UK Scleroderma Study Group (UKSSG) guidelines on the diagnosis and management of scleroderma renal crisis

The UK Scleroderma Study Group developed guidelines on the diagnosis and management of scleroderma renal crisis (SRC) based on best available evidence and clinical experience. SRC is characterised by the acute onset of severe hypertension and acute kidney injury. Current strategies to reduce the associated morbidity and mortality include identifying at risk patients to aid early diagnosis. ACE inhibitor therapy should be lifelong in all patients, regardless of whether they require renal replacement therapy. Patients with SRC may recover renal function up to 3 years after the crisis, most often within 12 to 18 months

Stem cell models as an in vitro model for predictive toxicology

Adverse drug reactions (ADRs) are the unintended side effects of drugs. They are categorised as either predictable or unpredictable drug-induced injury and may be exhibited after a single or prolonged exposure to one or multiple compounds. Historically, toxicology studies rely heavily on animal models to understand and characterise the toxicity of novel compounds. However, animal models are imperfect proxies for human toxicity and there have been several high-profile cases of failure of animal models to predict human toxicity e.g. fialuridine, TGN1412 which highlight the need for improved predictive models of human toxicity. As a result, stem cell-derived models are under investigation as potential models for toxicity during early stages of drug development. Stem cells retain the genotype of the individual from which they were derived, offering the opportunity to model the reproducibility of rare phenotypes in vitro Differentiated 2D stem cell cultures have been investigated as models of hepato- and cardiotoxicity. However, insufficient maturity, particularly in the case of hepatocyte-like cells, means that their widespread use is not currently a feasible method to tackle the complex issues of off-target and often unpredictable toxicity of novel compounds. This review discusses the current state of the art for modelling clinically relevant toxicities, e.g. cardio- and hepatotoxicity, alongside the emerging need for modelling gastrointestinal toxicity and seeks to address whether stem cell technologies are a potential solution to increase the accuracy of ADR predictivity in humans

Enrichment analysis of Alu elements with different spatial chromatin proximity in the human genome

Transposable elements (TEs) have no longer been totally considered as “junk DNA” for quite a time since the continual discoveries of their multifunctional roles in eukaryote genomes. As one of the most important and abundant TEs that still active in human genome, Alu, a SINE family, has demonstrated its indispensable regulatory functions at sequence level, but its spatial roles are still unclear. Technologies based on 3C(chromosomeconformation capture) have revealed the mysterious three-dimensional structure of chromatin, and make it possible to study the distal chromatin interaction in the genome. To find the role TE playing in distal regulation in human genome, we compiled the new released Hi-C data, TE annotation, histone marker annotations, and the genome-wide methylation data to operate correlation analysis, and found that the density of Alu elements showed a strong positive correlation with the level of chromatin interactions (hESC: r=0.9, P<2.2×1016; IMR90 fibroblasts: r = 0.94, P < 2.2 × 1016) and also have a significant positive correlation withsomeremote functional DNA elements like enhancers and promoters (Enhancer: hESC: r=0.997, P=2.3×10−4; IMR90: r=0.934, P=2×10−2; Promoter: hESC: r = 0.995, P = 3.8 × 10−4; IMR90: r = 0.996, P = 3.2 × 10−4). Further investigation involving GC content and methylation status showed the GC content of Alu covered sequences shared a similar pattern with that of the overall sequence, suggesting that Alu elements also function as the GC nucleotide and CpG site provider. In all, our results suggest that the Alu elements may act as an alternative parameter to evaluate the Hi-C data, which is confirmed by the correlation analysis of Alu elements and histone markers. Moreover, the GC-rich Alu sequence can bring high GC content and methylation flexibility to the regions with more distal chromatin contact, regulating the transcription of tissue-specific genes

Social problems in oncology

A study was undertaken to describe, evaluate and categorise the social problems experienced by cancer patients. Ninety-six adult cancer patients at all stages of disease participated in either a telephone focus group discussion, a face to face focus group or an individual interview which were tape recorded and transcribed. Six experts analysed the transcripts. A total of 32 social problems were identified categorized under eight headings plus four single items. The categories were: problems with (1) managing in the home, (2) health and welfare services, (3) finances, (4) employment, (5) legal matters, (6) relationships, (7) sexuality and body image and (8) recreation. Problems with relationships and communication were the most frequently reported with financial, employment, body image and domestic problems also being widely endorsed. Female groups, younger patient groups and groups where the aim of treatment was palliative reported more social problems than other groups. Social problems are common and important to cancer patients. The social problems identified in this study will contribute to an item pool generated for developing a Social Problems Inventory that may be included in patient centred assessment as part of routine oncology practice

Evidence That Mutation Is Universally Biased towards AT in Bacteria

Mutation is the engine that drives evolution and adaptation forward in that it generates the variation on which natural selection acts. Mutation is a random process that nevertheless occurs according to certain biases. Elucidating mutational biases and the way they vary across species and within genomes is crucial to understanding evolution and adaptation. Here we demonstrate that clonal pathogens that evolve under severely relaxed selection are uniquely suitable for studying mutational biases in bacteria. We estimate mutational patterns using sequence datasets from five such clonal pathogens belonging to four diverse bacterial clades that span most of the range of genomic nucleotide content. We demonstrate that across different types of sites and in all four clades mutation is consistently biased towards AT. This is true even in clades that have high genomic GC content. In all studied cases the mutational bias towards AT is primarily due to the high rate of C/G to T/A transitions. These results suggest that bacterial mutational biases are far less variable than previously thought. They further demonstrate that variation in nucleotide content cannot stem entirely from variation in mutational biases and that natural selection and/or a natural selection-like process such as biased gene conversion strongly affect nucleotide content

Genome size evolution at the speciation level: The cryptic species complex Brachionus plicatilis (Rotifera)

<p>Abstract</p> <p>Background</p> <p>Studies on genome size variation in animals are rarely done at lower taxonomic levels, e.g., slightly above/below the species level. Yet, such variation might provide important clues on the tempo and mode of genome size evolution. In this study we used the flow-cytometry method to study the evolution of genome size in the rotifer <it>Brachionus plicatilis</it>, a cryptic species complex consisting of at least 14 closely related species.</p> <p>Results</p> <p>We found an unexpectedly high variation in this species complex, with genome sizes ranging approximately seven-fold (haploid '1C' genome sizes: 0.056-0.416 pg). Most of this variation (67%) could be ascribed to the major clades of the species complex, i.e. clades that are well separated according to most species definitions. However, we also found substantial variation (32%) at lower taxonomic levels - within and among genealogical species - and, interestingly, among species pairs that are not completely reproductively isolated. In one genealogical species, called <it>B</it>. 'Austria', we found greatly enlarged genome sizes that could roughly be approximated as multiples of the genomes of its closest relatives, which suggests that whole-genome duplications have occurred early during separation of this lineage. Overall, genome size was significantly correlated to egg size and body size, even though the latter became non-significant after controlling for phylogenetic non-independence.</p> <p>Conclusions</p> <p>Our study suggests that substantial genome size variation can build up early during speciation, potentially even among isolated populations. An alternative, but not mutually exclusive interpretation might be that reproductive isolation tends to build up unusually slow in this species complex.</p

Does using a femoral nerve block for total knee replacement decrease postoperative delirium?

<p>Abstract</p> <p>Background</p> <p>The effect of peripheral nerve blocks on postoperative delirium in older patients has not been studied. Peripheral nerve blocks may reduce the incidence of postoperative opioid use and its side effects such as delirium via opioid-sparing effect.</p> <p>Methods</p> <p>A prospective cohort study was conducted in patients who underwent total knee replacement. Baseline cognitive function was assessed using the Telephone Interview for Cognitive Status. Postoperative delirium was measured using the Confusion Assessment Method postoperatively. Incidence of postoperative delirium was compared in two postoperative management groups: femoral nerve block ± patient-controlled analgesia and patient-controlled analgesia only. In addition, pain levels (using numeric rating scales) and opioid use were compared in two groups.</p> <p>Results</p> <p>85 patients were studied. The overall incidence of postoperative delirium either on postoperative day one or day two was 48.1%. Incidence of postoperative delirium in the femoral nerve block group was lower than patient controlled analgesia only group (25% vs. 61%, <it>P </it>= 0.002). However, there was no significant difference between the groups with respect to postoperative pain level or the amount of intravenous opioid use.</p> <p>Conclusions</p> <p>Femoral nerve block reduces the incidence of postoperative delirium. These results suggest that a larger randomized control trial is necessary to confirm these preliminary findings.</p

Genome-Scale Identification Method Applied to Find Cryptic Aminoglycoside Resistance Genes in Pseudomonas aeruginosa

BACKGROUND:The ability of bacteria to rapidly evolve resistance to antibiotics is a critical public health problem. Resistance leads to increased disease severity and death rates, as well as imposes pressure towards the discovery and development of new antibiotic therapies. Improving understanding of the evolution and genetic basis of resistance is a fundamental goal in the field of microbiology. RESULTS:We have applied a new genomic method, Scalar Analysis of Library Enrichments (SCALEs), to identify genomic regions that, given increased copy number, may lead to aminoglycoside resistance in Pseudomonas aeruginosa at the genome scale. We report the result of selections on highly representative genomic libraries for three different aminoglycoside antibiotics (amikacin, gentamicin, and tobramycin). At the genome-scale, we show significant (p<0.05) overlap in genes identified for each aminoglycoside evaluated. Among the genomic segments identified, we confirmed increased resistance associated with an increased copy number of several genomic regions, including the ORF of PA5471, recently implicated in MexXY efflux pump related aminoglycoside resistance, PA4943-PA4946 (encoding a probable GTP-binding protein, a predicted host factor I protein, a delta 2-isopentenylpyrophosphate transferase, and DNA mismatch repair protein mutL), PA0960-PA0963 (encoding hypothetical proteins, a probable cold shock protein, a probable DNA-binding stress protein, and aspartyl-tRNA synthetase), a segment of PA4967 (encoding a topoisomerase IV subunit B), as well as a chimeric clone containing two inserts including the ORFs PA0547 and PA2326 (encoding a probable transcriptional regulator and a probable hypothetical protein, respectively). CONCLUSIONS:The studies reported here demonstrate the application of new a genomic method, SCALEs, which can be used to improve understanding of the evolution of antibiotic resistance in P. aeruginosa. In our demonstration studies, we identified a significant number of genomic regions that increased resistance to multiple aminoglycosides. We identified genetic regions that include open reading frames that encode for products from many functional categories, including genes related to O-antigen synthesis, DNA repair, and transcriptional and translational processes

CREB Is Activated by Muscle Injury and Promotes Muscle Regeneration

The cAMP response element binding protein (CREB) plays key roles in differentiation of embryonic skeletal muscle progenitors and survival of adult skeletal muscle. However, little is known about the physiologic signals that activate CREB in normal muscle. Here we show that CREB phosphorylation and target genes are induced after acute muscle injury and during regeneration due to genetic mutation. Activated CREB localizes to both myogenic precursor cells and newly regenerating myofibers within regenerating areas. Moreover, we found that signals from damaged skeletal muscle tissue induce CREB phosphorylation and target gene expression in primary mouse myoblasts. An activated CREB mutant (CREBY134F) potentiates myoblast proliferation as well as expression of early myogenic transcription factors in cultured primary myocytes. Consistently, activated CREB-YF promotes myoblast proliferation after acute muscle injury in vivo and enhances muscle regeneration in dystrophic mdx mice. Our findings reveal a new physiologic function for CREB in contributing to skeletal muscle regeneration

Integrated Assessment of Genomic Correlates of Protein Evolutionary Rate

Rates of evolution differ widely among proteins, but the causes and consequences of such differences remain under debate. With the advent of high-throughput functional genomics, it is now possible to rigorously assess the genomic correlates of protein evolutionary rate. However, dissecting the correlations among evolutionary rate and these genomic features remains a major challenge. Here, we use an integrated probabilistic modeling approach to study genomic correlates of protein evolutionary rate in Saccharomyces cerevisiae. We measure and rank degrees of association between (i) an approximate measure of protein evolutionary rate with high genome coverage, and (ii) a diverse list of protein properties (sequence, structural, functional, network, and phenotypic). We observe, among many statistically significant correlations, that slowly evolving proteins tend to be regulated by more transcription factors, deficient in predicted structural disorder, involved in characteristic biological functions (such as translation), biased in amino acid composition, and are generally more abundant, more essential, and enriched for interaction partners. Many of these results are in agreement with recent studies. In addition, we assess information contribution of different subsets of these protein properties in the task of predicting slowly evolving proteins. We employ a logistic regression model on binned data that is able to account for intercorrelation, non-linearity, and heterogeneity within features. Our model considers features both individually and in natural ensembles (“meta-features”) in order to assess joint information contribution and degree of contribution independence. Meta-features based on protein abundance and amino acid composition make strong, partially independent contributions to the task of predicting slowly evolving proteins; other meta-features make additional minor contributions. The combination of all meta-features yields predictions comparable to those based on paired species comparisons, and approaching the predictive limit of optimal lineage-insensitive features. Our integrated assessment framework can be readily extended to other correlational analyses at the genome scale