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Decoding Salience: A Functional Magnetic Resonance Imaging Investigation of Reward and Contextual Unexpectedness in Memory Encoding and Retrieval.
Hum Brain Mapp
January 2025
Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University, Magdeburg, Germany.
The present study investigated the neuromodulatory substrates of salience processing and its impact on memory encoding and behaviour, with a specific focus on two distinct types of salience: reward and contextual unexpectedness. 46 Participants performed a novel task paradigm modulating these two aspects independently and allowing for investigating their distinct and interactive effects on memory encoding while undergoing high-resolution fMRI. By using advanced image processing techniques tailored to examine midbrain and brainstem nuclei with high precision, our study additionally aimed to elucidate differential activation patterns in subcortical nuclei in response to reward-associated and contextually unexpected stimuli, including distinct pathways involving in particular dopaminergic modulation.
View Article and Find Full Text PDFFocus on mechano-immunology: new direction in cancer treatment.
Int J Surg
January 2025
Department of Pathology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
The immune response is modulated by a diverse array of signals within the tissue microenvironment, encompassing biochemical factors, mechanical forces, and pressures from adjacent tissues. Furthermore, the extracellular matrix and its constituents significantly influence the function of immune cells. In the case of carcinogenesis, changes in the biophysical properties of tissues can impact the mechanical signals received by immune cells, and these signals can be translated into biochemical signals through mechano-transduction pathways.
View Article and Find Full Text PDFElectronic cigarette usage amongst high school students in South Africa: a mixed methods approach.
EClinicalMedicine
December 2024
Utrecht University, Department of Interdisciplinary Social Science, Netherlands.
Background: The WHO has highlighted that: "promotion of e-cigarettes has led to marked increases in e-cigarette use by children and adolescents." The long-term neuropsychiatric and psychological consequences of substance abuse in adolescence is well recognised. Limited data exists on the adolescent burden of vaping-related nicotine addiction and behavioural and/or psychological dependence to guide pharmacological or behavioural interventions to stop electronic cigarette usage.
View Article and Find Full Text PDFA butterfly-shaped acceptor with rigid skeleton and unique assembly enables both efficient organic photovoltaics and high-speed organic photodetectors.
Natl Sci Rev
January 2025
State Key Laboratory of Elemento-Organic Chemistry, Frontiers Science Center for New Organic Matter, The Centre of Nanoscale Science and Technology and Key Laboratory of Functional Polymer Materials, Institute of Polymer Chemistry, Renewable Energy Conversion and Storage Center (RECAST), Tianjin Key Laboratory of Functional Polymer Materials, Nankai University, Tianjin 300071, China.
It remains challenging to design efficient bifunctional semiconductor materials in organic photovoltaic and photodetector devices. Here, we report a butterfly-shaped molecule, named WD-6, which exhibits low energy disorder and small reorganization energy due to its enhanced molecular rigidity and unique assembly with strong intermolecular interaction. The binary photovoltaic device based on PM6:WD-6 achieved an efficiency of 18.
View Article and Find Full Text PDFThe integration of conventional omics data such as genomics and transcriptomics data into artificial intelligence models has advanced significantly in recent years; however, their low applicability in clinical contexts, due to the high complexity of models, has been limited in their direct use inpatients. We integrated classic omics, including DNA mutation and RNA gene expression, added a novel focus on promising omics methods based on A>I(G) RNA editing, and developed a drug response prediction model. We analyzed 104 patients from the Breast Cancer Genome-Guided Therapy Study (NCT02022202).
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