In vitro maintenance, under slow-growth conditions, of oil palm germplasm obtained by embryo rescue

The objective of this work was to evaluate the in vitro maintenance of oil palm (Elaeis guineensis and E. oleifera) accessions under slow-growth conditions. Plants produced by embryo rescue were subject to 1/2MS culture medium supplemented with the carbohydrates sucrose, mannitol, and sorbitol at 1, 2, and 3% under 20 and 25±2ºC. After 12 months, the temperature of 20°C reduced plant growth. Sucrose is the most appropriate carbohydrate for maintaining the quality of the plants, whereas mannitol and sorbitol result in a reduced plant survival.

Thermogenesis in obese women: effect of fructose vs. glucose added to a meal.

To assess the effect of a fructose meal on resting energy expenditure (EE), indirect calorimetry was used in 23 women (10 lean and 13 obese) for 30 min before and 6 h after the ingestion of a mixed meal containing 20% protein, 33% fat, and either 75 g glucose or 75 g fructose as carbohydrate source (47%). Expressed as a percentage of the energy content of the meal, the thermogenic response to the fructose meal was significantly greater (10.2 +/- 0.5%) than that of the glucose meal (8.4 +/- 0.4%, P less than 0.01). This difference was still apparent when the lean and obese women were considered separately. The mean respiratory quotient during the 6-h postprandial period was significantly greater (P less than 0.01) for the fructose (0.85 +/- 0.01) than for the glucose meal (0.83 +/- 0.01) in the combined subjects. In addition, cumulative carbohydrate oxidation was significantly greater after the fructose than after the glucose meal (51.1 +/- 2.3 vs. 40.9 +/- 2.0 g/6 h, respectively, P less than 0.01). Only small changes were observed in postprandial plasma levels of glucose and insulin after the fructose meal, but the plasma levels of lactate increased more with fructose than with the glucose meal. These results suggest that there might be some advantages (higher thermogenesis and carbohydrate oxidations) in using fructose as part of the carbohydrate source in diet of people with obesity and/or insulin resistance.

Effect of meal ingestion on liver stiffness in patients with cirrhosis and portal hypertension.

BACKGROUND AND AIMS: Liver stiffness is increasingly used in the non-invasive evaluation of chronic liver diseases. Liver stiffness correlates with hepatic venous pressure gradient (HVPG) in patients with cirrhosis and holds prognostic value in this population. Hence, accuracy in its measurement is needed. Several factors independent of fibrosis influence liver stiffness, but there is insufficient information on whether meal ingestion modifies liver stiffness in cirrhosis. We investigated the changes in liver stiffness occurring after the ingestion of a liquid standard test meal in this population. METHODS: In 19 patients with cirrhosis and esophageal varices (9 alcoholic, 9 HCV-related, 1 NASH; Child score 6.9±1.8), liver stiffness (transient elastography), portal blood flow (PBF) and hepatic artery blood flow (HABF) (Doppler-Ultrasound) were measured before and 30 minutes after receiving a standard mixed liquid meal. In 10 the HVPG changes were also measured. RESULTS: Post-prandial hyperemia was accompanied by a marked increase in liver stiffness (+27±33%; p<0.0001). Changes in liver stiffness did not correlate with PBF changes, but directly correlated with HABF changes (r = 0.658; p = 0.002). After the meal, those patients showing a decrease in HABF (n = 13) had a less marked increase of liver stiffness as compared to patients in whom HABF increased (n = 6; +12±21% vs. +62±29%,p<0.0001). As expected, post-prandial hyperemia was associated with an increase in HVPG (n = 10; +26±13%, p = 0.003), but changes in liver stiffness did not correlate with HVPG changes. CONCLUSIONS: Liver stiffness increases markedly after a liquid test meal in patients with cirrhosis, suggesting that its measurement should be performed in standardized fasting conditions. The hepatic artery buffer response appears an important factor modulating postprandial changes of liver stiffness. The post-prandial increase in HVPG cannot be predicted by changes in liver stiffness.

Contributions of fat protein to the incretin effect of a mixed meal

La régulation de la glycémie est une fonction complexe de l'organisme faisant intervenir de multiples mécanismes. Lors de la prise alimentaire, l'un des mécanismes impliqués dans l'homéostasie glucidique, notamment dans la sécrétion d'insuline, est l'axe entéroinsulaire. En effet, le contact des nutriments avec des cellules spécialisées réparties le long du tractus digestif déclenche la sécrétion d'hormones, appelées incretines, telles que le GLP-1 ou le GIP. Ces hormones gastro-intestinales potentialisent la sécrétion d'insuline (effet incrétine) et sont responsables d'une grande partie de la réponse insulinique à la prise orale de glucose.¦L'importance de ces hormones est particulièrement mise en évidence par des observations faites chez les sujets obèses ayant bénéficié d'une chirurgie bariatrique. En effet, après l'opération, la sensibilité à l'insuline et sa sécrétion sont améliorées chez des patients obèses diabétiques ou intolérants au glucose, alors que le pattern de sécrétion des hormones GI est nettement modifié avec notamment une augmentation de la sécrétion de GLP-1. L'augmentation de la sécrétion de ces hormones pourrait contribuer à l'amélioration de la tolérance glucidique en augmentant la sécrétion d'insuline en réponse à l'apport de nutriments. Cette activation exagérée de l'axe entéro-insulaire pourrait aussi contribuer à la pathogenèse des hypoglycémies postprandiales survenant parfois après un bypass gastrique¦Néanmoins, si le rôle des hormones gastro-intestinales est indubitale, il y a peu de données nous indiquant le rôle respectif des divers macronutriments composant un repas standard dans I'activation de l'axe entéro-insulaire. Dans ce travail, nous avons cherché à préciser le rôle spécifique de la partie lipidique et protéique d'un repas standard.¦Après avoir confirmé l'existence d'un effet incrétine lors de la consommation d'un repas test sous forme d'un sandwich, les résultats que nous avons obtenus montrent que l'ingestion de lipides en quantité correspondant à celle d'un repas standard augmente la sécrétion d'insuline, contribuant ainsi à l'effet incrétine, alors qu'à contrario, l'ingestion de protéines ne provoque pas d'augmentation de l'insulinémie et ainsi ne contribue pas à l'effet incrétine.¦Ces observations pourraient revêtir un intérêt pratique. En effet, la démonstration du rôle prépondérant d'un macronutriment dans l'effet incrétine suivant la prise d'un repas standard pourrait mener à des prescriptions diététiques dans le but d'améliorer le contrôle glycémique chez des patients diabétiques ou de diminuer les hypoglycémies suivant la prise alimentaire chez certains patients ayant bénéficié d'un bypass gastrique. De même, une meilleure compréhension du rôle des hormones incrétines a déjà ouvert de nouvelles perspectives thérapeutiques dans le traitement du diabète de type 2 avec le développement de nouvelles classes de médicaments telles que les analogues du GLP-1 ou les inhibiteurs de sa dégradation.

Effectiveness of antioxidants in preventing oxidation of palm oil enriched with heme iron: A model for iron fortification in baked products

Bakery products such as biscuits, cookies, and pastries represent a good medium for iron fortification in food products, since they are consumed by a large proportion of the population at risk of developing iron deficiency anemia, mainly children. The drawback, however, is that iron fortification can promote oxidation. To assess the extent of this, palm oil added with heme iron and different antioxidants was used as a model for evaluating the oxidative stability of some bakery products, such as baked goods containing chocolate. The palm oil samples were heated at 220°C for 10 min to mimic the conditions found during a typical baking processing. The selected antioxidants were a free radical scavenger (tocopherol extract (TE), 0 and 500 mg/kg), an oxygen scavenger (ascorbyl palmitate (AP), 0 and 500 mg/kg), and a chelating agent (citric acid (CA), 0 and 300 mg/kg). These antioxidants were combined using a factorial design and were compared to a control sample, which was not supplemented with antioxidants. Primary (peroxide value and lipid hydroperoxide content) and secondary oxidation parameters (p-anisidine value, p-AnV) were monitored over a period of 200 days in storage at room temperature. The combination of AP and CA was the most effective treatment in delaying the onset of oxidation. TE was not effective in preventing oxidation. The p-AnV did not increase during the storage period, indicating that this oxidation marker was not suitable for monitoring oxidation in this model.

Effectiveness of antioxidants in preventing oxidation of palm oil enriched with heme iron: A model for iron fortification in baked products

Bakery products such as biscuits, cookies, and pastries represent a good medium for iron fortification in food products, since they are consumed by a large proportion of the population at risk of developing iron deficiency anemia, mainly children. The drawback, however, is that iron fortification can promote oxidation. To assess the extent of this, palm oil added with heme iron and different antioxidants was used as a model for evaluating the oxidative stability of some bakery products, such as baked goods containing chocolate. The palm oil samples were heated at 220°C for 10 min to mimic the conditions found during a typical baking processing. The selected antioxidants were a free radical scavenger (tocopherol extract (TE), 0 and 500 mg/kg), an oxygen scavenger (ascorbyl palmitate (AP), 0 and 500 mg/kg), and a chelating agent (citric acid (CA), 0 and 300 mg/kg). These antioxidants were combined using a factorial design and were compared to a control sample, which was not supplemented with antioxidants. Primary (peroxide value and lipid hydroperoxide content) and secondary oxidation parameters (p-anisidine value, p-AnV) were monitored over a period of 200 days in storage at room temperature. The combination of AP and CA was the most effective treatment in delaying the onset of oxidation. TE was not effective in preventing oxidation. The p-AnV did not increase during the storage period, indicating that this oxidation marker was not suitable for monitoring oxidation in this model.

Brain dynamics of meal size selection in humans.

Although neuroimaging research has evidenced specific responses to visual food stimuli based on their nutritional quality (e.g., energy density, fat content), brain processes underlying portion size selection remain largely unexplored. We identified spatio-temporal brain dynamics in response to meal images varying in portion size during a task of ideal portion selection for prospective lunch intake and expected satiety. Brain responses to meal portions judged by the participants as 'too small', 'ideal' and 'too big' were measured by means of electro-encephalographic (EEG) recordings in 21 normal-weight women. During an early stage of meal viewing (105-145ms), data showed an incremental increase of the head-surface global electric field strength (quantified via global field power; GFP) as portion judgments ranged from 'too small' to 'too big'. Estimations of neural source activity revealed that brain regions underlying this effect were located in the insula, middle frontal gyrus and middle temporal gyrus, and are similar to those reported in previous studies investigating responses to changes in food nutritional content. In contrast, during a later stage (230-270ms), GFP was maximal for the 'ideal' relative to the 'non-ideal' portion sizes. Greater neural source activity to 'ideal' vs. 'non-ideal' portion sizes was observed in the inferior parietal lobule, superior temporal gyrus and mid-posterior cingulate gyrus. Collectively, our results provide evidence that several brain regions involved in attention and adaptive behavior track 'ideal' meal portion sizes as early as 230ms during visual encounter. That is, responses do not show an increase paralleling the amount of food viewed (and, in extension, the amount of reward), but are shaped by regulatory mechanisms.

Pointwise estimates for the Bergman kernel of the weighted Fock space

We prove upper pointwise estimates for the Bergman kernel of the weighted Fock space of entire functions in $L^{2}(e^{-2\phi}) $ where $\phi$ is a subharmonic function with $\Delta\phi$ a doubling measure. We derive estimates for the canonical solution operator to the inhomogeneous Cauchy-Riemann equation and we characterize the compactness of this operator in terms of $\Delta\phi$.

Kernel-PCA data integration with enhanced interpretability

Background Nowadays, combining the different sources of information to improve the biological knowledge available is a challenge in bioinformatics. One of the most powerful methods for integrating heterogeneous data types are kernel-based methods. Kernel-based data integration approaches consist of two basic steps: firstly the right kernel is chosen for each data set; secondly the kernels from the different data sources are combined to give a complete representation of the available data for a given statistical task. Results We analyze the integration of data from several sources of information using kernel PCA, from the point of view of reducing dimensionality. Moreover, we improve the interpretability of kernel PCA by adding to the plot the representation of the input variables that belong to any dataset. In particular, for each input variable or linear combination of input variables, we can represent the direction of maximum growth locally, which allows us to identify those samples with higher/lower values of the variables analyzed. Conclusions The integration of different datasets and the simultaneous representation of samples and variables together give us a better understanding of biological knowledge.

Beurling-Landau densities of weighted Fekete sets and correlation kernel estimates

Let $Q$ be a suitable real function on $C$. An $n$-Fekete set corresponding to $Q$ is a subset ${Z_{n1}},\dotsb, Z_{nn}}$ of $C$ which maximizes the expression $\Pi^n_i_{

New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

Estimating extreme value cumulative distribution functions using bias-corrected kernel approaches

We propose a new kernel estimation of the cumulative distribution function based on transformation and on bias reducing techniques. We derive the optimal bandwidth that minimises the asymptotic integrated mean squared error. The simulation results show that our proposed kernel estimation improves alternative approaches when the variable has an extreme value distribution with heavy tail and the sample size is small.

Effect of meal ingestion on liver stiffness in patients with cirrhosis and portal hypertension.

BACKGROUND AND AIMS: Liver stiffness is increasingly used in the non-invasive evaluation of chronic liver diseases. Liver stiffness correlates with hepatic venous pressure gradient (HVPG) in patients with cirrhosis and holds prognostic value in this population. Hence, accuracy in its measurement is needed. Several factors independent of fibrosis influence liver stiffness, but there is insufficient information on whether meal ingestion modifies liver stiffness in cirrhosis. We investigated the changes in liver stiffness occurring after the ingestion of a liquid standard test meal in this population. METHODS: In 19 patients with cirrhosis and esophageal varices (9 alcoholic, 9 HCV-related, 1 NASH; Child score 6.9±1.8), liver stiffness (transient elastography), portal blood flow (PBF) and hepatic artery blood flow (HABF) (Doppler-Ultrasound) were measured before and 30 minutes after receiving a standard mixed liquid meal. In 10 the HVPG changes were also measured. RESULTS: Post-prandial hyperemia was accompanied by a marked increase in liver stiffness (+27±33%; p<0.0001). Changes in liver stiffness did not correlate with PBF changes, but directly correlated with HABF changes (r = 0.658; p = 0.002). After the meal, those patients showing a decrease in HABF (n = 13) had a less marked increase of liver stiffness as compared to patients in whom HABF increased (n = 6; +12±21% vs. +62±29%,p<0.0001). As expected, post-prandial hyperemia was associated with an increase in HVPG (n = 10; +26±13%, p = 0.003), but changes in liver stiffness did not correlate with HVPG changes. CONCLUSIONS: Liver stiffness increases markedly after a liquid test meal in patients with cirrhosis, suggesting that its measurement should be performed in standardized fasting conditions. The hepatic artery buffer response appears an important factor modulating postprandial changes of liver stiffness. The post-prandial increase in HVPG cannot be predicted by changes in liver stiffness.

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.