To assess the renal growth and function of neonates during infancy in relation to birth weight and gestational age.A longitudinal study was conducted at a tertiary hospital in South India from June 2010 to August 2014. Low birth weight neonates (LBW) were further sub-classified based on gestational age and compared with normal birth weight (NBW) full term neonates at birth, 6 months and 18-24months of age. The renal volume was measured by ultrasound and renal function by Cystatin C- derived glomerular filtration rate (CysGFR) at the three time points during the dynamic phase of renal maturation in infancy.p < 0.001). CysGFR in the LBW and SGA infants, despite having low kidney volumes, were comparable to the GFRs of NBW and AGA neonates at the end of infancy.We recruited 100 LBW and 66 NBW term neonates. Thirty five percent of the LBW neonates were SGA. Among the AGA neonates, 39 % were LBW neonates. The mean height and weight of the LBW neonates were significantly lower compared to NBW neonates throughout infancy. The increment in kidney volume was in accordance with the change in body size, being lower in LBW compared to NBW infants. The combined kidney volume was significantly lower in LBW and SGA neonates across all three time points  contains supplementary material, which is available to authorized users. India is the cradle for 40 % of all low birth weight babies in the developing world . LBW hasLBW babies have a lower nephron mass . Fetal kLBW could be secondary to intrauterine growth restriction (SGA) or due to prematurity(AGA). It is well established that weight for gestational age is an important independent determinant of kidney size at birth and early infancy . There iThough nephron number is a non-modifiable factor, for the clinician increased awareness may lead to changes in practice that could have far reaching consequences. Therefore, evaluating the renal function and growth in LBW infants becomes vital during the dynamic phase of renal growth and maturity of infancy.The objective of this study was to primarily assess renal growth and function in LBW neonates compared to NBW neonates during infancy and secondarily to compare the renal growth and function in SGA and AGA newborns based on gestational age.This longitudinal study was conducted at St. Johns Medical college hospital, Bangalore from June 2010 to August 2014. Approval from the Institutional Ethical Review Board was obtained. Informed consent was taken from either of the parents of the newborn babies. NBW babies born at full term served as controls. LBW babies, born both intramural and extramural were included. The LBW babies consisted of term SGA, preterm SGA and preterm AGA. LBW was defined as a birth weight of < 2500 g. Prematurity was defined as any baby born before 37 completed weeks of gestation. Gestational age [Babies with congenital anomalies of kidneys, syndromic associations, birth weight <1000gms (extremely low birth neonates), serum creatinine >1 mg/dl, hypertension, single kidney and abdominal pathology that made ultrasonography difficult to perform were excluded from recruitment. Weight was checked on a digital weighing machine to the nearest 5 g, length was measured on a kidimeter to the nearest 0.1 cm. Weight, length renal function and renal volumes were measured at birth, 6 months and between 18–24 months.Kidney size was determined by ultrasonography  using a 5 MHz sector probe by an experienced ultrasonographer. The kidneys were identified in the sagital plane along the longitudinal axis. An average of the maximal length, transverse and anterior-posterior diameter was measured at the level of renal hilum to the nearest 0.1cms in both kidneys. Each measurement was made three times and averaged to minimize measurement error. The inter-observer and intra-observer interclass coefficients were 0.98(0.91-0.99) and 0.99(0.98-0.99) respectively. The renal sinus was eliminated to record accurately the dimensions of the renal parenchyma. Renal volume was calculated using an equation of an ellipsoid: Length x transverse diameter x anterior-posterior diameter x 0.523 (cm3). The combined renal volumes was obtained by adding the left and right renal volumes. The relative kidney volume was calculated as combined renal volume corrected to BSA to eliminate the birth weight as a confounding factor.Serum cystatin C is a better measure of GFR than serum creatinine in infants, since serum creatinine is influenced by infant’s muscle mass and hydration status. Cystatin C was measured using the N Latex cystatin kit (Dade Behring) by nephelometric assay with reference range of 0.53 to 0.95 mg/l.GFR was estimated from cystatin C levels (CysGFR) using the prediction equation (log cystatin GFR = 1.962+ (1.123 X Log (1/cystatin C).The microalbumin was measured using a Flex reagent cartridge is based on a particle –enhanced turbidometric inhibition immunoassay (PETINIA) adapted to Dimension clinical chemistry system which allows direct quantification of albumin in urine samples. The analytical measurement range is 1.3 -100 mg/l.t-test was used to compare the continuous variables such as body weight, body surface area, serum cystatin C, CysGFR and combined renal volumes between LBW and NBW neonates at birth. Pearson or Spearman’s Rho correlation was used to assess the relationship between clinical variables for each time point. In order to predict the expected growth of kidney volume and function in LBW and NBW babies, multiple regression analysis was performed and regression coefficients (the average change in the dependent variable for every unit change in the independent variable) are reported. Mixed model analysis was performed to compare the mean kidney volume and function overtime separately between LBW and NBW neonates, considering study group (LBW/NBW and SGA/AGA) and time  as factors adjusting for sex, BSA (for kidney volume) and kidney volume (for CysGFR). An alpha level of less than 0.05 was set as statistical significance. All analyses were carried out using SPSS version 21.Descriptive statistics were reported using mean and standard deviation. Assumption of normality was checked. Figures are presented as box plots and scatter plots. The independent p < 0.01) but was not significantly different between SGA and AGA neonates (SGA: 17.3 ± 5.0 Vs AGA: 19.5 ± 5.1 months p > 0.05). Gender distribution was comparable between LBW and NBW groups.We screened 142 low birth weight babies. Of these, 100 met inclusion criteria and agreed to come for follow up . The controls consisted of 66 normal weight term neonates. All these babies recruited at birth were followed at 6 months and 18–24 months. Of the 166 neonates, 53 % were males. The mean age of infants at last follow up varied between the LBW and NBW neonates . Thirty five percent of the LBW neonates were small for gestational age. Among the AGA neonates, 39 % were LBW.p < 0.001)  as shown in . There was a significant increase in kidney volumes in both groups over time  Fig. . The kid in Fig. . NBW neo2) at birth were 51.4 ± 14 and 48.5 ± 8.4 in LBW and NBW neonates respectively. CysGFR in LBW neonates were comparable to NBW neonates at the end of infancy  and SGA (12. ± 6 mg/l) babies were higher than NBW (9.3 ± 5.3 mg/l) and AGA (9.2 ± 5.2 mg/l) babies, this was statistically not significant ,despite no significant difference in birth weights, the mean combined renal volume, corrected to body surface area, of Indian babies at 1 month of age was significantly (p < 0.001) smaller than that of Canadian babies. Focusing on the relationship between glomerular filtration rate and kidney volume in LBW neonates in early post- natal period, Kandaswamy et al. reported that within 6 days of birth, LBW infants, though small in number (n = 13) achieved a similar GFR to NBW infants (n = 36), despite 25 % smaller kidney volumes [In a study  undertak volumes . We alsomber n =  achieved volumes . This suWe analyzed the rate of growth of renal volume per time for NBW and LBW. The rate of growth was greater in NBW neonates at both 6 and 18 months as compared to LBW neonates. Mixed model analysis was performed and we found that the rate of growth was significantly different between NBW and LBW neonates . However, we are cautious in interpreting these findings due to the drop outs that resulted in small sample size and the different ages at final kidney size measurement.Our study has several limitations. Over time, drop out of patients resulted in smaller numbers in the later age groups, which may have confounded our results. Because of the smaller numbers at later time points we could not further stratify by gestational age within the two birth weight groups. The ages at study were somewhat variable with birth parameters being measured between birth and 14 days and the latest parameters measured between 18 and 24 months of age. We observed that the parents of LBW/SGA infants were sensitized to report on time or earlier for follow up compared to NBW babies in late infancy. It is possible that the lower age at last measurement in the LBW group may have contributed to the smaller kidney size in this group, however our regression analysis over time show a consistently reduced rate of renal growth in the LBW group which would support smaller final kidney sizes. Importantly also, despite there being a difference in the mean ages at last follow up between 18–24 months in LBW and NBW babies, the CysGFR was not different between the two groups at this time point. We did not have data on other factors that may have influenced infant renal growth and function such as maternal factors, nutrition and genetic predisposition, and therefore other potential confounders could not be controlled for.Strengths of our study include the relatively large subject numbers, as well as the fact that this study was embedded within our day to day practice and therefore is likely generalizable to our population. In addition the repeated measurements over time and consistencies of trends underscore the validity of our findings as compared to single cross-sectional measurements. Our use of CysGFR is an important strength in that it reduces potential confounders introduced by serum creatinine and is one of only a few studies in neonates that use cysGFR estimation. The variability of findings in the literature especially with respect to GFR in LBW compared with NBW children demonstrates the challenges in studying GFR in these infants, where true GFR measurements as mentioned in literature  may not Our study focuses on a high risk group of neonates with LBW and SGA, which is of great relevance in developing nations. Our assessment of renal growth and function during the dynamic phase of body growth and glomerular functional maturation in infancy, demonstrates that renal growth, in accordance with body growth, is suboptimal in LBW and SGA neonates compared to NBW and AGA neonates during infancy. Renal function however was comparable between LBW and NBW neonates and similarly between SGA and AGA neonates in late infancy. This catch up in glomerular filtration rate despite having lower kidney volumes may reflect early glomerular hyperfiltration and therefore emphasises the need for long term follow up of LBW and SGA infants.th and 90th centile for that gestational age); cycGFR, Cystatin C derived glomerular filtration rate; GFR, glomerular filtration rate; LBW, low birth weight (birth weight < 2500 g); NBW, normal birth weight; SGA, small for gestational age AGA, appropriate for gestational age (babies’ whose birth weight is between the 10


Children with attention deficit/hyperactivity disorder (ADHD) often present with social difficulties, though the extent to which these clearly overlap with symptoms of autism spectrum disorder (ASD) is not well understood.n = 48) or ASD (n = 164).We explored parent-reported and directly-observed ASD symptoms on the Autism Diagnostic Interview-Revised (ADI-R) and the Autism Diagnostic Observation Schedule (ADOS) in children referred to ASD-specialty clinics who received diagnoses of either ADHD  adequately differentiated the groups while none of the items on the ADI-R met the criteria for adequate discrimination.Results of this work highlight the challenges that clinicians and researchers face when distinguishing ASD from other disorders in verbally fluent, school-age children. Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) [Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) restriction that prevented a dual diagnosis of ASD and ADHD. This provides clinicians with an opportunity to acknowledge both the converging and discrete symptom presentations of ASD and ADHD. It also underscores the importance of understanding the boundaries and overlaps between these disorders [Autism Spectrum Disorder (ASD) and Attention Deficit/Hyperactivity Disorder (ADHD) are two of the most commonly diagnosed childhood neurodevelopmental disorders . As desc (DSM-5) , core sy (DSM-5) –7) and 2 (DSM-5) –12). Ove (DSM-5) . This leisorders .and ASD-like symptoms occur separately in ADHD and lead to social dysfunction.One approach to achieve a better understanding of the convergence between the two disorders is through exploration of ASD symptoms in individuals with a diagnosis of ADHD. Research to date has found that social dysfunction occurs regularly in children with ADHD , 15–17 aOne limitation of research exploring ASD symptoms in individuals with ADHD is that the majority of studies have relied on parent questionnaires of ASD symptoms and/or measures of broad psychopathology that are not specific to ASD , 26, 27.In this study, we examined ADOS and ADI-R scores in a sample of children referred to ASD-specialty clinics for diagnostic evaluations who ultimately received clinical diagnoses of ADHD (not ASD). This is a unique sample given that most comparative work between ASD and ADHD has used research rather than clinical samples; this particular group of children may be especially relevant to clinicians. We aimed to explore (1) the specificity of standard ASD diagnostic instruments in children referred to an ASD clinic who received a diagnosis of ADHD and (2) the specific profiles of ASD symptoms  in this sample of children with ADHD compared to age, sex, and IQ-matched children with primary diagnoses of ASD.Data from the current study were extracted from an existing database of children whose parents had provided written informed consent for their child’s clinical information to be included in a research database which was approved by Institutional Review Boards (IRB) at three different ASD-specialty clinics (sites): the University of Chicago Developmental Disorders Clinic , the University of Michigan Autism and Communication Disorders Center , or the New York Presbyterian Center for Autism and the Developing Brain (CADB) at Weill Cornell Medicine (8 % of the sample). Children were only eligible for the current study if they had been referred for a clinical ASD diagnostic assessment  and had received an overall best estimate clinical diagnosis (BEC) of ASD or ADHD following the comprehensive assessment (see below).and ADHD  were not eligible for inclusion in this study. The final sample of children with a BEC of ASD included 164 children . Information about current psychotropic medication treatment was only available for 66 % (n = 139) of the sample, as this information was not systematically gathered for children seen at UCDDC. There was no statistically significant difference between the ADHD and ASD groups with regard to the proportion of children receiving psychotropic medication  = 3.36, p = 0.07). The children with ADHD did not differ from children with ASD in verbal IQ (VIQ), non-verbal IQ (NVIQ), age, gender, or ethnicity. However, given the large age (4 to 18 years old) and NVIQ (72–153) ranges included in the study, these variables were included as covariates in secondary analyses of dimensional data despite no significant overall group differences in means. In addition, because significantly more children with ADHD were seen in Michigan than New York and Chicago, site was included as a covariate in these secondary analyses , which are calculated by summing items within the areas of Qualitative Abnormalities in Reciprocal Social Interaction , Qualitative Abnormalities in Communication (Communication), Restricted, Repetitive, and Stereotyped Patterns of Behavior (RRB-ADI), and Abnormality of Development Evident at or Before 36 Months (Age of Onset). Totals from domains have algorithm cut-offs that yield classifications of autism or non-autism.In addition, in order to understand current behavior described on the ADI-R, domains of social communication (SC), repetitive sensory motor (RSM), and insistence on sameness (IS) were calculated using domains defined by Lord, Bishop, and Anderson . BecauseThe ADOS diagnostic algorithm yields classifications of ASD versus non-ASD , 40 as wTo aid in diagnostic symptom understanding, researchers have mapped individual items from the ADOS and ADI-R to ASD symptom domains . For theClinical Evaluation of Language Fundamentals (CELF) [For the majority of participants, a standard hierarchy was followed to select appropriate cognitive tests: the Differential Ability Scales (DAS)  was choss (CELF) , Peabodys (CELF) , Vinelans (CELF) , and NVIs (CELF) . There wAn overall best estimate clinical diagnosis (BEC)  was deteχ2 analyses were conducted to compare proportions of endorsed versus non-endorsed items that have been mapped to each symptom domain [α = 0.01 across analyses.First, we examined the proportion of participants who met standard ADI-R and ADOS algorithm cut-offs in the ADHD group. We expanded this to also explore less strict ADI-R cut-offs for ASD as defined by Lainhart et al. (Collaborative Program of Excellence in Autism (CPEA) ADI-R Criteria)  since orm domain . Fourth,m domain , 54, 55,m domain , especiaAs Table F = 66.80, p < 0.001, η2 = 0.24, F = 80.60, p < 0.001, η2 = 0.28, and F = 99.51, p < 0.001, η2 = 0.32, respectively. The ASD group also scored significantly higher on basic SOC, interaction quality, and RRBs factors [F = 41.16, p < 0.001, η2 = 0.17, F = 38.19, p < 0.001, η2 = 0.15, F = 53.26, p < 0.001, η2 = 0.20, respectively :  factors : F = 11.43, p < 0.01, η2 = 0.05, F = 12.24, p < 0.01, η2 = 0.06, and F = 8.22, p < 0. 01, η2 = 0.04. Analyses indicated that there was no statistically significant difference between groups in terms of the proportion of those who met the age of onset domain cut-off. There were no statistically significant differences between the groups across current symptom domains on the ADI-R  = 7.01, p < 0. 01, η2 = 0.04. See Fig. Children with ASD had significantly higher scores on the social, communication, and RRB domains of the ADI-R: fined by ). These F,200 = 11χ2 tests of differences in proportion indicate that all ADOS items in the symptom area of social-emotional reciprocity (A1), except Shared Enjoyment in Interaction and Asks for Information, were endorsed significantly more frequently in the ASD group than the ADHD group (see Table Results of χ2 tests of differences in proportion) and also met study criteria as adequate discriminators: Unusual Eye Contact and Facial Expressions Directed to Examiner , two of the ADOS items were endorsed significantly more frequently in the ASD group . None of the ADI-R items met the study criteria as adequate discriminators between the groups, and results of ms Table .Table 5Sχ2 tests of differences in proportion indicated that two items on the ADOS, Stereotyped/Idiosyncratic Use of Words or Phrases and Hand and Finger and Other Complex Mannerisms, were endorsed significantly more frequently in the ASD group than the ADHD group (see Table χ2 tests of differences in proportion). For symptom area B3, Excessive Interest in or References to Unusual or Highly Specific Topics or Objects or Repetitive Behaviors on the ADOS was endorsed more frequently in the ASD group than the ADHD group, but there were no significant differences in the ADI-R items , symptoms in the RRB domain were seen more frequently in the ASD group than the ADHD group. Stereotyped/Idiosyncratic Use of Words or Phrases on the ADOS and Stereotyped Utterances and Delayed Echolalia on the ADI-R were the RRB symptoms most clearly associated with ASD in this study. On the other hand, a number of children with ADHD exhibited RRBs similar to children with ASD (at least based on parent report). This has implications for clinical practice as the specificity of these behaviors may be limited depending on the comparison group.not specific to ASD and that interventions to address social difficulties should not be dependent on an ASD diagnosis.Although elevated scores on ASD measures in this sample of children with ADHD may suggest that actual ASD symptoms are common in ADHD , 10, 18,These results also suggest that care must be taken with regard to proposals of quick diagnoses based on abbreviated information , questioOur relatively small sample of children with ADHD represents a particular subset of children with ADHD: children whose parents had sufficient concern about ASD to bring them to an ASD-specialty clinic to determine whether a diagnosis of ASD was warranted. As such, these children are not representative of all children with ADHD. In addition, our group of children with ASD was deliberately selected from a much larger sample to be equivalent to the ADHD group in language level, age, and IQ and is therefore not representative of the whole ASD population. Future work should extend these results to samples that include individuals with lower language and intellectual abilities. In addition, this sample included relatively few females. Although this is consistent with the gender discrepancy seen in ASD samples, results of this study may not be characteristic of females with ASD and/or ADHD. Future studies should explore the unique symptom presentations in females with ASD and/or ADHD. Last, we could not rule out ADHD in our sample of children with ASD, although children with formal comorbid diagnoses of ADHD were excluded.There are many challenges in assessing verbally fluent, school-age children referred for possible ASD. Although some social communication symptoms measured by standard observations distinguished children with ASD from children with ADHD, domain cut-off scores on a detailed parent interview were less useful in diagnostic discrimination. Results of this study call for additional research exploring the prevalence, quality, intensity, and trajectories of social communication impairments in children with ADHD compared to children with ASD, in order to provide insights into the boundaries and overlaps between these disorders across development. Furthermore, detailed phenotyping of ASD-like traits in these children could provide insight into studies exploring the neurobiological , 34 and


An investigation is made of a recently introduced quantum interferometric method capable of measuring polarization mode dispersion (PMD) on sub-femtosecond scales, without the usual interferometric stability problems associated with such small time scales. The technique makes use of the extreme temporal correlation of orthogonally polarized pairs of photons produced via type-II phase-matched spontaneous parametric down-conversion. When sent into a simple polarization interferometer these photon pairs produce a sharp interference feature seen in the coincidence rate. The PMD of a given sample is determined from the shift of that interference feature as the sample is inserted into the system. The stability and resolution of this technique is shown to be below 0.2 fs. We explore how this precision is improved by reducing the length of the down-conversion crystal and increasing the spectral band pass of the system. The highly correlated nature of photons produced two at a time via parametric down-conversion has proved to be an extremely useful tool in exploring the strange nature of quantum mechanics. In particular, type-II parametric down-conversion, which can produce photon pairs entangled in both space-time and polarization, has provided a wealth of interesting new interferometric phenomena –8. One oThe method has a number of distinct differences with respect to conventional PMD measurement methods that may be exploited to advantage. A high stability is seen without taking any of the special precautions usually required by conventional interferometric optical measurement systems (such as white light interferometer systems). This stability is due to the common path design of this simple two-photon interferometer configuration. Another advantage of the method (relative to some nonwhite light interferometric methods) is that it determines the optical delay absolutely, as opposed to simply measuring the delay modulo the wavelength.Parametric down-conversion is a nonlinear process that takes place in an optically nonlinear crystal that allows an individual pump photon to, in effect, decay into a pair of photons. Because this decay occurs under the constraints of energy and momentum conservation, or phase matching, and because photons of a pair must be created virtually simultaneously, they are highly correlated. Our application uses a type-II phase matching arrangement, where a pump photon with extraordinary polarization is converted into a photon pair consisting of one extraordinary (e) polarization and one ordinary (o) polarization photon. Specifically, in the application here the down-conversion process is arranged so that the pair of output photons are emitted collinearly. This collinear pair of correlated photons enters a simple interferometer yielding an interference feature whose position is sensitive to the delay of one photon of a pair relative to the other.The interferometer consists of a single beamsplitter, a pair of polarizers, and a pair of detectors see . The colIt is useful to describe here how coincidences are actually observed. Coincidence measurement systems typically use one detector to start a clock and a second detector to stop it. A fixed delay is added to the second detection channel to ensure that the stop pulse occurs after the start. A histogram of these start-stop time intervals is recorded. Correlated photon pairs are seen as a peak in pair detections at some specific delay between start and stop see  inset. TThere are two requirements for achieving indistinguishability and observing the quantum interference. First, polarizers must be placed before each of the detectors and oriented at 458 to the polarization of the e and o down-converted photons. These polarizers destroy the information as to whether each individual detected photon was an e-ray or o-ray, a requirement for indistinguishability. The second constraint arises because the e-ray and o-ray photons travel at different speeds through the optical system components . This results in an arrival time difference that also could, in principle, be used to determine which polarization photon was registered at each detector, thus destroying the indistinguishability of the two types of coincidence events. This time difference would be seen in the coincidence system as two separate coincidence peaks (at different time delays between start and stop detections), one due to each coincidence type which we refer to as 1e2o and 1o2e.  Indistinguishability can be restored by adjusting the delay of the two photons in the common optical path so that the peaks due to both types of coincidence overlap. In this way, one can no longer tell (even in principle) whether a particular coincidence is an 1e2o or 1o2e type, allowing the two to interfere. In the present configuration, this indistinguishability condition is met when the two photons reach the beamsplitter simultaneously to within their coherence times. L/c, where L is the crystal length, ne and no are the e and o indices of refraction, and c is the speed of light. A spectrum limiting element can add to the spread of relative delays by adding random delays to individual photons. (This occurs in an interference filter because it operates as a resonant cavity where photons “rattle back and forth” with some probability for exiting on each bounce.) Thus, reducing the spectral bandpass of the system beyond a certain point broadens the observed dip.The following is an intuitive explanation of the interference profile  crystal oriented to produce orthogonally polarized, but collinearly propagating, down-conversion photons at a center frequency of 702 nm. A polarization insensitive 50-50 beam splitter directed the down-converted photons to two polarizers oriented at 45° to the e- and o-ray photons and at 0° to each other. A prism before the BBO crystal was used to reject laser light other than the 351 nm beam. A high efficiency 351 nm mirror after the BBO blocked the pump light from the system, while passing the longer wavelength down-converted light. The polarization delay line, essentially a continuously variable thickness birefringent plate, was made from a pair of identical 15 mm by 15 mm by 30 mm quartz wedges  due to the crystal length and the other inversely proportional to the spectral filter. The fitted value for a was 63.3 fs. The parameter b, giving the proportionality between the inverse bandpass and the coherence time, can be calculated for various passband shapes. Typically the value can be expected to fall between 1 and 0.32, the calculated values for rectangular and Lorentzian passbands respectively . In thib here is 0.76, again within the expected range.) The fact that a triangular shape was not reached here is likely due in part to the subtle transition between the two shapes , it was observed that restricting the spectral range also increased the uncertainty of optical delay determination (see An additional analysis of measurement uncertainty was made using the data series of tion see . This agIn conclusion, we have demonstrated a technique for measuring PMD with uncertainties as low as 0.15 fs. These results show that a simple two-photon interferometer with a common path geometry can be extremely stable, even without the usual engineering required for interferometric stability. It will be interesting to see what uncertainties can be achieved with proper attention to mechanical and thermal stability. We have shown that the best uncertainty is achieved with short crystal length and wide spectral bandpass and that practical systems can be made using crystals as thin as 0.05 mm.Finally, new entirely solid state systems to produce entangled pairs of photons have already been constructed . These c


Obstructive sleep apnea syndrome (OSAS) in children does not only present with symptoms of sleep disturbances but also with associated symptoms such as growth failure, enuresis, academic learning difficulties, and behavioral problems, including attention deficit/hyperactivity disorder- (ADHD-) like symptoms. We evaluated neurocognitive functions before and after adenotonsillectomy in a patient with OSAS. An 11-year-old boy suspected of having ADHD with nocturnal enuresis was referred for evaluation. He was found to have adenotonsillar hypertrophy. Presence of snoring was evident only after detailed medical interview. Polysomnography confirmed the diagnosis of OSAS, which was subsequently treated by adenotonsillectomy. The apnea/hypopnea index decreased from 21.9 at baseline to 1.8 after surgery, and the frequency of enuresis fell from almost nightly to 2-3 times per month. Neurocognitive and behavioral assessment after the treatment of OSAS showed significant improvement in cognitive functions, especially attention capacity and considerable amelioration of behavioral problems including ADHD-like symptoms. As the most common cause of pediatric OSAS is adenotonsillar hypertrophy, medical interview and oropharyngeal examination should always be performed in children suspected of having ADHD. The necessity of sleep evaluation for children with ADHD-like symptoms was also emphasized. Obstructive sleep apnea syndrome (OSAS) is a common disorder in adults as well as in children. The prevalence of pediatric OSAS is up to 5.7% –3. The cADHD is a neuropsychiatric syndrome affecting 3–16% of school children with world prevalence of 5.29% . The diaThere is a well-established correlation between sleep disturbances and ADHD . In the The aim of this study was to investigate the necessity of identifying pediatric OSAS for children with ADHD symptomatology and to assess the effects of treatment of OSAS on neurocognitive functions.An 11-year-old boy was referred to the university hospital with suspected ADHD. He tended to be hyperactive since he started crawling, and he has been still fidgeting at school, with academic problems related to inability to concentrate on work. The socioeconomical level of his family was on average. ADHD was suspected by teachers based on forgetfulness of school needs and homework. His symptoms were compatible with the diagnostic criteria of ADHD, predominantly inattentive type, based on the diagnostic criteria of Diagnostic and Statistical Manual, fourth edition, text revision (DSM-IV-TR) . The med2, Rohrer index: 129.2). His parents had not noticed his snoring until they had the detailed medical interview. Oropharyngeal examination showed adenotonsillar hypertrophy with Mackenzie stage II to stage III. Presence of snoring was evident only after medical interview to the parents. Based on suspicion of OSAS, the patient was scheduled for attended polysomnography (PSG) with video monitoring and multiple sleep latency test (MSLT). PSG recording included electroencephalography (EEG) (C3-A2 and C4-A1), electrooculography, submental and bilateral lower limb electromyography, and electrocardiography, together with continuous recording of oronasal airflow, chest and abdominal movements, and oxygen saturation. Sleep stages were scored according to the Rechtschaffen and Kales manual [Physical examination showed height within the normal range (155 cm), body weight of 48.4 kg, and normal body mass index , Kaufman Assessment Battery for Children (K-ABC), for assessment of intelligence and achievement, the Rey-Osterrieth Complex Figure Test (ROCF) as a scale of visuospatial construction, and the Rey's Auditory Verbal Learning Test (RAVLT) to assess verbal learning and memory –15. For Based on the diagnosis of pediatric OSAS, he underwent adenotonsillectomy.He was reevaluated for PSG, MSLT, and neurocognitive and neurobehavioral assessment 4 months after surgery. After adenotonsillectomy, the frequency of enuresis reduced to 2-3/month and his snoring disappeared. Although he did not complain about sleepiness before the operation, he reported improvement in daytime sleepiness and concentration after adenotonsillectomy.The present study demonstrated that adenotonsillectomy for severe pediatric OSAS resulted in significant improvement in nocturnal ventilation, sleep architecture, snoring, neurocognitive functions, especially attention capacity, and behavioral problems, including ADHD-like symptoms.ADHD in children is associated with various sleep disorders including pediatric OSAS, periodic limb movement (PLMD), enuresis, and delayed sleep phase syndrome (DSPS) –21. AccoOn the other hand, patients with sleep disturbances often display behavioral patterns that resemble some features of ADHD. Parents of children with OSAS tend to focus solely on daytime behavior problems, inattentiveness, and academic failure, rather than sleep problems. Therefore, these children are prone to be diagnosed with neurodevelopmental disorders, such as ADHD. Our patient was referred to the hospital with suspected ADHD, not OSAS, and initially fulfilled the diagnostic criteria of ADHD. It is often difficult to reveal which of the disorders is the primary and which is a byproduct of the other . MoreoveThe most common cause of nocturnal enuresis is neurological-developmental delay, but pediatric OSAS is occasionally associated with enuresis . BrouileThe performance on the K-ABC test can reflect the ability of a child for academic achievements . In our With regard to the behavior problems, externalizing behavior problems were obviously higher than internalizing behavior problems before adenotonsillectomy. Adenotonsillectomy in this patient did not result in significant changes in externalizing and internalizing behavior problems and all subscores of CBCL became below the cutoff point of clinical level, 70. In this regard, Lewin et al.  reportedThe present study has several limitations. As we reevaluated neurocognitive functions 4 months after the treatment, practice effect with regard to the neurocognitive function tests could have influenced the results. The interval between the tests before and after the treatment may have been short to confirm the effectiveness of adenotonsillectomy. A randomized trial of adenotonsillectomy for childhood sleep apnea reported that after a 7-month intervention period, school-age children with prolonged oxyhemoglobin desaturation, who underwent surgery, did not show the significant improvement in attention or executive function measured by neuropsychological testing, although the improvements of behavior, quality of life, and polysomnographic findings were observed . In the We reported a child initially suspected of having ADHD with drug resistant enuresis. Treatment of OSAS with adenotonsillectomy significantly improved snoring, enuresis, daytime behavioral problems, and neurocognitive functions. In order to identify pediatric OSAS, underlying neurodevelopmental disorders like ADHD, medical interview for snoring, and the oropharyngeal examination are important.


Background: Attention deficit-hyperactivity disorder (ADHD) is the most prevalent neuropsychiatric condition in childhood. ADHD is a multifactorial trait with a strong genetic component. One neurodevelopmental hypothesis is that ADHD is associated with a lag in brain maturation. Sphingolipids are essential for brain development and neuronal functioning, but their role in ADHD pathogenesis is unexplored. We hypothesized that serum sphingolipid levels distinguish ADHD patients from unaffected subjects.Methods: We characterized serum sphingolipid profiles of ADHD patients and two control groups: non-affected relatives and non-affected subjects without a family history of ADHD. Sphingolipids were measured by LC-MS/MS in 77 participants . ADHD diagnosis was based on the Diagnostic and Statistical Manual of Mental Disorders (DSM IV-TR). Diagnostic criteria were assessed by two independent observers. Groups were compared by parametrical statistics.Results: Serum sphingomyelins C16:0, C18:0, C18:1, C24:1, ceramide C24:0, and deoxy-ceramide C24:1 were significantly decreased in ADHD patients at 20–30% relative reductions. In our sample, decreased serum sphingomyelin levels distinguished ADHD patients with 79% sensitivity and 78% specificity.Conclusions: Our results showed lower levels of all major serum sphingomyelins in ADHD. These findings may reflect brain maturation and affect neuro-functional pathways characteristic for ADHD. Attention deficit-hyperactivity disorder (ADHD) is a neurobehavioral condition characterized by persistent, cross-situational and developmentally inappropriate levels of inattention, hyperactivity, and impulsiveness , (2) unaffected first-degree relatives of ADHD patients , and (3) unaffected participants without a family history of ADHD . Table This case-control study was designed to compare serum sphingolipid profiles of ADHD patients with two independent control groups: unaffected first degree relatives of ADHD patients, sharing housing, and dietary patterns with the index cases and unaffected subjects with no family history of ADHD. We studied 77 subjects belonging to one of the following 3 groups: 1) ADHD patients  and referred from general psychiatric/neurological and family medicine outpatient clinics serving a medium income area of urban Santiago, Chile. Seventeen patients were clinically classified as ADHD combined subtype, 10 patients as predominantly inattentive, and one patient as predominantly hyperactive-impulsive , we controlled for those in all subsequent statistical analyses.ADHD diagnosis was excluded from the unaffected groups (groups 2 and 3) by means of a brief clinical interview exploring DSM-IV-TR criteria  sphinganine-1-phosphate and sphingosine-1-phosphate; (2) ceramides C16:0, C18:0, C20:0, C22:0, C24:0, and C24:1; dihydroceramides C18, C18:1, C24:0, and C24:1; deoxy-ceramide C16:0 and C24:1 and deoxy-dihydroceramides C16:0 and C24:1; (3) sphingomyelins (SM) SM C16:0, SM C18:0, SM C18:1, and SM C24:1. Their relative location in the sphingolipid metabolic pathway is summarized in Figure  sphinganThe final serum level for each patient and analyte was calculated by averaging triplicate measurements. Subsequent statistical analyses were performed on these final levels. Average inter-assay imprecision for sphingolipid quantification was 8.7% (ranging from 2.5% for sphingomyelins to 12.3% for deoxyceramides).Post-hoc pair-wise comparisons were performed when significant effect for the variable “clinical group” was detected and significance was maintained as p = 0.05. This approach was verified using the adaptive procedure described by Benjamini and Hochberg (BH-A) for controlling the False Discovery Rate (FDR)  analyses Fawcett, , using tp < 0.0001; SM C18:1 p = 0.05; SM C18:0 p = 0.01; SM 24:1 p = 0.001)  . We explored dihydroceramide levels to evaluate if decreased ceramide C24:0 could originate from decreased de novo synthesis and found no differences between groups (data not shown). To further evaluate the de-novo pathway we also measured deoxy-ceramides, which originate obligatory through the de-novo pathway  .Analysis of ceramides  showed 20% lower ceramide C24:0 in ADHD patients compared to unaffected relatives  Figure . This dip = 0.48) from those found in unaffected relatives (mean ± SD = 1.44 ± 0.38 μM) or unaffected controls without a family history of ADHD (mean ± SD = 1.59 ± 0.38 μM). Mean serum sphinganine-1-phosphate was 0.23 μM (SD = 0.008 μM) in ADHD patients, 0.2 μM (SD = 0.01 μM) in unaffected relatives and 0.22 μM (SD = 0.007 μM) in non-related controls. Sphinganine-1-phosphate concentrations were not different between groups (p = 0.27). These findings suggest that serum sphingoid bases are not different in ADHD patients.We evaluated levels of sphingosine-1-phosphate and sphinganine-1-phosphate among the three groups, of potential interest as sphingosine-1-phosphate has been linked to regulation of neuronal excitability and neurotransmitter release , 79% sensitivity and 78% specificity  curves to evaluate whether any of the assayed sphingolipids would discriminate between ADHD-affected and unaffected subjects with adequate levels of sensitivity and specificity. The best detection accuracy was obtained for total SM levels , with an AUC of 0.81  .To explore whether any of our findings can be considered as a candidate endophenotype (or intermediate phenotype) for ADHD, we evaluated if they would fit an endophenotype-characteristic stair-like distribution, with the highest frequency of the marker among affected subjects, intermediate frequencies among unaffected subjects with positive family antecedents and the lowest frequencies among unaffected subjects without family antecedents of the condition. Based on the ROC curves, we chose the cut-off that best discriminated between ADHD and unaffected subjects for each analyte and built contingency tables that enabled us to evaluate the frequency of subjects below and above the cut-off inside the three clinical groups. The expected stair-like distribution was observed for SM C24:1 and deoxy-ceramide C24:1  Figure . As a coIn this pilot study, we characterized sphingolipid serum profiles in ADHD patients and two control groups: (1) unaffected first degree relatives of ADHD patients who live and eat with their index ADHD case and (2) unaffected subjects without a family history of ADHD among their first and second degree relatives. Sphingolipids and their metabolites are important for neuronal functioning  decreased sphingomyelin uptake or synthesis or (2) increased sphingomyelinase activity. Neither of these mechanisms was specifically evaluated in the current study.Figure de-novo pathway- was decreased 30% in ADHD patients. Notably, the low levels of ceramide C24:0 and deoxy-ceramide C24:1 in ADHD patients are not paralleled by a decrease in any dihydroceramide, suggesting that ceramide synthase-2 activity (which generates dihydroceramides with acyl chains C22–24) might not be impaired in ADHD. Comparable concentrations of all dihydroceramide species also suggest that low ceramide C24:0 and deoxy-ceramide C24:1 are not compensated by increased synthesis of other species through the de-novo pathway  has been reported in red blood cells of ADHD patients  and were able to confirm our observations in terms of significantly lower levels for all sphingomyelins . Of note, we also performed ROC analysis for total SM levels using an age-matched subsample, finding sensitivity and specificity values comparable with those reported for the complete sample , suggesting that results are not affected by age. We also observed the same i.e., decreased albeit non-significant trends for ceramide C24:0 and deoxy-ceramide C24:1 in the sub-sample analyses . As a second limitation, none of our patients were treatment naïve and we cannot rule-out that our findings correspond to a chronic treatment effect instead of being an actual pathogenic marker/factor. Acute treatment effects, on the other hand, were prevented by requiring a 24 h washout period for medication. Finally, our restricted sample size did not allow us to perform analyses by clinical subtype and we are not able to distinguish whether the reported results are applicable to all clinical subgroups or were driven by a specific clinical subtype. We also might be underpowered for detecting some differences of eventual clinical importance. As an example, taking into account the overall variation of our data, we estimate that our study is not able to detect differences less than 20% for the majority of the ceramides. In light of the potential relevance of the results reported by this pilot study, future research addressing these limitations and including the exploration of additional confounders, such as co-morbidities, is mandatory.The interpretation and extrapolation of our results must consider some limitations. First, cases and controls are not age-gender matched and we observe significant differences in the distributions for these variables among the groups (see Table Strengths of our study include (1) the presence of a comparison group of first degree relatives that live and eat with the index case to control for a potential “diet” effect and for other unknown environmental factors and (2) the inclusion of an additional control group of unaffected subjects without a family history of ADHD to assess replication of findings. This is relevant because differences observed between ADHD patients and their relatives could reveal either a true characteristic of ADHD patients, or reflect compensatory mechanisms exerted by unaffected relatives to constitutional risk factors shared with ADHD patients.In addition, the experimental design of this study allows to explore whether sphingolipid levels fulfill the distribution criteria proposed by Gottesman and Gould for endophenotypes of psychiatric disorders  that could reflect pathomechanisms relevant to the disorder.Study/Experiments design: MH, SS, and TQ. Experiment execution: MH and BK. Data analysis/Statistical analysis: MH and BK. Interpretation of results and discussion: MH, TW, and RD. Contributed reagents/materials/analysis tools: MH, TW, SS, and TQ. Elaboration of the manuscript: MH and TW. Critic lecture of the manuscript: TW, RD, SS, and TQ.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.


We found that five of the 65 behaviors measured by this screening tool were sufficient to distinguish ASD from ADHD with high accuracy (area under the curve=0.965). These results support the hypotheses that (1) machine learning can be used to discern between autism and ADHD with high accuracy and (2) this distinction can be made using a small number of commonly measured behaviors. Our findings show promise for use as an electronically administered, caregiver-directed resource for preliminary risk evaluation and/or pre-clinical screening and triage that could help to speed the diagnosis of these disorders.Although autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) continue to rise in prevalence, together affecting >10% of today's pediatric population, the methods of diagnosis remain subjective, cumbersome and time intensive. With gaps upward of a year between initial suspicion and diagnosis, valuable time where treatments and behavioral interventions could be applied is lost as these disorders remain undetected. Methods to quickly and accurately assess risk for these, and other, developmental disorders are necessary to streamline the process of diagnosis and provide families access to much-needed therapies sooner. Using forward feature selection, as well as undersampling and 10-fold cross-validation, we trained and tested six machine learning models on complete 65-item Social Responsiveness Scale score sheets from 2925 individuals with either ASD ( For example, a child with predominant ADHD might struggle with social interactions, but this may stem from inattention to the speaker or interrupting due to impulsivity, rather than a fundamental misunderstanding of social cues, which more strongly aligns to a child with autism.Autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) are among the most common childhood disorders, with the most recent prevalence estimates by the Centers for Disease Control at 1.5% and 9.5%, respectively.4 has recognized the frequency of co-occurrence of ASD and ADHD symptoms and has altered its diagnostic criteria, which previously precluded a dual-diagnosis under DSM-IV, to clinically formalize the autism-ADHD comorbidity.This is not to say that autism and ADHD are mutually exclusive. In fact, the most recent Diagnostic and Statistical Manual (DSM-V)5 or even longer if from a minority group or lower socio-economic status,6 contributing to the average ages of diagnosis of 4.5 years for ASD and 7 years for ADHD, despite the fact that a majority of parents identify developmental concerns before 36 months.2Both ASD and ADHD are identified through extensive examination, including evaluation by a team of behavioral pediatricians and child psychologists as well as administration of a number of diagnostic assessments by certified professionals. These rigorous diagnostic examinations often last multiple hours, and the ever-increasing demand for these appointments far exceeds the maximum capacity for developmental pediatrics clinics across the country. This bottleneck translates to wait times of up to 13 months from initial concern to diagnosis,7 and Autism Diagnostic Interview-Revised,8 to develop abbreviated classification algorithms that distinguish ASD from non-ASD with high accuracy.12 Using analogous methods, we hypothesized that we could achieve similar success in differentiating ASD from ADHD. On surveying the data available in archived research records, the Social Responsiveness Scale (SRS)13 provided the largest sample size of ADHD subjects for our analysis. The SRS is a parent-directed questionnaire that consists of 65 questions, and is commonly used to assess severity of autistic traits. Here, we train and test six different machine learning algorithms on SRS data from 2925 subjects, implementing forward feature selection methods that are tailored to each algorithm to reduce the original set of 65 features to ⩽9 in every case with no statistical decrease in performance as measured against the best estimate clinical diagnosis provided by both the physician and parent. The resulting classifiers show promise for use as pre-clinical screening tools for the evaluation of ASD/ADHD risk.In previous work, we applied machine learning to score sheets of two commonly used autism diagnostic tools, the Autism Diagnostic Observation ScheduleWe aggregated complete item-level score sheets of the SRS from the Simons Simplex Collection version 15, Boston Autism Consortium and Autism Genetic Resource Exchange for a total of 2775 subjects with autism and 150 subjects with ADHD . The SRSClassification of ASD was provided as physician-reported clinical diagnosis and classification of ADHD was provided as parent-reported clinical diagnosis. The ASD subjects selected had no documented ADHD comorbidity, and the ADHD subjects selected did not have any documented diagnosis of autism. The ADHD group consisted mainly of siblings of the autism probands that reported a prior clinical diagnosis of ADHD. The ASD group was 83.9% male and 15.6% female (0.5% unknown). The ADHD group was 62% male and 37.3% female (0.7% unknown).n=2775) and ADHD data (n=150). We used these folds to perform 10-fold cross-validation, where each trial dedicated nine folds for training data and the remaining one fold for testing. For each cross-validation trial, feature ranking was performed on the nine folds in the training set. All 65 features were ranked based on mutual information, calculated from the minimal-redundancy-maximal-relevance (mRMR) criterion described by Peng et al.14 The mRMR score is a metric to quantify the contribution of a feature to a model, calculated by subtracting the predictive power of the feature  from its similarity to other features already in the model .We tested the performance of six machine learning algorithms on our data, using the 65 items in the SRS as features and the diagnosis of either ASD or ADHD as the prediction class. We initialized our machine learning pipeline by splitting the entire data set into 10 stratified folds, where each fold consisted of 10% of both the ASD data (15 The Support Vector Classification (SVC) model was implemented using the linear kernel, Categorical Lasso was implemented as Logistic Regression with l1 regularization and our other Logistic Regression model (referred to here as Logistic Regression) was implemented with l2 regularization.After feature ranking on the training data was complete, we performed 10 random undersamplings on the ASD majority group in both the training and testing sets to achieve a ratio of 1.5:1 ASD to ADHD in each set. This subsampling technique was used to ameliorate the issue of significantly unbalanced classes, as well as to safeguard against any age or gender biases that may be inherent to the data. For each sampling, we implemented forward feature selection using the previously obtained feature rankings to train and test our six machine learning algorithms, recording the performance of each model with default parameters, as well as with parameter tuning for each choice of features. This process was repeated for each of the 10 cross-validation trials, resulting in an average area under the receiver operating characteristic (ROC) curve (AUC) for each model calculated over 100 trials. All machine learning analyses were performed in Python using the package Scikit-learn.X2-values comparing these distributions, for all 65 SRS items.For each trial in the 10-fold cross-validation, mutual information feature ranking was performed on the nine folds designated as the training set. In each of these 10 trials, the same 6 features were consistently identified as the top ranked features, and variation in feature order was not seen until rank 7 and beyond. The behaviors associated with the top six features can be found in Four of our algorithms  performed with comparable accuracy (0.962–0.965) utilizing the same five items, and represent the best models for this classification task. We compared ROC curves of these four classifiers applied to a subsample of our data using stratified 10-fold cross-validation , as well12 using a fraction of the behaviors that are traditionally measured, and others have performed similar analyses for detection of ADHD.16 Here, we sought to expand on these previous studies to test whether a limited set of behaviors derived from the SRS could be used to distinguish ASD from ADHD, thereby enabling increased specificity when confronted with clinically challenging cases. Using stratified 10-fold cross-validation, we implemented mutual information-based feature ranking and forward feature selection on six machine learning algorithms to develop classifiers that accurately separated these clinical populations using only a small number of features.Behavioral diagnosis of both ASD and ADHD is a time-intensive process that can be complicated by the overlaps in symptomatology. Due to the high demand for the multi-hour clinical assessments necessary for diagnosis, many children are waitlisted for over a year, delaying their diagnosis and thereby delaying the start of behavioral and/or pharmaceutical interventions. Currently, there is no diagnostic instrument that can directly distinguish autism from ADHD, nor does there exist a screening tool that is expressly designed to distinguish risk between the two disorders with high accuracy. We have previously utilized machine learning techniques to successfully detect ASD from non-ASD1 regularization is a discriminative model that enforces sparsity, guarding against the use of irrelevant features. Support vector machines do not admit a simple Bayesian interpretation and build a model based on extreme examples—data points near where a decision boundary should be. These properties allow us to automatically build models with potentially very different and more effective properties than conventional analyses might yield.Machine learning automates part of the process of model building. Conventional methods use probabilistic assumptions to evaluate the validity of classification schemes that often amount to human-crafted thresholding of features. The various machine learning methods we employed allowed us to construct models optimized on the observed data, discovering new classification criteria. These methods have beneficial properties that are generally orthogonal to the typical probabilistic assumptions used in more conventional statistical tests (often relying on distribution assumptions of the population of interest). For instance, Logistic Regression with lOur results showed that the tree-based algorithms, Decision Tree and Random Forest, were not well-suited to the classification task at hand. In 12 These models proved to be optimal for our classification task, not only due to their low error rate, but also due to their probabilistic qualities. Since they provide a probability score in addition to a classification decision, these models provide the ability to interpret their output in terms of confidence in the classification and subsequently in terms of risk level for either disorder  all performed with high accuracy (AUC>0.96) and utilized only five behaviors, representing a >92% reduction in the number of behaviors measured with the standard SRS. It is important to note that these five features were always chosen as the top-ranking features using the mRMR criterion in our 10 cross-validation trials, indicating that they are valuable for distinguishing between the two disorders. In fact, many of these features overlap with the behaviors that are measured in several of our previously created behavioral classifiers, including eye contact, reciprocal communication and peer play.disorder .2 there is strong impetus to focus energy on developing faster and mobilized systems for risk detection. Our results support the hypothesis that detection of ASD/ADHD risk earlier than these national averages is possible. However, further testing and validation must be done to confirm the accuracy in independent replicate samples.Our results suggest the possibilty that one of these classifiers, used singly or in conjunction with our previously created behavioral classifiers explicitly focused on differentiating autism from a more encompassing non-autism category, could act as a useful pre-clinical screening and triage tool to assess risk of ADHD and autism. Though the SRS is indicated for use in children aged 4–18 years, the behaviors that are measured by this tool are highly adaptable to younger ages, as is evidenced by the SRS-Preschool screening instrument, which implements a relatively small number of wording changes to make the 65 questions suitable for children as young as 3 years. This suggests the possibility that our classifier could be similarly adapted to this age group, and perhaps even younger. Given that the average age of diagnosis is currently 4.5 years for ASD and 7 years for ADHD and that roughly 90% of parents identify developmental concerns before 36 months,Furthermore, the caregiver-directed nature of our classifier coupled with the brevity of the question set, stresses a novel opportunity to create a mobile screening platform that could have broad access in terms of both geographic location and socio-economic status. By delivering this screening system via a mobile app, parents with developmental concerns about their child could receive an accurate assessment of their child's risk for ASD/ADHD more quickly than what is possible today. Moreover, if adapted by developmental medicine clinics, such a mobilized screening platform could prove useful for patient triage, enabling higher throughput and improved waitlist management.Further evaluation of this classification system is needed, including validation on a larger population of ADHD subjects, as well as broadening the classifiers to handle multi-label classification of individuals that have both ASD and ADHD. However, these preliminary results support the possibility that machine learning classifiers can be used as a short, comprehensible, caregiver-directed screening measure that, on a mobile platform, could provide a quick and streamlined assessment of risk.In this analysis of archival data, we were limited by the content of the data sets available. Given that these data stemmed from primarily autism-based collections, there was a large imbalance in favor of the ASD class . The 150


The as-synthesized products were characterized by X-ray diffraction (XRD), scanning electron microscope (SEM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), and UV-vis diffuse reflectance spectra (UV-vis DRS). It was found that BiPO4 was regular rods with smooth surfaces. However, BiPO4/Bi2S3 heterojunction had a rough surface, which could be attributed to the attachment of Bi2S3 on the surface of BiPO4 rods. The BiPO4/Bi2S3 composite exhibited better photocatalytic performance than that of pure BiPO4 and Bi2S3 for the degradation of methylene blue (MB) and Rhodamine B (RhB) under visible light. The enhanced photocatalytic performance could be ascribed to synergistic effect of BiPO4/Bi2S3 heterojunction, in which the attached Bi2S3 nanoparticles could improve visible-light absorption and the BiPO4/Bi2S3 heterojunction suppressed the recombination of photogenerated electron-hole pairs. Our work suggested that BiPO4/Bi2S3 heterojunction could be a potential photocatalyst under visible light.BiPO Currently, semiconductor photocatalysts have attracted a lot of interests due to their widely applications for the degradation of organic contaminants –4 and ge4 has recently been extensively studied [4 is strongly dependent on its crystal structure [4 showed a better photocatalytic performance than that of P25 for the photodegradation of organic contaminants under UV irradiation [4 had a wide band gap of about 3.8 eV and thus can only be excited by UV light to generate electron-hole pairs [4, many efforts have been taken. Lin et al. fabricated Ag3PO4/BiPO4 heterojunction with enhanced photocatalytic ability under visible-light irradiation [4/BiOCl heterojunction also had enhanced photocatalytic activity [4/g-C3N4 heterojunction could efficiently respond to visible-light irradiation [4/reduced graphene oxide composites with specific surface areas had better photocatalytic activity for the degradation of MB [4 with other semiconductors is still meaningful for improving light absorption in the visible spectrum and suppressing the recombination of the photogenerated electron-hole pairs more effectively.As a potential photocatalyst, BiPO studied –12. It htructure  and the adiation . Howeverle pairs . In ordeadiation . Duo et activity . Li et aadiation . Besideson of MB . Whereas2S3, a small band gap semiconductor (1.3 eV), has a high photoabsorption coefficient [2S3 [4/Bi2S3 [2S3/BiOBr [Bifficient –21. Hencent [2S3 , BiVO4/B[4/Bi2S3 , Bi2S3/BS3/BiOBr , and so 4/Bi2S3 heterostructure and their photocatalytic properties were evaluated by the degradation of MB and RhB under visible light. As expected, the as-prepared BiPO4/Bi2S3 heterojunction exhibited enhanced visible-light photocatalytic activity and a possible mechanism was presented.In this study, we reported the preparation of a novel BiPOAll reagents were of analytical purity  and used without further purification.4 was prepared by a facile hydrothermal method. Firstly, 0.5 g of PVP was dissolved in a beaker with deionized water (50 mL) under stirring. Secondly, Bi(NO3)3 · 5H2O and NaH2PO4 · 12H2O (molar radio of 1:1) were added into the solution. After the pH of the reaction system was adjusted to 3 by HNO3, the solution was transferred into a 100-mL Teflon-lined stainless steel autoclave and heated at 180 °C for 24 h. When the system cooled down to room temperature naturally, the resulting product was harvested and washed with deionized water and absolute alcohol for several times. Finally, the as-prepared products were dried at 60 °C for 12 h.BiPO4/Bi2S3 photocatalyst was prepared through an in situ ion exchange process. Typically, 0.1 g of PVP was dissolved in 50 mL of ethylene glycol, followed by the addition of 0.456 g of BiPO4 under stirring to achieve suspension. Then, a certain amount of thiourea  was added into above suspension and the solution was transferred into a 100-mL Teflon-lined stainless steel autoclave, which was sealed and maintained at 140 °C for 3 h. After the autoclave was cooled to room temperature naturally, the precipitates were collected and washed with water and ethanol several times. The BiPO4/Bi2S3 products were dried at 60 °C for 12 h. For comparison, pure Bi2S3 was prepared through hydrothermal method according to the literature [The BiPOterature .4 as a reference material. The elemental composition of the samples was analyzed by X-ray photoelectron spectrometer .The phase of the samples was measured by XRD  using an X-ray diffractometer with Cu Kα radiation. The morphology was analyzed by SEM on Hitachi S-4600 and TEM (FEI Tecnai G20). UV-vis DRS was tested on a Shimadzu UV240 UV-vis spectrophotometer with BaSO4/Bi2S3 heterojunction photocatalyst was evaluated by the degradation of MB and RhB under visible light. In each experiment, 50 mg of different photocatalysts were added into 100 mL of MB or RhB solution (10 mg/L) in a reactor. Before irradiation, the mixture was magnetically stirred for 30 min in the dark to achieve the adsorption/desorption equilibrium between dye and photocatalysts. Then, the solution was irradiated by visible light under continuous stirring. At a defined time interval, about 3 mL of solution was extracted from the reactors and then centrifuged to remove catalysts before analysis. Finally, MB (RhB) solution was analyzed through a UV-vis spectrophotometer. The degradation rate could be obtained through the formula [η = Ci/C0 × 100 %, where Ci was the absorbance of MB (RhB) which was measured every 30 min, and C0 was the absorbance of MB (RhB) before light up.The photocatalytic performance of BiPO formula : η = Ci/4 and BiPO4/Bi2S3 heterojunction with different Bi2S3 contents. In the pure BiPO4, all the diffraction peaks are well matched with the monoclinic phase of BiPO4 (JCPDS File No. 89–0287), indicating that the as-prepared BiPO4 has the high purity. On the other hand, the BiPO4/Bi2S3 composites exhibit a mixture of two crystalline phases. One can be identified as BiPO4, and the others originate from rutile Bi2S3 [2S3 gradually strengthen along with the increase of the Bi2S3 content, while those of BiPO4 simultaneously weaken. No other characteristic peaks of impurity are detected, suggesting that BiPO4/Bi2S3 composites are only composed of BiPO4 and Bi2S3 phases.Figure le Bi2S3 . Further5/2 and Bi 4f7/2 peaks of Bi3+, respectively [4 [5+. On the other hand, the binding energies of 164.12 and 158.76 eV are attributed to S 2p peaks  lattice plane of Bi2S3. Therefore, it can be summarized that BiPO4/Bi2S3 heterojunction is achieved through a facile ion-exchange method.TEM and HRTEM images are shown in Fig. age Fig. . The fri4, Bi2S3, and BiPO4/Bi2S3 composites. It reveals that BiPO4/Bi2S3 composites have a stronger absorption than that of BiPO4 in visible light. The band gap energy can be achieved through the formula [n values of BiPO4 and Bi2S3 are 4 [Eg of BiPO4 and Bi2S3 can be calculated as 4.08 and 1.30 eV. Moreover, Eg of BB-1, BB-2, and BB-3 are 4.01, 3.93, and 3.81 eV, respectively. Besides, Bi2S3 displays quantum size effect, which may influence the band gap, the position of both CB and VB band. Besides, the band gap shift relative to the bulk can be calculated by the following formula [Figure  formula , 31. BesS3 are 4  and 1 [3S3 are 4 , respect formula , 35:Fig.Eg (R) is the band gap shift, h is the Planck’s constant, and R is the crystal radius. Besides, mo is electron mass and me* and mh* are the effective masses of electrons and holes, respectively. Then, the size of Bi2S3 nanoparticles attached on the surface of BiPO4 rods can be calculated as 2.68, 2.72, and 2.78 nm, respectively, which is much smaller than Bohr excitation radius of 24 nm. Therefore, quantum size confinement can be observed obviously, which influences the band gap, the position of both CB and VB band, etc. These results also support the enhancement of photocatalytic activity.in which ∆4/Bi2S3 heterojunction was assessed by photodegradation of MB under visible-light irradiation . Interestingly, the coupling of BiPO4 with Bi2S3 leads to notable enhancement MB photodegradation. The MB removal rates are about 50, 80, and 60 %, respectively. Meantime, RhB here is also employed as an organic pollutant to further confirm the photodegradation activity of BiPO4/Bi2S3 heterojunction. As shown in Fig. 4/Bi2S3 composites show better photocatalytic activity in the degradation of RhB than that of pure BiPO4 and the best photocatalytic property was achieved for BB-2 sample. The enhanced visible-light-driven activity of the heterostructure must be attributed to the synergistic effect between BiPO4 and Bi2S3. What is more, the quantum size confinement of Bi2S3 in the visible spectrum also leads to the enhancement of photocatalytic activity. However, the excess Bi2S3 content in BiPO4/Bi2S3 composite will cause their photocatalytic performance to decrease (BB-3). It may be attributed to these reasons: one is reduction of active sites due to the excess Bi2S3 nanoparticles on the surface BiPO4 rod [2S3 may lower the separation efficiency of electron-hole pairs and further inhibit the photocatalytic activity [The photocatalytic performance of BiPOion Fig. . It can iPO4 rod . The othactivity .Fig. 6a4 and Bi2S3 are evaluated based on the equation [EVB and ECB) of BiPO4 and Bi2S3 are 4.39 eV, 0.31 eV and 1.43 eV, 0.13 eV, respectively. Therefore, the possible mechanism is shown in Fig. 2S3 nanoparticles absorb the visible light and give rise to electron-hole pairs. The photo-excited electrons in Bi2S3 CB will transfer to BiPO4 rods and holes are left in Bi2S3 VB, which will decrease recombination rate of photogenerated charge carriers. The electrons in BiPO4 CB can rapidly adsorb O2 to form O2−•, while the holes can interact with the absorbed H2O to achieve hydroxyl radicals. After then, O2−• and OH• with strong oxidizability can decompose MB (RhB) to generate CO2 and H2O. Moreover, BiPO4/Bi2S3 heterojunction photocatalysts have a stronger and wider absorption in visible light, which is beneficial to photocatalytic activity.The band positions of BiPOequation . Hence, 4/Bi2S3 heterojunction with a facile two-step hydrothermal method. Bi2S3 nanoparticles can be in situ formed on the surface of BiPO4 rods through ion exchange. As the quantum size confinement of Bi2S3 in the visible spectrum, it can be used as photosensitizer. When BiPO4 rods are modified with Bi2S3, the separation of electron-hole pairs could be accelerated and the photoabsorption could be promoted as well. These directly led to the enhancement of photocatalytic activity for the degradation of MB (RhB) under visible-light irradiation, and BB-2 sample exhibits the best photocatalytic property. Degradation rate of MB under visible-light irradiation with BB-2 could reach to 80 % in 3 h, double that of pure BiPO4. Besides, degradation rate of RhB could reach to 99.6 % in 3 h, while it only degraded for 8 % by pure BiPO4.In summary, we have synthesized the BiPO


Since the discovery and now widespread use of olefin metathesis, the evolution of metathesis catalysts towards air stability has become an area of significant interest. In this fascinating area of study, beginning with early systems making use of high oxidation state early transition metal centers that required strict exclusion of water and air, advances have been made to render catalysts more stable and yet more functional group tolerant. This review summarizes the major developments concerning catalytic systems directed towards water and air tolerance. Transition metal-catalyzed alkene metathesis –10, whicIn this review, we summarize improvements associated with the stability of well-defined metathesis homogeneous systems towards the presence of air and water in the alkene metathesis and hopefully raise the awareness of the significant tolerance of standard metathesis catalysts to these conditions.Although well-defined early transition metal-based catalysts formed the basis of early metathesis reactions and can be thought of as the forefathers of modern metathesis catalysts –30, thes9To overcome the sensitivity problems exhibited by early transition-based catalysts, late transition metals, which do not exhibit high oxophilicity, appeared as the most promising candidates for reactions performed in air.2O)6(tos)2 could polymerize 7-oxanorbonene 1 in water under air 3 in the self-metathesis of silicon-contaning olefins. The reactions were performed with 1 mol % of Ru at 150 °C in air, under solvent-free conditions for several days, to afford 1,2-bis(silyl)ethenes in moderate to good yields : Co: Cond ge systems , althougnd generation catalyst 15 was compared to an m-isopropoxy-substituted Hoveyda–Grubbs’ 2nd generation catalyst 41 . The quaternary group increased the solubility in solvent mixtures and also increased the activity of the complex due to the electron-withdrawing effects of substituents.Soon after, in 2006, the same group presented a variation of the Hoveyda–Grubbs 2roup 54,  63]. Co. Cond gend generation catalyst 33 (0.1 mol %) in air and in different solvents for the RCM of diethyl diallylmalonate (29) -diol was added to the water phase and isomerization to the trans isomer 71 was completeted after 1 h, with no decrease in activity (94% isolated yield) observed.In 2012, Grela and co-workers described the synthesis and use of 3 ammonium chloride-tagged variations of Hoveyda–Grubbs’ catalyst 67–69, [67]. Thnd generation catalyst bearing a sulfur-based anion , replacing one of the chlorides . Th. Th69]. nd generation catalyst, featuring the substitution of PCy3 with two molecules of 3-bromopyridine  showed increased activity and maintained the same thermal stability. Again, these complexes showed similar activity to the Grubbs 2nd generation catalysts ; ph; ph98a–d95) and diethyl bismalonate leading to the highest yields reported to date [Their stability at high temperatures allowed their use in the RCM of bistosylamide , using 0.1 mol % of 33, 85 and 98a under air and in refluxing toluene, showed a 60% conversion after 20 min for 98a. Under these conditions, the other catalysts were completely inactive after 20 min and lead to conversions lower than 40%, when used for prolonged reaction times. After evaluation of the detrimental effects of each of the components of air on catalyst activity, a general trend could be observed: H2O > CO2 ≥ O2. In all cases, water had the most deleterious effect, whereas reactions could be performed in dry air and in N2 atmosphere without any noticeable differences as compared to their use under inert atmosphere.A preliminary test on the RCM of bistosylamide  of all catalysts were required.As can be seen from 111a–f, 105a–f, 106a–f, 107a–f and 111a–c. RCM reactions proceeded smoothly using N,N-diallyltosylamide (46) giving, with all catalysts, quantitative yields. When a more challenging substrate tosylamide, 79) was used, a 24 h reaction time was needed in all cases, with the exception of 111d  was due to the presence of the electron-withdrawing substituents on the Schiff base.In 2009, surely inspired by the aforementioned work, the Verpoort group reported a family of indenylidene Schiff base–ruthenium complexes 111a–f,  for CM a of 111d . This reAlthough metathesis-type reactions represent one of the most valuable strategies in modern organic synthesis, making this highly valuable tool more accessible and practical for routine use still remains a challenge. Ruthenium-based catalysts have been at the centre of recent advancements making possible their use in air, moreover these catalysts are becoming more and more stable, efficient and economically friendly with time. With the current development directed towards air and moisture stability and high performance, there is no doubt that more reports will push these reactivity/tolerance limits even further. As seen in this review, conducting metathesis-type reactions in air, in the presence of water and under high temperature has become more concrete, with several groups leading the charge ,86.


Many clinical studies reported a compromised brain lateralization in patients with Attention-Deficit/Hyperactivity Disorder (ADHD) without being conclusive about whether the deficit existed in the left or right hemisphere. It is well-recognized that studying ADHD dimensionally is more controlled for comorbid problems and medication effects, and provides more accurate assessment of the symptoms. Therefore, the present study applied the dimensional approach to test the relationship between brain lateralization and self-reported ADHD symptoms in a population sample. Eighty-five right-handed university students filled in the Conners’ Adult ADHD Rating Scales and performed a lateralization reaction time task. The task consists of two matching conditions: one condition requires nominal identification for letters tapping left hemisphere specialization (Letter Name-Identity condition) and the other one requires physical and visuospatial identification for shapes tapping right hemisphere specialization . The letters or shapes to be matched are presented in left or right visual field of a fixation cross. For both task conditions, brain lateralization was indexed as the difference in mean reaction time between left and right visual field. Linear regression analyses, controlled for mood symptoms reported by a depression, anxiety, and stress scale, showed no relationship between the variables. These findings from a population sample of adults do not support the dimensionality of lateralized information processing deficit in ADHD symptomatology. However, group comparison analyses showed that subjects with high level of inattention symptoms close to or above the clinical cut-off had a reduced right hemisphere processing in the Shape Physical-Identity condition. With a prevalence rate of 5% in children and 1 to 7% in adults  AttentioMoreover, there is evidence that abnormal brain lateralization might be a core component underlying dysfunctions in ADHD , 2009. AOther studies have reported abnormalities in the left hemisphere; in particular, slightly greater left posterior cingulate cortex  that relAt the behavioral level, some studies have suggested a disruption of the right hemisphere attentional network. For instance, studies using divided visual field tasks have indicated perceptual asymmetry deficit in ADHD characterized by poor performance for Left Visual Field (LVF) during visuospatial attentional processing . Self-reOther behavioral studies have suggested a reduced left hemisphere contribution during lexical decision  and dichAll in all, the information presented above on abnormal brain lateralization in ADHD is inconclusive; albeit most evidence favors right hemisphere dysfunction. In arriving at this conclusion, it is underlined that atypical laterality is based on research carried out on individuals fulfilling the DSM criteria for ADHD which is termed the categorical approach. The approach is criticized because many individuals who fulfill the diagnostic criteria for ADHD have more mental problems such as mood disorders, aggression, and learning disabilities. In addition, many of them use medication. The two factors of comorbidity and medication use may confound experimental data and interpretation. In the present study, we aim to investigate lateralized brain dysfunction at the behavioral level from the perspective of the dimensional approach. The dimensional approach does not require the arbitrary dichotomization of individuals into categories based on an all-or-none principle but positions individuals on a continuum . It alloIt is well-recognized that studying ADHD dimensionally is more controlled for comorbid problems and medication effects. By measuring comorbidities related to the disorder and including them in the analyses, researchers can evaluate the effect of ADHD and its comorbidities apart on the variables of interest. With respect to medication effects, the effects are supposed to be minor or not present if the majority of the sample reported no clinical diagnosis. Moreover, the dimensional approach usually offers a more powerful statistical test of any hypothesis due to the large sample size and also provides more accurate assessment of the symptoms . This maThe present study has investigated the dimensional relationship between brain lateralization and self-reported ADHD symptoms in a sample of adults. Especially, inattention symptoms are of interest here, as it has been found that adults demonstrate more inattention symptoms than other ADHD symptoms Do Letter Name-Identity and Shape Physical-Identity task conditions tap different sizes of visual field advantage measured by reaction time and error rate?(2)After controlling for mood symptoms , do self-reported ADHD symptoms  predict the size of visual field advantage on each task condition?SD = 2.4, min:max = 18:32). All participants were right handed; they were selected based on a criterion of having a score above 40 on the Edinburgh Handedness Inventory  at the University of Groningen received course credit for their participation in the experiment. The exclusion criteria were: (a) reported former or current diagnosis with ADHD and/or a diagnosis concerning depression and/or anxiety/stress, (b) reported medication related to ADHD and/or mood disorders. The mean age was 20.3 years (nventory . ParticiI’m absent minded in daily life activity”). The items are surveying four dimensions; three dimensions correspond to core features of ADHD . The fourth dimension corresponds to an important consequence of ADHD . The scale also contains the ADHD index subscale seen to be the most reliable and valid measure of overall ADHD symptomatology  depression, (b) anxiety, and (c) stress. Each subscale contains 14 items . The participants rated how often each emotional state applied to them over the last week on a four-point scale ranging from 0  to 3 (applied to me very much). The sum score of each subscale classifies the participants into one of five categories  relative to the population mean.The CAARS and DASS questionnaires have a high reliability and validity and are suited for the dimensional approach on psychopathology . The queFigure 1). The two letters or shapes above the fixation cross were the probes, and the letter or shape below the fixation cross was the target. One of the two probes had to be matched with the target. When a match is detected the subject has to press a response button.The task was based on the Banich paradigm . The stiFigure 2). A match was defined when one of the probes matched the target in the shape and orientation.There were two matching conditions; in the first the Letter Name-Identity condition, letters were displayed in different cases (the probes in upper-case and the target in lower-case) and randomly chosen from the letters A, B, D, G, H, E, F, L, R, M, T, and Q. A match was defined when one of the probes and the target had same name identity regardless of the letter case. The match may rely on the phonetic code of the letter names tapping left hemisphere processing. In the second condition, Shape Physical-Identity, unfamiliar shapes (the probes as well as the target) were displayed in their original form or in their mirrored form  between the screen and participant’s eye. A response box of one button was used to record the reaction time. It was positioned half way between the chin rest and the screen to enable easy reach.The study procedures were approved by the ethical committee governing psychology at the University of Groningen. Before running the experiment, the examiner explained the study procedures to the participants and obtained written informed consent. Thereafter, participants filled in the questionnaires and performed the brain lateralization task in counterbalance order . To perform the task, the participants were seated in a dimly lit room, their chin upon the chin rest. They were instructed to press a button with their right hand as fast and accurate as possible when the target letter or shape matches one of two probe letters or shapes. It was emphasized to keep their gaze on the fixation cross all the time and not to move their eyes away when the stimuli appeared. For eye blinks, the participants were verbally informed to make their possible blinks directly after pressing the button. This procedure aimed to decrease the number of missing errors caused by eye blinking. We admit that using instruction to control eye movements is not the most effective method. It could be recommended to use an objective measure to monitor eye movements such as eye-tacking or electrooculography method. However, using such experimental equipment is time consuming in terms of experimental preparation, and is less flexible in terms of the participants. We decided to control for eye movements by using the most often used method in the literature: instructing the participant to fixate on a central point together with rapid lateralized stimulus presentation of 150 ms, which is faster than the latency of eye movements  in each task condition as the relative difference between RVF and LVF performance: [(RVF–LVF)/] × 100. Consequently, a compromised right hemisphere processing is reflected by longer LVF reaction time giving a small size of visual field advantage, especially in the shape matching condition; whereas, a compromised left hemisphere processing is reflected by a high value of brain lateralization index especially in the letter matching condition.We run two statistical analyses:(1)To test the difference between the two task conditions in brain lateralization, a repeated measure analysis of variance on the size of visual field advantage was performed. The within subject factor was task condition . To test performance consistency and possible speed-accuracy trade-off, the size of visual field advantage was calculated separately from mean reaction time and error rate.(2)The score on the ADHD index subscale of the CAARS is seen to be the most reliable measure of overall ADHD symptomatology. To test whether overall ADHD symptomatology can predict atypical brain lateralization, a linear regression analysis on the size of visual field advantage was performed using the ADHD index score as a predictor.To test whether mood symptoms confound the effects of ADHD symptoms on brain lateralization, the mood DASS subscales were included in the analysis using a backward elimination procedure. In the first step of the procedure, the effects of all mood subscales combined  are tested followed by deleting, one by one, the mood subscales that are least significant.Please note: the design of the task mainly relies on reaction time performance; therefore, visual field advantage was calculated using only reaction times, not the error rates.The scores on the inattention, impulsivity, and hyperactivity subscales of the CAARS are reflecting the three key domains of ADHD symptoms. To test which specific symptoms (domain) can predict brain lateralization, a second linear regression analysis on the size of visual field advantage was performed using the scores on the inattention, impulsivity, and hyperactivity as predictors. The effects of the mood symptoms are tested in the same manner as in the first regression analysis using a backward elimination procedure. Finally, in subsequent analyses, we thought to confirm and test whether the relationship between lateralization and ADHD symptoms is present at the categorical not the dimensional perspective. Repeated measures analyses of variance were performed to compare the size of visual field advantage of first and fourth quartile group on the ADHD index, inattention, hyperactivity, and impulsivity scores. The within subject factor was task condition  and the between subjects factor was group .Figure 3 shows the distribution of T-scores on the ADHD index, inattention, hyperactivity, and impulsivity subscales of the CAARS measuring the overall ADHD symptoms and its key domains. The figure indicates that scores on the four domains provide enough variance to test our lateralization hypothesis using the dimensional approach. According to the CAARS manual, the T-score of 65 can be used as a clinical cut-off for all subscales of the CAARS. As can be seen, few students scored above the clinical cut-off. Participants had reliable responses on the CAARS indicated by lower score than eight on the inconsistency index. Table 1 presents the number of subjects within the cut-off scores for the DASS reflecting the degree of severity of mood symptoms relative to the population.Figure 3 and Table 1 indicate that the sample can be seen as a population sample. Correlations between the overall ADHD symptoms  and mood symptoms  ranged from 0.31 to 0.43 with p < 0.005. This indicates that the closer the ADHD symptomatology comes to the clinical cut-off, the more pronounced the mood comorbidities.Taken together, p ≥ 0.33). Therefore, Figure 4 presents the mean size of visual field advantage for each task condition in males and females together.Neither the main effect of gender nor its interaction with the task condition was significant for the visual field advantage on reaction time  = 4.029, p < 0.05, M = 13.66, SD = 15.72) than the Letter Name-Identity condition .A repeated measure analysis of variance revealed a significant main effect of task condition for the visual field advantage, p ≥ 0.42). The analysis revealed a non-significant main effect of task condition, F = 3.424, p = 0.07, The main effect of gender and its interaction with the task condition was not significant for the visual field advantage on error rate  predict the visual field advantage calculated form reaction time performance on the task conditions . Pearson correlations between the size of visual field advantage and the CAARS subscales were not significant (p ≥ 0.16). In addition, the analyses showed that the DASS mood subscales did not relate to the size of visual field advantage. Therefore, it might be concluded that mood symptoms did not confound the outcome.n = 23) on the inattention subscale showed a significant lower LVF/right hemisphere advantage than the Low-score group (n = 28); the main effect of group was significant F = 5.97, p < 0.02, Post hoc analysis for the inattention subscale indicated that group differences were in the Shape Physical-Identity condition, t(49) = 2.38, p = 0.02, but not in the Letter Name-Identity condition, the mean size of visual field advantage were 6.27 and 12.03 in the Letter Name-Identity condition, and were 7.56 and 17.40 in the Shape Physical-Identity condition for, respectively, the High- and the Low-score group . Groups did not differ on the other scales in the two task conditions.Comparing participants in the first and fourth quartile scores on inattention, hyperactivity and impulsivity yielded a significant difference in the size of visual filed advantage for group composition based on inattention. The High-score group  is consistent with the clinical studies on children and adults with ADHD showing a compromised reaction time performance on the LVF . ConsequThe main conclusion that high level of inattention symptoms is associated with reduced right hemisphere function will be discussed in the view of some essential issues connected with the experimental design used in the present study.First, the effect of lateralized motor components/processes on task performance was not counted because the study was not designed to explore lateralized motor processes. The study was designed to explore lateralized perceptual processes in the letter and the shape matching condition, and its relation to ADHD symptoms. To address the lateralized perceptual processes, the main manipulation of the task was focused on stimuli type (letters vs. oriented shapes) and using two visual fields (LVF vs. RVF). We admit that nevertheless a motor component was involved in the task, namely in the LVF condition. Consequently, it is questioned whether less LVF advantage as found in our study mirrors reduced right hemisphere processing, or abnormal interhemispheric communication in individuals with high inattention scores. Following Poffenberger’s logic, if the right hand is the responding hand then reaction time in the LVF should be slower than reaction time in the RVF because the time needed to transfer information between the two hemispheres is added to the total processing duration . Our stuSecond, although the outcome of the present study suggests that right hemisphere dysfunction and not compromised interhemispheric interaction is at stake in individuals with high inattention symptoms, it must be underlined that evidence is growing that there is a dynamic relation between lateralized brain functions and interhemispheric interaction , and thaSo far, we discussed brain lateralization in terms of functional asymmetry. The question emerges to what extent the functional asymmetry is related to anatomical asymmetry. In healthy subjects the LVF advantage, reported in several visuospatial tasks such as covert attention task, has been associated with a bilateral network including dorsal and ventral fronto-partial attention related systems and subcortical structures, i.e., thalamus, basal ganglia, and brainstem . Siman-TThe dorsal and ventral attentional networks form key component of attentional regulatory systems of the brain. The former is closely related to circuits refer to as “salience network” and interrupting on going activity when appropriate. The network most likely to be affected by the ventral is the dorsal attentional network which mediates goal-directed, top–down executive control processes. The specificity of our task conditions may have challenged the ventral and dorsal networks. So far, most of the literature does not support clear involvement in the ventral attentional network in ADHD , but somIt is obvious that translating functional asymmetry into anatomical asymmetry needs the combination of a valid behavioral task and using fMRI. We hope that the present study provided some guidelines for the set-up of essential studies on ADHD symptomatology and brain laterality.The final considerations concerns the characteristics of the participating sample. Although a sample of university students may be considered more homogenous than clinical samples with respect to IQ level, demographic variables, and comorbidities related to ADHD, the sample may still have hidden disabilities such as learning and psychiatric disorders . We admiAnother factor that may have confounded the outcome is gender; our sample has more females than males. Meta-analytic reviews indicated that the prevalence rate of ADHD is higher in males than in females, and that there are gender differences in cognitive impairments, type of ADHD-comorbidities , and latIt is well-recognized that the validity of self-reports from students may be questioned. For instance, students may understate or exaggerate rating themselves as having significant clinical ADHD symptoms . Please The present study focused on right handed adults, it could be of interest to investigate the same relationship on ambidextrous or left handed adults. Since ADHD symptoms are related to non-right handedness , the detIn sum, we adopted the strategy of investigating the relevance of atypical lateralization for ADHD by using the dimensional approach. We assume that it provides more accurate assessment of the disorder than clinical classification. The results do not support, in a strict sense, the dimensionality of abnormal lateralized information processing in adult ADHD symptomatology, but underlines the role of atypical lateralization (right hemisphere deficit) in especially the inattention subtype of ADHD.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.