Role of PTEN in TNFα induced insulin resistance.

AIMS/HYPOTHESIS: PTEN may play a reversible role in TNFα induced insulin resistance, which has been linked to obesity-associated insulin resistance (IR). METHODS: Western blots for PTEN and p-Akt were performed on H-411E liver cells incubated with insulin, TNFα, and in selected experiments VO-OHpic vanadium complex in the presence and absence of PTEN siRNA. Total PTEN was compared to ß-actin loading control and p-Akt was compared to total Akt. RESULTS: Western blot and Real Time RT-PCR experiments showed increased PTEN after TNFα treatment (p = 0.04); slightly decreased PTEN after insulin treatment; and slightly increased PTEN after insulin + TNFα treatment. PTEN siRNA markedly inhibited the TNFα-induced increase in PTEN (p < 0.01) without significantly changing the p-Akt levels. The vanadium complex, exhibiting insulin-like effects, also significantly prevented the TNFα-induced increase in PTEN. Combining insulin and VO-OHpic was additive, providing both proof of concept and insight into mechanism. DISCUSSION: The PTEN increase due to TNFα treatment was reversible by both PTEN siRNA knockdown and VO-OHpic treatment. Thus, PTEN is identified as a potential new therapeutic target for reducing IR in Type 2 DM.

The effects of rhythmic structure on tapping accuracy.

Prior investigations of simple rhythms in familiar time signatures have shown the importance of several mechanisms; notably, those related to metricization and grouping. But there has been limited study of complex rhythms, including those in unfamiliar time signatures, such as are found outside mainstream Western music. Here, we investigate how the structures of 91 rhythms with nonisochronous onsets (mostly complex, several in unfamiliar time signatures) influence the accuracy, velocity, and timing of taps made by participants attempting to synchronize with these onsets. The onsets were piano-tone cues sounded at a well-formed subset of isochronous cymbal pulses; the latter occurring every 234 ms. We modelled tapping at both the rhythm level and the pulse level; the latter provides insight into how rhythmic structure makes some cues easier to tap and why incorrect (uncued) taps may occur. In our models, we use a wide variety of quantifications of rhythmic features, several of which are novel and many of which are indicative of underlying mechanisms, strategies, or heuristics. The results show that, for these tricky rhythms, taps are disrupted by unfamiliar period lengths and are guided by crude encodings of each rhythm: the density of rhythmic cues, their circular mean and variance, and recognizing common small patterns and the approximate positions of groups of cues. These lossy encodings are often counterproductive for discriminating between cued and uncued pulses and are quite different to mechanisms-such as metricization and emphasizing group boundaries-thought to guide tapping behaviours in learned and familiar rhythms.

Multilevel latent variable models for global health-related quality of life assessment.

Quality of life (QOL) assessment is a key component of many clinical studies and frequently requires the use of single global summary measures that capture the overall balance of findings from a potentially wide-ranging assessment of QOL issues. We propose and evaluate an irregular multilevel latent variable model suitable for use as a global summary tool for health-related QOL assessments. The proposed model is a multiple indicator and multiple cause style of model with a two-level latent variable structure. We approach the modeling from a general multilevel modeling perspective, using a combination of random and nonrandom cluster types to accommodate the mixture of issues commonly evaluated in health-related QOL assessments--overall perceptions of QOL and health, along with specific psychological, physical, social, and functional issues. Using clinical trial data, we evaluate the merits and application of this approach in detail, both for mean global QOL and for change from baseline. We show that the proposed model generally performs well in comparing global patterns of treatment effect and provides more precise and reliable estimates than several common alternatives such as selecting from or averaging observed global item measures. A variety of computational methods could be used for estimation. We derived a closed-form expression for the marginal likelihood that can be used to obtain maximum likelihood parameter estimates when normality assumptions are reasonable. Our approach is useful for QOL evaluations aimed at pharmacoeconomic or individual clinical decision making and in obtaining summary QOL measures for use in quality-adjusted survival analyses.

ChIPseqR: analysis of ChIP-seq experiments.

BACKGROUND: The use of high-throughput sequencing in combination with chromatin immunoprecipitation (ChIP-seq) has enabled the study of genome-wide protein binding at high resolution. While the amount of data generated from such experiments is steadily increasing, the methods available for their analysis remain limited. Although several algorithms for the analysis of ChIP-seq data have been published they focus almost exclusively on transcription factor studies and are usually not well suited for the analysis of other types of experiments. RESULTS: Here we present ChIPseqR, an algorithm for the analysis of nucleosome positioning and histone modification ChIP-seq experiments. The performance of this novel method is studied on short read sequencing data of Arabidopsis thaliana mononucleosomes as well as on simulated data. CONCLUSIONS: ChIPseqR is shown to improve sensitivity and spatial resolution over existing methods while maintaining high specificity. Further analysis of predicted nucleosomes reveals characteristic patterns in nucleosome sequences and placement.

Estimation of the reproductive number for the 2009 pandemic H1N1 influenza in rural and metropolitan New South Wales.

OBJECTIVE: During the early stages of pandemics, when resource planning occurs, the epidemiological parameters of the agent are often poorly described. These estimates are typically derived from metropolitan centres. This paper examines the spread of the 2009 pandemic H1N1 virus in rural and regional New South Wales compared with metropolitan centres. DESIGN: Retrospective statistical analysis of longitudinal data. SETTING: Ecological examination of spread of influenza in the general community of New South Wales, Australia. PARTICIPANTS: Number of notified infections with novel pandemic H1N1 influenza in rural/regional (n=241) and metropolitan (n=1788) health service areas of New South Wales during the period 1 June 2009 and 12 July 2009. MAIN OUTCOME MEASURES: A comparison of the reproductive number for the 2009 pandemic H1N1 in rural/regional and metropolitan New South Wales. RESULTS: The reproductive number of the pandemic H1N1 in rural New South Wales was 1.26 (95% confidence interval (CI), 1.22-1.30) compared with estimates of metropolitan New South Wales of 1.28 (95% CI, 1.26-1.30). This difference was not statistically significant (P=0.314). These estimates are lower than those previously published and of the order of magnitude typically observed with seasonal flu. This was consistent with the clinical observations in Greater Southern Area Health Service. CONCLUSION: The apparent invariance in the rate of spread of influenza between rural and metropolitan areas should provide rural health care providers with confidence in metropolitan derived estimates when planning in future influenza pandemics.

Chronic Systemic Inflammatory Skin Disease as a Risk Factor for Cardiovascular Disease.

Chronic systemic skin disease and cardiovascular disease are multisystem disorders which have been associated with each other for centuries. Recent research has strengthened this association, particularly in systemic inflammatory disease. Here we explore the current literature on psoriasis, hidradenitis suppurativa, lupus erythematosus, acanthosis nigricans, atopic dermatitis, and bullous pemphigoid. Psoriasis is a chronic inflammatory disorder that has been labeled as a risk-modifier for hyperlipidemia and coronary artery disease by the American College of Cardiology ACC lipid guidelines. Cardiovascular disease is also found at a significantly higher rate in patients with hidradenitis suppurativa and lupus erythematosus. Some associations have even been noted between cardiovascular disease and acanthosis nigricans, atopic dermatitis, and bullous pemphigoid. While many of these associations have been attributed to a shared underlying disease process such as chronic systemic inflammation and shared underlying risk factors, these dermatologic manifestations can help to identify patients at higher risk for cardiovascular disease.

Truncation of Pik3r1 causes severe insulin resistance uncoupled from obesity and dyslipidaemia by increased energy expenditure.

OBJECTIVE: Insulin signalling via phosphoinositide 3-kinase (PI3K) requires PIK3R1-encoded regulatory subunits. C-terminal PIK3R1 mutations cause SHORT syndrome, as well as lipodystrophy and insulin resistance (IR), surprisingly without fatty liver or metabolic dyslipidaemia. We sought to investigate this discordance. METHODS: The human pathogenic Pik3r1 Y657∗ mutation was knocked into mice by homologous recombination. Growth, body composition, bioenergetic and metabolic profiles were investigated on chow and high-fat diet (HFD). We examined adipose and liver histology, and assessed liver responses to fasting and refeeding transcriptomically. RESULTS: Like humans with SHORT syndrome, Pik3r1WT/Y657∗ mice were small with severe IR, and adipose expansion on HFD was markedly reduced. Also as in humans, plasma lipid concentrations were low, and insulin-stimulated hepatic lipogenesis was not increased despite hyperinsulinemia. At odds with lipodystrophy, however, no adipocyte hypertrophy nor adipose inflammation was found. Liver lipogenic gene expression was not significantly altered, and unbiased transcriptomics showed only minor changes, including evidence of reduced endoplasmic reticulum stress in the fed state and diminished Rictor-dependent transcription on fasting. Increased energy expenditure, which was not explained by hyperglycaemia nor intestinal malabsorption, provided an alternative explanation for the uncoupling of IR from dyslipidaemia. CONCLUSIONS: Pik3r1 dysfunction in mice phenocopies the IR and reduced adiposity without lipotoxicity of human SHORT syndrome. Decreased adiposity may not reflect bona fide lipodystrophy, but rather, increased energy expenditure, and we suggest that further study of brown adipose tissue in both humans and mice is warranted.

Barriers physicians face when referring patients to cardiac rehabilitation: a narrative review.

While cardiac rehabilitation (CR) has been shown to be a beneficial form of secondary prevention for patients with cardiovascular disease, barriers of referral to CR still exist for patients. Barriers that specifically make it difficult for physicians to make the referral could be worthwhile to examine. This narrative review hypothesizes that increasing awareness and education on the various aspects of CR as well as simplifying the referral process could lead to increased referral rates as they target physician-related barriers. This narrative review seeks to further understand the physician-related barriers of low CR awareness and hindering referral processes. A search in Scopus was conducted with preference for articles examining CR referral strategies used by physicians; physicians' awareness of CR programs; physicians' perceptions, beliefs, or knowledge of the benefits of CR; or physicians' experience with or understanding of the selection process of CR programs, including indications for referral. Two systematic reviews and two observational studies were selected for discussion. Three of the selected studies had findings supporting the notion that increasing physicians' awareness of CR could impact referral rates. One of the studies evaluated the perceptions that physicians and CR programs had on various referral strategies. While more study is needed to assess the actual level of knowledge and awareness physicians have regarding CR, this review supports using educational interventions as well as targeting various aspects of the referral process for improving referral rates.

Action plan for improving cardiac rehabilitation-related outcomes in a university hospital based on a review of previous interventions.

Although referral to cardiac rehabilitation (CR) is considered the standard of care and demonstrably reduces both mortality rates and hospital admissions after cardiac events, rates of referral continue to be suboptimal. In fact, national reports reveal rates ranging from approximately 60% to 85% depending on the type of cardiac event. At an urban teaching hospital in Tennessee, efforts to increase referral rates were launched during the first quarter of 2018 as part of the Define, Measure, Analyze, Improve, Control (DMAIC) Project: Acute Myocardial Infarction (AMI) Transition of Care. The goal of this Action Plan is to review the interventions taken and the outcomes data from this project in order to propose future deliverables that can address areas of improvement within the DMAIC project. A list of the DMAIC project's interventions, which were varied and multidisciplinary, were obtained from the university hospital as well as the project's data. Data from the National Cardiovascular Data Registry (NCDR)-ACTION Registry show that referral rates at this hospital have been on the rise since the initiation of the DMAIC project. Peak referral rates in the year before the interventions were implemented were approximately 39%; whereas, the peak referral rate in the year these interventions were launched rose to 86.4%. While the interventions of the DMAIC project are hypothesized to have contributed to this increase in referral rates, based on their collaborative nature and the types of referral strategies employed, there are still opportunities for improvement and growth. Thus, this Action Plan proposes future projects to increase inclusivity of CR referral pathways, improve physician education, and establish support for outpatient CR programs.

Parameter estimation for robust HMM analysis of ChIP-chip data.

BACKGROUND: Tiling arrays are an important tool for the study of transcriptional activity, protein-DNA interactions and chromatin structure on a genome-wide scale at high resolution. Although hidden Markov models have been used successfully to analyse tiling array data, parameter estimation for these models is typically ad hoc. Especially in the context of ChIP-chip experiments, no standard procedures exist to obtain parameter estimates from the data. Common methods for the calculation of maximum likelihood estimates such as the Baum-Welch algorithm or Viterbi training are rarely applied in the context of tiling array analysis. RESULTS: Here we develop a hidden Markov model for the analysis of chromatin structure ChIP-chip tiling array data, using t emission distributions to increase robustness towards outliers. Maximum likelihood estimates are used for all model parameters. Two different approaches to parameter estimation are investigated and combined into an efficient procedure. CONCLUSION: We illustrate an efficient parameter estimation procedure that can be used for HMM based methods in general and leads to a clear increase in performance when compared to the use of ad hoc estimates. The resulting hidden Markov model outperforms established methods like TileMap in the context of histone modification studies.

Caenorhabditis elegans DAF-2 as a Model for Human Insulin Receptoropathies.

Human exome sequencing has dramatically increased the rate of identification of disease-associated polymorphisms. However, examining the functional consequences of those variants has created an analytic bottleneck. Insulin-like signaling in Caenorhabditis elegans has long provided a model to assess consequences of human insulin signaling mutations, but this has not been evaluated in the context of current genetic tools. We have exploited strains derived from the Million Mutation Project (MMP) and gene editing to explore further the evolutionary relationships and conservation between the human and C. elegans insulin receptors. Of 40 MMP alleles analyzed in the C. elegans insulin-like receptor gene DAF-2, 35 exhibited insulin-like signaling indistinguishable from wild-type animals, indicating tolerated mutations. Five MMP alleles proved to be novel dauer-enhancing mutations, including one new allele in the previously uncharacterized C-terminus of DAF-2 CRISPR-Cas9 genome editing was used to confirm the phenotypic consequence of six of these DAF-2 mutations and to replicate an allelic series of known human disease mutations in a highly conserved tyrosine kinase active site residue, demonstrating the utility of C. elegans for directly modeling human disease. Our results illustrate the challenges associated with prediction of the phenotypic consequences of amino acid substitutions, the value of assaying mutant isoform function in vivo, and how recently developed tools and resources afford the opportunity to expand our understanding even of highly conserved regulatory modules such as insulin signaling. This approach may prove generally useful for modeling phenotypic consequences of candidate human pathogenic mutations in conserved signaling and developmental pathways.

Human biallelic MFN2 mutations induce mitochondrial dysfunction, upper body adipose hyperplasia, and suppression of leptin expression.

MFN2 encodes mitofusin 2, a membrane-bound mediator of mitochondrial membrane fusion and inter-organelle communication. MFN2 mutations cause axonal neuropathy, with associated lipodystrophy only occasionally noted, however homozygosity for the p.Arg707Trp mutation was recently associated with upper body adipose overgrowth. We describe similar massive adipose overgrowth with suppressed leptin expression in four further patients with biallelic MFN2 mutations and at least one p.Arg707Trp allele. Overgrown tissue was composed of normal-sized, UCP1-negative unilocular adipocytes, with mitochondrial network fragmentation, disorganised cristae, and increased autophagosomes. There was strong transcriptional evidence of mitochondrial stress signalling, increased protein synthesis, and suppression of signatures of cell death in affected tissue, whereas mitochondrial morphology and gene expression were normal in skin fibroblasts. These findings suggest that specific MFN2 mutations cause tissue-selective mitochondrial dysfunction with increased adipocyte proliferation and survival, confirm a novel form of excess adiposity with paradoxical suppression of leptin expression, and suggest potential targeted therapies.

Determination of Abraham model solute descriptors for the monomeric and dimeric forms of trans-cinnamic acid using measured solubilities from the Open Notebook Science Challenge.

BACKGROUND: Calculating Abraham descriptors from solubility values requires that the solute have the same form when dissolved in all solvents. However, carboxylic acids can form dimers when dissolved in non-polar solvents. For such compounds Abraham descriptors can be calculated for both the monomeric and dimeric forms by treating the polar and non-polar systems separately. We illustrate the method of how this can be done by calculating the Abraham descriptors for both the monomeric and dimeric forms of trans-cinnamic acid, the first time that descriptors for a carboxylic acid dimer have been obtained. RESULTS: Abraham descriptors were calculated for the monomeric form of trans-cinnamic acid using experimental solubility measurements in polar solvents from the Open Notebook Science Challenge together with a number of water-solvent partition coefficients from the literature. Similarly, experimental solubility measurements in non-polar solvents were used to determine Abraham descriptors for the trans-cinnamic acid dimer. CONCLUSION: Abraham descriptors were calculated for both the monomeric and dimeric forms of trans-cinnamic acid. This allows for the prediction of further solubilities of trans-cinnamic acid in both polar and non-polar solvents with an error of about 0.10 log units. Graphical abstractMolar concentration of trans-cinnamic acid in various polar and non-polar solvents.

Male brush-turkeys attempt sexual coercion in unusual circumstances.

Sexual coercion by males is generally understood to have three forms: forced copulation, harassment and intimidation. We studied Australian brush-turkeys, Alectura lathami, to determine whether some male behaviours towards females at incubation mounds could be classified as aggressive, whether males were attempting sexual coercion and, if so, whether the coercion was successful. We found that some male behaviours towards females were significantly more likely to be followed by the cessation of female mound activity, and hence could be classified as aggressive, while others were significantly more likely to be followed by the commencement of female mound activity, and hence could be classified as enticing. Copulation was preceded by higher rates of male enticement and by higher rates of certain types of male aggression. It therefore seemed that males were attempting sexual coercion. There was little evidence, however, that this combination of coercion and enticement was successful in obtaining copulations. While forced copulation did occur, it was infrequent, and no evidence could be found for intimidation. We conclude that harassment is the primary form of sexual coercion by male brush-turkeys. Although sexual coercion is understood to be a sub-optimal tactic, brush-turkey sexual coercion was employed as a primary tactic by dominant males who owned incubation mounds. One possible explanation for this apparent paradox is that aggression is the default solution for social conflicts in this species, and hence can be interpreted as a behavioural syndrome.

Trends and weekly and seasonal cycles in the rate of errors in the clinical management of hospitalized patients.

Studies on the rate of adverse events in hospitalized patients seldom examine temporal patterns. This study presents evidence of both weekly and annual cycles. The study is based on a large and diverse data set, with nearly 5 yrs of data from a voluntary staff-incident reporting system of a large public health care provider in rural southeastern Australia. The data of 63 health care facilities were included, ranging from large non-metropolitan hospitals to small community and aged health care facilities. Poisson regression incorporating an observation-driven autoregressive effect using the GLARMA framework was used to explain daily error counts with respect to long-term trend and weekly and annual effects, with procedural volume as an offset. The annual pattern was modeled using a first-order sinusoidal effect. The rate of errors reported demonstrated an increasing annual trend of 13.4% (95% confidence interval [CI] 10.6% to 16.3%); however, this trend was only significant for errors of minor or no harm to the patient. A strong "weekend effect" was observed. The incident rate ratio for the weekend versus weekdays was 2.74 (95% CI 2.55 to 2.93). The weekly pattern was consistent for incidents of all levels of severity, but it was more pronounced for less severe incidents. There was an annual cycle in the rate of incidents, the number of incidents peaking in October, on the 282 nd day of the year (spring in Australia), with an incident rate ratio 1.09 (95% CI 1.05 to 1.14) compared to the annual mean. There was no so-called "killing season" or "July effect," as the peak in incident rate was not related to the commencement of work by new medical school graduates. The major finding of this study is the rate of adverse events is greater on weekends and during spring. The annual pattern appears to be unrelated to the commencement of new graduates and potentially results from seasonal variation in the case mix of patients or the health of the medical workforce that alters health care performance. These mechanisms will need to be elucidated with further research.

Two-step cross-entropy feature selection for microarrays­power through complementarity.

Current feature selection methods for supervised classification of tissue samples from microarray data generally fail to exploit complementary discriminatory power that can be found in sets of features. Using a feature selection method with the computational architecture of the cross-entropy method, including an additional preliminary step ensuring a lower bound on the number of times any feature is considered, we show when testing on a human lymph node data set that there are a significant number of genes that perform well when their complementary power is assessed, but "pass under the radar" of popular feature selection methods that only assess genes individually on a given classification tool. We also show that this phenomenon becomes more apparent as diagnostic specificity of the tissue samples analysed increases.