Dark matter production in the early Universe: beyond the thermal WIMP paradigm

Increasingly stringent limits from LHC searches for new physics, coupled with lack of convincing signals of weakly interacting massive particle (WIMP) in dark matter searches, have tightly constrained many realizations of the standard paradigm of thermally produced WIMPs as cold dark matter. In this article, we review more generally both thermally and non-thermally produced dark matter (DM). One may classify DM models into two broad categories: one involving bosonic coherent motion (BCM) and the other involving WIMPs. BCM and WIMP candidates need, respectively, some approximate global symmetries and almost exact discrete symmetries. Supersymmetric axion models are highly motivated since they emerge from compelling and elegant solutions to the two fine-tuning problems of the Standard Model: the strong CP problem and the gauge hierarchy problem. We review here non-thermal relics in a general setup, but we also pay particular attention to the rich cosmological properties of various aspects of mixed SUSY/axion dark matter candidates which can involve both WIMPs and BCM in an interwoven manner. We also review briefly a panoply of alternative thermal and non-thermal DM candidates.Comment: 71 pages with 28 figure

Cumulative Lead Exposure and Age at Menopause in the Nurses’ Health Study Cohort

Background: Early menopause has been associated with many adverse health outcomes, including increased risk of cardiovascular disease morbidity and mortality. Lead has been found to be adversely associated with female reproductive function, but whether exposures experienced by the general population are associated with altered age at menopause has not been explored. Objective: Our goal was to assess the association between cumulative lead exposure and age at natural menopause. Methods: Self-reported menopausal status and bone lead concentration measured with K-shell X-ray fluorescence—a biomarker of cumulative lead exposure—were obtained from 434 women participants in the Nurses’ Health Study. Results: The mean (± SD) age at natural menopause was 50.8 ± 3.6 years. Higher tibia lead level was associated with younger age at menopause. In adjusted analyses, the average age of menopause for women in the highest tertile of tibia lead was 1.21 years younger (95% CI: –2.08, –0.35) than for women in the lowest tertile (p-trend = 0.006). Although the number of cases was small (n = 23), the odds ratio for early menopause (< 45 years of age) was 5.30 (95% CI: 1.42, 19.78) for women in the highest tertile of tibia lead compared with those in the lowest tertile (p-trend = 0.006). There was no association between patella or blood lead and age at menopause. Conclusions: Our results support an association between low-level cumulative lead exposure and an earlier age at menopause. These data suggest that low-level lead exposure may contribute to menopause-related health outcomes in older women through effects on age at menopause. Citation: Eum KD, Weisskopf MG, Nie LH, Hu H, Korrick SA. 2014. Cumulative lead exposure and age at menopause in the Nurses’ Health Study Cohort. Environ Health Perspect 122:229–234; http://dx.doi.org/10.1289/ehp.120639

Versatile RNA Interference Nanoplatform for Systemic Delivery of RNAs

Development of nontoxic, tumor-targetable, and potent in vivo RNA delivery systems remains an arduous challenge for clinical application of RNAi therapeutics. Herein, we report a versatile RNAi nanoplatform based on tumor-targeted and pH-responsive nanoformulas (NFs). The NF was engineered by combination of an artificial RNA receptor, Zn(II)-DPA, with a tumor-targetable and drug-loadable hyaluronic acid nanoparticle, which was further modified with a calcium phosphate (CaP) coating by in situ mineralization. The NF can encapsulate small-molecule drugs within its hydrophobic inner core and strongly secure various RNA molecules (siRNAs, miRNAs, and oligonucleotides) by utilizing Zn(II)-DPA and a robust CaP coating. We substantiated the versatility of the RNAi nanoplatform by demonstrating effective delivery of siRNA and miRNA for gene silencing or miRNA replacement into different human types of cancer cells in vitro and into tumor-bearing mice in vivo by intravenous administration. The therapeutic potential of NFs coloaded with an anticancer drug doxorubicin (Dox) and multidrug resistance 1 gene target siRNA (siMDR) was also demonstrated in this study. NFs loaded with Dox and siMDR could successfully sensitize drug-resistant OVCAR8/ADR cells to Dox and suppress OVCAR8/ADR tumor cell proliferation in vitro and tumor growth in vivo. This gene/drug delivery system appears to be a highly effective nonviral method to deliver chemo- and RNAi therapeutics into host cells.National Institute for Biomedical Imaging and Bioengineering (U.S.)National Institutes of Health (U.S.)AXA Research Fund (Postdoctoral Fellowship)National Research Foundation of Korea (Postdoctoral Fellowship 2013R1A6A3A03)National Research Foundation of Korea (Grant 2009-0080734

The factor structure and psychometric properties of the Clinical Outcomes in Routine Evaluation - Outcome Measure (CORE-OM) in Norwegian clinical and non-clinical samples

Background The Clinical Outcomes in Routine Evaluation - Outcome Measure (CORE-OM) is a 34-item instrument developed to monitor clinically significant change in out-patients. The CORE-OM covers four domains: well-being, problems/symptoms, functioning and risk, and sums up in two total scores: the mean of All items, and the mean of All non-risk items. The aim of this study was to examine the psychometric properties of the Norwegian translation of the CORE-OM. Methods A clinical sample of 527 out-patients from North Norwegian specialist psychiatric services, and a non-clinical sample of 464 persons were obtained. The non-clinical sample was a convenience sample consisting of friends and family of health personnel, and of students of medicine and clinical psychology. Students also reported psychological stress. Exploratory factor analysis (EFA) was employed in half the clinical sample. Confirmatory (CFA) factor analyses modelling the theoretical sub-domains were performed in the remaining half of the clinical sample. Internal consistency, means, and gender and age differences were studied by comparing the clinical and non-clinical samples. Stability, effect of language (Norwegian versus English), and of psychological stress was studied in the sub-sample of students. Finally, cut-off scores were calculated, and distributions of scores were compared between clinical and non-clinical samples, and between students reporting stress or no stress. Results The results indicate that the CORE-OM both measures general (g) psychological distress and sub-domains, of which risk of harm separates most clearly from the g factor. Internal consistency, stability and cut-off scores compared well with the original English version. No, or only negligible, language effects were found. Gender differences were only found for the well-being domain in the non-clinical sample and for the risk domain in the clinical sample. Current patient status explained differences between clinical and non-clinical samples, also when gender and age were controlled for. Students reporting psychological distress during last week scored significantly higher than students reporting no stress. These results further validate the recommended cut-off point of 1 between clinical and non-clinical populations. Conclusions The CORE-OM in Norwegian has psychometric properties at the same level as the English original, and could be recommended for general clinical use. A cut-off point of 1 is recommended for both genders

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

A computational approach to chemical etiologies of diabetes.

Computational meta-analysis can link environmental chemicals to genes and proteins involved in human diseases, thereby elucidating possible etiologies and pathogeneses of non-communicable diseases. We used an integrated computational systems biology approach to examine possible pathogenetic linkages in type 2 diabetes (T2D) through genome-wide associations, disease similarities, and published empirical evidence. Ten environmental chemicals were found to be potentially linked to T2D, the highest scores were observed for arsenic, 2,3,7,8-tetrachlorodibenzo-p-dioxin, hexachlorobenzene, and perfluorooctanoic acid. For these substances we integrated disease and pathway annotations on top of protein interactions to reveal possible pathogenetic pathways that deserve empirical testing. The approach is general and can address other public health concerns in addition to identifying diabetogenic chemicals, and offers thus promising guidance for future research in regard to the etiology and pathogenesis of complex diseases