Laparoscopic aortic surgery: Techniques and results.

OBJECTIVE: This review describes and evaluates the results of laparoscopic aortic surgery. METHODS: We describe the different laparoscopic techniques used to treat aortic disease, including (1) total laparoscopic aortic surgery (TLS), (2) laparoscopy-assisted procedures including hand-assisted laparoscopic surgery (HALS), and (3) robot-assisted laparoscopic surgery, with their current indications. Results of these techniques are analyzed in a systematic review of the clinical series published between 1998 and 2008, each containing >10 patients with complete information concerning operative time, clamping time, conversion rate, length of hospital stay, morbidity, and mortality. RESULTS: We selected and reviewed 29 studies that included 1073 patients. Heterogeneity of the studies and selection of the patients made comparison with current open or endovascular surgery difficult. Median operative time varied widely in TLS, from 240 to 391 minutes. HALS had the shortest operating time. Median clamping time varied from 60 to 146 minutes in TLS and was shorter in HALS. Median hospital stay varied from 4 to 10 days regardless of the laparoscopic technique. The postoperative mortality rate was 2.1% (95% confidence interval, 1.4-3.0), with no significant difference between patients treated for occlusive disease or for aneurysmal disease. Conversion to open surgery was necessary in 8.1% of patients and was slightly higher with TLS than with laparoscopy-assisted techniques (P = .07). CONCLUSIONS: Analysis of these series shows that laparoscopic aortic surgery can be performed safely provided that patient selection is adjusted to the surgeon's experience and conversion is liberally performed. The future of this technique in comparison with endovascular surgery is still unknown, and it is now time for multicenter randomized trials to demonstrate the potential benefit of this type of surgery.

Genome-wide arrays in routine diagnostics of hematological malignancies.

Over the last three decades, cytogenetic analysis of malignancies has become an integral part of disease evaluation and prediction of prognosis or responsiveness to therapy. In most diagnostic laboratories, conventional karyotyping, in conjunction with targeted fluorescence in situ hybridization analysis, is routinely performed to detect recurrent aberrations with prognostic implications. However, the genetic complexity of cancer cells requires a sensitive genome-wide analysis, enabling the detection of small genomic changes in a mixed cell population, as well as of regions of homozygosity. The advent of comprehensive high-resolution genomic tools, such as molecular karyotyping using comparative genomic hybridization or single-nucleotide polymorphism microarrays, has overcome many of the limitations of traditional cytogenetic techniques and has been used to study complex genomic lesions in, for example, leukemia. The clinical impact of the genomic copy-number and copy-neutral alterations identified by microarray technologies is growing rapidly and genome-wide array analysis is evolving into a diagnostic tool, to better identify high-risk patients and predict patients' outcomes from their genomic profiles. Here, we review the added clinical value of an array-based genome-wide screen in leukemia, and discuss the technical challenges and an interpretation workflow in applying arrays in the acquired cytogenetic diagnostic setting.

Interaction between neuropeptide Y (NPY) and brain-derived neurotrophic factor in NPY-mediated neuroprotection against excitotoxicity : a role for microglia

The neuroprotective effect of neuropeptide Y (NPY) receptor activation was investigated in organotypic mouse hippocampal slice cultures exposed to the glutamate receptor agonist alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA). Exposure of 2-week-old slice cultures, derived from 7-day-old C57BL/6 mice, to 8 microm AMPA, for 24 h, induced degeneration of CA1 and CA3 pyramidal cells, as measured by cellular uptake of propidium iodide (PI). A significant neuroprotection, with a reduction of PI uptake in CA1 and CA3 pyramidal cell layers, was observed after incubation with a Y(2) receptor agonist [NPY(13-36), 300 nm]. This effect was sensitive to the presence of the selective Y(2) receptor antagonist (BIIE0246, 1 microm), but was not affected by addition of TrkB-Fc or by a neutralizing antibody against brain-derived neurotrophic factor (BDNF). Moreover, addition of a Y(1) receptor antagonist (BIBP3226, 1 microm) or a NPY-neutralizing antibody helped to disclose a neuroprotective role of endogenous NPY in CA1 region. Cultures exposed to 8 microm AMPA for 24 h, displayed, as measured by an enzyme-linked immunosorbent assay, a significant increase in BDNF. In such cultures there was an up-regulation of neuronal TrkB immunoreactivity, as well as the presence of BDNF-immunoreactive microglial cells at sites of injury. Thus, an increase of AMPA-receptor mediated neurodegeneration, in the mouse hippocampus, was prevented by neuroprotective pathways activated by NPY receptors (Y(1) and Y(2)), which can be affected by BDNF released by microglia and neurons.

BIO-INSPIRED COMPUTATIONAL TECHNIQUES APPLIED TO THE CLUSTERING AND VISUALIZATION OF SPATIO-TEMPORAL GEOSPATIAL DATA

The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.

High b-value diffusion-weighted imaging: A sensitive method to reveal white matter differences in schizophrenia.

Over the last 10 years, diffusion-weighted imaging (DWI) has become an important tool to investigate white matter (WM) anomalies in schizophrenia. Despite technological improvement and the exponential use of this technique, discrepancies remain and little is known about optimal parameters to apply for diffusion weighting during image acquisition. Specifically, high b-value diffusion-weighted imaging known to be more sensitive to slow diffusion is not widely used, even though subtle myelin alterations as thought to happen in schizophrenia are likely to affect slow-diffusing protons. Schizophrenia patients and healthy controls were scanned with a high b-value (4000s/mm(2)) protocol. Apparent diffusion coefficient (ADC) measures turned out to be very sensitive in detecting differences between schizophrenia patients and healthy volunteers even in a relatively small sample. We speculate that this is related to the sensitivity of high b-value imaging to the slow-diffusing compartment believed to reflect mainly the intra-axonal and myelin bound water pool. We also compared these results to a low b-value imaging experiment performed on the same population in the same scanning session. Even though the acquisition protocols are not strictly comparable, we noticed important differences in sensitivities in the favor of high b-value imaging, warranting further exploration.

Quantification of the local heartwall motion by magnetic resonance myocardial tagging.

Sophisticated magnetic resonance tagging techniques provide powerful tools for the non-invasive assessment of the local heartwall motion towards a deeper fundamental understanding of local heart function. For the extraction of motion data from the time series of magnetic resonance tagged images and for the visualization of the local heartwall motion a new image analysis procedure has been developed. New parameters have been derived which allows quantification of the motion patterns and are highly sensitive to any changes in these patterns. The new procedure has been applied for heart motion analysis in healthy volunteers and in patient collectives with different heart diseases. The achieved results are summarized and discussed.

Diagnosis of invasive candidiasis in the ICU.

Invasive candidiasis ranges from 5 to 10 cases per 1,000 ICU admissions and represents 5% to 10% of all ICU-acquired infections, with an overall mortality comparable to that of severe sepsis/septic shock. A large majority of them are due to Candida albicans, but the proportion of strains with decreased sensitivity or resistance to fluconazole is increasingly reported. A high proportion of ICU patients become colonized, but only 5% to 30% of them develop an invasive infection. Progressive colonization and major abdominal surgery are common risk factors, but invasive candidiasis is difficult to predict and early diagnosis remains a major challenge. Indeed, blood cultures are positive in a minority of cases and often late in the course of infection. New nonculture-based laboratory techniques may contribute to early diagnosis and management of invasive candidiasis. Both serologic (mannan, antimannan, and betaglucan) and molecular (Candida-specific PCR in blood and serum) have been applied as serial screening procedures in high-risk patients. However, although reasonably sensitive and specific, these techniques are largely investigational and their clinical usefulness remains to be established. Identification of patients susceptible to benefit from empirical antifungal treatment remains challenging, but it is mandatory to avoid antifungal overuse in critically ill patients. Growing evidence suggests that monitoring the dynamic of Candida colonization in surgical patients and prediction rules based on combined risk factors may be used to identify ICU patients at high risk of invasive candidiasis susceptible to benefit from prophylaxis or preemptive antifungal treatment.

Néphrectomie par laparoscopie: aspects techniques [Laparoscopic nephrectomy: technical aspects]

The laparoscopic approach has emerged as a valid option for surgical management of kidney cancer, as well as a few benign pathologies. The immediate benefits of laparoscopy are well established and include less estimated blood loss, decreased pain, shorter perioperative convalescence, and improved cosmesis. Long-term oncologic outcomes of patients treated laparoscopically for kidney tumors are similar to those of open surgery.

Simultaneous quantification of selective serotonin reuptake inhibitors and metabolites in human plasma by liquid chromatography-electrospray mass spectrometry for therapeutic drug monitoring.

A simple and sensitive liquid chromatography-electrospray ionization mass spectrometry method was developed for the simultaneous quantification in human plasma of all selective serotonin reuptake inhibitors (citalopram, fluoxetine, fluvoxamine, paroxetine and sertraline) and their main active metabolites (desmethyl-citalopram and norfluoxetine). A stable isotope-labeled internal standard was used for each analyte to compensate for the global method variability, including extraction and ionization variations. After sample (250μl) pre-treatment with acetonitrile (500μl) to precipitate proteins, a fast solid-phase extraction procedure was performed using mixed mode Oasis MCX 96-well plate. Chromatographic separation was achieved in less than 9.0min on a XBridge C18 column (2.1×100mm; 3.5μm) using a gradient of ammonium acetate (pH 8.1; 50mM) and acetonitrile as mobile phase at a flow rate of 0.3ml/min. The method was fully validated according to Société Française des Sciences et Techniques Pharmaceutiques protocols and the latest Food and Drug Administration guidelines. Six point calibration curves were used to cover a large concentration range of 1-500ng/ml for citalopram, desmethyl-citalopram, paroxetine and sertraline, 1-1000ng/ml for fluoxetine and fluvoxamine, and 2-1000ng/ml for norfluoxetine. Good quantitative performances were achieved in terms of trueness (84.2-109.6%), repeatability (0.9-14.6%) and intermediate precision (1.8-18.0%) in the entire assay range including the lower limit of quantification. Internal standard-normalized matrix effects were lower than 13%. The accuracy profiles (total error) were mainly included in the acceptance limits of ±30% for biological samples. The method was successfully applied for routine therapeutic drug monitoring of more than 1600 patient plasma samples over 9 months. The β-expectation tolerance intervals determined during the validation phase were coherent with the results of quality control samples analyzed during routine use. This method is therefore precise and suitable both for therapeutic drug monitoring and pharmacokinetic studies in most clinical laboratories.

Electrochemical As(III) whole-cell based biochip sensor.

The development of a whole-cell based sensor for arsenite detection coupling biological engineering and electrochemical techniques is presented. This strategy takes advantage of the natural Escherichia coli resistance mechanism against toxic arsenic species, such as arsenite, which consists of the selective intracellular recognition of arsenite and its pumping out from the cell. A whole-cell based biosensor can be produced by coupling the intracellular recognition of arsenite to the generation of an electrochemical signal. Hereto, E. coli was equipped with a genetic circuit in which synthesis of beta-galactosidase is under control of the arsenite-derepressable arsR-promoter. The E. coli reporter strain was filled in a microchip containing 16 independent electrochemical cells (i.e. two-electrode cell), which was then employed for analysis of tap and groundwater samples. The developed arsenic-sensitive electrochemical biochip is easy to use and outperforms state-of-the-art bacterial bioreporters assays specifically in its simplicity and response time, while keeping a very good limit of detection in tap water, i.e. 0.8ppb. Additionally, a very good linear response in the ranges of concentration tested (0.94ppb to 3.75ppb, R(2)=0.9975 and 3.75 ppb to 30ppb, R(2)=0.9991) was obtained, complying perfectly with the acceptable arsenic concentration limits defined by the World Health Organization for drinking water samples (i.e. 10ppb). Therefore, the proposed assay provides a very good alternative for the portable quantification of As (III) in water as corroborated by the analysis of natural groundwater samples from Swiss mountains, which showed a very good agreement with the results obtained by atomic absorption spectroscopy.

An ultra-sensitive impedimetric immunosensor for detection of the serum oncomarker CA-125 in ovarian cancer patients.

Effective treatment of ovarian cancer depends upon the early detection of the malignancy. Here, we report on the development of a new nanostructured immunosensor for early detection of cancer antigen 125 (CA-125). A gold electrode was modified with mercaptopropionic acid (MPA), and then consecutively conjugated with silica coated gold nanoparticles (AuNP@SiO2), CdSe quantum dots (QDs) and anti-CA-125 monoclonal antibody (mAb). The engineered MPA|AuNP@SiO2|QD|mAb immunosensor was characterised using transmission electron microscopy (TEM), atomic force microscopy (AFM), cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). Successive conjugation of AuNP@SiO2, CdSe QD and anti-CA-125 mAb onto the gold electrode resulted in sensitive detection of CA-125 with a limit of detection (LOD) of 0.0016 U mL(-1) and a linear detection range (LDR) of 0-0.1 U mL(-1). Based on the high sensitivity and specificity of the immunosensor, we propose this highly stable and reproducible biosensor for the early detection of CA-125.

Regulated exocytosis from astrocytes physiological and pathological related aspects.

Astrocytes have traditionally been considered ancillary, satellite cells of the nervous system. However, it is a very recent acquisition that glial cells generate signaling loops which are integral to the brain circuitry and participate, interactively with neuronal networks, in the processing of information. Such a conceptual breakthrough makes this field of investigation one of the hottest in neuroscience, as it calls for a revision of past theories of brain function as well as for new strategies of experimental exploration of brain function. Glial cells are electrically not excitable, and it was only the use of optical recording techniques together with calcium sensitive dyes, that allowed the chemical excitability of glial cells to become apparent. Studies using these new techniques have shown for the first time that glial cells are activated by surrounding synaptic activity and translate neuronal signals into their own calcium code. Intracellular calcium concentration([Ca2+]i) elevations in glial cells have then shown to underlie spatial transfer of information in the glial network, accompanied by release of chemical transmitters (gliotransmitters) such as glutamate and back-signaling to neurons. As a consequence, optical imaging techniques applied to cell cultures or intact tissue have become a state-of-the-art technology for studying glial cell signaling. The molecular mechanisms leading to release of "gliotransmitters," especially glutamate, from glia are under debate. Accumulating evidence clearly indicates that astrocytes secrete numerous transmitters by Ca(2+)-dependent exocytosis. This review will discuss the mechanisms underlying the release of chemical transmitters from astrocytes with a particular emphasis to the regulated exocytosis processes.