Epidural analgesia with morphine or buprenorphine in ponies with lipopolysaccharide (LPS)-induced carpal synovitis

This study evaluated the analgesia effects of the epidural administration of 0.1 mg/kg bodyweight (BW) of morphine or 5 mu g/kg BW of buprenorphine in ponies with radiocarpal joint synovitis. Six ponies were submitted to 3 epidural treatments: the control group (C) received 0.15 mL/kg BW of a 0.9% sodium chloride (NaCl) solution; group M was administered 0.1 mg/kg BW of morphine; and group B was administered 5 mu g/kg BW of buprenorphine, both diluted in 0.9% NaCl to a total volume of 0.15 mL/kg BW administered epidurally at 10 s/mL. The synovitis model was induced by injecting 0.5 ng of lipopolysaccharide (LPS) in the left or right radiocarpal joint. An epidural catheter was later introduced in the lumbosacral space and advanced up to the thoracolumbar level. The treatment started 6 h after synovitis induction. Lameness, maximum angle of carpal flexion, heart rate, systolic arterial pressure, respiratory rate, temperature, and intestinal motility were evaluated before LPS injection (baseline), 6 h after LPS injection (time 0), and 0.5, 1, 2, 4, 6, 8, 10, 12, 16, 20, and 24 h after treatments. Although the model of synovitis produced clear clinical signs of inflammation, the lameness scores in group C were different from the baseline for only up to 12 h. Both morphine and buprenorphine showed a reduction in the degree of lameness starting at 0.5 and 6 h, respectively. Reduced intestinal motility was observed at 0.5 h in group M and at 0.5 to 1 h in group B. Epidural morphine was a more effective analgesic that lasted for more than 12 h and without side effects. It was concluded that morphine would be a valuable analgesic option to alleviate joint pain in the thoracic limbs in ponies.

PCA Tomography: how to extract information from data cubes

Astronomy has evolved almost exclusively by the use of spectroscopic and imaging techniques, operated separately. With the development of modern technologies, it is possible to obtain data cubes in which one combines both techniques simultaneously, producing images with spectral resolution. To extract information from them can be quite complex, and hence the development of new methods of data analysis is desirable. We present a method of analysis of data cube (data from single field observations, containing two spatial and one spectral dimension) that uses Principal Component Analysis (PCA) to express the data in the form of reduced dimensionality, facilitating efficient information extraction from very large data sets. PCA transforms the system of correlated coordinates into a system of uncorrelated coordinates ordered by principal components of decreasing variance. The new coordinates are referred to as eigenvectors, and the projections of the data on to these coordinates produce images we will call tomograms. The association of the tomograms (images) to eigenvectors (spectra) is important for the interpretation of both. The eigenvectors are mutually orthogonal, and this information is fundamental for their handling and interpretation. When the data cube shows objects that present uncorrelated physical phenomena, the eigenvector`s orthogonality may be instrumental in separating and identifying them. By handling eigenvectors and tomograms, one can enhance features, extract noise, compress data, extract spectra, etc. We applied the method, for illustration purpose only, to the central region of the low ionization nuclear emission region (LINER) galaxy NGC 4736, and demonstrate that it has a type 1 active nucleus, not known before. Furthermore, we show that it is displaced from the centre of its stellar bulge.

Morphine peripheral analgesia depends on activation of the PI3K gamma/AKT/nNOS/NO/K(ATP) signaling pathway

Morphine is one of the most prescribed and effective drugs used for the treatment of acute and chronic pain conditions. In addition to its central effects, morphine can also produce peripheral analgesia. However, the mechanisms underlying this peripheral action of morphine have not yet been fully elucidated. Here, we show that the peripheral antinociceptive effect of morphine is lost in neuronal nitric-oxide synthase null mice and that morphine induces the production of nitric oxide in primary nociceptive neurons. The activation of the nitric-oxide pathway by morphine was dependent on an initial stimulation of PI3K gamma/AKT protein kinase B (AKT) and culminated in increasedactivation of K(ATP) channels. In the latter, this intracellular signaling pathway might cause a hyperpolarization of nociceptive neurons, and it is fundamental for the direct blockade of inflammatory pain by morphine. This understanding offers new targets for analgesic drug development.

3D face computational photography using PCA spaces

In this paper, we present a 3D face photography system based on a facial expression training dataset, composed of both facial range images (3D geometry) and facial texture (2D photography). The proposed system allows one to obtain a 3D geometry representation of a given face provided as a 2D photography, which undergoes a series of transformations through the texture and geometry spaces estimated. In the training phase of the system, the facial landmarks are obtained by an active shape model (ASM) extracted from the 2D gray-level photography. Principal components analysis (PCA) is then used to represent the face dataset, thus defining an orthonormal basis of texture and another of geometry. In the reconstruction phase, an input is given by a face image to which the ASM is matched. The extracted facial landmarks and the face image are fed to the PCA basis transform, and a 3D version of the 2D input image is built. Experimental tests using a new dataset of 70 facial expressions belonging to ten subjects as training set show rapid reconstructed 3D faces which maintain spatial coherence similar to the human perception, thus corroborating the efficiency and the applicability of the proposed system.

Chemotaxonomic relationships in Celastraceae inferred from principal component analysis (PCA) and partial least squares (PLS)

This paper describes a chemotaxonomic analysis of a database of triterpenoid compounds from the Celastraceae family using principal component analysis (PCA). The numbers of occurrences of thirty types of triterpene skeleton in different tribes of the family were used as variables. The study shows that PCA applied to chemical data can contribute to an intrafamilial classification of Celastraceae, once some questionable taxa affinity was observed, from chemotaxonomic inferences about genera and they are in agreement with the phylogeny previously proposed. The inclusion of Hippocrateaceae within Celastraceae is supported by the triterpene chemistry.