Biolabeling with nanoparticles based on Y(2)O(3):Nd(3+) and luminescence detection in the near-infrared

Neodymium based fluorescence presents several advantages in comparison to conventional rare earth or enzyme-substrate based fluorescence emitting sources (e.g.Tb, HRP). Based on this fact we have herein explored a Nd-based fluoroimmunoassay. We efficiently detected the presence of an oxidized low-density lipoprotein (oxLDL) in human plasma a well-known marker for cardiovascular diseases, which causes around 30% of deaths worldwide. Conventional fluoroimmunoassay uses time-resolved luminescence techniques, with detection in the visible range, to eliminate the fluorescence background from the biological specimens. By using an immunoassay based on functionalized Y(2)O(3):Nd(3+) nanoparticles, where the excitation and emission processes in the Nd(3+) ion occur in the near-infrared (NIR) region, we have succeeded in eliminating the interferences from the biological fluorescence background, avoiding the use of time-resolved techniques. This yields higher emission intensity from the Nd(3+)-nanolabels and efficient detection of anti-oxidized low-density lipoproteins (anti-oxLDL) by Y(2)O(3):Nd(3+)-antibody-antigen conjugation, leading to a novel biolabeling method. (C) 2010 Elsevier B.V. All rights reserved.

Assessment of a new infrared laser transillumination technology (808nm) for the detection of occlusal caries-an in vitro study

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A field trial of infrared thermography as a non-invasive diagnostic tool for early detection of digital dermatitis in dairy cows

Infrared thermography (IRT) was used to detect digital dermatitis (DD) prior to routine claw trimming. A total of 1192 IRT observations were collected from 149 cows on eight farms. All cows were housed in tie-stalls. The maximal surface temperatures of the coronary band (CB) region and skin (S) of the fore and rear feet (mean value of the maximal surface temperatures of both digits for each foot separately, CBmax and Smax) were assessed. Grouping was performed at the foot level (presence of DD, n=99; absence, n=304), or at the cow level (all four feet healthy, n=24) or where there was at least one DD lesion on the rear feet, n=37). For individual cows (n=61), IRT temperature difference was determined by subtracting the mean sum of CBmax and Smax of the rear feet from that of the fore feet. Feet with DD had higher CBmax and Smax (P<0.001) than healthy feet. Smax was significantly higher in feet with infectious DD lesions (M-stage: M2+M4; n=15) than in those with non-infectious M-lesions (M1+M3; n=84) (P=0.03), but this was not the case for CBmax (P=0.12). At the cow level, an optimal cut-off value for detecting DD of 0.99°C (IRT temperature difference between rear and front feet) yielded a sensitivity of 89.1% and a specificity of 66.6%. The results indicate that IRT may be a useful non-invasive diagnostic tool to screen for the presence of DD in dairy cows by measuring CBmax and Smax.

The Role of Infrared Thermography as a Non-Invasive Tool for the Detection of Lameness in Cattle

The use of infrared thermography for the identification of lameness in cattle has increased in recent years largely because of its non-invasive properties, ease of automation and continued cost reductions. Thermography can be used to identify and determine thermal abnormalities in animals by characterizing an increase or decrease in the surface temperature of their skin. The variation in superficial thermal patterns resulting from changes in blood flow in particular can be used to detect inflammation or injury associated with conditions such as foot lesions. Thermography has been used not only as a diagnostic tool, but also to evaluate routine farm management. Since 2000, 14 peer reviewed papers which discuss the assessment of thermography to identify and manage lameness in cattle have been published. There was a large difference in thermography performance in these reported studies. However, thermography was demonstrated to have utility for the detection of contralateral temperature difference and maximum foot temperature on areas of interest. Also apparent in these publications was that a controlled environment is an important issue that should be considered before image scanning.

Detection and quantification of peanut traces in wheat flour by near infrared hyperspectral imaging spectroscopy using principal-component analysis

The use of a common environment for processing different powder foods in the industry has increased the risk of finding peanut traces in powder foods. The analytical methods commonly used for detection of peanut such as enzyme-linked immunosorbent assay (ELISA) and real-time polymerase chain reaction (RT-PCR) represent high specificity and sensitivity but are destructive and time-consuming, and require highly skilled experimenters. The feasibility of NIR hyperspectral imaging (HSI) is studied for the detection of peanut traces down to 0.01% by weight. A principal-component analysis (PCA) was carried out on a dataset of peanut and flour spectra. The obtained loadings were applied to the HSI images of adulterated wheat flour samples with peanut traces. As a result, HSI images were reduced to score images with enhanced contrast between peanut and flour particles. Finally, a threshold was fixed in score images to obtain a binary classification image, and the percentage of peanut adulteration was compared with the percentage of pixels identified as peanut particles. This study allowed the detection of traces of peanut down to 0.01% and quantification of peanut adulteration from 10% to 0.1% with a coefficient of determination (r2) of 0.946. These results show the feasibility of using HSI systems for the detection of peanut traces in conjunction with chemical procedures, such as RT-PCR and ELISA to facilitate enhanced quality-control surveillance on food-product processing lines.

Continuous statistical modelling for rapid detection of adulteration of extra virgin olive oil using mid infrared and Raman spectroscopic data

The main objective of this work was to develop a novel dimensionality reduction technique as a part of an integrated pattern recognition solution capable of identifying adulterants such as hazelnut oil in extra virgin olive oil at low percentages based on spectroscopic chemical fingerprints. A novel Continuous Locality Preserving Projections (CLPP) technique is proposed which allows the modelling of the continuous nature of the produced in-house admixtures as data series instead of discrete points. The maintenance of the continuous structure of the data manifold enables the better visualisation of this examined classification problem and facilitates the more accurate utilisation of the manifold for detecting the adulterants. The performance of the proposed technique is validated with two different spectroscopic techniques (Raman and Fourier transform infrared, FT-IR). In all cases studied, CLPP accompanied by k-Nearest Neighbors (kNN) algorithm was found to outperform any other state-of-the-art pattern recognition techniques.

Detection and assessment of electrocution in endangered raptors by infrared thermography

BACKGROUND Most European birds of prey find themselves in a poor state of conservation, with electrocution as one of the most frequent causes of unnatural death. Since early detection of electrocution is difficult, treatment is usually implemented late, which reduces its effectiveness. By considering that electrocution reduces tissue temperature, it may be detectable by thermography, which would allow a more rapid identification. Three individuals from three endangered raptor species [Spanish imperial eagle (Aquila adalberti), Lammergeier (Gypaetus barbatus) and Osprey (Pandion haliaetus)] were studied thermographically from the time they were admitted to a rehabilitation centre to the time their clinical cases were resolved. CASES PRESENTATION The three raptors presented lesions lacking thermal bilateral symmetry and were consistent with electrocution of feet, wings and eyes, visible by thermography before than clinically; lesions were well-defined and showed a lower temperature than the surrounding tissue. Some lesions evolved thermally and clinically until the appearance of normal tissue recovered, while others evolved and became necrotic. A histopathological analysis of a damaged finger amputated off a Lammergeier, and the necropsy and histopathology examination of an osprey, confirmed the electrocution diagnosis. CONCLUSIONS These results suggest that thermography is effective and useful for the objective and early detection and monitoring of electrocuted birds, and that it may prove especially useful for examining live animals that require no amputation or cannot be subjected to invasive histopathology.

Infra-red pupil detection for use in a face recognition system

This paper presents a new method of eye localisation and face segmentation for use in a face recognition system. By using two near infrared light sources, we have shown that the face can be coarsely segmented, and the eyes can be accurately located, increasing the accuracy of the face localisation and improving the overall speed of the system. The system is able to locate both eyes within 25% of the eye-to-eye distance in over 96% of test cases.

Hand-held monocular SLAM in thermal-infrared

Thermal-infrared imagery is relatively robust to many of the failure conditions of visual and laser-based SLAM systems, such as fog, dust and smoke. The ability to use thermal-infrared video for localization is therefore highly appealing for many applications. However, operating in thermal-infrared is beyond the capacity of existing SLAM implementations. This paper presents the first known monocular SLAM system designed and tested for hand-held use in the thermal-infrared modality. The implementation includes a flexible feature detection layer able to achieve robust feature tracking in high-noise, low-texture thermal images. A novel approach for structure initialization is also presented. The system is robust to irregular motion and capable of handling the unique mechanical shutter interruptions common to thermal-infrared cameras. The evaluation demonstrates promising performance of the algorithm in several environments.

The development of a new method for the determination of concentrations of carbonaceous gases using a non-dispersive infrared sensor

An analytical method for the detection of carbonaceous gases by a non-dispersive infrared sensor (NDIR) has been developed. The calibration plots of six carbonaceous gases including CO2, CH4, CO, C2H2, C2H4 and C2H6 were obtained and the reproducibility determined to verify the feasibility of this gas monitoring method. The results prove that squared correlation coefficients for the six gas measurements are greater than 0.999. The reproducibility is excellent, thus indicating that this analytical method is useful to determinate the concentrations of carbonaceous gases.

Breast cancer detection from thermal images using bispectral invariant features

Highly sensitive infrared (IR) cameras provide high-resolution diagnostic images of the temperature and vascular changes of breasts. These images can be processed to emphasize hot spots that exhibit early and subtle changes owing to pathology. The resulting images show clusters that appear random in shape and spatial distribution but carry class dependent information in shape and texture. Automated pattern recognition techniques are challenged because of changes in location, size and orientation of these clusters. Higher order spectral invariant features provide robustness to such transformations and are suited for texture and shape dependent information extraction from noisy images. In this work, the effectiveness of bispectral invariant features in diagnostic classification of breast thermal images into malignant, benign and normal classes is evaluated and a phase-only variant of these features is proposed. High resolution IR images of breasts, captured with measuring accuracy of ±0.4% (full scale) and temperature resolution of 0.1 °C black body, depicting malignant, benign and normal pathologies are used in this study. Breast images are registered using their lower boundaries, automatically extracted using landmark points whose locations are learned during training. Boundaries are extracted using Canny edge detection and elimination of inner edges. Breast images are then segmented using fuzzy c-means clustering and the hottest regions are selected for feature extraction. Bispectral invariant features are extracted from Radon projections of these images. An Adaboost classifier is used to select and fuse the best features during training and then classify unseen test images into malignant, benign and normal classes. A data set comprising 9 malignant, 12 benign and 11 normal cases is used for evaluation of performance. Malignant cases are detected with 95% accuracy. A variant of the features using the normalized bispectrum, which discards all magnitude information, is shown to perform better for classification between benign and normal cases, with 83% accuracy compared to 66% for the original.

SERS based detection of barcoded gold nanoparticle assemblies from within animal tissue

We have explored the potential of deep Raman spectroscopy, specifically surface enhanced spatially offset Raman spectroscopy (SESORS), for non-invasive detection from within animal tissue, by employing SERS-barcoded nanoparticle (NP) assemblies as the diagnostic agent. This concept has been experimentally verified in a clinic-relevant backscattered Raman system with an excitation line of 785 nm under ex vivo conditions. We have shown that our SORS system, with a fixed offset of 2-3 mm, offered sensitive probing of injected QTH-barcoded NP assemblies through animal tissue containing both protein and lipid. In comparison to that of non-aggregated SERS-barcoded gold NPs, we have demonstrated that the tailored SERS-barcoded aggregated NP assemblies have significantly higher detection sensitivity. We report that these NP assemblies can be readily detected at depths of 7-8 mm from within animal proteinaceous tissue with high signal-to-noise (S/N) ratio. In addition they could also be detected from beneath 1-2 mm of animal tissue with high lipid content, which generally poses a challenge due to high absorption of lipids in the near-infrared region. We have also shown that the signal intensity and S/N ratio at a particular depth is a function of the SERS tag concentration used and that our SORS system has a QTH detection limit of 10-6 M. Higher detection depths may possibly be obtained with optimization of the NP assemblies, along with improvements in the instrumentation. Such NP assemblies offer prospects for in vivo, non-invasive detection of tumours along with scope for incorporation of drugs and their targeted and controlled release at tumour sites. These diagnostic agents combined with drug delivery systems could serve as a “theranostic agent”, an integration of diagnostics and therapeutics into a single platform.