Perturbative quantum gravity with the Immirzi parameter

We study perturbative quantum gravity in the first-order tetrad formalism. The lowest order action corresponds to Einstein-Cartan plus a parity-odd term, and is known in the literature as the Holst action. The coupling constant of the parity-odd term can be identified with the Immirzi parameter of loop quantum gravity. We compute the quantum effective action in the one-loop expansion. As in the metric second-order formulation, we find that in the case of pure gravity the theory is on-shell finite, and the running of Newton's constant and the Immirzi parameter is inessential. In the presence of fermions, the situation changes in two fundamental aspects. First, non-renormalizable logarithmic divergences appear, as usual. Second, the Immirzi parameter becomes a priori observable, and we find that it is renormalized by a four-fermion interaction generated by radiative corrections. We compute its beta function and discuss possible implications. The sign of the beta function depends on whether the Immirzi parameter is larger or smaller than one in absolute value, and the values plus or minus one are UV fixed-points (we work in Euclidean signature). Finally, we find that the Holst action is stable with respect to radiative corrections in the case of minimal coupling, up to higher order non-renormalizable interactions.Comment: v2 minor amendment

Enhancement of Water Transport and Microstructural Changes Induced by High-Intesity Ultrasound Application on Orange Peel Drying

The main aim of this work was to evaluate the effect of high-intensity ultrasound (US) on the drying kinetics of orange peel as well as its influence on the microstructural changes induced during drying. Convective drying kinetics of orange peel slabs were carried out at a relative humidity of 26.5±0.9%, 40 °C and 1 m/s with (AIR+US) and without (AIR) ultrasound application. In order to identify the US effect on water transport, drying kinetics were analyzed by taking the diffusion theory into account. Fresh, AIR and AIR+US dried samples were analyzed using Cryo-Scanning Electron Microscopy. Results showed that the drying kinetics of orange peel were significantly improved by US application, which involved a significant (p<0.05) improvement of mass transfer coefficient and effective moisture diffusivity. The effects on mass transfer properties were confirmed with microstructural observations. In the cuticle surface of flavedo, the pores were obstructed by the spread of the waxy components, this fact evidencing US effects on the air solid interfaces. Furthermore, the cells of the albedo were disrupted by US, as it created large intercellular air spaces facilitating water transfer through the tissue.The authors would like to acknowledge the financial support of MICINN and CEE (European Regional Development Fund) from projects Ref. DPI2009-14549-C04-04, PSE-060000-2009-003, and FP6-2004-FOOD-23140 HIGHQ RTE.García Pérez, JV.; Ortuño Cases, C.; Puig Gómez, CA.; Cárcel Carrión, JA.; Pérez Munuera, IM. (2012). Enhancement of Water Transport and Microstructural Changes Induced by High-Intesity Ultrasound Application on Orange Peel Drying. Food and Bioprocess Technology. 5(6):2256-2265. https://doi.org/10.1007/s11947-011-0645-0S2256226556Alandes, L., Perez-Munuera, I., Llorca, E., Quiles, A., & Hernando, I. (2009). Use of calcium lactate to improve structure of “Flor de Invierno” fresh-cut pears. Postharvest Biology and Technology, 53(3), 145–151.Anagnostopoulou, M. A., Kefalas, P., Papageorgiou, V. P., Assimopoulou, A. N., & Boskou, D. (2006). Radical scavenging activity of various extracts and fractions of sweet orange peel (Citrus sinensis). Food Chemistry, 94(1), 19–25.AOAC. (1997). Official methods of analysis. Arlington: Association of Official Analytical Chemist.Arslan, D., Özcan, M. M. (2011). Evaluation of drying methods with respect to drying kinetics, mineral content, and color characteristics of savory leaves. Food and Bioprocess Technology. doi: 10.1007/s11947-010-0498-y , in press.Cárcel, J. A., Garcia-Perez, J. V., Riera, E., & Mulet, A. (2007). Influence of high intensity ultrasound on drying kinetics of persimmon. Drying Technology, 25(1), 185–193.Chafer, M., Gonzalez-Martinez, C., Chiralt, A., & Fito, P. (2003). Microstructure and vacuum impregnation response of citrus peles. Food Research International, 36(1), 35–41.Chau, C., Sheu, F., Huang, Y., & Su, L. (2005). Improvement in intestinal function and health by the peel fibre derived from Citrus sinensis L cv Liucheng. Journal of the Science of Food & Agriculture, 85(7), 1211–1216.Crank J. (1975). The Mathematics of diffusion. Oxford (2nd ed.), UK: Clarendon Press.Cruz, R. M. S., Vieira, M. C., Fonseca, S. C., Silva, C. L. M. (2010). Impact of thermal blanching and thermosonication treatments on watercress (Nasturtium officinale) quality: thermosonication process optimization and microstructure evaluation. Food and Bioprocess Technology. doi: 10.1007/s11947-009-0220-0 , in press.Delgado, A. E., Zheng, L., & Sun, D.-W. (2010). Influence of ultrasound on freezing rate of immersion-frozen apples. Food and Bioprocess Technology, 2(3), 263–270.FAOSTAT (2010). FAO Statistical Databases. Food and Agriculture of the United Nations. Available at: http://faostat.fao.org/site/291/default.aspx . Accessed 15 January 2010.Fernandes, F. A. N., Gallao, M. I., & Rodrigues, S. (2008a). Effect of osmotic dehydration and ultrasound pre-treatment on cell structure: Melon dehydration. Food Science and Technology, 41(4), 604–610.Fernandes, F. A. N., Oliveira, F. I. P., & Rodrigues, S. (2008b). Use of ultrasound for dehydration of papayas. Food and Bioprocess Technology, 1(4), 339–345.Gabaldon-Leyva, C. A., Quintero-Ramos, A., Barnard, J., Balandrán-Quintana, R., Talamás-Abbud, R., & Jiménez-Castro, J. (2007). Effect of ultrasound on the mass transfer and physical changes in brine bell pepper at different temperatures. Journal of Food Engineering, 81(2), 374–379.Gallego-Juárez, J. A. (1998). Some applications of air-borne power ultrasound to food processing. In M. J. W., Povey, T. J. Mason (Eds.), Ultrasound in Food Processing. UK: London, Chapman & Hall.Gallego-Juárez, J. A., Rodríguez-Corral, G., Gálvez-Moraleda, J. C., & Yang, T. S. (1999). A new high intensity ultrasonic technology for food dehydration. Drying Technology, 17(3), 597–608.Garau, M. C., Simal, S., Femenia, A., & Rosselló, C. (2006). Drying of orange skin: drying kinetics modelling and functional properties. Journal of Food Engineering, 75(2), 288–295.Garau, M. C., Simal, S., Rossello, C., & Femenia, A. (2007). Effect of air-drying temperature on physico-chemical properties of dietary fibre and antioxidant capacity of orange (Citrus aurantium v. Canoneta) by-products. Food Chemistry, 104(3), 1014–1024.Garcia-Perez, J. V., Cárcel, J. A., De la Fuente, S., & Riera, E. (2006). Ultrasonic drying of foodstuff in a fluidized bed. Parametric study. Ultrasonics, 44, 539–543.Garcia-Perez, J. V., Cárcel, J. A., Benedito, J., & Mulet, A. (2007). Power ultrasound mass transfer enhancement in food drying. Food and Bioproducts Proccessing, 85(3), 247–254.Guiné, R. P. F., Henrriques, F., Barroca, M. J. (2010). Mass transfer coefficients for the drying of pumpkin (Cucurbita moschata) and dried product quality. Food and Bioprocess Technology. doi: 10.1007/s11947-009-0275 , in press.Khalloufi, S., Almeida-Rivera, C., & Bongers, P. (2009). A theoretical model and its experimental validation to predict the porosity as a function of shrinkage and collapse phenomena during drying. Food Research International, 42(8), 1122–1130.Larrauri, J. A., Rupérez, P., Bravo, L., & Saura-Calixto, F. (1996). High dietary fibre powders from orange and lime peels: associated polyphenols and antioxidant capacity. Food Research International, 29(8), 757–762.Mujumdar, A. S., & Law, C. L. (2010). Drying technology: trends and applications in postharvest processing. Food and Bioprocess Technology, 3(6), 843–852.Mulet, A., Blasco, M., García-Reverter, J., & Garcia-Perez, J. V. (2005). Drying kinetics of Curcuma longa rhizomes. Journal of Food Science, 7(5), 318–323.Oliveira, F. I. P., Gallao, M. I., Rodrigues, S., Fernandes, F.A.N. (2010). Dehydration of malay apple (Syzygium malaccense L.) using ultrasound as a pretreatment. Food and Bioprocess Technology. doi: 10.1007/s11947-010-0351-3 , in press.Ortuño, C., Perez-Munuera, I., Puig, A., Riera, E., & Garcia-Perez, J.V. (2010). Influence of power ultrasound application on mass transport and microstructure of orange peel during hot air drying. Physics Procedia, 3, 153–159.Perry, R. H. & Chilton, C. H. (1973). Chemical Engineers’ Handbook. McGraw Hill (5th ed.), New York, US.Ruiz-López, I. I., Castillo-Zamudio, R. I., Salgado-Cervantes, M. A., Rodríguez-Jimenes, G. C., & García-Alvarado, M. A. (2010). Mass transfer modelling during osmotic dehydration of hexahedral pineapple slices in limited volume solutions. Food and Bioprocess Technology, 3(3), 427–433.Salvador, A., Salvador, L., Besada, C., Larrea, V., Hernando, I., & Perez-Munuera, I. (2008). Reduced effectiveness of the treatment for removing astringency in persimmon fruit when stored at 15 °C: Physiological and microstructural study. Postharvest Biology and Technology, 49(3), 340–347.Sanchez, E. S., Simal, S., Femenía, A., Benedito, J., & Roselló, C. (2001). Effect of acoustic brining on lipolysis and on sensory characteristics of Mahon cheese. Journal of Food Science, 66(6), 892–896.Sanchez, E. S., Simal, S., Femenía, A., Llul, P., & Roselló, C. (2001). Proteolysis of Mahon cheese as affected by acoustic-assited brining. European Food Research and Technology, 212(2), 147–152.Sharma, A., & Gupta, M. N. (2006). Ultrasonic pre-irradiation effect upon aqueous enzymatic oil extraction from almond and apricot seeds. Ultrasonics Sonochemistry, 13(6), 529–534.Simal, S., Rosello, C., & Mulet, A. (1998). Modelling of air drying in regular shaped bodies. Trends in Chemical Engineering, 4(4), 171–180.Simal, S., Femenia, A., & Garcia-Pascual, P. (2003). Simulation of the drying curves of a meat-based product: effect of the external resistance to mass transfer. Journal of Food Engineering, 58(2), 193–199.Singh, R. P., & Heldman, D. R. (2001). Introduction to Food Engineering. Academic Press (3rd ed.): San Diego.Toma, M., Vinatoru, M., Paniwnyk, L., & Mason, T. J. (2001). Investigation of the effects of ultrasound on vegetal tissues during solvent extraction. Ultrasonics Sonochemistry, 8(2), 137–142

Marfan syndrome with a complex chromosomal rearrangement including deletion of the FBN1 gene

<p>Abstract</p> <p>Background</p> <p>The majority of Marfan syndrome (MFS) cases is caused by mutations in the fibrillin-1 gene (<it>FBN1</it>), mapped to chromosome 15q21.1. Only few reports on deletions including the whole <it>FBN1 </it>gene, detected by molecular cytogenetic techniques, were found in literature.</p> <p>Results</p> <p>We report here on a female patient with clinical symptoms of the MFS spectrum plus craniostenosis, hypothyroidism and intellectual deficiency who presents a 1.9 Mb deletion, including the <it>FBN1 </it>gene and a complex rearrangement with eight breakpoints involving chromosomes 6, 12 and 15.</p> <p>Discussion</p> <p>This is the first report of MFS with a complex chromosome rearrangement involving a deletion of <it>FBN1 </it>and contiguous genes. In addition to the typical clinical findings of the Marfan syndrome due to <it>FBN1 </it>gene haploinsufficiency, the patient presents features which may be due to the other gene deletions and possibly to the complex chromosome rearrangement.</p

Evaluation of Xpert® MTB/RIF and ustar easyNAT™ TB IAD for diagnosis of tuberculous lymphadenitis of children in Tanzania : a prospective descriptive study

Fine needle aspiration biopsy has become a standard approach for diagnosis of peripheral tuberculous lymphadenitis. The aim of this study was to compare the performance of Xpert MTB/RIF and Ustar EasyNAT TB IAD nucleic acid amplification assays, against acid-fast bacilli microscopy, cytology and mycobacterial culture for the diagnosis of TB lymphadenitis in children from a TB-endemic setting in Tanzania.; Children of 8 weeks to 16 years of age, suspected of having TB lymphadenitis, were recruited at a district hospital in Tanzania. Fine needle aspirates of lymph nodes were analysed using acid-fast bacilli microscopy, liquid TB culture, cytology, Xpert MTB/RIF and EasyNAT. Latent class analysis and comparison against a composite reference standard comprising "culture and/or cytology" was done, to assess the performance of Xpert MTB/RIF and EasyNAT for the diagnosis of TB lymphadenitis.; Seventy-nine children were recruited; 4 were excluded from analysis. Against a composite reference standard of culture and/or cytology, Xpert MTB/RIF and EasyNAT had a sensitivity and specificity of 58 % and 93 %; and 19 % and 100 % respectively. Relative to latent class definitions, cytology had a sensitivity of 100 % and specificity of 94.7 %.; Combining clinical assessment, cytology and Xpert MTB/RIF may allow for a rapid and accurate diagnosis of childhood TB lymphadenitis. Larger diagnostic evaluation studies are recommended to validate these findings and on Xpert MTB/RIF to assess its use as a solitary initial test for TB lymphadenitis in children

Objective assessment of dietary patterns using metabolic phenotyping: a randomized, controlled, crossover trial

Background: The burden of non-communicable diseases, such as obesity, diabetes, coronary heart disease and cancer, can be reduced by the consumption of healthy diets. Accurate monitoring of changes in dietary patterns in response to food policy implementation is challenging. Metabolic profiling allows simultaneous measurement of hundreds of metabolites in urine, many of them influenced by food intake. We aim to classify people according to dietary behaviour and enhance dietary reporting using metabolic profiling of urine. Methods: To develop metabolite models from 19 healthy volunteers who attended a clinical research unit for four day periods on four occasions. We used the World Health Organisation’s healthy eating guidelines (increase fruits, vegetables, wholegrains, dietary fibre and decrease fats, sugars, and salt) to develop four dietary interventions lasting for four days each that ranged from a diet associated with a low to high risk of developing non-communicable disease. Urine samples were measured by 1H-NMR spectroscopy. This study is registered as an International Standard Randomized Controlled Trial, number ISRCTN 43087333. INTERMAP U.K. (n=225) and a healthy-eating Danish cohort (n=66) were used as free-living validation datasets. Findings: There was clear separation between the urinary metabolite profiles of the four diets. We also demonstrated significant stepwise differences in metabolite levels between the lowest and highest metabolic risk diets and developed metabolite models for each diet. Application of the derived metabolite models to independent cohorts confirmed the association between urinary metabolic and dietary profiles in INTERMAP (P<0•001) and the Danish cohort (P<0•001). Interpretation: Urinary metabolite models, developed in a highly controlled environment, can classify groups of free-living people into consumers of dietary profiles associated with lower or higher non-communicable disease risk based on multivariate metabolite patterns. This approach enables objective monitoring of dietary patterns in population settings and enhances validity of dietary reporting. Funding: National Institute for Health Research (NIHR) and Medical Research Council (MRC)

Synovial chondromatosis and soft tissue chondroma: extraosseous cartilaginous tumor defined by FN1 gene rearrangement

A fusion between fibronectin 1 (FN1) and activin receptor 2A (ACVR2A) has been reported previously in isolated cases of the synovial chondromatosis. To analyze further and validate the findings, we performed FISH and demonstrated recurrent FN1-ACVR2A rearrangements in synovial chondromatosis (57%), and chondrosarcoma secondary to synovial chondromatosis (75%), showing that FN1 and/or AVCR2A gene rearrangements do not distinguish between benign and malignant synovial chondromatosis. RNA sequencing revealed the presence of the FN1-ACVR2A fusion in several cases that were negative by FISH suggesting that the true prevalence of this fusion is potentially higher than 57%. In soft tissue chondromas, FN1 alterations were detected by FISH in 50% of cases but no ACVR2A alterations were identified. RNA sequencing identified a fusion involving FN1 and fibroblast growth factor receptor 2 (FGFR2) in the case of soft tissue chondroma and FISH confirmed recurrent involvement of both FGFR1 and FGFR2. These fusions were present in a subset of soft tissue chondromas characterized by grungy calcification, a feature reminiscent of phosphaturic mesenchymal tumor. However, unlike the latter, fibroblast growth factor 23 (FGF23) mRNA expression was not elevated in soft tissue chondromas harboring the FN1-FGFR1 fusion. The mutual exclusivity of ACVR2A rearrangements observed in synovial chondromatosis and FGFR1/2 in soft tissue chondromas suggests these represent separate entities. There have been no reports of malignant soft tissue chondromas, therefore differentiating these lesions will potentially alter clinical management by allowing soft tissue chondromas to be managed more conservatively

A novel PKC activating molecule promotes neuroblast differentiation and delivery of newborn neurons in brain injuries

Neural stem cells are activated within neurogenic niches in response to brain injuries. This results in the production of neuroblasts, which unsuccessfully attempt to migrate toward the damaged tissue. Injuries constitute a gliogenic/non-neurogenic niche generated by the presence of anti-neurogenic signals, which impair neuronal differentiation and migration. Kinases of the protein kinase C (PKC) family mediate the release of growth factors that participate in different steps of the neurogenic process, particularly, novel PKC isozymes facilitate the release of the neurogenic growth factor neuregulin. We have demonstrated herein that a plant derived diterpene, (EOF2; CAS number 2230806-06-9), with the capacity to activate PKC facilitates the release of neuregulin 1, and promotes neuroblasts differentiation and survival in cultures of subventricular zone (SVZ) isolated cells in a novel PKC dependent manner. Local infusion of this compound in mechanical cortical injuries induces neuroblast enrichment within the perilesional area, and noninvasive intranasal administration of EOF2 promotes migration of neuroblasts from the SVZ towards the injury, allowing their survival and differentiation into mature neurons, being some of them cholinergic and GABAergic. Our results elucidate the mechanism of EOF2 promoting neurogenesis in injuries and highlight the role of novel PKC isozymes as targets in brain injury regeneration

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur