Evaluation of high frequency jet ventilation in patients undergoing percutaneous thermal ablation

Purpose: To evaluate the use of high frequency jet ventilation (HFJV) in patients undergoing percutanous thermal ablation procedures.Materials: From may to september 2011 patients with lung, liver or kidney tumors suitable for percutanous thermal ablation were prospectively enrolled to be treated under general anesthesia using HFJV instead of conventional positive pressure ventilation (PPV). Our primary endpoint was feasability of HFJV during percutanous ablation, our secondary endpoints were assessment of breathing related movements by image fusion (CT/US), precision and ease of needle placement by number of CT aquisition/needle reposition and procedure related complications.Results: Twenty-nine patients (21 males, 8 females mean age 66.2 years) with 30 liver tumors, 1 kidney tumors and 6 lung tumors were included. Tumor ablation was performed by radiofrequency (RFA) in 26 cases, microwaves ( MWA) in 2 and cryoablation (CRA) in 1. The ablation procedure could be completed under HFJV in 22 patients. In 2 patients HFVJ had to be stopped in favor of PPV because the tumor was better seen under PPV. HFJV was not performed in 5. Breathing related movements of the target lesion in the cranio-caudal direction as estimated by image fusion were always inferior to 5mm compared to 20mm when patients are under PPV. Needle placement was straightforward under CT as well as US. No patient needed needle repositionning before ablation. We did not observe any HFJV related complications.Conclusions: HFJV significantly reduces breathing movements of target lesion during percutaneous ablation procedures. It does not seem to cause any particular complication. However in some cases such as tumors located at the base of the lungs or in the dome of the liver, the target may be best seen under PPV.

Different concentrations of Mg++ ions affect nuclear matrix protein distribution during thermal stabilization of isolated nuclei.

The nuclear matrix, a proteinaceous network believed to be a scaffolding structure determining higher-order organization of chromatin, is usually prepared from intact nuclei by a series of extraction steps. In most cell types investigated the nuclear matrix does not spontaneously resist these treatments but must be stabilized before the application of extracting agents. Incubation of isolated nuclei at 37C or 42C in buffers containing Mg++ has been widely employed as stabilizing agent. We have previously demonstrated that heat treatment induces changes in the distribution of three nuclear scaffold proteins in nuclei prepared in the absence of Mg++ ions. We studied whether different concentrations of Mg++ (2.0-5 mM) affect the spatial distribution of nuclear matrix proteins in nuclei isolated from K562 erythroleukemia cells and stabilized by heat at either 37C or 42C. Five proteins were studied, two of which were RNA metabolism-related proteins (a 105-kD component of splicing complexes and an RNP component), one a 126-kD constituent of a class of nuclear bodies, and two were components of the inner matrix network. The localization of proteins was determined by immunofluorescent staining and confocal scanning laser microscope. Mg++ induced significant changes of antigen distribution even at the lowest concentration employed, and these modifications were enhanced in parallel with increase in the concentration of the divalent cation. The different sensitivity to heat stabilization and Mg++ of these nuclear proteins might reflect a different degree of association with the nuclear scaffold and can be closely related to their functional or structural role.

Desensitization of thermal hyperemia in the skin is reproducible.

OBJECTIVE: Local heating increases skin blood flow SkBF (thermal hyperemia). In a previous study, we reported that a first local thermal stimulus could attenuate the hyperemic response to a second one applied later on the same skin spot, a phenomenon that we termed desensitization. However, other studies found no evidence for desensitization in similar conditions. The aim of the present work was to test whether it was related to differences in instrumentation. METHODS: Twenty-eight healthy young males were studied. Two pairs of heating chambers, one custom-made (our study) and one commercial (other groups), were affixed to forearm skin. SkBF was measured with single-point laser-Doppler flowmetry (LDF) (780nm) in one pair, and laser-Doppler imaging (LDI) (633nm) in the other. A temperature step from 34 to 41°C, was applied for 30minutes and repeated after two hours. RESULTS: During the second thermal challenge, the plateau SkBF was lower than during the first thermal and was observed with each of the four combinations of SkBF measurement techniques and heating equipment (p<0.05 for all conditions, range -9% to -16% of the initial value). CONCLUSION: Desensitization of thermal hyperemia is not specific to peculiar operating conditions.

Urban image classification with semisupervised multiscale cluster kernels

This paper presents a semisupervised support vector machine (SVM) that integrates the information of both labeled and unlabeled pixels efficiently. Method's performance is illustrated in the relevant problem of very high resolution image classification of urban areas. The SVM is trained with the linear combination of two kernels: a base kernel working only with labeled examples is deformed by a likelihood kernel encoding similarities between labeled and unlabeled examples. Results obtained on very high resolution (VHR) multispectral and hyperspectral images show the relevance of the method in the context of urban image classification. Also, its simplicity and the few parameters involved make the method versatile and workable by unexperienced users.

Generating controlled image sets in cognitive neuroscience research.

The investigation of perceptual and cognitive functions with non-invasive brain imaging methods critically depends on the careful selection of stimuli for use in experiments. For example, it must be verified that any observed effects follow from the parameter of interest (e.g. semantic category) rather than other low-level physical features (e.g. luminance, or spectral properties). Otherwise, interpretation of results is confounded. Often, researchers circumvent this issue by including additional control conditions or tasks, both of which are flawed and also prolong experiments. Here, we present some new approaches for controlling classes of stimuli intended for use in cognitive neuroscience, however these methods can be readily extrapolated to other applications and stimulus modalities. Our approach is comprised of two levels. The first level aims at equalizing individual stimuli in terms of their mean luminance. Each data point in the stimulus is adjusted to a standardized value based on a standard value across the stimulus battery. The second level analyzes two populations of stimuli along their spectral properties (i.e. spatial frequency) using a dissimilarity metric that equals the root mean square of the distance between two populations of objects as a function of spatial frequency along x- and y-dimensions of the image. Randomized permutations are used to obtain a minimal value between the populations to minimize, in a completely data-driven manner, the spectral differences between image sets. While another paper in this issue applies these methods in the case of acoustic stimuli (Aeschlimann et al., Brain Topogr 2008), we illustrate this approach here in detail for complex visual stimuli.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

MSight: an image analysis software for liquid chromatography-mass spectrometry.

Images obtained from high-throughput mass spectrometry (MS) contain information that remains hidden when looking at a single spectrum at a time. Image processing of liquid chromatography-MS datasets can be extremely useful for quality control, experimental monitoring and knowledge extraction. The importance of imaging in differential analysis of proteomic experiments has already been established through two-dimensional gels and can now be foreseen with MS images. We present MSight, a new software designed to construct and manipulate MS images, as well as to facilitate their analysis and comparison.

Thermal niches are more conserved at cold than warm limits in arctic-alpine plant species

Aim Understanding the stability of realised niches is crucial for predicting the responses of species to climate change. One approach is to evaluate the niche differences of populations of the same species that occupy regions that are geographically disconnected. Here, we assess niche conservatism along thermal gradients for 26 plant species with a disjunct distribution between the Alps and the Arctic. Location European Alps and Norwegian Finnmark. Methods We collected a comprehensive dataset of 26 arctic-alpine plant occurrences in two regions. We assessed niche conservatism through a multi-species comparison and analysed species rankings at cold and warm thermal limits along two distinct gradients corresponding to (1) air temperatures at 2 meters above ground level and (2) elevation distances to the treeline (TLD) for the two regions. We assessed whether observed relationships were close to those predicted under thermal limit conservatism. Results We found a weak similarity in species ranking at the warm thermal limits. The range of warm thermal limits for the 26 species was much larger in the Alps than in Finnmark. We found a stronger similarity in species ranking and correspondence at the cold thermal limit along the gradients of 2-m temperature and TLD. Yet, along the 2-m temperature gradient, the cold thermal limits of species in the Alps were lower on average than those in Finnmark. Main conclusion We found low conservatism of the warm thermal limits but a stronger conservatism of the cold thermal limits. We suggest that biotic interactions at the warm thermal limit likely modulate species responses more strongly than at the cold limit. The differing biotic context between the two regions is likely responsible for the observed differences in realised niches.