Previous neuroimaging studies have described shared and distinct neurobiological mechanisms between autism spectrum disorders (ASDs) and attention-deficit/hyperactivity disorder (ADHD). However, little is known about the similarities and differences in topologically structural connectivity patterns between the two disorders.Diffusion tensor imaging (DTI) and deterministic tractography were used to construct the brain white matter (WM) structural networks of children and adolescents ; 31 had ASD, 34 had ADHD, and 30 were age- and sex-matched typically developing (TD) individuals. Then, graph theoretical analysis was performed to investigate the alterations in the global and node-based properties of the WM structural networks in these groups. Next, measures of ASD traits [Social Responsiveness Scale (SRS)] and ADHD traits  were correlated with the alterations to determine the functional significance of such changes.Ki) of the right amygdala (AMYG.R) and right parahippocampal gyrus (PHG.R) were found in both the ASD and ADHD groups. Also, the ASD and ADHD groups shared four additional hubs, including the left middle temporal gyrus (MTG.L), left superior temporal gyrus (STG.L), left postcentral gyrus (PoCG.L), and right middle frontal gyrus (MFG.R) compared with the TD group. Moreover, the ASD and ADHD groups exhibited no significant differences regarding regional connectivity characteristics. Second, the ADHD group showed significantly increased nodal betweenness centrality (Bi) of the left hippocampus (HIP.L) compared with the ASD group; also, compared with the ADHD group, the ASD group lacked the left anterior cingulate gyrus (ACG.L) as a hub. Last, decreased nodal efficiency  of the AMYG.R, Ki of the AMYG.R, and Ki of the PHG.R were associated with higher SRS scores in the ASD group. Decreased Ki of the PHG.R was associated with higher SRS scores in the full sample, whereas decreased Bi of the PHG.R was associated with lower oppositional defiance subscale scores of the SNAP-IV in the ADHD group, and decreased Bi of the HIP.L was associated with lower inattention subscale scores of the SNAP-IV in the full sample.First, there were no significant differences in the global network properties among the three groups; moreover, compared with that of the TD group, nodal degree (From the perspective of the topological properties of brain WM structural networks, ADHD and ASD have both shared and distinct features. More interestingly, some shared and distinct topological properties of WM structures are related to the core symptoms of these disorders. Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are both neurodevelopmental disorders that manifest early in life. ASD is defined by core symptoms of persistent and pervasive deficits in social communication and interaction along with repetitive behavioral patterns and restricted interests or activities. ADHD is characterized by developmentally inappropriate levels of inattention, impulsivity, and hyperactivity .Aside from distinctive features, overlaps in the clinical symptoms and the genetic traits of ASD and ADHD are well documented. First, in terms of clinical phenotypes, 30 to 80% of all ASD children met the diagnostic criteria for ADHD, and 20 to 50% of children diagnosed with ADHD also met the diagnostic criteria for ASD . Second,n = 200) of school-aged children with ASD and ADHD compared with typically developing (TD) controls and found that decreased fractional anisotropy (FA) within the splenium of the corpus callosum was common among the three groups  measuring functional connectivity of the brain network also confirmed shared dysfunctional connectivity in the default mode network, dorsal attention network, and salience network of both ASD and ADHD patients between 7 and 21 years of age  data revealed ASD-specific cortical thickness differences in the frontal cortex of adult patients and ADHD-specific subcortical differences in children and adolescents; notably, the researchers did not find shared differences across the two disorders . A diffue groups . Evidencs of age . Interess of age . InconsiIndependent studies of ADHD and ASD have increasingly emphasized the role of dysconnectivity in large-scale networks in both disorders . As the Previous network studies have mainly focused on functional networks, while functional connectivity opens the door to the analysis of brain networks. We should not ignore that functional connections need structural support to make sense. DTI can help us map the structural connectivity between gray matter (GM) regions using white matter (WM) tractography, providing an avenue to probe structurally interconnected brain networks .Accordingly, in the present study, we analyzed DTI data from 95 children and adolescents aged 6 to 16 years with ASD, with ADHD, and who were TD to map their WM structural networks. First, we investigated the alterations in the global and regional properties of the WM structural networks in these groups. Second, we examined the relationship between the alterations and measures of ASD traits, as well as ADHD traits, to determine the functional significance of such changes. To our knowledge, no previous studies have directly contrasted the global and regional properties of WM structural networks in individuals with ASD, individuals with ADHD, and TD controls. Our work might be an important supplement to previous studies.Diagnostic and Statistical Manual of Mental Disorders, Fourth Text Revision (DSM-IV-TR) diagnostic criteria supported by parent interviews, direct observations, available teacher forms, and prior records. ASD diagnosis was supported by standardized clinical assessments, including the Autism Diagnostic Observation Scale . ADHD traits were indexed by Swanson, Nolan, and Pelham-IV (SNAP-IV)  scores of all participants were evaluated using the Wechsler Intelligence Scale for Children-IV , and thoon Scale  and Aution Scale . TD conton Scale , which iSNAP-IV) , which ib = 1,000 s/mm2. The thickness of each slice was 2.5 mm without a gap. The sequence parameters for the DTI were as follows: TE = 104 ms, TR = 9,000 ms, FOV = 230 × 230 mm2, and acquisition matrix = 128 × 128. The total DTI scanning time was 5.1 min. Before preprocessing, all the structural images were checked for artifacts. DWI image data were screened for subject motion and common artifacts related to diffusion sequences using PANDA  with a birdcage gradient head coil. The head of each participant was gently restrained with foam cushions to avoid the generation of motion artifacts during the scan. High-resolution T1-weighted images were obtained using a three-dimensional spoiled gradient recalled pulse sequence with the following scanning parameters: repetition time (TR) = 2,530 ms, echo time (TE) = 3.34 ms, flip angle = 7°, inversion time = 1,100 ms, field of view (FOV) = 256 × 256 mm, matrix = 256 × 159, slice thickness = 1.33 mm, and total scanning time = 8.7 min. Each participant’s head was positioned parallel to the anterior commissure–posterior commissure plane. DTI was performed with single-shot echo planar imaging sequences with diffusion gradients applied in 30 non-collinear directions and ng PANDA , a pipelng PANDA .Node definition is an important step in brain network construction as the node is a vital element of a network . TypicalT = 3) for the number of fiber bundles, meaning two regions were considered structurally connected if at least three fibers with two endpoints were located in these two regions. Such a threshold selection was reported to reduce the risk of false-positive connections due to noise or limitations in deterministic tractography , clustering coefficient (Cp), normalized shortest path length (λ), normalized clustering coefficient (γ), small-worldness σ (σ = λ/γ), local efficiency (Eloc), and global efficiency (Eglob) of the whole brain network were calculated to quantify the global network architecture. Also, we computed the local efficiency of node i , nodal degree of node i (Ki), and betweenness centrality of node i (Bi) to determine the nodal  characteristics of the networks. In addition, the normalized betweenness (bi) was used to identify the most central nodes (hubs) of the networks. These measures are detailed in the article by Lp is the average shortest path length between the nodes that quantifies the ability of a network to propagate parallel information, and Cp represents the fraction of the node’s neighbors that are also neighbors of each other, λ = Lpreal/Lprand, γ = Cpreal/Cprand, where Lprand and Cprand are the mean shortest path length and the mean clustering coefficient of 100 matched random networks, respectively. Eloc is the mean of the local efficiency of all the nodes in the graph. Eglob is the average inverse shortest path length and can be used to estimate the efficiency with which brain regions communicate. Enodal represents the regional efficiency of a node. The degree Ki is defined as the number of connections to that node, and highly connected nodes have a large degree. Bi is defined as the fraction of all the shortest paths in the network that pass through a given node.We investigated the topological properties of the WM structural networks at the global and nodal levels. Characteristic path length , followed by Bonferroni post hoc analysis. Effect size ηp2 is reported for one-way ANOVA tests, with 0.01, 0.06, and 0.14 representing small, medium, and large effects, respectively.The statistics of demographic and clinical characteristics were conducted using Statistical Product and Service Solutions . Normality of the distributions was assessed by the Shapiro–Wilk test. Categorical variables (sex) were investigated with χbi of all 90 regions for each subject and then calculated the mean value of the bi for each region according to the groups. If bi was greater than 1.5 times the average betweenness  of the network, the nodes were considered to be pivotal nodes .To identify the hub regions of the networks between groups, we first calculated the F test on every connectivity value to compare the structural connectivity differences between the ASD, ADHD, and TD groups. We set the primary threshold at p = 0.001 for the resulting F statistic matrix (based on a height threshold of F = 3.2 to stringently control for type I errors). Next, the data across groups were randomized 5,000 times to obtain the reference cluster distribution. We used the maximum number of connections across all clusters to form the reference distribution for each randomization; cluster scores exceeding the 95th percentile were considered significant (p < 0.05). For post hoc paired comparisons , the procedure was similar.Network-based statistics (NBS)  is a nonpost hoc analyses examined Pearson correlations in the patient groups to reveal the relationships between altered regional properties and ASD traits, as well as between altered regional properties and ADHD traits.Additionally, Pearson correlation analysis, performed in SPSS, was used to examine correlations in the full sample, and F = 4.979, p = 0.009, ηp2 = 0.098) . The ANOVAs showed significant group effects on SRS total scores  and SNAP-IV subscale scores, including inattention , hyperactivity , and oppositional defiance . Specifically, for pairwise comparisons, the ASD group showed greater social deficits than the ADHD and TD groups; moreover, the ADHD group showed more severe ADHD symptoms than the ASD and TD groups  of the global network for each participant and showed the mean values of these properties of the three groups. Analyses of covariance (ANCOVAs) on the global network properties showed no significant group effects of all the global topological properties  among the three groups.Based on the constructed networks, we calculated the topological properties , right amygdala (AMYG.R), left hippocampus (HIP.L), and right parahippocampal gyrus (PHG.R)], and subcortical [the right insula (INS.R)] cortices . Only one region  showed significant group differences, with a higher Bi observed in the ADHD group than in the ASD and TD groups  (eficits) .Bi of each node in all networks. In total, 23 hub regions were the same for all of the groups, including 10 regions of the association cortex , four regions of subcortical structures , four paralimbic regions , and five primary regions . The common hubs identified for all of the groups were predominantly distributed in the association cortices. Specially, the left anterior cingulate gyrus (ACG.L) was identified as a hub in the ADHD and TD groups but not in the ASD group, and both the ASD and ADHD groups exhibited four additional hubs  compared with TD controls . The involved nodal regions were the PreCG.L, left middle frontal gyrus (MFG.L), SFGdor.L, left inferior frontal gyrus, opercular part (IFGoperc.L), left rolandic operculum (ROL.L), left middle occipital gyrus (MOG.L), left paracentral lobule (PCL.L), PUT.L, and CAU.L. However, no significant differences were found with respect to connected components between the ASD and ADHD groups , and Bi of the HIP.L was significantly correlated with inattention subscale scores of the SNAP-IV . In the ASD group, Enodal of the AMYG.R was significantly correlated with SRS scores , and Ki of the PHG.R was significantly correlated with SRS scores . In the ADHD group, Bi of the PHG.R was significantly correlated with oppositional defiance subscale scores of the SNAP-IV   .The present study compared the global and regional properties of the WM structural networks in children and adolescents with ASD, ADHD, and TD controls; the findings suggest shared and distinct features underlying neurobiological mechanisms in ASD and ADHD children and adolescents from a network perspective.Cp and Lp did not significantly differ between children and adolescents with ASD and TD controls  in the full sample; these findings suggest the unique role of the HIP.L in the pathogenesis of ADHD.Numerous prior studies have addressed the relationship between the amygdala and autistic symptoms in ASD patients . Our cor regions . NotablyBi of the HIP.L and hubness of the ACG.L might be valuable markers for distinguishing ASD from ADHD. While disorder-specific abnormalities are present, overlapping results are consistent with the growing clinical, molecular, and neuroimaging evidence of commonalities  properties, providing comprehensive evidence for both shared and distinct underlying mechanisms in ASD and ADHD children and adolescents. Third, identifying and validating the similarities and differences of brain-based endophenotypes in the two disorders may be beneficial for personalized medicine (In conclusion, our findings demonstrate that nalities . In the medicine .There are several limitations that should be addressed. First, as mentioned previously, ASD and ADHD are neurodevelopmental disorders with overlapping clinical presentations , while iThe raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the Medical Ethics Committees of the Nanjing Brain Hospital Affiliated to Nanjing Medical University. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.XK designed the study and revised the draft. LQ, YL, YaW, YuW, XC, CL, XC, and GJ collected and analyzed the data. LQ wrote the first draft of the manuscript. All authors contributed to and approved the final manuscript.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.


Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder that affects the competence of academic performance and social wellness in children and adults. The causes of ADHD are unclear. Both genetic and environmental factors contribute to the development of ADHD. The behavioral impairments in ADHD are associated with epigenetic changes in genes that are important for neurodevelopment. Among environmental causes of ADHD, the neurotoxin methylmercury (MeHg) is associated with an increased risk for ADHD. Developing children are susceptible to neurotoxic effects of prenatal MeHg exposure. Human epidemiology studies have shown that prenatal MeHg exposure could invoke epigenetic changes in genes that are involved in ADHD. In addition, the pathogenesis of ADHD involves dopaminergic system, which is a target of developmental MeHg exposure. MeHg-induced alterations in the dopaminergic system have a profound impact on behavioral functions in adults. As a trace level of MeHg (around nM) can induce long-lasting behavioral alterations, potential mechanisms of MeHg-induced functional changes in the dopaminergic system may involve epigenetic mechanisms. Here, we review the relevant evidence on developmental MeHg exposures and the risk for ADHD. We also point out research gaps in understanding environmental causes of ADHD. Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder that affects children’s learning ability, social behavior and emotional wellness . ChildreCurrently, clinical management of ADHD relies on stimulants including methylphenidate and amphetamine; however, their efficacy is a subject for debate. For example, a recent review pointed out that there is a great uncertainty regarding the effect of long-term treatment with the dopamine agonist amphetamine in adults with ADHD . FurtherMethylmercury (MeHg) is an organic form of mercury species that naturally occurs in human environment . Human eRecent research suggests that environmental MeHg exposure may contribute to the development of ADHD . HoweverThe development of ADHD involves structural and functional alterations in the developing brain. These alterations are believed to be outcomes of deviation of ‘normal’ brain development . The cliDopaminergic neurotransmission is involved in brain functions including reward system, motor control and emotion regulation . The effdat-1 gene; however, a possible change in methylation levels in several individual sites of the dat-1 region was proposed [dat-1 epigenetics in the prognosis of ADHD was also demonstrated in a clinical study showing that the methylation status in the promoter region of dat-1 can predict the treatment outcomes of ADHD with methylphenidate, particularly on oppositional and hyperactive-impulsive symptoms [dat-1 in ADHD, it is showed that the methylation level in the dat-1 gene significantly changed in ADHD patients, which was not only related to the severity of ADHD symptoms but also had a predictive value for clinical prognosis [Studies have shown that the expression of DATs is epigenetically regulated, which is linked to the risk for ADHD . For exaproposed . The impsymptoms . Furtherrognosis .The neurotoxicity of MeHg is mediated via several well-established mechanisms including oxidative stress, mitochondria toxicity and disruption of calcium homeostasis . HoweverCaenorhabditis elegans was changed long after cessation of MeHg exposure, suggesting that mechanisms other than calcium signaling are also involved in MeHg-induced alterations in dopaminergic neurotransmission [in vitro study, it was shown that MeHg exposure (1 nM) can repress the expression of TH. The study further investigated methylation status at the promoter region of the TH gene and showed that tri-methylation of histone H3 lysine 27 was significantly increased following MeHg exposure (1 nM) [C. elegans study showing that reduced swimming speeds following MeHg exposure were modulated by the homolog of the TH gene [MeHg exposure can alter dopamine-mediated neurotransmission , which csmission . Given tsmission , 53, 54,e (1 nM) . The imp TH gene . Further TH gene .The importance of dopamine metabolism in MeHg’s neurotoxicity and its implication in ADHD was also supported by behavioral studies in rodents. A study in female rats showed that their behavioral sensitivity to d-amphetamine was increased following developmental exposure to MeHg . In anotDeveloping brains are especially sensitive to MeHg toxicity. Several large cohort studies investigated prenatal and postnatal MeHg exposures and neurodevelopmental outcomes in children. In the Seychelles Child Development Study, although the study did not reveal any significant adverse associations between MeHg exposure and a series of neurobehavioral outcomes , signifiMeHg exposure has been described as a risk factor for ADHD, given that the developing nervous system is most sensitive to the neurotoxicity of MeHg ; indeed,in vivo and its significance in behavioral outputs of ADHD. Apparently, a mechanistic understanding of MeHg exposure through eating fish and the risk for ADHD may suffice to generate a new hypothesis for future investigations on epigenetic factors that contribute to environmental influences on brain development [In addition, neuronal differentiation and migration in the developing brain require numerous epigenetic modifications to ensure proper regulation of gene expressions and integrated function . Epigeneelopment , 81. Furelopment .BDNF), glucocorticoid receptor (NR3C1) and glutamate receptor subunit NR2B (GRIN2B), all of which had been shown to be involved in the development of ADHD in other independent studies [NR3C1 associated with prenatal mercury exposure were also reported in another human study showing that the methylation level of NR3C1 was increased in those with an average mercury level of 0.17 µg/g compared with the reference mercury level of 0.01 µg/g [Studies on human epigenetic alterations following MeHg exposure used epigenetic markers in blood cells or saliva to infer possible epigenetic influences of MeHg on the brain , 83, 84. studies . Increas.01 µg/g .et al. showed that prenatal mercury exposure increased the risk for poorer quality of movement, poorer self-regulation and increased signs of physiologic stress [TCERG1L), a possible factor involved in ADHD [TCERG1L is a direct effect of mercury.It has been recognized that perinatal MeHg exposure adversely affects neurobehavior development . A birthc stress . In addi in ADHD . BecauseBDNF modified the association between mercury and behaviors of ADHD. The sex-specific effect on DNA methylation levels following prenatal mercury exposure was also reported in a cohort study in Japan [HDHD1) within the transcriptional regulation site was only noted in boys. Furthermore, the temporal changes of epigenetic effects related to prenatal mercury exposure were shown in a study on prenatal mercury exposure and neurocognitive effects [TCEANC2) was associated with cord blood mercury levels [TCEANC2 gene is a known risk factor for sporadic Parkinson’s disease [A recent new study carried out in Spain revealed that postnatal mercury exposure was associated with an increased risk for ADHD. The study also showed that boys were more vulnerable than girls to these effects . The stuin Japan . Specifi effects . The stu effects . The DNA effects . Anothery levels . The TCE disease ; howeverin utero exposure to arsenic [As mentioned before, the effects of prenatal mercury exposure on the epigenetic markers can be modulated by nutritional factors as well as other toxins. For example, the association between DNA methylation level and prenatal mercury was modified by  arsenic . Another arsenic , namely  arsenic . In addi arsenic . Studies arsenic . Consequ arsenic , 101, wh arsenic .ADHD is one of the most common neurodevelopmental disorders. Although the pathogenesis of ADHD is not fully understood, exposure to environmental contaminants is associated with the disease. Current evidence suggests that epigenetic regulatory mechanisms such as DNA methylation are a target of environmental MeHg exposure. The investigations on the link between DNA methylation and prenatal MeHg exposure have shown that MeHg exposure may be associated with the pathogenesis of ADHD. Although MeHg exposure is associated with ADHD, the behavioral impacts of MeHg-induced epigenetic alterations warrant further investigations. Furthermore, MeHg exposure may be associated with the epigenetic regulation of genes involved in dopamine metabolism. Developmental MeHg exposure alters the pharmacological effects of dopamine agonists through the interaction with dopaminergic system. These studies provide important clues on how developmental MeHg exposure alters brain functions and its effects on the epigenetic control of genes associated with dopaminergic neurotransmission. However, further studies on the role of MeHg exposure in epigenetic alterations are needed to better understand the association between MeHg and ADHD.The multifactorial nature of the causes for ADHD suggests that MeHg exposure can significantly alter neurobehavioral outcomes in animal models. As epigenetic marker is particularly susceptible to environmental factors, further investigations on the epigenetic effects of MeHg will shed new insights into the mechanisms of environmental causes of ADHD.


Patients with attention-deficit hyperactivity disorder (ADHD) manifest symptoms of hyperactivity, impulsivity, and/or inattention. ADHD medications available in Japan are limited compared with those in Western countries. Prescribing status has not been sufficiently evaluated in clinical settings in Japan. This study investigated the current use of ADHD medications and characteristics of patients who received multiple ADHD medications in a clinical setting in Japan.Study participants were those who visited the Department of Child and Adolescent Psychiatry, Kohnodai Hospital between April 2015 and March 2020. We investigated patients who received osmotic-controlled release oral delivery system methylphenidate, atomoxetine, or guanfacine. A retrospective case–control design was used to evaluate the characteristics of patients who received multiple ADHD medications. Patients who were given three ADHD medications were defined as the case group. Randomly sampled sex- and age-matched patients diagnosed with ADHD were defined as the control group. We compared data for child-to-parent violence, antisocial behavior, suicide attempt or self-harm, abuse history, refusal to attend school, and two psychological rating scales .Among the 878 patients who were prescribed any ADHD medications, 43 (4.9%) received three ADHD medications. Logistic regression revealed that children with severe ADHD symptoms, autistic characteristics, or tendency of child-to-parent violence were more likely to have been prescribed three medications during their treatment.Our findings suggest the approach to prevent the use of multiple ADHD medications. A prospective study to investigate the causality between prescribing status and clinical characteristics is warranted. Patients with attention-deficit hyperactivity disorder (ADHD) manifest symptoms of hyperactivity, impulsivity, and/or inattention in childhood. The symptoms affect cognitive, academic, behavioral, emotional, and social functioning . The estTreatment of ADHD involves pharmacotherapy, psychosocial treatment, or a combination of both . CurrentThe most recent Japanese guideline was published in 2016, which listed only OROS methylphenidate and atomoxetine as ADHD medications . The mosThis study investigated the current use of ADHD medications and characteristics of patients who received multiple ADHD medications in a clinical setting in Japan. It is inappropriate to simultaneously use all three medications for the potential risks of side effects. However, it seems reasonable to use three medications sequentially in certain conditions. The comorbidity of ADHD and autism spectrum disorder (ASD) is approximately 30%–50% , 10. Methttp://www.ncgmkohnodai.go.jp/subject/100/optout.html). The study participants included patients who visited the Department of Child and Adolescent Psychiatry, Kohnodai Hospital, National Center for Global Health and Medicine between April 2015 and March 2020. We investigated patients with ADHD who received OROS methylphenidate, atomoxetine, or guanfacine. In Japan, only patients with ADHD diagnosis can receive ADHD medication, regardless of whether it is a primary or secondary diagnosis, and with or without comorbidities. We examined the proportion of patients who had been prescribed for ≥180 days to determine the response rate of each drug treatment based on previous studies Reviewers' comments:Reviewer's Responses to QuestionsComments to the Author1. Is the manuscript technically sound, and do the data support the conclusions?The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: PartlyReviewer #2: PartlyReviewer #3: Yes**********2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: N/AReviewer #2: N/AReviewer #3: Yes**********3. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.The Reviewer #1: YesReviewer #2: NoReviewer #3: Yes**********4. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #2: YesReviewer #3: No**********5. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: The authors investigated pediatric ADHD patients who experienced osmotic-controlled release oral delivery system methylphenidate, atomoxetine, or guanfacine. A retrospective case–control design was used to evaluate the characteristics of patients who experienced multiple ADHD drugs.The authors stated that logistic regression revealed that children with severe ADHD symptoms, autistic characteristics, or tendency of child-to-parent violence were more likely to have been prescribed three drugs during their treatment.The strength of this study is the first study to evaluate the clinical characteristics of child and adolescent psychiatric outpatients prescribed three drugs  in Japan.However I have a few questions.#1 The authors stated that the clinical characteristics associated with the use of three drugs were severe ADHD symptoms, autistic characteristics, or a tendency of child-to-parent violence at the initial consultation.How do you assess these autistic characteristics, or a tendency of child-to-parent violence?I think that these symptoms might be caused by the symptoms of Post Traumatic Stress Disorder.#2 Related to #1, How do you assess the abuse types?Reviewer #2: Thank you very much for giving me an opportunity to review this article.Because the reason to choose certain prescription pattern is not clear, such kind of data finding is interesting for many clinicians. The sample size is large enough.However, the following points weaken the results:1) This study is done only in medical facility. Then, the result only reflects prescription pattern of small number of psychiatrists.2) Medical information (such as the history of being abused) are based on only medical records.3) Samples are collected in 2015-2020. Among this period, some new anti-ADHD agents are marketed.This changed the prescription status. Authors must address why authors can collapse these data into the same datasets.In addition, authors should examine the following points.The PDF of Registry Study of this article is written in Japanese. It seems an opt-out.Authors must change tables and figures. They are unclear.Reviewer #3: It was a pleasure to go through your valuable work, examining the current trend in ADHD medication use in Japan and factors related to multidrug therapy in children. I would like to clarify a few points for further improvement in the presentation of your material.1. Please reconsider the title of the manuscript, since it is somehow ambiguous.2. In the Abstract at the Conclusion section, you stated that your findings highlighted the approach to prevent multiple medications in children with ADHD. I am afraid that while you talked about the characteristics and possible reasons behind the multiple medications, I could not find notions regarding the approach/ways to avoid the multiple medications in the Discussion.3. The term prescription status sounds confusing. It refers to a status of a patient prescription . Similarly, prescribing status means if a physician or pharmacist is currently prescribing medications or not. I think you are discussing the current medication use and it would be better to re-check the use of those terms with the English editing service. Moreover, could you also check the term patients who experienced multiple ADHD drugs? I reckon patients who were multiply medicated or who received multiple ADHD medications or patients who were treated with all three ADHD medications is more appropriate. The word experience highlights the meaning of subjective experience of a person taking medication.4. In the final paragraph of the Introduction, you state that although it is not appropriate to simultaneously prescribe all three ADHD medications, a sequential trial of those is reasonable. You had better clarify why it is not appropriate to simultaneously prescribe all three ADHD medications.5. In the final paragraph of the Introduction, it is better to present the argument of ADHD-ASD co-occurrence/ADHD medication use in ASD (i.e. reasons behind your hypothesis) before stating your hypothesis.6. In the Method, the inclusion and exclusion criteria are not presented clearly enough. What was the targeted age range (the minimum age)? Did you include patients who were on any of the three ADHD medications continuously for more than 180 days regardless of their diagnoses? What were the diagnoses of 878 participants including comorbidity? As you mentioned in the Introduction, ADHD and ASD co-occur to a significant degree. Did you exclude or include (for the whole sample and the case and control groups) individuals with ASD and if so how did you make the diagnosis (like using the ADOS-2 or ADI-R)?Further, could you describe what you mean by autistic characteristics (Does this mean patients presenting some ASD symptoms but without ASD diagnosis or include those with ASD diagnosis)? In addition, how did you diagnose ADHD ? More details for the description of the diagnostic process are preferable.7. You should describe the medication dosage of the two groups.8. For the two-group comparison, I would like to clarify that it is comparing ADHD diagnosed children with a use of no more than 2 ADHD drugs  versus ADHD diagnosed children who were treated with all three ADHD medications. Were they diagnosed only with ADHD without any comorbidity including ASD/depression/anxiety disorders?9. For those who used more than 2 medications, did they switch medications due to insufficient treatment effects or was the switch due to adverse effects?10. You excluded patients with moderate to severe intellectual disability. How did you assess the intelligence?11. How did you assess the child-to-parent violence, anti-social behaviors, or abuse? Was it based on a parent report or asked to a patient in the clinician interview? It is possible that reports on these sensitive episodes, especially abuse, are different between those made by parents and those by children and I am wondering how and from whom you extracted this information.12. Is TABS applied to a general population to assess ASD symptoms like the Autism Spectrum Quotient or only to assess current ASD symptoms in those diagnosed with ASD? Is there any cut-off? It may be helpful to explain it in detail as it is used only in Japan.13. In the Method about the statistical analysis, the sentences for deciding on the explanatory variables for the univariate and multivariate analyses are not clear.14. In the Result, the age ranged from 10 to 15 years old (written below Table1), however the mean age is 8.55. How is this possible?15. In the Discussion Page 9 Line 19, approximately is not spelled right.16. In the Discussion Page 10 Line 12-18, you talk about the relationship between depression and violence and its possibility underlying the insufficient response to a single ADHD medication. I understand the importance but did you assess the depression/anxiety in the study or did you include those with ADHD comorbid with depression? Did any of the participants used anti-depressives along with ADHD medications? It seems a little leap to state the association with depression without mentioning such information.**********what does this mean?). If published, this will include your full peer review and any attached files.6. PLOS authors have the option to publish the peer review history of their article  digital diagnostic tool,  23 Apr 2021Thank you for reviewing our manuscript and providing us your valuable advice despite your busy schedules.We addressed all points raised by the academic editor and reviewers. In addition, to better facilitate the readers’ understanding, we modified some parts of the manuscript that were not pointed out by the reviewers. After these changes, scientific and academic editing services were used to re-edit the revised version of our manuscript before resubmission.We would appreciate it if you could let us know again whether there are still parts that need further explanation or should be corrected.AttachmentResponse to Reviewers_210417.docxSubmitted filename: Click here for additional data file. 17 May 2021Status of attention-deficit hyperactivity disorder (ADHD) drugs and clinical characteristics of child and adolescent psychiatric outpatients prescribed multiple ADHD drugs in JapanPONE-D-21-04661R1Dear Dr. Usami,We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.Within one week, you’ll receive an e-mail detailing the required amendments. 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For more information, please contact Kind regards,Kenji Hashimoto, PhDSection EditorPLOS ONEAdditional Editor Comments :Reviewers' comments:Reviewer's Responses to QuestionsComments to the Author1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.Reviewer #1: All comments have been addressedReviewer #2: (No Response)Reviewer #3: (No Response)**********2. Is the manuscript technically sound, and do the data support the conclusions?The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: YesReviewer #2: NoReviewer #3: Yes**********3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: I Don't KnowReviewer #2: NoReviewer #3: Yes**********4. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.The Reviewer #1: YesReviewer #2: NoReviewer #3: Yes**********5. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #2: YesReviewer #3: Yes**********6. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: Thank you for your polite reply.Response to Reviewer #1I have a few questions. #1 The authors stated that the clinical characteristics associated with the use of three drugs were severe ADHD symptoms, autistic characteristics, or a tendency of child-to-parent violence at the initial consultation. How do you assess these autistic characteristics, or a tendency of child-to-parent violence? I think that these symptoms might be caused by the symptoms of Post Traumatic Stress Disorder. #2 Related to #1, How do you assess the abuse types?As per Reviewer #1’s comments, we added a description in the Recruitment and participants. Readers’ misunderstandings or questions can be avoided by explaining in detail what we have conducted at our facility.REVISEDPsychologists and psychiatrists together established the initial interview forms, which included demographic and clinical characteristics. Consultation included the developmental history from caretakers, child observations, and school record reviews. TABS and ADHD-RS were then constructed. Psychiatrists specializing in child and adolescent psychiatry evaluated clinical findings, including psychological rating scales and diagnosed all patients according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition [1]. Meetings to discuss the psychopathology, symptoms, diagnosis, and possibility of abuse were conducted as needed. There were few patients Patients with moderate-to-severe intellectual disability according to the DSM-5, organic brain disease, drug-induced psychiatric disease, traumatic brain injury, and genetic syndromes because they were referred to other medical institutions when they call for an appointment in and were excluded from this study.In this study, child the TABS was filled out by caretakers and then psychiatrists checked the items in a medical interview. The TABS score indicated the strength of autistic characteristics, and the ADHS-RS indicated the strength of ADHD symptoms as well. Child-to-parent violence meant physical violence against parents living together or damage to property. The in-charge psychiatrists interviewed patients and parents individually, as needed, to evaluate for child-to-parent violence. After hearing both sides of the story, psychiatrists decided whether the patients’ behavior was indicative of child-to-parent violence. We considered patients as having “antisocial behavior” when patients engaged in illegal activities, such as smoking, drinking, illegal drug use, shoplifting, or causing injury to others. In Japan, smoking and drinking are legal after the age of 20 years. In many cases, the evaluation of antisocial behavior would be based on information from parents. “Abuse experience” included sexual abuse, physical abuse, psychological abuse, and neglect. Our department worked with local child protection services. Hence, information about abused children was often available before the initial consultation. In addition, the in-charge psychiatrists interviewed parents and patients separately to identify abused children as needed. These efforts were made to immediately identify abused children and to prevent missed abused children. Refusal to attend school was defined as absence from school for ≥30 days owing to any psychological, emotional, physical, or social reasons [16].Reviewer #2: Authors agree to my comments, however, they only add description to limitations. These points substantially lost the significance of this article. Therefore, I think that this article does not reach the standard for publication of PLOS ONE.Reviewer #3: (No Response)**********what does this mean?). If published, this will include your full peer review and any attached files.7. PLOS authors have the option to publish the peer review history of their article  medications and clinical characteristics of child and adolescent psychiatric outpatients prescribed multiple ADHD medications in Japan Dear Dr. Usami:I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. onepress@plos.org.If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact plosone@plos.org. If we can help with anything else, please email us at Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staffon behalf ofProf. Kenji Hashimoto Section EditorPLOS ONE


In addition, in contrast to ADHD in childhood, ADHD in adulthood is difficult to diagnose due to mixed psychopathologies. This study aimed to determine whether it is possible to predict ADHD symptoms in adults using the Minnesota Multiphasic Personality Inventory-2 (MMPI-2) with machine learning (ML) techniques; (2) Methods: Data collected from 5726 college students were analyzed. The MMPI-2-Restructured Form (MMPI-2-RF) was used, and ADHD symptoms in adults were evaluated using the Attention-Deficit/Hyperactivity Disorder Self-Report Scale (ASRS). For statistical analysis, three ML algorithms were used, i.e., K-nearest neighbors (KNN), linear discriminant analysis (LDA), and random forest, with the ASRS evaluation result as the dependent variable and the 50 MMPI-2-RF scales as predictors; (3) Results: When the KNN, LDA, and random forest techniques were applied, the accuracy was 93.1%, 91.2%, and 93.6%, respectively, and the area under the curve (AUC) was 0.722, 0.806, and 0.790, respectively. The AUC of the LDA method was the largest, with an excellent level of diagnostic accuracy; (4) Conclusions: ML using the MMPI-2 in a large group could provide reliable accuracy in screening for adult ADHD. Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsivity . Around ADHD has been regarded as a childhood-specific disorder for a long time because it is thought that ADHD symptoms improve as children develop ; howeverAdults with ADHD may have difficulties in interpersonal relationships, and it is known that they face problems at work, such as the inability to organize and process work efficiently ,12. ADHDThe number of adults diagnosed with ADHD in the United States has steadily increased over the past 20 years ,25. The Currently, the Adult ADHD Self-Report Scale (ASRS) developed by the World Health Organization can be used to screen for adult ADHD. It is a self-reported scale consisting of 18 items suitable for adulthood based on the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) diagnostic criteria. It has adequate sensitivity (68.7%), excellent specificity (99.5%), and excellent total classification accuracy (97.9%) . HoweverThere have been efforts to use the Minnesota Multiphasic Personality Inventory-2 (MMPI-2) as a detection tool for exaggerated or hidden ADHD ,33. The Machine learning (ML) is defined as a computational strategy that automatically determines methods and parameters to arrive at an optimal solution to a problem . A machiThis study aimed to differentiate risk groups with significant adult ADHD symptoms by applying the latest ML algorithms using the MMPI-2. In order to compensate for the under-assessment of symptoms due to mixed pathologies and self-reports of adult ADHD by using a valid scale that can detect the examinee’s psychopathology exaggeration and clinical scales to identify personality traits related to psychopathology with the MMPI-2, this study aimed to overcome the problem of screening for adult ADHD.We used part of the dataset of a survey conducted at Kongju National University ,49,50. Tt-score of 80 or more, and a True Response Inconsistency (TRIN) t-score of 80 or more according to the nonclinical scene guidelines in the MMPI-2 manual [For the MMPI-2-RF, a total of 50 scales that can effectively measure the clinical significance of MMPI-2 items were developed and consisted of 8 validity scales and 42 major scales. The validity criteria for the MMPI were not responding to 30 or more non-response questions, a Variable Response Inconsistency (VRIN) 2 manual . In this2 manual .The ASRS is a screening tool consisting of 18 questions about the latest frequency of symptoms based on the DSM-IV criteria symptoms of adult ADHD developed by the World Health Organization ,32. The Each item evaluates the frequency of occurrence of specific symptoms of ADHD over the past 6 months on a 5-point scale, and response options range from 0 to 4 points per question. In our study, the ASRS (+) group was defined as subjects whose total score in the first 9 questions (part 1) or the last 9 questions (part 2) exceeded 21 . In this study, the MMPI-2-RF and ASRS were inputted into the ML algorithm. We used three ML classification methods: K-nearest neighbors (KNN), linear discriminant analysis (LDA), and random forest. Of the ML algorithms, K-nearest neighbors (KNN) algorithm is non-parametric classification method, which collects the existing classes and classifies new classes based on the comparison measure . Linear p values were obtained using a two-sided test, and p < 0.05 was considered statistically significant.Of the total sample, 20% was used as the test dataset, and the remaining 80% were used as the validation dataset; the data were randomly separated into the training dataset and test dataset. To prevent machine learning from overfitting, a validation dataset was added as a verification step. If the model was overfitting, the prediction rate or the error rate would fall, so 20% of the entire dataset was designated as the test dataset and 80% as the validation dataset ,59. All t = 0.428, p = 0.669). The total ASRS score was 4.53 (SD = 0.93) in ASRS (+) group and 4.69 (SD = 1.41) in ASRS (-) group. However, all restructured clinical (RC) scales showed high scores in the ASRS (+) group  were above the cutoff point in the ASRS part 1, and 109 subjects (1.9%) were above the cutoff point in the ASRS part 2. A total of 381 patients (6.6%) were classified into the ASRS (+) group as patients exceeding the cutoff point in part 1 or 2. There were 2851 males (49.8%), and the mean age was 19.8 years (SD = 1.3). There was no significant difference in age between the two groups (+) group .Of the 5726 subjects for ML, 3664 subjects were used as the training dataset, 917 subjects were used as the validation dataset, and 1145 subjects were used as the test dataset. In this study, the prediction accuracy of the KNN, LDA, and random forest methods was 93.1%, 91.2%, and 93.6%, respectively .The AUC of the KNN, LDA, and random forest methods was 0.722 , 0.806 , and 0.790 , respectively. The AUC of the LDA method was the largest, with an excellent level of diagnostic accuracy, and the rest had an acceptable level of diagnostic accuracy .This study aimed to predict and report adult ADHD symptoms using ML with 50 scales of the MMPI-2-RF, the most commonly used self-report evaluation tool. The three ML algorithms showed high accuracy (91.2–93.6%). Although there were differences according to each method, ADHD symptoms in adults were predicted with an excellent level of accuracy. Therefore, using a common screening tool, the MMPI-2-RF, risk factors related to poor concentration, a symptom of ADHD in adults, may be predicted using ML algorithms.In our study, most of the clinical scales were high in the ASRS (+) group. This indicates emotional difficulties in adult ADHD, which can be screened using tools that measure existing psychopathology. Although several emotional difficulties may be attributed to concentration disorders and behavioral symptoms, a general increase in psychopathology symptoms is not specific to adult ADHD.A major difficulty in screening for adult ADHD is that it often has multiple comorbidities and coexistence pathologies . These sIn particular, it is important to differentiate the diagnoses of various mental disorders in ADHD including adult ADHD; for this purpose, discrimination studies through ML are being conducted ,55,56,57However, ML has the disadvantage of not being able to accurately describe the relationship between input and output ; thus, iThis study has some limitations. First, the results may not be representative of the entire population as the survey was conducted at one university. In particular, age homogeneity may limit the applicability of the results. Second, the study consisting of a self-reported questionnaire on adult ADHD symptoms in a non-clinical group lacked clinical diagnosis. In addition, there was no information on coexisting diseases or psychiatric treatment history. Considering that this was a retrospective analysis using data in a large university subjects, it was difficult to obtain the relevant information. In the future, the findings will need to be confirmed through follow-up studies that continuously evaluate the symptoms of ADHD in various populations, including clinical evaluation and analysis . In addition, this study selected adult ADHD using KNN, LDA, and random forest among machine learning techniques based on clinical theory, but we will suggest extended techniques that use various machine learning classification techniques .The strength of this study is that it is a large-scale, multi-faceted analysis of the same group of college students. In particular, the limitations of self-report tests were offset using the valid scale of the MMPI-2-RF. In the future, it may be possible to evaluate adult ADHD symptoms in a setting where only the MMPI-2 is used, such as assessment for employment and physical examination for military service.Thus far, studies that discriminate or classify ADHD through ML algorithms have mostly been based on neurological tests  ,68,69. TThe screening of adult ADHD symptoms is not conclusive with only the MMPI-2, and the use of the MMPI-2-RF makes it possible to obtain valid test results for various aspects of psychopathology. If used together with ML, it will be helpful as an auxiliary tool. In the future, if clinical data are added and analyzed for a wider variety of groups, the possibility of using the MMPI-2 in the evaluation of ADHD symptoms in adults is expected to increase.This study demonstrated that ML using the MMPI-2-RF could provide reliable accuracy in classifying and predicting adult ADHD symptoms. This will help clinicians to detect and treat adult ADHD symptoms early in clinical settings.


F  = 4.655, p=0.038). Moreover, a significant correlation was found between working memory and TOM with BM discrimination in an ADHD group . Our findings could suggest that social perception in noisy scenarios may be affected by memory and social cognitive abilities of children with ADHD.Children with attention deficit hyperactivity disorder (ADHD) are prone to peer rejection and disliking due to difficulties in social perception and interaction. To address social perception impairments in ADHD, we examined children with ADHD in a noisy biological motion (BM) direction discrimination paradigm in association with sociocognitive factors including emotion regulation, theory of mind (TOM), and working memory compared to healthy controls. Our results showed that children with ADHD were poorer in discriminating BM direction in noisy environments ( Attention deficit hyperactivity disorder (ADHD) is characterized by multiple deficits in cognitive, behavioral, and psychological domains including emotion regulation , working memory, and higher-order social cognitive processing, such as theory of mind (TOM) –3.Although social cognition impairment is not accounted as a diagnostic criterion for ADHD , impairmDue to the important role of visual processing of body movements or biological motions (BMs) in a dynamic social world , in the Moreover, successfully distinguishing BM may rely on bottom-up integration of signals from basic visual motion perception along with top-down social cognition . In thisIt has long been proposed that individuals with ADHD have deficits in regulating their emotions . There aGiven together, we hypothesized the possible association of deficits in emotion regulation, TOM, and working memory with BM perception impairments in children with ADHD. To examine BM detection, we administered a motion-noise BM paradigm similar to previous studies , 21. In Finally; we aimed to explore the association between BM performance and the mentioned triad of cognitive factors  in order to provide supplemental information about the underlying sociocognitive mechanisms involved in social difficulties in children with ADHD.Twenty-five children with ADHD and twenty-five age and sex-matched TD children  participated in this study. ADHD diagnosis was confirmed utilizing DSM-V  which waParticipants performed all the tasks within the same research laboratory. All task procedures were presented on a 15-inch Glossy Widescreen LCD display with a resolution of 1366 × 768 pixels. BM stimuli were implemented in a dark room while a mild light was emitted from the laptop. Participants were supposed to look at the display and keep their heads unmoving while being seated 65 cm apart from the screen. Before starting the experiment, participants completed two test runs of 10 trials including 10-point light motion at 100 percent coherence and 10 BM tests in light noisy screen, to ensure that they understood the tasks.Observers judged the overall direction of motion while a central and a stationary red color point was appeared. Observers were encouraged to guess the direction when they were not sure about the direction. They were allowed to indicate the direction of motion using their hand. Feedback was not provided after the child's response. The general experiments were run in a two-block order. Each observer completed 30 trials in the BM task and attended in the cognitive assessments' block. The block order varied between individuals and was counterbalanced within and between participant groups.The entire psychophysical testing took approximately 1 hour for each TD child and 2 hours for each child with ADHD to be completed. In fact, children with ADHD required more time to be focused and to rest between blocks.Accuracy of BM perception was tested by presenting noise into a standard point-light BM display of a walking human . Each BMIn order to evaluate the participants' ability and to recognize emotional expressions from the eye region, the electronic version of the RMET was administered . This abThe RMET contains 36 images, and each image remains on the screen until a response from the participant is registered. Each image has four options of different emotions, and the participants are supposed to choose the option which best described the emotional expression of the image. Performance was measured by the proportion of accurate responses to the total images.In order to assess working memory, we administered the Wechsler Intelligence Scale for Children-Forth Edition (WISC-IV). WISC-IV contains four subtests including verbal comprehension index, perceptual reasoning index, working memory index, and processing speed index. The working memory subtests of WISC-IV contain digit span (DS), letter-number sequencing, and arithmetic tests. In the current study, we utilized the DS test in which participants were supposed to hear and then verbally reproduce an increasing number of digit strings  in forward order (DS forward) and backward order (DS backward) .a = 0.79 for reappraisal and 0.73 for suppression) and test-retest reliability  (42).The Emotion Regulation Questionnaire for Children and Adolescents (ERQ-CA)  is a 10-t-test was conducted to examine the association between BM direction discrimination and scores on emotion dysregulation, RMET, and working memory. The p values less than 0.05 were considered as the level of significance. Analyses were performed using SPSS software version 24 .We calculated the percentage of accurate responses in discriminating BM direction for each participant. We performed ANOVA in order to compare the accuracy of responses regarding three levels of noise in BM direction discrimination both within and between groups. The p: 0.24). However, the results of ANOVA indicated significant between-group difference regarding BM direction discrimination in only the moderate noise-to-signal ratios (50% and 75%)  = 4.655, p=0.038). Furthermore, within-group analysis showed that among the ADHD participants, there is no significant difference regarding the three noise-to-signal ratios of BM direction discrimination  = 0.048, p=0.82). Nevertheless, the results in normal participants represented significant differences regarding BM direction discrimination between the very high and moderate noise-to-signal ratios (p=0.001) as well as very high and high ratio (p=0.001)  = 14.097, p=0.001) : 1.42, p=0.001) .t (36) = −5.24, p=0.01).We examined the difference in mean scores of the RMET between ADHD and normal groups (10.47 (4.61) and 16.47 (1.89), respectively). The results represented significant difference in the mean of correct responses in the RMET between two groups (t (36) = −5.082, p=0.001).We measured working memory (DS task) subtests of WISC-IV in which there was a significant difference between scores of two groups (t (36) = −2.767, p=0.009). Although, a significant difference existed between two groups regarding the expressive suppression subset  = −2.37, p=0.024), regarding the cognitive reappraisal subset, there was no significant difference between the ADHD and control groups  = −1.27, p=0.021). Generally, results showed a significantly lower scores in the ADHD group in comparison to the control group . However, no significant association found between scores of the BM task and emotion dysregulation in the ADHD group . Moreover, in the control group, there were significant associations between working memory and BM scores . Neither the RMET nor emotion regulation scores were significantly correlated with the BM task in the control group (Results showed that a significant correlation existed between scores of working memory and RMET with BM discrimination in the ADHD group (ol group .To the best of our knowledge, it is the first study investigating BM detection by using noisy environments in children with ADHD. Our findings represented that in the presence of visual motion noise, the children with ADHD showed poorer performance in moderate ratios of noise in comparison to TD children. One of the possible mechanisms underlying poorer performances of noisy BM perception in children with ADHD might be the existence of deficits in bottom-up brain processing. In other words, top-down brain processing in the BM task is about extracting and recognizing of that particular human action from several numbers of possibilities while bottom-up brain processing is about gathering visual environmental data about the BM features . ConsideThus, one can hypothesize that the poor performance of children with ADHD in the BM task implicates deficits in the bottom-up brain processing or basic motion perception that support discriminating basic features of BM such as direction.Interestingly, children with ADHD showed poorer performance in the BM task only in moderate ratio of noise, while in higher noise ratios, the performance of both TD and ADHD groups decreased similarly. It depicts the fact that when motion noise is high, even children with normal perceptual and cognitive development represent shortfalls in direction discrimination, while in moderate ratios of noises, a TD child with intact basic perceptual brain systems can surpass a child with ADHD in direction discrimination tasks. Difficulties in BM detection have also been observed in other psychiatric disorders such as autism and schizophrenia , 28. IntAs another part of the study, we found the lower scores of emotion regulation, working memory, and RMET in ADHD compared to the TD group. In addition, as a novel finding we showed that performances in the BM task is prominently correlated with performances in working memory and RMET experiments in all participants, particularly the ADHD group. This finding somehow reflects the role of top-down sociocognitive processing in BM perception. There are several investigations representing deficits in working memory and cognitive empathy among individuals with ADHD. For example, Fassbender et al. in an imaging study proposed that children with ADHD demonstrated a reduced working memory task-specific brain activation compared to their peers . FurtherAccording to Baddeley's model, working memory is an essential component for monitoring and modulating entering information by setting the allocation of attention in line with different social and nonsocial behaviors . For exaMoreover, we found association between the RMET and BM score in ADHD but not the TD group. Although there were little data in ADHD, Rice et al. assessed the developmental association between social perception and TOM ability, the two cornerstones of social development in TD children . After cRegarding emotion regulation, our findings showed that children with ADHD significantly were poorer at the expressive suppression subset of emotion regulation than TD children. However, we did not find any prominent association between emotion regulation and BM perception in both TD and ADHD groups. This finding may suggest that although emotion dysregulation is one of the main aspects of ADHD, this aspect may not necessarily contribute to difficulties in social perception and interaction in children with ADHD. It may also be due to the fact that our experiment is mostly related to recognition processes rather than emotional data processes.In sum, our study showed that children with ADHD have problems with discriminating BM direction in a noisy paradigm. This finding could redraw the therapists, teachers, and parents' attention on the role that different noisy environments such as school classes have on the quality of social interactions in children with ADHD. This may highlight the need for specific designs and requirements for a child with ADHD in order to have more effective social activities in different places. Moreover, our investigation represented that TOM and working memory deficits may underlie difficulties in BM perception in children with ADHD. This may help clinicians to provide novel therapeutic interventions to improve social perception and consequently the low quality and small quantity of the friendship in children with ADHD mentioned by previous studies , 44. In


Manihot esculenta Crantz.) has been a vital staple and food security crop in Tanzania for several centuries, and it is likely that its resilience will play a key role in mitigating livelihood insecurities arising from climate change. The sector is dominated by smallholder farmers growing traditional landrace varieties. A recent surge in virus diseases and awareness in the commercial potential of cassava has prompted a drive to disseminate improved varieties in the country. These factors however also threaten the existence of landraces and associated farmer knowledge. It is important that the landraces are conserved and utilized as the adaptive gene complexes they harbor can drive breeding for improved varieties that meet agro-ecological adaptation as well as farmer and consumer needs, thereby improving adoption rates. Here we report on cassava germplasm collection missions and documentation of farmer knowledge in seven zones of Tanzania. A total of 277 unique landraces are identified through high-density genotyping. The large number of landraces is attributable to a mixed clonal/sexual reproductive system in which the soil seed bank and incorporation of seedlings plays an important role. A striking divergence in genetic relationships between the coastal regions and western regions is evident and explained by (i) independent introductions of cassava into the country, (ii) adaptation to prevailing agro-ecological conditions and (iii) farmer selections according to the intended use or market demands. The main uses of cassava with different product profiles are evident, including fresh consumption, flour production, dual purpose incorporating both these uses and longer-term food security. Each of these products have different trait requirements. Individual landraces were not widely distributed across the country with limited farmer-to-farmer diffusion with implications for seed systems.Cassava ( Manihot esculenta Crantz), which originated around the rim of the Amazon Basin [th and 18th centuries. It is likely that this introduction occurred independently from the coast, through the trading ports on the islands of Zanzibar and Pemba, and from the West via Congo and Angola [per capita consumption [The clonally propagated crop cassava , and opportunities for commercialization have fueled efforts to distribute improved cassava varieties. The importance of these improved varieties is recognized for increased productivity and successful commercialization with the concomitant effects on income generation and improved livelihoods [Traditionally, in Tanzania, cassava roots are either consumed fresh  or are processed into flour and consumed as a stiff porridge . Varieties for fresh consumption taste sweet which indicates that they are low in cyanogenic glycosides, a compound that releases toxic hydrogen cyanide when chewed or digested and is associated with bitter cassava varieties . Some swelihoods . Indeed,elihoods  focus onet al. [Unfortunately, Tanzanian landraces and their associated farmer knowledge are seriously under-represented in national and international germplasm collections ,22. Tanzet al. .As a first step to conserve and characterize Tanzanian cassava landraces and farmer associated knowledge, germplasm collection missions were conducted, and knowledge documented. All landraces were genotyped to identify duplicates and a fingerprint obtained for future tracking purposes. Here we report on the collection missions, diversity of landraces and their associated farmer knowledge and on efforts to conserve them in perpetuity. It is anticipated that this will contribute to a gender-responsive, demand-led approach to cassava breeding that will result in the better adoption of new improved varieties ,27.http://www.fao.org/plant-treaty/en/). The collection team consisted of at least one cassava breeder/germplasm scientist and a social scientist.Sixty-six districts within Tanzania’s main cassava growing administrative zones were targeted for germplasm collection, namely; Lake, Western, Southern Highlands, Central, Northern, Coastal and Zanzibar Zones. The zone of Zanzibar includes the islands of Pemba and Unguja . Traditiet al. [et al. [In each district, a traditional custodian of crop diversity, or farmer known to grow a broad range of landraces was identified through local agricultural extension agents. That person was then asked about other farmers in the area keeping cassava landraces. Acquisition of farmers knowledge followed the ITPGRFA and the terms of the Convention on Biological Diversity including the Nagoya Protocol. These include prior informed consent. At each farm, three questionnaires were conducted which are detailed in Cox et al.  and were [et al. , and desDecision to collect germplasm from a farmer was based on the farmer information as well as the experience of the collector/germplasm scientist. Germplasm and its associated farmer information was collected if a landrace with a particular name had not been collected before or the landrace name had been collected before, but from a different Parish or area, and if the breeder identified any unusual or interesting characteristics. For the collection of the landraces, a stake or stakes from a single plant of each landrace to be collected was taken, clearly labeled, tied in bundles, and wrapped in newspaper or in a breathable sack so that nodes did not get damaged during transportation.A unique questionnaire code that referred to a single key informant interview with a single person, was assigned to each interviewed farmer. This questionnaire code linked all collected knowledge and material(s) to one location and the individual farmer who provided it. It was also used to record and track this information in the database. A unique collector number was also assigned to each collected landrace. The unique collector number connected all farmer knowledge to the individual landrace that it described and was also used to record and track the individual landraces in the database and germplasm repository.Within one week of collection, stakes from the Northern Zone, Southern Highlands Zone, Coastal Zone and the zone of Zanzibar, were planted in a field genebank at Naliendele Agriculture Research Institute (NARI), Mtwara, with a back-up repository in pots in a screen house at the Sugarcane Research Institute (SRI), Kibaha. Each clone was planted in a single row of five plants. Due to quarantine restrictions related to CBSD within the country, landraces collected in the Lake Zone and Western Zone, were planted in a screen house at the Lake Zone Agriculture Research and Development Institute (LZARDI), Ukiriguru.A relational database with all the collected information from the questionnaires was created in MS Access and the three sections of the questionnaire entered as three tables  linked to each other through the unique questionnaire codes and collector numbers. The database was queried to summarize information relating to the collected landraces, the farmers, their experiences, preferences and knowledge. Co-ordinates locating sampling sites were plotted on a map using ArcGIS 10.7 .To further investigate cooking quality and organoleptic traits, 22 genotypes were selected from the Naliendele field genebank for on-station evaluation and laboratory analysis. Criteria for selecting genotypes for evaluation were (1) five plants were available, (2) the clone was unique from other clones being selected according to genotyping data, and (3) according to the key informant interview, the clone was preferred, they wanted to grow more of that cultivar and usually it was sweet and had good cooking qualities. BKP13 used specifically for flour was included as a check/control. The following methodologies were used for cooking quality and organoleptic traits:Time to cook: Two 4cm cores of two roots per plant of two plants were peeled and placed in 2.5 litres of boiling water in a 4 litre aluminium pot. Cooking was done on a traditional ‘jiko’ stove with charcoal. Root cores were tested at 10 min after dropping in boiling water, and every minute after that to determine if they were cooked. This was be done by penetrating the side of the root using a toothpick. Time taken for each sample to cook was recorded in minutes.Softness/firmness: Each cooked root core was poked three times on three random spots on the root with a toothpick and scored on a scale of 1-3 where 1 = soft, 2 = intermediate; 3 = hard.Softness/Mealiness/Taste: Once declared ‘cooked’, each root core was partitioned into three parts with each part being given randomly to each of three panelists to evaluate. Softness was recorded by each panelist after chewing the boiled root on a scale of 1-5 where 1= Extremely soft, 2= Soft, 3= Neither soft nor hard, 4=Hard and 5=Extremely hard. The most common score was recorded. Mealiness was scored based on a scale described by Ngeve [by Ngeve  of 1-3, et al. [Cores of 4 cm thick of each of two roots per plant of three plants per clone were placed in a plastic bag in a cool box and transported to the IITA Food lab in Dar es Salaam for estimation of cyanogenic potential (CNP) and post-cooking softness. CNP was assessed according to Essers et al.  and postet al. [in vitro [SNP genotyping was used as the basis to identify duplicate samples and assess diversity among the collected landraces. Young fresh leaf samples were collected in 96-well format from sprouted cassava stakes in the screen house at SRI and at LZARDI and preserved with silica gel. On reaching the laboratory leaf samples were dried in a freeze drier before grinding using a Genogrinder (SPEXSamplePrep), and DNA extracted using a modified Dellaporta et al.  method. in vitro .Biological and technical replicates were included to determine the best cut-off for defining a unique variety. There is always some degree of error in genotyping and there may be a degree of variation between individual plants of the same clone derived from mutation, particularly when they are collected from distant locations. Including biological and technical duplicates in the study can help define whether two samples should be considered the same clone or different clones. Seven biological replicates (different plants of the same variety) were included from three reference landraces Albert, Kiroba and Nachinyaya, and two biological replicates from the breeding line NDL2003/031. Two technical replicates (samples from the same plant) were included from five reference landraces , and four reference breeding lines . In addition, two technical replicates were included for two of the collected landraces Horti_35 and SMS23, and three technical replicates of the collected landrace EPM46. The quality and quantity of DNA was assessed using Nanodrop, and high-quality DNA of standard concentration sent to Diversity Array Technology (DArT), Canberra, Australia, for high density SNP genotyping using DArTSeq.Allele calls from DArTSeq were converted to allele dosage format for downstream analysis. SNP data was filtered to exclude all SNPs with more than 5% missing data, together with all monomorphic SNPs ), and any SNP with a minor allele frequency less than 0.05. Any genotype with more than 5.5% missing data was also deleted. Missing data was not imputed due to the diversity of the samples.To identify duplicates a distance matrix was generated using in PLINK (ver. 1.9) in R (ver. 4.0.5 throughout) , based oInitially a discriminant analysis of principal components (DAPC), an assumption-free multivariate clustering method  was condGenetic diversity was assessed by Zones using Shannon’s Index  and the et al. [Cassava stakes of the unique set of landraces were collected from the field genebank at Naliendele and taken to the regional plant health quarantine station at Kenya Plant Health Inspectorate Service (KEPHIS), Muguga, Kenya, for virus elimination and subsequent conservation at a designated facility. Thermotherapy followed by meristem tip culture was used for virus elimination according to the manual by Ferguson et al. .A total of 193 farmers growing cassava landraces were identified and interviewed  and 427 Women made up 26% of the interviewed farmers while men were 74% with no attempt to meet a predefined gender ratio. Their ages ranged from 18 to 86 years and the majority (91%) were the principal caretakers/decision makers with regard to cassava cultivation in their respective households, meaning they were the people who decided which landraces or improved varieties and how many of each cultivar would be grown. All data from key informant interviews is provided in Thirteen and a half percent of farmers had access to less than 1 acre of agricultural land, 42.7% had access to between 1-4.9 acres, 24.5% had access to 5-9.9 acres, 17.7% had access to more than 10 acres of agricultural land and 1% did not state the size of agricultural land they have access to. All the farmers who had access to less than 1 acre of agricultural land grew cassava on all their land. Of the 82 farmers who made up the 42.7% of farmers who had access to between 1-4.9 acres of land, 51 (62.2%) of them had cassava grown on all the available land. As the size of the individual farms increased from 5 acres to 10 acres or more, the area of land allocated for cassava decreased; more than half of those that had access to 5-9.9 acres of agricultural land had cassava cultivated on land between less than 1 acre to 4.9 acres.The 427 landraces collected from the farmers had mostly local names. Some of the names, when translated to English, described characteristics of the landraces, for example ‘too sweet to eat’, ‘hunger fighter’, ‘needle leaves’, ‘sit and eat’ and ‘the great’. The varieties were named by various communities based on their morphological or agronomic traits or after the person who introduced them or the place where they originated.Most of the landraces (87.9%) were best estimated by the farmers to have arrived in their communities from a time period ranging from 1950s or before, to the 2010s, the remaining 12.1% the farmers had no idea when they arrived in their communities. In the preceding five years, the majority of the landraces had seen an increase in their general cultivation in the area where they were collected and by the individual farmers from whom they were collected  meaning Based on the categorial data collected on the use of cassava it was clear that growing cassava for use as household food (boiled fresh roots or dried and milled into a flour for a variety of culinary uses) and for consumption of leaves are common uses in all regions . In the Landraces were categorized according to their uses. If it was mentioned that either the primary, secondary or tertiary use included both fresh consumption and processing into flour, the landrace was classified as ‘dual purpose’; if fresh consumption was mentioned only, the landrace was classified as ‘fresh’ and if processing was mentioned alone, it was classified as ‘flour production’. The above classification may not accurately reflect the physical attributes of the landrace as use is influenced by cultural practices; for example, the fact that in the coastal zone, landraces are only used for fresh consumption, does not mean that the landraces could not be used for flour production. It does imply that they are sweet enough for fresh consumption.Based on the use, cited by key informants, 164 (38%) landraces were used purely for fresh consumption, 145 (34%) were dual purpose and 103 (24%) were for processing (flour) only. and 15 (4%) had unknown uses .The farmers were asked to rate various qualities of their landraces on a scale of 1 to 5 (1 being very bad and 5 being very good), a score of 0 was given if the informant couldn’t comment, for instance if they hadn’t yet experienced a drought with this landrace or didn’t participate in the market. The distribution of scores for the storability of the landrace in the ground after maturity indicates that the majority of the landraces store fairly well to very good. Farmers who scored 5 for storability (8.3% of landraces), indicated that the landraces could stay in the ground for 5 years or more after maturity. Those that scored 1 or 2 (5.5% of landraces) could be stored for less than 18 months which was considered poor. This was also associated with susceptibility to CBSD root necrosis where root necrosis increases dramatically after six months in susceptible varieties.There appeared to be great discrepancy, even understanding, of what constituted early, medium or late maturing varieties. If cassava was being used for income generation or food, a short time to maturity was preferred (< 12 months), however if the crop was being used purely for food security, a late maturing variety (> 12 months) which could be stored for more than 5 years was preferred. Drought tolerance scores indicated that 95% of farmers had experienced this stress but 97.3% of landraces still performed fairly well to very good (scores 3-5) under such conditions, in fact farmers commented that the yield was unchanged in drought years in 13 landraces.Pest and disease scores and comments for many of the landraces indicated that more than half of the landraces had good to very good resistance to pest and diseases, although many of the farmers could not recognize pests or diseases.2=0.6425 (S8.2 Table in Two hundred and ninety-two (97%) of the 300 landraces that scored 4 or 5 for cooking quality also scored 4 or 5 for taste indicating they were ‘sweet’. These were good for consuming raw, boiled or fried, and made up 71% of all 427 landraces. This is similar to the estimate of 72% of fresh (38%) and dual purpose (34%) calculated according to categorization of landraces based on uses provided by key informant interviews discussed above. The distribution of cooking quality scores according to purpose or use is given in S8.2 Fig in Scores indicate that the market demand of a number of landraces is quite high. Seventy-four (17%) landraces that scored 1 to 3 had poor market demand and of these 47% scored 1 to 3 for taste, indicating they were bitter. Two hundred and ninety-eight (70%) landraces scored 4 or 5 in terms of market demand and of these 228 (77%) landraces scored 4 or 5 in terms of taste indicating they were reasonably sweet cultivars. Indeed, in terms of market demand the highest correlation of scores was with cooking quality (R=0.4028), followed by taste (R=0.3496) and yield (R=0.3401)  and was classified as sweet both from key informant interviews and on-station panel assessments. It was also softest according to laboratory probe tests, but oddly had scores indicating hardness by the panel members. The panel did indicate that it was extremely mealy. This was clearly a fresh consumption variety with poor flour making characteristics.HORTI_23 was collected 11 times, from the Southern Highland Zone (BKP63), the Coastal Zone  and the Northern Zone  and had the shortest time to cook (boil) (13 min). Likewise, KS70 (same as KS73) from the Coastal Zone, also cooked in 13min. Both of these landraces were scored as sweet, extremely mealy and good or very good for both boiling and processing into flour. SMS11 from Zanzibar, which was not collected elsewhere, had the longest cooking time of 36min. It was also amongst the hardest according to laboratory probe tests and had a low mealiness score according to the panel assessment. It was clearly used for fresh consumption as the processing quality was unknown.Good quality DNA was obtained from 406 of the 427 landraces that were collected as some failed to sprout in the field genebank. Four landraces were excluded for having >5.5% missing SNP data, and KSF61 was deleted as it matched with the breeding line TME204, leaving 401 landraces, and a total dataset of 490 entries including landrace and breeding references and biological and technical replicates see . An initThe raw dataset and distance matrix can be found in In total 37 landraces could be identified through similarity with a reference landrace. Seventeen of the 35 reference landraces matched with at least one collected landrace thus aiding with identification and eliminating duplicates. All reference landraces that found a match were from Tanzania, except Mbundumali which is thought to be from Malawi, but was collected in the Southern Highlands of Tanzania, adjacent to Malawi  as well as in the Central Zone (EPM23). Two of the reference landraces, Namikonga (Tanzania) and XinoNn’gole (Mozambique) were found to be identical. In total 285 unique landraces were identified, including those matching with the 17 Tanzanian landrace references  . The refThe maximum number of landraces were collected in the Southern Highlands (57) followed by the Lake Zone (46) and closely followed by the Central Zone (45). Thirty landraces were collected in the smaller Western Zone. Seventy-eight landraces of the 277 unique landraces (28%), were collected more than once, either in the same zone, or a different zone. Only four landraces were collected in a maximum of three zones. None of the landraces was collected across more than three of the seven Zones . The numInterestingly, the island of Pemba in the Zanzibar Zone, only shared one of its 16 landraces with Zanzibar, with the remainder being unique to the island. The Northern Zone shared the maximum percentage of landraces with other zones (19%), followed by the Coastal Zone (17.9%) with Zanzibar, the Northern Zone or the Southern Highlands Zone . The LakA DAPC plot of the relationship between 401 landraces from the seven zones is given in Representatives of 158 unique clones were sent to KEPHIS, Kenya, for virus elimination in preparation for conservation. Of these 82 are currently virus free, 34 are still in the virus elimination pipeline and 42 either did not establish at KEPHIS or were lost during the virus elimination process. This process is on-going.Cassava landraces have provided vital food security and income in Tanzania for centuries. They have adapted over the years to prevailing agro-ecological conditions and have been selected by farmers based on a range of criteria, ranging from food security, preferred cooking and eating quality traits and market demand . The exiet al., [Interestingly 74% of the farmers interviewed, who were actively involved in decision making as to which cultivars to grow, and how much of each cultivar to grow, were male. Mtunguja et al.,  also fouLike others have found, preferences for cooking and eating qualities were very much depended on the intended use –48. Theret al. [Key informant interviews and on-station and laboratory assessments indicate that those used for flour were generally bitter with relatively higher CNP levels (up to 175mg/kg fresh weight). It also appeared that in these cultivars softness after boiling was not a priority, nor was mealiness. An example of such a variety was BKP13  which could be incorporated into breeding programs to confer both agro-ecological adaptation as well as other processing characteristics important to this product profile. In the neighbouring region of northern Malawi where cassava is consumed as a staple crop, Benesi et al.  found thLandraces used more specifically for fresh consumption were characterized by a short time to cook (minimum 13min), became soft after boiling, and mealy. Clearly, the texture of cassava products is a critical factor in the acceptance of fresh cassava . MealineAccording to information on use from key informant interviews, 34% of landraces were dual purpose, being used for flour, but also for fresh consumption, 38% were used purely for fresh consumption , and 24% were used for processing only. Based on these figures, 72% of landraces were consumed fresh. This was similar to the estimate of 71% based on scores of 4 and 5 for cooking quality and taste, although from these scores, and scores of processing quality, it was estimated that 45% were dual purpose. This highlights three product profiles; flour production, fresh consumption and dual purpose.et al. [et al. [Genetic distance based on SNP fingerprinting was used to identify duplicate samples among the collected landraces and to visualize genetic relationships among both landraces and regions. A similar approach was used by Rabbi et al.  to asseset al. . Interes [et al.  found th [et al. .et al. [Interestingly, most of the individual landraces were not widely distributed across the country. Only 28% of landraces were collected more than once, and only four landraces were collected in a maximum of three zones. From the key informant interviews, 35% of the landraces were acquired either as a gift or purchase within the community, sometimes supplementing their own seed . This has been documented previously by Mtunguja et al.  who founet al. , that maet al. [et al. [et al. [This study found that a large number of unique landraces are grown in farmers’ fields. A similar situation was found in cassava by Kizito et al. , Benesi  [et al.  and Mtun [et al. . This is [et al. . Cassava [et al. . This diet al. [et al. [There was a clear structure in the diversity Figs  and 4 wiet al.  and Clem [et al.  recogniz [et al. –60 whichet al. [Little difference in levels of diversity were observed, with the Southern Highlands exhibiting slightly more diversity. Benesi et al.  found thCassava is clearly a vital crop for smallholder farmers in Tanzania and a very large number of different landraces are grown. This likely reflects the incorporation by farmers of seedlings from the soil seed bank. The observed genetic relationships among zones are likely due to independent introductions of cassava into the country, adaptation to prevailing agro-ecological conditions and farmer selections according to the intended use or market demands. Several product profiles are evident, including fresh consumption, flour production, dual purpose and longer-term food security. Each of these products have different trait requirements. It is important that the consolidated adaptation to all these specific elements accumulated in landraces are conserved and utilized to improve customer acceptance and adoption of new cultivars. The majority of individual landraces were not widely distributed across the country with limited farmer-to-farmer diffusion with implications for seed systems.S1 File(XLSX)Click here for additional data file.S2 File(XLSX)Click here for additional data file.S3 File(TXT)Click here for additional data file.S4 File(XLSX)Click here for additional data file.S5 File(XLSX)Click here for additional data file.S6 File(XLSX)Click here for additional data file.S7 FileThis data forms the basis of (XLSX)Click here for additional data file.S8 File(PDF)Click here for additional data file.S9 File(XLSX)Click here for additional data file.S10 File(CSV)Click here for additional data file.S11 File(CSV)Click here for additional data file.S12 File(PDF)Click here for additional data file.S13 File(XLSX)Click here for additional data file.S14 File(PDF)Click here for additional data file.S15 File(PDF)Click here for additional data file.