Fentanyl related overdose in Indianapolis: Estimating trends using multilevel Bayesian models

Introduction: The opioid epidemic has been largely attributed to changes in prescribing practices over the past 20 years. Although current overdose trends appear driven by the opioid fentanyl, heroin has remained the focus of overdose fatality assessments. We obtained full toxicology screens on lethal overdose cases in a major US city, allowing more accurate assessment of the time-course of fentanyl-related deaths. Methods: We used coroner data from Marion County, Indiana comprising 1583 overdose deaths recorded between January 1, 2010 and April 30, 2017. Bayesian multilevel models were fitted to predict likelihood of lethal fentanyl-related overdose using information about the victim's age, race, sex, zip code, and date of death. Results: Three hundred and seventy-seven (23.8%) overdose deaths contained fentanyl across the seven-year period. Rates rose exponentially over time, beginning well below 15% from 2010 through 2013 before rising to approximately 50% by 2017. At the beginning of the study period, rates of fentanyl overdose were lowest among Black persons but increased more rapidly, eventually surpassing Whites. Currently, White females may be at particularly low risk of fentanyl overdose and Black females at high risk. Rates were highest for younger and middle-aged groups. Over time, fentanyl was more likely detected without the presence of other opioids. Conclusions: Fentanyl has increasingly been detected in fatal overdose deaths in Marion County. Policy and program responses must focus on education for those at highest risk of fentanyl exposure and death. These responses should also be tailored to meet the unique needs of high-risk demographics.This publication was supported by the Grant Number, 5 NU17CE002721-02, funded by the Centers for Disease Control and Prevention. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention or the Department of Health and Human Services

Whole-Genome Sequence Analysis of an Extensively Drug-Resistant Salmonella enterica Serovar Agona Isolate from an Australian Silver Gull (Chroicocephalus novaehollandiae) Reveals the Acquisition of Multidrug Resistance Plasmids.

Although most of the approximately 94 million annual human cases of gastroenteritis due to Salmonella enterica resolve without medical intervention, antimicrobial therapy is recommended for patients with severe disease. Wild birds can be natural hosts of Salmonella that pose a threat to human health; however, multiple-drug-resistant serovars of S. enterica have rarely been described. In 2012, silver gull (Chroicocephalus novaehollandiae) chicks at a major breeding colony were shown to host Salmonella, most isolates of which were susceptible to antibiotics. However, multiple-drug-resistant (MDR) Escherichia coli with resistance to carbapenems, ceftazidime, and fluoroquinolones was reported from this breeding colony. In this paper, we describe a novel MDR Salmonella strain subsequently isolated from the same breeding colony. SG17-135, an isolate of S. enterica with phenotypic resistance to 12 individual antibiotics but only nine antibiotic classes including penicillins, cephalosporins, monobactams, macrolides, fluoroquinolones, aminoglycosides, dihydrofolate reductase inhibitors (trimethoprim), sulfonamides, and glycylcyclines was recovered from a gull chick in 2017. Whole-genome sequence (WGS) analysis of SG17-135 identified it as Salmonella enterica serovar Agona (S Agona) with a chromosome comprising 4,813,284 bp, an IncHI2 ST2 plasmid (pSG17-135-HI2) of 311,615 bp, and an IncX1 plasmid (pSG17-135-X) of 27,511 bp. pSG17-135-HI2 housed a complex resistance region comprising 16 antimicrobial resistance genes including blaCTX-M-55 The acquisition of MDR plasmids by S. enterica described here poses a serious threat to human health. Our study highlights the importance of taking a One Health approach to identify environmental reservoirs of drug-resistant pathogens and MDR plasmids.IMPORTANCE Defining environmental reservoirs hosting mobile genetic elements that shuttle critically important antibiotic resistance genes is key to understanding antimicrobial resistance (AMR) from a One Health perspective. Gulls frequent public amenities, parklands, and sewage and other waste disposal sites and carry drug-resistant Escherichia coli Here, we report on SG17-135, a strain of Salmonella enterica serovar Agona isolated from the cloaca of a silver gull chick nesting on an island in geographic proximity to the greater metropolitan area of Sydney, Australia. SG17-135 is closely related to pathogenic strains of S Agona, displays resistance to nine antimicrobial classes, and carries important virulence gene cargo. Most of the antibiotic resistance genes hosted by SG17-135 are clustered on a large IncHI2 plasmid and are flanked by copies of IS26 Wild birds represent an important link in the evolution and transmission of resistance plasmids, and an understanding of their behavior is needed to expose the interplay between clinical and environmental microbial communities

Precision medicine for suicidality: from universality to subtypes and personalization

Suicide remains a clear, present and increasing public health problem, despite being a potentially preventable tragedy. Its incidence is particularly high in people with overt or un(der)diagnosed psychiatric disorders. Objective and precise identification of individuals at risk, ways of monitoring response to treatments and novel preventive therapeutics need to be discovered, employed and widely deployed. We sought to investigate whether blood gene expression biomarkers for suicide (that is, a ‘liquid biopsy’ approach) can be identified that are more universal in nature, working across psychiatric diagnoses and genders, using larger cohorts than in previous studies. Such markers may reflect and/or be a proxy for the core biology of suicide. We were successful in this endeavor, using a comprehensive stepwise approach, leading to a wealth of findings. Steps 1, 2 and 3 were discovery, prioritization and validation for tracking suicidality, resulting in a Top Dozen list of candidate biomarkers comprising the top biomarkers from each step, as well as a larger list of 148 candidate biomarkers that survived Bonferroni correction in the validation step. Step 4 was testing the Top Dozen list and Bonferroni biomarker list for predictive ability for suicidal ideation (SI) and for future hospitalizations for suicidality in independent cohorts, leading to the identification of completely novel predictive biomarkers (such as CLN5 and AK2), as well as reinforcement of ours and others previous findings in the field (such as SLC4A4 and SKA2). Additionally, we examined whether subtypes of suicidality can be identified based on mental state at the time of high SI and identified four potential subtypes: high anxiety, low mood, combined and non-affective (psychotic). Such subtypes may delineate groups of individuals that are more homogenous in terms of suicidality biology and behavior. We also studied a more personalized approach, by psychiatric diagnosis and gender, with a focus on bipolar males, the highest risk group. Such a personalized approach may be more sensitive to gender differences and to the impact of psychiatric co-morbidities and medications. We compared testing the universal biomarkers in everybody versus testing by subtypes versus personalized by gender and diagnosis, and show that the subtype and personalized approaches permit enhanced precision of predictions for different universal biomarkers. In particular, LHFP appears to be a strong predictor for suicidality in males with depression. We also directly examined whether biomarkers discovered using male bipolars only are better predictors in a male bipolar independent cohort than universal biomarkers and show evidence for a possible advantage of personalization. We identified completely novel biomarkers (such as SPTBN1 and C7orf73), and reinforced previously known biomarkers (such as PTEN and SAT1). For diagnostic ability testing purposes, we also examined as predictors phenotypic measures as apps (for suicide risk (CFI-S, Convergent Functional Information for Suicidality) and for anxiety and mood (SASS, Simplified Affective State Scale)) by themselves, as well as in combination with the top biomarkers (the combination being our a priori primary endpoint), to provide context and enhance precision of predictions. We obtained area under the curves of 90% for SI and 77% for future hospitalizations in independent cohorts. Step 5 was to look for mechanistic understanding, starting with examining evidence for the Top Dozen and Bonferroni biomarkers for involvement in other psychiatric and non-psychiatric disorders, as a mechanism for biological predisposition and vulnerability. The biomarkers we identified also provide a window towards understanding the biology of suicide, implicating biological pathways related to neurogenesis, programmed cell death and insulin signaling from the universal biomarkers, as well as mTOR signaling from the male bipolar biomarkers. In particular, HTR2A increase coupled with ARRB1 and GSK3B decreases in expression in suicidality may provide a synergistic mechanistical corrective target, as do SLC4A4 increase coupled with AHCYL1 and AHCYL2 decrease. Step 6 was to move beyond diagnostics and mechanistical risk assessment, towards providing a foundation for personalized therapeutics. Items scored positive in the CFI-S and subtypes identified by SASS in different individuals provide targets for personalized (psycho)therapy. Some individual biomarkers are targets of existing drugs used to treat mood disorders and suicidality (lithium, clozapine and omega-3 fatty acids), providing a means toward pharmacogenomics stratification of patients and monitoring of response to treatment. Such biomarkers merit evaluation in clinical trials. Bioinformatics drug repurposing analyses with the gene expression biosignatures of the Top Dozen and Bonferroni-validated universal biomarkers identified novel potential therapeutics for suicidality, such as ebselen (a lithium mimetic), piracetam (a nootropic), chlorogenic acid (a polyphenol) and metformin (an antidiabetic and possible longevity promoting drug). Finally, based on the totality of our data and of the evidence in the field to date, a convergent functional evidence score prioritizing biomarkers that have all around evidence (track suicidality, predict it, are reflective of biological predisposition and are potential drug targets) brought to the fore APOE and IL6 from among the universal biomarkers, suggesting an inflammatory/accelerated aging component that may be a targetable common denominator

Enhancement of h --> gamma gamma in the Two Higgs Doublet Model Type I

We show that in the Two Higgs Doublet Model (THDM) Type I the partial decay width of h --> gamma gamma can be considerably larger than in Type II, due to light charged scalars with a mass about 100 GeV, which are not yet excluded in Type I. A possible enhancement of the width compared to the SM is analyzed for different Higgs potentials, subject to constraints from tree-level unitarity, vacuum stability and electroweak precision tests.Comment: 12 pages. v2: Sign error in eq. (19) corrected. Results and figures for the IDM changed accordingly. Other minor corrections. References and improved discussion of interference effects adde

Decaying Hidden Dark Matter in Warped Compactification

The recent PAMELA and ATIC/Fermi/HESS experiments have observed an excess of electrons and positrons, but not anti-protons, in the high energy cosmic rays. To explain this result, we construct a decaying hidden dark matter model in string theory compactification that incorporates the following two ingredients, the hidden dark matter scenario in warped compactification and the phenomenological proposal of hidden light particles that decay to the Standard Model. In this model, on higher dimensional warped branes, various warped Kaluza-Klein particles and the zero-mode of gauge field play roles of the hidden dark matter or mediators to the Standard Model.Comment: 15 pages; v4, several clarifications added, update on Fermi/HESS result

Astrophysical Uncertainties in the Cosmic Ray Electron and Positron Spectrum From Annihilating Dark Matter

In recent years, a number of experiments have been conducted with the goal of studying cosmic rays at GeV to TeV energies. This is a particularly interesting regime from the perspective of indirect dark matter detection. To draw reliable conclusions regarding dark matter from cosmic ray measurements, however, it is important to first understand the propagation of cosmic rays through the magnetic and radiation fields of the Milky Way. In this paper, we constrain the characteristics of the cosmic ray propagation model through comparison with observational inputs, including recent data from the CREAM experiment, and use these constraints to estimate the corresponding uncertainties in the spectrum of cosmic ray electrons and positrons from dark matter particles annihilating in the halo of the Milky Way.Comment: 21 pages, 9 figure

Infectious Offspring: How Birds Acquire and Transmit an Avian Polyomavirus in the Wild

Detailed patterns of primary virus acquisition and subsequent dispersal in wild vertebrate populations are virtually absent. We show that nestlings of a songbird acquire polyomavirus infections from larval blowflies, common nest ectoparasites of cavity-nesting birds, while breeding adults acquire and renew the same viral infections via cloacal shedding from their offspring. Infections by these DNA viruses, known potential pathogens producing disease in some bird species, therefore follow an ‘upwards vertical’ route of an environmental nature mimicking horizontal transmission within families, as evidenced by patterns of viral infection in adults and young of experimental, cross-fostered offspring. This previously undescribed route of viral transmission from ectoparasites to offspring to parent hosts may be a common mechanism of virus dispersal in many taxa that display parental care

The Leptonic Higgs as a Messenger of Dark Matter

We propose that the leptonic cosmic ray signals seen by PAMELA and ATIC result from the annihilation or decay of dark matter particles via states of a leptonic Higgs doublet to $\tau$ leptons, linking cosmic ray signals of dark matter to LHC signals of the Higgs sector. The states of the leptonic Higgs doublet are lighter than about 200 GeV, yielding large $\bar{\tau} \tau$ and $\bar{\tau} \tau \bar{\tau} \tau$ event rates at the LHC. Simple models are given for the dark matter particle and its interactions with the leptonic Higgs, for cosmic ray signals arising from both annihilations and decays in the galactic halo. For the case of annihilations, cosmic photon and neutrino signals are on the verge of discovery.Comment: 34 pages, 9 figures, minor typos corrected, references adde