Farm diversification strategies, dietary diversity and farm size: results from a cross-country sample in South and Southeast Asia

South and Southeast Asia host almost half of the world's undernourished people. Food and agricultural systems in these regions are highly dependent on the production and consumption of staple cereals such as rice, maize and wheat. More diverse farming systems can potentially improve rural people's nutrition, while reducing the environmental impact of agriculture. Yet, it remains uncertain whether farm diversification is always the most suitable and viable strategy for all types of smallholder farms. We use generalised linear regression models to analyse the farm diversification strategies of 4772 rural households in Cambodia, India, Lao PDR and Vietnam. Our analysis is twofold and focuses first on drivers of farm diversification, and second, on the impacts of farm diversification and other livelihood strategies on dietary diversity. We find that (1) farm diversification is significantly influenced by environmental and climate variables, including rainfall patterns, as well as household and farm characteristics such as farm size and education level; and (2) farm diversification, market orientation and off-farm income generation are all strategies that can improve household and individual dietary diversity. However, their relative effects resulted influenced by farm size. Specifically, the positive effect of farm diversification on dietary diversity was larger for smaller farms, while it decreased for farms of larger size that may improve their diet more by increasing their engagement in off-farm activities and markets. These findings highlight that characteristics such as farm size can represent substantial determinants in production and consumption decisions, suggesting the importance of understanding and considering the type of farm and the situational context of analysis when targeting interventions for improving smallholder farm livelihoods

Making the most of imperfect data: A critical evaluation of standard information collected in farm household surveys

Household surveys are one of the most commonly used tools for generating insight into rural communities. Despite their prevalence, few studies comprehensively evaluate the quality of data derived from farm household surveys. We critically evaluated a series of standard reported values and indicators that are captured in multiple farm household surveys, and then quantified their credibility, consistency and, thus, their reliability. Surprisingly, even variables which might be considered ‘easy to estimate’ had instances of non-credible observations. In addition, measurements of maize yields and land owned were found to be less reliable than other stationary variables. This lack of reliability has implications for monitoring food security status, poverty status and the land productivity of households. Despite this rather bleak picture, our analysis also shows that if the same farm households are followed over time, the sample sizes needed to detect substantial changes are in the order of hundreds of surveys, and not in the thousands. Our research highlights the value of targeted and systematised household surveys and the importance of ongoing efforts to improve data quality. Improvements must be based on the foundations of robust survey design, transparency of experimental design and effective training. The quality and usability of such data can be further enhanced by improving coordination between agencies, incorporating mixed modes of data collection and continuing systematic validation programmes

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

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

The 'Harmonizing Optimal Strategy for Treatment of coronary artery stenosis - sAfety & effectiveneSS of drug-elUting stents & antiplatelet REgimen' (HOST-ASSURE) trial: study protocol for a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Second-generation drug-eluting stents (DES) have raised the bar of clinical performance. These stents are mostly made from cobalt chromium alloy. A newer generation DES has been developed from platinum chromium alloy, but clinical data regarding the efficacy and safety of the platinum chromium-based everolimus-eluting stent (PtCr-EES) is limited, with no comparison data against the cobalt chromium-based zotarolimus-eluting stent (CoCr-ZES). In addition, an antiplatelet regimen is an integral component of medical therapy after percutaneous coronary intervention (PCI). A 1-week duration of doubling the dose of clopidogrel (double-dose antiplatelet therapy (DDAT)) was shown to improve outcome at 1 month compared with conventional dose in acute coronary syndrome (ACS) patients undergoing PCI. However in Asia, including Korea, the addition of cilostazol (triplet antiplatelet therapy (TAT)) is used more commonly than doubling the dose of clopidogrel in high-risk patients.</p> <p>Methods</p> <p>In the 'Harmonizing Optimal Strategy for Treatment of coronary artery stenosis - sAfety & effectiveneSS of drug-elUting stents & antiplatelet REgimen' (HOST-ASSURE) trial, approximately 3,750 patients are being prospectively and randomly assigned in a 2 × 2 factorial design according to the type of stent (PtCr-EES vs CoCr-ZES) and antiplatelet regimen (TAT vs DDAT). The first primary endpoint is target lesion failure at 1 year for the stent comparison, and the second primary endpoint is net clinical outcome at 1 month for comparison of antiplatelet therapy regimen.</p> <p>Discussion</p> <p>The HOST-ASSURE trial is the largest study yet performed to directly compare the efficacy and safety of the PtCr-EES versus CoCr-ZES in an 'all-comers' population. In addition, this study will also compare the clinical outcome of TAT versus DDAT for 1-month post PCI.</p> <p>Trial registration</p> <p>ClincalTrials.gov number <a href="http://www.clinicaltrials.gov/ct2/show/NCT01267734">NCT01267734</a>.</p

Calibration induced uncertainty of the EPIC model to estimate climate change impact on global maize yield

Understanding the interactions between agricultural production and climate is necessary for sound decision-making in climate policy. Gridded and high-resolution crop simulation has emerged as a useful tool for building this understanding. Large uncertainty exists in this utilization, obstructing its capacity as a tool to devise adaptation strategies. Increasing focus has been given to sources of uncertainties for climate scenarios, input-data, and model, but uncertainties due to model parameter or calibration are still unknown. Here, we use publicly available geographical datasets as input to the Environmental Policy Integrated Climate model (EPIC) for simulating global gridded maize yield. Impacts of climate change are assessed up to the year 2099 under a climate scenario generated by HadEM2-ES under RCP 8.5. We apply five strategies by shifting one specific parameter in each simulation to calibrate the model and understand the effects of calibration. Regionalizing crop phenology or harvest index appears effective to calibrate the model for the globe, but using various values of phenology generates pronounced difference in estimated climate impact. However, projected impacts of climate change on global maize production are consistently negative regardless of the parameter being adjusted. Different values of model parameter results in a modest uncertainty at global level, with difference of the global yield change less than 30% by the 2080s. The uncertainty subjects to decrease if applying model calibration or input data quality control. Calibration has a larger effect at local scales, implying the possible types and locations for adaptatio

Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification

Similar estimates of temperature impacts on global wheat yield by three independent methods

The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 °C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify ‘method uncertainty’ in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security.<br/

Repression of the genome organizer SATB1 in regulatory T cells is required for suppressive function and inhibition of effector differentiation

Regulatory T cells (T(reg) cells) are essential for self-tolerance and immune homeostasis. Lack of effector T cell (T(eff) cell) function and gain of suppressive activity by T(reg) cells are dependent on the transcriptional program induced by Foxp3. Here we report that repression of SATB1, a genome organizer that regulates chromatin structure and gene expression, was crucial for the phenotype and function of T(reg) cells. Foxp3, acting as a transcriptional repressor, directly suppressed the SATB1 locus and indirectly suppressed it through the induction of microRNAs that bound the SATB1 3' untranslated region. Release of SATB1 from the control of Foxp3 in T(reg) cells caused loss of suppressive function, establishment of transcriptional T(eff) cell programs and induction of T(eff) cell cytokines. Our data support the proposal that inhibition of SATB1-mediated modulation of global chromatin remodeling is pivotal for maintaining T(reg) cell functionality.Marc Beyer... Timothy Sadlon...Simon C Barry... et al