Follow-up analysis revealed that most eye-tracking and CPT indicators improved significantly after taking an ADHD medication. The use of eye movement scales could be used to differentiate children with ADHD, with the possibility that integrating eye movement scales and CPTs could improve diagnostic precision.Attention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder of childhood. Although it requires timely detection and intervention, existing continuous performance tests (CPTs) have limited efficacy. Research suggests that eye movement could offer important diagnostic information for ADHD. This study aimed to compare the performance of eye-tracking with that of CPTs, both alone and in combination, and to evaluate the effect of medication on eye movement and CPT outcomes. We recruited participants into an ADHD group and a healthy control group between July 2021 and March 2022 from among children aged 6–10 years (n = 30 per group). The integration of eye-tracking with CPTs produced higher values for the area under the receiver operating characteristic  compared with using CPTs only  for identifying patients with ADHD. The use of eye-tracking alone showed higher performance compare with the use of CPTs alone (AUC of EYE: 0.856, AUC of CPT: 0.769,  It has a prevalence of about 5%, with symptoms persisting to adulthood in 40–60% of affected children3. In particular, the cognitive impairment associated with ADHD can have a life-long impact4, affecting academic achievement, occupational attainment, and quality of life5.Attention-deficit/hyperactivity disorder (ADHD) is a chronic and debilitating neurodevelopmental disorder characterised by inattention, hyperactivity, and impulsivity6. Among these, cognitive Event-Related Potentials (ERPs) in the electroencephalogram (EEG) showed robust neurophysiological differences between individuals with ADHD and without ADHD7. Differences in brain structural and functional measures regarding cognitive functions have been reported in patients with ADHD9. However, despite promising results, the use of brain scanning such as brain MRI or ERPs in clinical practice is limited by its high cost and the need for technical expertise10. By contrast, continuous performance tests (CPTs) are relatively inexpensive and easy to use, which has resulted in their widespread use for the assessment of cognitive function in suspected ADHD11. However, the poor sensitivity and specificity of CPTs limit their clinical utility12.Researchers have used various tests to evaluate cognitive function for the diagnosis of ADHD13. For example, Astar et al. showed that the integration of eye-tracking with CPTs enhanced diagnostic precision and clarified the cognitive domain in patients with ADHD14. Although such research has validated this approach, it has not included either children or the effect of medication. Moreover, eye movement itself could provide indirect information about learning, memory, and attention15. Therefore, research must also compare the performance of eye-tracking with that of CPTs.Given the issues with CPTs, researchers have attempted to integrate them with other psychophysiological measures. In this regard, eye movement represents a biomarker that could offer useful information about ADHD-related cognitionThis study aimed to fill the research gaps related to the use of eye-tracking and CPTs in children. First, we compared the performance of an eye tracker with that of CPTs. Second, we evaluated the performance of an eye tracker integrated with CPTs. Third, we evaluated the effect of medication on eye movement and CPTs.This study took place between July 2021 and March 2022 at the Ajou University Hospital in South Korea. Patients with ADHD and healthy controls (aged 6–10 years) were recruited through advertisements placed on bulletin boards around the hospital. The study received institutional review board approval, and all participants and caregivers provided written informed consent (no. AJIRB-MED-SUR-21-240).We included patients in the ADHD group after a psychiatrist confirmed the diagnosis according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). Healthy controls were evaluated by psychiatrists for psychiatric symptoms and medical history, including ADHD. Those with a history of eye disease, autism spectrum disorder, intellectual disability, major depressive disorder, bipolar disorder, schizophrenia, Tourette syndrome, obsessive–compulsive disorder, post-traumatic stress disorder, neurological disease, or severe medical problems were excluded.Patients with ADHD were also followed to compare symptoms by medication usage, including stimulants (methylphenidate) and non-stimulants (atomoxetine and clonidine). Among children who already used medication, primary testing took place after stopping the drug for at least one week, whereas all other children underwent primary testing before they started the drug. Follow-up testing took place 1 month after starting or re-starting ADHD medications.Participants and caregivers completed a demographic/health questionnaire and Korean versions of the ADHD Rating Scale (ARS) and Child Behavior Checklist (CBCL). To minimise external distractions, participants were then moved to a separate room with a computer, where they underwent calibration for the eye tracker and comprehensive attention testing (CAT) while their eye movements were tracked. Given the potential effect of medication on ADHD symptoms, together with the possibility of fatigue, all testing took place in the morning or early afternoon. We repeated the CAT once during follow-up after patients had received medical treatment for ADHD.16. Symptoms are rated on 4-point Likert-type scales, ranging from 0 (never) to 3 (very often). The Korean version of ARS has internal consistency ranging from 0.77 to 0.89 and test–retest reliability of 0.8517.Attention was evaluated with the ARS, an 18-item scale developed by DuPaul (1991) for use with children18, and the Korean version of the CBCL was standardised in 199719.Psychopathology was assessed with the CBCL, which contains 120 behavioural items that parents rate on 3-point Likert-type scales from zero to two (Not True to Very True/Often True). Items are summed to yield a syndrome scale score across three dimensions  and six DSM-oriented scale scores. The syndrome and DSM-oriented scales have been validated20. The CAT is composed of six subtests: the simple selective attention , continuous inhibition, interference selection, divided attention, and working memory tests. However, we excluded the auditory test for simple selective attention to allow comparison with the eye-tracking test, together with the divided attention and working memory tests that are only used from age 9 years. The CAT was performed using a computer, with participant understanding of text and voice guides presented at the start of each subtest checked by trained researchers.Computerized CAT is the type of the computer-based CPT, and has been developed for ages 4–49Overall, the amended CAT took approximately 25 min to complete, including the assessments of selective visual attention , continuous inhibition , and interference selection . For the selective attention test, participants press the space bar button quickly when they see a circle figure at the center of a monitor. For the continuous inhibition test, they press the space bar when they see any figure except an X at the center of monitor. For the interference selection test, participants are instructed to pay attention to a central target while ignoring interference stimuli. Each subtest has five indicators: commission errors (CE), for the number of wrong responses; omission errors (OE), for the number of missed responses; mean reaction time (RT mean), for the average response time to the stimuli; standard deviation of reaction time (RT SD), for response time variability; and sensitivity coefficient (d′), for how successfully the target stimuli are differentiated from the non-target stimuli. Because only four indicators were calculated in eye-tracking, we excluded d′ from the comparison.https://visual.camp/demo-archive/), eye movements were recorded at a 30 Hz sampling rate with an approximate accuracy of 1.7° . Calibration to each participant in SeeSo used a five-point procedure. Online Supplementary Fig. Stimuli were presented on a Samsung Notebook (NT551XCJF-COM) with a 15.6-inch display, a screen resolution of 1920 × 1080 pixels, and an eye-to-screen viewing distance of approximately 50 cm. The eye-tracking apparatus (Happymind Inc. CAT test) included a host PC that tracked and computed the participant’s gaze position, as well as a display PC to present the stimuli. After downloading and running the eye-tracking programme . As shown in online Supplementary Fig. 21. A recent study of eye-tracking among patients with ADHD showed that the ratio of center gaze duration between patients with ADHD (80.48%) and a healthy control group (88.35%) differed significantly according to Welch’s unequal variance t-test14. Therefore, allowing for a 5% probability of a type 1 error and a power of 80%, the minimum sample size was 29 participants in each group. Considering drop out, we decided a total sample size of 30 in each group.NCSS PASS (version 14) was used for the sample size calculationt-tests and chi-square analyses for parametric and non-parametric variables, respectively. Welch’s unequal variance t-test was used when data failed to meet the assumption of variance homogeneity. Group differences in gaze were visualised using the gaze coordinates in subtests.We compared baseline characteristics, ARS, CBCL, CAT indicators, and eye-tracking indicators between the ADHD group before medications and the control group by independent-sample 22, which we evaluated further based on a variance inflation factor (VIF) of < 523. Logistic regression then assessed the ability of the CAT indicators, eye-tracking indicators, or both indicators combined to identify group membership (control or ADHD). Sensitivity, specificity, and area under the curve (AUC) were compared against patients with ADHD by receiver operator characteristic (ROC) curve analysis. The method reported by DeLong et al. was used to compare AUC values24.Pearson’s correlation between CAT and eye-tracking indicators was evaluated before performing the regression analyses. Using the correlation matrix, we considered that indicators with r-values of > 0.7 had multicollinearityIn the secondary analysis, we used paired t-tests to assess the change in ARS, CBCL, and indicators (CAT and eye-tracking) within the medication group from before to after taking medication. Differences in gaze from before to after taking medication were visualised by using gaze coordinates according to subtests.p < 0.05), and all analyses were performed using R (version 4.1.0) and its open-source statistical packages.Statistical significance was evaluated at the 5% significance level , and All participants and caregivers provided written informed consent. All the experiment protocol for involving human data was in accordance with the guidelines of Declaration of Helsinki.In total, we included 30 children with a diagnosis of ADHD and 39 healthy controls, before excluding 9 participants from the control group Fig. . Among pp = 0.002 in maternal education, p < 0.001 in paternal education, respectively).The ADHD and control groups did not differ significantly by age, sex, height, weight, or main caregiver Table . Howeverp < 0.001) and both the inattentive (p < 0.001) and hyperactivity (p < 0.001) domains. Patients with ADHD also had significantly higher scores on the syndrome and DSM-5 domains (except for somatic problems) of the CBCL. Concerning the CAT indicators, patients with ADHD performed worse than healthy controls in simple selective attention OE (p = 0.005), simple selective attention CE (p = 0.022), simple selective attention RT SD (p < 0.001), continuous inhibition RT mean (p = 0.048), continuous inhibition RT SD (p = 0.010), and interference selection RT SD (p = 0.043). Although not included in the logistic regression, there were also differences in dʹ (online Supplementary Table p = 0.006) and continuous inhibition dʹ (p = 0.012).Table p < 0.001; time p = 0.002), continuous inhibition , and interference selection . The ADHD group also showed less central gaze in simple selective attention (p < 0.001), continuous inhibition (p < 0.001), and interference selection (p = 0.001). Moreover, patients with ADHD had increased gaze variability in the interference selection test (p = 0.028).Significant group differences existed for most eye-tracking indicators. Compared with controls, the ADHD group showed less fixation in simple selective attention  had VIF values of < 5. Among the eye-tracking indicators, eight were excluded due to multicollinearity and the four remaining indicators  had VIF values of < 5. These results are summarised in online Supplementary Table p = 0.029) and between the CAT indicators alone and both indicator sets combined (p < 0.001).Logistic regression using the CAT indicators showed a high specificity 0.931) and AUC (0.769), but a low sensitivity (0.533) (Table 1 and AUCp = 0.019) and hyperactivity (p = 0.025) scores decreased significantly within the medication group from before to after taking medication. Significant improvements were from before to after taking medication for all CAT indicators  and all eye-tracking indicators (except simple selective attention gaze SD and continuous inhibition gaze SD). However, we observed no significant change in CBCL scores within the medication group from before to after taking medication.Treatment with ADHD medications was associated with an overall improvement in the ARS and both the CAT and eye-tracking indicators Table . The ARSSimilar to the results of the primary analysis, we also found differences in the simple selective attention test (gaze and fixation time) within the medication group from before to after taking medication. Other subtests showed similar patterns Fig.  and S5, Integrating eye-tracking with CPTs improved task performance at identifying ADHD compared with the use of CPTs alone. The use of eye-tracking alone also showed higher performance compare with the use of CPTs alone. Moreover, most eye-tracking indicators  differed significantly between the ADHD and control groups. Follow-up analysis of the effect of medication revealed that most eye-tracking and CPT indicators improved significantly with treatment.14. For example, Elbaum et al. reported that eye-tracking had performance comparable to that of CPTs25, consistent with our results that the AUCs for eye-tracking was significantly higher than that of CPTs. In addition, while CPTs had a low sensitivity and a high false negative rate (47%), eye-tracking had a relatively high sensitivity and a low false negative rate (26%).Despite the limited research on eye-tracking applications in patients with ADHD, existing studies have shown the potential for them to discriminate between patients with ADHD and healthy controls14. When estimating central gaze duration with and without a distractor, we also showed that patients with ADHD had a lower CR than healthy controls. Estimating central gaze in this way could show the distractibility that underpins higher-order deficits in ADHD26. Another study revealed that evaluating eye movement distractibility could be used as a diagnostic tool for ADHD27. We used different indexes to estimate distractibility  and show that patients with ADHD often had lower fixation ratios and times. Elsewhere, Caldani et al. also demonstrated poor fixation in youths with ADHD compared with healthy controls28. Moreover, our finding of increased gaze variability in patients with ADHD is consistent with previous research showing that ADHD was associated with difficulties in suppressing exploratory saccades compared with healthy controls29. These findings are in line with the concept that children with ADHD exhibit poor inhibitory control. However, our approach produced superior differentiating performance  than the previous study that used central gaze duration only 14, possibly due the inclusion of additional distractibility variables. Overall, our findings confirmed that using eye movement indicators, alone or in combination, have the potential to improve ADHD case identification.Furthermore, our findings are consistent with those of a study with a similar methodology that demonstrated improved discriminatory performance after the integration of eye-trackingAnalyzing the effect of medication during the follow-up among patients with ADHD produced less dramatic results than the comparisons with healthy controls. However, we did observe a significant difference in most eye-tracking variables by the presence of drug treatment. These results suggest that eye-tracking may be suitable for both diagnosing ADHD and identifying treatment response to medications.15. However, important limitations warrant further consideration.A distinct advantage of our methods is the simplicity of the technical setup, which only required the downloading of eye-tracking software to a laptop computer. This could improve the translation of our findings to clinical practice and other settings. Eye-tracking systems could also be used in brief sessions to assess different tasks and treatment effects31, other research has considered ages 6 to 10 years as the same age group32. Complementing this, we found no age differences between the ADHD and control groups. Second, this study used the relatively small sample size. However, our study included an appropriate sample size considering the previous study. Third, we did not evaluate other methods that can be integrated with eye-tracking. For example, Stolicyn et al. combined measures of eye and face movement during cognitive performance to predict depression symptoms33, whereas Fernandez-Ruiz et al. performed the antisaccade task during an fMRI study34. We focused on integrating eye-tracking with CPT because these tests are easy to implement in practice. Fourth, we did not evaluate the difference in effect according to the drug type. Atomoxetine can have an onset of action within 1–2 weeks of starting treatment, while methylphenidate starts working within hours35. However, of the 30 patients with ADHD, 26 were on methylphenidate and only 4 were on atomoxetine, so we could not analyze them separately. In addition, since the drug-taking patterns of ADHD patients in this study were similar to those of ADHD patients in the Korean sample data36, it can be seen as a reflection of actual patients.First, we included participants aged 6–10 years old. Although research has indicated that ADHD symptoms differed significantly between these agesIn conclusion, the present study indicates that eye-tracking during CPTs can improve the identification and classification of children with ADHD by uncovering reductions in gaze fixation and central gaze, together with increases in gaze variability. These findings suggest that eye-tracking could be a feasible option for screening and testing patients with ADHD. Given this potential, prospective research should now include larger samples with equal sex distributions to compare different tasks.Supplementary Information.


Autism spectrum condition and attention-deficit/hyperactivity disorder (ADHD) are associated with a range of physical health conditions. The aim of this study was to examine the etiological components contributing to co-occurring physical health conditions in autism and ADHD./ADHD phenotypes were examined using generalized estimating equations. Bivariate twin models were applied to estimate the extent to which genetic and environmental risk factors accounted for physical health comorbidities.In this nationwide Child and Adolescent Twin Study in Sweden, we analyzed data from 10,347 twin pairs aged 9 and 12. Clinical diagnoses of autism, ADHD, and physical health conditions were identified through the Swedish National Patient Register. Subclinical phenotypes of autism and ADHD were defined by symptom thresholds on a standardized parent-interview, the Autism–Tics, ADHD, and Other Comorbidities inventory. Associations between physical health conditions and autismra) with epilepsy was 0.50 for clinical autism and 0.35 for subclinical autism. In addition, a modest genetic correlation was estimated between clinical autism and constipation (ra = 0.31), functional diarrhea (ra = 0.27) as well as mixed gastrointestinal disorders (ra = 0.30). Genetic effects contributed 0.86 for mixed gastrointestinal disorders in clinical ADHD (ra = 0.21). Finally, subclinical ADHD shared genetic risk factors with epilepsy, constipation, and mixed gastrointestinal disorders .Similar patterns of association with physical health conditions were found in clinical and subclinical autism/ADHD, with odds ratios ranging from 1.31 for asthma in subclinical ADHD to 8.03 for epilepsy in clinical autism. The estimated genetic correlation (Importantly, since medical records from primary care were not included in the registry data used, we probably identified only more severe rather than the full range of physical health conditions. Furthermore, it needs to be considered that the higher prevalence of physical health conditions among autistic children and children with ADHD could be associated with the increased number of medical visits.Shared genetic effects contribute significantly to autism and ADHD phenotypes with the co-occurring physical health conditions across different organ systems, including epilepsy and gastrointestinal disorders. The shared genetic liability with co-occurring physical health conditions was present across different levels of autism and ADHD symptom severity.The online version contains supplementary material available at 10.1186/s13229-023-00548-3. Autism spectrum condition (ASC) and attention-deficit/hyperactivity disorder (ADHD) are conditions of altered neurodevelopment caused by an interplay of polygenic predisposition and compounding environmental factors . AutistiWhile shared genetic susceptibility is postulated to partly account for the overlap between physical health conditions and autism/ADHD based on the identification of somatic pleiotropic genes , the magTo unravel the genetic and environmental contributions to phenotypic correlations between two conditions/disorders with complex etiologies , twin studies are particularly valuable and have been applied on the association between neurodevelopmental and physical health conditions . While gTherefore, the objective of this study was to provide a comprehensive picture of common co-occurring physical health conditions in autistic children and children with ADHD at clinical and subclinical levels. We used information on clinical diagnoses and symptom severity of autism/ADHD from a population-based twin cohort to estimate the association of autism/ADHD phenotypes with physical health conditions. Moreover, we applied quantitative genetic modeling to estimate the degree to which co-occurring physical health conditions in clinical and subclinical autism/ADHD are accounted for by genetic and environmental factors. In this article, we adopted “identity-first” language  rather than “person-first” language  to avoid ableist language which could reflect discrimination and marginalization .We used data collected from participants in the population-based Child and Adolescent Twin Study in Sweden (CATSS) . This onCo-occurring physical health conditions , 3 were https://www.gu.se/en/gnc/gncs-resources/screening-questionnaires/a-tac-screening-questionnaire  and ADHD modules (19 items) of the Autism–Tics, ADHD, and Other Comorbidities inventory (A-TAC), an open access instrument with full-versions in Swedish and English available on P < 0.05. Bonferroni correction was applied for multiple comparisons.MZ and same-sex DZ twins were included in the analyses for the potential differences in variance components across sex. We did not model the effects of sex in our analysis since no sex-specific genetic influences on behavioral traits of autism/ADHD have been reported in the literature , 34. ConStructural equation modeling was used to estimate the relative genetic and environmental contributions to variation in liability to the clinical  phenotypes of a disorder, with the assumption that a continuous distribution of liability underlies such disorders. Liability variance was divided into three latent components: additive genetic (A), non-additive genetic (D) or shared environments (C), and nonshared environment (E). Only C or D can be estimated in a model, as they confound one another in the classical twin design. These components are estimated based on comparing the correlations between MZ twins who share all their segregating DNA and DZ twins who share on average 50% of their segregating genes. Principles of twin design are provided in detail elsewhere .Univariate analyses were used to provide variance component estimates for physical health conditions and to test assumptions of the twin design. We tested only ACE but not ADE models to increase power. Thus, the proportion of genetic effects contributing to the variance should be interpreted as broad-sense heritability. Further nested models (AE and E models) were tested and compared to ACE models using the likelihood-ratio test. The correlations of one twin’s autism or ADHD phenotypes with their co-twin’s physical health condition (cross-twin cross-trait correlations) in MZ and DZ pairs were calculated. To study whether genetic and environmental risk factors for autism and ADHD phenotypes are associated with the co-occurring physical health conditions, we fitted the bivariate Cholesky decomposition to the categorical phenotype variables, which are presented here as the mathematically equivalent correlated factors solution. The genetic correlation estimates are correlation coefficients indicating the degree to which the genetic influences on two phenotypes correlate with one another. Bivariate heritability estimates, the proportion of phenotypic correlations explained by shared genetics, were calculated. To rule out that genetic correlations between subclinical autism/ADHD and co-occurring physical health conditions are driven by clinical autism/ADHD, sensitivity analyses were conducted by excluding clinical cases from subclinical groups. All twin models were conducted in OpenMx package for R .The prevalence of autism, ADHD, and physical health conditions in our sample across and by sex/zygosity is presented in Table h2) ranging from 0.41 for migraine to 0.61 for epilepsy, with no indication of shared environmental effects  between all the physical health conditions and autism/ADHD for both clinical and subclinical phenotypes, ranging from 0.09 for asthma and subclinical ADHD to 0.40 for epilepsy and clinical autism. For autism, a common genetic liability was of major importance for co-occurring epilepsy in both clinical and subclinical phenotypes . The estimated genetic correlation (ra) with epilepsy was 0.50 (95% CI = 0.27 − 0.76) for clinical autism and 0.35 (95% CI = 0.19 − 0.54) for subclinical autism. In addition, a modest genetic correlation was estimated between clinical autism and other physical health conditions, including constipation, functional diarrhea, and mixed FGIDs . For ADHD, subclinical phenotype displayed genetic correlations (ra) with epilepsy (0.30 [95% CI = 0.17 − 0.53]), constipation (0.17 [95% CI = 0.04 − 0.29]), and mixed FGIDs (0.17 [95% CI = 0.07 − 0.28]), while clinical ADHD showed significant genetic correlations (ra) only with mixed FGIDs (0.21 [95% CI = 0.02 − 0.44]). Model fit statistics are given in Additional file The phenotypic correlations, etiological correlations, and bivariate heritability between associated physical health conditions and autism/ADHD from each model are summarized in Fig. To our knowledge, this is the first twin study to systematically examine the shared etiologies of common physical health conditions in children with clinical and subclinical autism and ADHD phenotypes. We found that both clinical and subclinical autism and ADHD displayed phenotypic correlations with neurological, immunological, and GI conditions, which were found also moderately to highly heritable. Our findings indicate that children with higher liability for clinical autism and ADHD have an increased risk for even various co-occurring physical health conditions, and that the risk extends to subclinical variants of autism and ADHD. In addition, the majority of co-occurring physical health conditions in autism and ADHD were explained by shared genetic factors. Taken together, the results of this study support the notion that autism and ADHD are quantitative extremes of continuously altered neurodevelopment, where cumulative genetic effects also contribute to an increased liability for co-occurring physical health conditions.In addition to clinically diagnosed autism and ADHD, our findings suggest that subclinical phenotypes are also associated with a range of physical complications, with comorbidity profiles similar to those with clinical variants. Despite the under-threshold symptom severity, the potential clinical relevance of subclinical phenotypes of autism and ADHD has been discussed in the context of risk of psychiatric disorders and negative long-term outcomes –39. PresThe univariate twin modeling analysis of epilepsy, coeliac disease, and the selected GI conditions was conducted with a child twin sample for the first time. The heritability of pediatric epilepsy and irritable bowel syndrome was found similar to the results derived from other adult samples –22, 25, Our results do not support an association between coeliac disease and clinical autism and ADHD. Although the potential benefit of gluten-free diet on symptoms of autism and ADHD has recently received considerable scientific attention –58, the The present study provides evidence that the risk for co-occurring physical health conditions increased with the higher liability to autism and ADHD diagnosis. These findings are consistent with a biomedical approach to autism and ADHD , 3, in lOn the other hand, the co-occurring physical health conditions in autism/ADHD could also be related to other factors than exclusively genetic liability. For instance, internalizing symptoms , 75, medOur study had several strengths. First, we included both clinical diagnosis and subclinical phenotypes of autism and ADHD. The study design allowed us to examine the continuum model of genetics influence on co-occurring physical health conditions in autism and ADHD. Second, both autism and ADHD were analyzed in one cohort, resulting in a wealth of information on clinical and etiological profiles of somatic phenotypes in neurodevelopmental disorders.However, our results should be interpreted taking into account some of the study’s limitations. The prevalence of headaches and GI conditions in our study could be underestimated compared to previous epidemiological studies which utilized systematic screening for data collection , 78. SinThis study endorses the quantitative nature of autism and ADHD with genetic effects forming a continuum of behavioral traits that are associated with physical health conditions in different body systems. These associations vary in strength, and further research into the genetic links, biological pathways, and clinical implications of somatic phenotypes are required for a more complete picture of physical health in autism and ADHD.Additional file 1. ICD code list. Table S1: Sex distribution of clinical and subclinical autism/ADHD in our sample. Table S2: Associations between physical health conditions and the overlap of autism and ADHD in our sample. Table S3: Univariate twin model fit statistics. Table S4: Bivariate models for autism/ADHD and physical health conditions. Table S5: Etiological component contributing to phenotypic correlation between autism/ADHD and physical health conditions. Table S6: Bivariate twin model of clinical autism and physical health conditions fit statistics. Table S7: Bivariate twin model of subclinical autism and physical health conditions fit statistics. Table S8: Bivariate twin model of clinical ADHD and physical health conditions fit statistics. Table S9: Bivariate twin model of subclinical ADHD and physical health conditions fit statistics. Table S10: Etiological component contributing to phenotypic correlation between subclinical autism/ADHDand physical health conditions.Additional file 2. The English version of the Autism–Tics, ADHD, and Other Comorbidities inventory (A-TAC).


Predictive models correctly identified 66% of individuals with ADHD and 81% of those with ASD, but 62–88% of identified cases were false positives. The mean proportion of developmental deviations was 18.7% in the ADHD group, 20.0% in the ASD group, and 15.6% in peers; youth with both ADHD and ASD (n = 50) deviated on 21.8% of all developmental signs and had more pronounced deviations than those with ADHD or ASD alone. ADHD and ASD are characterized by broad and non-specific developmental deviations. Developmental information alone cannot be used to accurately predict diagnostic status in adolescence and false positives are likely if the diagnostic process relies heavily on such information. Developmental deviations are part of normal development and common in children without ADHD and ASD. Etiological heterogeneity and considerable temporal fluctuation in the core characteristics of ADHD and ASD may explain the lack of distinct developmental patterns.Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are neurodevelopmental disorders with an early onset. Guidelines recommend a careful evaluation of developmental history when assessing the disorders, but it is unclear how children with ADHD and ASD differ from their peers growing up. In this study, physical, family, psychological, social, and educational information were examined in 3623 ethnically diverse children that were prospectively followed from birth to age 15 as part of the Fragile Families and Child Wellbeing Study. Fifteen-thousand variables were screened, and 506 variables included in the final analyses. Accuracy of the most indicative information to predict ADHD and ASD diagnoses in adolescence was evaluated. Adolescents with ADHD (The online version contains supplementary material available at 10.1007/s00787-022-02024-4. Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are common neurodevelopmental disorders with an early onset , 2. ADHDEarly detection and diagnosis of ADHD and ASD have been highlighted as important so that affected individuals and their families can access proper information and support . Early dAccording to the evidence-based recommendations for health care in England, practitioners assessing ADHD and ASD in children and adolescents should carefully evaluate the core symptoms of the disorders , 19. TheA broader understanding of which developmental signs are indicative of ADHD and ASD needs to be based on comprehensive and systematically collected prospective data in diverse samples of children. At current, the literature has established that a myriad of social, behavioral, biological, neural, and psychological factors are under- and overrepresented in individuals with ADHD and ASD . A fairlThis study synthesized and analyzed rich developmental data in a diverse and prospectively and systematically assessed sample of children to identify how children with ADHD and ASD deviate as they grow up. The first aim was to establish which developmental signs were most indicative of ADHD and ASD . The second aim was to evaluate with which accuracy this information predicted ADHD and ASD diagnoses in adolescence . The goal was to provide empirical information about developmental deviations in ADHD and ASD to guide the evaluation of developmental history in clinical practice and inform research on behavioral phenotypes and developmental processes implicated in the disorders.https://fragilefamilies.princeton.edu/). The Fragile Families and Child Wellbeing Study included children born between 1998 and 2000 and oversampled children to unmarried mothers resulting in the inclusion of many Black, Hispanic, and low-income families. The first interview was conducted at the time of birth and follow-up interviews were conducted when children were approximately 1, 3, 5, 9, and 15 years old.Prospectively collected data from the Fragile Families and Child Wellbeing Study were analyzed. The Fragile Families and Child Wellbeing Study collected developmental, family, physical, psychological, social, and educational information at six time points from birth to age 15 and has been described in detail elsewhere ; plenty The study protocol for the Fragile Families and Child Wellbeing Study was approved by The Princeton University Institutional Review Board (IRB 13–1946). The study was also approved by appropriate review boards at affiliated universities and hospitals. Legal guardians and primary caregivers signed informed consent and adolescents provided assent. Participants received financial compensation for their time. To secure confidentiality, the data used in this study were deidentified and geographical identifiers and genetic and medical variables were not included.https://fragilefamilies.princeton.edu/data-and-documentation/public-data-documentation). The online documentation alongside a screening of all variables at each wave of data collection  resulted in the selection of 506 variables for the final analyses. All variables that tapped into the developmental domains of the child as well as family history of psychiatric disorders were included in analyses.The essential information at birth and ages 1 and 3 was provided by caregivers, particularly mothers. At age 5, both caregivers and teachers provided information. At age 9, caregivers, teachers, and the children themselves provided information. Information about all the variables collected as part of the larger study is available online , 20 variables for family presence of psychiatric disorders. In addition, 43 variables about broader physical development were analyzed and these included general health , language and speech difficulties, height and weight development, accidents, and service use (these variables were collected from birth to age 9). With regard to caregiver-reported developmental signs, 7 variables were included at age 1 , 67 variables at age 3 , 87 variables at age 5 , and 113 variables at age 9 . For teacher-reported developmental information, 18 variables were included at age 5  and 83 variables at age 9 . For self-reported information, 52 variables were included at age 9 . Eight performance-based variables were included. The Peabody Picture Vocabulary Test (PPVT) was conducted at years 3, 5, and 9 during in-home visits. PPVT is a standardized test that measures the vocabulary of children. At age 5, in addition to PPVT, Leiter tests measuring attention and impulsivity were conducted. At age 9, in addition to PPVT, the forward and backward digit span (working memory) from the Wechsler Intelligence Scales for Children (WISC) were conducted and two tests from the Woodcock-Johnson Test of Cognitive Abilities: the passage comprehension test (reading and language skills) and the applied problems Test (math reasoning). Last, four variables from the Maternal Description of Child (MDoC) test were included where mothers described their child verbally and the degree of positive affect, negative affect, detachment, and amount/descriptiveness of speech was scored.All variables that included information about developmental signs was transformed into binary variables with each variable indicating a clear deviation regarding that particular information. For example, a variable examining the child’s ability to feel guilt was coded such that a clear indication of problems with feeling guilt was indicated. Thus, ordinal items  were binarized (deviation or not). This was done to mirror the yes/no properties of developmental questions asked during an evaluation of developmental history and the ability of caregivers to remember developmental signs retrospectively. Test scores were not binarized since they were normally distributed and can be used as part of an overall evaluation of developmental history . In a supplementary file, available online, the design of each variable is described alongside information about which original variables were used.n = 1275) were omitted.ADHD and ASD status was derived using the information at year 9 and 15 where caregivers reported whether a medical professional had diagnosed their child with either ADHD or ASD. Participants with missing information about ADHD and ASD status at ages 9 and 15  logistic regression  to prediTable Figure Fig. Fig. SD = 26.48, 16.2% of variables). Only one participant (0.0003%) showed zero developmental deviations and only 10.1% of all participants showed deviations on less than 10% of the variables. In those without ADHD/ASD, 11.1% showed developmental deviations on less than 10% of the variables. The difference in the mean number of developmental deviations between those with  and without ADHD  was statistically significant (p < 0.0001). As was the difference between those with  and without ASD .To further explore patterns of developmental deviations in the cohort, the number of deviations each participant exhibited during childhood was counted. The maximum number was 496  and all participants that had data on 10% or more of all variables were included. Available data were used to estimate the number of deviations that each participant would exhibit whether no missing data were present. The mean number of developmental deviations was 80.11 (n = 50) differed from those with ADHD or ASD alone. The mean proportion of deviations across all analyzed variables and the 17 unique variables included in the final predictive models were compared across the three groups. A one-way ANOVA with Tukey-corrected follow-up pairwise group comparisons showed that the dually affected group deviated on more variables (21.8%) than those with ADHD alone  or ASD alone . The two latter groups did not differ statistically significantly from each other (p = 0.89). For 7 of the 17 variables in the final predictive models, chi-square tests showed that the proportion of youth exhibiting a specific deviation was higher in the dually affected group than in the ADHD/ASD only groups. Significant differences emerged for the following variables: parent-reported stubbornness at age 5 , clinical anxiety on the mother’s side , parent-reported restlessness at age 9 , parent-reported concentration problems at age 9 , parent-reported problems with being easily distracted at age 9 , teacher-reported problems with being anxious in groups of children at age 9 , and teacher-reported difficulties with making friends at age 9 .Post-hoc analyses were conducted to analyze whether the dually affected group  were directly related to the diagnostic criteria of the disorder, with these signs covering all three diagnostic domains: attention, hyperactivity, and impulsivity. Speech problems at age 9 and teacher-reported age 9 problems with anger and being anxious in groups of children were also included in the final model. The latter findings imply that signs and symptoms indicative of both internalized  and externalized emotionality  are prevalent in ADHD throughout development. These results are in line with current research showing increased rates of anxiety and behavioral disorders in children with ADHD  and studThe final model correctly classified 66% of adolescents with ADHD. Importantly, 62% of all identified cases were false positives, meaning that many adolescents were identified as having ADHD when they did not. A model in which a probability of 80% was used identified fewer with ADHD , but also resulted in a lower proportion of false positives . Low accuracy of developmental information to identify ADHD was also shown in a previous longitudinal study where information at 6 and 18 months could not adequately predict a later ADHD diagnosis, although several variables were statistically significantly associated with later ADHD . One creAdolescents with ASD also differed from their peers on a large number of developmental signs. Many signs were related to atypical behaviors in interaction with peers: tendencies of not joining others in play and aggressive and disturbing social behaviors. Attention, hyperactivity, and impulsivity problems were also linked to ASD, as were several signs indicating internalized symptoms such as anxiety, worry, and phobias. In contrast with ADHD, the final predictive model included a broader range of variables than signs and symptoms closely related to disorder criteria. Most of the included variables (6 out of 9) were from the age 9 assessment and these included speech problems, parent-reported difficulties with limited interests and lack of self-confidence, teacher-reported difficulties with problems making friends and arguing with others, and self-reported lack of helping with chores at home. Further, familial risk of clinical anxiety on the mother’s side and parent-reported stubbornness at age 5 were included. The model identified 82% of adolescents with ASD but 88% were false positives. An increased probability level of 80% resulted in lower sensitivity but higher PPV without changing the major interpretation of the result. Possible reasons for the low accuracy are the same as for ADHD, that is, ASD symptoms may be gradual rather than part of fixed states, heterogenous, and may fluctuate over time.The most probable explanation for the low accuracy of developmental information to identify youth with ADHD or ASD is that the disorders are characterized by substantial etiological and phenotypic heterogeneity and temporal fluctuation in signs and symptoms. However, a competing explanation is that the validity of the diagnostic information was low. For example, parents may have reported that their children had been diagnosed even when this was not the case. This is not supported by research about parent-reported ASD diagnoses that indicates very high concordance between parent-report and register information (93–98%) –39 and pAnother explanation is that the children had received diagnoses but that these diagnoses had limited clinical validity . This is partly supported by the prevalence of ADHD in this cohort, which was higher than what has been reported in other studies with US cohorts . HoweverThe only variables that were included in the final models for both ADHD and ASD were sex  and speech problems at age 9. This may be surprising since ADHD and ASD often co-occur and did so also in the present sample. Thematical overlap was found for difficulties interacting/getting along with peers, which is supported by prior research showing that impaired social functioning is a shared trait in ADHD and ASD . That spSeveral limitations merit mentioning. As mentioned above, the unknown validity of ASD and ADHD status in adolescence is a limitation of the present study and future studies that include high-quality diagnostic data can repeat the approach here and evaluate whether overall results converge. Second, very rich developmental material was analyzed but not all information that may be relevant was included; for example, more detailed information about developmental milestones would have strengthened conclusions. Third, variable selection when working with many variables is complex, and other statistical models and techniques than those used here are available . It is out of the scope of the present paper to compare model performance, but future work may want to do this, although type of statistical model was not linked to predictive performance in relation to life outcomes at age 15 in a large collaborative study that employed the same dataset as in this study . Last, fAdolescents with ADHD and ASD differ from their peers on a range of developmental signs growing up, but no single developmental sign or assembly of signs from birth to age 9 can be used to classify disorder status in adolescence. Etiological heterogeneity and considerable fluctuation over time in the core characteristics of the disorders may explain the lack of distinct developmental patterns in ADHD and ASD. This study also showed that developmental deviations are part of normal development with 89% of adolescents without ADHD and ASD showing deviations on at least 10% of all analyzed developmental signs. Study conclusions are limited by the uncertainty of the clinical validity of ADHD/ASD status in adolescence, but results are consistent with ADHD and ASD being gradual, heterogenous, and temporally unstable syndromes.Supplementary file1 (DOCX 54 KB)Supplementary file2 (DOCX 78 KB)Supplementary file3 (DOCX 72 KB)Below is the link to the electronic supplementary material.


We show that traditional family farming systems maintain diverse vegetable species, mainly squashes (Cucurbita spp.), sweet potato (Ipomoea batatas), beans (Phaseolus spp.), onion (Allium cepa), peppers (Capsicum spp.), tomato (Solanum lycopersicum), next to leafy vegetables and maize, among others. We propose the priority of systematic surveys as a basis for monitoring genetic erosion, increasing complementariness between in situ and ex situ conservation, and implementing sustainable conservation and utilization. The case studies highlight genetic diversity within each cultivated species, with different crop physiological responses; disease resistances, different quality traits and associated uses, from animal feeding in maize to a range of culinary uses linked to traditional culture in maize and vegetable species, and ornamental uses of specific Capsicum and Cucurbita. Some landraces were the basis for breeding, where improved cultivars allowed the competitiveness of landrace germplasm in the markets. Renewed industrialized products allowed the competitive and sustainable use of Capsicum landraces in Brazilian farmers communities. Strategies towards in situ conservation improvements and valorization are discussed; emphasizing the role played by agroecology, community seed banks and custodian farmers, participatory plant breeding, promotion of landraces specialties among consumers, and the need of research and capacity building, among others. Farmers’ participation in the decisions is a key factor, along with the academia and the public sector. Landraces and associated knowledge are treasures to be used to benefit from farmers to consumers, directing the course of agriculture towards sustainable directions.The historical meeting between originally American people, European colonizers, and slaved peoples from Africa in the biome Pampa in South Brazil and Uruguay involved a cultural syncretism and a great genetic diversity of landraces of cultivated species. Genetic richness evolved by selection and cultural processes in response to different environments, cultural backgrounds, and needs. This review summarized the knowledge on vegetable and maize landraces in South Brazilian and Uruguayan Pampa biome, to design a strategy towards the rediscovery, conservation, and sustainable use. Landraces diversity maintained  With thcampos . At the From the 16th century onwards, and in several waves until the 20th century, there was an influx of people from different ethnic groups and cultures of the Old World, generating a cultural mixture that also involved crops and landraces. Migration trends led to the movement of 56 million people out of the European continent between 1821 and 1932, most of them to the Americas. Of the 12 million people whose destination was Latin America, 42% went to the Brazilian - Uruguayan Pampa . For thecampos, the slaves were not exclusively dedicated to livestock farming, but also carried out small-scale agriculture  the identified main limiting constraints to set the landraces in value and resignification were described, in a context of agroecology and farmers’ right consideration.The aim of this work is to contribute to a diagnosis of the state of landrace plant genetic resources in the Pampa biome region of Brazil and Uruguay, which would allow us to contribute to the design of a strategy for their conservation and sustainable use. Particularly, (i) the knowledge about 2Pampa biome in South Brazil and Uruguay , farmers profile , vegetable crops maintained as landraces ; (2) assessing the state of ex situ conservation; (3) presenting crop case studies in which more in-depth research has been conducted; and (4) exploring the different approaches to conserving and valorizing local vegetable genetic resources that have been implemented, including farmers seeds networks and governmental regulations.The review focuses on (1) characterization of the productive agricultural systems where landraces are conserved in situ conservation, literature referred to specific vegetable species were analyzed, as well as others with an integral approach on the agrobiodiversity at a territorial level. To compare the agrobiodiversity of three surveys in Uruguayan areas where a similar methodology was followed to assess in situ landraces conservation, the Shannon-Wiener diversity index (H′) based on the frequency of species occurrence was estimated for each surveyed area; evenness was calculated as E = H′/lnS, where S represents the total species richness  is also presented, and the interaction between ex situ and in situ conservation is discussed.The state of Capsicum peppers), the general context of landraces cultivation is analyzed in a deeper manner. These cases were defined in attention to the knowledge accumulated by our research teams. Landrace phenotypic and genetic diversity, farmers’ uses and knowledge, and the state of conservation are presented and discussed, as well as information on nutritional quality, resistance to diseases, culinary uses, among other traits.Throughout four crop-based case studies  project stand out, carried out by a team from Brazil, Paraguay and Uruguay (2015-2019). In addition, we highlight seminars organized by Facultad de Agronomía in Uruguay; those organized annually by Embrapa Clima Temperado in Pelotas, Brazil; workshops organized by the ‘Red Nacional de Semillas Nativas y Criollas’, and other more specific meetings in the frame of the studies on maize races and landraces in the lowlands of South America. Besides, the authors participated in the country reports on the situation of plant genetic resources for food and agriculture, presented to the ITPGRFA , which allowed contact and exchange networks, facilitating the information and identifying information gaps.Regarding the situation and state of knowledge on landraces in the Brazilian - Uruguayan Pampa, research priorities were proposed to establish a baseline, whereas appropriate strategies for valorizing and conserving the agrobiodiversity of vegetable landraces were discussed.33.13.1.1The family farmers rooted in the territories for several generations act as the primary keepers of landraces. In more recent times, ‘neo-rural’ groups have also joined this endeavor like in ‘Maldonado’ territory, Uruguay . These aThe main characteristics of family productive systems include residing on the farm, with the work primarily conducted by the family, and relatively small land areas . The aveThese productive systems are agrobiodiverse, involving a combination of crops, livestock, dairy production, farm animals , fruit production, and non-productive areas rich in natural plant communities. In several cases, vegetable production is exclusively for self-consumption, with any surplus being sold . HoweverA notable aspect of family farming systems is the significant influence of generational succession on the stability of the production unit . The surFrom the surveys, as well, the fundamental role of women in the landrace conservation activities also arise, as well as the traditional knowledge on productive processes and uses that they hold. Although information on the agroecological management of landraces is usually lacking, some surveys indicated that approximately half of the farms practiced agroecology . In otheFarmers conserve landraces of various crops for several reasons, including adaptation or hardiness, organoleptic characteristics, culinary uses, post-harvest conservation, family tradition, heritage, food security, and economic importance . Landrac3.1.2Landraces of 49 vegetable crops belonging to 47 species and 11 botanical families (excluding aromatic herbs) are currently cultivated in the Brazilian-Uruguayan Pampa biome . However, it is not ruled out that in future work they may also be recorded in Uruguay. On the other hand, in Uruguay, there are also records of landraces of crops such as Lathyrus sativus, Lablab purpureus and Allium ampeloprasum, which do not appear in the Brazilian records until now. This distinction could be influenced by cultural factors, and may also apply to regions within the countries, where differences in landraces adapted to different environments and management are expected.There are crop differences between Brazil and Uruguay, such as For the more in-depth territorial surveys carried out by Pereira in ‘Rocha’ (2017), Favaro and Piazza in ‘Canelones’ (2019) and Cuadro in ‘Maldonado’ (2022) in Uruguay, 43 vegetable crops (40 species) belonging to 10 plant families and 426 landraces (cassava was notrecorded in these territories). Plant families more commonly found were Fabaceae, Cucurbitaceae and Brassicaceae, whereas the largest number of landraces corresponded to Cucurbitaceae (83), Fabaceae (71) and Solanaceae (60) , 152 in ‘Rocha’ , and 102 in ‘Maldonado’ . The distribution among plant families, the Shannon -Wiener index, the evenness and Beta indices  involves multiplication of landraces seeds of grass peas, squashes, peanuts, cowpea, and their participatory characterization. Some of these landraces will soon be made available through the ITPGRFA’s multilateral system.In Brazil, a survey conducted by Embrapa in 2020 for the national report on plant genetic resources for food and agriculture highlighted the contributions in the Pampa biome from the NGO ‘Bionatur/Conaterra’  and the ‘União das Associações Comunitárias do Interior de Canguçu’ (UNAIC) . Bionatu3.2ex situ conservation strategies and in situ/on-farm conservation can generate impactful results for the conservation and sustainable use of genetic resources. Both in Brazil and Uruguay, this integration between ex situ and in situ/on-farm conservation is still limited, but progress has been made.In a scenario of climate change, with the replacement of cultivated species, contamination by transgenes, and the reduction of human populations living in rural areas, the risk of landrace disappearance is increasing. Only an effective connection between Brazil has a germplasm collection and conservation system coordinated by Embrapa, in partnership with various public and private institutions. The most recent survey conducted  recordedEx situ conservation in Uruguay is carried out by the Instituto Nacional de Investigación Agropecuaria (INIA) and the Facultad de Agronomía, Universidad de la República (BG-Fagro). In the last decade, the number of systematic collections associated with different projects has expanded, and the new accessions have been characterized, including ethnobotanical information to enhance passport data , four community banks have been established. These banks, called Regional Community Centers for Agrobiodiversity Support (CCRA), are managed by farmers to facilitate access, storage, distribution, multiplication, and participatory improvement of landraces of 15 species .Community Seed Banks (or Seed Houses) in southern Brazil also deserve recognition as popular initiatives managed by groups of farmers with the objective of conserving landraces and ensuring access to seeds . These aIn Situ/On-Farm Conservation of Plant Genetic Resources and its interaction with Ex Situ Conservation/ConservaIn’ is led by Embrapa and involves several universities, NGOs, farmers’ associations, and seed guardians. The project’s activities are carried out in all Brazilian biomes and aim to systematize and make available information on in situ – on farm conservation actions of plant genetic resources. An interactive database is ongoing, where all the participants can enter data on the maintained landraces, indicating threats and the context of conservation and use of this germplasm. This database will allow the identification and mapping of landraces, enabling a diagnosis of on-farm conservation and facilitating the development of maintenance strategies while minimizing genetic erosion. Surveying data on traditional people and communities whose agricultural systems contribute to the existence of microcenters of local diversity of cultivated plants contribute to valorize and recognize territories and local culture that preserve this diversity  are the third vegetable crop after potatoes and tomatoes in Uruguay in terms of Gross Production Value, and the most relevant in the number of vegetable farmers involved , as well as in their response to leaf diseases such as white spots caused by squamosa  and mildstructor . The lanstructor  , whilst the ancient commercial maize group possessed hard endosperm. The modern landraces had dentate and semi-dentate endosperms. Maize dispersion in South American lowlands involved migratory flows from the Amazon region  started with the collection made by ex situ collection conserved by INIA was established in two schools. The students actively participated in these areas of multiplication, after they conserve seeds and the popped grains were consumed in schools . These landraces have been traded between relatives or neighbors or constitute a family heirloom, where seeds pass from generation to generation  in Uruguay, it was observed that more than a third of the landraces has been managed by families for more than 30 years: 48% of the surveyed rural families conserved landraces of squash, watermelon, melon and cucumber. Thirty-eight landraces of six different species were identified (14 neration .Citrullus lanatus), melon (Cucumis melo), cucumber (Cucumis sativus), bottle gourd (Lagenaria siceraria), sponge gourd (Luffa aegyptiaca) and the five domesticated species of squash and pumpkins .In Brazil, according to the data available in the Sistema ‘Alelo Vegetal’ – the database of genetic resources of Embrapa  –from 20Cucurbita landraces are widely used for food, depending on the species and the ethnic origin of the local communities. The largest number of landraces in cultivation in the Brazilian Pampa are the species Cucurbita maxima and Cucurbita moschata. The former presents great genetic variability for external morphological fruit traits, such as size, shape, color and shell texture, which results in a wide range of local names given to each type. The fruits of Cucurbita moschata represent an important food reserve for domestic animals (mainly swines and bovines), as well as being widely used in sweet recipes and also in savory dishes . Farmers descending from Portuguese immigrants who arrived in the Brazilian Pampa in the 19th century still grow Cucurbita pepo whose fruits, known as mogangos, have a fairly hard shell and fibrous pulp, and are appreciated in the preparation of ‘caramelized mogango’ and also in savoury dishes. In much smaller numbers, some farmers also keep landraces of ‘cidra’ or ‘gila’ (Cucurbita ficifolia), with extremely hard hulled fruits and white and very fibrous pulp, used in the preparation of a typical Portuguese sweet dish called ‘doce de gila’ , as well as landraces of Cucurbita maxima and Cucurbita moschata. The descendants of German and Pomeranian immigrants, in addition to Cucurbita maxima and Cucurbita moschata, keep ornamental landraces of Cucurbita pepo, some with edible fruits and others that are not suitable for consumption due to the bitterness of the pulp. With intense and quite varied colours, as well as quite diverse formats , the fruits are used in home decoration. The so-called ornamental poronguinhos have piriform format, are quite varied and can be used in decoration, with great post-harvest conservation. When they are star-shaped, they are called star squash or abóbora-dez-mandamentos, and are used in sweet preparations, with or without the addition of shredded coconut (Cucurbita maxima and Cucurbita moschata), some landraces can be used to develop biofortified cultivars aiming to promote consumer health . In turn, the fruits of the sponge gourd (Luffa aegyptiaca) are used in the Brazilian Pampa as a sponge for washing dishes or for bathing.The fruits of Cucurbita accessions of the Genebank of Embrapa Clima Temperado, we conclude that Brazil is a secondary center of Cucurbita diversity. The greatest genetic variability is found in the south of the country, especially in the Pampa biome  have the presence of capsaicin in their fruits as a distinctive feature. Originating in the Americas, these peppers became known worldwide after the voyages of Christopher Columbus in the 15th century . Due to their aesthetic characteristics, they are also cultivated as ornamental plants. century . Capsicungencies . Brazil chinense . The use regions . They arCapsicum peppers. Some people grow a few plants, produced in pots or planted in their domestic or vegetable gardens for various uses, such as in cooking and as ornamental plants , feijoada (consumed mainly in Brazil) and chimichurri .In the Pampa biome, many families maintain landraces of l plants , but thel plants . As in vCapsicum baccatum). Commercial crops have been produced for about a century, on small rural properties and with family labor. It is difficult to determine precisely when it began, or the origin of the seeds used in the first plantations , a disease which is difficult to control. However, to remain in the pepper market, some producers set up family agro-industries and began to diversify the crop with the support of several public education and research institutions . Before, they cultivated landraces of only one species (C. baccatum) and, from 2004, they started to cultivate landraces of more than three species , with fruits of different sizes, shapes, colors, and pungency. As a result, more than 100 different pepper-based products are produced, such as pepper chocolates, various types of sauces, sweets, preserves, dehydrated peppers, among many others . The characterisation and evaluation of pepper accessions from this genebank led to five doctoral theses , locally called ‘chícharo’ in Uruguay. It is a NUS crop , a variety of the common bean. The pods possess a low fiber content, rendering them more tender and suitable for consumption when cooked or boiled. There are landraces exhibiting either determinate or indeterminate growth habits, flattened or cylindrical pods with yellow, green, or purple color. Within the existing bean collection at Embrapa Clima Temperado, there are ten accessions of pod beans originating from the Pampa and Atlantic Forest biomes, with seven of them conserved by female guardians and three by male seed guardians. These landraces display different combinations of size, color, luster, and shape in their seeds.Another interesting case is the Arachis hypogaea) have traditionally been cultivated using landraces. A survey and collection of 285 landraces recorded variations in fruit color, number of kernels per fruit, pod size, and shape , is highlighted by farmers in this analysis. In most family farms, landraces of aromatic crops  are also conserved. The diversity of landraces conserved in situ is reflected not only in phenotypic and genetic diversity, but also in the diversity of uses and names by which farmers call them  and facilitate the necessary complementation between in situ and ex situ conservation. Landraces are dynamic populations . The conservation of agrobiodiversity is a public benefit, requiring positive incentives such as the implementation of in situ conservation projects  in Brazil, and the National Plan for the promotion of production based on agroecological principles (2018) in Uruguay, prioritize the conservation of plant genetic resources/socio biodiversity and propose various programs and projects, such as promoting government purchases , expanding and promoting marketing in street markets and specialized stores, giving incentives to add value, strengthening participatory guarantee systems and participatory plant breeding.Capsicum landraces. Seed festivals and fairs for native and landrace seeds held in the region serve as instances for farmers to gather and exchange valued seeds. These activities could be expanded and enhanced to increase social visibility for the conservation of agrobiodiversity in the context of agroecological production and healthy nutrition. Showcasing traditional dishes prepared by farmers, innovative dishes created by chefs, manufactured products, attractive handicrafts, and cultural products would be alternative approaches to be more implemented and in more locations.The development of high-quality artisanal products and specialized stores has shown to be a successful alternative. An example is the case of peppers as presented in this review, an initiative by ‘Cooperturuçu’ which, with initial support, was able to develop a set of attractive products with an appropriate marketing channel, ensuring the conservation of ad hoc mechanisms that are suitable for our farmers. Working on branding is more feasible than developing designations of origin, both in collective and participatory certification terms , plant breeding and participatory landraces breeding, development of local trades and appellations of origin, product and gastronomic innovations, agroecological management, among other aspects, including legal ones, are needed. Exchange of knowledge with and among farmers and capacity building is another strategy to enrich, using the classical divulgation texts and videos up to the internet social media   and pean4.5The relevance of agrobiodiversity, particularly landraces, is recognized in international instruments such as the Convention on Biological Diversity (CBD) , the IntBased on the analysis of the main tools to support the valorization of landraces, it is relevant to establish the most suitable governance framework that ensures the participation of farmers, academia, and public institutions, and enables effective progress in an action plan for the conservation, sustainable use, and effective implementation of farmers’ rights .www.inase.uy), whereas in Brazil selling landrace seeds among farmers or farmers organizations is fully permitted. While these regulations comply with Article 9.3 of the International Treaty on Plant Genetic Resources for Food and Agriculture (ITPGRFA), further measures are needed as proposed by the ‘Inventory of national measures, best practices and lessons learned from the realization of Farmers’ Rights, as set out in Article 9 of the International Treaty’ (www.fao.org/plant-treaty/tools/toolbox-for-sustainable-use/details/en/c/1473076/).Regulations in Uruguay and Brazil allow the free exchange of landrace seeds, but show differences in case of selling the seeds, as in Uruguay a previous registration of the landrace is required (This article highlights the status of conservation, use, and valorization of vegetable landraces in the Pampa biome, addressing the main socioeconomic and environmental challenges as a starting point to strengthen ongoing lines of action and generate new proposals aligned with the 2030 Agenda for Sustainable Development  and the MR - study conception and design, data collection, analysis and interpretation of results, draft manuscript preparation and final edition. RV - data collection, analysis and interpretation of results, draft manuscript preparation. RN - data collection. DP - data collection. NA - data collection. IF - data collection. GG - data collection, analysis and interpretation of results, draft manuscript preparation and final edition RB - study conception and design, data collection, analysis and interpretation of results, draft manuscript preparation and final edition. All authors contributed to the article and approved the submitted version.


Practical policy implications, which this group of countries can use to assess and address constraints to the technological knowledge progress, are also discussed.Do the famous laws of the motion of technological progress like the Moore’s Law, Wright’s Law, Goddard’s Law, and their derivatives explain the technological knowledge progress of developing and emerging economies? The aim of this paper is to investigate that question. For that purpose, we rationalize an existing framework  and employ it on a panel data set of 66 developing and emerging market economies over the 1995–2017 period. Empirical evidence is mixed. Some of the results confirm a positive relationship between technological knowledge progress and the progress of time. Other instances indicate that the slow rate of learning delays the doubling time by 18 years. Yet other results predict that this group of countries will double its rate of progress in 4–5 years. The explanatory power varies across the laws, with most laws suggesting acceptance of the hypotheses that the included variables affect the technological knowledge progress while others recommending that we “do not accept” the hypothesis that  DEMEs) over the 1995–2017 period. The topic is relevant for understanding the role of technology and technological change in the progress of this group of countries. The importance of the famous laws of motion of technological progress has long been acknowledged in many applications at the microeconomic level in some industries and mostly industrialized economies. How long? , a, aufficient with  as we ouIn the next section we provide a methodological as well as empirical structure for our objective, and estimate the laws separately and in combinations. Section 3 presents and discusses the results, while Section 4 concludes the paper.Yi(t)), technological knowledge (Ai(t)), and productive resources (Xi(t)). For example, in one version of economic growth theory, as in Ai(t) in combines  and [38]yi is current (in-situ) scale which is GDP per capita, and Moreover, combining the  and 37]37] resulwhere in  and 6)  Ai(t)= to,Ai(t) is said to be total factor productivity and this is the reason to decompose productivity as called for by [Ai(t).As for interpretation the original laws –6) repr repr6) rd for by  and 53]Ai(t) is d for by , for exad for by  has dubbd for by . 57] ha haAi(t) d for by , a key dThis section is structured in the following way: First, we describe the data employed in the analysis, and then the empirical model and estimation strategy.Ai(t) we use a Knowledge Economy Index (KEI). The data for this variable derive from the [and t are as previously defined.The 66 DEMEs are covered in from the , 59 updaAi(t−1), has delayed current progress, the results show that time (years) has been of crucial importance in these countries, contributing up to 99% towards progress for each one standard deviation. In In the main results obtained for different laws of technological progress we focus on standardized coefficients and their associated p-values to stress the economic importance of the variables rather than their statistical significance . In Tabl.1 years .yi(t) instead of it will take up to 131 years for this group to double its current rate of progress ) and historical rates of progress log (Ai(t−1)) have been negative. The exception has been Goddard’s law where both the constant term and the coefficients of log (Ai(t−1)) are positive, but their very high p-values (0.9890 and 1.000 respectively) recommend rejecting the null and accepting the alternative hypothesis. Although their study is at the microeconomic level [It is worth pointing out that in all these the constant terms log  allows for the doubling in 4.62 years. Ignoring the arithmetic signs Wright’s Law, Goddard’s Law, and SKC’s Law make reasonable predictions although for different reasons. On the other hand, they have the lowest explanatory power (R-square). The inconsistency between the explanatory power and predictive power of the estimate cautions bold interpretations. Furthermore, the results of the combined Goddard-Moore, and our own generalization recommend that we “do not accept” the hypothesis that in-situ scale explains the technological knowledge progress in these countries.For the SKC’s Law the current scale (per capita GDP) allows for the doubling time in 5.2 years, but net cumulative learning delays doubling time by 21 years. Our own generalized formulation suggests that the log difference between cumulative gross domestic product (GDP) per capita (learning rate) and GDP per capita  production capacity of this group of countries is too small such that it slows the rate of learning and lengthens the doubling time.in-situ scale translates into low cumulative GDP per capita, alternatively a slow learning rate. Originally, Moore predicted technology (represented by a chip) to change every 12–24 years but [We can conclude that the laws of progress do not all give a unique solution in this case. Moore’s Law indicates a positive correlation between progress and time, 73%-100% probability for each standard deviation, making the passage of time the most important determinant of technological knowledge progress. The problem of a small ears but  have estears but –71. Thes


Attention deficit and hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by core symptoms of inattention, and/or impulsivity and hyperactivity. In order to understand the basis for this multifaceted disorder, the investigation of sensory processing aberrancies recently reaches more interest. For example, during the processing of auditory stimuli comparable low sensory thresholds account for symptoms like higher distractibility and auditory hypersensitivity in patients with ADHD. It has further been shown that deficiencies not only exist on an intramodal, but also on a multimodal level. There is evidence that the visual cortex shows more activation during a focused auditory task in adults with ADHD than in healthy controls. This crossmodal activation is interpreted as the reallocation of more attentional resources to the visual domain as well as deficient sensory inhibition. In this study, we used, for the first time, electroencephalography to identify a potential abnormal regulated crossmodal activation in adult ADHD.15 adult subjects with clinically diagnosed ADHD and 14 healthy controls comparable in age and gender were included. ERP components P50, P100, N100, P200 and N200 were measured during the performance of a unimodal auditory and visual discrimination task in a block design. Sensory profiles and ADHD symptoms were assessed with inattention as well as childhood ADHD scores. For evaluating intramodal and crossmodal activations, we chose four EEG channels for statistical analysis and group-wise comparison.At the occipital channel O2 that reflects possible crossmodal activations, a significantly enhanced P200 amplitude was measured in the patient group. At the intramodal channels, a significantly enhanced N200 amplitude was observed in the control group. Statistical analysis of behavioral data showed poorer performance of subjects with ADHD as well as higher discrimination thresholds. Further, the correlation of the assessed sensory profiles with the EEG parameters revealed a negative correlation between the P200 component and sensation seeking behavior.Our findings show increased auditory crossmodal activity that might reflect an altered stimulus processing resource allocation in ADHD. This might induce consequences for later, higher order attentional deployment. Further, the enhanced P200 amplitude might reflect more sensory registration and therefore deficient inhibition mechanisms in adults with ADHD. AlthougSensory processing describes the nervous systems ability to receive, modulate, integrate, and organize external stimuli in order to generate an appropriate response to the environment . There iEarly stimulus processing can be measured electrophysiologically, for example, by means of event-related potentials ERPs; . For insWhen a person, neurotypical as well as on the ADHD spectrum, is confronted with stimuli of a certain sensory modality , the other senses are also co-activated . It describes a net positivity that occurs in the contralateral occipital electrodes 250–400 ms after the presentation of a sound. A recent study shows that the ACOP reflects facilitated visual processing and therefore might indicate an involuntary reallocation of attentional resources to the visual domain, as proposed by Recent evidence points to the fact that crossmodal sensory processing might be deficient in people with ADHD . Salmi e2.2.1.15 patients  with clinically diagnosed ADHD, based on the Diagnostic and Statistical Manual of Mental Disorders , and 14 Attention deficit and hyperactivity disorder symptoms were additionally investigated by the following questionnaires: The Conners Adult ADHD Rating Scales  and digitized using Labstreaminglayer .The experiment was programmed and presented using Presentation® software  for the auditory task.Participants performed the auditory and visual discrimination task in a block design with one block per task in a pseudorandomized order. Each task consists of 350 trials and started with a training of 10 trials.2.3.We recorded EEG with a mobile system  with 22 pre-mounted Ag/AgCl electrodes  that were placed according to the international 10/20 System . The ground (AFz) and reference electrode (FCz) were embedded in the fronto-polar region and in the frontocentral region, respectively.EEG data were digitized with a wireless EEG amplifier at a sampling rate of 500 Hz. Impedances were kept below 10 kΩ.2.4.Data were analyzed with EEGLAB  in MatlaFor artifact attenuation, an Independent Component Analysis (ICA) was computed on the merged blocks of visual and auditory presentation. Prior to ICA, the data were high-pass filtered at 1 Hz and low-pass filtered at 60 Hz . Dummy epochs of 1 s that were unrelated to the task structure were generated and an automatic epoch rejection was applied whenever two standard deviations of the mean signal were exceeded. ICA weights were saved on the raw data.For ERP analysis, the raw data sets were high-pass filtered at 0.1 Hz and low-pass filtered at 30 Hz . Artifactual ICA components were identified by visual inspection and confirmed by the component classification plugin ICLabel . After c2.5.t-tests , 75–125 ms (P100), and 175–250 ms (P200) as well as the most negative deflections 50–150 ms (N100) and 150–250 ms (N200) relative to stimulus onset by using the MATLAB function “findpeaks”  as well as hit/miss-rates were also group-wise compared with independent samples ests see , 5. In oBefore statistical comparison, response times had been outlier corrected with the MATLAB function “rmoutliers” with an outlier being defined as value above 3 median absolute deviation (MAD). Additionally, we correlated EEG amplitudes of the patient group with their ASP scores using the Pearson’s Correlation Coefficient. All statistical analysis was performed using SPSS Statistics (Version 28.0.1.1).3.3.1.ADHD= 34 (SD = 10.72), MControls = 32.14 (SD = 9.94), t = 0.483, p = 0.633] or gender .Demographical data of the 15 adult subjects with ADHD and 14 healthy controls are shown in t = 8.1, p < 0.01) as well as WURS-k scores  are significantly higher in the patient group, which is in line with their clinically confirmed ADHD diagnosis. Further, nine patients took regular ADHD medication with the agent methylphenidate (MPH) that was paused at least 24 h before the experiment.Conners Adult ADHD Rating Scales inattention and hyperactivity/impulsivity scores .Although BDI scores reflected descriptively more depressive symptoms in the patient group, no significant difference between groups was found (ADHD= 38.2 (SD = 6.2), MControls = 27.1 (SD = 6.2), t = 4.79, p < 0.01], sensory avoidance , and sensory sensitivity , but not in the domain sensation seeking behavior .Results of the ASP questionnaire show that adults with ADHD scored significantly higher in the domains low registration . Miss rates were accordingly higher in patients with ADHD but not significant , but not for the second half (p = 0.08). No within-group differences in misses were found between first half and second half if the trials. Patients with ADHD had overall higher auditory discrimination thresholds  and it took them more trials to reach their individual threshold , MControls = 468.80 ms (SD = 149.99 ms), t = 0.466, p = 0.645]. Additionally, subjects with ADHD made more mistakes in discriminating the gabor patches’ contrast difference , although no statistical significance was reached too (see tADHD = −3.859 (p ≤ 0.01), tControls = −4.556 (p ≤ 0.01)].It took the patients longer to discriminate the gabor patches correctly compared to the healthy controls, despite also not reaching a statistical significance . The details can be found in There were no significant group differences of P50, P100, N100, and P200 components at the channels Fz and Cz measured that represent intramodal auditory processing . At the 3.3.1.2.ADHD = 1.22 (SD = 0.73)M, MControls = 0.68 (SD = 0.48), t = 2.341, p < 0.05]. Additionally, the patient cohort showed higher activation, although not significant, at the channel O1 found in the P200 component compared to the control group  and channel O2 . Details can be found in There were no significant group differences of P50, P100, P200, and N200 components at the channels Cz and Fz measured that represent crossmodal visual processing . At the 3.4.r = −0.517, p < 0.049. Further, the mean P100 amplitude and sensation seeking behavior were found to be positively correlated, r = 0.703, p < 0.05 in patients with ADHD. Visual crossmodal amplitude at the channel Fz was negatively correlated in the patients group . No significant association were found in the healthy control group.In patients with ADHD sensation seeking behavior and the mean P200 amplitudes of the auditory discrimination task at the channel Fz was found to be significant negatively correlated, 4.lower intramodal P50 at the channels O1 and O2 that represent intramodal sensory processing. At the channel Fz which represents crossmodal visual processing, the N100 component amplitude was significantly lower in the patient group compared to the healthy controls.This is the first study addressing sensory crossmodal electrophysiological activity in adults with ADHD. In the auditory discrimination task, patients with ADHD showed a significantly enhanced crossmodal P200 amplitude and a significantly increased intramodal N200 amplitude compared to the healthy control group. No significant differences were found at earlier latencies. In the visual discrimination task, the patient group showed a significantly No other significant group differences of P50, P100, N100, P200, and N200 components were found. On the behavioral level, subjects with ADHD showed weaker auditory performances compared to the control group, although not reaching a statistical significance. In the visual discrimination task, the patient group also showed slightly but not significantly poorer performances.Physiologically, the visual and auditory cortex are anatomically connected and influence each other already at early stages of sensory processing . The earIn this study, we investigated auditory to visual crossmodal activations in ADHD by comparing the inter-group difference of the occipital P200 amplitude that was measured after the elicitation of a non-spatially specific sound. In general, the P200 component is associated with a number of early sensory processing steps including stimulus registration, discrimination, early attentive mechanisms as well as the inhibition of further processing of competing information . Until nThey were also able to show that the P50 component is related to later sensory processing, marked by a decreased P300 component that correlates with higher distractibility scores in the Sensory Gating Inventory. We found a higher intramodal auditory N200 and an enhanced crossmodal P200 component, indicating enhanced visual activity during the auditory discrimination task. This occipitally enhanced P200 component we measured in adults with ADHD can be related to the enhanced crossmodal visual activity in healthy populations that was mentioned before. One interpretation for the intergroup difference is that enhanced intra-and crossmodal auditory activity in ADHD reflects increased neuronal sensitivity in the processing of auditory stimuli and more sensory registration in the visual domain and thus more spreading of attentional resources, pointing toward deficient stimuli related inhibitory mechanisms in adults with ADHD. Our results are supported by the study of The lack of significant ERP amplitude differences in the visual discrimination task indicates that early visual sensory processing of low saliency stimuli such as Gabor patches is not impaired in adults with ADHD. Still, there is evidence that visual processing does not function properly in patients with ADHD. While we investigated possible aberrancies in early stages of sensory processing, In the current study, subjects with ADHD had higher auditory discrimination thresholds, made more mistakes and it took them more trials to reach their minimal threshold compared to the healthy controls, despite not reaching a statistical significance see ,D. FostiIn the current study, adults with ADHD performed worse, although not significant, in the auditory discrimination task.hypersensitivity suggests better performances in auditory discrimination (Besides the crossmodal spreading, one reason for the worse auditory performance might be impaired sustained attention capabilities in the patient group, as it is well reported as a common symptom in adult ADHD . Subjectmination , the undmination .Further, higher sensory sensitivity goes along with less sensation seeking behavior, indicating lower sensory thresholds that lead to more auditory sensory registration. It is worth noting that the higher “low registration” scores see  of the pThe performance differences in the visual discrimination task between the groups are minor and therefore congruent with the lack of electrophysiological group differences. Both groups made more errors in the second half of the experiment, which can be interpreted considering increased difficultness for the contrast detection threshold. The lack of major effects strengthens the hypothesis that early visual sensory processing of low saliency stimuli like Gabor patches is not impaired in adults with ADHD. Still, there is evidence that aberrant visual processing leads to impaired visual performance in patients with ADHD, indicated by worse temporal allocation of visual attention , slower 4.1.There are some limitations of this study worth noting. Although we recruited the patients by our outpatient department and the questionnaire results indeed suggest significant differences in ADHD traits and reflect characteristic sensory aberrancies that have shown to occur commonly in ADHD, it is possible that comorbidities may confound our findings. Further, we cannot rule out a possible medication influence despite having a wash-out period of at least 24 h. Additionally, the evaluation of the auditory task results might be limited through a ceiling effect, indicated by the fact that 10 of 14 healthy subjects reached the smallest possible frequency interval between two tones after only 40% of trials see .4.2.This is the first study to investigate early audiovisual crossmodal activations in adult ADHD using electrophysiology. The assessed difference in the enhanced auditory crossmodal P200 in subjects with ADHD can be interpreted as a marker for deficient inhibitory processes and more sensory registration, showing that there might be a distribution of attentional resources that participate in poorer unimodal auditory performances. One reason for those involuntary attentional shifts might be lower sensory thresholds that does not benefit subjects with ADHD, but leads to more impairment in their daily life through more inattention and higher distractibility. One potential next step that might help to understand the basic mechanism of impaired sensory processing in ADHD and their impact on symptomatology could be to study the interplay of crossmodal activation and attentional performance in ADHD.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving humans were approved by Kurt Racké, Ethical Committee Faculty of Medicine Bonn. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.MiS: formal analysis, data curation, visualization, writing, and original draft preparation, MaS: conceptualization, formal analysis, project administration, and writing, review, and editing. TG: formal analysis and writing, review, and editing. BA: recruitment and writing, review, and editing. PJ: software and paradigm realization. SL and AP: supervision and writing, review, and editing. All authors contributed to the article and approved the submitted version.This work was supported by the Open Access Publication Fund of the University of Bonn.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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.