Individual differences in temporal and probabilistic discounting are associated with a wide range of life outcomes in literature. Traditional approaches have focused on impulsiveness and cognitive control skills, on goal-oriented personality traits as well as on the psychological perception of time. More recently, literature started to consider the role of social and contextual factors in discounting behavior. Between others, higher generalized trust in human beings and specific trust in people who will deliver the future/probabilistic rewards have been related to a stronger willingness to wait and to assume risk. Moreover, the tendency to trust others has been associated with the oxytocin receptor gene regulation that can be modified by life experiences. In this perspective, we hypothesized that differences in the tendency to wait and to take risks for a more desirable reward according to the proposer's trustworthiness could be related to a different level of DNA methylation at the oxytocin receptor gene. Findings confirmed that participants are less willing to wait and to risk when the proposer is considered highly untrustworthy and revealed how higher oxytocin receptor gene DNA methylation is associated with a stronger effect due to the presence of an untrustworthy proposer. Limits and future directions are outlined.
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http://dx.doi.org/10.3390/brainsci12010098 | DOI Listing |
Acta Neuropathol Commun
January 2025
Institute of Cancer Research, London, UK.
Histone mutations (H3 K27M, H3 G34R/V) are molecular features defining subtypes of paediatric-type diffuse high-grade gliomas (HGG) (diffuse midline glioma (DMG), H3 K27-altered, diffuse hemispheric glioma (DHG), H3 G34-mutant). The WHO classification recognises in exceptional cases, these mutations co-occur. We report one such case of a 2-year-old female presenting with neurological symptoms; MRI imaging identified a brainstem lesion which was biopsied.
View Article and Find Full Text PDFEpigenetics Chromatin
January 2025
Department of Maternal‑Fetal Biology, National Center for Child Health and Development, Tokyo, 157‑8535, Japan.
Background: DNA methylation plays a crucial role in mammalian development. While methylome changes acquired in the parental genomes are believed to be erased by epigenetic reprogramming, accumulating evidence suggests that methylome changes in sperm caused by environmental factors are involved in the disease phenotypes of the offspring. These findings imply that acquired sperm methylome changes are transferred to the embryo after epigenetic reprogramming.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Biological Sciences, Virginia Tech, Blacksburg, VA, 24061-0910, USA.
Sepsis is a leading cause of death worldwide, with most patient mortality stemming from lingering immunosuppression in sepsis survivors. This is due in part to immune dysfunction resulting from monocyte exhaustion, a phenotype of reduced antigen presentation, altered CD14/CD16 inflammatory subtypes, and disrupted cytokine production. Whereas previous research demonstrated improved sepsis survival in Ticam2 mice, the contribution of TICAM2 to long-term exhaustion memory remained unknown.
View Article and Find Full Text PDFSci Data
January 2025
Department of Botany and Evolutionary Ecology, University of Warmia and Mazury in Olsztyn, Plac Łódzki 1, Olsztyn, 10-719, Poland.
Riccia sorocarpa Bisch., commonly known as common crystalwort, is a plant belonging to the Marchantiales order with a cosmopolitan distribution among a wide range of habitats: fields, gardens, waste ground, on paths, cliff tops, and thin soil over rocks or by water bodies. However, research into the genetic aspects of this species is limited.
View Article and Find Full Text PDFNat Commun
January 2025
The Medical Image and Health Informatics Lab, the School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Despite vast data support in DNA methylation (DNAm) biomarker discovery to facilitate health-care research, this field faces huge resource barriers due to preliminary unreliable candidates and the consequent compensations using expensive experiments. The underlying challenges lie in the confounding factors, especially measurement noise and individual characteristics. To achieve reliable identification of a candidate pool for DNAm biomarker discovery, we propose a Causality-driven Deep Regularization framework to reinforce correlations that are suggestive of causality with disease.
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