Guinea pigs in hypersensitivity testing

The aim of the present paper is to mention steps of development of predictive guinea pig animal models for contact sensitization evaluation in parallel with the development of understanding the mechanism of contact sensitization. The guinea pigs methods are reviewed and the presently accepted methods (Buehler test, Maximization test) are discussed in details. Influences on the outcome of guinea pig sensitization assays are mentioned too. The predictability of the guinea pig methods is compared with predictive methods in mice, with human tests (human repeated insult patch test, HRIPT) and epidemiological data. In the last part, a testing strategy and steps for risk assessment of contact sensitizing potential is proposed.     

Characteristics of users of traditional contraceptive methods in Bangladesh

Various national surveys suggest that the % of eligible couples in Bangladesh who are using traditional methods of contraception has been growing. This article presents detailed information on knowledge and use patterns of traditional methods and compares the use patterns of traditional and modern methods of contraception. The data are derived from the 1981 Contraceptive Prevalence Survey and information collected from a nationally representative sample of ever married women aged under 50, by way of field interviews using female interviewers. Quality of data was checked at different phases of the survey. Over 96% of the women reported that they knew at least 1 traditional method of contraception. The safe period was the most well known method (36.5%); about 30% reported knowledge of abstinence and 22% knew about withdrawal. Compared with modern methods, where knowledge declined with increased age, the knowledge of traditional methods shows no systematic pattern by age. Respondents with primary and higher education have higher knowledge of traditional methods than women who have never been to school. A similar pattern exists for employment status; non-Muslim women have consistently higher levels of knowledge than Muslim women. Data on patterns of use suggest that about 36% have used at least 1 contraceptive method, 15% having used traditional methods and 20.4% modern methods. The number of women who have used traditional methods increases from ages 20 to 44 and then declines. Use of traditional methods is relatively higher by the number of living children than by the number of children ever born. A similar pattern of association between background characteristics (education, employment and religion) and contraceptive knowledge is evident regarding level of use. Husband's level of education does not show any significant relationship with the use of traditional methods. The use rate of traditional methods was more than doubled among the women owning land compared to those having no land. The total current use rate of modern methods was higher among women aged 40-44 having relatively higher numbers of living children. As with current use, a positive relationship was observed between the socioeconomic variables and ever use. In general, it is concluded that socioeconomic variables played a dominant role in the decision of couples in choosing various methods of contraception. It is suggested that traditional methods still have an important role in family planning and that this should not be disregarded.     

Analysis of continuous covariables in epidemiological studies: Dose‐response modelling and confounder adjustment

The analysis of continuous covariables with regression models commonly used in epidemiology are reviewed and compared. While some methods have been in use for decades, other more recent methods are not yet common or have not yet been formally described. It is shown that recently developed methods such as fractional polynomials and others are very useful to obtain dose‐response curves or for confounder adjustment. Different methods have their specific merits making it difficult to give general recommendations. The application of some of the methods is demonstrated with real data examples from epidemiological studies. Some suggestions for practical strategies in analysing continuous covariables are given.     

Assessment of a method for immunochemical detection of antigen on nitrocellulose membranes

Immunoblotting techniques are widely used for detection of antigen immobilized on nitrocellulose membranes. There are many immunolabeling methods and staining methods available to disclose the presence of antigen in such techniques. Five common staining methods each for alkaline phosphatase and horseradish peroxidase were examined. The staining methods with the highest sensitivity and the lowest background were selected for studies comparing five immunological labeling methods using human IgG as a model antigen. Results were evaluated on the basis of the least amount of detectable antigen and background staining. The most sensitive dot-blot method was then tested for its applicability to Western blots. For both dot-blots and Western blots, the immunoalkaline phosphatase methods are more sensitive than the corresponding immunoperoxidase methods. The use of biotinylated secondary antibodies and an avidin-enzyme conjugate is recommended. Disclosure of alkaline phosphate is best achieved with naphthol AS phosphate as substrate and fast blue BB as chromogen. Peroxidase is best stained using H2O2 and diaminobenzidine (DAB). Potential endogenous enzyme activities are demonstrable by blotting methods but can be inhibited by including levamisole in the disclosure reaction medium for calf intestinal alkaline phosphatase indicators, or by incubation of blots with sodium azide and hydrogen peroxide before immunolabeling when using horseradish peroxidase indicators.     

Propensity score methods for time-dependent cluster confounding

In observational studies, subjects are often nested within clusters. In medical studies, patients are often treated by doctors and therefore patients are regarded as nested or clustered within doctors. A concern that arises with clustered data is that cluster-level characteristics (e.g., characteristics of the doctor) are associated with both treatment selection and patient outcomes, resulting in cluster-level confounding. Measuring and modeling cluster attributes can be difficult and statistical methods exist to control for all unmeasured cluster characteristics. An assumption of these methods however is that characteristics of the cluster and the effects of those characteristics on the outcome (as well as probability of treatment assignment when using covariate balancing methods) are constant over time. In this paper, we consider methods that relax this assumption and allow for estimation of treatment effects in the presence of unmeasured time-dependent cluster confounding. The methods are based on matching with the propensity score and incorporate unmeasured time-specific cluster effects by performing matching within clusters or using fixed- or random-cluster effects in the propensity score model. The methods are illustrated using data to compare the effectiveness of two total hip devices with respect to survival of the device and a simulation study is performed that compares the proposed methods. One method that was found to perform well is matching within surgeon clusters partitioned by time. Considerations in implementing the proposed methods are discussed.     

Dynamic metabolomic data analysis: a tutorial review

In metabolomics, time-resolved, dynamic or temporal data is more and more collected. The number of methods to analyze such data, however, is very limited and in most cases the dynamic nature of the data is not even taken into account. This paper reviews current methods in use for analyzing dynamic metabolomic data. Moreover, some methods from other fields of science that may be of use to analyze such dynamic metabolomics data are described in some detail. The methods are put in a general framework after providing a formal definition on what constitutes a ‘dynamic’ method. Some of the methods are illustrated with real-life metabolomics examples.     

A comparative study of machine-learning methods to predict the effects of single nucleotide polymorphisms on protein function

MOTIVATION: The large volume of single nucleotide polymorphism data now available motivates the development of methods for distinguishing neutral changes from those which have real biological effects. Here, two different machine-learning methods, decision trees and support vector machines (SVMs), are applied for the first time to this problem. In common with most other methods, only non-synonymous changes in protein coding regions of the genome are considered. RESULTS: In detailed cross-validation analysis, both learning methods are shown to compete well with existing methods, and to out-perform them in some key tests. SVMs show better generalization performance, but decision trees have the advantage of generating interpretable rules with robust estimates of prediction confidence. It is shown that the inclusion of protein structure information produces more accurate methods, in agreement with other recent studies, and the effect of using predicted rather than actual structure is evaluated. AVAILABILITY: Software is available on request from the authors.     

Coding polymorphism for phylogeny reconstruction

The methodology of coding polymorphic taxa has received limited attention to date. A search of the taxonomic literature revealed seven types of coding methods. Apart from ignoring polymorphic characters (sometimes called the fixed-only method), two main categories can be distinguished: methods that identify the start of a new character state with the origin of an evolutionary novelty, and methods that identify the new state with the fixation of a novelty. The methods of the first category introduce soft reversals, yielding signals that support cladograms incompatible with true phylogenies. We conclude that coding the plesiomorphy is the method to be preferred, unless the ancestral state is unknown, in which case coding as ambiguous is recommended. This holds for coding polymorphism in species as well as in supraspecific taxa. In this light we remark on methods proposed by previous authors.     

Identification and quantification of polyphenol phytoestrogens in foods and human biological fluids

We review the methods used to measure phytoestrogens (genistein, daidzein, lignans and their derivatives) in foods and biological fluids, and discuss advantages and disadvantages of each. The range of detection limits reported varies widely between individual laboratories, but generally the best reported sensitivity is as follows: immunoassay>HPLC-mass spectrometry=HPLC-multichannel electrochemical detection (coularray)>GC-single ion monitoring-mass spectrometry>HPLC-UV diode array>HPLC-single channel electrochemical detection. The best sensitivity reported so far is 0.002 pmol per assay for daidzein by radioimmunoassay. HPLC with UV diode array detection is the most commonly employed, but is the least sensitive and specific. GC and HPLC coupled with mass spectrometry or electrochemical detection are the most accurate and reproducible methods for a wide variety of analytes. Generally most methods, with the exception of immunoassay, have not been correlated with other methods. Recoveries from extraction methods, limits of detection, nature of compounds analysed and the internal standards used are summarised for more than 90 reports in the literature. From this data, it is clear that an inter-laboratory validation and correlation between a wide range of methods for phytoestrogen analysis is required. One underdeveloped area that requires particular attention is the analysis of plant lignans.     

Measuring the efficiency of sound production

Sound production efficiency is a complex phenotypic trait that incorporates biochemical and mechanical events beginning with substrate oxidation and ending with the radiation of sound. Its accurate measurement is significant in understanding the mechanisms and energetics underlying acoustic signaling and sexual selection. I show that in the short-tailed cricket Anurogryllus arboreus Walker, acoustic performance is apparently the same in acoustic free fields and in the reverberant conditions of a respirometry chamber. I present three methods for simultaneous and nearly simultaneous determination of calling metabolic rate and acoustic power output. The new methods yielded metabolic rates 3%-6% lower than matched controls using traditional flow-through respirometry (mean=8.1 mW); however, none of theses differences were statistically significant. I also evaluate four methods for determining the efficiency of sound production. The means of an individual's efficiencies calculated using these methods vary between 0.50% and 0.60%, with no statistically significant differences between the methods. I conclude with a critical evaluation of these techniques.     

Methods of weighted averaging of ECG signals using Bayesian inference and criterion function minimization

Averaging signals in time domain is one of the main methods of noise attenuation in biomedical signal processing in case of systems producing repetitive patterns such as electrocardiographic (ECG) acquisition systems. This paper presents a comprehensive study of weighted averaging of ECG signal. Presented methods use criterion function minimization, partitioning of input set of data in the time domain as well as Bayesian and empirical Bayesian framework. The existing methods are described together with their extensions. Performance of all presented methods is experimentally evaluated and compared with the traditional averaging by using arithmetic mean and well-known weighted averaging methods based on criterion function minimization (WACFM).     

Assessing the correlation of microscopy‐based and volumetry‐based measurements for resin swelling in a range of potential greener solvents for SPPS

The degree of resin swelling in a particular solvent system is one of the critical parameters for solid‐phase peptide synthesis (SPPS) and for solid‐phase synthesis in general. Methods used for measuring the degree of resin swelling include microscopy‐based and volumetry‐based methods. This study describes and compares the use of both methods for a number of commercially available resins commonly used in SPPS, with a range of solvents, which have been identified in the literature as ‘greener’ than DCM, DMF and NMP. The results were analysed by statistical methods, and a significant correlation between the two distinct methods has been demonstrated for the first time. The results will likely be used, in conjunction with other literature methods, to help in choosing both the resin and solvent system for greener SPPS, as well as for continuous flow SPPS, which is of growing importance.     

The use of laser-nephelometry in evaluating fibrinogenaemia in patients with hepatocarcinoma and cirrhosis

In the present study fibrinogen was assayed by the immunonephelometric method in 19 patients afflicted with hepatocarcinoma and 24 patients afflicted with cirrhosis. The two groups were similar in age, sex and presence of HbsAg. The incidence of values above the norm was significantly greater in patients with hepatocarcinoma (p less than 0.05). Then, the concentration of fibrinogen was measured in all using two other immunological methods (Laurell and Mancini) and two coagulative methods (Clauss and Ratnoff). A dysfibrinogenemia (an excess of fibrinogen assayed by immunological methods to be greater than 100 mg/dl with respect to biological methods). is more frequent using the Nephelometer-Clauss (p less than 0.01) and Mancini-Clauss (p less than 0.01) methods in patients with hepatocarcinoma with respect to those with cirrhosis. The study of the kinetics of antifibrinogen antigen-antibody reaction failed to show differences between patients with hepatocarcinoma or cirrhosis and normal subjects.     

Separation methods that are capable of revealing blood-brain barrier permeability

The objective of this review is to emphasize the application of separation science in evaluating the blood-brain barrier (BBB) permeability to drugs and bioactive agents. Several techniques have been utilized to quantitate the BBB permeability. These methods can be classified into two major categories: in vitro or in vivo. The in vivo methods used include brain homogenization, cerebrospinal fluid (CSF) sampling, voltametry, autoradiography, nuclear magnetic resonance (NMR) spectroscopy, positron emission tomography (PET), intracerebral microdialysis, and brain uptake index (BUI) determination. The in vitro methods include tissue culture and immobilized artificial membrane (IAM) technology. Separation methods have always played an important role as adjunct methods to the methods outlined above for the quantitation of BBB permeability and have been utilized the most with brain homogenization, in situ brain perfusion, CSF sampling, intracerebral microdialysis, in vitro tissue culture and IAM chromatography. However, the literature published to date indicates that the separation method has been used the most in conjunction with intracerebral microdialysis and CSF sampling methods. The major advantages of microdialysis sampling in BBB permeability studies is the possibility of online separation and quantitation as well as the need for only a small sample volume for such an analysis. Separation methods are preferred over non-separation methods in BBB permeability evaluation for two main reasons. First, when the selectivity of a determination method is insufficient, interfering substances must be separated from the analyte of interest prior to determination. Secondly, when large number of analytes is to be detected and quantitated by a single analytical procedure, the mixture must be separated to each individual component prior to determination. Chiral separation in particular can be essential to evaluate the stereo-selective permeation and distribution of agents into the brain. In conclusion, the usefulness of separation methods during BBB permeability evaluation is immense and more application of these methods is foreseen in the future.     

Faithful consensus methods for n-trees

A class of new consensus methods for n-trees (hierarchical clusterings) is proposed. These methods apply systematically to an arbitrary collection of given classifications of a fixed set of taxa, and produce a single consensus classification. They are motivated by the desire that the consensus classification retain as much information as possible from the given classifications, even in the case of only approximate agreement among them. A focus of the paper is the concept of faithfulness of consensus methods; this concept explicates the informal notion of adequate retention of information referred to above, and is proposed as a desirable requirement for consensus methods in general. The new methods are all faithful; they have the additional property that they take hierarchical level into account. Other general properties of consensus methods are investigated, especially with reference to their relation with faithfulness. The most important of these properties is neutrality; loosely speaking a consensus method is neutral if all nontrivial clusters are treated equally in the conditions on the given classifications required to guarantee the appearance of a cluster in the consensus. A central result of the paper is an analogue of the classical impossibility theorem of K. Arrow: with trivial exceptions it is impossible to have a consensus method that is simultaneously faithful and neutral. Thus two intuitively very appealing general properties of consensus methods are seen to be incompatible.     

Fine-scale mapping in case-control samples using locus scoring and haplotype-sharing methods

Both haplotype-based and locus-based methods have been proposed as the most powerful methods to employ when fine mapping by association. Although haplotype-based methods utilize more information, they may lose power as a result of overparameterization, given the large number of haplotypes possible over even a few loci. Recently methods have been developed that cluster haplotypes with similar structure in the hope that this reflects shared genealogical ancestry. The aim is to reduce the number of parameters while retaining the genotype information relating to disease susceptibility. We have compared several haplotype-based methods with locus-based methods. We utilized 2 regions (D2 and D4) simulated to be in linkage disequilibrium and to be associated with disease susceptibility, combining 5 replicates at a time to produce 4 datasets that were analyzed. We found little difference in the performance of the haplotype-based methods and the locus-based methods in this dataset.     

转基因食品DNA提取研究进展

为了满足消费者对转基因食品的知情权,建立准确、快速、高效的转基因成分检测技术至关重要,而高质量DNA模板的获取,是转基因食品进行基因检测的前提.对近几年来国内外转基因食品DNA提取方法:十六烷基三甲基溴化铵(hexadecyl trimethyl ammonium bromide,CTAB)法、十二烷基硫酸钠(dode...     

Evaluation of residue-residue contact prediction methods: From retrospective to prospective

Sequence-based residue contact prediction plays a crucial role in protein structure reconstruction. In recent years, the combination of evolutionary coupling analysis (ECA) and deep learning (DL) techniques has made tremendous progress for residue contact prediction, thus a comprehensive assessment of current methods based on a large-scale benchmark data set is very needed. In this study, we evaluate 18 contact predictors on 610 non-redundant proteins and 32 CASP13 targets according to a wide range of perspectives. The results show that different methods have different application scenarios: (1) DL methods based on multi-categories of inputs and large training sets are the best choices for low-contact-density proteins such as the intrinsically disordered ones and proteins with shallow multi-sequence alignments (MSAs). (2) With at least 5L (L is sequence length) effective sequences in the MSA, all the methods show the best performance, and methods that rely only on MSA as input can reach comparable achievements as methods that adopt multi-source inputs. (3) For top L/5 and L/2 predictions, DL methods can predict more hydrophobic interactions while ECA methods predict more salt bridges and disulfide bonds. (4) ECA methods can detect more secondary structure interactions, while DL methods can accurately excavate more contact patterns and prune isolated false positives. In general, multi-input DL methods with large training sets dominate current approaches with the best overall performance. Despite the great success of current DL methods must be stated the fact that there is still much room left for further improvement: (1) With shallow MSAs, the performance will be greatly affected. (2) Current methods show lower precisions for inter-domain compared with intra-domain contact predictions, as well as very high imbalances in precisions between intra-domains. (3) Strong prediction similarities between DL methods indicating more feature types and diversified models need to be developed. (4) The runtime of most methods can be further optimized.     

Methods for the euthanasia of experimental animals--the ethics, esthetics and personnel safety

In this paper there are shown chemical and physical methods of euthanasia of vertebrate animals. All methods are divided into three categories: A) Acceptable methods of euthanasia, B) methods acceptable only for unconscious animals, C) methods that are not acceptable for euthanasia. The acceptability or non-acceptability of the method is determined by ethic or aesthetic conceptions and also by conceptions of the personnel safety and the environment. There is provided a table of acceptable methods of euthanasia. Recommendations of working group of the Federation of Laboratory Animal Science Association (FELASA) were taken into consideration in this paper. The survey can be useful for the experimenters and personnel concerned with laboratory animals.