This study describes the 24-h changes in plasma prolactin levels, and dopamine (DA), serotonin (5HT), gamma-aminobutyric acid (GABA) and taurine concentration in median eminence and adenohypophysis of newborn male rabbits.Animals were kept under controlled light-dark cycles (LD 16:8, lights on at 08:00 h), housed in individual metal cages, and fed ad libitum with free access to tap water. On day 1 after parturition, litter size was standardized to 8–9 to assure similar lactation conditions during the experiment. Groups of 6–7 suckling male rabbits were killed by decapitation on day 11 of life at six different time points during a 24-h period.Plasma prolactin levels changed significantly throughout the day, showing a peak at the beginning of the active phase (at 01:00 h) and a second maximum during the first part of the resting phase (at 13:00 h). Median eminence DA concentration also changed significantly during the day, peaking at the same time intervals as plasma prolactin. A single maximum (at 13:00 h) was found for adenohypophysial DA concentration. Individual adenohypophysial DA concentrations correlated significantly with their respective plasma prolactin levels. A maximum in median eminence 5HT concentration occurred at 21:00 h whereas adenohypophysial 5HT peaked at 13:00 h. Median eminence 5HT concentration and circulating prolactin correlated inversely. In the median eminence, GABA concentration attained maximal values at 21:00 h, whereas it reached a maximum at 13:00 h in the pituitary gland. Median eminence GABA concentration correlated inversely with circulating prolactin. In the median eminence, taurine values varied in a bimodal way showing two maxima, at the second half of the rest span and of the activity phase, respectively. In the adenohypophysis, minimal taurine levels coincided with the major plasma prolactin peak (at 01:00 h). Circulating prolactin and adenohypophysial taurine levels correlated inversely.The correlations among the changes in the neurotransmitters analyzed and circulating prolactin levels explain the circadian secretory pattern of the hormone in newborn male rabbits. The mechanisms that regulate prolactin secretion are complex . Two majIt is well known that basal secretion of prolactin varies throughout the day, describing a characteristic pattern with maximal values close to the light-dark transition ,8. Such The rat is very immature at birth, so that newborn and suckling rats are very sensitive to manipulations that can affect adulthood -18. CircThe rabbit is probably the best-studied laboratory animal in the wild, due to its abundance, size and importance as an agricultural pest ,24. WildIn contrast to the large amount of information available on circadian rhythms in adult mammals, studies on circadian phenomena in neonates are few ,27. For This study was performed using 24 multiparous, lactating Californian × New Zealand White crossbreed doe rabbits. Animals were housed in research facilities of the Animal Production Department. They were maintained under controlled light-dark cycles (LD 16:8, light on at 08:00 h), housed in individual metal cages, fed at libitum using a commercial pellet diet (Lab Rabbit Chow, Purina Mills, Torrejón de Ardoz, Madrid, Spain) with free access to tap water. On day 1 after parturition, litter size was standardized to 8–9 by adding or removing kits to assure similar lactation conditions during the experiment. This study was performed according to the CEE Council Directive (86/609, 1986) for the care of experimental animals. Groups of 6–7 suckling male rabbits were killed by decapitation on day 11 of life at six different time points throughout a 24-hour cycle. The brains were quickly removed, and the median eminence and the anterior pituitary were taken out. Anterior pituitaries were weighed and homogenized in chilled (0–1°C) 2 M acetic acid. After centrifugation (at 15000 × g for 30 min, at 5°C), the samples were either analyzed for DA and 5HT or boiled for 10 min and further centrifuged at 14000 rpm for 20 min to measure GABA and taurine.L-RP-1. Hormone was labeled with 125I by the chloroamine-T method [Staphylococcus aureus (prepared by the Department of Plant Physiology, U.A.M., Madrid, Spain) was used to precipitate the bound fraction [Plasma prolactin levels were measured by a specific homologous RIA method  using AFT method . The volfraction . All sam2/H+ reference electrode were: conditioning electrode: -0.4 V; preoxidation electrode: +0.10; working electrode: +0.35 V. Indoleamine and catecholamine concentration was calculated from the chromatographic peak heights by using external standards and was expressed as pg/μg protein. The linearity of the detector response for DA and 5HT was tested within the concentration ranges found in median eminence and adenohypophysial supernatants.DA and 5HT concentration was measured by high pressure liquid chromatography (HPLC) using electrochemical detection , as described elsewhere . A C-18 Amino acids were isolated and analyzed by HPLC with fluorescence detection after precolumn derivatization with O-phthalaldehyde (OPA) as described elsewhere . An aliqStatistical analysis of results was performed by a one-way analysis of variance (ANOVA) followed by post-hoc Tukey-Kramer's multiple comparisons tests. Curve estimation in regression analysis was made by using SPSS software, version 10.1 (SPSS Inc., Chicago, ILL). P values lower than 0.05 were considered evidence for statistical significance.Figure Figures 2 = 0.16, b0 = -123.7 and b1= 18.1 (F = 4.69, p= 0.04).Median eminence DA concentration changed in a bimodal way as a function of time of day, showing two maxima, coinciding with those of plasma prolactin at the active and resting phase of the diurnal cycle .As shown in Figure 2= 0.21, b0 = 25.7 and b1 = -0.22, F = 6.6, p < 0.01).Figure 2= 0.42, b0 = 11.6 and b1 = -0.11, F = 17.4, p < 0.0001).Figure The present study, performed in neonatal male rabbit pups sacrificed at 6 different time intervals during a 24-h cycle, describes for the first time significant changes in plasma prolactin levels throughout the day. In concomitant measurements of median eminence and adenohypophysial concentration of DA, 5HT, GABA and taurine, a clear daily pattern was found in almost every case. Contrasting with neonatal rats that did not display any circadian pattern of plasma prolactin , a dailyIn adult rabbits, daily patterns of prolactin secretion depend on light/dark phases . The preThe activity of several nuclei of rabbit hypothalamus increases with age and with experience of anticipatory arousal . HoweverAmong other possible neuromodulators of prolactin secretion, the arcuate nucleus receives a dense serotonergic innervation consisting of a population of brainstem neurons arising mainly from the midbrain raphe nuclei  and fromTaurine has also been implicated in the regulation of prolactin release ,13,35,36A relatively dense innervation of GABA terminals exists in the external layer of the median eminence , and theGABA acting on specific receptors in the anterior pituitary has been reported to suppress prolactin secretion ,40, althIn suckling male rabbits plasma prolactin and median eminence and anterior pituitary concentration of several neuromodulators change on a daily basis. The existence of significant correlations among several of the neurotransmitters analyzed and plasma prolactin levels may explain the circadian secretory pattern of prolactin at this age in suckling rabbits. Collectively, the present results differ from the reported absence of circadian rhythmicity of prolactin and median eminence and adenohypophysial neuromodulators in rats at a comparable age.The author(s) declare that they have no competing interests.MPA and PC carried out the experiment and the immunoassays and the analysis of catecholamines, indoleamines and amino acids. DPC and AIE designed the experiments. Also, DPC performed the statistical analysis. PR took care of the experimental animals. AIE supervised its technical implementation and drafted the manuscript. All authors read and approved the final manuscript.


We assessed the applicability of the T&C test as an accurate and convenient means to screen for dementia in primary care and community settings.The study group comprised 59 patients and 405 community participants, all of who were aged 65 years and over. The time component of the T&C test evaluated the ability of a subject to comprehend clock hands that indicated a time of 11:10, while the change component of the T&C test evaluated the ability of a subject to make 1,000 Won from a group of coins with smaller denominations (one 500, seven 100, and seven 50 Won coins).The T&C test had a sensitivity and specificity of 73.0 and 90.9%, respectively, and positive and negative predictive values of 93.1, and 66.7%, respectively. The test-retest and interobserver agreement rates were both 95% (κ = 0.91) . The association between the T&C test and K-MMSE test was modest, while significant (r = 0.422, p < 0.001). The T&C test scores were not influenced by educational status.We conclude that the T&C test is useful as supplemental testing of important domains  to traditional measures such as the MMSE. However, because T&C test is simple, rapid, and easy to use, it can be applied conveniently to elderly subjects by non-specialist personnel who receive training. Dementia, an acquired persistent impairment of cognitive functioning is an increasingly common problem in Korea, and is associated with increased morbidity and mortality, functional loss, caregiver burden, and institutionalization . NeverthScreening for dementia has been recommended to increase detection of dementia. The Mini-Mental State Examination (MMSE) is a brief screening test that quantitatively assesses the cognitive status of elderly people ,5. AlthoWe have therefore introduced a T&C test, and assessed the applicability of the T&C test as a convenient and accurate means to detect early stage dementia in primary care and community settings.One study group initially comprised 60 participants who either visited or were admitted to a hospital that was located in an urban area, namely Gwangju city (referred to forthwith as area A) between November and December 2001. Of these 60 participants, 37 were diagnosed with Alzheimer's disease or vascular dementia, 11 had mental illness such as schizophrenia or depression, 7 had organic brain disease such as cerebral apoplexy or Parkinson's disease, and 5 were alcoholics.Another study group initially comprised 412 participants who were recruited from all residents of Jangseong-county, Jeonnam province, South Korea, aged 65 and over in 2002(referred to forthwith as area B). The area consists of 11 towns and had an estimated population 54,528 of whom about 16.5% were aged 65 and over. The subjects were selected from each stratum (town) using cluster sampling. All subjects in whom vision or hearing was impaired were excluded from the study. We selected 59 (of 60) and 405 (of 412) participants from area A and B, respectively. All participants gave informed consent, and when participants with dementia cannot provide informed consent, caregivers were asked to provide it.The 'time' component of the T&C test evaluated the ability of a subject to comprehend that the hands of a clock indicated 11:10. The diameter of the clock was 15 cm, and the distance between the clock and the participant was 25–35 cm . When the subject responded incorrectly on the first attempt, the interviewer posed the same question, i.e., a second attempt was permitted. The time (in seconds) that it took for the participant to respond correctly was recorded. A time limit of 60 s for a response was imposed.In the 'change' component of the T&C test, the participants were required to make 1,000 Won from a group of coins of several smaller denominations, namely one 500, seven 100, and seven 50 Won coins, that were placed on a table in front of the participant. The participants were given 120 s to complete the task, and an additional 120 s was granted if the subject failed to complete the task at the first attempt. The time (in seconds) that it took for the participant to complete the task was recorded by the interviewer.The participants who completed both of the aforementioned tasks of the T&C test successfully were determined to be negative for suspected dementia, whereas participants who failed to complete either or both of the tasks were determined to be positive for suspected dementia. The T&C test was performed prior to the other cognitive tests by an interviewer who was unaware of the results of the other tests.In the participants from area A, the T&C test was conducted by a nurse, while a physician who were blinded to the result of the T&C test performed a clinical examination and neuropsychiatric inventory. The diagnostic criteria for dementia were based on those of the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) . To deteThe participants from area B were interviewed by interviewers who had undergone sufficient training to be able to conduct the K-MMSE and T&C test.All participants were interviewed for data on social and demographic factors such as address, age, sex, educational status, and the number of family members living together.To assess the validity of the T&C test as a method to screen for dementia in the participants from area A, we compared the results of the test to a reference standard (diagnosed by a physician), and evaluated sensitivity, specificity, and positive and negative predictive values. To assess the test-retest reliability, the one type of interviewer  conducted the same test twice at an interval of 24 h (n = 22 participants). To assess the interobserver reliability, two different types of interviewer  conducted the same test, at an interval of 24 h (n = 22 participants).To assess the applicability of the T&C test as a method to screen for dementia in the participants from area B, the association between the T&C and K-MMSE test scores was evaluated.The sensitivity, specificity, and positive and negative predictive values and 95% Confidence interval of the T&C test were analyzed. After classifying the participants from area B into a group in which dementia was suspected, and another group in which dementia was not suspected based on the results from the T&C test, a Student's t-test was used to compare the total K-MMSE score with the scores for each of the components of the K-MMSE test, and Spearman's rank correlation was used to analyze the correlation between the T&C and K-MMSE test scores. SPSS for Windows  and Stata Software 6.0 (Stata Corporation, College Station, Texas) were used to analyze data and statistics.For the participants from area A, the average age was 73.2 ± 7.9 years, 55.9% of the group was female, the average number of years of education was 4.2 ± 5.4, and 62.7% lived alone. For the participants from area B, the average age was 73.1 ± 6.1 years, 58.5% of the group was female, the average number of years of education was 3.1 ± 4.0, and 29.0% lived alone  .There was a significant difference between the total K-MMSE score and the scores for each of the components of the K-MMSE test between participants that were classified as positive and those that were classified as negative for dementia according to the T&C test Table . The assThe results of a logistic regression in which the T&C test as a dichotomous and dependent variable was performed with education status adjusting for age and sex revealed no association between them. The odds ratio for T&C test associated with educational status is 0.877 (95% CI = 0.766–1.004).For the time task in the T&C test, 75.8% of the participants produced a correct response on the first attempt after 6.3 ± 6.7 s, and 45 participants (11.1%) produced a correct response on the second attempt. For the change task in the T&C test, 81.2% of the participants produced a correct response on the first attempt after 12.7 ± 14.2 s, and 43 participants (10.6%) produced a correct response on the second attempt. 34 participants(8.4%) were tested twice for both the time and change task. None of the subjects refused to respond during the tests.Interracial variability in both the etiology of dementia and the accuracy of cognitive testing suggests that there is an urgent need to develop racially appropriate methods of cognitive assessment. The rate of vascular dementia due to cerebrovascular disease is much higher in Koreans than in other races; this is due to insufficient prevention, diagnosis, and treatment of hypertension, diabetes, and hyperlipidemia in Korea. Vascular dementia, unlike Alzheimer's disease, can be prevented by appropriate treatment and prevention for the risk factors of cerebrovascular diseases, can be treated to improve symptoms and inhibit progression of the disease.In the present study, the original T&C test of Inouye et al.  was modiWhen compared to the results of Kawamato , in whicIn elderly patients, the assessment of cognitive function is affected by psychological factors and by the circumstances under which the tests are conducted. In our measurement of the reliability of the T&C test, the test-retest and interobserver agreement rates were both remarkably high (95% for each, κ = 0.91). In a study by Inouye et al.  the testIn the present study, no association was observed between T&C test scores and educational status. This result may be explained by the fact that interpreting the hands of a clock and calculation using change are behaviors that are common to all people during daily life, irrespective of race and education. In addition, unlike the language-focused MMSE, the questions in the T&C test cannot be misinterpreted or misunderstood, and are effective for assessing calculation ability and attention. Clock test (similar to T&C test) is less likely to be confounded by educational attainment , and meaThis study has several important limitations. First, while the hospital patients underwent an evaluation of their medical history as well as neurological and physical examinations before a diagnosis of dementia was made, the elderly community sample were evaluated using only the K-MMSE as a reference. Second, the hospital patients would appear to be a rather unusual sample in that there was a high prevalence of psychiatric morbidity in the non-demented subjects. Third, dementia in the present study was not classified as vascular or Alzheimer's-type, nor did we consider the severity of symptoms. Finally, the T&C test has limitations in assessment of a wide range of deficits associated with dementia. However, because T&C test is simple, rapid, and easy to use, the T&C test may pose particular advantages in primary care and community settings where frequent assessment of cognitive functioning is required. The T&C test adds supplemental testing of important domains  to traditional measures such as MMSE. In addition, because the T&C test is less influenced by educational status, it may be particularly useful in populations with diverse educational and cultural backgrounds.We conclude that the T&C test is useful as a supplemental testing of important domains  to traditional measures such as the MMSE, because sensitivity of T&C test is not great and the association between the T&C test and MMSE is modest. However, because T&C test is simple, rapid, and easy to use, it can be applied conveniently to elderly subjects by non-specialist personnel who receive training. In addition, the T&C test is less influenced by educational statusThis work was supported by grants from Chonnam National University Hospital (CUHRI-U-200241).The author(s) declare that they have no competing interests.JAR conceived of the study, collected data and drafted the manuscript. EKC participated in its design, performed data collection, and reviewed the manuscript. MHS participated in data analysis and reviewed the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


The project should lead to large-scale models of molecular and cellular processes involved in neuronal signaling. A prerequisite is the proper storage of knowledge coming from the literature.DopaNet DopaNet Molecular Pages are highly structured descriptions of quantitative parameters related to a specific molecular complex involved in neuronal signal processing. A Molecular Page is built by maintainers who are experts in the field, and responsible for the quality of the page content. Each piece of data is identified by a specific ontology code, annotated (method of acquisition, species, etc.) and linked to the relevant bibliography. The Molecular Pages are stored as XML files, and processed through the DopaNet Web Service, which provides functionalities to edit the Molecular Pages, to cross-link the Pages and generate the public display, and to search them.DopaNet Molecular Pages are one of the core resources of the DopaNet project but should be of widespread utility in the field of Systems Neurobiology. Genes to Cognition consortium . Anot. AnotGen Gilman ,4), whic, whicGenSimilarly, we started at the end of 2001 the mesotelencephalic dopamine consortium (DopaNet, ). The inA first step, prior to the design of large-scale dedicated experiments, consists in data mining the current literature in molecular and cellular neurobiology for existing quantitative knowledge. The resulting data has to be properly stored and annotated.α and βγ subunits. The information collected deals with the structure of the complex, its anatomical distribution within DopaNet target cells, and its functional properties. Each page is under the responsibility of its maintainer(s), who decide which data is to be included or not, and acknowledge the input of the various contributors. All the data included in a Molecular Page is annotated (Species, Methods, variability etc.), and linked to bibliographic references. In addition, each single data stored in the databases of DopaNet is attached to one or several terms of the DopaNet Neuronal Ontology. This ontology will therefore act as a glue, relating the various pieces of data one to the other.A DopaNet Molecular Page is a collection of annotated numerical data relative to a "molecular complex" present in one or several DopaNet target cells. The "molecular complex" is taken here in the sense of the DopaNet Neuronal Ontology (see below), as a "stable assembly of molecules", a "molecule" being described as a "set of atoms linked together by covalent bounds". As a consequence, we can have a Molecular Page storing data relative to a molecular complex made up of components, that are themselves described in other Molecular Pages. An anticipated example is an heterotrimeric G protein and its 2(beta2)3 nAChR. Each term can be the child of several others. Therefore the complete picture is not a genealogical tree, but rather a network or relationships.An ontology is defined here in its information science meaning, as a hierarchical structuring of knowledge. In our case, it is a relational vocabulary, that is a set of terms linked together, aiming to describe a neuron. Each term has a definition and a unique identifier. Terms are related by "is a" inheritances, which represent sub-classing, and "part of" inheritances which represent deepening knowledge. For instance, the nicotinic receptor subunit alpha6 "is a" nicotinic receptor subunit, and is "part of" the There are several biological ontologies, the most famous (and complete) being Gene Ontology ,10). Num. Num10])A Molecular Page is made up of a header followed by several lists, each list containing a sequence of identical elements. There are currently twelve main lists, described below. Several other lists of items are used to described the page data at a finer level. According to the molecular complex described in the page, some of the lists can be empty.The Molecular Page header contains the name of the molecular complex described in the page, an abbreviation, the unique ontology code used to identify the page, the dates of creation and last modification of the page, and the page status. The possible status are:The Molecular Page has been submitted by the maintainers and is ready for public release.A new version of the Molecular Page, not yet ready for public release.A new Molecular Page in construction, that has never been submitted for public release.α4)2(β2)3 is described in the Page describing the complex "_2(beta2)_3 nAChR" . The related Ontology term can be found at For instance, the nicotinic acetylcholine receptor _2(beta2)_3 nAChR"                         status="stable">                         The main lists that compose a Molecular Page are:Maintainers are the only people authorized to directly modify the Molecular Pages. They are responsible for the quality and the completeness of the data included in the Page. However, maintainers are not assumed to systematically gather the information all by themselves. They are encouraged to contact experts to help them. Helpful people should be acknowledged as contributors.Contributors are all the people who bring new information about a Molecular Page, or correct an existing piece of information. Contributors can be seen as the equivalent of authors of an article. Except maintainers (who are contributors by definition), they cannot directly modify a Molecular Page. They have to contact a maintainer instead. Note that the database administration team can directly modify the Molecular Pages to comply with the guidelines.A Molecular Page describes a molecular complex. This complex is made up of components (at least one). The listOfComponents describes those components, their stoichiometry, and lists useful related resources. Each component is annotated by its ontology code.α4 and the subunit β2.The complex "_2(beta2)_3 nAChR" [DA:0000027] is made up of two components, the subunit <listOfComponents> <component DopaNetontology="DA:0000188"  name="alpha4 nicotinic receptor subunit"                     stoichiometry="2">                     <listOfResources>   <resource identifier="ACHa4hosa"     name="Ligand-Gated Ion Channel database"                     references="1"                   "> url="                    <taxon>Homo sapiens</taxon>             </resource>     </listOfResources>     </component>  </listOfComponents> The function of a molecular complex is most often modulated by permutations between various states . Accordingly, most of the quantitative data are actually relevant only for one state or a subset of states. Those states should therefore be listed, described and annotated. The quantitative data described in the "functional" lists (see below) will refer both to the states of the molecular complex itself, listed here, and the list of states of other relevant Molecular Pages.The complex "_2(beta2)_3 nAChR" may exist under (at least) three different states: "basal", "active", and "desensitized".<listOfStates>  <state identifier="basal" name="basal">         <description>                In the basal state, the ionic pore is closed. This state displays a weak affinity for agonists such as acetylcholine or nicotine.                 </description>                 </state>       </listOfStates>  A list of properties that depends solely on the molecular complex itself, and not on its relationships with other entities, such as ligands or substrates. Example of such properties are molecular weight or Stoke radius.<listOfGenericProperties>  <property name="MW" stateMolecule="basal">        <taxon>Homo sapiens</taxon>            <listOfValues>                <value mean="310971" unit="Dalton">                        <comment>without covalent modifications.</comment>                             </value>                        </listOfValues>                 </property>        </listOfGenericProperties>  listOfExtracellular shall be necessary at some point.The distribution of the molecular complex and its components is described within the relevant DopaNet target cells: cortical glutamatergic pyramidal neuron, mesencephalic dopaminergic neuron, striatal cholinergic interneuron, striatal enkephalinergic/GABAergic medium spiny neuron, striatal substance p/GABAergic medium spiny neuron. It is likely that a Each cell is divided into compartments, where the distribution of transcripts and molecules can be described. The approach used to explore the distribution is specified, since both the accuracy and the quantitativeness of the observations strongly depends on the method chosen. As for all the following data, the species where the study has been conducted is also mandatory.α4 is present in 100% of neurons and β2 is probably also present in 100% of neurons.One entry in the complex "_2(beta2)_3 nAChR" is the fact that in the cell soma of the rat mesencephalic dopaminergic neuron, single cell RT-PCR experiments showed that <listOfCells>  <cell cellName="mesencephalic dopaminergic neuron" DopaNetontology=" DA:0000702">    <listOfCompartments>         <compartment DopaNetontology="DA:0000137" name="cell soma">           <listOfTranscripts>               <transcript method="single cell RT-PCR" references="17">                     <taxon>Rattus norvegicus</taxon>                         <description>                            a4 is present in 100% of neurons. b2 is probably also present in 100% of neurons.                               </description>                           </transcript>                     </listOfTranscripts>               </compartment>          </listOfCompartments>      </cell>  </listOfCells>The ligands of a molecular complex are molecules or ions that bind to it. The size of the ligand relative to the molecular complex is irrelevant. Within the Molecular Page of "transforming growth factor receptor type I", one ligand is "transforming growth factor betal". Conversely, in the Molecular Page of "transforming growth factor beta1", one ligand is "transforming growth factor receptor type I"! See table kon, koff or Km can be stored in a controlled manner, in order to be easily retrieved later. Whenever possible, the quantitative values are related to the states of the molecular complexes involved, not only the state of the molecular complex subject of the Molecular Page but also the state of the ligand. This remark holds for the substrates, the translocators and the modulated substances as well (see below). See table Functional parameters such as The desensitized "_2(beta2)_3 nAChR" of the rat binds acetylcholine with a Ki versus the epibatidine of 8.6 ± 1.98 nM.<listOfLigands>   <ligand DopaNetontology="DA:0000184"       name="acetylcholine"                    origin="endogenous">                    <listOfProperties>          <property name="Ki_epibatidine"               references="10 18"                          stateMolecule="desensitized">                             <taxon>Rattus norvegicus</taxon>                <listOfValues>                 <value mean="8.6" sd="1.98" unit="nanomole per litre"/>                      </listOfValues>                 </property>             </listOfProperties>         </ligand>       </listOfLigands> Km, kcat or Vmax.All substances modified as a result of an interaction with the molecular complex. The parameters stored here are for instance The translocators are substances that go from one subcellular compartment to another, the translocation being mediated by the molecular complex. Typical parameters are conductance or relative permeability.The active complex "_2(beta2)_3 nAChR" of the rat translocates cations with a conductance of 13.3 ± 1.5 pS.<listOfTranslocators>  <translocator DopaNetontology="DA:0000264"            name="cation"                         origin="endogenous">                              <listOfProperties>          <property name="conductance" references="14" stateMolecule="active">            <taxon>Rattus norvegicus</taxon>                   <listOfValues>                 <value mean="13.3" sd="1.5" unit="picosiemens"/>                        </listOfValues>                  </property>            </listOfProperties>          </translocator>       </listOfTranslocators>  modulated entries are to be avoided as much as possible, since they generally reflect a set of binding and/or enzymatic events.In many case, one knows about the effect of a molecular complex on a substance, without knowing the detailed mechanism of action. The Possible conversions between the states described in the listOfStates, such as a conformational transition, or a covalent modification.The complex "_2(beta2)_3 nAChR" undergoes conformational transitions between the basal and active states. <listOfTransitions>  <transition state 1="basal" state2="active">        <comment>                       In the absence of ligand, the equilibrium is strongly displaced toward the basal state. Agonists, such as acetylcholine and nicotine, stabilise the active state and shift the equilibrium. The transition from basal to active corresponds to an opening of the ionic pore.                  </comment>             </transition>       </listOfTransitions>  The list of bibliographic resources used to gather and annotate the data. Each piece of data included in the Molecular Page should be linked to those bibliographic items by internal references.Molecular Pages are saved as XML files , and theMolecular Pages XML files are stored within two different repositories, depending on the status of the Page. One repository contains only the stable Pages ready for public release (22 pages as of October 21, 2004), while the other repository contains also the unstable and the forthcoming Pages (39 pages as of October 21, 2004).In addition to the two XML repositories, there is also a third HTML repository, containing the human-readable HTML versions of the stable Pages, automatically generated from their XML counterparts using XSL Transformations  with theDopaNet Web Service has been designed and implemented, which provide functionalities to:As described above, Molecular Pages are continuously modified and updated by the maintainers, with the help of the contributors. In order to automatize, safe-guard and simplify as much as possible the work required by a maintainer to create and edit a Molecular Page, an application called the 1. authenticate Page maintainers2. browse pages by maintainers3. grant exclusive Page editing rights to a maintainer4. create and edit a Page via a rich user interface5. save or submit the edited Page, setting the "stable/unstable" statusThe DopaNet Web Service is made of both server-side and client-side components, all written in Java, and communicating via either the SOAP  or the HIn addition to support the remote creation and editing of Molecular Pages, the DopaNet Web Service provide also functionalities to:1. register new DopaNet contributors2. update existing DopaNet contributor information3. browse Molecular Pages by status4. search Molecular PagesSearching of Molecular Pages is implemented by using the API provided by the Apache Xindice  native XAlthough in their early stage of development, DopaNet Molecular Pages provide a unique source of structured, annotated quantitative data about the molecules involved in neuronal signaling. They will feed both the experimental biologist and the theoretician with the best available estimates for all kind of knowledge, whether biochemical, anatomical or functional. This will allow them to design better experiments or formal models, and to benchmark their results. As a side-effect triggered by the mandatory annotations, DopaNet Molecular Pages will also a bibliographic resource, each page being the equivalent of a small review of the literature.Gene Ontology is now a fully grown project, and is being widely used in several biological domains. Nevertheless, in its present form, Gene Ontology was not found suitable to be directly used by the DopaNet project. We hope to collaborate with Gene Ontology maintainers in the future. In particular, effort will be made to complete Gene Ontology in the area of Neurobiology. However, DopaNet Neuronal Ontology will never actually be a subset of Gene Ontology. Indeed, the purpose of the latter is to classify the gene products – and one of its most useful application so far has been the annotation of sequence database entries. The purpose of DopaNet Ontology is broader in term of knowledge, and not limited to the classification of gene products. At the same time it is focused onto a specific system, and therefore of interest for a narrower audience.molecular function, biological process, and cellular component. Only the latter is at the moment relevant to DopaNet purposes, that is the Molecular Pages. However, it is anticipated that the biological process vocabulary will be needed in the near future, for instance to annotate electrophysiological data. DopaNet cellular component vocabulary is larger than Gene Ontology one, since it contains the different kinds of neuronal cells  In additology, .A cellular component may be for instance an anatomical structure, e.g. "dendrite" or "synaptic vesicle" but also a cell or a protein. Note that a "molecule" is defined in the Neuronal Ontology as a set of atoms covalently linked. A molecule cannot contains other molecules. Hence, a protein made up of several subunits, or a polypeptide and a co-enzyme are not "molecules", but "molecular complexes". Although our ontology is built for DopaNet purposes, it can be viewed as a more general "Neuronal Ontology". Therefore, we incorporate terms related to components present (or events taking place) in any neuron, not necessarily DopaNet target cells. In particular, such additions are advised if they clarify some hierarchical relationship.As described above, a "molecular complex" in DopaNet Neuronal Ontology contains one or several components, also present in the "molecule" branch. It could be considered redundant that all monomeric proteins are represented by two terms, as a "molecule" part of a "molecular complex". However, the meanings of the two branches are different. The "molecule" can be seen as an ideal entity, while the latter would rather represent an actual physical object of the cell. Moreover, the hierarchical structures of the two branches are different. In addition, a lot of proteins have only recently been discovered as functional complexes (e.g. the polymeric G-protein coupled receptors), and more are to be discovered. Finally, the systematic dissociation between the functional molecular complex and its components is handy when it comes to write the Molecular Pages.The Alliance for Cellular Signaling was a pioneer in designing Molecule Page. Contrary to DopaNet Molecular Pages, their focus is truly a "molecule" rather than a "molecular complex". For instance, an heteropolymeric receptor will not be represented by a Molecule Page, but rather by a collection of Pages, one per subunit.Kd In addition, pieces of quantitative knowledge, like binding or enzymatic reactions, should be provided in standardized format such as the Systems Biology Markup Language [DopaNet Molecular Pages are highly structured. While this could appear as an obvious choice, it actually comes with a double burden. First, the edition interface has to be sufficiently complex to reflect the underlying structure. This complexity certainly acts as a repellent for the biologist who wish to build a Molecular Page. Second, the high quality required, in particular concerning the annotations, leads to the rejection of a significant portion of the published knowledge. However, we think that a piece of data that cannot be properly annotated is of limited use for the community. For instance, a large amount of pharmacological properties is published without the species. Since those properties vary from one species to the other, one cannot easily re-use the value provided. Similarly, a numerical piece of knowledge cannot be used without caution if one does not know the method used to collect it, and the variability attached to it. Currently, the access to the data is only possible through the web interface. Moreover, although the user is able to search the content of the Molecular Pages using various criteria, the result is always presented as one or several Molecular Pages. However, the DopaNet Web Service should be enriched on a steady pace, and specific pieces of data should be served soon. One can envision interfaces providing precise and meaningful responses to queries like "All Kd for the ligand X of all molecules that bind it", under the form of a list of Language .Ka, Kd, Ki, Kp, IC50, but all those quantities can only be analyzed in regards of the knowledge about the various states of the complex, and its conformational transitions. The distributed annotation can cause concerns related to peer-validation and quality control. With the help of Nature Publishing Group, a peer review process has been set-up by the Alliance for Cellular Signaling to survey the edition of its Molecule Pages. Such an infrastructure is currently out of reach of DopaNet. However, we ensure that the maintainers are always recognized experts in the fields, or, for members of the EBI group, work in close relation. In addition, we included as much as possible guidance through the constraints imposed by the Page editing environment. That way, any Molecular Page complies with at least a minimal set of quality rules. Such an approach has already been successful in other areas. One of the most striking example is the Debian operating system project ([The Molecular Pages are maintained in a distributed fashion, with one or several experts in charge of each complex. Such an approach is mandatory for two reasons. Firstly, the knowledge accumulated by the project will soon become much too large to be handled by one individual, or even one team. Secondly, the level of detail and accuracy sought by the resource is such that only experts can fruitfully mine the adequate literature for relevant information. To extract the simple affinity of a receptor for a ligand can be a daunting prospect. Not only that affinity can be expressed by various parameters with different meaning, project , that mOn the contrary of the Molecular Pages, the Neuronal Ontology is currently developed only by the EBI team. Everyone can contribute by sending their suggestions, but for the sake of coherence the final building is centralized.DopaNet Molecular Pages allow to store annotated numerical data about molecular complexes involved in neuronal signaling. Although the Pages are one of the core resources of the DopaNet project, and therefore their focus on the mesotelencephalic dopamine system, the repository should be of widespread utility in the field of Systems Neurobiology. This is also the case of The DopaNet Neuronal Ontology. The resource is in its early stage of development and will benefit much from the feedback of users.All data contained in the DopaNet Molecular Pages may be copied and redistributed freely, under terms derived from the MIT license ..More information about the DopaNet project can be found at the URL DopaNet ontology is available at the URL DopaNet Molecular Pages are available at the URLNLN designed the database DTDs and schemas, wrote the XSL and acted as the final editorial authority on Molecule Pages. MD implemented all the edition and validation software, as well as the user interface, including the servers.


Assessment of the QT interval started to receive increased regulatory attention in the late 1980s.The heightened safety concern was precipitated by repeated reports on torsade de pointes (TdP) and other arrhythmias occurring in patients treated with an antihistamine drug (terfenadine) . ECG meaSimilarly, in early 1990s, attempts to decrease sudden cardiac death by novel antiarrhythmic drugs , have demonstrated that a certain degree of arrhythmia suppression was paralleled by a proarrhythmic effect, translated in 3-fold increase in mortality rate among patients treated with encainide or flecainide [Awareness about the potential risk of drug-induced QT prolongation and subsequent risk of malignant arrhythmias has increased gradually since then and, particularly during the past years, regulatory requirements for short- and long-term safety of any new chemical entities have become more stringent. For example, after CAST, the FDA changed its advice regarding antiarrhythmic drugs and required evidence showing minimally, that a new antiarrhythmic agent did not cause death in patients.th draft document on the matter, clarifying the specific safety issues related to QT/QTc prolongation [The first regulatory guidelines regarding clinical evaluation of the QT/QTc interval prolongation in the context of new drug development were issued in 1997 by the Committee for Proprietary Medicinal Products (CPMP) . Most reongation .The frequency of congenital long QT syndrome (LQTS) is unknown, but appears to be a common cause of sudden and unexplained death in children and young adults. It is much more common than previously thought – possibly as frequent as 1 in 5,000, and may cause 3,000 – 4,000 sudden deaths in children and young adults each year in US . It is pClinically, the diagnosis of LQTS is suggested by the occurrence of syncope, cardiac arrest or sudden death . The diaTorsade de pointes (TdP) tends to appear during exercise  or psychological stress in LQT1, during stress or startle (particularly auditory stimuli) in LQT2 and during rest in LQT3 . StudiesThe maximal QT interval over 24 hours in normal subjects is longer than thought so far (440 ms). Both QT and QTc intervals are longer during sleep. The QT interval and QTc variability reach peak shortly after awakening, which may reflect increased autonomic instability during early waking hours. The time of the peak value corresponds to the period of reported increased vulnerability to ventricular tachycardia and sudden cardiac death. These findings have implications regarding the definition of QT prolongation and its use in predicting arrhythmias and sudden death .At rest, the surface ECG in women displays longer QT interval , lower THowever, most recent data derived from a novel, automated QT-analysis algorithm, indicate that there are also sex differences in the dynamics of the QT interval during exercise and recovery in healthy subjects . Women eIn this context, the currently 20 ms sex difference in the rate-adjusted QT interval, recommended by the regulatory agencies, might need to be revised.It is estimated that more than 50 marketed agents and an equivalent number of drugs under development have been found to block potassium channels, to prolong the QT interval and induce, in some individuals, malignant arrhythmias. TdP is, however, a relatively rare event with a rate of 2–3% for some drugs . Drugs wProlongation of the QT interval on the ECG is caused by increased duration of the action potential (AP) of the ventricular myocytes. Inhibition or activation of the potassium channels in the cells belonging to the different myocardial layers  , interfeKr) channel. Blockage of the channel caused by the human ether-a-go-go-related gene (HERG) protein, the gene encoding for the IKr, has been implicated in many of the drug-induced changes.The potassium channels are of particular importance in drug-related QT changes, most notably the rapid component of the delayed rectifier potassium current , which register on the surface ECG as prolonged QT interval .Kr) in order to achieve a desired antiarrhythmic effect. These types of changes facilitate additional inward Ca++ currents that further prolong the action potential. Consequently, the AP not only fails to repolarize but also depolarizes again, creating characteristics "humps" which, actually are EADs  and thereby delayed repolarization. Certain drugs have the property to block the potassium channels  in o+ or of the K+ channels lead to lengthening of QT interval and EADs which may trigger ventricular extrasystoles (VES). Occurrence of burst-like, repetitive EADs may degenerate in a tachycardia  defects. The TPE interval, as an index of TDR, has been proved to be clinically useful in assessing arrhythmic risk [Results from more recent research (27) suggest that changes in a new variable termed "T-wave peak to T-wave end" interval (TPE) would predict increased risk in subjects with LQT1 and LQT2. These changes would reflect the dynamicity of the transmural dispersion of repolarization (TDR) in clinical setting, in LQTS patients. Increased TPE interval may show to be the electrophysiological substrate for TdP. Modulation of the TPE interval magnitude seems to be a property of the mic risk -31.Drugs with significant effects on repolarization must be identified and their risk quantified in preclinical and clinical development. Risk-benefit assessment of drugs under development, with particular emphasis to their propensity to prolong repolarization should be individualized to their pharmacokinetic and pharmacodynamic profile as well as to their safety characteristics. The following major aspects need to be addressed:• Rigorous assessment of the agent's effects on the QT/QTc interval.• Assessment of the QT/QTc prolongation-related safety risks of the particular drug against its potential benefits.The above-mentioned issues should be taken into account in any of the following circumstances:• Development of a novel agent (with non-antiarrhythmic properties).• A marketed agent for which new dose or route is being developed .• A marketed agent for which a new indication or new target patient population is pursued.• A marketed agent belonging to a chemical or pharmacological class in which any other drug may have been associated with any of the following events: QT/QTc prolongation, TdP or sudden death during postmarketing surveillance.The "thorough QT/QTc study" is about to emerge as the comprehensive "clinical data set" fully complying with current regulatory requirements, as opposed to "non-clinical" testing that may, or may not generate sufficient information considered to preclude risk of QT/QTc prolongation. Judgement is required on a case-to-case basis on whether the "clinical data set" following completed non-clinical testing ,33 is stBeing considered a biomarker of proarrhythmic risk, the QT/QTc interval is the pharmacodynamic (PD) parameter which is explored to assess drug induced changes in heart rate (HR) and ECG parameters as correlated to plasma drug concentrations (PK). The PK/PD analysis implies a standardized collection of blood samples for determination of PK parameters (Cmax, Tmax, AUC) and recording of 12-lead ECGs for measurement and computation of specific ECG parameters (PR, QRS, QT/QTc). All of these measurements can be expected to show exposure-response relationships that enhance comparison of the investigated drug with its comparator (placebo or active), primarily with respect to its safety.plasma concentration-time profiles , the sampling plan for both blood collection and ECG recordings will be spaced to match the known peak plasma concentration (Cmax – for single doses of the formulations) or the attained "steady state" after multiple dosing. Importantly, there can be large interindividual variability in the time to peak concentration with differences in the PK profile (e.g., Tmax, time to Cmax) due to demographics, disease states, etc., compelling to closely spaced samplings to account for these differences.randomised, double-blind and controlled.The study design needs to be adjusted to the individual drug's pharmacokinetics and safety characteristics. Both the crossover and the parallel designs have specific advantages and relative disadvantages that need to be taken into account in the particular case at hand see . HoweverTo quantify the dose-, concentration-, and time-relationships of the drug on the QT/QTc interval in the target population at therapeutic and supra-therapeutic plasma concentrations.Collection of (serious) adverse events such as:• Absolute QT/QTc prolongation: - QTc > 500 ms and/or- QTc > 60 ms increase as compared to baseline• Events suggestive of arrhythmia:- TdP- Cardiac arrest/Sudden death- VT/VF- Syncope- Dizziness- Seizures- PalpitationsSelecting a control for the purpose of demonstrating safety of a product in terms of "no risk for QT/QTc prolongation effect" is inevitably facing the question of whether an active control or a placebo should be used. The basic assumption is however, that the largest time-matched mean (baseline subtracted) difference between the drug and control (placebo or active control) for the QT interval is ≤ 5 ms, with a one-sided 95% CI that excludes an effect at <8 ms.Placebo-controlled trials are still used to demonstrate effectiveness of new drugs and, for circumstance in which no increased risk for patients is foreseen, use of placebo seems appropriate and ethical, provided that the patients are fully informed and that they give written, informed consent -36.At closer scrutiny, use of placebo in the particular case of demonstrating safety of a drug is not, by far, so much ethically charged as usually, as the subjects supposed to receive it are, in fact, exposed to a lesser degree of risk by QT prolongation. On the other hand, the "placebo-induced changes" are a reflection of underlying variability of the QT/QTc, an otherwise a well-known phenomenon. With other words, use of placebo-control in these cases is fully justifiable.Use of an active control, while extensively advocated currently, due to its considerable credibility as compared with placebo, may raise troublesome methodological issues, typical for equivalence trials, such as the rigorous choice of control agent with special emphasis to essay sensitivity, etc.. CommonlThe 5 ms value, as an average threshold for demonstrating non-inferiority of the tested drug versus a comparator, might be a too ambitious cut-off point (i.e., too low). With the technique currently available, this level of accuracy may possibly be attained by some highly skilled analysts, but it might be difficult to be maintained as an average level for an entire group of analysts. A more reasonable and practically attainable average value would be 10 ms. Individual subjects displaying prolongation in excess of 10 ms would, however, need to be given careful scrutiny.These studies are generally performed in normal, healthy, adult volunteers. The subject population should be selected carefully to minimize inter-subjects variations.Restrictive eligibility criteria are recommended in early phase studies (I and II) of compounds known to have APD or QT prolonging effects, with subsequent widening of criteria in later phase studies (II and III).It is estimated that ECGs should be generated in at least 100 volunteers , for NCE with no pre-clinical evidence of QT prolongation , and in The test and the reference products are usually administered to the subjects in the fasting state (overnight fast for at least 10 hours). These subjects should not take any other medication for one week prior to the study or during the study. Identical test conditions must be used for the two group subjects with respect to: foods, fluid intake, physical activity, posture, etc. and, the physical characteristics of the subjects should be standardized  .Clinical studies in later phases of development (phase III) and after market approval (phase IV) are supposed to have enlarged inclusion criteria to encompass female and elderly patients, patients with associated comorbidities and with concomitant treatment. Exposure to the relative new treatment of a heterogeneous population, to mimic the real population anticipated to be the end-user of the drug in the future, is meant to create a "worst case scenario" for drugs that in the pre-clinical and clinical development stages have shown effects on the QT/QTc interval. Establishing with confidence the behaviour of the QT/QTc interval in these patients, while exposed to the peak effect (Cmax/steady state) of the drug, is not only an effective risk management tool but also a highly ethical issue.For NCE with suspected, or known from previous clinical studies, effects on the HR and/or APD, 10 to 20 baseline ECGs are required see Fig. . For ageDuring the run-in period of later phase trials (II-III), at least three baseline ECGs should be recorded .The pattern of ECG sampling should match the planned blood sample collections for PK assessment see Fig. . There wHowever, regardless of the study design, whenever possible, ECGs should be recorded at the same time of the day during both baseline period and after randomisation (during "on-treatment") to minimize the confounding effects of diurnal variations and postprandial effects .For drugs with known metabolite(s), the ECG recordings should cover the prolonged blood sampling for the plasma concentration-time profile of the metabolite see Fig. .Whenever ethically justifiable, for the case of inadvertent over-dosage or metabolic inhibition, it is recommendable that ECGs should be recorded at substantial multiples of the maximum therapeutic exposure, even in excess of the upper bound of the anticipated therapeutic range . Means are computed consequently, from one or three leads.Manual measurement of different ECG parameters is charged with problems of accuracy and reproducibility due to the inter- and intra-observer variability inherent in such highly demanding tasks while, interpretation of ECG tracings is known to vary from one clinician to another .However, ICH-GCP-compliant quality control and quality assurance SOPs, as well as systematic performance analyses applied to the individual analysts/technicians and their output data, employed nowadays in certain core laboratories, ensure the prospective clients of minimized inter- and intra-observer variability regarding the measurements performed and of high level of accuracy of the output results in the range of ± 10 ms, around a selected/agreed "gold standard" .In order to ensure an overall high level of performance within a group of technicians/analysts who perform the factual measurements on ECG tracings, performance analysis applied to the group and each individual member of the group, should be run at six months interval. Deviation in the measurements performed of more than ± 10 ms should be addressed speedily and corrective measures implemented. Such quality-assurance performance analyses may maintain a high level of measurements' homogeneity and ensure a high quality of the data provided.Likewise, ECG tracings as well as summary data are subject to interpretation and reporting by qualified cardiologist(s) .Fig. The beginning of the QRS complex is best determined in a lead with an initial "q" wave – commonly standard lead I or II, and leads aVL, V5 and V6. Sometimes, the "q" wave may be missing  due to its incorporation within the PR interval.Determining the precise end of the T wave may be simple, when a tangent line to the steepest part of the descending portion of the T wave is drawn and the intercept between the tangent and the isoelectric line is indicating the end of T wave. At times, however, the T wave may be obscured by a superimposed U wave or, in the case of sinus tachycardia, by the ensuing P wave, making the positioning of the fiducial point difficult.The U wave deflection is usually minimal or isoelectic in lead aVL. The aVL lead is therefore a useful for QT measurement since the end of the T wave is least likely to be obscured by a U wave.Different repolarization properties among the epicardium, M cells, and endocardium, as well as their interplay, are responsible for various morphologies of the T-wave and the pathologic U-waves. The T-wave is a symbol of the transmural dispersion of repolarization.Several hypotheses have been proposed to explain the genesis of the U-wave, which represents the last repolarization component of the ventricules  however,per se. Clearly, both qualitative and quantitative assessments of the repolarization changes occurring with different degrees of merger between the T and the U-wave are subject to a certain degree of subjectivity of the assessor. Therefore, it is recommendable that TU-wave morphology assessment to be made by qualified cardiologist(s) according to a standardised methodology. Morphology changes of the T and U-wave should be interpreted as warning signs of TdP. Sometimes, a clear demarcation between the two waves is very difficult, exposing to the risk of underestimating the QT interval and, ultimately, to missing the clinical significance of the changes Given the high level of subjectivity inherent in this type of assessments, with considerable discrepancies between two assessors, even when identical data are assessed, an overall, reasonable conclusion on the TU morphology changes can be provided by use of a visual analogue scale see Fig. . The degIncreased dispersion on the QT interval of the electrocardiogram has been proposed as a marker for increased risk of arrhythmias in patients with hypertrophic cardiomyopathy , long QTDespite sophisticated methods of computerised measurements of QT dispersion ,50, the The analysis of repolarization variability is commonly based on methods that evaluate spatial and temporal QT dispersion. Recent experimental studies  in arterThe length of the QT interval varies inversely with heart rate and therefore shortens as the heart rate increases. Due to the known substantial inter-subject variability of the QT/RR interval relation, there is no mathematical formula to fit every individual. A formula that performs well in one healthy individual may not do so in another, resulting in over- or undercorrection of the QT interval.1/2) [1/3) [Several correction formulas exist. The Bazett formula (square root – QTcB = QT/RR1/2) ,56, most1/2) ,58. The 2) [1/3)  is consiA more recent formula is the Framingham linear correction (QTcL = QT + 0.154 × [1 - RR]) known to be derived from a large patient population and thereby to be considered the most rigorous from an epidemiological perspective ,61.α) they demonstrated a large variability of the α exponent (range: 0.233 – 0.485) in 50 healthy subjects. The same parameter in Fridericia's and Bazett's formulas is 0.33 and 0.50 respectively. Malik and colleagues concluded that correction of QT interval by heart rate may be misleading, regardless of the method used.The main limitation in the aforementioned formulas is that each of them attempts to correct for heart rate only, while leaving into play a number of other known confounders . Disappointingly, analysis done on ECGs sampled from periods of stable heart rate provided no better results . AccordiQT/RR regression models ,65 can bReporting of results becomes mostly informative if tabular frequency distribution and frequency histograms are used to display PR, QRS and QTc data (QTcB, QTcF, QTcL) for individuals and/or groups. For the hypothetic example captured in Fig. baseline, mean and mean maximum values for all parameters measured/computed for one group (PR, QRS, QT, QTcB, QTcF and QTcL) and displays the difference (D1) between the mean value of each parameter "on-treatment" and the corresponding mean value at baseline. Given that a D2 value is to be computed for the second group (comparator), their difference (D2 – D1), for all parameters and the resulting p value (Bomferoni adjusted) could be displayed in Risk-benefit assessment with respect to a drug's propensity to prolong the QT/QTc interval entails a careful judgement of the frequency and magnitude of QT changes encountered in the preclinical and/or clinical program and balancing the potential risks against the drug's benefit.The large variability in the prolonged QT/QTc behaviour as to the potential risk for a TdP ensuing, makes this task difficult and requires individual characterisation of a specific drug's effects on repolarization.Amiodarone, for example, is known to prolong repolarization but to cause rarely TdP. Sotalol which prolongs repolarization through the same mechanism of action as Amiodarone (blockade of the IKr channel) causes a more frequent occurrence of TdP .Some agents may cause slight QTc prolongation but when combined with other drugs that inhibit the metabolism of the suspected drug (e.g., terfenadine and cisapride), marked prolongation can occur . A typicIt is estimated that about 40–50% of the cases of drug-induced QT interval prolongation and/or TdP, result from drug-drug interactions with metabolic inhibitors (as in the example of dofetilide-cimetidine) and that only 10% are associated with electrolyte imbalance, some 10% with concurrent use of other QT-prolonging drugs and approximately 10–20% of cases have no obvious risk factors .As a general rule, it is recommended that any prolongation should be considered as a potential toxicity . In thisIdeally, therapy should be individualized on the basis of patient's genotype/phenotype determined through pharmacogenetic studies performed in the early stages of a drug's development and through application of that information while exploring the drug's pharmacokinetic and pharmacodynamic properties, its drug interaction potential as well as when ethnical-based bridging data is generated.While genotyping of individual cases, where prior informed consent is obtained, based on strong suspicion of genetic substrate having caused substantial QT/QTc prolongation is highly recommendable (such as, outliers in phase I-III studies, patients withdrawn from study due to lack of efficacy or due to type A adverse events), large-scale genotyping in early stages of drug development or pre-prescription genotyping are still controversial.Consequently, the clinical and scientific community is facing the need to apply classical "individualizing therapy" approaches  in reducObviously, the most elementary requirement in this respect is that prescribing physicians should fully comply with contraindications regarding co-prescription of interacting drugs and with the recommendation on appropriate monitoring of targeted patients. More specifically, attention should be given to pharmacokinetic and pharmacodynamic factors that constitute important risk factors .Liver and/or renal diseases act as risk factors at pharmacokinetic level. Likewise, a multitude of metabolic inhibitors see , when tePharmacodynamic risk factors include diseases that are associated with QT interval prolongation see .sine qua non condition for preventing SAE in patients known to be treated with QT-prolonging drugs. QT interval should be monitored in these patients: (i) at baseline; (ii) at steady-state post-dose and at each incremental dose; (iii) when there is an inter-current change in level of risk, and (iv) if the patient develops symptoms of tachycardia or impaired cerebral circulation [Obviously, appropriate monitoring is a culation . TreatmeOccurrence of typical AE suggestive of eventual QT-prolongation, should prompt careful investigation of this possibility even in cases where initial QT/QTc assessment has shown to be negative. In such instances, it is recommended that screening for risk factors shall be employed and genotyping performed after receipt of informed consent. Furthermore, consideration should be give to "re-challenge" with the investigational drug under appropriate monitoring conditions, with the aim of obtaining an accurate assessment of the situation at hand as well as for getting useful information on dose- and concentration-response relationship.Compelling evidence has accrued during the past years on the potential of several cardiac and non-cardiac drugs to prolong cardiac repolarization (reflected as prolonged QT on surface ECG) and to predispose to life-threatening arrhythmias.This evidence has a major impact on the risk-benefit ratio of any drug, currently carefully considered from early stages of clinical drug development by pharmaceutical companies, by ethics committees as well as by regulatory agencies.The broad spectrum of risk factors that may interplay in the increased propensity toward malignant arrhythmias of any new chemical entity is just increasing  and adding to the complexity of the problem.This calls for standardized methodologies to deal with the multifaceted aspects that the QT/QTc prolongation poses in practice, meant to ensure that drugs awarded market approval have undergone appropriate quality assurance scrutiny and, where necessary, further post-marketing surveillance is systematically planned and reported on, in a timely manner.The author(s) declare that they have no competing interests.Frequency distribution of TU morphology changes across two groups.Click here for fileTU morphology changes in individual subjects.Click here for fileFrequency distribution of TU morphology changes across two groups.Click here for fileFrequency distribution of the PR/QRS/QTc(B/F/L) data matching PK sampling .Click here for fileSummary of PR/QRS/QTc(B/F/L) data .Click here for fileNormal ranges for the PR/QRS/QTc(B/F/L) data and for the QTc(B/F/L) relative changes to baseline.Click here for fileFrequency distribution of the baseline and on-treatment values pertaining the PR, QRS, QT, QTcB, QTcF and QTcL parameters as well as the D1 difference.Click here for fileSummary of outcome differences between the two groups regarding key ECG parameters.Click here for fileAlert criteria based on ECG findings (measurements) and rational for subject withdrawal from study.Click here for fileCharacteristics of the cross-over and parallel study designs.Click here for fileDisease associated with prolonged QT/QTc interval.Click here for fileAbbreviations (Not mentioned in the text!)Click here for file


An increasing number of researchers have released novel RNA structure analysis and prediction algorithms for comparative approaches to structure prediction. Yet, independent benchmarking of these algorithms is rarely performed as is now common practice for protein-folding, gene-finding and multiple-sequence-alignment algorithms.Here we evaluate a number of RNA folding algorithms using reliable RNA data-sets and compare their relative performance.We conclude that comparative data can enhance structure prediction but structure-prediction-algorithms vary widely in terms of both sensitivity and selectivity across different lengths and homologies. Furthermore, we outline some directions for future research. RNA, once considered a passive carrier of genetic information, is now known to play a more active role in nature. Many recently discovered RNAs are catalytic, for example RNase P which is involved in tRNA maturation and the self-splicing introns involved in mRNA maturation . In addiA fundamental tenet of biology is that a stable tertiary structure is essential for biological function. In the case of RNA the secondary structure (the base-pair set for an RNA molecule) provides a scaffold for the tertiary structure ,10. Yet,O(nm3) in time, and O(nm2) in space, where n is the sequence length and m is the number of sequences). Current implementations, Foldalign [This has motivated plan B, the use of the "Sankoff-Algorithm", an algorithm designed for the simultaneous alignment, folding and inference of a protosequence for a set of homologous structural RNA sequences . The recoldalign ,28, Dynaoldalign  and PMcooldalign , are resThe final approach (plan C) applies when no helpful level of sequence conservation is observed. We may exclude the sequence alignment step, predict secondary structures for each sequence (or sub-group of sequences) separately, and directly align the structures. Because of the nested branching nature of RNA structures, these are adequately represented as trees. The concept of a similarity measurement via edit operations, a standard procedure for string comparisons, has been generalised to trees -33. Tree• the viability of plan A, B, or C given tools available today, and• the relative performance of the tools used within each plan..We shall explicitly not evaluate computational efficiency, which (by necessity) differs widely between the tools. We also do not evaluate user friendliness  except for some remarks in the discussion section. Data-sets, documentation and relevant scripts are freely available from in vivo structure, given only the sequence of bases. Three general considerations apply: (1) The in vivo structure is not only predetermined by the primary structure, but also by cellular components such as chaperones, base modifications, and even by the transcriptional process itself. There are currently no computational tools available that assess these effects. (2) There are 'ribo-switches', whereby two or more functional structures exist for a given sequence [RNA secondary structure inference is the prediction of base-pairs which form the sequence -57. Suchsequence -60. (3) in-vivo structure for each of them, as well as a consensus structure that captures the common, relevant structural aspects. The consensus structure per se does not exist in vivo, and so some mathematical rigour should be applied when working with this notion.The comparative approach to structure inference is initiated from a set of homologous RNA sequences. Attempts are made to infer the A, C, G, U}. An RNA sequence B = b1,...,bn contains n bases, but no structural information. For comparative analysis, we are given the RNA sequences B1,...,Bk. A secondary structure can be associated with each sequence B as a string S over the alphabet {"(",".",")"}, where parentheses in S must be properly nested, and B and S must be compatible: If (si, sj) are matching parentheses, then (bi, bj) must be a legal base-pair. A base-pair is also denoted as bi·bj, si·sj, or simply i·j when the sequence is clear from the context. Both sequences and structures may be padded with a gap symbol "-", in order to align sequences and structures of different lengths. For compatibility of padded sequences and structures, we require that bi = "-" iff si = "-".An RNA sequence is a string over the RNA alphabet {structural alignment is a multiple sequence alignment of the 2 * k sequences, B1, S1,..., Bk, Sk, such that Bi is compatible with Si, and the following consistency criterion is satisfied: For any Si and Sj and any base-pair , we have  ≠ ")" and  ≠ "(", and if  = "(" or  = ")", then . This means that if one partner of a base-pair in Sj is aligned to one partner in Si, their partners must also be aligned to each other  which is the best thermodynamic folding for B that exhibits the base-pairs specified by C, plus additional ones that do not conflict with the former. Refolding can be achieved by RNAfold with option -C (this option is used to constrain the minimum free energy prediction with prior knowledge – such as known base-pairs, unpaired regions, etc). If B and S contain gaps, we remove them before refolding and reintroduce them in the same positions afterwards.A consensus structure exhibits base-pairs shared by the majority of structures under consideration, but has no sequence information associated with it. Each individual structure for a concrete sequence typically has additional base-pairs which are properly nested between those that constitute the consensus. Given a consensus structure Given a consistent structural alignment, it is easy to derive a consensus structure, as we can count majorities at individual positions. If the 5' partner of a base-pair passes the majority threshold, consistency implies that its 3' partner also makes it into the consensus.without structural information, we can approximate a structural alignment by computing Si = refold(Bi, C). We call this structural alignment reconstruction. While all Si will be consistent with C, and with each other as far as the base-pairs of C are concerned, they may be inconsistent for the base-pairs introduced in refolding. This is tolerable, since if we trust the consensus to capture the relevant common structural features, there is no need to require that all members of a family agree upon extra-consensus features.Given a consensus structure and a sequence alignment We note in passing that it seems worthwhile to study the conditions under which consensus derivation and structural alignment reconstruction are mutually inverse operations, but such theoretical issues are outside our present scope.consensus by example: They provide a reference sequence, say B1, with an experimentally proved structure S1, and provide a multiple sequence alignment of B1, S1 and additional sequences B2,..., Bn in the family under consideration. The sequence alignment is chosen to exhibit structural similarities between the reference structure and the other family members, but in general, we do not know the precise model of achieving similarity, nor do we know whether this model has been solved to optimality.While the plans A, B and C we are about to evaluate strive to find a good consensus structure from sequence data, the "truth" available to us comes in a different form. Structural databases only convey a consensus reconstruction.One consequence of this situation would be to conclude that the reference structure is the only reliable anchor point available to us for evaluation. Comparative analysis tools would then be evaluated by the capacity to predict this particular structure by using family information. This would be a meaningful way to proceed, however, the effect of structural homogeneity within a sequence family would go unmeasured, and so would the difficulty or success of exploiting it. We therefore proceed in a different way which we call S1 need not be compatible with any Bi except for i = 1. However, we can still compute Si := refold(Bi, S1) by treating bases as unpaired where they violate compatibility.  What we obtain in this way is a reconstructed structural alignment, which will be consistent to the extent that the reference structure indeed describes the common structural features, and to the extent that the database sequence alignment reflects these. In all our test cases, this alignment was overall consistent, an indicator that the families and their structural features are in fact well defined. From this alignment, we derive a consensus structure as explained above using a threshold p = 0.5, which will serve as the standard of truth in our evaluation.The reference structure One may argue that our approach to reconstruct the truth is somewhat ad-hoc and should be replaced by a more systematic method. However, this is what the tools we evaluate try to achieve, and we should not add one of our own as the standard of truth. Hence, our consensus reconstruction is designed to stay as close as possible to the database information.Results of observations based on the above measures must be interpreted with care. We list a number of caveats that must be kept in mind when proceeding to the subsequent sections.In all tests, one could possibly obtain better predictions by tuning the program's parameters. We felt that it would be inappropriate to do so, since in the evaluation, we know the correct result and could use this knowledge in the tuning, whereas in a true application context, one does not have such guidance. Hence we used the recommended defaults in all cases.In some cases we apply a tool to data where we know that the model structure has features not recognised by the tool. An example is a structure with multiloops or pseudoknots, searched for with a tool that explicitly excludes such structures. We permit such cases, because again, in a true application context one does not know whether the tool is appropriate or not, and it is still of interest to see how close to the correct structure one can get.We take for granted the correctness of structural alignments taken from the literature, and the consensus reconstructed thereof. Should one of the tested algorithms produce a result that is actually better , it may be penalised. Also, we do not consider a large number of data-sets here, it is possible that performance of some algorithms improves on a different selection of data-sets.Our data reflect the state of the art in 2004. Most of the tools tested are very recent, and their authors are still improving them. Hence, not all observations will remain reproducible. In fact, we hope this study helps to obtain better results in the future.B1 with (preferably) an experimentally verified secondary structure S1. Experimental verification of a structure may be from a variety of sources: x-ray crystallography, NMR, enzymatic structure probing or phylogenetic inference. A comparison of phylogenetic with x-ray crystallographic structures has shown the phylogenetic predictions of rRNA to be very reliable (sensitivity > 97%) [We have compiled RNA sequence alignments consisting of up to 11 sequences derived from reliable sources (see table y > 97%) . This daTo avoid results bias, we constructed test alignments, with corresponding phylogenies that, wherever possible, were free of highly similar clades. In addition, we endeavoured to ensure that the reference sequence was central to the phylogeny, or more specifically, not an out group. To meet these requirements, sequences from large data-sets were sorted into high-similarity and medium-similarity groups (with respect to the model sequence), from which maximum-likelihood phylogenies  were conOur data-sets are quite diverse and must for the purposes of this study be considered difficult to analyse in structural terms. The shape of ribosomal RNA is believed to be influenced by interaction with ribosomal proteins. The shape of RNase P shows relatively little sequence and structure conservation, and furthermore, it contains pseudoknots which are generally excluded by prediction algorithms. Transfer RNAs are known to be a hard case for thermodynamic folding, primarily due to the propensity of modified bases which influence structure formation. All tools tested may perform better upon less complex data-sets, but the purpose of this study is not to show how good the algorithms are but to compare relative performance when prediction is difficult.Sensitivity (X) and selectivity (Y) are common measures for determining the accuracy of prediction methods [X and Y for examining RNA secondary structure prediction: methods . Selecti methods  and "pos methods ,65. We uTP is the number of "true positives" (correctly predicted base-pairs), FN is the number of "false negatives" (base-pairs in the reference structure that were not predicted) and FP is the number of "false positives" (in-correctly predicted base-pairs). However, not all FP base-pairs are equally false! We classify FP base-pairs as either inconsistent, contradicting or compatible. Predicted base-pairs which conflict with a base-pair in the reference structure are labelled inconsistent (i.e. i·j is predicted where either i·k and/or h·j are paired in the reference structure (h ≠ i and j ≠ k)). Predicted base-pairs (i·j) which are non-nested with respect to the reference structure are labelled contradicting (i.e. there exists base-pairs k·l in the reference satisfying k <i <l <j). Note that some base-pairs may both contradict and be inconsistent with the reference structure. Predicted base-pairs which are neither true positive, contradicting or inconsistent are labelled compatible and can be considered neutral with respect to algorithm accuracy. Hence these are subtracted in the selectivity evaluation, their number is ξ in the above equation. It is of interest to note that the base-pair metric [dBP(Sref, Spred) is the sum of FN and FP, and hence is different from the measure used here.where r metric ,67 betweMatthews correlation coefficient [A measure combining both selectivity and sensitivity is useful for ranking algorithms. For this we employ the fficient  defined MCC ranges from -1 for extremely inaccurate (TP = TN = 0) to 1 for very accurate predictions (FP - ξ = FN = 0). When comparing RNA structures TN = 0 occurs only in extreme examples, hence MCC generally ranges from 0 to 1. Furthermore, for the specific case of RNA structure comparisons, MCC can be approximated by the arithmetic-mean or geometric-mean of X and Y [ X and Y .The accuracy of the MFE single sequence method has been evaluated elsewhere and was found to have an accuracy of 73% when averaged over many different RNAs and "base-pair slippage" was tolerated in the evaluation . A recenO(n3) in time and O(n2) in memory where n is the sequence length. Both employ the same thermodynamic parameters [Mfold ,72 and Rrameters . Hence, S. cerevisiae tRNA-PHE which the free energy methods favour. Mfold infers 'suboptimal' structures by calculating minimum free energy structures with the restriction that every possible base-pair is forced in a one-by-one fashion. Unique structures are then ranked by energy. Investigating the top two suboptimal structures from Mfold resulted in an overall increase in the range of sensitivity, selectivity and correlation, 22–69%, 20–67% and 0.18–0.68 respectively. The predictions shown here are used to illustrate the potential advantages of using comparative analyses over single sequence methods.The sensitivity, selectivity and correlation of MFE methods (for the four data-sets considered here) ranged from 22–63%, 20–60% and 0.18–0.61 respectively  and a covariation score matrix, augmented with penalties for inconsistent sequences, Bij. A standard trace-back procedure is performed to recover a consensus structure with the optimal sum-of-average-energy-and-covariation-score . The algorithm is remarkably efficient O(N·n2 + n3) in time and O(n2) in memory.RNAalifold ,76 impleThe sensitivity, selectivity and correlation of the RNAalifold predictions ranged from 57–91%, 57–100% and 0.57–0.95 respectively, showing a significant increase in the accuracy measures when compared to the MFE-methods.Pfold implements a "stochastic context free grammar" (SCFG) designed to produce a "prior probability distribution of RNA structures" for an RNA alignment input ,24,77. AThe algorithm is generally accurate and efficient. Hence, the over-all sensitivity, selectivity and correlation of the Pfold predictions ranged from 0–100%, 0–100% and 0.0–1.0, respectively. But removing those points where Pfold predictions were empty structures (LSU rRNA (H & M) and SSU rRNA (M), see figure must decrease when a significant proportion of the true base-pairs are engaged in pseudo-knots.ILM (iterated loop matching) is one of the few comparative RNA folding algorithms which can return pseudo-knotted structures ,78. It uThe inclusion of pseudo-knots prediction vastly increases the number of possible secondary structures, this is why they are generally excluded from exhaustive folding algorithms. In addition, there is a general lack of experimentally derived thermodynamic parameters which include pseudo-knots. ILM is a method still under development, hence the performance may improve once pseudo-knots can be more accurately modelled.O(nm3) in time, and O(nm2) in space for sequence length n and m sequences) to be practical [The Sankoff algorithm is a dynamic programming approach to obtain a common base-pair list with maximal sum of base-pair weights. Basically, this is a merger of sequence alignment and Nussinov   in time (where N is the number of sequences and n is the length of the longest sequence). A simple match-based scoring scheme is used to rank putative conserved structure elements.Foldalign  can be iThe Tool Abuse Caveat generally applies to the tool Foldalign as all of our data-sets contain multi-loops. The use of Foldalign for the prediction of global, multi-looped secondary structures is not recommended-as Foldalign is specifically designed for the location of short regulatory motifs such as IREs  where thi and j of aligned nucleotides (where i indexes positions in sequence 1 and j indexes sequence 2) to be less than M. In addition, Dynalign uses the same method employed by MFold to reduce the conformation space, by limiting the size of internal loops [O(n3M3).Dynalign ,85 is a al loops ,86. The  pairwise foldings we compared all sequences with the reference structure. Due to the computational expense of this algorithm it could only be used to predict tRNA and RNase P structures. Dynalign performed well on the tRNA, medium sequence homology data-set . With this one high-scoring point removed, averaged sensitivity, selectivity and correlation values ranged from 32–54%, 33–54% and 0.32–0.54 respectively. Comparing the performances of MFold and Dynalign showed that MFold performance was always superior on the RNase P data-set, Dynalign however did much better on the shorter and more diverse tRNA sequences. Performance gains could be made by investing more computer time and refolding RNase P with larger ' maximum insert size', which was set to 10 during this study. The use of Dynalign on the RNase P data-sets in this study is therefore a case of tool-abuse, as the parameters recommended by the authors of Dynalign were not used .The current Dynalign implementation is restricted to pair-wise sequence comparisons. Rather than compute all The Carnac algorithm, as mentioned previously, is not strictly an implementation of the Sankoff algorithm. A set of filters are employed through which sets of sequences are passed in a pair-wise fashion ,81,87. SThe Carnac algorithm was remarkably selective at base-pair predictions. However, the sensitivity of the algorithm was generally low, although when evaluated with the correlation coefficient it is comparable to RNAalifold and Pfold. Sensitivity, selectivity and correlation values for Carnac predictions ranged from 45–71%, 92–100% and 0.65–0.82 respectively. The sensitivity of Carnac can be increased by constraining a minimum free energy fold (i.e. with "RNAfold-C") with the Carnac predicted structure, but this cost in terms of selectivity. On average this increased the sensitivity by 22.5, decreased the selectivity by 17.2 and slightly increased the correlation by 0.05.RNAforester ,88 impleWe used the tRNA and RNase P data-sets and generated structure single sequence predictions with RNAfold. All predicted structures were aligned pairwise and a neighbour-joining approach used to cluster and align high similarity sequences and structure profiles. The highest scoring alignment was used to derive a predicted consensus that was evaluated against the consensus tRNA model structures. Sensitivity, selectivity and correlation ranges of consensus structures computed from the highest scoring RNAforester alignments were 29–67%, 27–67% and 0.26–0.66 respectively. It seems likely that much of the inaccuracy of this approach is due to MFE structure prediction, however the structure-clustering approach frequently separates mis-folded MFE predictions from the accurate folds.The MARNA algorithm ,89 proceQij > 1, where , , and pij are pair-probabilities computed using McCaskilPs partition function [Sensitivity, selectivity and correlation values of consensus structures computed from MARNA alignments of MFE structures ranged from 29–52%, 32–84% and 0.30–0.65 respectively. We also tried trimming high entropy base-pairs from the MFE predictions using the bound function . The newWe have evaluated three different strategies for comparative structure prediction, and altogether eight tools (not counting the single sequence methods). The results of which are summarised in figures For well aligned short sequences, both Pfold and RNAalifold generally perform well, PFold performed marginally better than RNAalifold. It is likely that some moderate refinements to RNAalifold would improve accuracy without altering the efficiency, for example, if gaps were not penalised in the free-energy evaluation and a more sophisticated model for scoring mutations was employed, perhaps ribosum matrices  could beCarnac produced highly selective structures for all the test data-sets, which if used to constrain a free energy fold produced sensitive predictions with a cost to selectivity. The consistency of Carnac performance is remarkable, for all the data-sets considered here this heuristic approach performed well. It is however unclear how Carnac will perform on highly diverse data-sets.For advocates of plan C, we have an encouraging message: Both MARNA and RNAforester perform better on the medium similarity data than on high similarity data. This seems paradoxical at first glance, but one must understand that for an approach purely based on predicted structures, high sequence similarity can be a curse rather than a blessing: If sequences are very similar, they may jointly fold into the wrong MFE structure. With more sequence variation, it becomes more likely that at least some family members have good predictions, which by their mutual similarity can be picked out from the rest. This means that especially in the case of low sequence similarity, where nothing else works, plan C, currently the least explored strategy of all, has a certain promise.Finally, let us outline some directions for future research.An implementation of the single sequence pseudoknot algorithms ,43,94 emAgain allowing constrained foldings and alignments would be useful. The further development of "BLAST-like" folding heuristics for this should be a priority, obviously Carnac is a good start. The MARNA approach for producing structurally enhanced multiple alignments produced rather selective results after trimming high-entropy base-pairs from MFE predictions. This suggests that weighting edit-distances with partition-function derived probabilities or entropies will produce reasonable RNA alignments. A consensus structure could then be derived from MFE-structures or from PFold or RNAalifold predictions on the resultant alignment. This approach would effectively decouple the Sankoff algorithm into manageable structure-enhanced-alignment and folding stages.Two further developments are likely to increase the power of plan C. Pure multiple structure alignment  presented in  may leavMore training data is essential for this field to progress, for this homology search tools are essential. Infernal ,97 used PPG carried out the experiments, the analysis and drafted the manuscript. RG suggested comparing comparative structure prediction methods and assisted in the manuscript preparation. All authors read and approved the final manuscript.