In this study, the antiulcerogenic effect of essential oil from Baccharis dracunculifolia was evaluated using the model of acute gastric lesions induced by ethanol. The ulcerative lesion index (ULI) was significantly reduced by oral administration of the essential oil of B. dracunculifolia at doses of 50, 250 and 500 mg/kg which reduced the lesions by 42.79, 45.70 and 61.61%, respectively. The analysis of the chemical composition of the essential oil from B. dracunculifolia by GC showed that this was composed mainly of mono-and sesquiterpenes and the majority compound was nerolidol. Therefore, antiulcerogenic activity of nerolidol (50, 250 and 500 mg/kg) was investigated using ethanol-, indomethacin-and stress-induced ulcer models in rat. In the stress-induced ulcer model, a significant reduction of the ULI in animals treated with nerolidol (50, 250 and 500 mg/kg) and cimetidine (100 mg/kg) was observed, compared to the control group (p Ͻ 0.05). The percentage of inhibition of ulcer was 41.22, 51.31, 56.57 and 53.50% in groups treated with 50, 250, 500 mg/kg of nerolidol and 100 mg/kg of cimetidine (positive control), respectively. Regarding ethanol-and indomethacin-induced ulcer models, it was observed that the treatment with nerolidol (250 and 500 mg/ kg) significantly reduced the ULI in comparison with the control group (p Ͻ 0.05). The dose of 50 mg/kg reduced the parameters analyzed but this was not statistically significant. In the ethanol-induced model percentage of inhibition of ulcer was 34.20, 52.63, 87.63 and 50.87% in groups treated with 50, 250, 500 mg/kg of nerolidol and 30 mg/kg of omeprazol (positive control), respectively. In indomethacin-ulcer the percentage of inhibition of ulcer was 34.69, 40.80, 51.02 and 46.93% in groups treated with 50, 250, 500 mg/kg of nerolidol and 100 mg/ kg of cimetidine (positive control), respectively. The results of this study show that nerolidol displays antiulcer activity, as it significantly inhibited the formation of ulcers induced in different animal models. However, further pharmacological and toxicological investigations, to delineate the mechanism(s) of action and the toxic effects, are required to allow the use of nerolidol for the treatment of gastric ulcer.
In this paper, an irregular displacement-based lensless wide-field microscopy imaging platform is presented by combining digital in-line holography and computational pixel super-resolution using multi-frame processing. The samples are illuminated by a nearly coherent illumination system, where the hologram shadows are projected into a complementary metal-oxide semiconductor-based imaging sensor. To increase the resolution, a multi-frame pixel resolution approach is employed to produce a single holographic image from multiple frame observations of the scene, with small planar displacements. Displacements are resolved by a hybrid approach: (i) alignment of the LR images by a fast feature-based registration method, and (ii) fine adjustment of the sub-pixel information using a continuous optimization approach designed to find the global optimum solution. Numerical method for phase-retrieval is applied to decode the signal and reconstruct the morphological details of the analyzed sample. The presented approach was evaluated with various biological samples including sperm and platelets, whose dimensions are in the order of a few microns. The obtained results demonstrate a spatial resolution of 1.55 µm on a field-of-view of ≈30 mm2.
The current work describes the use of multidimensional Euclidean geometric distance (EGD) and Bayesian methods to characterize and classify the sky and cloud patterns present in image pixels. From specific images and using visualization tools, it was noticed that sky and cloud patterns occupy a typical locus on the redgreen-blue (RGB) color space. These two patterns were linearly distributed parallel to the RGB cube's main diagonal at distinct distances. A characterization of the cloud and sky patterns EGD was done by supervision to eliminate errors due to outlier patterns in the analysis. The exploratory data analysis of EGD for sky and cloud patterns showed a Gaussian distribution, allowing generalizations based on the central limit theorem. An intensity scale of brightness is proposed from the Euclidean geometric projection (EGP) on the RGB cube's main diagonal. An EGD-based classification method was adapted to be properly compared with existing ones found in related literature, because they restrict the examined color-space domain. Elimination of this limitation was considered a sufficient criterion for a classification system that has resource restrictions. The EGD-adapted results showed a correlation of 97.9% for clouds and 98.4% for sky when compared to established classification methods. It was also observed that EGD was able to classify cloud and sky patterns invariant to their brightness attributes and with reduced variability because of the sun zenith angle changes. In addition, it was observed that Mie scattering could be noticed and eliminated (together with the reflector's dust) as an outlier during the analysis. Although Mie scattering could be classified with additional analysis, this is left as a suggestion for future work.
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