Phytochemicals Recovery from Grape Pomace: Extraction Improvement and Chemometric Study

In the last 20 years, an increased interest has been shown in the application of different types and combinations of enzymes to obtain phenolic extracts from grape pomace in order to maximize its valorization. Within this framework, the present study aims at improving the recovery of phenolic compounds from Merlot and Garganega pomace and at contributing to the scientific background of enzyme-assisted extraction. Five commercial cellulolytic enzymes were tested in different conditions. Phenolic compound extraction yields were analyzed via a Design of Experiments (DoE) methodology and a second extraction step with acetone was sequentially added. According to DoE, 2% w/w enzyme/substrate ratio was more effective than 1%, allowing a higher total phenol recovery, while the effect of incubation time (2 or 4 h) variation was more enzyme-dependent. Extracts were characterized via spectrophotometric and HPLC-DAD analyses. The results proved that enzymatic and acetone Merlot and Garganega pomace extracts were complex mixtures of compounds. The use of different cellulolytic enzymes led to different extract compositions, as demonstrated using PCA models. The enzyme effects were observed both in water enzymatic and in the subsequent acetone extracts, probably due to their specific grape cell wall degradation and leading to the recovery of different molecule arrays

Small structure, big significance: seed morphology of South American species of M itracarpus (Rubiaceae - Spermacoceae)

Mitracarpus Zuce, ex Schult. & Schult.f. comprises about 50 species distributed mainly throughout tropical and subtropical regions of the New World, from Southern United States to central Argentina. Considering the importance of micromorphological characters for the taxonomy of Spermacoceae s.s. (Rubiaceae), the present study aimed to analyse the taxonomic significance of seed micromorphology in Mitracarpus species from South America. The seeds of 29 species were analysed through light microscopy and scanning electrón microscopy (SEM). For SEM analyses the seeds were mounted on stubs, air dried, covered with gold-palladium. The analyses revealed four pattems and eight subtypes in Mitracarpus, based mainly on the shape of the ventral groove and exotesta features: (1) X-shaped groove: 1.1. reticulate-areolate exotesta, without cruciform depression (M eritricoides, M. parvulus, M. longicalyx, M. nitidus)', 1.2. reticulate-areolate exotesta, with cruciform depression (M. albomarginatus, M. bacigalupoae, M. femandesii); 1.3. reticulate-foveate exotesta, without cruciform depression (M. brasiliensis, M. federalensis, M. hirtus, M. microspermus, M. nitidus, M. polygonifolius); 1.4. papillate exotesta, without cruciform depression (M. pusillus, M. recurvatus, M. steyermarkii); 1.5. reticulate-foveate exotesta, with cruciform depression (M. anthospermoides,M. carajasensis,M. baturitensis,M. bicrucis,M. frigidus); (2) Inverted-Y-shaped groove, reticulate-foveate exotesta, without cruciform depression (M. eichleri, M. salzmannianus, M. semirianus); (3) Rectangularquadrangular-shaped groove, reticulate-areolate exotesta, without cruciform depression (M hasslerianus, M. Ihotzkyanus, M. megapotamicus, M. rigidifolius); (4) Oblong-shaped groove, reticulate-foveate exotesta, without cruciform depression (M. diversifolius). The data obtained here have shown the systematic importance o f seed characteristics in Mitracarpus, as well their valué to indicate affinities among species. It is expected that this study regarding the seed characters in Mitracarpus can provide a potential source o f apomorphies to discem the clades in future molecular phylogenetic analyses. Acknowledgements: FUNCAP (Process BP5-0197-00136.01.00/22); Royal Botanic Gardens, Kew; KLARF (Kew Latín American Research Fellowships Programme); CONICET

Storage Infrastructure at the INFN LHC Tier-1

In this paper we will describe the Storage Infrastructure of the INFN-CNAF Tier-1, used to store data of High Energy Physics experiments, in particular those operating at the Large Hadron Collider

Revealing histological and morphological features of female reproductive system in tree shrew (Tupaia belangeri)

The tree shrew has been used as a primate animal model in neuroscience studies but it has only rarely been employed in the study of reproductive systems. This is mainly because we know very little about the histological features of reproductive organs of the tree shrew. In this study, we have systematically analyzed the histology of reproductive organs of tree shrew, in comparison with human organs. The uterus of female tree shrew is uterus biomes unicolis, which is connected with an enveloped ovary through a thin fallopian tube. Histologically, the fallopian tube consists of folded mucosa, muscularis and serosa. Like other mammalian animals, the different developmental stages (primordial, primary, secondary and Graafian follicles) of ovarian follicles including inner oocyte and outer granulosa cells are embedded in the cortex. The luminal endometrium, middle muscular myometrium and serosa constitute the wall of uterus of tree shrew. The uterine endometrium contains simple columnar ciliated cells and goblet cells, and there are rich uterine glands in underlying stroma. Furthermore, these glands of tree shrew are round and smaller during anestrus, and become much longer when they are in estrus. The uterine endometrium in younger animals was less developed when compared to a mature tree shrew. Compared to human uterine endometrium, the histological features of tree shrew are very similar, indicating that it could potentially be good primate animal model for studying the diseases in reproductive system

Recognition of Crowd Behavior from Mobile Sensors with Pattern Analysis and Graph Clustering Methods

Mobile on-body sensing has distinct advantages for the analysis and understanding of crowd dynamics: sensing is not geographically restricted to a specific instrumented area, mobile phones offer on-body sensing and they are already deployed on a large scale, and the rich sets of sensors they contain allows one to characterize the behavior of users through pattern recognition techniques. In this paper we present a methodological framework for the machine recognition of crowd behavior from on-body sensors, such as those in mobile phones. The recognition of crowd behaviors opens the way to the acquisition of large-scale datasets for the analysis and understanding of crowd dynamics. It has also practical safety applications by providing improved crowd situational awareness in cases of emergency. The framework comprises: behavioral recognition with the user's mobile device, pairwise analyses of the activity relatedness of two users, and graph clustering in order to uncover globally, which users participate in a given crowd behavior. We illustrate this framework for the identification of groups of persons walking, using empirically collected data. We discuss the challenges and research avenues for theoretical and applied mathematics arising from the mobile sensing of crowd behaviors