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1.
Phys Med Biol ; 69(11)2024 May 20.
Article in English | MEDLINE | ID: mdl-38631364

ABSTRACT

Cortical bone is characterized by a dense solid matrix permeated by fluid-filled pores. Ultrasound scattering has potential for the non-invasive evaluation of changes in bone porosity. However, there is an incomplete understanding of the impact of ultrasonic absorption in the solid matrix on ultrasound scattering. In this study, maps were derived from scanning acoustic microscopy images of human femur cross-sections. Finite-difference time domain ultrasound scatter simulations were conducted on these maps. Pore density, diameter distribution of the pores, and nominal absorption values in the solid and fluid matrices were controlled. Ultrasound pulses with a central frequency of 8.2 MHz were propagated, both in through-transmission and backscattering configurations. From these data, the scattering, bone matrix absorption, and attenuation extinction lengths were calculated. The results demonstrated that as absorption in the solid matrix was varied, the scattering, absorption, and attenuation extinction lengths were significantly impacted. It was shown that for lower values of absorption in the solid matrix (less than 2 dB mm-1), attenuation due to scattering dominates, whereas at higher values of absorption (more than 2 dB mm-1), attenuation due to absorption dominates. This will impact how ultrasound attenuation and scattering parameters can be used to extract quantitative information on bone microstructure.


Subject(s)
Cortical Bone , Scattering, Radiation , Cortical Bone/diagnostic imaging , Humans , Ultrasonic Waves , Ultrasonography/methods , Bone Matrix/metabolism , Bone Matrix/diagnostic imaging , Femur/diagnostic imaging
2.
Preprint in English | bioRxiv | ID: ppbiorxiv-478759

ABSTRACT

Accurate, high-resolution environmental monitoring of SARS-CoV-2 traces indoors through sentinel cards is a promising approach to help students safely return to in-person learning. Because SARS-CoV-2 RNA can persist for up to a week on several indoor surface types, there is a need for increased temporal resolution to determine whether consecutive surface positives arise from new infection events or continue to report past events. Cleaning sentinel cards after sampling would provide the needed resolution, but might interfere with assay performance. We tested the effect of three cleaning solutions (BZK wipes, wet wipes, RNase Away) at three different viral loads: "high" (4 x 104 GE/mL), "medium" (1 x 104 GE/mL), and "low" (2.5 x 103 GE/mL). RNAse Away, chosen as a positive control, was the most effective cleaning solution on all three viral loads. Wet wipes were found to be more effective than BZK wipes in the medium viral load condition. The low viral load condition was easily reset with all three cleaning solutions. These findings will enable temporal SARS-CoV-2 monitoring in indoor environments where transmission risk of the virus is high and the need to avoid individual-level sampling for privacy or compliance reasons exists. ImportanceBecause SARS-CoV-2, the virus that causes COVID-19, persists on surfaces, testing swabs taken from surfaces is useful as a monitoring tool. This approach is especially valuable in school settings, where there are cost and privacy concerns that are eliminated by taking a single sample from a classroom. However, the virus persists for days to weeks on surface samples, so it is impossible to tell whether positive detection events on consecutive days are persistent signal or new infectious cases, and therefore whether the positive individuals have been successfully removed from the classroom. We compare several methods for cleaning "sentinel cards" to show that this approach can be used to identify new SARS-CoV-2 signals day to day. The results are important for determining how to monitor classrooms and other indoor environments for SARS-CoV-2 virus.

3.
Smruthi Karthikeyan; Joshua I Levy; Peter De Hoff; Greg Humphrey; Amanda Birmingham; Kristen Jepsen; Sawyer Farmer; Helena M. Tubb; Tommy Valles; Caitlin E Tribelhorn; Rebecca Tsai; Stefan Aigner; Shashank Sathe; Niema Moshiri; Benjamin Henson; Abbas Hakim; Nathan A Baer; Tom Barber; Pedro Belda-Ferre; Marisol Chacon; Willi Cheung; Evelyn S Crescini; Emily R Eisner; Alma L Lastrella; Elijah S Lawrence; Clarisse A Marotz; Toan T Ngo; Tyler Ostrander; Ashley Plascencia; Rodolfo A Salido; Phoebe Seaver; Elizabeth W Smoot; Daniel McDonald; Robert M Neuhard; Angela L Scioscia; Alysson M. Satterlund; Elizabeth H Simmons; Dismas B. Abelman; David Brenner; Judith Carbone Bruner; Anne Buckley; Michael Ellison; Jeffrey Gattas; Steven L Gonias; Matt Hale; Faith Kirkham Hawkins; Lydia Ikeda; Hemlata Jhaveri; Ted Johnson; Vince Kellen; Brendan Kremer; Gary C. Matthews; Ronald McLawhon; Pierre Ouillet; Daniel Park; Allorah Pradenas; Sharon Reed; Lindsay Riggs; Alison M. Sanders; Bradley Sollenberger; Angela Song; Benjamin White; Terri Winbush; Christine M Aceves; Catelyn Anderson; Karthik Gangavarapu; Emory Hufbauer; Ezra Kurzban; Justin Lee; Nathaniel L Matteson; Edyth Parker; Sarah A Perkins; Karthik S Ramesh; Refugio Robles-Sikisaka; Madison A Schwab; Emily Spencer; Shirlee Wohl; Laura Nicholson; Ian H Mchardy; David P Dimmock; Charlotte A Hobbs; Omid Bakhtar; Aaron Harding; Art Mendoza; Alexandre Bolze; David Becker; Elizabeth T Cirulli; Magnus Isaksson; Kelly M Schiabor Barrett; Nicole L Washington; John D Malone; Ashleigh Murphy Schafer; Nikos Gurfield; Sarah Stous; Rebecca Fielding-Miller; Tommi Gaines; Richard Garfein; Cheryl A. M. Anderson; Natasha K. Martin; Robert T Schooley; Brett Austin; Duncan R. MacCannell; Stephen F Kingsmore; William Lee; Seema Shah; Eric McDonald; Alexander T. Yu; Mark Zeller; Kathleen M Fisch; Christopher A. Longhurst; Patty Maysent; David Pride; Pradeep K. Khosla; Louise C Laurent; Gene W Yeo; Kristian G Andersen; Rob Knight.
Preprint in English | medRxiv | ID: ppmedrxiv-21268143

ABSTRACT

As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing/sequencing capacity, which can also introduce biases. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here, we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We develop and deploy improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detect emerging variants of concern up to 14 days earlier in wastewater samples, and identify multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.

4.
Preprint in English | medRxiv | ID: ppmedrxiv-21251159

ABSTRACT

As of January of 2021, the highly transmissible B.1.1.7 variant of SARS-CoV-2, which was first identified in the United Kingdom (U.K.), has gained a strong foothold across the world. Because of the sudden and rapid rise of B.1.1.7, we investigated the prevalence and growth dynamics of this variant in the United States (U.S.), tracking it back to its early emergence and onward local transmission. We found that the RT-qPCR testing anomaly of S gene target failure (SGTF), first observed in the U.K., was a reliable proxy for B.1.1.7 detection. We sequenced 212 B.1.1.7 SARS-CoV-2 genomes collected from testing facilities in the U.S. from December 2020 to January 2021. We found that while the fraction of B.1.1.7 among SGTF samples varied by state, detection of the variant increased at a logistic rate similar to those observed elsewhere, with a doubling rate of a little over a week and an increased transmission rate of 35-45%. By performing time-aware Bayesian phylodynamic analyses, we revealed several independent introductions of B.1.1.7 into the U.S. as early as late November 2020, with onward community transmission enabling the variant to spread to at least 30 states as of January 2021. Our study shows that the U.S. is on a similar trajectory as other countries where B.1.1.7 rapidly became the dominant SARS-CoV-2 variant, requiring immediate and decisive action to minimize COVID-19 morbidity and mortality.

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