This study examined the use of the Folstein Mini Mental Status Exam (MMSE) and the Clock Drawing Test (CDT) in predicting retrospective reports of driving problems among the elderly. The utility of existing scoring systems for the CDT was also examined.T-test, correlation, and regression procedures were used to analyze the data.Archival chart records of 325 patients of a geriatric outpatient clinic were reviewed, of which 162 had CDT results . Both CDT and MMSE scores were significantly worse among non-drivers than individuals who were currently or recently driving. Among current or recent drivers, scores on both instruments correlated significantly with the total number of reported accidents or near misses, although the magnitude of the respective correlations was small. Only MMSE scores, however, significantly predicted whether or not any accidents or near misses were reported at all. Neither MMSE nor CDT scores predicted unique variance in the regressions.The overall results suggest that both the MMSE and CDT have limited utility as potential indicators of driving problems in the elderly. The demonstrated predictive power for these instruments appears to be redundant, such that both appear to assess general cognitive function versus more specific abilities. Furthermore, the lack of robust prediction suggests that neither are sufficient to serve as stand-alone instruments on which to solely base decisions of driving capacity. Rather, individuals who evidence impairment should be provided a more thorough and comprehensive assessment than can be obtained through screening tools. Assessment of cognitive function pertaining to capacity for safe and independent living among elderly patients is a central responsibility of many geriatric medical clinics and service agencies. Specific concerns pertaining to judgments of driving capacity are also befalling upon the medical profession in primary care settings . To aid The MMSE is a widely used cognitive screening tool, due to its brevity, ease of administration, and relative breadth . NumerouIn addition to the MMSE, results on the CDT are often used in clinical settings to inform clinical impressions pertaining to whether or not patients are impaired to such an extent that they should not be driving . AlthougDespite this apparent widespread use, there appears to be a dearth of research addressing the validity of the CDT for detecting driving impairment. Although a small number of studies exist that suggest CDT scores may relate to driving problems, the size of this literature base coupled with methodological concerns indicate a need for further research. For example, one study  examinedAdditional evidence for the potential utility of the CDT in predicting driving behaviors is provided in an examination of neurophysiologic phenomena related to caregiver reports of driving impairment in 79 individuals with Alzheimer's disease . Single A pilot study examining the comparability of simulated driving tests in predicting actual driving problems also suggested that CDT scores may be significant predictors . A smallGiven the typically low rate of follow-up for patients referred for more formal driving assessments, it would be beneficial to further investigate the relations between scores on the CDT and reports of actual driving problems. Furthermore, the predictive power of the CDT alone and in conjunction with other assessment tools in predicting reported driving problems has yet to be fully assessed. Additionally, previous studies examining CDT scores and driving behaviors have employed markedly small sample sizes, warranting future research with greater numbers of participants. Finally, previous studies differ in terms of what, if any, scoring systems were used to score the clock drawings. Thus, further investigation of the comparability of different scoring systems is needed.To address these concerns, this study explored the relations of patient scores on the CDT and MMSE to patient or family reports of driving problems. In so doing, the utility and comparability of three scoring systems for the CDT that are commonly used by researchers and practitioners, namely the Shulman et al. , SunderlExploratory analyses also were conducted to examine the predictive utility of the CDT and MMSE in predicting whether driving problems, namely accidents or near misses, were reported. Further analyses examined whether linear relationships existed between CDT and MMSE scores and the reported number of such incidents. Finally, regression tests examined whether the CDT and MMSE uniquely predicted the number of reported incidents.IRB approval was obtained for the study, and data was collected from archival records of patients seen over a 10-year period at a geriatric assessment center of a general teaching hospital in the Midwest. The center operated as a full-service outpatient clinic, where new patient assessments included a full medical and psychosocial history. This history included patients' and collateral others' reports of driving behaviors within the past year, including whether patients were currently driving or had recently stopped driving within the past year, and number of driving accidents or near misses. The data was often collected during the initial intake assessment, when both the patient and available family members or caregivers were interviewed by a geriatrician, social worker, and/or a nurse specialist. In addition, the MMSE and CDT were typically administered to patients to assess cognitive functioning.Chart records did not clarify whether the reported driving problems were acknowledged by the patient or caregiver, nor the extent to which any discrepancies existed, but rather only reported the number of incidents. The content of the incidents was also not always documented, but examples that were provided typically included crashes or minor accidents for which the patients were at fault. Nevertheless, despite the subjectivity inherent to such reports, it was the intent of these authors to remain true to the figures documented in the patient charts. Indeed, given that medical professionals typically must rely to some extent on subjective reports of patients or caregivers during intake evaluations to inform initial judgments about patient safety, it was decided that incorporation of such data in the present study would nonetheless be useful.SD = 6.67), and ranging from 58 to 99 years of age. As is typical of many outpatient geriatric populations, there was a range in type and severity of presenting concerns, with some patients reporting relatively few problems and others evidencing diagnoses of vascular dementia, Alzheimer's disease, or depression in addition to other health concerns. Of these, concerns due to cognitive function predominated; approximately 60% of the patient sample was referred to the clinic for evaluation of memory loss, cognitive decline, or dementia. MMSE data was available for 311 patients; of these, 159 also had CDT data sufficient for analysis. Of the 162 charts that had CDT data, only 3 did not also have MMSE data.Data was obtained from charts of 325 patients, including 162 original clock drawings that were scored according to the systems provided by Shulman et al. , and WolThe raters' corresponding CDT scores for each scoring system correlated above 0.70, suggesting adequate inter-rater correspondence. The corresponding scores for each scoring system were then averaged to create three composite scores for each clock drawing, one for each scoring system. Descriptive data pertaining to scores for the overall sample on the MMSE and CDT is provided in Table t-tests were conducted to examine whether CDT scores and MMSE scores differed between individuals who had been currently or recently driving, versus those who had not been reported to be driving for a more extensive time period. In each case, current and recent drivers evidenced better scores on all of the cognitive measures than individuals who had not been driving. Results for these analyses are provided in Table Initial exploratory t-tests were incorporated to examine whether CDT and MMSE scores differed among individuals for whom driving problems had been reported, versus those with none. Drivers with reported problems evidenced significantly lower MMSE scores, but no significant differences were obtained for CDT scores. Nevertheless, the trends for the overall mean differences on CDT scores, although small, were in the same direction as the findings for the MMSE. Specifically, in every case the CDT scores for each scoring system were worse for drivers with reported problems than those with none. Overall, these results suggest that the presence of driving problems may have been reflective of greater levels of cognitive impairment, although the overall differences reflected in CDT scores were nonetheless very small in magnitude. These results are detailed in Table Further analyses examined whether CDT or MMSE scores predicted the presence of reported driving problems among individuals who had been current or recent drivers. Patients who had not been driving for a longer period of time were excluded from the analyses, since no driving problems would have been reported as a function of not driving. Specifically, n of the resultant cases is included for each cell.Next, the linear relations for both CDT and MMSE scores in predicted the number of reported problem incidents were examined. Specifically, correlation coefficients were calculated separately for number of reported accidents or near misses, and scores on the CDT and MMSE. Patients who had not been currently or recently driving were excluded from the analysis, since no problems would have been reported if they had not been driving. The number of reported incidents correlated significantly and positively with the level of cognitive impairment as measured by MMSE and CDT scores. Additionally, each of the CDT scoring systems appeared to evidence similar predictive utility, as they correlated highly (above 0.80). Means, standard deviations, and correlations for these variables are provided in Table Finally, hierarchical regression analyses examined whether MMSE or CDT scores uniquely predicted number of reported accidents or near misses. The non-significant R-squared change term in the second step of each regression indicates that neither the MMSE nor set of CDT scores predicted significant incremental variance. Thus, it appears that the variance in reported accidents or near misses predicted by the MMSE and CDT was redundant. Regression results are provided in Table n-sizes within each cell may have limited statistical power.The results of this study suggest that both the MMSE and the CDT appear to have only limited utility in predicting retrospective reports of driving problems among elderly drivers. The finding that MMSE and CDT scores were worse among patients who had not been currently or recently driving may be due to a number of factors, including the possibility that some individuals may have never driven at all before. Nevertheless, it appears likely that many of these individuals probably had been driving in the past, but may have since stopped due to problems related to cognitive impairment. This assertion is supported by the finding that individuals who had been currently or recently driving at the time of the assessment, and who had lower MMSE scores, were more likely to have had reports of accidents or near misses. Although similar mean tests with the CDT were not significant, it is notable that the direction of the obtained differences for each scoring system of the CDT was consistent with the findings of the MMSE. Furthermore, the relatively modest More robust findings were obtained, however, for the correlations examining number of reported accidents or near misses to CDT and MMSE scores. Among individuals who had been currently or recently driving at the time of assessment, greater levels of cognitive impairment as evidenced by MMSE and CDT scores also predicted greater numbers of reported accidents or near misses. This finding held regardless of which CDT scoring system was incorporated, suggesting that each may have equal utility.Finally, the results of the regression analyses appear to indicate that the predictive power of the CDT and MMSE are somewhat redundant, since neither added significant incremental variance to prediction. Although it is possible that the regressions may have had limited power to detect significant incremental differences due to the relatively small sample sizes, in each case the increment to R-squared was small nonetheless. Thus, it appears that both the MMSE and CDT served as gross assessments of general cognitive function, versus more specific cognitive capacities, in predicting reported numbers of accidents or near misses.Although the current results appear to suggest limited predictive utility for the MMSE and CDT in predicting driving problems, an additional cautionary note is in order. The significant predictive power for each instrument as demonstrated by the magnitudes of the correlation coefficients was nevertheless small. Furthermore, significant predictive utility was not obtained for every test in the current research. Additionally, the use of a retrospective design does not necessarily allow for definitive conclusions about predicting instances of future driving problems. Thus, although poor CDT or MMSE scores appear to indicate greater potential for driving problems, the current data do not support the use of the CDT or MMSE alone in making definitive decisions pertaining to driving competence. Rather, the empirical findings of the current research appear to best support the use of the CDT and MMSE solely as their originally intended purpose as screening tools. Thus, scores evidencing impairment on either of these instruments may indicate a need for driver caution, followed by more comprehensive and extensive assessment of driving capacity on which to base decisions regarding safety. As such, the role and utility of these instruments in predicting driving problems may be more fully understood through future research that incorporates a prospective design, along with a more comprehensive assessment of specific and relevant cognitive skills (like psychomotor speed or executive function) and objective assessment of driving abilities (such as can be obtained through simulated or practice driving situations).The author(s) declare that they have no competing interests.ND, AG, and JM conceived of the study purpose and design. ND, EB, and MM collected, entered, and analyzed the data. ND conducted the literature review and critique, and drafted the manuscript. AG, JM, EB, and MM provided comments on the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


Great apes are threatened with extinction, but precise information about the distribution and size of most populations is currently lacking. We conducted orangutan nest counts in the Malaysian state of Sabah (North Borneo), using a combination of ground and helicopter surveys, and provided a way to estimate the current distribution and size of the populations living throughout the entire state. We show that the number of nests detected during aerial surveys is directly related to the estimated true animal density and that a helicopter is an efficient tool to provide robust estimates of orangutan numbers. Our results reveal that with a total estimated population size of about 11,000 individuals, Sabah is one of the main strongholds for orangutans in North Borneo. More than 60% of orangutans living in the state occur outside protected areas, in production forests that have been through several rounds of logging extraction and are still exploited for timber. The role of exploited forests clearly merits further investigation for orangutan conservation in Sabah. A new aerial method for surveying orangutan densities provides robust estimates of their number and could be used for large- scale surveying of great ape populations in Asia and Africa Pongo abelii in Sumatra and Pongo pygmaeus in Borneo, are threatened with extinction in the near future [The two orangutan species, r future ,2. A prer future . Densitir future ,5. In orr future . In addir future .The latest estimates available for orangutan populations in the Malaysian state of Sabah (North Borneo) range from 20,000  to less 2R = 0.86, n = 13, p < 0.001), by the second observer (2R = 0.70, n = 13, p < 0.001), by both observers (2R = 0.58, n = 26, p < 0.001), and with the average value obtained for both observers at each site (2R = 0.83, n = 13, p < 0.001).Ground densities estimated with Distance 3.5 and aerial densities predicted with our model are given in We recorded 2,708 orangutan nests during ground surveys  and 6,936 nests from the helicopter . The size of the sampling areas ranged from 0.001% to 1% (ground survey) and from 1.8% to 16.9% (helicopter survey, assuming an average strip width of 300 m) of the total size of each forest surveyed .Our surveys confirmed that orangutans were patchily distributed throughout their range in Sabah , occurri2 locally) were identified in the semi-inundated lowland forests of Kinabatangan (population 13) and Segama floodplains (population 16), Kulamba (population 12), and Tabin (population 14). Most of these forests were highly disturbed, fragmented, and located at the edge of newly established oil palm plantations.The highest nest abundances were recorded in lowland forests below 300 m asl, although we recorded a few nests as high as 1,300 m asl, which appeared to be the upper altitudinal limit for the species in Sabah. The highest orangutan densities  than in areas where more conventional practices were implemented : Mann–Whitney U test, U = 5.5, p = 0.03. Hunting pressure was low in all these forests  yielded higher orangutan densities in old exploited areas and in areas that were exploited under sustainable logging practices  were present in Sabah at the time of our surveys . Two majAerial surveys are widely used for estimating animal abundance and population trends in open and semi-open landscapes . In SabaNest detectability from the helicopter depends on observers and canopy structure. Ideally, specific models for deriving nest densities from aerial indexes (number of nests detected per kilometer of flight) should be designed for different human observation skills and for different habitat types. However, observer bias can be avoided if the same team of skilled people conducts the entire survey. The second source of bias could be overcome with the design of several habitat-specific models. Before these types of models are designed, ground-truthing must be conducted in different habitat types in order to validate a baseline model and to determine habitat-specific correction factors when necessary.Nest parameters used for obtaining the final orangutan density estimates (nest decay rate, daily rate of nest construction) are a major source of inaccuracy in aerial and ground nest surveys , and theP. p. morio subspecies [Our survey shows that there are currently about 11,000 orangutans present in Sabah, making the state the main stronghold for the bspecies . Howeverbspecies . This debspecies .P. p. morio found in Borneo (population 16).The current network of protected areas in Sabah harbors about 4,000 orangutans, representing about 40% of the total number found in the state. About 60% of the total number of orangutans survives in commercial forest reserves subjected to timber extraction, and these forests harbor the largest unfragmented population of the subspecies The impacts of forest exploitation on ape abundance and ecology depend on several factors, such as (1) the forest types that existed initially and the quality of the regrowth forest , (2) typOur results tend to indicate that the mosaic of habitats found in the semi-inundated mixed dipterocarp forests that were originally occurring in the floodplains of east Sabah could potentially still harbor a significant number of animals following high disturbance levels (populations 12, 13, and 14). However, we can assume that the very high orangutan densities documented in some of the areas located close to oil palm plantations partly result from the influx of newcomers following recent land conversion to agriculture ,30. We cLess diverse habitats (dry lowland dipterocarp forests) located in the interior of the state appear to maintain fewer orangutans, particularly following conventional, nonsustainable logging practices (populations 15 and 16). In the extensive tracts of dry lowland dipterocarp forests exploited for timber (populations 15 and 16), our data suggest that, when hunting pressure is low, orangutan abundance is directly related to the degree of logging and associated damage. For these two populations, the highest orangutan densities were identified in Deramakot, a commercial forest reserve (part of population 15) implementing sustainable logging practices , suggestP.p. morio are not necessarily valid for other Bornean orangutan subspecies and for the Sumatran species [Possible inter- and intraspecific differences in general ecology and feeding behavior of orangutans may also influence population responses to habitat disturbances , and the species ,33,34,35All great ape species require large forest areas to survive. An ecological network combining protected areas with seminatural landscape elements and production forests could be seen as an option to conserve biodiversity, while also providing opportunities for the sustainable use of natural resources ,37. HoweFinally, aerial nest surveys may also be of use in Africa, although it may be difficult to detect nests of African great apes from a helicopter because they tend to be lower in the canopy and it may be impossible to distinguish between gorilla and chimpanzee nests in those areas where the two species are sympatric .2 in the northern portion of the island of Borneo. It is one of the 13 states in the federation of Malaysia. Approximately half of the total land mass is covered with forests (Sabah covers about 76,000 km forests . Commerc forests .Macaranga sp. (crown shape and color easily distinguishable from other tree species), some emergent trees; (3) recently exploited forests (timber extraction was conducted less than 15 y ago): logging roads not entirely colonized by pioneer tree species; few emergent trees; (4): active exploitation: logging activities were ongoing at the time of the survey.All major forest blocks in Sabah were identified from 1:50,000 vegetation maps, and these were divided into 16 different blocks. For each block, we determined a systematic stratified sampling using equidistant parallel line transects, the location of the first line being randomly selected . BecauseFrom the back seats, two observers looked for orangutan nests from either side of the helicopter. All visible nests were recorded. It was impossible to estimate the impact of nest age on nest detection, and the observers acknowledged that a few days-old fresh nests (still green in color) and nests at their latest stages of decay (just a few branches visible) were difficult to detect in the canopy. These nest categories are likely to have been underdetected. The two observers indicated all sightings to a nest recorder seated between them. The nest recorder noted the number of nests detected by the observers per each 30-s period. All crew members were in constant radio contact during the flights. After the flight, data collected by the copilot and the nest recorder were matched in order to determine the location of all sightings along the aerial line transect precisely. The same team of observers conducted all aerial surveys in order to avoid the observer bias.For technical reasons, it was impossible to fit external devices to the helicopter to estimate the distance of the nests to the aerial transects. This prevented us from determining the detection function from our data alone . TrailinBecause the proportion of the actual nest population existing in the forest that was detected from the helicopter was unknown, it was impossible to directly estimate nest densities from our aerial results . We thusth percentile). Heaping was assessed from histograms, and data were grouped where necessary [Nest densities and their variances were estimated by ground line transects using distance sampling ,12. A seecessary ,14. The ecessary . The adeecessary . Finallyecessary . Resultsecessary .D^ was a linear function of both the logarithm of the aerial index AI and the observer effect obs, plus their interaction, in order to include possible differences between observers. We weighted the general regression by the estimated variances of ground nest densities, thus giving a greater emphasis to precise density estimates. The least squares method was used for model fitting by incorporating weights 1/σ^i)log(D^where σ^i)log, and X was the matrix of covariates:where N26(0,Σ), where Σwas a 26 × 26matrix with σ2 · diag(var(logD^i))in the diagonal and zeroes elsewhere.βwas a 4 × 1 vector of parameters to be estimated, and ɛ was a 26 × 1 vector of errors with multivariate normal distribution D^ rewritten using the quantities log (D^)w = W · log(D^), wX = W · X, and ɛw = W · ɛ, with W = diag(σ^−1i)log(D^asTo simplify, (2) was w has a more familiar distribution N26(0, σ2·I26), allowing the use of linear regression tools to estimate model parameters via least square theory. We used the backward model selection procedure [p value and greater than a 10% cutoff were then removed one by one, and each new model was retested until all p values of the remaining covariates were less than the cutoff value. We assessed the goodness of fit of the best model by computing the coefficient of determination 2R. The best model supported by the data considered only the aerial index effect  withUnlike ɛ, ɛrocedure  to selec0,AI recorded during helicopter flights, asUsing this model (5), we predicted an orangutan nest density from any new aerial index values, . This mowithX, the matrix defined above, once the observer effect had been removed, s2 the residual mean square up to a constant that was an estimate of σ2, and t23,0.025 the appropriate two-sided t-distribution percentile [and rcentile . Followircentile , this inwhereandA numerical application gaveThese intervals are shown in t-test, n = 5, t = −1.738, p = 0.157; 95% confidence interval of the difference: −110 to 25; ratio between ground and aerial nest densities = 0.94). This result showed that nest detectability was similar in forests that had been exploited for timber in Sabah and in Kinabatangan. Thus, we used the baseline model without any correction for all recent and old exploited forests of the state. Exploited swamp forests had a very open canopy, and predicted aerial nest densities were higher than estimated ground densities, although the difference was not significant . However, in order to not overestimate the final densities, we applied a correction factor of 0.54 to aerial indexes obtained in two areas of extensive exploited swamp forests (parts of populations 12 and 14). In primary lowland dipterocarp forest, the predicted aerial nest density was lower than the estimated ground density in the only site that was tested . Aerial indexes obtained for Danum (part of population 16), the only site of primary lowland forest with a significant orangutan population assessed during our survey, were multiplied by a correction factor of 1.5.Model (5) was obtained with results from the old and recently exploited semi-inundated mixed lowland dipterocarp forests of Kinabatangan. We tested its validity by comparing nest densities predicted from aerial data and estimated from ground line transects at several sites. We found no significant differences for five sites of old and recently exploited dry lowland dipterocarp forests . This interval was then back-transformed to obtain a confidence interval for D^whereThe numerical application gavewithThe results of the ground and aerial surveys were processed with a geographic information system , using a combination of administrative maps and satellite images. When necessary, we stratified each forest block according to (1) disturbance type: no disturbance, old or recently exploited forests, ongoing exploitation; (2) altitude: lowland, below 500 m above sea level (asl); upper land, 500–1,000 m asl; lower mountain, 1,000–1,500 m asl; mountain, above 1,500 m asl; and (3) habitat type: swamp forests, semi-inundated mixed lowland dipterocarp forests, dry lowland dipterocarp forests. We then determined the percentage of habitat actually occupied by orangutans as the ratio between the total length of aerial transects and the length flown over areas with no visible orangutan nests (large areas with no trees, such as grasslands, large forest gaps, rivers, and oxbow lakes). This percentage was applied to the total size of each forest block determined from maps in order to estimate the final size of “habitat occupied by orangutans.” We then multiplied the estimated orangutan densities by the estimated size of orangutan habitat occupation to obtain overall population estimates.A confidence interval for the population estimate was computed via parametric bootstrapping for the whole population in Sabah . We assuOver a 2-y period (2002–2003), ground surveys  and aerial surveys (72 “man days”) were conducted in all major forests of the state . Recce w


A high frequency of childhood abuse has often been reported in adult psychiatric patients. The present survey explores the relationship between psychiatric diagnoses and positive and negative life events during childhood and adulthood in psychiatric samples.A total of 192 patients with diagnoses of alcohol-related disorders (n = 45), schizophrenic disorders (n = 52), affective disorders (n = 54), and personality disorders (n = 41) completed a 42-item self-rating scale (Traumatic Antecedents Questionnaire, TAQ). The TAQ assesses personal positive experiences (competence and safety) and negative experiences  during four developmental periods, beginning from early childhood to adulthood. Patients were recruited from four Psychiatric hospitals in Germany, Switzerland, and Romania; 63 subjects without any history of mental illness served as controls.The amount of positive experiences did not differ significantly among groups, except for safety scores that were lower in patients with personality disorders as compared to the other groups. On the other side, negative experiences appeared more frequently in patients than in controls. Emotional neglect and abuse were reported in patients more frequently than physical and sexual abuse, with negative experiences encountered more often in late childhood and adolescence than in early childhood. The patients with alcohol-related and personality disorders reported more negative events than the ones with schizophrenic and affective disorders.The present findings add evidence to the relationship between retrospectively reported childhood experiences and psychiatric diagnoses, and emphasize the fact that a) emotional neglect and abuse are the most prominent negative experiences, b) adolescence is a more 'sensitive' period for negative experiences as compared to early childhood, and c) a high amount of reported emotional and physical abuse occurs in patients with alcohol-related and personality disorders respectively. It is difficult to assess the impact of childhood traumatic events on the psychiatric disorders in adulthood, as neither prospective research studies, nor experimental approaches are possible. Nevertheless, an increasing number of retrospective reports suggest that psychiatric disorders may be related to childhood psychological traumas such as neglect, physical or emotional abuse -6. In paAny conclusion to such reports, however, must be drawn by taking into consideration that the validity of childhood memories, particularly in psychiatric patients, may be questioned, as the range of childhood traumas indexed in these studies is generally limited, and often only childhood sexual abuse is targeted. Moreover, the observed relationships are correlational in nature, and do not justify the conclusion that childhood trauma favors the development of psychiatric disorders. Antecedents of developing psychopathology may also provoke certain parental behavior. Also, a third variable, such as social conditions, may have caused both childhood abuse and later pathological development. Another notable finding is that the prevalence rates of antecedent traumatic events vary considerably across studies. This may be due to different definitions of abuse which include more detailed  or more The present study sets out to evaluate reported positive and negative life events from early childhood to adulthood in psychiatric patients. We addressed some of the above-mentioned problems by examining abuse histories across a range of several psychiatric diagnoses within a controlled cross-national design. We sought to examine whether (a) negative life experiences are positively associated with psychiatric diagnoses in adulthood, and (b) early childhood and adolescence were 'sensitive periods', that is, whether psychiatric diagnoses were more closely related to negative experience in these developmental periods.The present study includes a German/Swiss and a Romanian psychiatric group, in order to determine whether reports vary between cultural backgrounds.Patients were recruited from four Psychiatric Hospitals within two different cultural settings, Switzerland/Southern Germany versus the Moldavia region in Romania: the Center for Psychiatry Reichenau and the Center for Psychiatry Weissenau in Germany, the Psychiatric Hospital Münsterlingen in Switzerland, and the Psychiatric Hospital "Socola", Jassy in Romania. A total of 192 psychiatric inpatients (98 German and 94 Romanian psychiatric patients, range 18–78 years) filled in the questionnaire. Sixty-three control subjects without any history of psychiatric diagnosis were recruited from the clinical staff and the university employees (Konstanz in Germany, Jassy in Romania) as controls (38 Germans and 25 Romanians). The control subjects have been simply inquired whether they had any stationary hospitalization in the psychiatry; no further assessments have been done. After a full explanation of the study, written informed consent was obtained from all subjects.By considering the clinician-made diagnoses which were written down from the medical files available in the psychiatric clinics the patients were recruited from, the patients were distributed in four diagnostic groups: alcohol-related disorders (n = 45), schizophrenic disorders (n = 52), affective disorders (n = 54), and personality disorders (n = 41). At all psychiatric clinics in Germany/Switzerland and Romania the diagnoses were made according to the ICD-10 criteria. Within our patient groups, the following lifetime mental disorders were assessed by using the ICD-10: alcohol-related disorders , schizophrenic disorders (paranoid schizophrenia, schizoaffective disorder, and undifferentiated schizophrenia), affective disorders (bipolar depressive disorders, recurrent depressive disorder, cyclothymia, and dysthymia), and personality disorders . A few patients within our sample were diagnosed with comorbid symptoms: 4 patients with affective disorders had symptoms of substance abuse and 7 of them had anxiety symptoms; also, within the schizophrenic disorders group, 2 patients had symptoms of alcohol abuse and 6 had depressive symptoms. There were also patients who received two diagnoses: one of which was a personality disorder . In these cases, we considered the other diagnosis for the distribution into the diagnostic groups.Table Life experiences were assessed with the Traumatic Antecedents Questionnaire (TAQ) . The TAQComparisons of demographic data were made with analysis of variance (ANOVA) and with two-tailed unpaired t-tests for continuous variables. Chi-square analysis was used to compare nominal data. The differences between groups were evaluated individually for each TAQ scale by repeated-measures ANOVA with the cultural background (German/Swiss versus Romanian), psychiatric status , and gender  as between-subjects factors, and developmental period (4 periods) as within-subjects factor. The probability level for rejecting the null hypothesis was set at P < 0.05. Post-hoc comparisons were carried out to evaluate main effects and interactions using Bonferroni/Dunn tests. A principal components analysis was also applied to the entire sample in order to identify those factors, which could account for individual variability across the eleven scales of the TAQ. The principal components were derived by using varimax rotation to orthogonalize solutions.competence did not differ between diagnostic groups [F(4,198) = 0.8, n.s] or cultural samples [F(1,198) = 0.1, n.s]. A main effect of developmental period [F(3,594) = 25.7, P < 0.001] was explained by the increase of competence from early childhood to adolescence (P < 0.05), and by the decrease of competence in adulthood as compared to adolescence (P < 0.05).Table safety subscale than any of the other groups [F(4,215) = 4.5, P < 0.01]. Post hoc tests showed that patients with personality disorders (P < 0.001) and those with affective disorders (P < 0.01) reported less such experiences as compared to the controls. The reported level of safety increased through adolescence [F(3,645) = 11.1, P < 0.001], but the interaction of the developmental period with the psychiatric status revealed a decrease in safety accounts from the age of 13–18 years towards adulthood in all patient groups [F(12,645) = 2.8, P < 0.001].For both cultural samples, patients with personality disorders reported lower values on the Table neglect, the psychiatric patients reported higher rates than the controls [F(4,214) = 5.7, P < 0.001], the post hoc tests revealing that all patient groups reported more such experiences as compared to the controls: patients with personality disorders (P < 0.001), alcohol-related disorders (P < 0.05), schizophrenic disorders (P < 0.05), and affective disorders (P < 0.05). There was an increase of the amount of reported neglect experiences across developmental periods [F(3,642) = 91.5, P < 0.001]. Across developmental periods there were significant effects of the psychiatric status [F(12,642) = 3.2, P < 0.001]: the post hoc tests showed that patients with personality disorders (P < 0.001) and with alcohol-related disorders (P < 0.01) reported a highly significant increase of the amount of neglect experiences across developmental periods as compared to the controls  = 6.4, P < 0.05]. Romanian patients, particularly those with schizophrenic disorders, reported a higher incidence of neglect experiences than their German counterparts (P < 0.01), as revealed by the interaction between the psychiatric status and cultural background [F(4,214) = 5.6, P < 0.001]. As indicated by the interaction between the developmental period and the cultural background, the mean scores of neglect experiences were higher in the Romanian sample as compared to the German/Swiss one for the earliest (0–6 years) period [F(3,642) = 5.3, P < 0.001].Patients, particularly those with alcohol-related disorders, personality disorders, and affective disorders reported more often separation experiences than controls [F(4,227) = 3.3, P < 0.01, P < 0.01 for post-hocs]. Mean scores on separation increased with age, and were highest in adulthood [F(3,681) = 103.0, P < 0.001].Higher patient mean scores were confirmed by the main effect of the psychiatric status [F(4,182) = 6.8, P < 0.001], especially for those with personality disorders (P < 0.001) and with schizophrenic disorders (P < 0.001), as revealed by post-hoc tests. There was also an indication of sensitivity to the cultural background [F(1,182) = 7.5, P < 0.01], as there was an increase in these scores in the Romanian sample, irrespective of the diagnosis and developmental period.Emotional abuse was more frequently reported by patients than by controls [F(4,194) = 7.0, P < 0.001] and more frequently by patients with personality disorders (P < 0.01) and by schizophrenic patients (P < 0.05) than the ones with a history of alcohol-related disorders  = 5.7, P < 0.001]  = 8.0, P < 0.001]. Post-hoc tests showed that patients with affective disorders (P < 0.01) and with alcohol-related disorders (P < 0.05) also reported more experiences of trauma witnessing than the controls. Irrespective of the diagnosis, Romanian patients, but not controls, reported higher mean scores on this variable and more often than their German/Swiss counterparts [F(1,209) = 17.0, P < 0.001]. The interaction between the cultural background and developmental period indicated in the Romanian sample an increase of trauma witnessing in adulthood [F(3,627) = 8.0, P < 0.001].Similar to the pattern of trauma witnessing, all patients reported a greater number of traumatic events than the control group [F(4,211) = 8.0, P < 0.001]: alcohol-related disorders (P < 0.001), personality disorders (P < 0.001), schizophrenic disorders (P < 0.01), and affective disorders (P < 0.01), as explained by post-hocs. An increase in the amount of other traumas reports across the developmental periods with highest values in adulthood for all patient groups [F(12, 633) = 7.0, P < 0.001] was also revealed.As previously expected, patients treated for alcohol-related disorders reported more alcohol and drug abuse than all the other groups [F(4,213) = 12.3, P < 0.001]. The post-hoc tests showed that the other patient groups also reported more alcohol and drug abuse when compared to the control group: affective disorders (P < 0.001), personality disorders, (P < 0.001) and schizophrenic disorders (P < 0.05). As also anticipated, abuse increased across developmental periods until adulthood [F(3,639) = 110.0, P < 0.001], particularly in patients with alcohol-related disorders, as revealed by the interaction between the developmental period and psychiatric status [F(12,639) = 14.3, P < 0.001]. Irrespective of the diagnosis, Romanian patients, but not controls, showed higher mean scores on reporting alcohol and drug abuse than their German/Swiss counterparts [F(4,213) = 3.4, P < 0.01], as shown by the interaction between the psychiatric status and cultural background. Compared to the German group, alcohol and drug abuse in the Romanian sample was higher, particularly in adulthood [F(3,639) = 9.8, P < 0.001].physical abuse, sexual abuse, trauma witnessing, and other traumas, obviously explains the traumatic experiences. The second factor showed high positive loadings on competence and safety, apparently accounting for variance attributed to positive experiences. The third factor showed high positive loadings on the first year of illness with alcohol and drug abuse. The fourth factor, consisting of separation, evidently explains disruptions of attachment. The fifth factor, which included secrets and emotional abuse, appeared to account for family chaos. Thus, the structure of the study instrument was well reproduced for the present sample, which included different psychiatric diagnoses and different cultural backgrounds.A principal components factor analysis was performed to explore interrelationships among TAQ subscales. The results of this analysis indicated that the most appropriate solution involved five factors that jointly accounted for 56.2% of the total variance in the dataset. Table The study aimed at exploring whether psychiatric diagnoses, e.g. alcohol-related disorders, schizophrenic disorders, affective disorders, and personality disorders are related to retrospectively reported positive and negative life events across developmental periods, and if so, whether special developmental periods are characterized by more negative experiences than others.Our findings demonstrate a strong association between reports of traumatic events and certain psychiatric disorders. In other studies, negative experiences were reported by individuals with diagnoses such as affective disorders ,41 and sIf the present findings are consistent with some prior studies ,9,16 in Furthermore, experiences of parental loss or separation were prominent in adulthood especially for the patients with alcohol-related disorders and with affective disorders. The high incidence of such negative experiences during this period in the patients with alcohol-related disorders could be, at the same time, a direct consequence of the behavioral deviance of these individuals and contribute to the maintenance of alcohol abuse.The present data has to be considered in the light of several possible limitations. First, the information obtained by self-report and without external evidence could be less reliable and valid, especially if we take into account the sensitive nature of this research. Herman and Schatzow, however, provide empirical support for the validity of abused patients' self-reports as well . They foBoth individual interviews and self-report questionnaire methods present higher figures than chart reviews do, indicating that patients usually do not spontaneously offer such information to their therapists. When offered, the information is not reliably documented . HoweverRomanian patients diagnosed with schizophrenic disorders differed significantly, with respect to the number of negative events, as compared to their German counterparts. One factor accounting for this difference might be the stressful environment during the former Ceausescu regime in Romania. During this 25-year period violations of human rights, terror, and corruption prevailed ,62. ThisThe present study demonstrates an association between negative life events in childhood and psychiatric diagnoses in adult life, which is in line with a number of other studies ,63. UnliAlthough one cannot assume a direct causal relationship between childhood abuse and adult psychopathology from the present data, the present study provides further preliminary and explorative evidence for the high load of negative life events in psychiatric patients. An advantage of this study is the examination of the abuse histories across a range of four psychiatric diagnoses within a controlled comparison design. Our findings are important and clinically highly relevant for further etiological research of causal and maintenance factors of psychiatric symptomatic, as well as for the research on the treatment of these conditions.The special value of the study lies in its cross-national comparison from a clinical psychological point of view including a highly underresearched country like Romania. More attention should be paid to the sad situation of the patients in Romania who are often under inadequate pharmacological and insufficient psychotherapeutic treatment, as well as under inappropriate hospitalization conditions. Further research should concentrate on the epidemiology and developmental psychopathology of psychiatric populations in other countries than the usually researched ones. Generally, reports of traumatic experiences during the whole lifespan should be more carefully considered in the clinical diagnosis process and in the development of treatment programs for the psychiatric patients.The author(s) declare that they have no competing interests.ES carried out the study in Germany, performed the statistical analysis and drafted the manuscript. DB carried out the study in Romania and drafted the manuscript. BR conceived of the study and drafted the manuscript. FN participated in the design of the study. MS participated in the design of the study. KS participated in the coordination of the study. KH participated in the coordination of the study. TE conceived of the study and drafted the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


In recent years, Australian state and territory governments have reviewed and restructured the health systems they lead and regulate. This paper examines the outcomes of the most recent official published reviews of systems and structures; identifies the common themes; and addresses two questions: what problems are being addressed? And how would we know if the changes were successful?In all the broad, systemic reviews, the main health system problems identified were money, hospital utilisation and a weak primary health care system. The solutions are various, but there is a common trend towards centralisation of governance, often at state health authority level, and stronger accountability measures. Other common themes are hospital substitution (services to avoid the need for admission); calls for cooperation across the Commonwealth:state divide, or for its abolition; and the expected range of current efficiency and effectiveness measures  and ideas in good currency . The top-down nature of the public review process is noted, along with the political nature of the immediate catalysts for calling on a review.The long-standing tension between the pull to centralisation of authority and the need for innovation in care models is heightened by recent changes, which may be counterproductive in an era dominated by the burden of chronic disease. I argue that the current reforms will not succeed in achieving the stated goals unless they make a difference for people with chronic illness. And if this is correct, the most useful focus for evaluation of the success of the reforms may be their impact on the system's ability to develop and deliver better models of care for this growing group of patients. In recent years, there has been a rolling (and sometimes repetitive) tide of structural change in the way state and territory governments organise to lead and/or provide health care within their jurisdictions, with every state and territory of Australia involved at least once in the last 10 years.This paper examines the outcomes of the most recent official published reviews of systems and structures; identifies the common themes; and addresses two questions: what problems are being addressed? And how would we know if the changes were successful?This analysis focuses on those reviews which are 'systemic' in the sense that they examine broadly the structure and performance of a state/territory health system, and/or address governance of the system. The NSW restructure has been included, although it differs from the others in the absence of an independent review process and in the related lack of detailed documentation of the rationale for change.The most recent wave of systemic reviews in the Australian public health system saw New South Wales , South ANSW has relinquished its status as an island of relative stability, which had been maintained since 1986 in spite of several reviews, penultimately by IPART [Queensland stays with central control  while Tasmania is reviewing hospital services only , having The pattern of systemic reviews over the last 10 years is summarised in Table In what has emerged as a strong centralising tendency, 6 of 8 jurisdictions have centralised governance authority for public sector health care agencies at the level of the state or territory health authority. Victoria and South Australia are mixed, with regionalised or 'networked' structures predominating in the capital city; and several different approaches to both regional and institutional governance elsewhere. As Somgen points out, Victoria and South Australia were the states most strongly influenced by the 1990's trend to privatisation, outsourcing and output-based funding , with leTable The recent NSW decision means that there is now a strong predominance of governance at state health authority level, with two-thirds of the Australian population living in areas served by centralised health services.The second notable trend is the virtual end of 'atomised' structures – stand-alone, single-service agencies  in the public sector. There are of course exceptions , and the picture is different for non-government organisations (like district nursing) which are less amenable to restructuring.The most recent reviews in WA and SA are characterised by claims to radical change, based on both financial and health goals:'...incremental reform is no longer the pathway to a financially sustainable vision for WA. A fundamental re-prioritisation of the public health system is needed, and should be carried out over the next decade in a systematic and integrated way' [p v).ted way' , p v).'The people of South Australia have a decision to make on what type of health system they need now and for the future generation...there needs to be a significant shift from a system focused on illness to a health system reoriented towards health promotion, illness prevention and early intervention' [p xiii.vention' p xiii.Western Australia is taking on the tertiary hospitals, and reducing the number of tertiary sites from 5 to 2 . All state-run health services are to report through three metropolitan regions (north, south and Women's and Children's) and one rural region, with the CEO's reporting directly to the Department – there are to be no boards of governance. South Australia has succeeded in amalgamating most of Adelaide's hospital and community health boards to form 2 regional health services and 1 child, youth and women's health service . This is a notable achievement for a minority government, after at least five separate attempts in the last 20 years to rebalance power and responsibility had largely failed -17.Not all of the systemic reviews claim to set a bold new vision, but there are strong common themes. The reports tell a familiar story of the need to bring increases in state health spending to sustainable levels, set against the trend of increasing costs due to increasing incidence of chronic disease, and more technologies for intervention, in an ageing population. They all focus on the need to improve quality and safety for patients.The reviews also find that the health system is too fragmented to meet the needs of patients with long-term complex conditions well. This is seen to be partly because the system was designed for acute illness, with the current funding mechanisms also designed primarily on the pattern of acute interventions. The reviews call for better integration of services, so that navigating the system is easier for patients, their carers and care providers.The reviews consistently argue that in order to achieve this, the primary care system needs to be more effective in managing or coordinating patients' needs for several different kinds of services when and where they are needed. The inevitable corollary is that inpatient care and hospitals have to become less central in the organisation and funding of the system. What can be done elsewhere should be; and the primary care level must have more of the action and more of the pulling power.In turn, this will require different facilities for different modes of service delivery; different funding allocations and methods of allocation; and a solution to the atomisation of primary care caused by the Commonwealth/state split and the current model of fee-for-service medicine. The need for changes in the private sector is noted in the reviews, but proposals are not developed, because the states have such a limited role here.Much is also made of the need for providers to be more accountable to government and the community, and/or better governed and managed. While the reports mostly call for less micro-managing from the head offices of health authorities, and a better separation between the roles of central policy-makers and peripheral service providers , there is also a countervailing tendency to recommend tighter engagement and control. For example, the Kibble review of governance in Victoria (2003) notes confusion about relative roles and responsibilities and calls for the Department of Human Services to reduce 'attention to the day-to-day operations of Health Services and monitoring of detailed activities' (p 27) but later recommends 'a standardised reporting template' for internal reports to boards across the system (p 35), along with stronger accountability for the CEOs to the Secretary of the Department. More public reporting of service outcomes and activity levels is a related common theme, intended to inform the public and to underpin attention to safety and quality.The final major common theme in the reviews is the inclusion of an opportunistic range of technical efficiency and effectiveness measures, picking up ideas in good currency or known productivity opportunities. For example, almost everyone recommends a call centre; a web-based method of sharing innovations; amalgamation of support services where relevant; and improvements in the effectiveness of information systems and the use of information.are the providers (NT, WA, ACT) or because intended changes to the service provider level of the system require changes to the roles of central health authorities.There are two other commonalities worth noting. Firstly, it is a fact of organisational and political life that official reviews are a top-down affair, commissioned by one level of the system to examine a lower level. Thus it is not surprising that there are no published official reviews of the roles and responsibilities of the Commonwealth health authority in the last twenty years. When the published reviews do address the roles and responsibilities of state health authorities, it is either because they This is an important limitation in the current environment, when some of the key barriers to improving the effectiveness of health care delivery lie in the system's seldom seen upper reaches. As the reviews note, the way that the Commonwealth/state split of responsibility for health is enacted and managed is probably the single most significant problem in health system design. But it is not the only one. I refer not so much to important policy settings  which are studied and articulated in publicly-available documents, but rather to the influence of administrative decisions  and the effectiveness of relationships with health care provider organisations (as judged from the bottom up as well as the top down). The administrative actions of health authorities seem to go largely unexamined.Secondly, while the underlying problems the reviews set out to address are all about money, hospital utilisation and a weak primary health care system, the immediate context is often the election of a new government (Victoria, SA, NT), the appointment of a new minister or health authority CEO (WA), media unrest about health in a state with a looming election (ACT) or scandal (NSW). This observation may simply be another way of saying that the health portfolio is highly politically sensitive as well as complex, and so risky that reference to independent expertise is seen as essential.The main line of logic running through the recent reviews seems sound. The primary care system needs strengthening; what can be done outside hospitals should be; and a continuing focus on safety, performance and accountability is necessary.The reports also make it clear that this is all about responding to the major challenge for the system: to improve its capacity to prevent, intervene early in, and manage chronic disease, the main driver of increased demand. Such a focus is clearly justified. Chronic disease is responsible for approximately 80% of the total burden of disease, with an estimated three million Australians suffering from one or more chronic illnesses . About 4If this is the imperative, the trend away from atomised governance structures, and towards bringing multiple agencies which serve (at least some) common patients together, seems like the right direction. But there is another important requirement which may not be served by these moves – that is, a stronger focus on innovation in care models. While recommendations abound, we don't yet really know what will work best for the new pattern of illness – how do you best coordinate care around the needs of the chronicly ill?Uncertainty about care models, and the institutional and policy arrangements needed to support them, can only be resolved through the continued development and testing of innovative approaches, on the ground in health care delivery, as happened most notably with the Coordinated Care Trials . As manyThis reality implies that there is a secondary criterion by which the effectiveness of health system structural changes might be judged: do the changes enhance or inhibit the system's ability to innovate? The requirement for innovation and experimentation may not sit comfortably with government requirements for standardisation of known good practice. However in an area where best practice is not known, innovation is critical, and must be supported.Unfortunately, the Commonwealth:state responsibility split, the one structural barrier most central to the systemic weakness of Australian primary care (and therefore most important for the capacity to develop and support new models of care for chronic diseases), is one that a state can't address, at least not alone. The Productivity Commission's recent call for an independent public review of the whole health system , focusedThe other pessimistic sign is the trend to more direct control of health care provision by state governments, related no doubt to the twin problems of increasing demand (and therefore cost) and increasing disclosure of safety and quality problems, both of which can only politicise the system more. Research on innovation, in relation to quality and safety as well as other performance measures, indicates that micro-management from above is not helpful ,23.Local evidence to support this view is scant. While the effectiveness of the new arrangements during Queensland's brief period of devolved governance was judged harshly when it came time to re-centralise, some commentators suggest that this period also allowed Queensland to catch up to other states in areas like accreditation, casemix, IT and 'attention to performance management and outcomes' .This may be a critical problem. While recognising that perspectives on this question are highly related to one's place in the structure, I would suggest that real innovation in public hospitals and health services is less likely to be driven by clinicians who are more tightly controlled, staff who have learnt to be risk-averse, or managers who are increasingly frightened of tomorrow's headlines, and whose planning horizon extends to next month's financial and activity data. This problem is only compounded while hospitals and community health services on the one hand, and GPs on the other, continue to work with so little in the way of common incentives.The recent reviews were established largely to address financial imperatives in an environment of upward pressure on demand for services, and accountability concerns , mostly in a highly political context. The reviewers rightly sought to take a longer-term strategic perspective. They attempted (with varying degrees of success) to focus on good system design and capacity to meet the broad and complex purposes of public health systems, recognizing the growing challenges the systems face.Structural reform is hardly ever evaluated, other than when its weaknesses are articulated by those proposing the next round of changes, as part of the rationale for their efforts. There are many reasons for this failure, some of them political. One pertinent reason is that outcomes like containing the pressure of future growth in demand, or improving health outcomes for the population, cannot be judged within a realistic time frame.However, in the current environment, with strong convergence in the themes addressed by a fairly comprehensive round of reviews of Australian health systems, an argument can be made for evaluation 'at the pointy end' of the changes. Given the challenges the reviews were intended to address, there are grounds to suggest that the current reforms will not succeed in achieving the stated (shorter- and longer-term) goals unless they make a difference for people with chronic illness. And if this is correct, the most useful immediate focus for evaluation of the success of the reforms may be their impact on the system's ability to develop and deliver better models of care for this growing group of patients.The 'data' for this project were the published reports of systemic reviews of the health systems, and related material published on departmental websites and in the professional and academic literature.These sources were analysed to generate an understanding of the recommended governance authority structures; and the common themes emerging from the reasoning on which the recommendations were based. The themes underpinning the recommendations were then assessed in the light of the overarching goals of reform.I was a member of the South Australian 'Generational Health Review' Steering Committee, chaired its Governance and Funding Task Force and continue to consult to the SA Department of Human Services. I worked for twenty years in health care agencies, and only one in a central health authority.


The current progress in sequencing projects calls for rapid, reliable and accurate function assignments of gene products. A variety of methods has been designed to annotate sequences on a large scale. However, these methods can either only be applied for specific subsets, or their results are not formalised, or they do not provide precise confidence estimates for their predictions.Xenopus laevis sequences, yielding functional annotation for more than half of the known expressed genome. Compared to the currently available annotation, we provided more than twice the number of contigs with good quality annotation, and additionally we assigned a confidence value to each predicted GO term.We have developed a large-scale annotation system that tackles all of these shortcomings. In our approach, annotation was provided through Gene Ontology terms by applying multiple Support Vector Machines (SVM) for the classification of correct and false predictions. The general performance of the system was benchmarked with a large dataset. An organism-wise cross-validation was performed to define confidence estimates, resulting in an average precision of 80% for 74% of all test sequences. The validation results show that the prediction performance was organism-independent and could reproduce the annotation of other automated systems as well as high-quality manual annotations. We applied our trained classification system to Xenopus laevis contig sequences was predicted and the results are publicly available at .We present a complete automated annotation system that overcomes many of the usual problems by applying a controlled vocabulary of Gene Ontology and an established classification method on large and well-described sequence data sets. In a case study, the function for  Accurate annotation has traditionally been maintained manually with the experience of individual experts and the experimental characterisation of sequences. However, the increasing gap between the amount of sequence data available and the time needed for their experimental characterisation demands computational function prediction in complementing manual curation [and establish a method to provide a confidence value for each annotation.Ongoing genome sequencing and recent developments in cDNA sequencing projects have led to an exponential rise in the amount of sequence information. This has increased the need for acquiring knowledge from sequences as to their biological function. Annotating a single sequence is the gateway to interpreting its biological relevance. However, the usefulness of these annotations is highly correlated with their quality. curation -4. Commocuration . Such ancuration . Howevercuration ,7,8. A ncuration , GAIA [1curation , Genotatcuration , Magpie curation , GeneQuicuration , GeneAtlcuration  and PEDAcuration . Howeveret al predicted GO terms by intersecting domain profiles [The current annotation, written in a rich, non-formalised language also complicates this automated process. We addressed this problem by applying a controlled vocabulary from Gene Ontology (GO) -17. GO pprofiles . The Swiprofiles . Text miprofiles . HoweverXenopus laevis, a widely studied model organism in developmental biology. Because many researchers are now focussing on the functional genomics of this organism, a demand exists for a quality annotation [Xenopus laevis contig sequences (from TIGR Gene Indices) yielding annotation with good confidence values for more than half of these sequences.We have developed an automated system for large-scale cDNA function assignment, designed and optimised to achieve a high-level of prediction accuracy without any manual refinement. Our system assigns molecular function GO terms to uncharacterised cDNA sequences and defines a confidence value for each prediction. The cDNA sequences were searched against GO-mapped protein databases and the GO terms were extracted from the homologues. In the training phase, these GO terms were compared to the GO annotation of the query sequences and labelled correspondingly. We applied Support Vector Machines (SVMs) as the machine learning method to classify whether the extracted GO terms were appropriate to the cDNA sequence or not. In order to classify the GO terms we used a broad variety of elaborated features (attributes) including sequence similarity measures, GO term frequency, GO term relationships between homologues, annotation quality of the homologues, and the level of annotation within the GO hierarchy. To enhance the reliability of the prediction, we used multiple SVMs for classification and applied a committee approach to combine the results with a voting scheme . The connotation . TherefoThe classifier (SVM) needs to specify attribute values (features) for a broad list of samples and a class label for each of these samples. Through the training samples it learns the feature patterns and tries to group them according to their class labels. After training, the algorithm assigns class labels to new samples according to the class that they best match.We selected GO-annotated cDNA sequences for training the SVM classifier. The nucleotide sequences were searched against GO-mapped protein databases and GO-annotations were extracted from the significant hits. Then, each GO term obtained was utilized as a sample for the feature table. The sample GO terms were then labelled as either correct "+1") or false ("-1") by comparing them to the original annotation. Note that we applied the relationships of the GO terms based on their graph structure: "Correct" was assigned not only if they were exact matches but also if the GO terms were related as either "parent" or "child" , Drosophila melanogaster (fly), Mus musculus (mouse), Arabidopsis thaliana (Arabidopsis), Caenorhabditis elegans (worm), Rattus norvegicus (rat), Danio rerio (fish), Leishmania major (Leishmania), Bacillus anthracis Ame (Bacillus), Coxiella burnetii RSA 493 (Coxiella), Shewanella oneidensis MR-1 (Shewanella), Vibrio cholerae (Vibrio) and Plasmodium falciparum (Plasmodium) (Table Arabidopsis, mouse and fly (22.1%, 18%, and 15.2% respectively). Prokaryotic bacteria (Bacillus, Coxiella, Shewanella and Vibrio) contributed 20.6% and the remaining 24.1% of the sequences came from rat, fish, worm, Plasmodium, Leishmania and yeast. Yeast and fly are purely manually annotated datasets. Where as Bacillus, Coxiella, Vibrio, Shewanella, Leishmania and Plasmodium are mostly manually, and the rest mostly automatically annotated datasets. Manual annotation tends to be conservative and sparse, since the GO terms are assigned only if the annotator is highly confident. Therefore, a GO term may be missed due to a poor definition of a false negative. To reduce this critical problems, yeast and fly annotations are accompanied by an "unknown molecular function" term for sequences with questionable further functions. To reduce false negatives, we discarded all sequences with these tags for training and testing (yeast: 2999 discarded out of 6355, fly: 8495 out of 14335).For training and testing the SVM, we selected 39,740 GO-annotated cDNA sequences from the following organisms: Shewanella, Coxiella and Vibrio sequences had the lowest number of GO terms per sequence (10.78, 12.33 and 12.54, respectively).The cDNA sequences were searched across the protein databases covering a wide range of organisms from prokaryotes to eukaryotes and SWISSPROT. For 36,771 sequences we got hits with GO terms, contributing to 856,632 sample GO terms and yielding an average of 23.29 GO terms per query sequence (Table We set up multiple classifiers by splitting the whole dataset (856,632 samples) into 99 equal subsets. Note that, amongst these 99 subsets, 96 contained data from a single organism and the remaining 3 from two organisms each. Subsequently, we built 99 classifiers with these subsets. Since the training sets were created organism-wise, the classifiers were trained from different ranges of data, based on purely manual annotation (yeast, fly), mostly automated annotation or a mixture of both. For training each of these classifiers, we performed a model selection , which yielded varying accuracy values ranging from 78.81% to 96.03%, with an average accuracy of 85.11%.Plasmodium and Leishmania, 98 classifiers; minimum: Arabidopsis, 74 classifiers). The quality of the predictions was estimated by comparing the predicted terms with the original annotation and the results were expressed in terms of precision and accuracy values (see Methods). The average-accuracy refers to the average of the accuracy values attained by all classifiers used for the prediction. The maximum average-accuracy was achieved for fly (81.51%), followed by yeast (80.50%), and the minimum for mouse (76.0%).To test the classifiers performance, we prepared 13 test sets (each set corresponding to a single organism) using the same 856,632 sample GO terms. The prediction quality of all 99 classifiers were assessed by an organism-wise cross-validation approach, i.e. for each organism (test set), we used all the classifiers for prediction except those that corresponded to the same organism. With this approach, we were able to simulate the annotation of a new organism. The number of classifiers used for predictions varied highly across organisms (maximum: Arabidopsis) with the manually annotated test sequences (yeast and fly). The prediction of the yeast and fly sequences with the 20 classifiers from the mouse sequences produced an average-accuracy of 79% and 80% respectively. Similar results were acquired with the 25 classifiers from Arabidopsis (79% and 80%). Likewise, the worm classifiers (11 classifiers) yielded the average-accuracy of 82% for yeast and 83% for fly. These values were comparable with the average-accuracy of 81% achieved by both, using yeast as test sequences against fly classifiers (16 classifier) and vice-versa (fly test sequences against yeast classifiers). Likewise, we classified the mouse test sequences against yeast classifiers (5 classifier) and fly classifiers yielding 69% and 71% average-accuracy respectively.Additionally, we compared the classification efficiency of the classifier derived from automatic annotation . The classification performances revealed by the ROC plots were comparable between IEA and non-IEA annotated test organisms  and non-IEA . All sequences from Xenopus laevis contig sequences from the TIGR Xenopus laevis Gene Index (XGI) [We extracted all ex (XGI)  and got Xenopus, fly, yeast and mouse  to the high-level, i.e. more generalised or high-level terms of the molecular function ontology ("GO slim" for molecular function) . These me Figure . Note thXenopus contigs (TIGR Xenopus laevis gene indices). We compared our annotation with the TIGR GO annotation for molecular function. From 35,251 contig sequences, TIGR annotated 5,444 contigs with a total of 16,432 molecular function GO terms. In contrast, our approach was able to predict function terms for 17,804 contigs, i.e. more than three times that of TIGR sequences. Our procedure did not annotate 295 contigs from the TIGR annotated contigs. For the remaining 5,149 contigs, 85% of all TIGR terms were found to be exact with those using our method; 3.2% of the TIGR terms were at a higher-level of the GO tree than our annotation, so in this case we provided annotation at a deeper level; in 0.9% of the cases our annotation was at a higher-level; 8.3% of the cases were completely different; and 0.6% of the TIGR terms were obsolete. We compared the quality of TIGR and that of our annotations by a raising stringency and found that when we applied a confidence threshold of 80% for our annotation, we lost 46.6% of the sequences. This included 1,492 sequences holding equivalent TIGR annotation or 27.4% of the total TIGR annotation. With this stringency, our system annotated 9,510 contig sequences, i.e. twice the TIGR annotation at this quality.TIGR provides a GO mapping for endopeptidase activity and more specifically serine-type peptidase activity (98% and 97% confidence respectively). 2) TC209487 and TC190605 are predicted to be aminopeptidases, however for the latter the more specific prediction of prolyl aminopeptidase activity is assigned with 86% confidence. 3) TC199713 is predicted as glutathione peroxidase at 100% confidence and TC194305 is annotated as protein kinase with the same confidence. 4) Both TC187949 and TC210151 are transmembrane receptors but the latter one is classified as frizzled receptor with 82% confidence. In most of these examples the functional assignment and associated confidence were recorded in multiple levels of granularity.We were interested in novel annotated sequences with the highest confidence values and found we could predict GO terms for 557 contigs with a confidence value of 100% . Interestingly, 192 of these lacked any GO annotation by TIGR. Out of these, 184 had got a descriptive TIGR annotation and the rest had not got any. Table In this paper, we presented an automatic annotation system that is able to cope with the expanding amount of biological sequence data. Our approach efficiently combines the ongoing efforts of Gene Ontology and the availability of GO-mapped sequences with a profound machine learning system. The GO-mapped databases provide annotation described in a controlled vocabulary and also a measure of reliability, as these GO entries are labelled with their type of origin. Furthermore, GO terms are structured hierarchically, which allow us a twofold use of the information: i) the level within the tree is taken as a classification criterion to distinguish low from high-level annotations during the learning procedure, and, ii) the hierarchical structure allows us to extend hits by slightly moving up and down within a restricted local area of the tree. This may overcome fluctuations of the annotation levels coming from varying annotation experts.Our annotation system exploits the different combinations of attributes and yields functional transitivity: SVM learning and prediction are organism-independent and comparable to manual annotation, which may be supported by the nature of the attributes we utilise. Subsets and overlaps are counted in a balanced fashion to avoid biases due to the complexity of an organism and a potentially correlated complexity of its sequences. The committee approach allows us to improve the prediction quality as well as to assign confidence values for the new predictions in a straightforward manner. Our classifiers performance is hardly limited by the varying quality of the training data, whether manual or automatic annotated. The prediction results of manually annotated test sets with the classifiers based on automated annotation as well as classifiers based on manual annotation were comparable. Regarding the outcome of the overall classifiers, we achieve consistency with existing annotation from automatic annotations. This is the less complex part of our work and shows a comparable efficiency of our system. Additionally, our system reproduces annotation of purely manually annotated datasets (fly, yeast, etc). However, the performance results for these datasets are low in terms of recall, i.e. 47.4% recall with 80% precision compared to 60.6% recall with the same precision of the complete test set. Note that manual annotation tends to be conservative and sparse, yielding stringent true positive definitions, whereas automatically annotated sequences may accumulate information to a greater extent.Xenopus since it is a familiar model organism. However, the sequences were not very well annotated. Our system was applied to annotate the Xenopus contig sequences from TIGR. Through our approach, we annotated 50.5% of all contig sequences available at present, and associated a confidence value for each prediction, yielding roughly three times more sequences as compared to the currently available GO annotation. However, the coverage of annotation to new organism like Xenopus is crucial. We were able to attain predictions for 50.5% of all Xenopus contig sequences (no singletons). This compares to the applied databases that contained 53% satisfactory annotation for their sequences (not regarding sequences with unknown function terms), and better than the organism specific databases (36%). Obviously, improving the quality and quantity of annotation within the available databases goes along with the coverage exploit of machine learning algorithms for new organisms. In future we want to extend our method with the information from other sources such as domain databases and protein family databases.We were interested in annotating Xenopus laevis contig sequences, we obtained a remarkably enhanced annotation coverage compared to the existing annotation.We developed an automated annotation system to assign functional GO terms to an unknown sequence. We used the well-established technique of Support Vector Machines (SVM) for the classification of correct and incorrect GO terms. Our approach benefited from the broad variety of potential attributes used for the functional transitivity and a vast amount of data used for training and validating. The committee scheme exploited in our system provided a means to assign confidence values in a straightforward manner. Our system performance was robust, organism-independent and reproduced the high-quality manual annotation. When applying it to We used the following statistical terms ,31.Accuracy was the rate of correct predictions compared to all predictions,Accuracy: = (TP + TN) / (TP + FP + TN + FN),     (1)Precision was the portion of true positives with respect to all positives,where TP denotes true positives, FP false positives, TN true negatives and FN false negatives. Precision: = TP / (TP + FP).     (2)sensitivity := TP / (TP + FN), specificity := TN / (FP + TN), and false positive rate := 1 - specificity. We defined the term "coverage-of-sequences" as the portion of query sequences for which the classifier delivers a prediction; "Precision-per-sequence" the (average) portion of correct GO terms for a single query sequence, with respect to all GO terms assigned to it. Note that these terms were defined within our model, i.e. a good "accuracy" meant good consistency with respect to our training and test sets.Also used were 1 with respect to GO2 was classified as "parent", "child", "sibling" or "different" Pi denotes the set of nodes from GOi to the rootP2 is a "child" of GO1 if their paths P2 and P1 intersect such thatGO1 ⊃ P2,     (4)P2 is a "sibling" of GO1 if a common parent exists with a distance of one to GO1 and GO2  and is henceforth referred to as "path-pairs". This method could yield a list of several relations. To select the appropriate relation from this list, we considered the parent relationship to be most relevant, followed by the child relationship, and the sibling was considered least relevant. We implemented the following order:We could apply the single path relationship for most of the GO terms (3665 out of 5391). However, for the remaining 1726 terms more than one path to the root were found. For these cases we defined multiple path relationships and each path was considered individually. The single path relationship was applied to each possible pair of these paths (path for GO1. The parent relationship was set if at least one of the path-pairs gave a (single path) parent relationship;2. The child relationship was set if at least one of the path-pairs gave a child relationship. To avoid a bias due to an overwhelming number of path-pairs that did not match, we set a threshold: we considered this relationship only, if the number of path-pairs with no child relationship was equal or less than four times the number of path-pairs with child relationship;3. The sibling relationship was set if at least one of the path-pairs gave a sibling relationship. We again set a threshold: we considered this relationship only, if the number of path-pairs with no sibling relationship was equal or less than twice the number of pairs with sibling relationship;4. If none of these criteria could be applied, the relationship "different" was set.Note that we also implemented the hierarchy of these relations by tuning the stringencies for the fractions of path-pairs that must match (parent: no threshold, child: 1/4, sibling: 1/2).Arabidopsis, worm, rat, fish, Leishmania, Bacillus, Coxiella, Shewanella, Vibrio, Plasmodium, Oryza sativa, Trypanosoma brucei, and Homo sapiens. Apart from this, the SWISS-PROT database was also included [Arabidopsis, worm, rat, fish, Leishmania, Bacillus, Coxiella, Shewanella, Vibrio and Plasmodium (see Table Since the function transitivity at the protein level is more reliable, we used GO-mapped protein databases for searching homologues. Gene association files were obtained via the Gene Ontology Consortium. By combining the gene association files with corresponding sequence databases we created the unified protein databases. The following organisms were used: yeast, fly, mouse, included . For SVMEach cDNA sequence was searched across the protein databases, using BLASTX within the HUSAR system . A queryA) GO level and path: The GO structure was exploited to derive the first two attributes,GO level: the distance of the sample GO term to the root (molecular function node);A.1.GO path: the number of paths from the sample GO term to the root.A.2. B) Alignment quality criteria: These attributes are based on the BLAST alignments. For attributes B.1 - B.4, the best value for the corresponding attribute was taken, if a GO term occurred in more than one hit,Expectation value: the expectation value  from BLASTX;B.1. Bit score: the bit score value provided by BLASTX;B.2. and the hits to offset biases due to different complexities of the query and subject organisms. Attributes B.3, B.4, C.3 and D.3 were obtained from initial trials with a small dataset (6270 cDNA sequences, data not shown) and applying parameter optimisation to distinguish the samples.We wanted to award alignment length and quality by combining features. This was done with respect to the length of the query Query coverage score (QCS): Combined measure of alignment size and quality concerning the query sequence,B.3. S := (AL / QL) × (I + S),     (5)QCL denotes the alignment length, QL the length of the query sequence, I the number of identities in the alignment, and S the number of positively contributing residues in the alignment;where ASubject coverage score (SCS): as in B.3, however only with respect to the corresponding subject sequence (database hit),B.4. S := (AL / SL) × (I + S),     (6)SCL denotes the length of the subject sequence;where SAdditionally, we decomposed these attributes into the following further six attributes (B.5 - B.10). For these attributes, we considered the hit with the best coverage score if a GO term occurred in more than one hit (query coverage score for attributes B.5, B.7, B.9, and subject coverage score for B.6, B.8, B.10).Query percentage (QPC): Percentage of coverage of the alignment region in the query sequence (with respect to QCS), i.e.B.5. C := (AL / QL) × 100;     (7)QPSubject percentage (SPC) Percentage of coverage of the alignment region in the corresponding subject sequence (with respect to SCS), i.e.B.6. C := (AL / SL) × 100;     (8)SPQuery identity (QI): Percentage of identical residues in the BLASTX alignment (with respect to QCS);B.7. Subject identity (SI): Percentage of identical residues in the BLASTX alignment (with respect to SCS);B.8. Query similarity (QS): Percentage of similar or positively contributing residues in the alignment (with respect to QCS);B.9. Subject similarity (SS): Percentage of similar or positively contributing residues in the alignment (with respect to SCS).B.10.C) GO frequency related attributes: We extracted information about the frequency of GO terms in the hits by the following attributes:GO frequency (FG): the number of hits that contained the sample GO term.C.1.Number of hits (TH): the total number of hits for the query.C.2.Frequency score (FS): the number of hits that contained the sample GO term. Unlike C.1, we limited this score to emphasize differences in queries with few hits:C.3. Species frequency: The number of organisms contributing to a sample GO term for a single query sequence;C.4.Total GO (TG): total number of GO terms from all hits.C.5.Unique GO (UG): as C.5, except, that GO terms occurring more than once (in the hits) were counted only once.C.6. D) GO frequency by considering relationships: For these attributes we applied the structure of the Gene Ontology graph. Not only perfectly matching terms were considered, but also their defined parents, children or siblings:Relative frequency for all (RA): the relationships for the sample GO term with all GO terms that occurred in the hits were calculated. The sum of non-"different" relationships i.e. parent, child, or sibling was used for this attribute;D.1.Relative frequency for unique (RU): similar to attribute D.1, with the exception that GO terms occurring more than once were counted only once.D.2.Relative frequency for all (limited) (RAlim): same as attribute D.1, however this score was limited to emphasize differences of queries with few hits:D.3.Relative frequency for unique (limited) (RUlim): same as attribute D.2, however this score was limited to emphasize differences of queries with few hits:D.4.E) Annotation quality related attributes: Quality attributes were selected from the evidence codes provided by the gene association tables of the GO-mapped sequence databases. We selected 9 commonly used evidence codes (TAS, NAS, ISS, IPI, IMP, IGI, IEP, IEA, IDA), resulting in attributes E.1 to E.9. The entries of these attributes for each sample GO term were calculated by summing the occurrences of the corresponding evidence codes of all hits.Before training, normalisation was performed. We normalised the attributes by taking the logarithm (log) and log of log if necessary. We used log values for 16 attributes (B.3-B.10, C.3, C.4, D.1, D.2, D.4 and E.1) and log of log for 8 attributes (B.2, C.1, E.2, E.4-E.8). Furthermore, we converted the attribute values into mean 0 and standard deviation 1 by applying the Z-transformation. The feature table contained 856,632 samples and 31 attributes. We split the dataset into 99 training subsets. Each subset comprised of approximately 1% of the samples i.e. 8,566 GO terms. This resulted in 96 organism specific subsets and 3 hybrid subsets. We applied the support vector machines in the implementation of LIBSVM , which sXenopus laevis contig sequences is downloadable at . We followed the standard GO annotation style (using Gene ontology guideline). The evidence code is always IEA. The confidence value is included for each GO term.The annotation for The main work was carried out by AV. RK and KG conceived the idea of the study. AV and RK drafted the manuscript. FS developed and JM applied the machine learning strategy. KG implemented the databases in SRS. RE and SS supervised the work. All authors participated in reading, approving and revising the manuscript.