Converting simulated total dry matter to fresh marketable yield for field vegetables at a range of nitrogen supply levels

Simultaneous analysis of economic and environmental performance of horticultural crop production requires qualified assumptions on the effect of management options, and particularly of nitrogen (N) fertilisation, on the net returns of the farm. Dynamic soil-plant-environment simulation models for agro-ecosystems are frequently applied to predict crop yield, generally as dry matter per area, and the environmental impact of production. Economic analysis requires conversion of yields to fresh marketable weight, which is not easy to calculate for vegetables, since different species have different properties and special market requirements. Furthermore, the marketable part of many vegetables is dependent on N availability during growth, which may lead to complete crop failure under sub-optimal N supply in tightly calculated N fertiliser regimes or low-input systems. In this paper we present two methods for converting simulated total dry matter to marketable fresh matter yield for various vegetables and European growth conditions, taking into consideration the effect of N supply: (i) a regression based function for vegetables sold as bulk or bunching ware and (ii) a population approach for piecewise sold row crops. For both methods, to be used in the context of a dynamic simulation model, parameter values were compiled from a literature survey. Implemented in such a model, both algorithms were tested against experimental field data, yielding an Index of Agreement of 0.80 for the regression strategy and 0.90 for the population strategy. Furthermore, the population strategy was capable of reflecting rather well the effect of crop spacing on yield and the effect of N supply on product grading

Can community retail pharmacist and diabetes expert support facilitate insulin initiation by family physicians? Results of the AIM@GP randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Limited evidence exists on the effectiveness of external diabetes support provided by diabetes specialists and community retail pharmacists to facilitate insulin-prescribing in family practice.</p> <p>Methods</p> <p>A stratified, parallel group, randomized control study was conducted in 15 sites across Canada. Family physicians received insulin initiation/titration education, a physician-specific ‘report card’ on the characteristics of their type 2 diabetes (T2DM) population, and a registry of insulin-eligible patients at a workshop. Intervention physicians in addition received: (1) diabetes specialist/educator consultation support (active diabetes specialist/educator consultation support for 2 months [the educator initiated contact every 2 weeks] and passive consultation support for 10 months [family physician initiated as needed]); and (2) community retail pharmacist support (option to refer patients to the pharmacist(s) for a 1-hour insulin-initiation session). The primary outcome was the insulin prescribing rate (IPR) per physician defined as the number of insulin starts of insulin-eligible patients during the 12-month strategy.</p> <p>Results</p> <p>Consenting, eligible physicians (n = 151) participated with 15 specialist sites and 107 community pharmacists providing the intervention. Most physicians were male (74%), and had an average of 81 patients with T2DM. Few (9%) routinely initiated patients on insulin. Physicians were randomly allocated to usual care (n = 78) or the intervention (n = 73). Intervention physicians had a mean (SE) IPR of 2.28 (0.27) compared to 2.29 (0.25) for control physicians, with an estimated adjusted RR (95% CI) of 0.99 (0.80 to 1.24), <it>p</it> = 0.96.</p> <p>Conclusions</p> <p>An insulin support program utilizing diabetes experts and community retail pharmacists to enhance insulin prescribing in family practice was not successful. Too few physicians are appropriately intensifying diabetes management through insulin initiation, and aggressive therapeutic treatment is lacking.</p> <p>Trial registration</p> <p>ClinicalTrial.gov: NCT00593489</p

Autoreactive Effector/Memory CD4⁺ and CD8⁺ T Cells Infiltrating Grafted and Endogenous Islets in Diabetic NOD Mice Exhibit Similar T Cell Receptor Usage

<div><p>Islet transplantation provides a “cure” for type 1 diabetes but is limited in part by recurrent autoimmunity mediated by β cell-specific CD4⁺ and CD8⁺ T cells. Insight into the T cell receptor (TCR) repertoire of effector T cells driving recurrent autoimmunity would aid the development of immunotherapies to prevent islet graft rejection. Accordingly, we used a multi-parameter flow cytometry strategy to assess the TCR variable β (Vβ) chain repertoires of T cell subsets involved in autoimmune-mediated rejection of islet grafts in diabetic NOD mouse recipients. Naïve CD4⁺ and CD8⁺ T cells exhibited a diverse TCR repertoire, which was similar in all tissues examined in NOD recipients including the pancreas and islet grafts. On the other hand, the effector/memory CD8⁺ T cell repertoire in the islet graft was dominated by one to four TCR Vβ chains, and specific TCR Vβ chain usage varied from recipient to recipient. Similarly, islet graft- infiltrating effector/memory CD4⁺ T cells expressed a limited number of prevalent TCR Vβ chains, although generally TCR repertoire diversity was increased compared to effector/memory CD8⁺ T cells. Strikingly, the majority of NOD recipients showed an increase in TCR Vβ12-bearing effector/memory CD4⁺ T cells in the islet graft, most of which were proliferating, indicating clonal expansion. Importantly, TCR Vβ usage by effector/memory CD4⁺ and CD8⁺ T cells infiltrating the islet graft exhibited greater similarity to the repertoire found in the pancreas as opposed to the draining renal lymph node, pancreatic lymph node, or spleen. Together these results demonstrate that effector/memory CD4⁺ and CD8⁺ T cells mediating autoimmune rejection of islet grafts are characterized by restricted TCR Vβ chain usage, and are similar to T cells that drive destruction of the endogenous islets.</p> </div