Development of Biomarkers Based on Diet-Dependent Metabolic Serotypes: Concerns and Approaches for Cohort and Gender Issues in Serum Metabolome Studies

This is the publisher's version, also available electronically from: http://online.liebertpub.com/doi/pdfplus/10.1089/omi.2004.8.209Mathematical models that reflect the effects of dietary restriction (DR) on the sera metabolome may have utility in understanding the mechanisms of DR and in applying this knowledge to human epidemiological studies. Previous studies demonstrated both the feasibility of identifying biomarkers through metabolome analysis and the validity of our approach in independent cohorts of 6-month-oId male and female ad libitum fed or DR rats. Cross-cohort studies showed that cohort-specific effects distorted the dataset The present study extends these observations across the entire sample set, thereby validating our markers independently of specific cohorts. Metabolites originally identified in males were examined in females and vice-versa. DR's effect on the metabolom e is partially gender-specific and is modulated by environmental factors. DR reduces inter-gender differences in the metabolome. Univariate statistical methods showed that 56/93 metabolites in the female samples and 39/93 metabolites in the male samples were significantly altered (using our previous cut-off criteria of p ^ 0.2) by DR. The metabolites modulated by DR present a wide spectrum of concentration, redox reactivity and hydrophilicity, suggesting that our serotype is broadly representative of the metabolome and that DR has broad effects on the metabolome. These studies, coupled with those in the preceding and following reports, also highlight the utility for consideration of the metabolome as a network of metabolites using appropriate data analysis approaches. The inter-cohort and inter-gender differences addressed herein suggest potential cautions, and potential approaches, for identification of multivariate biomarker profiles that reflect changes in physiological status, such as a metabolism that predisposes to increased risk of neoplasia

Development of Biomarkers Based on Diet-Dependent Metabolic Serotypes: Characteristics of Component-Based Models of Metabolic Serotypes

This is the publisher's version, also available electronically from: http://online.liebertpub.com/doi/pdfplus/10.1089/omi.2004Our research seeks to identify a scrum profile, or serotype, that reflects the systemic physiologic modifications resultant from dietary restriction (DR), in part such that this knowledge can be applied for biomarker studies. Direct comparison suggests that component-based classification algorithms consistently out-perform distance-based metrics for studies of nutritional modulation of metabolic serotype, but are subject to over-fitting concerns. Intercohort differences in the sera metabolome could partially obscure the effects of DR. Further analysis now shows that implementation of component-based approaches (also called projection methods) optimized for class separation and controlled for over-fitting have >97% accuracy for distinguishing sera from control or DR rats. DR's effect on the metabolome is shown to be robust across cohorts, but differs in males and females (although some metabolites are affected in both). We demonstrate the utility of projection-based methods for both sample and variable diagnostics, including identification of critical metabolites and samples that are atypical with respect to both class and variable models. Inclusion of non-statistically different variables enhances classification models. Variables that contribute to these models are sharply dependent on mathematical processing techniques; some variables that do not contribute under one paradigm arc powerful under alternative mathematical paradigms. In practical terms, this information may find purpose in other endeavors, such as mechanistic studies of DR. Application of these approaches confirms the utility of megavariate data analysis techniques for optimal generation of biomarkers based on nutritional modulation of physiological processes

Development of Biomarkers Based on Diet-Dependent Metabolic Serotypes: Practical Issues in Development of Expert System-Based Classification Models in Metabolomic Studies

This is the publisher's official version, also available electronically from: http://online.liebertpub.com/doi/pdfplus/10.1089/omi.2004.8.197Dietary restriction (DR)-induced changes in the serum metabolome may be biomarkers for physiological status (e.g., relative risk of developing age-related diseases such as cancer). Megavariate analysis (unsupervised hierarchical cluster analysis IHCAJ; principal components analysis [PCAJ) of serum metabolites reproducibly distinguish DR from ad libitum fed rats. Component-based approaches (i.e., PCA) consistently perform as well as or better than distance-based metrics (i.e., HCA). We therefore tested the following: (A) Do identified subsets of serum metabolites contain sufficient information to construct mathematical models of class membership (i.e., expert systems)? (B) Do component-based metrics out-perform distance-based metrics? Testing was conducted using KNN (k-nearest neighbors, supervised HCA) and SIMCA (soft independent modeling of class analogy, supervised PCA). Models were built with single cohorts, combined cohorts or mixed samples from previously studied cohorts as training sets. Both algorithms over-fit models based on single cohort training sets. KNN models had >85% accuracy within training/test sets, but were unstable (i.e., values of k could not be accurately set in advance). SIMCA models had 100% accuracy within all training sets, 89% accuracy in test sets, did not appear to over-fit mixed cohort training sets, and did not require post-hoc modeling adjustments. These data indicate that (i) previously defined metabolites are robust enough to construct classification models (expert systems) with SIMCA that can predict unknowns by dietary category; (ii) component-based analyses outperformed distance-based metrics; (iii) use of over-fitting controls is essential; and (iv) subtle inter-cohort variability may be a critical issue for high data density biomarker studies that lack state markers

“That’ll Teach Them”: Investigating the Soft Power Conversion Model through the Case of Russian Higher Education

While the international environment remains characterized by the desire of states to strengthen their position, the literature has revealed a growing preference for soft power instruments over military intervention. Higher education has been repurposed as a tool to achieve foreign policy goals, with many states embracing the international norm on world-class universities in an attempt to improve their international competitiveness and their image abroad. This paper considers the soft power conversion model of higher education and attempts to determine its effectiveness through a case study devoted to Russian Higher Education. A survey of foreign students starting their studies and of another finishing their studies in three leading Russian universities reveals that receiving a higher education in Russia may contribute to aligning students’ positions with the Russian perspective on international issues diffused in these universities as was confirmed by surveying a control group of Russian students. These preliminary findings suggest that the benefits of internationalizing national higher education systems are not just reserved to the norm initiators (US, UK) but extend to second wave norm adopters (Russia, China)

Report of the Working Group on Commercial Catches (WGCATCH)

The Working Group on Commercial Catches (WGCATCH), chaired by Hans Gerritsen (Ireland) and Nuno Prista (Sweden), met in Lisbon, Portugal, 9–13 November 2015. WGCATCH is responsible for documenting national fishery sampling schemes, establishing best practice and guidelines on sampling and estimation procedures, and providing advice on other uses of fishery data. The meeting was attended by 30 participants from 15 countries. The group addressed a large number of terms of reference and the meeting was con-ducted through presentations, discussions and analysis of questionnaires. The main terms of reference were addressed in subgroups. The report is structured directly along the terms of reference and the main outcomes are listed below. Data collection schemes for small-scale fisheries WGCATCH provided descriptions of national small-scale fisheries through question-naires. An overview was obtained on the current data collection methods. Two major approaches were identified - census (e.g., sales, logbooks) and sampling methods (e.g., catch surveys) - and their main pros and cons were discussed. In most cases, specific sampling approaches are needed for these fisheries. The group developed a work plan to establish good-practice guidelines. Analysis of case studies of commercial fishery sampling designs and estimation Case studies of sampling designs and estimation involving megrim in divisions 7-8 were presented. A common theme is that issues with practical implementation of prob-ability-based sampling remain. WGCATCH summarized the main issues and provided a set of possible solutions. The group also provided guidance on dealing with previous data collected under métier-based sampling designs. Simulation models to investigate survey designs Several simulation studies were presented, most of them outlining the work of fishPi project (funded under MARE/2014/19) in evaluating regional sampling designs. A crit-ical review was carried out and WGCATCH produced general considerations and guidelines. WGCATCH recommends that these are taken into account when analysing the results of simulations of regional sampling design at RCM level. The affect of the landing obligation on catch sampling opportunities The affects on sampling and data quality of the current implementation of the landing obligation in the Baltic were reviewed. The group found that refusal rates for observer trips have increased to nearly 100% in at least one country, while in many other coun-tries on-board observer programmes did not suffer noticeable changes. WGCATCH established that the catches below the minimum size cannot be accurately estimated by sampling the landings below the minimum size because an unknown proportion of the catches may be discarded. The group also reiterated that it is important that the logbooks distinguish landings below and above the minimum size. Publication on statistically sound sampling schemes WGCATCH drafted detailed plans to produce a peer-reviewed paper in 2016. The pa-per will provide a synthesis of the evolution of sampling design towards best practice, illustrated with a number of concise case studies. Estimation procedures in the Regional Database (RDB) The work of WKRDB 2015 presented alongside existing and planned estimation pro-cedures in the RDB. Current work by Norway on a software package that will allow design-based estimation and optimization for stock assessment purposes was also pre-sented. The advantages of ensuring compatibility of this new software with the devel-opments currently planned for RDB-FishFrame are underscored. Repository of resources relevant to catch sampling WGCATCH initiated a repository with key resources; putting them into context with brief descriptions or review of each report, paper, book, website, software package etc. The intention is for this repository to be made available online by ICES. Sampling of incidental bycatches WGCATCH agreed to start routine documentation of sampling practices for bycatches of protected, endangered and threatened species (PETS) and rare fish species as well as routine evaluation of the limitations of current methods for collection and analysis. Training course on Design and Analysis of Statistical Sound catch sampling pro-grammes WGCATCH considered continuous training and expertise on sampling design, estima-tion and simulation to be the basis for successful implementation of statistical sound catch sampling programs. A new ICES Training Course in Design and Analysis of Sta-tistical Sound will take place at ICES HQ in Copenhagen, 12–16 September 2016. WGCATCH recommends that RCMs promote the attendance of these meetings among all MS involved

Sensitive radio-frequency read-out of quantum dots using an ultra-low-noise SQUID amplifier

Fault-tolerant spin-based quantum computers will require fast and accurate qubit readout. This can be achieved using radio-frequency reflectometry given sufficient sensitivity to the change in quantum capacitance associated with the qubit states. Here, we demonstrate a 23-fold improvement in capacitance sensitivity by supplementing a cryogenic semiconductor amplifier with a SQUID preamplifier. The SQUID amplifier operates at a frequency near 200 MHz and achieves a noise temperature below 600 mK when integrated into a reflectometry circuit, which is within a factor 120 of the quantum limit. It enables a record sensitivity to capacitance of 0.07 aF/ \sqrt{Hz}. The setup is used to acquire charge stability diagrams of a gate-defined double quantum dot in a short time with a signal-to-noise ration of about 38 in 1 μs of integration time

Could the clinical interpretability of subgroups detected using clustering methods be improved by using a novel two-stage approach?

Background: Recognition of homogeneous subgroups of patients can usefully improve prediction of their outcomes and the targeting of treatment. There are a number of research approaches that have been used to recognise homogeneity in such subgroups and to test their implications. One approach is to use statistical clustering techniques, such as Cluster Analysis or Latent Class Analysis, to detect latent relationships between patient characteristics. Influential patient characteristics can come from diverse domains of health, such as pain, activity limitation, physical impairment, social role participation, psychological factors, biomarkers and imaging. However, such 'whole person' research may result in data-driven subgroups that are complex, difficult to interpret and challenging to recognise clinically. This paper describes a novel approach to applying statistical clustering techniques that may improve the clinical interpretability of derived subgroups and reduce sample size requirements. Methods: This approach involves clustering in two sequential stages. The first stage involves clustering within health domains and therefore requires creating as many clustering models as there are health domains in the available data. This first stage produces scoring patterns within each domain. The second stage involves clustering using the scoring patterns from each health domain (from the first stage) to identify subgroups across all domains. We illustrate this using chest pain data from the baseline presentation of 580 patients. Results: The new two-stage clustering resulted in two subgroups that approximated the classic textbook descriptions of musculoskeletal chest pain and atypical angina chest pain. The traditional single-stage clustering resulted in five clusters that were also clinically recognisable but displayed less distinct differences. Conclusions: In this paper, a new approach to using clustering techniques to identify clinically useful subgroups of patients is suggested. Research designs, statistical methods and outcome metrics suitable for performing that testing are also described. This approach has potential benefits but requires broad testing, in multiple patient samples, to determine its clinical value. The usefulness of the approach is likely to be context-specific, depending on the characteristics of the available data and the research question being asked of it

Red Clump Morphology as Evidence Against a New Intervening Stellar Population as the Primary Source of Microlensing Toward the LMC

We examine the morphology of the color-magnitude diagram (CMD) for core helium-burning (red clump) stars to test the recent suggestion by Zaritsky & Lin (1997) that an extension of the red clump in the Large Magellanic Cloud (LMC) toward brighter magnitudes is due to an intervening population of stars that is responsible for a significant fraction of the observed microlensing toward the LMC. Using our own CCD photometry of several fields across the LMC, we confirm the presence of this additional red clump feature, but conclude that it is caused by stellar evolution rather than a foreground population. We do this by demonstrating that the feature (1) is present in all our LMC fields, (2) is in precise agreement with the location of the blue loops in the isochrones of intermediate age red clump stars with the metallicity and age of the LMC, (3) has a relative density consistent with stellar evolution and LMC star formation history, and (4) is present in the Hipparcos CMD for the solar neighborhood where an intervening population cannot be invoked. Assuming there is no systematic shift in the model isochrones, which fit the Hipparcos data in detail, a distance modulus of $\mu_{LMC} = 18.3$ provides the best fit to our dereddened CMD.Comment: 21 pages LaTex (aaspp4.sty), including three tables and 9 figures (1 is .ps, 8 are .gif). Accepted for publication by Astronomical Journal on March 16, 1998. One error corrected and major revisions now lead to an even stronger argument for the stellar evolutionary origin of features in the LMC color magnitude diagram, claimed by others to be an intervening stellar population and major source of microlensing optical depth toward the LM

A double blind randomized trial of wound infiltration with ropivacaine after breast cancer surgery with axillary nodes dissection

<p>Abstract</p> <p>Background</p> <p>The effect of local infiltration after breast surgery is controversial. This prospective double blind randomized study sought to document the analgesic effect of local anaesthetic infiltration after breast cancer surgery.</p> <p>Methods</p> <p>Patients scheduled for mastectomy or tumorectomy and axillary nodes dissection had immediate postoperative infiltration of the surgical wound with 20 ml of ropivacaine 7.5 mg.ml^-1or isotonic saline. Pain was assessed on a visual analogue scale at H2, H4, H6, H12, H24, H72, and at 2 month, at rest and on mobilization of the arm. Patient'comfort was evaluated with numerical 0-3 scales for fatigue, quality of sleep, state of mood, social function and activity.</p> <p>Results</p> <p>Twenty-two and 24 patients were included in the ropivacaine and saline groups respectively. Postoperative pain was lower at rest and on mobilization at 2, 4 and 6 hour after surgery in the ropivacaine group. No other difference in pain intensity and patient 'comfort scoring was documented during the first 3 postoperative days. Patients did not differ at 2 month for pain and comfort scores.</p> <p>Conclusion</p> <p>Single shot infiltration with ropivacaine transiently improves postoperative pain control after breast cancer surgery.</p> <p>Trial registration number</p> <p><a href="http://www.clinicaltrials.gov/ct2/show/NCT01404377">NCT01404377</a></p