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Biomedical subjects

G Palm

Publications and source records attributed to G Palm.

At least 19 recordsLinked to original sources
PubMed2006

Pelvicaliceal biomodeling as an aid to achieving optimal access in percutaneous nephrolithotripsy.

PURPOSE: To investigate prospectively the benefits of three-dimensional stereolithographic biomodeling produced from CT data as an aid to achieving optimal access for percutaneous nephrolithotripsy (PCNL). PATIENTS AND METHODS: Eight patients with complex urinary calculi were selected. Multislice CT scans of the kidney in native and excretory phases were acquired with the patient in the prone position to simulate the position during surgery. Contiguous reconstructed slices were produced from the data volume. The data of interest were processed to transform them into a format acceptable for production of a biomodel. Exact plastic replicas of the pelvicaliceal system and the calculi were created and used for morphologic assessment, preoperative planning, patient education, and surgical navigation. RESULTS: The survey results were based on subjective opinions rather than objective data. The biomodels enhanced the ability to visualize a patient's unique anatomy before surgery. This aided the planning and rehearsal of endourologic procedures. CONCLUSION: Although this study is only a preliminary investigation, we postulate that biomodeling has the advantage of allowing imaging data to be displayed in a physical form. In difficult cases, this technique may improve treatment, operative planning, and communication with colleagues and patients. The limitations of the technology include the manufacturing time and cost, but more accurate puncture-site selection may reduce costs by saving operating time.

Adult↗
PubMed2001

Three learning phases for radial-basis-function networks.

In this paper, learning algorithms for radial basis function (RBF) networks are discussed. Whereas multilayer perceptrons (MLP) are typically trained with backpropagation algorithms, starting the training procedure with a random initialization of the MLP's parameters, an RBF network may be trained in many different ways. We categorize these RBF training methods into one-, two-, and three-phase learning schemes. Two-phase RBF learning is a very common learning scheme. The two layers of an RBF network are learnt separately; first the RBF layer is trained, including the adaptation of centers and scaling parameters, and then the weights of the output layer are adapted. RBF centers may be trained by clustering, vector quantization and classification tree algorithms, and the output layer by supervised learning (through gradient descent or pseudo inverse solution). Results from numerical experiments of RBF classifiers trained by two-phase learning are presented in three completely different pattern recognition applications: (a) the classification of 3D visual objects; (b) the recognition hand-written digits (2D objects); and (c) the categorization of high-resolution electrocardiograms given as a time series (ID objects) and as a set of features extracted from these time series. In these applications, it can be observed that the performance of RBF classifiers trained with two-phase learning can be improved through a third backpropagation-like training phase of the RBF network, adapting the whole set of parameters (RBF centers, scaling parameters, and output layer weights) simultaneously. This, we call three-phase learning in RBF networks. A practical advantage of two- and three-phase learning in RBF networks is the possibility to use unlabeled training data for the first training phase. Support vector (SV) learning in RBF networks is a different learning approach. SV learning can be considered, in this context of learning, as a special type of one-phase learning, where only the output layer weights of the RBF network are calculated, and the RBF centers are restricted to be a subset of the training data. Numerical experiments with several classifier schemes including k-nearest-neighbor, learning vector quantization and RBF classifiers trained through two-phase, three-phase and support vector learning are given. The performance of the RBF classifiers trained through SV learning and three-phase learning are superior to the results of two-phase learning, but SV learning often leads to complex network structures, since the number of support vectors is not a small fraction of the total number of data points.

Algorithms↗
PubMed2001

Structures of two highly homologous bacterial L-asparaginases: a case of enantiomorphic space groups.

Quasi-enantiomorphic crystals of the Y25F mutant of Escherichia coli L-asparaginase and of the native Erwinia chrysanthemi L-asparaginase were obtained in the hexagonal space groups P6(5)22 and P6(1)22, respectively. The structures of these highly homologous enzymes were solved by molecular replacement and were refined with data extending to 2.2-2.5 A. These structures were compared with each other, as well as with other L-asparaginase structures previously observed with different crystal packing. It is concluded that the observed phenomenon, which is rare, was most likely to have arisen by chance.

Amino Acid Sequence↗
PubMed1999

Direct visualization of HIV-1 entry: mechanisms and role of cell surface receptors.

Highly fluorescent virions of T- and M-tropic HIV-1 strains were obtained by incorporation of the viral accessory protein Vpr, fused to the green fluorescent protein, in trans. The fluorescent virions displayed normal morphology, were infectious, and could be used for direct visualization of HIV-1 attachment and trafficking in various cell lines. More than 90% of the viral particles were found to enter the cells by direct membrane fusion in T-cells, CD4+ HeLa cells, and macrophages. Visualizing HIV-1 attachment and entry in the absence or presence of CD4 and/or the appropriate coreceptors indicated that CD4 is the major receptor for virus attachment in the case of JR-CSF and NL-4-3 HIV-1 isolates; however, the coreceptors are required for membrane fusion. Internalization of the coreceptor CXCR4 inhibited entry, but did not prevent virus binding suggesting that transient downregulation of the coreceptor(s) may not be the most efficient way of blocking HIV infection in vivo.

CD4 Antigens↗
PubMed1999

Dynamical cluster analysis of cortical fMRI activation.

Localized changes in cortical blood oxygenation during voluntary movements were examined with functional magnetic resonance imaging (fMRI) and evaluated with a new dynamical cluster analysis (DCA) method. fMRI was performed during finger movements with eight subjects on a 1.5-T scanner using single-slice echo planar imaging with a 107-ms repetition time. Clustering based on similarity of the detailed signal time courses requires besides the used distance measure no assumptions about spatial location and extension of activation sites or the shape of the expected activation time course. We discuss the basic requirements on a clustering algorithm for fMRI data. It is shown that with respect to easy adjustment of the quantization error and reproducibility of the results DCA outperforms the standard k-means algorithm. In contrast to currently used clustering methods for fMRI, like k-means or fuzzy k-means, DCA extracts the appropriate number and initial shapes of representative signal time courses from data properties during run time. With DCA we simultaneously calculate a two-dimensional projection of cluster centers (MDS) and data points for online visualization of the results. We describe the new DCA method and show for the well-studied motor task that it detects cortical activation loci and provides additional information by discriminating different shapes and phases of hemodynamic responses. Robustness of activity detection is demonstrated with respect to repeated DCA runs and effects of different data preprocessing are shown. As an example of how DCA enables further analysis we examined activation onset times. In areas SMA, M1, and S1 simultaneous and sequential activation (in the given order) was found.

Cerebral Cortex↗
PubMed1998

Synaptic delay learning in pulse-coupled neurons.

We present rules for the unsupervised learning of coincidence between excitatory postsynaptic potentials (EPSPs) by the adjustment of postsynaptic delays between the transmitter binding and the opening of ion channels. Starting from a gradient descent scheme, we develop a robust and more biological threshold rule by which EPSPs from different synapses can be gradually pulled into coincidence. The synaptic delay changes are determined from the summed potential--at the site where the coincidence is to be established--and from postulated synaptic learning functions that accompany the individual EPSPs. According to our scheme, templates for the detection of spatiotemporal patterns of synaptic activation can be learned, which is demonstrated by computer simulation. Finally, we discuss possible relations to biological mechanisms.

Excitatory Postsynaptic Potentials↗
PubMed1995

Detecting higher-order interactions among the spiking events in a group of neurons.

We propose a formal framework for the description of interactions among groups of neurons. This framework is not restricted to the common case of pair interactions, but also incorporates higher-order interactions, which cannot be reduced to lower-order ones. We derive quantitative measures to detect the presence of such interactions in experimental data, by statistical analysis of the frequency distribution of higher-order correlations in multiple neuron spike train data. Our first step is to represent a frequency distribution as a Markov field on the minimal graph it induces. We then show the invariance of this graph with regard to changes of state. Clearly, only linear Markov fields can be adequately represented by graphs. Higher-order interdependencies, which are reflected by the energy expansion of the distribution, require more complex graphical schemes, like constellations or assembly diagrams, which we introduce and discuss. The coefficients of the energy expansion not only point to the interactions among neurons but are also a measure of their strength. We investigate the statistical meaning of detected interactions in an information theoretic sense and propose minimum relative entropy approximations as null hypotheses for significance tests. We demonstrate the various steps of our method in the situation of an empirical frequency distribution on six neurons, extracted from data on simultaneous multineuron recordings from the frontal cortex of a behaving monkey and close with a brief outlook on future work.

Action Potentials↗
PubMed1994

Molecular characterization of native and recombinant apolipoprotein A-IMilano dimer. The introduction of an interchain disulfide bridge remarkably alters the physicochemical properties of apolipoprotein A-I.

The disulfide-linked dimer of apolipoprotein A-IMilano (A-IM/A-IM), a natural Arg173-->Cys variant of apoA-I, was purified from carriers' plasma and produced in Escherichia coli. The recombinant A-IM/A-IM is identical to native A-IM/A-IM, by mass spectrometry, SDS-polyacrylamide gel electrophoresis, and isoelectric focusing. Lipid-free A-IM/A-IM undergoes concentration-dependent self-association similar to apoA-I, but at all concentrations apoA-I is more self-associated than A-IM/A-IM. Far-ultraviolet CD spectra of A-IM/A-IM reveal a highly alpha-helical structure predicted to be approximately 65% in the lipid-free and approximately 78% in the lipid-associated states, versus 43 and 73% for apoA-I. A significant loss of alpha-helix occurs below pH 3.5 and above pH 10 in both apoA-I and A-IM/A-IM; A-IM/A-IM constantly shows a higher alpha-helical content than apoA-I over the entire pH range (1.7-12.8), suggesting that hydrophobic forces stabilize the interaction between the two A-IM chains. Indeed, and differently from apoA-I, the alpha-helical content of A-IM/A-IM is minimally affected by solvent ionic strength. The aromatic side chains in both lipid-free and lipid-bound A-IM/A-IM are immobilized in a more asymmetric and hydrophobic environment than in lipid-free apoA-I, the conformation of A-IM/A-IM being instead similar to that achieved by apoA-I following interaction with lipids. The present findings prove that rA-IM/A-IM is structurally identical to the native protein; the conformation of A-IM/A-IM is remarkably different from that of apoA-I, thus possibly explaining some of the peculiar functional properties of the apoA-IMilano dimer.

Amino Acid Sequence↗
PubMed1992

Disulfide exchange folding of insulin-like growth factor I.

The disulfide exchange folding properties of insulin-like growth factor I (IGF-I) have been analyzed in a redox buffer containing reduced (10 mM) and oxidized (1 mM) glutathione. Under these conditions, the 3 disulfide bridges of the 70 amino acid peptide were not quantitatively formed. Instead, five major forms of IGF-I were detected, and these components were concluded to be in equilibrium as their relative amounts were similar starting from either reduced, native, or a mismatched variant of IGF-I containing two non-native disulfides. The different components in the mixtures were trapped by thiol alkylation using vinylpyridine and subsequently isolated by reverse-phase HPLC. The purified variants were further characterized using plasma desorption mass spectrometry and peptide mapping. Two of the five different forms were identified as native and mismatched IGF-I. One form was a variant with only one disulfide bond, and the other two major components had two disulfides formed. In a separate experiment, early refolding intermediates were trapped by pyridylethylation after only 90 s of refolding in the glutathione buffer, starting from reduced IGF-I. The intermediates were identical to the components observed at equilibrium, but at different relative concentrations. On the basis of the disulfide bond patterns of the different components in the equilibrium mixtures, we conclude that the disulfide between cysteines-47 and -52 in IGF-I is an unfavorable high-energy bond that may exist in the native molecule in a strained configuration.

Alkylation↗
PubMed1991

Perceptual rivalry between illusory and real contours.

The interactions between illusory and real contours have been investigated under monocular, binocular and dichoptic conditions. Results show that under all three presentation conditions, periodic alterations, generally called rivalry, occur during the perception of cognitive (or illusory) triangles, while earlier research had failed to find such rivalry (Bradley and Dumais 1975). With line triangles, rivalry is experienced only under dichoptic conditions. A model is proposed to account for the observed phenomena.

Computer Simulation↗
PubMed1990

Separation and characterization of modified variants of recombinant human insulin-like growth factor I derived from a fusion protein secreted from Escherichia coli.

Human insulin-like growth factor I, IGF-I, was produced in Escherichia coli fused to a synthetic IgG-binding peptide The fusion protein is secreted into the medium during fermentation and was initially purified on an IgG-Sepharose column. After hydroxylamine cleavage, IGF-I was purified to homogeneity. During purification, impurities in the form of modified variants of IGF-I were detected and characterized. The closely related impurities were identified to be a misfolded form of IGF-I, having mismatched disulphide bonds, a form with the single methionine residue in IGF-I oxidized to methionine sulphoxide and a variant in which the methionine residue was substituted by a norleucine residue during protein synthesis. A form proteolytically cleaved between two arginine residue was also detected. These impurities were separated from the major component, native IGF-I, by using reverse-phase h.p.l.c. The modified molecules as well as native IGF-I were characterized both as intact molecules and as fragments, after pepsin digestion, using the techniques of plasma desorption m.s., N-terminal sequencing and amino acid analysis. The oxidized form was 90%, and the norleucine analogue was 70%, as potent as native IGF-I in a biological radioreceptor assay, and the form having mismatched disulphides lacked receptor affinity.

Amino Acid Sequence↗
PubMed1989

Density of neurons and synapses in the cerebral cortex of the mouse.

Quantitative anatomical investigations provide the basis for functional models. In this study the density of neurons and synapses was measured in three different areas (8, 6, and 17) of the neocortex of the mouse. Both kinds of measurements were made on the same material, embedded in Epon/Araldit. In order to determine the synaptic density per mm3, the proportion of synaptic neuropil was also measured; it was found to be 84%. The cortical volume occupied by cell bodies of neurons and glia cells amounted to 12%, that by blood vessels to 4%. The total average was 9.2 x 10(4) neurons/mm3 and 7.2 x 10(8) synapses/mm3. About 11% of the synapses were of type II. The density of neurons increased with decreasing cortical thickness; thus the number of neurons under a given surface area was about constant. The synaptic density, on the other hand, was almost constant in the three areas, the number of synapses under a given cortical surface area tended, therefore, to increase with cortical thickness. The average number of synapses per neuron was 8,200, with a tendency to increase with increasing cortical thickness. Shrinkage of the tissue was also measured for various staining techniques. No shrinkage occurred during perfusion with 3.7% formaldehyde or with a solution of buffered paraformaldehyde and glutaraldehyde and during fixation in situ. Electron microscopical material showed almost no shrinkage, whereas Nissl-preparations on paraffin-embedded material had only 43% of their original volume. After Nissl stain on frozen sections the volume had shrunken to 68% and after Golgi impregnation and embedding in celloidin to 70%. The total volume of the neocortex was 112 mm3 (both hemispheres together). The total number of neurons was thus 1.0 x 10(7) and the total number of synapses 8.1 x 10(10).

Animals↗
PubMed1989

Dynamics of neuronal firing correlation: modulation of "effective connectivity".

1. We reexamine the possibilities for analyzing and interpreting the time course of correlation in spike trains simultaneously and separably recorded from two neurons. 2. We develop procedures to quantify and properly normalize the classical joint peristimulus time scatter diagram. These allow separation of the "raw" correlation into components caused by direct stimulus modulations of the single-neuron firing rates and those caused by various types of interaction between the two neurons. 3. A newly developed significance test ("surprise") is applied to evaluate such inferences. 4. Application of the new procedures to simulated spike trains allowed the recovery of the known circuitry. In particular, it proved possible to recover fast stimulus-locked modulations of "effective connectivity," even if they were masked by strong direct stimulus modulations of individual firing rates. These procedures thus present a clearly superior alternative to the commonly used "shift predictor." 5. Adopting a model-based approach, we generalize the classical measures for quantifying a direct interneuronal connection ("efficacy" and "contribution") to include possible stimulus-locked time variations. 6. Application of the new procedures to real spike trains from several different preparations showed that fast stimulus-locked modulations of "effective connectivity" also occur for real neurons.

Animals↗
PubMed1988

On the significance of correlations among neuronal spike trains.

We consider several measures for the correlation of firing activity among different neurons, based on coincidence counts obtained from simultaneously recorded spike trains. We obtain explicit formulae for the probability distributions of these measures. This allows an exact, quantitative assessment of significance levels, and thus a comparison of data obtained in different experimental paradigms. In particular it is possible to compare stimulus-locked, and therefore time dependent correlations for different stimuli and also for different times relative to stimulus onset. This allows to separate purely stimulus-induced correlation from intrinsic interneuronal correlation. It further allows investigation of the dynamic characteristics of the interneuronal correlation. For the display of significance levels or the corresponding probabilities we propose a logarithmic measure, called "surprise".

Animals↗
PubMed1987

A model of direction-selective "simple" cells in the visual cortex based on inhibition asymmetry.

Direction selectivity is a prominent feature of single units in the central visual pathway of cat and monkey. Various mechanisms have been proposed for the generation of this property. Experimental evidence suggests that intracortical inhibition is a major factor contributing to direction selectivity. We have developed a one-dimensional computer model for direction selective simple cells in the visual cortex under two basic assumptions: 1) Inhibition is exerted upon a cortical cell by neighboring cells from either side within a retinotopic array, 2) The relative strength of inhibition from both neighbors can be varied, interneurons always having larger time constants than the simple cells. Summation in the model is linear, but is followed by an essential non-linearity. ON- and/or OFF-center cells of the sustained type (X-cells) are used as an input to the simple cells. The computer simulation demonstrates that various subtypes of direction-selective simple cells in area 17, as described by Schiller et al. (1976), can be generated by different amounts of inhibition asymmetry, different delays and by different spatial arrangements of the input. Only one type of input (ON or OFF) is required to generate direction selectivity, but a greater variety of cell subtypes is created by combining both. Length-summation, contributing to orientation selectivity, was not considered in this one-dimensional model.

Animals↗