Cell size influences inorganic carbon acquisition in artificially selected phytoplankton

Cell size influences the rate at which phytoplankton assimilate dissolved inorganic carbon (DIC), but it is unclear whether volume-specific carbon uptake should be greater in smaller or larger cells. On the one hand, Fick's Law predicts smaller cells to have a superior diffusive CO2 supply. On the other, larger cells may have greater scope to invest metabolic energy to upregulate active transport per unit area through CO2 -concentrating mechanisms (CCMs). Previous studies have focused on among-species comparisons, which complicates disentangling the role of cell size from other covarying traits. In this study, we investigated the DIC assimilation of the green alga Dunaliella tertiolecta after using artificial selection to evolve a 9.3-fold difference in cell volume. We compared CO2 affinity, external carbonic anhydrase (CAext ), isotopic signatures (δ13 C) and growth among size-selected lineages. Evolving cells to larger sizes led to an upregulation of CCMs that improved the DIC uptake of this species, with higher CO2 affinity, higher CAext and higher δ13 C. Larger cells also achieved faster growth and higher maximum biovolume densities. We showed that evolutionary shifts in cell size can alter the efficiency of DIC uptake systems to influence the fitness of a phytoplankton species

Remote sensing for cost-effective blue carbon accounting

Blue carbon ecosystems (BCE) include mangrove forests, tidal marshes, and seagrass meadows, all of which are currently under threat, putting their contribution to mitigating climate change at risk. Although certain challenges and trade-offs exist, remote sensing offers a promising avenue for transparent, replicable, and cost-effective accounting of many BCE at unprecedented temporal and spatial scales. The United Nations Framework Convention on Climate Change (UNFCCC) has issued guidelines for developing blue carbon inventories to incorporate into Nationally Determined Contributions (NDCs). Yet, there is little guidance on remote sensing techniques for monitoring, reporting, and verifying blue carbon assets. This review constructs a unified roadmap for applying remote sensing technologies to develop cost-effective carbon inventories for BCE – from local to global scales. We summarise and discuss (1) current standard guidelines for blue carbon inventories; (2) traditional and cutting-edge remote sensing technologies for mapping blue carbon habitats; (3) methods for translating habitat maps into carbon estimates; and (4) a decision tree to assist users in determining the most suitable approach depending on their areas of interest, budget, and required accuracy of blue carbon assessment. We designed this work to support UNFCCC-approved IPCC guidelines with specific recommendations on remote sensing techniques for GHG inventories. Overall, remote sensing technologies are robust and cost-effective tools for monitoring, reporting, and verifying blue carbon assets and projects. Increased appreciation of these techniques can promote a technological shift towards greater policy and industry uptake, enhancing the scalability of blue carbon as a Natural Climate Solution worldwide

The future of Cybersecurity in Italy: Strategic focus area

This volume has been created as a continuation of the previous one, with the aim of outlining a set of focus areas and actions that the Italian Nation research community considers essential. The book touches many aspects of cyber security, ranging from the definition of the infrastructure and controls needed to organize cyberdefence to the actions and technologies to be developed to be better protected, from the identification of the main technologies to be defended to the proposal of a set of horizontal actions for training, awareness raising, and risk management

Material deprivation affects the management and clinical outcome of hepatocellular carcinoma in a high-resource environment

none94Aim: This study investigated how material deprivation in Italy influences the stage of hepatocellular carcinoma (HCC) at diagnosis and the chance of cure. Methods: 4114 patients from the Italian Liver Cancer database consecutively diagnosed with HCC between January 2008 and December 2018 were analysed about severe material deprivation (SMD) rate tertiles of the region of birth and region of managing hospitals, according to the European Statistics on Income and Living Conditions. The main outcomes were HCC diagnosis modalities (during or outside surveillance), treatment adoption and overall survival. Results: In more deprived regions, HCC was more frequently diagnosed during surveillance, while the incidental diagnosis was prevalent in the least deprived. Tumour characteristics did not differ among regions. The proportion of patients undergoing potentially curative treatments progressively decreased as the SMD worsened. Consequently, overall survival was better in less deprived regions. Patients who moved from most deprived to less deprived regions increased their probability of receiving potentially curative treatments by 1.11 times (95% CI 1.03 to 1.19), decreasing their mortality likelihood (hazard ratio 0.78 95% CI 0.67 to 0.90). Conclusions: Socioeconomic status measured through SMD does not seem to influence HCC features at diagnosis but brings a negative effect on the chance of receiving potentially curative treatments. Patient mobility from the most deprived to the less deprived regions increased the access to curative therapies, with the ultimate result of improving survival.openCucchetti A.; Gramenzi A.; Johnson P.; Giannini E.G.; Tovoli F.; Rapaccini G.L.; Marra F.; Cabibbo G.; Caturelli E.; Gasbarrini A.; Svegliati-Baroni G.; Sacco R.; Zoli M.; Morisco F.; Di Marco M.; Mega A.; Foschi F.G.; Biasini E.; Masotto A.; Nardone G.; Raimondo G.; Azzaroli F.; Vidili G.; Brunetto M.R.; Farinati F.; Trevisani F.; Avanzato F.; Biselli M.; Caraceni P.; Garuti F.; Neri A.; Santi V.; Pellizzaro F.; Imondi A.; Sartori A.; Penzo B.; Sanmarco A.; Granito A.; Muratori L.; Piscaglia F.; Sansone V.; Forgione A.; Dajti E.; Marasco G.; Ravaioli F.; Cappelli A.; Golfieri R.; Mosconi C.; Renzulli M.; Cela E.M.; Facciorusso A.; Cacciato V.; Casagrande E.; Moscatelli A.; Pellegatta G.; de Matthaeis N.; Allegrini G.; Lauria V.; Ghittoni G.; Pelecca G.; Chegai F.; Coratella F.; Ortenzi M.; Missale G.; Olivani A.; Inno A.; Marchetti F.; Busacca A.; Camma C.; Di Martino V.; Maria Rizzo G.E.; Franze M.S.; Saitta C.; Sauchella A.; Berardinelli D.; Bevilacqua V.; Borghi A.; Gardini A.C.; Conti F.; Dall'Aglio A.C.; Ercolani G.; Adotti V.; Arena U.; Di Bonaventura C.; Campani C.; Dragoni G.; Gitto S.; Laffi G.; Coccoli P.; Malerba A.; Guarino M.; Capasso M.; Oliveri F.; Romagnoli V.Cucchetti, A.; Gramenzi, A.; Johnson, P.; Giannini, E. G.; Tovoli, F.; Rapaccini, G. L.; Marra, F.; Cabibbo, G.; Caturelli, E.; Gasbarrini, A.; Svegliati-Baroni, G.; Sacco, R.; Zoli, M.; Morisco, F.; Di Marco, M.; Mega, A.; Foschi, F. G.; Biasini, E.; Masotto, A.; Nardone, G.; Raimondo, G.; Azzaroli, F.; Vidili, G.; Brunetto, M. R.; Farinati, F.; Trevisani, F.; Avanzato, F.; Biselli, M.; Caraceni, P.; Garuti, F.; Neri, A.; Santi, V.; Pellizzaro, F.; Imondi, A.; Sartori, A.; Penzo, B.; Sanmarco, A.; Granito, A.; Muratori, L.; Piscaglia, F.; Sansone, V.; Forgione, A.; Dajti, E.; Marasco, G.; Ravaioli, F.; Cappelli, A.; Golfieri, R.; Mosconi, C.; Renzulli, M.; Cela, E. M.; Facciorusso, A.; Cacciato, V.; Casagrande, E.; Moscatelli, A.; Pellegatta, G.; de Matthaeis, N.; Allegrini, G.; Lauria, V.; Ghittoni, G.; Pelecca, G.; Chegai, F.; Coratella, F.; Ortenzi, M.; Missale, G.; Olivani, A.; Inno, A.; Marchetti, F.; Busacca, A.; Camma, C.; Di Martino, V.; Maria Rizzo, G. E.; Franze, M. S.; Saitta, C.; Sauchella, A.; Berardinelli, D.; Bevilacqua, V.; Borghi, A.; Gardini, A. C.; Conti, F.; Dall'Aglio, A. C.; Ercolani, G.; Adotti, V.; Arena, U.; Di Bonaventura, C.; Campani, C.; Dragoni, G.; Gitto, S.; Laffi, G.; Coccoli, P.; Malerba, A.; Guarino, M.; Capasso, M.; Oliveri, F.; Romagnoli, V

Embedded Software of the KM3NeT Central Logic Board

The KM3NeT Collaboration is building and operating two deep sea neutrino telescopes at the bottom of the Mediterranean Sea. The telescopes consist of latices of photomultiplier tubes housed in pressure-resistant glass spheres, called digital optical modules and arranged in vertical detection units. The two main scientific goals are the determination of the neutrino mass ordering and the discovery and observation of high-energy neutrino sources in the Universe. Neutrinos are detected via the Cherenkov light, which is induced by charged particles originated in neutrino interactions. The photomultiplier tubes convert the Cherenkov light into electrical signals that are acquired and timestamped by the acquisition electronics. Each optical module houses the acquisition electronics for collecting and timestamping the photomultiplier signals with one nanosecond accuracy. Once finished, the two telescopes will have installed more than six thousand optical acquisition nodes, completing one of the more complex networks in the world in terms of operation and synchronization. The embedded software running in the acquisition nodes has been designed to provide a framework that will operate with different hardware versions and functionalities. The hardware will not be accessible once in operation, which complicates the embedded software architecture. The embedded software provides a set of tools to facilitate remote manageability of the deployed hardware, including safe reconfiguration of the firmware. This paper presents the architecture and the techniques, methods and implementation of the embedded software running in the acquisition nodes of the KM3NeT neutrino telescopes

Prospects for combined analyses of hadronic emission from γ\gamma-ray sources in the Milky Way with CTA and KM3NeT

The Cherenkov Telescope Array and the KM3NeT neutrino telescopes are major upcoming facilities in the fields of $\gamma$-ray and neutrino astronomy, respectively. Possible simultaneous production of $\gamma$ rays and neutrinos in astrophysical accelerators of cosmic-ray nuclei motivates a combination of their data. We assess the potential of a combined analysis of CTA and KM3NeT data to determine the contribution of hadronic emission processes in known Galactic $\gamma$-ray emitters, comparing this result to the cases of two separate analyses. In doing so, we demonstrate the capability of Gammapy, an open-source software package for the analysis of $\gamma$-ray data, to also process data from neutrino telescopes. For a selection of prototypical $\gamma$-ray sources within our Galaxy, we obtain models for primary proton and electron spectra in the hadronic and leptonic emission scenario, respectively, by fitting published $\gamma$-ray spectra. Using these models and instrument response functions for both detectors, we employ the Gammapy package to generate pseudo data sets, where we assume 200 hours of CTA observations and 10 years of KM3NeT detector operation. We then apply a three-dimensional binned likelihood analysis to these data sets, separately for each instrument and jointly for both. We find that the largest benefit of the combined analysis lies in the possibility of a consistent modelling of the $\gamma$-ray and neutrino emission. Assuming a purely leptonic scenario as input, we obtain, for the most favourable source, an average expected 68% credible interval that constrains the contribution of hadronic processes to the observed $\gamma$-ray emission to below 15%.Comment: 18 pages, 15 figures. Submitted to journa

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

Data from: Size-abundance rules? evolution changes scaling relationships between size, metabolism and demography

Body size often strongly covaries with demography across species. Metabolism has long been invoked as the driver of these patterns but tests of causal links between size, metabolism and demography within a species are exceedingly rare. We used 400 generations of artificial selection to evolve a 2427% size difference in the microalga Dunaliella tertiolecta. We repeatedly measured size, energy fluxes and demography across the evolved lineages. Then, we used standard metabolic theory to generate predictions of how size and demography should covary based on the scaling of energy fluxes that we measured. The size-dependency of energy remained relatively consistent in time, but metabolic theory failed to predict demographic rates, which varied unpredictably in strength and even sign across generations. Classic theory holds that size affects demography via metabolism – our results suggest that both metabolism and size act separately to drive demography and that among-species patterns may not predict within-species processes

Nitrate–nitrite dynamics and phytoplankton growth: formulation and experimental evaluation of a dynamic model

A multi-nutrient quota model was modified to describe the coupled dynamics of nitrate and nitrite utilization for four phytoplankton species, Picochlorum atomus (Butcher) (Chlorophyta), Nannochloropsis oculata (Droop) (Ochrophyta), Isochrysis sp. (Haptophyta), and Pyrocystis lunula (Schütt) (Dinophyta). Although rarely considered in nutrient-limited phytoplankton models, nitrite can be an important nitrogen source, as it can be either released due to incomplete reduction of nitrate or taken up to supplement low nitrogen availability. The model accurately characterizes the dynamics of nitrite uptake and excretion, nitrate uptake and assimilation efficiency, and population growth for the study species in batch culture, despite the fact that the species display a range of qualitatively different nutrient utilization patterns. The good performance of the model suggests that per-capita secretion and re-assimilation of nitrite, together with changes to the per-capita internal nitrogen supply, can be inferred from daily observations of medium nitrate and nitrite utilization and population growth. The model also reproduces qualitative characteristics of nitrite dynamics that have been observed in previous empirical studies, such as a rise in per-capita nitrite secretion when culture medium nitrate concentrations and intracellular nitrogen levels are high. Our model therefore provides a new framework for evaluating the potential broader trophic consequences of the effects of nitrite uptake and release on the dynamics of phytoplankton populations