A Study of Interstellar Gas and Stars in the Gravitationally Lensed Galaxy `The Cosmic Eye' from Rest-Frame Ultraviolet Spectroscopy

We report the results of a study of the rest-frame UV spectrum of the Cosmic Eye, a luminous Lyman break galaxy at z=3.07331 gravitationally lensed by a factor of 25. The spectrum, recorded with the ESI spectrograph on the Keck II telescope, is rich in absorption features from the gas and massive stars in this galaxy. The interstellar absorption lines are resolved into two components of approximately equal strength and each spanning several hundred km/s in velocity. One component has a net blueshift of -70 km/s relative to the stars and H II regions and presumably arises in a galaxy-scale outflow similar to those seen in most star-forming galaxies at z = 2-3. The other is more unusual in showing a mean redshift of +350 km/s relative to the systemic redshift; possible interpretations include a merging clump, or material ejected by a previous star formation episode and now falling back onto the galaxy, or more simply a chance alignment with a foreground galaxy. In the metal absorption lines, both components only partially cover the OB stars against which they are being viewed. We tentatively associate the redshifted component with the strong damped Lyman alpha line, indicative of a column density N(H I) = (3.0 +/- 0.8) x 10(21) atoms/cm2, and propose that it provides the dust `foreground screen' responsible for the low ratio of far-infrared to UV luminosities of the Cosmic Eye. Compared to other well-studied examples of strongly lensed galaxies, we find that the young stellar population of the Cosmic Eye is essentially indistinguishable from those of the Cosmic Horseshoe and MS 1512-cB58, while the interstellar spectra of all three galaxies are markedly different, attesting to the real complexity of the interplay between starbursts and ambient interstellar matter in young galaxies (abridged).Comment: 14 pages, 6 Figures, Accepted for publication in Monthly Notices of the Royal Astronomical Society after minor revision

Inhaled Nitric Oxide in preterm infants: a systematic review and individual patient data meta-analysis

BACKGROUND: Preterm infants requiring assisted ventilation are at significant risk of both pulmonary and cerebral injury. Inhaled Nitric Oxide, an effective therapy for pulmonary hypertension and hypoxic respiratory failure in the full term infant, has also been studied in preterm infants. The most recent Cochrane review of preterm infants includes 11 studies and 3,370 participants. The results show a statistically significant reduction in the combined outcome of death or chronic lung disease (CLD) in two studies with routine use of iNO in intubated preterm infants. However, uncertainty remains as a larger study (Kinsella 2006) showed no significant benefit for iNO for this combined outcome. Also, trials that included very ill infants do not demonstrate significant benefit. One trial of iNO treatment at a later postnatal age reported a decrease in the incidence of CLD. The aim of this individual patient meta-analysis is to confirm or refute these potentially conflicting results and to determine the extent to which patient or treatment characteristics may explain the results and/or may predict benefit from inhaled Nitric Oxide in preterm infants. METHODS/DESIGN: The Meta-Analysis of Preterm Patients on inhaled Nitric Oxide (MAPPiNO) Collaboration will perform an individual patient data meta-analysis to answer these important clinical questions. Studies will be included if preterm infants receiving assisted ventilation are randomized to receive inhaled Nitric Oxide or to a control group. The individual patient data provided by the Collaborators will be analyzed on an intention-to-treat basis where possible. Binary outcomes will be analyzed using log-binomial regression models and continuous outcomes will be analyzed using linear fixed effects models. Adjustments for trial differences will be made by including the trial variable in the model specification. DISCUSSION: Thirteen (13) trials, with a total of 3567 infants are eligible for inclusion in the MAPPiNO systematic review. To date 11 trials (n = 3298, 92% of available patients) have agreed to participate. Funding was successfully granted from Ikaria Inc as an unrestricted grant. A collaborative group was formed in 2006 with data collection commencing in 2007. It is anticipated that data analysis will commence in late 2009 with results being publicly available in 2010

Characterization of early host responses in adults with dengue disease

BACKGROUND: While dengue-elicited early and transient host responses preceding defervescence could shape the disease outcome and reveal mechanisms of the disease pathogenesis, assessment of these responses are difficult as patients rarely seek healthcare during the first days of benign fever and thus data are lacking. METHODS: In this study, focusing on early recruitment, we performed whole-blood transcriptional profiling on dengue virus PCR positive patients sampled within 72 h of self-reported fever presentation (average 43 h, SD 18.6 h) and compared the signatures with autologous samples drawn at defervescence and convalescence and to control patients with fever of other etiology. RESULTS: In the early dengue fever phase, a strong activation of the innate immune response related genes were seen that was absent at defervescence (4-7 days after fever debut), while at this second sampling genes related to biosynthesis and metabolism dominated. Transcripts relating to the adaptive immune response were over-expressed in the second sampling point with sustained activation at the third sampling. On an individual gene level, significant enrichment of transcripts early in dengue disease were chemokines CCL2 (MCP-1), CCL8 (MCP-2), CXCL10 (IP-10) and CCL3 (MIP-1α), antimicrobial peptide β-defensin 1 (DEFB1), desmosome/intermediate junction component plakoglobin (JUP) and a microRNA which may negatively regulate pro-inflammatory cytokines in dengue infected peripheral blood cells, mIR-147 (NMES1). CONCLUSIONS: These data show that the early response in patients mimics those previously described in vitro, where early assessment of transcriptional responses has been easily obtained. Several of the early transcripts identified may be affected by or mediate the pathogenesis and deserve further assessment at this timepoint in correlation to severe disease

Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis.

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis

The Immune Response to Melanoma Is Limited by Thymic Selection of Self-Antigens

The expression of melanoma-associated antigens (MAA) being limited to normal melanocytes and melanomas, MAAs are ideal targets for immunotherapy and melanoma vaccines. As MAAs are derived from self, immune responses to these may be limited by thymic tolerance. The extent to which self-tolerance prevents efficient immune responses to MAAs remains unknown. The autoimmune regulator (AIRE) controls the expression of tissue-specific self-antigens in thymic epithelial cells (TECs). The level of antigens expressed in the TECs determines the fate of auto-reactive thymocytes. Deficiency in AIRE leads in both humans (APECED patients) and mice to enlarged autoreactive immune repertoires. Here we show increased IgG levels to melanoma cells in APECED patients correlating with autoimmune skin features. Similarly, the enlarged T cell repertoire in AIRE−/− mice enables them to mount anti-MAA and anti-melanoma responses as shown by increased anti-melanoma antibodies, and enhanced CD4+ and MAA-specific CD8+ T cell responses after melanoma challenge. We show that thymic expression of gp100 is under the control of AIRE, leading to increased gp100-specific CD8+ T cell frequencies in AIRE−/− mice. TRP-2 (tyrosinase-related protein), on the other hand, is absent from TECs and consequently TRP-2 specific CD8+ T cells were found in both AIRE−/− and AIRE+/+ mice. This study emphasizes the importance of investigating thymic expression of self-antigens prior to their inclusion in vaccination and immunotherapy strategies

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Lack of Support for the Association between GAD2 Polymorphisms and Severe Human Obesity

The demonstration of association between common genetic variants and chronic human diseases such as obesity could have profound implications for the prediction, prevention, and treatment of these conditions. Unequivocal proof of such an association, however, requires independent replication of initial positive findings. Recently, three (−243 A>G, +61450 C>A, and +83897 T>A) single nucleotide polymorphisms (SNPs) within glutamate decarboxylase 2 (GAD2) were found to be associated with class III obesity (body mass index > 40 kg/m(2)). The association was observed among 188 families (612 individuals) segregating the condition, and a case-control study of 575 cases and 646 lean controls. Functional data supporting a pathophysiological role for one of the SNPs (−243 A>G) were also presented. The gene GAD2 encodes the 65-kDa subunit of glutamic acid decarboxylase—GAD65. In the present study, we attempted to replicate this association in larger groups of individuals, and to extend the functional studies of the −243 A>G SNP. Among 2,359 individuals comprising 693 German nuclear families with severe, early-onset obesity, we found no evidence for a relationship between the three GAD2 SNPs and obesity, whether SNPs were studied individually or as haplotypes. In two independent case-control studies (a total of 680 class III obesity cases and 1,186 lean controls), there was no significant relationship between the −243 A>G SNP and obesity (OR = 0.99, 95% CI 0.83–1.18, p = 0.89) in the pooled sample. These negative findings were recapitulated in a meta-analysis, incorporating all published data for the association between the −243G allele and class III obesity, which yielded an OR of 1.11 (95% CI 0.90–1.36, p = 0.28) in a total sample of 1,252 class III obese cases and 1,800 lean controls. Moreover, analysis of common haplotypes encompassing the GAD2 locus revealed no association with severe obesity in families with the condition. We also obtained functional data for the −243 A>G SNP that does not support a pathophysiological role for this variant in obesity. Potential confounding variables in association studies involving common variants and complex diseases (low power to detect modest genetic effects, overinterpretation of marginal data, population stratification, and biological plausibility) are also discussed in the context of GAD2 and severe obesity

Swarm Learning for decentralized and confidential clinical machine learning

Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine1,2. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes3. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation4,5. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning—a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine

Toward community standards and software for whole-cell modeling

Whole-cell (WC) modeling is a promising tool for biological research, bioengineering, and medicine. However, substantial work remains to create accurate, comprehensive models of complex cells. Methods: We organized the 2015 Whole-Cell Modeling Summer School to teach WC modeling and evaluate the need for new WC modeling standards and software by recoding a recently published WC model in SBML. Results: Our analysis revealed several challenges to representing WC models using the current standards. Conclusion: We, therefore, propose several new WC modeling standards, software, and databases. Significance:We anticipate that these new standards and software will enable more comprehensive models