: a new approach by means of chemometrics.

In conformational analysis, the systematic search method completely maps the space but suffers from the combinatorial explosion problem because the number of conformations increases exponentially with the number of free rotation angles. This study introduces a new methodology of conformational analysis that controls the combinatorial explosion. It is based on a dimensional reduction of the system through the use of principal component analysis. The results are exactly the same as those obtained for the complete search but, in this case, the number of conformations increases only quadratically with the number of free rotation angles. The method is applied to a series of three drugs: omeprazole, pantoprazole, lansoprazole-benzimidazoles that suppress gastric-acid secretion by means of H+, K+-ATPase enzyme inhibition.

2-Pyridinylmethylsulfinylbenzimidazoles↗

PubMed2003

Machine learning approaches to lung cancer prediction from mass spectra.

We addressed the problem of discriminating between 24 diseased and 17 healthy specimens on the basis of protein mass spectra. To prepare the data, we performed mass to charge ratio (m/z) normalization, baseline elimination, and conversion of absolute peak height measures to height ratios. After preprocessing, the major difficulty encountered was the extremely large number of variables (1676 m/z values) versus the number of examples (41). Dimensionality reduction was treated as an integral part of the classification process; variable selection was coupled with model construction in a single ten-fold cross-validation loop. We explored different experimental setups involving two peak height representations, two variable selection methods, and six induction algorithms, all on both the original 1676-mass data set and on a prescreened 124-mass data set. Highest predictive accuracies (1-2 off-sample misclassifications) were achieved by a multilayer perceptron and Naïve Bayes, with the latter displaying more consistent performance (hence greater reliability) over varying experimental conditions. We attempted to identify the most discriminant peaks (proteins) on the basis of scores assigned by the two variable selection methods and by neural network based sensitivity analysis. These three scoring schemes consistently ranked four peaks as the most relevant discriminators: 11683, 1403, 17350 and 66107.

Algorithms↗

PubMed1996

Tobacco smoke upper respiratory response relationships in healthy nonsmokers.

This study determined exposure-response relationships to side-stream tobacco smoke (2 hrs; 0, 1, 5, and 15 ppm CO) in 29 healthy nonsmoking young adults. Sixteen subjects had no history of environmental tobacco smoke rhinitis (ETS-NS) while 13 subjects had a history of ETS rhinitis (ETS-S). Eye irritation and odor perception showed a statistically significant exposure response in both groups; headache was significant in ETS-S and nose irritation was significant in ETS-NS subjects. Significant postexposure (P1) symptoms were first reported at 1 ppm CO among both groups, but in 3/9 symptoms were significantly greater at this exposure level in ETS-S subjects. Nasal congestion, rhinorrhea, and cough increased significantly at 15 ppm CO only. In ETS-S subjects, nasal volume decreased and nasal resistance increased in an exposure-response fashion. ETS-NS subjects had a qualitatively different shape to the exposure-response curve; significant dimensional reductions in mid- and posterior nasal volume occurred with exposure at 1 ppm CO but not at 5 ppm CO and reductions in posterior nasal volume occurred at 15 ppm CO exposure. These studies indicate subjective and objective response relationships with exposure to sidestream tobacco smoke at concentrations from 1 to 15 ppm CO. Some differences are noted among the two subject groups in the magnitude of some symptoms at the lowest exposure level and in the qualitative shape of the acoustic rhinometry and nasal resistance exposure-response curves.

Adult↗

PubMed1988

Auto-association by multilayer perceptrons and singular value decomposition.

The multilayer perceptron, when working in auto-association mode, is sometimes considered as an interesting candidate to perform data compression or dimensionality reduction of the feature space in information processing applications. The present paper shows that, for auto-association, the nonlinearities of the hidden units are useless and that the optimal parameter values can be derived directly by purely linear techniques relying on singular value decomposition and low rank matrix approximation, similar in spirit to the well-known Karhunen-Loève transform. This approach appears thus as an efficient alternative to the general error back-propagation algorithm commonly used for training multilayer perceptrons. Moreover, it also gives a clear interpretation of the rôle of the different parameters.

Mathematics↗

PubMed1993

Time-course of recovery of atrial contraction after cardioversion of chronic atrial fibrillation.

We aimed to study the time-course of recovery of atrial contraction after cardioversion of chronic atrial fibrillation (duration of more than 3 months) to sinus rhythm. Using M-mode, two-dimensional and pulsed Doppler echocardiography, we determined left atrial (LA) and ventricular (LV) dimensions, peak velocities, and velocity-time integrals of early and atrial filling velocity-time profiles in both LV and right ventricular (RV) inflows (peak E and peak A, Ea and Aa). Results of the LA and LV functions in seven elderly patients (an initial study group) were as follows. The extent of the LA dimensional reduction resulting from atrial contraction was significantly increased up to 5-8 weeks compared with values 0-1 day after cardioversion [from 1.3 +/- 0.8 (mean +/- SD) mm to 3.9 +/- 1.1, P < 0.01]. In conjunction with the progressive increase in peak A, the ratio of peak E to peak A (peak E/A) was significantly decreased and reached a plateau at 5-8 weeks (from 1.93 +/- 0.59 to 0.67 +/- 0.11, P < 0.01). LV fractional shortening was increased significantly 5-8 weeks after cardioversion (from 0.20 +/- 0.06 to 0.29 +/- 0.05, P < 0.01). Since a large part of the improvement in LA contraction was expected to occur in an early stage after cardioversion, we studied eight additional patients more frequently in the early stage (an additional study group). Furthermore, we studied the time course of LA and right atrial (RA) contractions.(ABSTRACT TRUNCATED AT 250 WORDS)

Aged↗

PubMed2000

Characterisation of three-dimensional anatomic shapes using principal components: application to the proximal tibia.

The objective of the research is to determine if principal component analysis (PCA) provides an efficient method to characterise the normative shape of the proximal tibia. Bone surface data, converted to analytical surface descriptions, are aligned, and an auto-associative memory matrix is generated. A limited subset of the matrix principal components is used to reconstruct the bone surfaces, and the reconstruction error is assessed. Surface reconstructions based on just six (of 1452) principal components have a mean root-mean-square (RMS) reconstruction error of 1.05% of the mean maximum radial distance at the tibial plateau. Surface reconstruction of bones not included in the auto-associative memory matrix have a mean RMS error of 2.90%. The first principal component represents the average shape of the sample population. Addition of subsequent principal components represents the shape variations most prevalent in the sample and can be visualised in a geometrically meaningful manner. PCA offers an efficient method to characterise the normative shape of the proximal tibia with a high degree of dimensionality reduction.

Adult↗

PubMed2004

[Therapy of unstable sacrum fractures in pelvic ring fractures with dorsal sacrum distraction osteosynthesis].

Unstable pelvic ring injuries AO type C ("vertical shear") with a fractured sacrum are treated operatively in less than 50% of the cases (DGU pelvis study group). Furthermore, only 12% of these ORIF involve the sacrum bone itself. No specific technique has gained wide acceptance in treating transsacral instability. In accordance with earlier publications (Käch, Josten) suggesting an internal fixator, we developed the dorsal sacrum fracture distantly anchored ORIF (DSDO). This procedure closes the dorsal pelvic ring by joining the two dorsal iliac crests (fixed-angle screws inserted in the posterior superior iliac spine) and additionally anchors in a lumbar pedicle. Thus, a three-dimensional reduction and stable fixation device with optional local nerve decompression and even plating possibility is achieved. Between January 1996 and July 2001, 35 unstable sacrum disruptions were treated with DSDO in 180 patients operated for pelvic trauma. This allowed immediate mobilization in all cases. The radiologic follow-up examination ( n=20) revealed a solid union in all patients. Complications focused on management of the soft tissue degloving injury (Morel-Lavalleé lesion), which needs special attention.

Adolescent↗

PubMed2002

Multidimensional analysis of the concentrations of 17 substances in the CSF of schizophrenics and controls.

The concentrations of 17 substances were determined in the cerebrospinal fluid (CSF) of 28 paranoid schizophrenic patients and 16 controls. Results were standardized and simultaneously evaluated through Multidimensional Scaling (MDS). The full data set can be considered as a cloud of points consisting of the 44 subjects in the 17-dimensional parameter space. MDS seeks a two-dimensional representation of this 17-dimensional cloud of points, while retaining as much as possible the distances between the subjects. The two-dimensional reduction of the 17 CSF parameters correctly separated 15 of 16 controls from the schizophrenic subjects. This indicates that a biological heterogeneity between schizophrenic and nonschizophrenic subjects can be detected by the simultaneous analysis of the CSF concentrations of substances related directly or indirectly to the neuronal activity in the brain.

Adult↗

PubMed1985

Multidimensional analysis of the concentrations of 17 substances in the CSF of schizophrenics and controls.

Adult↗

PubMed2026

An Integrated Machine Learning and Genomic Framework for Precise Detection of Gastric Cancer.

This study presents a novel integrative approach for the analysis of high-dimensional gene expression data, leveraging the complementary strengths of unsupervised clustering and supervised classification. Using K-means clustering, the data set is stratified into three distinct clusters, revealing intrinsic biological patterns and relationships. The resulting cluster assignments are subsequently used as pseudolabels to train machine learning models, including support vector machines, random forest, and a stacking ensemble classifier. To validate and enhance the robustness of clustering, complementary methods, such as hierarchical clustering and density-based spatial clustering of applications with noise (DBSCAN), are used, with results visualized through principal component analysis-driven dimensionality reduction. The high predictive accuracy achieved by the classifiers underlines the separability and reliability of the identified clusters. Furthermore, feature importance analysis highlighted key genetic determinants within each cluster, offering actionable insights into potential biomarkers and critical genomic features. This framework bridges the gap between exploratory unsupervised learning and predictive supervised modeling, providing a scalable and interpretable method for analyzing complex genomic data sets. Its applicability extends to biomarker discovery, patient stratification, and other precision medicine applications, emphasizing its utility in advancing genomic research and clinical practice.

Humans↗

PubMed2026

Methylome Profiling of Cartilage Tumors: A Promising New Diagnostic Tool?

DNA methylation and copy number variation (CNV) profiling has emerged as a promising tool for the classification of bone and soft tissue tumors. We evaluated its utility in cartilage tumors, where distinguishing low-grade from high-grade conventional central chondrosarcomas (CSs) and atypical cartilaginous tumors (ACTs) from enchondromas (ECs) is a frequent diagnostic challenge, particularly on biopsy material. We analyzed 214 chondrogenic tumors, including ECs, ACTs, conventional CSs, dedifferentiated chondrosarcomas (DDCSs), and clear cell CSs, and determined their IDH1/2 mutation status. Unsupervised dimensionality reduction of genome-wide DNA methylation patterns revealed 4 clusters among IDH-mutant (MUT) tumors (IDH-MUT-1: mostly ECs and ACTs and some high-grade CSs; IDH-MUT-2: predominantly high-grade CSs; IDH-MUT-3: largely DDCSs; and IDH-MUT-SB: distinct skull base group with a markedly different methylation pattern) and 2 clusters among IDH-wild-type (WT) tumors (IDH-WT-1 and IDH-WT-2: both primarily high-grade CSs, with IDH-WT-2 showing higher tumor grade and more extensive CNVs). Clear cell CSs formed a separate cluster. The amount of CNVs, including loss of CDKN2A, increased with tumor grade, reflecting increased genomic instability during chondrosarcoma progression. Supervised classifiers trained separately, both on methylation and CNV data, and distinguished low-grade and high-grade cartilaginous tumors with area under the curve values of 0.87 to 0.97 and 85% to 90% accuracy. Furthermore, we tested whether DDCSs can be distinguished from metastatic carcinomas and other high-grade sarcomas of the bone. Across 246 reference samples, a supervised classifier achieved 97.2% accuracy (area under the curve, 99.8%) and correctly identified 30 of 32 DDCSs (93.8%). These results indicate that DNA methylation and CNV data analysis provide a valuable tool for distinguishing most low- and high-grade CSs, with additional utility also in differentiating DDCS from morphologic mimics.

cartilaginous tumors↗

PubMedDate not supplied

Dynamics of influenza A drift: the linear three-strain model.

We analyze an epidemiological model consisting of a linear chain of three cocirculating influenza A strains that provide hosts exposed to a given strain with partial immune cross-protection against other strains. In the extreme case where infection with the middle strain prevents further infections from the other two strains, we reduce the model to a six-dimensional kernel capable of showing self-sustaining oscillations at relatively high levels of cross-protection. Dimensional reduction has been accomplished by a transformation of variables that preserves the eigenvalue responsible for the transition from damped oscillations to limit cycle solutions.

Antigenic Variation↗

PubMed2000

Picture recognition in animals and humans.

The question of object-picture recognition has received relatively little attention in both human and comparative psychology; a paradoxical situation given the important use of image technology (e. g. slides, digitised pictures) made by neuroscientists in their experimental investigation of visual cognition. The present review examines the relevant literature pertaining to the question of the correspondence between and/or equivalence of real objects and their pictorial representations in animals and humans. Two classes of reactions towards pictures will be considered in turn: acquired responses in picture recognition experiments and spontaneous responses to pictures of biologically relevant objects (e.g. prey or conspecifics). Our survey will lead to the conclusion that humans show evidence of picture recognition from an early age; this recognition is, however, facilitated by prior exposure to pictures. This same exposure or training effect appears also to be necessary in nonhuman primates as well as in other mammals and in birds. Other factors are also identified as playing a role in the acquired responses to pictures: familiarity with and nature of the stimulus objects, presence of motion in the image, etc. Spontaneous and adapted reactions to pictures are a wide phenomenon present in different phyla including invertebrates but in most instances, this phenomenon is more likely to express confusion between objects and pictures than discrimination and active correspondence between the two. Finally, given the nature of a picture (e.g. bi-dimensionality, reduction of cues related to depth), it is suggested that object-picture recognition be envisioned in various levels, with true equivalence being a limited case, rarely observed in the behaviour of animals and even humans.

Animals↗

PubMed1979

Application of pattern recognition and feature extraction techniques to volatile constituent metabolic profiles obtained by capillary gas chromatography.

The applicability of threshold logic units, a form of nonparametric pattern recognition, to the processing of metabolic profile data obtained by high-efficiency glass capillary column gas chromatography has been investigated. The test data included profiles of the volatile constituents of urine from normal individuals and from individuals with diabetes mellitus. A feature extraction algorithm allowed for dimensionality reduction and indicated the constituents most important in the normal versus pathological distinction. With an optimum number of dimensions, a normal versus pathological prediction rate of 93.75% was achieved. Gas chromatography-mass spectrometry was utilized to identify important profile constituents.

Chromatography, Gas↗

PubMedDate not supplied

Data visualisation and manifold mapping using the ViSOM.

The self-organising map (SOM) has been successfully employed as a nonparametric method for dimensionality reduction and data visualisation. However, for visualisation the SOM requires a colouring scheme to imprint the distances between neurons so that the clustering and boundaries can be seen. Even though the distributions of the data and structures of the clusters are not faithfully portrayed on the map. Recently an extended SOM, called the visualisation-induced SOM (ViSOM) has been proposed to directly preserve the distance information on the map, along with the topology. The ViSOM constrains the lateral contraction forces between neurons and hence regularises the interneuron distances so that distances between neurons in the data space are in proportion to those in the map space. This paper shows that it produces a smooth and graded mesh in the data space and captures the nonlinear manifold of the data. The relationships between the ViSOM and the principal curve/surface are analysed. The ViSOM represents a discrete principal curve or surface and is a natural algorithm for obtaining principal curves/surfaces. Guidelines for applying the ViSOM constraint and setting the resolution parameter are also provided, together with experimental results and comparisons with the SOM, Sammon mapping and principal curve methods.

Algorithms↗

PubMed2003

The information content of receptive fields.

The nervous system must observe a complex world and produce appropriate, sometimes complex, behavioral responses. In contrast to this complexity, neural responses are often characterized through very simple descriptions such as receptive fields or tuning curves. Do these characterizations adequately reflect the true dimensionality reduction that takes place in the nervous system, or are they merely convenient oversimplifications? Here we address this question for the target-selective descending neurons (TSDNs) of the dragonfly. Using extracellular multielectrode recordings of a population of TSDNs, we quantify the completeness of the receptive field description of these cells and conclude that the information in independent instantaneous position and velocity receptive fields accounts for 70%-90% of the total information in single spikes. Thus, we demonstrate that this simple receptive field model is close to a complete description of the features in the stimulus that evoke TSDN response.

Action Potentials↗

PubMed2002

An ischemia detection method based on artificial neural networks.

An automated technique was developed for the detection of ischemic episodes in long duration electrocardiographic (ECG) recordings that employs an artificial neural network. In order to train the network for beat classification, a cardiac beat dataset was constructed based on recordings from the European Society of Cardiology (ESC) ST-T database. The network was trained using a Bayesian regularisation method. The raw ECG signal containing the ST segment and the T wave of each beat were the inputs to the beat classification system and the output was the classification of the beat. The input to the network was produced through a principal component analysis (PCA) to achieve dimensionality reduction. The network performance in beat classification was tested on the cardiac beat database providing 90% sensitivity (Se) and 90% specificity (Sp). The neural beat classifier is integrated in a four-stage procedure for ischemic episode detection. The whole system was evaluated on the ESC ST-T database. When aggregate gross statistics was used the Se was 90% and the positive predictive accuracy (PPA) 89%. When aggregate average statistics was used the Se became 86% and the PPA 87%. These results are better than other reported.

Automation↗

PubMed2001

Stepping out of the box: information processing in the neural networks of the basal ganglia.

The Albin-DeLong 'box and arrow' model has long been the accepted standard model for the basal ganglia network. However, advances in physiological and anatomical research have enabled a more detailed neural network approach. Recent computational models hold that the basal ganglia use reinforcement signals and local competitive learning rules to reduce the dimensionality of sparse cortical information. These models predict a steady-state situation with diminished efficacy of lateral inhibition and low synchronization. In this framework, Parkinson's disease can be characterized as a persistent state of negative reinforcement, inefficient dimensionality reduction, and abnormally synchronized basal ganglia activity.

Animals↗