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Lanthanide-based polyhedral clusters are of great interest due to their unique geometries and functional properties, but their controlled synthesis remains a major challenge. Here, we report a nested three-shell cluster, [GdNi(MeIDA)(OH)(CO) (HO)]·(ClO)·(HO) (GdNi, HMeIDA = N-Methyliminodiacetic acid), achieved by using urea as a slow-release carbonate source to direct the formation of a dodecahedral inner shell. Single-crystal X-ray diffraction reveals a unique Gd@Gd@Ni arrangement, with the innermost Gd forming a Platonic dodecahedron templated by carbonate. A machine learning-guided, high-throughput synthesis platform enabled the exploration of 780 reaction conditions, uncovering key parameters and phase boundaries governing cluster formation. This work demonstrates data-driven strategies can accelerate the discovery of complex lanthanide architectures.
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http://dx.doi.org/10.1002/anie.202516130 | DOI Listing |
Talanta
September 2025
Faculty of Applied Sciences, Ton Duc Thang University, Ho Chi Minh City, Viet Nam. Electronic address:
Food spoilage poses a global challenge with far-reaching consequences for public health, economic stability, and environmental sustainability. Conventional analytical methods for spoilage detection though accurate are often cost-prohibitive, labor-intensive, and unsuitable for real-time or field-based monitoring. Microfluidic paper-based analytical devices (μPADs) have emerged as a transformative technology offering rapid, portable, and cost-effective solutions for food quality assessment.
View Article and Find Full Text PDFJMIR Ment Health
September 2025
Department of Psychology, University of California, Los Angeles, 1285 Franz Hall, Box 951563, Los Angeles, CA, 90095, United States, 1 3107941262.
Background: Youth mental health issues have been recognized as a pressing crisis in the United States in recent years. Effective, evidence-based mental health research and interventions require access to integrated datasets that consolidate diverse and fragmented data sources. However, researchers face challenges due to the lack of centralized, publicly available datasets, limiting the potential for comprehensive analysis and data-driven decision-making.
View Article and Find Full Text PDFJMIR Med Inform
September 2025
Department of Hepatobiliary and Vascular Surgery, First Affiliated Hospital of Chengdu Medical College, Chengdu, China.
Background: Primary liver cancer, particularly hepatocellular carcinoma (HCC), poses significant clinical challenges due to late-stage diagnosis, tumor heterogeneity, and rapidly evolving therapeutic strategies. While systematic reviews and meta-analyses are essential for updating clinical guidelines, their labor-intensive nature limits timely evidence synthesis.
Objective: This study proposes an automated literature screening workflow powered by large language models (LLMs) to accelerate evidence synthesis for HCC treatment guidelines.
JCO Clin Cancer Inform
August 2025
Telperian, Austin, TX.
Purpose: Lymphocytes play critical roles in cancer immunity and tumor surveillance. Radiation-induced lymphopenia (RIL) is a common side effect observed in patients with cancer undergoing chemoradiation therapy (CRT), leading to impaired immunity and worse clinical outcomes. Although proton beam therapy (PBT) has been suggested to reduce RIL risk compared with intensity-modulated radiation therapy (IMRT), this study used Bayesian counterfactual machine learning to identify distinct patient profiles and inform personalized radiation modality choice.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
September 2025
Behavioral Neuroscience Research Branch, Intramural Research Program, National Institute on Drug Abuse, Baltimore, MD 21224.
Learning when to initiate or withhold actions is essential for survival, requiring the integration of past experiences with new information to adapt to changing environments. The prelimbic cortex (PL) plays a central role in this process, with a stable PL neuronal population (ensemble) recruited during operant reward learning to encode response execution. However, it is unknown how this established reward-learning ensemble adapts to changing reward contingencies, such as reward omission during extinction.
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