[Forced delivery instead of postmortem cesarean section].

The Lex Regia stipulated that no pregnant women shall be buried unless the child has been removed from her womb. The post mortem caesarean delivery was upheld till 1861 by the majority of obstetricians but nevertheless, anterior to the XIXth century, in 1729, Delamotte practiced delivery in the agonising patient in the absence of labour in view to bypass the cesarean section in hope of better child survival. This article describes the beginning of forced ante mortem delivery upon post mortem cesarean section, which contributed to a decrease in child mortality.

[Medicinal leeches].

Leeches are hermaphroditic and hematophagous annelids. One important medical species, Hirudo medicinalis, comes from hirudiniculture of fresh water pools. Thanks to their three mandibles with some 300 teeth on their anterior muscular sucker, they easily grab to tissues and by secreting their saliva containing numerous powerful enzymes, such as hyaluronidase, collagenase and inhibitors of platelet aggregation and coagulation, like hirudin, allow blood sucking.

Improving QSAR models for the biological activity of HIV Reverse Transcriptase inhibitors: Aspects of outlier detection and uninformative variable elimination.

The goal of this study is to derive a methodology for modeling the biological activity of non-nucleoside HIV Reverse Transcriptase (RT) inhibitors. The difficulties that were encountered during the modeling attempts are discussed, together with their origin and solutions. With the selected multivariate techniques: robust principal component analysis, partial least squares, robust partial least squares and uninformative variable elimination partial least squares, it is possible to explore and to model the contaminated data satisfactory.

Determination of total antioxidant capacity in green tea by near-infrared spectroscopy and multivariate calibration.

A principal component regression (PCR) model is built for prediction of total antioxidant capacity in green tea using near-infrared (NIR) spectroscopy. The modelling procedures are systematically studied with the focus on outlier detection. Different outlier detection methods are used and compared.

A journey into low-dimensional spaces with autoassociative neural networks.

The compression and the visualization of the data have been always a subject of a great deal of excitement. Since multidimensional data sets are difficult to interpret and visualize, much of the attention is drawn how to compress them efficiently. Usually, the compression of dimensionality is considered as the first step of exploratory data analysis.

Pattern recognition techniques screening for drugs of abuse with gas chromatography-Fourier transform infrared spectroscopy.

As many drugs of abuse are relatively volatile substances, gas chromatography-mass spectrometry (GC-MS), and more recently gas chromatography-Fourier transform infrared spectroscopy (GC-FTIR) became the most powerful techniques applied for their identification. We are presenting a combination of pattern recognition techniques discriminating illicit amphetamines according to the substitution pattern associated with the psychotropic activity (stimulants and hallucinogens) for which they are abused, and with the corresponding level of health hazard. As we determined, GC-FTIR provides the best selectivity in identifying the structural features associated with the full constellation of pharmacological effects of amphetamines.

Identification of novel illicit amphetamines from vapor-phase FTIR spectra - a chemometrical solution.

A computer-aided procedure automating the identification of illicit amphetamine analogs eluting from a gas chromatograph coupled to a Fourier transform infrared spectrometer is presented. The expert system discriminates novel amphetamines from other classes of drugs of abuse normally screened in illicit tablets or powders. The main analytical advantages of the system over the automated procedures dedicated to general unknown analysis are the objectivity and the accuracy in predicting the class identity of the compound (i.

Application of neural network calibrations to an halide ISE array.

The Neural Network (NN) technique was applied to the calibration of an ion selective electrode (ISE) array comprising a bromide selective electrode, two chloride ISEs and one thiocyanate ISE. The measured samples were synthetic mixture solutions of chlorides and bromides in concentration ranges such that interference occurs. The NN method allowed to perform the calibration without estimating the coefficients of the Nikolskii-Eisenman theoretical relation.

The application of Kohonen neural networks to diagnose calibration problems in atomic absorption spectrometry.

In atomic absorption spectrometric measurements calibration lines are measured daily. These lines are not always acceptable. They can, for instance, contain outliers, have a bad precision or can be curved.

Halide ion-selective electrode array calibration.

The calibration of several ions (Cl(-), Br(-), F(-) and OH(-)) measured with an ion selective electrodes (ISE) array has been carried out in the presence of interferents using an experimental design and multivariate calibration methods. Partial least squares regression and principal component regression do not seem to improve the test set prediction compared to multivariate linear regression. In the case of very slight or no interference on the ISE, each ion can be determined using the corresponding ISE and univariate calibration methods, but the use of multivariate methods does not lead to worse results.

Odour perception in relation to age, general health, anthropometry and dental state.

Considering the possible role of age-related phenomena such as general health, dental health and nutrition in odour perception, their joint effect on variability in odour perception was evaluated in the present study. A total of 171 apparently healthy adults with a mean age of 66.0 years (S.

Updating multivariate calibrations with the delaunay triangulation method.

Multivariate calibrations must be updated when new samples show different spectral characteristics. In this paper, we discuss how to do this when the calibration is performed with a topological multivariate calibration method based on Delaunay triangulation (DT). The updating leads either to the expansion of the original calibration set or to the creation of a new local model.

Local factor analysis of rank-deficient reaction systems.

The analysis of spectral measurement data sets using local factor analysis (LFA) requires the rank of the sub-matrix under study to be equal to the number of absorbing species present in the associated sub-system. However, because of mass balance or kinetic constraints, LFA will fail if local rank deficiency occurs. A local rank deficiency sub-system may be present in a global full-rank reaction system or a rank-deficient one.

Near-infrared spectroscopy applications in pharmaceutical analysis.

Near-infrared (NIR) spectroscopy is a fast and non-destructive analytical technique that offers many advantages for a broad range of industrial applications. In this work, we reviewed recent developments in the pharmaceutical domain where it can be applied from raw material identification to final product release. The characteristics of NIR allow the technique to be implemented as a process analytical technology (PAT).

Direct orthogonal signal correction as data pretreatment in the classification of clinical lots of creams from near infrared spectroscopy data.

Direct orthogonal signal correction (DOSC) is applied to correct for major variance sources such as temperature effects, time influences and instrumental differences in near infrared (NIR) data. The samples analysed are creams containing different concentrations of an active drug. The final aim is to classify the samples according to their concentration of active compound.

Chemometric analysis of soil pollution data using the Tucker N-way method.

N-way methods, particularly the Tucker method, are often the methods of choice when analyzing data sets arranged in three- (or higher) way arrays, which is the case for most environmental data sets. In the future, applying N-way methods will become an increasingly popular way to uncover hidden information in complex data sets. The reason for this is that classical two-way approaches such as principal component analysis are not as good at revealing the complex relationships present in data sets.

Class identity assignment for amphetamines using neural networks and GC-FTIR data.

An exploratory analysis was performed in order to evaluate the feasibility of building of neural network (NN) systems automating the identification of amphetamines necessary in the investigation of drugs of abuse for epidemiological, clinical and forensic purposes. A first neural network system was built to distinguish between amphetamines and nonamphetamines. A second, more refined system, aimed to the recognition of amphetamines according to their toxicological activity (stimulant amphetamines, hallucinogenic amphetamines, nonamphetamines).

Chemometric treatment of vanillin fingerprint chromatograms. Effect of different signal alignments on principal component analysis plots.

This study describes the chemometric treatment of vanillin fingerprint chromatograms to distinguish vanillin from different sources. Prior to principal component analysis, which is used to discriminate vanillin from different origins, the fingerprints are aligned. Three alignment algorithms are tested, correlation optimized warping (COW), target peak alignment (TPA) and semi-parametric time warping (STW).

Evaluation of chemometric techniques to select orthogonal chromatographic systems.

Several chemometric techniques were compared for their performance to determine the orthogonality and similarity between chromatographic systems. Pearson's correlation coefficient (r) based color maps earlier were used to indicate selectivity differences between systems. These maps, in which the systems were ranked according to decreasing or increasing dissimilarities observed in the weighted-average-linkage dendrogram, were now applied as reference method.

Prediction of total green tea antioxidant capacity from chromatograms by multivariate modeling.

In this paper, a fast strategy for determining the total antioxidant capacity of Chinese green tea extracts is developed. This strategy includes the use of experimental techniques, such as fast high-performance liquid chromatography (HPLC) on monolithic columns and a spectrophotometric approach to determine the total antioxidant capacity of the extracts. To extract the chemically relevant information from the obtained data, chemometrical approaches are used.

Automatic program for peak detection and deconvolution of multi-overlapped chromatographic signals part II: peak model and deconvolution algorithms.

Several interlinked algorithms for peak deconvolution by non-linear regression are presented. These procedures, together with the peak detection methods outlined in Part I, have allowed the implementation of an automatic method able to process multi-overlapped signals, requiring little user interaction. A criterion based on the evaluation of the multivariate selectivity of the chromatographic signal is used to auto-select the most efficient deconvolution procedure for each chromatographic situation.

Automatic program for peak detection and deconvolution of multi-overlapped chromatographic signals part I: peak detection.

A series of two papers describing a procedure for automated peak deconvolution is presented. The goal is to develop a package of routines that can be used by non-experienced users. Part I (this paper) concerns peak detection, whereas Part II is dedicated to the deconvolution itself.

Strategy for the chiral separation of non-acidic pharmaceuticals using capillary electrochromatography.

In completion of an earlier defined generic chiral screening approach, a generic separation strategy for basic, bifunctional, and neutral compounds was proposed and evaluated. This strategy adds to a previously defined strategy for acidic compounds. The screening experiment of the actual strategy used a mobile phase of 5 mM phosphate buffer pH 11.

Development of a ginkgo biloba fingerprint chromatogram with UV and evaporative light scattering detection and optimization of the evaporative light scattering detector operating conditions.

A fingerprint chromatogram of a standardized Ginkgo biloba extract is developed on a monolithic silica column using a ternary gradient containing water, iso-propanol and tetrahydrofuran. For the detection, UV and evaporative light scattering (ELS) detectors are used, the latter allowing detection of the poor UV absorbing compounds as ginkgolides (A-C and J) and bilobalide in the extract. The complementary information between the UV and ELS fingerprint is evaluated.