Sustainable development of smallholder crop-livestock farming in developing countries

Meeting the growing demand for animal-sourced food, prompted by population growth and increases in average per-capita income in low-income countries, is a major challenge. Yet, it also presents significant potential for agricultural growth, economic development, and reduction of poverty in rural areas. The main constraints to livestock producers taking advantage of growing markets include; lack of forage and feed gaps, communal land tenure, limited access to land and water resources, weak institutions, poor infrastructure and environmental degradation. To improve rural livelihood and food security in smallholder crop-livestock farming systems, concurrent work is required to address issues regarding efficiency of production, risk within systems and development of whole value chain systems. This paper provides a review of several forage basedstudies in tropical and non-tropical dry areas of the developing countries. A central tenet of this paper is that forages have an essential role in agricultural productivity, environmental sustainability and livestock nutrition in smallholder mixed farming systems

Mitigating Off-Policy Bias in Actor-Critic Methods with One-Step Q-learning: A Novel Correction Approach

Compared to on-policy counterparts, off-policy model-free deep reinforcement learning can improve data efficiency by repeatedly using the previously gathered data. However, off-policy learning becomes challenging when the discrepancy between the underlying distributions of the agent's policy and collected data increases. Although the well-studied importance sampling and off-policy policy gradient techniques were proposed to compensate for this discrepancy, they usually require a collection of long trajectories and induce additional problems such as vanishing/exploding gradients or discarding many useful experiences, which eventually increases the computational complexity. Moreover, their generalization to either continuous action domains or policies approximated by deterministic deep neural networks is strictly limited. To overcome these limitations, we introduce a novel policy similarity measure to mitigate the effects of such discrepancy in continuous control. Our method offers an adequate single-step off-policy correction that is applicable to deterministic policy networks. Theoretical and empirical studies demonstrate that it can achieve a "safe" off-policy learning and substantially improve the state-of-the-art by attaining higher returns in fewer steps than the competing methods through an effective schedule of the learning rate in Q-learning and policy optimization

Promising Forage Options to Enhance Livestock Production in Mediterranean Climate Agricultural Systems

The increasing demand for food, fibre and animal products inevitably requires intensifying agricultural production worldwide. This can present a number of environmental and farming systems challenges in Mediterranean climate areas of the world. Developments of novel strategies, employing ecologically sound intensification practices, are crucial to enhance production in the Mediterranean agropastoral production systems. In this paper, we have discussed forage based systems that improve productivity, profitability, environmental quality and resilience of the farming systems. Key opportunities include better use and integration of diverse genetic resources, new agronomic techniques and the utilization of perennial forage plants that are adapted to land that may not be suited to traditional species. This article has a specific focus on the recent developments on forage based production options for the ecologically sound intensification and enhanced livestock productivity in the low to medium rainfall (\u3c 500 mm/year) Mediterranean agropastoral production systems from the farming context of smallholdings of south Mediterranean countries (West Asia and North Africa; WANA) and large-scale farming systems of southern Australia

Streptococcus pyogenes pSM19035 requires dynamic assembly of ATP-bound ParA and ParB on parS DNA during plasmid segregation

The accurate partitioning of Firmicute plasmid pSM19035 at cell division depends on ATP binding and hydrolysis by homodimeric ATPase δ2 (ParA) and binding of ω2 (ParB) to its cognate parS DNA. The 1.83 Å resolution crystal structure of δ2 in a complex with non-hydrolyzable ATPγS reveals a unique ParA dimer assembly that permits nucleotide exchange without requiring dissociation into monomers. In vitro, δ2 had minimal ATPase activity in the absence of ω2 and parS DNA. However, stoichiometric amounts of ω2 and parS DNA stimulated the δ2 ATPase activity and mediated plasmid pairing, whereas at high (4:1) ω2 : δ2 ratios, stimulation of the ATPase activity was reduced and δ2 polymerized onto DNA. Stimulation of the δ2 ATPase activity and its polymerization on DNA required ability of ω2 to bind parS DNA and its N-terminus. In vivo experiments showed that δ2 alone associated with the nucleoid, and in the presence of ω2 and parS DNA, δ2 oscillated between the nucleoid and the cell poles and formed spiral-like structures. Our studies indicate that the molar ω2 : δ2 ratio regulates the polymerization properties of (δ•ATP•Mg2+)2 on and depolymerization from parS DNA, thereby controlling the temporal and spatial segregation of pSM19035 before cell division

Methylation of Leukocyte DNA and Ovarian Cancer: Relationships with Disease Status and Outcome

Genome-wide interrogation of DNA methylation (DNAm) in blood-derived leukocytes has become feasible with the advent of CpG genotyping arrays. In epithelial ovarian cancer (EOC), one report found substantial DNAm differences between cases and controls; however, many of these disease-associated CpGs were attributed to differences in white blood cell type distributions. We examined blood-based DNAm in 336 EOC cases and 398 controls; we included only high-quality CpG loci that did not show evidence of association with white blood cell type distributions to evaluate association with case status and overall survival

Betatrophin levels are related to the early histological findings in nonalcoholic fatty liver disease

Betatrophin, a liver hormone, regulates glucose and lipid metabolism. We investigated the betatrophin levels in nonalcoholic fatty liver disease (NAFLD) and searched for any relationship with histological severity and metabolic parameters. Fifty males with NAFLD [Nonalcoholic Steatohepati-tis (NASH) (n = 32); non-NASH (n = 18)] and 30 healthy controls were included. Plasma betatrophin was measured by ELISA method. Insulin sensitivity was assessed by HOMA-IR index. Histological features were scored by the semi quantitative classification and combined as the NAFLD activity score (NAS). Betatrophin levels in the non-NASH group were significantly higher than the controls. Betatrophin was positively correlated to the age, waist circumference, total cholesterol, triglycerides, LDL cholesterol, glucose, insulin, HOMA-IR index and gamma glutamyl transpeptidase levels, and negatively correlated to the steatosis and NAS. In the stepwise linear regression analysis, the triglyceride (β = 0.457, p < 0.001), glucose (β = 0.281, p = 0.02) and NAS (β = −0.260, p = 0.03) were the independent determinants of betatrophin. Betatrophin levels are higher in the early stages of NAFLD and tend to decrease when the disease progresses. This could be an important preliminary mechanistic finding to explain the increased frequency of glucose intolerance during the course of NAFLD

Uptake of agroforestry-based crop management in the semi-arid Sahel – Analysis of joint decisions and adoption determinants.

Open Access JournalIntroduction: Agroforestry plays a vital role in maintaining and developing the resilience and productivity of farms and landscapes. Scientific evidence from the Sahel region suggests that integration of trees and shrubs has the potential to improve temperature and moisture levels whilst providing bio-based fertilizer that contributes to increased yields of annual crops. However, little is known about the factors that influence the diusion of agroforestry. This study examines joint decisions on the use of agroforestry alongside other complementary agricultural practices and disentangles agroforestry awareness fromadoption and disadoption decisions. Methods: Our analysis is based on a comprehensive farm-level dataset covering almost 3,000 farm households in Mali and Senegal. A large number of adoption determinants are utilized, with a special focus on information access, information flows and social groups. Results: The findings suggest that extension access and training participation boost awareness of agroforestry-based soil fertility management, while information provided by public extension, NGOs and community members is strongly associated with higher adoption intensity. In the analysis of disadoption, farmer-to-farmers exchange in the community was found to be a key factor in the decision to maintain agroforestry use. Membership in cooperatives and youth groups appear to have a favorable eect on awareness and adoption in Mali, but less so in the Senegalese case. Similarly, only results from Mali show that adoption of agroforestry is accompanied by the adoption of other sustainable intensification practices and lower use of synthetic pesticides. Discussion: We conclude that in order to support the transition to more widespread agroforestry-based soil fertility management, it is essential to strengthen public and NGO-based advisory systems that fully engage with local knowledge networks

Metabolomics approaches in pancreatic adenocarcinoma: Tumor metabolism profiling predicts clinical outcome of patients

Background: Pancreatic adenocarcinomas (PAs) have very poor prognoses even when surgery is possible. Currently, there are no tissular biomarkers to predict long-term survival in patients with PA. The aims of this study were to (1) describe the metabolome of pancreatic parenchyma (PP) and PA, (2) determine the impact of neoadjuvant chemotherapy on PP and PA, and (3) find tissue metabolic biomarkers associated with long-term survivors, using metabolomics analysis. Methods: 1H high-resolution magic angle spinning (HRMAS) nuclear magnetic resonance (NMR) spectroscopy using intact tissues was applied to analyze metabolites in PP tissue samples (n = 17) and intact tumor samples (n = 106), obtained from 106 patients undergoing surgical resection for PA. Results: An orthogonal partial least square-discriminant analysis (OPLS-DA) showed a clear distinction between PP and PA. Higher concentrations of myo-inositol and glycerol were shown in PP, whereas higher levels of glucose, ascorbate, ethanolamine, lactate, and taurine were revealed in PA. Among those metabolites, one of them was particularly obvious in the distinction between long-term and short-term survivors. A high ethanolamine level was associated with worse survival. The impact of neoadjuvant chemotherapy was higher on PA than on PP. Conclusions: This study shows that HRMAS NMR spectroscopy using intact tissue provides important and solid information in the characterization of PA. Metabolomics profiling can also predict long-term survival: the assessment of ethanolamine concentration can be clinically relevant as a single metabolic biomarker. This information can be obtained in 20 min, during surgery, to distinguish long-term from short-term survival. © 2017 The Author(s)

An approach for the identification of targets specific to bone metastasis using cancer genes interactome and gene ontology analysis

Metastasis is one of the most enigmatic aspects of cancer pathogenesis and is a major cause of cancer-associated mortality. Secondary bone cancer (SBC) is a complex disease caused by metastasis of tumor cells from their primary site and is characterized by intricate interplay of molecular interactions. Identification of targets for multifactorial diseases such as SBC, the most frequent complication of breast and prostate cancers, is a challenge. Towards achieving our aim of identification of targets specific to SBC, we constructed a 'Cancer Genes Network', a representative protein interactome of cancer genes. Using graph theoretical methods, we obtained a set of key genes that are relevant for generic mechanisms of cancers and have a role in biological essentiality. We also compiled a curated dataset of 391 SBC genes from published literature which serves as a basis of ontological correlates of secondary bone cancer. Building on these results, we implement a strategy based on generic cancer genes, SBC genes and gene ontology enrichment method, to obtain a set of targets that are specific to bone metastasis. Through this study, we present an approach for probing one of the major complications in cancers, namely, metastasis. The results on genes that play generic roles in cancer phenotype, obtained by network analysis of 'Cancer Genes Network', have broader implications in understanding the role of molecular regulators in mechanisms of cancers. Specifically, our study provides a set of potential targets that are of ontological and regulatory relevance to secondary bone cancer.Comment: 54 pages (19 pages main text; 11 Figures; 26 pages of supplementary information). Revised after critical reviews. Accepted for Publication in PLoS ON

Clinical characteristics of ovarian cancer classified by BRCA1, BRCA2, and RAD51C status.

We evaluated homologous recombination deficient (HRD) phenotypes in epithelial ovarian cancer (EOC) considering BRCA1, BRCA2, and RAD51C in a large well-annotated patient set. We evaluated EOC patients for germline deleterious mutations (n = 899), somatic mutations (n = 279) and epigenetic alterations (n = 482) in these genes using NGS and genome-wide methylation arrays. Deleterious germline mutations were identified in 32 (3.6%) patients for BRCA1, in 28 (3.1%) for BRCA2 and in 26 (2.9%) for RAD51C. Ten somatically sequenced patients had deleterious alterations, six (2.1%) in BRCA1 and four (1.4%) in BRCA2. Fifty two patients (10.8%) had methylated BRCA1 or RAD51C. HRD patients with germline or somatic alterations in any gene were more likely to be high grade serous, have an earlier diagnosis age and have ovarian and/or breast cancer family history. The HRD phenotype was most common in high grade serous EOC. Identification of EOC patients with an HRD phenotype may help tailor specific therapies.This work was supported by National Institutes of Health grants R01-CA122443, P50-CA136393, P30-CA15083, and the Fred C. and Katherine B. Andersen Foundation. We thank Gary Kenney, M.D. for pathology review of tumor tissue. We thank Craig Luccarini, Caroline Baynes from University of Cambridge for assisting our sample sequencing