Determination of Varying Group Sizes for Pooling Procedure.
Ontology highlight
ABSTRACT:
SUBMITTER: Xiong W
PROVIDER: S-EPMC6466917 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Massive molecular testing for COVID-19 has been pointed out as fundamental to moderate the spread of the pandemic. Pooling methods can enhance testing efficiency, but they are viable only at low incidences of the disease. We propose Smart Pooling, a machine learning method that uses clinical and sociodemographic data from patients to increase the efficiency of informed Dorfman testing for COVID-19 by arranging samples into all-negative pools. To do this, we ran an automated method to train numerous machine learning models on a retrospective dataset from more than 8000 patients tested for SARS-CoV-2 from April to July 2020 in Bogotá, Colombia. We estimated the efficiency gains of using the predictor to support Dorfman testing by simulating the outcome of tests. We also computed the attainable efficiency gains of non-adaptive pooling schemes mathematically. Moreover, we measured the false-negative error rates in detecting the ORF1ab and N genes of the virus in RT-qPCR dilutions. Finally, we presented the efficiency gains of using our proposed pooling scheme on proof-of-concept pooled tests. We believe Smart Pooling will be efficient for optimizing massive testing of SARS-CoV-2.
| S-EPMC9020431 | biostudies-literature
Project description:We present new results concerning probability distributions of times in the coalescence tree and expected allele frequencies for coalescent with large sample size. The obtained results are based on computational methodologies, which involve combining coalescence time scale changes with techniques of integral transformations and using analytical formulae for infinite products. We show applications of the proposed methodologies for computing probability distributions of times in the coalescence tree and their limits, for evaluation of accuracy of approximate expressions for times in the coalescence tree and expected allele frequencies, and for analysis of large human mitochondrial DNA dataset.
| S-EPMC5295683 | biostudies-literature
Project description:Although host-guest pairing interactions between bisradical dicationic cyclobis(paraquat-p-phenylene) (BB2(˙+) ) and the bipyridinium radical cation (BIPY˙+ ) have been studied extensively, host molecules other than BB2(˙+) are few and far between. Herein, four bisradical dicationic cyclophanes with tunable cavity sizes are investigated as new bisradical dicationic hosts for accommodating the methyl viologen radical cation (MV˙+ ) to form trisradical tricationic complexes. The structure-property relationships between cavity sizes and binding affinities have been established by comprehensive solution and solid-state characterizations as well as DFT calculations. The association constants of the four new trisradical tricationic complexes are found to range between 7400 and 170 000 M-1, with the strongest one being 4.3 times higher than that for [MV⊂BB]3(˙+) . The facile accessibility and tunable stability of these new trisradical tricationic complexes make them attractive redox-controlled recognition motifs for further use in supramolecular chemistry and mechanostereochemistry.
| S-EPMC7012021 | biostudies-literature
Project description:A common non-pharmaceutical intervention (NPI) during the COVID-19 pandemic has been group size limits. Furthermore, educational settings of schools and universities have either fully closed or reduced their class sizes. As countries begin to reopen classrooms, a key question will be how large classes can be while still preventing local outbreaks of disease. Here, we develop and analyse a simple, stochastic epidemiological model where individuals (considered as students) live in fixed households and are assigned to a fixed class for daily lessons. We compare key measures of the epidemic-the peak infected, the total infected by day 180 and the calculated R 0-as the size of class is varied. We find that class sizes of 10 could largely restrict outbreaks and often had overlapping inter-quartile ranges with our most cautious case of classes of five. However, class sizes of 30 or more often result in large epidemics. Reducing the class size from 40 to 10 can reduce R 0 by over 30%, as well as significantly reducing the numbers infected. Intermediate class sizes show considerable variation, with the total infected varying by as much as from 10% to 80% for the same class size. We show that additional in-class NPIs can limit the epidemic still further, but that reducing class sizes appears to have a larger effect on the epidemic. We do not specifically tailor our model for COVID-19, but our results stress the importance of small class sizes for preventing large outbreaks of infectious disease.
| S-EPMC8206692 | biostudies-literature
Project description:Temporal variation in the detectability of a species can bias estimates of relative abundance if not handled correctly. For example, when effort varies in space and/or time it becomes necessary to take variation in detectability into account when data are analyzed. We demonstrate the importance of incorporating seasonality into the analysis of data with unequal sample sizes due to lost traps at a particular density of a species. A case study of count data was simulated using a spring-active carabid beetle. Traps were 'lost' randomly during high beetle activity in high abundance sites and during low beetle activity in low abundance sites. Five different models were fitted to datasets with different levels of loss. If sample sizes were unequal and a seasonality variable was not included in models that assumed the number of individuals was log-normally distributed, the models severely under- or overestimated the true effect size. Results did not improve when seasonality and number of trapping days were included in these models as offset terms, but only performed well when the response variable was specified as following a negative binomial distribution. Finally, if seasonal variation of a species is unknown, which is often the case, seasonality can be added as a free factor, resulting in well-performing negative binomial models. Based on these results we recommend (a) add sampling effort (number of trapping days in our example) to the models as an offset term, (b) if precise information is available on seasonal variation in detectability of a study object, add seasonality to the models as an offset term; (c) if information on seasonal variation in detectability is inadequate, add seasonality as a free factor; and (d) specify the response variable of count data as following a negative binomial or over-dispersed Poisson distribution.
| S-EPMC3401226 | biostudies-literature
Project description:Researchers often face the problem of needing to protect the privacy of subjects while also needing to integrate data that contains personal information from diverse data sources. The advent of computational social science and the enormous amount of data about people that is being collected makes protecting the privacy of research subjects ever more important. However, strict privacy procedures can hinder the process of joining diverse sources of data that contain information about specific individual behaviors. In this paper we present a procedure to keep information about specific individuals from being "leaked" or shared in either direction between two sources of data without need of a trusted third party. To achieve this goal, we randomly assign individuals to anonymous groups before combining the anonymized information between the two sources of data. We refer to this method as the Yahtzee procedure, and show that it performs as predicted by theoretical analysis when we apply it to data from Facebook and public voter records.
| S-EPMC3564933 | biostudies-literature
Project description:In response to the ever increasing threat of radiological and nuclear terrorism, active development of nontoxic new drugs and other countermeasures to protect against and/or mitigate adverse health effects of radiation is ongoing. Although the classical LD(50) study used for many decades as a first step in preclinical toxicity testing of new drugs has been largely replaced by experiments that use fewer animals, the need to evaluate the radioprotective efficacy of new drugs necessitates the conduct of traditional LD(50) comparative studies (FDA, 2002, Federal Register 67, 37988-37998). There is, however, no readily available method to determine the number of animals needed for establishing efficacy in these comparative potency studies. This article presents a sample-size formula based on Student's t for comparative potency testing. It is motivated by the U.S. Food and Drug Administration's (FDA's) requirements for robust efficacy data in the testing of response modifiers in total body irradiation experiments where human studies are not ethical or feasible. Monte Carlo simulation demonstrated the formula's performance for Student's t, Wald, and likelihood ratio tests in both logistic and probit models. Importantly, the results showed clear potential for justifying the use of substantially fewer animals than are customarily used in these studies. The present article may thus initiate a dialogue among researchers who use animals for radioprotection survival studies, institutional animal care and use committees, and drug regulatory bodies to reach a consensus on the number of animals needed to achieve statistically robust results for demonstrating efficacy of radioprotective drugs.
| S-EPMC3036987 | biostudies-other
Project description:Humpback dolphins (Sousa spp.) are obligate shallow-water and resident species, and they typically live in fission-fusion societies composed of small-sized groups with changeable membership. However, we have scant knowledge of their behavioral ecology, starting with potential factors influencing inter-population variability of their group sizes. Here, we compiled a new global dataset of humpback dolphin group sizes based on 150 published records. Our data indicated an inter-specific consistency of group-living strategy among the 4 species in the Sousa genus, as these species preferred living in small-sized groups with a mean size of mostly no more than 10, a minimum size of single individual or small pairs, and a maximum size of several tens or ≈100. In addition, we clearly showed the geographic variations in group sizes of humpback dolphins at a global scale. We found that the geographic variations in humpback dolphin group sizes were primarily associated with the latitude, sea surface temperature, and abundance. To conclude, our findings provide insights into social dynamics and socioecological trade-offs of humpback dolphins, and help better understand how these resident animals adapted to their shallow-water habitats from the perspectives of biogeography and socioecology.
| S-EPMC9291994 | biostudies-literature
Project description:Saturation is commonly used to determine sample sizes in qualitative research, yet there is little guidance on what influences saturation. We aimed to assess saturation and identify parameters to estimate sample sizes for focus group studies in advance of data collection. We used two approaches to assess saturation in data from 10 focus group discussions. Four focus groups were sufficient to identify a range of new issues (code saturation), but more groups were needed to fully understand these issues (meaning saturation). Group stratification influenced meaning saturation, whereby one focus group per stratum was needed to identify issues; two groups per stratum provided a more comprehensive understanding of issues, but more groups per stratum provided little additional benefit. We identify six parameters influencing saturation in focus group data: study purpose, type of codes, group stratification, number of groups per stratum, and type and degree of saturation.
| S-EPMC6635912 | biostudies-literature
Project description:Even though superresolution microscopy indicates that size of plasma membrane rafts is <20 nm, those structures have never been observed. Förster resonance energy transfer (FRET) is therefore still the most powerful optical method for characterization of such domains. In this letter we investigate relation between nanodomain affinity of a donor-acceptor (D/A) pair and the detectable nanodomain size/area. We show that probes with high affinity to the liquid-ordered (L(o)) phase are required for detecting domain sizes of a few nanometers, and/or domains that occupy a few percent of the bilayer area. A combination of donors and acceptors that prefer different phases is the more favorable approach. For instance, a D/A pair with the distribution constant of donors K(D) = 5 and acceptors K(A) = 0.01 can resolve a broad spectrum of nanodomain sizes. On the other hand, currently available donors and acceptors that prefer the same phase, either the liquid-disordered (L(d)) or L(o) phase, are not so convenient for determining domain sizes <20 nm. Here the detection limits of FRET experiments employing several commonly used D/A pairs have been investigated.
| S-EPMC3297789 | biostudies-literature