Methotrexate and vasculoprotection: Mechanistic insights and potential therapeutic applications in old age

Increasing age is a strong, independent risk factor for atherosclerosis and cardiovascular disease. Key abnormalities driving cardiovascular risk in old age include endothelial dysfunction, increased arterial stiffness, blood pressure, and the pro-atherosclerotic effects of chronic, low-grade, inflammation. The identification of novel therapies that comprehensively target these alterations might lead to a major breakthrough in cardiovascular risk management in the older population. Systematic reviews and meta-analyses of observational studies have shown that methotrexate, a first-line synthetic disease-modifying anti-rheumatic drug, significantly reduces cardiovascular morbidity and mortality in patients with rheumatoid arthritis, a human model of systemic inflammation, premature atherosclerosis, and vascular aging. We reviewed in vitro and in vivo studies investigating the effects of methotrexate on endothelial function, arterial stiffness, and blood pressure, and the potential mechanisms of action involved. The available evidence suggests that methotrexate might have beneficial effects on vascular homeostasis and blood pressure control by targeting specific inflammatory pathways, adenosine metabolism, and 5' adenosine monophosphate-activated protein kinase. Such effects might be biologically and clinically relevant not only in patients with rheumatoid arthritis but also in older adults with high cardiovascular risk. Therefore, methotrexate has the potential to be repurposed for cardiovascular risk management in old age because of its putative pharmacological effects on inflammation, vascular homeostasis, and blood pressure. However, further study and confirmation of these effects are essential in order to adequately design intervention studies of methotrexate in the older population

Oxidative Stress Biomarkers and Peripheral Endothelial Dysfunction in Rheumatoid Arthritis: A Monocentric Cross-Sectional Case-Control Study

Previous studies have suggested that oxidative stress may heighten atherosclerotic burden in rheumatoid arthritis (RA), but direct evidence is lacking. Objective: To evaluate the relationship between established plasma oxidative stress biomarkers and peripheral endothelial dysfunction (ED), a marker of early atherosclerosis, in RA. Methods: Paroxonase-1 (PON-1), protein-SH (PSH), and malondialdehyde (MDA) were measured in 164 RA patient s and 100 age- and sex-matched healthy controls without previous cardiovascular events. Peripheral ED, evaluated by flow-mediated pulse amplitude tonometry, was defined by log-transformed reactive hyperemia index (Ln-RHI) values < 0.51. Results: PON-1 activity and PSH concentrations were significantly reduced in RA patients compared to controls. In regression analysis, increased plasma MDA levels were significantly associated with reduced Ln-RHI [B coefficient (95% CI) = −0.003 (−0.005 to −0.0008), p = 0.008] and the presence of peripheral ED (OR (95% CI) = 1.75 (1.06–2.88), p = 0.028). Contrary to our expectations, increased PON-1 activity was significantly associated, albeit weakly, with the presence of ED (OR (95% CI) = 1.00 (1.00–1.01), p = 0.017). Conclusions: In this first evidence of a link between oxidative stress and markers of atherosclerosis, MDA and PON-1 showed opposite associations with peripheral vasodilatory capacity and the presence of ED in RA. Further studies are needed to determine whether this association predicts atherosclerotic events in the RA population

Comprehensive arginine metabolomics and peripheral vasodilatory capacity in rheumatoid arthritis: A monocentric cross-sectional study

Background: The relationship between plasma arginine metabolites influencing vascular homeostasis and peripheral vasodilatory capacity in rheumatoid arthritis (RA) patients is not known. Methods: L-arginine (Arg), monomethyl-L-arginine (MMA), L-homoarginine (hArg), asymmetric dimethyl-L-arginine (ADMA), symmetric dimethyl-L-arginine, and L-citrulline (Cit) were measured by liquid chromatography tandem mass spectrometry (LC-MS/MS) in 164 RA patients and 100 age- and sex-matched healthy controls without previous cardiovascular events. Log-transformed reactive hyperemia index (Ln-RHI) evaluated by flow-mediated pulse amplitude tonometry (PAT, EndoPAT2000 device) was assessed as surrogate measure of peripheral vasodilatory capacity in RA patients. Ln-RHI values <0.51 indicated peripheral endothelial dysfunction (ED). The relationship between plasma arginine metabolite concentrations, RA descriptors and peripheral vasodilatory capacity was evaluated by bivariate correlation and regression analyses. Results: Plasma ADMA concentrations were significantly higher, and plasma hArg concentrations significantly lower, in RA patients than in controls (0.53 ± 0.09 vs 0.465 ± 0.07 μmol/L and 1.50 ± 0.60 vs 1.924 ± 0.78 μmol/L, respectively; p < 0.001 for both comparisons). Bivariate correlation analysis demonstrated no significant correlation between arginine metabolites and disease descriptors. In regression analysis in RA patients, higher plasma ADMA concentrations were independently associated with presence of ED [OR(95% CI) = 77.3(1.478–4050.005), p = 0.031] and lower Ln-RHI [B coefficient(95% CI) = −0.57(−1.09 to −0.05), p = 0.032]. Conclusions: ADMA was significantly, albeit weakly, associated with impaired microcirculatory vasodilatory capacity and peripheral endothelial dysfunction in RA. This suggests an important pathophysiological role of this metabolite in the vascular alterations observed in this patient group

Genetic characterization and implications for conservation of the last autochthonous Mouflon population in Europe

Population genetic studies provide accurate information on population structure, connectivity, and hybridization. These are key elements to identify units for conservation and define wildlife management strategies aimed to maintain and restore biodiversity. The Mediterranean island of Sardinia hosts one of the last autochthonous mouflon populations, descending from the wild Neolithic ancestor. The first mouflon arrived in Sardinia ~ 7000 years ago and thrived across the island until the twentieth century, when anthropogenic factors led to population fragmentation. We analysed the three main allopatric Sardinian mouflon sub-populations, namely: the native sub-populations of Montes Forest and Mount Tonneri, and the reintroduced sub-population of Mount Lerno. We investigated the spatial genetic structure of the Sardinian mouflon based on the parallel analysis of 14 highly polymorphic microsatellite loci and mitochondrial D-loop sequences. The Montes Forest sub-population was found to harbour the ancestral haplotype in the phylogeny of European mouflon. We detected high levels of relatedness in all the sub-populations and a mitochondrial signature of hybridization between the Mount Lerno sub-population and domestic sheep. Our findings provide useful insights to protect such an invaluable genetic heritage from the risk of genetic depletion by promoting controlled inter-population exchange and drawing informed repopulation plans sourcing from genetically pure mouflon stocks

Soil Organic Carbon and Nitrogen Feedbacks on Crop Yields under Climate Change

Articles in A&EL are published under the CC-BY NC ND (non-commercial; no derivatives) license (https://creativecommons.org/licenses/by-nc-nd/2.0/). Users are free to copy and redistribute the material in any medium or format. Any further publication of the article will require proper attribution; no derivative works may be made from this article; and the article may not be used for any commercial gain (https://creativecommons.org/licenses/by-nc-nd/2.0/). The author is given explicit permission to publish the final article in her/his institutional repository. There is an option for the CC-BY license if required by an author's institution.Peer reviewedPublisher PD

Current warming will reduce yields unless maize breeding and seed systems adapt immediately

The development of crop varieties that are better suited to new climatic conditions is vital for future food production1, 2. Increases in mean temperature accelerate crop development, resulting in shorter crop durations and reduced time to accumulate biomass and yield3, 4. The process of breeding, delivery and adoption (BDA) of new maize varieties can take up to 30 years. Here, we assess for the first time the implications of warming during the BDA process by using five bias-corrected global climate models and four representative concentration pathways with realistic scenarios of maize BDA times in Africa. The results show that the projected difference in temperature between the start and end of the maize BDA cycle results in shorter crop durations that are outside current variability. Both adaptation and mitigation can reduce duration loss. In particular, climate projections have the potential to provide target elevated temperatures for breeding. Whilst options for reducing BDA time are highly context dependent, common threads include improved recording and sharing of data across regions for the whole BDA cycle, streamlining of regulation, and capacity building. Finally, we show that the results have implications for maize across the tropics, where similar shortening of duration is projected

Comparing correction methods of RCM outputs for improving crop impact projections in the Iberian Peninsula for 21st century

Assessment of climate change impacts on crops in regions of complex orography such as the Iberian Peninsula (IP) requires climate model output which is able to describe accurately the observed climate. The high resolution of output provided by Regional Climate Models (RCMs) is expected to be a suitable tool to describe regional and local climatic features, although their simulation results may still present biases. For these reasons, we compared several post-processing methods to correct or reduce the biases of RCM simulations from the ENSEMBLES project for the IP. The bias-corrected datasets were also evaluated in terms of their applicability and consequences in improving the results of a crop model to simulate maize growth and development at two IP locations, using this crop as a reference for summer cropping systems in the region. The use of bias-corrected climate runs improved crop phenology and yield simulation overall and reduced the inter-model variability and thus the uncertainty. The number of observational stations underlying each reference observational dataset used to correct the bias affected the correction performance. Although no single technique showed to be the best one, some methods proved to be more adequate for small initial biases, while others were useful when initial biases were so large as to prevent data application for impact studies. An initial evaluation of the climate data, the bias correction/reduction method and the consequences for impact assessment would be needed to design the most robust, reduced uncertainty ensemble for a specific combination of location, crop, and crop management

Impact of progressive global warming on the global-scale yield of maize and soybean

Global surface temperature is projected to warm over the coming decades, with regional differences expected in temperature change, rainfall and the frequency of extreme events. Temperature is a major determinant of crop growth and development, affecting planting date, growing season length and yield. We investigated the effects of increments of mean global temperature warming from 0.5 °C to 4 °C on soybean and maize development and yield, both globally and for the main producing countries, and simulated adaptation through changing planting date and variety. Increasing temperature resulted in reduced growing season lengths and ultimately reduced yields for both crops. The global yield for maize decreased as temperature increased, although the severity of the decrease was dependent on geographic region. Small temperature increases of 0.5 °C had no effect on soybean yield, although yield decreased as temperature increased. These negative effects, however, were partly compensated for by the implementation of adaptation strategies including planting earlier in the season and changing variety. The degree of compensation was dependent on geographical area and crop, with maize adaptation delaying the negative effects of temperature on yield, compared to soybean adaptation which increased yield in China, India and Korea DPR as well as delaying the effects in the remaining countries. The results of this paper indicate the degree to which farmer-controlled adaptation strategies can alleviate the negative impacts of increasing temperature on two major crop species

Intensifying Maize Production Under Climate Change Scenarios in Central West Burkina Faso

Combination of poor soil fertility and climate change and variability is the biggest obstacle to agricultural productivity in Sub-Saharan Africa. While each of these factors requires different promising adaptive and climate-resilient options, it is important to be able to disaggregate their effects. This can be accomplished with ordinary agronomic trials for soil fertility and climate year-to-year variability, but not for long-term climate change effects. In turn, by using climate historical records and scenario outputs from climate models to run dynamic models for crop growth and yield, it is possible to test the performance of crop management options in the past but also anticipate their performance under future climate change or variability. Nowadays, the overwhelming importance given to the use of crop models is motivated by the need of predicting crop production under future climate change, and outputs from running crop models may serve for devising climate risk adaptation strategies. In this study we predicted yield of one maize variety named Massongo for the time periods 1980–2010 (historical) and 2021–2050 (2030s, near future) across agronomic practices including the fertilizer input rates recommended by the national extension services (28 kg N, 20 kg P, and 13 kg K ha−1). The performance of the crop model DSSAT 4.6 for maize was first evaluated using on-farm experimental data that encompassed two seasons in the Sudano-Sahelian zone in six contrasting sites of Central West Burkina Faso. The efficiency of the crop model was evidenced by reliable simulations of total aboveground biomass and yields after calibration and validation. The root-mean-square error (RMSE) of the entire dataset for grain yield was 643 kg ha−1 and 2010 kg ha−1 for total aboveground biomass. Three regional climate change projections for Central West Burkina Faso indicate a decrease in rainfall during the growing period of maize. All the three scenarios project that the decrease in rainfall is to the tune of 3–9% in the 2030s under RCP4.5 in contrast to climate scenarios produced by the regional climate model GCM ICHEC-EC-Earth which predicted an increase of rainfall of 25% under RCP8.5. Simulations using the CERES-DSSAT model reveal that maize yields without fertilizer show the same trend as with fertilizer in response to climate change projections across RCPs. Under RCP4.5 with output from the climate model ICHEC-EC-Earth, yield can slightly increase compared to the historical baseline on average by less than 5%. In contrast, under RCP8.5, yield is increased by 13–22% with the two other climate models in fertilized and non-fertilized plots, respectively. Nevertheless, the average maize yield will stay below 2000 kg ha−1 under non-fertilized plots in RCP4.5 and with recommended mineral fertilizer rates regardless of the RCP scenarios produced by ICHEC-EC-Earth. Giving the fact that soil fertility improvement alone cannot compensate for the adverse impact of future climate on agricultural production particularly in case of high rainfall predicted by ICHEC-EC-Earth, it is recommended to combine various agricultural techniques and practices to improve uptake of nitrogen and to reduce nitrogen leaching such as the splitting of fertilizer applications, low-release nitrogen fertilizers, agroforestry, and any other soil and water conservation practices

How do various maize crop models vary in their responses to climate change factors?

Comments This article is a U.S. government work, and is not subject to copyright in the United States. Abstract Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly 0.5 Mg ha 1 per °C. Doubling [CO2] from 360 to 720 lmol mol 1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information