Effects of Microwave Heating on Sensory Characteristics of Kiwifruit Puree

The effect of microwave processing on the characteristics of kiwifruit puree was evaluated by applying various gentle treatments. Different combinations of microwave power/processing time were applied, with power among 200-1,000 W and time among 60-340 s, and various sensory and instrumental measurements were performed with the aim of establishing correlations and determining which instrumental parameters were the most appropriate to control the quality of kiwi puree. The water and soluble solids of the product, 83 and 14/100 g sample, respectively, did not change due to treatments. For sensory assessment, an expert panel was previously trained to describe the product. Fourteen descriptors were defined, but only the descriptors 'typical kiwifruit colour', 'tone', 'lightness', 'visual consistency' and 'typical taste' were significant to distinguish between kiwifruit puree samples. The instrumental analysis of samples consisted in measuring consistency, viscosity, colour and physicochemical characteristics of the treated and fresh puree. Applying intense treatments (600 W-340 s, 900 W-300 s and 1,000 W-200 s) through high power or long treatment periods or a combination of these factors, mainly affects the consistency (flow distance decreased from 5. 9 to 3. 4 mm/g sample), viscosity (increased from 1. 6 to 2. 5 Pa/s), colour (maximun ¿E was 6 U) and taste of the product. As a result, samples were thicker and with an atypical flavour and kiwifruit colour due to increased clarity (L* increased from 38 to 43) and slight changes in the yellow-green hue (h* decreased from 95 to 94). For the instrumental determinations of colour and visual perception of consistency, the most suitable parameters for quality control are the colour coordinates L*, a*, h*, whiteness index and flow distance measured with a Bostwick consistometer. © 2011 Springer Science+Business Media, LLC.The authors thank the Ministerio de Educacion y Ciencia for the financial support given throughout the Project AGL 2010-22176. The authors are indebted to the Generalitat Valenciana (Valencia, Spain) for the Grant awarded to the author Maria Benlloch. The translation of this paper was funded by the Universidad Politecnica de Valencia, Spain.Benlloch Tinoco, M.; Varela Tomasco, PA.; Salvador Alcaraz, A.; Martínez Navarrete, N. (2012). Effects of Microwave Heating on Sensory Characteristics of Kiwifruit Puree. Food and Bioprocess Technology. 5(8):3021-3031. https://doi.org/10.1007/s11947-011-0652-1S3021303158Albert, A., Varela, P., Salvador, A., & Fiszman, S. M. (2009). 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Clinical inertia in poorly controlled elderly hypertensive patients: a cross-sectional study in Spanish physicians to ascertain reasons for not intensifying treatment

Background Clinical inertia, the failure of physicians to initiate or intensify therapy when indicated, is a major problem in the management of hypertension and may be more prevalent in elderly patients. Overcoming clinical inertia requires understanding its causes and evaluating certain factors, particularly those related to physicians. Objective The objective of our study was to determine the rate of clinical inertia and the physician-reported rea- sons for it. Conclusion Physicians provided reasons for not intensi- fying treatment in poorly controlled patients in only 30 % of instances. Main reasons for not intensifying treatment were borderline BP values, co-morbidity, suspected white coat effect, or perceived difficulty achieving target. nJCI was associated with high borderline BP values and car- diovascular diseas

Evaluation of a minimally invasive glucose biosensor for continuous tissue monitoring

We describe here a minimally invasive glucose biosensor based on a microneedle array electrode fabricated from an epoxy-based negative photoresist (SU8 50) and designed for continuous measurement in the dermal compartment with minimal pain. These minimally invasive, continuous monitoring sensor devices (MICoMS) were produced by casting the structures in SU8 50, crosslinking and then metallising them with platinum or silver to obtain the working and reference electrodes, respectively. The metallised microneedle array electrodes were subsequently functionalised by entrapping glucose oxidase in electropolymerised polyphenol (PP) film. Sensor performance in vitro showed that glucose concentrations down to 0.5 mM could be measured with a response times (T90) of 15 s. The effect of sterilisation by Co60 irradiation was evaluated. In preparation for further clinical studies, these sensors were tested in vivo in a healthy volunteer for a period of 3–6 h. The sensor currents were compared against point measurements obtained with a commercial capillary blood glucometer. The epoxy MICoMS devices showed currents values that could be correlated with these

Long-term postharvest aroma evolution of tomatoes with the alcobaça (alc) mutation

The postharvest evolution of Penjar tomatoes has been studied in four accessions representative of the variability of the varietal type. The long-term shelf life of these materials, which carry the alc allele, was confirmed with 31.2-59.1% of commercial fruits after 6 months of effective conservation at room temperature and a limited loss of weight (21.1-27.9%). Aroma in Penjar tomatoes is differentiated from other tomato varieties by a characteristic 'sharp-floral' aroma descriptor. The evolution of the 'sharp-floral' aroma during postharvest showed a peak of intensity at 2 months of postharvest, though in one accession a delay of 2 months in this response was detected. Out of 25 volatiles analysed, including main and background notes, a reverse iPLS variable selection revealed that the main candidates behind this aromatic behaviour are ¿-terpineol, trans-2-hexenal, 6-methyl-5-hepten-2-one, trans-2-octenal, ¿-pinene, ß-ionone, 2 + 3-methylbutanol and phenylacetaldehyde. Between harvest and 2 months postharvest, most compounds reduced considerably their concentration, while the intensity of the 'sharp-floral' descriptor increased, which means that probably there is a rearrangement of the relative concentrations among volatiles that may lead to masking/unmasking processes. © 2011 Springer-Verlag.This work was supported by grants from the Conselleria de Agricultura, Pesca y Alimentacio de la Comunidad Valenciana, the Fundacion de la Comunidad Valenciana para la Investigacion Agroalimentaria (AGROALIMED) and from the Departament d'Agricultura, Alimentacio i Accio Rural (DAR) de la Generalitat de Catalunya.Casals Missio, J.; Cebolla Cornejo, J.; Rosello Ripolles, S.; Beltran Arandes, J.; Casanas, F.; Nuez Viñals, F. (2011). Long-term postharvest aroma evolution of tomatoes with the alcobaça (alc) mutation. 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Disrupted Small-World Brain Networks in Moderate Alzheimer's Disease: A Resting-State fMRI Study

The small-world organization has been hypothesized to reflect a balance between local processing and global integration in the human brain. Previous multimodal imaging studies have consistently demonstrated that the topological architecture of the brain network is disrupted in Alzheimer's disease (AD). However, these studies have reported inconsistent results regarding the topological properties of brain alterations in AD. One potential explanation for these inconsistent results lies with the diverse homogeneity and distinct progressive stages of the AD involved in these studies, which are thought to be critical factors that might affect the results. We investigated the topological properties of brain functional networks derived from resting functional magnetic resonance imaging (fMRI) of carefully selected moderate AD patients and normal controls (NCs). Our results showed that the topological properties were found to be disrupted in AD patients, which showing increased local efficiency but decreased global efficiency. We found that the altered brain regions are mainly located in the default mode network, the temporal lobe and certain subcortical regions that are closely associated with the neuropathological changes in AD. Of note, our exploratory study revealed that the ApoE genotype modulates brain network properties, especially in AD patients

Resting-State Multi-Spectrum Functional Connectivity Networks for Identification of MCI Patients

In this paper, a high-dimensional pattern classification framework, based on functional associations between brain regions during resting-state, is proposed to accurately identify MCI individuals from subjects who experience normal aging. The proposed technique employs multi-spectrum networks to characterize the complex yet subtle blood oxygenation level dependent (BOLD) signal changes caused by pathological attacks. The utilization of multi-spectrum networks in identifying MCI individuals is motivated by the inherent frequency-specific properties of BOLD spectrum. It is believed that frequency specific information extracted from different spectra may delineate the complex yet subtle variations of BOLD signals more effectively. In the proposed technique, regional mean time series of each region-of-interest (ROI) is band-pass filtered ( Hz) before it is decomposed into five frequency sub-bands. Five connectivity networks are constructed, one from each frequency sub-band. Clustering coefficient of each ROI in relation to the other ROIs are extracted as features for classification. Classification accuracy was evaluated via leave-one-out cross-validation to ensure generalization of performance. The classification accuracy obtained by this approach is 86.5%, which is an increase of at least 18.9% from the conventional full-spectrum methods. A cross-validation estimation of the generalization performance shows an area of 0.863 under the receiver operating characteristic (ROC) curve, indicating good diagnostic power. It was also found that, based on the selected features, portions of the prefrontal cortex, orbitofrontal cortex, temporal lobe, and parietal lobe regions provided the most discriminant information for classification, in line with results reported in previous studies. Analysis on individual frequency sub-bands demonstrated that different sub-bands contribute differently to classification, providing extra evidence regarding frequency-specific distribution of BOLD signals. Our MCI classification framework, which allows accurate early detection of functional brain abnormalities, makes an important positive contribution to the treatment management of potential AD patients

Network Analysis of Intrinsic Functional Brain Connectivity in Alzheimer's Disease

Functional brain networks detected in task-free (“resting-state”) functional magnetic resonance imaging (fMRI) have a small-world architecture that reflects a robust functional organization of the brain. Here, we examined whether this functional organization is disrupted in Alzheimer's disease (AD). Task-free fMRI data from 21 AD subjects and 18 age-matched controls were obtained. Wavelet analysis was applied to the fMRI data to compute frequency-dependent correlation matrices. Correlation matrices were thresholded to create 90-node undirected-graphs of functional brain networks. Small-world metrics (characteristic path length and clustering coefficient) were computed using graph analytical methods. In the low frequency interval 0.01 to 0.05 Hz, functional brain networks in controls showed small-world organization of brain activity, characterized by a high clustering coefficient and a low characteristic path length. In contrast, functional brain networks in AD showed loss of small-world properties, characterized by a significantly lower clustering coefficient (p<0.01), indicative of disrupted local connectivity. Clustering coefficients for the left and right hippocampus were significantly lower (p<0.01) in the AD group compared to the control group. Furthermore, the clustering coefficient distinguished AD participants from the controls with a sensitivity of 72% and specificity of 78%. Our study provides new evidence that there is disrupted organization of functional brain networks in AD. Small-world metrics can characterize the functional organization of the brain in AD, and our findings further suggest that these network measures may be useful as an imaging-based biomarker to distinguish AD from healthy aging