Sequencing and characterisation of fliC was performed in the development of a molecular serotyping technique.The FliC sequencing of 106 strains revealed two groups; the g-complex included those exhibiting "g" or "m,t" antigenic factors, and the non-g strains which formed a second more diverse group. Variation in fliC was characterised and sero-specific motifs identified. Furthermore, it was possible to identify differences in certain H antigens that are not detected by traditional serotyping. A rapid short sequencing assay was developed to target serotype-specific sequence motifs in fliC. The assay was evaluated for identification of H1 antigens with a panel of 55 strains.FliC sequences were obtained for more than 100 strains comprising 29 different H1 alleles. Unique pyrosequencing profiles corresponding to the H1 component of the serotype were generated reproducibly for the 23 alleles represented in the evaluation panel. Short read sequence assays can now be used to identify fliC alleles in approximately 97% of the 50 medically most important Salmonella in England and Wales. Capability for high throughput testing and automation give these assays considerable advantages over traditional methods. Salmonella express flagellar (H), polysaccharide (O) and capsular (Vi) antigens which determine strain pathogenicity and therefore variation of these antigens has formed the basis for Salmonella serotyping. The Kauffmann-White scheme, first published in 1929, divides Salmonella into more than 2500 serotypes according to their antigenic formulae. Within these, 46 O antigen groups are recognised by Salmonella serotyping. O antigen synthesis and assembly is encoded by the rfb gene cluster which typically contains 12 open reading frames, and ranges in size between serotypes, from approximately 8 kbp to 23 kbp. The variation of O antigens is not due to individual gene sequence variation, but rather to different sets of genes [fliC (phase 1) and fljB (phase 2) which encode flagellins of different antigenicity. Salmonella serotyping methods recognise 63 distinct phase 1 flagellar antigenic factors and 37 phase 2 flagellar antigenic factors although the latter are not always present. Some antigenic factors, denoted by square brackets in formulae, may be present or absent without affecting serotype designation. Serotyping methods are stable, reproducible and have high typeability, yet there are several drawbacks, particularly the dependence on availability of antisera considering the ethics, cost and quality control measures necessary to maintain such a supply.Salmonella, however it is best used in combination with plasmid profiling and ribotyping for strain discrimination for epidemiological purposes [Salmonella strains by sampling variation in a set of housekeeping genes which precludes antigen encoding genes [et al [et al [FliC fragment restriction patterns using a dual enzyme combination allowed differentiation of flagellar types b, i, d, j, l,v, and z10 but r and e,h nor [f],g,m, [p], g,p, and g,m,s could be separated using this technique [fliC and fljB for serotyping of poultry Salmonella but could not distinguish S. Enteritidis from S. Gallinarum and S. Dublin [15 second-phase antigens has been reported [fliC restriction fragment length polymorphism (RFLP) profiles were not specific enough to differentiate between certain serotypes [Pulsed-field gel electrophoresis (PFGE) ,3 is curpurposes . Other apurposes  and multpurposes  which sang genes . In 1993s [et al  publishe. Dublin . Design reported . Peters erotypes . To datefliC, evidence from antibody binding studies suggests that sequences of ~300 nucleotides of the central variable region of flagellin correlate with serotype [salmonella serotypes or biotypes [Salmonella enterica.For serotype  and diffbiotypes -18. PrevfliC sequences generated in this study and 32 phase 1 flagellin sequences previously published (see Methods section), representing 35 phase 1 flagellar serotypes revealed a clear division of sequences into two groups. Representative sequences are aligned in fliC sequences of this group clustered exclusively with the non-motile strains Gallinarum and Pullorum on the tree  represented here as sequence type Typhimurium_a).Alignment of 106 Salmonella fliC sequences were conserved at their termini and variable in the central region between serotypes [fliC gene containing sero-specific polymorphisms were identified at nucleotide positions 917 – 933 and 739–749 in Cluster I and Cluster II respectively  were known from full sequencing to be identical at the target region.All polymorphisms within the g-complex sequences analysed are displayed in Figure fliC of the g-complex are likely to be involved in specific epitope formation: two amino acid sequence types were observed in 25 fliC-[f],g,m, [p] sequences obtained from Salmonella enterica serovar Enteritidis strains. Twenty-three S. Enteritidis strains demonstrated complete conservation in their DNA sequence (B16, B18, JTCM02 and 20 phage type 4 strains (Enteritidis_b)). The sequence of B17 was congruent with published S. Enteritidis (M84980) (Enteritidis_a), and exhibited a single amino acid (Ser>Gly at 302) substitution compared to sequence type Enteritidis_b. Published S. Othmarschen (U06455) fliC-g,m, [t] sequence inferred the same amino acid sequence as Enteritidis_a but exhibited a silent mutation at the DNA level. As the fliC sequence for these two serotypes was identical it was apparent that the sequence included here represented an S. Othmarschen strain in which the t factor was absent.The following polymorphisms located in S. Gallinarum sequences demonstrated 100% DNA homology to Enteritidis_b except for a SNP encoding a stop codon in M84975. S. Pullorum and S. Gallinarum are non-motile as they do not express flagella. Antisera to the g factor antigen react strongly with induced-motility S. Pullorum culture, indicating that g epitopes are expressed in these cells [S. Pullorum were observed at amino acid position 91 and 323. Molecular identification of S. Pullorum and S. Gallinarum would be of considerable benefit as standard serotyping cannot differentiate these two serotypes.Published se cells . This coFliC-g,q was differentiated from all other g-complex sequences by an Asp>Gly serotype-specific polymorphism observed at position 284 for S. Moscow. A Thr>Ala substitution at residue 304 conferred by a single nucleotide polymorphism (SNP) was identified between sequences of g,m and g,p, congruent with a previous report [fliC sequences of these strains.s report , and forS. Essen fliC-g,m was distinct from other g and m coding sequences by an Asp>Asn substitution at 283. fliC-g,p,s could be differentiated from fliC-g,p by a Thr>Ala substitution at 254. A motif of two amino acids at positions 302 and 307 was common to S. Derby, S. Agona, S. Adelaide, and S. Berta which exhibit phase 1 flagellar antigenic factors "f" and "g". This motif was exclusive to these serotypes. DNA sequence variation at corresponding positions allowed S. Derby and S. Agona to be distinguished from S. Adelaide and S. Berta. FliC-g,z51; and fliC-m,t with fliC-g,m,t each form distinct clusters  meant that there was a choice of regions that could be used for differentiation. Following testing of four possible regions, the region encompassing amino acids 248–250 was selected for use in the final non-g assay. Each serotype had a unique motif at the target region except 4,z23  differed from that published (AF159459) at one nucleotide, conferring amino acid substitution of Thr >Ser at codon 99.Some amino acid sequences were not identical within non-g alleles, including i, r, d, e,h, a and z4,z23 . A previ strains . Six fulFliC sequences of nine S. Heidelberg strains were identical, consistent with the results of a previous report [fliC-r of S. Rubislaw (X04505) differed from S. Heidelberg at three amino acids. The S. Muenchen sequence determined in this study differs in twelve amino acids to the published S. Muenchen (X03395), and differed in 25 amino acids from the S. Duisberg sequence in this study. S. Anatum, S. Newport and S. Saintpaul exhibit factors e,h in their phase 1 flagellar. Amino acid sequence was conserved in two strains of S. Saintpaul but distinct for each serotype due to four amino acid substitutions at codons 192, 213, 238, 356. S. Brandenburg and S. Panama exhibit l,v in the phase 1 antigen, no inferred amino acid differences were detected. FliC-l,v sequences clustered with fliC-l,z13. Z4,z24 is distinct from z4,z23 and z4,z23 sequences varied within the serotype at seven amino acid positions: 235, 237, 239, 242, 253, 351 and 369. The complex mosaic nature of fliC is evident from analysis of amino acid alignment of sequences in particular strains from subgroups in the SARC collection .fliC were selected for the g-group and non-g group to provide unique sequence for as many serotypes as possible, while keeping the assay simple to perform and analyse. Two multiplex PCRs were developed for the production of fliC amplicon of g-complex strains and fliC amplicon of non-g strains. Sero-specific motifs in each amplicon were consequently identified by sequencing-by-synthesis.By comparison of amino acid sequences coding for antigens of the different serotypes, sero-specific motifs were identified. Individual regions of Fifteen sequence types were identified in the 17 bp of nucleotide sequence assayed Figure . Twenty-13 gave the same motif at the target region but could be separated by nucleotide substitution A>G at position 783 conferring a Thr>Ala change.Fourteen sequence types were identified in the 9 bp of nucleotide sequence assayed Figure . Thirty Salmonella phase 1 flagellar antigens was demonstrated through testing on a panel of 55 isolates. The SNP responsible for the antigenic difference between serotypes g,m and g,p was within the target region and so could be differentiated by the assay. The amino acid substitution that separated fliC-g,p,u was also encoded within the sequence assayed. Antigens i, r, c, d, b, e,h, k, a, z41, z, z10, z4,z23, z4z24, g,q, g,m,p, g,p,u, [f],g,t, g,z51 and biotype S. Pullorum gave unique motifs, l,v and l,z13 shared a motif. Some serotypes for which certain factors may be present or absent (denoted by square brackets in antigenic formulae) were not separated from similar serotypes: [f],g,m, [p], g,m and g,m, [p],s; [f],g,m, [p] and g,m, [t]; g, [s],t and g,t although these could be separated by other DNA polymorphisms as discussed. Two motifs were observed for k, each specific to S. Thompson and IIIb. Two motifs were observed for d, specific to S. Duisberg and S. Muenchen / S. Schwarzengrund. Published sequence data for fliC-m,t, from serotypes S. Banana, S. Oranienburg and S. Pensacola were included in assay design. The polymorphic region targeted by the assay is predicted to differentiate m,t sequences from other g-complex antigens, and also differentiate S. Pensacola from S. Banana and S. Oranienberg. Strains exhibiting factors m,t were not available for testing.The stability of the targeted polymorphisms in fliC genes of g-complex strains was observed. Data produced for this study is congruent with a previous report of g-complex sequences [A high level of sequence homology between equences . The genFull gene sequences were distinct for each antigen analysed in this study. Furthermore, analysis of multiple representatives revealed that some antigens were encoded for by multiple sequences. In these cases DNA sequence based methods are more discriminatory than traditional serotyping methods which do not recognise these as distinct antigens.Assays were designed such that an unknown strain could be identified in respect of its phase 1 flagellar antigen in two steps. The specific PCR acted as the first level of identification and the resultant amplicon was used for the pyrosequencing assay. A positive PCR indicated which of two Pyrosequencing assays to apply. Each assay was uniform in that only one mix of pyrosequencing primers and one dispensation order was needed. All the strains tested were successfully amplified by PCR. As some analyses have been performed on unpublished data, exhaustive testing of the assay will be performed to confirm specificity and typeability of all recognised serotypes.Molecular serotyping will incorporate the desirable properties of serology  together with the advantages of DNA analysis (ability to automate, labour saving, serum independent). Antisera production and associated quality control measures would be unnecessary for a DNA sequence based method. Time-consuming flagellar phase reversal to identify both flagellar antigens is not necessary at the genetic level. Other advantages include reduced labour costs, rapid results in comparison to traditional serotyping methods. DNA sequence data is highly portable and easy to interpret. The method described was easily automated by use of the vacuum preparation tool for the DNA strand separation step and could be further automated by use of robotics for PCR set-up. Result output included a pyrogram, raw text and confidence level; automation of data analysis could be achieved by use of a computer script to screen at a set confidence level and cross-check results against a database of recognised motifs.Salmonella strains occurring in England and Wales, the assay can be used now as an economic screen of unknown isolates and alleviate the burden on routine serotyping work. A scheme including the phase 1 flagellar assay and complementary assays for phase 2 flagellar and polysaccharide antigens is currently being piloted and based on incidence data of the top 50 serotypes from 2003, it is anticipated that the scheme will provide a complete molecular serotype for around 80% of isolates and confident prediction of 76% of the remainder.With the capability to identify approximately 97% of phase 1 flagellar antigens from medically important Alternative sero-specific polymorphisms identified in this study could be exploited by similar assays to allow further separation when antigens did not give unique pyrograms.fliC assay to a fljB and rfb assay would allow the full antigenic formulae of Salmonella serotypes to be determined. Common phase 2 flagellar antigens will be selected for sequencing and together with published data will be analysed for sero-specific motifs and a short sequence assay designed with the approach described in this study.The alliance of the et al [Salmonella major serogroups A, B, C2, and D. They based their PCR on the presence/absence of genes or sequence polymorphisms within shared genes. Essentially, only serogroups A and D possess a gene to synthesise tyvelose but serogroup A genes carry an early stop codon and do not produce the sugar itself. Only groups B and C2 possess a gene to synthesise abequose but the sequences are distinct. We have also designed a preliminary pyrosequencing assay to distinguish these serogroups based on amplification and short sequences of these genes (data not shown).In 1993, Luk et al  outlinedIn summary, epitopes are conformational and it is difficult to determine which amino acids would interact from a linear sequence. However, in the g-complex sequences some amino acid changes could be identified as responsible for differences in antigenic factors because variation was minimal. There is no common factor among the non-g antigens and the sequences are much more heterogenous; there are too many substitutions to draw conclusions about epitope specific sequences. Epitope mapping could be used to further investigate epitopes responsible for antigenic specificity.Salmonella Reference Collections A, B and C obtained from the University of Calgary. Multiple isolates of S. Enteritidis phage type 4, and S. Typhimurium phage type DT104 plus a panel of serotyped strains were gratefully received from the Salmonella Reference Laboratory, Health Protection Agency, Colindale .MagNA Pure instrument and Total Nucleic Acid Extraction Kit 1 (Roche, East Sussex). PCR reactions contained 1X PCR buffer, 20 pmoles of FL_START2, 20 pmoles rFSa1 , 1 U TaqfliC gene was performed with an 9700 GeneAmp PCR System (Applied Biosystems, Cheshire): 35 cycles of 95°C for 60 sec, 50°C for 60 sec, 72°C for 30 sec followed by a 7 min final extension at 72°C. PCR products were purified with Qiaquick spin columns (Qiagen Ltd, West Sussex) and quantitated by gel electrophoresis using Ready-to-Run pre-cast gels (Amersham Biosciences, Buckinghamshire). Fifty to one-hundred nanograms of the purified PCR product was used for cycle sequencing, with specific primers .fliC sequences. Some previously published sequences were included  was used to compute a distance matrix from protein sequences and build trees illustrating the relatedness of included . Polymor MOP-UPs  identififliC sequences. Amplicon sizes were approximately 316 bp for g-complex strains, 170 bp – 250 bp, (size varied according to serotype) from non-g strains. The order of nucleotide dispensation was tailored to enable the first two dispensations to act as negative and positive controls.Two multiplex PCRs were designed to amplify polymorphic regions of both g- and non-g complex fliC gene. Fifty microlitres of PCR product was prepared containing 1 U Taq polymerase, 0.25 mM of each dNTP, 4 mM MgCl2. PCR for amplification of g-complex strains used three forward primers: 100 pmol GPYRO-A; 12.5 pmol GPYRO-B; and 12.5 pmol GPYRO-C; and 125 picomoles of reverse biotinylated primer G-REV. PCR for amplification of non-g strains used 14 forward primers (NON-G-PYRO-A, NON-G-PYRO-B etc.) in equal concentrations. Thirteen biotinylated reverse primers (NON-G-REV-A, NON-G-REV-B etc.) were used in equal concentrations. In each 50 μl reaction 125 pmol of mixed forward primer and 125 pmol mixed reverse primer was used. Primer sequences are detailed in A 1 μl loop of cells was boiled in 100 μl of sterile distilled water for 10 min at 95°C. One microlitre of lysate was used for PCR. Two PCRs were run in parallel to amplify fragments of the Thermocycling was performed with an Applied Biosystems 9700 GeneAmp PCR System using a touch-down programme: initial denaturation step of 94°C for 2 min; followed by 17 cycles of 94°C for 20 sec, 66°C (-1°C per cycle) for 30 sec, 72°C for 30 sec; followed by 20 cycles of 94°C for 20 sec, 54°C for 30 sec, 72°C for 30 sec. The excess primers were removed using a filter plate and vacuum system (Genetix Ltd, Hampshire) before visualising the PCR products on the Ready-To-Run agarose system (as previously). Biotinylated single-stranded DNA was immobilized on streptavidin-coated sepharose beads (Amersham Biosciences, Buckinghamshire) with binding buffer. The mixture was agitated at 1400 rpm for 10 min at room temperature. Single stranded DNA bound to beads was isolated from the mixture using a series of wash steps for 5 seconds each in turn, 70% ethanol, 0.2M NaOH and washing buffer. Ninety-six samples were prepared in 2 minutes by automation of strand separation step using a vacuum preparation tool . A combination of pyrosequencing primers was used for each assay; 20 primers for the non-g complex assay, and three for the g-complex assay  into whiSalmonella serotyping and provided strains. CA CM SG TP and JL participated in the design of the study. CA conceived of and coordinated the study. All authors read and approved the final manuscript.CM carried out the sequencing, constructed the multiple alignments and designed the assays. TP carried out the serotyping. TP advised on fliC gene sequences representing 32 H1 alleles. Sequences labelled with _a, _b or _c indicate an H1 allele encoded by multiple sequences . Codon numbering is in reference to the sequence of Typhimurium_a which represents sequenced strain LT2.Amino acid alignment. Amino acid alignment of 106 Click here for filefliC *These primers were also used as pyrosequencing primersPrimers used for PCR and Pyrosequencing. Orientation of the primer is represented by F (forward) or R (reverse) and approximate position is given as nucleotide distance from 5' end of Click here for fileSequences used in this study. Sequences labelled with _a, _b or _c indicate an H1 allele encoded by multiple sequencesClick here for file


Parsing a mental operation into components, characterizing the parallel or serial nature of this flow, and understanding what each process ultimately contributes to response time are fundamental questions in cognitive neuroscience. Here we show how a simple theoretical model leads to an extended set of predictions concerning the distribution of response time and its alteration by simultaneous performance of another task. The model provides a synthesis of psychological refractory period and random-walk models of response time. It merely assumes that a task consists of three consecutive stages—perception, decision based on noisy integration of evidence, and response—and that the perceptual and motor stages can operate simultaneously with stages of another task, while the central decision process constitutes a bottleneck. We designed a number-comparison task that provided a thorough test of the model by allowing independent variations in number notation, numerical distance, response complexity, and temporal asynchrony relative to an interfering probe task of tone discrimination. The results revealed a parsing of the comparison task in which each variable affects only one stage. Numerical distance affects the integration process, which is the only step that cannot proceed in parallel and has a major contribution to response time variability. The other stages, mapping the numeral to an internal quantity and executing the motor response, can be carried out in parallel with another task. Changing the duration of these processes has no significant effect on the variance. The inability to operate two cognitive processes simultaneously - a mental bottleneck - can be explained by a model in which evidence is accumulated stochastically to reach a decision Even the most simple behaviour involves a chain of computations, which link perception, decision making, and action ,2,3. MeaWhen two tasks are presented simultaneously , a delay in the execution of the second task has been systematically observed ,9,10,11.A separate line of psychological research has investigated how the decision to respond is achieved. The decision-making process has been modelled as a noisy integrator that accumulates evidence provided by the sensory system ,23,24,25In the present work, we propose a single assumption that unifies those two lines of research. We postulate that only the integration process establishes a serial bottleneck, while all other stages can proceed in parallel with stages of another task . This moWe designed a behavioural task to test the validity of the model. This number-comparison task involves deciding whether a digit presented on the screen is larger or smaller than 45. Different manipulations of the task render it more difficult, presumably, at different stages of processing. The different task manipulations include notation (whether the number was presented in Arabic digits or in spelled words), distance , and response complexity (whether subjects were asked to tap once or twice to indicate their choice). Previous studies have shown that all of these manipulations change the difficulty of the task: RTs increase when numerical distance decreases and when numbers are presented in spelled words ,29. ThesSubjects were asked to perform a dual task. One of the two tasks was presented visually and involved a number comparison: subjects decided whether a digit presented on the screen was larger or smaller than 45. Hereafter we will refer to it as “number task”. The other was a tone-discrimination task that involved deciding whether the frequency of a single pure tone that was presented for 150 ms was high (880 Hz) or low (440 Hz) (subjects heard both tones repeatedly before the beginning of the experience). Hereafter we will refer to it as “tone task”. Two different populations of subjects performed the task in the two possible orders, tone task followed by number task or vice versa.The number task was our main task of study, and was manipulated using three different factors: notation (whether the number was presented in Arabic digits or in spelled words), distance , and response complexity (whether subjects were asked to tap once or twice to indicate their choice). The tone task was never varied throughout the experiment. The rationale underlying this experimental design is that the tone task is used as a probe to study, through interference experiments, the different stages of processing of the number task. This asymmetry between the two tasks, which might be helpful to keep in mind, was of course not stated to the subjects, who were just asked to attend equally to both tasks.The results section is organized as follows. We first report an analysis of basic measures of central tendency and dispersion. We then address how different manipulations (within the number task or through the interference with the tone task) change the mean RTs and their dispersion. These types of tests allow us to test the additivity of the effects of each factor and, through the interference analysis, whether they affect the perceptual, the central, or the motor stage. A second level of analysis involves a more detailed characterization of the shapes of the distributions of RTs. Fitting the distributions allows us to evaluate the accumulation model of response decision and to relate its components to those identified by their patterns of interference in the first-level analysis.For clarity and as a reference throughout the paper, all the definitions, components of the models, and experimental manipulations are summarized in The first analysis involved studying the effects of the different manipulations of notation, distance, and response complexity on mean RTs and response dispersion on the number task when it came first. Our model predicted that manipulations that affect separate stages should have additive effects on mean RTs, and that only manipulations that affect the central stage should significantly increase response dispersion.For this analysis (and throughout the paper unless otherwise specified) distance, which is the absolute value of the difference between the presented number and 45, was binned in two groups, close (≤12) and far (>12). Central tendency was measured by estimating the mean RT after trimming for outliers, by discarding responses slower than 1,200 ms. Response dispersion was measured by estimating the interquartile range, i.e., the difference between the 75th percentile and 25th percentile of the distribution of RTs. As we expected from several prior experiments ,30, perfInterestingly the effects of the different manipulations on response dispersion did not follow the effects on the mean, indicating that some factors slowed RT but did not significantly increase their dispersion. The distance manipulation resulted in a significant increase of the interquartile range typical of stochastic process, where the dispersion increases with the mean. In contrast, notation and response complexity, while causing an important change in the mean, did not result in a significant increase of the interquartile range B.To fully address whether the number-comparison task involves three separate stages with each experimental factor (distance, notation, and response complexity), a complete “additive factors” experimental design is needed, in which the different factors are crossed and thus all the interactions can be tested. However, such a factorial design, if tested in the double-task experiment, would involve an exceedingly large number of conditions, which would be very difficult to test on a subject by subject basis within a single session. Instead, we ran it as an independent experiment, in which a new group of subjects was asked to perform only the number task.The results of this new experiment, summarized in Taken together with the assumption of our model that only the central stage contributes to response variance, our observations suggest that the numerical distance factor affects the C decision component, while notation and response complexity affect noncentral P or M components.In addition to tests of additivity, a useful experimental technique to address the separable nature of different components and to understand their organization in time, is the interference analysis, in which the task of study (the number-comparison task) is performed together with a probe task (the tone task). The delay in the onset between the two tasks is controlled experimentally, and to achieve a full separation of the three components, the two tasks must be presented in both possible orders . Under tWe begin by describing the mean RT results when the number task  was performed first, and the tone task came second. The PRP model predicts that each of the manipulated variables of notation, distance, and response complexity should have a main effect on the first number-comparison task, but only some of those effects (those that affect P and C components of the first task) should propagate to the RT2, and should do so only at short interstimulus delays (Δ) .To evaluate these predictions, mean RTs were calculated within each condition and each subject, and submitted to ANOVAs with subjects as a random factor and delay and the variable of interest as within-subject factors. The detailed results of those ANOVAs are reported in The ANOVAs on number-comparison RTs (RT1) revealed the expected main effects of number notation , numerical distance (91 ms, slower for close digits than for far digits), and response complexity (175 ms, slower for two-tap responses than for one-tap responses). There was no main effect of Δ, and none of the task effects interacted with delay. These results suggest that, as requested, participants performed the number comparison as task 1 independently of the delay of presentation of the subsequent tone task.Similar ANOVAs on tone-decision RTs (RT2) revealed a main effect of delay, characteristic of the PRP phenomenon. As shown in Crucially, our three experimental factors had differential effects on those two segments of the RT curve. Notation and distance showed both a main effect and an interaction with delay .As a further test, we analysed the data for short delays, within the interference regime (Δ ≤ 350 ms) and long delays (Δ ≥ 600 ms) . For thet-tests, where we did not observe a significant difference either in the short delays or in the long delays  came second. In this case the PRP model predicts that there should be no effect of the manipulated variables of notation, distance, and response complexity on the first tone task; in addition, the RT2 should exhibit a constant increase (independent of delay) when the change affects the M and C components and should change only for large delays when the change affects the P component see . As descThe ANOVAs on the tone task RTs (first task, RT1) revealed no effects on the task manipulation, as predicted by the PRP model because response to task 1 should be independent of the nature of task 2. The ANOVAs on the number-comparison RTs (second task, RT2) again revealed a very significant nonlinear effect of delay characteristic of the PRP effect. In addition, for the distance and response-complexity manipulations, we observed a task effect that did not interact with delay see , typicalt-tests performed for short and long delays. When data were collapsed across all short delays for the distance and motor manipulation, there was a significant effect of both factors (respectively 86 ms and 255 ms). In contrast, there was no significant difference in RT for the number task for the different notations for small delays . In both cases we find that the response is slower when the task is presented first: number task, 756 ms when presented first and 678 ms when presented second; tone task, 720 ms when presented first and 518 ms when presented second. Thus there is a fixed component (independent of delay) of approximately 150 ms, which needs to be added to RT1 to fully explain the data.to, followed by a forced random walk to a threshold T with slope α and diffusion constant σ (to) corresponds to the sum of the P and the M components  was analysed for each task when it was presented first. For the number task we analysed six different cases corresponding to the three different manipulations (Digits 1 Tap, Words 1 Tap, and Digits 2 Taps), and two levels of numerical distance: close distances (≤12) and far distances (>12). For each of these distributions, the histograms of RTs and their cumulative distributions were calculated, and the latter were fitted to a simple model of RTs. The model was based on a fixed onset delay, nstant σ . The fixents see .T can be set to one without loss of generality. For simplicity, we assumed that σ was the same for all six experimental conditions, while α and to could vary . The best-fitting values were determined by exhaustive search using a minimum-squares criterion. The value of 1/α characterizes the integration time , while to captures fixed components that do not contribute to the variance. Thus, our purpose was to test the prediction of our model that the notation and response-complexity manipulations should affect the parameter to while the distance manipulation should affect the parameter α.The applicability of random-walk models to RT data has been widely studied in numerous tasks ,21,22,23to that provided the best fit. We found that the to changes from task to task but does not depend on distance. In contrast, 1/α does not change across tasks but changes with numerical distance (y-intercept at x = 0)  does not differ significantly from zero (p > 0.3) and the value of the intercept differs significantly across tasks (p < 0.001). In contrast, for 1/α the intercept is not significantly different across tasks (p > 0.5) while the slope is significantly different from zero (p < 0.001) Thus, response complexity and notation manipulation affect to, while numerical distance affects 1/α. These results are consistent with the prior analysis, which showed that response complexity and notation manipulations did not significantly affect the interquartile range (another measure of dispersion) while the distance manipulation did significantly change the interquartile range.For a finer-grained analysis, and to test the significance of this phenomenon, we binned the data in 24 different bins based on their distance to the reference 45 used for numerical comparison. For each bin, we calculated the α and distance C. To test x = 0) D. For tHere we try to explain the precise shape of RT2s, by combining, based on the PRP model, the distributions obtained for each task when presented first. If the two tasks were completely sequential, then the resulting distribution would be simply the convolution of the two original distributions. However, the PRP model states that only the C component is sequential, and, thus, because some operations can be done in parallel, the resulting RT2s are shorter than expected from a convolution. The operation performed is not completely trivial and is described step by step in P2 and M1 as free parameters. We found that with these parameters alone, the data could not be fitted . It seemed evident that the problem was that the predicted distributions were shifted in time with respect to the original distributions, and thus we decided to add one parameter, Td, a rigid shift in time of all distributions of RT2 . We then found good fits for the ensemble of distributions  we tried to fit the 20 distributions of RT2  from the distributions of RT1, with P2 and M1. When the number task was second, the parameters are P(Number) and M(Tone). When the tone task was the second, the fit parameters are P(Tone) and M(Number). The obtained values of the square residuals for different parameters were not sufficient to actually calculate precisely each parameter, since the fit was unstable in the P2 − M1 direction (i.e., it did not change much if both parameters were changed but their sum was kept constant), but they were sufficient to calculate their sum (P(Number) + M(Tone) (P(Tone) + M(Number) (P(Tone) + M(Number) (P(Number) + M(Tone) (Each fit provides the parameters heir sum . In agre M(Tone) , left bu(Number) , right. (Number) , left bu M(Tone) , right.to (a fixed delay). As expected from our model, across the different conditions summarized in to is always approximately equal to the sum of the durations of the P and M components, while 1/α is equal to the duration of the C component. This provides further evidence that the process of accumulation of evidence does indeed constitute the characteristic bottleneck (the C component) in dual-task experiments.Finally, the parameters obtained from the interference experiment may be compared to those of the previous fit, which was based on the shape of the distributions of RTs for the first task, and which yielded estimates of 1/α (the time of integration) and We proposed a basic model that relates the organization of parallel and serial components and the process of accumulation of evidence to reach a decision. The model, although simple, results in a wide number of predictions that, as we have shown, hold over a vast variety of manipulations. We show that the perceptual transformation of sensory information into an abstract quantity representation can be carried out in parallel with another task and is a low-variability process (whose variability does not increase with the mean); that the accumulation of evidence establishes a bottleneck and is an intrinsically variable process; and that the execution of the response constitutes yet another parallel, low-variability process. Our data suggest that the integration of evidence in time to reach a decision constitutes the only central process in a simple cognitive task that links perceptions to actions.While dual-task experiments (in which two tasks are presented at variable delays) allow different interpretations, experiments in which one of the two tasks is parametrically manipulated provide a severe test of the PRP model ,13,16. IHere we have tested, within the number-comparison task, three different manipulations, in the two possible orderings of the sequential tasks, thus providing an exhaustive test of the model. Our finding that all manipulations fall reliably within one of the PRP components provides strong evidence of the generality of this phenomenon. In addition, while it had been shown previously that the distribution of dual-task RTs was wider than that predicted by noninterfering processing of the two tasks , preciseA striking result, however, is the duration of the C component, which even in a simple task represents about 70% of the total RT. Considering the simplest version of our task , our results indicate that 180 ms is taken by the sum of P and M components, while a full 550 ms is taken by the C component. Previous event-related potential experiments suggested that it takes approximately 190 ms to identify an Arabic digit and begin to access a quantity representation . The preWhile all the PRP predictions held, the only discrepancy with the model arose from an unexpected slowness of responses to the first task. As predicted, RT1 was independent of the delay. However the mean RT was larger than found previously when subjects performed only the number-comparison task . Even wiHere, as in other PRP experiments, we have designed the tasks in order to maximally separate the inputs and outputs to the system . Under these conditions, as described above, we still find a source of central interference. Moreover we find that the transformation from a word form to an abstract semantic representation does not participate in this central process, nor does the execution of two consecutive and repetitive motor actions. The generality of these findings, however, has obvious bounds. We do not state here that any motor manipulation should result in a change in a parallel component; more complex motor responses, however, might require central supervision and create a bottleneck. Similarly, while we claim that mapping a word form to an abstract number representation can be done in parallel, we do not mean that it would not interfere with any possible stimulus. Finally, under some situations that lead to high automaticity, either through extensive training ,40 or veThere is a vast literature on the analysis of the shape of RT distributions as a source of knowledge about the human information-processing system, and many different models of these distributions have been proposed ,49,50,51A second important type of alternative to our model concerns the nature of the central process. Instead of a unique integrator, there might be a network of interacting integrators with lateral connections, which collectively implement the decision-making process and whose interactions create a functional bottleneck . The exiT. In a more complicated model, the value of the threshold might be changeable. Such a feature might be needed to fit the results of experiments in which one varies the prior probability of a given response or its associated reward (variables that were fixed throughout our experiment). For example, in a go/no-go experiment involving digit comparison, in which the probability of a response was fixed at a controlled probability pgo, it has been shown that pgo affects T, but not the drift rate (α) [Finally, for simplicity our model assumed a constant decision threshold rate (α) . Even inrate (α) . Such adrate (α) ,56.While typically even simple tasks result in highly variable distributions of RTs, under some particular circumstances, including extensive practice, very precise  distributions of RTs can be obtained, e.g., in subjects trained to estimate a fixed duration . It has While we characterized the different processing stages through behavioural observations, it is an essential issue to relate these findings to brain anatomy and physiology. At the single-task level, the neurophysiological bases of simple perceptual decision making have been widely studied in tactile- ,59,60 anIn humans, a similar indicator of accumulated evidence towards a motor decision is provided by scalp recordings of the lateralized readiness potential (LRP) . The LRPIndeed, functional magnetic resonance imaging studies of the comparison task show that intraparietal and precentral cortices are systematically activated and that their activation correlates with the distance between the objects to be compared . This biWhat happens to those physiological decision processes during dual-task performance? At present, we know of no neurophysiological study and only a handful of human physiological studies of the PRP phenomenon. In event-related potentials, when C and P components were manipulated, perceptual manipulation led to a change in the P2 component , while the central manipulation affected the amplitude and the onset of the P3 component . The LRPAltogether, neurophysiological and brain-imaging studies suggest that, beyond an initial perceptual delay of about 200 ms, there begins a process of accumulation of evidence, which involves the joint activation of a distributed network of areas, with partially changing topography as a function of the nature of the task, but with frequent coactivation of parietal and premotor regions. Our results suggest that this accumulation system is responsible for establishing the PRP bottleneck. This bottleneck might occur because the cerebral accumulation system is broadly distributed and largely shared across tasks, and thus must be entirely “mobilized”, at any given moment, by whichever task is currently performed (for a simulation of this process, see ). This nA total of 42 participants, all right-handed, were involved in this study . Sixteen participants (aged 25 y ± 5 y) performed the experiment in which the tone task was presented first, and the other 16 (aged 24 y ± 4 y) performed the experiment in which the number-comparison task was presented first. Ten participants (aged 22 y ± 2 y) performed the numeric task with the addition of the Words 2 Taps condition. Participants were all native French speakers and were remunerated for their participation.Participants were asked to perform two tasks, with the clear instruction that they had to respond accurately and as fast as possible to each of them. The delay in the onset of the two tasks changed randomly from trial to trial from 0 ms (simultaneous presentation) to 1,025 ms. Subjects responded to both tasks with key presses, with the right hand for the number-comparison task and with the left hand for the tone task. In the number-comparison task, a number was flashed in the centre of the screen for 150 ms, and subjects had to respond whether the number was larger or smaller than 45. The presented number ranged between 21 and 69, excluding 45. In different blocks, subjects performed three different versions of the number task. In the first version, the number was presented in Arabic digits and subjects were asked to respond by tapping once over the corresponding key (Digits 1 Tap). In the second version, the number was presented as a written word (in French), and subjects were also asked to respond with a single key press . Finally, in the third version, the number was presented in Arabic digits, but subjects were asked to respond by tapping the corresponding key twice . Within each block, both the numerical distance between the target and 45 and the delay between the presentation of the two stimuli varied randomly, and trials were presented with an intertrial interval that fluctuated between 2,600 and 3,000 ms.In each block, which lasted almost 2 min, subjects performed 40 trials. Before the beginning of each block, subjects saw instructions on the screen, which instructed them what the number task would be for this corresponding block. Subjects practiced one block of each task to get familiar with the task. After this brief training, they performed a total of 18 blocks (six for each version) in an approximately 45-min session.Stimuli were shown on a black-and-white display on a 17-in. monitor with a refresh rate of 60 Hz. Subjects sat 1 m from the screen. Stimuli were always presented in the fovea, and their size was 1° for the Arabic digits and 2.5° for the words. Auditory stimuli were pure tones of 150-ms duration and 440- or 880-Hz frequency. Auditory stimulation was provided through headphones.http://www.r-project.org/, and in all ANOVAs subjects were treated as a random factor. Throughout the paper, RTs for both tasks are, per convention, measured from trial onset, i.e., the onset of the first stimulus.All the analyses described here were done only on correct responses . Since there were two tasks and each task had two possible responses, chance level for this experiment is at 25%. Errors (17%) included errors in either the first or second task and trials in which subjects failed to respond to either of the tasks, or both. One subject was discarded from the analysis because the data clearly revealed that he had not performed the task as required. His RT1 arrived systematically a few hundred milliseconds after the onset of the second task, indicating that he was waiting for both tasks to be presented in order to respond and not, as indicated, responding to both tasks as fast as possible. For similar reasons, for all analyses, trials in which the RTs to the first task were larger than 1,200 ms  were excluded. All the statistics were done using the R software package (to) followed by a forced random walk dV = α · dt + σ · dz and response emission as soon as V reaches a threshold b (see R =T inf[t ≥ 0, V(t) ≥ b], where b is the threshold. This problem (of the first hitting time to an absorbing barrier of a Brownian motion) has been widely studied and can be solved analytically using the Fokker–Planck equation. The probability of hitting threshold for the first time at time t is given by the following equation:RTs were fitted to a model based on a fixed delay onset  × (Distance Far, Distance Close) were fit to a fixed value of Here we describe how RTs for task 2 can be predicted based on the distribution of RTs for both tasks when presented first. Because of the presence of the PRP wait , this operation is not strictly a convolution. Since the method is not trivial and, to our knowledge, it has not been performed elsewhere, we will describe it step by step:1 and R2, the probability of performing the sequence at time T is given byIn a serial sequence of two processes (in which one needs to be finished before the next one starts), each with a probability distribution of RTs given respectively by RThis formula is simply the convolution of the two original distributions.R1*(t) = R1(t + M1). The second modification, because of the nature of the PRP experiment, is that task 2 obviously cannot start until it is presented and thus the onset time is actually given by R1**(t) = max[R1*(t), Δ]. Thus the real distribution of onsets of task 2 is given by the accumulated probability of a shifted R1 up to Δ (which results in a spike at Δ) followed by the tail of R1*(t). The spike becomes more pronounced as the delay is larger, and thus the two tasks become independent.In a PRP experiment, however, the execution of the two tasks is not serial, since there are both serial  and parallel  components. The first difference is that task 2 waits not for the complete execution of task 1 but rather for the completion of the P and C components of task 1 see . Hence, t is given by R2(t). However, within the interference regime , P2 (or part of it) has been executed by the time that the P and C components of the first task (which corresponds to t − M1) are finished (see R2 at t = Δ, but as t increases, part of the P component of task 2 has been carried out and this saturates at t = Δ + P2. Thus the probability of executing task 2 at time t2 given that task 1 has been executed at time t + M1 is given by R2(t2), where t2 = min[(t − Δ), P2] + t. This formula is only valid for t > Δ, but this is not important because in any case R1**(t) = 0 for t < Δ. The important issue, however, is that this transformation depends on t and thus the sum described in R2*(t,T) = R2[T − t2(t)] as the probability of completing task 2 in time T − t given that task 1 has been completed in t + M1.The last consideration has to do with the time it takes to respond to task 2. If Δ is sufficiently large (in the independent regime), the probability of executing task 2 at time shed see . The disThe final formula (adapting Td) to the fit. With the inclusion of the parameter Td, the errors, measured as the mean square residual  were consistently below 0.015 , and we observed a parabolic type of distribution, with a clear minimum . As described in Results, this model was not sufficient to fit the data (note that we are simultaneously fitting a family of 30 curves), so we included a third fixed delay parameter (


The main genomic region controlling the predisposition to type 1 diabetes is the Human Leukocyte Antigens (HLA) class II of the major histocompatibility complex. Association with different HLA types depends also on the studied populations. In our investigation, we tried to measure the phenotypic HLA class II association frequencies of DR3 and/or DR4 antigens, using a serologic method called microlymphocytotoxicity analysis, in diabetic and nondiabetic (ND) subjects originating from the west-Algerian region of Tlemcen. The aim of the present study was to determine which HLA DR antigens represent a high susceptibility to develop the disease in this area. Using a case-control retrospective study design, we randomly recruited ninety-one related subjects, 39 type 1 diabetics and 52 ND as controls, at the Internal Medicine Board of Medical Centre University of Tlemcen.p = 1.000, OR = 0.95), whereas DR4 and DR3DR4 antigens were associated with susceptibility to develop type 1 diabetes . Also, no incidence for DR3 (p = 0.2646) or DR3DR4 (p = 0.0699) antigen frequencies was related to the sex ratio. However, significant differences in HLA DR4 frequencies between type 1 diabetics and ND were found to be related to sex (p = 0.0085).DR3 antigen frequencies were comparable between the type 1 diabetics and the ND subjects and showed no association with the disease (Taken together, our investigation showed that the strongest association with type 1 diabetes was noticed in the presence of HLA DR4 antigens followed by DR3DR4 antigens. This study highlighted a characteristic of Tlemcen population; a history of consanguineous marriages. Association studies between the disease and genetic polymorphisms should be undertaken in a population where consanguinity is more limited to reduce confounding in result interpretations. INS) promoter situated on the chromosome 11p15 [The type 1 diabetes, previously called insulin-dependent diabetes mellitus (IDDM), is the consequence of progressive and selective destruction of pancreatic β cells by an immune-mediated process . It is wme 11p15 ,11. Otheme 11p15  etc. Theme 11p15 ,12. Due However, the different HLA types associated with diabetes depend also on the population. The purpose of our study is to measure HLA DR3 and/or DR4 antigen frequencies and their association in diabetic and nondiabetic subjects originating from the west-Algerian region of Tlemcen. Using a case-control retrospective study design, we attempt to determine which is the greatest HLA DR susceptibility contributing to developing type 1 diabetes. Ninety-one (91) eligible subjects (thirty-nine (39) type 1 diabetics and fifty-two (52) nondiabetics with relatives with type 1 diabetes as controls), were recruited at the Internal Medicine Board of the Medical Centre University of Tlemcen.Table DR4 and DR3DR4 antigens showed an association with susceptibility to type 1 diabetes , in contrast, DR3 antigens showed no association with the disease . It is important to notice that the strongest association is found in DR4 phenotype as indicated in Figure p = 0.0361 and p = 0.5887 respectively). On the contrary, the DR3 molecules frequency is slightly decreased in type 1 diabetic patients compared to the controls and presents no statistically significant difference (p = 1.000). Furthermore, no incidence was related to the sex criteria for the frequencies of DR3 and DR3DR4 molecules (p > 0.05). However, significant differences in HLA DR4 frequencies are linked to the female sex and present a value definitely higher in type 1 diabetic patients compared to those of nondiabetics for the same sex (p < 0.05)  and genFortunately, molecular epidemiology offers the hope of the possibility of preventing the disease in the future, by evaluating the potential factors of risk of developing this pathology . AlthougIt is well established that associations between type 1 diabetes and certain HLA antigens largely facilitate the identification of the subjects having a potential risk to develop the disease. Among the putative HLA molecules known to confer a high susceptibility are DQA1 (*0301)-DQB1 (*0302) (= DQ8), DQA1 (*0501)-DQB1 (*0201) (= DQ2), DRA-DRB1 (*0401) (= DR4) and DRA-DRB1 (*0301) (= DR3) . HoweverIn Algeria, and especially in its western region (Tlemcen), which is known for its history of consanguineous marriage, there is a high rate of consanguinity. This fact could increase the risk of developing type 1 diabetes by favouring the transmission of HLA haplotypes and recessive genes of susceptibility except for HLA antigens that are common in both parents. For these reasons, we were interested in checking whether phenotypically DR3DR4 antigens would involve less risk to develop the disease, in comparison with DR3 or DR4 antigens, knowing the fact that the presence of a probable consanguinity could reduce the frequency of DR3DR4 polymorph phenotype compared to that of DR3 or DR4 phenotype.On a purely comparative basis, similarities seem to be found between our results and those of other investigators ,13,15 wiIn Algeria, very few investigations have been undertaken to study the impact of the genetic background on the risk to develop type 1 diabetes in its population, where an annual average incidence of 4.7 per 100000 has already been listed . In a siIt is certain that screening of HLA class II sub-types and determination of DNA coding sequences allows more precise characterization of ethnic groups, especially, because the same coded molecules can differ by the position of few amino acids. For example, it is well established that DQA1 and DQB1 alleles (sub-types of HLA DQ) code respectively for the alpha and beta chain of the DQ molecule . Thus, tMoreover, it is true that the search of an association with a candidate gene allows a better characterization for most of the frequent multifactorial diseases, because the candidate genes are directly implied in the pathological processes. Today, it is reported that the CTLA-4 (cytotoxic T-lymphocyte antigen-4) allele, localised on the chromosome 2p33, former IDDM12, is largely associated with the susceptibility of numerous common complex diseases, such as the common autoimmune disorders Graves' disease, the autoimmune hypothyroidism and type 1 diabetes . CombineType 1 diabetes, or youth diabetes, is a multifactorial disease occurring on a genetic ground of predisposition and starts under certain environmental conditions. The most effective preventive strategy must be designed at the pre-diabetes stage, since immune and/or genetic markers can easily indicate subjects with high risk before the clinical symptoms. Thus, the genetic analysis of HLA class II associations has allowed a screening of the contributing molecules to the type 1 diabetes development and the selection of subjects, which are likely to contract the disease.In this study, we were confronted with difficulties in interpretation of our results which are mainly due to the presence of some indices of consanguinity in our studied population, showing a non excess of DR3DR4 phenotype compared to the DR3 or DR4 phenotype, and a no link of DR3 phenotype to the disease. This result could be due to an ethnic characteristic of Tlemcen population, a history of consanguineous marriages. Nevertheless, these preliminary results made it possible to answer the asked questions. Thus, the strongest type 1 diabetes association is statistically revealed with phenotypic expression of DR4 followed by DR3DR4 phenotype. Association studies between the disease and genetic polymorphisms should be carried out on the population having more limited consanguinity to reduce confusions in result interpretations.via a questionnaire. The patients' mean (± Standard Deviation) age at clinical onset was 12.28 ± 5.97 years with range of 5 to 22 years and median of 11 years. Subjects who were not first degree related and who were not originating from Tlemcen region were excluded. The use of first-degree relatives eliminates exposures of environmental factors such as food items and viruses since first-degree relatives usually share the same milieu. For execution of the protocol, the informed consent was obtained from all the participating subjects to the designated study.The study was conducted on ninety-one first-degree related subjects (brothers, sisters and siblings), randomly recruited at the Internal Medicine Board of the Medical Centre University of Tlemcen (west-Algeria). The sample included thirty-nine patients with type 1 diabetes , and fifty-two healthy subjects  selected from diabetes relatives as controls. Prior medical histories and personal characteristics were obtained from participants The applied serologic technique lies on the aptitude of the antibodies to recognize allotropic determinants of HLA molecules on cellular surface . This me2 vs. expected χ2 was employed to show significance of frequency differences with the sex ratio. A p value of less than 0.05 was considered statistically significant (two-by-two table: degrees of freedom (df) = 1, chi-square ≥ 3.84) [The comparison of phenotypic frequencies was obtained by using chi-square analysis with Yates' correction or by Fisher's Exact test, whenever appropriate. The application of the observed χ ≥ 3.84) . The ass ≥ 3.84) ,34 (confAM drafted the manuscript, performed statistical analyses and carried out the bibliography research. MS participated by coordinating and orienting the designated study. BA carried out HLA phenotyping and participated in the study design. KM recruited the eligible subjects. All authors read and approved the final version of the manuscript.


Studies of the transcriptional transactivator (Tat), a key regulatory protein of HIV, have yielded insight into the control of eukaryotic transcription Viruses are intracellular pathogens that are subject to intense selective pressures during their ongoing battles within the host. To propagate successfully, they must exploit numerous machineries of the infected cell. Thus, studies of their replicative cycles have yielded fundamental insights into eukaryotic biology. A prime example is the human immunodeficiency virus (HIV), which is a lentivirus that causes the acquired immunodeficiency syndrome (AIDS). Unlike simpler oncoviruses that rely exclusively on host cell machinery, lentiviruses code for additional accessory and regulatory proteins that act as molecular switches at different stages of viral entry and exit from the infected cell. Studying the actions of these viral proteins has yielded understanding of diverse cellular functions such as the innate immunity against retroviruses, control of transcriptional elongation, export of macromolecules from the nucleus to the cytoplasm, and intracellular trafficking of proteins (reviewed in ).The transcriptional transactivator (Tat) is a key regulatory protein of HIV. It is expressed early after the virus integrates into the cell, and stimulates the elongation of RNA polymerase II (RNAPII). This type of transcriptional control had not been previously appreciated; thus, work on Tat established a new paradigm in the field of eukaryotic biology. Moreover, these findings impacted greatly studies of cotranscriptional processing of nascent mRNA. To understand these processes better, we need to start with the basics of transcriptional control.RNAPII is the enzyme that transcribes protein-coding genes in eukaryotic cells. Elegant studies in vitro first suggested that the simple recruitment of RNAPII to transcription units was not sufficient for the copying of genes and cotranscriptional processing of their transcripts. Rather, distinct steps could be defined, which began with the assembly of the preinitiation complex (PIC), promoter clearance, pausing, and arrest, and ended with efficient elongation of transcription (reviewed in ). The ceDrosophila melanogaster  of the RPB1 subunit of RNAPII (reviewed in ). This piewed in ) and humiewed in .The transition to robust elongation depends on the positive transcription elongation factor b (P-TEFb) (reviewed in ). P-TEFbPLoS Biology suggests that Tat and P-TEFb can also recruit TAF-independent transcription complexes to the HIV LTR [Tat is unique among transcriptional activators in eukaryotic cells in that it functions via RNA rather than DNA promoter elements . It bind HIV LTR  , myoblast determination protein (MyoD), and nuclear factor κ-B (NF-κB). The last one is of great interest as it explains how the HIV genome can be transcribed before the synthesis of Tat . CellulaRecently, important aspects of the regulation of P-TEFb have been revealed . Of inteSaccharomyces cerevisiae, there are two candidates for PTEFb, CTDK-1 and Bur1/2. CTDK1-negative but not Bur1/Bur2-negative yeasts still grow, albeit poorly and only on rich media (reviewed in [Caenorhabditis elegans, genetic inactivation of CDK9 or CycT1 and CycT2 resulted in the inhibition of all RNAPII transcription [D. melanogaster, following heat shock, PTEFb is recruited upstream of activated promoters [C. elegans, binds the histidine-rich stretch in CycT1, thus decoying P-TEFb away from RNAPII and blocking the elongation of transcription [How central is P-TEFb to eukaryotic transcription? In cription . Moreoveromoters . Althougromoters . Indeed,romoters , it mighcription .These are exciting findings and suggest a plethora of future experiments, including the genetic inactivation of subunits of P-TEFb and isoforms of HEXIM1 in the mouse. Of special interest are questions as to where to place this mechanism of transcriptional regulation in the hierarchy of competing or complementary processes. What roles do different P-TEFb complexes play in the transcription of specific genes? How central will the regulation of P-TEFb be to cellular growth, proliferation, and differentiation, and what roles will it play in normal development and disease states? As to HIV, how can we use our knowledge of P-TEFb to slow down viral replication and/or to eliminate the state of proviral latency in the host? Obviously, we are only at the beginning of this journey, which promises to change radically our view of eukaryotic transcription.


Serial Analysis of Gene Expression (SAGE) is a method of large-scale gene expression analysis that has the potential to generate the full list of mRNAs present within a cell population at a given time and their frequency. An essential step in SAGE library analysis is the unambiguous assignment of each 14 bp tag to the transcript from which it was derived. This process, called tag-to-gene mapping, represents a step that has to be improved in the analysis of SAGE libraries. Indeed, the existing web sites providing correspondence between tags and transcripts do not concern all species for which numerous EST and cDNA have already been sequenced. web site.This is the reason why we designed and implemented a freely available tool called Identitag for tag identification that can be used in any species for which transcript sequences are available. Identitag is based on a relational database structure in order to allow rapid and easy storage and updating of data and, most importantly, in order to be able to precisely define identification parameters. This structure can be seen like three interconnected modules : the first one stores virtual tags extracted from a given list of transcript sequences, the second stores experimental tags observed in SAGE experiments, and the third allows the annotation of the transcript sequences used for virtual tag extraction. It therefore connects an observed tag to a virtual tag and to the sequence it comes from, and then to its functional annotation when available. Databases made from different species can be connected according to orthology relationship thus allowing the comparison of SAGE libraries between species. We successfully used Identitag to identify tags from our chicken SAGE libraries and for chicken to human SAGE tags interspecies comparison. Identitag sources are freely available on Identitag is a flexible and powerful tool for tag identification in any single species and for interspecies comparison of SAGE libraries. It opens the way to comparative transcriptomic analysis, an emerging branch of biology. In order to characterize the molecular basis underlying self-renewal versus differentiation decision-making process we investigated the transcriptomic changes of various states related to this process, in two model systems : one derived from chicken and the other from human cells. We decided to use Serial Analysis of Gene Expression (SAGE)  to attaia priori regarding the genes to be studied. It can be used with mRNAs derived from cells of any eukaryotic species. SAGE is based on the isolation of a unique sequence tag from each individual transcript and on serial concatenation of several tags into long DNA molecules. Sequencing of concatemer clones reveals individual tags and allows quantification and identification of transcripts. Tag counts are digitally archived and statistically significant comparisons of expression levels can be made between tag counts derived from different populations of cells.Serial Analysis of Gene Expression is a comprehensive method for analyzing transcriptomes  without any An essential step in SAGE library analysis is the unambiguous assignment of each 14 bp tag to the transcript from which it was derived. This process, called tag-to-gene mapping, represents a step that has yet to be completed in the analysis of SAGE libraries. The automated version of this process mostly involves extracting "virtual tags" from sequence databanks : these virtual tags are predictions of the 14 bp sequences that might be produced by a SAGE experiment. The quality of the databanks from which the virtual tags are extracted represents a limiting step in this process. Ideally, the databanks should represent the complete collection of each and every transcript, fully sequenced and annotated. This clearly has yet to be achieved for most species, and therefore one must use the available information that comes mainly from large EST (Expressed Sequence Tags) projects.Arabidopsis thaliana, Bos taurus, Homo sapiens, Medicago truncatula, Meleagris gallopavo, Mus musculus, Pinus taeda, Rattus norvegicus, Sus scrofa, Triticum aestivum and Vitis vinifera). However, this site doesn't include tag to UniGene mapping for several other species for which numerous EST and cDNA have already been sequenced. This is the reason why we designed and implemented a freely available tool for tag identification that can be used in any species for which transcript sequences are available. It can include both complete cDNAs and EST cluster sequences and allow to interrogate the database according to the source of data, to assess the quality of virtual tags derived from different transcript sequences. In this paper we describe the use of this tool for the chicken  where a large EST sequencing effort was completed [Different resources have already been described for tag identification in human and mouse, including the SAGE Map , the SAGompleted .In order to allow rapid and easy storage and updating of data and, most importantly, in order to be able to query the results using sophisticated combinations of criteria, we have designed a relational database structure. We implemented this relational database called Identitag using the freely available MySQL database management system (DBMS) .One important function of Identitag is the possibility to compare the tags obtained in a given species to their counterpart present in another species. This allows a direct comparison of SAGE transcription profiles obtained from different species. To the best of our knowledge, this is the first tool that allows SAGE libraries interspecies comparison : this open the way to comparative transcriptomic analysis.Here we describe the use of Identitag for chicken SAGE tag identification as well as for chicken to human interspecies comparison.. We implemented this database using the freely available and cross-platform Mysql DBMS. A perl script which generates the SQL script creating Identitag tables according to the name of the species considered, is also available on Identitag web site.The Identitag relational schema is presented in Figure query software [Various sources of data presented in Figure software ) and 885software . The firsoftware . The lassoftware  in orderSeveral programs were then used for loading these data into Identitag database. They are written in Perl and Shell and are available on Identitag web site. A Shell script that allows to launch all these programs is also available on this web site : it asks for all information required by these different programs, then launches all programs with adapted arguments and loads the files generated by these programs in the corresponding Identitag tables. The creation and completion of Identitag tables with these programs was successfully tested on SUN, Linux and Mac OS X operating systems.The completed database can be interrogated using SQL (Structured Query Language) and allows a number of tag identification procedures to be launched (see for example the procedure described in results section).When several transcripts identify a same tag, these transcripts are compared with each other using Blastclust  to deterWe connected two Identitag databases from two different species by using orthology relationships between transcripts that identify SAGE tags Figure .We designed a method for identifying transcript sequence pairs that are putatively orthologous between the two species considered. This method .The database for interspecies comparisons of SAGE libraries is composed of two Identitag databases for tag identification in two different species, and connected through the SpeciesA_SpeciesB_Transcript table , together with information that can then be used for assessing the quality of the "virtual" SAGE. The quality of virtual tags depends on the source of the transcript sequence from which it was derived , this is why this information is stored in the Species_Transcript table. Other information can also be used for assessing the quality of the "virtual" SAGE. This information allows one to assess if a transcript sequence is complete and if its orientation correct. This includes the presence or absence of different polyA signals (AATAAA and its most common variant ATTAAA) as well as their localization along the sequence and the length of the possible poly A tail. This length corresponds to the longest poly A stretch among the 50 last base pairs of the transcript sequence : this calculation allows us to take into account the polyA tail even if there are some bases belonging to a cloning vector or sequencing errors at the end of the corresponding transcript sequence. Some of the EST we used were labeled as constructed and sequenced from the 3' region. When available this information was stored in the database. The Species_Transcript table is linked with an NN relationship to the Species_Virtual_Tag table. This table contains virtual tags extracted from the transcript sequences and information about how the tags were extracted. This includes the anchoring enzyme considered (e.g. NlaIII) and the position of its recognition site in the transcript sequence : the Species_Virtual_Tag table stores both the 10 bp sequence immediately downstream of the most 3' anchoring enzyme recognition site and 10 bp sequence downstream of the next-to-last anchoring enzyme recognition site. Indeed, the cutting enzyme may on rare occasions (0,1 %, ) cut notThe second Identitag module allows storage and retrieval of the experimental part of the SAGE experiments. It consists of a table containing information about the construction of SAGE libraries (Species_SAGE_Library table), connected with a table that stores tag sequences from that SAGE library and their corresponding count (Species_Observed_Tag table).The connection between modules 1 and 2 leads to a direct comparison between observed and virtual tags : it is the key to the tag identification procedure. Only perfect matches are allowed at that stage.The third Identitag module allows annotation of transcript sequences from which virtual tags are extracted, via their similarity to known proteins. For this purpose we compare each transcript sequence with the protein sequences from Swissprot and TrEMBL databanks, using the BLASTX algorithm . For thiIdentitag web site provides all scripts necessary to build a such Identitag database and to load all data into this database, for any species from which transcript sequences are available. To do this one need data represented in figure Identitag can be interrogated in various ways, using different identification criteria concerning the quality of the virtual SAGE and the annotation provided. For example, the interrogator can use the following step-by-step procedure Figure , for eac1. If the observed tag matched to no virtual tag, then it is declared unidentified and the identification process is aborted : approximately 25% of the tags belonging to the four chicken SAGE libraries we have studied are unidentified. If this is not the case it means that the observed tag corresponds to a virtual tag extracted from one or more transcript sequence(s) ; the identification process proceeds to the next step.2. If these transcript sequences are not annotated , the observed tag is identified as matching non-annotated EST cluster(s) : 37% of the tags belonging to the four chicken SAGE libraries we studied correspond to non-annotated EST cluster(s). Then we distinguish tags identified as matching one EST cluster (57% of these tags) or more than one EST clusters. For tags corresponding to more than one EST clusters, we compare these sequences to determine whether they are redundant or not. Indeed, there could be redundancy in transcript databanks based on EST clusters due to the threshold for sequence similarity being to high to assign different EST to the same cluster. Therefore, there could be different EST clusters corresponding to the same transcript. This is the reason why we use the procedure described in implementation section to identify sequence redundancy. Among the tag identifications corresponding to more than one EST clusters, 19% correspond to redundant sequences. Finally, 65% of identifications corresponding to non-annotated EST cluster(s) are unambiguous (one corresponding EST cluster or more than one but redundant corresponding EST clusters). If the observed tag does not correspond to previous identification cases, it means that the observed tag corresponds to a virtual tag extracted from one or more annotated transcript sequence(s) and the identification process proceeds to the next step.3. If there is only one annotated transcript sequence from which this virtual tag has been extracted, then the protein name (i.e. the description field corresponding to its Swissprot or TrEMBL accession number) is used to identify this tag and the identification process is stopped : 26% of the tags belonging to the four chicken libraries we studied correspond to this identification case. We call these tags "annotated tags". When this is not the case it means that the observed tag corresponds to a virtual tag extracted from different annotated transcript sequences ; the identification process proceeds to the next step.4. If the different transcript sequences have the same annotation (i.e. the same best BLASTX hit), then the protein name is used as the identification and the identification process halts. This case is mainly due to transcript databank redundancy. Thus by using annotation to identify SAGE tags, we reduce the number of multiple matches. As in previous identification situation we designate the corresponding tags as "annotated tags" because their annotation is not ambiguous : 4% of the tags belonging to the four chicken libraries we studied correspond to this identification case. When this is not the case it means that the observed tag corresponds to a virtual tag extracted from several transcript sequences differently annotated ; the identification process proceeds to the next step.5. The last case corresponds to an observed tag matching to more than one transcript sequences with more than one different annotations. This corresponds to 8% of the tags belonging to the four chicken SAGE libraries we studied. By using annotation to identify SAGE tags, we reduce the number of multiple matches that may occur because of redundancy in transcript databanks. Nevertheless, some of these multiple matches remain. This may occur because there is redundancy in protein databank, thus the redundant transcripts can be differently annotated : this leads to a multiple match. It also appear when redundant transcripts match to the same protein but in different species. Indeed the annotation is provided by a BLASTX against Swissprot and TrEMBL databanks  : thus we could annotate transcripts for which we don't already know the corresponding protein in the species considered, but which is identified in another species. However, this method presents the drawback of causing multiple matches when redundant transcripts match to the same protein in different species. This case is considered as a multiple match because the best BLASTX hits of transcripts identifying the same tag are different. To reduce these two cases of ambiguity, we align the different transcript sequences identifying the same tag (see implementation section) : according to the sequence similarity between them we could avoid these cases of multiple matches. Among the 521 identifications corresponding to more than one transcript sequences with more than one different annotations in our four chicken libraries, 28% could be discarded by this method. The cases of multiple matches remaining occur presumably mainly due to different transcripts that really have the same tag.We provide an example illustrating the repartition of these different situations regarding tag identification in the chicken libraries we studied figure . When weThis process could be pursued further by discriminating between multiple matches, using criteria concerning the quality of the virtual SAGE, e.g. the quality of the transcript sequences (cDNA or EST), the tag position in the transcript sequence (last or next-to-last) and/or the availability of the transcript sequence end.One can also consider a process for tag identification based only on high quality tag identifications. For example, one could obtain an identification based solely on cDNA sequences, or only using tags appearing at the last position. One can also use any logical combination of the above criteria.In order to directly compare SAGE libraries performed in chicken (4 libraries performed in our lab until now) with those performed in human ), 1190 have a human orthologue as previously defined. Therefore the corresponding tags can now be translated into their human counterpart and thus SAGE libraries from two different species can be compared.We have designed and implemented a tool allowing the identification of SAGE tags, based on a relational database. This structure allows to use Identitag in two different ways.First one can precisely choose identification criteria and obtain only the tag identifications provided by using these criteria. One can specify different criteria and thus determine the quality of the identification : e.g. identification generated from EST clusters or mRNA sequences, from last or next-to-last tag, presence of the 3' end of the transcript sequence that could be inferred through the presence of a 3' label or a poly A tail and/or signal. One can also specify different criteria allowing the quality of the annotation to be controlled, e.g. quality of the similarity between transcript and protein sequences through BLAST parameters, quality of the protein sequence used to annotate the transcript via the databank from which the protein originated (Swissprot or TrEMBL) and its species (an annotation with a protein from the same species than that we consider is more accurate than with a protein from another species). All these criteria can be combined allowing the investigator to perform sophisticated interrogations of the database. To the best of our knowledge it is the first tool that allows the user to precisely adjust the identification parameters depending upon its needs.The second way to use Identitag is to ask for all identifications available, for example for a tag of interest, and how these identifications have been generated : it is then possible to consider all these identifications and to further choose among the different identifications if necessary.. Identitag can therefore be used to build a tag-to-gene mapping procedure in any species, using a flat file containing transcript sequences and a BLASTX file results as input of these programs.These two different ways of using Identitag can be used for any species for which transcript sequences are available. Identitag is an open source tool, the programs necessary to build and run the database are available on the Identitag web site Identitag was successfully used for tag-to-gene mapping in chicken. It played a key role for allowing biological interpretation of the SAGE libraries obtained from normal chicken erythroid progenitor cells and allowed us to better understand the changes underlying the self-renewal versus differentiation-making process in these cells . Among tThe next step will be to compare gene expression patterns between our chicken and human model systems, in order to study the possible conservation of the molecular basis of self-renewal during evolution. Comparisons of gene expression between two organisms have recently been initiated with DNA arrays ,20). But. But20])Identitag is a flexible and powerful tool for tag identification in any single species and for interspecies comparison of SAGE libraries. It opens the way to comparative transcriptomic analysis, an emerging branch of biology.Project name: Identitag• Project home page: • Operating system(s): SUN, Linux, Mac OS X• Programming languages: Perl, Bourne Shell, MySQL• License: GNU GPL• CK participated to the design of Identitag, implemented Identitag, and participated to the biological validation of Identitag with SAGE libraries. FD constructed the first two SAGE libraries with which Identitag was tested and participated to the biological validation of Identitag with these data. LD and DM brought their expertise in the orthology area, in order to design the orthology relationship. OG supervised this work. All authors participated in the writing of the manuscript, read and approved the final manuscript.


The objective of this randomized prospective study was to compare the efficacy of 50 mcg vaginal misoprostol and 3 mg dinoprostone, administered every nine hours for a maximum of three doses, for elective induction of labor in a specific cohort of nulliparous women with an unfavorable cervix and more than 40 weeks of gestation.One hundred and sixty-three pregnant women with more than 285 days of gestation were recruited and analyzed. The main outcome measures were time from induction to delivery and incidence of vaginal delivery within 12 and 24 hours. Admission rate to the neonatal intensive care unit within 24 hours post delivery was a secondary outcome.The induction-delivery interval was significantly lower in the misoprostol group than in the dinoprostone group (11.9 h vs. 15.5 h, p < 0.001). With misoprostol, more women delivered within 12 hours (57.5% vs. 32.5%, p < 0.01) and 24 hours (98.7% vs. 91.4%, p < 0.05), spontaneous rupture of the membranes occurred more frequently (38.8% vs. 20.5%, p < 0.05), there was less need for oxytocin augmentation (65.8% vs. 81.5%, p < 0.05) and fewer additional doses were required (7.5% vs. 22%, p < 0.05). Although not statistically significant, a lower Caesarean section (CS) rate was observed with misoprostol (7.5% vs. 13.3%, p > 0.05) but with the disadvantage of higher abnormal fetal heart rate (FHR) tracings (22.5% vs. 12%, p > 0.05). From the misoprostol group more neonates were admitted to the intensive neonatal unit, than from the dinoprostone group (13.5% vs. 4.8%, p > 0.05). One woman had an unexplained stillbirth following the administration of one dose of dinoprostone.Vaginal misoprostol, compared with dinoprostone in the regimens used, is more effective in elective inductions of labor beyond 40 weeks of gestation. Nevertheless, this is at the expense of more abnormal FHR tracings and more admissions to the neonatal unit, indicating that the faster approach is not necessarily the better approach to childbirth. Induction of labor is carried out for maternal and fetal indications. One of the most common indications is prolonged pregnancy . Recent 2) and misoprostol (PGE1), are widely used in "induction of labor" practice for ripening the cervix and stimulating uterine contractions in order to achieve vaginal delivery. Although dinoprostone has been approved by the FDA for cervical ripening in women at or near term, misoprostol is not currently approved for such use by the FDA, although it has the advantages of lower cost, no need for refrigeration and probably higher efficacy.Prostaglandin analogues, dinoprostone  with that of vaginal dinoprostone (3 mg) when both are administered at an interval of nine hours between repeated doses in a well-homogenized cohort of full term pregnancies (nulliparous women with an unfavorable cervix and without pregnancy complications).th day of gestation. A sequence from a computerized random number generator was used for the allocation of patients to each group. The vaginal administration of prostaglandins was performed by one of the resident doctors on duty, who was not involved in managing these women in labor or delivery. The study was double blind, since the patients were not aware of which type of medication was used, and the deliveries were then performed by two gynecologists blinded to the induction regimen utilized.Between March 1, 2001 and July 16, 2003, 163 women were recruited for the study: 80 women in the misoprostol group and 83 women in the dinoprostone group. All of the women were recruited at Ioannina University Hospital, a tertiary referral center for high-risk pregnancies, with about 1600 deliveries a year. The Ethics Committee of the University of Ioannina approved the study and all participants gave their written informed consent after they had been made aware of the purpose of the study. Although the main indication was prolonged pregnancy, some of the inductions were performed at the patient's request after consultation at 40 weeks of gestation,  and only if they had not delivered by the 285Inclusion criteria were: 1) age>18 years old 2) nulliparity, 3) accurate dating of gestation, including crown rump length (CRL) measurements in the first trimester of pregnancy, 4) singleton viable pregnancy, 5) gestational age ≥ 285 days, 6) cephalic presentation, 7) unfavorable cervical status defined as a Bishop score (BS) of ≤5, 8) intact membranes, 9) reactive non-stress test (NST). Exclusion criteria were: 1) known contraindications to receiving prostaglandins, 2) placenta previa, 3) prior uterine surgery and 4) any antenatal complications.GA was estimated by ultrasound biometry (via CRL measurements in the first trimester of pregnancy) in cases where there were more than 3 days difference from that obtained from the last menstrual period (LMP) . UterineA NST to ensure the well-being of the fetus was performed for each patient at the time of recruitment and admission to the hospital (at least 285 days of gestation) and one hour before the application of the prostaglandin. After the reassessment of the cervical BS, either 50 mcg misoprostol, or 3 mg dinoprostone was administered in the posterior vaginal fornix at 23:00 hours. The NST was repeated (duration of two hours) after 1 h and 5 h. If the woman was in active labor, the membranes spontaneously ruptured or the FHR not reassuring, the patient was transferred to the labor room. Otherwise, a second BS evaluation was carried out the next morning at 08:00 am (after 9 hours). If the cervix was favorable, (BS ≥ 5), the patient was admitted to the labor ward where oxytocin augmentation was carried out if the uterine contractions were unsatisfactory and amniotomy was performed when appropriate. If the cervix was still unfavorable, a second dose of misoprostol or dinoprostone was given and the same evaluation steps as described above were followed. After a total of 18 h had elapsed, non-responders were given a third dose of prostaglandin. When the third dose was insufficient for initiating spontaneous labor, a trial of labor was offered with oxytocin infusion and if no progress was achieved within 6 hours , the patient underwent a CS.The outcome measures were divided into "obstetrical" and "neonatal". The primary outcome measures were time from induction to delivery and incidence of vaginal delivery within 12 and 24 hours; the secondary outcomes were the CS rate, the need for oxytocin augmentation, the incidence of meconium stained amniotic fluid, the incidence of uterine tachysystole, abnormal FHR tracings, maternal morbidity, the admission to neonatal intensive care within 24 hours and neonatal arterial cord ph, base deficit.Statistical analysis was performed using SPSS version 11 software. The Chi square test and Fisher's exact test were used to analyze nominal variables in the form of frequency tables. Normally distributed (Kolmogorov-Smirnov Test with Lilliefors correction) metric variables were tested by the T-test for independent samples, while non-normally distributed metric variables were analyzed by the Mann-Whitney U test. All tests were two-tailed with a confidence level of 95% (p < 0.05). Values are expressed as mean ± standard error (SEM).The two groups were comparable in terms of patients' age (28.1 years vs.27.5, p > 0.05) and indication for induction  in the misoprostol and dinoprostone groups, respectively. Gestational age (286 days, range:285–292) and the preinduction BS (2.7 ± 0.1) in the misoprostol group were also comparable to the dinoprostone group (286 days, range:285–293) and (2.9 ± 0.1), respectively.The induction-delivery interval was significantly shorter (11.9 h vs. 15.6 h, p < 0.001) in the misoprostol group, with even less need for a second or third dose (7.5% vs. 22%, p < 0.05) compared to dinoprostone. With misoprostol, more women delivered within 12 h (57.5% vs. 32.5%, p < 0.01) and almost all of the women delivered within 24 h (98.8% vs. 91.6%, p < 0.05). In addition, spontaneous rupture of the membranes occurred more often after the administration of misoprostol (p < 0.05) and there was a reduced need for oxytocin augmentation in labor: 65.8% vs. 80.7% with dinoprostone (p < 0.05). However, uterine tachysystole (p < 0.05)) and meconium stained amniotic fluid (p > 0.05) occurred more often in the misoprostol group as did abnormal heart rate tracing (22.5% vs.12%, p > 0.05) , or needed neonatal resuscitation (11.4% vs. 9.9%, p > 0.05) but none of the babies had birth asphyxia . The meaA 28-year-old woman at 41 weeks of gestation had an unexplained stillbirth after receiving a single dose of dinoprostone. Seven hours later she had a cardiotocogram without abnormal FHR patterns and regular contractions of the uterus were evident. We decided to move her to the labor ward and within half an hour of entry, no cardiac activity of the fetus was found. During these 30 minutes FHR monitoring had been discontinued, as it was not included in the study design. We decided to let her attempt vaginal delivery. An amniotomy was performed and the amniotic fluid was found to be clear and a vaginal delivery was achieved within 6 hours. Direct examination of the fetus, the placenta and the umbilical cord (UC) showed only a thin UC with excess twisting around its axis. The anatomopathology examination of the fetus revealed no abnormality except a microscopically decreased Wharton's jelly.Nowadays, induction of labor is more widely used than ever before ,25. ReceTo the best of our knowledge, the present study is the only one that compares misoprostol and dinoprostone in such well-homogenized groups. All of the women were nulliparous with intact membranes and at more than forty weeks' gestation with no antenatal complications and all had an unfavorable cervix. In these carefully selected patients, misoprostol at the dose used not only shortened the time between induction and delivery (11.9 vs. 15.6 h), but it also was significantly more effective than dinoprostone. The positive point was that this result was achieved with a very low CS rate even in the dinoprostone group, (7.5%, and 13.3%), respectively. A difference of 5% in favor of misoprostol, although not statistically significant, might have clinical importance in terms of patient health and cost effectiveness. Although in the recent large meta-analysis . In addiEven though misoprostol improves the kinetics of labor during induction in a more efficient way than dinoprostone, concerns persist with respect to intrapartum fetal "wellbeing". In order to avoid uterine hyperstimulation and abnormal FHR tracings, we used for first time in the literature, a 9 h interval between the prostaglandin doses. Although we indeed achieved a low rate of uterine hyperstimulation syndrome (2.5% with misoprostol and 1.2% with dinoprostone, respectively), we still noticed a trend towards a high rate of abnormal FHR tracings during induction with misoprostol. Our findings, in accordance with the previous Cochrane metanalysis [Attempting an explanation to the aforementioned side effects of misoprostol use and taking into account other reports ,31,32, iIt still has to be mentioned that in many of our participants, the vertex was not engaged in the pelvic inlet on the day of admittance and this should have been included as an independent risk factor in the initial study design. The exact cause of the stillbirth in the dinoprostone group remains unclear, emphasizing thus, the need for continuous FHR monitoring during labor induction if regular uterine contractions persist ,36.To conclude, 50 mcg misoprostol at a 9 h interval is more highly effective in promoting cervical ripening and in inducing labor, compared to dinoprostone. However, certain aspects concerning fetal well being during labor induction remain questionable. Larger prospective studies comparing elective induction to expectant management after a completed 40-week gestation (on the basis of early ultrasound biometry) might reveal a subgroup of women, such as nulliparous with an unfavorable cervix, who might benefit from an elective induction, preferably with a 25 mcg misoprostol initial dose.E.P: conceived of the study, participated in the sequence alignment, performed the statistical analysis and drafted the manuscript.N.P: conceived of the study, and performed the labor inductionsA.D: performed the neonatal examination and follow upS.A: performed the neonatal examination and participated in the neonatal data analysisC.V: was the midwife involved in women allocation, medications preparation and labour data registrationT.S: conceived of the study and data analysisE.P: conceived of the study and coordinated the studyK.Z: conceived of the study, performed the labor inductions and coordinated the study