Spatio-temporal variability of micro-, nano- and pico-phytoplankton in the Mediterranean Sea from satellite ocean colour data of SeaWiFS

Abstract. The seasonal and year-to-year variability of the phytoplankton size class (PSC) spatial distribution has been examined in the Mediterranean Sea by using the entire time series of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) space observations (1998–2010). Daily maps of PSCs have been determined using an empirical model based on a synoptic relationship between surface chlorophyll a and diagnostic pigments referred to different taxonomic groups. The analysis of micro-, nano- and pico-phytoplankton satellite time series (1998–2010) describes, quantitatively, the algal assemblage structure over the basin and reveals that the main contribution to chlorophyll a in most of the Mediterranean Sea comes from the pico-phytoplankton component, especially in nutrient-poor environments. Regions with different and peculiar features are the Northwestern Mediterranean Sea, the Alborán Sea and several coastal areas, such as the North Adriatic Sea. In these areas, local interactions between physical and biological components modulate the composition of the three phytoplankton size classes. It results that, during the spring bloom season, micro-phytoplankton dominates in areas of intense vertical winter mixing and deep/intermediate water formation, while in coastal areas micro-phytoplankton dominates in all seasons because of the nutrient supply from the terrestrial inputs. In the Alborán Sea, where the Atlantic inflow modulates the nutrient availability, any predominance of one class over the other two has been observed. The nano-phytoplankton component instead remains widespread over the entire basin along the year, and its contribution to chlorophyll a is of the order of 30–40 %. The largest inter-annual signal occurs in the Northwestern Mediterranean Sea, driven by the year-to-year variation in intensity and extension of the spring bloom, followed by the Alborán Sea, in which the inter-annual variability is strongly modulated by the Atlantic inflow. In absence of sufficient in situ data of community composition, the satellite-based analysis demonstrated that pico-, nano- and micro-phytoplankton classes often coexist. The predominance of one group over the other ones is strongly dependent on the physical and biological processes occurring at the mesoscale. These processes directly influence the nutrient and light availability, which are the principal forcing for the algae growth

Selective inhibition of genomic and non-genomic effects of thyroid hormone regulates muscle cell differentiation and metabolic behavior

Thyroid hormones (THs) are key regulators of different biological processes. Their action involves genomic and non-genomic mechanisms, which together mediate the final effects of TH in target tissues. However, the proportion of the two processes and their contribution to the TH-mediated effects are still poorly understood. Skeletal muscle is a classical target tissue for TH, which regulates muscle strength and contraction, as well as energetic metabolism of myofibers. Here we address the different contribution of genomic and non-genomic action of TH in skeletal muscle cells by specifically silencing the deiodinase Dio2 or the β3-Integrin expression via CRISPR/Cas9 technology. We found that myoblast proliferation is inversely regulated by integrin signal and the D2-dependent TH activation. Similarly, inhibition of the nuclear receptor action reduced myoblast proliferation, confirming that genomic action of TH attenuates proliferative rates. Contrarily, genomic and non-genomic signals promote muscle differentiation and the regulation of the redox state. Taken together, our data reveal that integration of genomic and non-genomic signal pathways finely regulates skeletal muscle physiology. These findings not only contribute to the understanding of the mechanisms involved in TH modulation of muscle physiology but also add insight into the interplay between different mechanisms of action of TH in muscle cells

Explainable Artificial Intelligence in communication networks: A use case for failure identification in microwave networks

Artificial Intelligence (AI) has demonstrated superhuman capabilities in solving a significant number of tasks, leading to widespread industrial adoption. For in-field network-management application, AI-based solutions, however, have often risen skepticism among practitioners as their internal reasoning is not exposed and their decisions cannot be easily explained, preventing humans from trusting and even understanding them. To address this shortcoming, a new area in AI, called Explainable AI (XAI), is attracting the attention of both academic and industrial researchers. XAI is concerned with explaining and interpreting the internal reasoning and the outcome of AI-based models to achieve more trustable and practical deployment. In this work, we investigate the application of XAI for network management, focusing on the problem of automated failure-cause identification in microwave networks. We first introduce the concept of XAI, highlighting its advantages in the context of network management, and we discuss in detail the concept behind Shapley Additive Explanations (SHAP), the XAI framework considered in our analysis. Then, we propose a framework for a XAI-assisted ML-based automated failure-cause identification in microwave networks, spanning model's development and deployment phases. For the development phase, we show how to exploit SHAP for feature selection and how to leverage SHAP to inspect misclassified instances during model's development process, and how to describe model's global behavior based on SHAP's global explanations. For the deployment phase, we propose a framework based on predictions uncertainty to detect possibly wrong predictions that will be inspected through XAI

Ecoregions in the Mediterranean Sea Through the Reanalysis of Phytoplankton Functional Types and Carbon Fluxes

In this work we produced a long‐term reanalysis of the phytoplankton community structure in the Mediterranean Sea and used it to define ecoregions. These were based on the spatial variability of the phytoplankton type fractions and their influence on selected carbon fluxes. A regional ocean color product of four phytoplankton functional types (PFTs; diatoms, dinoflagellates, nanophytoplankton, and picophytoplankton) was assimilated into a coupled physical‐biogeochemical model of the Mediterranean Sea (Proudman Oceanographic Laboratory Coastal Ocean Modelling System‐European Regional Seas Ecosystem Model, POLCOMS–ERSEM) by using a 100‐member ensemble Kalman filter, in a reanalysis simulation for years 1998–2014. The reanalysis outperformed the reference simulation in representing the assimilated ocean color PFT fractions to total chlorophyll, although the skill for the ocean color PFT concentrations was not improved significantly. The reanalysis did not impact noticeably the reference simulation of not assimilated in situ observations, with the exception of a slight bias reduction for the situ PFT concentrations, and a deterioration of the phosphate simulation. We found that the Mediterranean Sea can be subdivided in three PFT‐based ecoregions, derived from the spatial variability of the PFT fraction dominance or relevance. Picophytoplankton dominates the largest part of open ocean waters; microphytoplankton dominates in a few, highly productive coastal spots near large‐river mouths; nanophytoplankton is relevant in intermediate‐productive coastal and Atlantic‐influenced waters. The trophic and carbon sedimentation efficiencies are highest in the microphytoplankton ecoregion and lowest in the picophytoplankton and nanophytoplankton ecoregions. The reanalysis and regionalization offer new perspectives on the variability of the structure and functioning of the phytoplankton community and related biogeochemical fluxes, with foreseeable applications in Blue Growth of the Mediterranean Sea

Discovery of a Thirty-Degree Long Ultraviolet Arc in Ursa Major

Our view of the interstellar medium of the Milky Way and the universe beyond is affected by the structure of the local environment in the Solar neighborhood. Here, we present the discovery of a thirty-degree long arc of ultraviolet emission with a thickness of only a few arcminutes: the Ursa Major Arc. It consists of several arclets seen in the near- and far-ultraviolet bands of the GALEX satellite. A two-degree section of the arc was first detected in the H{\alpha} optical spectral line in 1997; additional sections were seen in the optical by the team of amateur astronomers included in this work. This direction of the sky is known for very low hydrogen column density and dust extinction; many deep fields for extra-galactic and cosmological investigations lie in this direction. Diffuse ultraviolet and optical interstellar emission are often attributed to scattering of light by interstellar dust. The lack of correlation between the Ursa Major Arc and thermal dust emission observed with the Planck satellite, however, suggests that other emission mechanisms must be at play. We discuss the origin of the Ursa Major Arc as the result of an interstellar shock in the Solar neighborhood.Comment: Accepted by A&A on April 3, 202

Prognostic factors in Krukenberg tumor

BACKGROUND: Krukenberg tumor (KT) is a rare secondary ovarian tumor. Little is known about clinicopathologic factors affecting prognosis in KT. OBJECTIVE: To assess the prognostic value of clinicopathologic factors in KT through a systematic review and meta-analysis. METHODS: Electronic databases were searched from their inception to February 2019 for studies assessing the association of clinicopathologic factors with overall survival in KT. Pooled hazard ratio (HR) was calculated for each factor; a p value < 0.05 was considered significant. RESULTS: Twenty-three studies with 1743 patients were included. A decreased overall survival was significantly associated with peritoneal involvement (HR 1.944; p = 0.003), ascites (HR 2.055; p = 0.034), synchronous presentation (HR 1.679; p = 0.034) and increased serum CEA levels (HR 1.380; p = 0.010), but not with age > 50 (HR 0.946; p = 0.743), menopausal status (HR 1.565; p = 0.204), gastric origin (HR 1.600; p = 0.201), size > 5 cm (HR 1.292; p = 0.119), size > 10 cm (HR 0.925; p = 0.714), bilateral ovarian involvement (HR 1.113; p = 0.347), non-peritoneal extaovarian metastases (HR 1.648; p = 0.237), liver metastases (HR 1.118, p = 0.555), predominant signet ring cell morphology (HR 1.322; p = 0.208) and levels of CA125 (HR 0.933; p = 0.828) and CA19.9 (HR 0.996; p = 0.992). CONCLUSION: Peritoneal involvement, synchronous presentation, ascites and increased serum CEA levels appear as unfavorable prognostic factors in KT and might affect the patient management

The NANOG transcription factor induces type 2 deiodinase expression and regulates the intracellular activation of thyroid hormone in keratinocyte carcinomas

Type 2 deiodinase (D2), the principal activator of thyroid hormone (TH) signaling in target tissues, is expressed in cutaneous squamous cell carcinomas (SCCs) during late tumorigenesis, and its repression attenuates the invasiveness and metastatic spread of SCC. Although D2 plays multiple roles in cancer progression, nothing is known about the mechanisms regulating D2 in cancer. To address this issue, we investigated putative upstream regulators of D2 in keratinocyte carcinomas. We found that the expression of D2 in SCC cells is positively regulated by the NANOG transcription factor, whose expression, besides being causally linked to embryonic stemness, is associated with many human cancers. We also found that NANOG binds to the D2 promoter and enhances D2 transcription. Notably, blockage of D2 activity reduced NANOG-induced cell migration as well as the expression of key genes involved in epithelial–mesenchymal transition in SCC cells. In conclusion, our study reveals a link among endogenous endocrine regulators of cancer, thyroid hormone and its activating enzyme, and the NANOG regulator of cancer biology. These findings could provide the basis for the development of TH inhibitors as context-dependent anti-tumor agents

Free electron laser-driven ultrafast rearrangement of the electronic structure in Ti

High-energy density extreme ultraviolet radiation delivered by the FERMI seeded free-electron laser has been used to create an exotic nonequilibrium state of matter in a titanium sample characterized by a highly excited electron subsystem at temperatures in excess of 10 eV and a cold solid-density ion lattice. The obtained transient state has been investigated through ultrafast absorption spectroscopy across the Ti M2,3-edge revealing a drastic rearrangement of the sample electronic structure around the Fermi level occurring on a time scale of about 100 fs