The intrinsic dimension of protein sequence evolution

It is well known that, in order to preserve its structure and function, a protein cannot change its sequence at random, but only by mutations occurring preferentially at specific locations. We here investigate quantitatively the amount of variability that is allowed in protein sequence evolution, by computing the intrinsic dimension (ID) of the sequences belonging to a selection of protein families. The ID is a measure of the number of independent directions that evolution can take starting from a given sequence. We find that the ID is practically constant for sequences belonging to the same family, and moreover it is very similar in different families, with values ranging between 6 and 12. These values are significantly smaller than the raw number of amino acids, confirming the importance of correlations between mutations in different sites. However, we demonstrate that correlations are not sufficient to explain the small value of the ID we observe in protein families. Indeed, we show that the ID of a set of protein sequences generated by maximum entropy models, an approach in which correlations are accounted for, is typically significantly larger than the value observed in natural protein families. We further prove that a critical factor to reproduce the natural ID is to take into consideration the phylogeny of sequences

Data segmentation based on the local intrinsic dimension

One of the founding paradigms of machine learning is that a small number of variables is often sufficient to describe high-dimensional data. The minimum number of variables required is called the intrinsic dimension (ID) of the data. Contrary to common intuition, there are cases where the ID varies within the same data set. This fact has been highlighted in technical discussions, but seldom exploited to analyze large data sets and obtain insight into their structure. Here we develop a robust approach to discriminate regions with different local IDs and segment the points accordingly. Our approach is computationally efficient and can be proficiently used even on large data sets. We find that many real-world data sets contain regions with widely heterogeneous dimensions. These regions host points differing in core properties: folded versus unfolded configurations in a protein molecular dynamics trajectory, active versus non-active regions in brain imaging data, and firms with different financial risk in company balance sheets. A simple topological feature, the local ID, is thus sufficient to achieve an unsupervised segmentation of high-dimensional data, complementary to the one given by clustering algorithms

Low- and intermediate-beta, 352-MHz superconducting half-wave resonators for high power hadron acceleration

Two prototypes of superconducting, 352 MHz coaxial half-wave resonators with β=0.17 and β=0.31 have been designed, constructed, and tested at INFN-LNL, in the framework of the SPES and EURISOL DS projects. Main features of these double-wall, 2-gap structures are compactness, mechanical stability, and easy installation in different kinds of cryostats. Their acceleration capabilities are similar to the ones of Spoke resonators with similar β. These cavities are being developed for acceleration of high power hadron beams in the 5–100  MeV/u energy range

TL1A/DR3 axis involvement in the inflammatory cytokine network during pulmonary sarcoidosis

BACKGROUND: TNF-like ligand 1A (TL1A), a recently recognized member of the TNF superfamily, and its death domain receptor 3 (DR3), firstly identified for their relevant role in T lymphocyte homeostasis, are now well-known mediators of several immune-inflammatory diseases, ranging from rheumatoid arthritis to inflammatory bowel diseases to psoriasis, whereas no data are available on their involvement in sarcoidosis, a multisystemic granulomatous disease where a deregulated T helper (Th)1/Th17 response takes place. METHODS: In this study, by flow cytometry, real-time PCR, confocal microscopy and immunohistochemistry analyses, TL1A and DR3 were investigated in the pulmonary cells and the peripheral blood of 43 patients affected by sarcoidosis in different phases of the disease (29 patients with active sarcoidosis, 14 with the inactive form) and in 8 control subjects. RESULTS: Our results demonstrated a significant higher expression, both at protein and mRNA levels, of TL1A and DR3 in pulmonary T cells and alveolar macrophages of patients with active sarcoidosis as compared to patients with the inactive form of the disease and to controls. In patients with sarcoidosis TL1A was strongly more expressed in the lung than the blood, i.e., at the site of the involved organ. Additionally, zymography assays showed that TL1A is able to increase the production of matrix metalloproteinase 9 by sarcoid alveolar macrophages characterized, in patients with the active form of the disease, by reduced mRNA levels of the tissue inhibitor of metalloproteinase (TIMP)-1. CONCLUSIONS: These data suggest that TL1A/DR3 interactions are part of the extended and complex immune-inflammatory network that characterizes sarcoidosis during its active phase and may contribute to the pathogenesis and to the progression of the disease

Optimization of the appearance quality in CO2 processed ready-to-eat carrots through image analysis

A high-pressure CO2 process applied to ready-to-eat food products guarantees an increase of both their microbial safety and shelf-life. However, the treatment often produces unwanted changes in the visual appearance of products depending on the adopted process conditions. Accordingly, the alteration of the visual appearance influences consumers’ perception and acceptability. This study aims at identifying the optimal treatment conditions in terms of visual appearance by using an artificial vision system. The developed methodology was applied to fresh-cut carrots (Daucus carota) as the test product. The results showed that carrots packaged in 100% CO2 and subsequently treated at 6 MPa and 40◦C for 15 min maintained an appearance similar to the fresh product for up to 7 days of storage at 4◦C. Mild appearance changes were identified at 7 and 14 days of storage in the processed products. Microbiological analysis performed on the optimal treatment condition showed the microbiological stability of the samples up to 14 days of storage at 4◦C. The artificial vision system, successfully applied to the CO2 pasteurization process, can easily be applied to any food process involving changes in the appearance of any food product

Análise da biomassa em pastagens com indicativos de degradação na bacia do Alto Tocantins.

Resumo: O presente estudo objetivou aplicar o Surface Algorithm For Retrieving Evapotranspiration (SAFER) e imagens MODIS, juntamente com medições de campo, para analisar a biomassa de acordo com classes indicativas de degradação das pastagens na Bacia Hidrográfica do Alto Tocantins. Para o ano de 2012 observou-se que as classes não degradado e baixa degradação tiveram valores de biomassa muito próximos, com média em torno de 1550 kg ha-1 mês-1. Para as classes de degradação moderada e forte a biomassa média foi de 1400 e 965 kg ha-1 mês-1, respectivamente. Estes resultados indicam perda significativa do potencial de produção das áreas de pastagens. Abstract: This study aimed to apply the Surface Algorithm For Retrieving Evapotranspiration (SAFER) and MODIS images together with field measurements in order to analyze the biomass in each class with indicatives of degradation of pastures in the Watershed Alto Tocantins. For the year 2012 it was observed that biomass in the low degradation class was very close to the values found for pasture areas of nondegraded class, with average value around 1,550 kg ha-1 month-1. For the classes of moderate and strong degradation the average biomass was 1,400 and 965 kg ha-1 month- 1, respectively. These results indicate significant loss of potential production of pasture areas

Zoneamento das áreas cafeeiras aptas para a mecanização agrícola no Estado do Espírito Santo.

O Estado do Espírito Santo possui destaque nacional em termos de produção de café. Porém têm-se na declividade um fator limitante para a implantação da mecanização. Diante disso, objetivou-se efetuar com base na declividade, o zoneamento das áreas cafeeiras aptas para a mecanização agrícola no Estado do Espírito Santo. O levantamento planialtimétrico usado foi o do Geobases com resolução de 5m, com o auxílio de software de geoprocessamento, gerou-se o Modelo Digital do Terreno (MDT) e, posteriormente, a declividade das áreas da cafeicultura, as quais foram classificadas de acordo com o potencial de mecanização do terreno: Extremamente Apta (0 - 5 %), Muito Apta (5,1 - 10 %), Apta (10,1 - 15 %), Moderadamente Apta (15,1 - 20 %) e Não Recomendada (> 20 %). O Estado apresenta 428.482,6 mil hectares de Coffea canephora e Coffea arabica. Sendo 21,6%; 11,3% e 11,2% com potencial de mecanização extremamente apta, muito apta e apta. Além disso, 10,7% da área cultivada foi classificada como moderadamente apta e 45,3% como área não recomendada para atividades mecanizadas. Ressalta-se também que os municípios com alta produção de Coffea canephora apresentam as lavouras com maior aptidão para a mecanização quando comparados com os municípios que possuem lavouras de Coffea arábica de alta produção