86 research outputs found

    Opioid dose and risk of suicide

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    Chronic pain is associated with increased risk of suicide, and opioids are commonly used to treat moderate to severe pain. However, the association between opioid dose and suicide mortality has not been examined closely. This retrospective data analysis described the risk of suicide associated with differing prescribed opioid doses. Data were from Veterans Affairs health care system treatment records and the National Death Index. Records analyzed were those of Veterans Affairs patients with chronic pain receiving opioids in fiscal years 2004 to 2005 (N = 123,946). Primary predictors were maximum prescribed morphine-equivalent daily opioid dose and opioid fill type. The main outcome measured was suicide death, by any mechanism, and intentional overdose death during 2004 to 2009. Controlling for demographic and clinical characteristics, higher prescribed opioid doses were associated with elevated suicide risk. Compared with those receiving ≤20 milligrams/day (mg/d), hazard ratios were 1.48 (95% confidence intervals [CI], 1.25-1.75) for 20 to <50 mg/d, 1.69 (95% CI, 1.33-2.14) for 50 to <100 mg/d, and 2.15 (95% CI, 1.64-2.81) for 100+ mg/d. The magnitude of association between opioid dose and suicide by intentional overdose was not substantially different from that observed for the overall measure of suicide mortality. Risk of suicide mortality was greater among individuals receiving higher doses of opioids, and treatment providers may want to view high opioid dose as a marker of elevated risk for suicide. Additional research is needed on opioid use, pain treatment, and suicide

    Transcriptomic analysis of field-droughted sorghum from seedling to maturity reveals biotic and metabolic responses.

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    Drought is the most important environmental stress limiting crop yields. The C4 cereal sorghum [Sorghum bicolor (L.) Moench] is a critical food, forage, and emerging bioenergy crop that is notably drought-tolerant. We conducted a large-scale field experiment, imposing preflowering and postflowering drought stress on 2 genotypes of sorghum across a tightly resolved time series, from plant emergence to postanthesis, resulting in a dataset of nearly 400 transcriptomes. We observed a fast and global transcriptomic response in leaf and root tissues with clear temporal patterns, including modulation of well-known drought pathways. We also identified genotypic differences in core photosynthesis and reactive oxygen species scavenging pathways, highlighting possible mechanisms of drought tolerance and of the delayed senescence, characteristic of the stay-green phenotype. Finally, we discovered a large-scale depletion in the expression of genes critical to arbuscular mycorrhizal (AM) symbiosis, with a corresponding drop in AM fungal mass in the plants' roots

    ChIP-seq Accurately Predicts Tissue-Specific Activity of Enhancers

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    A major yet unresolved quest in decoding the human genome is the identification of the regulatory sequences that control the spatial and temporal expression of genes. Distant-acting transcriptional enhancers are particularly challenging to uncover since they are scattered amongst the vast non-coding portion of the genome. Evolutionary sequence constraint can facilitate the discovery of enhancers, but fails to predict when and where they are active in vivo. Here, we performed chromatin immunoprecipitation with the enhancer-associated protein p300, followed by massively-parallel sequencing, to map several thousand in vivo binding sites of p300 in mouse embryonic forebrain, midbrain, and limb tissue. We tested 86 of these sequences in a transgenic mouse assay, which in nearly all cases revealed reproducible enhancer activity in those tissues predicted by p300 binding. Our results indicate that in vivo mapping of p300 binding is a highly accurate means for identifying enhancers and their associated activities and suggest that such datasets will be useful to study the role of tissue-specific enhancers in human biology and disease on a genome-wide scale

    Discovery of High-Affinity Protein Binding Ligands – Backwards

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    BACKGROUND: There is a pressing need for high-affinity protein binding ligands for all proteins in the human and other proteomes. Numerous groups are working to develop protein binding ligands but most approaches develop ligands using the same strategy in which a large library of structured ligands is screened against a protein target to identify a high-affinity ligand for the target. While this methodology generates high-affinity ligands for the target, it is generally an iterative process that can be difficult to adapt for the generation of ligands for large numbers of proteins. METHODOLOGY/PRINCIPAL FINDINGS: We have developed a class of peptide-based protein ligands, called synbodies, which allow this process to be run backwards--i.e. make a synbody and then screen it against a library of proteins to discover the target. By screening a synbody against an array of 8,000 human proteins, we can identify which protein in the library binds the synbody with high affinity. We used this method to develop a high-affinity synbody that specifically binds AKT1 with a K(d)<5 nM. It was found that the peptides that compose the synbody bind AKT1 with low micromolar affinity, implying that the affinity and specificity is a product of the bivalent interaction of the synbody with AKT1. We developed a synbody for another protein, ABL1 using the same method. CONCLUSIONS/SIGNIFICANCE: This method delivered a high-affinity ligand for a target protein in a single discovery step. This is in contrast to other techniques that require subsequent rounds of mutational improvement to yield nanomolar ligands. As this technique is easily scalable, we believe that it could be possible to develop ligands to all the proteins in any proteome using this approach

    Canonical A-to-I and C-to-U RNA Editing Is Enriched at 3′UTRs and microRNA Target Sites in Multiple Mouse Tissues

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    RNA editing is a process that modifies RNA nucleotides and changes the efficiency and fidelity of the central dogma. Enzymes that catalyze RNA editing are required for life, and defects in RNA editing are associated with many diseases. Recent advances in sequencing have enabled the genome-wide identification of RNA editing sites in mammalian transcriptomes. Here, we demonstrate that canonical RNA editing (A-to-I and C-to-U) occurs in liver, white adipose, and bone tissues of the laboratory mouse, and we show that apparent non-canonical editing (all other possible base substitutions) is an artifact of current high-throughput sequencing technology. Further, we report that high-confidence canonical RNA editing sites can cause non-synonymous amino acid changes and are significantly enriched in 3′ UTRs, specifically at microRNA target sites, suggesting both regulatory and functional consequences for RNA editing

    Thermodynamic Additivity of Sequence Variations: An Algorithm for Creating High Affinity Peptides Without Large Libraries or Structural Information

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    BACKGROUND: There is a significant need for affinity reagents with high target affinity/specificity that can be developed rapidly and inexpensively. Existing affinity reagent development approaches, including protein mutagenesis, directed evolution, and fragment-based design utilize large libraries and/or require structural information thereby adding time and expense. Until now, no systematic approach to affinity reagent development existed that could produce nanomolar affinity from small chemically synthesized peptide libraries without the aid of structural information. METHODOLOGY/PRINCIPAL FINDINGS: Based on the principle of additivity, we have developed an algorithm for generating high affinity peptide ligands. In this algorithm, point-variations in a lead sequence are screened and combined in a systematic manner to achieve additive binding energies. To demonstrate this approach, low-affinity lead peptides for multiple protein targets were identified from sparse random sequence space and optimized to high affinity in just two chemical steps. In one example, a TNF-α binding peptide with K(d) = 90 nM and high target specificity was generated. The changes in binding energy associated with each variation were generally additive upon combining variations, validating the basis of the algorithm. Interestingly, cooperativity between point-variations was not observed, and in a few specific cases, combinations were less than energetically additive. CONCLUSIONS/SIGNIFICANCE: By using this additivity algorithm, peptide ligands with high affinity for protein targets were generated. With this algorithm, one of the highest affinity TNF-α binding peptides reported to date was produced. Most importantly, high affinity was achieved from small, chemically-synthesized libraries without the need for structural information at any time during the process. This is significantly different than protein mutagenesis, directed evolution, or fragment-based design approaches, which rely on large libraries and/or structural guidance. With this algorithm, high affinity/specificity peptide ligands can be developed rapidly, inexpensively, and in an entirely chemical manner

    Fine Tuning of Craniofacial Morphology by Distant-Acting Enhancers

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    The shape of the human face and skull is largely genetically determined, but the genetic drivers of craniofacial morphology remain poorly understood. Here we used a combination of epigenomic profiling, in vivo characterization of candidate enhancer sequences in transgenic mice, and targeted deletion experiments to examine the role of distant-acting enhancers in craniofacial development. We identified complex regulatory landscapes, consisting of enhancers that drive a remarkable spatial complexity of developmental expression patterns. Deletion of individual craniofacial enhancers from the mouse genome resulted in significant alterations of craniofacial shape, demonstrating their functional importance in defining face and skull morphology. These results demonstrate that enhancers play a pervasive role in mammalian craniofacial development and suggest that enhancer sequence variation contributes to human facial morphology
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