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This study delves into the potential use of large language models (LLMs) for generating Library of Congress subject headings. The authors employed ChatGPT to generate subject headings for electronic theses and dissertations (ETDs) based on their titles and abstracts. The results suggest that LLMs such as ChatGPT have the potential to reduce the cataloging time needed for assigning subject terms from Library of Congress Subject Headings (LCSH) for ETDs as well as to improve the discovery of this type of resource in academic libraries. Nonetheless, human catalogers remain essential for verifying and enhancing the validity, exhaustivity, and specificity of Library of Congress subject headings generated by LLMs. [ABSTRACT FROM AUTHOR]

Transitive inference (TI) has a long history in the study of human development. There have, however, few pediatric studies that report clinical diagnoses have tested trial-and-error TI learning, in which participants infer item relations, rather than evaluate them explicitly from verbal descriptions. Children aged 8-10 underwent a battery of clinical assessments and received a range of diagnoses, potentially including autism spectrum disorder (ASD), attention-deficit hyperactive disorder (ADHD), anxiety disorders (AD), specific learning disorders (SLD), and/or communication disorders (CD). Participants also performed a trial-and-error learning task that tested for TI. Response accuracy and reaction time were assessed using a statistical model that controlled for diagnostic comorbidity at the group level. Participants in all diagnostic categories showed evidence of TI. However, a model comparison analysis suggested that those diagnosed with ASD succeeded in a qualitatively different way, responding more slowly to each choice and improving faster across trials than their non-ASD counterparts. Additionally, TI performance was not associated with IQ. Overall, our data suggest that superficially similar performance levels between ASD and non-ASD participants may have resulted from a difference in the speed-accuracy tradeoff made by each group. Our work provides a preliminary profile of the impact of various clinical diagnoses on TI performance in young children. Of these, an ASD diagnosis resulted in the largest difference in task strategy., (© 2024 International Society for Autism Research and Wiley Periodicals LLC.)

Objective: To compare the performance of 1D and 3D tumor response assessment for predicting median overall survival (mOS) in patients who underwent immunotherapy for hepatocellular carcinoma (HCC)., Methods: Patients with HCC who underwent immunotherapy between 2017 and 2023 and received multi-phasic contrast-enhanced MRIs pre- and post-treatment were included in this retrospective study. Tumor response was measured using 1D, RECIST 1.1, and mRECIST, and 3D, volumetric, and percentage quantitative EASL (vqEASL and %qEASL). Patients were grouped into disease control vs progression and responders vs non-responders. Kaplan-Meier curves analyzed with log-rank tests assessed the predictive value for mOS. Cox regression modeling evaluated the association of clinical baseline parameters with mOS., Results: This study included 37 patients (mean age, 69.1 years [SD, 8.0]; 33 men). The mOS was 16.9 months. 3D vqEASL and %qEASL successfully stratified patients into disease control and progression (vqEASL: HR 0.21, CI: 0.55-0.08, p < 0.001; %qEASL: HR 0.18, CI: 0.83-0.04, p = 0.013), as well as responder and nonresponder (vqEASL: HR 0.25, CI: 0.08-0.74, p = 0.007; %qEASL: HR 0.17, CI: 0.04-0.72, p = 0.007) for predicting mOS. The 1D criteria, mRECIST stratified into disease control and progression only (HR 0.24, CI: 0.65-0.09, p = 0.002), and RECIST 1.1 showed no predictive value in either stratification. Multivariate Cox regression identified alpha-fetoprotein > 500 ng/mL as a predictor for poor mOS (p = 0.04)., Conclusion: The 3D quantitative enhancement-based response assessment tool qEASL can predict overall survival in patients undergoing immunotherapy for HCC and could identify non-responders., Clinical Relevance Statement: Using 3D quantitative enhancement-based tumor response criteria (qEASL), radiologists' predictions of tumor response in patients undergoing immunotherapy for HCC can be further improved., Key Points: MRI-based tumor response criteria predict immunotherapy survival benefits in HCC patients. 3D tumor response assessment methods surpass current evaluation criteria in predicting overall survival during HCC immunotherapy. Enhancement-based 3D tumor response criteria are robust prognosticators of survival for HCC patients on immunotherapy., (© 2024. The Author(s), under exclusive licence to European Society of Radiology.)

Oral delivery, while a highly desirable form of nanoparticle-drug administration, is limited by challenges associated with overcoming several biological barriers. Here, the authors study how fluorescent and poly(ethylene glycol)-coated (PEGylated) core-shell silica nanoparticles sized 5 to 50 nm interact with major barriers including intestinal mucus, intestinal epithelium, and stomach acid. From imaging fluorescence correlation spectroscopy studies using quasi-total internal reflection fluorescence microscopy, diffusion of nanoparticles through highly scattering mucus is progressively hindered above a critical hydrodynamic size around 20 nm. By studying Caco-2 cell monolayers mimicking the intestinal epithelia, it is observed that ultrasmall nanoparticles below 10 nm diameter (Cornell prime dots, [C' dots]) show permeabilities correlated with high absorption in humans from primarily enhanced passive passage through tight junctions. Particles above 20 nm diameter exclusively show active transport through cells. After establishing C' dot stability in artificial gastric juice, in vivo oral gavage experiments in mice demonstrate successful passage through the body followed by renal clearance without protein corona formation. Results suggest C' dots as viable candidates for oral administration to patients with a proven pathway towards clinical translation and may generate renewed interest in examining silica as a food additive and its effects on nutrition and health., (© 2023 Wiley-VCH GmbH.)