Publications by authors named "S Poland"

Purpose: Previous studies document underuse of next-generation sequencing (NGS). We examined the impact to oncology care for veterans of incorporating NGS ordering into the Veterans Affairs (VA) electronic medical record (EMR) at two New York City VA Medical Centers.

Methods: We identified patients with non-small cell lung cancer and prostate cancer with oncology clinic visits and NGS testing indications between January and December 2021.

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We report the development of a novel line-scanning microscope capable of acquiring high-speed time-correlated single-photon counting (TCSPC)-based fluorescence lifetime imaging microscopy (FLIM) imaging. The system consists of a laser-line focus, which is optically conjugated to a 1024 × 8 single-photon avalanche diode (SPAD)-based line-imaging complementary metal-oxide semiconductor (CMOS), with 23.78 µm pixel pitch at 49.

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Background: Studies conducted in the United States such as the National Survey of Family Growth (NSFG) and the Pregnancy Risk Assessment Monitoring System (PRAMS) collect data on pregnancy intentions to aid in improving health education, services, and programs. PRAMS collects data from specific sites, and NSFG is a national household-based survey. Like NSFG, the Surveys of Women was designed to survey participants residing in households using an address-based sample and a multimode data collection approach.

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Cell migration is important for development and its aberrant regulation contributes to many diseases. The Scar/WAVE complex is essential for Arp2/3 mediated lamellipodia formation during mesenchymal cell migration and several coinciding signals activate it. However, so far, no direct negative regulators are known.

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Article Synopsis
  • EUS-guided needle-based confocal laser endomicroscopy (EUS-nCLE) can help identify high-grade dysplasia/adenocarcinoma (HGD-Ca) in intraductal papillary mucinous neoplasms (IPMNs), but traditionally requires manual analysis.
  • Researchers developed two computer-aided diagnosis (CAD) algorithms using convolutional neural networks (CNNs) to automate and improve the accuracy of IPMN diagnosis and risk assessment.
  • The study showed that these CNN-CAD algorithms outperformed established guidelines in sensitivity and accuracy for detecting HGD-Ca, indicating their potential for real-time clinical application with future enhancements.
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