Evaluation of light energy to H2 energy conversion efficiency in thin films of cyanobacteria and green alga under photoautotrophic conditions

Cyanobacteria and green algae harness solar energy to split water and to fix CO2. Under specific conditions, they are capable of photoproduction of molecular hydrogen (H2). This study compares the light-energy-to-hydrogen-energy conversion efficiency (LHCE) in two heterocystous, N2-fixing cyanobacteria (wild-type Calothrix sp. strain 336/3 and the δhupL mutant of Anabaena sp. strain PCC 7120) and in the sulfur-deprived green alga, Chlamydomonas reinhardtii strain CC-124, after entrapment of the cells in thin Ca2+-alginate films. The experiments, performed under photoautotrophic conditions, showed higher LHCEs in the cyanobacteria as compared to the green alga. The highest efficiency of ca. 2.5% was obtained in films of the entrapped δhupL strain under low light condition (2.9Wm-2). Calothrix sp. 336/3 films produced H2with a maximum efficiency of 0.6% under 2.9Wm-2, while C. reinhardtii films produced H2most efficiently under moderate light (0.14% at 12.1Wm-2). Exposure of the films to light above 16Wm-2led to noticeable oxidative stress in all three strains, which increased with light intensity. The presence of oxidative stress was confirmed by increased (i) degradation of chlorophylls and some structural carotenoids (such as β-carotene), (ii) production of hydroxylated carotenoids (such as zeaxanthin), and (iii) carbonylation of proteins. We conclude that the H2photoproduction efficiency in immobilized algae and cyanobacteria can be further improved by entrapping cultures in immobilization matrices with increased permeability for gases, especially oxygen, while matrices with low porosity produced increased amounts of xanthophylls and other antioxidant compounds.</p

Chapter 5: Food Security

The current food system (production, transport, processing, packaging, storage, retail, consumption, loss and waste) feeds the great majority of world population and supports the livelihoods of over 1 billion people. Since 1961, food supply per capita has increased more than 30%, accompanied by greater use of nitrogen fertilisers (increase of about 800%) and water resources for irrigation (increase of more than 100%). However, an estimated 821 million people are currently undernourished, 151 million children under five are stunted, 613 million women and girls aged 15 to 49 suffer from iron deficiency, and 2 billion adults are overweight or obese. The food system is under pressure from non-climate stressors (e.g., population and income growth, demand for animal-sourced products), and from climate change. These climate and non-climate stresses are impacting the four pillars of food security (availability, access, utilisation, and stability)

Food security

Peer reviewe

Correlations Between Life-Detection Techniques and Implications for Sampling Site Selection in Planetary Analog Missions

We conducted an analog sampling expedition under simulated mission constraints to areas dominated by basaltic tephra of the Eldfell and Fimmvorouhals lava fields (Iceland). Sites were selected to be homogeneous at a coarse remote sensing resolution (10-100m) in apparent color, morphology, moisture, and grain size, with best-effort realism in numbers of locations and replicates. Three different biomarker assays (counting of nucleic-acid-stained cells via fluorescent microscopy, a luciferin/luciferase assay for adenosine triphosphate, and quantitative polymerase chain reaction (qPCR) to detect DNA associated with bacteria, archaea, and fungi) were characterized at four nested spatial scales (1m, 10m, 100m, and >1km) by using five common metrics for sample site representativeness (sample mean variance, group F tests, pairwise t tests, and the distribution-free rank sum H and u tests). Correlations between all assays were characterized with Spearman's rank test. The bioluminescence assay showed the most variance across the sites, followed by qPCR for bacterial and archaeal DNA; these results could not be considered representative at the finest resolution tested (1m). Cell concentration and fungal DNA also had significant local variation, but they were homogeneous over scales of >1km. These results show that the selection of life detection assays and the number, distribution, and location of sampling sites in a low biomass environment with limited a priori characterization can yield both contrasting and complementary results, and that their interdependence must be given due consideration to maximize science return in future biomarker sampling expeditions. Key Words: AstrobiologyBiodiversityMicrobiologyIcelandPlanetary explorationMars mission simulationBiomarker. Astrobiology 17, 1009-1021

Understanding the Threshold Voltage Instability during OFF-State Stress in p-GaN HEMTs

© 1980-2012 IEEE. In this letter, we investigate by means of experimental results and TCAD simulations the threshold voltage instability due to OFF-state drain stress in p-GaN gate AlGaN/GaN-on-Si HEMTs. When the drain of the p-GaN HEMT is biased in the OFF-state the threshold voltage (Vth) shows a linear increase up to 40%. This increase saturates at drain bias voltages above 50 V. The positive Vth shift is attributed to the ionization of acceptor traps in the AlGaN region below the p-GaN gate with the source of these trapping sites suggested to be the p-GaN gate out-diffused Mg dopant atoms. The ionization of the Mg acceptors due to high electric field during OFF-state bias and the removal of the generated holes from the AlGaN region through the gate contact creates the charge conditions for a positive Vth shift. The sharp decrease in the gate drain capacitance (Cgd) for VD< 50 V, the simulated gate edge electric field reaching its peak for a drain voltage bias VD ∼ 50 V and the positive threshold voltage shift observed for negative gate stress further validate the proposed model

Hydrogen Photoproduction by Immobilized N2-fixing Cyanobacteria: Understanding the Role of Uptake Hydrogenase in the Long-term Process.

We have investigated two approaches to enhance and extend H-2 photoproduction yields in heterocystous, N-2-fixing cyanobacteria entrapped in thin alginate films. In the first approach, periodic CO2 supplementation was provided to alginate-entrapped, N-deprived cells. N deprivation led to the inhibition of photosynthetic activity in vegetative cells and the attenuation of H-2 production over time. Our results demonstrated that alginate-entrapped Delta hupL cells were considerably more sensitive to high light intensity, N deficiency, and imbalances in C/N ratios than wild-type cells. In the second approach, Anabaena strain PCC 7120, its Delta hupL mutant, and Calothrix strain 336/3 films were supplemented with N-2 by periodic treatments of air, or air plus CO2. These treatments restored the photosynthetic activity of the cells and led to a high level of H-2 production in Calothrix 336/3 and Delta hupL cells (except for the treatment air plus CO2) but not in the Anabaena PCC 7120 strain (for which H-2 yields did not change after air treatments). The highest H-2 yield was obtained by the air treatment of Delta hupL cells. Notably, the supplementation of CO2 under an air atmosphere led to prominent symptoms of N deficiency in the Delta hupL strain but not in the wild-type strain. We propose that uptake hydrogenase activity in heterocystous cyanobacteria not only supports nitrogenase activity by removing excess O-2 from heterocysts but also indirectly protects the photosynthetic apparatus of vegetative cells from photoinhibition, especially under stressful conditions that cause an imbalance in the C/N ratio in cells.</p

Is It Possible to Predict Cardiac Death?

Cardiovascular diseases are the leading cause of death in all the world; despite having the knowledge of the main risk factors, they keep on being complicated pathologies to deal with. Cardiovascular management has introduced a lot of parameters as regards patients’ state of health; particularly, nuclear cardiology with Stress single-photon emission computed tomography myocardial perfusion imaging can carry out interesting parameters that have encouraged researchers to apply machine learning techniques to predict whether patients will die due to a cardiac event or not. The dataset consisted of 661 patients that were evaluated for suspected of known coronary artery disease at the Department of Advanced Biomedical Sciences of the University Hospital “Federico II” in Naples. Knime analytics platform was employed to implement a decision tree and Random forests. After a procedure of features reduction, 29 features were included, and the overall accuracy was 91.0%, while recall, precision, sensitivity and specificity overcame the value of 90.0%. This implementation shows the feasibility of machine learning combined with data coming from nuclear cardiology. Moreover, the possibility to predict cardiac death exploiting clinical data and parameters carried out from instrumental exams would help clinicians to provide patients with the best treatments and interventions