Exploring the role of fear in human decision making

This study explores the use of Convolutional Neural Networks (CNNs) to classify fear in the context of decision-making. The approach involves developing a CNN model that is trained using hyper-parameter tuning and K-fold cross-validation to accurately classify fear from video footage of participants’ facial expressions during an experiment. The videos are presented along with a map to show the location of the participants along the route. The study reports an overall accuracy of 95.05% for fear classification. The results show that the model can successfully predict fear levels in different conditions. For example, the most desolate route with the lowest light levels recorded an overall fear detected at 49.15%, while the safest route with the highest light levels in a densely populated area saw an overall fear detected at 2.69%. These findings demonstrate the potential for using CNNs to classify fear and provide insight into how fear can be taken into consideration for decision-making in realistic scenarios

DNA Methylation Signature for EZH2 Functionally Classifies Sequence Variants in Three PRC2 Complex Genes.

Weaver syndrome (WS), an overgrowth/intellectual disability syndrome (OGID), is caused by pathogenic variants in the histone methyltransferase EZH2, which encodes a core component of the Polycomb repressive complex-2 (PRC2). Using genome-wide DNA methylation (DNAm) data for 187 individuals with OGID and 969 control subjects, we show that pathogenic variants in EZH2 generate a highly specific and sensitive DNAm signature reflecting the phenotype of WS. This signature can be used to distinguish loss-of-function from gain-of-function missense variants and to detect somatic mosaicism. We also show that the signature can accurately classify sequence variants in EED and SUZ12, which encode two other core components of PRC2, and predict the presence of pathogenic variants in undiagnosed individuals with OGID. The discovery of a functionally relevant signature with utility for diagnostic classification of sequence variants in EZH2, EED, and SUZ12 supports the emerging paradigm shift for implementation of DNAm signatures into diagnostics and translational research

Discrete family symmetry, Higgs mediators and theta_{13}

We present a new (supersymmetric) framework for obtaining an excellent description of quark, charged lepton and neutrino masses and mixings from a Delta(6n^2) family symmetry with multiplet assignments consistent with an underlying SO(10) Grand Unification. It employs a Higgs mediator sector in place of the usual Froggatt-Nielsen messengers, with quark and lepton messengers, and provides significant improvements over existing models of this type having unsuppressed Yukawa couplings to the third generation and a simplified vacuum alignment mechanism. The neutrino mass differences are naturally less hierarchical than those of the quarks and charged leptons. Similarly the lepton mixing angles are much larger than those in the quark sector and have an approximate tri-bi-maximal (TB) mixing form for theta_{12} and theta_{23}. However the mixing angle theta_{13} is naturally much larger than in pure TB mixing and can be consistent with the value found in recent experiments. The magnitude of theta_{13} is correlated with a the predicted deviation of theta_{23} from bi-maximal mixing. The model has light familon fields that can significantly modify the associated SUSY phenomenology.Comment: v3: accepted in JHE

Lithium Suppresses Astrogliogenesis by Neural Stem and Progenitor Cells by Inhibiting STAT3 Pathway Independently of Glycogen Synthase Kinase 3 Beta

Transplanted neural stem and progenitor cells (NSCs) produce mostly astrocytes in injured spinal cords. Lithium stimulates neurogenesis by inhibiting GSK3b (glycogen synthetase kinase 3-beta) and increasing WNT/beta catenin. Lithium suppresses astrogliogenesis but the mechanisms were unclear. We cultured NSCs from subventricular zone of neonatal rats and showed that lithium reduced NSC production of astrocytes as well as proliferation of glia restricted progenitor (GRP) cells. Lithium strongly inhibited STAT3 (signal transducer and activator of transcription 3) activation, a messenger system known to promote astrogliogenesis and cancer. Lithium abolished STAT3 activation and astrogliogenesis induced by a STAT3 agonist AICAR (5-aminoimidazole-4-carboxamide 1-beta-D-ribofuranoside), suggesting that lithium suppresses astrogliogenesis by inhibiting STAT3. GSK3β inhibition either by a specific GSK3β inhibitor SB216763 or overexpression of GID5-6 (GSK3β Interaction Domain aa380 to 404) did not suppress astrogliogenesis and GRP proliferation. GSK3β inhibition also did not suppress STAT3 activation. Together, these results indicate that lithium inhibits astrogliogenesis through non-GSK3β-mediated inhibition of STAT. Lithium may increase efficacy of NSC transplants by increasing neurogenesis and reducing astrogliogenesis. Our results also may explain the strong safety record of lithium treatment of manic depression. Millions of people take high-dose (>1 gram/day) lithium carbonate for a lifetime. GSK3b inhibition increases WNT/beta catenin, associated with colon and other cancers. STAT3 inhibition may reduce risk for cancer

Resolution of inflammation: a new therapeutic frontier

Dysregulated inflammation is a central pathological process in diverse disease states. Traditionally, therapeutic approaches have sought to modulate the pro- or anti-inflammatory limbs of inflammation, with mixed success. However, insight into the pathways by which inflammation is resolved has highlighted novel opportunities to pharmacologically manipulate these processes — a strategy that might represent a complementary (and perhaps even superior) therapeutic approach. This Review discusses the state of the art in the biology of resolution of inflammation, highlighting the opportunities and challenges for translational research in this field