5 resultados para SURF

em Repositório da Produção Científica e Intelectual da Unicamp


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The mesoporous SBA-15 silica with uniform hexagonal pore, narrow pore size distribution and tuneable pore diameter was organofunctionalized with glutaraldehyde-bridged silylating agent. The precursor and its derivative silicas were ibuprofen-loaded for controlled delivery in simulated biological fluids. The synthesized silicas were characterized by elemental analysis, infrared spectroscopy, (13)C and (29)Si solid state NMR spectroscopy, nitrogen adsorption, X-ray diffractometry, thermogravimetry and scanning electron microscopy. Surface functionalization with amine containing bridged hydrophobic structure resulted in significantly decreased surface area from 802.4 to 63.0 m(2) g(-1) and pore diameter 8.0-6.0 nm, which ultimately increased the drug-loading capacity from 18.0% up to 28.3% and a very slow release rate of ibuprofen over the period of 72.5h. The in vitro drug release demonstrated that SBA-15 presented the fastest release from 25% to 27% and SBA-15GA gave near 10% of drug release in all fluids during 72.5 h. The Korsmeyer-Peppas model better fits the release data with the Fickian diffusion mechanism and zero order kinetics for synthesized mesoporous silicas. Both pore sizes and hydrophobicity influenced the rate of the release process, indicating that the chemically modified silica can be suggested to design formulation of slow and constant release over a defined period, to avoid repeated administration.

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Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.

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It is well known that long term use of shampoo causes damage to human hair. Although the Lowry method has been widely used to quantify hair damage, it is unsuitable to determine this in the presence of some surfactants and there is no other method proposed in literature. In this work, a different method is used to investigate and compare the hair damage induced by four types of surfactants (including three commercial-grade surfactants) and water. Hair samples were immersed in aqueous solution of surfactants under conditions that resemble a shower (38 °C, constant shaking). These solutions become colored with time of contact with hair and its UV-vis spectra were recorded. For comparison, the amount of extracted proteins from hair by sodium dodecyl sulfate (SDS) and by water were estimated by the Lowry method. Additionally, non-pigmented vs. pigmented hair and also sepia melanin were used to understand the washing solution color and their spectra. The results presented herein show that hair degradation is mostly caused by the extraction of proteins, cuticle fragments and melanin granules from hair fiber. It was found that the intensity of solution color varies with the charge density of the surfactants. Furthermore, the intensity of solution color can be correlated to the amount of proteins quantified by the Lowry method as well as to the degree of hair damage. UV-vis spectrum of hair washing solutions is a simple and straightforward method to quantify and compare hair damages induced by different commercial surfactants.

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Pathological conditions associated with the impairment of nitric oxide (NO) production in the vasculature, such as Raynaud's syndrome and diabetic angiopathy, have stimulated the development of new biomaterials capable of delivering NO topically. With this purpose, we modified poly(vinyl-alcohol) (PVA) by chemically crosslinking it via esterification with mercaptosuccinic acid. This reaction allowed the casting of sulfhydrylated PVA (PVA-SH) films. Differential scanning calorimetry and X-ray diffractometry showed that the crosslinking reaction completely suppressed the crystallization of PVA, leading to a non-porous film with a homogeneous distribution of -SH groups. The remaining free hydroxyl groups in the PVA-SH network conferred partial hydrophylicity to the material, which was responsible for a swelling degree of ca. 110%. The PVA-SH films were subjected to an S-nitrosation reaction of the -SH groups, yielding a PVA containing S-nitrosothiol groups (PVA-SNO). Amperometric and chemiluminescence measurements showed that the PVA-SNO films were capable of releasing NO spontaneously after immersion in physiological medium. Laser Doppler-flowmetry, used to assess the blood flow in the dermal microcirculation, showed that the topical application of hydrated PVA-SNO films on the health skin led to a dose- and time-dependent increase of more than 5-fold in the dermal baseline blood flow in less than 10min, with a prolonged action of more than 4h during continuous application. These results show that PVA-SNO films might emerge as a new material with potential for the topical treatment of microvascular skin disorders.

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Several biotechnological processes can show an undesirable formation of emulsions making difficult phase separation and product recovery. The breakup of oil-in-water emulsions stabilized by yeast was studied using different physical and chemical methods. These emulsions were composed by deionized water, hexadecane and commercial yeast (Saccharomyces cerevisiae). The stability of the emulsions was evaluated varying the yeast concentration from 7.47 to 22.11% (w/w) and the phases obtained after gravity separation were evaluated on chemical composition, droplet size distribution, rheological behavior and optical microscopy. The cream phase showed kinetic stability attributed to mechanisms as electrostatic repulsion between the droplets, a possible Pickering-type stabilization and the viscoelastic properties of the concentrated emulsion. Oil recovery from cream phase was performed using gravity separation, centrifugation, heating and addition of demulsifier agents (alcohols and magnetic nanoparticles). Long centrifugation time and high centrifugal forces (2h/150,000×g) were necessary to obtain a complete oil recovery. The heat treatment (60°C) was not enough to promote a satisfactory oil separation. Addition of alcohols followed by centrifugation enhanced oil recovery: butanol addition allowed almost complete phase separation of the emulsion while ethanol addition resulted in 84% of oil recovery. Implementation of this method, however, would require additional steps for solvent separation. Addition of charged magnetic nanoparticles was effective by interacting electrostatically with the interface, resulting in emulsion destabilization under a magnetic field. This method reached almost 96% of oil recovery and it was potentially advantageous since no additional steps might be necessary for further purifying the recovered oil.