862 resultados para image-based dietary records
Resumo:
Promotion of adherence to healthy-eating norms has become an important element of nutrition policy in the United States and other developed countries. We assess the potential consumption impacts of adherence to a set of recommended dietary norms in the United States using a mathematical programming approach. We find that adherence to recommended dietary norms would involve significant changes in diets, with large reductions in the consumption of fats and oils along with large increases in the consumption of fruits, vegetables, and cereals. Compliance with norms recommended by the World Health Organization for energy derived from sugar would involve sharp reductions in sugar intakes. We also analyze how dietary adjustments required vary across demographic groups. Most socio-demographic characteristics appear to have relatively little influence on the pattern of adjustment required to comply with norms, Income levels have little effect on required dietary adjustments. Education is the only characteristic to have a significant influence on the magnitude of adjustments required. The least educated rather than the poorest have to bear the highest burden of adjustment. Out- analysis suggests that fiscal measures like nutrient-based taxes may not be as regressive as commonly believed. Dissemination of healthy-eating norms to the less educated will be a key challenge for nutrition policy.
Resumo:
Promotion of adherence to healthy-eating norms has become an important element of nutrition policy in the United States and other developed countries. We assess the potential consumption impacts of adherence to a set of recommended dietary norms in the United States using a mathematical programming approach. We find that adherence to recommended dietary norms would involve significant changes in diets, with large reductions in the consumption of fats and oils along with large increases in the consumption of fruits, vegetables, and cereals. Compliance with norms recommended by the World Health Organization for energy derived from sugar would involve sharp reductions in sugar intakes. We also analyze how dietary adjustments required vary across demographic groups. Most socio-demographic characteristics appear to have relatively little influence on the pattern of adjustment required to comply with norms, Income levels have little effect on required dietary adjustments. Education is the only characteristic to have a significant influence on the magnitude of adjustments required. The least educated rather than the poorest have to bear the highest burden of adjustment. Out- analysis suggests that fiscal measures like nutrient-based taxes may not be as regressive as commonly believed. Dissemination of healthy-eating norms to the less educated will be a key challenge for nutrition policy.
Resumo:
In order to establish firm evidence for the health effects of dietary polyphenol consumption, it is essential to have quantitative information regarding their dietary intake. The usefulness of the current methods, which rely mainly on the assessment of polyphenol intake using food records and food composition tables, is limited as they fail to assess total intake accurately. This review highlights the problems associated with such methods with regard to polyphenol-intake predictions. We suggest that the development of biological biomarkers, measured in both blood and urine, are essential for making accurate estimates of polyphenol intake. However, the relationship between dietary intakes and nutritional biomarkers are often highly complex. This review identifies the criteria that must be considered in the development of such biomarkers. In addition, we provide an assessment of the limited number of potential biomarkers of polyphenol intake currently available.
Resumo:
Sixteen early to mid lactation Finnish Ayrshire dairy cows were used in a cyclic change-over experiment with four 21-day experimental periods and a 4 5 2 factorial arrangement of treatments to evaluate the effects of heat-treated rapeseed expeller and solvent-extracted soya-bean meal protein supplements on animal performance. Dietary treatments consisted of grass silage offered ad libitum supplemented with a fixed amount of a cereal based concentrate (10 kg/day on a fresh weight basis) containing 120, 150, 180 or 210 g crude protein (CP) per kg dry matter (DM). Concentrate CP content was manipulated by replacement of basal ingredients (g/kg) with either rapeseed expeller (R; 120, 240 and 360) or soya-bean meal (S; 80, 160 and 240). Increases in concentrate CP stimulated linear increases (P < 0.05) in silage intake (mean 22.5 and 23.8 g DM per g/kg increase in dietary CP content, for R and S, respectively) and milk production. Concentrate inclusion of rapeseed expeller elicited higher (P < 0.01) milk yield and milk protein output responses (mean 108 and 3.71 g/day per g/kg DM increase in dietary CP content) than soya-bean meal (corresponding values 62 and 2.57). Improvements in the apparent utilization of dietary nitrogen for milk protein synthesis (mean 0.282 and 0.274, for R and S, respectively) were associated with higher (P < 0.05) plasma concentrations of histidine, branched-chain, essential and total amino acids (35, 482, 902 and 2240 and 26, 410, 800 and 2119 mu mol/l, respectively) and lower (P < 0.01) concentrations of urea (corresponding values 4.11 and 4.52 mmol/l). Heat-treated rapeseed expeller proved to be a more effective protein supplement than solvent-extracted soya-bean meal for cows offered grass silage-based diets.
Resumo:
Mechanisms underlying milk fat conjugated linoleic acid (CLA) responses to supplements of fish oil were investigated using five lactating cows each fitted with a rumen cannula in a simple experiment consisting of two consecutive 14-day experimental periods. During the first period cows were offered 18 kg dry matter (DM) per day of a basal (B) diet formulated from grass silage and a cereal based-concentrate (0.6 : 0.4; forage : concentrate ratio, on a DM basis) followed by the same diet supplemented with 250 g fish oil per day (FO) in the second period. The flow of non-esterified fatty acids leaving the rumen was measured using the omasal sampling technique in combination with a triple indigestible marker method based on Li-Co-EDTA, Yb-acetate and Cr-mordanted straw. Fish oil decreased DM intake and milk yield, but had no effect on milk constituent content. Milk fat trans-11C(18:1), total trans-C-18:1, cis-9 trans-11 CLA, total CLA, C-18 :2 (n- 6) and total C-18:2 content were increased in response to fish oil from 1.80, 4.51, 0.39, 0. 56, 0.90 and 1.41 to 9.39, 14.39, 1.66, 1.85, 1.25 and 4.00 g/100 g total fatty acids, respectively. Increases in the cis-9, trans-11 isomer accounted for proportionately 0.89 of the CLA response to fish oil. Furthermore, fish oil decreased the flow of C-18:0 (283 and 47 g/day for B and FO, respectively) and increased that of trans-C-18:1 fatty acids entering the omasal canal (38 and 182 g/day). Omasal flows of trans-C-18:1 acids with double bonds in positions from delta-4 to -15 inclusive were enhanced, but the effects were isomer dependent and primarily associated with an increase in trans-11C(18:1) leaving the rumen (17.1 and 121.1 g/day for B and FO, respectively). Fish oil had no effect on total (4.36 and 3.50 g/day) or cis-9, trans-11 CLA (2.86 and 2.08 g/day) entering the omasal canal. Flows of cis-9, trans-11 CLA were lower than the secretion of this isomer in milk. Comparison with the transfer of the trans-9, trans-11 isomer synthesized in the rumen suggested that proportionately 0.66 and 0.97 of cis-9, trans-11 CLA was derived from endogenous conversion of trans-11 C-18:1 in the mammary gland for B and FO, respectively. It is concluded that fish oil enhances milk fat cis-9, trans-11 CLA content in response to increased supply of trans-11 C-18:1 that arises from an inhibition of trans C-18:1 reduction in the rumen.
Resumo:
Aims: To develop a quantitative equation [prebiotic index ( PI)] to aid the analysis of prebiotic fermentation of commercially available and novel prebiotic carbohydrates in vitro, using previously published fermentation data. Methods: The PI equation is based on the changes in key bacterial groups during fermentation. The bacterial groups incorporated into this PI equation were bifidobacteria, lactobacilli, clostridia and bacteroides. The changes in these bacterial groups from previous studies were entered into the PI equation in order to determine a quantitative PI score. PI scores were than compared with the qualitative conclusions made in these publications. In general the PI scores agreed with the qualitative conclusions drawn and provided a quantitative measure. Conclusions: The PI allows the magnitude of prebiotic effects to be quantified rather than evaluations being solely qualitative. Significance and Impact of the Study: The PI equation may be of great use in quantifying prebiotic effects in vitro. It is expected that this will facilitate more rational food product development and the development of more potent prebiotics with activity at lower doses.
Resumo:
Objective: To describe the calculations and approaches used to design experimental diets of differing saturated fatty acid (SFA) and monounsaturated fatty acid (MUFA) compositions for use in a long-term dietary intervention study, and to evaluate the degree to which the dietary targets were met. Design, setting and subjects: Fifty-one students living in a university hall of residence consumed a reference (SFA) diet for 8 weeks followed by either a moderate MUFA (MM) diet or a high MUFA (HM) diet for 16 weeks. The three diets were designed to differ only in their proportions of SFA and MUFA, while keeping total fat, polyunsaturated fatty acids (PUFA), trans-fatty acids, and the ratio of palmitic to stearic acid, and n-6 to n-3 PUFA, unchanged. Results: Using habitual diet records and a standardised database for food fatty acid compositions, a sequential process of theoretical fat substitutions enabled suitable fat sources for use in the three diets to be identified, and experimental margarines for baking, spreading and the manufacture of snack foods to be designed. The dietary intervention was largely successful in achieving the fatty acid targets of the three diets, although unintended differences between the original target and the analysed fatty acid composition of the experimental margarines resulted in a lower than anticipated MUFA intake on the HM diet, and a lower ratio of palmitic to stearic acid compared with the reference or MM diet. Conclusions: This study has revealed important theoretical considerations that should be taken into account when designing diets of specific fatty acid composition, as well as practical issues of implementation.
Resumo:
Prebiotics are non-digestible (by the host) food ingredients that have a beneficial effect through their selective metabolism in the intestinal tract. Key to this is the specificity of microbial changes. The present paper reviews the concept in terms of three criteria: (a) resistance to gastric acidity, hydrolysis by mammalian enzymes and gastrointestinal absorption; (b) fermentation by intestinal microflora; (c) selective stimulation of the growth and/or activity of intestinal bacteria associated with health and wellbeing. The conclusion is that prebiotics that currently fulfil these three criteria are fructo-oligosaccharides, galacto-oligosaccharides and lactulose, although promise does exist with several other dietary carbohydrates. Given the range of food vehicles that may be fortified by prebiotics, their ability to confer positive microflora changes and the health aspects that may accrue, it is important that robust technologies to assay functionality are used. This would include a molecular-based approach to determine flora changes. The future use of prebiotics may allow species-level changes in the microbiota, an extrapolation into genera other than the bifidobacteria and lactobacilli, and allow preferential use in disease-prone areas of the body.
Resumo:
The average UK adult consumes less than three portions of fruit and vegetables daily, despite evidence to suggest that consuming five portions daily could help prevent chronic diseases. It is recommended that fruit juice should only count as one of these portions, as juicing removes fibre and releases sugars. However, fruit juices contain beneficial compounds such as vitamin C and flavonoids and could be a useful source of dietary phytochemicals. Two randomised controlled cross-over intervention studies investigating the effects of chronic and acute consumption of commercially-available fruit- and vegetable-puree-based drinks (FVPD) on bioavailability, antioxidant status and CVD risk factors are described. Blood and urine samples were collected during both studies and vascular tone was measured using laser Doppler imaging. In the chronic intervention study FVPD consumption was found to significantly increase dietary carotenoids (P = 0.001) and vitamin C (P = 0.003). Plasma carotenoids were increased (P = 0.001), but the increase in plasma vitamin C was not significant. There were no significant effects on oxidative stress, antioxidant status and other CVD risk factors. In the acute intervention study FVPD were found to increase total plasma nitrate and nitrite (P = 0.001) and plasma vitamin C (P = 0.002). There was no effect on plasma lipids or uric acid, but there was a lower glucose and insulin peak concentration after consumption of the FVPD compared with the sugar-matched control. There was a trend towards increased vasodilation following both chronic and acute FVPD consumption. All volunteers were retrospectively genotyped for the eNOS G298T polymorphism and the effect of genotype on the measurements is discussed. Overall, there was a non-significant trend towards increased endothelium-dependent vasodilation following both acute and chronic FVPD consumption. However, there was a significant time x treatment effect (P < 0.05) of acute FVPD consumption in individuals with the GG variant of the eNOS gene.
Resumo:
Dietary antioxidants can affect cellular processes relevant to chronic inflammatory diseases such as atherosclerosis. We have used non- standard techniques to quantify effects of the antioxidant soy isoflavones genistein and daidzein on translocation of Nuclear Factor-KB (NF-KB) and nitric oxide (NO) production, which are important in these diseases. Translocation was quantified using confocal immunofluoresecence microscopy and ratiometric image analysis. NO was quantified by an electrochemical method after reduction of its oxidation products in cell culture supernatants. Activation of the RAW 264.7 murine monocyte/macrophage cell line increased the ratio of nuclear to cytoplasmic immunostaining for NF-kB. The increase was exacerbated by pre-treatment with genistein or daidzein. To show that decreases could also be detected, pre-treatment with the pine bark extract Pycnogenol (R) r was examined, and found to reduce translocation. NO production was also increased by activation, but was reduced by pre-treatment with genistein or daidzein. In the EA. hy926 human endothelial cell line, constitutive production was detectable and was increased by thrombin. The confocal and electrochemical methods gave data that agreed with results obtained using the established electromobility shift and Griess assays, but were more sensitive, more convenient, gave more detailed information and avoided the use of radioisotopes.
Resumo:
Several pixel-based people counting methods have been developed over the years. Among these the product of scale-weighted pixel sums and a linear correlation coefficient is a popular people counting approach. However most approaches have paid little attention to resolving the true background and instead take all foreground pixels into account. With large crowds moving at varying speeds and with the presence of other moving objects such as vehicles this approach is prone to problems. In this paper we present a method which concentrates on determining the true-foreground, i.e. human-image pixels only. To do this we have proposed, implemented and comparatively evaluated a human detection layer to make people counting more robust in the presence of noise and lack of empty background sequences. We show the effect of combining human detection with a pixel-map based algorithm to i) count only human-classified pixels and ii) prevent foreground pixels belonging to humans from being absorbed into the background model. We evaluate the performance of this approach on the PETS 2009 dataset using various configurations of the proposed methods. Our evaluation demonstrates that the basic benchmark method we implemented can achieve an accuracy of up to 87% on sequence ¿S1.L1 13-57 View 001¿ and our proposed approach can achieve up to 82% on sequence ¿S1.L3 14-33 View 001¿ where the crowd stops and the benchmark accuracy falls to 64%.
Resumo:
Garment information tracking is required for clean room garment management. In this paper, we present a camera-based robust system with implementation of Optical Character Reconition (OCR) techniques to fulfill garment label recognition. In the system, a camera is used for image capturing; an adaptive thresholding algorithm is employed to generate binary images; Connected Component Labelling (CCL) is then adopted for object detection in the binary image as a part of finding the ROI (Region of Interest); Artificial Neural Networks (ANNs) with the BP (Back Propagation) learning algorithm are used for digit recognition; and finally the system is verified by a system database. The system has been tested. The results show that it is capable of coping with variance of lighting, digit twisting, background complexity, and font orientations. The system performance with association to the digit recognition rate has met the design requirement. It has achieved real-time and error-free garment information tracking during the testing.
Resumo:
Objective: This paper presents a detailed study of fractal-based methods for texture characterization of mammographic mass lesions and architectural distortion. The purpose of this study is to explore the use of fractal and lacunarity analysis for the characterization and classification of both tumor lesions and normal breast parenchyma in mammography. Materials and methods: We conducted comparative evaluations of five popular fractal dimension estimation methods for the characterization of the texture of mass lesions and architectural distortion. We applied the concept of lacunarity to the description of the spatial distribution of the pixel intensities in mammographic images. These methods were tested with a set of 57 breast masses and 60 normal breast parenchyma (dataset1), and with another set of 19 architectural distortions and 41 normal breast parenchyma (dataset2). Support vector machines (SVM) were used as a pattern classification method for tumor classification. Results: Experimental results showed that the fractal dimension of region of interest (ROIs) depicting mass lesions and architectural distortion was statistically significantly lower than that of normal breast parenchyma for all five methods. Receiver operating characteristic (ROC) analysis showed that fractional Brownian motion (FBM) method generated the highest area under ROC curve (A z = 0.839 for dataset1, 0.828 for dataset2, respectively) among five methods for both datasets. Lacunarity analysis showed that the ROIs depicting mass lesions and architectural distortion had higher lacunarities than those of ROIs depicting normal breast parenchyma. The combination of FBM fractal dimension and lacunarity yielded the highest A z value (0.903 and 0.875, respectively) than those based on single feature alone for both given datasets. The application of the SVM improved the performance of the fractal-based features in differentiating tumor lesions from normal breast parenchyma by generating higher A z value. Conclusion: FBM texture model is the most appropriate model for characterizing mammographic images due to self-affinity assumption of the method being a better approximation. Lacunarity is an effective counterpart measure of the fractal dimension in texture feature extraction in mammographic images. The classification results obtained in this work suggest that the SVM is an effective method with great potential for classification in mammographic image analysis.
Resumo:
Most active-contour methods are based either on maximizing the image contrast under the contour or on minimizing the sum of squared distances between contour and image 'features'. The Marginalized Likelihood Ratio (MLR) contour model uses a contrast-based measure of goodness-of-fit for the contour and thus falls into the first class. The point of departure from previous models consists in marginalizing this contrast measure over unmodelled shape variations. The MLR model naturally leads to the EM Contour algorithm, in which pose optimization is carried out by iterated least-squares, as in feature-based contour methods. The difference with respect to other feature-based algorithms is that the EM Contour algorithm minimizes squared distances from Bayes least-squares (marginalized) estimates of contour locations, rather than from 'strongest features' in the neighborhood of the contour. Within the framework of the MLR model, alternatives to the EM algorithm can also be derived: one of these alternatives is the empirical-information method. Tracking experiments demonstrate the robustness of pose estimates given by the MLR model, and support the theoretical expectation that the EM Contour algorithm is more robust than either feature-based methods or the empirical-information method. (c) 2005 Elsevier B.V. All rights reserved.
Resumo:
We introduce a classification-based approach to finding occluding texture boundaries. The classifier is composed of a set of weak learners, which operate on image intensity discriminative features that are defined on small patches and are fast to compute. A database that is designed to simulate digitized occluding contours of textured objects in natural images is used to train the weak learners. The trained classifier score is then used to obtain a probabilistic model for the presence of texture transitions, which can readily be used for line search texture boundary detection in the direction normal to an initial boundary estimate. This method is fast and therefore suitable for real-time and interactive applications. It works as a robust estimator, which requires a ribbon-like search region and can handle complex texture structures without requiring a large number of observations. We demonstrate results both in the context of interactive 2D delineation and of fast 3D tracking and compare its performance with other existing methods for line search boundary detection.