PubMed Health⌕ Search

Biomedical subjects

P Picart

Publications and source records attributed to P Picart.

At least 19 recordsLinked to original sources
PubMed2003

Development of a biosensor for on-line detection of tributyltin with a recombinant bioluminescent Escherichia coli strain.

A biosensor was developed for the detection of tributyltin (TBT), using a bioluminescent recombinant Escherichia coli:: luxAB strain. Dedicated devices allowed the on-line measurement of bioluminescence, pH and dissolved oxygen values and the feed-back regulation of temperature. Bacterial physiology was monitored by the measurement of the cellular density, respiratory activity and the intracellular level of ATP, glucose and acetate levels. Our results showed that a synthetic glucose medium gave a better TBT detection limit than LB medium (respectively 0.02 micro M and 1.5 micro M TBT). High growth and dilution rates ( D=0.9 h(-1)) allowed maximum light emission from the bacterium. Moreover, simple atmospheric air bubbling was sufficient to provide oxygen for growth and the bioluminescence reaction. Real-time monitoring of bioluminescence after TBT induction occurred with continuous addition of decanal up to 300 micro M, which was not toxic throughout a 7-day experiment. The design of our biosensor and the optimization of the main parameters that influence microbial activity led to the capacity for the detection of TBT.

Biosensing Techniques↗
PubMed1987

Turning the mass-spectrometer into an easy to handle clinical instrument for routine multipatient surveillance of respiratory and anesthetic gases during anesthesia.

Although most authors use it as the reference instrument for respiratory gases measurement, the use of mass-spectrometer in clinical routine in ICU and in anesthesia remains quite limited. We developed a fully automatically controlled system, carrying on a twinned goal: The ACS-2000 (Automatic Calibration System) turns the Airspec MGA-2000 mass-spectrometer into a true clinical instrument, as easy to use as any routine monitoring instrument, and lets the clinician and the anesthetist benefit from its uncomparable metrological performances. PAMS-M, multibed monitoring system, shares the mass-spectrometer time among 4 to 8 rooms, providing each anesthetist with full composition of inspired and end tidal gases composition, trend evolution of those data, as with the display of capnogram. Each room is equipped with an IBM PC compatible intelligent terminal, abling the user to select the nature of the displayed information and enter into an easy menu driven dialog with the system. As a subproduct, the informatic infrastructure on which the system is based allowed, beyond the standard monitoring function, to set the bases of a computerized patient's anesthesia or respiratory monitoring report.

Anesthetics↗
PubMed1984

Real time mathematical analysis of instantaneous respiratory signals at the bedside by a multiprocessor system (PAMS).

The authors address the following problems: How to turn a mass spectrometer, or a set of individual gas sensors, into a real and useful medical instrument? In other words, how to transform the instantaneous gas composition signals into meaningful physiological variables? The parameters that can be computed breath by breath from the real time processing of gas concentration signals, combined with flow and pressure signals at the mouth are first described. Particularly, we point out the theoretical and practical importance of alveolo-capillary gas exchange parameters, as opposed to gas exchange parameters estimated at the mouth level: A-c exchange parameters are a more sensitive and more specific indicator of any physiological change and they are less sensitive to breath by breath fluctuations of ventilation. We discuss the clinical usefulness of breath by breath computations, as a more sensitive way to monitor the patient as well as the anesthesia circuit, and to generate all the information required for on line analysis of functional tests. We describe a system for the real time processing of the respiratory signals. Based on three microprocessors it takes over the calibration, the offset correction of each signal ... It also corrects for the dynamics of each sensor and resynchronizes all the signals. It computes breath by breath more than 50 physiological variables that can be either recorded analogically, either printed, either acquired by a general monitoring system of the patient, which then combines respiratory data with other physiological. therapeutical and medical data from the patient.

Mass Spectrometry↗