Testing separate families of segregation hypotheses: bootstrap methods.

Aspects of the statistical modeling and assessment of hypotheses concerning quantitative traits in genetics research are discussed. It is suggested that a traditional approach to such modeling and hypothesis testing, whereby competing models are "nested" in an effort to simplify their probabilistic assessment, can be complimented by an alternative statistical paradigm - the separate-families-of-hypotheses approach to segregation analysis. Two bootstrap-based methods are described that allow testing of any two, possibly non-nested, parametric genetic hypotheses. These procedures utilize a strategy in which the unknown distribution of a likelihood ratio-based test statistic is simulated, thereby allowing the estimation of critical values for the test statistic. Though the focus of this paper concerns quantitative traits, the strategies described can be applied to qualitative traits as well. The conceptual advantages and computational ease of these strategies are discussed, and their significance levels and power are examined through Monte Carlo experimentation. It is concluded that the separate-families-of-hypotheses approach, when carried out with the methods described in this paper, not only possesses some favorable statistical properties but also is well suited for genetic segregation analysis.     

Why is indigo blue?

Although the color of indigo is strongly dependent on its environment, it is blue in most commonly encountered situations. Indigo's absorption at such long wavelengths for such a small molecule is unique, and I provide here an overview of the concepts advanced to account for this feature. A traditional valence-bond approach may be used to provide a reasonable qualitative explanation. A more rigorous, quantitative explanation is provided by molecular orbital methods of varying degrees of sophistication and several explanations have been proposed based on these models. Commonly, it is suggested that the important structural unit in determining color is based on the cross-conjugated “H-chromophore” concept. A second closely related explanation describes it as two symmetrically coupled merocyanine chains. Another proposal suggests that the basic chromophore may be interpreted as the aza analogue of two coupled anti aromatic-cyclopentadienyl ions. PiSYSTEM, a commercially available quantum mechanics program, has been used to provide a successful quantitative account of the colors of indigo and indirubin, a red isomer.     

Quality-by-Design II: Application of Quantitative Risk Analysis to the Formulation of Ciprofloxacin Tablets

Qualitative risk assessment methods are often used as the first step to determining design space boundaries; however, quantitative assessments of risk with respect to the design space, i.e., calculating the probability of failure for a given severity, are needed to fully characterize design space boundaries. Quantitative risk assessment methods in design and operational spaces are a significant aid to evaluating proposed design space boundaries. The goal of this paper is to demonstrate a relatively simple strategy for design space definition using a simplified Bayesian Monte Carlo simulation. This paper builds on a previous paper that used failure mode and effects analysis (FMEA) qualitative risk assessment and Plackett-Burman design of experiments to identity the critical quality attributes. The results show that the sequential use of qualitative and quantitative risk assessments can focus the design of experiments on a reduced set of critical material and process parameters that determine a robust design space under conditions of limited laboratory experimentation. This approach provides a strategy by which the degree of risk associated with each known parameter can be calculated and allocates resources in a manner that manages risk to an acceptable level.     

Use of an immediate, qualitative progesterone assay for determination of day of ovulation in an equine embryo transfer program

An immediate, qualitative enzyme-linked immunosorbent assay (ELISA) for progesterone was evaluated for use in determining the day of ovulation in an equine embryo transfer program. Plasma samples were collected from 27 mares from the third day of estrus to the second day of diestrus for 50 cycles. Ovulation was detected by ultrasound examination per rectum. Plasma progesterone concentrations were estimated using the qualitative assay to detect the time of the rise in progesterone after ovulation. Qualitative scores were compared to progesterone concentrations for the same samples as measured by a quantitative ELISA; the correlation between the two methods, expressed as a contingency coefficient, was 0.56. The accuracy of determining day of ovulation using qualitative progesterone results was compared to that achieved using the quantitative assay or detection of the first day of diestrus by teasing. Accuracy in determining day of ovulation +/- 1 d using the three methods was qualitative, 36/50 (72%); quantitative, 44/50 (88%); and teasing, 43/50 (86%). There was a significant difference in accuracy between the qualitative and quantitative progesterone assays (P<0.05).     

The Fluorane Derivatives: Methods for the Standardization of Biological Stains: Part II

In this paper the methods are given which are used in determining whether to approve the sale of certain dyes of the fluorane group as certified biological stains. The methods have been worked out by the Commission on Standardization of Biological Stains in cooperation with the Color and Farm Waste Division, Bureau of Chemistry and Soils, U. S. Dept. of Agriculture. The dyes for which the methods are given in the present paper are: Fluorescein, eosin yellowish, ethyl eosin, eosin bluish, erythrosin, phloxine B, and rose bengal. For each of these dyes methods are given under the following headings: (1) identification or qualitative examination; (2) quantitative analysis; and (3) biological tests.     

Modularization of biochemical networks based on classification of Petri net t-invariants

Background  

Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior.     

Methods for the Standardization of Biological Stains: Part IV

In this paper are given methods for determining the suitability of certain dyes of the triphenylmethane group for certification by the Commission on Standardization of Biological Stains. These methods have been developed by the Commission, in cooperation with the Color and Farm Waste Division, Bureau of Chemistry and Soils, U. S. Department of Agriculture. The dyes for which the methods are given in the present paper are: Malachite green, brilliant green, light green SF yellowish, fast green FCF, basic fuchsin (rosanilin and pararosanilin), acid fuchsia, methyl violet, crystal violet, gentian violet, methyl green and anilin blue. For each of these dyes, methods are discussed under the following headings: (1) identification or qualitative examination; (2) quantitative analysis; and (3) biological tests.     

Experimental and computational approaches to quantitative proteomics: status quo and outlook

Proteomics has come a long way from the initial qualitative analysis of proteins present in a given sample at a given time (“cataloguing”) to large-scale characterization of proteomes, their interactions and dynamic behavior. Originally enabled by breakthroughs in protein separation and visualization (by two-dimensional gels) and protein identification (by mass spectrometry), the discipline now encompasses a large body of protein and peptide separation, labeling, detection and sequencing tools supported by computational data processing. The decisive mass spectrometric developments and most recent instrumentation news are briefly mentioned accompanied by a short review of gel and chromatographic techniques for protein/peptide separation, depletion and enrichment. Special emphasis is placed on quantification techniques: gel-based, and label-free techniques are briefly discussed whereas stable-isotope coding and internal peptide standards are extensively reviewed. Another special chapter is dedicated to software and computing tools for proteomic data processing and validation. A short assessment of the status quo and recommendations for future developments round up this journey through quantitative proteomics.     

Application of Petri net based analysis techniques to signal transduction pathways

Background  

Signal transduction pathways are usually modelled using classical quantitative methods, which are based on ordinary differential equations (ODEs). However, some difficulties are inherent in this approach. On the one hand, the kinetic parameters involved are often unknown and have to be estimated. With increasing size and complexity of signal transduction pathways, the estimation of missing kinetic data is not possible. On the other hand, ODEs based models do not support any explicit insights into possible (signal-) flows within the network. Moreover, a huge amount of qualitative data is available due to high-throughput techniques. In order to get information on the systems behaviour, qualitative analysis techniques have been developed. Applications of the known qualitative analysis methods concern mainly metabolic networks. Petri net theory provides a variety of established analysis techniques, which are also applicable to signal transduction models. In this context special properties have to be considered and new dedicated techniques have to be designed.     

Advances of infrared spectroscopy in natural product research

Natural product's properties are related to certain classes of compounds such as alkaloids, flavonoids, essential oils and others. Traditionally, separation techniques including thin layer chromatography (TLC), liquid chromatography (LC), gas chromatography (GC) and capillary electrophoresis (CE) even hyphenated to mass spectrometry (MS) were used for the elucidation, qualitative and quantitative analysis of individual compounds.In food industry, spectroscopic investigations using infrared radiation have been used to monitor and evaluate the composition and quality already since the early sixties. During the last four decades near-infrared spectroscopy (NIR; 800–2500 nm; 12,500–4000 cm⁻¹) has become one of the most attractive and used methods for analysis for the following reasons: it represents a non-invasive analytical tool allowing a fast and simultaneous qualitative and quantitative characterization of natural products and their constituents. Additionally, the development of custom-made hand-held instruments enables in-field measurement for determining the optimum harvest time.Attenuated total reflection (ATR) and Fourier transform infrared (FTIR) spectroscopic imaging are suitable not only for the differentiation of different plant species, but also to distinct various ingredients within a plant. FTIR spectroscopic microscopy enables molecular imaging of complex botanical samples and therefore the detection and characterization of the molecular components of biological tissue.In the present contribution, the principle, technique and methodology of the different infrared spectroscopic methods are described followed by a discussion of quantitative and qualitative application possibilities in the field of natural product analysis.     

Quantitative metabolomics based on gas chromatography mass spectrometry: status and perspectives

Metabolomics involves the unbiased quantitative and qualitative analysis of the complete set of metabolites present in cells, body fluids and tissues (the metabolome). By analyzing differences between metabolomes using biostatistics (multivariate data analysis; pattern recognition), metabolites relevant to a specific phenotypic characteristic can be identified. However, the reliability of the analytical data is a prerequisite for correct biological interpretation in metabolomics analysis. In this review the challenges in quantitative metabolomics analysis with regards to analytical as well as data preprocessing steps are discussed. Recommendations are given on how to optimize and validate comprehensive silylation-based methods from sample extraction and derivatization up to data preprocessing and how to perform quality control during metabolomics studies. The current state of method validation and data preprocessing methods used in published literature are discussed and a perspective on the future research necessary to obtain accurate quantitative data from comprehensive GC-MS data is provided.     

Decision analysis of prenatal testing for chromosomal disorders: what do the preferences of pregnant women tell us?

Current guidelines recommend offering invasive testing for chromosomal disorders only to women who are aged 35 or older, or who are at similarly elevated risk (as determined by maternal serum and/or ultrasonographic screening). We conducted a decision analysis, using preference scores obtained from pregnant women, to determine whether current guidelines maximize the health-related quality of life of these women. If only miscarriage and chromosomal abnormalities are considered, the expected value of testing exceeds that of not testing for women 30 years of age or older. However, if a comprehensive range of relevant testing outcomes is considered, testing offers a higher expected value than not testing, regardless of age. Furthermore, patient preferences for specific testing outcomes play a much more substantial role in determining the course of action with the highest expected value than does the probability of any of the possible testing outcomes. The current age- and risk-based guideline for prenatal diagnosis does not maximize expected value and fails to appropriately consider individual patient preferences. For counseling purposes, how an individual values the presence and timing of fetal chromosomal information should be carefully understood.     

Collection of pedigree data for genetic analysis in isolate populations

Pedigree data are useful for a wealth of research purposes in human population biology and genetics. The collection of extended pedigrees represents the most powerful sampling design for quantitative genetic and linkage studies of both normal and disease-related quantitative traits. In this paper we outline an approach for collecting pedigree data in stable isolate populations. As an example, the pedigree for the Jirel population, which was obtained using the methods presented, is described. The Jirel pedigree contains 2,000 study participants and more than 62,000 pairwise relationships that are informative for genetic analysis. Once such pedigrees are genetically characterized by a genome scan for a given trait, they become an invaluable resource for future genetic studies of any quantitative trait.     

Statistical issues with microarrays: processing and analysis

The study of gene expression with printed arrays and prefabricated chips is evolving from a qualitative to a quantitative science. Statistical procedures for determining quality control, differential expression, and reproducibility of findings are a natural consequence of this evolution. However, problems inherent to the technologies have raised important issues of how to apply adequate statistical tests. As a consequence, statistical approaches to microarray research are not yet as routine as they are in other sciences. Statistical methods, tailored to microarrays, continue to be adapted and developed. We present an overview of these methods and of outstanding issues in their use and validation.     

The emerging role of ICP-MS in proteomic analysis

Quantitative proteomics and absolute determination of proteins are topics of fast growing interest, since only the quantity of proteins or changes in their abundance reflect the status and extent of changes of a given biological system. Quantification of the desired proteins has been carried out by molecule specific MS techniques, but relative quantifications are commonplace so far even resorting to stable isotope labelling techniques such as ICAT and SILAC. In the last decade the idea of using element-selective mass spectrometric detection (e.g. ICP-MS instruments) to achieve absolute quantification has been realised and ICP-MS stands now as a new tool in the field of quantitative proteomics.In this review the emerging role of ICP-MS in protein and proteomic analysis is highlighted. The potential of ICP-MS methods and strategies for screening multiple heteroatoms (e.g. S, P, Se, metals) in proteins and their mixtures and extraordinary capabilities to tackle the problem of absolute protein quantifications, via heteroatom determinations, are discussed and illustrated. New avenues are also open derived from the use of ICP-MS for precise isotope abundance measurements in polyisotopic heteroatoms. The “heteroatom (isotope)-tagged proteomics” concept is focused on the use of naturally present element tags and also extended to any protein by resorting to bioconjugation reactions (i.e. labelling sought proteins and peptides with ICP-MS detectable heteroatoms). A major point of this review is displaying the possibilities of using a “hard” ion source, the ICP, to complement well-established “soft” ion sources for mass spectrometry to tackle present proteomic analysis.     

A Modification of the Technic of Handling Chick Embryos

In this paper are given methods for determining the suitability of certain dyes of the triphenylmethane group for certification by the Commission on Standardization of Biological Stains. These methods have been developed by the Commission, in cooperation with the Color and Farm Waste Division, Bureau of Chemistry and Soils, U. S. Department of Agriculture. The dyes for which the methods are given in the present paper are: Malachite green, brilliant green, light green SF yellowish, fast green FCF, basic fuchsin (rosanilin and pararosanilin), acid fuchsia, methyl violet, crystal violet, gentian violet, methyl green and anilin blue. For each of these dyes, methods are discussed under the following headings: (1) identification or qualitative examination; (2) quantitative analysis; and (3) biological tests.     

乙型肝炎病毒e抗原定量检测的性能验证和临床应用探索

乙型肝炎病毒e抗原(hepatitis B e antigen, HBeAg)的定量检测对乙型肝炎临床诊疗具有一定的重要性,但其定量检测还未成为常规检验项目。本研究对HBeAg定量检测系统进行性能验证,比较HBeAg定量和定性检测的相关性和一致性,分析HBeAg定量结果和乙型肝炎病毒DNA(hepatitis B virus DNA, HBV DNA)的关系,为HBeAg定量检测在临床诊疗的应用提供依据。通过收集710例2019年3月至5月于复旦大学附属华山医院就诊的慢性乙型肝炎患者血清样本,参照美国临床实验室标准化协会(The Clinical & Laboratory Standards Institute, CLSI)相关文件的要求,对雅培ARCHITECTi4000SR全自动免疫分析仪检测的HBeAg定量试剂的精密度、分析灵敏度、线性范围/可报告范围、携带污染率进行验证和评价;采用化学发光微粒子免疫检测技术(chemiluminescence microparticle immuno assay, CMIA)对618例患者进行HBeAg定性和定量检测;采用荧光定量PCR对慢性乙型肝炎患者进行HBV DNA检测,比较HBV DNA和HBeAg定量结果的相关性。本研究证实HBeAg定量试剂检测性能验证结果良好;HBeAg定量和定性检测相关性良好;126例同时有HBeAg定量检测和HBV DNA定量检测的结果显示,两种方法呈正相关且一致性良好。HBeAg定量检测可用于常规实验室检测来辅助HBV感染的临床诊疗。     

Doing Philosophy Effectively: Student Learning in Classroom Teaching

An important aim of teaching philosophy in Dutch secondary schools is to learn about philosophy (i.e., the great philosophers) by doing philosophy. We examined doing philosophy and focused specifically on the relationship between student learning activities and teacher behavior; in doing so, a qualitative cross-case analysis of eight philosophy lessons was performed. The effectiveness of doing philosophy was operationalized into five learning activities comprising rationalizing, analyzing, testing, producing criticism, and reflecting, and scored by means of qualitative graphical time registration. Using CA we find a quantitative one-dimensional scale for the lessons that contrasts lessons that are more and less effective in terms of learning and teaching. A relationship was found between teaching by teachers and doing philosophy by students. In particular we found students to produce a higher level of doing philosophy with teachers who chose to organize a philosophical discussion with shared guidance by the teacher together with the students.