一种适用于短肽制备抗体的亲和纯化方法

在免疫组织化学检测过程中，抗体的纯度对于减少检测背景和假阳性起着关键作用。为了获得高纯度的抗体，亲和纯化的方法被广泛应用。为了研究某种特定基因编码产物的时空表达模式，一叮将基因的序列克降到原核表达载体上，获得目的基因的原核表达蛋白，用于制备抗体进行免疫组化研究。但是，如果研究对象是同源忡较高的基因家族某一个基因时，为了避免交叉反应，提高免疫组化的准确性。     

Relative entropy as a measure of diagnostic information.

Relative entropy is a concept within information theory that provides a measure of the distance between two probability distributions. The author proposes that the amount of information gained by performing a diagnostic test can be quantified by calculating the relative entropy between the posttest and pretest probability distributions. This statistic, in essence, quantifies the degree to which the results of a diagnostic test are likely to reduce our surprise upon ultimately learning a patient's diagnosis. A previously proposed measure of diagnostic information that is also based on information theory (pretest entropy minus posttest entropy) has been criticized as failing, in some cases, to agree with our intuitive concept of diagnostic information. The proposed formula passes the tests used to challenge this previous measure.     

Assessment of a short scale to measure social support

A wide variety of measures have been used to assess the effects of social support on both physical and psychological status. Information on the reliability and validity of many of these instruments is unavailable; other instruments appear to be reasonably valid but involve large numbers of questions and require considerable time for completion. This study examines the properties of a short, self-administered social support scale (SSS). Data are available from 3 samples: HMO clients in a weight loss program (N = 268); chronic facial pain patients (N = 92); and colorectal cancer patients (N = 318). Three scoring strategies measuring two dimensions (structural and perceptual) of social support are compared with respect to internal consistency and criterion and construct validity. One of these strategies results in a measure that behaves in a way consistent with other, longer instruments and appears to possess acceptable reliability and validity. Scores can be broken down by source (e.g. spouse, friends), and wording can be modified to measure either general support or support for a specific situation.     

Development of a short form of the Workstyle measure

BACKGROUND: 'Workstyle', or how a worker behaviourally, cognitively and physiologically responds to increased or stressful work demands, has been proposed to help explain the link between ergonomic and psychosocial factors in work-related upper limb disorder symptoms and disorders (WRULD). AIM: To describe the psychometric properties of a shortened version of the original Workstyle measure. METHODS: Factor analyses of the Workstyle measure items were conducted to reduce the number of total items. Each of the subscales was then further reduced by randomly selecting half of the items within each subscale. Additionally, two subscales from the original survey (Pain/Tension and Numbness/Tingling) were eliminated because they were not used to calculate the original workstyle total score in order to reduce the influence of current symptoms on an individual's total score. RESULTS: The Workstyle Short Form was reduced to 32 items. Cronbach's alpha was 0.89 and the test-retest reliability was r = 0.88, P < 0.01, for the total score. The short form score was significantly correlated with the full workstyle total score, r = 0.98, P < 0.01. Higher total workstyle scores were significantly associated with pain, functional limitations and adverse mental and physical health. CONCLUSION: The Workstyle Short Form demonstrated acceptable psychometric properties. These findings indicate its potential utility in research on WRULD.     

Choice of effect measure for epidemiological data

The debate concerning the choice of effect measure for epidemiologic data has been renewed in the literature, and it suggests some continuing disagreement between the pertinent clinical and statistical criteria. In this article, some defining characteristics of the main choices of effect measure [risk difference (RD), relative risk (RR), and odds ratio (OR)] for binary data are presented and compared, with consideration of both the clinical and statistical perspectives. Relationships of these measures to the relative risk reduction (RRR) and number needed to treat (NNT) are also discussed. A numerical comparison of models of constant RD, RR, and OR is made to assess when and by how much they might differ in practice. Typically the models show only small numerical differences, unless extreme extrapolation is involved. The RD and RR models can predict impossible event rates, either less than zero or greater than 100%. Each measure has potential theoretical justification. RD and RR may enjoy some advantages for communication of risk, but OR may be preferred for data analysis. A clear distinction should be maintained between the objectives of data analysis and subsequent risk communication, and different effect measures may be needed for each.     

The EUROSTROKE cohorts: a short description and data analytical approach

This paper describes the design and methodology of the participating cohorts in the EUROSTROKE project. Information is given about the cohort sampling, its size, the follow up procedures and event classification. Information is also given about the measurement of the cardiovascular and cerebrovascular risk factors in each of the cohorts separately. The cohorts described are the Caerphilly study in Cardiff, United Kingdom; the Kuopio Ischaemic Heart disease study in Kuopio, Finland; the Portugal study in Coimbra, Portugal; the EPIC cohort in Athens, Greece; the Ilsa study from Firenze, Italy; the Rotterdam Study in Rotterdam, the Netherlands, and the Novosibirsk cohort in Novosibirsk, Russia.