On the challenges of using field spectroscopy to measure the impact of soil type on leaf traits

Understanding the causes of variation in plant functional traits is a central issue in ecology, particularly in the context of global change.  Spectroscopy is increasingly used for rapid and non-destructive estimation of foliar traits, but few studies have evaluated its accuracy when assessing phenotypic variation in multiple traits. Working with 24 chemical and physical leaf traits of six European tree species growing on strongly contrasting soil types (i.e. deep alluvium versus nearby shallow chalk), we asked (i) whether variability in leaf traits is greater between tree species or soil type; and (ii) whether field spectroscopy is effective at predicting intraspecific variation in leaf traits as well as interspecific differences.  Analysis of variance showed that inter-specific differences in traits were generally much stronger than intraspecific differences related to soil type, accounting for 25% versus 5% of total trait variation, respectively. Structural traits, phenolic defences and pigments were barely affected by soil type.  In contrast, foliar concentrations of rock-derived nutrients did vary: P and K concentration were lower on chalk than alluvial soils, while Ca, Mg, B, Mn and Zn concentrations were all higher, consistent with the findings of previous ecological studies. Foliar traits were predicted from 400-2500 nm reflectance spectra collected by field spectroscopy using partial least square regression, a method that is commonly employed in chemometrics.  Pigments were best modelled using reflectance data from the visible region (400 - 700 nm), whilst all other traits were best modelled using reflectance data from the shortwave infrared region (1100 - 2500 nm) region. Spectroscopy delivered accurate predictions of species-level variation in traits. However, it was ineffective at detecting intraspecific variation in rock-derived nutrients (with the notable exception of P). The explanation for this failure is that rock-derived elements do not have absorption features in the 400-2500 nm region, and their estimation is indirect, relying on elemental concentrations co-varying with structural traits that do have absorption features in that spectral region (“constellation effects”).  Since the structural traits did not vary with soil type, it was impossible for our regression models to predict intraspecific variation in rock-derived nutrients via constellation effects. This study demonstrates the value of spectroscopy for rapid, non-destructive estimation of foliar traits across species, but highlights problems with predicting intraspecific variation indirectly. We discuss the implications of these findings for mapping functional traits by airborne imaging spectroscopy.David Coomes was supported by a grant from NERC (NE/K016377/1) and Matheus H. Nunes is supported by a PhD scholarship from the Conselho Nacional de Pesquisa e Desenvolvimento (CNPq)

Recycling the purpose of old drugs to treat ovarian cancer

The main challenge in ovarian cancer treatment is the management of recurrences. Facing this scenario, therapy selection is based on multiple factors to define the best treatment sequence. Target therapies, such as bevacizumab and polymerase (PARP) inhibitors, improved patient survival. However, despite their achievements, ovarian cancer survival remains poor; these therapeutic options are highly costly and can be associated with potential side effects. Recently, it has been shown that the combination of repurposed, conventional, chemotherapeutic drugs could be an alternative, presenting good patient outcomes with few side effects and low costs for healthcare institutions. The main aim of this review is to strengthen the importance of repurposed drugs as therapeutic alternatives, and to propose an in vitro model to assess the therapeutic value. Herein, we compiled the current knowledge on the most promising non-oncological drugs for ovarian cancer treatment, focusing on statins, metformin, bisphosphonates, ivermectin, itraconazole, and ritonavir. We discuss the primary drug use, anticancer mechanisms, and applicability in ovarian cancer. Finally, we propose the use of these therapies to perform drug efficacy tests in ovarian cancer ex vivo cultures. This personalized testing approach could be crucial to validate the existing evidences supporting the use of repurposed drugs for ovarian cancer treatment.Funding: This manuscript was funded by HOPE: Improving ovarian cancer patients’ survival—donation from an ovarian cancer patient and by the FCT (Fundação para a Ciência e a Tecnologia) project PTDC/MEC-ONC/29503/2017

Mapping Aboveground Carbon in Oil Palm Plantations Using LiDAR: A Comparison of Tree-Centric versus Area-Based Approaches

Southeast Asia is the epicentre of world palm oil production. Plantations in Malaysia have increased 150% in area within the last decade, mostly at the expense of tropical forests. Maps of the aboveground carbon density (ACD) of vegetation generated by remote sensing technologies, such as airborne LiDAR, are vital for quantifying the effects of land use change for greenhouse gas emissions, and many papers have developed methods for mapping forests. However, nobody has yet mapped oil palm ACD from LiDAR. The development of carbon prediction models would open doors to remote monitoring of plantations as part of efforts to make the industry more environmentally sustainable. This paper compares the performance of tree-centric and area-based approaches to mapping ACD in oil palm plantations. We find that an area-based approach gave more accurate estimates of carbon density than tree-centric methods and that the most accurate estimation model includes LiDAR measurements of top-of-canopy height and canopy cover. We show that tree crown segmentation is sensitive to crown density, resulting in less accurate tree density and ACD predictions, but argue that tree-centric approach can nevertheless be useful for monitoring purposes, providing a method to detect, extract and count oil palm trees automatically from images.Airborne laser scanning data were collected by NERC ARF as part of NERC’s Human-modified Tropical Forests Programme (Biodiversity And Land-use Impacts on tropical ecosystem function (BALI) project; grant number: NE/K016377/1). We are grateful to the flight team and the data analysts at NERC’s data analysis node. Marion Pfeifer kindly provided us access to Pléiades imagery. We thank the Sime Darby Foundation, the Sabah Foundation, Benta Wawasan and the Sabah Forestry Department for their support of the SAFE Project. We thank the Royal Society South East Asia Rainforest Research Partnership for logistical support in the field

The Dynamics of Nestedness Predicts the Evolution of Industrial Ecosystems

In economic systems, the mix of products that countries make or export has been shown to be a strong leading indicator of economic growth. Hence, methods to characterize and predict the structure of the network connecting countries to the products that they export are relevant for understanding the dynamics of economic development. Here we study the presence and absence of industries at the global and national levels and show that these networks are significantly nested. This means that the less filled rows and columns of these networks' adjacency matrices tend to be subsets of the fuller rows and columns. Moreover, we show that nestedness remains relatively stable as the matrices become more filled over time and that this occurs because of a bias for industries that deviate from the networks' nestedness to disappear, and a bias for the missing industries that reduce nestedness to appear. This makes the appearance and disappearance of individual industries in each location predictable. We interpret the high level of nestedness observed in these networks in the context of the neutral model of development introduced by Hidalgo and Hausmann (2009). We show that, for the observed fills, the model can reproduce the high level of nestedness observed in these networks only when we assume a high level of heterogeneity in the distribution of capabilities available in countries and required by products. In the context of the neutral model, this implies that the high level of nestedness observed in these economic networks emerges as a combination of both, the complementarity of inputs and heterogeneity in the number of capabilities available in countries and required by products. The stability of nestedness in industrial ecosystems, and the predictability implied by it, demonstrates the importance of the study of network properties in the evolution of economic networks.Comment: 26 page

Discomfort experienced at the daily life of relatives of people admitted at ICU

This is a qualitative research that aimed to get to know the discomforts experienced at the daily life of relatives of people admitted at the intensive care unit (ICU). It happened on a general ICU at a public hospital, in Salvador-BA, by the second half of 2009. Nine relatives of people admitted were interviewed. The technique used was the analysis from the Grounded Theory. The results showed that the interaction of the families with the reality of life threat from the relative admitted, had as main discomfort, the discontinuity in their daily life, which was characterized by four categories: Living the distress of a possible loss, difficulties to take care of themselves, facing a separation in the family, suffering with changes in their social and professional lives. These discomforts can be minimized by the healthcare team’s effectiveness to the demands of the family and the support of its social network

Predicting progression of mild cognitive impairment to dementia using neuropsychological data: a supervised learning approach using time windows

Background: Predicting progression from a stage of Mild Cognitive Impairment to dementia is a major pursuit in current research. It is broadly accepted that cognition declines with a continuum between MCI and dementia. As such, cohorts of MCI patients are usually heterogeneous, containing patients at different stages of the neurodegenerative process. This hampers the prognostic task. Nevertheless, when learning prognostic models, most studies use the entire cohort of MCI patients regardless of their disease stages. In this paper, we propose a Time Windows approach to predict conversion to dementia, learning with patients stratified using time windows, thus fine-tuning the prognosis regarding the time to conversion. Methods: In the proposed Time Windows approach, we grouped patients based on the clinical information of whether they converted (converter MCI) or remained MCI (stable MCI) within a specific time window. We tested time windows of 2, 3, 4 and 5 years. We developed a prognostic model for each time window using clinical and neuropsychological data and compared this approach with the commonly used in the literature, where all patients are used to learn the models, named as First Last approach. This enables to move from the traditional question "Will a MCI patient convert to dementia somewhere in the future" to the question "Will a MCI patient convert to dementia in a specific time window". Results: The proposed Time Windows approach outperformed the First Last approach. The results showed that we can predict conversion to dementia as early as 5 years before the event with an AUC of 0.88 in the cross-validation set and 0.76 in an independent validation set. Conclusions: Prognostic models using time windows have higher performance when predicting progression from MCI to dementia, when compared to the prognostic approach commonly used in the literature. Furthermore, the proposed Time Windows approach is more relevant from a clinical point of view, predicting conversion within a temporal interval rather than sometime in the future and allowing clinicians to timely adjust treatments and clinical appointments.FCT under the Neuroclinomics2 project [PTDC/EEI-SII/1937/2014, SFRH/BD/95846/2013]; INESC-ID plurianual [UID/CEC/50021/2013]; LASIGE Research Unit [UID/CEC/00408/2013

Effect of base–acid properties of the mixtures of water with methanol on the solution enthalpy of selected cyclic ethers in this mixture at 298.15 K

The enthalpies of solution of cyclic ethers: 1,4- dioxane, 12-crown-4 and 18-crown-6 in the mixture of water and methanol have been measured within the whole mole fraction range at T = 298.15 K. Based on the obtained data, the effect of base–acid properties of water– methanol mixtures on the solution enthalpy of cyclic ethers in these mixtures has been analyzed. The solution enthalpy of cyclic ethers depends on acid properties of water– methanol mixtures in the range of high and medium water contents in the mixture. Based on the analysis performed, it can be assumed that in the mixtures of high methanol contents, cyclic ethe

Vibrational analysis of d-PCL(530)/siloxane based hybrids doped with two lithium salts

Published online: 22 May 2013The present study has been focused on environmentally friendly sol-gel derived electrolytes based on a di-urethane cross-linked d-PCL(530)/siloxane network (where d represents di, PCL identifies the poly(ε–caprolactone) biopolymer and 530 is the average molecular weight in g.mol-1) doped with a wide range of concentration of lithium perchlorate (LiClO4) and lithium bis(trifluoromethanesulfonyl)imide (LiTFSI). Fourier Transform Infrared and Raman (FT-IR and FT-Raman, respectively) spectroscopies have been applied to evaluate the extent of ionic association. Characteristic bands of the PCL(530) segments, of the urethane cross-links and of the anions have been examined to gain insight into the cation/biopolymer, cation/anion and cation/cross-link interactions. In both electrolyte systems “free” ions and contact ions have been identified. The addition of salt modifies the hydrogen-bonded array of the host matrix, causing the destruction/formation of the urethane/urethane aggregates.Fundação para a Ciência e a Tecnologia (FCT

The major barriers to evidence-informed conservation policy and possible solutions

Conservation policy decisions can suffer from a lack of evidence, hindering effective decision-making. In nature conservation, studies investigating why policy is often not evidence-informed have tended to focus on Western democracies, with relatively small samples. To understand global variation and challenges better, we established a global survey aimed at identifying top barriers and solutions to the use of conservation science in policy. This obtained the views of 758 people in policy, practice, and research positions from 68 countries across six languages. Here we show that, contrary to popular belief, there is agreement between groups about how to incorporate conservation science into policy, and there is thus room for optimism. Barriers related to the low priority of conservation were considered to be important, while mainstreaming conservation was proposed as a key solution. Therefore, priorities should focus on convincing the public of the importance of conservation as an issue, which will then influence policy-makers to adopt pro-environmental long-term policies.NERC (1653183) Grantham Foundation for the Protection of the Environment Kenneth Miller Trust (unknown) NERC (1653183) NERC (NE/L002507/1) European Commission (308454

Identification and characterization of a novel non-structural protein of bluetongue virus

Bluetongue virus (BTV) is the causative agent of a major disease of livestock (bluetongue). For over two decades, it has been widely accepted that the 10 segments of the dsRNA genome of BTV encode for 7 structural and 3 non-structural proteins. The non-structural proteins (NS1, NS2, NS3/NS3a) play different key roles during the viral replication cycle. In this study we show that BTV expresses a fourth non-structural protein (that we designated NS4) encoded by an open reading frame in segment 9 overlapping the open reading frame encoding VP6. NS4 is 77–79 amino acid residues in length and highly conserved among several BTV serotypes/strains. NS4 was expressed early post-infection and localized in the nucleoli of BTV infected cells. By reverse genetics, we showed that NS4 is dispensable for BTV replication in vitro, both in mammalian and insect cells, and does not affect viral virulence in murine models of bluetongue infection. Interestingly, NS4 conferred a replication advantage to BTV-8, but not to BTV-1, in cells in an interferon (IFN)-induced antiviral state. However, the BTV-1 NS4 conferred a replication advantage both to a BTV-8 reassortant containing the entire segment 9 of BTV-1 and to a BTV-8 mutant with the NS4 identical to the homologous BTV-1 protein. Collectively, this study suggests that NS4 plays an important role in virus-host interaction and is one of the mechanisms played, at least by BTV-8, to counteract the antiviral response of the host. In addition, the distinct nucleolar localization of NS4, being expressed by a virus that replicates exclusively in the cytoplasm, offers new avenues to investigate the multiple roles played by the nucleolus in the biology of the cell