In 2009, the Western Australian (WA) Government introduced the Four-Hour Rule (FHR) program. The policy stated that most patients presenting to Emergency Departments (EDs) were to be seen and either admitted, transferred, or discharged within 4 hours. This study utilised de-identified data from five participating hospitals, before and after FHR implementation, to assess the impact of the FHR on several areas of ED functioning.A state (WA) population-based intervention study design, using longitudinal data obtained from administrative health databases via record linkage methodology, and interrupted time series analysis technique.There were 3,214,802 ED presentations, corresponding to 1,203,513 ED patients.After the FHR implementation, access block for patients admitted through ED for all five sites showed a significant reduction of up to 13.2%  per quarter. Rate of ED attendances for most hospitals continued to rise throughout the entire study period and were unaffected by the FHR, except for one hospital. Pattern of change in ED re-attendance rate post-FHR was similar to pre-FHR, but the trend reduced for two hospitals. ED occupancy was reduced by 6.2% per quarter post-FHR for the most ‘crowded’ ED. ED length of stay and ED efficiency improved in four hospitals and deteriorated in one hospital. Time to being seen by ED clinician and Did-Not-Wait rate improved for some hospitals. Admission rates in post-FHR increased, by up to 1% per quarter, for two hospitals where the pre-FHR trend was decreasing.The FHR had a consistent effect on ‘flow’ measures: significantly reducing ED overcrowding and access block and enhancing ED efficiency. Time-based outcome measures mostly improved with the FHR. There is some evidence of increased ED attendance, but no evidence of increased ED re-attendance. Effects on patient disposition status were mixed. Overall, this reflects the value of investing resources into the ED/hospital system to improve efficiency and patient experience. Further research is required to illuminate the exact mechanisms of the effects of FHR on the ED and hospital functioning across Australia. Access Block and Emergency Department (ED) overcrowding remain a major problem for patients, professionals and public health care systems worldwide. Adverse effects of these phenomena are numerous, wide-ranging and well described in the literature–5. TheseIn 2000, responding to these pressures, the United Kingdom (UK) Blair Government developed a health plan containing the first version of the “Four-Hour Rule” (FHR) where 100% of patients were expected to be admitted, transferred or discharged from the ED within four hours of arrival at ED . In 2005Learning from the UK experience, the state of Western Australia (WA) introduced a modified version of the FHR program, using gradual incremental targets and multiple quality measures, to its four tertiary hospitals  with EDs on 14 April 2009. The original target of this Stage 1 required that by April 2011, 98% of patients presenting to ED would be seen and be discharged, admitted, or transferred within 4 hours of their arrival, 20. DueThis study assessed the impact of the WA FHR program on multiple measures of ED functioning and patient outcomes for five de-identified participating hospitals, including all four tertiary hospitals from Stage 1 and one general hospital from Stage 2.This was a population-based intervention study, using de-identified record-linkage health data in Western Australia between 2002 and 2013.Data definitions below).The study utilised the WA Emergency Department Data Collection (EDDC) and the WA Hospital Morbidity Data Collection (HMDC), of which WA Department of Health is the custodian. The EDDC contained all 3,219,905 ED presentations, corresponding to 1,206,466 patients, to the five-participating hospital EDs between 1 January 2002 and 31 December 2013, except for Hospital E whose data were included from 1 July 2004 . The HMDC was used for identifying hospital admissions following ED presentations  are assessed in this study. The five principal measures are: Access Block (defined as ED length of stay (EDLOS) longer than 8 hours) for an admitted patient, ED occupancy rate, ED attendances and re-attendance (within 7 days of index ED discharge) and ED length of stay (EDLOS). These are designated ‘principal’ as they are considered as the direct markers of the intended outcomes or changes expected of the FHR. Secondary measures include: time to be seen by ED clinician, ED efficiency (indicated by the percentage of ED attendances with EDLOS ≤ 4 hours), Did-Not-Wait (DNW–left ED before being seen by an ED clinician), admission, and short-stay admission .Identification of a hospital admission subsequent to an ED attendance was via match-merging records from the EDDC and HMDC. Records from the HMDC would need to have their status flagged as ‘emergency’ admissions to be considered in the match-merging process with EDDC records. The timeframe that allowed for an ED-Morbidity match was ED discharge time being within  of the subsequent hospital admission time. The absolute value of 1-hour buffer time was included to take into account the potential inaccuracy/imprecision of the time recorded in the HMDC; as the data custodian recommended these times be rounded up to the hour unit. One extra hour was allowed after ED discharge time and before hospital admission time, taking into account logistic reasons, such as time taken for finalizing hospital paperwork and/or transfer to another hospital for admission.ED occupancy rate served as an index of ED overcrowding, whereby ED occupancy rate greater than 100% indicates an overcrowded ED environment. It was calculated for every one-hour block throughout the study period for each hospital ED, and defined as the total ED patient count divided by the concerned ED’s functional capacity. Functional capacity are numerical values agreed by the Western Australian Department of Health, the ED concerned and the respective hospital, as the volume of patients that the ED can functionally receive and treat at a given point in time.Data were first summarised in quarters and presented graphically as time series for the 10 outcomes separately. The impact of the FHR on these ED outcome measures was assessed statistically using Interrupted Time Series (ITS) analysis, which is the recommended technique for analysing data from a population-based interventional study such as this one –24. SeveIn the ITS analysis, the pre-FHR period was comprised of 29 Quarters (14 January 2002 to 13 April 2009 inclusive) for the four Stage 1 hospitals, and 21 Quarters (26 July 2004 to 25 October 2009 inclusive) for the Stage 2 hospital. Similarly, the post-FHR period spanned over 18 Quarters (14 April 2009 to 13 October 2013 inclusive) for the four Stage 1 hospitals, and 16 Quarters (26 October 2009–25 October 2013) for the Stage 2 hospital. Results from these analyses are reported in relation to: (i) trend pre-intervention, (ii) immediate change in levels from pre-intervention to post-intervention, and (iii) change in trend post-intervention.Data on Access Block were log-transformed before being subjected to the ITS analysis, and then back-transformed  once modelled, to ensure the predicted values derived from the statistical models were non-negative. This consideration was not required for the ITS analysis of the other nine outcomes, where data in  normal base were used. Accordingly, estimates derived from the ITS models are to be interpreted as “differences” for these nine outcomes, and as “ratios” for Access Block.Inferential statistics presented in this paper are accompanied by the respective 95% Confidence Intervals (CI). Statistical significance levels are not adjusted for multiple outcome analyses in this study, because such adjustments are argued by some as unnecessary and potentially misleading , 27. HowData were managed and analysed using SAS software version 9.3.The study received ethics approval from the respective Human Research Ethics Committees of Western Australian Department of Health, University of New South Wales, and The University of Western Australia, as well as governance approval from all participating hospitals.Checks for data completeness and validity led to the removal of 5,103 ineligible records . Of these, 4,568 (89.5%) were coded as ‘Dead on Arrival’, while the remaining 535 records had missing, duplicated, or invalid time measures . Accordingly, a total of 3,214,802 ED presentation records, corresponding to 1,203,513 persons, were deemed eligible and retained for reporting in this study..Rate of ED attendance was on an increasing trend for Hospitals C through E pre-FHR. This increase was as high as 14% , per quarter for Hospital E see . Post-FHMedian EDLOS for Hospital A was on the increase pre-FHR, estimated at a rate of 0.03 hours per quarter see . ImmediaThe statistics in Similar to the findings of ED occupancy rate, the FHR completely reversed the pre-existing pattern in access block , which hAs shown in ED efficiency, a categorical version of EDLOS, improved significantly post-FHR for the four hospitals A through D. The largest magnitude of improvement was observed for Hospital D, with an increase in ED efficiency by 2.1% per quarter see . For HosTrends in admission increased post-FHR for Hospitals C and E, who had decreasing trends pre-FHR see . The magThe increase in admission rate at Hospital D described above was also reflected in its short-stay admission rate increase immediately post-FHR . There wDid-Not-Wait (DNW) rate was already on a declining trend pre-FHR for Hospitals A and E . The FHRCollectively speaking, the FHR produced improvements in several areas of ED functioning. These include: shortening ED length of stay and enhancing ED efficiency for most hospitals; alleviating access block and ED overcrowding dramatically for all hospitals; reducing time to be seen by ED clinicians; and reducing rates of ED re-attendance and DNW in some hospitals.The most consistent and substantial benefits of the FHR program were observed in the ‘flow’ measures, especially access block. This was expected, given that the primary objective of the program was to improve ED and hospital efficiency and reduce congestion and patients waiting. Also notable was the stable, or even downward, trend in ED re-attendance within 7 days. This provides some indication that improvements in flow were not made at the expense of patient care, a concern noted from the UK FHR experience . NeverthConversely, it is also interesting to note that, while the FHR could be seen as a time-based target, its effect on the two time-based outcome measures, namely ED length of stay and time to be seen by ED clinician, were less uniform than that on the ‘flow’ measures. Broken down by acuity (ATS) categories, the data showed that: ED length of stay for lower acuity (ATS 4 and 5) attendances were already low, and hence remained unchanged with the FHR. The majority of improvement in ED length of stay was seen in the higher acuity levels (ATS 1 through 3) attendances . By contAdmission rates increased for most hospitals in post-FHR and in one hospital this trend was accompanied by an increase in short-stay admissions. There had been some clinical concern, documented in the international literature  that efforts to meet the FHR target could lead to a somewhat ‘strategic’ increase in admissions, particularly admissions for low-severity ED attendances, in order to ‘stop the clock’. This woRate of ED attendance on the whole was already increasing over time, independently of the FHR, except for a significant upward trend observed post-FHR for Hospital A, whilst it’s pre-FHR trend was stable, unlike most other participating hospitals. It is interesting and worth noting that the attendance rate did not increase uniformly as a result of the FHR and its publicity. Similarly, there was no evidence for the ‘dilution’ effect  in the aDespite over a decade since the UK FHR was introduced, and several similar interventions being introduced worldwide to alleviate the overcrowding and related issues faced by EDs, little systematic research has been published in the peer-reviewed literature . Also prAnother strength of our study is the large data coverage, which has allowed us to reliably measure ED occupancy over time for each participating hospital, hence providing an accurate estimate of the extent of ED overcrowding throughout the long study period. ED overcrowding represents a key aspect of the ED and hospital environment, which should be of significant value in subsequent related studies in assessing specific patient outcomes of interest, such as: “Does presenting to an overcrowded ED and hospital environment put the patient at significantly higher risk of mortality?” Some previous studies applied a perhaps less informative proxy measure for ED overcrowding ; whThese strengths are juxtaposed by two shortcomings. First, while reporting on an extensive range of ten outcome measures related to ED and hospital functioning, we needed to restrict our scope of analysis to time trends and intervention effects only , in order to fit into the scope of one paper. As such, examination of factors considered important such as patient age, comorbidity, mode of transport, socio-economic disadvantage, as well as system and environmental factors such as ED shift, ED environment  and seasonal factors, and their interplay with the intervention effect, have not been included here. Second, with WA being the first Australian state to implement the FHR–hence acquiring a lengthy series of longitudinal data, it is not currently possible to include a similarly long series of data from hospitals in other Australian jurisdictions. Consequently, with the five sites under investigation, the level of homogeneity may not have been ideal, which is why we presented the results for the five sites separately. Hence, the generalisability of our findings may be limited .Another limitation in this study is its primary focus on the intervention’s impact on ED performance indicators, and this focus is not extended to ‘downstream’ effects on specific inpatients’ outcomes, except for the study’s examination of admission and access block measures, which concern inpatients. On this point, we also note some recent literature examining such issues. For example, Perera and colleagues , 38 repoDespite between-hospital variations in certain outcomes as noted earlier, the FHR experience in WA has overall been positive for the observed measures. This reflects the potential value of investing resource and effort into the hospital system resulting in improved functionality, which improves the patient experience (at least in the ED environment). Although mortality outcome has not been assessed in this report, we have addressed some important clinical questions, including whether the FHR (i) brought about unintended adverse, or suboptimal consequences such as increased ED re-attendance; (ii) was associated with a dilution effect in acuity of ED presentations; (iii) ‘bed-shuffling’ of patients just to ‘stop the clock’ and meet the time-based target by increasing admissions, and particularly short-stay admissions. As summarised in Results and discussed in the Principal Findings section earlier, we found no clear evidence from our study to serve as a basis for any of these concerns, which is positive.Our results also suggest that the FHR in WA was not regarded simply as a time-based target by the participating WA hospitals. Rather, it was a major driver or catalyst for system and practice changes on many levels. For example, for some hospitals, despite demonstrating modest changes in their median EDLOS, their other ED experiences such as access block and ED overcrowding, still benefited from adopting the intervention. Changes and improvements, to some extent, were different for different participating hospitals, depending on their inherent structure and setup  and context , to name a few. Accordingly, these factors need to be taken into account when attempting to translate this study’s findings into meaningful changes to policies and practices for other hospitals.We are exploring the exact mechanisms of the introduction and effects of the FHR on the ED and hospital functioning such as mortality, comorbidities, and other variables described above, as well as the national impact. This is important mainly for two reasons: (a) to assess further the question of any FHR unintended adverse consequences, and (b) to compare with preliminary national and international findings , 30, 39.S1 File(DOCX)Click here for additional data file.S1 Fig(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 Fig(TIF)Click here for additional data file.S4 Fig(TIF)Click here for additional data file.S1 Acknowledgments(PDF)Click here for additional data file.


The easy availability of food has caused a shift from eating for survival to hedonic eating. Women, compared to men, have shown to respond differently to food cues in the environment on a behavioral and a neural level, in particular to energy rich (compared to low energy) foods. It has been demonstrated that the right posterior superior temporal sulcus (STS) is the only region exhibiting greater activation for high vs. low calorie food choices. In order to test for a possible causal role of STS in food choice, we applied high frequency transcranial random noise stimulation (tRNS) on STS assuming a different response pattern between males and females. Our participants  performed a forced choice task between food pairs matched for individual liking but differed in calorie, during the left STS, right STS stimulation and sham condition. Male participants showed a general preference for low calorie (LC) foods compared to females. In addition, we observed in males, but not in females, an increase of high calorie (HC) food choice during right STS tRNS compared to sham condition and left STS tRNS. Finally, we found an increase of missed choices during right STS stimulation compared to sham condition and left STS stimulation. In conclusion, thanks to tRNS evidence, we both confirm the involvement and suggest a causal role of right posterior STS in feeding behavior. Moreover, we suggest that gender differences exist in STS mechanisms underlying food choice. The easy availability of food in our western society has caused a shift from eating for survival (energy intake) to an hedonic eating aimed to obtain pleasant feelings (reward) from food intake  food, such as fruit and vegetables, the preference for high-calorie (HC) foods  years old, 25 females and 22 males normal-weight with a mean BMI of 22.8 (SD = ±2.1). All participants were right-handed. Only non-smokers subjects were recruited reporting no drug abuse history, no diagnosis of psychiatric and neurological illness and no metallic implants/implanted electric devices. All participants completed a screening package aimed to check the absence of eating disorders. Other, no one followed special diets or had dietary restrictions, due to allergies, intolerances, or vegetarianism.N = 11). Another participant did not want to attend the second task. The final sample of 17 males and 18 females did not show significant differences in age and BMI.In order to bring all participants to a comparable sated state  and administered in two different days. In particular, participants performed the forced choice task at least 7 days after the rating task. Participants were tested individually: they sat comfortably in front of the computer monitor  with the head at approximately 60 cm distance. First, participants’ height and weight were measured in order to assess the BMI, and they were asked to report their sex and age. Then, the experimenter instructed the participants and left the experimental room.t-test) in the BUT-A’s General Severity Index and in the Emotional Eating subscale of DEBQ scores, both higher in females compared to the males  and the other half in the afternoon (after lunch). Each participant was asked to eat the same meal until satiety before both experiments. Specifically, they reported the meal consumed before starting the rating task and then, prior to the forced choice task, we requested them to eat the same foodstuffs. We evaluated satiety level, before both tasks, using the same paper-and-pencil test performed in the demographic phase of FRIDa’s validation  were matched on liking  and taste , to make the pairs as equal as possible. They differed in perceived healthiness, absolute and perceived caloric content. To check whether our manipulations were successful, mean actual caloric content , mean liking, perceived caloric content, and healthiness  were calculated. As expected, all variables, except for liking, differed significantly between the choice options within each food pair Table . Hence, Forced choice tRNS task Figure  consiste2) placed at the T7-CP5 or T8-CP6 positions of the 10–10 EEG system . The stimulation started 150 s before the beginning of the task. During the task the stimulation lasted from a variable time between a minimum of 278 s to a maximum of 488 s  depending on the trials number (ranged from 48 to 77) and the response times of our participants. A ramping period of 15 s both at the beginning and at the end of the stimulation was also applied. Thus, the total stimulation time ranged from ~450 s to ~650 s . In the SH control condition, the electrode was placed on one of the two stimulation sites , and the current was turned off after 15 s. The stimulation conditions  order were counterbalanced across participants. There was a break of 360 s between blocks.tRNS . Dependent variables in the tRNS forced choice task were the percentage of HC food choices, the median of reaction times (RTs) for both HC and LC, and the percentage of missed choices (no response given within 3 s of food pairs presentation). All these variables were normally distributed except for the missed choice percentage and thus, to obtain a normal distribution, we applied a fractional rank transformation  and a second group of trials  were performed on HC food choices, RTs and percentage of missed choices for all stimulation conditions . For all comparisons, no significant effect was found .Finally, given the variability of stimulation time across our sample, we controlled for possible effects deriving from different stimulation time. Thus, a series of F = 7.67, p = 0.009, F = 4.23, p = 0.018, post hoc analysis showed , lSTS (p = 0.011) and rSTS (p = 0.029) stimulation. In males, the percentage of HC choices was higher during rSTS stimulation compared to SH condition (p = 0.013) and lSTS stimulation (p = 0.028).Considering the percentage of HC food choice as dependent variable, ANOVA with tRNS condition  and participants gender  as factors showed a significant effect of gender , food choice  and gender  as factors showed no significant effects.F = 11.44, p < 0.001, post hoc analysis showed  and lSTS stimulation (p < 0.001).Considering the rank transformed percentage of missed choice as dependent variable, ANOVA with tRNS condition  and participants gender  as factors showed a significant effect of tRNS (F2,6 = 11.44,In the present study, we tested the hypothesis that HF tRNS on the right posterior STS causally influences food choices between equally valenced high and low caloric foods in sated individuals. Given the gender differences in food preference and brain responses to food (e.g., Del Parigi et al., Regular eating of HC foods in the absence of hunger might lead to a positive energy balance and overweight on the long term. As showed by our rating data, low energy foods are perceived to be healthier and less heavy compared with high energy foods (Deng and Kahn, This conflict has been analyzed by a neuroimaging study of Killgore and Yurgelun-Todd . They foWhile different studies using tDCS showed that the dorsolateral prefrontal cortex modulated food evaluation, desire and consumptions (Fregni et al., Our results are limited to a young adult sample; thus, given the age effect on food perception (e.g., Kremer et al., In conclusion, we confirm the involvement of right posterior STS in feeding behavior and assign to its activity a possible causal role in modulating this function. As a novel finding, we report a difference between men and women indicating a prominent role of STS in HC/LC food choice confirming the existence of different neuro-cognitive reward pattern based on sex.VM, CP and AB conceived and designed the experiment. VM collected and analyzed the data. VM, CP, LNL and AB interpreted the data. VM wrote the manuscript and CP, LNL and AB provided critical revisions and contributed to the final version of the manuscript by interpreting results, reviewing and critically revising text. All authors approved the final version for submission and agreed to be accountable to for all aspects of the work.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer BW and handling Editor declared their shared affiliation.


Whereas the clinical manifestations and the neuropsychological predictors of Developmental Dyslexia (DD) are already well documented in Italian-speaking children, empirical evidence on DD in Italian adults is in contrast rather scarce. The aim of the present study was to investigate the role of a subset of neuropsychological skills, which have been identified by previous literature to be related to reading, in the decoding abilities of a group of Italian undergraduates with and without DD. For this purpose, 39 university students aged between 19 and 27 years, 19 of whom with a diagnosis of DD, underwent an assessment battery including standardized reading tests, rapid automatized naming (RAN), verbal working memory, and rhythmic pattern discrimination tests. Cross-group differences confirmed significantly lower performances of undergraduates with DD in all measures but rhythm discrimination, compared to typical readers, thus showing a non-compensated neuropsychological profile. Regression analyses showed that, while reading speed was strongly and uniquely predicted by RAN speed, reading accuracy was concurrently predicted by RAN and rhythmic abilities. Finally, RAN speed emerged as a strong predictor of reading performance and risk of receiving a diagnosis of DD. The difficulties associated with developmental dyslexia (DD) persist into adulthood ,2,3. EveAlthough DD has been widely investigated in childhood and adolescence, research on DD in adults is yet rather scarce. The need for a better understanding of the neuropsychological and behavioral manifestations of DD in older populations is fueled by the recently growing number of students with a diagnosis of DD undertaking university studies . In ItalDue to its multidimensional clinical manifestation, a multifactorial neurocognitive explanatory model has been applied to DD . EvidencA large-scale cross-linguistic study showed that predictors of DD vary across languages, due to differences in orthographic depth . More prThe relationship between RAN and reading supports the notion that RAN accounts for variance in reading beyond the effect of phonological awareness and verbal short-term memory; e.g., ,13,14. MA double-deficit hypothesis of DD ,17 has bAs for WM, links between reading performances of children with DD and WM, measured by span tasks, are well established ,22,23. TAlong with the core predictors of DD, a more basic ability has been observed to be associated with dyslexia-related difficulties, namely, auditory temporal processing ,26,27. WAlthough the majority of research on the predictive nature of the aforementioned cognitive skills has primarily focused on children, few contributions reported significantly lower performances in RAN , WM 33,,33,34, aIn order to extend the existing research on the predictive role of such a sub-set of reading-related cognitive abilities to older populations and in a language with a regular orthography, the associations between RAN, verbal WM, rhythmic perceptual abilities, and reading performances have been explored in a study involving Italian undergraduate students with and without DD.Our decision to focus only on RAN, WM, and rhythmic abilities as predictors of reading in an Italian adult population, thus excluding phonological awareness, stemmed from the tendency for readers in a transparent language to score highly in phonological awareness tests . MoreoveThe main aims of the present study were the following: (a) Investigating the specific reading and neuropsychological profile of a group of Italian undergraduates with a diagnosis of DD. To do so, their performance in a battery of behavioral tests assessing reading and a subset of reading-related abilities—which have been identified as core predictors of DD in transparent orthography by previous literature concerning children—was compared with that of a typically-reading control group; (b) Measuring the independent and combined contributions of rapid-naming, verbal WM, and rhythmic skills on specific reading parameters—namely, reading speed, reading accuracy, and global reading performance—in a sample of undergraduates who are native speakers of a transparent language ; (c) Testing the contribution of the strongest predictor of reading performance in estimating an Italian undergraduate’s probability of receiving a diagnosis of DD.Thirty-nine Italian undergraduate students, aged 19–27 , participated in the study. Participants were enrolled in undergraduate courses  at three universities of Milan, Italy. Their average academic grade level at recruitment was of 26.25 (SD = 1.90), considering the 30-point scale used by Italian universities for grading ordinary exams. Since the assessment battery included a measure of rhythm discrimination ability, we controlled for the influence of musical expertise. Hence, we collected information about participants’ music practice: 18 participants reported to have practiced a music instrument  for at least 1 year.Nineteen participants out of the whole sample had a diagnosis of DD (ICD-10 code: F81.0), made by independent clinicians prior to the enrolment in the study, on the basis of standard inclusion and exclusion criteria   and of the diagnosis procedure followed in Italy . All parAs for the 20 participants without DD, they had no history of learning problems, nor of educational assistance, had not repeated a grade, and were not on medication. By selecting participants in the highest range of education, and controlling for the aforementioned exclusion criteria, we have minimized the risk of recruiting individuals with other uncorrelated deficits. Typically-reading participants were recruited through each professor of the course in which they were enrolled, who asked them to participate as subjects in at least one experimental study out of a list of ongoing scientific projects, in which the present study was included. Participation was on a voluntary basis and no pressure to take part to the study was exerted. Refusal to participate did not reduce the benefits of participants, who could interrupt participation at any phase of the procedure.Students who agreed to participate were individually contacted by the researcher and, prior to their enrolment in the investigation, written informed consent was obtained. Clinical records and diagnosis documentation of the sub-sample with DD were collected as well.To exclude the influence of potential confounding factors, the two sub-groups of participants  were matched for age, academic grade level, gender, and music expertise see .Participants were asked to undergo a neuropsychological assessment including Italian tests for measuring reading abilities, RAN, verbal WM (digit span), and rhythmic discrimination ability. The battery of tests was administered by a psychologist specialized in cognitive assessment during individual sessions taking place in a quiet room.Participants’ reading skills and reading-related cognitive abilities were measured using the following battery of tests. Text reading. The ability to read aloud prose texts was assessed using the ‘Text reading speed test for high-school and higher education’ [ucation’ , which cVerbal working memory. Forward and backward digit span subtests were used to assess verbal WM [erbal WM . Scores Rapid Automatized Naming. Naming of familiar stimuli was assessed using the ‘Rapid Automatized Naming test–RAN’ [est–RAN’ . Two subRhythm discrimination. The ability to discriminate acoustic rhythmic patterns was assessed using an ad hoc devised test with a same-different-judgment task. Twenty pairs of rhythmic patterns of drum same-pitch notes were presented as pre-recorded auditory stimuli. All items featured a complex time signature , so as to set a suitable difficulty level for an adult population. Straight after listening to each pair of rhythms, the participant had to judge whether they were identical or they differed in metrical structure. Scores were computed as the number of incorrect responses.z-scored reading speed and accuracy measures were compared for each subgroup using non-parametric statistics. First, we measured differences in performance between the two sub-groups (dyslexia vs. non-dyslexia) in all tasks using non-parametric tests. In order to investigate further the differences in reading profiles of undergraduates with and without DD in terms of specific decoding parameter development, z-scores).Then, we employed regression analyses to test the predictive role of the abilities in question on reading. More precisely, three linear regression models were tested to measure the contribution of RAN speed, RAN accuracy, verbal WM, and rhythm discrimination in predicting the variance of each reading parameter  and global reading performance  (where Z is the z-score of the test statistic and N is the number of observations).Effected sizes have been reported as p-values are two-tailed.All reported Mean values of the observed measures have been compared between the two sub-groups of participants, namely, undergraduates with and without DD, prior to testing regression models including reading and diagnosis of DD as outcomes.z-scored reading measure in the DD group was below the cut-off of −2 SDs from the mean, as provided for by the Italian diagnosis criteria [Significant differences emerged for almost every measure see . More prcriteria . Such reBoth RAN speed and accuracy performances differed significantly between the two groups, with the DD group showing a slower and more inaccurate RAN. As for verbal WM, a significant difference emerged in both forward and backward digit span subtests, confirming difficulties in the DD group. Finally, the two subgroups performed similarly in the rhythm discrimination task, as no significant differences emerged.z-scored performances in each reading parameter, namely, reading speed and accuracy, were compared considering each subgroup of participants separately.To investigate the characteristics of reading profiles in adults with a diagnosis of DD, p = 0.01; η2 = 0.17), with reading speed performance being lower than accuracy performance . As expected, typical readers showed normative and similar performances in both reading parameters   see .r’s ranged between 0.35 and 0.52; therefore no strong correlations emerged. Furthermore, collinearity diagnostics confirmed the assumption of no multicollinearity in the multiple regression models performed .Three linear regression models were tested to measure the predictors’ contributions to each specific reading parameter  and to global reading performance. To exclude multicollinearity between predictors, correlation matrices have been computed. Significant Pearson’s p < 0.0001), accounting for a large portion of its variance  = 29.46; p < 0.0001).Firstly, reading speed was considered as the dependent variable. RAN speed only was found to significantly predict reading speed , RAN accuracy , and rhythm discrimination  together were found to significantly predict reading accuracy, accounting for a large portion of its variance  = 13.30; p < 0.0001)  see .p < 0.0001), RAN accuracy , and verbal WM  were found to predict reading performance independently. More precisely, RAN speed accounted for 50% of global reading variance  = 37.11; p < 0.0001) and RAN accuracy for roughly 25%  = 11.58; p < 0.01), whereas verbal WM contribution was smaller  = 8.15; p < 0.01)  was tested as the dependent variable. RAN speed  see .After the regression analyses, which led us to identify RAN speed as the strongest predictor of global reading performance in undergraduates, we tested if an individual’s probability of receiving a diagnosis of DD changes according to their RAN speed, employing a logistic regression model with the binary outcome dyslexia/non-dyslexia.2 = 23.97; p < 0.0001). Nagelkerke’s R2 of 0.61 indicated that RAN speed significantly contributed to the prediction of grouping participants according to their diagnosis of DD  (see Results confirmed that RAN speed produced a strong prediction of diagnosis of DD in undergraduates (Model: χ.01) see .The aim of the present study was to explore whether and to what extent a set of reading-related cognitive abilities—namely, RAN, verbal WM, and rhythm discrimination—predicted reading skills in Italian undergraduate students with and without DD.Our decision to focus on undergraduate students was driven by the exponentially growing number of Italian individuals with a diagnosis of LD who decide to undertake university studies and enroll in LDs services for receiving special education aids. We suggest that a better understanding of their specific neuropsychological profile, relative to their typically-reading peers, and the identification of the cognitive predictors of their specific reading difficulties would foster the development of diagnostic and rehabilitation tools specifically designed for this population.z-scores exceeding the clinical cut-off of −2 SDs below the normative sample mean, as defined by Italian diagnosis criteria [The two observed reading parameters  were found to be both significantly impaired in the DD group (with both mean criteria ). Furthecriteria . RAN and verbal WM measures were found to be significantly lower in the subgroup of participants with a diagnosis if DD, relative to the typically-reading group, consistently with previous literature on adult DD ,33,34. TRhythmic abilities, as measured by the rhythmic discrimination task, did not differ between groups.As for the unique and concurrent contribution of the studied predictors to reading, RAN speed was found to be a strong independent predictor of reading speed, explaining 44% of its variability. As for reading accuracy, 53% of its variance was shared between RAN speed, RAN accuracy, and rhythm discrimination. Finally, global reading performance was independently predicted by RAN speed, accounting for 50% of its variance alone and, on a smaller scale, by RAN accuracy and verbal WM.Our finding that RAN is predictive of both text reading speed and accuracy is consistent with the results by Di Filippo and colleagues  in typicThe ability to detect differences in auditory rhythmical patterns was found to be associated with reading performances in Italian adults with DD, consistently with many developmental studies ,26,27, tThe contribution of rhythmic abilities to the prediction of text reading was found to be specific for the accuracy parameter, consistently with the findings by Flaugnacco et al. , who repFinally, RAN speed produced a strong prediction of the probability to receive a diagnosis of DD, accounting independently for 61% of its total variation. The binary dependent variable entered in the logistic regression model  was defined by the diagnoses of DD made by independent clinicians prior to the enrollment in the present investigation. The standard Italian diagnostic procedure for DD  includesThe selection of the predictors and outcome measures considered in the present investigation was driven by both methodological and theoretical reasons. As for the predictors, only RAN e.g., ,32, verbWe exclude that articulation could have had a significant role on reading or RAN performance. In their study on Italian children, Di Filippo and colleagues  found noN = 39). However, with a sample size of 39, the statistical power of a multiple regression model comprising 4 predictors would be 0.99, with a large effect size of . Power analyses for the regression models applied to our data ranged from 0.81 to 0.99. We therefore assumed that, in spite of being rather small, a sample size of 39 would be adequate for employing the regression analyses here reported.As any small-scale investigation, the present study has a few limitations that should be taken into account, the first being the small sample size (Another potential limitation of the study is the different methods of recruitment used for the undergraduates with and without DD. We understand that undergoing a neuropsychological assessment could potentially have a different meaning for the participants of two sub-groups. We argue that, since participants of both groups had, however different, a motivation to participate in the study, no major difference in the level of engagement would emerge. The aim of the present study was to extend the knowledge about the predictive nature of a set of cognitive skills, widely investigated in child populations, to Italian adults’ reading ability. RAN, verbal WM, and rhythmic perception abilities were found to be associated with prose reading speed and accuracy in a sample of undergraduate students with and without a diagnosis of DD. Both reading speed and accuracy performances were found to be significantly impaired in the subgroup of participants with a diagnosis of DD, with the speed parameter being significantly lower compared to accuracy. It has been previously reported that, in individuals with DD, compensatory mechanisms would contribute over development to overcome the reading performance deficit, even though mostly phonological processing and spelling deficits would persist into adulthood ,49. Our Such findings contribute to extend the knowledge about the development of a neuropsychological profile of adults with DD and may have some useful clinical implications. The predictive contribution of RAN could be exploited by devising a screening instrument for DD in adults including RAN tasks. Identifying DD in adults is indeed important for supporting those who want to undertake university studies, whose number is growing , and thuFinally, the dyslexia-related problems that have been found to persist into adulthood may be targeted by remedial interventions specific for adults with DD. As an example, the association between reading accuracy and rhythmic skills may suggest to take benefit from rhythmic interventions specifically focused on synchronization mechanisms in reading, which have been proved to be effective also in undergraduates with DD .


Prostate-specific antigen (PSA) is a serine protease that is secreted by prostate cells and it is useful as a tumor marker for prostate cancer. In this study, the relationship between some of metabolic factors and serum PSA level was investigated. In this cross-sectional study, patients with urinary symptoms or for screening of the prostate cancer (after 50 years of age or 40 years with a family history of prostate cancer), were evaluated. Collected data included metabolic syndrome factors such as cholesterol (Chol), triglycerides (TG), fasting blood sugar (FBS), and body mass index (BMI), serum PSA level, prostate volume and age.P < 0.001, r = 0.30) and prostate volume . There were not significant relationship between serum PSA level with TG , Chol , FBS , and BMI . 481 patients were enrolled to this study with the average age of 60.69 ± 9.72 years and the average PSA level of 1.70 ng/ml. Data analysis showed that there was a significant relationship between serum PSA level with age ( This study showed that, with increasing age and prostate volume, serum PSA level increased, and an increase in the levels of cholesterol, TG, FBS and BMI did not have significant effect on serum PSA level. Prostate-specific antigen (PSA) is a serine protease that is secreted by prostate cells and it is useful as a tumor marker forprostate cancer. Screening by PSA, has reduced the age of the detection of prostate cancer and it has become a middle-agedpeople cancer. Data analysis showed that there was a significant relationship between serum PSA level, age and prostate volumeand there were not a significant relationship between serum PSA level, TG, Chol, FBS and BMI. This study shows that, withincreasing age and prostate volume , serum prostate-specific antigen (PSA) level increased, and an increase in the levels ofcholesterol, triglycerides (TG), fasting blood sugar (FBS) and body mass index (BMI) did not have significant effect on serumPSA level.Prostate cancer is the fourth prevalent cancer in the world and the most prevalent non-skin malignant disease in men, and the second cause of cancer death in American men, and its prevalence is higher in developing countries . ScreeniPSA  is a serine protease, and it is almost exclusively secreted by prostate epithelial cells, and it is used to detect prostate cancer in asymptomatic individuals over 50 years, people over 40 years with a family history of prostate cancer, and those who come with prostatism symptoms .Even though serum PSA level in men is considered less than 4 ng/ml, but this amount is influenced by various factors such as benign prostatic hyperplasia, a patient’s age, prostate weight, recent history of prostate massage or manipulation and severe infection of the prostate or prostatitis. In cases that the PSA is between 4-10 ng/ml, the use of other tests such as PSA density (PSA to prostate weight ratio), PSA velocity (the increase in PSA over a year), and the ratio of free PSA to total PSA is helpful to distinguish prostate cancer from other prostatic diseases  or for screening of the prostate cancer, after 50 years of age or 40 years with a family history of prostate cancer.Inclusion criteria included patients with benign prostate disorders that were proved by PSA and rectal examination, whether the patient had came for screening or was a candidate for medical or surgical treatment. If the patient had urinary tract infection, he underwent antibiotic treatment and PSA testing was performed again. If the PSA was between 4-10 ng/ml, the patient was asked to perform the free to total PSA test again. Patients who had a history of prostate cancer at present or in the past and were under supervision or treatment, and also patients for whom there was a strong suspicion of prostate cancer due to PSA greater than 10 or by abnormal free to total PSA test (in case of PSA being between 4-10 ng/ml), or abnormal prostate consistency in rectal examination, and he was a candidate for prostate biopsy, were excluded from the study.A questionnaire was used to collect the information. The patients age, height and weight and size of the prostate through the rectal examination and sonography, were recorded. Also all patients were asked to do PSA, fasting blood sugar (FBS), and blood lipid tests including cholesterol and triglycerides (TG) and the results were recorded.1) The research followed the tenets of the Declaration of Helsinki; 2) informed consent was obtained, and they were free to leave the study at any time; and 3) the research was approved by the ethical committee of Semnan University of Medical Sciences.To show magnitude and direction of probable associations, we calculated Spearman’s correlation coefficient using SPSS 16 software, and P value less than 0.05 was considered as significant.In this study data of 481 people were analyzed. The mean age of the participants was 60.69 ± 9.72 (SD), the youngest was 36 years old and the oldest was 97 years old. Among all participants, 243 ones (50.5%) were 60 years old and younger, and 238 ones (49.5%) were older than 60. In terms of the checked PSA values, mean PSA value for these people was 1.70 ± 1.44 (SD), ng/ml. P<0.001, r=0.3). Data analysis also showed, a significant relationship between serum PSA level, and prostate volume . However no significant relationship between serum PSA level and TG , FBS , Chol  and BMI  were observed. Considering the correlation coefficient between laboratory factors related to metabolic syndrome and PSA, there was a significant positive correlation between PSA and age, revealed the PSA level increased along with age (2) in 40-59 years of age, and the reason of this relationship has been explained with these two hypotheses:PSA is a glycoprotein that is secreted primarily from prostate cylindrical cells, and is strongly influenced by androgens. Even though it is organ-specific but it is not cancer-specific. There is a considerable overlap in PSA levels among men with benign prostate diseases versus men with malignant prostate disease ,2. Some 1- PSA concentration is regulated by androgens, and androgenic activities decrease in obese people.2- People with high BMI have high plasma volumes which can decrease serum PSA concentration .Another study by Liu-Ming et al on healthy men who went to urologic clinics for check-ups had the same result .In a study that was conducted by Han et al about the relationship between some metabolic syndrome factors such as FBS, TG, high-density lipid (HDL-C), BMI, age and serum PSA level , it was Also the study, conducted by Mohammad et al, showed a negative relationship between serum PSA level and BMI, TG, and FBS, with similar reasons .In another study that was conducted by Cvitkovic et al, a negative relationship between FBS and serum PSA level, as well as a positive relationship between age and PSA level was shown. The cause of a positive relationship between PSA and age is that prostate volume increases with age, thus the production content of PSA in prostate tissue increases . MoreoveThere were limitations to this study, as in other studies, which can somewhat affect the results of the study, including the limited population, the type of diabetes and received medicine in study subjects had not been separated. In relation to high BMI, the type of diet may also affect the results, as well above all is that the absence of prostate cancer in men was not proved by biopsy.The present study showed that serum PSA level increases with age, and prostate volume, while no relationship were observed to changes in PSA levels, by increasing TG, Chol, FBS and BMI. We hope that, in the near future, we can increase the precision of the study by increasing statistical population and reducing the restrictions which can be somewhat effective on clinical judgment.This is a single-center non-randomized study with a limited number of patients.This study is adapted from the M.D. thesis of Azadeh Beiglarzadeh (Thesis#417). We gratefully thank the Research and Technology Deputy Semnan University of Medical Sciences and all the patients and people who assisted us in conducting this thesis. We would like to thank the Clinical Research Development Unit of Kowsar Educational and Research and Therapeutic Center of Semnan University of Medical Sciences for providing facilities to this work.The authors declared no competing interests.DA, AA and AB conducted the research. MM analyzed the data. AB prepared the primary draft. DA and AA edited the final draft. All authors signed the manuscript.This research was supported by Surgery Department, Semnan University of Medical Sciences, Semnan, Iran.


Choroidal neovascularization (CNV) is a severe eye disease that leads to blindness, especially in the elderly population. Various endogenous and exogenous regulatory factors promote its pathogenesis. However, the detailed molecular biological mechanisms of CNV have not been fully revealed. In this study, by using advanced computational tools, a number of key gene ontology (GO) terms and KEGG pathways were selected for CNV. A total of 29 validated genes associated with CNV and 17,639 nonvalidated genes were encoded based on the features derived from the GO terms and KEGG pathways by using the enrichment theory. The widely accepted feature selection method—maximum relevance and minimum redundancy (mRMR)—was applied to analyze and rank the features. An extensive literature review for the top 45 ranking features was conducted to confirm their close associations with CNV. Identifying the molecular biological mechanisms of CNV as described by the GO terms and KEGG pathways may contribute to improving the understanding of the pathogenesis of CNV. Choroidal neovascularization (CNV) is a serious eye disease involving the abnormal growth of blood vessels in the choroid region –3. The gClinically, most patients with CNV share a group of characteristic signs and symptoms, including painless loss of vision, metamorphopsia, paracentral or central scotoma, and apparent changes in image size perception , 13. GenRecent publications have partially revealed the detailed pathological mechanisms of CNV, which involve the interactions between genetic factors and exogenous environments. For the environmental factors, the personal physical factors induced by the exogenous factors are directly involved in the pathogenesis . Age, obAs mentioned earlier, the genetic basis and the environmental influences of CNV have been revealed. However, its biological molecular mechanisms have not been explained thoroughly. Here, the detailed biological processes, cellular components, and molecular functions that may participate in the pathogenesis of CNV were screened out by using computational methods. In this study, GO  and KEGGThis study aimed to extract some key GO terms and KEGG pathways that share close biological associations with CNV by using a computational framework. The flowchart of our method is illustrated in p < 0.1 and fold change ⩾ 1.5 among 31 normal, 7 MD1, 4 MD2, 17 Dry AMD, 2 GA, 4 CNV, and 3 GA/CNV samples. Therefore, the final CNV genes we used were both reported by literature and differentially expressed.In 2012, Newman et al.  reportedThe obtained 35 CNV genes were mapped onto their Ensembl IDs. We excluded IDs that are not in the PPI network reported in STRING (Version 10.0) . 38 EnseThe goal of this study was to refine important GO terms and KEGG pathways that are associated with CNV genes. To fulfill that goal, all the genes in the dataset were needed to be represented by all the GO terms and KEGG pathways. Here, the enrichment theory  of the GGO Enrichment Score. The GO enrichment score was utilized to represent the association between a GO term and an involved gene as a numeric value. For a given GO term, such as GOj, and a gene g, the gene set G1 consisted of genes annotated to GOj and gene set G2 consisted of the neighbor genes of g in the protein–protein interaction network reported in STRING (http://string-db.org/) [j and g can be defined as the −log10 of the hypergeometric test p value [G1 and G2 according to the following equation:N is the total number of genes in humans, M is the number of genes in G1, n is the number of genes in G2, and m is the number of the common genes of G1 and G2. A large enrichment score of GOj and g indicated a close relationship between them. In this study, 20,686 GO terms were considered. Thus, 20,686 GO enrichment scores were calculated for each gene in the dataset, which were obtained by using an in-house program using R function phyper. The R code is “score ← −log10),” where numW, numB, and numDrawn correspond to the number of genes annotated to GOj, number of genes not annotated to GOj, and number of neighbor genes g, respectively. db.org/) , a well- p value , 32–35 oKEGG Enrichment Score. Similar to the GO enrichment score, the KEGG pathway score was calculated using the same theory to represent the quantitative associations between the KEGG pathways and genes in the dataset. For a given KEGG pathway Kj and a gene g, G1 was a gene set containing genes in Kj and G2 had the same meaning as described in preceding paragraph. The KEGG enrichment score shared a similar definition with the GO enrichment score between Kj and g, which was formulated asN, M, n, and m share similar definitions as described in  and p(f) are the marginal probabilities of c and f and p is their joint probabilistic distribution. According to  maximum relevance and (2) minimum redundancy. According to their names, the former criterion measures the importance of features by relying on their correlation to target variable, whereas the latter criterion provides a guarantee that the selected features also have minimum redundancies. If one decides to construct an optimal feature subspace, both maximum relevance and minimum redundancy should be used. In this study, the purpose was to extract important features that are closely related to CNV rather than construct an optimal feature subspace. Therefore, only the criterion of maximum relevance was employed to rank the features in this study. The maximum relevance of each feature was measured by the mutual information (MI) between the feature and the target variable. For each feature,  follows:Ic,f=∬pc,N is the total number of features in the feature space. A high rank received by a feature indicates a strong association with CNV. Based on the properties of the top ranked features, a new insight into the CNV can be proposed for the investigation of the corresponding GO terms and KEGG pathways.Based on the MI value assigned to each feature, the feature ranking list called MaxRel feature list was obtained and formulated as follows:As described in As mentioned in the preceding paragraphs, not all GO terms or KEGG pathways shared equal roles on influencing the progression of CNV. Thus, extracting the key GO terms or KEGG pathways was necessary. By applying the maximum relevance criterion, all the features were ranked by their relevance to the target variables, and the rank of a corresponding feature in the output MaxRel feature list for a GO term or KEGG pathway indicated its association with CNV. According to their MI values, some GO terms or KEGG pathways received high MI values in the MaxRel feature list; these features were extracted and their importance was further investigated. To determine the cut-off of MI value, a curve was plotted in As mentioned earlier, based on our current computational methods, a group of functional biological processes that may directly contribute to the initiation and progression of CNV as a pathological mechanism were screened out. In the prediction list, the top 45 biological processes described by the GO terms as optimal CNV-associated biological processes were selected. Due to the limitation of such manuscript, an individual analysis of all the items was not feasible. Therefore, the top terms were chosen, and their respective connection with CNV according to recent publications was discussed. According to recent publications, such GO terms can be summarized into three major subgroups: angiogenesis, local neural metabolism, and immune-associated biological processes. The detailed discussion follows.GO: 0031091 and GO: 0031093—both describe the functional cellular components of platelet alpha-granules. In 2015, a specific study [The two GO terms in our prediction list—ic study  on proanic study . Therefo GO: 0038133 describes a detailed pathway called the ERBB2-ERBB3 signaling pathway. According to recent publications, this signaling pathway contributes to the regulation of cell survival and tumorigenesis [ GO: 0038129, also describes the ERBB3-associated signaling pathway. This finding not only implied the prediction consistency of the current computational methods but also further confirmed the specific role of such pathways during the initiation and progression of CNV.GO termigenesis , 56. As igenesis –59. GiveGO: 0031983 was the next predicted GO term and describes the vesicle lumen as a functional cellular component. As the parent term of GO: 0060205 describing the cytoplasmic vesicle lumen, such cellular component definitely is associated with the initiation and progression of CNV. As for detailed literature evidence, in 2009, a specific study on the vascular permeability and pathological angiogenesis of CNV confirmed that the vesicle lumen in living cells is related to the vascular hyperpermeability and abnormal angiogenesis [ogenesis  and abnoogenesis ; thus, s GO: 0005576, describes a general term called extracellular region. Various extracellular substances participate in the pathogenesis of CNV, including LOX [ GO: 0035767, as the next predicted GO in our prediction list, describes an effective biological process called endothelial cell chemotaxis. Based on recent publications, such biological process is involved in the activation of platelets [The next GO term, calledding LOX , LOXL2 [ding LOX , Thy-1 [ding LOX , and intding LOX . Such splatelets  and exoslatelets  and angilatelets  are direGO: 0060205, as another cellular component associated item, describes the cytoplasmic vesicle lumen. Based on recent publications, such cellular component participates in autophagy and secretion-associated biological processes in living cells [ GO: 1902847 describes the regulation of neuronal signal transduction. In the biological process of neuronal signal transduction, a specific gene called IKK2 has been confirmed to be significant [ GO: 1902949 describes the positive regulation of tau protein kinase activity. Tau protein is a major pathological factor that contributes to the initiation and progression of Alzheimer's disease (AD) [ng cells , 71. As ng cells , 73. Thinificant . Coincidnificant , 76. Thease (AD) –79. Duriase (AD)  and partase (AD) . Given tase (AD)  and its ase (AD) , tau pro GO: 0061517 describes the proliferation of a specific immune-associated cell subgroup: macrophage. Based on recent publications, macrophages contribute to CNV by regulating CCR2-dependent and proangiogenic biological processes [ GO: 0061518 in our prediction list. Mediated by neuroprotectin D1, microglial ramifications and redistribution participate in the pathological processes of CNV [The GO termrocesses , 84, indrocesses . Apart fs of CNV . Therefos of CNV , this prs of CNV . Besidess of CNV , GO: 004s of CNV , and GO:s of CNV , 91. TheBased on our presented computational method, a group of functional biological functions that have been confirmed by recent publications to be related to the pathogenesis of CNV were screened out. Such predicted biological processes not only further revealed the detailed pathological mechanisms of CNV but also provided a new tool to identify potential functional disease-associated biological processes in multiple categories of the disease. Finally, we will try our best to develop a computational method based on some extracted features in this study to predict novel CNV genes in the future.


F1 score of 0.9142, which was better than other popular classification methods, and an average receiver operating characteristic (ROC) of 0.9475 showed a significant correlation between these selected biomarkers from microbiome and corresponding phenotypes. The results from this study indicate that machine learning is a vital tool in data mining from microbiome in order to identify disease-related biomarkers, which may contribute to the application of microbiome-based precision medicine in the future. The dysbiosis of human microbiome has been proven to be associated with the development of many human diseases. Metagenome sequencing emerges as a powerful tool to investigate the effects of microbiome on diseases. Identification of human gut microbiome markers associated with abnormal phenotypes may facilitate feature selection for multiclass classification. Compared with binary classifiers, multiclass classification models deploy more complex discriminative patterns. Here, we developed a pipeline to address the challenging characterization of multilabel samples. In this study, a total of 300 biomarkers were selected from the microbiome of 806 Chinese individuals , and then logistic regression prediction algorithm was applied to those markers as the model intrinsic features. The estimated model produced an  The human microbiome plays an important role in energy harvesting, metabolism of dietary components, immunity, inflammatory bowel disease, cancer therapy, and the progression of cancers –4. RecenMachine learning algorithms have been widely introduced to tackle problems in both genomics and bioinformatics, for instance, the identification and annotation of genomic regulatory elements like promoters, transcription start sites, enhancers, splice sites, and the classification of various phenotypes . Some reHere, we performed multiclass classification analysis on the microbiome of 806 Chinese individuals, together with phenotype information, including gender, age, and BMI. Feature-associated gene markers were identified after addressing the imbalanced datasets between classes, which could be used to establish models to predict the type of disease. The human microbiome-based knowledge that associated with the abnormal phenotypes provides cues to the future application of precision medicine .We process 806 shotgun metagenomic samples from three studies, 170 type 2 diabetes (T2D), 130 liver cirrhosis, 123 rheumatoid arthritis (RA), and 383 normal controls, to identify microbiome-based biomarkers. All these normal controls are with normal values on recent screen for physical examination and other clinical testing –17. Thosai is the relative abundance of gene i, xi is the number of reads that were aligned to gene i of IGC reference, Li is the length of gene i, and j is the total number of genes.Sequence Read Archive (SRA) datasets or compressed files of raw reads were downloaded from NCBI or EBI. As described in One key problem that we are trying to solve in this study is to identify disease-associated biomarkers in human microbiome and to build a classifier with the selected biomarkers that can classify a single sample with accurate diagnostic disease status. In this study, there are three challenges in biomarkers selection. The first one is that the selected feature list is susceptible to the training data and is sensitive to different methods due to a small sample size in high-dimensional features. The second challenge is that the process of feature selection will be performed on multiclass datasets, which is much more difficult than on binary datasets. The last challenge is the complexity of computation. Some methods have been reported, such as Max-Relevance and Min-Redundancy (mRMR) and iterative sure independence screening (ISIS), which are robust algorithms in feature selection and have been applied in T2D biomarker discovery . ConsideReferring to bioinformatics and genomics, a common problem in the application of classification algorithms is the imbalanced sample size of classes, because machine learning algorithms naturally work well on quite equal number of samples in each class. At present, datasets with skewed labels are becoming more and more frequent, and unbalanced samples have been reported to generate wrong prediction models. One approach to address this plight is to resample the dataset to offset this imbalance to generate a more robust and fair decision boundary. Random resampling of the data is a common way to solve those problems as seen in other studies . While tK-nearest neighbor (KNN) classifier to achieve undersampling. It selects a given number of the closest majority samples for each minority sample to guarantee that every minority sample is surrounded by some majority samples. On the other hand, SMOTEENN, the method of oversampling, tends to remove examples from both classes by filtering the misclassified example's three nearest neighbors from the training dataset. Thus, SMOTEENN shows an improved performance on datasets with a small number of positive samples [In this study, NearMiss (version 3) and SMOTEENN were applied to solve unbalanced datasets. NearMiss uses the  samples .F1 score and the receiver operating characteristic curve (ROC) [F1 score can be interpreted as a weighted average of precision and recall. Correspondingly, the F1 score reaches its best value at 1 and worst value at 0. The relative contributions of precision and recall to the F1 score are equal. The formula for the F1 score isMore than one measurement can be used to assess the performance of machine learning algorithms, such as ve (ROC) . The F1 F1 score of each class is computed. To evaluate the precision of the algorithm, the AUC was also calculated for comparison with that in previous work.In the multiclass and multilabel case, the weighted average of the k-nearest neighbors (KNN), logistic regression (LR), random forest (RF), support vector machine (SVM), gradient boosting decision tree (GBDT), stochastic gradient descent (SGD), and adaptive boosting (ADA), were performed on the selected features. Based on the F1 score, the best algorithm of classification on this dataset was selected in this analysis.The prediction performance of the selected biomarkers should be measured by training a classifier on the data that are restricted to the selected biomarkers. Seven popular classifiers, The classification of multiclasses can be implemented as known one-versus-all strategy . This stScikit-learn method is a simple but efficient tool for data mining and subsequent data analysis. It brings machine learning to nonspecialists with a general-purpose high-level language, where the API of seven algorithms was provided .We utilized the 5-fold cross-validation approach to evaluate the performance of prediction models. Following this method, the dataset was randomly divided into five equal-sized partitions. Each time we fitted a model on four partitions as the training data and test it on the remaining partition. The process was repeated five times and the average result was used to generate the estimation.http://meta.genomics.cn/meta/dataTools. Finally, we interpreted the biomarkers with details in multiple levels, such as Phylum, genus, KEGG, and eggNOG.The integrated gene catalog that has been annotated is a comprehensive resource for metagenomics analyses . To undehttp://genevenn.sourceforge.net/).To address the problem whether these biomarkers are specifically associated with a particular phenotype, Venn diagram was plotted with the online program (P = 1.11e−27) among these four groups. However, in line with previous findings, the body mass index (BMI) shows no significantly direct correlation with phenotype  [In this study, 806 samples with different phenotypes were analyzed. Those samples were from three large available metagenome-wide association studies at present, which focused on type 2 diabetes (T2D), liver cirrhosis, and rheumatoid arthritis (RA)  7, 14–1–114–17. A total of 383 samples with normal phenotype were sequenced to generate an average of 9.30 (±4.02) Gb data, and 92% of these were aligned to the IGC reference. In addition, 423 samples with abnormal phenotype generated a total of 11.27 (±6.95) Gb data also with an average mapping rate of 92% . The strf1 value of optimized combination achieved 0.9142 on 300 features with the logistic regression , supporting the fact that this model is stable and accurate . The AUC that we obtained with optimized features and algorithm was 0.85 in normal samples, 0.99 in type 2 diabetes, 0.96 in rheumatoid arthritis, and 0.99 in liver cirrhosis, respectively . The AUCThe predictive power of these microbiome biomarkers is promising to be applied to disease diagnostics, especially disease screening within large-scale population. The multiclass classifier is a potential tool in the personalized medicine in a wide spectrum of phenotypes.ANOVA was performed to investigate the difference among these four groups, and these biomarkers showed significant difference . These b P value from ANOVA is DOF003_GL0053139, which is a gene from the phylum of Firmicutes and the genus of Clostridium. The relative abundance of this biomarker in RA is higher than that of others, which is consistent with the previous report [ Bacteroides with its function being well studied [It is well accepted that many factors synergistically shape the diversity of human microbiome, so phenotype-specific biomarkers are important in the evaluation of health status. The top biomarker in the ranking list according to thes report . The bio studied .To comprehensively investigate the phenotype-related microbiome, we performed pairwise comparison of the relative abundance of one phenotype against other phenotypes. A total of 117 biomarkers were significantly correlated with T2D disease, 257 biomarkers with rheumatoid arthritis, and 220 biomarkers with liver cirrhosis, respectively . Bacteroides involved in the process of protein and carbohydrate breakdown. However, 69 of 117 biomarkers were significantly reduced in T2D disease and 78% of them were Firmicutes known to enhance the absorption of fat. All these results support the previous finding that the ratio of Bacteroides/Firmicutes was altered in T2D patients [In the T2D group, 48 biomarkers were enriched and 81% of them werepatients . Veillonella, one biomarker of Haemophilus, and 74% of 73 depleted biomarkers of Bacteroides are Gram-negative bacteria in this study. Besides, we also identified 184 RA-enriched biomarkers including 16 Clostridium, 16 Faecalibacterium, and 10 Blautia as well as Coprococcus, Enterococcus, Eubacterium, and Roseburia. The component of biomarkers found in RA patients was also consistently reported from previous results.In the early stage of RA, Gram-positive bacteria were enriched and Gram-negative bacteria were depleted in the microbiome of RA patients . However Streptococcus and 2 Veillonella, in line with previous work. It indicated that these two genera should play important roles in the development of liver cirrhosis. Interestingly, another important genus, Faecalibacterium, an anti-inflammatory commensal bacterium, was also found [In the liver cirrhosis group, 66 biomarkers were found to be enriched in liver cirrhosis, including 8so found , 32. Clostridium, 13 with Faecalibacterium, and 10 with Blautia as well as Coprococcus, Enterococcus, Eubacterium, Roseburia, and Ruminococcus. The phenomenon may be attributed to interindividual variation in the human microbiome.In this study, 154 biomarkers were depleted in the microbiome of liver cirrhosis patients, which is similar to the RA enriched biomarkers, including 12 with Streptococcus ( Streptococcus is associated with liver disease [To address the problem of whether these biomarkers are specific to a specific phenotype, Venn diagram shows that no biomarker was shared by three phenotypes. T2D shared 78 biomarkers with RA and 39 biomarkers with liver cirrhosis. RA shared 179 biomarkers with liver cirrhosis. No biomarker was specific to T2D and RA. It is noteworthy that two biomarkers were specific to liver cirrhosis. These two biomarkers are 1000570.HMPREF9966_1928 and 1000570.HMPREF9966_1926, which belong totococcus . Previou disease .To characterize the functional role of microbiome in phenotype, we annotated each biomarker by the KEGG database. The pathways that include more than 10 biomarkers are related to membrane transport, genetic information processing, translation, and cellular processes and signaling . ParticuIn this study, we improved the performance of classification considering the problem of multiclass and imbalanced datasets by using the technology of machine learning. A total of 300 biomarkers were selected from 13,990 features including clinical information and the matrix of relative gene abundance from 806 human microbiomes through using logistic regression classifier. The phenotype-specific biomarkers were interpreted comprehensively.Our study pinpoints the potential role of human microbiome which may lead to the research and development of microbiome knowledge-based personalized precision medicine by monitoring and modulating the diversity of microbiome . While i Bacteroides/Firmicutes was altered in T2D patients, which is in line with previous study. Second, these biomarkers related to RA were found to be depleted in Gram-negative bacteria and enriched in Gram-positive bacteria. Third, Streptococcus and Veillonella were found to be enriched in liver cirrhosis and, particularly, another bacterium named Faecalibacterium was also found. Finally, some bacteria were enriched in one phenotype; however, they were depleted in anther phenotype. All these findings suggest the complexity of microbiome and give us cues to treat microbiome according to the status of one person.This study uncovered some interesting phenomena. First, the ratio of Streptococcus were found. Other biomarkers were shared by two types of disease. Many intriguing biomarkers play important role in the core metabolism process, such as O2.UC32-1_GL0019091 that belongs to K03088, which is thought to play a role in enhancing transcriptional specificity in low-G+C Gram-positive bacteria [Disease-specific biomarkers were analyzed in this study and two liver cirrhosis specific biomarkers that belong to the genus ofbacteria .Incorporated with clinical information and the profiling of human microbiome, the healthy status of one individual can be predicted. However, those previously published microbiome-based biomarkers were almost specific to the population studies; it means that all these biomarkers should be demonstrated in other independent study cohorts. Other pitfalls and challenges such as the diversity of dietary, standardization in sample collection and the treatment, and different microbiome analytic tools play a vital, important role in the utility of microbiome. Thus, comprehensive information of human and standardization in the pipeline of treatment will be the promise, which will ensure the machine learning to tap its full potential.Finally, this study reveals that gut microbiome biomarkers are able to distinguish abnormal cases from controls with a higher level of specificity than previous results , 16, 17.


P = 0.008), balance , and functional mobility . At follow-up assessment , functional mobility (TUG) remained significantly improved (P = 0.005) in contrast to the other outcome measures. In summary, unsupervised exercises at home with the VR training system led to beneficial functional training effects in subjects with chronic iSCI, suggesting that it may be useful as a neurorehabilitation tool.Key factors positively influencing rehabilitation and functional recovery after spinal cord injury (SCI) include training variety, intensive movement repetition, and motivating training tasks. Systems supporting these aspects may provide profound gains in rehabilitation, independent of the subject’s treatment location. In the present study, we test the hypotheses that virtual reality (VR)-augmented training at home  is feasible with subjects with an incomplete SCI (iSCI) and that it improves motor functions such as lower limb muscle strength, balance, and functional mobility. In the study, 12 chronic iSCI subjects used a home-based, mobile version of a lower limb VR training system. The system included motivating training scenarios and combined action observation and execution. Virtual representations of the legs and feet were controlled via movement sensors. The subjects performed home-based training over 4 weeks, with 16–20 sessions of 30–45 min each. The outcome measures assessed were the Lower Extremity Motor Score (LEMS), Berg Balance Scale (BBS), Timed Up and Go (TUG), Spinal Cord Independence Measure mobility, Walking Index for Spinal Cord Injury II, and 10 m and 6 min walking tests. Two pre-treatment assessment time points were chosen for outcome stability: 4 weeks before treatment and immediately before treatment. At post-assessment , high motivation and positive changes were reported by the subjects . Significant improvements were shown in lower limb muscle strength ,  An injured spinal cord leads to diminished functional recovery. The injured axons are limited in their spontaneous regeneration and compensatory fiber growth –3. From Based on these findings and a previous study by our group , the oveTherefore, in this study, we hypothesized that unsupervised home-based VR-augmented neurorehabilitation training is feasible in subjects with an iSCI and that it would improve their motor functions .Outpatients with a chronic (time since injury >1 year) iSCI (age 41–74 years) from the University Hospital Balgrist  were included in the study by a medical referral between 2013 and 2015, and the sample size was restricted by this time period Table .Exclusion criteria were as follows: head injuries leading to cognitive or visual impairment, spasticity limiting lower limb movements, medication influencing therapy, and psychiatric limitation, depressive symptoms   or otherThe purpose of the study was clear to all subjects, and written informed consent was acquired. The experimental protocol was in accordance with the Declaration of Helsinki and approved by the Canton of Zurich ethics committee .Home-based VR-augmented training was done with the mobile prototype of the YouKicker system  for the lower limbs, which is the successor of the stationary therapy system YouKicker described previously in a clinic-based study  , 19. TheIn collaboration with therapists, clinically relevant exercises for foot and leg while seated or in a standing position were generated. Five VR scenarios were provided on the training system to train foot and leg movements in sitting and standing positions. The system contained applications to train different isolated movements as follows.Footbag (sitting/standing): the subject juggles a ball between the left and right foot. An ankle dorsal flexion (approx. 35/min per leg depending on patient ability) is performed preventing foot drag. The path of the ball is pre-set. Hamster Splash (sitting): hamsters rush to the subject’s feet. With a dorsal flexion of the ankle (approx. 15/min per leg) the subject launches each hamster into a swimming pool. Higher scores are achieved when faster ankle movement are performed. This also leads to more elaborate hamster movements . Get to the Game—Activity of Daily Living (sitting/standing): a virtual person (avatar), representing the subject, walks from home via a tram station to a stadium, as fast as possible. To make the avatar move, the subject has to alternately lift his/her feet. By increasing the range of motion of the ankle and by faster ankle movements, the subject can achieve a better score due to faster and bigger footsteps.Ankle dorsal flexion (three scenarios): Star Kick (sitting/standing): knee extensions are performed by the subjects (approx. 12/min per leg) hitting a ball toward presented stars with foot. For every kick, the subject scores points. With this exercise, the subject trains knee extension not using direct measurement of the knee angle.Knee extension (one scenario): Planet Drive (sitting): Cars are driving on a roadway toward virtual feet. The lower legs are tilted sideways (approx. 4/min per leg) to avoid touching the cars.Leg ad-/abduction (one scenario): All subjects were trained at home on the VR tasks over a period of 4 weeks, with 16–20 sessions of 30–45 min each. The following information was collected at the beginning of the study: age, gender, height, weight, etiology, and level of lesion, AIS, time since injury, medication, pain presence, and intensity. In addition, the motivation was scored by the subjects on an 11-point Numeric Rating Scale (NRS) from 0  to 10  after the completion of each training session.The training system was set up by a therapist at the subject’s home. The subject completed the first training under the supervision of the therapist and on a weekly basis the therapist visited the subject to check the training and collect data. During a typical training session, each subject completed either one block  of training and a Get to the Game session (approx. 5 min), or twice the block without a Get to the Game session. The tasks were always presented in the same order during a session using the muscle groups alternately to prevent fatigue. Around 500 repetitions of ankle movements  and 100 knee movements (Star Kick) with each leg are performed by a typical patient during a training session. When a subject came either to the same and/or higher number of repetitions in three successive sessions  or the number of repetitions was less in three successive sessions  during the week the therapist changed the difficulty level of the task. A higher difficulty level resulted in higher speed or number  of the specific target movements.pre-baseline assessments, and directly before treatment program, i.e., baseline assessments. After finishing of the training program, post-assessments were performed, and 2–3 months after treatment program, follow-up assessments were performed. The results at the four different assessment time points are presented in Table All outcome measures were tested at the University Hospital Balgrist. For outcome stability for the subjects with iSCI before the intervention, two different assessment time points were chosen before treatment: 4 weeks before treatment program, i.e., Outcome measures were included to test muscle strength, balance, and mobility, and for each field, the most conclusive outcome measure was chosen as primary outcome before testing: Lower Extremity Motor Score (LEMS) for lower limb muscle strength, Berg Balance Scale (BBS) for balance during functional activities, and the outcome Timed Up and Go (TUG), which covers functional mobility. This test correlates with performance in other mobility/walking outcomes, e.g., 10 m walking test (10MWT) and Walking Index for Spinal Cord Injury (WISCI) II, in subjects with iSCI . All othThe minimal clinically important differences (MCIDs) are listed in the following section, if available for SCI. MCID is the minimal change of an assessment considering the clinical importance for the subject or clinician.From 0  to 50 , which is measured by the LEMS . The MCI14 balance items, each from 0  to 4 , are measured by the BBS . The MCIThe TUG assesses various aspects of mobility in seconds  . The MCIWith the 10MWT, the time in seconds is measured by walking 10 m and with the 6minWT, and the distance in meter is measured by walking 6 min , 24. TheThe use of assistive devices is assessed by the WISCI II from 0  to 20  , 28. A cThe Patients’ Global Impression of Change (PGIC)  was adapP ≤ 0.017 was set.SPSS 23  was used for statistical analysis. First, pair-wise comparisons were performed between the pre-baseline and baseline assessments with the Wilcoxon signed-rank test. Second, the outcome measures of the averaged pre-baseline and baseline time points were compared to post-assessment and follow-up assessment time points with the Wilcoxon signed-rank test. Third, a correction for multiple comparisons was calculated with the Bonferroni correction and a significance level of The clinical characteristics of the subjects with iSCI (mean age 60 ± SD 10.2 years) are presented in Table The motivation after training was 8.6 ± 1.3. The most attractive games as voted by the patients were the following: Hamster Splash (number of subjects: 5), Star Kick and Planet Drive (2 each), and Footbag and Get to the Game (1 each). The most difficult and challenging game for all patients was “Planet Drive.” The subjects played mainly in a sitting position (chair or wheelchair) but changed to a standing position for the last repetitions of Footbag, Star Kick, and Get to the Game.All subjects familiarized themselves with the VR system quite quickly. Overall, the subjects evaluated the system very positively. It was reported to be user-friendly and they liked the visual features. Some of the subjects could also imagine using the system for longer than the required 4 weeks and reported a positive effect such as being able to lift their feet better, improved sensation in the legs/feet, and improved swimming and walking.Between the time points pre-baseline and baseline, the outcome measures did not differ, which is an indication for outcome stability for the included subjects before the intervention. The values of the outcome measures are presented in Table P ≤ 0.017) in comparison with the averaged pre-baseline and baseline were found in the primary outcome measures such as muscle strength , balance , and functional mobility . In addition, 7 out of 11 subjects improved  in ankle dorsiflexion (L4) and four of them reached the MCID of LEMS  at post-assessment. The secondary outcome measures showed with respect to walking speed/distance and mobility no significant effects: 10MWT (P = 0.169), 6minWT (P = 0.037); SCIM III mobility (P = 0.018), and WISCI II (P = 0.180). Concerning walking speed/distance, seven tested subjects met the limits for the MCID of 10MWT and one subject reached the MCID of 6minWT at post-assessment. In addition, a clinically important difference was shown in two subjects using WISCI II.At post-assessment, significant increases (P ≤ 0.017) in comparison with the averaged pre-baseline and baseline was found in functional mobility . No significant changes were found in muscle strength  and balance  as well as in walking speed/distance and mobility: 10MWT (P = 0.169), 6minWT (P = 0.32), SCIM III mobility (P = 0.026), and WISCI II (P = 0.317).At follow-up assessment, a significant increase , and a general increase in lower limb muscle strength (LEMS) was achieved. In addition, an MCID by one-third of the subjects was reached. These changes may have been of relevance in enabling the observed gains in walking speed, stability, and mobility (reflected by improvements in TUG and BBS). However, it has been argued that changes in the LEMS, i.e., muscle strength, do not necessarily relate to changes in SCIM and WISCI . ReliancFurthermore, longer walking distances included in the outcome measures SCIM mobility and 6minWT (only one subject reached MCID) might not be specifically trained by the performed VR tasks. Nevertheless, the TUG assesses various aspects of mobility which are correlated with performance in for example the 10MWT (one-third of the tested subjects met the limits for the MCID) in subjects with iSCI . In healIn accordance with the objective assessments, 64% of the subjects rated their motor functions as markedly improved  when they were asked after the treatment: “since beginning of this program, how would you describe the change (if any) in activity limitations and motor function related to your condition?” The other tested subjects reported at least minimal improvements . This is in opposition to a report claiming that evaluated functional improvements were not actually perceived as such by subjects with a SCI .Despite the task specificity of the training, i.e., isolated single-joint movements, subjects improved on global functional scores. In other words, this type of training with task- and deficit-specific variation enabled a transfer of gained function to other tasks . In line with our results, a study with lower limb strength training  also showed a transfer of specific training to general improvements. They found attenuated neuromuscular impairments and improved locomotion in subjects with iSCI . AnotherThe central idea of motor learning is repeating exercises, feedback about movement execution and motivation . When foAs mentioned earlier, beside the amount of training, active participation and motivation is a key element for achieving functional improvements . The motInterestingly, the clinic-based training, i.e., training at the hospital with one-to-one therapist–patient support, showed greater improvements of balance and walking capacity in the absolute assessment values as the currently tested home-based system . The setThe study described here is limited by the small and heterogeneous group of 12 subjects with iSCI (AIS C/D with various lesion levels), the uncontrolled study design and non-blinded assessment. While the pre-baseline did at least help to ensure that each subject was at a stable level before the beginning of the intervention, it is recommended to conduct a larger randomized controlled study to verify or refute the conclusions of this study.Virtual reality-based rehabilitation training combining action observation and execution and providing intensive, repetitive, and motivating training scenarios led to improvements in lower limb motor function. Therefore, the system may be of benefit as a neurorehabilitation tool. In addition, because the study design used unsupervised training at subjects’ homes, it suggests that the system can be successfully used in ecologically valid home-based training settings. Such a system may provide additional benefits in terms of reduced subject transportation cost and effort and for monitoring of subjects’ activity outside the clinic. This data may provide a window to gain insights into how the results of inpatient rehabilitation translate to post-clinic everyday life and track the maintenance, gain, or loss of function after the end of supervised rehabilitation.The VR-augmented neurorehabilitation described in this study is not limited to subjects with iSCI. Other subject groups with neurological disorders, e.g., stroke, are also likely to benefit from the intervention described here. Furthermore, studies are needed to determine advantages, disadvantages, cost-effectiveness, and comparative efficacy of home-based versus clinic-based VR training.All authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. The purpose of the study was clear to all subjects, and written informed consent was acquired. The experimental protocol was conducted in accordance with the Declaration of Helsinki and performed with the approval of the Canton of Zurich ethics committee .MV was involved in study design, data collection, analysis of data, discussion of results, and writing the article. JL was involved in data collection, data analysis, and discussion of results. LA, RS, and RC were involved in the discussion of results and manuscript editing. PP and AC were involved in study design, discussion of results, and editing the article. KE and MB were involved in study design, data analysis, discussion of results, and article editing.All authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. The experiment was conducted in accordance with the Declaration of Helsinki.