Search

Manuela De Gregori,1–3 Inna Belfer,2,4 Roberto De Giorgio,5 Maurizio Marchesini,2,3,6 Carolina Muscoli,7 Mariangela Rondanelli,2,8 Daniela Martini,9 Pedro Mena,9 Laura Isabel Arranz,2,10 Silvia Lorente-Cebrián,2,11 Simone Perna,8 Anna Villarini,12 Maurizio Salamone,2,13,14 Massimo Allegri,2,15 Michael E Schatman2,16,17 1 Pain Therapy Service, Fondazione IRCCS Polclinico San Matteo, Pavia, Italy; 2Study in Multidisciplinary Pain Research Group, Parma, Italy; 3Young Against Pain Group, Parma, Italy; 4Faculty of Dentistry, McGill University, Montreal, QC, Canada; 5Department of Clinical Sciences, Nuovo Arcispedale S. Anna, University of Ferrara, Ferrara, Italy; 6Anesthesia, Intensive Care and Pain Therapy Service, Azienda Ospedaliero, Universitaria of Parma, Parma, Italy; 7Department of Health Sciences, Institute of Research for Food Safety and Health, University “Magna Graecia” of Catanzaro, Parma, Italy; 8Department of Public Health, Section of Human Nutrition and Dietetics, Azienda di Servizi alla Persona di Pavia, University of Pavia, Pavia, Italy; 9Human Nutrition Unit, Department of Food & Drugs, University of Parma, Parma, Italy; 10Department of Nutrition, Food Sciences and Gastronomy, University of Barcelona, Barcelona, Spain; 11Department of Nutrition, Food Science and Physiology, Faculty of Pharmacy, Center for Nutrition Research, University of Navarra, Pamplona, Spain; 12Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy; 13Science department, Metagenics Italia srl, Milano, Italy; 14Società internazionale di Neuropsicocardiologia, Trapani, Italy; 15Anesthesia and Intensive Care Service – IRCCS MultiMedica Hospital, Sesto San Giovanni, Milano, Italy; 16Research and Network Development, Boston Pain Care, Waltham, MA, USA; 17Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, USA Abstract: This review is aimed to summarize the latest data regarding pain and nutrition, which have emerged during the second edition of Feed Your Destiny (FYD). Theme presentations and interactive discussions were held at a workshop on March 30, 2017, in Florence, Italy, during the 9th Annual Meeting of Study in Multidisciplinary Pain Research, where an international faculty, including recognized experts in nutrition and pain, reported the scientific evidence on this topic from various perspectives. Presentations were divided into two sections. In the initial sessions, we analyzed the outcome variables and methods of measurement for health claims pertaining to pain proposed under Regulation EC No 1924/2006 of the European Parliament and of the Council of 20 December 2006 on nutrition and health claims made on foods. Moreover, we evaluated how the Mediterranean diet can have a potential impact on pain, gastrointestinal disorders, obesity, cancer, and aging. Second, we discussed the evidence regarding vitamin D as a nutraceutical that may contribute to pain control, evaluating the interindividual variability of pain nature and nurture, and the role of micro-RNAs (miRNAs), polyunsaturated omega 3 fatty acids, and phenolic compounds, with a final revision of the clinical role of nutrition in tailoring pain therapy. The key take-home message provided by the FYD workshop was that a balanced, personalized nutritional regimen might play a role as a synergic strategy that can improve management of chronic pain through a precision medicine approach. Keywords: chronic pain, multidisciplinary pain management, personalized nutrition, nutritional supplements

Abstract While there is growing attention toward the changes in flood magnitude and frequency, little is known about the way climate change could impact flood duration. Here we focus on 378 streamgages across the eastern United States to develop statistical models that allow the description of the year-to-year changes in flood duration above two National Weather Service (NWS) flood severity levels (i.e., minor and moderate). We use climate-related variables (i.e., basin- and season-averaged precipitation and temperature) as predictors, and show that they can be used to describe the inter-annual variability in seasonal flood durations for both NWS flood severity levels. We then use the insights from the understanding of the historical changes to provide an assessment of the projected changes in flood durations using global climate models from the Coupled Model Intercomparison Project Phase 6 and multiple shared socio-economic pathways. Our results show that the eastern United States is projected to experience longer flood durations, especially in winter (i.e., the main flood season) and under higher emission scenarios.

Acting as ‘antioxidants’, phenolic compounds have been shown to have a potential protective effect against a wide range of noncommunicable diseases. However, their content in plant-based products – and, in turn, their potential benefits – might be affected by the thermal procedures used in food cooking. In light of this, the aim of this work was a characterization of Patata Rossa di Colfiorito (PRC, an Italian PGI red-skinned potato) and an investigation of the impact of cooking and storage on its bioactive compounds, phenolic content, and antioxidant activity. After the harvesting (T0), samples were analyzed using instrumental analysis (e.g., HPLC-ESI-MS/MS) and a set of chemical assays (total phenolic content, 2,2-Diphenyl-1-picrylhydrazyl – DPPH, 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) – ABTS, and oxygen radical absorbance capacity – ORAC assays). Analyses were also performed on boiled, pressure-cooked and one-month-stored (T1) products. A commercial red-skinned potato (RSP) was also analyzed.Overall, compared with the raw product, both boiling and pressure-cooking led to a significant increase in bioactive compounds (raw: 168.15 mg kg−1 of fresh matter, FM; boiled: 398.92 mg kg−1 FM; pressure-cooked: 309.24 mg kg−1 FM), total phenolic content and antioxidant activity measured by DPPH and ABTS assays.PRC samples showed higher content in bioactive compounds, TPC values and antioxidant activity compared with commercial RSP (with some sporadic exceptions in ORAC values). Interestingly, one month of domestic storage did not affect the freshly harvested product’s features.In conclusion, these results highlighted the quality of this local product and its property to withstand thermal processing and storage. We believe that the results we have obtained should be taken into consideration by health professionals, at both local and national levels, and that PRC deserves to be further studied to investigate its potential human health benefits, as well.

Abstract Urban areas have been shown to impact rainfall by altering both its intensity and spatial structure at sub‐hourly and sub‐kilometer scales. However, there is currently no clear understanding of the precise pattern of change and the mechanisms that drive these changes. Since the hydrological response in urban areas is highly sensitive to such rainfall properties, understanding these changes is critical to improving our ability to assess urban flood risk. We use 7 years of high‐resolution weather radar data (4‐ or 5‐min and 1 km) to analyze changes in patterns of rainfall intensity, spatial structure, and storm evolution across eight urban areas within Europe and the United States. The use of the same methodology across the different cities enables a consistent comparison among them. We track convective rainfall events using a storm tracking algorithm and assess changes in rainfall properties in the upwind, center, and downwind regions of each city. We also investigate changes in the frequency of storm initiations, terminations, splitting, and merging. Our results show that urban areas act to intensify rainfall—mostly over them, but sometimes on their peripheries. Overall, larger cities tend to show the largest rainfall enhancements. Our findings highlight that rainfall spatial structure is altered over the urban core; usually resulting in more spatially concentrated rainfall. We also observe increased storm initiations over most cities and increased storm splitting over one. Given that demographic projections show that future urban population will increase, our results point toward an increased future flood risk in growing cities.

In response to flood risk, design flood estimation is a cornerstone of planning, infrastructure design, setting of insurance premiums, and emergency response planning. Under stationary assumptions, flood guidance and the methods used in design flood estimation are firmly established in practice and mature in their theoretical foundations, but under climate change, guidance is still in its infancy. Human-caused climate change is influencing factors that contribute to flood risk such as rainfall extremes and soil moisture, and there is a need for updated flood guidance. However, a barrier to updating flood guidance is the translation of the science into practical application. For example, most science pertaining to historical changes to flood risk focuses on examining trends in annual maximum flood events or the application of non-stationary flood frequency analysis. Although this science is valuable, in practice, design flood estimation focuses on exceedance probabilities much rarer than annual maximum events, such as the 1 % annual exceedance probability event or even rarer, using rainfall-based procedures, at locations where there are few to no observations of streamflow. Here, we perform a systematic review to summarize the state-of-the-art understanding of the impact of climate change on design flood estimation in the Australian context, while also drawing on international literature. In addition, a meta-analysis, whereby results from multiple studies are combined, is conducted for extreme rainfall to provide quantitative estimates of possible future changes. This information is described in the context of contemporary design flood estimation practice to facilitate the inclusion of climate science into design flood estimation practice.

Abstract Understanding changes in the hazard component of climate risk is important to inform societal resilience planning in a changing climate. Here, we examine local changes in wind speed, rainfall, and flooding related to tropical cyclones (TCs) and compare them across statistical and dynamical modeling approaches. Our focus region is the Delaware River Basin, located in the northeastern United States. We pair event‐based downscaling with large ensemble climate model information to capture the details of extreme TC wind, rain, and flooding, and their likelihood, in a changing climate. We identify local TCs in the Community Earth System Model 2 Large Ensemble (CESM2‐LENS). We find fewer TCs in the future, but these future storms have higher wind speeds and are wetter. We also find that TCs produce heavier 3‐day precipitation distributions than all other summertime weather events, with TCs constituting a larger percentage of the upper tail of the full precipitation distribution. With this information, we identify a small collection of 200‐year return events and compare the resulting TC rain and wind across dynamical and statistical downscaling methods. We find that dynamical downscaling produces peak rain rates far higher than CESM or the statistical downscaling method. It can also produce quite different future changes in precipitation totals for the small set of events considered here. This leads to vastly different flood responses. Overall, our results highlight the need to interpret future changes of event‐based simulations in the context of downscaling method limitations.

Abstract Understanding projected changes in flooding across the contiguous United States (CONUS) helps increase our capability to adapt to and mitigate against this hazard. Here, we assess future changes in flooding across CONUS using outputs from 28 global climate models and four scenarios of the Coupled Model Intercomparison Project Phase 6. We find that CONUS is projected to experience an overall increase in flooding, especially under higher emission scenarios; there are subregional differences, with the Northeast and Southeast (Great Plains of the North and Southwest) showing higher tendency towards increasing (decreasing) flooding due to changes in flood processes at the seasonal scale. Moreover, even though trends may not be detected in the historical period, these projected future trends highlight the current needs for incorporating climate change in the future infrastructure designs and management of the water resources.

Abstract Extreme flood events have regional differences in their generating mechanisms due to the complex interaction of different climate and catchment processes. This study aims to examine the capability of climate drivers to capture year‐to‐year variability in global flood extremes. Here, we use a statistical attribution approach to model seasonal and annual maximum daily discharge for 7,886 stations worldwide, using season‐ and basin‐averaged precipitation and temperature as predictors. The results show robust performance of our seasonal climate‐informed models in describing the inter‐annual variability in seasonal and annual maximum discharges regardless of the geographical region, climate type, basin size, degree of regulation, and impervious area. The developed models enable the assessment of the sensitivity of flood discharge to precipitation and temperature changes, indicating their potential to reliably project changes in the magnitude of flood extremes.

Abstract This study evaluates five bias correction and statistical downscaling (BCSD) techniques for daily precipitation and examines their impacts on the projected changes in flood extremes (i.e., 1%, 0.5%, and 0.2% floods). We use climate model outputs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to conduct hydrologic simulations across watersheds in Iowa and determine historical and future flood extreme estimates based on generalized extreme value distribution fitting. Projected changes in these extremes are examined with respect to four Shared Socioeconomic Pathways (SSPs) alongside five BCSD techniques. We find the magnitude of the estimates of future annual exceedance probabilities (AEPs) are expected to increase under all SSPs, especially for the emission scenarios with higher greenhouse gases concentrations (i.e., SSP370 and SSP585). Our results also suggest the choice of BCSD impacts the magnitude of the projected changes, with the SSPs that play a more limited role compared to the choice of downscaling method. The variability in projected flood changes across Iowa is similar across the downscaling technique but increases as the AEP increases. Our findings provide insights into the impact of downscaling techniques on flood extremes' projections and useful information for climate planning across the state.

Abstract The detection of nonstationarities in partial duration time series (PDS) depends on several factors, including the length of the time series, the selected statistical test, and the heaviness of the tail of the distribution. Because of the more limited attention received in the literature when compared to the trend detection on block maxima variables, we perform a Monte Carlo simulation study to evaluate the performance of different approaches: Spearman's rho, Mann–Kendall, ordinary least squares (OLS), Sen's slope estimator (SEN), and the nonstationary generalized Pareto distribution fit to identify the presence of trends in PDS records characterized by different sample sizes (n), shape parameter (ξ) and degrees of nonstationarity. The results point to a power gain for all tests by increasing n and the degree of nonstationarity and by reducing ξ. The use of a nonparametric test is recommended in samples with a high positive skew. Furthermore, the use of sampling rates greater than one to increase the PDS sample size is encouraged, especially when dealing with small records. The use of SEN to estimate the magnitude of a trend is preferable over OLS due to its slightly smaller probability of occurrence of type S error when ξ is positive.

Abstract Structural connectivity describes how landscapes facilitate the transfer of matter and plays a critical role in the flux of water, solutes, and sediment across the Earth’s surface. The strength of a landscape’s connectivity is a function of climatic and tectonic processes, but the importance of these drivers is poorly understood, particularly in the context of climate change. Here, we provide global estimates of structural connectivity at the hillslope level and develop a model to describe connectivity accounting for tectonic and climate processes. We find that connectivity is primarily controlled by tectonics, with climate as a second order control. However, we show climate change is projected to alter global-scale connectivity at the end of the century (2070 to 2100) by up to 4% for increasing greenhouse gas emission scenarios. Notably, the Ganges River, the world’s most populated basin, is projected to experience a large increase in connectivity. Conversely, the Amazon River and the Pacific coast of Patagonia are projected to experience the largest decreases in connectivity. Modeling suggests that, as the climate warms, it could lead to increased erosion in source areas, while decreased rainfall may hinder sediment flow downstream, affecting landscape connectivity with implications for human and environmental health.