Ependymoma (EPN) posterior fossa group A (PFA) has the highest rate of recurrence and the worst prognosis of all EPN types. At relapse, it is typically incurable even with re-resection and re-irradiation. The biology of recurrent PFA EPN remains largely unknown, which hinders clinical advances. In this longitudinal large multicenter study, we examined matched samples of primary and recurrent disease from PFA EPN patients (n=95) to investigate the biology of recurrence. DNA methylomic data was used to measure copy number variants (CNVs), revealing progressive large scale chromosome gains and losses in successive recurrences. These CNV changes were dominated by chromosome 1q gain and/or 6q loss (1q+/6q-), both previously identified as high-risk factors in PFA EPN, which were present in ~20% at presentation but increased to ~60% at 1st recurrence. Because 6q testing is not routinely performed, this very high incidence at recurrence has not been previously reported. Evolution of chromosomal aberrations was further explored using CNV analysis of single-nuclei RNAseq on approximately 46,000 PFA EPN cells from 6 matched pairs of primary and 1st relapse tumors that harbored CNV changes at recurrence. No evidence of rare subclones in primary tumors was observed, suggesting that chromosomal rearrangement events occur after initial presentation. Cellular and molecular characteristics associated with CNVs were examined by single-nuclei RNAseq, bulk transcriptomic analysis and immunohistochemistry, revealing that 1q+/6q- PFA have a significantly higher mitotic index, increased proportions of proliferative epithelial progenitors and decreased differentiated neoplastic subpopulations. Multivariate survival analyses showed that cases with 1q gain or 6q loss at 1st recurrence were significantly more likely to recur than cases with no 1q or 6q change. The high prevalence of 1q+/6q- at recurrence and the associated shortened survival, suggest that both these abnormalities should be routinely tested for, and used for trial stratification.

Exploring how businesses can adopt eco-innovations, which may involve their market expansion, and meet their climate change targets, was the objective of this research. We investigated to what extent an organization with a milk packaging eco-innovation could create a positive impact on climate and calculated their potential carbon handprint using the Sustainability and Health Initiative for NetPositive Enterprise (SHINE) Handprint assessment method. Changes and potential handprint pathways were defined from the perspective of two actors who can bring about the change: organization and consumers. The potential carbon handprints were calculated for changes resulting from switching from current milk packaging to eco-innovation at the global milk market. The assessment explored options for organization to realize handprints within their own markets and via market expansion in their competitors' markets. Results showed that SHINE Handprint assessment provides a systemic approach for organizations to adopt eco-innovations, pursue market expansion, and reduce overall sector's climate change impacts.

The Sustainability and Health Initiative for NetPositive Enterprise (SHINE) project is dedicated to improving the scientific basis for transformative environmental, social, and economic positive changes called handprints. Organizations and individuals can create handprints relative to their business-as-usual (BAU) through voluntary reductions in their own footprint as well as in the footprints of others. The novel SHINE handprint framework expands thus the scope, retains accountability for the outcomes, and increases widespread pursuit of net-positive goals. Handprints are quantified using the dynamic life cycle assessment (LCA)-based modeling and measured in footprint-related impact units. Like LCA, the SHINE handprint framework includes the goal and scope definition, inventory analysis, impact assessment, and interpretation. Existing life cycle inventory databases are adopted to promote widespread use of the method. However, in the SHINE handprint framework, the BAU footprint and the actor’s actions and positive changes (handprints) are defined. The scope of the handprint assessment includes changes caused by the action within the system boundary. The BAU footprint is then compared with actual footprint calculated with changes to assess the handprint. An additional element for making comparative claims about net positivity that are meant to be disclosed to the public is an attestation. The SHINE handprint framework is demonstrated through a case study collaboration with Interface, a global carpet tiles and flooring manufacturer. Historic handprints are estimated from Interface’s initiative to capture and flare nearby landfill gas and utilize a portion of the captured gas to produce heat in their facility and in a third actor’s facility. The handprints are calculated by dynamic LCA which included Interface’s BAU footprint during the years of landfill gas capture and the amount of natural gas displaced from landfill gas use in both facilities, and the amount flared at the landfill. Results are presented for the years of landfill gas capture and flaring (2003–2016). The results showed Interface could achieve net positive outcomes when all actions leading to positive changes are activated. While actors’ efforts to reduce their own footprints are essential, this perspective alone may not be enough to encourage the scale of action necessary to face global challenges. The SHINE handprint framework quantifies positive actions and changes caused by an actor, both within and outside the scope of the actor’s footprint. This shift in accounting for change can promote innovation and collaboration by multiple actors, which ultimately creates widespread ripple effects of positive impacts.

Net Positive may well be the buzzword of this decade. Beyond the noise, it has the potential to be a transformational movement, helping businesses to redefine their role in society, their social purpose. As an idea, it simplicity and candor make it both extremely attractive and powerful. It poses a great question and sets a challenge: Can we give more to the environment and society than we take? To be Net Positive a company (and its supply chain) handprint needs to be greater than its footprint. The Net Positive Project and Harvard SHINE have worked to clarify the Principles and methodology that can make the Net Positive concept both actionable and valid. This include defining handprints in a measurable way. In this paper, we are developing on the methods that can be used to assess the social Net Positive impacts. Reviewing and building on social life cycle assessment, we introduce a structure for Net Positive analysis of social impacts. This framework is meant to be practical, actionable and inclusive.

This article introduces a process that can be used by companies to obtain an increasingly precise picture of their supply chain social footprint (negative impacts) and identify potential social handprints (i.e., changes to business as usual that create positive impacts) using social organizational life cycle assessment (SO-LCA). The process was developed to apply to the electronics sector but can be used by companies in any industry. Our case study presents the social footprint of a typical US computer manufacturing company and identifies potential salient social risks and hotspots using generic information about the inputs that are related to a global trade model. The global trade model enables us to map the likely supply chain based on where inputs are usually sourced from by the US electronic computer manufacturing sector. In order to identify material impacts, normalization factors were created and used. Once the material impacts and salient risks are known, it becomes necessary to identify root causes in order to plan actions that will truly make a meaningful change, addressing the issues at stake. The article concludes by establishing a methodology that enables the use of the industry-level impacts and assessment in combination with the organization's own data to calculate company-specific results.

Our study illustrates how consumer social risk footprints can assist in achieving the Sustainable Development Goals (SDGs). Combining the Social Hotspots Database (SHDB) and the Eora global multi-regional input-output table, we use input-output analysis to calculate a consumer social risk footprint (SF) of nations' imports. For our SFs, we select four indicators related to five of the UN's SDGs: gender equality (SDG 5 also 8.5 & 8.8); mother and child health (SDG 3, especially 3.1 & 3.2); governance (SDG 16, especially 16.5 & 16.6); and access to clean water (SDG 6, especially 6.1 & 62). After examining results for all four indicators we focus on gender equality to fully convey the value and limitations of using this method of analysis. Our study compares producer (domestic) social risk and consumer social risk footprints resulting from international trade patterns. Generally, developed countries show higher social risk footprints while developing countries show higher domestic social risks with the exceptions of UK and Ireland in the developed-world, and China and India in the developing-world. Details of the SFs associated with exported products worldwide reveal that Pakistan, Yemen and Iran have some of the highest SF risk, while Australia, Canada and Denmark are among the lowest. These results are important for the UN in developing partnerships to address the Sustainable Development Goals and for organisations such as the World Bank, Trade Unions and NGOs' work towards a fairer world. (C) 2017 Elsevier B.V. All rights reserved.

In this study, we innovatively apply multiregional input-output analysis to calculate corruption footprints of nations and show the details of commodities that use the most employment affected by corruption (EAC), as they flow between countries. Every country's corruption footprint includes its domestic corruption and the corruption imported by global supply chains to meet final demand. Our results show that, generally, the net corruption exporters are developing countries, with the exception of Italy where corruption is likely to be more affected by political and cultural factors than economic factors. China is the largest gross corruption exporter, and India follows close behind, with clothing as one of the industries in which the most people are affected by corruption. This is because: (1) China and India are major clothing exporters, thus many workers are employed in the clothing industry within the country as well as in countries providing intermediate commodities by supply chains, and (2) corruption is high in China and India. Our results can be useful to identify where regulations to combat corruption can have the greatest impact. More important, the method we use can be applied to link corruption to other economic and social aspects of trade, such as working conditions, thus making it possible to find avenues for tackling the problem that are not usually considered in anticorruption strategies.

Innovative strategies are needed to improve the sustainability of beef production and consumption systems. Increasing reliance on regional or local food systems may improve resilience, and consumer demand for such foods is high. In the Northeastern U.S., the dairy sector may provide beef at a low environmental cost relative to other systems due to multi-functionality (i.e., milk and meat outputs). Additionally, landscape and market factors indicate suitability and demand for regional grass-fed beef. We used ISO-compliant life cycle assessment (LCA) to quantify the environmental burdens of grass-fed beef with management-intensive grazing (GF) and confinement dairy beef (DB) production systems in the Northeastern U.S. The impact scope included global warming potential, eutrophication and acidification potential, fossil fuel and water depletion, and agricultural land use. The foundation of the production system models was a herd-level, life cycle livestock feed requirements model, which we adapted and applied for the first time within LCA. Per kg carcass weight beef produced, DB had lower global warming potential, eutrophication potential, acidification potential, and agricultural land use than GF with higher fossil fuel depletion and water depletion. Calculating eutrophication and acidification per hectare agricultural land resulted in lower impacts for GF compared to DB. Maintaining the breeding herd accounted for over half of GF (60%) and DB (52%) impacts on average across categories. Sensitivity analyses indicated potential pasture carbon sequestration and lower enteric methane emissions under management-intensive grazing may substantially reduce the carbon footprint of GF (though not lower than DB), which should be explored with further research. Future research should also examine holistic strategies to reduce regional GF and DB system footprints, such as substituting food waste for traditional feeds and accounting for ecosystem services provided by pasture-based farming systems within LCA.

Social sustainability may be assessed using a variety of methods and indicators, such as the social footprint, social impact assessment, or wellbeing indices. The UNEP guidelines on social life cycle assessment (sLCA) present key elements to consider for product-level, life cycle-based social sustainability assessment. This includes guidance for the goal and scope definition, inventory, impact assessment, and interpretation phases of S-LCA. Methods for and studies of the broader scale, life cycle social dimensions of production and consumption are largely unavailable to date. The current study assesses social risks associated with trade-based consumption in EU Member States using a life cycle-based compared to a non-life cycle-based approach in order to assess the value-added of life cycle thinking and assessment in this context. Social risk refers to the potential for one or more parties to be exposed to negative social conditions that, in turn, undermine social sustainability. In order to shed light on these risks, a macro-scale analysis of the social risk profile of trade-based consumption in the EU Member States has been conducted by combining intra- and extra-territorial import statistics with country- and sector-specific social risk indicator data derived from the Social Hotspots Database. These data cover 17 social risk indicators in five thematic areas, many of which are linked with the sustainable development goals set by the recent United Nations Agenda 2030. The apparent social risk profiles of EU imports have then been assessed based on consideration of country-of-origin social risk data (non-life cycle-based approach) as compared to a life cycle-based social risk assessment which also took into account the distribution of social risk along product supply chains. The intention was to better understand how and to what extent current trade-based consumption within the EU-27 may be associated with socially unsustainable conditions domestically and abroad, and the extent to which life cycle-based consideration of social risk is necessary. The analysis confirms the importance of a life cycle-based assessment of social risks in support of policies for socially sustainable production and consumption. Moreover, the methods presented herein offer a potentially powerful decision-support methodology for policy makers wishing to better understand the magnitude and distribution of social risks associated with EU production and consumption patterns, the mitigation of which will contribute to socially sustainable development.

Life cycle assessment (LCA) has a technical architecture that limits data interoperability, transparency, and automated integration of external data. More advanced information technologies offer promise for increasing the ease with which information can be synthesized within an LCA framework.

Data collection, or the inventory step, is often the most labor-intensive phase of any Life Cycle Assessment (LCA) study. The S-LCA Guidelines and numerous authors have recommended generic assessment in this first phase of an S-LCA. In an effort to identify the social hotspots in the supply chains of 100 product categories during just a few months' time, adopting a streamlined approach was essential. The Social Hotspots Database system was developed by New Earth over 5 years. It includes a Global Input Output (IO) model derived from the Global Trade Analysis Project, a Worker Hours Model constructed using annual wage payments and wage rates by country and sector, and Social Theme Tables covering 22 themes within five Social Impact CategoriesLabor Rights and Decent Work, Health and Safety, Human Rights, Governance and Community Impacts. The data tables identify social risks for over 100 indicators. Both the ranking of worker hour intensity and the risk levels across multiple social themes for the Country Specific Sectors (CSS) within a product category supply chain are used to calculate Social Hotspots Indexes (SHI) using an additive weighting method. The CSS with the highest SHI are highlighted as social hotspots within the supply chain of the product in question. This system was tested in seven case studies in 2011. In order to further limit the number of hotspots, a set of prioritization rules was applied. This paper will review the method implemented to study the social hotspots of the 100 product categories and provide one detailed example. Limitations of the approach and recommended research avenues will be outlined.

Christoph Koffler & Jon Dettling & Cashion East & Matthias Finkbeiner & Sergio F. Galeano & Roland Geyer & Mark J. Goedkoop & Troy R. Hawkins & Connie D. Hensler & Arpad Horvath & Sebastien Humbert & Scott M. Kaufman & Amy E. Landis & Lise Laurin & Pascal Lesage & Manuele Margni & Ken Martchek & H. Scott Matthews & Jamie K. Meil & Gregory Norris & Rita C. Schenk & Thomas P. Seager & Maureen Sertich & Greg Thoma & Casey Wagner

The analysis of social impacts of product supply chains is receiving substantial interest from corporations and their stakeholders. Social LCA is a technique that allows for the generation, organization, assessment and communication of product life cycles’ social impacts. The Social Hotspots Database provides a three layered system to assess the potential social risks and opportunities associated with product life cycles. The system was used to carry out social scoping assessments on seven product categories for The Sustainability Consortium. This article summarizes the methodology and discusses the main findings generated by the application of the system and database.

Companies benefit greatly from streamlined models and tools that can be used to mine for data and prioritize issues regarding the potential impacts of their operations and products. Guided by the well-established fields of Environmental Life Cycle Assessment (LCA) and Corporate Social Responsibility, Social LCA is a developing technique that allows for the generation, organization, assessment and communication of product life cycles’ social impacts. As a precursor to a full Social LCA study, Social Hotspots can be identified through the use of a generic (ie., top-down) database of country and sector-level social issues relative to the share of worker hours in the supply chain. Over the last three years, researchers at New Earth constructed such a prioritization tool, called The Social Hotspot Database (SHDB, www.socialhotspot.org) . The SHDB system includes a Global IO model derived from GTAP that allows to model product category supply chains by Country Specific Sector. The system also offer a Worker Hours Model which integrates GTAP data on payment of wages to workers and that was supplemented with wage rate data (obtained primarily from the International Labor Organization and the United Nations Industrial Development Organization), to calculate worker hour estimates by Country-specific Sector (CSS). This Worker Hours Model is then used to rank CSS within the supply chain of a product category by labor intensity. Those with the highest share of worker hours are considered as potential Social Hotspots. The last component is comprised of 22 Social Theme Tables that are populated with global statistical data. They include quantitative and qualitative indicators by country, and sector when relevant, that are characterized for their level of risk that the specific social issue is present. Some examples of Tables include Excessive Working Time, Corruption, or Gender Inequality. By testing the CSS with the greatest share of worker hours and other r...

The United Nations Environmental Programme published the Guidelines for Social Life Cycle Assessment (S-LCA) of products in 2009. Social Life Cycle Assessment is a technique to analyze systematically the social impacts of products, from extraction of raw materials to final disposal. Social LCA plays a specific role, generating information to effectively improve the social conditions of production and alleviate inequalities and poverty. The S-LCA guidelines recommend that a social hotspots assessment be carried in order to prioritize production activities for which further data collection activities should be organized (UNEP, 2009). The Sustainability Consortium, a global membership organization, is developing a standardized framework for the communication of sustainability-related information throughout the product value chain (www.sustainabilityconsortium.org). The framework, called the Sustainability Measurement & Reporting System (SMRS) serves as a common, global platform for companies to measure and report on product sustainability. In the context of SMRS development, The Sustainability Consortium mandated New Earth to conduct seven social scoping assessments on products of the home and personal care, food beverages and agriculture and electronic sector demonstrating its Social Hotspots Database. An international Input Output model derived from The Global Trade Analysis Project (GTAP) by New Earth supports the Social Hotspot Database system. It enables to model supply chains by country specific sector and provides estimate of worker hours. Associated to the model, a set of 22 social risk and opportunity tables including 138 indicators are mobilized to inform about the potential social impacts by country and sector. The data was collected from best publicly available data and the references are fully transparent. An overview of the methodology utilized in the seven studies will be presented along with the example of a social scoping assessment report.

One emerging tool to measure the social-related impacts in supply chains is Social Life Cycle Assessment (S-LCA), a derivative of the well-established environmental LCA technique. LCA has recently started to gain popularity among large corporations and initiatives, such as The Sustainability Consortium or the Sustainable Apparel Coalition. Both have made the technique a cornerstone of their applied-research program. The Social Hotspots Database (SHDB) is an overarching, global database that eases the data collection burden in S-LCA studies. Proposed “hotspots” are production activities or unit processes (also defined as country-specific sectors) in the supply chain that may be at risk for social issues to be present. The SHDB enables efficient application of S-LCA by allowing users to prioritize production activities for which site-specific data collection is most desirable. Data for three criteria are used to inform prioritization: (1) labor intensity in worker hours per unit process and (2) risk for, or opportunity to affect, relevant social themes or sub-categories related to Human Rights, Labor Rights and Decent Work, Governance and Access to Community Services (3) gravity of a social issue. The Worker Hours Model was developed using a global input/output economic model and wage rate data. Nearly 200 reputable sources of statistical data have been used to develop 20 Social Theme Tables by country and sector. This paper presents an overview of the SHDB development and features, as well as results from a pilot study conducted on strawberry yogurt. This study, one of seven Social Scoping Assessments mandated by The Sustainability Consortium, identifies the potential social hotspots existing in the supply chain of strawberry yogurt. With this knowledge, companies that manufacture or sell yogurt can refine their data collection efforts in order to put their social responsibility performance in perspective and effectively set up programs and initiatives to improve the social conditions of production along their product supply chain.

The analysis of social impacts of product supply chains is receiving substantial interest from corporations and their stakeholders. Social LCA is a technique that allows for the generation, organization, assessment and communication of product life cycles’ social impacts. The Social Hotspots Database provides a three layered system to assess the potential social risks and opportunities associated with product life cycles. The system was used to carry out social scoping assessments on seven product categories for The Sustainability Consortium. This article summarizes the methodology and discusses the main findings generated by the application of the system and database.