Sustainability experiments in the agri-food system : uncovering the factors of new governance and collaboration success

In recent years, research, society and industry recognize the need to transform the agri-food system towards sustainability. Within this process, sustainability experiments play a crucial role in transforming the structure, culture and practices. In literature, much attention is given to new business models, even if the transformation of conventional firms toward sustainability may offer opportunities to accelerate the transformation. Further acceleration could be achieved through collaboration of multiple actors across the agri-food system, but this calls for a systems approach. Therefore, we developed and applied a new sustainability experiment systems approach (SESA) consisting of an analytical framework that allows a reflective evaluation and cross-case analysis of multi-actor governance networks based on business and learning evaluation criteria. We performed a cross-case analysis of four agri-food sustainability experiments in Flanders to test and validate SESA. Hereby, the key factors of the success of collaboration and its performance were identified at the beginning of a sustainability experiment. Some of the key factors identified were risk sharing and the drivers to participate. We are convinced that these results may be used as an analytical tool for researchers, a tool to support and design new initiatives for policymakers, and a reflective tool for participating actors

The Consequences of Overlapping Tax Bases for Redistribution and Public Spending in a Federation

Tax and expenditure policies are studied in a federation with imperfectly mobile households. States implement a linear progressive tax and supply a public good. A vertical fiscal externality, reflecting the effect of state policies on federal revenues, provides an incentive for state taxes to be too progressive. A horizontal fiscal externality causes non-optimal states taxes and expenditures because of the migration effect. The federal government implements its own linear progressive tax and makes transfers to the states. The federal government can nullify both externalities by appropriate fiscal policies, and redistributive taxation can be decentralized to the states.TAXES ; FISCAL POLICY

Chain Governance Systems and Sustainable Capital Use – A Conceptual Approach

Due to pressures such as climate change, globalization, price volatility and scarcity of natural resources, our agri-food chain is urged to make a transition towards more sustainable production. How to organize such a transition, given the various stakeholders involved, and how to monitor progress still remain important challenges. This paper presents a new conceptual framework that follows an integrated chain approach to help address these challenges. First, it tackles the complex ecological and socio-economic challenges along the chain and its members (agriculture and food industries), and second, allows for decision support to chain members and policy.This framework combines two existing theoretical frameworks. The first framework is global chain value analysis (GCVA) of Gereffi (2005) which has its roots in institutional economics. GCVA categorizes five governance types of value chains (markets – modular – relational – captive – hierarchy) based on three variables: (i) the complexity of information and knowledge transfer required to sustain a particular transaction, (ii) the ability to regulate transactions, and (iii) the capabilities of actual and potential suppliers. The second framework, which was first formulated in ecological economics, extends the set of traditional economic resources to various forms of capital in the production system. These are natural (land, water, …), manufactured (buildings, machinery, ...), human (labour, skills,…), and social capital (networks,…). The economic system is fully embedded in the social system which in turn is embedded within the finite ecological system. Throughput of natural, social, human, and manufactured capital allows for the description of agri-food systems in terms of the maximal sustainable use of their stocks and flows.These two frameworks can be combined to perform an integrated system analysis of the agri-food chain, including the governance structures and the boundary conditions for the various types of capital. This paper describes this new conceptual framework illustrated by means of a case study of the agri-food chain in Flanders, Belgium

A reflexive assessment of a regional initiative in the agri-food system to test whether and how it meets the premises of transdisciplinary research

In recent sustainability assessments, transdisciplinary approaches have been used to bridge contested normative views among many societal actors, policymakers and researchers. Transdisciplinary research is mainly based on three premises: (1) various perspectives need to be incorporated and discussed to empower actors, (2) the collaboration and co-creation of knowledge between academic and societal actors allows to better grasp the complexity of a real-world problem, and (3) a mutual learning process arises which could increase the legitimacy of decisions and their implementation in practice. Despite many examples of transdisciplinary projects, few assessments have been done that question whether such a project fulfils the premises of transdisciplinary research. Therefore, we report on a reflexive assessment of an initiative set up to foster the transformation of the Flemish agri-food system towards sustainability. The case study involved both scientific and societal actors with different views, making it possible to implement a transdisciplinary process, evaluate the expectations and give suggestions for future processes. Evaluation criteria are linked to context, process and outcomes. Analysis of the qualitative and quantitative data indicates that the initiative did empower the transformation towards sustainability. Furthermore, results show that, in this case, a transdisciplinary approach can fulfil its premises. However, some critical factors are identified, such as the importance of the context specificity and a flexible, adaptive and iterative process

Tumor collagenase stimulatory factor (TCSF) expression and localization in human lung and breast cancers.

Tumor cell-derived collagenase stimulatory factor (TCSF) stimulates in vitro the biosynthesis of various matrix metalloproteinases involved in tumor invasion, such as interstitial collagenase, gelatinase A, and stromelysin 1. The expression of TCSF mRNAs was studied in vivo, using in situ hybridization and Northern blotting analysis, in seven normal tissues and in 22 squamous cell carcinomas of the lung, and in seven benign proliferations and in 22 ductal carcinomas of the mammary gland. By in situ hybridization, TCSF mRNAs were detected in 40 of 44 carcinomas, in pre-invasive and invasive cancer cells of both lung and breast cancers. TCSF mRNAs and gelatinase A mRNAs were both visualized in the same areas in serial sections in breast cancers, and were expressed by different cells, tumor cells, and fibroblasts. The histological results were confirmed by Northern blot analysis, which showed a higher expression of TCSF mRNAs in cancers than in benign and normal tissues. These observations support the hypothesis that TCSF is an important factor in lung and breast tumor progression

Identification and Analysis of the Active Phytochemicals from the Anti-Cancer Botanical Extract Bezielle

Bezielle is a botanical extract that has selective anti-tumor activity, and has shown a promising efficacy in the early phases of clinical testing. Bezielle inhibits mitochondrial respiration and induces reactive oxygen species (ROS) in mitochondria of tumor cells but not in non-transformed cells. The generation of high ROS in tumor cells leads to heavy DNA damage and hyper-activation of PARP, followed by the inhibition of glycolysis. Bezielle therefore belongs to a group of drugs that target tumor cell mitochondria, but its cytotoxicity involves inhibition of both cellular energy producing pathways. We found that the cytotoxic activity of the Bezielle extract in vitro co-purified with a defined fraction containing multiple flavonoids. We have isolated several of these Bezielle flavonoids, and examined their possible roles in the selective anti-tumor cytotoxicity of Bezielle. Our results support the hypothesis that a major Scutellaria flavonoid, scutellarein, possesses many if not all of the biologically relevant properties of the total extract. Like Bezielle, scutellarein induced increasing levels of ROS of mitochondrial origin, progressive DNA damage, protein oxidation, depletion of reduced glutathione and ATP, and suppression of both OXPHOS and glycolysis. Like Bezielle, scutellarein was selectively cytotoxic towards cancer cells. Carthamidin, a flavonone found in Bezielle, also induced DNA damage and oxidative cell death. Two well known plant flavonoids, apigenin and luteolin, had limited and not selective cytotoxicity that did not depend on their pro-oxidant activities. We also provide evidence that the cytotoxicity of scutellarein was increased when other Bezielle flavonoids, not necessarily highly cytotoxic or selective on their own, were present. This indicates that the activity of total Bezielle extract might depend on a combination of several different compounds present within it

Association of the CHRNA5-A3-B4 Gene Cluster With Heaviness of Smoking: A Meta-Analysis

Introduction: Variation in the CHRNA5-A3-B4 gene cluster is a promising candidate region for smoking behavior and has been linked to multiple smoking-related phenotypes (e.g., nicotine dependence) and diseases (e.g., lung cancer). Two single nucleotide polymorphisms (SNPs), rs16969968 in CHRNA5 and rs1051730 in CHRNA3, have generated particular interest. Methods: We evaluated the published evidence for association between rs16969968 (k = 27 samples) and rs1051730 (k = 44 samples) SNPs with heaviness of smoking using meta-analytic techniques. We explored which SNP provided a stronger genetic signal and investigated study-level characteristics (i.e., ancestry, disease state) to establish whether the strength of association differed across populations. We additionally tested for small study bias and explored the impact of year of publication. Results and Conclusions: Meta-analysis indicated compelling evidence of an association between the rs1051730/rs16966968 variants and daily cigarette consumption (fixed effects: B = 0.91, 95% CI = 0.77, 1.06, p < .001; random effects: B = 1.01, 95% CI = 0.81, 1.22, p < .001), equivalent to a per-allele effect of approximately 1 cigarette/day. SNP rs1051730 was found to provide a stronger signal than rs16966968 in stratified analyses (pdiff = .028), although this difference was only qualitatively observed in the subset of samples that provided data on both SNPs. While the functional relevance of rs1051730 is unknown, it may be a strong tagging SNP for functional haplotypes in this region

Prediction of Opioid-Induced Respiratory Depression on Inpatient Wards Using Continuous Capnography and Oximetry: An International Prospective, Observational Trial.

BACKGROUND: Opioid-related adverse events are a serious problem in hospitalized patients. Little is known about patients who are likely to experience opioid-induced respiratory depression events on the general care floor and may benefit from improved monitoring and early intervention. The trial objective was to derive and validate a risk prediction tool for respiratory depression in patients receiving opioids, as detected by continuous pulse oximetry and capnography monitoring. METHODS: PRediction of Opioid-induced respiratory Depression In patients monitored by capnoGraphY (PRODIGY) was a prospective, observational trial of blinded continuous capnography and oximetry conducted at 16 sites in the United States, Europe, and Asia. Vital signs were intermittently monitored per standard of care. A total of 1335 patients receiving parenteral opioids and continuously monitored on the general care floor were included in the analysis. A respiratory depression episode was defined as respiratory rate ≤5 breaths/min (bpm), oxygen saturation ≤85%, or end-tidal carbon dioxide ≤15 or ≥60 mm Hg for ≥3 minutes; apnea episode lasting \u3e30 seconds; or any respiratory opioid-related adverse event. A risk prediction tool was derived using a multivariable logistic regression model of 46 a priori defined risk factors with stepwise selection and was internally validated by bootstrapping. RESULTS: One or more respiratory depression episodes were detected in 614 (46%) of 1335 general care floor patients (43% male; mean age, 58 ± 14 years) continuously monitored for a median of 24 hours (interquartile range [IQR], 17-26). A multivariable respiratory depression prediction model with area under the curve of 0.740 was developed using 5 independent variables: age ≥60 (in decades), sex, opioid naivety, sleep disorders, and chronic heart failure. The PRODIGY risk prediction tool showed significant separation between patients with and without respiratory depression (P \u3c .001) and an odds ratio of 6.07 (95% confidence interval [CI], 4.44-8.30; P \u3c .001) between the high- and low-risk groups. Compared to patients without respiratory depression episodes, mean hospital length of stay was 3 days longer in patients with ≥1 respiratory depression episode (10.5 ± 10.8 vs 7.7 ± 7.8 days; P \u3c .0001) identified using continuous oximetry and capnography monitoring. CONCLUSIONS: A PRODIGY risk prediction model, derived from continuous oximetry and capnography, accurately predicts respiratory depression episodes in patients receiving opioids on the general care floor. Implementation of the PRODIGY score to determine the need for continuous monitoring may be a first step to reduce the incidence and consequences of respiratory compromise in patients receiving opioids on the general care floor