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"Martin, Eric"
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Brown bear, Brown Bear, what do you see?
Children see a variety of animals, each one a different color, and a teacher looking at them.
Book
TETs compete with DNMT3 activity in pluripotent cells at thousands of methylated somatic enhancers
Mammalian cells stably maintain high levels of DNA methylation despite expressing both positive (DNMT3A/B) and negative (TET1-3) regulators. Here, we analyzed the independent and combined effects of these regulators on the DNA methylation landscape using a panel of knockout human embryonic stem cell (ESC) lines. The greatest impact on global methylation levels was observed in DNMT3-deficient cells, including reproducible focal demethylation at thousands of normally methylated loci. Demethylation depends on TET expression and occurs only when both DNMT3s are absent. Dynamic loci are enriched for hydroxymethylcytosine and overlap with subsets of putative somatic enhancers that are methylated in ESCs and can be activated upon differentiation. We observe similar dynamics in mouse ESCs that were less frequent in epiblast stem cells (EpiSCs) and scarce in somatic tissues, suggesting a conserved pluripotency-linked mechanism. Taken together, our data reveal tightly regulated competition between DNMT3s and TETs at thousands of somatic regulatory sequences within pluripotent cells.
Whole-genome bisulfite sequencing analysis of human embryonic stem cells shows that DNMT3 deficiency leads to global and local demethylation, which depends on TET activity. Dynamic loci overlap with putative somatic enhancers that are highly methylated in ESCs.
Journal Article
Brown Bear, Brown Bear, what do you see?
Children see a variety of animals, each one a different color, and a teacher looking at them.
Book
Panda Bear, Panda Bear, what do you see?
Illustrations and rhyming text present ten different endangered animals.
Book
Pan-RAF inhibitor exarafenib targets BRAF class II/III NSCLC and reveals ARAF-KSR1 resistance and combination strategies
Oncogenic BRAF mutations, including those in non-small cell lung cancer (NSCLC), are classified as Class I, II, or III. While approved therapies exist for BRAF Class I mutants, no approved therapies exist for Class II and III BRAF-mutated NSCLC. Analysis of a circulating tumor DNA database reveals Class II and III mutations comprise ~65% of BRAF-mutant NSCLC cases, with Class II patients showing worse outcomes than Class I. Exarafenib, a distinct pan-RAF inhibitor, demonstrates potent activity against BRAF Class II and III mutant preclinical models and initial clinical activity. Resistance studies reveal rewiring to an ARAF-mediated bypass pathway, characterized by RAS-mediated ARAF-KSR1 complexes maintaining MAPK signaling despite pan-RAF inhibitor treatment. RAS or MEK inhibition co-targeting is effective against this resistance mechanism. This study provides preclinical rationale for clinical testing of exarafenib in BRAF Class II/III cancers and unveils RAS-mediated ARAF-KSR1 complex formation as a resistance mechanism and rational co-therapy strategies.
While therapies targeting type I BRAF mutations have been developed, there are limited options for those with type II and III mutations. Here, the authors identify a subset of BRAF-mutant non-small cell lung cancer patients and characterise the pan-RAF inhibitor exarafenib, demonstrating efficacy in preclinical models and investigating subsequent resistance mechanisms.
Journal Article
Baby bear, baby bear, what do you see?
Illustrations and rhyming text portray a young bear searching for its mother and meeting many North American animals along the way.
Book
Quantum Dynamics of Attractive and Repulsive Polarons in a Doped MoSe2 Monolayer
When mobile impurities are introduced and coupled to a Fermi sea, new quasiparticles known as Fermi polarons are formed. There are two interesting, yet drastically different regimes of the Fermi polaron problem: (i) the attractive polaron (AP) branch connected to pairing phenomena spanning the crossover from BCS superfluidity to the Bose-Einstein condensation of molecules and (ii) the repulsive branch (RP), which underlies the physics responsible for Stoner’s itinerant ferromagnetism. Here, we study Fermi polarons in two-dimensional systems, where many questions and debates regarding their nature persist. The model system we investigate is a dopedMoSe2monolayer. We find the observed AP-RP energy splitting and the quantum dynamics of attractive polarons agree with the predictions of polaron theory. As the doping density increases, the quantum dephasing of the attractive polarons remains constant, indicative of stable quasiparticles, while the repulsive polaron dephasing rate increases nearly quadratically. The dynamics of Fermi polarons are of critical importance for understanding the pairing and magnetic instabilities that lead to the formation of rich quantum phases found in a wide range of physical systems including nuclei, cold atomic gases, and solids.
Journal Article
Polar bear, polar bear, what do you hear?
Zoo animals from polar bear to walrus make their distinctive sounds for each other, while children imitate the sounds for the zookeeper.
Book
A diffusion model conditioned on compound bioactivity profiles for generating high-content images
High-content imaging (HCI) provides a rich snapshot of compound-induced phenotypic outcomes that augment our understanding of how compounds affect cellular systems. Generative imaging models for HCI provide a route towards anticipating the phenotypic outcomes of chemical perturbations in silico at unprecedented scale and speed. Here, we developed Profile-Diffusion (pDIFF), a generative method leveraging a profile-to-image latent diffusion model conditioned on in silico bioactivity profiles to generate high-content images displaying the cellular outcomes induced by compound treatment. We trained and evaluated a pDIFF model using high-content images from a Cell Painting assay profiling 3750 molecules (3375 training compounds and 375 held-out compounds) with corresponding in silico bioactivity profiles. Using the held-out set we demonstrate that pDIFF provides improved visual depictions of phenotypic responses of compounds that are structurally dissimilar to training compounds, compared to a baseline profile-to-image latent diffusion model trained on substructural molecular descriptors only. In a virtual hit expansion scenario, pDIFF yielded statistically significant improvement in expansion outcomes as measured by nearest-neighbor retrieval accuracy, compared to expansions based on compound structural representations, bioactivity profiles, and generative imaging models based only on substructural molecular descriptors, thus showcasing the potential of the methodology to speed up and improve the search for novel phenotypically active molecules.
Journal Article