Health effects of acid aerosols formed by atmospheric mixtures.

Under ambient conditions, sulfur and nitrogen oxides can react with photochemical products and airborne particles to form acidic vapors and aerosols. Inhalation toxicological studies were conducted, exposing laboratory animals, at rest and during exercise, to multicomponent atmospheric mixtures under conditions favorable to the formation of acidic reaction products. Effects of acid and ozone mixtures on early and late clearance of insoluble radioactive particles in the lungs of rats appeared to be dominated by the oxidant component (i.e., the mixture did cause effects that were significantly different from those of ozone alone). Histopathological evaluations showed that sulfuric acid particles alone did not cause inflammatory responses in centriacinar units of rat lung parenchyma (expressed in terms of percent lesion area) but did cause significant damage (cell killing followed by a wave of cell replication) in nasal respiratory epithelium, as measured by uptake of tritiated thymidine in the DNA of replicating cells. Mixtures of ozone and nitrogen dioxide, which form nitric acid, caused significant inflammatory responses in lung parenchyma (in excess of effects seen in rats exposed to ozone alone), but did not damage nasal epithelium. Mixtures containing acidic sulfate particles, ozone, and nitrogen dioxide damaged both lung parenchyma and nasal epithelia. In rats exposed at rest, the response of the lung appeared to be dominated by the oxidant gas-phase components, while responses in the nose were dominated by the acidic particles. In rats exposed at exercise, however, mixtures of ozone and sulfuric acid particles significantly (2.5-fold) elevated the degree of lung lesion formation over that seen in rats exposed to ozone alone under an identical exercise protocol

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

Pediatric Feeding Disorder: Consensus Definition and Conceptual Framework

Pediatric feeding disorders (PFDs) lack a universally accepted definition. Feeding disorders require comprehensive assessment and treatment of 4 closely related, complementary domains (medical, psychosocial, and feeding skill-based systems and associated nutritional complications). Previous diagnostic paradigms have, however, typically defined feeding disorders using the lens of a single professional discipline and fail to characterize associated functional limitations that are critical to plan appropriate interventions and improve quality of life. Using the framework of the World Health Organization International Classification of Functioning, Disability, and Health, a unifying diagnostic term is proposed: “Pediatric Feeding Disorder” (PFD), defined as impaired oral intake that is not age-appropriate, and is associated with medical, nutritional, feeding skill, and/or psychosocial dysfunction. By incorporating associated functional limitations, the proposed diagnostic criteria for PFD should enable practitioners and researchers to better characterize the needs of heterogeneous patient populations, facilitate inclusion of all relevant disciplines in treatment planning, and promote the use of common, precise, terminology necessary to advance clinical practice, research, and health-care policy

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

Inhalation exposure methodology.

Modern man is being confronted with an ever-increasing inventory of potentially toxic airborne substances. Exposures to these atmospheric contaminants occur in residential and commercial settings, as well as in the workplace. In order to study the toxicity of such materials, a special technology relating to inhalation exposure systems has evolved. The purpose of this paper is to provide a description of the techniques which are used in exposing laboratory subjects to airborne particles and gases. The various modes of inhalation exposure (whole body, head only, nose or mouth only, etc.) are described at length, including the advantages and disadvantages inherent to each mode. Numerous literature citations are included for further reading. Among the topics briefly discussed are the selection of appropriate animal species for toxicological testing, and the types of inhalation studies performed (acute, chronic, etc.)

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

Simplified Models for LHC New Physics Searches

This document proposes a collection of simplified models relevant to the design of new-physics searches at the LHC and the characterization of their results. Both ATLAS and CMS have already presented some results in terms of simplified models, and we encourage them to continue and expand this effort, which supplements both signature-based results and benchmark model interpretations. A simplified model is defined by an effective Lagrangian describing the interactions of a small number of new particles. Simplified models can equally well be described by a small number of masses and cross-sections. These parameters are directly related to collider physics observables, making simplified models a particularly effective framework for evaluating searches and a useful starting point for characterizing positive signals of new physics. This document serves as an official summary of the results from the "Topologies for Early LHC Searches" workshop, held at SLAC in September of 2010, the purpose of which was to develop a set of representative models that can be used to cover all relevant phase space in experimental searches. Particular emphasis is placed on searches relevant for the first ~50-500 pb-1 of data and those motivated by supersymmetric models. This note largely summarizes material posted at http://lhcnewphysics.org/, which includes simplified model definitions, Monte Carlo material, and supporting contacts within the theory community. We also comment on future developments that may be useful as more data is gathered and analyzed by the experiments.Comment: 40 pages, 2 figures. This document is the official summary of results from "Topologies for Early LHC Searches" workshop (SLAC, September 2010). Supplementary material can be found at http://lhcnewphysics.or

Precision medicine for mood disorders: objective assessment, risk prediction, pharmacogenomics, and repurposed drugs

Mood disorders (depression, bipolar disorders) are prevalent and disabling. They are also highly co-morbid with other psychiatric disorders. Currently there are no objective measures, such as blood tests, used in clinical practice, and available treatments do not work in everybody. The development of blood tests, as well as matching of patients with existing and new treatments, in a precise, personalized and preventive fashion, would make a significant difference at an individual and societal level. Early pilot studies by us to discover blood biomarkers for mood state were promising [1], and validated by others [2]. Recent work by us has identified blood gene expression biomarkers that track suicidality, a tragic behavioral outcome of mood disorders, using powerful longitudinal within-subject designs, validated them in suicide completers, and tested them in independent cohorts for ability to assess state (suicidal ideation), and ability to predict trait (future hospitalizations for suicidality) [3-6]. These studies showed good reproducibility with subsequent independent genetic studies [7]. More recently, we have conducted such studies also for pain [8], for stress disorders [9], and for memory/Alzheimer's Disease [10]. We endeavored to use a similar comprehensive approach to identify more definitive biomarkers for mood disorders, that are transdiagnostic, by studying mood in psychiatric disorders patients. First, we used a longitudinal within-subject design and whole-genome gene expression approach to discover biomarkers which track mood state in subjects who had diametric changes in mood state from low to high, from visit to visit, as measured by a simple visual analog scale that we had previously developed (SMS-7). Second, we prioritized these biomarkers using a convergent functional genomics (CFG) approach encompassing in a comprehensive fashion prior published evidence in the field. Third, we validated the biomarkers in an independent cohort of subjects with clinically severe depression (as measured by Hamilton Depression Scale, (HAMD)) and with clinically severe mania (as measured by the Young Mania Rating Scale (YMRS)). Adding the scores from the first three steps into an overall convergent functional evidence (CFE) score, we ended up with 26 top candidate blood gene expression biomarkers that had a CFE score as good as or better than SLC6A4, an empirical finding which we used as a de facto positive control and cutoff. Notably, there was among them an enrichment in genes involved in circadian mechanisms. We further analyzed the biological pathways and networks for the top candidate biomarkers, showing that circadian, neurotrophic, and cell differentiation functions are involved, along with serotonergic and glutamatergic signaling, supporting a view of mood as reflecting energy, activity and growth. Fourth, we tested in independent cohorts of psychiatric patients the ability of each of these 26 top candidate biomarkers to assess state (mood (SMS-7), depression (HAMD), mania (YMRS)), and to predict clinical course (future hospitalizations for depression, future hospitalizations for mania). We conducted our analyses across all patients, as well as personalized by gender and diagnosis, showing increased accuracy with the personalized approach, particularly in women. Again, using SLC6A4 as the cutoff, twelve top biomarkers had the strongest overall evidence for tracking and predicting depression after all four steps: NRG1, DOCK10, GLS, PRPS1, TMEM161B, GLO1, FANCF, HNRNPDL, CD47, OLFM1, SMAD7, and SLC6A4. Of them, six had the strongest overall evidence for tracking and predicting both depression and mania, hence bipolar mood disorders. There were also two biomarkers (RLP3 and SLC6A4) with the strongest overall evidence for mania. These panels of biomarkers have practical implications for distinguishing between depression and bipolar disorder. Next, we evaluated the evidence for our top biomarkers being targets of existing psychiatric drugs, which permits matching patients to medications in a targeted fashion, and the measuring of response to treatment. We also used the biomarker signatures to bioinformatically identify new/repurposed candidate drugs. Top drugs of interest as potential new antidepressants were pindolol, ciprofibrate, pioglitazone and adiphenine, as well as the natural compounds asiaticoside and chlorogenic acid. The last 3 had also been identified by our previous suicidality studies. Finally, we provide an example of how a report to doctors would look for a patient with depression, based on the panel of top biomarkers (12 for depression and bipolar, one for mania), with an objective depression score, risk for future depression, and risk for bipolar switching, as well as personalized lists of targeted prioritized existing psychiatric medications and new potential medications. Overall, our studies provide objective assessments, targeted therapeutics, and monitoring of response to treatment, that enable precision medicine for mood disorders

The antioxidant enzyme peroxiredoxin-2 is depleted in lymphocytes seven days after ultra-endurance exercise

Purpose: Peroxiredoxin-2 (PRDX-2) is an antioxidant and chaperone-like protein critical for cell function. This study examined whether the levels of lymphocyte PRDX-2 are altered over one month following ultra-endurance exercise. Methods: Nine middle-aged men undertook a single-stage, multi-day 233 km (145 mile) ultra-endurance running race. Blood was collected immediately before (PRE), upon completion/retirement (POST), and following the race at DAY 1, DAY 7 and DAY 28. Lymphocyte lysates were examined for PRDX-2 by reducing SDS-PAGE and western blotting. In a sub-group of men who completed the race (n = 4) PRDX-2 oligomeric state (indicative of redox status) was investigated. Results: Ultra-endurance exercise caused significant changes in lymphocyte PRDX-2 (F (4,32) 3.409, p=0.020, ?(2) =0.299): seven-days after the race, PRDX-2 levels in lymphocytes had fallen to 30% of pre-race values (p=0.013) and returned to near-normal levels at DAY 28. Non-reducing gels demonstrated that dimeric PRDX-2 (intracellular reduced PRDX-2 monomers) was increased in 3 of 4 race completers immediately post-race, indicative of an "antioxidant response". Moreover, monomeric PRDX-2 was also increased immediately post-race in 2 of 4 race-completing subjects, indicative of oxidative damage, which was not detectable by DAY 7. Conclusions: Lymphocyte PRDX-2 was decreased below normal levels 7 days after ultra-endurance exercise. Excessive accumulation of reactive oxygen species induced by ultra-endurance exercise may underlie depletion of lymphocyte PRDX-2 by triggering its turnover after oxidation. Low levels of lymphocyte PRDX-2 could influence cell function and might, in part, explain reports of dysregulated immunity following ultra-endurance exercise