Enhancing nature-based solutions acceptance through stakeholders' engagement in co-benefits identification and trade-offs analysis

Nature-based solutions (NBS) are increasingly recognized as a valid alternative to grey infrastructures - i.e. hard, human-engineered structures – as measures for reducing climate-related risks. Increasing evidences demonstrated that NBS can reduce risks to people and property as effectively as traditional grey infrastructures, but potentially offering many additional benefits, e.g. improving the natural habitat for wildlife, enhancing water and air quality, improving socio-cultural conditions of communities. The growing attention on the NBS, triggered an increasing interest in developing integrated and multi-disciplinary frameworks for assessing NBS effectiveness accounting for the co-benefits production. Starting from the analysis of the existing frameworks, this work claims for a more direct engagement of stakeholders – i.e. co-benefits beneficiaries – in developing NBS assessment framework. This work aims at demonstrating that differences in co-benefits perception and valuation might lead to trade-offs and, thus, to potential conflicts. An innovative methodology using a quasi-dynamic Fuzzy Cognitive Map approach based on multiple-time-steps was developed in order to assess NBS effectiveness, and to detect and analyze trade-offs among stakeholders due to differences in co-benefits perception. The developed methodology was implemented in the Lower Danube case study. The trade-off analysis among stakeholders shows that they are quite low in the short term. Most of the potential conflicts can be detected in the long term, involving mainly the stakeholders that assigned a high value to the agricultural productivity variable. The results demonstrated that accounting for the different stakeholders' perception of the co-benefits is key for reducing trade-offs and enhance NBS acceptability

The violent youth of bright and massive cluster galaxies and their maturation over 7 billion years

In this study, we investigate the formation and evolution mechanisms of the brightest cluster galaxies (BCGs) over cosmic time. At high redshift (z ∼ 0.9), we selected BCGs and most massive cluster galaxies (MMCGs) from the Cl1604 supercluster and compared them to low-redshift (z ∼ 0.1) counterparts drawn from the MCXC meta-catalogue, supplemented by Sloan Digital Sky Survey imaging and spectroscopy. We observed striking differences in the morphological, colour, spectral, and stellar mass properties of the BCGs/MMCGs in the two samples. High-redshift BCGs/MMCGs were, in many cases, star-forming, late-type galaxies, with blue broad-band colours, properties largely absent amongst the low-redshift BCGs/MMCGs. The stellar mass of BCGs was found to increase by an average factor of 2.51 ± 0.71 from z ∼ 0.9 to z ∼ 0.1. Through this and other comparisons, we conclude that a combination of major merging (mainly wet or mixed) and in situ star formation are the main mechanisms which build stellar mass in BCGs/MMCGs. The stellar mass growth of the BCGs/MMCGs also appears to grow in lockstep with both the stellar baryonic and total mass of the cluster. Additionally, BCGs/MMCGs were found to grow in size, on average, a factor of ∼3, while their average Sérsic index increased by ∼0.45 from z ∼ 0.9 to z ∼ 0.1, also supporting a scenario involving major merging, though some adiabatic expansion is required. These observational results are compared to both models and simulations to further explore the implications on processes which shape and evolve BCGs/MMCGs over the past ∼7 Gyr

Postdiagnosis dietary factors, supplement use and breast cancer prognosis: Global Cancer Update Programme (CUP Global) systematic literature review and meta-analysis

Little is known about how diet might influence breast cancer prognosis. The current systematic reviews and meta-analyses summarise the evidence on postdiagnosis dietary factors and breast cancer outcomes from randomised controlled trials and longitudinal observational studies. PubMed and Embase were searched through 31st October 2021. Random-effects linear dose-response meta-analysis was conducted when at least three studies with sufficient information were available. The quality of the evidence was evaluated by an independent Expert Panel. We identified 108 publications. No meta-analysis was conducted for dietary patterns, vegetables, wholegrains, fish, meat, and supplements due to few studies, often with insufficient data. Meta-analysis was only possible for all-cause mortality with dairy, isoflavone, carbohydrate, dietary fibre, alcohol intake and serum 25-hydroxyvitamin D (25(OH)D), and for breast cancer-specific mortality with fruit, dairy, carbohydrate, protein, dietary fat, fibre, alcohol intake and serum 25(OH)D. The results, with few exceptions, were generally null. There was limited-suggestive evidence that predefined dietary patterns may reduce the risk of all-cause and other causes of death; that isoflavone intake reduces the risk of all-cause mortality (relative risk (RR) per 2 mg/day: 0.96, 95% confidence interval (CI): 0.92-1.02), breast cancer-specific mortality (RR for high vs low: 0.83, 95% CI: 0.64-1.07), and recurrence (RR for high vs low: 0.75, 95% CI: 0.61-0.92); that dietary fibre intake decreases all-cause mortality (RR per 10 g/day: 0.87, 95% CI: 0.80-0.94); and that serum 25(OH)D is inversely associated with all-cause and breast cancer-specific mortality (RR per 10 nmol/L: 0.93, 95% CI: 0.89-0.97 and 0.94, 95% CI: 0.90-0.99, respectively). The remaining associations were graded as limited-no conclusion

Postdiagnosis body fatness, weight change and breast cancer prognosis: Global Cancer Update Program (CUP global) systematic literature review and meta-analysis

Previous evidence on postdiagnosis body fatness and mortality after breast cancer was graded as limited-suggestive. To evaluate the evidence on body mass index (BMI), waist circumference, waist-hip-ratio and weight change in relation to breast cancer prognosis, an updated systematic review was conducted. PubMed and Embase were searched for relevant studies published up to 31 October, 2021. Random-effects meta-analyses were conducted to estimate summary relative risks (RRs). The evidence was judged by an independent Expert Panel using pre-defined grading criteria. One randomized controlled trial and 225 observational studies were reviewed (220 publications). There was strong evidence (likelihood of causality: probable) that higher postdiagnosis BMI was associated with increased all-cause mortality (64 studies, 32 507 deaths), breast cancer-specific mortality (39 studies, 14 106 deaths) and second primary breast cancer (11 studies, 5248 events). The respective summary RRs and 95% confidence intervals per 5 kg/m2 BMI were 1.07 (1.05-1.10), 1.10 (1.06-1.14) and 1.14 (1.04-1.26), with high between-study heterogeneity (I2 = 56%, 60%, 66%), but generally consistent positive associations. Positive associations were also observed for waist circumference, waist-hip-ratio and all-cause and breast cancer-specific mortality. There was limited-suggestive evidence that postdiagnosis BMI was associated with higher risk of recurrence, nonbreast cancer deaths and cardiovascular deaths. The evidence for postdiagnosis (unexplained) weight or BMI change and all outcomes was graded as limited-no conclusion. The RCT showed potential beneficial effect of intentional weight loss on disease-free-survival, but more intervention trials and well-designed observational studies in diverse populations are needed to elucidate the impact of body composition and their changes on breast cancer outcomes