Early prenatal diagnosis of cystic fibrosis (CF) has become possible after the identification of linked DNA markers on chromosome 7. Chorionic villus sampling (CVS) has made possible the first-trimester prenatal diagnosis of CF. We report our experience of 336 pregnant women between 8-12th week. Six different types of sampling devices have been used to get chorionic tissue. Our results proved that the quantity and the quality of the sample gained was the same irrespective of the method employed in obtaining them.
- MeSH
- Models, Biological MeSH
- False Positive Reactions MeSH
- Gestational Age MeSH
- Humans MeSH
- Chorionic Villi Sampling instrumentation methods MeSH
- Retrospective Studies MeSH
- Pregnancy MeSH
- Vacuum MeSH
- Maternal Age MeSH
- Check Tag
- Humans MeSH
- Pregnancy MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Evaluation Study MeSH
In survival and stochastic lifespan modeling, numerous families of distributions are sometimes considered unnatural, unjustifiable theoretically, and occasionally superfluous. Here, a novel parsimonious survival model is developed using the Bilal distribution (BD) and the Kavya-Manoharan (KM) parsimonious transformation family. In addition to other analytical properties, the forms of probability density function (PDF) and behavior of the distributions' hazard rates are analyzed. The insights are theoretical as well as practical. Theoretically, we offer explicit equations for the single and product moments of order statistics from Kavya-Manoharan Bilal Distribution. Practically, maximum likelihood (ML) technique, which is based on simple random sampling (SRS) and ranked set sampling (RSS) sample schemes, is employed to estimate the parameters. Numerical simulations are used as the primary methodology to compare the various sampling techniques.
- Keywords
- KM transformation, Ranked set sampling, Simulation, Statistical model, Survival function,
- Publication type
- Journal Article MeSH
The effects of sampling artifacts are often not fully considered in the design of air monitoring with active air samplers. Semivolatile organic contaminants (SVOCs) are particularly vulnerable to a range of sampling artifacts because of their wide range of gas-particle partitioning and degradation rates, and these can lead to erroneous measurements of air concentrations and a lack of comparability between sites with different environmental and sampling conditions. This study used specially adapted filter-sorbent sampling trains in three types of active air samplers to investigate breakthrough of SVOCs, and the possibility of other sampling artifacts. Breakthrough volumes were experimentally determined for a range of polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs) and polybrominated diphenyl ethers (PBDEs) in sampling volumes from 300 to 10,000 m(3), and sampling durations of 1-7 days. In parallel, breakthrough was estimated based on theoretical sorbent-vapor pressure relationships. The comparison of measured and theoretical determinations of breakthrough demonstrated good agreement between experimental and estimated breakthrough volumes, and showed that theoretical breakthrough estimates should be used when developing air monitoring protocols. Significant breakthrough in active air samplers occurred for compounds with vapor pressure >0.5 Pa at volumes <700 m(3). Sample volumes between 700 and 10,000 m(3) may lead to breakthrough for compounds with vapor pressures between 0.005 and 0.5 Pa. Breakthrough is largely driven by sample volume and compound volatility (therefore indirectly by temperature) and is independent of sampler type. The presence of significant breakthrough at "typical" sampling conditions is relevant for air monitoring networks, and may lead to under-reporting of more volatile SVOCs.
- Keywords
- Air sampling, Breakthrough, Persistent organic pollutants, Sampling artifacts, Semivolatile organic contaminants,
- MeSH
- Artifacts * MeSH
- Hydrocarbons, Chlorinated analysis MeSH
- Halogenated Diphenyl Ethers analysis MeSH
- Air Pollutants analysis MeSH
- Environmental Monitoring methods MeSH
- Polychlorinated Biphenyls analysis MeSH
- Polycyclic Aromatic Hydrocarbons analysis MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Hydrocarbons, Chlorinated MeSH
- Halogenated Diphenyl Ethers MeSH
- Air Pollutants MeSH
- Polychlorinated Biphenyls MeSH
- Polycyclic Aromatic Hydrocarbons MeSH
As COVID-19 is spreading, national agencies need to monitor and track several metrics. Since we do not have perfect testing programs on the hand, one needs to develop an advanced sampling strategies for prevalence study, control and management. Here we introduce REDACS: Regional emergency-driven adaptive cluster sampling for effective COVID-19 management and control and justify its usage for COVID-19. We show its advantages over classical massive individual testing sampling plans. We also point out how regional and spatial heterogeneity underlines proper sampling. Fundamental importance of adaptive control parameters from emergency health stations and medical frontline is outlined. Since the Northern hemisphere entered Autumn and Winter season (this paper was originally submitted in November 2020), practical illustration from spatial heterogeneity of Chile (Southern hemisphere, which already experienced COVID-19 winter outbreak peak) is underlying the importance of proper regional heterogeneity of sampling plan. We explain the regional heterogeneity by microbiological backgrounds and link it to behavior of Lyapunov exponents. We also discuss screening by antigen tests from the perspective of "on the fly" biomarker validation, i.e., during the screening.
- Keywords
- ACS, REDACS, antigen test validation, prevalence, sampling,
- Publication type
- Journal Article MeSH
The distribution of patch occupancy (the proportion of suitable patches occupied by a species) in ecological communities is often unimodal with a mode at minimum patch occupancy values, or bimodal with two local maxima that correspond to the minimum and the maximum patch occupancy. The bimodal distribution is predicted by a metapopulation model known as the core-satellite species hypothesis, but could also be an artifact caused by spatially restricted sampling from a unimodal distribution. A sampling artifact with the opposite effect, producing samples with a unimodal patch occupancy distribution from communities with a bimodal distribution is described here. This artifact is particularly likely to occur when the accuracy of sampling varies among species, as is often the case.
- Keywords
- Core-satellite species hypothesis, Metapopulation, Patch occupancy, Sampling artifacts,
- Publication type
- Journal Article MeSH
Remote work from coworking spaces developed as an alternative to remote work from home, aiming to retain its benefits while overcoming its costs. There are reasons to question whether work from coworking spaces delivers on these aims, however. The current study uses the Experience Sampling Method to explore within-participant differences in well-being, work engagement, and productivity among remote workers, depending on (1) whether they are working from home or from a community-based coworking space, and - when working from a coworking space - (2) whether they work in a shared space and (3) whether the work is collaborative. Results suggest that coworking promotes higher outcomes on all measures relative to working from home. Within the coworking space, the impact of other people in the room and of collaboration is mixed, suggesting distinct strategies for how to best use a coworking space depending on the activity.
This study applied Experience Sampling Method to the study of work in coworking spaces. It shows that work from a coworking space as an alternative to home-based work promotes greater well-being, productivity, and work engagement. The value of a coworking space seems to be in providing flexible access to diverse work environments and enabling live collaboration with other coworking space users.
- Keywords
- Coworking, Experience Sampling Method, performance, remote work, well-being,
- Publication type
- Journal Article MeSH
We investigated a combination of approaches to extend the attainment of partition equilibria between silicone passive samplers (samplers) and surface or treated waste water towards more hydrophobic organic compounds (HOC). The aim was to identify the HOC hydrophobicity range for which silicone sampler equilibration in water is feasible within a reasonable sampler deployment period. Equilibrium partitioning of HOC between sampler and water is desirable for a simpler application as a "chemometer", aiming to compare chemical activity gradients across environmental media (e.g. water, sediment, biota). The tested approaches included a) long sampler exposure periods and high water flow to maximize mass transfer from water to sampler; b) the use of samplers with reduced sheet thicknesses; and c) pre-equilibration of samplers with local bottom sediment, followed by their exposure in surface water at the same sampling site. These approaches were tested at three sites including a fish pond with a low level of pollution, a river impacted by an urban agglomeration and an effluent of municipal wastewater treatment plant. Tested compounds included polychlorinated biphenyls (PCB), polycyclic aromatic hydrocarbons (PAH), DDT, its metabolites and their isomers, hexachlorobenzene (HCB) and polybrominated diphenyl ethers (PBDE). The study shows that samplers with a surface area of 400-800 cm2 consisting of thin (100-500 μm) silicone sheets exposed at sampling rates of 10-40 L d-1 for a time period of up to four months reach partition equilibrium with water for compounds with log Kow ≤ 5.5. Nevertheless, for compounds beyond this limit it is challenging, within a reasonable time period, to reach equilibrium between sampler and water in an open system where water boundary layer resistance controls the mass transfer. For more hydrophobic HOC (log Kow > 6), the kinetic method using performance reference compounds is recommended instead.
- Keywords
- Aquatic pollution, Equilibrium partitioning, Mass transfer, Passive sampling, Persistent organic pollutants, Silicone,
- Publication type
- Journal Article MeSH
Biodiversity conservation faces a methodological conundrum: Biodiversity measurement often relies on species, most of which are rare at various scales, especially prone to extinction under global change, but also the most challenging to sample and model. Predicting the distribution change of rare species using conventional species distribution models is challenging because rare species are hardly captured by most survey systems. When enough data are available, predictions are usually spatially biased towards locations where the species is most likely to occur, violating the assumptions of many modelling frameworks. Workflows to predict and eventually map rare species distributions imply important trade-offs between data quantity, quality, representativeness and model complexity that need to be considered prior to survey and analysis. Our opinion is that study designs need to carefully integrate the different steps, from species sampling to modelling, in accordance with the different types of rarity and available data in order to improve our capacity for sound assessment and prediction of rare species distribution. In this article, we summarize and comment on how different categories of species rarity lead to different types of occurrence and distribution data depending on choices made during the survey process, namely the spatial distribution of samples (where to sample) and the sampling protocol in each selected location (how to sample). We then clarify which species distribution models are suitable depending on the different types of distribution data (how to model). Among others, for most rarity forms, we highlight the insights from systematic species-targeted sampling coupled with hierarchical models that allow correcting for overdispersion and spatial and sampling sources of bias. Our article provides scientists and practitioners with a much-needed guide through the ever-increasing diversity of methodological developments to improve the prediction of rare species distribution depending on rarity type and available data.
- Keywords
- bias, detectability, distribution change, methods, occupancy, rare species, sampling, spatial data, species distribution modelling, survey,
- MeSH
- Biodiversity * MeSH
- Publication type
- Journal Article MeSH
Some species of centipedes and millipedes inhabit upper soil layers exclusively and are not recorded by pitfall trapping. Because of their sensitivity to soil conditions, they can be sampled quantitatively for evaluation of soil conditions. Soil samples are heavy to transport and their processing is time consuming, and such sampling leads to disturbance of the soil surface which land-owners do not like. We evaluated the use of hay-bait traps to sample soil dwelling millipedes and centipedes. The effectiveness of this method was found to be similar to the effectiveness of soil sampling. Hay-bait traps installed for 8-10 weeks can substitute for direct soil sampling in ecological and inventory studies.
- Keywords
- Chilopoda, Diplopoda, agroecosystem, soil fauna, soil sampling,
- Publication type
- Journal Article MeSH
