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Burn injury induces a systemic hyperinflammatory response with detrimental side effects. Studies have described the biochemical changes induced by severe burns, but the transcriptome response is not well characterized. The goal of this work is to characterize the blood transcriptome after burn injury. Burn patients presenting to a regional center between 2012 and 2017 were prospectively enrolled. Blood was collected on admission and at predetermined time points (hours 2, 4, 8, 12, and 24). RNA was isolated and transcript levels were measured with a gene expression microarray. To identify differentially regulated genes (false-discovery rate ≤0.1) by burn injury severity, patients were grouped by TBSA above or below 20% and statistically enriched pathways were identified. Sixty-eight patients were analyzed, most patients were male with a median age of 41 (interquartile range, 30.5–58.5) years, and TBSA of 20% (11%–34%). Thirty-five patients had % TBSA injury ≥20%, and this group experienced greater mortality (26% vs 3%, P = .008). Comparative analysis of genes from patients with

Adverse effects of spaceflight on musculoskeletal health increase the risk of bone injury and impairment of fracture healing. Its yet elusive molecular comprehension warrants immediate attention, since space travel is becoming more frequent. Here we examined the effects of spaceflight on bone fracture healing using a 2 mm femoral segmental bone defect (SBD) model. Forty, 9-week-old, male C57BL/6J mice were randomized into 4 groups: 1) Sham surgery on Ground (G-Sham); 2) Sham surgery housed in Spaceflight (FLT-Sham); 3) SBD surgery on Ground (G-Surgery); and 4) SBD surgery housed in Spaceflight (FLT-Surgery). Surgery procedures occurred 4 days prior to launch; post-launch, the spaceflight mice were house in the rodent habitats on the International Space Station (ISS) for approximately 4 weeks before euthanasia. Mice remaining on the Earth were subjected to identical housing and experimental conditions. The right femur from half of the spaceflight and ground groups was investigated by micro-computed tomography (µCT). In the remaining mice, the callus regions from surgery groups and corresponding femoral segments in sham mice were probed by global transcriptomic and metabolomic assays. µCT confirmed escalated bone loss in FLT-Sham compared to G-Sham mice. Comparing to their respective on-ground counterparts, the morbidity gene-network signal was inhibited in sham spaceflight mice but activated in the spaceflight callus. µCT analyses of spaceflight callus revealed increased trabecular spacing and decreased trabecular connectivity. Activated apoptotic signals in spaceflight callus were synchronized with inhibited cell migration signals that potentially hindered the wound site to recruit growth factors. A major pro-apoptotic and anti-migration gene network, namely the RANK-NFκB axis, emerged as the central node in spaceflight callus. Concluding, spaceflight suppressed a unique biomolecular mechanism in callus tissue to facilitate a failed regeneration, which merits a customized intervention strategy.

Funding Information: This work was supported by the National Institute of Mental Health / U.S. Army Medical Research and Development Command (Grant No. R01MH106595 [to CMN, IL, MBS, KJRe, and KCK], National Institutes of Health (Grant No. 5U01MH109539 to the Psychiatric Genomics Consortium ), and Brain & Behavior Research Foundation (Young Investigator Grant [to KWC]). Genotyping of samples was provided in part through the Stanley Center for Psychiatric Genetics at the Broad Institute supported by Cohen Veterans Bioscience . Statistical analyses were carried out on the LISA/Genetic Cluster Computer ( https://userinfo.surfsara.nl/systems/lisa ) hosted by SURFsara. This research has been conducted using the UK Biobank resource (Application No. 41209). This work would have not been possible without the financial support provided by Cohen Veterans Bioscience, the Stanley Center for Psychiatric Genetics at the Broad Institute, and One Mind. Funding Information: MBS has in the past 3 years received consulting income from Actelion, Acadia Pharmaceuticals, Aptinyx, Bionomics, BioXcel Therapeutics, Clexio, EmpowerPharm, GW Pharmaceuticals, Janssen, Jazz Pharmaceuticals, and Roche/Genentech and has stock options in Oxeia Biopharmaceuticals and Epivario. In the past 3 years, NPD has held a part-time paid position at Cohen Veterans Bioscience, has been a consultant for Sunovion Pharmaceuticals, and is on the scientific advisory board for Sentio Solutions for unrelated work. In the past 3 years, KJRe has been a consultant for Datastat, Inc., RallyPoint Networks, Inc., Sage Pharmaceuticals, and Takeda. JLM-K has received funding and a speaking fee from COMPASS Pathways. MU has been a consultant for System Analytic. HRK is a member of the Dicerna scientific advisory board and a member of the American Society of Clinical Psychopharmacology Alcohol Clinical Trials Initiative, which during the past 3 years was supported by Alkermes, Amygdala Neurosciences, Arbor Pharmaceuticals, Dicerna, Ethypharm, Indivior, Lundbeck, Mitsubishi, and Otsuka. HRK and JG are named as inventors on Patent Cooperative Treaty patent application number 15/878,640, entitled “Genotype-guided dosing of opioid agonists,” filed January 24, 2018. RP and JG are paid for their editorial work on the journal Complex Psychiatry. OAA is a consultant to HealthLytix. All other authors report no biomedical financial interests or potential conflicts of interest. Funding Information: This work was supported by the National Institute of Mental Health/ U.S. Army Medical Research and Development Command (Grant No. R01MH106595 [to CMN, IL, MBS, KJRe, and KCK], National Institutes of Health (Grant No. 5U01MH109539 to the Psychiatric Genomics Consortium), and Brain & Behavior Research Foundation (Young Investigator Grant [to KWC]). Genotyping of samples was provided in part through the Stanley Center for Psychiatric Genetics at the Broad Institute supported by Cohen Veterans Bioscience. Statistical analyses were carried out on the LISA/Genetic Cluster Computer (https://userinfo.surfsara.nl/systems/lisa) hosted by SURFsara. This research has been conducted using the UK Biobank resource (Application No. 41209). This work would have not been possible without the financial support provided by Cohen Veterans Bioscience, the Stanley Center for Psychiatric Genetics at the Broad Institute, and One Mind. This material has been reviewed by the Walter Reed Army Institute of Research. There is no objection to its presentation and/or publication. The opinions or assertions contained herein are the private views of the authors and are not to be construed as official or as reflecting true views of the U.S. Department of the Army or the Department of Defense. We thank the investigators who comprise the PGC-PTSD working group and especially the more than 206,000 research participants worldwide who shared their life experiences and biological samples with PGC-PTSD investigators. We thank Mark Zervas for his critical input. Full acknowledgments are in Supplement 1. MBS has in the past 3 years received consulting income from Actelion, Acadia Pharmaceuticals, Aptinyx, Bionomics, BioXcel Therapeutics, Clexio, EmpowerPharm, GW Pharmaceuticals, Janssen, Jazz Pharmaceuticals, and Roche/Genentech and has stock options in Oxeia Biopharmaceuticals and Epivario. In the past 3 years, NPD has held a part-time paid position at Cohen Veterans Bioscience, has been a consultant for Sunovion Pharmaceuticals, and is on the scientific advisory board for Sentio Solutions for unrelated work. In the past 3 years, KJRe has been a consultant for Datastat, Inc. RallyPoint Networks, Inc. Sage Pharmaceuticals, and Takeda. JLM-K has received funding and a speaking fee from COMPASS Pathways. MU has been a consultant for System Analytic. HRK is a member of the Dicerna scientific advisory board and a member of the American Society of Clinical Psychopharmacology Alcohol Clinical Trials Initiative, which during the past 3 years was supported by Alkermes, Amygdala Neurosciences, Arbor Pharmaceuticals, Dicerna, Ethypharm, Indivior, Lundbeck, Mitsubishi, and Otsuka. HRK and JG are named as inventors on Patent Cooperative Treaty patent application number 15/878,640, entitled ?Genotype-guided dosing of opioid agonists,? filed January 24, 2018. RP and JG are paid for their editorial work on the journal Complex Psychiatry. OAA is a consultant to HealthLytix. All other authors report no biomedical financial interests or potential conflicts of interest. Publisher Copyright: © 2021 Society of Biological Psychiatry Background: Posttraumatic stress disorder (PTSD) is heritable and a potential consequence of exposure to traumatic stress. Evidence suggests that a quantitative approach to PTSD phenotype measurement and incorporation of lifetime trauma exposure (LTE) information could enhance the discovery power of PTSD genome-wide association studies (GWASs). Methods: A GWAS on PTSD symptoms was performed in 51 cohorts followed by a fixed-effects meta-analysis (N = 182,199 European ancestry participants). A GWAS of LTE burden was performed in the UK Biobank cohort (N = 132,988). Genetic correlations were evaluated with linkage disequilibrium score regression. Multivariate analysis was performed using Multi-Trait Analysis of GWAS. Functional mapping and annotation of leading loci was performed with FUMA. Replication was evaluated using the Million Veteran Program GWAS of PTSD total symptoms. Results: GWASs of PTSD symptoms and LTE burden identified 5 and 6 independent genome-wide significant loci, respectively. There was a 72% genetic correlation between PTSD and LTE. PTSD and LTE showed largely similar patterns of genetic correlation with other traits, albeit with some distinctions. Adjusting PTSD for LTE reduced PTSD heritability by 31%. Multivariate analysis of PTSD and LTE increased the effective sample size of the PTSD GWAS by 20% and identified 4 additional loci. Four of these 9 PTSD loci were independently replicated in the Million Veteran Program. Conclusions: Through using a quantitative trait measure of PTSD, we identified novel risk loci not previously identified using prior case-control analyses. PTSD and LTE have a high genetic overlap that can be leveraged to increase discovery power through multivariate methods. publishersversion published

The Tri-Service Microbiome Consortium (TSMC) was founded to enhance collaboration, coordination, and communication of microbiome research among U.S. Department of Defense (DoD) organizations and to facilitate resource, material and information sharing among consortium members. The 2019 annual symposium was held 22–24 October 2019 at Wright-Patterson Air Force Base in Dayton, OH. Presentations and discussions centered on microbiome-related topics within five broad thematic areas: 1) human microbiomes; 2) transitioning products into Warfighter solutions; 3) environmental microbiomes; 4) engineering microbiomes; and 5) microbiome simulation and characterization. Collectively, the symposium provided an update on the scope of current DoD microbiome research efforts, highlighted innovative research being done in academia and industry that can be leveraged by the DoD, and fostered collaborative opportunities. This report summarizes the presentations and outcomes of the 3rd annual TSMC symposium.

Active-duty Army personnel can be exposed to traumatic warzone events and are at increased risk for developing post-traumatic stress disorder (PTSD) compared with the general population. PTSD is associated with high individual and societal costs, but identification of predictive markers to determine deployment readiness and risk mitigation strategies is not well understood. This prospective longitudinal naturalistic cohort study—the Fort Campbell Cohort study—examined the value of using a large multidimensional dataset collected from soldiers prior to deployment to Afghanistan for predicting post-deployment PTSD status. The dataset consisted of polygenic, epigenetic, metabolomic, endocrine, inflammatory and routine clinical lab markers, computerized neurocognitive testing, and symptom self-reports. The analysis was computed on active-duty Army personnel (N = 473) of the 101st Airborne at Fort Campbell, Kentucky. Machine-learning models predicted provisional PTSD diagnosis 90–180 days post deployment (random forest: AUC = 0.78, 95% CI = 0.67–0.89, sensitivity = 0.78, specificity = 0.71; SVM: AUC = 0.88, 95% CI = 0.78–0.98, sensitivity = 0.89, specificity = 0.79) and longitudinal PTSD symptom trajectories identified with latent growth mixture modeling (random forest: AUC = 0.85, 95% CI = 0.75–0.96, sensitivity = 0.88, specificity = 0.69; SVM: AUC = 0.87, 95% CI = 0.79–0.96, sensitivity = 0.80, specificity = 0.85). Among the highest-ranked predictive features were pre-deployment sleep quality, anxiety, depression, sustained attention, and cognitive flexibility. Blood-based biomarkers including metabolites, epigenomic, immune, inflammatory, and liver function markers complemented the most important predictors. The clinical prediction of post-deployment symptom trajectories and provisional PTSD diagnosis based on pre-deployment data achieved high discriminatory power. The predictive models may be used to determine deployment readiness and to determine novel pre-deployment interventions to mitigate the risk for deployment-related PTSD.

DNA methylation patterns at specific cytosine-phosphate-guanine (CpG) sites predictably change with age and can be used to derive “epigenetic age”, an indicator of biological age, as opposed to merely chronological age. A relatively new estimator, called “DNAm GrimAge”, is notable for its superior predictive ability in older populations regarding numerous age-related metrics like time-to-death, time-to-coronary heart disease, and time-to-cancer. PTSD is associated with premature mortality and frequently has comorbid physical illnesses suggestive of accelerated biological aging. This is the first study to assess DNAm GrimAge in PTSD patients. We investigated the acceleration of GrimAge relative to chronological age, denoted “AgeAccelGrim” in combat trauma-exposed male veterans with and without PTSD using cross-sectional and longitudinal data from two independent well-characterized veteran cohorts. In both cohorts, AgeAccelGrim was significantly higher in the PTSD group compared to the control group (N = 162, 1.26 vs −0.57, p = 0.001 and N = 53, 0.93 vs −1.60 Years, p = 0.008), suggesting accelerated biological aging in both cohorts with PTSD. In 3-year follow-up study of individuals initially diagnosed with PTSD (N = 26), changes in PTSD symptom severity were correlated with AgeAccelGrim changes (r = 0.39, p = 0.049). In addition, the loss of CD28 cell surface markers on CD8 + T cells, an indicator of T-cell senescence/exhaustion that is associated with biological aging, was positively correlated with AgeAccelGrim, suggesting an immunological contribution to the accelerated biological aging. Overall, our findings delineate cellular correlates of biological aging in combat-related PTSD, which may help explain the increased medical morbidity and mortality seen in this disease.

Epigenetic changes are currently invoked as explanations for both the chronicity and tenacity of post-traumatic stress disorder (PTSD), a heterogeneous condition showing varying, sometimes idiosyncratic responses to treatment. This study evaluated epigenetic markers in the context of a randomized clinical trial of PTSD patients undergoing prolonged-exposure psychotherapy with and without a hydrocortisone augmentation prior to each session. The purpose of the longitudinal epigenome-wide analyses was to identify predictors of recovery (from pretreatment data) or markers associated with symptom change (based on differences between pre- and post-therapy epigenetic changes). The results of these analyses identified the CREB–BDNF signaling pathway, previously linked to startle reaction and fear learning and memory processes, as a convergent marker predicting both symptom change and severity. Several previous-reported resilience markers were also identified (FKBP5, NR3C1, SDK1, and MAD1L1) to associate with PTSD recovery in this study. Especially, the methylation levels of FKBP5 in the gene body region decreased significantly as CAPS score decreased in responders, while no changes occurred in nonresponders. These biomarkers may have future utility in understanding clinical recovery in PTSD and potential applications in predicting treatment effects.

Spaceflight results in reduced mechanical loading of the skeleton, which leads to dramatic bone loss. Low bone mass is associated with increased fracture risk, and this combination may compromise future, long-term, spaceflight missions. Here, we examined the systemic effects of spaceflight and fracture surgery/healing on several non-injured bones within the axial and appendicular skeleton. Forty C57BL/6, male mice were randomized into the following groups: (1) Sham surgery mice housed on the earth (Ground + Sham); (2) Femoral segmental bone defect surgery mice housed on the earth (Ground + Surgery); (3) Sham surgery mice housed in spaceflight (Flight + Sham); and (4) Femoral segmental bone defect surgery mice housed in spaceflight (Flight + Surgery). Mice were 9 weeks old at the time of launch and were euthanized approximately 4 weeks after launch. Micro-computed tomography (μCT) was used to evaluate standard bone parameters in the tibia, humerus, sternebra, vertebrae, ribs, calvarium, mandible, and incisor. One intriguing finding was that both spaceflight and surgery resulted in virtually identical losses in tibial trabecular bone volume fraction, BV/TV (24–28% reduction). Another important finding was that surgery markedly changed tibial cortical bone geometry. Understanding how spaceflight, surgery, and their combination impact non-injured bones will improve treatment strategies for astronauts and terrestrial humans alike.

Attempts to correlate blood levels of brain-derived neurotrophic factor (BDNF) with post-traumatic stress disorder (PTSD) have provided conflicting results. Some studies found a positive association between BDNF and PTSD diagnosis and symptom severity, while others found the association to be negative. The present study investigated whether serum levels of BDNF are different cross-sectionally between combat trauma-exposed veterans with and without PTSD, as well as whether longitudinal changes in serum BDNF differ as a function of PTSD diagnosis over time. We analyzed data of 270 combat trauma-exposed veterans (230 males, 40 females, average age: 33.29 ± 8.28 years) and found that, at the initial cross-sectional assessment (T0), which averaged 6 years after the initial exposure to combat trauma (SD=2.83 years), the PTSD positive group had significantly higher serum BDNF levels than the PTSD negative controls [31.03 vs. 26.95 ng/mL, t(268) = 3.921, p

We sought to find clinical subtypes of posttraumatic stress disorder (PTSD) in veterans 6–10 years post-trauma exposure based on current symptom assessments and to examine whether blood biomarkers could differentiate them. Samples were males deployed to Iraq and Afghanistan studied by the PTSD Systems Biology Consortium: a discovery sample of 74 PTSD cases and 71 healthy controls (HC), and a validation sample of 26 PTSD cases and 36 HC. A machine learning method, random forests (RF), in conjunction with a clustering method, partitioning around medoids, were used to identify subtypes derived from 16 self-report and clinician assessment scales, including the clinician-administered PTSD scale for DSM-IV (CAPS). Two subtypes were identified, designated S1 and S2, differing on mean current CAPS total scores: S2 = 75.6 (sd 14.6) and S1 = 54.3 (sd 6.6). S2 had greater symptom severity scores than both S1 and HC on all scale items. The mean first principal component score derived from clinical summary scales was three times higher in S2 than in S1. Distinct RFs were grown to classify S1 and S2 vs. HCs and vs. each other on multi-omic blood markers feature classes of current medical comorbidities, neurocognitive functioning, demographics, pre-military trauma, and psychiatric history. Among these classes, in each RF intergroup comparison of S1, S2, and HC, multi-omic biomarkers yielded the highest AUC-ROCs (0.819–0.922); other classes added little to further discrimination of the subtypes. Among the top five biomarkers in each of these RFs were methylation, micro RNA, and lactate markers, suggesting their biological role in symptom severity.

Major depressive disorder (MDD) is associated with premature mortality and is an independent risk factor for a broad range of diseases, especially those associated with aging, such as cardiovascular disease, diabetes, and Alzheimer’s disease. However, the pathophysiology underlying increased rates of somatic disease in MDD remains unknown. It has been proposed that MDD represents a state of accelerated cellular aging, and several measures of cellular aging have been developed in recent years. Among such metrics, estimators of biological age based on predictable age-related patterns of DNA methylation (DNAm), so-called ‘epigenetic clocks’, have shown particular promise for their ability to capture accelerated aging in psychiatric disease. The recently developed DNAm metric known as ‘GrimAge’ is unique in that it was trained on time-to-death data and has outperformed its predecessors in predicting both morbidity and mortality. Yet, GrimAge has not been investigated in MDD. Here we measured GrimAge in 49 somatically healthy unmedicated individuals with MDD and 60 age-matched healthy controls. We found that individuals with MDD exhibited significantly greater GrimAge relative to their chronological age (‘AgeAccelGrim’) compared to healthy controls (p = 0.001), with a median of 2 years of excess cellular aging. This difference remained significant after controlling for sex, current smoking status, and body-mass index (p = 0.015). These findings are consistent with prior suggestions of accelerated cellular aging in MDD, but are the first to demonstrate this with an epigenetic metric predictive of premature mortality.

With increased human presence in space, bone loss and fractures will occur. Thrombopoietin (TPO) is a recently patented bone healing agent. Here, we investigated the systemic effects of TPO on mice subjected to spaceflight and sustaining a bone fracture. Forty, 9-week-old, male, C57BL/6 J were divided into 4 groups: (1) Saline+Earth; (2) TPO + Earth; (3) Saline+Flight; and (4) TPO + Flight (n = 10/group). Saline- and TPO-treated mice underwent a femoral defect surgery, and 20 mice were housed in space (“Flight”) and 20 mice on Earth for approximately 4 weeks. With the exception of the calvarium and incisor, positive changes were observed in TPO-treated, spaceflight bones, suggesting TPO may improve osteogenesis in the absence of mechanical loading. Thus, TPO, may serve as a new bone healing agent, and may also improve some skeletal properties of astronauts, which might be extrapolated for patients on Earth with restraint mobilization and/or are incapable of bearing weight on their bones.

Background Traumatic stress can adversely affect physical and mental health through neurobiological stress response systems. We examined the effects of trauma exposure and posttraumatic stress disorder (PTSD) on telomere length, a biomarker of cellular aging, and volume of the amygdala, a key structure of stress regulation, in combat-exposed veterans. In addition, the relationships of psychopathological symptoms and autonomic function with telomere length and amygdala volume were examined. Methods Male combat veterans were categorized as having PTSD diagnosis (n = 102) or no lifetime PTSD diagnosis (n = 111) based on the Clinician-Administered PTSD Scale. Subjects were assessed for stress-related psychopathology, trauma severity, autonomic function, and amygdala volumes by magnetic resonance imaging. Results A significant interaction was found between trauma severity and PTSD status for telomere length and amygdala volume after adjusting for multiple confounders. Subjects with PTSD showed shorter telomere length and larger amygdala volume than those without PTSD among veterans exposed to high trauma, while there was no significant group difference in these parameters among those exposed to low trauma. Among veterans exposed to high trauma, greater telomere shortening was significantly correlated with greater norepinephrine, and larger amygdala volume was correlated with more severe psychological symptoms and higher heart rates. Conclusions These data suggest that the intensity of the index trauma event plays an important role in interacting with PTSD symptomatology and autonomic activity in predicting telomere length and amygdala volume. These results highlight the importance of trauma severity and PTSD status in predicting certain biological outcomes.

Post-traumatic stress disorder (PTSD) is a heterogeneous condition evidenced by the absence of objective physiological measurements applicable to all who meet the criteria for the disorder as well as divergent responses to treatments. This study capitalized on biological diversity observed within the PTSD group observed following epigenome-wide analysis of a well-characterized Discovery cohort (N = 166) consisting of 83 male combat exposed veterans with PTSD, and 83 combat veterans without PTSD in order to identify patterns that might distinguish subtypes. Computational analysis of DNA methylation (DNAm) profiles identified two PTSD biotypes within the PTSD+ group, G1 and G2, associated with 34 clinical features that are associated with PTSD and PTSD comorbidities. The G2 biotype was associated with an increased PTSD risk and had higher polygenic risk scores and a greater methylation compared to the G1 biotype and healthy controls. The findings were validated at a 3-year follow-up (N = 59) of the same individuals as well as in two independent, veteran cohorts (N = 54 and N = 38), and an active duty cohort (N = 133). In some cases, for example Dopamine-PKA-CREB and GABA-PKC-CREB signaling pathways, the biotypes were oppositely dysregulated, suggesting that the biotypes were not simply a function of a dimensional relationship with symptom severity, but may represent distinct biological risk profiles underpinning PTSD. The identification of two novel distinct epigenetic biotypes for PTSD may have future utility in understanding biological and clinical heterogeneity in PTSD and potential applications in risk assessment for active duty military personnel under non-clinician-administered settings, and improvement of PTSD diagnostic markers.

Childhood maltreatment is highly prevalent and serves as a risk factor for mental and physical disorders. Self-reported childhood maltreatment appears heritable, but the specific genetic influences on this phenotype are largely unknown. The aims of this study were to 1) identify genetic variation associated with reported childhood maltreatment, 2) calculate the relevant SNP-based heritability estimates, and 3) quantify the genetic overlap of reported childhood maltreatment with mental and physical health-related phenotypes. Genome-wide association analysis for childhood maltreatment was undertaken, using a discovery sample from the UK Biobank (UKBB) (n=124,000) and a replication sample from the Psychiatric Genomics Consortium–posttraumatic stress disorder working group (PGC-PTSD) (n=26,290). Heritability estimations for childhood maltreatment and genetic correlations with mental/physical health traits were calculated using linkage disequilibrium score regression (LDSR). Two genome-wide significant loci associated with childhood maltreatment, located on chromosomes 3p13 (rs142346759, beta=0.015, p=4.35×10−8,FOXP1) and 7q31.1 (rs10262462, beta=-0.016, p=3.24×10−8,FOXP2), were identified in the discovery dataset but were not replicated in the PGC-PTSD sample. SNP-based heritability for childhood maltreatment was estimated to be ∼6%. Childhood maltreatment was most significantly genetically correlated with depressive symptoms (rg=0.70, p=4.65×10−40). This is the first large-scale genetic study to identify specific variants associated with self-reported childhood maltreatment.FOXPgenes could influence traits such as depression and thereby be relevant to childhood maltreatment. Alternatively, these variants may be associated with a greater likelihood of reporting maltreatment. A clearer understanding of the genetic relationships of childhood maltreatment, including particular abuse subtypes, with various psychiatric disorders, may ultimately be useful in in developing targeted treatment and prevention strategies.

PTSD is associated with metabolic comorbidities; however it is not clear how the neuroendocrine disturbances affect metabolism. To analyze this we employed a systems biological approach using an integrated mathematical model of metabolism, HPA axis and inflammation. We combined the metabolomics, neuroendocrine, clinical lab and cytokine data from combat-exposed veterans with and without PTSD, to characterize the differences in regulatory effects. We used the pattern of fold change in metabolites representing pathway level differences as reference for metabolic control analysis (MCA) using the model. MCA revealed parameters constituting the HPA axis, inflammation and GPCR pathway that yielded metabolic dysfunction consistent with PTSD. To support this, we performed causal analysis between regulatory components and the significantly different metabolites in our sample. Causal inference revealed that the changes in glucocorticoid receptor sensitivity were mechanistically associated with metabolic dysfunction and the effects were jointly mediated by insulin resistance, inflammation, oxidative stress and energy deficit.

The degree of brain injury is the governing factor for the magnitude of the patient's psycho- and physiological deficits post-injury, and the associated long-term consequences. The present scaling method used to segregate the patients among mild, moderate and severe phases of traumatic brain injury (TBI) has major limitations; however, a more continuous stratification of TBI is still elusive. With the anticipation that differentiating molecular markers could be the backbone of a robust method to triage TBI, we used a modified closed-head injury (CHI) Marmarou model with two impact heights (IH). By definition, IH directly correlates with the impact force causing TBI. In our modified CHI model, the rat skull was fitted with a helmet to permit a diffuse axonal injury. With the frontal cortex as the focal point of injury, the adjacent brain regions (hippocampus, HC and cerebellum, CB) were susceptible to diffuse secondary shock injury. At 8 days post injury (po.i.), rats impacted by 120 cm IH (IH120) took a longer time to find an escape route in the Barnes maze as compared to those impacted by 100 cm IH (IH100). Using a time-resolved interrogation of the transcriptomic landscape of HC and CB tissues, we mined those genes that altered their regulations in correlation with the variable IHs. At 14 days po.i., when all rats demonstrated nearly normal visuomotor performance, the bio-functional analysis suggested an advanced healing mechanism in the HC of IH100 group. In contrast, the HC of IH120 group displayed a delayed healing with evidence of active cell death networks. Combining whole genome rat microarrays with behavioral analysis provided the insight of neuroprotective signals that could be the foundation of the next generation triage for TBI patients.

In the event of a mass casualty radiation scenario, rapid assessment of patients' health and triage is required for optimal resource utilization. Identifying the level and extent of exposure as well as prioritization of care is extremely challenging under such disaster conditions. Blood-based biomarkers, such as RNA integrity numbers (RIN), could help healthcare personnel quickly and efficiently determine the extent and effect of multiple injuries on patients' health. Evaluation of the effect of different radiation doses, alone or in combination with burn injury, on total RNA integrity over multiple time points was performed. Total RNA integrity was tallied in blood samples for potential application as a marker of radiation exposure and survival. Groups of aged mice (3-6 mice/group, 13-18 months old) received 0.5, 1, 5, 10 or 20 Gy ionizing radiation. Two additional mouse groups received low-dose irradiation (0.5 or 1 Gy) with a 15% total body surface area (TBSA) burn injury. Animals were euthanized at 2 or 12 h and at day 1, 2, 3, 7 or 14 postirradiation, or when injury-mediated mortality occurred. Total RNA was isolated from blood. The quality of RNA was evaluated and RNA RIN were obtained. Analysis of RIN indicated that blood showed the clearest radiation effect. There was a time- and radiation-dose-dependent reduction in RIN that was first detectable at 12 h postirradiation for all doses in animals receiving irradiation alone. This effect was reversible in lower-dose groups (i.e., 0.5, 1 and 5 Gy) that survived to the end of the study (14 days). In contrast, the effect persisted for 10 and 20 Gy groups, which showed suppression of RIN values4.5 with high mortalities. Radiation doses of 20 Gy were lethal and required euthanasia by day 6. A low RIN (2.5) at any time point was associated with 100% mortality. Combined radiation-burn injury produced significantly increased mortality such that no dually-injured animals survived beyond day 3, and no radiation dose1 Gy resulted in survival past day 1. More modest suppression of RIN was observed in the surviving dually challenged mice, and no statistically significant changes were identified in RIN values of burn-only mice at any time point. In this study of an animal model, a proof of concept is presented for a simple and accurate method of assessing radiation dose exposure in blood which potentially predicts lethality. RIN assessment of blood-derived RNA could form the basis for a clinical decision-support tool to guide healthcare providers under the strenuous conditions of a radiation-based mass casualty event.

Research into potentially novel biomarkers for chronic pain development is lacking. microRNAs (miRNAs) are attractive candidates as biomarkers due to their conservation across species, stability in liquid biopsies, and variation that corresponds to a pathologic state. miRNAs can be sorted into extracellular vesicles (EVs) within the cell and released from the site of injury. EVs transfer cargo molecules between cells thus affecting key intercellular signaling pathways. The focus of this study was to determine the plasma derived EV miRNA content in a chronic neuropathic pain rat model. This was accomplished by performing either spinal nerve ligation (SNL; n = 6) or sham (n = 6) surgery on anesthetized male Sprague-Dawley rats. Mechanosensitivity was assessed and plasma derived EV RNA was isolated at baseline (BL), day 3, and 15 postnerve injury. EV extracted small RNA was sequenced followed by differentially expressed (DE) miRNAs and gene target enrichment/signaling pathway analysis performed using R packages and TargetScan/Ingenuity pathway analysis (IPA), respectively. Seven of the DE miRNAs were validated by Reverse Transcription-quantitative Polymerase Chain Reaction (RT-qPCR). The data indicated that SNL rats displayed a time-dependent threshold reduction in response to evoked stimuli from day 3 to day 15 postnerve injury. The data also revealed that 22 and 74 miRNAs at day 3 and 15, respectively, and 33 miRNAs at both day 3 and 15 were uniquely DE between the SNL and sham groups. The key findings from this proposal include (1) the majority of the DE EV miRNAs, which normally function to suppress inflammation, were downregulated, and (2) several of the plasma derived DE EV miRNAs reflect previously observed changes in the injured L5 nerve. The plasma derived DE EV miRNAs regulate processes important in the development and maintenance of neuropathic pain states and potentially serve as key regulators, biomarkers, and targets in the progression and treatment of chronic neuropathic pain. Perspective This article describes the DE miRNA content of plasma derived EVs, comparing neuropathic pain to normal conditions. This data indicates that EV miRNAs may be important in nociception and may also serve as biomarkers for chronic pain. These results encourage further research on EV miRNAs in chronic neuropathic pain sufferers.

Posttraumatic stress disorder (PTSD) is defined by classic psychological manifestations, although among the characteristics are significantly increased rates of serious somatic comorbidities, such as cardiovascular disease, immune dysfunction, and metabolic syndrome. In this review, we assess the evidence for disturbances that may contribute to somatic pathology in inflammation, metabolic syndrome, and circulating metabolites (implicating mitochondrial dysfunction) in individuals with PTSD and in animal models simulating features of PTSD. The clinical and preclinical data highlight probable interrelated features of PTSD pathophysiology, including a proinflammatory milieu, metabolomic changes (implicating mitochondrial and other processes), and metabolic dysregulation. These data suggest that PTSD may be a systemic illness, or that it at least has systemic manifestations, and the behavioral manifestations are those most easily discerned. Whether somatic pathology precedes the development of PTSD (and thus may be a risk factor) or follows the development of PTSD (as a result of either shared pathophysiologies or lifestyle adaptations), comorbid PTSD and somatic illness is a potent combination placing affected individuals at increased physical as well as mental health risk. We conclude with directions for future research and novel treatment approaches based on these abnormalities.

When wireless sensor network (WSN) is applied in defence like applications, the security of the network becomes a necessity as confidential information is being processed and communicated amongst nodes. In this paper, taking confidentiality and security of the remotely managed WSNs into consideration, a trivariate polynomials based key management scheme (TPB-KMS) is being proposed. This scheme utilises the multivariate polynomial here trivariate polynomials to generate keys for secure communication between the cluster heads and amongst sensor nodes also. The base station generates the polynomials and transmitted to the cluster head. In addition to this a particular emphasis is given to the key establishment between two nodes. The proposed scheme provides better security and reduced computational overhead in terms of keys generated and shared. The main feature of this scheme is scalability, as the WSN adapts with the new nodes joining into the network.

High throughput and reduced delays are the basic necessities of next-generation networks which use multimedia applications (ftp, videoconferencing, VoIP, etc.). In order to make the network function efficiently, these necessities should be improved and maintained at a desired level. This provides a better quality of service (QoS) to the traffic which ensures a maximum customers’ satisfaction. These basic necessities are provided by using the appropriate scheduler mechanism at the router. The data are handled in the form of packets in the required manner. Presently, the scheduler mechanisms which are used have still some drawbacks in them. Therefore, they cannot handle the packets in a proper way in next-generation networks which are real-time applications. In this paper, various existing scheduling techniques are explained like First-In First-Out (FIFO), Priority Queue (PQ), Fair Queue (FQ), and Deficit Weighted Round Robin (DWRR). A new scheduling technique is introduced in this paper which is a combination of PQ and DWRR. Then a comparative analysis of the scheduling technique, i.e., PQ and proposed scheduling technique, i.e., PQDWRR is performed. PQDWRR technique provides a better QoS than the existing queuing mechanisms.

Posttraumatic stress disorder (PTSD) is a common condition induced by life-threatening stress, such as that experienced by soldiers under battlefield conditions. Other than the commonly recognized behavioral and psychological dysfunction, epidemiological studies have also revealed that PTSD patients have a higher risk of other diseases, such as cardiovascular disorders. Using a PTSD mouse model, we investigated the longitudinal transcriptomic changes in heart tissues after the exposure to stress through intimidation. Our results revealed acute heart injury associated with the traumatic experience, reflecting the underlying biological injury processes of the immune response, extracellular matrix remodeling, epithelial-to-mesenchymal cell transitions, and cell proliferation. Whether this type of injury has any long-term effects on heart function is yet to be determined. The differing responses to stress leading to acute heart injury in different inbred strains of mice also suggest that this response has a genetic as well as an environmental component. Accordingly, the results from this study suggest a molecular basis for the observed higher risk of cardiovascular disorders in PTSD patients, which raises the likelihood of cardiac dysfunction induced by long-term stress exposures.

Sophisticated controllers using building models and effects of disturbances are required for saving energy in buildings. Occupancy and climate are the disturbances acting on the building thermal model. This investigation presents a procedure for constructing building thermal model using experiments, simple sensor and least-absolute shrinkage and selection operator (LASSO). The thermal model so obtained is simple and can be used to construct model based controllers. Further, the methods leads to a linear model as against the non-linear thermal building models making it easier to design model based controllers. The building model is illustrated on a heating, ventilation and air-conditioning (HVAC) test-bed in a laboratory. Our results show that the LASSO based captures the non-linear disturbances and improves the model accuracy. The obtained results are compared with the actual measurements and least-squares to illustrate the accuracy.

Lyme disease, caused by the spirochete Borrelia burgdorferi sensu lato, is a multisystem disease and the most prevalent tick-borne disease world-wide. The spirochete infects humans and other mammals via the bite of infected Ixodes ticks (Burgdorfer et al. 1982). Following infection, spirochetes disperse to multiple organs including the skin, central and peripheral nervous systems, bladder, joints, eyes, and heart and persist in them for a long time causing many of the diverse manifestations of Lyme disease. Manifestations of the disease include, among others, acute or chronic arthritis, carditis, and neuroborreliosis (Steere 2001; Steere et al. 2004)

Cloud Computing is bound to become an integral part of the enterprises which seek to minimize their services cost by availing the services of application, platform, information, storage and mobility that the cloud provides. Mobility Services in Cloud enable nodes to move seamlessly between access networks while maintaining network connectivity and utilize uninterrupted services while on the move. A widespread usage of these services indicates the requirement of more IP addresses, but the IPv4 addresses are exhausting and a transition to IPv6 address is required. The concern is to find a secure, efficient, reliable, and cost effective method to enable mobility for Cloud Services in an environment with support to both IPv4 and IPv6 addresses. In this paper we propose a model to enhance the mobility services in Cloud by utilizing the concept of HMIPv6 in coexistent network and produce a performance analysis of the existing models with the proposed model. The proposed model reduces the burden on existing IPv4 addresses and enhances Mobility as a service in Cloud Computing.