Lung mechanics and gas exchange in ventilated preterm infants during treatment of hyaline membrane disease with multiple doses of artificial surfactant (Exosurf)

Eight premature infants ventilated for hyaline membrane disease and enrolled in the OSIRIS surfactant trial were studied. Lung mechanics, gas exchange [PaCO2, arterial/alveolar PO2 ratio (a/A ratio)], and ventilator settings were determined 20 minutes before and 20 minutes after the end of Exosurf instillation, and subsequently at 12-24 hour intervals. Respiratory system compliance (Crs) and resistance (Rrs) were measured by means of the single breath occlusion method. After surfactant instillation there were no significant immediate changes in PaCO2 (36 vs. 37 mmHg), a/A ratio (0.23 vs. 0.20), Crs (0.32 vs. 0.31 mL/cm H2O/kg), and Rrs (0.11 vs. 0.16 cmH2O/mL/s) (pooled data of 18 measurement pairs). During the clinical course, mean a/A ratio improved significantly each time from 0.17 (time 0) to 0.29 (time 12-13 hours), to 0.39 (time 24-36 hours) and to 0.60 (time 48-61 hours), although mean airway pressure was reduced substantially. Mean Crs increased significantly from 0.28 mL/cmH2O/kg (time 0) to 0.38 (time 12-13 hours), to 0.37 (time 24-38 hours), and to 0.52 (time 48-61 hours), whereas mean Rrs increased from 0.10 cm H2O/mL/s (time 0) to 0.11 (time 12-13 hours), to 0.13 (time 24-36 hours) and to (time 48-61 hours) with no overall significance. A highly significant correlation was found between Crs and a/A ratio (r = 0.698, P less than 0.001). We conclude that Exosurf does not induce immediate changes in oxygenation as does the instillation of (modified) natural surfactant preparations. However, after 12 and 24 hours of treatment oxygenation and Crs improve significantly.(ABSTRACT TRUNCATED AT 250 WORDS)

Analysis of postprandial lipemia as a Cardiovascular Disease risk factor using genetic and clinical information: an Artificial Neural Network perspective

Clinical studies indicate that exaggerated postprandial lipemia is linked to the progression of atherosclerosis, leading cause of Cardiovascular Diseases (CVD). CVD is a multi-factorial disease with complex etiology and according to the literature postprandial Triglycerides (TG) can be used as an independent CVD risk factor. Aim of the current study is to construct an Artificial Neural Network (ANN) based system for the identification of the most important gene-gene and/or gene-environmental interactions that contribute to a fast or slow postprandial metabolism of TG in blood and consequently to investigate the causality of postprandial TG response. The design and development of the system is based on a dataset of 213 subjects who underwent a two meals fatty prandial protocol. For each of the subjects a total of 30 input variables corresponding to genetic variations, sex, age and fasting levels of clinical measurements were known. Those variables provide input to the system, which is based on the combined use of Parameter Decreasing Method (PDM) and an ANN. The system was able to identify the ten (10) most informative variables and achieve a mean accuracy equal to 85.21%.

New online method for water isotope analysis of speleothem fluid inclusions using laser absorption spectroscopy (WS-CRDS)

A new online method to analyse water isotopes of speleothem fluid inclusions using a wavelength scanned cavity ring down spectroscopy (WS-CRDS) instrument is presented. This novel technique allows us simultaneously to measure hydrogen and oxygen isotopes for a released aliquot of water. To do so, we designed a new simple line that allows the online water extraction and isotope analysis of speleothem samples. The specificity of the method lies in the fact that fluid inclusions release is made on a standard water background, which mainly improves the δ D robustness. To saturate the line, a peristaltic pump continuously injects standard water into the line that is permanently heated to 140 °C and flushed with dry nitrogen gas. This permits instantaneous and complete vaporisation of the standard water, resulting in an artificial water background with well-known δ D and δ18O values. The speleothem sample is placed in a copper tube, attached to the line, and after system stabilisation it is crushed using a simple hydraulic device to liberate speleothem fluid inclusions water. The released water is carried by the nitrogen/standard water gas stream directly to a Picarro L1102-i for isotope determination. To test the accuracy and reproducibility of the line and to measure standard water during speleothem measurements, a syringe injection unit was added to the line. Peak evaluation is done similarly as in gas chromatography to obtain &delta D; and δ18O isotopic compositions of measured water aliquots. Precision is better than 1.5 ‰ for δ D and 0.4 ‰ for δ18O for water measurements for an extended range (−210 to 0 ‰ for δ D and −27 to 0 ‰ for δ18O) primarily dependent on the amount of water released from speleothem fluid inclusions and secondarily on the isotopic composition of the sample. The results show that WS-CRDS technology is suitable for speleothem fluid inclusion measurements and gives results that are comparable to the isotope ratio mass spectrometry (IRMS) technique.

New method for porewater extraction from claystone and determination of transport properties with results for Opalinus Clay (Switzerland)

A new technique to porewater extraction from claystone employs advective displacement of the in situ porewater by traced artificial porewater. Monitoring of tracer breakthrough yields species-specific transport properties. Results for Opalinus Clay from the Mont Terri Research Laboratory indicate that the chemical disturbances due to the method are minimal, and the observed significant differences in transport properties for Br– and 2H are in agreement with existing data. Sampling times are 2–4 months, and observation of tracer breakthrough takes 12–24 months at hydraulic conductivity of ∼10-13 m/s.

SNARE-fusion mediated insertion of membrane proteins into native and artificial membranes

Membrane proteins carry out functions such as nutrient uptake, ATP synthesis or transmembrane signal transduction. An increasing number of reports indicate that cellular processes are underpinned by regulated interactions between these proteins. Consequently, functional studies of these networks at a molecular level require co-reconstitution of the interacting components. Here, we report a SNARE protein-based method for incorporation of multiple membrane proteins into artificial membrane vesicles of well-defined composition, and for delivery of large water-soluble substrates into these vesicles. The approach is used for in vitro reconstruction of a fully functional bacterial respiratory chain from purified components. Furthermore, the method is used for functional incorporation of the entire F1F0 ATP synthase complex into native bacterial membranes from which this component had been genetically removed. The novel methodology offers a tool to investigate complex interaction networks between membrane-bound proteins at a molecular level, which is expected to generate functional insights into key cellular functions.

SNARE-fusion mediated inserton of membrane proteins into native and artificial membranes

Membrane proteins carry out functions such as nutrient uptake, ATP synthesis or transmembrane signal transduction. An increasing number of reports indicate that cellular processes are underpinned by regulated interactions between these proteins. Consequently, functional studies of these networks at a molecular level require co-reconstitution of the interacting components. Here, we report a SNARE-protein based method for incorporation of multiple membrane proteins into membranes, and for delivery of large water-soluble substrates into closed membrane vesicles. The approach is used for in vitro reconstruction of a fully functional bacterial respiratory chain from purified components. Furthermore, the method is used for functional incorporation of the entire F1F0-ATP synthase complex into native bacterial membranes from which this component had been genetically removed. The novel methodology offers a tool to investigate complex interaction networks between membrane-bound proteins at a molecular level, which is expected to generate functional insights into key cellular functions.

GoCARB in the Context of an Artificial Pancreas

Background: In an artificial pancreas (AP), the meals are either manually announced or detected and their size estimated from the blood glucose level. Both methods have limitations, which result in suboptimal postprandial glucose control. The GoCARB system is designed to provide the carbohydrate content of meals and is presented within the AP framework. Method: The combined use of GoCARB with a control algorithm is assessed in a series of 12 computer simulations. The simulations are defined according to the type of the control (open or closed loop), the use or not-use of GoCARB and the diabetics’ skills in carbohydrate estimation. Results: For bad estimators without GoCARB, the percentage of the time spent in target range (70-180 mg/dl) during the postprandial period is 22.5% and 66.2% for open and closed loop, respectively. When the GoCARB is used, the corresponding percentages are 99.7% and 99.8%. In case of open loop, the time spent in severe hypoglycemic events (<50 mg/dl) is 33.6% without the GoCARB and is reduced to 0.0% when the GoCARB is used. In case of closed loop, the corresponding percentage is 1.4% without the GoCARB and is reduced to 0.0% with the GoCARB. Conclusion: The use of GoCARB improves the control of postprandial response and glucose profiles especially in the case of open loop. However, the most efficient regulation is achieved by the combined use of the control algorithm and the GoCARB.

Serum tests, liver stiffness and artificial neural networks for diagnosing cirrhosis and portal hypertension

BACKGROUND The diagnostic performance of biochemical scores and artificial neural network models for portal hypertension and cirrhosis is not well established. AIMS To assess diagnostic accuracy of six serum scores, artificial neural networks and liver stiffness measured by transient elastography, for diagnosing cirrhosis, clinically significant portal hypertension and oesophageal varices. METHODS 202 consecutive compensated patients requiring liver biopsy and hepatic venous pressure gradient measurement were included. Several serum tests (alone and combined into scores) and liver stiffness were measured. Artificial neural networks containing or not liver stiffness as input variable were also created. RESULTS The best non-invasive method for diagnosing cirrhosis, portal hypertension and oesophageal varices was liver stiffness (C-statistics=0.93, 0.94, and 0.90, respectively). Among serum tests/scores the best for diagnosing cirrhosis and portal hypertension and oesophageal varices were, respectively, Fibrosis-4, and Lok score. Artificial neural networks including liver stiffness had high diagnostic performance for cirrhosis, portal hypertension and oesophageal varices (accuracy>80%), but were not statistically superior to liver stiffness alone. CONCLUSIONS Liver stiffness was the best non-invasive method to assess the presence of cirrhosis, portal hypertension and oesophageal varices. The use of artificial neural networks integrating different non-invasive tests did not increase the diagnostic accuracy of liver stiffness alone.

New algorithms for automated phylogenetic reconstruction using artificial intelligence and data mining techniques

Academic and industrial research in the late 90s have brought about an exponential explosion of DNA sequence data. Automated expert systems are being created to help biologists to extract patterns, trends and links from this ever-deepening ocean of information. Two such systems aimed on retrieving and subsequently utilizing phylogenetically relevant information have been developed in this dissertation, the major objective of which was to automate the often difficult and confusing phylogenetic reconstruction process. ^ Popular phylogenetic reconstruction methods, such as distance-based methods, attempt to find an optimal tree topology (that reflects the relationships among related sequences and their evolutionary history) by searching through the topology space. Various compromises between the fast (but incomplete) and exhaustive (but computationally prohibitive) search heuristics have been suggested. An intelligent compromise algorithm that relies on a flexible “beam” search principle from the Artificial Intelligence domain and uses the pre-computed local topology reliability information to adjust the beam search space continuously is described in the second chapter of this dissertation. ^ However, sometimes even a (virtually) complete distance-based method is inferior to the significantly more elaborate (and computationally expensive) maximum likelihood (ML) method. In fact, depending on the nature of the sequence data in question either method might prove to be superior. Therefore, it is difficult (even for an expert) to tell a priori which phylogenetic reconstruction method—distance-based, ML or maybe maximum parsimony (MP)—should be chosen for any particular data set. ^ A number of factors, often hidden, influence the performance of a method. For example, it is generally understood that for a phylogenetically “difficult” data set more sophisticated methods (e.g., ML) tend to be more effective and thus should be chosen. However, it is the interplay of many factors that one needs to consider in order to avoid choosing an inferior method (potentially a costly mistake, both in terms of computational expenses and in terms of reconstruction accuracy.) ^ Chapter III of this dissertation details a phylogenetic reconstruction expert system that selects a superior proper method automatically. It uses a classifier (a Decision Tree-inducing algorithm) to map a new data set to the proper phylogenetic reconstruction method. ^

Over-determined charbonate chemstry dataset from different kinds of manipulation (TA, DIC) and water types (natural and artificial seawater)

The growing field of ocean acidification research is concerned with the investigation of organism responses to increasing pCO2 values. One important approach in this context is culture work using seawater with adjusted CO2 levels. As aqueous pCO2 is difficult to measure directly in small-scale experiments, it is generally calculated from two other measured parameters of the carbonate system (often AT, CT or pH). Unfortunately, the overall uncertainties of measured and subsequently calculated values are often unknown. Especially under high pCO2, this can become a severe problem with respect to the interpretation of physiological and ecological data. In the few datasets from ocean acidification research where all three of these parameters were measured, pCO2 values calculated from AT and CT are typically about 30% lower (i.e. ~300 µatm at a target pCO2 of 1000 µatm) than those calculated from AT and pH or CT and pH. This study presents and discusses these discrepancies as well as likely consequences for the ocean acidification community. Until this problem is solved, one has to consider that calculated parameters of the carbonate system (e.g. pCO2, calcite saturation state) may not be comparable between studies, and that this may have important implications for the interpretation of CO2 perturbation experiments.

Counts and abundance of macrozoobenthic organisms settled in artificial soft sediment at Brandal, Kongsfjorden, Spitsbergen

In the Arctic the currently observed rising air temperature results in more frequent calving of icebergs. The latter are derived from tidewater glaciers. Arctic macrozoobenthic soft-sediment communities are considerably disturbed by direct hits and sediment reallocation caused by iceberg scouring. With the aim to describe the primary succession of macrozoobenthic communities following these events, scientific divers installed 28 terracotta containers in the soft-sediment off Brandal (Kongsfjorden, Svalbard, Norway) at 20 m water depth in 2002. The containers were filled with a bentonite-sand-mixture resembling the natural sediment. Samples were taken annually between 2003 and 2007. A shift from pioneering species (e.g. Cumacea: Lamprops fuscatus) towards more specialized taxa, as well as from surface-detritivores towards subsurface-detritivores was observed. This is typical for an ecological succession following the facilitation and inhibition succession model. Similarity between experimental and non-manipulated communities from 2003 was significantly highest after three years of succession. In the following years similarity decreased, probably due to elevated temperatures, which prevented the fjord-system from freezing. Some organisms numerically important in the non-manipulated community (e.g., the polychaete Dipolydora quadrilobata) did not colonies the substrate during the experiment. This suggests that the community had not fully matured within the first three years. Later, the settlement was probably impeded by consequences of warming temperatures. This demonstrates the long-lasting effects of severe disturbances on Arctic macrozoobenthic communities. Furthermore, environmental changes, such as rising temperatures coupled with enhanced food availability due to an increasing frequency of ice-free days per year, may have a stronger effect on succession than exposure time.

Improvement for detection of microcalcifications through clustering algorithms and artificial neural networks

A new method for detecting microcalcifications in regions of interest (ROIs) extracted from digitized mammograms is proposed. The top-hat transform is a technique based on mathematical morphology operations and, in this paper, is used to perform contrast enhancement of the mi-crocalcifications. To improve microcalcification detection, a novel image sub-segmentation approach based on the possibilistic fuzzy c-means algorithm is used. From the original ROIs, window-based features, such as the mean and standard deviation, were extracted; these features were used as an input vector in a classifier. The classifier is based on an artificial neural network to identify patterns belonging to microcalcifications and healthy tissue. Our results show that the proposed method is a good alternative for automatically detecting microcalcifications, because this stage is an important part of early breast cancer detection

Face Lift Surgery for Reconstructed Virtual Humans

We introduce an innovative, semi-automatic method to transform low resolution facial meshes into high definition ones, based on the tailoring of a generic, neutral human head model, designed by an artist, to fit the facial features of a specific person. To determine these facial features we need to select a set of "control points" (corners of eyes, lips, etc.) in at least two photographs of the subject's face. The neutral head mesh is then automatically reshaped according to the relation between the control points in the original subject's mesh through a set of transformation pyramids. The last step consists in merging both meshes and filling the gaps that appear in the previous process. This algorithm avoids the use of expensive and complicated technologies to obtain depth maps, which also need to be meshed later.

A knowledge-based method for generating summaries of spatial movement in geographic areas

In this article we describe a method for automatically generating text summaries of data corresponding to traces of spatial movement in geographical areas. The method can help humans to understand large data streams, such as the amounts of GPS data recorded by a variety of sensors in mobile phones, cars, etc. We describe the knowledge representations we designed for our method and the main components of our method for generating the summaries: a discourse planner, an abstraction module and a text generator. We also present evaluation results that show the ability of our method to generate certain types of geospatial and temporal descriptions.