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Understanding Individual Differences in Happiness Sources and Implications for Health Technology Design: Exploratory Analysis of an Open Dataset.
JMIR Form Res
January 2025
School of Psychology, Ulster University, Coleraine, United Kingdom.
Background: Psychologists have developed frameworks to understand many constructs, which have subsequently informed the design of digital mental health interventions (DMHIs) aimed at improving mental health outcomes. The science of happiness is one such domain that holds significant applied importance due to its links to well-being and evidence that happiness can be cultivated through interventions. However, as with many constructs, the unique ways in which individuals experience happiness present major challenges for designing personalized DMHIs.
View Article and Find Full Text PDFFoundation Models for Translational Cancer Biology.
Annu Rev Biomed Data Sci
January 2025
1Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, California, USA;
Cancer remains a leading cause of death globally. The complexity and diversity of cancer-related datasets across different specialties pose challenges in refining precision medicine for oncology. Foundation models offer a promising solution.
View Article and Find Full Text PDFStudy of the role of transmembrane emp24 domain-containing protein 2 in oral squamous cell carcinoma.
J Appl Oral Sci
January 2025
Ningde Hospital Affiliated to Ningde Normal University, Department of Stomatology, Fujian, China.
Objective: This study aimed to investigate the role of transmembrane emp24 domain-containing protein 2 (TMED2) in oral squamous cell carcinoma (OSCC).
Methodology: A bioinformatics analysis was first conducted to explore TMED2 expression in OSCC and its relation with overall survival. The analysis results were further verified by assessing TMED2 expression levels in human normal oral keratinocyte cells and human OSCC cell lines using quantitative real-time polymerase chain reaction and the Western blot.
Classification-based pathway analysis using GPNet with novel P-value computation.
Brief Bioinform
November 2024
Center for Artificial Intelligence Research, Wake Forest University School of Medicine, Winston-Salem, NC 27101, United States.
Pathway analysis plays a critical role in bioinformatics, enabling researchers to identify biological pathways associated with various conditions by analyzing gene expression data. However, the rise of large, multi-center datasets has highlighted limitations in traditional methods like Over-Representation Analysis (ORA) and Functional Class Scoring (FCS), which struggle with low signal-to-noise ratios (SNR) and large sample sizes. To tackle these challenges, we use a deep learning-based classification method, Gene PointNet, and a novel $P$-value computation approach leveraging the confusion matrix to address pathway analysis tasks.
View Article and Find Full Text PDFMassively parallel Hong-Ou-Mandel interference based on independent soliton microcombs.
Sci Adv
January 2025
State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, China.
Hong-Ou-Mandel (HOM) interference is the foundation of quantum optics to test the degree of indistinguishability of two incoming photons, playing a key role in quantum communication, sensing, and photonic quantum computing. Realizing high-visibility HOM interference with massively parallel optical channels is challenging due to the lack of available natural optical references for aligning independent arrayed laser pairs. Here, we demonstrate 50 parallel comb-teeth pairs of continuous-wave weak coherent photons HOM interference using two independently frequency post-aligned soliton microcombs (SMCs), achieving an average fringe visibility over 46%.
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