Consistent research findings indicate that parents and teachers observe genuinely different Attention Deficit/Hyperactivity Disorder (ADHD) behaviours in their respective settings.To evaluate the utility of information provided by teacher informant assessments (INFAs) of ADHD symptoms, and the implications of aggregation algorithms in combing parents’ information, i.e. using ‘or-rule’ (endorsement by either one informant) versus ‘and-rule’ (endorsement by both informants).Teacher ratings on Conners scales and clinical data from parental accounts on 1383 probands and their siblings from the IMAGE study were analysed. The psychometric properties of teacher and combined ratings using the item response theory model (IRT) are presented. Kappa coefficients, intraclass correlations and linear regression were employed.κ = 0.01–0.15) and for dimensional scores (r = 0.12–0.16). The ‘or-rule’ captured milder expressions of ADHD symptoms, whereas the ‘and-rule’ indexed greater severity of ADHD.First, teacher endorsement of symptoms is located in a narrow part of the trait continuum close to the average levels. Symptoms exhibit comparable perception in the measurement of the trait(s) with similar discrimination ability and information (reliability). Second, the IRT properties of the ‘or-rule’ ratings are predominantly influenced by parent-INFAs; and the ‘and-rule’ ratings predominantly by teacher-INFAs ratings. Third, parent-teacher INFAs agreement was low, both for individual items  contains supplementary material, which is available to authorized users. Attention Deficit/Hyperactivity Disorder (ADHD) is one of the most frequently diagnosed child psychiatric disorders in clinical practice, affecting about 3–5% of all school age children. Authoritative diagnostic manuals and practice guidelines recommend aggregating information for diagnostic purposes across informants and settings, in particular, from the home and school settings, with information typically derived from parents and teachers .However, the agreement between parent and teacher ratings of ADHD symptoms is typically low to moderate with different studies reporting correlations between these ratings ranging from 0.09 to 0.43 Tripp et al.  found thOther authors have previously carried out item-response theory (IRT) analyses on parent and teacher ratings using different instruments. Briefly, Gomez  carried A range of studies have found that diagnostic labelling and the distribution of ADHD subtypes varies according to the diagnostic aggregation algorithm used , 10. Thedifferential item functioning in the IRT framework) exists when an item functions differently based on group membership: that is, when individuals with the same trait levels have different probabilities of endorsing the symptom criterion based only on group membership. Accordingly, we investigated whether for the same underlying levels or the traits (Inattention (IA) or Hyperactivity/impulsivity (HI) separately) parents and teachers have the same probability of endorsing a symptom criterion; and the result was negative. Teacher-INFAs were fundamentally different from that of parents, which we argued, could be attributable to different behaviours at home and at school, to different understanding of the symptom criteria by teachers and parents, or most likely to a combination of different child behaviour and different rater understanding—a view in keeping with those proposed by Willcutt et al. [One of our recent studies, with the same sample, examined measurement invariance and established that parent and teacher informant assessments (INFAs) essentially rate different kinds of behaviours expressed in different settings, instead of their differences arising from measurement bias . Lack oft et al. , Hartmant et al.  and Martt et al. .Having established the lack of measurement invariance between parent and teacher-INFAs, we considered important to explore next the patterns in parents and teacher-INFAs across the latent trait continuum /symptom dimension using an item-response theory (IRT) framework.Previously, Garcia-Rosales et al.  exploredTo make an ADHD diagnosis, DSM-5 and ICD systems require the presence of symptoms pervasive across settings. In real-life clinical diagnostic evaluation, clinicians therefore need to obtain valid and reliable information from informants more than one setting in a cost-effective manner. Apart from mental state examination of the child and a qualitative school report from the teacher, a clinician usually relies on additional information from two key sources: (i) clinical interviews of parents; and (ii) rating scale information from teachers. However, how to best utilize the different pieces of information and how to best combine them has not been examined in depth using IRT, in particular, using the ‘and-rule’ and the ‘or-rule’.In this study, we utilised IRT to explore (a) the IRT properties of the teacher-INFAs for each symptom  across the symptom dimension (b) the IRT properties of the aggregated ratings (‘or-rule’ and ‘and-rule’), and (c) the differences in total symptoms endorsed by parent and teacher INFAs and the implications of the aggregation methods in diagnosis. The statistical robustness of this study is underpinned by the previous one  where a The International Multicentre AD/HD Genetics (IMAGE) project was an international collaborative study funded by the National Institute of Mental Health (NIMH) to identify candidate genes, genetic markers, and quantitative trait loci associated with ADHD. The sample consisted of European Caucasian subjects recruited from twelve specialist host centres in eight countries: Belgium, Germany, Holland, Ireland, Israel, Spain, Switzerland and the United Kingdom. Ethical approval for the study was obtained from Ethical Review Boards within each country and informed consent obtained from the children and their families. All children (probands and siblings) were aged 5 to 17, had an IQ ≥ 70, were of European Caucasian descent, and had access to at least one biological parent for DNA collection. Exclusion criteria applying to both probands and siblings included autism, epilepsy, IQ < 70, brain disorders, and any genetic or medical disorder associated with externalizing behaviours that might mimic ADHD. A detailed description of the study design and diagnostic approach has been published elsewhere , 17.M = 10.9, SD = 2.9 years). The two genderst(1358) = 1.13, p = 0.261).The initial sample from the IMAGE project consisted of 3229 entries, of which 1788 were selected with complete Parental Account of Children’s Symptoms (PACS) data and ADHD ratings by teachers. Among those, 1383 children were initially referred with an ADHD diagnosis (as ‘probands’) and 405 were siblings of the probands . For thThe Long Version of the Conners’ Teacher Rating Scale (CTRS-R:L)  was usedADHD symptoms derived from parental accounts were obtained from PACS ratings. PACS is a standardized semi-structured, investigator-based interview, developed as an instrument to provide an objective measure of a child’s behaviour. For full details, see sister paper by Garcia-Rosales et al. The choice of different scales to collect information from parents and teachers should constitute a closer reflection of clinical reality where clinicians collect a lot more detailed and historical information in the home setting from parents usually present in the clinic as well as information from teacher observations over the course of months sometimes years encapsulated in a questionnaire as opposed to a formal clinical interview.The abbreviations of DSM items used in this report are adapted from those used in the DSM-IV field trial  and are θ) may not be directly measurable but it can be measured indirectly in a multivariate manner via a set of observed items. Here we implemented the two-parameter logistic IRT model [Teacher-INFAs and combination ratings were examined using IRT (see glossary of IRT terms in Table S3). According to IRT, a latent trait . Higher levels of IA were required for loses and forgetful to be endorsed . The slopes of all ICCs were broadly similarly steep ; even small differences in the levels of IA (x-axis) corresponded to large differences in the probability of endorsing this symptom (y-axis), and this applied to all IA symptom criteria.In terms of IA Fig. b, distrafidgets was the least severe item contrasting with runs/climbs being the most severe. That is, teachers would endorse fidgets even for children with HI levels at the lower end of the continuum, however would require high levels of HI to endorse runs/climbs. Quiet was the least discriminating item and motor was the most discriminating symptom. That is, endorsement of quiet discriminated less between children with and without HI trait levels, compared to the endorsement of motor.Regarding HI Fig. f, fidgetIn both IA and HI, we observe that the ICCs are clustered together, close to the average value (0) and with broadly similar slopes, in contrast to the parent-INFAs.disorganised and the least one was forgetful. For HI . That is, the teacher-INFAs in all symptoms are mostly reliable for the average person, in terms of IA/HI levels. In contrast to the parental curves, there were no symptoms isolated in terms of precision at a certain point on the continuum .The item information curves (IIC), which correspond to the teacher-INFAs are presented in Fig.  HI Fig. f, the moSee Tables S1 and S2 for parameter estimates for both parent and teacher-INFAs and Figures S1 and S2 for the corresponding ICCs and Figures S2 and S6 for all IICs for each gender.Figure . Patterns were broadly similar for IA and HI dimensions as well as the precision of the items, depicted in the IICs  as the dependent variable predicted by gender, adjusted for age, separately for parents and teachers and for IA and HI. The Benjamini and Hochberg  correctims Table , accordip < 0.001; for HI: median 7 vs 4 symptoms, p < 0.001) than teachers. The percentage of children rated as having a symptom by the parents-only ranged from 12 to 56%. On the other hand, the percentage of children rated by the teachers-only was comparatively lower with a range of 2 to 19% (with the exception of attention at 39%). The agreement ranged from 41% for runs/climbs to 65% for careless and 74% for distracted, with most of the symptoms having about 50% agreement between raters. On the sum-score level, the intraclass correlation coefficients were low for both IA and HI (r = 0.17 and 0.12 respectively) indicating very low agreement.Parents endorsed significantly more symptoms , the ICCs were located closer to that of the teacher-INFA ICCs, but made the parent-INFA more spread out  could be made based on teacher-INFA as they provide richer information within a narrower middle window. Parent-INFA described the symptoms along the continuum of the traits as the ICC were spread from very low to very high trait levels; in contrast, for teachers, symptoms are clustered within that narrower middle window. As the number of symptoms is one of the criteria for the diagnosis of ADHD, this middle window potentially constitutes the diagnostic threshold where cases could be differentiated from non-cases. Teacher information would therefore be more likely helpful in informing diagnosis, whereas parental information would help gathering information across the full continuum. These findings have a bearing in terms of re-thinking the diagnostic criteria for ADHD. Consistent with our view, Gomez  noted thFinally the ‘potential case status’ (defined here solely by the 6-item threshold) varied widely depending both on the source of information and on the aggregation algorithm employed (‘and-rule’ versus ‘or-rule’). Our findings are in line with previous studies which focused on caseness and subtype stability across aggregation methods in both clinical , 25 and group invariance property of the IRT item parameters, our findings are potentially statistically generalizable to the general population, however other factors need to be taken into account such as the effects of instruments and measurement factors which could not be fully disentangled from that of raters. Our findings must be regarded as preliminary before replication using either community samples or clinic samples with independently ascertained controls. Our sample also consisted of participants recruited from different centres located in different European countries, Müller et al. [Several limitations need to be considered. Different methodological tools were used to assess ADHD symptoms in our study: PACS interviews for parents and Conners rating scales for teachers. PACS provides far more detailed and minute information compared to Conners. This is in keeping with clinical practice where clinicians often have more information from parents; but often are sent a completed ADHD questionnaire such as Conners by teachers. For this reason, our results should be closer to the busy clinician’s everyday practice. Our sample consisted of ADHD cases ascertained from psychiatric and paediatric clinics with their non-ADHD siblings forming the comparison group, so the comparison group was not independently ascertained. Due to genetic relatedness, there were likely many subthreshold ADHD cases among the siblings, which probably reduced our item discrimination parameters. Furthermore, the sample analysed consisted of a high proportion of probands. Despite this, due to the r et al.  have dem’ and ‘or-rule’ with a finer differentiation on information contribution and utility, such as determining severity and diagnosis of ADHD in lower-level severity groups. Parents are better at screening than diagnosing. Overall, the ‘or-rule’ appears more appropriate for capturing cases with milder and more nuanced symptom expression (more sensitive); and the ‘and-rule’ for determining and indexing severity in the clinical range (more specific). Therefore, for diagnosing ADHD in under-identified groups , the ‘or-rule’ may be more applicable. The DSM-5 [Our findings identify the specific merits of the ‘and-rulehe DSM-5  has intrOverall, our findings highlight important and valuable aspects of different INFAs and their combinations. Each group uniquely provides clinically relevant and valuable information.Supplementary file1 (DOCX 1405 kb)Below is the link to the electronic supplementary material.


Subintimal angioplasty (SIA) was introduced in the late 1980s and is a supplement to bypass surgery. Adaptation of the technique has been hampered by high rates of early intervention to maintain patency, but the long term assisted patency is good.The superficial femoral and popliteal artery containing a patent subintimal canal were explanted from a patient who died in the authors' ward. Histological analysis indicated that the lumen was created in the medial layer of the vessel wall. A collagen rich neointima and fragmented internal elastic lamina were observed, presumably as a result of activated smooth muscle cells. The luminal surface was partly covered by a single layer of CD31, von Willebrand factor, and partly CD144 positive cells. An early atherosclerotic lesion was observed distally in the subintimal canal.Remodelling and neo-cellularisation of the vascular wall after SIA are described. Notably, hallmarks of early and late stage atherosclerotic disease were evident throughout the subintimal canal. These observations require confirmation in a larger number of specimens but underscore the need for surveillance after SIA. •The subintimal canal was created in the medial layer of the vessel wall.•Early and late stage atherosclerosis is observed throughout the subintimal canal.•Neo-cellularisation of single layer luminal cells is apparent in the subintimal canal.•The findings underscore the need for surveillance of subintimal canals. Peripheral artery disease affects about 20% of the population aged > 60 years, of whom about 35% have symptoms. The disease is associated with the lowest quality of life of all symptomatic cardiovascular disease manifestations and is the costliest.As a supplement to bypass surgery, recanalisation of occluded arteries using a subintimal angioplasty technique (SIA) was introduced by Bolia and co-workers in the late 1980s.In this report, the superficial and popliteal artery containing a patent subintimal canal were explanted from a patient who died in the authors' ward. A detailed histological analysis of the subintimal canal is presented.A 69 year old man presented with gradually worsening right calf pain on walking. Three years earlier he had undergone an above knee femoropopliteal bypass operation with a PTFE graft. The graft occluded, thrombolysis was initiated twice, but re-occlusion occurred shortly after both procedures despite antiplatelet therapy (aspirin 160 mg once daily) and warfarin. He had stopped smoking 12 years previously. Following months of exercise without improvement in symptoms, subintimal angioplasty (SIA) was performed via ipsilateral femoral access, and the entire superficial femoral artery was traversed with re-entry in the popliteal artery beyond the distal bypass graft anastomosis. A 6 mm balloon was inflated to create the new lumen A. CompleDuring those six years he had been taking aspirin and, for the last three years, a statin. He did not have, nor did he develop, diabetes. Then, at age 79, he was referred with an occluded bypass in his left leg. Thrombolysis was initiated, but the procedure was complicated by intracranial haemorrhage and the patient died. Consent was obtained from the patient's next of kin to remove the patient's right femoral and popliteal arteries, containing the patent subintimal canal, for analysis.The subintimal canal was approximately 30 cm in length. Histological examination suggested that the lumen was created in the medial layer of the vessel wall B. FocusiThe main finding in this report is evidence of arterial wall remodelling and neo-cellularisation in a subintimal canal 10 years after it was created in the superficial femoral artery.In SIA, a guide wire is used to traverse an occlusion blindly, where it follows the path of least resistance.During the SIA procedure, when the balloon is inflated to create a new lumen, profound activation of smooth muscle cells occurs. Subsequent increase in synthesis of extracellular matrix proteins, such as collagen and elastin, may be the result. The collagen rich neointima observed in the middle part of the subintimal canal B and C iA thin and fragmented internal elastic lamina (IEL), the inner “rubber band” of arteries mainly composed of elastin, can be observed in the middle part of the subintimal canal B. It is Stretches of single layer luminal cells positive for CD31, vWF and partly VE-cadherin are observed in the middle part of the subintimal canal F–H. PatcIn the distal part of the canal, hallmarks of an early atherosclerotic lesion can be observed A–C, withFifteen years ago, the present authors published results from 101 patients treated by SIA in the authors' department.Histological evidence is presented of arterial wall remodelling and neo-cellularisation in a subintimal canal 10 years after it was created in the superficial femoral artery. A large part of the remodelling resembles that of late stage atherosclerosis, but an early atherosclerotic lesion was observed in the distal part of the canal. There is evidence of neo-endothelialisation, but this must be confirmed. Whether or not these observations can explain why the patency of subintimal canals improves over time remains uncertain. The authors believe that it is safe to conclude that long term follow up of subintimal canals is warranted.


Oryza sativa L.) largely depend on its physicochemical and cooking properties, which are found to be superior for landraces than modern varieties. In this study, we assessed and evaluated milled rice of 30 rice landraces on their physicochemical and cooking characteristics which aim to promote the revival of old landraces. Six parameters of physical properties, four parameters of chemical properties, and five parameters of cooking properties were evaluated based on the standard protocols. Significant variations (p < 0.05) were found in all the properties that were evaluated. The result showed that the highest milling recovery was found in Indrabeli (75.55%) whereas the lowest was found in Kalo Masino (66.98%) and bulk density ranged from 0.81 g/cm3 to 0.88 g/cm3 showing not much variability. Although most of them were of medium grain type, their 1000 kernel weight varied between 12.62 g and 25.65 g. From the observed chemical properties, Pahelo Anadi (9.73 ± 0.55 mm) showed the highest gel consistency and lowest apparent amylose content (7.23 ± 0.36%). Also, 13% of landraces possessed strong aroma while noble cooking properties were showed by Thakali Lahare Marsi with the highest elongation ratio (2.41 ± 0.05) and by Chiniya with the lowest gruel solid loss (0.033 ± 0.03%) and minimum optimum cooking time (23.45 ± 0.03 min). In the principal component analysis, the first four principal components retained 73.8% of the variance. The first and second principal components were mostly related with the physical and chemical characteristics while the third and fourth principal components were concerned with cooking characters. Superior characters possessed by rice landraces can be further assessed for the breeding programs so that the cultivation of these cherished rice landraces can be enhanced.After the Green Revolution, the increase in the choice of modern varieties at the expense of landraces has become a major cause of varietal loss. The preference, choice, and the economy of rice ( Oryza sativa L.) has occupied the position as one of the leading food crops of the world that feeds nearly over one-half of the world population as a staple food [Rice , Lamjung Campus, in irrigated transplanting condition during July-November, 2018. Rice was harvested manually, threshed, cleaned, and the moisture percentage was decreased to 12%. The samples were then shelled using the Otake Rice Sheller  in order to obtain the brown rice. The obtained brown rice was polished in Yamamoto Rice Polisher  to obtain milled rice of 4% degree of milling. Shelling and polishing activities were done in the Food Research Division, Nepal Agricultural Research Council, Khumaltar, Lalitpur. All the lab experiments were carried out in the Laboratory of IAAS, Lamjung Campus, in February 2019.The obtained brown rice after shelling was weighed to determine the hulling percentage with the equation given by Bhattacharya . (1)HulThe obtained milled rice after polishing was weighed to determine the milling recovery of the rice sample using the following equation given by Shaeed, Akinoso, and Nahemiah ; Bhattac3) of milled rice was calculated according to the equation used by Fraser, Verma, and Muir [The bulk density (g/cmand Muir :(3)BulkAs per the method mentioned by Nadvornikova et al.  and ShaeL/W is the length-width ratio of milled rice, L is the average length of milled rice (mm), and W is the average width of milled rice (mm). Based on the length-width ratio, grains were classified according to the classification provided by IRRI: slender (>3.0), medium (2.1-3.0), bold (1.1-2.0), and round (<1.1) grain types [Grain shape here is referred to as the length-width ratio, which is calculated using the equationin types .This was determined by counting 1000 kernels from each sample randomly and weighing 1000 kernels of each landraces separately .For the alkali spreading test, seven whole kernels of each landraces were taken in Petri dish with three replications; then, 20 ml of 1.7% potassium hydroxide (KOH), 1.7 g in 100 ml of distilled water, was added to the sample and kept undisturbed for 23 hours at room temperature of 21°C. The spreading value of each replication was rated visually on a 7-point numerical scale. Average scores of seven kernels were taken as the spreading value .The gel consistency was determined following the method given by Cagampang, Perez, and Juliano For amylose content determination, the method given by Juliano  was used200 mg (0.2 g) of whole grain milled rice kernel was weighed and placed in a culture tube. 0.5 ml of 0.1 N KOH was pipetted into the culture tube and closed with the lid. After 15 min, the lid was opened and smelled. Three persons were used as judges, and the mean score was taken. In case of doubt, the lid was again closed and was smelled again after 15 min .oC in 20 ml of water. The optimum cooking time was estimated by pressing the cooked rice samples between two glass slides at regular intervals till no white starch core was left [It was determined using the Ranghino method, where milled rice samples 2 g were placed in a 100 ml beaker and cooked in boiling hot water bath at 95was left .According to Bhattacharya and Sowbhagya , rice saW1 (g). Then, the remaining gruel liquor was poured in the Petri dish with few washings and the weight of the empty Petri dish with gruel was measured and recorded as W2 (g). The Petri dish was subjected to 110°C at a hot air oven for 5 hours, until the dry gruel was obtained. The weight of the Petri dish with dry gruel was measured and recorded as W3 (g) [W3–W1, where W1 is the weight of the empty Petri dish, W3 is the weight of the empty dishes+dry gruel [Remaining residual water from the sample used for the water uptake ratio was used for the determination of the gruel solid loss. The weight of the empty Petri dish was measured and noted as The elongation ratio is given by the average length of cooked rice divided by the average length of uncooked rice . The eloThe cooked rice length-breadth ratio was expressed using the equation :(8)CookThe experiment was conducted under laboratory condition with three replications. The data obtained from the experiment were entered and recorded in Microsoft Excel. Analysis of variance (ANOVA), post hoc test using LSD, principle component analysis (PCA), and graphs were made using R and its packages-agricolae, FactoMineR, factoextra, and ggplot2.The hulling percentage ranged from 76.18% to 82.53%, with CV of only 2.18%. Marsi had the highest hulling percentage of 82.53%, whereas Pahelo Anadi had the lowest hulling percentage of 76.18% followed by Kalo Masino (76.19%) (see Table Milled polished rice obtained from whole grain varied from 66.98% to 75.55% among the landraces with a CV of 3.32%. The highest milling recovery was obtained in Indrabeli (75.55%) followed by Baryang Masino (74.93%), and the lowest milling recovery was obtained in Kalo Masino (66.98%) followed by Aanga (67.86%) (see Table 3) and Thakali Lahare Marsi (0.88 g/cm3) whereas the minimum bulk density was obtained in Mansara (0.81 g/cm3) and Kalo Masino (0.81 g/cm3). No wide variation was observed in bulk density as the value only varied between 0.81 g/cm3 and 0.88 g/cm3 with a CV of 2.34%  . In long-type grain, the maximum length was seen in Jetho Budo (7.09 ± 0.084 mm) and the minimum length in Jarneli (6.8 ± 0.056 mm), in medium-type grain the maximum length was obtained in Biramful (6.54 ± 0.092 mm) and the minimum length in Pahelo Anadi (5.51 ± 0.069 mm), and in short-type grains the length ranged from Eakle (4.4 ± 0.041 mm) to Marsi (5.38 ± 0.059 mm). Although the grain breadth was significant between the landraces, their value only ranged from Kalo Jhinuwa (2.11 ± 0.021 mm) to Anadi Local (2.9 ± 0.003 mm) which suggest that variation in breadth among the landraces was not obtained as likely as the variation in length.As shown in p < 0.001) was observed for the length-breadth ratio between the landraces. The length-breadth ratio was maximum for Jetho Budo (2.99 ± 0.035 mm) and minimum for Thakali Lahare Marsi (1.7 ± 0.028 mm) followed by Pudke Dhan (1.66 ± 0.02 mm) and Juhari (1.72 ± 0.012 mm). From the length-breadth ratio, landraces were further grouped based on grain shape, in which 11 were bold grains and 19 were medium-type grains.The shape of the rice grain was expressed on the basis of length and breadth ratio. Significant difference  (The landraces were found significantly different for their average gel consistency (< 0.001) . Pahelo p < 0.001), but only small variation was found among them (CV = 3.63%), as shown in Apparent amylose content was found maximum in Jetho Budo (58.39 ± 1.17%) and minimum in Pahelo Anadi (7.23 ± 0.365%). The landraces evaluated were found significantly different in their amylose content (As shown in p < 0.001). Cooking time was found to be maximum for Aanga (44.4 ± 1.464 min) followed by Pahele (41.40 ± 1.892 min) whereas minimum cooking time was found in Chiniya (23.45 ± 0.029 min) followed by Jarneli (23.85 ± 0.267 min).The results of the optimum cooking time for the rice varieties are presented in p < 0.001).The water uptake ratio varied from 7.96 to 3.91 , in whicThe gruel solid loss in different rice landraces varied significantly. As shown in p < 0.001); however, low variability was obtained among them (CV = 4.15%)  which was significant than other landraces whereas the minimum elongation ratio was obtained in Rato Masino (1.20 ± 0.028) followed by Pakhe Sali (1.23 ± 0.024) and Kalo Jhinuwa (1.30 ± 0.052). The average elongation ratio of landraces varied significantly (= 4.15%) .p < 0.001) with the highest in Thakali Lahare Marsi (3.87 ± 0.065) followed by Jetho Budo (3.78 ± 0.09) and lowest in Kathe (2.05 ± 0.05) followed by Pakhe Sali (2.07 ± 0.062) (The average cooked length-breadth ratio was significantly different among the landraces (± 0.062) . In the In this study, the principal component analysis (PCA) was carried out to summarize the information contained in the multivariate data  of landraces without losing important information. The eigenvalues which measure the variation retained by the principal components were obtained to be 4.55, 2.61, 1.92, and 1.24 for the first four principal components. Also, the eigenvalues and variance percentage were evaluated from the scree plot  to deterThe milling characteristics are the important parameters to determine the grain quality for further processing of the milled rice as these are related with cooking and eating characters. In this study, we found landraces like Marsi, Baryang Masino, and Lekali Marsi have the highest hulling percentage which suggest they have a higher head rice recovery than long grain variety like Kalo Masino. Among the landraces not much variability was obtained in their milling characteristics. However, besides the varietal difference, the type of mill used for milling also highly affects the bran percentage and milling recovery .L : W ratio, round grain showed the highest bulk density, and slender grain showed the lowest [The physical characteristics like grain dimensions and weight are of vital interest to those involved in many facets of the rice industry, and these are major criteria to judge rice grain quality. According to Thomas, Wan-Nadiah, and Bhat , physicae lowest –23. Simie lowest , 24. Lone lowest , these pThe chemical characters are said to be the determinants of cooking quality and are positively or negatively correlated with the cooking characteristics. The gelatinisation temperature depicts the cooking time required as it is highly related with cooking time . It alsol/b ratio was obtained in white rice; they stated that breadthwise increase in cooking of rice is an undesirable trait, while high-quality rice varieties are characterized and preferred based on the increase in length. In this study also, the first principal component shows that landraces like Lekali Marsi, Thakali Lahare Marsi, Indrabeli, and Baryang Masino have a high elongation ratio which means they can fetch premium price in the market. A study on rice landraces from Lamjung and Tanahun districts reported wide diversity and huge variability for agromorphological characteristics of those landraces and suggested their utilisation in future breeding programme [Rice being a major staple food in most of the developing countries, cooking quality possesses utmost importance for its economy and marketing. Cooking time is also related to fuel and energy consumption, and longer cooking time may be due to the lesser degree of milling. Cooking time is also related to the amylose content and varied significantly among the varieties . Hettiarrogramme . Thus, tThis study conducted on 30 landraces collected from Tanahun and Lamjung, revealed the variability of landraces based on their physicochemical and cooking characteristics. Landraces were highly significant in physicochemical characteristics as well as in cooking characteristics. However high variation among the landraces was only obtained in the characteristics like gel consistency, gruel solid loss, and water uptake ratio. Some of the landraces showed noble physicochemical and cooking characteristics that can fetch premium prices. Landraces belonging to the Anadi group showed high gel consistency and medium amylose content and landraces like Lekali Marsi, Thakali Lahare Marsi, Indrabeli, Baryang Masino, Jetho Budo, and Chiniya showed lengthwise elongation which gives them economy and market. The information obtained through this study could be used in rice breeding programmes and molecular research for further improvement of rice.


Both groups showed numerous comorbidities, predominantly depression (27.2% in the ADHD group vs. 45% in the non-ADHD group) and substance-use disorders . Patients with ADHD showed significant higher activity (2.07 ± 1.23) than patients without ADHD , whereas for the other core parameters, inattention and impulsivity no differences could be found. Reaction time variability has been discussed as a typical marker for inattention in ADHD. Therefore, we investigated how well ex-Gaussian analysis of response time can differentiate between ADHD and other patients, showing, that it does not help to identify patients with ADHD. Even though patients with ADHD showed significantly higher activity, this parameter differed only poorly between patients (accuracy AUC 65% of an ROC-Curve). We conclude that CPTs do not help to identify patients with ADHD in a specialized outpatient clinic. The usability of this test for differentiating between ADHD and other psychiatric disorders is poor and a sophisticated analysis of reaction time did not decisively increase the test accuracy.The differential diagnosis of attention deficit hyperactivity disorder (ADHD) in adulthood is complicated by comorbid disorders, but also by the overlapping of main symptoms such as inattentiveness, impulsivity, and hyperactivity with other disorders. Neuropsychological tests like continuous performance tests (CPT) try to solve this dilemma by objectively measurable parameters. We investigated in a cohort of n=114 patients presenting to an ADHD outpatient clinic how well a commercially available CPT test (QbTest Attention deficit hyperactivity disorder (ADHD) is the most frequently diagnosed childhood neurodevelopmental disorder defined by the core symptoms inattention, hyperactivity, and impulsivity leading to negative consequences for life and health in patients . SymptomDue to the heterogeneity of symptoms and the high comorbidity with other psychiatric diseases like anxiety disorder, depression, bipolar disorder, borderline personality disorder (BPD), and substance use disorder (SUD) , 11, the®, marketed by Qbtech) is a further developed CPT which is frequently used in clinical practice. Measures of motor activity were added by recording movements of a subject from a reflective marker attached to a headband while performing the CPT tasks  are validated in a normal population, so that test results above the 93rd percentile are suggestive of ADHD , to measure inattention and impulsivity were added to the diagnostic process. Even though CPTs have been frequently used as a diagnostic tool, their use has been criticized due to the lack of specificity and sensitivity for adult ADHD , especiaPT tasks . Head mo of ADHD . There icontrols . But, in ability , 29, 32.Computationally sophisticated analysis of CPT RTs might provide additional information in discriminating among different disorders. Previous studies showed RT variability (RTV) to be consistently increased in people with ADHD and other disorders with attention problems like autism or bipolar disorder , 34. The® which means to what extent the results of the QbTest® can be generalized to real-life patients that undergo diagnostic assessment for adult ADHD in an outpatient clinic. This we test by looking at the receiver-operating curves (accuracy) and subsequent sensitivity and specificity. We were especially interested which of the three components  are the most accurate in diagnosing ADHD. And (2), in addition to standard-analysis data, we wanted to explore whether a more sophisticated data analysis like fitting an ex-Gaussian distribution model to our RT could provide better accuracy.Thus, the aims of our investigation were to (1) examine the ecological validity of the QbTest® were collected at the Department of Psychiatry, Psychosomatic Medicine, and Psychotherapy from a naturalistic sample of 114 patients (Data from structured diagnostic interview for ADHD in adults (DIVA 2.0), Wender-Utah-rating-scale short form (WURS-K) , adult AThe ADHD group is composed of 94 (82.5%) patients who, in the end, met the criteria for an ADHD diagnosis. Among these, 49 (52.1%) patients had no other psychiatric disorder while 45 (47.9%) of the ADHD cases displayed a comorbidity with at least one other psychiatric disorder, five of them (4.4%) had at least two other psychiatric disorders. 26 (22.8%) had ADHD and Depression, 17 (14.9%) ADHD, and SUD, two (1.8%) ADHD and bipolar disorder (BD), eight (7.0%) ADHD and other disorders such as posttraumatic stress disorder, somatization disorders, or obsessive-compulsive disorder. The patients with affective comorbidities all suffered from moderate to severe depressive episodes at the time of examination.The “Non-ADHD-Group,” where adult ADHD was ruled out during the diagnostic process, consists of 20 patients (17.5%). Eight patients (7%) had no psychiatric disorder according to ICD-10 criteria, nine (7.9%) patients suffered from depression, two (1.8%) patients from a SUD, one patient met the criteria for a bipolar disorder (0.9%) and three (2.6%) patients suffered from other psychiatric disorders.Informed written consent was obtained from all subjects. The study followed an observational parallel group design. The study was approved by the Ethics Committee of the University Hospital Frankfurt (No. 425/14).The diagnostic process consisted of an open clinical interview by an experienced clinician to obtain a broad view of the medical history concerning current and former symptoms and associated impairment and functioning, history of substance abuse, psychiatric comorbidities, somatic disorders, and family history of ADHD. To ascertain symptoms in childhood all patients were asked to hand in primary school reports or childhood medical documents.For the main diagnostic assessment, the diagnostic interview for adult ADHD (DIVA 2.0)  was used®  on an additional appointment. A diagnosis of ADHD was established when the DIVA interview was positive, no other diagnoses explained the symptomatology better, and when clinical judgement was in line with the DIVA.Additional information concerning symptoms of ADHD in childhood were obtained from the short form of the Wender Utah Rating Scale (WURS-K) questionnaire. Finally, all patients were tested by the QbTest® is a variant of a CPT. It is based on a one-back task. Apart from the classical assessment of commission and omission errors, the QbTest® additionally measures motor activity with an infrared camera and a reflector attached to a headband during the 20 min of testing. The QbTest® presents raw scores from measures of movement , raw scores of inattention  and impulsivity raw scores . From those raw scores the three cardinal parameters Qb-activity (QbAct), Qb-inattention (QbIna), and Qb-impulsivity (QbImp) are derived by performing a principal component analysis. These parameters are transformed into normally distributed Q-scores implicating information about the difference between the raw score of a patient compared to scores of a gender- and age-controlled group  and σ (sigma), mean and SD of the Gaussian portion, respectively; and τ (tau), mean of the exponential portion. The value of τ captures the tail of the RT skewed distribution and provides better measures of increased RTV in terms of extremely slow but infrequent responses, while µ represents the mean of the normal distributed RT and σ represents the variability of responses both above and below the mean, that is, normal distributions. Larger τ consistently and stably differentiates ADHD from controls across experimental tasks.® and the ex-Gaussian parameters an ROC (receiver operating characteristic) curve and the area under the curve were computed. The clinical ADHD diagnosis was used as the external criterion for the calculation of sensitivity, specificity, and area under the ROC curve (AUC) for activity, impulsivity and inattention and µ, σ, and τ.Data were analyzed with SPSS version 22 . To test for normal distribution of the cardinal Qb parameters the Kolmogorov-Smirnov test was used. The t-test and the Mann-Whitney U-test were used for group comparison. For further analysis a multiple logistic regression analysis of independent variables was carried out. The variables of the ex-Gaussian analyses were extracted using a maximum-likelihood algorithm and implemented using the quantile maximum probability estimator (QMPE) software, an open source ANSI Fortran program for response time distribution estimation . For eva2(1)=2.023 p=0.155). Furthermore, a higher rate of depression was found in the non-ADHD group and a higher percentage of patients with SUD in the ADHD group (2(1)=2.331 p=0.127), Bipolar (X2(1)=0.531 p=0.466), SUD (X2(1)=0.776 p=0.378), other (X2(1)=2.023 p=0.155). In the non-ADHD group were eight subjects without psychiatric disorders, reaching statistical significance in a Chi-square test (X2 (1)=40.438 p < 0.001) The age of the patients in the ADHD group (M=34.7 SD=11.05) did not differ from the age of the non-ADHD group (M=35.8 SD=10.6) in an independent-sample t-test (t(112)=0.399 p=0.69)  and QbImpulsivity (QbImp) showed Gaussian distribution according to the Kolmogorov-Smirnoff test . QbInattention (QbIna) showed no normal distribution .There were no statistically significant differences between patients with ADHD (0.63 ± 1.12) and patients without ADHD for QbImp  and QbIna . Patients with ADHD showed significantly higher QbAct-values (2.07 ± 1.23) than patients without ADHD  , all other independent variables did not  as well as for ADHD and QbInattention ;. In the regression model with QbImp as dependent variable, neither disease , nor age or gender  reached significance, the same applies for QbIna: disease ; age or gender . A detailed list of regression results is found in the A multiple regression was carried out to investigate whether psychiatric disorders, sex or age represented as independent variables significantly influenced parameters measured by the QbTest® items. It is distinct from chance (AUC=0.5), but still performs poor  curve for QbAct, QbImp, and QbIna. The only variable with prognostic value according to the ROC-curve seems to be QBAct, reaching a sensitivity of app. 50% at a specificity of app. 70%  and a cut-off of 2.95 gives a specificity of 92% (sensitivity 28%).Analyzing the discriminative ability of RTV all three ROC-curves show an AUC smaller than 0.6 .® in a naturalistic setting in an outpatient clinic. The lack of CPTs to differentiate between ADHD and other psychiatric disorders was already described by others  with positive QbTest® result. In contrast to the use of the QbTest® as a diagnostic tool, our data shows that it has a very low discriminative power. QbAct has an AUC of 0.65 , and the AUC of QbImp (0.539) and QbIna (0.556) are at chance level. Taken together, these values render this test not clinically useful at least in a secondary care setting.In addition to the comparison of the different groups we were interested in the discriminative power of the QbTestA recent line of research indicates that technically more sophisticated modes of analysis like ex-Gaussian modelling are able to capture ADHD-specific variations in RT during cognitive demanding tasks , 46. How® showed varying results, depending on whether ADHD patients were compared to healthy controls or to clinical controls. Edebol et al. reported a sensitivity of 86% and a specificity of 83% for the QbTest® when comparing ADHD patients to healthy controls, which decreased to a specificity of 41% when comparing ADHD patients to patients with a bipolar II disorder and to a specificity of 36% when comparing ADHD patients to disconfirmed ADHD patients . Therefore, we suggest that patients above much higher thresholds than previously proposed (1.5) are correctly identified as ADHD cases in a naturalistic setting.®  included patients with psychiatric comorbidities and some patients had more than one comorbidity which however reflects clinical reality; our patient sample was representative of other clinical German ADHD population with respect to the prevalence of comorbid conditions , 52. The® . Given t® was for inattention and impulsivity values close to a random ROC curve. This renders the test clinically useless. The hyperactivity score reached a somewhat better AUC accuracy of 65%. This must be compared to other clinical screening tests, for example the PSA-screening for prostate cancer, which has a very high sensitivity (95%) but a very low specificity (20%–30%). The QbTest®'s performance reminds on the test of brain-natriuretic-peptide (BNP) in the diagnosis of heart failure in an emergence setting. While the specificity is high, the accuracy is about 80%. As a consequence of this, clinicians do not base their diagnosis on BNP .The QbTest®was partially funded in the framework of the PRADA study which was funded by Medice Arzneimittel Pütter GmbH.AR has received a research grant from Medice and served on advisory board and/or speaker's bureau from Medice, Shire/Takeda, Janssen, Servier, and neuraxpharm. SK-S has served on advisory board and/or speaker's bureau for Medice Arzneimittel Pütter GmbH and Shire/Takeda. GO has served on advisory board and/or speaker's bureau for Medice Arzneimittel Pütter GmbH.The remaining 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.


Despite many types of research about tools of ADHD have been done over the past decade, lack of a Valid and Reliable tool is observed. The purpose of this study was to investigate the validity and reliability of ADHD questionnaire in epidemiological studies based on confirmatory factor analysis (PLS).The present study is a case-control study that was conducted on 456 male motorcyclists and research tool was ADHD questionnaire in 2013. A total of 30 items from experts and audience community were detected necessary. Content validity was verified using expert opinion and construct validity was verified by factor analysis. The results of the Partial Least Squares -based confirmatory factor analysis was done by SMARTPLS3 software. The Cv-communality index, whose positive values indicate the quality of the model and the Cv-redundancy was calculated.According to expert’s opinion, content validity was confirmed. Model fit indicators  the adequacy of the model and the result structural validity Confirmed. Also, there was also a significant relationship between sub-scales and items. There was a direct, positive and significant relationship between the subscale ASS, CSS and DSS with ADHD. Cronbach s alpha (> 0.7) and combined reliability (> 0.7) confirmed the reliability of the questionnaire.The results showed the validity and reliability of the ADHD questionnaire in epidemiologic studies and various studies for review and generalizability suggested in other communities.ADHD, CFA, Reliability and Validity, Traffic


Exploratory factor analysis of the three measures identified one principal component for EF (EF-PC). Linear regression models were used to analyze the association between each PRS and the EF measures. The role of EF measures in mediating the effects of the PRSs on ADHD symptoms was also analyzed. The result showed the PRSs for MDD, ADHD and BIP were all significantly associated with the EF-PC. For each EF component, the association results were different for the PRSs of the five psychiatric disorders: the PRSs for ADHD and MDD were associated with inhibitory control , the PRS for BIP was associated with working memory (adjusted P = 0.0416), and the PRS for SZ was associated with cognitive flexibility (adjusted P = 0.0335). All three EF measures were significantly correlated with ADHD symptoms. In mediation analyses, the ADHD and MDD PRSs, which were associated with inhibitory control, had significant indirect effects on ADHD symptoms through the mediation of inhibitory control. These findings indicate that the polygenic risks for several psychiatric disorders influence specific executive dysfunction in children with ADHD. The results helped to clarify the relationship between risk genes of each mental disorder and the intermediate cognitive domain, which may further help elucidate the risk genes and motivate efforts to develop EF measures as a diagnostic marker and future treatment target.Many psychiatric disorders are associated with impaired executive functioning (EF). The associated EF component varies by psychiatric disorders, and this variation might be due to genetic liability. We explored the genetic association between five psychiatric disorders and EF in clinically-recruited attention deficit hyperactivity disorder (ADHD) children using polygenic risk score (PRS) methodology. Genome-wide association study (GWAS) summary data for ADHD, major depressive disorder (MDD), schizophrenia (SZ), bipolar disorder (BIP) and autism were used to calculate the PRSs. EF was evaluated by the Stroop test for inhibitory control, the trail-making test for cognitive flexibility, and the digital span test for working memory in a Chinese ADHD cohort ( EF dysfunction is associated with many psychiatric disorders, such as attention deficit hyperactivity disorder (ADHD), major depressive disorder (MDD), bipolar disorder (BIP), autism (ASD), and schizophrenia (SZ)5. EF encompasses multiple processes7. Although most psychiatric disorders are associated with EF dysfunction, different neuropsychiatric disorders showed disorder-specific EF deficits9; for example, the largest effect sizes were observed for response inhibition in individuals with ADHD10, for verbal and nonverbal memory in individuals with BIP11, and for cognitive flexibility in individuals with SZ12. These results suggest that specific EF components might be good markers for specific types of psychopathology. Understanding the role of separate EF components in psychiatric disorders is a critical step in gaining a better understanding of disease psychopathology. Currently, the specificity of these EF component deficits in different psychiatric disorders is not clear13.Executive functioning (EF) is a high-order set of cognitive functions that regulate an individual’s capacity to change and adjust his or her behaviors according to the shifting demands of complex environments14. The association between EF dysfunction and the psychiatric diseases may, in part, reflect pleiotropy, which is the overlap between the genetic liability of two or more traits, perhaps owing to shared causal pathways15. Thus, the genes that influence vulnerability to psychiatric disorders may also influence EF deficits.EF is heritable. Similar EF performance has been observed in family members and twins. The heritability of EF was calculated to be approximately 20 to 40%18. Most of the studies investigated shared genetics among a variety of disorders. Only a few studies have discussed the relationship between genetic risk of disorders and intermediate phenotypes. Shared genetic risks have been reported between SZ20, depression21, ADHD22 and decreased general cognitive ability17, autism and increased cognitive ability23, while BIP had mixed results24. Polygenic risk score (PRS) of ADHD has been associated with components of EF: working memory, vigilance arousal, but not inhibitory control, verbal-numerical reasoning27. The research for the genetic association of other disorders with specific component was limited or inconsistent29. The Brainstorm project identified several correlations between psychiatric disorders and intelligence, cognition and education17, but not specific EF components. Benca et al. examined the PRSs of five psychiatric disorders  with three EF components (mainly involving the shifting component) in a small sample of twins, but failed to find any significant results30.It has been widely acknowledged that many psychiatric disorders share genetic etiology31 but not in adult sample23. So, additional data on this topic is warranted to illuminate the genetic associations among psychiatric disorders and EF.The reported studies showed inconsistent results for the genetic association between polygenic risk score of psychiatric disorders with cognition. Most of the cognition data of previous studies used population-based samples, whose phenotype distribution may differ with clinical-based samples. Sample difference in ages also yielded inconsistent results. For example, polygenic risk score of ADHD was associated with cognition in children samplesBased on the correlation between psychiatric disorder and executive function at phenotype level, our hypothesis Fig.  is that 33. Individuals with major neurological disorders , SZ, pervasive developmental disorder or intellectual disability (IQ < 70) were excluded. Individuals with comorbidities were not necessarily excluded. In this sample, 349 (29.7%) children had oppositional defiant disorder (ODD), 28 (2.4%) had conduct disorder, 79 (6.7%) had a specific phobia, 18 (1.5%) had a social phobia, 19 (1.6%) had generalized anxiety disorder, 13 (1.1%) had MDD, 6 (0.5%) had BIP, and 178 (15.1%) had a tic disorder. IQ was assessed using the third edition of the Chinese version of the Wechsler Intelligence Scale for Children. Most subjects were drug naive. Only 31 (2.6%) patients had used methylphenidate, and 150 (12.8%) had used Chinese herbal medicine. For individuals who had been medicated, the drugs were washed out for at least 1 month before the patient was tested. All these samples were independent from the samples in our previous ADHD GWAS paper34, neither overlapping individuals nor related siblings or cousins. The study was approved by the Institutional Review Board of the Peking University Sixth Hospital. Written informed consent was obtained from the parents of the ADHD probands.The participants who underwent EF tests included 1147 ADHD patients  aged between 6 and 17 years [average (10.1 ± 2.6) years] who were recruited from the Child and Adolescent Psychiatric Outpatient Department of the Peking University Sixth Hospital. All participants met the DSM-IV diagnostic criteria for ADHD. The clinical diagnosis was first made by a senior child and adolescent psychiatrist based on the parent- and teacher-completed ADHD Rating Scale-IV and was then confirmed by a semi-structured interview with the parents and child, using the Chinese version of the Clinical Diagnostic Interview ScaleFrom the 1,147 subjects with EF measures, the numbers of ADHD patients for each EF test are shown in Table 35. At the beginning, thirty stimuli were presented in a 10 × 3 matrix for three cards each sized 21 × 29.7 cm2. In the first session, the research participants were asked to read the names of colors  printed in black ink. In the second session, they were asked to name the colored squares . In the third session, the participants were asked to read the color words printed in different colors. In the fourth session, they were asked to name the colors of the ink. The time required to complete each session was recorded. In this study, we used the word interference time, which equals the time required to complete session 4 minus that for session 2, to assess interference inhibition. Higher score indicates worse performance.The child and adolescent psychiatrist monitored all the tests conducted on patients. The task included four sessions as described in36. In section A, numbers from 1 to 25 were randomly scattered on the page, and the participant was asked to connect these numbers sequentially as quickly as possible. In section B, the participant was asked to connect numbers and letters alternately . When the participant made an error, the investigator pointed out the error immediately before continuing the test. The time to complete section A, TA, indicates motor speed and visuo-perceptual abilities, while the time to complete section B, TB, is sensitive to working memory and cognitive flexibility. The time difference TB−TA, which was highly related to TB (r = 0.94), minimizes visuo-perceptual and working memory demands, providing a relatively pure indicator of executive control. Therefore, the shifting time = TB−TA was the main measure for assessing cognitive flexibility37. Higher score indicates worse cognitive flexibility.The test consisted of two sections (A and B), as described in38. In this test, the child listens to a sequence of numbers and repeats them in reverse order. The length of each sequence of numbers increases as the child responds correctly. Higher score indicates better working memory.The digit span test is a component of the Chinese version of Wechsler Intelligence Scales for Children (C-WISC). In this study, we used the digits backward digit span test to assess the patient’s working memory, as it measures the child’s ability to manipulate verbal information while it is in temporary storage39, we used a loose threshold to remove the samples with inhibitory control or cognitive flexibility below FL−4 × (FU−FL) or above FU + 4 × (FU−FL), in which FL and FU were the lower and upper fourths of the phenotype. We removed 1 and 2 outliers for inhibitory control and cognitive flexibility respectively. From the 1134 subjects, we also collected ADHD symptoms according to the Clinical Diagnostic Interview Scale40. The phenotype distribution plot and related skewness and kurtosis after removing outliers is shown in Fig. The phenotype distribution plot showed working memory was normally distributed, but inhibitory control and cognitive flexibility had some outliers. Considering excessive scores on cognitive measures may indicate the participant did not understand the task or something else happened during testing, using the method described in ref. P < 0.001), which denoted the three EF measures had high correlation and were suitable for EFA. The scree plot showed the first principal component (EF-PC) had eigenvalue >1. Detailed parameters for the EFA model was shown in Fig. For subjects with all three EF measures, we did exploratory factor analysis (EFA) using SPSS 26. EFA method is to identify the underlying relationships between measured variables and get a latent variable to denote common factor of the measured variables. The KMO and Bartlett’s test was significant . First, we removed individuals with per-individual autosomal heterozygosity >5 S.D. larger than the mean, individuals without age or sex information, individuals with a per-individual call rate <95% and individuals with the lower call rate in a pair of individuals with proportion identity by descent (IBD) PI_HAT > 0.185. Next, we removed the SNPs with a per-SNP call rate <95%, a Hardy–Weinberg equilibrium test result with r2 < 0.05 for each pair of SNPs) that were outside the 5 long-range LD regions41 using the EIGENSOFT 4.2 software42. The PCA plot for the first two principal components (PCs) was shown in Fig. 43. Genotype imputation was performed using the pre-phasing/imputation stepwise approach implemented in IMPUTE244 and SHAPEIT45. The imputation reference set consisted of 2186 phased haplotypes from the full 1000 Genomes Project Integrated Phase 3 Release46. Imputed SNPs with a squared correlation between the imputed and true genotypes (rsq) <0.9 or SNPs with minor allele frequency <0.01 were removed. After imputation, 6,064,858 SNPs were used.Principal component analyses (PCA) was conducted using the SNPs with low linkage disequilibrium , sex, IQ and the first two PCs from PCA as covariates. The P-value threshold with the largest Nagelkerke’s r2 (variance explained by the PRS) was considered the best-fit threshold. The P-value for the linear regression was adjusted by using 10,000 label-swapping (randomly shuffle the phenotype) permutations. Adjusted P < 0.05 was considered as significant. To compare the effect of the PRS from different disorders on EF, we did normalization for the PRS under the best P-value threshold from PRSice-2 and further ran regression model using the same covariates in R to get the standardized beta coefficient.The polygenic risk score (PRS) was introduced to summarize the effect of a set of SNPs in a test data set based on the GWAS summary statistics of a discovery dataset. PRSice-2 was used to calculate the results52. Both the mediator model and the outcome model included months (measure of age), IQ, sex and two PCs as covariates. Nonparametric bootstrapping with n = 10,000 was used to estimate the sampling distribution of the indirect effect. If the confidence interval (CI) of the effect didn’t cross zero, the indirect effect was significant. R package “mediation” was further used to for the mediation analysis to double check the result.Since the inhibitory control is the core deficit of ADHD, the hypothesis is the PRS associated with inhibitory control may could affect the ADHD symptoms too. So, two mediation models were analyzed: (1) ADHD PRS associated with inhibitory control as independent variable (X), inhibitory control as mediator (M), ADHD symptoms as outcome (Y); (2) MDD PRS associated with inhibitory control as independent variable (X), inhibitory control as mediator (M), ADHD symptoms as outcome (Y). The standardized PRS was used for this analysis. The analysis was performed using the model 4 in PROCESSr = 0.337); working memory was negatively correlated with inhibitory control (r = −0.267) and cognitive flexibility (r = −0.390). As expected, the correlations of EF-PC with the EF measures were higher . All four EF measures were significantly correlated with ADHD symptoms  and IQ , which denoted the EF measures could significantly affect ADHD symptom and IQ; the correlation between ADHD symptoms and IQ was not significant (r = 0.037) ), ADHD ), and BIP ).As shown in Table P = 0.018, r2 = 0.923%, coefficient = 1.6922 (se = 0.5225)); the PRS for SZ was significantly associated with cognitive flexibility ); the PRS for MDD was significantly associated with inhibitory control ); the PRS for BIP was significantly associated with working memory ); and the association of PRS for ASD with all three EF components did not pass the permutation correction.We further explored the association of each EF component with the genetic risk for psychiatric disorders Fig. . The PRSP = 2.41E−03 for ADHD PRS and P = 2.86E−03 for MDD PRS, and the interaction was not significant ). The ASD PRS was significantly associated with ADHD symptoms ). The PRSs of other disorders were not associated with ADHD symptoms  that differ from the general population, which might facilitate the finding of shared cognition deficit with other psychiatric disorders by using PRS analysis. Another difference was the age of the samples. Most prior studies used adolescent or adult samples, whose cognitive development differs with children’s. The association of genetic risk of some disease with children’s cognition may not be consistent for adults. For example, ADHD related impairment that exist in childhood can disappear or attenuate in late adolescence or adults65, which reduces the power to find associations. We also attempted to analyze the association of PRSs for the Chinese ADHD GWAS data34 with EF. Since the sample size of the Chinese ADHD GWAS is small, there was no significant result for all EF components (data not shown). A larger sample size is important for the PRS definition to address a comprehensive genetic component. As estimated by Martin et. al.66, applying GWAS summary statistics from the European population to other ancestries will reduce prediction accuracy. If using Chinese population GWAS data with the same sample size, the effect size might be bigger.This study has some limitations. The sample sizes for the EF measures were small. Replication in larger samples is needed. Second, the GWAS summary data for the PRS calculations in this study were from European individuals. Cross-ethnic PRS analyses are affected by the different LD structures and allele frequencies in different ethnicitiesIn conclusion, by using polygenic risk score analyses, we found that the polygenic risk for different psychiatric disorders  showed distinct effects on executive function domains. Although all psychiatric disorders had general cognition dysfunction, the specific impairments of the EF components may be different. The results of this study helped to identify the core cognitive impairment that most associated with the genetic risk for each mental disorder, which may further help elucidate the risk genes and motivate efforts to develop EF measures as a diagnostic marker and future treatment target.Supplementary Information


The behavioral evaluation included a parent interview directed at sweetened food/drink habits. The clinical evaluation included physical measurements , and dental examination . Results showed a higher prevalence of abnormal body weight, hip circumference, and BMI, and a higher frequency of caries (84.6%) in the ADHD group. Significant caries differences for primary  and permanent teeth  were recorded. The questionnaire pinpointed interplays between sugar consumption and tooth decay, especially for primary dentition. It can be concluded that the consumption of sweetened foods/drinks among ADHD children may lead to an increased rate of overweight, but may also affect oral health. Limiting sugar consumption might be one of the important elements in prevention programmes against dental caries and overweight/obesity.In recent years, attention has been paid to the co-occurrence of attention deficit hyperactivity disorder (ADHD) and obesity, but results in relation to dental caries outcomes differ. The study was conducted to determine obesity/overweight and dental caries in children suffering from ADHD and to draw comparisons with non-ADHD children. A total of 119 children under 11 years old (8.2 ± 1.2) were enrolled into a cross-sectional study: those with confirmed ADHD ( Attention deficit hyperactivity disorder (ADHD) is one of the most commonly diagnosed neurodevelopmental disorders among school children. Its characteristics are permanent behavioral patterns such as motoric hyperactivity, impulsiveness, and attention deficit . DependiBesides, earlier studies have shown that ADHD is associated with dysfunctional eating patterns such as skipping breakfast, eating in the evening and at night, eating and drinking more during the day, impulsive and emotional eating, preferences for high caloric food, eating more snacks and junk food in comparison to peers, increased focus on eating, and significantly more bulimic behaviors . There aIt can be assumed that some intermediary factors coexist, and one of them is sugar consumption ,21,22,23ADHD may be associated with poor oral hygiene. This connection was analyzed in clinical and behavioral studies including parent interviews by Chandra et al., where dental caries prevalence in the primary dentition was increased in the children suffering from ADHD due to poor oral hygiene and increased consumption of sugary foods . Anothern = 100) and mental health outpatient clinics for children and youth (n = 20). Sixty-six parents of children with unconfirmed ADHD diagnosis responded to the announcement, agreeing to include their child in the investigation. Finally, in sixty-six children the diagnosis was verified independently by both a psychiatrist and clinical psychologist, in accordance with ICD-10 and DSM-V diagnostic criteria [We planned an enrollment of children with ADHD from the Poznan region, living permanently in this part of the country (western part of Poland). The announcement about the recruitment for children with suspected ADHD was forwarded to the family doctors’ outpatient clinics . Parents registered four hundred children for participation in the project; one hundred and fifty children were selected for the control group according to the inclusion criteria . After tThe methodology of this cross-sectional research assumed non-invasive methods of analysis such as the body measurement of the children, dental examination, and questionnaire provided to the children taking part in the project. The protocol of the study followed the standards of Good Clinical Practice (GCP) and was accepted by the local Ethics Committee at the University of Medical Sciences (resolution no. 26/18) . All chiThe clinical evaluation of health status included general body measurements such as height, waist, hip circumference, and body weight. Body height in a standing position was measured with the SECA 216  wall-mounted stadiometer with an accuracy of 0.1 cm. Body weight was recorded in lightweight clothing on a digital scale with an accuracy of 0.1 kg. The waist circumference was determined halfway between the lower edge of the rib arch and the upper iliac crest using metric tape . The hipIn both groups the researcher (A.P.) filled in a questionnaire based on the individual conversation with parents and children; an interview included questions about the history of dental care as well as dietary habits, with an emphasis on the consumption of fermentable carbohydrates in food and beverages. An oral examination was performed with the use of sterile dental diagnostic sets in artificial light in accordance with the aseptic rules performed in the dental office. The sets consisted of a dental mirror, dental probe, sterile pads, and an air-water spray tip. During the examination, rubber gloves and protective masks were used. The methodology of the study included the dental examination of teeth with the criteria of the International Caries Detection and Assessment System (ICDAS II) . For theDental and anthropometric examiners were thoroughly experienced researchers who had led similar subject measurements in several clinical studies ,17,36. TThe parents’ questionnaire was designed as a question/answer sheet and individual filling. The examiner involved in the anthropometric assessment was always the same person which administered the questionnaire.t-test for data that followed a normal distribution and had homogeneity of variances or the Mann–Whitney U-test. The relationship between variables was analyzed with Spearman’s rank correlation coefficient and categorical data were analyzed with the χ2 test. All results were considered significant at p < 0.05. Statistical analyses were performed with STATISTICA 13.0 .The analyzed data are expressed as mean ± standard deviation, median, minimum and maximum values, interquartile range, or percentage, as appropriate. Normality of distribution was tested using the Shapiro–Wilk test, and equality of variances was checked using Levene’s test. Comparison of two unpaired groups was performed using either the unpaired p = 0.008, p = 0.001, p = 0.016) between the sample and control groups. Other parameters like height and waist circumference were not significantly different between groups , as can be seen in Assessment of the present physical development of children was carried out based on body measurements and showed significant differences in parameters such as body weight, hip circumference, and BMI (respectively The use of the ICDAS II index (0–6 degrees) for primary and permanent teeth was performed for all participants. In the ADHD group, the condition of primary dentition was definitely worse in comparison with the control group, with the frequency of caries of 84.6% (41.6% in the control group). ICDAS II showed significant differences for ICDAS codes 0, 1, 2, 5, 6 with unfavorable results for children with ADHD, who compared to healthy children had more primary teeth with advanced caries lesions .p = 0.071, p = 0.01 respectively) who compared to healthy children had more permanent teeth with advanced caries lesions , and supervision from the parents is limited (p < 0.0005).The results of parent interviews indicate that children with ADHD frequently eat sweetened food products containing fermentable carbohydrates in the form of snacks between main meals , as can be seen in In the ADHD group a number of positive answers on sweet snack/drink-related questions differed from the control group. The consumption of carbonated or sweetened beverages was declared to be more frequent in the ADHD group than among the control group , as well as eating without supervision and ICDAS code 3 in primary teeth (p < 0.02). There were no statistical correlations between all declared nutritional habits and ICDAS results in permanent teeth. Body measurement calculations were not significantly related to sweetened food/drink consumption (p > 0.05). Nevertheless, it is worth noting that the relationship between waist circumference and the drinking of carbonated sweet drinks was nearly statistically significant in the ADHD group (p = 0.086). There was also an important negative relationship revealed between healthy permanent teeth (ICDAS 0 score) and BMI .In the ADHD group, statistical analysis (Mann–Whitney U-Test) evidenced a positive relationship between declared sweetened snacks consumption and ICDAS 1, 3 scores in primary teeth . The present study was also limited by its cross-sectional design and general measures of nutritional status. Laboratory instruments for body composition measurements are more accurate, but difficulties  limit their application. All mentioned differences do not, however, undermine the representativeness of the groups we examined.Our main conclusion is that the outcomes of the present survey support the hypothesis that ADHD might be related to excessive weight gain. Unhealthy dietary habits related to ADHD may lead to an increased rate of overweight in this group of patients, but may also affect oral health. Children with diagnosed ADHD may present a higher risk of dental caries in primary and permanent dentition than the healthy population. It can be assumed that tooth decay is associated with the consumption of sugar-sweetened drinks, and that this is one of the essential factors for the intensive development of caries disease in children with ADHD.


Background: Deficient decision-making (DM) in attention deficit/hyperactivity disorder (ADHD) is marked by altered reward sensitivity, higher risk taking, and aberrant reinforcement learning. Previous meta-analysis aggregate findings for the ADHD combined presentation (ADHD-C) mostly, while the ADHD predominantly inattentive presentation (ADHD-I) and the predominantly hyperactive/impulsive presentation (ADHD-H) were not disentangled. The objectives of the current meta-analysis were to aggregate findings from DM for each presentation separately.Methods: A comprehensive literature search of the PubMed (Medline) and Web of Science Database took place using the keywords “ADHD,” “attention-deficit/hyperactivity disorder,” “decision-making,” “risk-taking,” “reinforcement learning,” and “risky.” Random-effects models based on correlational effect-sizes were conducted. Heterogeneity analysis and sensitivity/outlier analysis were performed, and publication biases were assessed with funnel-plots and the egger intercept.Results: Of 1,240 candidate articles, seven fulfilled criteria for analysis of ADHD-C (N = 193), seven for ADHD-I (N = 256), and eight for ADHD-H (N = 231). Moderate effect-size were found for ADHD-C . Small effect-sizes were found for ADHD-I  and for ADHD-H . Heterogeneity was moderate for ADHD-H. Sensitivity analyses show robustness of the analysis, and no outliers were detected. No publication bias was evident.Conclusion: This is the first study that uses a meta-analytic approach to investigate the relationship between the different presentations of ADHD separately. These findings provide first evidence of lesser pronounced impairment in DM for ADHD-I and ADHD-I compared to ADHD-C. While the exact factors remain elusive, the current study can be considered as a starting point to reveal the relationship of ADHD presentations and DM more detailed. ADHD is a neurodevelopmental disorder associated with inappropriate levels of inattention and/or hyperactivity/impulsivity . SubtypeDecision-making (DM) can be viewed as choosing one specific action among others after evaluating the potential outcomes, preferences, and context. This encompasses scenarios ranging from simple perceptual decisions to complex learned situations  as well as risky DM, all of which have been studied empirically , 9. To oThis study followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)  to achieStudies were included if they met the following criteria: (1) a publication of the research paper in a peer-reviewed journal, (2) standardized ADHD-diagnostic/assessment procedures  according to DSM IV/V [see , 23 for The recorded variables from each study were: sample size, mean age of the participants, type of control group, kind of DM-task, and metric for calculation of ES. Data were extracted from each study by one of the authors (MS) and checked by another author (SL) to minimize data selection errors.F-or t-values were provided, correlation coefficients were obtained according to the following formula , eight studies for ADHD-H presentation , and seven studies for ADHD-I presentation  . No significant heterogeneity is present . Visual inspection of the funnel-plots and the egger intercept  suggesting the absence of a publication bias . No outlier was identified.Moderate ES for ADHD-C presentation was found: bias see . Influenr = 0.1 . The forest plot with the within-study ES and aggregated ES is presented in p = 0.003, I2 = 61.02%, df = 7). Since we included pediatric and adult studies in the analysis, we performed a moderator analysis with age, suggesting that age has no influence on the heterogeneity, Q(df = 1)=1.24, p = 0.26. Visual inspection of the funnel-plots and the egger intercept  suggesting the absence of a publication bias . Influence analysis, that is, leave-one out analysis, suggests general robustness of the result. Outlier analysis could not detect any outlier in the current analysis.The main ES for the ADHD-H presentation was r = 0.09  was found . No publication bias is evident as visual inspection of the funnel-plots (see p = 0.9) suggest. Moderator with age as regressor show no moderate influence, Q(df = 1) = 0.03, p = 0.85. Influence analysis showed general robustness of the results, and no outlier was detected.For ADHD-I presentation an ES of lots see  and Egger = 0.34), small ES for ADHD-H (r = 0.1), and ADHD-I (r = 0.09). Heterogeneity was moderate in ADHD-H and low for ADHD-I and ADHD-C. In all analyses, no outlier studies were evident. The ES for ADHD-C were comparable to other meta-analyses, which also report medium ES, for example, d = 0.43  and probabilistic-game task (r = 0.09), it was also associated with highest ES for the make-a-match task (r = 0.41). These differences could be due to diagnostical differences, that is, used instruments and experience in rating ADHD-symptoms across studies . While some patients do show intact neuropsychological functioning in some aspects of cognition, others do not appear to have any cognitive deficits in commonly assessed domains , 43. CogSince the majority of published studies include mostly the combined type or fail to differentiate between the different ADHD presentations, the number of included studies in the current analysis and the total sample size is rather small. In future studies, researchers should include data relating to the different ADHD presentations and provide metrics on the association of ADHD presentations and DM. Another limitation is the absence to control for diagnostical instruments used to assess ADHD symptoms. There may be certain variability in the diagnostical validity of the symptoms due to the use of different diagnostical tools and also the experience of the staff to rate symptoms for interview-based assessments. Unfortunately, due to the limited number of included studies, we could not assess the impact of the used diagnostical instruments. Further, ADHD subtypes are not discrete entities that are constant over time. When followed over time, patients may switch from one subtype to another, for example, from ADHD-C to ADHD-I , 46. ThiThis is the first study to use a meta-analytic approach to investigate the relationship of ADHD-C, ADHD-I, and ADHD-H presentations in DM separately. While meta-analytic evidence in the literature shows deficient DM in ADHD-C presentations, it appears less clear in comparison to ADHD-I and ADHD-H presentations. The current meta-analysis provides rather limited evidence, but cautiously interpreted, it might be that patients with ADHD-I and ADHD-H presentations show less impairment in DM skills. However, the interplay between the triad of ADHD-presentation-specific symptoms, DM skills and neuropsychological functions are complex and not yet fully understood. The current study is considered as a starting point to clarify the relationship of ADHD presentations and DM. Since the current evidence is rather limited, future work is needed to support our findings and clarify the interplay.marcel.schulze@ukbonn.de.The datasets analyzed in this article are not publicly available. Requests to access the datasets should be directed to MS and SL: literature search, figures, data analysis, data interpretation, and writing. DC and AP: data interpretation, writing, and supervision. All authors contributed to the article and approved the submitted version.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.


Significance: Attention-deficit/hyperactivity disorder (ADHD) is the most common psychological disease in childhood. Currently, widely used neuroimaging techniques require complete body confinement and motionlessness and thus are extremely hard for brain scanning of ADHD children.Aim: We present resting-state functional near-infrared spectroscopy (fNIRS) as an imaging technique to record spontaneous brain activity in children with ADHD.Approach: The brain functional connectivity was calculated, and the graph theoretical analysis was further applied to investigate alterations in the global and regional properties of the brain network in the patients. In addition, the relationship between brain network features and core symptoms was examined.Results: ADHD patients exhibited significant decreases in both functional connectivity and global network efficiency. Meanwhile, the nodal efficiency in children with ADHD was also found to be altered, e.g., increase in the visual and dorsal attention networks and decrease in somatomotor and default mode networks, compared to the healthy controls. More importantly, the disrupted functional connectivity and nodal efficiency significantly correlated with dimensional ADHD scores.Conclusions: We clearly demonstrate the feasibility and potential of fNIRS-based connectome technique in ADHD or other neurological diseases in the future. Typical symptoms are age-inappropriate levels of inattention, hyperactivity, and impulsivity, which often lead them to dysfunctions in academic performance and social skills.––,,–,,,,–Recent neuroimaging studies have demonstrated the disruption of functional or structural brain network organization in children with ADHD.Functional near-infrared spectroscopy (fNIRS) is an optics-based brain imaging tool. It shows the advantages of high motion tolerance, few body constraints, and high portability.,––Resting state is a natural imaging paradigm, and the resting-state fNIRS (rs-fNIRS) imaging has advantages over task-associated fNIRS.,However, no rs-fNIRS study has been applied to explore the alterations in brain topological organization in ADHD children. To bridge this gap, we conducted an rs-fNIRS study with 30 ADHD patients and 30 healthy controls (HCs). As one of the neurodevelopment disorders, there is growing evidence from fMRI studies supporting both categorical and dimensional aspects of ADHD.22.1Sixty participants were recruited for this study, which comprised 30 children with ADHD  and 30 sex-, age-, and education-matched HCs. The children with ADHD were recruited from Peking University Sixth Hospital, Beijing, China, and HCs were enrolled from a primary school in the local community. For the children with ADHD, the inclusion criteria were as follows: (1) a full-scale intelligence quotient ,The ADHD and comorbidities were diagnosed according to the DSM-IV criteria based on a semistructured interview using the clinical diagnostic interview scaleThis study was approved by the Ethics and Committee of Peking University Sixth Hospital/Institute of Mental Health. All subjects were treated according to the Declaration of Helsinki. Written informed consent was obtained from parents of the children. Meanwhile, the children aged above 10 years old also provided written informed consent by themselves. All the children provided oral consent before the experiment and were free to withdraw from the experiment at any time for any reason without prejudice to future care.2.2fNIRS data were collected using a multichannel continuous wave near-infrared optical imaging system  with a sampling rate of 17 Hz. This system contains 24 light sources and 28 detectors. The optode arrays generated 80 different measurement channels with a fixed 3-cm interoptode distance, which covered primary regions of the whole head, e.g., frontal, temporal, parietal, and visual cortexes . The opt,,,We used an in-house FC-NIRS package2.3,For each participant, functional connectivity was calculated by conducting Pearson correlation analyses between time series of every pair of nodes, where the nodes were the measurement channels. This procedure generated an 2.4A graph theory method was used to characterize the topological organization of the brain functional networks in the ADHD and HC groups. Network measures were calculated using our FC-NIRS package.The global efficiency In addition, for a given node 2.5,–Two-sample 2.6To test the associations between altered brain functional connectivity/network features and core symptoms  in ADHD, Pearson correlation analyses were performed in the ADHD group with significance threshold of 33.1The 3.2HC group . FurtherHC group .3.3For global network properties, the global efficiency in children with ADHD significantly decreased as compared to that in the HC group . HoweverFor regional nodal characteristic, the ADHD group exhibited both decreased and increased nodal efficiency in some primary brain regions  (p<0.05)3.4For nodal efficiency, we identified one node in the right somatomotor network, as indicated by a black arrow in 4,The categorical–dimensional hybrid model of ADHD has provided insights to the pathophysiological mechanisms of this disorder in recent years.–,,This study showed that children with ADHD, compared to the HCs, exhibited decreased homotopic, intrahemispheric, and heterotopic functional connectivity . Specifically, the decreased homotopic connectivity was primarily located in the prefrontal cortices and bilateral posterior cortices involving dorsal attention networks and visual networks, which are, respectively, related to executive,,We also found decreased global efficiency in the ADHD group, which are consistent with the previous investigations from fMRI-derived network analysis in the patient group.The correlation results further confirmed the relationship between the functional connectivity network and ADHD symptoms. Specifically, decreased connectivity between the frontoparietal network and visual network was associated with increased hyperactive/impulsive and total scores in ADHD. This provides further evidence that the insufficient coordination between frontal cortex and visual networks may underlie the hyperactive/impulsive symptom in ADHD. In addition, the decreased nodal efficiencies in the right somatomotor network showed a negative correlation with the hyperactive/impulsive and total scores, which suggests that children with hyperactive/impulsive symptoms tended to have reduced information processing efficiency in the brain regions, i.e., somatomotor regions.,Despite the intriguing findings in our study, several issues need to be addressed. First, the approach adopted in this study should be applied to a larger sample to validate its robustness. Second, only the boys with ADHD were enrolled in this study, which limited the examination of the influence from gender differences on the current findings.It is noteworthy that the diagnosis of ADHD still heavily relies on the clinical information provided by parents and teachers and the ratings of the ADHD presentations.5In summary, we validated that the rs-fNIRS is a promising technique to characterize the topological network properties associated with ADHD. This study not only provides potential biomarkers for the diagnosis of ADHD but also has potential application for the investigation of neural basis underlying development, aging, and neurological diseases.