Environmental assessment of industrial production of microalgal biodiesel in central-south Chile

Biofuels from microalgae have the potential to replace fossil fuels, without competing with other products derived from crops. This study aims to perform a cradle-to-gate Life Cycle Assessment of the industrial production of microalgal biodiesel, using an autochthonous Chilean Phaeodactylum tricornutum strain, considering 1 MJ of biodiesel as the functional unit. For the compilation of the Life Cycle Inventory, real experimental data were obtained from the pilot-scale cultivation in a photobioreactor (PBR) module located in the city of Concepción, in Chile. The scale-up to the industrial plant considers that PBR modules are of the same size as those used in the pilot-scale. The Life Cycle Impacts Analysis considered the ReCiPe 2016 Endpoint (H) V1.00 method. Results show that the whole process contributes to a total of 5.74 kgCO2eq per MJ of biodiesel produced. PBR construction materials and energy consumption are the main contributors to the life cycle environmental impacts. The sensitivity analysis shows that energy consumption, water reuse and transportation distance of seawater from ocean to the industrial plant are the critical parameters that most affect the overall environmental performance of the system. The rate of water reuse is particularly critical to the global warming potential. Results also show that the valorization of co-products is an important aspect to improve the environmental performance of microalgal biodiesel production. Therefore, this study supports the decision-making process in biofuel production to promote the development of sustainable pilot and large-scale algae-based industry.publishe

New insights into the genetic etiology of Alzheimer's disease and related dementias.

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele

Brazilian Flora 2020: Leveraging the power of a collaborative scientific network

International audienceThe shortage of reliable primary taxonomic data limits the description of biological taxa and the understanding of biodiversity patterns and processes, complicating biogeographical, ecological, and evolutionary studies. This deficit creates a significant taxonomic impediment to biodiversity research and conservation planning. The taxonomic impediment and the biodiversity crisis are widely recognized, highlighting the urgent need for reliable taxonomic data. Over the past decade, numerous countries worldwide have devoted considerable effort to Target 1 of the Global Strategy for Plant Conservation (GSPC), which called for the preparation of a working list of all known plant species by 2010 and an online world Flora by 2020. Brazil is a megadiverse country, home to more of the world's known plant species than any other country. Despite that, Flora Brasiliensis, concluded in 1906, was the last comprehensive treatment of the Brazilian flora. The lack of accurate estimates of the number of species of algae, fungi, and plants occurring in Brazil contributes to the prevailing taxonomic impediment and delays progress towards the GSPC targets. Over the past 12 years, a legion of taxonomists motivated to meet Target 1 of the GSPC, worked together to gather and integrate knowledge on the algal, plant, and fungal diversity of Brazil. Overall, a team of about 980 taxonomists joined efforts in a highly collaborative project that used cybertaxonomy to prepare an updated Flora of Brazil, showing the power of scientific collaboration to reach ambitious goals. This paper presents an overview of the Brazilian Flora 2020 and provides taxonomic and spatial updates on the algae, fungi, and plants found in one of the world's most biodiverse countries. We further identify collection gaps and summarize future goals that extend beyond 2020. Our results show that Brazil is home to 46,975 native species of algae, fungi, and plants, of which 19,669 are endemic to the country. The data compiled to date suggests that the Atlantic Rainforest might be the most diverse Brazilian domain for all plant groups except gymnosperms, which are most diverse in the Amazon. However, scientific knowledge of Brazilian diversity is still unequally distributed, with the Atlantic Rainforest and the Cerrado being the most intensively sampled and studied biomes in the country. In times of “scientific reductionism”, with botanical and mycological sciences suffering pervasive depreciation in recent decades, the first online Flora of Brazil 2020 significantly enhanced the quality and quantity of taxonomic data available for algae, fungi, and plants from Brazil. This project also made all the information freely available online, providing a firm foundation for future research and for the management, conservation, and sustainable use of the Brazilian funga and flora

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele. © 2022. The Author(s)

Dielectron and heavy-quark production in inelastic and high-multiplicity proton–proton collisions at √s = 13 TeV

The measurement of dielectron production is presented as a function of invariant mass and transverse momentum (pT) at midrapidity (|ye| < 0.8) in proton–proton (pp) collisions at a centre-of-mass energy of √s = 13 TeV. The contributions from light-hadron decays are calculated from their measured cross sections in pp collisions at √s = 7 TeV or 13 TeV. The remaining continuum stems from correlated semileptonic decays of heavy-flavour hadrons. Fitting the data with templates from two different MC event generators, PYTHIA and POWHEG, the charm and beauty cross sections at midrapidity are extracted for the first time at this collision energy: dσcc¯/dy|y=0 = 974 ± 138 (stat.) ± 140 (syst.) ± 214(BR) μb and dσbb¯ /dy|y=0 = 79 ± 14 (stat.) ± 11 (syst.) ± 5(BR) μb using PYTHIA simulations and dσcc¯/dy|y=0 = 1417 ± 184 (stat.) ± 204 (syst.) ± 312(BR) μb and dσbb¯ /dy|y=0 = 48 ± 14 (stat.) ± 7 (syst.) ± 3(BR) μb for POWHEG. These values, whose uncertainties are fully correlated between the two generators, are consistent with extrapolations from lower energies. The different results obtained with POWHEG and PYTHIA imply different kinematic correlations of the heavy-quark pairs in these two generators. Furthermore, comparisons of dielectron spectra in inelastic events and in events collected with a trigger on high charged-particle multiplicities are presented in various pT intervals. The differences are consistent with the already measured scaling of light-hadron and open-charm production at high charged-particle multiplicity as a function of pT. Upper limits for the contribution of virtual direct photons are extracted at 90% confidence level and found to be in agreement with pQCD calculations

Measurement of the radius dependence of charged-particle jet suppression in Pb–Pb collisions at sNN=5.02\sqrt{s_{\rm NN}} = 5.02 TeV

The ALICE Collaboration reports a new differential measurement of inclusive jet suppression using pp and Pb–Pb collision data at center-of-mass energy per nucleon–nucleon collision $\sqrt{s_{\rm NN}} = 5.02$ TeV. Charged-particle jets are reconstructed using the anti-$k_{\rm T}$ algorithm with resolution parameters $R$ = 0.2, 0.3, 0.4, 0.5, and 0.6 in pp collisions and $R$ = 0.2, 0.4, 0.6 in central (0–10\%), semi-central (30–50\%), and peripheral (60–80\%) Pb–Pb collisions. The analysis uses a novel approach based on machine learning to mitigate the influence of jet background in central heavy-ion collisions, which enables measurements of inclusive jet suppression for jet $p_{\rm T} \ge 40$ GeV/$c$ in central collisions at a resolution parameter of $R$ = 0.6. This is the lowest value of jet $p_{\rm T}$ achieved for inclusive jet measurements at $R$ = 0.6 at the LHC, and is an important step for discriminating different models of jet quenching in the quark-gluon plasma. The transverse momentum spectra, nuclear modification factors, and derived cross section and nuclear modification factor ratios for different jet resolution parameters of charged-particle jets are presented and compared to model predictions. A mild dependence of the nuclear modification factor ratios on collision centrality and resolution parameter is observed. The results are compared to a variety of jet quenching models with varying levels of agreement, demonstrating the effectiveness of this observable to discriminate between models.The ALICE Collaboration reports a new differential measurement of inclusive jet suppression using pp and Pb$-$Pb collision data at center-of-mass energy per nucleon-nucleon collision $\sqrt{s_{\rm NN}} = 5.02$ TeV. Charged-particle jets are reconstructed using the anti-$k_{\rm T}$ algorithm with resolution parameters $R =$ 0.2, 0.3, 0.4, 0.5, and 0.6 in pp collisions and $R =$ 0.2, 0.4, 0.6 in central (0$-$10%), semi-central (30$-$50%), and peripheral (60$-$80%) Pb$-$Pb collisions. The analysis uses a novel approach based on machine learning to mitigate the influence of jet background in central heavy-ion collisions, which enables measurements of inclusive jet suppression for jet $p_{\rm T} \geq 40$ GeV/$c$ in central collisions at a resolution parameter of $R = 0.6$. This is the lowest value of jet $p_{\rm T}$ achieved for inclusive jet measurements at $R=0.6$ at the LHC, and is an important step for discriminating different models of jet quenching in the quark-gluon plasma. The transverse momentum spectra, nuclear modification factors, and derived cross section and nuclear modification factor ratios for different jet resolution parameters of charged-particle jets are presented and compared to model predictions. A mild dependence of the nuclear modification factor ratios on collision centrality and resolution parameter is observed. The results are compared to a variety of jet quenching models with varying levels of agreement, demonstrating the effectiveness of this observable to discriminate between models

Symmetry plane correlations in Pb–Pb collisions at √sNN = 2.76 TeV

A newly developed observable for correlations between symmetry planes, which characterize the direction of the anisotropic emission of produced particles, is measured in Pb-Pb collisions at sNN−−−√=2.76 TeV with ALICE. This so-called Gaussian Estimator allows for the first time the study of these quantities without the influence of correlations between different flow amplitudes. The centrality dependence of various correlations between two, three and four symmetry planes is presented. The ordering of magnitude between these symmetry plane correlations is discussed and the results of the Gaussian Estimator are compared with measurements of previously used estimators. The results utilizing the new estimator lead to significantly smaller correlations than reported by studies using the Scalar Product method. Furthermore, the obtained symmetry plane correlations are compared to state-of-the-art hydrodynamic model calculations for the evolution of heavy-ion collisions. While the model predictions provide a qualitative description of the data, quantitative agreement is not always observed, particularly for correlators with significant non-linear response of the medium to initial state anisotropies of the collision system. As these results provide unique and independent information, their usage in future Bayesian analysis can further constrain our knowledge on the properties of the QCD matter produced in ultrarelativistic heavy-ion collisions