Real-time label-free detection of dynamic aptamer-small molecule interactions using a nanopore nucleic acid conformational sensor.

Nucleic acids can undergo conformational changes upon binding small molecules. These conformational changes can be exploited to develop new therapeutic strategies through control of gene expression or triggering of cellular responses and can also be used to develop sensors for small molecules such as neurotransmitters. Many analytical approaches can detect dynamic conformational change of nucleic acids, but they need labeling, are expensive, and have limited time resolution. The nanopore approach can provide a conformational snapshot for each nucleic acid molecule detected, but has not been reported to detect dynamic nucleic acid conformational change in response to small -molecule binding. Here we demonstrate a modular, label-free, nucleic acid-docked nanopore capable of revealing time-resolved, small molecule-induced, single nucleic acid molecule conformational transitions with millisecond resolution. By using the dopamine-, serotonin-, and theophylline-binding aptamers as testbeds, we found that these nucleic acids scaffolds can be noncovalently docked inside the MspA protein pore by a cluster of site-specific charged residues. This docking mechanism enables the ion current through the pore to characteristically vary as the aptamer undergoes conformational changes, resulting in a sequence of current fluctuations that report binding and release of single ligand molecules from the aptamer. This nanopore tool can quantify specific ligands such as neurotransmitters, elucidate nucleic acid-ligand interactions, and pinpoint the nucleic acid motifs for ligand binding, showing the potential for small molecule biosensing, drug discovery assayed via RNA and DNA conformational changes, and the design of artificial riboswitch effectors in synthetic biology.

Estimated Effectiveness of JYNNEOS Vaccine in Preventing Mpox: A Multijurisdictional Case-Control Study - United States, August 19, 2022-March 31, 2023.

As of March 31, 2023, more than 30,000 monkeypox (mpox) cases had been reported in the United States in an outbreak that has disproportionately affected gay, bisexual, and other men who have sex with men (MSM) and transgender persons (1). JYNNEOS vaccine (Modified Vaccinia Ankara vaccine, Bavarian Nordic) was approved by the Food and Drug Administration (FDA) in 2019 for the prevention of smallpox and mpox via subcutaneous injection as a 2-dose series (0.5 mL per dose, administered 4 weeks apart) (2). To expand vaccine access, an Emergency Use Authorization was issued by FDA on August 9, 2022, for dose-sparing intradermal injection of JYNNEOS as a 2-dose series (0.1 mL per dose, administered 4 weeks apart) (3). Vaccination was available to persons with known or presumed exposure to a person with mpox (postexposure prophylaxis [PEP]), as well as persons at increased risk for mpox or who might benefit from vaccination (preexposure mpox prophylaxis [PrEP]) (4). Because information on JYNNEOS vaccine effectiveness (VE) is limited, a matched case-control study was conducted in 12 U.S. jurisdictions,† including nine Emerging Infections Program sites and three Epidemiology and Laboratory Capacity sites,§ to evaluate VE against mpox among MSM and transgender adults aged 18-49 years. During August 19, 2022-March 31, 2023, a total of 309 case-patients were matched to 608 control patients. Adjusted VE was 75.2% (95% CI = 61.2% to 84.2%) for partial vaccination (1 dose) and 85.9% (95% CI = 73.8% to 92.4%) for full vaccination (2 doses). Adjusted VE for full vaccination by subcutaneous, intradermal, and heterologous routes of administration was 88.9% (95% CI = 56.0% to 97.2%), 80.3% (95% CI = 22.9% to 95.0%), and 86.9% (95% CI = 69.1% to 94.5%), respectively. Adjusted VE for full vaccination among immunocompromised participants was 70.2% (95% CI = -37.9% to 93.6%) and among immunocompetent participants was 87.8% (95% CI = 57.5% to 96.5%). JYNNEOS is effective at reducing the risk for mpox. Because duration of protection of 1 versus 2 doses remains unknown, persons at increased risk for mpox exposure should receive the 2-dose series as recommended by the Advisory Committee on Immunization Practices (ACIP),¶ regardless of administration route or immunocompromise status.

Lessons From the First Decade of the Native American Summer Research Internship at the University of Utah.

PROBLEM: American Indian/Alaska Native (AI/AN) populations are facing multiple health crises, including limited access to care, high rates of chronic disease, and early mortality that is far worse than other underrepresented minorities in the United States. According to the Association of American Indian Physicians, AI/AN people represent 2.0% of the U.S. population but only 0.2% of medical students and 0.1% of full-time faculty at MD-granting institutions. Increasing the number of AI/AN clinicians and scientists is one strategy to improve health outcomes in the AI/AN population and address these crises. APPROACH: In 2010, the University of Utah partnered with research, cultural, and professional mentors to create a 10-week summer Native American Research Internship (NARI) program for AI/AN college students across the United States who are interested in pursuing biomedical careers. NARI attracts and supports AI/AN students by offering mentored summer research internships in an innovative, culturally aware framework that adapts to observed challenges to optimize educational experiences and support biomedical career aspirations. OUTCOMES: During the first decade of the NARI program, 128 students from 22 U.S. states, representing 46 tribal nations and 57 colleges and universities, participated. Of those 128 students, 113 (88%) have completed a bachelor's degree and the remaining 15 (12%) are currently working toward a bachelor's degree. No NARI student has dropped out of college. Twenty-six (20%) NARI alumni have matriculated to medical school and 30 (23%) to graduate school. Eight (6%) participants have completed medical school, and 3 (2%) are pursuing a PhD in science. An additional 36 (28%) have gained employment in biomedical research fields. NEXT STEPS: The NARI program has increased the participation of AI/AN students in medicine and the biomedical sciences. The innovative, culturally aware, and adaptive framework is a model for other programs for AI/AN students and students in other underrepresented communities.

Reproducibility and Prognosis of Quantitative Features Extracted from CT Images.

We study the reproducibility of quantitative imaging features that are used to describe tumor shape, size, and texture from computed tomography (CT) scans of non-small cell lung cancer (NSCLC). CT images are dependent on various scanning factors. We focus on characterizing image features that are reproducible in the presence of variations due to patient factors and segmentation methods. Thirty-two NSCLC nonenhanced lung CT scans were obtained from the Reference Image Database to Evaluate Response data set. The tumors were segmented using both manual (radiologist expert) and ensemble (software-automated) methods. A set of features (219 three-dimensional and 110 two-dimensional) was computed, and quantitative image features were statistically filtered to identify a subset of reproducible and nonredundant features. The variability in the repeated experiment was measured by the test-retest concordance correlation coefficient (CCCTreT). The natural range in the features, normalized to variance, was measured by the dynamic range (DR). In this study, there were 29 features across segmentation methods found with CCCTreT and DR ≥ 0.9 and R(2) Bet ≥ 0.95. These reproducible features were tested for predicting radiologist prognostic score; some texture features (run-length and Laws kernels) had an area under the curve of 0.9. The representative features were tested for their prognostic capabilities using an independent NSCLC data set (59 lung adenocarcinomas), where one of the texture features, run-length gray-level nonuniformity, was statistically significant in separating the samples into survival groups (P ≤ .046).