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Consumption of contaminated food, especially seafood, is a key source of human perfluoroalkyl and polyfluoroalkyl substances (PFAS) exposure. Here, we examine the occurrence of PFAS in shiner surfperch (Cymatogaster aggregata), striped bass (Morone saxatilis), white croaker (Genyonemus lineatus), and seven other sport fish from San Francisco Bay, California, U.S. over a decade of monitoring to assess the potential risks from dietary exposures. In fish collected in 2009, 2014, and 2019, perfluorooctanesulfonic acid (PFOS) was predominantly detected at levels exceeding PFOS consumption advisory thresholds established in other U.S. states. The southern regions of San Francisco Bay have been especially impacted, with over 80% of samples above the strictest U.S. PFOS consumption advisory threshold set in Massachusetts (for one eight-ounce serving a week) at 3.5 ng/g (detected range: 2.0-18 ng/g ww) compared to only 8% in the other subembayments (detected range: 0.59-8.5 ng/g ww). An additional 19 PFAS were detected, with particularly elevated levels of 7:3 fluorotelomer carboxylic acid (7:3 FTCA) found in several species and sites, representing the first observations in marine fish globally. These findings indicate the need to consider a wider range of PFAS in assessing dietary exposure risks and environmental impacts.
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http://dx.doi.org/10.1021/acsestwater.4c00999 | DOI Listing |
JMIR Hum Factors
September 2025
Department of Community Health Systems, University of California, San Francisco, School of Nursing, San Francisco, CA, United States.
Background: The COVID-19 pandemic forced the world to quarantine to slow the rate of transmission, causing communities to transition into virtual spaces. Asian American and Pacific Islander communities faced the additional challenge of discrimination that stemmed from racist and xenophobic rhetoric in the media. Limited data exist on technology use among Asian American and Pacific Islander adults during the height of the COVID-19 shelter-in-place period and its effect on their physical and mental health.
View Article and Find Full Text PDFJAMA Cardiol
September 2025
Department of Medicine, Cardiovascular Medicine, Stanford University, Stanford, California.
Importance: Consumer wearable technologies have wide applications, including some that have US Food and Drug Administration clearance for health-related notifications. While wearable technologies may have premarket testing, validation, and safety evaluation as part of a regulatory authorization process, information on their postmarket use remains limited. The Stanford Center for Digital Health organized 2 pan-stakeholder think tank meetings to develop an organizing concept for empirical research on the postmarket evaluation of consumer-facing wearables.
View Article and Find Full Text PDFJAMA Psychiatry
September 2025
Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville.
Importance: Behavioral variant frontotemporal dementia (bvFTD), the most common subtype of FTD, is a leading form of early-onset dementia worldwide. Accurate and timely diagnosis of bvFTD is frequently delayed due to symptoms overlapping with common psychiatric disorders, and interest has increased in identifying biomarkers that may aid in differentiating bvFTD from psychiatric disorders.
Objective: To summarize and critically review studies examining whether neurofilament light chain (NfL) in cerebrospinal fluid (CSF) or blood is a viable aid in the differential diagnosis of bvFTD vs psychiatric disorders.
mBio
September 2025
Department of Microbiology and Immunology, University of California San Francisco, San Francisco, California, USA.
The human fungal pathogen changes its morphology in response to temperature. At 37°C, it grows as a budding yeast, whereas at room temperature (RT), it transitions to hyphal growth. Prior work has demonstrated that 15-20% of transcripts are temperature-regulated, and that transcription factors (TFs) Ryp1-4 are necessary to establish yeast growth.
View Article and Find Full Text PDFInt J Surg
September 2025
Department of Human Structure and Repair, Ghent University Faculty of Medicine, Belgium.
Background: Staging laparoscopy (SL) is an essential procedure for peritoneal metastasis (PM) detection. Although surgeons are expected to differentiate between benign and malignant lesions intraoperatively, this task remains difficult and error-prone. The aim of this study was to develop a novel multimodal machine learning (MML) model to differentiate PM from benign lesions by integrating morphologic characteristics with intraoperative SL images.
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