Decision support for spatially targeted livestock policies: Diverse examples from Uganda and Thailand

Public policies are needed to guide livestock sector¿s changes along a path that is sustainable in economic, social and environmental terms. These policies should include multiple development objectives and be adapted to location-specific contexts. Policy makers need assistance in dealing with such complex decisions. Spatial information can be integrated in decision support tools to support policy making, and is becoming increasingly available in the developing world. Spatial information, however, has seldom been used in livestock sector policy formulation because policy makers generally do not have access to resources for spatial modelling. The objective of this paper is to bridge this gap by proposing an approach to consolidating and analysing spatial information in the context of limited modelling resources. Rooted in practical experience, a method is proposed that combines two multiple criteria decision-making techniques (weighted linear combination and analytical hierarchical processes), parameterised in a participatory process and implemented in a GIS. The method is tested in two different contexts: support to single objective decision-making for targeting trypanosomiasis control interventions in Uganda, and support to multiple objective decision-making for spatial planning of livestock production development in Thailand. The results show the advantages of such an approach, in terms of stakeholder involvement and practical application to support decision-making, but also highlight two shortcomings: dependence on high quality data and uncertainty with regard to the decision rule. While the former will be addressed as digital information becomes increasingly available, the latter, embedded in any decision-making process, calls for thorough sensitivity analyses and careful scrutiny of results

Role of autoantibody levels as biomarkers in the management of patients with myasthenia gravis: A systematic review and expert appraisal

Background and purpose Although myasthenia gravis (MG) is recognized as an immunoglobulin G autoantibody-mediated disease, the relationship between autoantibody levels and disease activity in MG is unclear. We sought to evaluate this landscape through systematically assessing the evidence, testing the impact of predefined variables on any relationship, and augmenting with expert opinion. Methods In October 2020, a forum of leading clinicians and researchers in neurology from across Europe (Expert Forum for Rare Autoantibodies in Neurology in Myasthenia Gravis) participated in a series of virtual meetings that took place alongside the conduct of a systematic literature review (SLR). Results Forty-two studies were identified meeting inclusion criteria. Of these, 10 reported some correlation between a patient's autoantibody level and disease severity. Generally, decreased autoantibody levels (acetylcholine receptor, muscle-specific kinase, and titin) were positively and significantly correlated with improvements in disease severity (Quantitative Myasthenia Gravis score, Myasthenia Gravis Composite score, Myasthenia Gravis Activities of Daily Living score, Myasthenia Gravis Foundation of America classification). Given the limited evidence, testing the impact of predefined variables was not feasible. Conclusions This first SLR to assess whether a correlation exists between autoantibody levels and disease activity in patients with MG has indicated a potential positive correlation, which could have clinical implications in guiding treatment decisions. However, in light of the limited and variable evidence, we cannot currently recommend routine clinical use of autoantibody level testing in this context. For now, patient's characteristics, clinical disease course, and laboratory data (e.g., autoantibody status, thymus histology) should inform management, alongside patient-reported outcomes. We highlight the need for future studies to reach more definitive conclusions on this relationship.Neurological Motor Disorder

Enrichment of serum IgG4 in MuSK myasthenia gravis patients

Muscle-specific kinase (MuSK) myasthenia gravis (MG) is a neuromuscular autoimmune disease belonging to a growing group of IgG4 autoimmune diseases (IgG4-AIDs), in which the majority of pathogenic autoantibodies are of the IgG4 subclass. The more prevalent form of MG with acetylcholine receptor (AChR) antibodies is caused by IgG1-3 autoantibodies. A dominant role for IgG4 in autoimmune disease is intriguing due to its antiinflammatory characteristics. It is unclear why MuSK autoantibodies are predominantly IgG4. We hypothesized that MuSK MG patients have a general predisposition to generate IgG4 responses, therefore resulting in high levels of circulating IgG4. To investigate this, we quantified serum Ig isotypes and IgG subclasses using nephelometric and turbidimetric assays in MuSK MG and AChR MG patients not under influence of immunosuppressive treatment. Absolute serum IgG1 was increased in both MuSK and AChR MG patients compared to healthy donors. In addition, only MuSK MG patients on average had significantly increased and enriched serum IgG4. Although more MuSK MG patients had elevated serum IgG4, for most the IgG4 serum levels fell within the normal range. Correlation analyses suggest MuSK-specific antibodies do not solely explain the variation in IgG4 levels. In conclusion, although serum IgG4 levels are slightly increased, the levels do not support ubiquitous IgG4 responses in MuSK MG patients as the underlying cause of dominant IgG4 MuSK antibodies.Neurological Motor Disorder