More Like this

1. Semi‐quantitative group testing for efficient and accurate qPCR screening of pathogens with a wide range of loads

   Nambiar, Ananthan; Pan, Chao; Rana, Vishal; Cheraghchi, Mahdi; Ribeiro, Joao; Maslov, Sergei; Milenkovic, Olgica (May 2024, BMC bioinformatics)

   Abstract Background: Results: To address these issues, we introduce a novel adaptive semi-quantitative group testing (SQGT) scheme to e ciently screen populations via two-stage qPCR testing. The SQGT method quantizes cycle threshold (Ct) values into multiple bins, leveraging the information from the rst stage of screening to improve the detection sensitivity. Dynamic Ct threshold adjustments mitigate dilution e ects and enhance test accuracy. Comparisons with traditional binary outcome GT methods show that SQGT reduces the number of tests by 24% on the only complete real-world qPCR group testing dataset from Israel, while maintaining a negligible false negative rate. Conclusion: In conclusion, our adaptive SQGT approach, utilizing qPCR data and dynamic threshold adjustments, o ers a promising solution for e cient population screening. With a reduction in the number of tests and minimal false negatives, SQGT holds potential to enhance disease control and testing strategies on a global scale. Keywords: Group testing, Pooled testing, Semiquantitative group testing, qPCR, Ct values, Viral load, COVID-19 

   more » « less
2. Array testing for multiplex assays

   https://doi.org/10.1093/biostatistics/kxy058  

   Hou, Peijie; Tebbs, Joshua M; Wang, Dewei; McMahan, Christopher S; Bilder, Christopher R (October 2018, Biostatistics)

   null (Ed.)

   Summary Group testing involves pooling individual specimens (e.g., blood, urine, swabs, etc.) and testing the pools for the presence of disease. When the proportion of diseased individuals is small, group testing can greatly reduce the number of tests needed to screen a population. Statistical research in group testing has traditionally focused on applications for a single disease. However, blood service organizations and large-scale disease surveillance programs are increasingly moving towards the use of multiplex assays, which measure multiple disease biomarkers at once. Tebbs and others (2013, Two-stage hierarchical group testing for multiple infections with application to the Infertility Prevention Project. Biometrics69, 1064–1073) and Hou and others (2017, Hierarchical group testing for multiple infections. Biometrics73, 656–665) were the first to examine hierarchical group testing case identification procedures for multiple diseases. In this article, we propose new non-hierarchical procedures which utilize two-dimensional arrays. We derive closed-form expressions for the expected number of tests per individual and classification accuracy probabilities and show that array testing can be more efficient than hierarchical procedures when screening individuals for multiple diseases at once. We illustrate the potential of using array testing in the detection of chlamydia and gonorrhea for a statewide screening program in Iowa. Finally, we describe an R/Shiny application that will help practitioners identify the best multiple-disease case identification algorithm. 

   more » « less
3. Spatial Gradients of Quantitative MRI as Biomarkers for Early Detection of Osteoarthritis: Data From Human Explants and the Osteoarthritis Initiative

   https://doi.org/10.1002/jmri.28471  

   Wilson, Robert L.; Emery, Nancy C.; Pierce, David M.; Neu, Corey P. (October 2022, Journal of Magnetic Resonance Imaging)

   BackgroundHealthy articular cartilage presents structural gradients defined by distinct zonal patterns through the thickness, which may be disrupted in the pathogenesis of several disorders. Analysis of textural patterns using quantitative MRI data may identify structural gradients of healthy or degenerating tissue that correlate with early osteoarthritis (OA). PurposeTo quantify spatial gradients and patterns in MRI data, and to probe new candidate biomarkers for early severity of OA. Study TypeRetrospective study. SubjectsFourteen volunteers receiving total knee replacement surgery (eight males/two females/four unknown, average age ± standard deviation: 68.1 ± 9.6 years) and 10 patients from the OA Initiative (OAI) with radiographic OA onset (two males/eight females, average age ± standard deviation: 57.7 ± 9.4 years; initial Kellgren‐Lawrence [KL] grade: 0; final KL grade: 3 over the 10‐year study). Field Strength/Sequence3.0‐T and 14.1‐T, biomechanics‐based displacement‐encoded imaging, fast spin echo, multi‐slice multi‐echoT2mapping. AssessmentWe studied structure and strain in cartilage explants from volunteers receiving total knee replacement, or structure in cartilage of OAI patients with progressive OA. We calculated spatial gradients of quantitative MRI measures (eg, T2) normal to the cartilage surface to enhance zonal variations. We compared gradient values against histologically OA severity, conventional relaxometry, and/or KL grades. Statistical TestsMultiparametric linear regression for evaluation of the relationship between residuals of the mixed effects models and histologically determined OA severity scoring, with a significance threshold atα = 0.05. ResultsGradients of individual relaxometry and biomechanics measures significantly correlated with OA severity, outperforming conventional relaxometry and strain metrics. In human explants, analysis of spatial gradients provided the strongest relationship to OA severity (R² = 0.627). Spatial gradients of T2 from OAI data identified variations in radiographic (KL Grade 2) OA severity in single subjects, while conventional T2 alone did not. Data ConclusionSpatial gradients of quantitative MRI data may improve the predictive power of noninvasive imaging for early‐stage degeneration. Evidence Level1 Technical EfficacyStage 1 

   more » « less
4. Quantitatively assessing the impact of the quality of SNOMED CT subtype hierarchy on cohort queries

   https://doi.org/10.1093/jamia/ocae272  

   Hao, Xubing; Li, Xiaojin; Huang, Yan; Shi, Jay; Abeysinghe, Rashmie; Tao, Cui; Roberts, Kirk; Zhang, Guo-Qiang; Cui, Licong (November 2024, Journal of the American Medical Informatics Association)

   Abstract ObjectiveSNOMED CT provides a standardized terminology for clinical concepts, allowing cohort queries over heterogeneous clinical data including Electronic Health Records (EHRs). While it is intuitive that missing and inaccurate subtype (or is-a) relations in SNOMED CT reduce the recall and precision of cohort queries, the extent of these impacts has not been formally assessed. This study fills this gap by developing quantitative metrics to measure these impacts and performing statistical analysis on their significance. Material and MethodsWe used the Optum de-identified COVID-19 Electronic Health Record dataset. We defined micro-averaged and macro-averaged recall and precision metrics to assess the impact of missing and inaccurate is-a relations on cohort queries. Both practical and simulated analyses were performed. Practical analyses involved 407 missing and 48 inaccurate is-a relations confirmed by domain experts, with statistical testing using Wilcoxon signed-rank tests. Simulated analyses used two random sets of 400 is-a relations to simulate missing and inaccurate is-a relations. ResultsWilcoxon signed-rank tests from both practical and simulated analyses (P-values < .001) showed that missing is-a relations significantly reduced the micro- and macro-averaged recall, and inaccurate is-a relations significantly reduced the micro- and macro-averaged precision. DiscussionThe introduced impact metrics can assist SNOMED CT maintainers in prioritizing critical hierarchical defects for quality enhancement. These metrics are generally applicable for assessing the quality impact of a terminology’s subtype hierarchy on its cohort query applications. ConclusionOur results indicate a significant impact of missing and inaccurate is-a relations in SNOMED CT on the recall and precision of cohort queries. Our work highlights the importance of high-quality terminology hierarchy for cohort queries over EHR data and provides valuable insights for prioritizing quality improvements of SNOMED CT's hierarchy. 

   more » « less
5. Early detection of Pseudocapillaria tomentosa by qPCR in four lines of zebrafish, Danio rerio (Hamilton 1882)

   https://doi.org/10.1111/jfd.13773  

   Schuster, Corbin J.; Leong, Connor; Kasschau, Kristin D.; Sharpton, Thomas J.; Kent, Michael L. (February 2023, Journal of Fish Diseases)

   Abstract The intestinal nematodePseudocapillaria tomentosain zebrafish (Danio rerio) causes profound intestinal lesions, emaciation and death and is a promoter of a common intestinal cancer in zebrafish. This nematode has been detected in zebrafish from about 15% of the laboratories. Adult worms are readily detected about 3 weeks after exposure by either histology or wet mount preparations of the intestine, and larval worms are inconsistently observed in fish before this time. A quantitative PCR (qPCR) test was recently developed to detect the worm in fish and water, and here we determined that the test on zebrafish intestines was effective for earlier detection. Four lines of zebrafish (AB, TU, 5D and Casper) were experimentally infected and evaluated by wet mounts and qPCR at 8, 15‐, 22‐, 31‐ and 44‐day post‐exposure (dpe). At the first two time points, only 8% of the wet mounts from exposed fish were identified as infected, while the same intestines screened by qPCR showed 78% positivity, with low and consistent cycle threshold (Ct) values at these times. Wet mounts at later time points showed a high prevalence of infection, but this was still surpassed by qPCR. 

   more » « less