Advances in concepts and methods for the marine environment: implications for policy

Science-based indicators aimed at measuring the sustainability of human activities on the environment have become of prime importance in the policy arena. At the international level, the Commission on Sustainable Development and the Convention on Biological Diversity and other Multilateral Environmental Agreements have recognised the need to develop a set of scientific indicators related to changes in biodiversity and other environmental issues able to direct policy decisions. In the marine realm, the study of the effects of both ‘top-down’ extractive activities such as fishing is more and more dealt with, in conjunction with ‘bottom-up’ activities such as nutrient loading and the effects on biogeochemical cycles, marine geochemistry and ecosystem structure and functioning of other pollutants and contaminants. ‘Conventional’ approaches such as the identification of taxa, model organisms and related methodologies will continue playing a key role for the monitoring of human-induced changes in the marine environment. On the other hand, newly developed disciplines such as genomics, proteomics and biodiversity informatics are increasingly looked at as a source of information and applications that can respond to questions and concerns by the policy community such as the need to adapt to global and climate change in the marine environment so as to mitigate its societal implications.

Visual data analysis and decision support methods for non-deterministic LCA

Principal components analysis coupled with non-parametric bootstrapping is introduced with an example as a powerful tool to help visualise, analyse and decide on comparative or single non-deterministic LCI/LCIA results. Decision support is provided by adding non-parametric bootstrapping (NPB) to the GA1A plane, which is a special case of principle comments analysis (PCA) built around the Promethée multicriteria decision aid model. In addition to an easy to analyse visual presentation of otherwise complex and cluttered numerical results, PCA with NPB is equally at ease will all data uncertainty formats used to date in LCA.     

Scaling up functional traits for ecosystem services with remote sensing: concepts and methods

Ecosystem service‐based management requires an accurate understanding of how human modification influences ecosystem processes and these relationships are most accurate when based on functional traits. Although trait variation is typically sampled at local scales, remote sensing methods can facilitate scaling up trait variation to regional scales needed for ecosystem service management. We review concepts and methods for scaling up plant and animal functional traits from local to regional spatial scales with the goal of assessing impacts of human modification on ecosystem processes and services. We focus our objectives on considerations and approaches for (1) conducting local plot‐level sampling of trait variation and (2) scaling up trait variation to regional spatial scales using remotely sensed data. We show that sampling methods for scaling up traits need to account for the modification of trait variation due to land cover change and species introductions. Sampling intraspecific variation, stratification by land cover type or landscape context, or inference of traits from published sources may be necessary depending on the traits of interest. Passive and active remote sensing are useful for mapping plant phenological, chemical, and structural traits. Combining these methods can significantly improve their capacity for mapping plant trait variation. These methods can also be used to map landscape and vegetation structure in order to infer animal trait variation. Due to high context dependency, relationships between trait variation and remotely sensed data are not directly transferable across regions. We end our review with a brief synthesis of issues to consider and outlook for the development of these approaches. Research that relates typical functional trait metrics, such as the community‐weighted mean, with remote sensing data and that relates variation in traits that cannot be remotely sensed to other proxies is needed. Our review narrows the gap between functional trait and remote sensing methods for ecosystem service management.     

InraPorc: A model and decision support tool for the nutrition of sows

From results obtained over the last 20 years on energy and amino acid utilisation in reproductive sows, it has become possible to improve the determination of nutrient requirements (factorial approach) and the prediction of an animal's response to nutrient supplies (modelling). The objective of this project was to integrate the current state of knowledge in a nutritional model for growing pigs and for sows and make it available as a software tool to end-users, mainly nutritionists involved in the pig industry and students in animal nutrition. The aim of this paper is to describe the basis of the sow model. The sow is represented as different compartments that change over the reproductive cycle. Nutrient flows considered are those of energy and digestible amino acids. Nutrients are used with the highest priority for maintenance and uterine growth or milk production. Subsequently, deposition and/or mobilisation of body proteins and lipids are determined and used for estimating the changes in body weight and backfat thickness of the sow. A decision support tool was built from the set of equations given, with additional modules to describe animal's characteristics and adjust some model parameters to account for variations in genotypes and performance. This tool can be used to determine energy and amino acids requirements of sows according to production objectives, or to predict body composition changes according to a given feeding strategy. The use of the decision support tool is illustrated through some examples.     

Early signatures of bleeding and mortality in patients on left ventricular assist device support: novel methods for personalized risk-stratification

Background: Left ventricular assist devices (LVADs) provide support for patients with end-stage heart failure. The aims of this study were to determine whether baseline analysis and early trends in routine laboratory data, platelet activity, and thromboinflammatory biomarkers following LVAD implantation reveal trends that predict personalized risks of one-year gastrointestinal (GI) bleeding, stroke, pump thrombosis, drive-line infections and mortality in patients on LVAD support.

Methods: We performed an observational study at the University of Kentucky with 61 participants who underwent first-time LVAD implantation. Blood was collected at baseline and post-op days 0, 1, 3 and 6 as well as clinical follow-up. Demographics, clinical characteristics, one-year adverse events and routine laboratory data were collected from electronic medical records. Platelet function and plasma biomarkers were profiled.

Results: Evaluation of routine laboratory results revealed that sustained thrombocytopenia and increased mean platelet volume (MPV) were associated with development of GI bleeding and mortality. Platelet function at follow-up visit predicted one-year bleeding events. Thrombotic biomarker sCD40L strongly predicted one-year GI bleeding at baseline before implantation and within the first week following LVAD implant.

Conclusions: Early trends in routine bloodwork and platelet function may serve as novel signatures of patients at risk to experience adverse events.     

Development of concepts for human labour accounting in Emergy Assessment and other Environmental Sustainability Assessment methods

Human labour is central to the functioning of any human-influenced process. Nevertheless, Environmental Sustainability Assessments (ESAs) do not systematically include human labour as an input. Systematic omission of labour inputs in ESAs may constitute an unfortunate, significant bias in favour of labour intensive processes and a systematic underestimation of environmental impacts has implications for decision-making. A brief review of the evaluation of human labour in ESAs reveals that only Emergy Assessment (EmA) accounts for labour as standard. Focussing on EmA, we find, however, that there is no agreement on the calculation method for labour. We formalise the calculation of human labour unit emergy values (UEVs) as being the ratio between the emergy resource basis of the labour system and a proxy for labour, with or without allocation to account for different qualities of labour. The formalised calculation approach is demonstrated using examples from the literature (USA, with allocation based on educational level; Ghana, with allocation based on income level; the World, with no allocation). We elaborate on how labour may be considered as endogenous or exogenous to the studied system, and how inputs can be categorised as direct labour taking place in the system under study and indirect labour occurring upstream in the supply chain associated with the studied system. With appropriate modifications, the formalised calculation approach and the distinction between direct and indirect labour may be transferred to other ESA methodologies. Concerning EmA, we recommend that product UEVs should systematically be calculated with and without labour, and that working hours rather than salary should be used when accounting for labour inputs. We recognise that there is a risk of double counting of environmental impacts when including labour. We conclude, however, that it can be ignored for most production systems, since only a negligible fraction of emergy already accounted for is likely to be included in the emergy flow from labour inputs.     

Friends with benefits: Social support and its relevance for farm animal welfare

Despite growing interest in promoting positive welfare, rather than just alleviating poor welfare, potential measures of good welfare, and means to provide it, have remained elusive. In humans social support improves stress-coping abilities, health, and promotes positive psychological welfare. Therefore, social support may be a key approach to promote positive physical and psychological welfare in farm animals. However, the roles of positive social behaviors and social support have been overlooked in comparison to negative social behaviors such as agonistic interactions. The benefits of social partners on an animal's stress coping abilities and welfare are yet poorly understood.The purpose of this paper is to review the protective or buffering effects of social support against stressful challenges and its potential implications for farm animal welfare. The biology of social support is first presented with its behavior, endocrine, autonomic and immune components. The major factors modulating the social support process are then synthesized. Research and implications for animal welfare in different farm species are discussed. Lastly, this review identifies research areas that especially deserve further attention in our effort to understand and implement social support in farm animal welfare.Social support could constitute one of the foundations for welfare researchers to leap from the absence of negative welfare to the provision of positive welfare and emotional experiences.     

InraPorc: A model and decision support tool for the nutrition of growing pigs

Animal production is facing new challenges that call for a more integrative approach towards nutrition. Although considerable research progress has been made by the development of mathematical models of nutrient utilisation in farm animals, practical application of these models has been rather limited. The objective of the InraPorc^® project is to integrate the current state of knowledge in a nutritional model for growing pigs and sows, and make it available as a decision support tool to end-users. The objective for the growing pig (15–150 kg BW) model is to analyse nutrient utilisation for characterised pig types and to evaluate the effects of using different nutritional strategies in terms of nutrient utilisation, performance and carcass characteristics. As model parameters related to feed intake and growth potential are adjusted by the model user, growth (in an absolute sense) is not predicted. The model is based on the transformation of dietary nutrients to body protein and lipid, which are then used to predict body weight, lean body mass and backfat thickness. The representation of nutrient utilisation is mostly based on concepts used in net energy and ideal protein systems. Driving forces of the model include feed intake, the partitioning of energy between protein and lipid deposition, and availability of dietary protein and amino acids. Using literature data, the model appeared reasonably well capable of predicting the consequence of a nutrient intake restriction. The decision support tool is available at http://www.rennes.inra.fr/inraporc/. Through a user-friendly interface, the tool can be used to visualise different aspects of nutrient utilisation and excretion.     

Statistical issues and methods for meta-analysis of microarray data: a case study in prostate cancer

With the proliferation of related microarray studies by independent groups, a natural step in the analysis of these gene expression data is to combine the results across these studies. However, this raises a variety of issues in the analysis of such data. In this article, we discuss the statistical issues of combining data from multiple gene expression studies. This leads to more complications than those in standard meta-analyses, including different experimental platforms, duplicate spots and complex data structures. We illustrate these ideas using data from four prostate cancer profiling studies. In addition, we develop a simple approach for assessing differential expression using the LASSO method. A combination of the results and the pathway databases are then used to generate candidate biological pathways for cancer.     

Design of recombinant antibody microarrays for complex proteome analysis: choice of sample labeling-tag and solid support

Antibody-based microarray is a novel technology with great potential within high-throughput proteomics. The process of designing high-performing antibody (protein) microarrays has, however, turned out to be a challenging process. In this study, we have developed further our human recombinant single-chain variable-fragment (scFv) antibody microarray methodology by addressing two crucial technological issues, choice of sample labeling-tag and solid support. We examined the performance of a range of dyes in a one- or two-color approach on a selection of solid supports providing different surface and coupling chemistries, and surface structures. The set-ups were evaluated in terms of sensitivity, specificity, and selectivity. The results showed that a one-color approach, based on NHS-biotin (or ULS-biotin) labeling, on black polymer Maxisorb slides (or Nexterion slide H) was the superior approach for targeting low-abundant (pg/mL) analytes in nonfractionated, complex proteomes, such as human serum or crude cell supernatants. Notably, microarrays displaying adequate spot morphologies, high S/Ns, minimized nonspecific binding, and most importantly a high selectivity, specificity, and sensitivity (>or=fM range) were obtained. Taken together, we have designed the first generation of a high-performing recombinant scFv antibody microarray technology platform on black polymer Maxisorb slides for sensitive profiling of low-abundant analytes in nonfractionated biotinylated complex proteomes.     

Algorithm-based modular psychotherapy vs. cognitive-behavioral therapy for patients with depression,psychiatric comorbidities and early trauma: a proof-of-concept randomized controlled trial

Effect sizes of psychotherapies currently stagnate at a low-to-moderate level. Personalizing psychotherapy by algorithm-based modular procedures promises improved outcomes, greater flexibility, and a better fit between research and practice. However, evidence for the feasibility and efficacy of modular-based psychotherapy, using a personalized treatment algorithm, is lacking. This proof-of-concept randomized controlled trial was conducted in 70 adult outpatients with a primary DSM-5 diagnosis of major depressive disorder, a score higher than 18 on the 24-item Hamilton Rating Scale for Depression (HRSD-24), at least one comorbid psychiatric diagnosis according to the Structured Clinical Interview for DSM-5 (SCID-5), a history of at least “moderate to severe” childhood maltreatment on at least one domain of the Childhood Trauma Questionnaire (CTQ), and exceeding the cut-off value on at least one of three measures of early trauma-related transdiagnostic mechanisms: the Rejection Sensitivity Questionnaire (RSQ), the Interpersonal Reactivity Index (IRI), and the Difficulties in Emotion Regulation Scale-16 (DERS-16). Patients were randomized to 20 sessions of either standard cognitive-behavioral therapy alone (CBT) or CBT plus transdiagnostic modules according to a mechanism-based treatment algorithm (MoBa), over 16 weeks. We aimed to assess the feasibility of MoBa, and to compare MoBa vs. CBT with respect to participants’ and therapists’ overall satisfaction and ratings of therapeutic alliance (using the Working Alliance Inventory - Short Revised, WAI-SR), efficacy, impact on early trauma-related transdiagnostic mechanisms, and safety. The primary outcome for efficacy was the HRSD-24 score at post-treatment. Secondary outcomes included, among others, the rate of response (defined as a reduction of the HRSD-24 score by at least 50% from baseline and a score <16 at post-treatment), the rate of remission (defined as a HRSD-24 score ≤8 at post-treatment), and improvements in early trauma-related mechanisms of social threat response, hyperarousal, and social processes/empathy. We found no difficulties in the selection of the transdiagnostic modules in the individual patients, applying the above-mentioned cut-offs, and in the implementation of MoBa. Both participants and therapists reported higher overall satisfaction and had higher WAI-SR ratings with MoBa than CBT. Both approaches led to major reductions of depressive symptoms at post-treatment, with a non-significant superiority of MoBa over CBT. Patients randomized to MoBa were nearly three times as likely to experience remission at the end of therapy (29.4% vs. 11.4%; odds ratio, OR = 3.2, 95% CI: 0.9-11.6). Among mechanism-based outcomes, MoBa patients showed a significantly higher post-treatment effect on social processes/empathy (p<0.05) compared to CBT patients, who presented an exacerbation on this domain at post-treatment. Substantially less adverse events were reported for MoBa compared to CBT. These results suggest the feasibility and acceptability of an algorithm-based modular psychotherapy complementing CBT in depressed patients with psychiatric comorbidities and early trauma. While initial evidence of efficacy was observed, potential clinical advantages and interindividual heterogeneity in treatment outcomes will have to be investigated in fully powered confirmation trials.     

Functional differentiation between the inner and outer leaves in a mechanical support by a pseudostem of Veratrum album subsp. oxysepalum

The pseudostem of Veratrum album subsp. oxysepalum consists of radical leaves, which have tubular and concentrically aggregated petioles. We examined a hypothesis that the major role of the inner leaves is to raise the leaf blades higher for increased photosynthesis, while that of the outer leaves is to mechanically support the inner leaves at the expense of displaying their leaf blades. The removal of outer leaves resulted in the collapse of the remaining inner leaves, showing outer leaves provide important support for inner leaves. The estimation of mechanical properties for the constituting leaves revealed that inner leaves possess greater mass of leaf blades for their capacity of mechanical support them compared to outer leaves. These results uphold the hypothesis that the primary role of inner leaves is to display leaf blades for photosynthesis, while that for outer leaves is to mechanically support the less stable inner leaves.     

Using principal component analysis and support vector machine to predict protein structural class for low-similarity sequences via PSSM

The accurate identification of protein structure class solely using extracted information from protein sequence is a complicated task in the current computational biology. Prediction of protein structural class for low-similarity sequences remains a challenging problem. In this study, the new computational method has been developed to predict protein structural class by fusing the sequence information and evolution information to represent a protein sample. To evaluate the performance of the proposed method, jackknife cross-validation tests are performed on two widely used benchmark data-sets, 1189 and 25PDB with sequence similarity lower than 40 and 25%, respectively. Comparison of our results with other methods shows that the proposed method by us is very promising and may provide a cost-effective alternative to predict protein structural class in particular for low-similarity data-sets.     

Expression and amplification of glutamine synthetase gene endows HepG2 cells with ammonia-metabolizing activity for bioartificial liver support system

To establish the ammonia-metabolizing cell lines for a bioartificial liver support system, CHO-K1 and HepG2 were transformed with pBK-CMV-GS vector that contains glutamine synthetase (gs) gene. The recombinant cell lines were selected under the various concentrations of glutamine synthetase inhibitor, methionine sulfoximine (MSX). The host CHO-K1 and HepG2 cell lines produces ammonia, but the both MSX tolerable CHO (GS-CHO) and HepG2 (GS-HepG2) cell lines endowed with the high GS activity could metabolize the ammonium from medium. The ammonia-metabolizing activity of CHO and HepG2 cell was about one-fourth of that of primary hepatocyte.     

GnRHa for trigger and luteal phase support in natural cycle frozen embryo transfer – A proof of concept study

We aimed to explore whether ovulation induced by a GnRH analogue (GnRHa), followed by daily GnRHa luteal support provides an efficient platform for natural cycle frozen embryo transfer (NC-FET).In this cohort study, included were normo-ovulatory women who underwent NC-FET cycles, under the age of 40, with an antral follicle count > eight. Ovulation was triggered with triptorelin (0.2 mg Decapeptyl; Ferring), and luteal support was initiated two days later, using a Nafarelin inhaler (Synarel, Pfizer), 200 μg twice daily. Main outcome measures were luteal estradiol and progesterone levels (three to five days following ovulation), implantation rate, ongoing pregnancy rate, early pregnancy loss rate, and live birth rate.Fifty-one patients treated between 2017 and 2018 were included. Mid luteal progesterone levels among study patients, were non-significantly different between patients who achieved pregnancy and those who did not, but differed significantly on day 14 following ovulation (86.0 ± 31.3 vs. 9.8 ± 9.5 nmol/L, respectively, p < 0.001). Twenty-three patients achieved a clinical pregnancy (45.1 %); interestingly, there were no chemical pregnancies. Three pregnancies ended in an early abortion at 6–7 weeks gestation, and 20 pregnancies continued as ongoing pregnancies (39.2 %). One patient had a late abortion at 16 weeks gestation, and 14 had a live birth.In conclusion, in this proof of concept study, inducing ovulation with a bolus of GnRHa in NC-FET, followed by repeated daily GnRHa administration, resulted in satisfactory luteal phase steroid levels and high ongoing pregnancy and live birth rates.     

Improvement of the enantioselectivity and activity of lipase from Pseudomonas sp. via adsorption on a hydrophobic support: kinetic resolution of 2-octanol

Pseudomonas sp. lipase (PSL) was successfully immobilized on a novel hydrophobic polymer support through physical adsorption and the immobilized PSL was used for resolution of (R,S)-2-octanol with vinyl acetate as acyl donor. Enhanced activity and enantioselectivity were observed from the immobilized PSL compared with free PSL. The effects of reaction conditions such as temperature, water activity, substrate molar ratio and the amount of immobilized lipase were investigated. Under optimum conditions, the residual (S)-2-octanol was recovered with 99.5% enantiomeric excess at 52.9% conversion. The results also indicated that the immobilized PSL could maintain 94% of its initial activity even after reusing it five times.