Are the variables used in building composite indicators of well-being relevant? Validating composite indexes of well-being

This paper explores the relevance of the variables that define well-being and human progress and makes a quantitative inquiry into the validity of three of the well-known and well-documented composite indicators of well-being: the Human Development Index (HDI), the Legatum Prosperity Index (LPI) and the Happy Planet Index (HPI). After choosing the key variables that describe most of the objective and subjective dimensions of well-being, we perform cluster analysis to come up with an optimal grouping of countries based on their multidimensional performance on well-being. A comparison of the classifications obtained with the three indexes invalidates the HPI, confirms results obtained for the HDI, and validates for the first time the LPI as a reliable measure of well-being. The optimal cluster structure yields robust results, which correct the rank discrepancies between the HDI and LPI for a large number of countries. It also proves that a robust ranking of countries based on multidimensional well-being can be achieved with a relatively small number of variables, which mitigates the risk of including variables that are not reliable and/or not available for a significant number of countries. The fact that cluster analysis generates results based on similarities between observations and not on computed values based on the aggregation of variables helps overcome problems that may occur due to the distribution of variables and increases its value as a validation method. Therefore, validation results achieved through cluster analysis are more robust and help to achieve a good check of the validity and relevance of the composite indexes, provide an objective perspective that can guide policy-makers and the public in making a fair assessment of actual levels of well-being, and avoid unfounded claims that may overstate it and delay or postpone measures to increase it.     

Impacts of human‐induced environmental change in wetlands on aquatic animals

Many wetlands harbour highly diverse biological communities and provide extensive ecosystem services; however, these important ecological features are being altered, degraded and destroyed around the world. Despite a wealth of research on how animals respond to anthropogenic changes to natural wetlands and how they use created wetlands, we lack a broad synthesis of these data. While some altered wetlands may provide vital habitat, others could pose a considerable risk to wildlife. This risk will be heightened if such wetlands are ecological traps – preferred habitats that confer lower fitness than another available habitat. Wetlands functioning as ecological traps could decrease both local and regional population persistence, and ultimately lead to extinctions. Most studies have examined how animals respond to changes in environmental conditions by measuring responses at the community and population levels, but studying ecological traps requires information on fitness and habitat preferences. Our current lack of knowledge of individual‐level responses may therefore limit our capacity to manage wetland ecosystems effectively since ecological traps require different management practices to mitigate potential consequences. We conducted a global meta‐analysis to characterise how animals respond to four key drivers of wetland alteration: agriculture, mining, restoration and urbanisation. Our overarching goal was to evaluate the ecological impacts of human alterations to wetland ecosystems, as well as identify current knowledge gaps that limit both the current understanding of these responses and effective wetland management. We extracted 1799 taxon‐specific response ratios from 271 studies across 29 countries. Community‐ (e.g. richness) and population‐level (e.g. density) measures within altered wetlands were largely comparable to those within reference wetlands. By contrast, individual fitness measures (e.g. survival) were often lower, highlighting the potential limitations of using only community‐ and population‐level measures to assess habitat quality. Only four studies provided habitat‐preference data, preventing investigation of the potential for altered wetlands to function as ecological traps. This is concerning because attempts to identify ecological traps may detect previously unidentified conservation risks. Although there was considerable variability amongst taxa, amphibians were typically the most sensitive taxon, and thus, may be a valuable bio‐indicator of wetland quality. Despite suffering reduced survival and reproduction, measures such as time to and mass at metamorphosis were similar between altered and reference wetlands, suggesting that quantifying metamorphosis‐related measures in isolation may not provide accurate information on habitat quality. Our review provides the most detailed evaluation to date of the ecological impacts of human alterations to wetland ecosystems. We emphasise that the role of wetlands in human‐altered ecosystems can be complex, as they may represent important habitat but also pose potential risks to animals. Reduced availability of natural wetlands is increasing the importance of altered wetlands for aquatic animals. Consequently, we need to define what represents habitat quality from the perspective of animals, and gain a greater understanding of the underlying mechanisms of habitat selection and how these factors could be manipulated. Furthermore, strategies to enhance the quality of these wetlands should be implemented to maximise their conservation potential.     

Integrative analysis of ocular complications in atherosclerosis unveils pathway convergence and crosstalk

Abstract

Atherosclerosis is a life-threatening disease and a major cause of mortalities worldwide. While many of the atherosclerotic sequelae are reflected as microvascular effects in the eye, the molecular mechanisms of their development is not yet known. In this study, we employed a systems biology approach to unveil the most significant events and key molecular mediators of ophthalmic sequelae caused by atherosclerosis. Literature mining was used to identify the proteins involved in both atherosclerosis and ophthalmic diseases. A protein–protein interaction (PPI) network was prepared using the literature-mined seed nodes. Network topological analysis was carried out using Cytoscape, while network nodes were annotated using database for annotation, visualization and integrated discovery in order to identify the most enriched pathways and processes. Network analysis revealed that mitogen-activated protein kinase 1 (MAPK1) and protein kinase C occur with highest betweenness centrality, degree and closeness centrality, thus reflecting their functional importance to the network. Our analysis shows that atherosclerosis-associated ophthalmic complications are caused by the convergence of neurotrophin signaling pathways, multiple immune response pathways and focal adhesion pathway on the MAPK signaling pathway. The PPI network shares features with vasoregression, a process underlying multiple vascular eye diseases. Our study presents a first clear and composite picture of the components and crosstalk of the main pathways of atherosclerosis-induced ocular diseases. The hub bottleneck nodes highlight the presence of molecules important for mediating the ophthalmic complications of atherosclerosis and contain five established drug targets for future therapeutic modulation efforts.     

Targeted biochemical profiling of brain from Huntington's disease patients reveals novel metabolic pathways of interest

Huntington's disease (HD) is a devastating, progressive neurodegenerative disease with a distinct phenotype characterized by chorea and dystonia, incoordination, cognitive decline and behavioral difficulties. The precise mechanisms of HD progression are poorly understood; however, it is known that there is an expansion of the trinucleotide cytosine-adenine-guanine (CAG) repeat in the Huntingtin gene. Herein DI/LC-MS/MS was used to accurately identify and quantify 185 metabolites in post mortem frontal lobe and striatum from HD patients and healthy control cases. The findings link changes in energy metabolism and phospholipid metabolism to HD pathology and also demonstrate significant reductions in neurotransmitters. Further investigation into the oxidation of fatty acids and phospholipid metabolism in pre-clinical models of HD are clearly warranted for the identification of potential therapies. Additionally, panels of 5 metabolite biomarkers were identified in both the frontal lobe (AUC?=?0.962 (95% CI: 0.85–1.00) and striatum (AUC?=?0.988 (95% CI: 0.899–1.00). This could have clinical utility in more accessible biomatrices such as blood serum for the early detection of those entering the prodromal phase of the disease, when treatment is believed to be most effective. Further evaluation of these biomarker panels in human cohorts is justified to determine their clinical efficacy.     

Data mining analysis of the PP2A cell cycle axis in mesothelioma patients

Mesothelioma is an aggressive tumor that affects thousands of people every year. The therapeutic options for patients are limited; hence, a better understanding of mesothelioma biology is crucial to improve patient survival. To find new molecular targets and therapeutic strategies related to the protein phosphatase 2A (PP2A) network, we analyzed the gene expression of known PP2A inhibitors in mesothelioma patient samples. Our analysis disclosed a general overexpression of all PP2A-negative regulators in mesothelioma patients. Moreover, the expression of ANP32E and CIP2A genes, increased in 16% and 11% of cases, positively correlates with the ones of all the other PP2A regulators and the ones of the main cyclins and CDKs, suggesting the existence of a feed-forward loop that might contribute to the mesothelioma progression via PP2A inactivation. Overall, our study indicates the existence of a strategic and targetable axis between PP2A inhibitors (ANP32E and CIP2A) and cell cycle regulators (cyclin B2/CDK1) and provides a valuable rationale for using a personalized combinational therapy approach to improve mesothelioma patient survival.     

A computational framework for integration of lipidomics data into metabolic pathways

Lipids are important compounds for human physiology and as renewable resources for fuels and chemicals. In lipid research, there is a big gap between the currently available pathway-level representations of lipids and lipid structure databases in which the number of compounds is expanding rapidly with high-throughput mass spectrometry methods.In this work, we introduce a computational approach to bridge this gap by making associations between metabolic pathways and the lipid structures discovered increasingly thorough lipidomics studies. Our approach, called NICELips (Network Integrated Computational Explorer for Lipidomics), is based on the formulation of generalized enzymatic reaction rules for lipid metabolism, and it employs the generalized rules to postulate novel pathways of lipid metabolism. It further integrates all discovered lipids in biological networks of enzymatic reactions that consist their biosynthesis and biodegradation pathways.We illustrate the utility of our approach through a case study of bis(monoacylglycero)phosphate (BMP), a biologically important glycerophospholipid with immature synthesis and catabolic route(s). Using NICELips, we were able to propose various synthesis and degradation pathways for this compound and several other lipids with unknown metabolism like BMP, and in addition several alternative novel biosynthesis and biodegradation pathways for lipids with known metabolism. NICELips has potential applications in designing therapeutic interventions for lipid-associated disorders and in the metabolic engineering of model organisms for improving the biobased production of lipid-derived fuels and chemicals.     

Sediment Contamination along Desert Wash Systems from Historic Mining Sites in a Hyperarid Region of Southern Nevada,USA

Abandoned mining sites in hyperarid environments are generally assumed to present an insignificant risk to water availability. This study investigated the impact abandoned mine sites in Southern Nevada can have on the wider environment. Southern Nevada is characterized with little precipitation and prolonged droughts. Precipitation in Southern Nevada is often in the form of short and intense events with the potential to mobilize and transport contaminated sediments down gradient. This work evaluated the movement of trace elements (Ag, As, Ba, Cd, Cr, Hg, Pb, and Se) and cyanide in surface sediments of three desert washes near the historic mining town of Nelson, a hyperarid region of Southern Nevada. Results indicate trace elements have been mobilized and transported down gradient from sources to areas not directly impacted by mining. Contaminants used in mining operations (Hg and CN^?) as well as those of geogenic nature migrated as far as 6000 m, providing evidence of their transport in hyperarid environments, contrary to the generally held belief. Although contaminants in this study are below levels that are environmentally significant, the findings show that transport is possible. This study demonstrates that large amounts of contaminant-laden sediments might be a significant threat in hyperarid environment and to areas down gradient from source materials.     

Chinese Glioma Genome Atlas(CGGA):A Comprehensive Resource with Functional Genomic Data from Chinese Glioma Patients

Gliomas are the most common and malignant intracranial tumors in adults. Recent studies have revealed the significance of functional genomics for glioma pathophysiological studies and treatments. However, access to comprehensive genomic data and analytical platforms is often limited. Here, we developed the Chinese Glioma Genome Atlas(CGGA), a user-friendly data portal for the storage and interactive exploration of cross-omics data, including nearly 2000 primary and recurrent glioma samples from Chinese cohort. Currently, open access is provided to whole-exome sequencing data(286 samples), mRNA sequencing(1018 samples) and microarray data(301 samples), DNA methylation microarray data(159 samples), and microRNA microarray data(198 samples), and to detailed clinical information(age, gender, chemoradiotherapy status,WHO grade, histological type, critical molecular pathological information, and survival data). In addition, we have developed several tools for users to analyze the mutation profiles,mRNA/microRNA expression, and DNA methylation profiles, and to perform survival and gene correlation analyses of specific glioma subtypes. This database removes the barriers for researchers,providing rapid and convenient access to high-quality functional genomic data resources for biological studies and clinical applications. CGGA is available at http://www.cgga.org.cn.