Howard Hughes Medical Institute

About: Howard Hughes Medical Institute is a nonprofit organization based out in Chevy Chase, Maryland, United States. It is known for research contribution in the topics: Gene & RNA. The organization has 20371 authors who have published 34677 publications receiving 5247143 citations. The organization is also known as: HHMI & hhmi.org.

X-ray and NMR structure of human Bcl-xL, an inhibitor of programmed cell death.

Abstract: THE Bcl-2 family of proteins regulate programmed cell death by an unknown mechanism. Here we describe the crystal and solution structures of a Bcl-2 family member, Bcl-xL (ref. 2). The structures consist of two central, primarily hydrophobic alpha-helices, which are surrounded by amphipathic helices. A 60-residue loop connecting helices alpha1 and alpha2 was found to be flexible and non-essential for anti-apoptotic activity. The three functionally important Bcl-2 homology regions (BH1, BH2 and BH3) are in close spatial proximity and form an elongated hydrophobic cleft that may represent the binding site for other Bcl-2 family members. The arrangement of the alpha-helices in Bcl-xL is reminiscent of the membrane translocation domain of bacterial toxins, in particular diphtheria toxin and the colicins. The structural similarity may provide a clue to the mechanism of action of the Bcl-2 family of proteins.

CTCF mediates methylation-sensitive enhancer-blocking activity at the H19/Igf2 locus

Abstract: The Insulin-like growth factor 2 (Igf2) and H19 genes are imprinted, resulting in silencing of the maternal and paternal alleles, respectively This event is dependent upon an imprinted-control region two kilobases upstream of H19 (refs 1, 2) On the paternal chromosome this element is methylated and required for the silencing of H19 (refs 2-4) On the maternal chromosome the region is unmethylated and required for silencing of the Igf2 gene 90 kilobases upstream We have proposed that the unmethylated imprinted-control region acts as a chromatin boundary that blocks the interaction of Igf2 with enhancers that lie 3' of H19 (refs 5, 6) This enhancer-blocking activity would then be lost when the region was methylated, thereby allowing expression of Igf2 paternally Here we show, using transgenic mice and tissue culture, that the unmethylated imprinted-control regions from mouse and human H19 exhibit enhancer-blocking activity Furthermore, we show that CTCF, a zinc finger protein implicated in vertebrate boundary function, binds to several sites in the unmethylated imprinted-control region that are essential for enhancer blocking Consistent with our model, CTCF binding is abolished by DNA methylation This is the first example, to our knowledge, of a regulated chromatin boundary in vertebrates

Fulminant Myocarditis with Combination Immune Checkpoint Blockade

Abstract: Immune checkpoint inhibitors have improved clinical outcomes associated with numerous cancers, but high-grade, immune-related adverse events can occur, particularly with combination immunotherapy. We report the cases of two patients with melanoma in whom fatal myocarditis developed after treatment with ipilimumab and nivolumab. In both patients, there was development of myositis with rhabdomyolysis, early progressive and refractory cardiac electrical instability, and myocarditis with a robust presence of T-cell and macrophage infiltrates. Selective clonal T-cell populations infiltrating the myocardium were identical to those present in tumors and skeletal muscle. Pharmacovigilance studies show that myocarditis occurred in 0.27% of patients treated with a combination of ipilimumab and nivolumab, which suggests that our patients were having a rare, potentially fatal, T-cell-driven drug reaction. (Funded by Vanderbilt-Ingram Cancer Center Ambassadors and others.).

An Introduction to TRP Channels

Abstract: The aim of this review is to provide a basic framework for understanding the function of mammalian transient receptor potential (TRP) channels, particularly as they have been elucidated in heterologous expression systems. Mammalian TRP channel proteins form six-transmembrane (6-TM) cation-permeable channels that may be grouped into six subfamilies on the basis of amino acid sequence homology (TRPC, TRPV, TRPM, TRPA, TRPP, and TRPML). Selected functional properties of TRP channels from each subfamily are summarized in this review. Although a single defining characteristic of TRP channel function has not yet emerged, TRP channels may be generally described as calcium-permeable cation channels with polymodal activation properties. By integrating multiple concomitant stimuli and coupling their activity to downstream cellular signal amplification via calcium permeation and membrane depolarization, TRP channels appear well adapted to function in cellular sensation. Our review of recent literature implicating TRP channels in neuronal growth cone steering suggests that TRPs may function more widely in cellular guidance and chemotaxis. The TRP channel gene family and its nomenclature, the encoded proteins and alternatively spliced variants, and the rapidly expanding pharmacology of TRP channels are summarized in online supplemental material.

Opportunities and obstacles for deep learning in biology and medicine.

Abstract: Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood. Hence, deep learning techniques may be particularly well suited to solve problems of these fields. We examine applications of deep learning to a variety of biomedical problems-patient classification, fundamental biological processes and treatment of patients-and discuss whether deep learning will be able to transform these tasks or if the biomedical sphere poses unique challenges. Following from an extensive literature review, we find that deep learning has yet to revolutionize biomedicine or definitively resolve any of the most pressing challenges in the field, but promising advances have been made on the prior state of the art. Even though improvements over previous baselines have been modest in general, the recent progress indicates that deep learning methods will provide valuable means for speeding up or aiding human investigation. Though progress has been made linking a specific neural network's prediction to input features, understanding how users should interpret these models to make testable hypotheses about the system under study remains an open challenge. Furthermore, the limited amount of labelled data for training presents problems in some domains, as do legal and privacy constraints on work with sensitive health records. Nonetheless, we foresee deep learning enabling changes at both bench and bedside with the potential to transform several areas of biology and medicine.