The modeling of medical expenditure data from a longitudinal survey using the generalized method of moments (GMM) approach

Medical expenditure data analysis has recently become an important problem in biostatistics. These data typically have a number of features making their analysis rather difficult. Commonly, they are heavily right-skewed, contain a large percentage of zeros, and often exhibit large numbers of missing observations because of death and/or the lack of follow-up. They are also commonly obtained from records that are linked to large longitudinal data surveys. In this manuscript, we suggest a novel approach to modeling these data through the use of generalized method of moments estimation procedure combined with appropriate weights that account for both dropout due to death and the probability of being sampled from among the National Long Term Care Survey (NLTCS) subjects. This approach seems particularly appropriate because of the large number of subjects relative to the length of observation period (in months). We also use a simulation study to compare our proposed approach with and without the use of weights. The proposed model is applied to medical expenditure data obtained from the 2004-2005 NLTCS-linked Medicare database. The results suggest that the amount of medical expenditures incurred is strongly associated with higher number of activities of daily living (ADL) disabilities and self-reports of unmet need for help with ADL disabilities

FliPpr: A Prettier Invertible Printing System

When implementing a programming language, we often write a parser and a pretty-printer. However, manually writing both programs is not only tedious but also error-prone; it may happen that a pretty-printed result is not correctly parsed. In this paper, we propose FliPpr, which is a program transformation system that uses program inversion to produce a CFG parser from a pretty-printer. This novel approach has the advantages of fine-grained control over pretty-printing, and easy reuse of existing efficient pretty-printer and parser implementations

The Geometry of Entanglement Sudden Death

In open quantum systems, entanglement can vanish faster than coherence. This phenomenon is usually called sudden death of entanglement. In this paper sudden death of entanglement is discussed from a geometrical point of view, in the context of two qubits. A classification of possible scenarios is presented, with important known examples classified. Theoretical and experimental construction of other examples is suggested as well as large dimensional and multipartite versions of the effect.Comment: 6 pages, 2 figures, references added, initial paragraph corrected, sectioning adopted, some parts rewritten; accepted by New J. Phy

Test of a simple and flexible S8 model molecule in alpha-s8 crystals

Alpha S8 is the most stable crystalline form, at ambient pressure and temperature (STP), of elemental sulfur. In this paper we analyze the zero pressure low temperature part of the phase diagram of this crystal, in order to test a simple and flexible model molecule. The calculations consist in a series of molecular dynamics (MD) simulations, performed in the constant pressure- constant temperature ensemble. Our calculations show that this model, that gives good results for three crystalline phases at STP and T>~300 K, fails at low temperatures, predicting a structural phase transition at 200 K where there should be none.Comment: 6 pages, 4 figures, submitted to Chem. Phys. Lett, a figure change

Imaging Renal Urea Handling in Rats at Millimeter Resolution using Hyperpolarized Magnetic Resonance Relaxometry

\textit{In vivo} spin spin relaxation time ($T_2$) heterogeneity of hyperpolarized \textsuperscript{13}C urea in the rat kidney was investigated. Selective quenching of the vascular hyperpolarized \textsuperscript{13}C signal with a macromolecular relaxation agent revealed that a long-$T_2$ component of the \textsuperscript{13}C urea signal originated from the renal extravascular space, thus allowing the vascular and renal filtrate contrast agent pools of the \textsuperscript{13}C urea to be distinguished via multi-exponential analysis. The $T_2$ response to induced diuresis and antidiuresis was performed with two imaging agents: hyperpolarized \textsuperscript{13}C urea and a control agent hyperpolarized bis-1,1-(hydroxymethyl)-1-\textsuperscript{13}C-cyclopropane-$^2\textrm{H}_8$. Large $T_2$ increases in the inner-medullar and papilla were observed with the former agent and not the latter during antidiuresis suggesting that $T_2$ relaxometry may be used to monitor the inner-medullary urea transporter (UT)-A1 and UT-A3 mediated urea concentrating process. Two high resolution imaging techniques - multiple echo time averaging and ultra-long echo time sub-2 mm$^3$ resolution 3D imaging - were developed to exploit the particularly long relaxation times observed

1H NMR Signals from urine excreted protein are a source of bias in probabilistic quotient normalization

Normalization to account for variation in urinary dilution is crucial for interpretation of urine metabolic profiles. Probabilistic quotient normalization (PQN) is used routinely in metabolomics but is sensitive to systematic variation shared across a large proportion of the spectral profile (>50%). Where 1H nuclear magnetic resonance (NMR) spectroscopy is employed, the presence of urinary protein can elevate the spectral baseline and substantially impact the resulting profile. Using 1H NMR profile measurements of spot urine samples collected from hospitalized COVID-19 patients in the ISARIC 4C study, we determined that PQN coefficients are significantly correlated with observed protein levels (r2 = 0.423, p < 2.2 × 10–16). This correlation was significantly reduced (r2 = 0.163, p < 2.2 × 10–16) when using a computational method for suppression of macromolecular signals known as small molecule enhancement spectroscopy (SMolESY) for proteinic baseline removal prior to PQN. These results highlight proteinuria as a common yet overlooked source of bias in 1H NMR metabolic profiling studies which can be effectively mitigated using SMolESY or other macromolecular signal suppression methods before estimation of normalization coefficients

"We're worth what we are paid": Unravelling the 'paradox of the contented female worker'

Pay satisfaction research has suggested that women are more satisfied with their pay than men, even though, in general, women earn less. This paper argues that this body of research has misconceptualised this phenomenon as an issue of women only. It also argues that previous explanations for this gender pay paradox have not adequately explained these patterns of satisfaction. A social constructionist approach to pay satisfaction is proposed which situates satisfaction within the context of structural inequality. This draws upon the scholarly work of feminist scholars and the conceptual ideas of Pierre Bourdieu. This theoretical approach is explored with data from qualitative interviews with support staff at universities in the United Kingdom. This evidence suggests that their pay satisfaction is influenced by beliefs about the ‘value’ of different occupations

The gut microbiota and metabolome are associated with diminished COVID-19 vaccine-induced antibody responses in immunosuppressed inflammatory bowel disease patients

Background: Patients with inflammatory bowel disease (IBD) treated with anti-TNF therapy exhibit attenuated humoral immune responses to vaccination against SARS-CoV-2. The gut microbiota and its functional metabolic output, which are perturbed in IBD, play an important role in shaping host immune responses. We explored whether the gut microbiota and metabolome could explain variation in anti-SARS-CoV-2 vaccination responses in immunosuppressed IBD patients. Methods: Faecal and serum samples were prospectively collected from infliximab-treated patients with IBD in the CLARITY-IBD study undergoing vaccination against SARS-CoV-2. Antibody responses were measured following two doses of either ChAdOx1 nCoV-19 or BNT162b2 vaccine. Patients were classified as having responses above or below the geometric mean of the wider CLARITY-IBD cohort. 16S rRNA gene amplicon sequencing, nuclear magnetic resonance (NMR) spectroscopy and bile acid profiling with ultra-high-performance liquid chromatography mass spectrometry (UHPLC-MS) were performed on faecal samples. Univariate, multivariable and correlation analyses were performed to determine gut microbial and metabolomic predictors of response to vaccination. Findings: Forty-three infliximab-treated patients with IBD were recruited (30 Crohn's disease, 12 ulcerative colitis, 1 IBD-unclassified; 26 with concomitant thiopurine therapy). Eight patients had evidence of prior SARS-CoV-2 infection. Seventeen patients (39.5%) had a serological response below the geometric mean. Gut microbiota diversity was lower in below average responders (p = 0.037). Bilophila abundance was associated with better serological response, while Streptococcus was associated with poorer response. The faecal metabolome was distinct between above and below average responders (OPLS-DA R2X 0.25, R2Y 0.26, Q2 0.15; CV-ANOVA p = 0.038). Trimethylamine, isobutyrate and omega-muricholic acid were associated with better response, while succinate, phenylalanine, taurolithocholate and taurodeoxycholate were associated with poorer response. Interpretation: Our data suggest that there is an association between the gut microbiota and variable serological response to vaccination against SARS-CoV-2 in immunocompromised patients. Microbial metabolites including trimethylamine may be important in mitigating anti-TNF-induced attenuation of the immune response. Funding: JLA is the recipient of an NIHR Academic Clinical Lectureship (CL-2019-21-502), funded by Imperial College London and The Joyce and Norman Freed Charitable Trust. BHM is the recipient of an NIHR Academic Clinical Lectureship (CL-2019-21-002). The Division of Digestive Diseases at Imperial College London receives financial and infrastructure support from the NIHR Imperial Biomedical Research Centre (BRC) based at Imperial College Healthcare NHS Trust and Imperial College London. Metabolomics studies were performed at the MRC-NIHR National Phenome Centre at Imperial College London; this work was supported by the Medical Research Council (MRC), the National Institute of Health Research (NIHR) (grant number MC_PC_12025) and infrastructure support was provided by the NIHR Imperial Biomedical Research Centre (BRC). The NIHR Exeter Clinical Research Facility is a partnership between the University of Exeter Medical School College of Medicine and Health, and Royal Devon and Exeter NHS Foundation Trust. This project is supported by the National Institute for Health Research (NIHR) Exeter Clinical Research Facility. The views expressed are those of the authors and not necessarily those of the NIHR or the UK Department of Health and Social Care