A machine learning approach to the assessment of the vulnerability of Posidonia oceanica meadows

In this study, we adopted a modelling approach to assess the vulnerability of Posidonia oceanica meadows, the most widespread seagrass in Mediterranean Sea. P. oceanica has a crucial ecological role all over the basin. In fact, this seagrass is a habitat-forming species that can extend from the surface to 45 m depth, forming meadows. These meadows rank among the most valuable ecosystem in the Mediterranean Sea, in term of the services they provide. However, in areas where alterations of environmental conditions happened, regression of the meadows may occur. Despite it is one of the main targets of conservation actions all over the basin, P. oceanica is declining at alarming rate, especially due to the anthropogenic impacts. Thereby, there is a urgent need to study the effects of environmental factors that could affect its ecological status. We used a Random Forest for developing a Habitat Suitability Model (HSM) for P. oceanica in the Italian seas. The use of HSMs has been especially promoted to support ecosystem assessment and conservation planning, since they allow to better understand both the habitat requirements and the potential distribution of species. Since the spatial distribution of meadows in Italian seas is already known, we used the HSM predictions to evaluate the suitability of the habitat for P. oceanica at large spatial scale and, consequently, we assessed the vulnerability of the meadows. Particularly, our occurrence data included both areas were P. oceanica was known as living and regressed meadows. After the RF training, we validated the model using an independent test set and we evaluated the performance using both ROC curve and K statistic. The results showed that the HSM presented a quite good level of accuracy. Thus, we carried out a spatial analysis of the HSM predictions in relation to the actual ecological status of P. oceanica. The results showed that in areas where living meadows actually occurred, high habitat suitability predictions were significantly more frequent. On the contrary, where regressed meadows were actually observed, predictions indicated low habitat suitability for P. oceanica. This study stressed that modeling can effectively support the assessment of ecosystem status as well as conservation actions

The role of geological origin of smectites and of their physico-chemical properties on aflatoxin adsorption

Since 2013, bentonite in the form of dioctahedral smectite is an additive authorised in the EU as a substance for the reduction of the contamination of feed by aflatoxins. Several studies indicate a big difference in the effectiveness of smectites in sequestering aflatoxins. A clear correlation between mineralogical and physico-chemical properties of smectites and aflatoxin adsorption has not been well established. In the effort to identify the most critical mineralogical, chemical, and physical properties that affect aflatoxin adsorption by smectites, 29 samples of bentonites obtained from different sources around the world were evaluated. “As received” samples were divided into two main groups, i.e. hydrothermal (n=14) and sedimentary (n=15) bentonites depending on their geological origin. The characterization studies showed that all samples contained dioctahedral smectite as major mineral; a moderate CEC value (60-116 cmol/kg); the presence of iron; a small organic matter content; a near-neutral pH; and a fine and uniform particle size (<45μm). They differed substantially in their sodium, calcium and magnesium contents, and in the swelling properties depending on the geological origin. Several in vitro adsorption studies showed that they also differed in a significant manner in adsorbing aflatoxin B1 (AFB1). A correlation between geological origin and AFB1 adsorption capacity was found (p<0.001), being sedimentary smectites significantly more effective than hydrothermal ones in adsorbing the toxin at different pH values. The extent of AFB1 adsorption by all samples was negatively and linearly correlated to the extent of desorption, and sedimentary smectites were significantly more effective than hydrothermal smectites in keeping bound the adsorbed fraction of the toxin (p < 0.001). In addition, correlation studies using the Pearson statistical method showed a significant relationship among some physico-chemical properties of smectites and the amounts of adsorbed toxin. In particular, AFB1 adsorption by smectites correlated positively with sodium content and swell index, but negatively with d001-value, magnesium and calcium contents. In conclusion, it seems that the geological origin of smectite is a useful guide for the selection of bentonites for AFB1 detoxification. Sedimentary bentonites containing sodium/swelling-smectite should be preferred to hydrothermal samples as potential aflatoxin binders. Taking into account the geographical origin of our samples, this approach should be applicable to bentonites worldwide

Defend as You Can, React Quickly: The Effects of the COVID-19 Shock on a Large Fishery of the Mediterranean Sea

This paper presents an analysis of the effect of SARS-CoV-2 coronavirus pandemic and related restrictive measures on the activity of the Italian fleet of trawlers, which represents one of the most important fisheries in the Mediterranean Sea. We integrated multiple sources of information including: (1) Fleet activity data from Vessel Monitoring System, the most important satellite-based tracking device; (2) vessel-specific landing data disaggregated by species; (3) market and economic drivers affecting the effort variation during the lockdown and in the related fishing strategies; (4) monthly landings of demersal species in the main Italian harbors. These data sources are combined to: (1) Assess the absolute and relative changes of trawling effort in the geographical sub- areas surrounding the Italian coasts; (2) integrate and compare these changes with the market and economic drivers in order to explain the observed changes in fishing effort and strategy; (3) analyze the changes of the fishing effort on the Landing-per-unit- effort (LPUE) in order to further understand the strategy adopted by fishers during this crisis and to infer the potential consequence for the different stocks. The results provide an overview of the effects of the “COVID-19 shock,” in terms of fishing activity and socio-economic drivers, demonstrating that the consequences of the pandemic have been very varied. Although the COVID-19 shock has caused a marked overall reduction in activity in the first semester of 2020, in some cases the strategies adopted by fishermen and the commercial network linked to their activity have significantly reduced the impact of the emergency and taken back catch and effort to levels similar to those of previous years. These results could provide insights for management measures based on temporal stops of fishing activities. In particular, if no limits to the fishing effort after the restart of fishing activities are adopted, the benefits of fishing pressure reduction on fishery resources could be nullified. On the other hands, when fishing activities restart, and in the absence of catch control, effort tends to increase on coastal bottoms characterized by greater abundance of resources and longer effective fishing time

A New Orbiting Deployable System for Small Satellite Observations for Ecology and Earth Observation

In this paper, we present several study cases focused on marine, oceanographic, and atmospheric environments, which would greatly benefit from the use of a deployable system for small satellite observations. As opposed to the large standard ones, small satellites have become an effective and affordable alternative access to space, owing to their lower costs, innovative design and technology, and higher revisiting times, when launched in a constellation configuration. One of the biggest challenges is created by the small satellite instrumentation working in the visible (VIS), infrared (IR), and microwave (MW) spectral ranges, for which the resolution of the acquired data depends on the physical dimension of the telescope and the antenna collecting the signal. In this respect, a deployable payload, fitting the limited size and mass imposed by the small satellite architecture, once unfolded in space, can reach performances similar to those of larger satellites. In this study, we show how ecology and Earth Observations can benefit from data acquired by small satellites, and how they can be further improved thanks to deployable payloads. We focus on DORA—Deployable Optics for Remote sensing Applications—in the VIS to TIR spectral range, and on a planned application in the MW spectral range, and we carry out a radiometric analysis to verify its performances for Earth Observation studies

The Wiskott-Aldrich syndrome protein is required for iNKT cell maturation and function

The Wiskott-Aldrich syndrome (WAS) protein (WASp) is a regulator of actin cytoskeleton in hematopoietic cells. Mutations of the WASp gene cause WAS. Although WASp is involved in various immune cell functions, its role in invariant natural killer T (iNKT) cells has never been investigated. Defects of iNKT cells could indeed contribute to several WAS features, such as recurrent infections and high tumor incidence. We found a profound reduction of circulating iNKT cells in WAS patients, directly correlating with the severity of clinical phenotype. To better characterize iNKT cell defect in the absence of WASp, we analyzed was−/− mice. iNKT cell numbers were significantly reduced in the thymus and periphery of was−/− mice as compared with wild-type controls. Moreover analysis of was−/− iNKT cell maturation revealed a complete arrest at the CD44+ NK1.1− intermediate stage. Notably, generation of BM chimeras demonstrated a was−/− iNKT cell-autonomous developmental defect. was−/− iNKT cells were also functionally impaired, as suggested by the reduced secretion of interleukin 4 and interferon γ upon in vivo activation. Altogether, these results demonstrate the relevance of WASp in integrating signals critical for development and functional differentiation of iNKT cells and suggest that defects in these cells may play a role in WAS pathology

Interactions between heavy metals and photosynthetic materials studied by optical techniques

In this work studies on rapid inhibitory interactions between heavy metals and photosynthetic materials at different organization levels were carried out by optical assay techniques, investigating the possibility of applications in the heavy metal detection field. Spinach chloroplasts, thylakoids and Photosystem II proteins were employed as biotools in combination with colorimetric assays based on dichlorophenol indophenole (DCIP) photoreduction and on fluorescence emission techniques. It was found that copper and mercury demonstrated a strong and rapid photosynthetic activity inhibition, that varied from proteins to membranes, while other metals like nickel, cobalt and manganese produced only slight inhibition effects on all tested photosynthetic materials. By emission measurements, only copper was found to rapidly influence the photosynthetic material signals. These findings give interesting information about the rapid effects of heavy metals on isolated photosynthetic samples, and are in addition to the literature data concerning the effects of growth in heavy metal enriched media

A Machine Learning approach to the assessment of the vulnerability of Posidonia oceanica meadows

Posidonia oceanicais an endemic Mediterranean seagrass that ranks among the most important and valuable species, with regard to both its ecological role and the services it provides. Despite this species is one of the main targets of conservation actions, the current regression trend of P. oceanicais alarming, underlying the urgent need for reliable methods capable of assessing meadows vulnerability. To address this need, we developed a Habitat Suitability Model (HSM) aimed at assessing the vulnerability ofP. oceanicameadows in the Italian marine coastal waters using the Random Forest (RF) Machine Learning technique. Building on the current knowledge on both spatial distribution and condition of meadows in the Italian seas, the RF was used as a classifier aimed at modeling the habitat suitability forP. oceanica, rather than for predictive purposes. The assessment of the potentially most vulnerableP. oceanicameadows at increasing risk of regression was performed through the analysis of the RF output. The HSM showed a good level of accuracy, i.e. Cohen’s K = 0.685. The proposed approach provided valuable information regarding the vulnerability ofP. oceanicameadows over the Italian marine coastal waters. In addition, an evaluation of the relative importance of the predictors was carried out using the permutation measure. The developed HSM can support conservation and monitoring programs regarding this species playing a crucial role in the marine ecosystems of the Mediterranean Sea

Fractal dimension of Posidonia oceanica meadows for the assessment of their ecological condition

Ecological analyses are aimed at characterizing the complexity of the structure of natural objects, yet their heterogeneity is hardly described by the Euclidean concepts. For such purpose, the fractal geometry can be best suited due to its ability in describing, with mathematical rigor, the inherent irregularity of nature. Fractal dimension provides indeed a measurement of the complexity of the analyzed object in terms of space occupation. In this study, we applied the fractal geometry to Posidonia oceanica in order to characterize the structural complexity of its meadows, which are widely recognized as one of the most important coastal ecosystems in the Mediterranean basin. For achieving our aim, we developed an ad hoc implementation of the Box-Counting algorithm based on the Moore neighborhood analysis. Our approach allowed to render the structural complexity of P. oceanica meadows spatially explicit, thus expressing an intrinsic ecological property. The fractal analysis suggested that the complexity of meadows structure is intimately connected with the ecological conditions of P. oceanica. In fact, meadows in living and mixed conditions showed a higher fractal dimension, suggesting a largely uniform and smooth structure. While the fractal dimension associated to the regressed ecological condition of P. oceanica meadows exhibited lower values, highlighting a more jagged and rough structure. Therefore, the fractal theory may prove useful to both fundamental and applied ecological research focusing on P. oceanica and its interactions with Mediterranean coastal ecosystems. In fact, the fractal analysis we performed could result in an effective and straightforward approach for assessing the condition of P. oceanica at large spatial scale, enhancing an integrated maritime spatial planning over the whole Mediterranean basin

Detecting Variants in the NBN Gene While Testing for Hereditary Breast Cancer: What to Do Next?

The NBN gene has been included in breast cancer (BC) multigene panels based on early studies suggesting an increased BC risk for carriers, though not confirmed by recent research. To evaluate the impact of NBN analysis, we assessed the results of NBN sequencing in 116 BRCA-negative BC patients and reviewed the literature. Three patients (2.6%) carried potentially relevant variants: two, apparently unrelated, carried the frameshift variant c.156_157delTT and another one the c.628G&gt;T variant. The latter was subsequently found in 4/1390 (0.3%) BC cases and 8/1580 (0.5%) controls in an independent sample, which, together with in silico predictions, provided evidence against its pathogenicity. Conversely, the rare c.156_157delTT variant was absent in the case-control set; moreover, a 50% reduction of NBN expression was demonstrated in one carrier. However, in one family it failed to co-segregate with BC, while the other carrier was found to harbor also a probably pathogenic TP53 variant that may explain her phenotype. Therefore, the c.156_157delTT, although functionally deleterious, was not supported as a cancer-predisposing defect. Pathogenic/likely pathogenic NBN variants were detected by multigene panels in 31/12314 (0.25%) patients included in 15 studies. The risk of misinterpretation of such findings is substantial and supports the exclusion of NBN from multigene panels