Statistical methods for temporal and space–time analysis of community composition data

This review focuses on the analysis of temporal beta diversity, which is the variation in community composition along time in a study area. Temporal beta diversity is measured by the variance of the multivariate community composition time series and that variance can be partitioned using appropriate statistical methods. Some of these methods are classical, such as simple or canonical ordination, whereas others are recent, including the methods of temporal eigenfunction analysis developed for multiscale exploration (i.e. addressing several scales of variation) of univariate or multivariate response data, reviewed, to our knowledge for the first time in this review. These methods are illustrated with ecological data from 13 years of benthic surveys in Chesapeake Bay, USA. The following methods are applied to the Chesapeake data: distance-based Moran''s eigenvector maps, asymmetric eigenvector maps, scalogram, variation partitioning, multivariate correlogram, multivariate regression tree, and two-way MANOVA to study temporal and space–time variability. Local (temporal) contributions to beta diversity (LCBD indices) are computed and analysed graphically and by regression against environmental variables, and the role of species in determining the LCBD values is analysed by correlation analysis. A tutorial detailing the analyses in the R language is provided in an appendix.     

IRAP — A system for the retrieval and analysis of orthopaedic implant data

An interactive computer system for the storage, retrieval and analysis of standardized clinical and material characterization data associated with orthopaedic implants is described. The system consists basically of four independent modules. The essence of the system centers on the cross-referencing capabilities which are virtually unlimited. The system has been designed for use by non-computer trained personnel.     

HOSEpipE—a WWW-hosted data management and analysis system for STS content mapping projects

We have developed a data management system, `HOSEpipe' (High Output STS Evaluation pipeline) to aid sample tracking and data analysis in STS content mapping projects. The system is based around a World Wide Web (WWW) server that provides a number of pages including forms for sample processing and data entry accessible via a standard WWW browser application. The system is split into two main modules: firstly, a sequence evaluation and annotation module that takes de novo sequence for a potential STS, screens it against existing STSs and DNA sequence databases, followed by appropriate primer sequence design; secondly, a module that handles YAC library STS screening and includes facilities for both sample tracking and experimental data analysis. We present the design and rationale of the HOSEpipe system and its development to support a whole chromosomal physical mapping project. This software and design approach is potentially applicable to physical mapping projects of varying sizes and resolution and to similar projects, such as sample sequencing and the construction of sequence-ready maps. Received: 18 November 1996 / Accepted: 19 March 1997     

CGHPRO – A comprehensive data analysis tool for array CGH

Background  

Array CGH (Comparative Genomic Hybridisation) is a molecular cytogenetic technique for the genome wide detection of chromosomal imbalances. It is based on the co-hybridisation of differentially labelled test and reference DNA onto arrays of genomic BAC clones, cDNAs or oligonucleotides, and after correction for various intervening variables, loss or gain in the test DNA can be indicated from spots showing aberrant signal intensity ratios.     

Are the existing EU Ecolabel criteria for furniture products too complex? An analysis of complexity from a material and a supply chain perspective and suggestions for ways ahead

The International Journal of Life Cycle Assessment - One possible reason for the poor uptake of the EU Ecolabel for furniture products may be that the criteria are too complex for applicants....     

A Fad too Far? Dietary Strategies for the Prevention and Treatment of NAFLD

Nonalcoholic fatty liver disease (NAFLD) is a major health problem, and its prevalence has increased in recent years, concurrent with rising rates of obesity and other metabolic diseases. Currently, there are no FDA‐approved pharmacological therapies for NAFLD, and lifestyle interventions, including weight loss and exercise, remain the cornerstones for treatment. Manipulating diet composition and eating patterns may be a sustainable approach to NAFLD treatment. Dietary strategies including Paleolithic, ketogenic, Mediterranean, high‐protein, plant‐based, low‐carbohydrate, and intermittent fasting diets have become increasingly popular because of their purported benefits on metabolic disease. This review highlights what is currently known about these popular dietary approaches in the management of NAFLD in clinical populations with mechanistic insight from animal studies. It also identifies key knowledge gaps to better inform future preclinical and clinical studies aimed at the treatment of NAFLD.     

caBIG™ VISDA: Modeling, visualization, and discovery for cluster analysis of genomic data

Background

We sketch our species identification tool for palm sized computers that helps knowledgeable observers with census activities. An algorithm turns an identification matrix into a minimal length series of questions that guide the operator towards identification. Historic observation data from the census geographic area helps minimize question volume. We explore how much historic data is required to boost performance, and whether the use of history negatively impacts identification of rare species. We also explore how characteristics of the matrix interact with the algorithm, and how best to predict the probability of observing a previously unseen species.

Results

Point counts of birds taken at Stanford University's Jasper Ridge Biological Preserve between 2000 and 2005 were used to examine the algorithm. A computer identified species by correctly answering, and counting the algorithm's questions. We also explored how the character density of the key matrix and the theoretical minimum number of questions for each bird in the matrix influenced the algorithm. Our investigation of the required probability smoothing determined whether Laplace smoothing of observation probabilities was sufficient, or whether the more complex Good-Turing technique is required.

Conclusion

Historic data improved identification speed, but only impacted the top 25% most frequently observed birds. For rare birds the history based algorithms did not impose a noticeable penalty in the number of questions required for identification. For our dataset neither age of the historic data, nor the number of observation years impacted the algorithm. Density of characters for different taxa in the identification matrix did not impact the algorithms. Intrinsic differences in identifying different birds did affect the algorithm, but the differences affected the baseline method of not using historic data to exactly the same degree. We found that Laplace smoothing performed better for rare species than Simple Good-Turing, and that, contrary to expectation, the technique did not then adversely affect identification performance for frequently observed birds.     

Statistical survey of “saturation analysis” calibration curve data for prednisolone,prednisone and digoxin

An extensive survey of radioimmunoassay calibration data for prednisolone, prednisone and digoxin indicated that the common practice of preparing calibration curves with individual subject's pre-dose plasma or serum, and using this to estimate unknown concentrations for the same subject, is not supported by statistical considerations. Preparation of calibration plots from pooled data is better because this introduces less bias in estimated concentrations. Such a method also saves a great deal of time, since it is not necessary to repeat the calibration procedure each time “unknowns” are being assayed. The data suggest that there is no optimum calibration plot for all radioimmunoassays. Rather, each antibody-drug combination should be investigated thoroughly to determine the best calibration plot for the particular combination. We found that the best calibration plots are; the logistic-logarithmic plot for prednisolone; nonlinear least squares fit to a polyexponential equation for prednisone; and a weighted least squares regression of normalized % bound $\text{versus}$ concentration for digoxin. The error in the radioimmunoassay is usually concentration-dependent, and, in certain regions of the standard curve, is larger than the literature indicates, since, frequently, the error has been gauged from % bound values, but should be gauged from inversely-estimated concentrations.     

Performance analysis of optical interconnects’ architectures for data center networks

Electrical interconnects in Data Center Networks (DCNs) suffer from various problems which include high energy consumption, high latency, fixed throughput of links and limited reconfigurability. Introducing optical interconnects in DCNs help to reduce these problems to a large extent. Optical interconnects are the technology of the future. To implement optical switching in DCNs various optical components are used which include wavelength selective switch, tunable wavelength converter, arrayed waveguide grating, semiconductor optical amplifier based switch, wavelength division multiplexers and demultiplexers. All these optical components vary the shape, attenuate the optical signal and introduce time delay in bits. A comprehensive study of various architectures for optical interconnects in data center networks (DCN) is carried out. Performance of various architectures is investigated in terms of jitter, bit error rate (BER), receiver sensitivity and eye diagram opening. It is also investigated how different optical components used in optical interconnects in DCNs are effecting the signal degradation in different architectures. The paper concludes with the categorization of the signal degradation types in optical interconnects in DCNs and ways to reduce them. This enables the design of low BER optical interconnects in DCNs.     

Are crocodiles really monophyletic?--Evidence for subdivisions from sequence and morphological data

Recently, the phylogenetic placement of the African slender snouted crocodile, Crocodylus cataphractus, has come under scrutiny and herein we address this issue using molecular and morphological techniques. Although it is often recognized as being a "basal" form, morphological studies have traditionally placed C. cataphractus within the genus Crocodylus, while molecular studies have suggested that C. cataphractus is very distinct from other Crocodylus. To address the relationship of this species to its congeners we have sequenced portions of two nuclear genes (C-mos 302bp and ODC 294bp), and two mitochondrial genes (ND6-tRNA(glu)-cytB 347bp and control region 457bp). Analyses of these molecular datasets, both as individual gene sequences and as concatenated sequences, support the hypothesis that C. cataphractus is not a member of Crocodylus or Osteolaemus. Examination of 165 morphological characters supports and strengthens our resurrection of an historic genus, Mecistops (Gray 1844) for cataphractus.     

Is sperm FISH analysis still useful for Robertsonian translocations? Meiotic analysis for 23 patients and review of the literature

Background

Robertsonian translocations (RobT) are common structural chromosome rearrangements where carriers display a majority of chromosomally balanced spermatozoa from alternate segregation mode. According to some monotony observed in the rates of balanced segregation, is sperm FISH analysis obsolete for RobT carriers?

Methods

Retrospective cohort research study on 23 patients analyzed in our center from 2003 to 2017 and compared to the data of 187 patients in literature from 1983 to 2017.Robertsonian translocation carriers were divided in six groups according to the chromosomes involved in the translocation: 9 patients from our center and 107 from literature carrying 45,XY,der(13;14) karyotype, 3 and 35 patients respectively with 45,XY,der(14;21), 5 and 11 patients respectively with 45,XY,der(13;15), 4 and 7 patients respectively with 45,XY,der(14;15), 1 and 4 patients respectively with 45,XY,der(13;22),and 1 and 10 patients respectively with 45,XY,der(14;22).

Results

Alternate segregation mode is predominant in our group of Robertsonian translocation carriers with 73.45% ±8.05 of balanced spermatozoa (min 50.92%; max 89.99%). These results are compliant with the data from literature for all translocations types (p?>?0.05) and are consistent among the different types of Robertsonian translocations (p?>?0.05) except for der(13;15) that exhibit lower balanced spermatozoa rates (p?<?0.05 versus der(13;14), der(14;21), (13;21) and der(15;22)). Normozoospermic patients also display a significantly (p?<?0.01) higher rate of balanced sperm cells than patients with abnormal seminograms whatever the defect implied.

Conclusions

According to the discrepancies observed between der(13;15) and all the other Rob T carriers, the differences observed among patients presenting normal and abnormal sperm parameters and the input in genetical counselling, sperm FISH does not seem obsolete for these patients. Moreover, it seems important to collect more data for rare RobT.

     

Genopal?: A Novel Hollow Fibre Array for Focused Microarray Analysis

Expression profiling of target genes in patient blood is a powerful tool for RNA diagnosis. Here, we describe Genopal™, a novel platform ideal for efficient focused microarray analysis. Genopal™, which consists of gel-filled fibres, is advantageous for high-quality mass production via large-scale slicing of the Genopal™ block. We prepared two arrays, infectant and autoimmunity, that provided highly reliable data in terms of repetitive scanning of the same and/or distinct microarrays. Moreover, we demonstrated that Genopal™ had sensitivity sufficient to yield signals in short hybridization times (0.5 h). Application of the autoimmunity array to blood samples allowed us to identify an expression pattern specific to Takayasu arteritis based on the Spearman rank correlation by comparing the reference profile with those of several autoimmune diseases and healthy volunteers (HVs). The comparison of these data with those obtained by other methods revealed that they exhibited similar expression profiles of many target genes. Taken together, these data demonstrate that Genopal™ is an advantageous platform for focused microarrays with regard to its low cost, rapid results and reliable quality.     

Never too late? Consequences of late birthdate for mass and survival of bighorn lambs

In strongly seasonal environments, the timing of birth can have important fitness consequences. We investigated which factors affect parturition date and how birthdate interacts with sex, maternal characteristics and environmental variables to affect the growth and survival of bighorn sheep (Ovis canadensis) lambs in a marked population in Alberta. Over 14 years, the estimated birthdate of 216 lambs ranged from 21 May to 18 July. Parturition date was heritable and genetically correlated with maternal mass the previous fall. Weaning a lamb delayed parturition the following year by about 7 days. Birthdate did not affect summer growth rate, but late-born lambs were lighter in mid September (the approximate time of weaning) than early-born ones. Birthdate did not affect survival to weaning, but late birth decreased survival to 1 year for male lambs. Forage quality, measured by fecal crude protein, did not affect survival to 1 year. Once we accounted for lamb mass in mid September, birthdate no longer affected the probability of survival, suggesting that late birth decreased survival by shortening a lamb's growing season. Because there was no compensatory summer growth, late-born lambs were smaller than early-born ones at the onset of winter. Our data highlight the importance of birthdate on life history traits and suggest that resource scarcity had more severe consequences for juvenile males than for females.     

Is agNOR and DNA ploidy analysis useful for evaluating thyroid neoplasms?

OBJECTIVE: To correlate the subjective AgNOR counting method and DNA content with histologic diagnoses of thyroid cancer and invasion. STUDY DESIGN: Eighty-one consecutive cases of thyroid carcinoma were selected for DNA and AgNOR analysis. The diagnoses were: papillary carcinoma (n = 40), follicular carcinoma (n = 31), Hürthle cell adenocarcinoma (n = 4), and undifferentiated carcinoma (n = 6). Seven normal thyroids were used as controls. DNA quantitative measurement was performed with Vidas 2.0 software (Kontron Bildanalyse, Munich, Germany) connected to an MPM 210 photometer microscope (Carl Zeiss, Oberkochen, Germany). The DNA index was obtained using histograms. Counting the NORs was performed by subjectively counting the NORs in 200 malignant cells. RESULTS: DNA ploidy analysis showed all Hürthle cell adenocarcinomas, 21 (67%)follicular tumors, 23 (57%) papillary tumors and 4 (67%) undifferentiated carcinomas to be aneuploid. DNA analysis correlated with histologic type of the tumor (p = 0.032). There was no statistical significance to the AgNOR counting variables studied. Statistical analysis showed correlation between ploidy and histologic diagnosis, but not AgNOR counting, to have prognostic value. CONCLUSION: DNA ploidy is more useful than subjective counting of NORs as an adjunct method for thyroid lesion analysis.