Daniel John Greene to John Kean, July 22, 1789

Daniel John Greene wrote to John Kean, addressed to Beaufort, SC. He had not been to Beaufort since he wrote him last which is why he did not get Major Wigg\u27s note. He said any issues with the account will be rectified when he is in town.https://digitalcommons.kean.edu/lhc_1780s/1291/thumbnail.jp

Methods for Determining the Genetic Causes of Rare Diseases

Thanks to the affordability of DNA sequencing, hundreds of thousands of individuals with rare disorders are undergoing whole-genome sequencing in an effort to reveal novel disease aetiologies, increase our understanding of biological processes and improve patient care. However, the power to discover the genetic causes of many unexplained rare diseases is hindered by a paucity of cases with a shared molecular aetiology. This thesis presents research into statistical and computational methods for determining the genetic causes of rare diseases. Methods described herein treat important aspects of the nature of rare diseases, including genetic and phenotypic heterogeneity, phenotypes involving multiple organ systems, Mendelian modes of inheritance and the incorporation of complex prior information such as model organism phenotypes and evolutionary conservation. The complex nature of rare disease phenotypes and the need to aggregate patient data across many centres has led to the adoption of the Human Phenotype Ontology (HPO) as a means of coding patient phenotypes. The HPO provides a standardised vocabulary and captures relationships between disease features. I developed a suite of software packages dubbed 'ontologyX' in order to simplify analysis and visualisation of such ontologically encoded data, and enable them to be incorporated into complex analysis methods. An important aspect of the analysis of ontological data is quantifying the semantic similarity between ontologically annotated entities, which is implemented in the ontologyX software. We employed this functionality in a phenotypic similarity regression framework, 'SimReg', which models the relationship between ontologically encoded patient phenotypes of individuals and rare variation in a given genomic locus. It does so by evaluating support for a model under which the probability that a person carries rare alleles in a locus depends on the similarity between the person's ontologically encoded phenotype and a latent characteristic phenotype which can be inferred from data. A probability of association is computed by comparison of the two models, allowing prioritisation of candidate loci for involvement in disease with respect to a heterogeneous collection of disease phenotypes. SimReg includes a sophisticated treatment of HPO-coded phenotypic data but dichotomises the genetic data at a locus. Therefore, we developed an additional method, 'BeviMed', standing for Bayesian Evaluation of Variant Involvement in Mendelian Disease, which evaluates the evidence of association between allele configurations across rare variants within a genomic locus and a case/control label. It is capable of inferring the probability of association, and conditional on association, the probability of each mode of inheritance and probability of involvement of each variant. Inference is performed through a Bayesian comparison of multiple models: under a baseline model disease risk is independent of allele configuration at the given rare variant sites and under an alternate model disease risk depends on the configuration of alleles, a latent partition of variants into pathogenic and non-pathogenic groups and a mode of inheritance. The method can be used to analyse a dataset comprising thousands of individuals genotyped at hundreds of rare variant sites in a fraction of a second, making it much faster than competing methods and facilitating genome-wide application

One- and two-photon ionization cross sections of the laser excited 6s6p^1P_1 state of barium

Stimulated by a recent measurement of coherent control in photoionization of atomic barium, we have calculated one- and two-photon ionization cross sections of the aligned 6s6p^1P_1 state of barium in the energy range between the 5d_{3/2} and 5d_{5/2} states of Ba^+. We have also measured these photionization spectra in the same energy region, driving the one- or two-photon processes with the second or first harmonic of a tunable dye laser, respectively. Our calculations employ the eigenchannel R-matrix method and multichannel quantum defect theory to calculate the rich array of autoionizing resonances in this energy range. The non-resonant two-photon process is described using lowest-order perturbation theory for the photon-atom interactions, with a discretized intermediate state one-electron continuum. The calculations provide an absolute normalization for the experiment, and they accurately reproduce the rich resonance structures in both the one and two-photon cross sections, and confirm other aspects of experimental observations. These results demonstrate the ability of these computationally inexpensive methods to reproduce the experimental observables in one- and two-photon ionization of heavy alkaline earths, and they lay the groundwork for future studies of the phase-controlled interference between one-photon and two-photon ionization processes.Comment: 10 pages, 9 figures, submitted to Phys.Rev.

NIRCam: Development and Testing of the JWST Near-Infrared Camera

The Near Infrared Camera (NIRCam) is one of the four science instruments of the James Webb Space Telescope (JWST). Its high sensitivity, high spatial resolution images over the 0.6 - 5 microns wavelength region will be essential for making significant findings in many science areas as well as for aligning the JWST primary mirror segments and telescope. The NIRCam engineering test unit was recently assembled and has undergone successful cryogenic testing. The NIRCam collimator and camera optics and their mountings are also progressing, with a brass-board system demonstrating relatively low wavefront error across a wide field of view. The flight model?s long-wavelength Si grisms have been fabricated, and its coronagraph masks are now being made. Both the short (0.6 - 2.3 microns) and long (2.4 - 5.0 microns) wavelength flight detectors show good performance and are undergoing final assembly and testing. The flight model subsystems should all be completed later this year through early 2011, and NIRCam will be cryogenically tested in the first half of 2011 before delivery to the JWST integrated science instrument module (ISIM)

Effect of frequent hemodialysis on residual kidney function.

Frequent hemodialysis can alter volume status, blood pressure, and the concentration of osmotically active solutes, each of which might affect residual kidney function (RKF). In the Frequent Hemodialysis Network Daily and Nocturnal Trials, we examined the effects of assignment to six compared with three-times-per-week hemodialysis on follow-up RKF. In both trials, baseline RKF was inversely correlated with number of years since onset of ESRD. In the Nocturnal Trial, 63 participants had non-zero RKF at baseline (mean urine volume 0.76 liter/day, urea clearance 2.3 ml/min, and creatinine clearance 4.7 ml/min). In those assigned to frequent nocturnal dialysis, these indices were all significantly lower at month 4 and were mostly so at month 12 compared with controls. In the frequent dialysis group, urine volume had declined to zero in 52% and 67% of patients at months 4 and 12, respectively, compared with 18% and 36% in controls. In the Daily Trial, 83 patients had non-zero RKF at baseline (mean urine volume 0.43 liter/day, urea clearance 1.2 ml/min, and creatinine clearance 2.7 ml/min). Here, treatment assignment did not significantly influence follow-up levels of the measured indices, although the range in baseline RKF was narrower, potentially limiting power to detect differences. Thus, frequent nocturnal hemodialysis appears to promote a more rapid loss of RKF, the mechanism of which remains to be determined. Whether RKF also declines with frequent daily treatment could not be determined

Oriented attachment of VNAR proteins, Q2 via site-selective modification, on PLGA–PEG nanoparticles enhances nanoconjugate performance

This work was partially funded through a US-Ireland R&D Partnership grant (STL/5010/14, MRC grant MC_PC_15013). JCFN is funded by the EU’s Horizon 2020 programme under Marie-Curie grant agreement 675007. We acknowledge UCL Chemistry Mass Spectrometry Facility (Dr K. Karu/Dr X. Yang).Peer reviewedPublisher PDFsupplementary_dat

Common mental disorders, neighbourhood income inequality and income deprivation: small-area multilevel analysis

Background. Common mental disorders are more prevalent in areas of high neighbourhood socioeconomic deprivation but whether the prevalence varies with neighbourhood income inequality is not known. Aims. To investigate the hypothesis that the interaction between small-area income deprivation and income inequality was associated with individual mental health. Method. Multilevel analysis of population data from the Welsh Health Survey, 2003/04–2010. A total of 88 623 respondents aged 18–74 years were nested within 50 587 households within 1887 lower super output areas (neighbourhoods) and 22 unitary authorities (regions), linked to the Gini coefficient (income inequality) and the per cent of households living in poverty (income deprivation). Mental health was measured using the Mental Health Inventory MHI-5 as a discrete variable and as a ‘case’ of common mental disorder. Results. High neighbourhood income inequality was associated with better mental health in low-deprivation neighbourhoods after adjusting for individual and household risk factors (parameter estimate +0.70 (s.e. = 0.33), P = 0.036; odds ratio (OR) for common mental disorder case 0.92, 95% CI 0.88–0.97). Income inequality at regional level was significantly associated with poorer mental health (parameter estimate -1.35 (s.e. = 0.54), P = 0.012; OR = 1.13, 95% CI 1.04–1.22). Conclusions. The associations between common mental disorders, income inequality and income deprivation are complex. Income inequality at neighbourhood level is less important than income deprivation as a risk factor for common mental disorders. The adverse effect of income inequality starts to operate at the larger regional level