Naturally Acquired Bovine Besnoitiosis

The pathogenesis of bovine besnoitiosis, a disease of increasing concern within Europe, is still incompletely understood. In this study, disease progression after natural infection with the causative apicomplexan Besnoitia besnoiti was monitored in histological skin sections of 5 individual female cattle over time. High-frequency skin sampling of 2 cattle with mild and 2 with severe acute, subacute, and chronic besnoitiosis, as well as from 1 animal during subclinical disease, enabled documentation from the beginning of the disease. Skin sections were stained with hematoxylin and eosin and Giemsa, periodic acid–Schiff reaction, and anti-Besnoitia immunohistochemistry. In all 4 clinically affected animals, tachyzoite-like endozoites could be detected for the first time by immunohistochemistry, and tissue cyst evolution was monitored. Besnoitiosis-associated lesions were not detected in the animal showing the subclinical course. Because of the inconsistency of the nomenclature of Besnoitia tissue cyst layers in the literature, a new nomenclature for B. besnoiti cyst wall layers is proposed: tissue cysts consist of a hypertrophied host cell with enlarged nuclei, an intracytoplasmic parasitophorous vacuole with bradyzoites, a sometimes vacuolated inner cyst wall, and an outer cyst wall in more developed cysts. Inner and outer cyst walls can be readily distinguished by using special stains. In 1 animal, extracystic B. besnoiti zoites were immunohistochemically detected during the chronic stage. At necropsy, the 2 severely affected cows displayed large numbers of B. besnoiti cysts in a variety of tissues, including the corium of the claws, contributing mainly to the development of chronic laminitis in these 2 cases

The formation, properties and impact of secondary organic aerosol: current and emerging issues

Secondary organic aerosol (SOA) accounts for a significant fraction of ambient tropospheric aerosol and a detailed knowledge of the formation, properties and transformation of SOA is therefore required to evaluate its impact on atmospheric processes, climate and human health. The chemical and physical processes associated with SOA formation are complex and varied, and, despite considerable progress in recent years, a quantitative and predictive understanding of SOA formation does not exist and therefore represents a major research challenge in atmospheric science. This review begins with an update on the current state of knowledge on the global SOA budget and is followed by an overview of the atmospheric degradation mechanisms for SOA precursors, gas-particle partitioning theory and the analytical techniques used to determine the chemical composition of SOA. A survey of recent laboratory, field and modeling studies is also presented. The following topical and emerging issues are highlighted and discussed in detail: molecular characterization of biogenic SOA constituents, condensed phase reactions and oligomerization, the interaction of atmospheric organic components with sulfuric acid, the chemical and photochemical processing of organics in the atmospheric aqueous phase, aerosol formation from real plant emissions, interaction of atmospheric organic components with water, thermodynamics and mixtures in atmospheric models. Finally, the major challenges ahead in laboratory, field and modeling studies of SOA are discussed and recommendations for future research directions are proposed

Towards an online-coupled chemistry-climate model: evaluation of trace gases and aerosols in COSMO-ART

Peer reviewe

Enhanced Volatile Organic Compounds emissions and organic aerosol mass increase the oligomer content of atmospheric aerosols

Secondary organic aerosol (SOA) accounts for a dominant fraction of the submicron atmospheric particle mass, but knowledge of the formation, composition and climate effects of SOA is incomplete and limits our understanding of overall aerosol effects in the atmosphere. Organic oligomers were discovered as dominant components in SOA over a decade ago in laboratory experiments and have since been proposed to play a dominant role in many aerosol processes. However, it remains unclear whether oligomers are relevant under ambient atmospheric conditions because they are often not clearly observed in field samples. Here we resolve this long-standing discrepancy by showing that elevated SOA mass is one of the key drivers of oligomer formation in the ambient atmosphere and laboratory experiments. We show for the first time that a specific organic compound class in aerosols, oligomers, is strongly correlated with cloud condensation nuclei (CCN) activities of SOA particles. These findings might have important implications for future climate scenarios where increased temperatures cause higher biogenic volatile organic compound (VOC) emissions, which in turn lead to higher SOA mass formation and significant changes in SOA composition. Such processes would need to be considered in climate models for a realistic representation of future aerosol-climate-biosphere feedbacks.Research at the University of Cambridge was supported by a Marie Curie Intra-European fellowship (project no. 254319) and the ERC grant no. 279405. We thank the SAPHIR and TNA2012 team in Jülich for supporting our measurements and the support by EUROCHAMP2 contract no. 228335. The field-work was funded by ERC grant 227463 and the Academy of Finland Centre of Excellence (grants 1118615 and 272041) and by the Office of Science (BER), US Department of Energy via Biogenic Aerosols - Effects on Clouds and Climate (BAECC). European Union’s Horizon 2020 research and innovation programme under grant agreement no. 654109 and previously from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 262254. We thank the Met Office for use of the NAME model. S.C. thanks the UK Natural Environment Research Council for her studentship

Leaf segmentation in plant phenotyping: a collation study

Image-based plant phenotyping is a growing application area of computer vision in agriculture. A key task is the segmentation of all individual leaves in images. Here we focus on the most common rosette model plants, Arabidopsis and young tobacco. Although leaves do share appearance and shape characteristics, the presence of occlusions and variability in leaf shape and pose, as well as imaging conditions, render this problem challenging. The aim of this paper is to compare several leaf segmentation solutions on a unique and first-of-its-kind dataset containing images from typical phenotyping experiments. In particular, we report and discuss methods and findings of a collection of submissions for the first Leaf Segmentation Challenge of the Computer Vision Problems in Plant Phenotyping workshop in 2014. Four methods are presented: three segment leaves by processing the distance transform in an unsupervised fashion, and the other via optimal template selection and Chamfer matching. Overall, we find that although separating plant from background can be accomplished with satisfactory accuracy (>>90 % Dice score), individual leaf segmentation and counting remain challenging when leaves overlap. Additionally, accuracy is lower for younger leaves. We find also that variability in datasets does affect outcomes. Our findings motivate further investigations and development of specialized algorithms for this particular application, and that challenges of this form are ideally suited for advancing the state of the art. Data are publicly available (online at http://​www.​plant-phenotyping.​org/​datasets) to support future challenges beyond segmentation within this application domain

TOMOBFLOW: feature-preserving noise filtering for electron tomography

<p>Abstract</p> <p>Background</p> <p>Noise filtering techniques are needed in electron tomography to allow proper interpretation of datasets. The standard linear filtering techniques are characterized by a tradeoff between the amount of reduced noise and the blurring of the features of interest. On the other hand, sophisticated anisotropic nonlinear filtering techniques allow noise reduction with good preservation of structures. However, these techniques are computationally intensive and are difficult to be tuned to the problem at hand.</p> <p>Results</p> <p>TOMOBFLOW is a program for noise filtering with capabilities of preservation of biologically relevant information. It is an efficient implementation of the Beltrami flow, a nonlinear filtering method that locally tunes the strength of the smoothing according to an edge indicator based on geometry properties. The fact that this method does not have free parameters hard to be tuned makes TOMOBFLOW a user-friendly filtering program equipped with the power of diffusion-based filtering methods. Furthermore, TOMOBFLOW is provided with abilities to deal with different types and formats of images in order to make it useful for electron tomography in particular and bioimaging in general.</p> <p>Conclusion</p> <p>TOMOBFLOW allows efficient noise filtering of bioimaging datasets with preservation of the features of interest, thereby yielding data better suited for post-processing, visualization and interpretation. It is available at the web site <url>http://www.ual.es/%7ejjfdez/SW/tomobflow.html</url>.</p

A European aerosol phenomenology - 7: High-time resolution chemical characteristics of submicron particulate matter across Europe

Similarities and differences in the submicron atmospheric aerosol chemical composition are analyzed from a unique set of measurements performed at 21 sites across Europe for at least one year. These sites are located between 35 and 62°N and 10° W – 26°E, and represent various types of settings (remote, coastal, rural, industrial, urban). Measurements were all carried out on-line with a 30-min time resolution using mass spectroscopy based instruments known as Aerosol Chemical Speciation Monitors (ACSM) and Aerosol Mass Spectrometers (AMS) and following common measurement guidelines. Data regarding organics, sulfate, nitrate and ammonium concentrations, as well as the sum of them called non-refractory submicron aerosol mass concentration ([NR-PM1]) are discussed. NR-PM1 concentrations generally increase from remote to urban sites. They are mostly larger in the mid-latitude band than in southern and northern Europe. On average, organics account for the major part (36–64%) of NR-PM1 followed by sulfate (12–44%) and nitrate (6–35%). The annual mean chemical composition of NR-PM1 at rural (or regional background) sites and urban background sites are very similar. Considering rural and regional background sites only, nitrate contribution is higher and sulfate contribution is lower in mid-latitude Europe compared to northern and southern Europe. Large seasonal variations in concentrations (μg/m³) of one or more components of NR-PM1 can be observed at all sites, as well as in the chemical composition of NR-PM1 (%) at most sites. Significant diel cycles in the contribution to [NR-PM1] of organics, sulfate, and nitrate can be observed at a majority of sites both in winter and summer. Early morning minima in organics in concomitance with maxima in nitrate are common features at regional and urban background sites. Daily variations are much smaller at a number of coastal and rural sites. Looking at NR-PM1 chemical composition as a function of NR-PM1 mass concentration reveals that although organics account for the major fraction of NR-PM1 at all concentration levels at most sites, nitrate contribution generally increases with NR-PM1 mass concentration and predominates when NR-PM1 mass concentrations exceed 40 μg/m³ at half of the sites. © 2021 The Author

Atmospheric nucleation: highlights of the EUCAARI project and future directions

Within the project EUCAARI (European Integrated project on Aerosol Cloud Climate and Air Quality interactions), atmospheric nucleation was studied by (i) developing and testing new air ion and cluster spectrometers, (ii) conducting homogeneous nucleation experiments for sulphate and organic systems in the laboratory, (iii) investigating atmospheric nucleation mechanism under field conditions, and (iv) applying new theoretical and modelling tools for data interpretation and development of parameterisations. The current paper provides a synthesis of the obtained results and identifies the remaining major knowledge gaps related to atmospheric nucleation. The most important technical achievement of the project was the development of new instruments for measuring sub-3 nm particle populations, along with the extensive application of these instruments in both the laboratory and the field. All the results obtained during EUCAARI indicate that sulphuric acid plays a central role in atmospheric nucleation. However, also vapours other than sulphuric acid are needed to explain the nucleation and the subsequent growth processes, at least in continental boundary layers. Candidate vapours in this respect are some organic compounds, ammonia, and especially amines. Both our field and laboratory data demonstrate that the nucleation rate scales to the first or second power of the nucleating vapour concentration(s). This agrees with the few earlier field observations, but is in stark contrast with classical thermodynamic nucleation theories. The average formation rates of 2-nm particles were found to vary by almost two orders of magnitude between the different EUCAARI sites, whereas the formation rates of charged 2-nm particles varied very little between the sites. Overall, our observations are indicative of frequent, yet moderate, ion-induced nucleation usually outweighed by much stronger neutral nucleation events in the continental lower troposphere. The most concrete outcome of the EUCAARI nucleation studies are the new semi-empirical nucleation rate parameterizations based on field observations, along with updated aerosol formation parameterizations