Definitions, Criteria and Global Classification of Mast Cell Disorders with Special Reference to Mast Cell Activation Syndromes: A Consensus Proposal

Activation of tissue mast cells (MCs) and their abnormal growth and accumulation in various organs are typically found in primary MC disorders also referred to as mastocytosis. However, increasing numbers of patients are now being informed that their clinical findings are due to MC activation (MCA) that is neither associated with mastocytosis nor with a defined allergic or inflammatory reaction. In other patients with MCA, MCs appear to be clonal cells, but criteria for diagnosing mastocytosis are not met. A working conference was organized in 2010 with the aim to define criteria for diagnosing MCA and related disorders, and to propose a global unifying classification of all MC disorders and pathologic MC reactions. This classification includes three types of `MCA syndromes' (MCASs), namely primary MCAS, secondary MCAS and idiopathic MCAS. MCA is now defined by robust and generally applicable criteria, including (1) typical clinical symptoms, (2) a substantial transient increase in serum total tryptase level or an increase in other MC-derived mediators, such as histamine or prostaglandin D 2, or their urinary metabolites, and (3) a response of clinical symptoms to agents that attenuate the production or activities of MC mediators. These criteria should assist in the identification and diagnosis of patients with MCAS, and in avoiding misdiagnoses or overinterpretation of clinical symptoms in daily practice. Moreover, the MCAS concept should stimulate research in order to identify and exploit new molecular mechanisms and therapeutic targets. Copyright (C) 2011 S. Karger AG, Base

Can We Really Prevent Suicide?

Every year, suicide is among the top 20 leading causes of death globally for all ages. Unfortunately, suicide is difficult to prevent, in large part because the prevalence of risk factors is high among the general population. In this review, clinical and psychological risk factors are examined and methods for suicide prevention are discussed. Prevention strategies found to be effective in suicide prevention include means restriction, responsible media coverage, and general public education, as well identification methods such as screening, gatekeeper training, and primary care physician education. Although the treatment for preventing suicide is difficult, follow-up that includes pharmacotherapy, psychotherapy, or both may be useful. However, prevention methods cannot be restricted to the individual. Community, social, and policy interventions will also be essentia

Modeling of uncertainty associated with dose-response curves as applied for probabilistic risk assessment in laser safety

In laser safety, dose-response curves describe the probability for ocular injury as a function of ocular energy, and are often used to quantify the risk for ocular injury given a certain level of exposure to laser radiation. In principal, a dose-response curve describes the biological variation of the individual thresholds in a population. In laser safety, a log-normal cumulative distribution is generally assumed for the dose-response curve, for instance, when Probit analysis is performed. The log-normal distribution is defined by two parameters, the median, called ED50 and the slope. When animal experiments are performed to obtain dose-response curves for laser induced injury, ecperimental uncertainty such as focussing errors as well as variability within the group of experimental animals, such as inter-individual variability of obsorption of the ocular media, can influence the shape of the dose-response curve. We present simulations of uncertainties and cariabilities that show that the log-normal dose-response curve as obtained in a animal experiments can grossly overestimate the probability for ocular damage for small doses. It is argued that the intrinsic slope for an individual's dose response curve is rather steep, even for retinal injury, however, the dose-response curve for a group or population can be broader when there is inter-individual variability of parameters which influence the threshold. the quantitative results of the simulation of the grouping of individual dose-response curves can serve as basis to correct potentially biased dose-response curves as well as to characterize the uncertainty associated with the ED50 and the slope of the dose-response curve. A probabilistic risk analysis model, which accounts for these uncertainties by using Monte-Carlo simulation, was developed for retinal laser injuries from pulsed lasers with wavelengths from 200 nm to 20mu m, and the interpretation of the results are discussed on the basis of example calculations

Royal Society Open Science / Suicides on the Austrian railway network: hotspot analysis and effect of proximity to psychiatric institutions

Railway suicide is a significant public health problem. In addition to the loss of lives, these suicides occur in public space, causing traumatization among train drivers and passengers, and significant public transport delays. Prevention efforts depend upon accurate knowledge of clustering phenomena across the railway network, and spatial risk factors. Factors such as proximity to psychiatric institutions have been discussed to impact on railway suicides, but analytic evaluations are scarce and limited. We identify 15 hotspots on the Austrian railway system while taking case location uncertainties into account. These hotspots represent 0.9% of the total track length (5916km/3676 miles) that account for up to 17% of all railway suicides (N=1130). We model suicide locations on the network using a smoothed inhomogeneous Poisson process and validate it using randomization tests. We find that the density of psychiatric beds is a significant predictor of railway suicide. Further predictors are population density, multitrack structure andless consistentlyspatial socio-economic factors including total suicide rates. We evaluate the model for the identified hotspots and show that the actual influence of these variables differs across individual hotspots. This analysis provides important information for suicide prevention research and practice. We recommend structural separation of railway tracks from nearby psychiatric institutions to prevent railway suicide.(VLID)487534

Supplementary Figures S1-S3 from Suicides on the Austrian railway network: hotspot analysis and effect of proximity to psychiatric institutions

Railway suicide is a significant public health problem. In addition to the loss of lives, these suicides occur in public space, causing traumatization among train drivers and passengers, and significant public transport delays. Prevention efforts depend upon accurate knowledge of clustering phenomena across the railway network, and spatial risk factors. Factors such as proximity to psychiatric institutions have been discussed to impact on railway suicides, but analytic evaluations are scarce and limited. We identify 15 hotspots on the Austrian railway system while taking case location uncertainties into account. These hotspots represent 0.9% of the total track length (5916 km/3676 miles) that account for up to 17% of all railway suicides (<i>N</i>=1130). We model suicide locations on the network using a smoothed inhomogeneous Poisson process and validate it using randomization tests. We find that the density of psychiatric beds is a significant predictor of railway suicide. Further predictors are population density, multitrack structure and—less consistently—spatial socio-economic factors including total suicide rates. We evaluate the model for the identified hotspots and show that the actual influence of these variables differs across individual hotspots. This analysis provides important information for suicide prevention research and practice. We recommend structural separation of railway tracks from nearby psychiatric institutions to prevent railway suicide