The term chimera has been borrowed from Greek mythology and has a long history of use in biology and genetics. A chimera is an organism whose cells are derived from two or more zygotes. Recipients of tissue and organ transplants are artificial chimeras. This review concerns natural human chimeras. The first human chimera was reported in 1953. Natural chimeras can arise in various ways. Fetal and maternal cells can cross the placental barrier so that both mother and child may become microchimeras. Two zygotes can fuse together during an early embryonic stage to form a fusion chimera. Most chimeras remain undetected, especially if both zygotes are of the same genetic sex. Many are discovered accidently, for example, during a routine blood group test. Even sex-discordant chimeras can have a normal male or female phenotype. Only 28 of the 50 individuals with a 46,XX/46,XY karyotype were either true hermaphrodites or had ambiguous genitalia. Blood chimeras are formed by blood transfusion between dizygotic twins via the shared placenta and are more common than was once assumed. In marmoset monkey twins the exchange via the placenta is not limited to blood but can involve other tissues, including germ cells. To date there are no examples in humans of twin chimeras involving germ cells. If human chimeras are more common than hitherto thought there could be many medical, social, forensic, and legal implications. More multidisciplinary research is required for a better understanding of this fascinating subject.
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http://dx.doi.org/10.1016/j.ejmg.2020.103971 | DOI Listing |
Nucleic Acids Res
January 2025
Department of Chemistry and State Key Laboratory of Marine Pollution, City University of Hong Kong, Hong Kong SAR 999077, China.
RNA G-quadruplexes (rG4s) are non-canonical secondary nucleic acid structures found in the transcriptome. They play crucial roles in gene regulation by interacting with G4-binding proteins (G4BPs) in cells. rG4-G4BP complexes have been associated with human diseases, making them important targets for drug development.
View Article and Find Full Text PDFACS Chem Biol
January 2025
Department of Chemistry, Northwestern University, Evanston, Illinois 60208, United States.
Conventional small-molecule drugs primarily operate by inhibiting protein function, but this approach is limited when proteins lack well-defined ligand-binding pockets. Targeted protein degradation (TPD) offers an alternative approach by harnessing cellular degradation pathways to eliminate specific proteins. Recent studies have expanded the potential of TPD by identifying additional E3 ligases, with DCAF16 emerging as a promising candidate for facilitating protein degradation through both proteolysis-targeting chimera (PROTAC) and molecular glue mechanisms.
View Article and Find Full Text PDFSci Rep
January 2025
Research Institute, National Cancer Center, Goyang-si, 10408, Gyeonggi, Republic of Korea.
The VHL-containing cullin-RING E3 ubiquitin ligase (CRL2) complex is an E3 ligase commonly used in targeted protein degradation (TPD). Hydroxyproline-based ligands that mimic VHL substrates have been developed as anchor molecules for proteolysis-targeting chimeras (PROTACs) in TPD. To expand the chemical space for VHL ligands, we conducted fragment screening using VHL-ELOB-ELOC (VBC) proteins.
View Article and Find Full Text PDFBiol Aujourdhui
January 2025
Université de Caen Normandie, CERMN UR4258, Boulevard Becquerel, 14000 Caen, France.
The disruption of proteostasis provides a favourable context for the emergence of therapeutic innovations, in particular by exploiting technologies such as the PROTAC (Proteolysis Targeting Chimera) approach. These technologies aim to selectively target proteins involved in various diseases, including cancer and neurodegenerative diseases, by inducing their specific degradation via the ubiquitin-proteasome system. The PROTAC approach opens new opportunities for restoring altered protein homeostasis and modulating the pathological consequences of proteostasis deregulation.
View Article and Find Full Text PDFSci Rep
January 2025
Department of General Psychology and Padova Neuroscience Center, University of Padova, Padova, Italy.
Hierarchical generative models can produce data samples based on the statistical structure of their training distribution. This capability can be linked to current theories in computational neuroscience, which propose that spontaneous brain activity at rest is the manifestation of top-down dynamics of generative models detached from action-perception cycles. A popular class of hierarchical generative models is that of Deep Belief Networks (DBNs), which are energy-based deep learning architectures that can learn multiple levels of representations in a completely unsupervised way exploiting Hebbian-like learning mechanisms.
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