Influence of ellagitannins extracted by pomegranate fruit on disulfide isomerase PDIA3 activity

Pomegranate fruit is a functional food of high interest for human health due to its wide range of phytochemicals with antioxidant properties are implicated in the prevention of inflammation and cancer. Ellagitannins, such as punicalagin and ellagic acid, play a role as anti-atherogenic and neuroprotective molecules in the complex fighting against the degenerative diseases. The aim of this work was to evaluate the composition in punicalagins and ellagic acid of differently obtained extracts from whole fruit, peels and juices, prepared by squeezing or by centrifugation, of pomegranate belonging to different cultivars. Moreover, a wider phenolic fingerprint was also determined. The bioactivity of the extracts was tested on the redox activity of PDIA3 disulfide isomerase, an enzyme involved in the regulation of several cellular functions and associated with different diseases such as cancer, prion disorders, Alzheimer’s and Parkinson’s diseases. The results demonstrate that the different ratios between punicalagin and ellagic acid modulate the enzyme activity and other ellagitannins could interfere with this activity

Real-time adaptive algorithm for resource monitoring

In large scale systems, real-time monitoring of hardware and software resources is a crucial means for any management purpose. In architectures consisting of thousands of servers and hundreds of thousands of component resources, the amount of data monitored at high sampling frequencies represents an overhead on system performance and communication, while reducing sampling may cause quality degradation. We present a real-time adaptive algorithm for scalable data monitoring that is able to adapt the frequency of sampling and data updating for a twofold goal: to minimize computational and communication costs, to guarantee that reduced samples do not affect the accuracy of information about resources. Experiments carried out on heterogeneous data traces referring to synthetic and real environments confirm that the proposed adaptive approach reduces utilization and communication overhead without penalizing the quality of data with respect to existing monitoring algorithms

Adaptive, scalable and reliable monitoring of big data on clouds

Real-time monitoring of cloud resources is crucial for a variety of tasks such as performance analysis, workload management, capacity planning and fault detection. Applications producing big data make the monitoring task very difficult at high sampling frequencies because of high computational and communication overheads in collecting, storing, and managing information. We present an adaptive algorithm for monitoring big data applications that adapts the intervals of sampling and frequency of updates to data characteristics and administrator needs. Adaptivity allows us to limit computational and communication costs and to guarantee high reliability in capturing relevant load changes. Experimental evaluations performed on a large testbed show the ability of the proposed adaptive algorithm to reduce resource utilization and communication overhead of big data monitoring without penalizing the quality of data, and demonstrate our improvements to the state of the art.Real-time monitoring of cloud resources is crucial for a variety of tasks such as performance analysis, workload management, capacity planning and fault detection. Applications producing big data make the monitoring task very difficult at high sampling frequencies because of high computational and communication overheads in collecting, storing, and managing information. We present an adaptive algorithm for monitoring big data applications that adapts the intervals of sampling and frequency of updates to data characteristics and administrator needs. Adaptivity allows us to limit computational and communication costs and to guarantee high reliability in capturing relevant load changes. Experimental evaluations performed on a large testbed show the ability of the proposed adaptive algorithm to reduce resource utilization and communication overhead of big data monitoring without penalizing the quality of data, and demonstrate our improvements to the state of the art

Monitoring large cloud-based systems

Large scale cloud-based services are built upon a multitude of hardware and software resources, disseminated in one or multiple data centers. Controlling and managing these resources requires the integration of several pieces of software that may yield a representative view of the data center status. Today’s both closed and open-source monitoring solutions fail in different ways, including the lack of scalability, scarce representativity of global state conditions, inability in guaranteeing persistence in service delivery, and the impossibility of monitoring multi-tenant applications. In this paper, we present a novel monitoring architecture that addresses the aforementioned issues. It integrates a hierarchical scheme to monitor the resources in a cluster with a distributed hash table (DHT) to broadcast system state information among different monitors. This architecture strives to obtain high scalability, effectiveness and resilience, as well as the possibility of monitoring services spanning across different clusters or even different data centers of the cloud provider. We evaluate the scalability of the proposed architecture through a bottleneck analysis achieved by experimental results

Vapor and Liquid Phase Profiles of Essential Oils from Abies, Picea and Pinus Species and Their Phytotoxic Interactions with Weed Growth in Pre- and Post-Emergence Conditions

The chemical content of essential oils (EO) obtained from the leaves of four Pinaceae (Abies alba, Picea abies, Pinus cembra and Pinus mugo) was investigated by SPME-GC-MS technique. The vapor phase was characterized by the monoterpenes with values higher than 95.0%. Among them, a-pinene (24.7–48.5%), limonene (17.2–33.1%) and b-myrcene (9.2–27.8%) were the most abundant. The monoterpenic fraction prevailed over the sesquiterpenic one ( 74.7%) in the EO liquid phase. Limonene was the major compound in A. alba (30.4%), P. abies (20.3%) and P. mugo (78.5%), while a-pinene in P. cembra (36.2%). Regarding the phytotoxic properties, EOs were studied at different doses (2–100 L) and concentrations (2–20/100 L/mL). All EOs were found to be significantly active (p-value < 0.05) against the two recipient species in a dose-dependent way. In pre-emergence tests, germination of Lolium multiflorum and Sinapis alba was reduced by up to 62–66% and 65–82%, respectively, as well as their growth by up to 60–74% and 65–67%, due to the effects of compounds in both the vapor and liquid phases. In post-emergence cconditions, at the highest concentration, the phytotoxicity of EOs caused heavy symptoms and, in the case of S. alba, A. alba EO completely destroyed (100%) the treated seedlings

Italian reference rivers under the Water Framework Directive umbrella: do natural factors actually depict the observed nutrient conditions?

Abstract Background Despite the efforts made in the last century to counteract the nutrient enrichment from diffuse and point-sources, the excess of nitrogen and phosphorous is among the main causes of degradation of European rivers. In this context, determining natural background concentrations of nutrients in rivers is crucial for a correct definition of their ecological status. In the most anthropized regions, this is a difficult task. This study provides a nation-wide assessment of the nutrient concentration variability between Italian river reference sites. Results We applied the Affinity Propagation technique to identify groups of river sites classified as reference based on measured nutrients and oxygen water saturation. The role of natural and anthropogenic factors determining differences in nutrients concentration between groups of sites was explored. Nitrate concentrations varied from 0.01 mg N l−1 to more than 5 mg N l−1. Ammonia and total phosphorous varied between 0.001 and 0.12 mg l−1. Observed nutrient levels, although in line with those identified for reference sites in other countries, largely exceed the ranges reported for natural basins. Atmospheric deposition of inorganic N and artificial and/or high-impact agricultural land use are the major factors determining differences in nutrient concentration. Factors like, e.g. catchment size, precipitation amount and altitude do not play a relevant role in explaining nutrient differences between groups of reference sites. Conclusions We especially focused on (i) major causes of failure in the selection of appropriate reference sites in Italy; (ii) the potential of setting higher NO3-N thresholds for the classification of ecological status in specific areas, and (iii) the prospective of a regionalization approach, in which human effects are accepted to a low degree for reference site selection or when setting thresholds for peculiar geographical areas

Mealworms for Food: A Water Footprint Perspective

In this paper, we have explored the possibility of substituting traditional meat products with an alternative source of protein (insects) in order to reduce human pressure on water. Insects, in fact, could represent a good alternative source of quality proteins and nutrients and they are already a very popular component of the diet of one third of the world's population in approximately 80% of countries. In the study, we have taken into account only two species of edible insects (Tenebrio molitor and Zophobas morio mealworms), because they are already commercially produced even in Western countries, and for this reason it is possible to find specific data in literature about their diets. We have used the water footprint (WF) as a reliable indicator to calculate the volume of water required for production and to compare different products. The final aim of the work is, in fact, to evaluate the WF of the production of edible insects with a focus on water consumption associated with protein content, in order to make a comparison with other animal protein sources. We have demonstrated that, from a freshwater resource perspective, it is more efficient to obtain protein through mealworms rather than other traditional farmed animals

"Armato di carnagione": Chromatic Regimes of Racial Profiling in the Italian Press.

Marcello Messina, Stefania Capogreco. "Armato di carnagione": Chromatic Regimes of Racial Profiling in the Italian Press. Francielle Maria Modesto Mendes; Francisco Aquinei Timóteo Queirós; Wagner da Costa Silva. Pesquisa em comunicação: jornalismo, raça e gênero, Nepan Editora, 2021, 978-65-89135-20-3

The ratio of lentic to lotic habitat features strongly affects macroinvertebrate metrics used in southern Europe for ecological status classification

Abstract Biological quality in rivers based on benthic macroinvertebrates is typically assessed by comparison with expected reference conditions, which represent relatively undisturbed situations. Commonly, reference conditions are set in agreement with river typologies to handle major ecological differences and limit biological variability. Although natural hydrological variation can be highly influential, site-specific tuning of reference conditions is rare in Mediterranean countries. River flow and local hydraulics change continuously over time, shaping the occurrence of lentic and lotic habitat features. Thus, biological reference conditions might require site-specific adjustment based on the ratio of lentic to lotic habitats assessed at the time of sampling. This would help reducing systematic bias in ecological assessments, interpreting benthic invertebrate responses to pressures, and diminishing the amount of unexplained biological variability. In this study, the response to the lentic-lotic character of river reaches was assessed for nineteen macroinvertebrate metrics and indices commonly used for the classification of ecological status in South European rivers. The study sites, with a prevalent temporary character, were located in Sardinia, southwestern Italy. Most metrics were significantly related to the lentic-lotic habitat conditions, both in pool and riffle mesohabitats, and their response curves were either parabolic or linearly decreasing at increasing lentic conditions. Taxonomic richness, score-based metrics, ovoviviparous taxa and multi-metric indices related well to the lentic-lotic conditions, while abundance metrics correlated less. The potential impact on ecological status classification was tested for the method formally used in Italy, which had a major role in comparing and inter-calibrating European assessment methods for the Water Framework Directive. After adjusting for bias due to the ratio of lentic to lotic habitat features, quality classification shifted towards better ecological status for ≈ 23% samples. This highlighted the impact of ignoring lentic-lotic information when defining reference conditions for assessing ecological status, varying from difficulties in understanding the biological response to pressures, to largely biased ecological status classification. The observed response of macroinvertebrate metrics to lentic-lotic conditions should be a key consideration for realistic ecological status assessment and could further be a valuable input for evaluating the effects of human-induced hydrological alteration and for assessing environmental flows