The Birth and Evolution of a Discipline Devoted to Information in Biomedicine and Health Care

Background: The journal Methods of Information in Medicine, founded in 1962, has now completed its 50th volume. Its publications during the last five decades reflect the formation of a discipline that deals with information in biomedicine and health care. Objectives: To report about 1) the journal‘s origin, 2) the individuals who have significantly contributed to it, 3) trends in the journal’s aims and scope, 4) influential papers and 5) major topics published in Methods over the years.

Methods: Methods included analysing the correspondence and journal issues in the archives of the editorial office and of the publisher, citation analysis using the ISI and Scopus databases, and analysing the articles’ Medical Subject Headings (MeSH) in MEDLINE.

Results: In the journal’s first 50 years 208 editorial board members and/or editors contributed to the journal’s development, with most individuals coming from Europe and North America. The median time of service was 11 years. At the time of analysis 2,456 articles had been indexed with Me SH. Topics included computerized systems of various types, informatics methodologies, and topics related to a specific medical domain. Some MeSH topic entries were heavily and regularly represented in each of the journal‘s five decades (e.g. information systems and medical records), while others were important in a particular decade, but not in other decades (e.g. punched-card systems and systems integration). Seven papers were cited more than 100 times and these also covered a broad range of themes such as knowledge representation, analysis of biomedical data and knowledge, clinical decision support and electronic patient records. Conclusions: Methods of Information in Medicine is the oldest international journal in biomedical informatics. The journal’s development over the last 50 years correlates with the formation of this new discipline. It has and continues to stress the basic methodology and scientific fundamentals of organizing, representing and analysing data, information and knowledge in biomedicine and health care. It has and continues to stimulate multi-disciplinary communication on research that is devoted to high-quality, efficient health care, to quality of life and to the progress of biomedicine and the health sciences.

The Student Editorial Board of Methods of Information in Medicine

Objective : Peer review is a critical process in the publication of scientific findings; trainees and young investigators, however, have few opportunities to learn systematically how to review manuscripts. Journal editors have an opportunity to engage trainees and young investigators in the peer review process early during their career.

Methods : Methods of Information in Medicine, an official journal of the International Medical Informatics Association, is initiating a Student Editorial Board. The journal invites applications from international graduate and post-doctoral training programs that have a focus on health informatics, biomedical informatics, or a related field.

Results : Each year up to six trainees will be invited to join the Student Editorial Board. The trainees will go through a mentored training experience that includes an active involvement in the various aspects of peer review during their one to two-year term of appointment.

Conclusions : The journal expects that the Student Editorial Board will benefit trainees and young investigators in becoming skilled reviewers and engaged peers who can offer professional, constructive, and informative feedback and enhance the process of scientific communication.

Methods in year 50: preserving the past and preparing for the future

BACKGROUND

Founded in 1962 and, therefore, the oldest international journal in medical informatics, Methods of Information in Medicine will publish its 50th volume in 2011. At the start of the journal's sixth decade, a discussion on the journal's profile seems appropriate.

OBJECTIVES

To report on the new opportunities for online access to Methods publications as well as on the recent strategic decisions regarding the journal's aims and editorial policies.

METHODS

Describing and analyzing the journal's aims and scope. Reflecting on recent publications and on the journal's development during the last decade.

RESULTS

From 2011 forward all articles of Methods from 1962 until the present can be accessed online. Methods of Information in Medicine stresses the basic methodology and scientific fundamentals of processing data, information and knowledge in medicine and health care. Although the journal's major focus is on publications in medical informatics, it has never been restricted to publications only in this discipline. For example, articles in medical biometry, in or close to biomedical engineering, and, later, articles in bioinformatics continue to be a part of this journal.

CONCLUSIONS

There is a continuous and, as it seems, ever growing overlap in the research methodology and application areas of the mentioned disciplines. As there is a continuing and even growing need for such a publication forum, Methods of Information in Medicine will keep its broad scope. As an organizational consequence, the journal's number of associate editors has increased accordingly.

Section 5: Decision Support, Knowledge Representation and Management: Free and Open Source Enabling Technologies for Patient-Centric, Guideline-Based Clinical Decision Support: A Survey

Guideline-based clinical decision support is an emerging paradigm to help reduce error, lower cost, and improve quality in evidence-based medicine. The free and open source (FOS) approach is a promising alternative for delivering cost-effective information technology (IT) solutions in health care. In this paper, we survey the current FOS enabling technologies for patient-centric, guideline-based care, and discuss the current trends and future directions of their role in clinical decision support.

We searched PubMed, major biomedical informatics websites, and the web in general for papers and links related to FOS health care IT systems. We also relied on our background and knowledge for specific subtopics. We focused on the functionalities of guideline modeling tools, and briefly examined the supporting technologies for terminology, data exchange and electronic health record (EHR) standards.

To effectively support patient-centric, guideline-based care, the computerized guidelines and protocols need to be integrated with existing clinical information systems or EHRs. Technologies that enable such integration should be accessible, interoperable, and scalable. A plethora of FOS tools and techniques for supporting different knowledge management and quality assurance tasks involved are available. Many challenges, however, remain in their implementation.

There are active and growing trends of deploying FOS enabling technologies for integrating clinical guidelines, protocols, and pathways into the main care processes. The continuing development and maturation of such technologies are likely to make increasingly significant contributions to patient-centric, guidelinebased clinical decision support.

The Student Editorial Board of Methods of Information in Medicine--an opportunity to educate tomorrow's peer reviewers

OBJECTIVE

Peer review is a critical process in the publication of scientific findings; trainees and young investigators, however, have few opportunities to learn systematically how to review manuscripts. Journal editors have an opportunity to engage trainees and young investigators in the peer review process early during their career.

METHODS

Methods of Information in Medicine, an official journal of the International Medical Informatics Association, is initiating a Student Editorial Board. The journal invites applications from international graduate and post-doctoral training programs that have a focus on health informatics, biomedical informatics, or a related field.

RESULTS

Each year up to six trainees will be invited to join the Student Editorial Board. The trainees will go through a mentored training experience that includes an active involvement in the various aspects of peer review during their one to two-year term of appointment.

CONCLUSIONS

The journal expects that the Student Editorial Board will benefit trainees and young investigators in becoming skilled reviewers and engaged peers who can offer professional, constructive, and informative feedback and enhance the process of scientific communication.

Free and open source enabling technologies for patient-centric, guideline-based clinical decision support: a survey

OBJECTIVES

Guideline-based clinical decision support is an emerging paradigm to help reduce error, lower cost, and improve quality in evidence-based medicine. The free and open source (FOS) approach is a promising alternative for delivering cost-effective information technology (IT) solutions in health care. In this paper, we survey the current FOS enabling technologies for patient-centric, guideline-based care, and discuss the current trends and future directions of their role in clinical decision support.

METHODS

We searched PubMed, major biomedical informatics websites, and the web in general for papers and links related to FOS health care IT systems. We also relied on our background and knowledge for specific subtopics. We focused on the functionalities of guideline modeling tools, and briefly examined the supporting technologies for terminology, data exchange and electronic health record (EHR) standards.

RESULTS

To effectively support patient-centric, guideline-based care, the computerized guidelines and protocols need to be integrated with existing clinical information systems or EHRs. Technologies that enable such integration should be accessible, interoperable, and scalable. A plethora of FOS tools and techniques for supporting different knowledge management and quality assurance tasks involved are available. Many challenges, however, remain in their implementation.

CONCLUSIONS

There are active and growing trends of deploying FOS enabling technologies for integrating clinical guidelines, protocols, and pathways into the main care processes. The continuing development and maturation of such technologies are likely to make increasingly significant contributions to patient-centric, guideline-based clinical decision support.

Constructing influence views from data to support dynamic decision making in medicine

A dynamic decision model can facilitate the complicated decision-making process in medicine, in which both time and uncertainty are explicitly considered. In this paper, we address the problem of automatic construction of a dynamic decision model from a large medical database. Within the DynaMoL (a dynamic decision modeling language) framework, a model can be represented in influence view. Thus, our proposed approach first learns the structures of the influence view based on the minimal description length (MDL) principle, and then obtains the conditional probabilities of the model by Bayesian method. The experiment results demonstrate that our system can efficiently construct the influence views from data with high fidelity.

Nonparametric techniques to extract fuzzy rules for breast cancer diagnosis problem

This paper addresses breast cancer diagnosis problem as a pattern classification problem. Specifically, the problem is studied using Wisconsin-Madison breast cancer data set. Fuzzy rules are generated from the input-output relationship so that the diagnosis becomes easier and transparent for both patients and physicians. For each class, at least one training pattern is chosen as the prototype, provided (a) the maximum membership of the training pattern is in the given class, and (b) among all the training patterns, the neighborhood of this training pattern has the least fuzzy-rough uncertainty in the given class. Using the fuzzy-rough uncertainty, a cluster is constructed around each prototype. Finally, these clusters are interpreted as the fuzzy rules that relate the prognostic factors and the diagnosis results. The advantages of the proposed algorithm are, (a) there is no need to know the structure of the training data, (b) the number of fuzzy rules does not increase with the increase of the number of input dimensions, and (c) small number of fuzzy rules is generated. With the three generated fuzzy rules, 96.20% classification efficiency is achieved, which is comparable to other rule generation techniques.

PDL: a definition language for trend pattern representation and detection in medicine

This paper proposes a pattern definition language, PDL, to effectively represent and manipulate trend patterns to support medical decision making in time-critical domains. Based on a modified version of SDL, a shape definitional language introduced by Agrawal, PDL extends the expressive power of SDL in the temporal domains. PDL also permits irregular length of elementary patterns to be matched in the query. This paper describes the syntax and the semantics of PDL, as well as illustrating how it can be applied in a time-critical medical domain.

Fuzzy K-means clustering with missing values

Fuzzy K-means clustering algorithm is a popular approach for exploring the structure of a set of patterns, especially when the clusters are overlapping or fuzzy. However, the fuzzy K-means clustering algorithm cannot be applied when the real-life data contain missing values. In many cases, the number of patterns with missing values is so large that if these patterns are removed, then sufficient number of patterns is not available to characterize the data set. This paper proposes a technique to exploit the information provided by the patterns with the missing values so that the clustering results are enhanced. There are various preprocessing methods to substitute the missing values before clustering the data. However, instead of repairing the data set at the beginning, the repairing can be carried out incrementally in each iteration based on the context. In that case, it is more likely that less uncertainty is added while incorporating the repair work. This scheme is further consolidated in this paper by fine-tuning the missing values using the information from other attributes. The applications of the proposed method in medical domain have produced good performance.

The rapid diagnosis of smear-negative pulmonary tuberculosis: a cost-effectiveness analysis

OBJECTIVE

The prompt diagnosis of smear-negative pulmonary tuberculosis (PTB) is a clinical challenge. It may be achieved by a number of tests which have varying accuracies, costs and degrees of invasiveness. The objective of this study was to compare the cost-effectiveness of clinical judgement (empirical), the Roche Cobas amplicor assay for Mycobacterium tuberculosis (amplicor), acid-fast staining of bronchoalveolar lavage specimens (BAL), nucleic acid amplification tests of bronchoalveloar lavage specimens for M. tuberculosis (BAL + NAA), computed tomography (CT) and amplicor assay followed by BAL.

METHODOLOGY

The range of predictive values of the various strategies were derived from published data and a new study of 441 consecutive adult patients with suspected smear-negative PTB prospectively stratified into three pretest risk groups: low, intermediate and high. The cost-effectiveness was evaluated with a decision tree model (DATA software).

RESULTS

The incidence of PTB was 5.7% (4% culture positive) for the whole group, 95% in the high-risk group, 0.9% in the low-risk group and 3.4% in the intermediate-risk group. The sensitivity of the empirical approach was 49% and of the amplicor assay was 44%. Patient outcomes were expressed as life expectancy for the base case of a 58-year-old man with a pretest probability of 5.7%. At this low pretest risk the differences in life expectancies between tests was < 0.1 years and the empirical approach incurred the lowest cost. Sensitivity analysis at increasing pretest risks showed better life expectancies (approximately 1 years) for CT scan and test combinations than empirical and amplicor for additional costs of US$243-US$309. Bronchoalveolar lavage had the worst overall cost-effectiveness.

CONCLUSIONS

We conclude that the pretest risk of active PTB was a key determinant of test utility; that the AMPLICOR assay was comparable to clinical judgement; that BAL was the least useful test; and that with increasing risks, CT scan and test combinations performed better. Further studies are needed to better define patients with intermediate risk for PTB and to directly compare the cost-effectiveness of more sensitive nucleic acid amplification tests such as the enhanced Gen Probe, CT scan and test combinations/sequences in these patients.

Application of K-nearest neighbors algorithm on breast cancer diagnosis problem

This paper addresses the Breast Cancer diagnosis problem as a pattern classification problem. Specifically, this problem is studied using the Wisconsin-Madison Breast Cancer data set. The K-nearest neighbors algorithm is employed as the classifier. Conceptually and implementation-wise, the K-nearest neighbors algorithm is simpler than the other techniques that have been applied to this problem. In addition, the Knearest neighbors algorithm produces the overall classification result 1.17% better than the best result known for this problem.

A data preprocessing framework for supporting probability-learning in dynamic decision modeling in medicine

Data preprocessing is needed when real-life clinical databases are used as the data sources to learn the probabilities for dynamic decision models. Data preprocessing is challenging as it involves extensive manual effort and time in developing the data operation scripts. This paper presents a framework to facilitate automated and interactive generation of the problem-specific data preprocessing scripts. The framework has three major components: 1) A model parser that parses the decision model definition, 2) A graphical user interface that facilitates the interaction between the user and the system, and 3) A script generator that automatically generates the specific database scripts for the data preprocessing. We have implemented a prototype system of the framework and evaluated its effectiveness via a case study in the clinical domain. Preliminary results demonstrate the practical promise of the framework.

Using linear regression functions to abstract high-frequency data in medicine

This paper investigates the problem of representing medical time series in linear piece-wise functions and proposes a novel algorithm to transform time-stamped numeric data into simple linear regression functions. We apply methods that involve the hat matrix leverage value and the studentized deleted residual to identify outliers, and a heuristic approach to remove them from the data sets. By distinguishing the breaking points from true outliers, we can efficiently break the data set with respect to the underlying patterns. Using a rough segmentation step, our approach avoids using the whole data set as input, and reduces space requirement. The experimental results indicate our method can achieve more accurate representation of the underlying patterns in data sets collected in the intensive care units efficiently.

Consistency management in multiple perspective medical decision analysis

Multiple perspective reasoning is often involved in real-world decision analysis. Different perspectives may be suitable for different stages of the decision modeling process. Multiple perspective modeling calls for consistency management which ensures that the different perspectives reflect the same information. This paper summarizes the graphical perspectives currently supported in DynaMoL, a new framework for dynamic decision analysis. We introduce a new perspective, the tree view, into the framework. We present the main ideas involved in consistency management in the framework. We also discuss the critical issues involved in multiple perspective modeling of a simplified case study in medicine.

Induction of diagnostic test strategies with multi-level information measures

This paper presents a method for inducing clinical diagnostic test protocols or strategies from data. We represent testing strategies as a strategy tree. To support induction of strategy tree, we define three information measures: K-level information, K-level information gain, K-level gain ratio, and K-level cost index, for test selection during strategy building. These measures generalize Quinlan's information measures used in decision tree induction. We present theoretical and experimental results to show that the K-level cost index can be used to induce strategy trees in a practical domain.

PROBES: a framework for probability elicitation from experts

A decision analytic model represents uncertainties as probability distributions. These distributions are hard to assess especially for large and dynamic models. We propose an integrated framework that facilitates elicitation of the relevant probability distributions for dynamic decision models from the domain experts. The experts usually use some judgmental heuristics to aid probability assessments; the resulting distributions may be proned to cognitive biases. Our framework aims to minimize the effects of these biases and to improve the quality of decisions made. We have implemented a prototype system of the framework and evaluated its effectiveness via a case study in the follow-up management of colorectal cancer patients after curative surgery. Preliminary results demonstrate the practical promise of the framework.

Supporting multi-level multi-perspective dynamic decision making in medicine

Most medical decision problems are exceedingly complex and contain a large number of variables. Abstraction facilitates the process of building a decision model by allowing a model builder to work at a level of detail that he is most comfortable with; it is also useful in time-critical situations or when there is insufficient data to support complete specification of probabilities of the uncertain events. In this paper, we identify and formalize abstraction and refinement operations commonly used in model construction. We illustrate the use of these mechanisms with an example on the follow-up management of colorectal cancer patients after surgery.

Decision analytic approach to severe head injury management

Severe head injury management in the intensive care unit is extremely challenging due to the complex domain, the uncertain intervention efficacies, and the time-critical setting. We adopt a decision analytic approach to automate the management process. We document our experience in building a simplified influence diagram that involves about 3000 numerical parameters. We identify the inherent problems in structuring a model with unclear domain relationships, numerous interacting variables, and real-time multiple inputs. We analyze the effectiveness and limitations of the decision analytic approach and present a set of desiderata for effective knowledge acquisition in this setting. We also propose a semi-qualitative approach to parameter elicitation.

Dynamic decision analysis in medicine: a data-driven approach

Dynamic decision analysis concerns decision problems in which both time and uncertainty are explicitly considered. Two major challenges in dynamic decision analysis are on proper formulation of a model for the problem and effective elicitation of the numerous time-dependent conditional probabilities for the model. Based on a new, general dynamic decision modeling framework called DynaMoL (Dynamic decision Modeling Language), we propose a data-driven approach to addressing these issues. Our approach uses available problem data from large medical databases, guides the decision modeling at a proper level of abstraction and establishes a Bayesian learning method for automatic extraction of the probabilistic parameters. We demonstrate the theoretical implications and practical promises of this new approach to dynamic decision analysis in medicine through a comprehensive case study in the optimal follow-up of patients after curative colorectal cancer surgery.

Modelling medical decisions in DynaMoL: a new general framework of dynamic decision analysis

Dynamic decision analysis concerns decision problems in which both time and uncertainty are explicitly considered. We present a new dynamic decision analysis framework, called DynamoL, that supports graphical presentation of the decision factors in multiple perspectives. To alleviate the difficulty in assessing conditional probabilities over time in dynamic decision models, DynaMoL incorporates a Bayesian learning system to automatically learn the probabilistic parameters from large medical databases. We describe the DynaMoL modeling and learning architecture through a medical decision problem on the optimal follow-up schedule for patients after curative colorectal cancer surgery. We also show that the modeling experience and results indicate practical promise for the framework.

The Medical Informatics Program at the National University of Singapore

The Medical Informatics Program at the National University of Singapore was established in September 1996 with a $4 million joint funding from the National Science and Technology Board and the Ministry of Education. The primary aims of the research program are to undertake upstream basic research in medical informatics and to build a critical mass of medical informatics expertise to meet long-term research goals and to effect technology transfer to the health sector of Singapore. Research projects fall into five groups: Clinical Decision Systems, Health Information Systems, Biomedical Datamining Systems, Medical Education Systems and Medical Networking, Applications Development and Integration Systems.

Dynamic decision modeling in medicine: a critique of existing formalisms

Dynamic decision models are frameworks for modeling and solving decision problems that take into explicit account the effects of time. These formalisms are based on structural and semantical extensions of conventional decision models, e.g., decision trees and influence diagrams, with the mathematical definitions of finite-state semi-Markov processes. This paper identifies the common theoretical basis of existing dynamic decision modeling formalisms, and compares and contrasts their applicability and efficiency. It also argues that a subclass of such dynamic decision problems can be formulated and solved more effectively with non-graphical techniques. Some insights gained from this exercise on automating the dynamic decision making process are summarized.

Representation requirements for supporting knowledge-based construction of decision models in medicine

This paper analyzes the medical knowledge required for formulating decision models in the domain of pulmonary infectious diseases (PIDs) with acquired immunodeficiency syndrome (AIDS). Aiming to support dynamic decision-modeling, the knowledge characterization focuses on the ontology of the clinical decision problem. Relevant inference patterns and knowledge types are identified.

Effect of Light Quality on the Composition, Function, and Structure of Photosynthetic Thylakoid Membranes of Asplenium australasicum (Sm.) Hook

The effect of light quality on the composition, function and structure of the thylakoid membranes, as well as on the photosynthetic rates of intact fronds from Asplenium australasicum, a shade plant, grown in blue, white, or red light of equal intensity (50 microeinsteins per square meter per second) was investigated. When compared with those isolated from plants grown in white and blue light, thylakoids from plants grown in red light have higher chlorophyll a/chlorophyll b ratios and lower amounts of light-harvesting chlorophyll a/b-protein complexes than those grown in blue light. On a chlorophyll basis, there were higher levels of PSII reaction centers, cytochrome f and coupling factor activity in thylakoids from red light-grown ferns, but lower levels of PSI reaction centers and plastoquinone. The red light-grown ferns had a higher PSII/PSI reaction center ratio of 4.1 compared to 2.1 in blue light-grown ferns, and a larger apparent PSI unit size and a lower PSII unit size. The CO(2) assimilation rates in fronds from red light-grown ferns were lower on a unit area or fresh weight basis, but higher on a chlorophyll basis, reflecting the higher levels of electron carriers and electron transport in the thylakoids.The structure of thylakoids isolated from plants grown under the three light treatments was similar, with no significant differences in the number of thylakoids per granal stack or the ratio of appressed membrane length/nonappressed membrane length. The large freeze-fracture particles had the same size in the red-, blue-, and white-grown ferns, but there were some differences in their density. Light quality is an important factor in the regulation of the composition and function of thylakoid membranes, but the effects depend upon the plant species.

Adaptation of the thylakoid membranes of pea chloroplasts to light intensities. I. Study on the distribution of chlorophyll-protein complexes

The effect of light intensity (16 h white light and 8 h dark) during growth of pea plants at 20°C on the chlorophyll composition and on the relative distribution of chlorophyll amongst the various chlorophyll-protein of pea thylakoids was studied. The chl a/chl b ratios increased from 2.1 to 3.2 as light intensity during growth varied from 10 to 840 μEm(-2) s(-1). This function can be described by two straight lines intersecting at a transition point of approximately 200 μEm(-2) s(-1). Similar discontinuities in the responses were observed in the changes in the relative distribution of chlorophyll amongst the various chlorophyll-protein complexes. This demonstrates that the chl a/chl b ratio of the various thylakoids is a good indicator of changes in the relative distribution of chlorophyll. As the chl a/chl b ratio decreased, the amount of chlorophyll associated with photosystem I complexes decreased, that with photosystem II core reaction centre complex was halved, and that with the main chl a/b-proteins of the light-harvesting complex was markedly increased.

Adaptation of the thylakoid membranes of pea chloroplasts to light intensities. II. Regulation of electron transport capacities, electron carriers, coupling factor (CF1) activity and rates of photosynthesis

The electron transport rates of photosystems II and I, amounts of electron carriers, coupling factor activity and photosynthetic rates were investigated in thylakoids isolated from pea plants grown under a wide range of light intensities (16 h light-8 h dark). The electron transport rates of PS II and PS I, as partial reactions or in whole chain, and coupling factor activity on a unit chlorophyll basis, all increased as the light intensity available for growth was altered from a very low intensity of 10 μE m(-2)s(-1) to a high intensity of 840 μE m(-2)s(-1). Similarly, there were increases in the amounts of atrazine binding sites, plastoquinine, cytochrome f and P700 per unit chlorophyll; significantly, the amounts of reaction centres of PS II and PS I were not equal at any light intensity. The rate of change of all parameters with respect to light intensity could be represented by two straight lines of different slopes which met at a transition point corresponding to approximately 200 μE m(-2)s(-1) during growth. These photoadaptations were similar to those observed for both the relative distribution of chlorophyll in chlorophyll-protein complexes and the chl a/chl b ratios [Leong and Anderson, 1984, Photosynthesis Research 5:117-128]. Since these thylakoid components and functions were affected in the same direction by light intensity during growth and all show linear relationships with chl a/chl b ratios, it indicates that they are closely regulated and markedly well co-ordinated. Plants compensate for the limited amount of low light intensities by drastically increasing the light-harvesting antenna unit size of photosystem II and to a lesser extent that of photosystem I. Changes in the composition of the thylakoid membranes exert a regulatory effect on the overall photosynthetic rate up to approximately 450 μE m(-2)s(-1).

Evidence from studies with acifluorfen for participation of a flavin-cytochrome complex in blue light photoreception for phototropism of oat coleoptiles

The diphenyl ether acifluorfen enhances the blue light-induced absorbance change in Triton X100-solubilized crude membrane preparations from etiolated oat (Avena sativa L. cv. Lodi) coleoptiles. Enhancement of the spectral change is correlated with a change in rate of dark reoxidation of a b-type cytochrome. Similar, although smaller, enhancement was obtained with oxyfluorfen, nitrofen, and bifenox. Light-minus-dark difference spectra in the presence and absence of acifluorfen, and the dithionite-reduced-minus oxidized difference spectrum indicate that acifluorfen is acting specifically at a blue light-sensitive cytochrome-flavin complex. Sodium azide, a flavin inhibitor, decreases the light-induced absorbance change significantly, but does not affect the dark reoxidation of the cytochrome. Hence, it is acting on the light reaction, suggesting that the photoreceptor itself is a flavin. Acifluorfen sensitizes phototropism in dark-grown oat seedlings such that the first positive response occurs with blue light fluences as little as one-third of those required to elicit the same response in seedlings grown in the absence of the herbicide. Both this increase in sensitivity to light and the enhancement of the light-induced cytochrome reduction vary with the applied acifluorfen concentration in a similar manner. The herbicide is without effect either on elongation or on the geotropic response of dark-grown oat seedlings, indicating that acifluorfen is acting specifically close to, or at the photoreceptor end of, the stimulus-response chain. It seems likely that the flavin-cytochrome complex serves to transduce the light signal into curvature in phototropism in oats, with the flavin moiety itself serving as the photoreceptor.

Partial purification and characterization of a blue light-sensitive cytochrome-flavin complex from corn membranes

A membrane fraction which contains a blue light-sensitive flavin-cytochrome complex (Brain et al. 1977 Plant Physiol 59:948) has been partially purified by sucrose and Renografin gradient centrifugations. Assays for marker enzymes show that this membrane fraction is distinct from endoplasmic reticulum, golgi, and mitochondria. This membrane fraction co-sedimented with glucan synthetase II activity, a proposed marker for plasma membrane in higher plants. The purified membrane fraction shows virtually identical light minus dark and dithionite reduced minus oxidized difference spectra with difference bands near 427 and 557 nanometers, suggesting that contamination by other cytochrome-containing membrane fractions is not significant. The photoactivity can be completely solubilized by 0.1% Triton X-100, leaving the bulk of the membrane undissolved. The kinetics for cytochrome photoreduction are not significantly affected by solubilization, indicating that both flavin and cytochrome could be associated with the same protein moiety.

The role of chloroplast-membrane-protein synthesis in the circadian clock. Purification and partial characterization of a polypeptide which is suggested to be involved in the clock

A polypeptide (polypeptide P39), which is presumed to involved in the photosynthetic circadian rhythm in the green alga Acetabularia, was purified from the EDTA-insoluble chloroplast membrane fraction by means of preparative dodecylsulfate gel electrophoresis and then partially characterized. The purity of the isolated polypeptide P39 was confirmed by a further electrophoresis on an analytical dodecylsulfate gel and further elucidated by amino-terminal analysis which shows that glycine is the only amino-terminal amino acid of the purified polypeptide material. The molecular weight of the polypeptide P39 was found to be about 39,000 on analytical gel electrophoresis and the value was further supported by those obtained from amino acid composition and peptide mapping. The amino acid composition of polypeptide P39 showed that the proportion of intermediate amino acid groups is high while the proportion of hydrophilic amino acid groups is well balanced by that of hydrophobic amino acid groups, a property characteristic of membrane proteins.