Occupational and environmental exposure to SARS-CoV-2 in and around infected mink farms.

OBJECTIVE: Unprecedented SARS-CoV-2 infections in farmed minks raised immediate concerns regarding transmission to humans and initiated intensive environmental investigations to assess occupational and environmental exposure. METHODS: Air sampling was performed at infected Dutch mink farms, at farm premises and at nearby residential sites. A range of other environmental samples were collected from minks' housing units, including bedding materials. SARS-CoV-2 RNA was analysed in all samples by quantitative PCR. RESULTS: Inside the farms, considerable levels of SARS-CoV-2 RNA were found in airborne dust, especially in personal inhalable dust samples (approximately 1000-10 000 copies/m3). Most of the settling dust samples tested positive for SARS-CoV-2 RNA (82%, 75 of 92). SARS-CoV-2 RNA was not detected in outdoor air samples, except for those collected near the entrance of the most recently infected farm. Many samples of minks' housing units and surfaces contained SARS-CoV-2 RNA. CONCLUSIONS: Infected mink farms can be highly contaminated with SARS-CoV-2 RNA. This warns of occupational exposure, which was substantiated by considerable SARS-CoV-2 RNA concentrations in personal air samples. Dispersion of SARS-CoV-2 to outdoor air was found to be limited and SARS-CoV-2 RNA was not detected in air samples collected beyond farm premises, implying a negligible risk of environmental exposure to nearby communities. Our occupational and environmental risk assessment is in line with whole genome sequencing analyses showing mink-to-human transmission among farm workers, but no indications of direct zoonotic transmission events to nearby communities.

The Development and Calibration of a Mechanistic Asbestos Removal Exposure Assessment Tool (AREAT).

Exposure to asbestos fibres is linked to numerous adverse health effects and the use of asbestos is currently banned in many countries. Still, asbestos applications are present in numerous residential and professional/industrial buildings or installations which need to be removed. Exposure measurements give good insight in exposure levels on the basis of which the required control regime is determined to ensure that workers are protected against adverse health effects. However, it is a costly and time-consuming process to measure all situations as working conditions and materials may vary greatly. Therefore, the mechanistic model 'Asbestos Removal Exposure Assessment Tool (AREAT)' was developed to estimate exposure to respirable asbestos fibres released during asbestos abatement processes where measurements are not available. In such instances tailored control regimes can be implemented based on modelled exposure levels. The mechanistic model was developed using scientific literature, an in-house asbestos abatement dataset, and knowledge with regard to previously developed models. Several exposure determinants such as the substance emission potential, activity emission potential, control measures, and dilution in air were identified and specific modifiers were developed for each category. Through an algorithm, AREAT calculates a dimensionless score based on the model inputs. The model was calibrated using a statistical model on an extensive measurement dataset containing a broad variety of exposure scenarios. This statistical model enabled the translation of dimensionless AREAT scores to actual estimated fibre concentrations in fibres m-3. In total, 370 personal inhalation exposure measurements from 71 different studies were used for calibration of AREAT. Of these measurements, in 191 cases (52%) with microscopic analysis (all asbestos fibre analyses were conducted with scanning electron microscopy/energy dispersive X-ray analysis in accordance with ISO 14966) no fibres were detected and the limit of detection values(LODs) were given. To assess the influence of the large number of measurements with exposures below LOD values on the performance of the model, calibrations were performed on the total dataset and the selection of data excluding measurements below LOD. The AREAT model correlated well with the datasets, with a Pearson correlation of 0.73 and 0.8 and Spearman rank correlation of 0.56 and 0.8. The model was fitted to estimate a typical exposure value [i.e. geometric mean (GM) exposures], but it is recommended to use a more conservative worst case higher percentile (for example the 90th percentile; which adds a factor of 17.3 based on the model uncertainty on the GM estimate), to account for variability in the measurements and uncertainty in model estimates. This work has shown the development and calibration of a mechanistic model, capable of estimating asbestos fibre exposures during asbestos abatement processes. The AREAT model will be implemented as a lower tier exposure model in a risk assessment tool used within the Netherlands to plan abatement processes and to develop control strategies.

Quantitative analysis of the concentrations of IGFs and several IGF-binding proteins in a large fibrous abdominal tumor and the circulation of a patient with hypoglycemia.

The syndrome of nonislet cell tumor induced hypoglycemia (NICTH) represent extreme cases of excessive expression and production of incompletely processed high-molecular-mass pro-IGF-II forms (big IGF-II) by an often large tumor. Tumor-derived big IGF-II is responsible for enhanced insulin-like effects in the body through complicated mechanisms, leading to hypoglycemia. Case studies on NICTH usually focus on measurements of diagnostic parameters in the circulation of patients. Some studies have also reported on qualitative immunohistochemical analysis of tumor tissue, in particular with respect to the expression of IGF-II at the mRNA or protein level. However, quantitative data on the concentrations of IGFs and IGFBPs in tumor specimen causing NICTH, in relation to their corresponding plasma levels are lacking. Such an analysis would provide an estimate of the total potential of (big) IGF-II retained by the tumor and more insight in the relative levels of different IGFBPs and their origin in the circulation, that is, systemically induced by tumor related factors or directly tumor-derived. Here we investigated quantitatively the levels of IGFs and IGFBPs in a large, 1.76 kg weighing, solitary fibrous tumor from a typical case of NICTH using highly specific immunometric assays. Besides a high level of big IGF-II, patient's plasma also contained increased levels of both IGFBP-2 and -6 which declined after removal of the tumor. These IGFBPs have a higher affinity for (pro-) IGF-II than IGF-I and exhibit intrinsic IGF-independent bioactivities. Tumor tissue contained high amounts of big IGF-II and IGFBP-6, exceeding that in patient's circulation many-fold. A relatively low tumor content of IGFBP-2 was found suggesting that the preoperative high levels in plasma were attributable to systemic mechanisms. The background literature and possible implications of these findings are briefly discussed. Based on the present results we postulate that tumor tissue is not the source of the elevated levels of IGFBP-2 often seen in NICTH patients. Large tumors that cause NICTH can produce IGFBP-6 leading to enhanced levels of this IGFBP in the circulation. Hence, the measurement of IGFBP-6 in plasma may serve as an additional marker of this disease pattern.