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1.
Laura Zanchi Massimo Delogu Alessandra Zamagni Marco Pierini 《The International Journal of Life Cycle Assessment》2018,23(3):519-535
Purpose
Social life cycle assessment (S-LCA) applications have been growing during the last years. Most of the scientific articles published so far have addressed the applicability of S-LCA, focusing on selecting suitable indicators, and only recently, the developments in the area of impact pathway are increasing. However, a critical analysis of how to set an S-LCA study, in particular the goal and scope and inventory phase, is missing. This article critically analyses the most important elements affecting the goal and scope and inventory phase of S-LCA, with a focus on the automotive sector, with the ultimate goal of developing a structured approach to guide practitioners in the critical application of S-LCA.Methods
The literature review covers 67 publications from 2006 to 2015, including all the case studies published so far, to the best knowledge of the authors, in several sectors and the automotive one. The reviewed works have been structured along the key elements affecting the goal and scope and inventory phases of the S-LCA.Results and discussion
The methodological and practical issues affecting S-LCA have been organized into a conceptual map, in which all the elements are sequentially placed. This sequence is an orderly procedure consisting of several nodes representing crucial points where a decision needs to be taken or a further reflection is necessary. The case studies of the automotive sector and the corporate-related documents have been used also for the discussion of the conceptual map nodes to identify which aspects are already covered by the literature and which ones need further research.Conclusions
Facing the inventory phase of S-LCA needs also to set specific elements of the goal and scope phase which are fundamental for approaching coherently the product system at hand and for supporting the selection of stakeholders, indicators, and data. Moreover, in order to foster S-LCA applications and make it a robust decision-support tool, the authors suggest to re-define its framework and approach according to the organizational perspective, as laid down in the recent Organisation Environmental Footprint and Organizational LCA. This implies that social aspects will be evaluated both in relation to the organization behavior and to the basket of products, thus reconciling the need to keep together the conduct-of-a-company perspective, typical of social evaluations, and the product-oriented approach, inherent to the life cycle and in particular to the functional unit concept.2.
Introduction
Untargeted metabolomics is a powerful tool for biological discoveries. To analyze the complex raw data, significant advances in computational approaches have been made, yet it is not clear how exhaustive and reliable the data analysis results are.Objectives
Assessment of the quality of raw data processing in untargeted metabolomics.Methods
Five published untargeted metabolomics studies, were reanalyzed.Results
Omissions of at least 50 relevant compounds from the original results as well as examples of representative mistakes were reported for each study.Conclusion
Incomplete raw data processing shows unexplored potential of current and legacy data.3.
Antonio Rosato Leonardo Tenori Marta Cascante Pedro Ramon De Atauri Carulla Vitor A. P. Martins dos Santos Edoardo Saccenti 《Metabolomics : Official journal of the Metabolomic Society》2018,14(4):37
Introduction
Metabolomics is a well-established tool in systems biology, especially in the top–down approach. Metabolomics experiments often results in discovery studies that provide intriguing biological hypotheses but rarely offer mechanistic explanation of such findings. In this light, the interpretation of metabolomics data can be boosted by deploying systems biology approaches.Objectives
This review aims to provide an overview of systems biology approaches that are relevant to metabolomics and to discuss some successful applications of these methods.Methods
We review the most recent applications of systems biology tools in the field of metabolomics, such as network inference and analysis, metabolic modelling and pathways analysis.Results
We offer an ample overview of systems biology tools that can be applied to address metabolomics problems. The characteristics and application results of these tools are discussed also in a comparative manner.Conclusions
Systems biology-enhanced analysis of metabolomics data can provide insights into the molecular mechanisms originating the observed metabolic profiles and enhance the scientific impact of metabolomics studies.4.
Jack W. KentJr 《BMC genetics》2016,17(Z2):S5
Background
New technologies for acquisition of genomic data, while offering unprecedented opportunities for genetic discovery, also impose severe burdens of interpretation andpenalties for multiple testing.Methods
The Pathway-based Analyses Group of the Genetic Analysis Workshop 19 (GAW19) sought reduction of multiple-testing burden through various approaches to aggregation of highdimensional data in pathways informed by prior biological knowledge.Results
Experimental methods testedincluded the use of "synthetic pathways" (random sets of genes) to estimate power and false-positive error rate of methods applied to simulated data; data reduction via independent components analysis, single-nucleotide polymorphism (SNP)-SNP interaction, and use of gene sets to estimate genetic similarity; and general assessment of the efficacy of prior biological knowledge to reduce the dimensionality of complex genomic data.Conclusions
The work of this group explored several promising approaches to managing high-dimensional data, with the caveat that these methods are necessarily constrained by the quality of external bioinformatic annotation.5.
Daniel Cañueto Josep Gómez Reza M. Salek Xavier Correig Nicolau Cañellas 《Metabolomics : Official journal of the Metabolomic Society》2018,14(3):24
Introduction
Adoption of automatic profiling tools for 1H-NMR-based metabolomic studies still lags behind other approaches in the absence of the flexibility and interactivity necessary to adapt to the properties of study data sets of complex matrices.Objectives
To provide an open source tool that fully integrates these needs and enables the reproducibility of the profiling process.Methods
rDolphin incorporates novel techniques to optimize exploratory analysis, metabolite identification, and validation of profiling output quality.Results
The information and quality achieved in two public datasets of complex matrices are maximized.Conclusion
rDolphin is an open-source R package (http://github.com/danielcanueto/rDolphin) able to provide the best balance between accuracy, reproducibility and ease of use.6.
N. Cesbron A.-L. Royer Y. Guitton A. Sydor B. Le Bizec G. Dervilly-Pinel 《Metabolomics : Official journal of the Metabolomic Society》2017,13(8):99
Introduction
Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.Objectives
In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.Methods
The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.Results
A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.Conclusion
The workflow generated repeatable and informative fingerprints for robust metabolome characterization.7.
8.
Testing environmental and social indicators for biorefineries: bioethanol and biochemical production
Clara Valente Andreas Brekke Ingunn Saur Modahl 《The International Journal of Life Cycle Assessment》2018,23(3):581-596
Purpose
The article aims to test indicators for assessing the environmental and social impacts of biorefineries. Testing environmental and social impact categories and indicators, and selecting the most suitable ones, will simultaneously contribute to the further development of social life cycle assessment (S-LCA) methodologies while assessing several dimensions of sustainability at biorefineries.Methods
The work applies two methodologies, environmental LCA (E-LCA) and social LCA (S-LCA), to two hypothetical production processes of second-generation bioethanol and biochemical in two alternative locations (Norway and the USA). Five impact categories were chosen for the E-LCA. The S-LCA was performed in two stages: a generic assessment (top-down approach) using the social hotspot database (SHDB 2013) to screen for potential social issues in the stakeholder group Worker in Norway and the USA and a specific assessment (bottom-up approach) for collecting data and confirming or refuting the SHDB results in the Norwegian case only.Results and discussion
Bioethanol produced in the Norwegian biorefinery would perform relatively well in relation to climate change targets, with emissions of approximately 11 g CO2-eq/MJ. The same production process located in the USA would produce emissions of approximately 29 g CO2-eq/MJ. Other biorefinery products are difficult to compare because of a lack of clear alternatives. Bioethanol and biochemicals produced in the hypothetical USA production process have higher burdens than those from the Norwegian production process in all environmental categories assessed. For both production processes, the main social risks were in the category Health and safety followed by Labor rights and decent work. More detailed investigations in an existing Norwegian biorefinery value chain confirmed some of the risk issues but discarded others, demonstrating the necessity of providing specific data and results for the social dimension.Conclusions
E-LCA and S-LCA make it possible to highlight the main environmental and social challenges when producing biochemicals. The SHDB has potential as a social screening tool although social indicators are not yet well established. Hence, specific assessment is necessary for validating the results in the social dimension. S-LCA is still in its infancy and needs to be applied in order to develop the best practice. The two methodologies addressed bioethanol and biochemical production performance in two different dimensions (environmental and social), and their combination makes it possible to achieve results that integrate the product-oriented approach with the more location-specific approach.9.
Nikolaos Thomakos Khandra Galaal Georgios Georgopoulos Lakshmi Nagaraju Dianne Hemming Raj Naik 《International Seminars in Surgical Oncology : ISSO》2009,6(1):3
Background
Choroidal metastases from gynaecological primary are extremely rare. There is no documented case in the literature of choroid metastasis in a patient with primary peritoneal carcinoma (PPC).Methods & Results
We describe the first case of a 54-year-old woman with a history of borderline mucinous tumour who presented 17 months later with PPC and 21 months after with recurrent disease metastatic to the eye, and review pertinent literature.Conclusion
High index of suspicion is warranted when patients with history of primary peritoneal carcinoma present with visual complaints in order to treat and/or relieve symptomatology from metastatic eye disease.10.
Background
This paper summarizes the contributions from the Genome-wide Association Study group (GWAS group) of the GAW20. The GWAS group contributions focused on topics such as association tests, phenotype imputation, and application of empirical kinships. The goals of the GWAS group contributions were varied. A real or a simulated data set based on the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study was employed by different methods. Different outcomes and covariates were considered, and quality control procedures varied throughout the contributions.Results
The consideration of heritability and family structure played a major role in some contributions. The inclusion of family information and adaptive weights based on data were found to improve power in genome-wide association studies. It was proven that gene-level approaches are more powerful than single-marker analysis. Other contributions focused on the comparison between pedigree-based kinship and empirical kinship matrices, and investigated similar results in heritability estimation, association mapping, and genomic prediction. A new approach for linkage mapping of triglyceride levels was able to identify a novel linkage signal.Conclusions
This summary paper reports on promising statistical approaches and findings of the members of the GWAS group applied on real and simulated data which encompass the current topics of epigenetic and pharmacogenomics.11.
Haresh Devalia Anushka Chaudhry Richard M Rainsbury Neda Minakaran Dibyesh Banerjee 《International Seminars in Surgical Oncology : ISSO》2007,4(1):29
Background
Lateral skin folds or 'dog-ears' are frequent following mastectomy, particularly in patients with large body habitus.Methods
We describe a method of modifying the mastectomy incision and suturing to eliminate these lateral 'dog-ears'.Conclusion
This surgical technique, as compared to others described in the literature, is simple, does not require additional incisions and is cosmetically acceptable to the patient.12.
Rachel A. Spicer Christoph Steinbeck 《Metabolomics : Official journal of the Metabolomic Society》2018,14(1):16
Introduction
Data sharing is being increasingly required by journals and has been heralded as a solution to the ‘replication crisis’.Objectives
(i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals’ policies to those that publish the most metabolomics papers.Methods
A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications.Results
Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data.Conclusion
Further efforts are required to improve data sharing in metabolomics.13.
Dimitrios J. Floros Paul R. Jensen Pieter C. Dorrestein Nobuhiro Koyama 《Metabolomics : Official journal of the Metabolomic Society》2016,12(9):145
Introduction
Natural products from culture collections have enormous impact in advancing discovery programs for metabolites of biotechnological importance. These discovery efforts rely on the metabolomic characterization of strain collections.Objective
Many emerging approaches compare metabolomic profiles of such collections, but few enable the analysis and prioritization of thousands of samples from diverse organisms while delivering chemistry specific read outs.Method
In this work we utilize untargeted LC–MS/MS based metabolomics together with molecular networking to inventory the chemistries associated with 1000 marine microorganisms.Result
This approach annotated 76 molecular families (a spectral match rate of 28 %), including clinically and biotechnologically important molecules such as valinomycin, actinomycin D, and desferrioxamine E. Targeting a molecular family produced primarily by one microorganism led to the isolation and structure elucidation of two new molecules designated maridric acids A and B.Conclusion
Molecular networking guided exploration of large culture collections allows for rapid dereplication of know molecules and can highlight producers of uniques metabolites. These methods, together with large culture collections and growing databases, allow for data driven strain prioritization with a focus on novel chemistries.14.
Background
Literature based discovery (LBD) automatically infers missed connections between concepts in literature. It is often assumed that LBD generates more information than can be reasonably examined.Methods
We present a detailed analysis of the quantity of hidden knowledge produced by an LBD system and the effect of various filtering approaches upon this. The investigation of filtering combined with single or multi-step linking term chains is carried out on all articles in PubMed.Results
The evaluation is carried out using both replication of existing discoveries, which provides justification for multi-step linking chain knowledge in specific cases, and using timeslicing, which gives a large scale measure of performance.Conclusions
While the quantity of hidden knowledge generated by LBD can be vast, we demonstrate that (a) intelligent filtering can greatly reduce the number of hidden knowledge pairs generated, (b) for a specific term, the number of single step connections can be manageable, and (c) in the absence of single step hidden links, considering multiple steps can provide valid links.15.
Nicholas J. Bond Albert Koulman Julian L. Griffin Zoe Hall 《Metabolomics : Official journal of the Metabolomic Society》2017,13(11):128
Introduction
Mass spectrometry imaging (MSI) experiments result in complex multi-dimensional datasets, which require specialist data analysis tools.Objectives
We have developed massPix—an R package for analysing and interpreting data from MSI of lipids in tissue.Methods
massPix produces single ion images, performs multivariate statistics and provides putative lipid annotations based on accurate mass matching against generated lipid libraries.Results
Classification of tissue regions with high spectral similarly can be carried out by principal components analysis (PCA) or k-means clustering.Conclusion
massPix is an open-source tool for the analysis and statistical interpretation of MSI data, and is particularly useful for lipidomics applications.16.
Clara Pérez-Rambla Leonor Puchades-Carrasco María García-Flores José Rubio-Briones José Antonio López-Guerrero Antonio Pineda-Lucena 《Metabolomics : Official journal of the Metabolomic Society》2017,13(5):52
Introduction
Prostate cancer (PCa) is one of the most common malignancies in men worldwide. Serum prostate specific antigen (PSA) level has been extensively used as a biomarker to detect PCa. However, PSA is not cancer-specific and various non-malignant conditions, including benign prostatic hyperplasia (BPH), can cause a rise in PSA blood levels, thus leading to many false positive results.Objectives
In this study, we evaluated the potential of urinary metabolomic profiling for discriminating PCa from BPH.Methods
Urine samples from 64 PCa patients and 51 individuals diagnosed with BPH were analysed using 1H nuclear magnetic resonance (1H-NMR). Comparative analysis of urinary metabolomic profiles was carried out using multivariate and univariate statistical approaches.Results
The urine metabolomic profile of PCa patients is characterised by increased concentrations of branched-chain amino acids (BCAA), glutamate and pseudouridine, and decreased concentrations of glycine, dimethylglycine, fumarate and 4-imidazole-acetate compared with individuals diagnosed with BPH.Conclusion
PCa patients have a specific urinary metabolomic profile. The results of our study underscore the clinical potential of metabolomic profiling to uncover metabolic changes that could be useful to discriminate PCa from BPH in a clinical context.17.
Zhongwei Xu Kaimin Xu Shijia Ding Jiao Luo Tingmei Chen Aiguo Zhou Zhenxing Wen Jian Zhang 《Metabolomics : Official journal of the Metabolomic Society》2017,13(6):73
Introduction
Non-traumatic osteonecrosis of the femoral head (NTONFH) is a progressive disease, always leading to hip dysfunction if no early intervention was applied. The difficulty for early diagnosis of NTONFH is due to the slight symptoms at early stages as well as the high cost for screening patients by using magnetic resonance imaging.Objective
The aim was to detect biomarkers of early-stage NTONFH, which was beneficial to the exploration of a cost-effective approach for the early diagnose of the disease.Methods
Metabolomic approaches were employed in this study to detect biomarkers of early-stage NTONFH (22 patients, 23 controls), based on the platform of ultra-performance liquid chromatography tandem quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) and the uses of multivariate statistic analysis, putative metabolite identification, metabolic pathway analysis and biomarker analysis.Results
In total, 33 serum metabolites were found altered between NTONFH group and control group. In addition, glycerophospholipid metabolism and pyruvate metabolism were highly associated with the disease.Conclusion
The combination of LysoPC (18:3), l-tyrosine and l-leucine proved to have a high diagnostic value for early-stage NTONFH. Our findings may contribute to the protocol for early diagnosis of NTONFH and further elucidate the underlying mechanisms of the disease.18.
Egidio Imbalzano Sebastiano Quartuccio Eleonora Di Salvo Teresa Crea Marco Casciaro Sebastiano Gangemi 《Clinical and molecular allergy : CMA》2017,15(1):12
Background
Recently, some studies demonstrated that HMGB1, as proinflammatory mediator belonging to the alarmin family, has a key role in different acute and chronic immune disorders. Asthma is a complex disease characterised by recurrent and reversible airflow obstruction associated to airway hyper-responsiveness and airway inflammation.Objective
This literature review aims to analyse advances on HMGB1 role, employment and potential diagnostic application in asthma.Methods
We reviewed experimental studies that investigated the pathogenetic role of HMGB in bronchial airway hyper-responsiveness, inflammation and the correlation between HMGB1 level and asthma.Results
A total of 19 studies assessing the association between HMGB1 and asthma were identified.Conclusions
What emerged from this literature review was the confirmation of HMGB-1 involvement in diseases characterised by chronic inflammation, especially in pulmonary pathologies. Findings reported suggest a potential role of the alarmin in being a stadiation method and a marker of therapeutic efficacy; finally, inhibiting HMGB1 in humans in order to contrast inflammation should be the aim for future further studies.19.
Background
Automatic recognition of relations between a specific disease term and its relevant genes or protein terms is an important practice of bioinformatics. Considering the utility of the results of this approach, we identified prostate cancer and gene terms with the ID tags of public biomedical databases. Moreover, considering that genetics experts will use our results, we classified them based on six topics that can be used to analyze the type of prostate cancers, genes, and their relations.Methods
We developed a maximum entropy-based named entity recognizer and a relation recognizer and applied them to a corpus-based approach. We collected prostate cancer-related abstracts from MEDLINE, and constructed an annotated corpus of gene and prostate cancer relations based on six topics by biologists. We used it to train the maximum entropy-based named entity recognizer and relation recognizer.Results
Topic-classified relation recognition achieved 92.1% precision for the relation (an increase of 11.0% from that obtained in a baseline experiment). For all topics, the precision was between 67.6 and 88.1%.Conclusion
A series of experimental results revealed two important findings: a carefully designed relation recognition system using named entity recognition can improve the performance of relation recognition, and topic-classified relation recognition can be effectively addressed through a corpus-based approach using manual annotation and machine learning techniques.20.
Korey J. Brownstein Mahmoud Gargouri William R. Folk David R. Gang 《Metabolomics : Official journal of the Metabolomic Society》2017,13(11):133