Silver diagnosis in neuropathology: principles, practice and revised interpretation

Silver-staining methods are helpful for histological identification of pathological deposits. In spite of some ambiguities regarding their mechanism and interpretation, they are widely used for histopathological diagnosis. In this review, four major silver-staining methods, modified Bielschowsky, Bodian, Gallyas (GAL) and Campbell–Switzer (CS) methods, are outlined with respect to their principles, basic protocols and interpretations, thereby providing neuropathologists, technicians and neuroscientists with a common basis for comparing findings and identifying the issues that still need to be clarified. Some consider “argyrophilia” to be a homogeneous phenomenon irrespective of the lesion and the method. Thus, they seek to explain the differences among the methods by pointing to their different sensitivities in detecting lesions (quantitative difference). Comparative studies, however, have demonstrated that argyrophilia is heterogeneous and dependent not only on the method but also on the lesion (qualitative difference). Each staining method has its own lesion-dependent specificity and, within this specificity, its own sensitivity. This “method- and lesion-dependent” nature of argyrophilia enables operational sorting of disease-specific lesions based on their silver-staining profiles, which may potentially represent some disease-specific aspects. Furthermore, comparisons between immunohistochemical and biochemical data have revealed an empirical correlation between GAL+/CS-deposits and 4-repeat (4R) tau (corticobasal degeneration, progressive supranuclear palsy and argyrophilic grains) and its complementary reversal between GAL-/CS+deposits and 3-repeat (3R) tau (Pick bodies). Deposits containing both 3R and 4R tau (neurofibrillary tangles of Alzheimer type) are GAL+/CS+. Although no molecular explanations, other than these empiric correlations, are currently available, these distinctive features, especially when combined with immunohistochemistry, are useful because silver-staining methods and immunoreactions are complementary to each other

European aerosol phenomenology - 8: Harmonised source apportionment of organic aerosol using 22 Year-long ACSM/AMS datasets

Organic aerosol (OA) is a key component of total submicron particulate matter (PM1), and comprehensive knowledge of OA sources across Europe is crucial to mitigate PM1 levels. Europe has a well-established air quality research infrastructure from which yearlong datasets using 21 aerosol chemical speciation monitors (ACSMs) and 1 aerosol mass spectrometer (AMS) were gathered during 2013-2019. It includes 9 non-urban and 13 urban sites. This study developed a state-of-the-art source apportionment protocol to analyse long-term OA mass spectrum data by applying the most advanced source apportionment strategies (i.e., rolling PMF, ME-2, and bootstrap). This harmonised protocol was followed strictly for all 22 datasets, making the source apportionment results more comparable. In addition, it enables quantification of the most common OA components such as hydrocarbon-like OA (HOA), biomass burning OA (BBOA), cooking-like OA (COA), more oxidised-oxygenated OA (MO-OOA), and less oxidised-oxygenated OA (LO-OOA). Other components such as coal combustion OA (CCOA), solid fuel OA (SFOA: mainly mixture of coal and peat combustion), cigarette smoke OA (CSOA), sea salt (mostly inorganic but part of the OA mass spectrum), coffee OA, and ship industry OA could also be separated at a few specific sites. Oxygenated OA (OOA) components make up most of the submicron OA mass (average = 71.1%, range from 43.7 to 100%). Solid fuel combustion-related OA components (i.e., BBOA, CCOA, and SFOA) are still considerable with in total 16.0% yearly contribution to the OA, yet mainly during winter months (21.4%). Overall, this comprehensive protocol works effectively across all sites governed by different sources and generates robust and consistent source apportionment results. Our work presents a comprehensive overview of OA sources in Europe with a unique combination of high time resolution (30-240 min) and long-term data coverage (9-36 months), providing essential information to improve/validate air quality, health impact, and climate models

Modelling continuous cover forests

Many well established techniques such as yield tables and age-based growth models are not applicable in continuous cover forestry (CCF). A further complexity in CCF is the need to predict regeneration. It is possible to model CCF using stand-based approaches such as transition matrices and stand table projection but the utility of these approaches is limited. Individual-based approaches are the most promising and may take two forms: cohort-based and single-tree models. While the utility and limitations of site indices based on age and dominant height is well established for plantation situations, there is no dominant paradigm for dealing with site productivity in stands managed as CCF. Alternatives include dendrometric approaches, indicator species and site descriptors such as elevation, slope and soil depth. In even-aged forests, the self-thinning line provides an effective way to estimate mortality in forest stands, but the concept is of limited utility in CCF. With CCF, the best option is to predict individual-tree survival from the resources deemed to be available to each tree. Fertile areas for further research include site productivity assessment and the modelling of regeneration and species interactions