Ethnicity and OPRM variant independently predict pain perception and patient-controlled analgesia usage for post-operative pain

<p>Abstract</p> <p>Background</p> <p>Morphine consumption can vary widely between individuals even for identical surgical procedures. As mu-opioid receptor (OPRM1) is known to modulate pain perception and mediate the analgesic effects of opioid compounds in the central nervous system, we examined the influence of two OPRM polymorphisms on acute post-operative pain and morphine usage in women undergoing elective caesarean delivery.</p> <p>Results</p> <p>Data on self-reported pain scores and amount of total morphine use according to patient-controlled analgesia were collected from 994 women from the three main ethnic groups in Singapore. We found statistically significant association of the OPRM 118A>G with self-administered morphine during the first 24-hour postoperative period both in terms of total morphine (p = 1.7 × 10^-5) and weight-adjusted morphine (p = 6.6 × 10^-5). There was also significant association of this OPRM variant and time-averaged self-rated pain scores (p = 0.024). OPRM 118G homozygotes used more morphine and reported higher pain scores than 118A carriers. Other factors which influenced pain score and morphine usage include ethnicity, age and paying class.</p> <p>Conclusion</p> <p>Our results suggest that ethnicity and OPRM 118A>G genotype are independent and significant contributors to variation in pain perception and postoperative morphine use in patients undergoing cesarean delivery.</p

Manipulation Strategies for the Rank Maximal Matching Problem

We consider manipulation strategies for the rank-maximal matching problem. In the rank-maximal matching problem we are given a bipartite graph $G = (A \cup P, E)$ such that $A$ denotes a set of applicants and $P$ a set of posts. Each applicant $a \in A$ has a preference list over the set of his neighbours in $G$, possibly involving ties. Preference lists are represented by ranks on the edges - an edge $(a,p)$ has rank $i$, denoted as $rank(a,p)=i$, if post $p$ belongs to one of $a$'s $i$-th choices. A rank-maximal matching is one in which the maximum number of applicants is matched to their rank one posts and subject to this condition, the maximum number of applicants is matched to their rank two posts, and so on. A rank-maximal matching can be computed in $O(\min(c \sqrt{n},n) m)$ time, where $n$ denotes the number of applicants, $m$ the number of edges and $c$ the maximum rank of an edge in an optimal solution. A central authority matches applicants to posts. It does so using one of the rank-maximal matchings. Since there may be more than one rank- maximal matching of $G$, we assume that the central authority chooses any one of them randomly. Let $a_1$ be a manipulative applicant, who knows the preference lists of all the other applicants and wants to falsify his preference list so that he has a chance of getting better posts than if he were truthful. In the first problem addressed in this paper the manipulative applicant $a_1$ wants to ensure that he is never matched to any post worse than the most preferred among those of rank greater than one and obtainable when he is truthful. In the second problem the manipulator wants to construct such a preference list that the worst post he can become matched to by the central authority is best possible or in other words, $a_1$ wants to minimize the maximal rank of a post he can become matched to

Integrated analysis of dermal blister fluid proteomics and genome-wide skin gene expression in systemic sclerosis: an observational study

Background: Skin fibrosis is a hallmark feature of systemic sclerosis. Skin biopsy transcriptomics and blister fluid proteomics give insight into the local environment of the skin. We have integrated these modalities with the aim of developing a surrogate for the modified Rodnan skin score (mRSS), using candidate genes and proteins from the skin and blister fluid as anchors to identify key analytes in the plasma. Methods: In this single-centre, prospective observational study at the Royal Free Campus, University College London, London, UK, transcriptional and proteomic analyses of blood and skin were performed in a cohort of patients with systemic sclerosis (n=52) and healthy controls (n=16). Weighted gene co-expression network analysis was used to explore the association of skin transcriptomics data, clinical traits, and blister fluid proteomic results. Candidate hub analytes were identified as those present in both blister and skin gene sets (modules), and which correlated with plasma (module membership >0·7 and gene significance >0·6). Hub analytes were confirmed using RNA transcript data obtained from skin biopsy samples from patients with early diffuse cutaneous systemic sclerosis at 12 months. Findings: We identified three modules in the skin, and two in blister fluid, which correlated with a diagnosis of early diffuse cutaneous systemic sclerosis. From these modules, 11 key hub analytes were identified, present in both skin and blister fluid modules, whose transcript and protein levels correlated with plasma protein concentrations, mRSS, and showed statistically significant correlation on repeat transcriptomic samples taken at 12 months. Multivariate analysis identified four plasma analytes as correlates of mRSS (COL4A1, COMP, SPON1, and TNC), which can be used to differentiate disease subtype. Interpretation: This unbiased approach has identified potential biological candidates that might be drivers of local skin pathogenesis in systemic sclerosis. By focusing on measurable analytes in the plasma, we generated a promising composite plasma protein biomarker that could be used for assessment of skin severity, case stratification, and as a potential outcome measure for clinical trials and practice. Once fully validated, the biomarker score could replace a clinical score such as the mRSS, which carries substantial variability. Funding: GlaxoSmithKline and UK Medical Research Council

Molecular basis for clinical diversity between autoantibody subsets in diffuse cutaneous systemic sclerosis.

OBJECTIVES: Clinical heterogeneity is a cardinal feature of systemic sclerosis (SSc). Hallmark SSc autoantibodies are central to diagnosis and associate with distinct patterns of skin-based and organ-based complications. Understanding molecular differences between patients will benefit clinical practice and research and give insight into pathogenesis of the disease. We aimed to improve understanding of the molecular differences between key diffuse cutaneous SSc subgroups as defined by their SSc-specific autoantibodies METHODS: We have used high-dimensional transcriptional and proteomic analysis of blood and the skin in a well-characterised cohort of SSc (n=52) and healthy controls (n=16) to understand the molecular basis of clinical diversity in SSc and explore differences between the hallmark antinuclear autoantibody (ANA) reactivities. RESULTS: Our data define a molecular spectrum of SSc based on skin gene expression and serum protein analysis, reflecting recognised clinical subgroups. Moreover, we show that antitopoisomerase-1 antibodies and anti-RNA polymerase III antibodies specificities associate with remarkably different longitudinal change in serum protein markers of fibrosis and divergent gene expression profiles. Overlapping and distinct disease processes are defined using individual patient pathway analysis. CONCLUSIONS: Our findings provide insight into clinical diversity and imply pathogenetic differences between ANA-based subgroups. This supports stratification of SSc cases by ANA antibody subtype in clinical trials and may explain different outcomes across ANA subgroups in trials targeting specific pathogenic mechanisms

Non-invasive single-cell biomechanical analysis using live-imaging datasets

The physiological state of a cell is governed by a multitude of processes and can be described by a combination of mechanical, spatial and temporal properties. Quantifying cell dynamics at multiple scales is essential for comprehensive studies of cellular function, and remains a challenge for traditional end-point assays. We introduce an efficient, non-invasive computational tool that takes time-lapse images as input to automatically detect, segment and analyze unlabeled live cells; the program then outputs kinematic cellular shape and migration parameters, while simultaneously measuring cellular stiffness and viscosity. We demonstrate the capabilities of the program by testing it on human mesenchymal stem cells (huMSCs) induced to differentiate towards the osteoblastic (huOB) lineage, and T-lymphocyte cells (T cells) of naïve and stimulated phenotypes. The program detected relative cellular stiffness differences in huMSCs and huOBs that were comparable to those obtained with studies that utilize atomic force microscopy; it further distinguished naïve from stimulated T cells, based on characteristics necessary to invoke an immune response. In summary, we introduce an integrated tool to decipher spatiotemporal and intracellular dynamics of cells, providing a new and alternative approach for cell characterization

Multi-scalar tachyon potential on non-BPS domain walls

We have considered the multi-scalar and multi-tachyon fields living on a 3d domain wall embedded in a 5d dimensional Minkowski spacetime. The effective action for such a domain wall can be found by integrating out the normal modes as vibrating modes around the domain wall solution of a truncated 5d supergravity action. The multi-scalar tachyon potential are good enough to modeling assisted inflation scenario with multi-tachyon fields. The tachyon condensation are also briefly addressed.Comment: version to appear in JHEP, 18 pages, 3 figure

A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci.

We conducted a multi-stage, genome-wide association study of bladder cancer with a primary scan of 591,637 SNPs in 3,532 affected individuals (cases) and 5,120 controls of European descent from five studies followed by a replication strategy, which included 8,382 cases and 48,275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P = 8 × 10⁻¹²) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 × 10⁻¹¹) on 19q12 maps to CCNE1 and rs11892031 (P = 1 × 10⁻⁷) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P = 4 × 10⁻¹¹) and a tag SNP for NAT2 acetylation status (P = 4 × 10⁻¹¹), and found interactions with smoking in both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into the mechanisms of carcinogenesis

Somatic mutations of GNA11 and GNAQ in CTNNB1-mutant aldosterone-producing adenomas presenting in puberty, pregnancy or menopause.

Most aldosterone-producing adenomas (APAs) have gain-of-function somatic mutations of ion channels or transporters. However, their frequency in aldosterone-producing cell clusters of normal adrenal gland suggests a requirement for codriver mutations in APAs. Here we identified gain-of-function mutations in both CTNNB1 and GNA11 by whole-exome sequencing of 3/41 APAs. Further sequencing of known CTNNB1-mutant APAs led to a total of 16 of 27 (59%) with a somatic p.Gln209His, p.Gln209Pro or p.Gln209Leu mutation of GNA11 or GNAQ. Solitary GNA11 mutations were found in hyperplastic zona glomerulosa adjacent to double-mutant APAs. Nine of ten patients in our UK/Irish cohort presented in puberty, pregnancy or menopause. Among multiple transcripts upregulated more than tenfold in double-mutant APAs was LHCGR, the receptor for luteinizing or pregnancy hormone (human chorionic gonadotropin). Transfections of adrenocortical cells demonstrated additive effects of GNA11 and CTNNB1 mutations on aldosterone secretion and expression of genes upregulated in double-mutant APAs. In adrenal cortex, GNA11/Q mutations appear clinically silent without a codriver mutation of CTNNB1