Explore the vast range of titles available.

Thermal nociception involves the transmission of temperature-related noxious information from the periphery to the CNS and is a heritable trait that could predict transition to persistent pain. Rodent forward genetics complement human studies by controlling genetic complexity and environmental factors, analysis of end point tissue, and validation of variants on appropriate genetic backgrounds. Reduced complexity crosses between nearly identical inbred substrains with robust trait differences can greatly facilitate unbiased discovery of novel genes and variants. We found BALB/cByJ mice showed enhanced sensitivity on the 53.5°C hot plate and mechanical stimulation in the von Frey test compared to BALB/cJ mice and replicated decreased gross brain weight in BALB/cByJ versus BALB/cJ. We then identified a quantitative trait locus (QTL) on chromosome 13 for hot plate sensitivity (LOD = 10.7; p < 0.001; peak = 56 Mb) and a QTL for brain weight on chromosome 5 (LOD = 8.7; p < 0.001). Expression QTL mapping of brain tissues identified H2afy (56.07 Mb) as the top transcript with the strongest association at the hot plate locus (FDR = 0.0002) and spliceome analysis identified differential exon usage within H2afy associated with the same locus. Whole brain proteomics further supported decreased H2AFY expression could underlie enhanced hot plate sensitivity, and identified ACADS as a candidate for reduced brain weight. To summarize, a BALB/c reduced complexity cross combined with multiple-omics approaches facilitated identification of candidate genes underlying thermal nociception and brain weight. These substrains provide a powerful, reciprocal platform for future validation of candidate variants.

Glioblastoma (GBM) is the most aggressive and frequently occurring type of malignant brain tumor in adults. The initiation, progression, and recurrence of malignant tumors are known to be driven by a small subpopulation of cells known as tumor-initiating cells or cancer stem cells (CSCs). GBM CSCs play a pivotal role in orchestrating drug resistance and tumor relapse. As a prospective avenue for GBM intervention, the targeted suppression of GBM CSCs holds considerable promise. In this study, we found that rocaglates, compounds which are known to inhibit translation via targeting of the DEAD-box helicase eIF4A, exert a robust, dose-dependent cytotoxic impact on GBM CSCs with minimal killing of nonstem GBM cells. Subsequent optimization identified novel rocaglate derivatives (rocaglate acyl sulfamides or Roc ASFs) that selectively inhibit GBM CSCs with nanomolar EC50 values. Furthermore, comparative evaluation of a lead CSC-optimized Roc ASF across diverse mechanistic and target profiling assays revealed suppressed translation inhibition relative to that of other CSC-selective rocaglates, with enhanced targeting of the DEAD-box helicase DDX3X, a recently identified secondary target of rocaglates. Overall, these findings suggest a promising therapeutic strategy for targeting GBM CSCs.

Uncompetitive inhibition is an effective strategy for suppressing dysregulated enzymes and their substrates, but discovery of suitable ligands depends on often-unavailable structural knowledge and serendipity. Hence, despite surging interest in mass spectrometry-based target identification, proteomic studies of substrate-dependent target engagement remain sparse. Herein, we describe a strategy for the discovery of substrate-dependent ligand binding. Using proteome integral solubility alteration (PISA) assays, we show that simple biochemical additives can enable detection of RNA-protein-small molecule complexes in native cell lysates. We apply our approach to rocaglates, molecules that specifically clamp RNA to eukaryotic translation initiation factor 4A (eIF4A), DEAD-box helicase 3X (DDX3X), and potentially other members of the DEAD-box (DDX) helicase family. To identify unexpected interactions, we used a target class-specific thermal window and compared ATP analog and RNA base dependencies for key rocaglate-DDX interactions. We report and validate novel DDX targets of high-profile rocaglates - including the clinical candidate Zotatifin - using limited proteolysis-mass spectrometry and fluorescence polarization (FP) experiments. We also provide structural insight into divergent DDX3X affinities between synthetic rocaglates. Taken together, our study provides a model for screening uncompetitive inhibitors using a chemical proteomics approach and uncovers actionable DDX clamping targets, clearing a path towards characterization of novel molecular clamps and associated RNA helicases.

Sensitivity to the subjective reinforcing properties of opioids has a genetic component and can predict addiction liability of opioid compounds. We previously identified as a candidate gene underlying increased brain concentration of the oxycodone ( ) metabolite oxymorphone ( ) in BALB/cJ ( ) versus BALB/cByJ ( ) females that could increase OXY state-dependent reward. A large structural intronic variant is associated with a robust reduction of Zhx2 expression in J mice, which we hypothesized enhances OMOR levels and OXY addiction-like behaviors. We tested this hypothesis by restoring the loss-of-function in Js ( ) and modeling the loss-of-function variant through knocking out the coding exon ( ) in Bys and assessing brain OXY metabolite levels and behavior. Consistent with our hypothesis, Zhx2 E3KO females showed an increase in brain OMOR levels and OXY-induced locomotor activity. However, contrary to our hypothesis, state-dependent expression of OXY-CPP was decreased in E3KO females and increased in E3KO males. We also overexpressed Zhx2 in the livers and brains of Js and observed Zhx2 overexpression in select brain regions that was associated with reduced OXY state-dependent learning. Integrative transcriptomic and proteomic analysis of E3KO mice identified astrocyte function, cell adhesion, extracellular matrix properties, and endothelial cell functions as pathways influencing brain OXY metabolite concentration and behavior. These results support as a quantitative trait gene underlying brain OMOR concentration that is associated with changes in OXY behavior and implicate potential quantitative trait mechanisms that together inform our overall understanding of in brain function.

The majority of SARS-CoV-2 infections among healthy individuals result in asymptomatic to mild disease. However, the immunological mechanisms defining effective lung tissue protection from SARS-CoV-2 infection remain elusive. Unlike mice solely engrafted with human fetal lung xenograft (fLX), mice co-engrafted with fLX and a myeloid-enhanced human immune system (HNFL mice) are protected against SARS-CoV-2 infection, severe inflammation, and histopathology. Effective control of viral infection in HNFL mice associated with significant macrophage infiltration, and the induction of a potent macrophage-mediated interferon response. The pronounced upregulation of the USP18-ISG15 axis (a negative regulator of IFN responses), by macrophages was unique to HNFL mice and represented a prominent correlate of reduced inflammation and histopathology. Altogether, our work shed light on unique cellular and molecular correlates of lung tissue protection during SARS-CoV-2 infection, and underscores macrophage IFN responses as prime targets for developing immunotherapies against coronavirus respiratory diseases. Competing Interest Statement D.K., A.K.O., J.T., P.M., R.M.H., T.T., A.R.B., T.R.C., S.A.A., B.B., S.I.G., B.L.H., H.P.G., E.B., A.T., E.C., A.S., S.K., K.G., M.B., M.A., B.R.H., M.S., A.B.B., J.D.C. J.H.C., A.E., N.A.C., A.P. and F.D declare no conflict of interest. K.P.F. reports that he is an employee of PerkinElmer, Inc., manufacturer of diagnostic and analytical equipment. N.P. and A.K. declare the following competing interest as shareholders of InVivo Analytics with issued patents.

Understanding the pharmacogenomics of opioid metabolism and behavior is vital to therapeutic success as mutations can dramatically alter therapeutic efficacy and addiction liability. We found robust, sex-dependent BALB/c substrain differences in oxycodone behaviors and whole brain concentration of oxycodone metabolites. BALB/cJ females showed robust state-dependent oxycodone reward learning as measured via conditioned place preference when compared to the closely related BALB/cByJ substrain. Accordingly, BALB/cJ females also showed a robust increase in brain concentration of the inactive metabolite noroxycodone and the active metabolite oxymorphone compared to BALB/cByJ mice. Oxymorphone is a highly potent full agonist at the mu opioid receptor that could enhance drug-induced interoception and state-dependent oxycodone reward learning. Quantitative trait locus (QTL) mapping in a BALB/c F2 reduced complexity cross revealed one major QTL on chromosome 15 underlying brain oxymorphone concentration that explained 32% of the female variance. BALB/cJ and BALB/cByJ differ by fewer than 10,000 variants which can greatly facilitate candidate gene/variant identification. Hippocampal and striatal cis-expression QTL (eQTL) and exon-level eQTL analysis identified Zhx2, a candidate gene coding for a transcriptional repressor with a private BALB/cJ retroviral insertion that reduces Zhx2 expression and sex-dependent dysregulation of CYP enzymes. Whole brain proteomics corroborated the Zhx2 eQTL and identified upregulated CYP2D11 that could increase brain oxymorphone in BALB/cJ females. To summarize, Zhx2 is a highly promising candidate gene underlying brain oxycodone metabolite levels. Future studies will validate Zhx2 and its site of action using reciprocal gene editing and tissue-specific viral manipulations in BALB/c substrains. Competing Interest Statement The authors have declared no competing interest. Footnotes * https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE198375 * https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE196334 * https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE196352

Little is known about the genetic causes of stillbirth. In this study, investigators used exome sequencing analysis to identify a genetic cause in a relatively small percentage of cases and to provide some interesting clues as to where to look for more genes that, when mutated, cause stillbirth. The article is accompanied by interactive tables and an illustrated glossary.

The class of L1-regularized optimization problems has received much attention recently because of the introduction of \"compressed sensing,\" which allows images and signals to be reconstructed from small amounts of data. Despite this recent attention, many L1-regularized problems still remain difficult to solve, or require techniques that are very problem-specific. In this paper, we show that Bregman iteration can be used to solve a wide variety of constrained optimization problems. Using this technique, we propose a \"split Bregman\" method, which can solve a very broad class of L1-regularized problems. We apply this technique to the Rudin-Osher-Fatemi functional for image denoising and to a compressed sensing problem that arises in magnetic resonance imaging.

Variational models for image segmentation have many applications, but can be slow to compute. Recently, globally convex segmentation models have been introduced which are very reliable, but contain TV-regularizers, making them difficult to compute. The previously introduced Split Bregman method is a technique for fast minimization of L1 regularized functionals, and has been applied to denoising and compressed sensing problems. By applying the Split Bregman concept to image segmentation problems, we build fast solvers which can out-perform more conventional schemes, such as duality based methods and graph-cuts. The convex segmentation schemes also substantially outperform conventional level set methods, such as the Chan-Vese level set-based segmentation algorithm. We also consider the related problem of surface reconstruction from unorganized data points, which is used for constructing level set representations in 3 dimensions. The primary purpose of this paper is to examine the effectiveness of “Split Bregman” techniques for solving these problems, and to compare this scheme with more conventional methods.

Background Studies have noted variations in the cost-effectiveness of school-located influenza vaccination (SLIV), but little is known about how SLIV’s cost-effectiveness may vary by targeted age group (e.g., elementary or secondary school students), or vaccine consent process (paper-based or web-based). Further, SLIV’s cost-effectiveness may be impacted by its spillover effect on practice-based vaccination; prior studies have not addressed this issue. Methods We performed a cost-effectiveness analysis on two SLIV programs in upstate New York in 2015–2016: (a) elementary school SLIV using a stepped wedge design with schools as clusters (24 suburban and 18 urban schools) and (b) secondary school SLIV using a cluster randomized trial (16 suburban and 4 urban schools). The cost-per-additionally-vaccinated child (i.e., incremental cost-effectiveness ratio (ICER)) was estimated by dividing the incremental SLIV intervention cost by the incremental effectiveness (i.e., the additional number of vaccinated students in intervention schools compared to control schools). We performed deterministic analyses, one-way sensitivity analyses, and probabilistic analyses. Results The overall effectiveness measure (proportion of children vaccinated) was 5.7 and 5.5 percentage points higher, respectively, in intervention elementary (52.8%) and secondary schools (48.2%) than grade-matched control schools. SLIV programs vaccinated a small proportion of children in intervention elementary (5.2%) and secondary schools (2.5%). In elementary and secondary schools, the ICER excluding vaccine purchase was $85.71 and $86.51 per-additionally-vaccinated-child, respectively. When additionally accounting for observed spillover impact on practice-based vaccination, the ICER decreased to $80.53 in elementary schools -- decreasing substantially in secondary schools. (to $53.40). These estimates were higher than the published practice-based vaccination cost (median = $25.50, mean = $45.48). Also, these estimates were higher than our 2009–2011 urban SLIV program mean costs ($65) due to additional costs for use of a new web-based consent system ($12.97 per-additionally-vaccinated-child) and higher project coordination costs in 2015–2016. One-way sensitivity analyses showed that ICER estimates were most sensitive to the SLIV effectiveness. Conclusions SLIV raises vaccination rates and may increase practice-based vaccination in primary care practices. While these SLIV programs are effective, to be as cost-effective as practice-based vaccination our SLIV programs would need to vaccinate more students and/or lower the costs for consent systems and project coordination. Trial Registration ClinicalTrials.gov NCT02227186 (August 25, 2014), updated NCT03137667 (May 2, 2017).