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IntroductionThe 2024 Voice AI Symposium, hosted by the Bridge2AI-Voice Consortium in Tampa, FL, featured two keynote speeches that addressed the intersection of voice AI, healthcare, ethics, and law. Dr. Rupal Patel and Dr. Nicholson Price provided insights into the advancements, applications, and challenges of AI-driven voice tools in healthcare. The symposium aimed to advance cross-disciplinary collaboration and establish frameworks for the ethical use of AI technologies in healthcare.MethodsThe keynote speeches, delivered on May 1st and 2nd, were 30 minutes each, followed by 10-minutes Q&A sessions. The audio was recorded and transcribed using Whisper (v7.13.1). Content summaries were generated with the aid of ChatGPT (v4.0), and the authors reviewed and edited the final transcripts to ensure accuracy and clarity.ResultsDr. Rupal Patel’s keynote, “Reflections and New Frontiers in Voice AI”, explored the potential of voice AI for early detection of health conditions, monitoring disease progression, and promoting non-invasive global health management. She highlighted innovative uses beyond traditional applications, such as examining menopause-related symptoms. Dr. Nicholson Price’s keynote, “Governance for Clinical Voice AI”, addressed the regulatory and ethical challenges posed by AI in healthcare. He stressed the need for context-aware systems and dynamic legal frameworks to address liability and accountability.ConclusionsThe 2024 Voice AI Symposium highlighted the transformative potential of voice AI for early detection, health monitoring, and reducing healthcare disparities. It also underscored the importance of dynamic governance to address the ethical and regulatory challenges of deploying AI in clinical settings.

IntroductionThe 2024 Voice AI Symposium, presented by the Bridge2AI-Voice Consortium, featured deep-dive educational workshops conducted by experts from diverse fields to explore the latest advancements in voice biomarkers and artificial intelligence (AI) applications in healthcare. Through five workshops, attendees learned about topics including international standardization of vocal biomarker data, real-world deployment of AI solutions, assistive technologies for voice disorders, best practices for voice data collection, and deep learning applications in voice analysis. These workshops aimed to foster collaboration between academia, industry, and healthcare to advance the development and implementation of voice-based AI tools.MethodsEach workshop featured a combination of lectures, case studies, and interactive discussions. Transcripts of audio recordings were generated using Whisper (Version 7.13.1) and summarized by ChatGPT (Version 4.0), then reviewed by the authors. The workshops covered various methodologies, from signal processing and machine learning operations (MLOps) to ethical concerns surrounding AI-powered voice data collection. Practical demonstrations of AI-driven tools for voice disorder management and technical discussions on implementing voice AI models in clinical and non-clinical settings provided attendees with hands-on experience.ResultsKey outcomes included the discussion of international standards to unify stakeholders in vocal biomarker research, practical challenges in deploying AI solutions outside the laboratory, review of Bridge2AI-Voice data collection processes, and the potential of AI to empower individuals with voice disorders. Additionally, presenters shared innovations in ethical AI practices, scalable machine learning frameworks, and advanced data collection techniques using diverse voice datasets. The symposium highlighted the successful integration of AI in detecting and analyzing voice signals for various health applications, with significant advancements in standardization, privacy, and clinical validation processes.DiscussionThe symposium underscored the importance of interdisciplinary collaboration to address the technical, ethical, and clinical challenges in the field of voice biomarkers. While AI models have shown promise in analyzing voice data, challenges such as data variability, security, and scalability remain. Future efforts must focus on refining data collection standards, advancing ethical AI practices, and ensuring diverse dataset inclusion to improve model robustness. By fostering collaboration among researchers, clinicians, and technologists, the symposium laid a foundation for future innovations in AI-driven voice analysis for healthcare diagnostics and treatment.

Woodland management is critical for ensuring forests are sustainably managed, yet few forest landowners have management plans and are often unsure of where to turn for advice. In New York State, the Master Forest Owner (MFO) Volunteer program provides free support from trained volunteers, however participation in the program has declined since 2012. To encourage engagement with the program, we pilot tested a message consisting of descriptive norm, benefit appeal, and individual self-frame via a direct mail campaign. Compared to a control message, requests for visits with MFOs increased from receiving the treatment message via a cost-effective postcard.

Monitoring population size at ecosystem scales is difficult for most species of conservation concern. While assessing site occupancy at broad scales has proven feasible, rigorous tracking of changes in population size over time has not – even though it can provide a stronger basis for assessing population status and conservation-decision making. Therefore, we demonstrate how relatively low-intensity, ecosystem-scale passive acoustic monitoring (PAM) can be linked to local-density monitoring to estimate the population size of native California spotted owls (Strix occidentalis occidentalis) and invasive barred owls (S. varia) across the western Sierra Nevada, California. Based on a PAM sampling grid with 400 ha cells (the approximate home range size of these species), we estimated site occupancy to be between 0.42 (SE = 0.02) and 0.30 (SE = 0.02) for California spotted owls using relatively liberal and strict criteria, respectively, for considering a cell occupied. PAM-based site occupancy estimates within local-scale density monitoring study areas (range = 0.41–0.78 and 0.28–0.76 for liberal and strict criteria, respectively) were strongly and positively correlated with local density (range = 0.08–0.31 owl/km2) for this species. In contrast, ecosystem-wide site occupancy of barred owls was very low based on PAM (0.034, SE

The leafminers on gymnosperms receive much less attention than those on either angiosperms or ferns. Given the distinctly different leaf shape and leaf venation found in gymnosperms, they would be expected to host significantly different leafminer groups. Very few comprehensive reports on gymnosperm-feeding leafminers have been presented.Based on the well-studied fauna in North America and Europe, we compiled a list of 133 species, 30 genera and 13 families of gymnosperm-feeding leafminers. The gymnosperm-mining families (in descending order of leafminer number) included Tortricidae, Gelechiidae, Argyresthiidae, Yponomeutidae, Batrachedridae, Pyralidae, Adelidae, Agromyzidae, Blastobasidae, Bucculatricidae, Coleophoridae, Curculionidae and Noctuidae. There were 109 species, 22 genera and ten families in North America and 34 species, 19 genera and nine families in Europe. We compiled a list of 102 species and 16 genera of host plants, belonging to four families: Pinaceae, Cupressaceae, Taxaceae and Zamiaceae. There were 84 host species, 15 genera and three host families in North America and 46 host species, ten genera and three host families in Europe. Dominant gymnosperm-mining families and dominant host families were generally the same in the two continents.

This paper examines the feasibility of developing a new Master Volunteer training program to help communities adapt to and mitigate the impacts of climate change. Traditional models of volunteer training programs, such as the Cooperative Extension Master Volunteer peer-to-peer learning model, are based in part on Diffusion Theory. The existing model of education could provide a useful base upon which to develop a volunteer training program about climate change but requires more depth. Data were collected using a mixed-method approach, consisting of focus groups and a survey among key stakeholders associated with the Cooperative Extension Service in the Northeastern United States. The results demonstrate the need for a climate change Extension volunteer training program, one that extends beyond the traditional deficit model of information sharing and is developed with a comprehensive theoretical approach to climate change education that focuses on collective action, as opposed to individual action. Based on emergent themes, this paper presents a theoretical framework for a new volunteer training program based on Social Practice, Sense of Community, and Self-efficacy theories. The proposed program could be successful, provided it encompasses a learning model that fosters social practices, feelings of a sense of community, and builds self-efficacy.

PurposeOnly one chemical class of topoisomerase I (TOP1) inhibitors is FDA approved, the camptothecins with irinotecan and topotecan widely used. Because of their limitations (chemical instability, drug efflux-mediated resistance, and diarrhea), novel TOP1 inhibitors are warranted. Indenoisoquinoline non-camptothecin topoisomerase I (TOP1) inhibitors overcome chemical instability and drug resistance that limit camptothecin use. Three indenoisoquinolines, LMP400 (indotecan), LMP776 (indimitecan), and LMP744, were examined in a phase I study for lymphoma-bearing dogs to evaluate differential efficacy, pharmacodynamics, toxicology, and pharmacokinetics.Experimental designEighty-four client-owned dogs with lymphomas were enrolled in dose-escalation cohorts for each indenoisoquinoline, with an expansion phase for LMP744. Efficacy, tolerability, pharmacokinetics, and target engagement were determined.ResultsThe MTDs were 17.5 mg/m2 for LMP 776 and 100 mg/m2 for LMP744; bone marrow toxicity was dose-limiting; up to 65 mg/m2 LMP400 was well-tolerated and MTD was not reached. None of the drugs induced notable diarrhea. Sustained tumor accumulation was observed for LMP744; γH2AX induction was demonstrated in tumors 2 and 6 hours after treatment; a decrease in TOP1 protein was observed in most lymphoma samples across all compounds and dose levels, which is consistent with the fact that tumor response was also observed at low doses LMP744. Objective responses were documented for all indenoisoquinolines; efficacy (13/19 dogs) was greatest for LMP744.ConclusionsThese results demonstrate proof-of-mechanism for indenoisoquinoline TOP1 inhibitors supporting their further clinical development. They also highlight the value of the NCI Comparative Oncology Program (https://ccr.cancer.gov/Comparative-Oncology-Program) for evaluating novel therapies in immunocompetent pets with cancers.

Hedgehog signaling is essential for bone formation. Here, the authors show that the transmembrane protein SLITRK5 is a negative regulator of hedgehog signaling in osteoblasts, suggesting it may be a potential therapeutic target to enhance bone formation.

Febrile seizures are the most common seizure disorder in childhood. Most febrile seizures have a benign course and children have a good prognosis. However, febrile seizures are traumatizing events for a child's family or caregiver to witness. Appropriate caregiver education is crucial to ease anxiety. This article reviews the risk factors, clinical presentation, diagnostics, treatment, and prevention of febrile seizures in addition to providing a guideline for effective caregiver education and support. [ABSTRACT FROM AUTHOR]