Modelling plant species distribution in alpine grasslands using airborne imaging spectroscopy.

Remote sensing using airborne imaging spectroscopy (AIS) is known to retrieve fundamental optical properties of ecosystems. However, the value of these properties for predicting plant species distribution remains unclear. Here, we assess whether such data can add value to topographic variables for predicting plant distributions in French and Swiss alpine grasslands. We fitted statistical models with high spectral and spatial resolution reflectance data and tested four optical indices sensitive to leaf chlorophyll content, leaf water content and leaf area index. We found moderate added-value of AIS data for predicting alpine plant species distribution. Contrary to expectations, differences between species distribution models (SDMs) were not linked to their local abundance or phylogenetic/functional similarity. Moreover, spectral signatures of species were found to be partly site-specific. We discuss current limits of AIS-based SDMs, highlighting issues of scale and informational content of AIS data.

The Discrimination of Colored Acrylic, Cotton, and Wool Textile Fibers Using Micro-Raman Spectroscopy. Part 1 : In Situ Detection and Characterization of Dyes

Raman spectroscopy has been applied to characterize fiber dyes and determine the discriminating ability of the method. Black, blue, and red acrylic, cotton, and wool samples were analyzed. Four excitation sources were used to obtain complementary responses in the case of fluorescent samples. Fibers that did not provide informative spectra using a given laser were usually detected using another wavelength. For any colored acrylic, the 633-nm laser did not provide Raman information. The 514-nm laser provided the highest discrimination for blue and black cotton, but half of the blue cottons produced noninformative spectra. The 830-nm laser exhibited the highest discrimination for red cotton. Both visible lasers provided the highest discrimination for black and blue wool, and NIR lasers produced remarkable separation for red and black wool. This study shows that the discriminating ability of Raman spectroscopy depends on the fiber type, color, and the laser wavelength.

Compartmentalized Cerebral Metabolism of [1,6-(13)C]Glucose Determined by in vivo (13)C NMR Spectroscopy at 14.1 T.

Cerebral metabolism is compartmentalized between neurons and glia. Although glial glycolysis is thought to largely sustain the energetic requirements of neurotransmission while oxidative metabolism takes place mainly in neurons, this hypothesis is matter of debate. The compartmentalization of cerebral metabolic fluxes can be determined by (13)C nuclear magnetic resonance (NMR) spectroscopy upon infusion of (13)C-enriched compounds, especially glucose. Rats under light α-chloralose anesthesia were infused with [1,6-(13)C]glucose and (13)C enrichment in the brain metabolites was measured by (13)C NMR spectroscopy with high sensitivity and spectral resolution at 14.1 T. This allowed determining (13)C enrichment curves of amino acid carbons with high reproducibility and to reliably estimate cerebral metabolic fluxes (mean error of 8%). We further found that TCA cycle intermediates are not required for flux determination in mathematical models of brain metabolism. Neuronal tricarboxylic acid cycle rate (V(TCA)) and neurotransmission rate (V(NT)) were 0.45 ± 0.01 and 0.11 ± 0.01 μmol/g/min, respectively. Glial V(TCA) was found to be 38 ± 3% of total cerebral oxidative metabolism, accounting for more than half of neuronal oxidative metabolism. Furthermore, glial anaplerotic pyruvate carboxylation rate (V(PC)) was 0.069 ± 0.004 μmol/g/min, i.e., 25 ± 1% of the glial TCA cycle rate. These results support a role of glial cells as active partners of neurons during synaptic transmission beyond glycolytic metabolism.

Are glutamate and lactate increases ubiquitous to physiological activation? A (1)H functional MR spectroscopy study during motor activation in human brain at 7Tesla.

Recent studies at high field (7Tesla) have reported small metabolite changes, in particular lactate and glutamate (below 0.3μmol/g) during visual stimulation. These studies have been limited to the visual cortex because of its high energy metabolism and good magnetic resonance spectroscopy (MRS) sensitivity using surface coil. The aim of this study was to extend functional MRS (fMRS) to investigate for the first time the metabolite changes during motor activation at 7T. Small but sustained increases in lactate (0.17μmol/g±0.05μmol/g, p<0.001) and glutamate (0.17μmol/g±0.09μmol/g, p<0.005) were detected during motor activation followed by a return to the baseline after the end of activation. The present study demonstrates that increases in lactate and glutamate during motor stimulation are small, but similar to those observed during visual stimulation. From the observed glutamate and lactate increase, we inferred that these metabolite changes may be a general manifestation of the increased neuronal activity. In addition, we propose that the measured metabolite concentration increases imply an increase in ΔCMRO2 that is transiently below that of ΔCMRGlc during the first 1 to 2min of the stimulation.

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.

In vivo measurement of tissue oxygenation by time-resolved luminescence spectroscopy: advantageous properties of dichlorotris(1, 10-phenanthroline)-ruthenium(II) hydrate.

Measuring tissue oxygenation in vivo is of interest in fundamental biological as well as medical applications. One minimally invasive approach to assess the oxygen partial pressure in tissue (pO2) is to measure the oxygen-dependent luminescence lifetime of molecular probes. The relation between tissue pO2 and the probes' luminescence lifetime is governed by the Stern-Volmer equation. Unfortunately, virtually all oxygen-sensitive probes based on this principle induce some degree of phototoxicity. For that reason, we studied the oxygen sensitivity and phototoxicity of dichlorotris(1, 10-phenanthroline)-ruthenium(II) hydrate [Ru(Phen)] using a dedicated optical fiber-based, time-resolved spectrometer in the chicken embryo chorioallantoic membrane. We demonstrated that, after intravenous injection, Ru(Phen)'s luminescence lifetime presents an easily detectable pO2 dependence at a low drug dose (1 mg∕kg) and low fluence (120 mJ∕cm2 at 470 nm). The phototoxic threshold was found to be at 10 J∕cm2 with the same wavelength and drug dose, i.e., about two orders of magnitude larger than the fluence necessary to perform a pO2 measurement. Finally, an illustrative application of this pO2 measurement approach in a hypoxic tumor environment is presented.

Structured output SVM for remote sensing image classification

In the recent years, kernel methods have revealed very powerful tools in many application domains in general and in remote sensing image classification in particular. The special characteristics of remote sensing images (high dimension, few labeled samples and different noise sources) are efficiently dealt with kernel machines. In this paper, we propose the use of structured output learning to improve remote sensing image classification based on kernels. Structured output learning is concerned with the design of machine learning algorithms that not only implement input-output mapping, but also take into account the relations between output labels, thus generalizing unstructured kernel methods. We analyze the framework and introduce it to the remote sensing community. Output similarity is here encoded into SVM classifiers by modifying the model loss function and the kernel function either independently or jointly. Experiments on a very high resolution (VHR) image classification problem shows promising results and opens a wide field of research with structured output kernel methods.

Active mitral ring for post-surgical remote correction of residual mitral regurgitation on the beating heart.

OBJECTIVES: Residual mitral regurgitation after valve repair worsens patients' clinical outcome. Postimplant adjustable mitral rings potentially address this issue, allowing the reshaping of the annulus on the beating heart under echocardiography control. We developed an original mitral ring allowing valve geometry remodelling after the implantation and designed an animal study to assess device effectiveness in correcting residual mitral regurgitation. METHODS: The device consists of two concentric rings: one internal and flexible, sutured to the mitral annulus and a second external and rigid. A third conic element slides between the two rings, modifying the shape of the flexible ring. This sliding element is remotely activated with a rotating tool. Animal model: in adult swine, under cardio pulmonary bypass and cardiac arrest, we shortened the primary chordae of P2 segment to reproduce Type III regurgitation and implanted the active ring. We used intracardiac ultrasound to assess mitral regurgitation and the efficacy of the active ring to correct it. RESULTS: Severe mitral regurgitation (3+ and 4+) was induced in eight animals, 54 ± 6 kg in weight. Vena contracta width decreased from 0.8 ± 0.2 to 0.1 cm; proximal isovelocity surface area radius decreased from 0.8 ± 0.2 to 0.1 cm and effective regurgitant orifice area decreased from 0.50 ± 0.1 to 0.1 ± 0.1 cm(2). Six animals had a reversal of systolic pulmonary flow that normalized following the activation of the device. All corrections were reversible. CONCLUSIONS: Postimplant adjustable mitral ring corrects severe mitral regurgitation through the reversible modification of the annulus geometry on the beating heart. It addresses the frequent and morbid issue of recurrent mitral valve regurgitation.

MR spectroscopy of the human brain with enhanced signal intensity at ultrashort echo times on a clinical platform at 3T and 7T.

Recently, the spin-echo full-intensity acquired localized (SPECIAL) spectroscopy technique was proposed to unite the advantages of short TEs on the order of milliseconds (ms) with full sensitivity and applied to in vivo rat brain. In the present study, SPECIAL was adapted and optimized for use on a clinical platform at 3T and 7T by combining interleaved water suppression (WS) and outer volume saturation (OVS), optimized sequence timing, and improved shimming using FASTMAP. High-quality single voxel spectra of human brain were acquired at TEs below or equal to 6 ms on a clinical 3T and 7T system for six volunteers. Narrow linewidths (6.6 +/- 0.6 Hz at 3T and 12.1 +/- 1.0 Hz at 7T for water) and the high signal-to-noise ratio (SNR) of the artifact-free spectra enabled the quantification of a neurochemical profile consisting of 18 metabolites with Cramér-Rao lower bounds (CRLBs) below 20% at both field strengths. The enhanced sensitivity and increased spectral resolution at 7T compared to 3T allowed a two-fold reduction in scan time, an increased precision of quantification for 12 metabolites, and the additional quantification of lactate with CRLB below 20%. Improved sensitivity at 7T was also demonstrated by a 1.7-fold increase in average SNR (= peak height/root mean square [RMS]-of-noise) per unit-time.

Continuous monitoring of liver oxygenation with near infrared spectroscopy during naso-gastric tube feeding in neonates.

Near infrared spectroscopy (NIRS) is a non-invasive method of estimating the haemoglobin concentration changes in certain tissues. It is frequently used to monitor oxygenation of the brain in neonates. At present it is not clear whether near infrared spectroscopy of other organs (e.g. the liver as a corresponding site in the splanchnic region, which reacts very sensitively to haemodynamic instability) provides reliable values on their tissue oxygenation. The aim of the study was to test near infrared spectroscopy by measuring known physiologic changes in tissue oxygenation of the liver in newborn infants during and after feeding via a naso-gastric tube. The test-retest variability of such measurements was also determined. On 28 occasions in 25 infants we measured the tissue oxygenation index (TOI) of the liver and the brain continuously before, during and 30 minutes after feeding via a gastric tube. Simultaneously we measured arterial oxygen saturation (SaO2), heart rate (HR) and mean arterial blood pressure (MAP). In 10 other newborn infants we performed a test-retest analysis of the liver tissue oxygenation index to estimate the variability in repeated intra-individual measurements. The tissue oxygenation index of the liver increased significantly from 56.7 +/- 7.5% before to 60.3 +/- 5.6% after feeding (p < 0.005), and remained unchanged for the next 30 minutes. The tissue oxygenation index of the brain (62.1 +/- 9.7%), SaO2 (94.4 +/- 7.1%), heart rate (145 +/- 17.3 min-1) and mean arterial blood pressure (52.8 +/- 10.2 mm Hg) did not change significantly. The test-retest variability for intra-individual measurements was 2.7 +/- 2.1%. After bolus feeding the tissue oxygenation index of the liver increased as expected. This indicates that near infrared spectroscopy is suitable for monitoring changes in tissue oxygenation of the liver in newborn infants.

Insights into neuronal cell metabolism using NMR spectroscopy: uridyl diphosphate N-acetyl-glucosamine as a unique metabolic marker.

Making the switch: Compounds 1 and 2 are used as metabolic markers for NMR detection. When neuronal cells switch to a glycolytic state, an uneven distribution of (13) C in the N-acetyl group results, thus giving a mixture of the metabolites 1 and 2. It is therefore possible to monitor flux through different metabolic pathways, such as glycolysis, the tricarboxylic acid cycle, and the hexosamine biosynthetic pathway, using a single molecule.

Characterization of metabolites in infiltrating gliomas using ex vivo &supl;H high-resolution magic angle spinning spectroscopy.

Gliomas are routinely graded according to histopathological criteria established by the World Health Organization. Although this classification can be used to understand some of the variance in the clinical outcome of patients, there is still substantial heterogeneity within and between lesions of the same grade. This study evaluated image-guided tissue samples acquired from a large cohort of patients presenting with either new or recurrent gliomas of grades II-IV using ex vivo proton high-resolution magic angle spinning spectroscopy. The quantification of metabolite levels revealed several discrete profiles associated with primary glioma subtypes, as well as secondary subtypes that had undergone transformation to a higher grade at the time of recurrence. Statistical modeling further demonstrated that these metabolomic profiles could be differentially classified with respect to pathological grading and inter-grade conversions. Importantly, the myo-inositol to total choline index allowed for a separation of recurrent low-grade gliomas on different pathological trajectories, the heightened ratio of phosphocholine to glycerophosphocholine uniformly characterized several forms of glioblastoma multiforme, and the onco-metabolite D-2-hydroxyglutarate was shown to help distinguish secondary from primary grade IV glioma, as well as grade II and III from grade IV glioma. These data provide evidence that metabolite levels are of interest in the assessment of both intra-grade and intra-lesional malignancy. Such information could be used to enhance the diagnostic specificity of in vivo spectroscopy and to aid in the selection of the most appropriate therapy for individual patients.

Identification of early metabolic markers of various degrees of ischemia in the mouse brain by localized H-1 magnetic resonance spectroscopy

Objectives: Magnetic resonance (MR) imaging and spectroscopy (MRS) allow the establishment of the anatomical evolution and neurochemical profiles of ischemic lesions. The aim of the present study was to identify markers of reversible and irreversible damage by comparing the effects of 10-mins middle cerebral artery occlusion (MCAO), mimicking a transient ischemic attack, with the effects of 30-mins MCAO, inducing a striatal lesion. Methods: ICR-CD1 mice were subjected to 10-mins (n = 11) or 30-mins (n = 9) endoluminal MCAO by filament technique at 0 h. The regional cerebral blood flow (CBF) was monitored in all animals by laser- Doppler flowmetry with a flexible probe fixed on the skull with < 20% of baseline CBF during ischemia and > 70% during reperfusion. All MR studies were carried out in a horizontal 14.1T magnet. Fast spin echo images with T2-weighted parameters were acquired to localize the volume of interest and evaluate the lesion size. Immediately after adjustment of field inhomogeneities, localized 1H MRS was applied to obtain the neurochemical profile from the striatum (6 to 8 microliters). Six animals (sham group) underwent nearly identical procedures without MCAO. Results: The 10-mins MCAO induced no MR- or histologically detectable lesion in most of the mice and a small lesion in some of them. We thus had two groups with the same duration of ischemia but a different outcome, which could be compared to sham-operated mice and more severe ischemic mice (30-mins MCAO). Lactate increase, a hallmark of ischemic insult, was only detected significantly after 30-mins MCAO, whereas at 3 h post ischemia, glutamine was increased in all ischemic mice independently of duration and outcome. In contrast, glutamate, and even more so, N-acetyl-aspartate, decreased only in those mice exhibiting visible lesions on T2-weighted images at 24 h. Conclusions: These results suggest that an increased glutamine/glutamate ratio is a sensitive marker indicating the presence of an excitotoxic insult. Glutamate and NAA, on the other hand, appear to predict permanent neuronal damage. In conclusion, as early as 3 h post ischemia, it is possible to identify early metabolic markers manifesting the presence of a mild ischemic insult as well as the lesion outcome at 24 h.