Attention-deficit/hyperactivity disorder (ADHD) is a known risk factor for substance-related problems (SRP) during adolescence, but the nature of this relationship and the importance of co-occurring conduct problems are not fully understood.n = 9,411).Data stem from a linked dataset between a large population-based survey conducted in 2012 of Norwegian adolescents aged 16 to 19, and registry-based data from specialized child and adolescent mental health services (Adolescents with “ADHD + high conduct problems” had increased risk of SRP (odds ratios = 2.37–10.14). Adolescents with “ADHD only” had very similar risk of SRP as adolescents from the general population with low symptoms of conduct problems. Relative to boys, girls with “ADHD + high conduct problems” appeared to have somewhat higher risk for SRP.The present study suggests that the risk for SRP among adolescent with ADHD is largely driven by co-existing conduct problems. Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by pervasive and impairing symptoms of inattention, hyperactivity and impulsivity . Among sA recent Norwegian study reported that only 4% of adolescents in CAMHS had received a disruptive behavior diagnosis . This raLittle is known regarding the influence of sex and negative life events on associations between ADHD, conduct problems, and SRP. Girls with disruptive behavior disorders tend to experience more social problems than boys , and resThe primary purpose of this paper was to assess if severity of self-reported conduct problems is associated with differential risk for SRP among adolescents diagnosed with ADHD in a Norwegian CAMHS-setting, and whether these associations differ across sexes. Specifically, we hypothesized that individuals with ADHD and high levels of conduct problems, used as a proxy for a CD, would have a significantly increased risk of SRP. Furthermore, we hypothesized that associations between ADHD and co-existing conduct problems and SRP would be stronger among girls than boys. Finally, we hypothesized that adjusting for negative life events would attenuate, but not fully account for, these associations.This study used data from a linkage between a large population-based study  and registry-based data from CAMHS (the Norwegian Patient Registry [NPR]). This linkage has been described in previous studies .y@h-survey was conducted in 2012 and included adolescents aged 16 to 19 years living in Hordaland County in Western Norway. Ten thousand, two hundred fifty-seven adolescents participated in the survey, comprising 53% of the total adolescent population . Prior to inclusion in the study, informed consent was retrieved from all participants and one school hour was used to complete the web-based questionnaire. Adolescents not going to school received the questionnaire by mail at their home address and child welfare service institutions and inpatient psychiatric hospitals were also contacted to let adolescents from these settings participate. Eight hundred and forty six adolescents that participated in the y@h  did not consent to linkage with official registries. Therefore, 9,411 adolescents from the y@h-survey were available for the linkage with CAMHS data.The NPR is the official registry on CAMHS use in Norway and includes information on psychiatric diagnoses, and data on the treatment provided for each patient. The majority of contacts with CAMHS in Norway comprise outpatient clinical consultations, including direct contact , the adolescent, and/or the family) and indirect contact  (The rsonnel) . Of the The Regional Committee for Medical and Health Research Ethics in Western Norway  and Norwegian Centre for Research Data  approved the study. All management of data in the present study adhered to the General Data Protection Regulation (GDPR) directive and a Data Protection Impact Assessment was conducted for the linkage.Approximately 5% of Norwegian adolescents below 18 years of age receive treatment in CAMHS yearly . Data frClinical professionals assessed psychiatric diagnoses for each of the adolescents that received treatment from CAMHS. These diagnoses were coded on Axis 1 according to the ICD-10 diagnostic manual  and regiSelf-reported conduct problems were measured in the y@h-survey using the self-reported 8-item scale for conduct disorders (CD) from the Diagnostic Interview Schedule for Children Predictive Scales (DPS) instrument . The DPSn = 89; “ADHD + low conduct problems”: n = 32; and “ADHD + high conduct problems”: n = 49. Individuals from the general population comprised the survey sample. This full survey sample consisted of 8,441 individuals, but after the exclusion of those without valid scores on the DPS-CD-scale (n = 170) and those with scores ≥1 on the DPS-CD scale , the survey sample consisted of 6,130 individuals .We created a variable for ADHD groups, in which individuals who received an ADHD diagnosis during their contact with CAMHS were categorized into the following three groups: (i) “ADHD only”; (ii) “ADHD + low conduct problems”; and (iii) “ADHD + high conduct problems.” The first group was defined as those who had no indications of conduct problems . The second group was defined as those who had a score of 1 on the DPS-CD scale. The third group was defined as those who had a score of 2 or more on the DPS-CD scale, as this cut-off is suggested to indicate a potential CD . Seven iIllicit drug use was based on a single item: “Have you ever tried hash, marijuana or other narcotic substances?” (Yes/No). (2) High-level alcohol consumption was based on a variable that added up five items measuring how many glasses of (i) beer, (ii) cider, (iii) wine, (iv) spirits, and (v) illegally distilled spirits the adolescents usually consumed during a period of 14 days. The variable separated those above the 80th sex-specific percentile on alcohol consumption among adolescents with any usual alcohol consumption, from those below. (3) Frequent alcohol intoxication was based on a single item: “Have you ever consumed so much alcohol that you were clearly intoxicated (drunk)?” The original item had five categories ranging from “No, never” to “Yes, more than 10 times.” Frequent alcohol intoxication was defined as drinking so much that one was clearly intoxicated more than 10 times, and on this basis, a dichotomous variable was created. (4) Positive CRAFFT score was based on the 6-item, validated CRAFFT scale , in which we summed up the number of positive scores on lifetime illicit drug use, high-level alcohol consumption, frequent alcohol intoxication, and positive CRAFFT-score.SRP were measured as part of the y@h-survey, with five variables that are thoroughly described in a previous article . (1) IllFT scale . CRAFFT FT scale . A dichoNegative life events (NLE) were measured as part of the y@h-survey with eight items covering different events  in ICD-10. Hence, we summarized both CD diagnoses (F91.0–F91.2) and other disruptive behavior diagnoses, including ODD (F91.3). To secure that no F91-diagnoses were ignored, we also included F92 .M = 11.45; SD = 10.33; median = 8; interquartile range = 4–16).Contact with CAMHS was defined as having a valid registration in the NPR. A continuous variable was constructed for the duration of treatment in CAMHS, which counted the number of months with a registered contact with the services. This variable spanned from 1 to 65 months , and maternal and paternal educational attainment . Three variables were also included that separated those with Norway as their country of origin from those born outside of Norway. These variables related to (1) the adolescent’s country of origin; (2) the adolescents mother’s country of origin; and (3) the adolescent’s father’s country of origin defined as Norway or “other country.” One variable specified whether the adolescents’ parents were living together.t-tests were used to compare means between the groups in all these analyses, while Pearson chi-square tests were used to compare differences across categorical variables. Second, we described comorbidity with formal disruptive behavior disorder diagnoses across the subgroups of ADHD. Third, we calculated the unadjusted rates of total symptoms of SRP with 95% confidence interval in the three ADHD-subgroups as well as in the survey sample and visualized these rates in a figure. Finally, we used logistic and ordered logistic regression analyses to investigate associations between ADHD and SRP stratified by each of the three ADHD-groups with the survey sample as base level  and adolescents with ADHD . In approach 2, we described the same variables across the three ADHD-subgroups using the “ADHD only” group as reference level against “ADHD + low conduct problems,” and “ADHD + high conduct problems, respectively. These analyses were conducted stepwise, comparing “ADHD only” with each of the other ADHD-subgroups separately. The analyses are summarized in se level . In Modese level .p < .05) than in the “ADHD only” group.As shown in n = 13) had a comorbid disruptive behavior disorder diagnosis according to CAMHS. In contrast, 29% (n = 49) of the adolescents with ADHD were screen positive for CD , compared with 10% in the full survey sample . Rates of diagnosed disruptive behavior disorders were low across all subtypes of ADHD, with 10% in the “ADHD + high conduct problems” group, and <5% in the “ADHD + low conduct problems,” and the “ADHD only” group.Of the 170 adolescents with an ADHD diagnosis, 8% . Compared to the survey sample, the “ADHD only” group had very similar rates of SRP while the “ADHD + low conduct problems” group had slightly higher SRP rates. The “ADHD + high conduct problems” group had considerably higher rates of SRP than both the survey sample and the “ADHD only” group. Specifically, 28.6%  of the adolescents with “ADHD + high conduct problems” had three or more indicators of SRP, compared to 4.7%  in the survey sample and 3.9%  in the “ADHD only”-group.Rates of total symptoms of SRP differed considerably across the ADHD subgroups  of boys with “ADHD + high conduct problems” had three or more indicators of total symptoms of SRP compared with 4.8%  in the non-clinical male survey sample and 5.9%  of those with ADHD only, while 42.9%  of girls with “ADHD + high conduct problems” had three or more indicators of total symptoms of SRP compared with 4.6%  in the non-clinical female survey sample and 2.4%  of those with ADHD only. See In the present study, we aimed to investigate SRP among subgroups of adolescents with ADHD characterized by different severity levels of conduct problems, using unique data with a linkage between a large population-based survey of Norwegian adolescents and an official registry on CAMHS-use.The main finding of the present study was a considerably increased risk of SRP among adolescents with an ADHD diagnosis in combination with a high self-reported conduct problems score. This finding was evident for all the included measures of SRP, although with varying magnitude. For example, adolescents with ADHD and high conduct problems had seven-fold increased odds for illicit drug use compared with the survey sample, even after adjustment for negative life events. On the other hand, adolescents with “ADHD only” had similar risk compared with the expected SPR rate in the survey sample. This pattern was evident across all the included measures of SRP. Our findings thus lend support to the notion that the risk of SRP among ADHD-diagnosed adolescents can largely be attributed to co-existing conduct problems , and thaA range of previous studies have reported that adolescents with ADHD have a high probability of co-existing conduct problems . This waNegative life events were reported more often by adolescents with an ADHD diagnosis in combination with conduct problems compared with those without these co-existing problems. However, negative life events only modestly attenuated the risk for SRP among adolescents with ADHD and high conduct problems. Thus, our findings suggest that the risk for SRP among adolescents with combined ADHD and conduct problems may not be restricted to those exposed to higher levels of negative life events. More specifically, following the inclusion of negative life events, all associations with SRP were still significant, and the strength of the odds ratios were reduced with 17% to 25%. Therefore, negative life events did not appear to explain the increased risk of SRP among adolescents with combined ADHD and conduct problems, but it should nevertheless be regarded as a relevant factor in the association between ADHD and SRP. Furthermore, the high prevalence of negative life events among adolescents with ADHD was most pronounced in relation to interpersonal violence. Potential explanations for this finding include: (1) that negative life events are part of the etiological mechanisms for development of conduct problems in adolescents with ADHD; (2) that a lifestyle characterized by disruptive behaviors increase the risk of exposure to certain negative life events; or (3) that unmeasured third variables account for this finding. While the present study did not investigate mechanisms that may explain the link between negative life events and conduct problems, our findings lend some support to a CAMHS-study which reported that exposure to interpersonal violence—but not non-interpersonal traumas—was related to more severe disruptive behavioral problems, independent of demographics and psychiatric diagnoses .The presence of ADHD and co-existing conduct problems was associated with SRP for both boys and girls. Although we did not have sufficient subgroup sample sizes for formal investigations of sex differences, our findings suggest that the association between “ADHD + high conduct problems” and SRP may be somewhat stronger among girls. A previous study of co-occurring ADHD and disruptive disorders reported that despite similar or less behavioral dysfunction, girls with disruptive disorders experienced more social problems than boys . A populFinally, the present study highlights several sociodemographic characteristics of the sample that should be considered. Previous investigations have reported that ADHD prevalence rates are higher among adolescents from low SES families, in terms of both family income and parental education . This paFew adolescents with ADHD had received a comorbid disruptive behavior disorder diagnosis, even among those reporting symptoms indicating CD in the “ADHD + high conduct problems” group. The high levels of self-reported conduct problems in this group, along with the increased risk for SRP, suggest that under-detection in CAMHS may leave adolescents at high-risk for unidentified SRP. Behavior problems associated with disruptive disorders are shown to be a potent risk factor for SRP, and particularly illicit drug use . On the A strength of the present study was the linkage between a large population-based sample and official registry data from CAMHS in which diagnoses were set by health professionals after thorough examinations. The use of a validated scale for conduct problems to assess self-reported symptoms at different severity levels and the inclusion of relevant co-variates, provide further strengths to the study.The study also had some limitations. The use of hyperkinetic disorder diagnosis to define ADHD prevent more detailed studies of the inattentive and hyperactive/impulsive presentations described in the DSM-5 . The relThe response rate of the population-based y@h-study was 53%. Our CAMHS-sample was retrieved from a linkage between the y@h and an official registry and does not comprise all adolescents receiving psychiatric treatment in the target population. SES is higher among the adolescents participating in the y@h-survey than expected from national statistics of the general Norwegian population . TherefoFinally, a range of other factors beyond those included in the present study are likely to affect the association between ADHD and SRP, such as adverse psychosocial conditions, negative peer influence, dropout from school, and previous experience with substance use. To study these factors was, however, beyond the scope of the present study. Although the present study reported heightened levels of exposure to interpersonal violence in the “ADHD + high conduct problems” group, our study did not explore potential mechanisms behind this link. Thus, we recommend future studies to investigate the role of negative life events more thoroughly, particularly exposure to interpersonal violence, on functional outcomes in adolescents with ADHD and conduct problems at different severity levels.In the present register-linked population-based study, there was a high rate of self-reported conduct problems among adolescents with ADHD. Nearly one-third of the adolescents with an ADHD diagnosis reported conduct problems at a severity level indicating the presence of a conduct disorder, but still only a minority of these screen-positive adolescents (10%) received any registered disruptive behavior disorder diagnosis in CAMHS. These findings may point to a need for improved detection of comorbid conduct disorders in adolescents with ADHD-diagnoses in CAMHS. Adolescents with “ADHD + high conduct problems” had a considerably increased risk of SRP. This risk remained significant after the adjustment for sex, age, and negative life events. The present study thus supports the notion that the risk for SRP among adolescent with ADHD may be due to co-existing conduct problems . RelativClick here for additional data file.Supplemental material, sj-docx-1-jad-10.1177_10870547221105063 for Substance-Related Problems in Adolescents with ADHD-Diagnoses: The Importance of Self-Reported Conduct Problems by Ove Heradstveit, Kristin Gärtner Askeland, Tormod Bøe, Astri Johansen Lundervold, Irene Bircow Elgen, Jens Christoffer Skogen, Mads Uffe Pedersen and Mari Hysing in Journal of Attention Disorders


Autism spectrum disorder (ASD) presents a diagnostic challenge due to its highly heterogeneous nature. The most common clinical manifestations include difficulty with social interaction and the presence of repetitive sensory-motor behaviors. Females are more likely to be misdiagnosed or have a delayed diagnosis compared to males. Other factors that contribute to delayed diagnosis include low socioeconomic status and belonging to an ethnic minority. In pediatrics, the goal of ASD screening is to diagnose ASD earlier, with timely referral to early intervention services, so that better long-term neurodevelopmental outcomes can be achieved. Moreover, attention deficit hyperactivity disorder (ADHD) is the most common comorbidity in patients with ASD. While the Diagnostic and Statistical Manual of Mental Disorders fourth edition (DSM-4) prohibited a co-diagnosis of autism and ADHD, the DSM-5 has modified exclusion criteria to allow such. This case describes a minority adolescent male patient who presented initially with complex ADHD, who upon extensive evaluation, was ultimately diagnosed with co-existing autism. This patient’s diagnosis of ASD at the age of 14 in the setting of a pre-existing complex ADHD diagnosis demonstrates how symptoms of inattention or hyperactivity may convolute underlying or newly emerging social interaction difficulties. We highlight how children who are diagnosed with ADHD should be screened or evaluated for autism in the right clinical setting, such as evident persistence of social interaction impairment despite ADHD treatment. Autism spectrum disorder (ASD) is a highly heterogeneous disorder that presents with persistent difficulties with communication and social interaction, in addition to restrictive, repetitive, or stereotyped sensory-motor behaviors ,2. ASD hPoor eye contact, decreased responsiveness to name, inability to show and share, and absence of gesturing by 12 months are concerning for early signs of ASD -9. OlderThe literature has shown that Early Intensive Behavioral Intervention (EIBI) is beneficial for some children with ASD, improving overall outcomes later in life . This caAt the age of 13, the patient established care with our pediatrics clinic for his well-child exam. The patient’s mother voiced concern regarding longstanding difficulty with “making and keeping friends” that had worsened since the age of nine in the setting of a complicated psychiatric history.The patient had been diagnosed at the age of 12 with complex ADHD in the setting of bipolar II disorder by an outside psychiatric provider prior to establishing care with our clinic. He was started on methylphenidate and aripiprazole. The patient’s mother noted improved mood, affect, and decreased difficulty making friends after starting medical treatment. The mother reported that another psychiatric provider, whose notes were not disclosed to us, noted a lack of classic symptoms of ADHD, given that the patient was an excellent student with no problems of inattention, hyperactivity, or behavioral concerns. This provider recommended that methylphenidate be discontinued due to concern for appetite suppression. The patient’s mother noted worsening impaired social interaction and declining grades following the discontinuation of methylphenidate, which prompted the medication to be restarted by our clinic. During the first encounter with our clinic, the patient was noted to have poor eye contact. The patient was described by his mother to have struggled with engaging with same-age peers and frequent avoidance of social activities, even while on methylphenidate. Gestational and developmental histories were unremarkable, with no developmental delay for motor and speech milestones noted. The patient was noted to lack functional play and would only engage in functional play if modeled by his mother. The patient also did not engage in mimicking or playing telephone. Family history amongst first-degree relatives was remarkable for suicide attempts without completion, depression, anxiety, bipolar disorder, and ADHD. The parent and patient agreed to have the evaluation for autism scheduled due to his persistent social interaction impairment. A comprehensive psychological evaluation by a clinical psychologist revealed that although the patient had a history of having a few friends, he reported that he struggled to recognize if someone was his friend. He specifically struggled with interpreting nonverbal forms of communication, such as interpreting body language. Per his mother, he demonstrated a preference for engaging in activities independently outside of school. The patient reported that he could recognize emotions in others but lacked an understanding of how to respond to these emotions. The patient’s affect was flat with a restricted range. He struggled in sustaining conversation and providing insight into his emotional experiences. The patient was found to have sensory sensitivities to clothing and foods. Several tests were administered, including the Stanford Binet fifth edition (SB-5), Autism Diagnostic Observation Schedule-2 (ADOS-2) - module 4, and Delis-Kaplan Executive Function System (D-KEFS) tests. Cognitive abilities fell in the high average range, with a full-scale IQ (FSIQ) of 113 (81st percentile). The patient was found to have high evidence of autism-related symptoms on the ADOS-2, which in conjunction with his clinical evaluation, indicated that he met the criteria for the diagnosis of ASD level 1. The patient’s D-KEFS test suggested that the patient’s occasional difficulties with attention and executive function were not consistent with a diagnosis of ADHD but were relative to perseverative thought and slower processing connected with the primary diagnosis of ASD. However, methylphenidate was continued due to functional response to the medication. Furthermore, psychiatry re-evaluated the patient and noted that, regardless of the D-KEFS test results, he still met DSM-5 criteria for ADHD. The patient currently continues to follow with outpatient psychiatry and is currently on amphetamine/dextroamphetamine. His symptoms were further clarified, and it was determined that there was no history of mania or hypomania that would be consistent with a diagnosis of bipolar disorder. The diagnosis of bipolar II disorder was removed, and aripiprazole was discontinued. The depressive features noted in his initial diagnosis of bipolar II disorder were also re-evaluated, and it was determined that he had a diagnosis of major depressive disorder (MDD) instead. Therefore, escitalopram was initiated in place of aripiprazole. His ultimate diagnosis is ASD with co-existing complex ADHD in the setting of MDD.Early ASD diagnosis and individualized intervention plans have been associated with better overall outcomes than when receiving a delayed diagnosis ,14. AutiADHD is the most common comorbidity in people with ASD, with rates of co-occurrence cited in the literature ranging from 25% to 81% . OverlapThis patient’s diagnosis of ASD at the age of 14 in the setting of a pre-existing complex ADHD diagnosis demonstrates how symptoms of inattention or hyperactivity may convolute underlying or newly emerging social interaction difficulties. Considering the growing body of research surrounding the association of ADHD and ASD, children who are diagnosed with ADHD should be screened or evaluated for autism in the right clinical setting, such as evident persistence of social interaction impairment despite ADHD treatment. Methylphenidate and atomoxetine are medications commonly used in the treatment of ADHD and have been noted to demonstrate a varying level of effectiveness in children with co-occurring ASD and ADHD. There is evidence in the literature that suggests medication response rates are markedly lower in children with ASD than in children without ASD. Also, individuals with co-occurring ASD and ADHD have been shown to have an increased risk of experiencing side effects . The patWhile a pre-existing diagnosis of complex ADHD was primarily attributed as the underlying factor for delayed diagnosis of ASD in the male adolescent patient for this case, other factors are also contributory. Delayed or missed diagnoses of ASD have been shown in the primary literature to be associated with patients belonging to an ethnic minority, lower parental education level, and low socioeconomic status . All of ASD is a highly heterogeneous disorder characterized by social communication deficits and the presence of restricted interests and repetitive behaviors that continues to serve as a diagnostic challenge. ASD core symptoms can be confounded by other neurodevelopmental disorders and comorbidities, especially in cases of a pre-existing diagnosis of ADHD. Screening for ASD in children diagnosed with ADHD should be considered in the setting of persistent social impairment or newly emerging social difficulties despite ADHD treatment. Socioeconomic and cultural factors have also been frequently cited as contributory factors to delayed diagnosis of ASD and should be considered when considering ASD screening and evaluation. Early diagnosis allows for early treatment with individualized intervention and access to public support systems, which ultimately results in better overall outcomes for children than when diagnosed at later ages. Children with a delayed diagnosis of ASD will still likely benefit from interventional services.


Bartonella spp. are vector-borne pathogens that cause zoonotic infections in humans. One of the most well-known of these is cat-scratch disease caused by Bartonella henselae and Bartonella clarridgeiae, with cats being the major reservoir for these two bacteria. Izmir, Turkey is home to many stray cats, but their potential role as a reservoir for the transmission of Bartonella to humans has not been investigated yet. Therefore, the aim of this study was to investigate the prevalence of Bartonella species and their genetic diversity in stray cats living in Izmir.Bartonella spp. in stray cats (n = 1012) was investigated using a PCR method targeting the 16S-23S internal transcribed spacer gene (ITS), species identification was performed by sequencing and genetic diversity was evaluated by haplotype analysis.Molecular prevalence of Bartonella-positive, which is a molecular prevalence of 12.05% . Among the Bartonella-positive specimens, 100  were successfully sequenced, and B. henselae , B. clarridgeiae  and Bartonella koehlerae  were identified by BLAST and phylogenetic analyses. High genetic diversity was detected in B. clarridgeiae with 19 haplotypes, followed by B. henselae (14 haplotypes) and B. koehlerae (8 haplotypes).Analysis of the DNA extracted from 1012 blood samples collected from stray cats revealed that 122 samples were Bartonella species are an important source of infection to humans living in Izmir. In addition, high genetic diversity was detected within each Bartonella species.This comprehensive study analyzing a large number of samples collected from stray cats showed that The online version contains supplementary material available at 10.1186/s13071-022-05431-3. Bartonella spp. are Gram-negative bacteria from the family Bartonellaceae with more than 23 defined species that infect domestic and wild mammals and humans [Bartonella henselae, B. clarridgeiae, B. quintana, and B. bacilliformis are the most common species associated with human diseases [B. henselae and B. clarridgeiae cause cat-scratch disease while B. quintana causes trench fever disease. Both diseases are called bartonellosis and manifest with symptoms such as fever, bacteremia, bacillary angiomatosis and endocarditis [Bartonella koehlerae, B. elizabethae and B. alsatica also have been associated with sporadic cases of endocarditis in humans [d humans –3. Bartodiseases , 2. Amoncarditis . Bartonen humans , 6.B. henselae, B. clarridgeiae and B. koehlerae are domestic cats [Bartonella species, such as B. rochalimae, B. elizabethae, B. quintana and B. grahamii, have been detected in cats [Bartonella species, but they usually show no symptoms. However, uveitis and endocarditis have been associated with B. henselae infection in cats [The principal reservoir hosts for tic cats , 7, 8. O in cats . Cats ca in cats , and lym in cats .Bartonella-specific gene sequences have become a very important tool for the diagnosis of Bartonella species, which are very difficult to isolate from blood or tissue samples [16S ribosomal RNA (rRNA) gene was initially used during the molecular diagnosis of Bartonella species, but was subsequently shown that it could not provide sufficient distinction in phylogenetic analysis at the species level [gltA genes [Various diagnostic methods are currently in use to diagnose bartonellosis and/or applied during epidemiological surveys, such as culture, PCR assay, histopathology and serology. Among these methods, PCR assays targeting  samples , 12. Thees level . More retA genes –15.Bartonella in cats has been reported to vary from 4% to 70% using blood culture methods [Bartonella in cats also varies, ranging from 0 to 80%. An increased prevalence has been especially reported in warmer regions; for example, in a study conducted in California, the seroprevalence in cats was 80% compared to 0% in a study conducted in Norway [B. henselae and 12.6% for B. clarridgeiae whereas Bartonella DNA positivity was 9.25% [Bartonella DNA positivity was reported to vary from 14% to 74.2% in dogs [Bartonella DNA positivity was reported to be 7.14% and 1.42% in nail and saliva samples collected from cats [Bartonella was found to be 9.4% in domestic cats by blood culture methods but seroprevalence reached up to 40% [The prevalence of  methods , and then Norway , 18. In as 9.25% , 20. In  in dogs , 22. In rom cats . In TurkBartonella occurs by a cat scratch or through the bite of a vector, the prevalence of Bartonella in stray cats that are in close contact with humans is frequently being screened in many countries [Bartonella and species of Bartonella have not been investigated. Therefore, the aim of this study was to investigate the molecular prevalence of Bartonella in a large number of blood samples collected from stray cats and to sequence the positive samples for species identification. In addition, genetic diversity within each detected species was investigated by haplotype analysis.Since the zoonotic transmission of ountries , 24–26. n = 1012) were collected from stray cats in Izmir city that had been brought to veterinary clinics located in the districts of Balçova (n = 110), Bayraklı (n = 43), Bornova (n = 48), Buca (n = 54), Çiğli (n = 6), Gaziemir (n = 4), Güzelbahçe (n = 10), Karabağlar (n = 115), Karşıyaka (n = 4), Konak (n = 614) and Narlıdere (n = 4). These stray cats were captured by persons in an animal friendly manner, without any harm being inflicted on the animal, and brought to the clinics for sterilization. The probability sampling method was used for sampling.Blood samples  in accordance with the manufacturer’s instructions. The species . During  species . The ampBartonella PCR-positive samples, sequences obtained by Sanger sequencing (Eurofins Genomics Germany GmbH) were aligned with MEGA 7.0 software and subject to BLAST analysis against the GenBank database. In addition, the obtained results also were confirmed by phylogenetic analysis performed by maximum likelihood method using the Kimura 2-parameter gamma distribution (K2 + G) model with 1000 bootstrap replications [Anaplasma phagocytophilum was used as an outgroup. For sequences with identical nucleotides (100% identity), only one was used for phylogenetic analysis. The reference 16S-23S rRNA ITS sequences used in this study are given in Additional file For species identification of ications . AnaplasBartonella isolates detected in this study and reference B. henselae, B. clarridgeiae and B. koehlerae strains isolated from cats in different countries. A haplotype network was generated in PopArt using the TCS network [Bartonella species detected in the present study, the number of variable sites (VS), C + G content (GC%), number of haplotypes (h), haplotype diversity (Hd), nucleotide diversity (π), number of nucleotide differences (K) and standard deviation (SD) were calculated using the DNASP program. Sequences belonging to B. henselae, B. clarridgeiae and B. koehlerae from cats were retrieved in GenBank and used in the haplotype analysis. These included 24 B. henselae sequences from 10 countries , 40 B. clarridgeiae sequences from 13 countries , and five B. koehlerae sequences from two countries .Haplotype analysis was performed using the DNASP program  using Ba network , 31. ForBartonella positivity values detected in stray cats in Izmir were computed with the exact binomial confidence intervals of 95% (95% CI), and comparison of the proportions was performed by the Chi-square test using PASW Statistics version 18 software. Statistically significant differences were determined at P < 0.05.Bartonella DNA. The highest prevalence was detected in samples collected from cats in Güzelbahçe (20%), followed by Bayraklı (14%) .DNA extracted from 1012 blood samples collected from stray cats was screened by PCR; of these 1012 DNA samples, 12.1%  were positive for Bartonella-positive samples, 100  were successfully sequenced. BLAST and phylogenetic analyses revealed the presence of B. henselae, B. clarridgeiae and B. koehlerae in the positive samples. Bartonella henselae was the most common species detected in the stray cats  detected, followed by B. clarridgeiae  and then by B. koehlerae   belonged to 19 haplotypes (H-1 to H-19). Among these haplotypes, the most prevalent haplotype was H-1, which contained 47 B. clarridgeiae isolates from 14 countries, including Turkey  belonged to 14 haplotypes (H-1 to H-14). Among these haplotypes, the most prevalent haplotype was H-1, which included 40 B. henselae sequences from 10 countries, including Turkey  belonged to eight haplotypes (H-1 to H-8). Among these haplotypes, the most prevalent haplotype was H-1, which contained 21 B. koehlerae sequences from three countries, including Turkey  together with B. clarridgeiae and B. koehlerae. While less frequent than B. henselae, B. clarridgeiae is accepted as a causative agent for cat scratch disease [B. koehlerae has been linked to endocarditis in humans [ disease  and B. kB. clarridgeiae sequences. Bartonella clarridgeiae H-1 has been detected in Spain [B. henselae H-1 has been reported in Spain [Bartonella henselae H-2 was detected in Spain [B. henselae H-3 has been reported in Spain [B. koehlerae H-1 has been detected in Brazil [Bartonella species, there were haplotypes that are apparently unique to Turkey in addition to haplotypes from different countries including Turkey (Figs. Bartonella sequences obtained in this study belong to haplotypes that have also detected in cats in different countries.The highest haplotype diversity was detected among in Spain , Brazil in Spain , USA [35in Spain , Greece in Spain , Portugain Spain , Philippin Spain , Paraguain Spain , Japan [in Spain , Taiwan in Spain  and Indoin Spain . Also, Bin Spain , Malta [in Spain , Brazil in Spain , Paraguain Spain , Taiwan in Spain , Guatemain Spain , Korea [in Spain  and Austin Spain . Bartonein Spain  and Brazin Spain  whereas in Spain . Finallyn Brazil  and Maltn Brazil . Within ey Figs. –6. NonetB. henselae antibodies in different human groups such as adult and pediatric patients [Bartonella infection to humans in this country.Since previous studies carried out in Turkey reported anti-patients , healthypatients , cattle patients  and kidnpatients , stray cBartonella spp. infection in stray cats in Turkey, with B. henselae, B. clarridgeiae and B. koehlerae being the species detected.In conclusion, we detected a 12.1% prevalence of Additional file 1: Table S1. Reference Bartonella isolates used in phylogenetic tree and haplotype analysis.


The risk rate of criminality is increased in ADHD, especially in children who, in addition to ADHD, express externalizing behavior of oppositional defiant disorder (ODD), later followed by conduct disorder (CD), substance misuse and antisocial personality disorder (ASPD). Studies report ADHD to be about ten times more common in prison populations than in the general adult population. Prisoners with ADHD have compared to prisoners without ADHD, an earlier onset of offending, higher rates of coexistent psychiatric disorders, and are more often incarcerated due to violent- and drug-related offences. Within prison settings, inmates with ADHD are more often reported for intra-institutional aggression and they are often experienced as more difficult to manage and costly to rehabilitate. Further, they relapse comparably more often and faster into criminality after being conditionally released. Despite high prevalence rates of ADHD within prisons and serious consequences related to untreated ADHD, few controlled trials have evaluated methylphenidate treatment in prisoners with ADHD and coexistent disorders. Evidence and clinical experience of pharmacological and psychosocial interventions of prison populations with ADHD will be presented briefly.No significant relationships.


Ferromagnetism to non-ferromagnetism transition is detected in a chemically bonded MoSe Spintronics is an approach to manipulating spin polarization and to realizing spin-based functionalities. Dilute magnetic semiconductor (DMS) is one of the promising materials for spintronics applications , 2. The The quantum anomalous Hall effect is the quantum Hall effect without an external magnetic field, but instead due to intrinsic ferromagnetism . The quaty field –32. The The chemical-bonded MoSeThe chemical-bonded MoSeThe X-ray diffraction (XRD) was performed in a D2 phaser using the Cu KThe JEOL-6330 Field-Emission SEM backscattering electron image (BEI) mode was used to verify the atomics ratio. Under the BEI mode, one distinguished the MoSeMagnetism measurements were performed using the standard technique in a SQUID MPMS-3 magnetometer (Quantum Design), and the magnetic field step is 50 Oe.Figure mentclass2pt{minimFigure entclass1pt{minimaentclass1pt{minimaFigure Moreover, we seek to know the source of the ferromagnetism and the reason why ferromagnetism is not detected in the MWS-1100. It is known that a slight magnetic or transition element dopant might lead to great ferromagnetism in 2D TMDs.The MWS with different thermal annealing temperatures are from the same raw material and have no difference in treatment processes and equipment. It is expected that the magnetic element concentration would be the same and its contribution to the ferromagnetism would be similar. Figure The ferromagnetism might originate from the lattice defect or zigzag structure –42. FiguThe ferromagnetism is studied in the MoSanosheet . This sucument}x . These eAs shown in Fig. operties . Experimoperties –42. The  spectra . It is 2elements . Upon fuagnetism .Ferromagnetism to non-ferromagnetism transition is detected in a chemical-bonded MoSe


Attention-deficit/hyperactivity disorder (ADHD) has been associated with several autoimmune diseases (AD), both within individuals and across relatives, implying common underlying genetic or environmental factors in line with studies indicating that immunological mechanisms are key to brain development. To further elucidate the relationship between ADHD and autoimmunity we performed a population-wide familial co-aggregation study.We linked Swedish national registries, defined a birth cohort with their biological relatives and identified individuals diagnosed with ADHD and/or 13 ADs. The cohort included 5 178 225 individuals born between 1960 and 2010, of whom 118 927 (2.30%) had been diagnosed with ADHD. We then investigated the associations between ADHD and ADs within individuals and across relatives, with logistic regression and structural equation modelling.Within individuals, ADHD was associated with a diagnosis of any of the 13 investigated ADs (adjusted odds ratio (OR) =1.34, 95% confidence interval (CI) = 1.30-1.38) as well as several specific ADs. Familial co-aggregation was observed. For example, ADHD was associated with any of the 13 ADs in mothers , fathers , full siblings , aunts , uncles  and cousins . Still, the absolute risks of AD among those with ADHD were low. The genetic correlation between ADHD and a diagnosis of any of the investigated ADs was 0.13 (95% CI = 0.09–0.17) and the environmental correlation was 0.02 (95% CI = -0.03–0.06).We found that ADHD and ADs co-aggregate among biological relatives, indicating that the relationship between ADHD and autoimmune diseases may in part be explained by shared genetic risk factors. The patterns of familial co-aggregation of ADHD and ADs do not readily support a role of maternal immune activation in the aetiology of ADHD. The findings have implications for aetiological models of ADHD. However, screening for autoimmunity among individuals with ADHD is not warranted. Key MessagesSome studies show that individuals with attention-deficit/hyperactivity disorder (ADHD), and their biological relatives, have an increased risk of autoimmune disorders, though the aetiology underlying this increased risk remains unclear.Using Swedish population-wide registers it was found that individuals diagnosed with ADHD, and their biological relatives, had a moderately increased risk of autoimmune diseases.The noted associations between ADHD and autoimmune diseases may in part be explained by shared genetic risk factors.Due to the low absolute risks and limited benefit, screening for autoimmunity among individuals with ADHD is not warranted.Attention-deficit/hyperactivity disorder (ADHD) is a common, and often chronic, childhood-onset neurodevelopmental disorder with hyperactivity, inattention and impulsivity constituting the core symptoms.,,,,,,,,,,Several immunological mechanisms are central to brain development and functioning, e.g. the primary immune cells of the brain, glial cells, are key to synaptic pruning during neurodevelopment,To further advance knowledge on the relationship between ADHD and ADs, we conducted a population-based, within-individual-and familial, co-aggregation cohort study using Swedish population-wide national registers. If ADHD was found to be associated with ADs across relatives who are assumed to share little to no environment, such as cousins, this would be in support of common genetic factors. Moreover, if one saw stronger associations between ADHD and ADs across maternal relatives, as compared with paternal relatives, this could indicate a role of AD-mediated maternal effects.The study was approved by the Regional Ethical Review Board in Stockholm, Sweden (reference number 2013/862–31/5). As the study is register-based, informed consent was waived.,The present cohort study was based on linked data from several Swedish population-based registers, using each individual’s unique national personal identification number for linkage.The Swedish Multi-Generation Register contains information on the biological parents of Swedish inhabitants born after 1931 and alive in Sweden after 1960.The Swedish National Patient Register (NPR) was established in 1964 as a somatic inpatient care register.The Swedish Prescribed Drug Register (PDR) was established July 2005 and holds information on all dispensed drug prescriptions in Sweden.IJE online) for case definitions.We identified individuals ever diagnosed with ADHD and ADs of interest using NPR and PDR. We only included ADs with more than 2000 diagnosed individuals in the index cohort. Since ADs share genetic architecture, and one individual might have several ADs, we defined an ‘any of the 13 ADs’ variable (anyAD) that constituted our primary outcome; see We organized, managed and analysed the data with Statistical Analysis Software (SAS) 9.4 (SAS Institute Inc.) and R 3.4.3 (R Foundation) with built-in commands, and the drgee,ad modum Wald. We did not adjust for multiple testing, given that tests across different index-relatives relationships would not constitute independent tests.Associations between ADHD and ADs were calculated as odds ratios (OR) with logistic regression. In all analyses, lifetime ADHD defined predictor/exposure and the dependents/outcomes were defined as lifetime diagnosis of the respective ADs, with anyAD being the primary outcome and the specific ADs secondary outcomes. To adjust for familial clustering, we computed cluster-robust standard errors; 95% confidence intervals (95% CI) were calculated Absolute estimates, such as absolute risk (AR) and risk difference (RD), may be more informative in clinical and public health settings than relative measures, such as ORs.,We calculated the associations between ADHD and ADs within individuals with adjustment for sex and year of birth. Year of birth was modelled as natural cubic splines to minimize residual confounding and loss of statistical power.In the familial co-aggregation analyses we investigated whether the relatives of individuals diagnosed with ADHD had an increased odds of ADs, as compared with the relatives of non-ADHD individuals. The analyses were adjusted for year of birth of both the index individuals and the relatives modelled as natural cubic splines. Other covariates were not adjusted for under the same rationales as in the within-individual analyses.Differences in the ORs for the associations between index (offspring) ADHD and maternal AD as compared with index ADHD and paternal AD, could be due to maternal  effects. To test whether the index-mother associations were different from the index-father associations, we conducted a Wald test: we merged the mother and father cohorts and conducted ‘parent analyses’ with the inclusion of an interaction term between parent type (mother or father), and ADHD . The resulting estimate for the interaction may thus reflect a maternal effect. As reference, we performed similar analyses for: ‘aunts versus uncles’ unconditioned by parental side, where we assumed no maternal effects; and ‘maternal aunts and uncles versus paternal aunts and uncles’, where we assumed that ADs on the maternal side would be associated with maternal autoimmunity, and thus indirectly with maternal effects on the offspring.IJE online) for rationales and methods descriptions.We conducted several sensitivity analyses to investigate whether the results in the main analyses could be due to the direct effects of ADHD on ADs, direct effects of ADs on ADHD, the psychiatric comorbidities of ADHD, off-label prescription of ADHD medication in the treatment of ADs, misdiagnosis (including psychosomatic disorders and other AD mimics), geographical factors, period effects related to the registers  and right-censoring; see To assess the relative contribution of genetic and environmental factors to the association between ADHD and anyAD, we performed structural equation modelling. We used full siblings, assumed to share 50% genetic variance and 100% shared environmental variance, and full cousins, assumed to share 12.5% genetic variance and 0% shared environmental variance. All included individuals were born 1960–2010 and did not die or emigrate before age 10. From each family we randomly selected one pair of siblings or cousins, resulting in 1 663 093 sibling pairs and 107 800 cousin pairs. We decomposed ADHD and anyAD’s variance and covariance into additive genetic (A), non-shared environmental (C) and unique environmental (E) factors, using liability threshold models that again were used to fit bivariate models to calculate the correlation of A, C and E across ADHD and anyAD. The analyses were adjusted for year of birth (modelled as a linear and cubic covariate) and sex. The presented results are from the best-fitting and most parsimonious model (lowest Akaike information criteria).IJE online).Of the 5 178 225 individuals  in the final birth cohort, 118 927 (2.3%) were defined as having ADHD. Descriptive information on the composition of the cohorts is presented in IJE online) for within-individual and familial co-aggregation analyses presented as ORs.ADHD was associated with anyAD  and several specific ADs with ORs ranging between 1.11 (95% CI = 1.02–1.20) for ulcerative colitis and 1.79 (95% CI = 1.38–2.31) for Sjögren's syndrome; see IJE online) for sex-specific within-individual results.Minor sex differences were noted for ADHD’s association with psoriasis and Hashimoto’s disease; see IJE online) for the results of the within-individual and family co-aggregation analyses presented as ORs.In the familial co-aggregation analyses, ADHD was associated with an increased odds of anyAD in all relatives: mothers , fathers , full siblings , aunts , uncles  and cousins . Moreover, ADHD was associated with all specific ADs in at least one of the first-degree relatives , including all first-degree relatives for Crohn’s disease, psoriasis and rheumatoid arthritis. ADHD was also associated with an increased odds of several specific ADs in aunts, uncles and cousins; see IJE online).Among individuals diagnosed with ADHD, and their relatives, the standardized ARs for ADs were modestly elevated (IJE online).Index ADHD had stronger association with maternal anyAD as compared with paternal anyAD (ratio of odds ratios (ROR)=1.13, 95% CI = 1.09–1.17). ADHD had stronger association with aunt anyAD, as compared with uncle anyAD . There was no signal for a stronger or weaker association between ADHD and maternal aunt and uncle anyAD as compared with paternal aunt and uncle anyAD . Statistical power was limited in the analyses of the specific ADs; see IJE online).After exclusion of index individuals who had ever received a diagnosis of a non-ADHD psychiatric disorder, the within-individual and index-relative ADHD-AD associations were attenuated and the 95% CIs were widened; see IJE online).The results of the other sensitivity analyses were not in contrast to the main analyses; see The best-fitting and most parsimonious model was a model that described ADHD with AE, and anyAD with ACE. As shown in Our comprehensive population-based multigenerational family study found ADHD to be associated with several ADs, both within individuals and across biological relatives. ADHD was to some degree more strongly associated with maternal than paternal ADs, but by utsing aunts and uncles in a genetically informative study design, we demonstrate that this difference cannot be readily explained by AD-mediated maternal effects. Quantitative genetic modelling further indicates that the familial co-aggregation of ADHD and ADs is partly due to shared genetic factors.,,,In light of our results, shared genetic liabilities between ADHD and ADs seem plausible. As the heritability of ADHD is 70–80% and the role of shared environmental factors in ADHD’s aetiology has been demonstrated to be limited,,IJE online). Of note, a large number of individuals were excluded from these analyses; for example, from the index cohort 70.5% of those diagnosed with ADHD were removed, with consequential bias and reduced statistical power.However, the sensitivity analyses where we adjusted for ADHD in the relatives would not adjust for all ADHD liability/symptoms in the study population, and we cannot rule out that behaviours secondary to ADHD symptoms, e.g. smoking, again increase the risk of AD, and as such partly explain the noted familial co-aggregations. This is an area where more research is needed. It could also be that pronounced ADHD symptoms of an individual might lead to more familial stress that, in turn, increases the risk of ADs among the closest relatives, especially in mothers who are the primary caregivers. Still, it seems unlikely that this could explain all of the familial co-aggregation between ADHD and ADs, as we note familial co-aggregation in relatives as distant as full cousins. Several neuropsychiatric disorders have been associated with both ADHDin utero neurodevelopmental disturbances in the offspring.,,in utero) effects to have a role in ADHD, but merely demonstrate that other factors should be taken into consideration before attributing maternal-paternal discrepancies in ORs, hazard ratios or risk ratios to maternal AD-mediated environment. In further opposition to a causal role of MIA in ADHD, a sibling-controlled study could not find maternal infections during pregnancy to be associated with offspring ADHD.,,The association between ADHD and maternal anyAD was stronger than the association between ADHD and paternal anyAD (and similar findings were noted for four specific ADs). Therefore, one could argue that our results support a role for AD-mediated maternal effects in the aetiology of offspring ADHD, in line with experimental studies in rodents and non-human primates that suggest that gestational maternal immune activation (MIA) may cause ,,vice versa) and their relatives is not warranted.Despite the fact that both the within-individual and the index-relative ADHD-AD associations were not miniscule on the OR scale, they were still substantially smaller than what is typically reported between ADHD and other neuropsychiatric disorders.,,,,Some of this study’s findings are replications of previous findings in independent materials.,,,Studies employing alternative study designs, e.g. insurance data and molecular genetics, have reported findings that are in direct contrast to our study.,,To avoid bias we excluded individuals who died or emigrated before age 10, as ADs seldom debut earlier than this age and those that do are often followed up in specialist health care and are thus recorded in the registers. Setting the cut-off age higher could lead to bias since ADHD is associated with increased mortality.To conclude, we demonstrate within-individual and familial co-aggregation of ADHD and several ADs, likely reflecting shared genetic factors. Moreover, we demonstrate contrasting findings of of AD-mediated maternal effects, including MIA, having a causal role in the development of offspring ADHD. Our results have implications for the understanding of ADHD’s aetiology, but do not warrant screening for ADs among asymptomatic individuals with ADHD.https://www.socialstyrelsen.se/en/].The population-wide individual-specific register data underlying this article were provided by Socialstyrelsen and may not be shared with outside researchers. Data may be obtained after application to Socialstyrelsen . None of the funding sources had any involvement in any parts of this study.J.H. has served as a speaker for Eli-Lilly, Shire, HB Pharma, Medice and Biocodex. H.L. has served as a speaker for Eli-Lilly and Shire and has received research grants from Shire, all outside the submitted work. None of the other authors have any conflicts of interests to declare.dyab151_Supplementary_DataClick here for additional data file.


Prenatal organophosphorus pesticides (OPs) are ubiquitous and have been linked to adverse neurodevelopmental outcomes. However, few studies have examined prenatal OPs in relation to diagnosed attention-deficit/hyperactivity disorder (ADHD), with only two studies exploring this relationship in a population primarily exposed through diet. In this study, we used a nested case-control study to evaluate prenatal OP exposure and ADHD diagnosis in the Norwegian Mother, Father, and Child Cohort Study (MoBa). For births that occurred between 2003 and 2008, ADHD diagnoses were obtained from linkage of MoBa participants with the Norwegian Patient Registry (N = 297), and a reference population was randomly selected from the eligible population (N = 552). Maternal urine samples were collected at 17 weeks’ gestation and molar sums of diethyl phosphates (ΣDEP) and dimethyl phosphates metabolites (ΣDMP) were calculated. Multivariable adjusted logistic regression models were used to estimate the association between prenatal OP metabolite exposure and child ADHD diagnosis. Additionally, multiplicative effect measure modification (EMM) by child sex was assessed. In most cases, mothers in the second and third tertiles of ΣDMP and ΣDEP exposure had slightly lower odds of having a child with ADHD, although confidence intervals were wide and included the null. EMM by child sex was not observed for either ΣDMP or ΣDEP. In summary, we did not find evidence that OPs at 17 weeks’ gestation increased the odds of ADHD in this nested case-control study of ADHD in MoBa, a population primarily experiencing dietary exposure.  Attention-deficit/hyperactivity disorder (ADHD) affects 3 to 6% of children worldwide ,2 and isOne group of potential environmental risk factors for ADHD are organophosphorus pesticides (OPs). OPs are insecticides that were originally used as nerve agents during conflicts in the 1930s and 1940s, with some later used in lower doses as insecticides ,15. At hEpidemiological studies have observed associations between prenatal OP exposure and adverse neurodevelopmental and behavioral outcomes in children including increased risk for autism ,22, decrThe bulk of the neurodevelopmental literature includes studies conducted in agricultural settings proximate to agricultural OP applications or in urban populations that were enrolled during a period where residential applications of OPs were allowed ,32. HoweIn this study, we sought to investigate the association of prenatal OP exposure with clinical ADHD diagnosis, while accounting for the potential beneficial role of a diet rich in fruit and vegetables. We additionally explored the role of child sex as a potential modifier of this relationship, given the pronounced sex disparity in ADHD diagnosis. We hypothesized that higher OP exposure would be associated with greater odds of an offspring ADHD diagnosis, with stronger associations among boys compared to girls.We utilized a sub-study of the Norwegian Mother, Father, and Child Cohort Study (MoBa). MoBa is a prospective population-based cohort that enrolled participants between 1999 and 2008 . All NorChildren were eligible for the present study if they were born after 2002 , had completed a 36-month postnatal questionnaire , did not have Down’s syndrome or cerebral palsy , had available maternal biospecimens , were the result of a singleton pregnancy , and resided within close proximity of Oslo  . From thADHD diagnoses were obtained from linkage of study participants with NPR, as previously described by Engel (2018) et al. . NPR is We randomly selected 554 mother-child pairs from the final MoBa eligible population to represent the exposure distribution in the population of pregnancies that gave rise to the cases; we refer to these mother-child pairs as the MoBa reference population. As only two individuals that were identified as diagnosed ADHD cases via the NPR were also randomly sampled into our MoBa reference population, we decided to analyze this study as a nested case-control study. As such, these 2 overlapping individuals were treated as cases, decreasing the number of mother-child pairs in the MoBa reference population from 554 to 552.Maternal spot urine samples were collected at the mother’s first ultrasound appointment (~17 weeks’ gestation). Details regarding shipment, storage, and quality assurance and control procedures for MoBa urine samples have been detailed previously ,52. BrieMeasurement of dialkylphosphate (DAP) metabolites was conducted at the Norwegian Institute of Public Health using a ultra-performance liquid chromatography-time-of-flight system . The sixTo assess assay performance, procedural blank samples and two in-house control samples were included per analytic batch as well as 4–6 laboratory-blinded quality control (QC) pooled urine samples. Samples were randomized to analytic batch and technicians were blinded to outcome status. Specific gravity was measured using a pocket refractometer (PAL-10S) from Atago. One urine sample was excluded as an OP metabolite measurement could not be obtained; this decreased the number of ADHD cases from 298 to 297.ij is the specific gravity corrected value of Pij, Pij is the measured or imputed value of the OP i for participant j, SGj is the specific-gravity for participant j, and c the geometric mean of specific-gravity across all participants for the OP i.The percent above limit of detection (LOD) for DMP, DMTP, DMDTP, DEP, and DETP were 66.1%, 99.9%, 28.9%, 98.7%, and 66.8% respectively; values of these metabolites below the LOD were imputed from a log-normal distribution truncated at the LOD . DEDTP wj is molar sum of DMP, DMTP, and DMDTP for a participant, j. DMPj is the DMP measured or imputed value for participant j. DMTPj is the DMTP measured or imputed value for participant j. DMDTPj is the DMDTP measured or imputed value for participant j. All values are in in nanomole/liter.j is molar sum of DEP and DETP for a participant j. DEPj is the DEP measured or imputed value for participant j. DETPj is the DETP measured or imputed value for participant j. All values are in in nanomole/liter.Next, metabolites were converted from ng/mL to nmol/L by dividing each metabolite by its respective molecular mass. OP metabolites were next grouped by molecular weight, thus ΣDMP was the sum of DMP, DMTP, and DMDTP and ΣDEP was the sum of DEP and DETP . CalculaEvaluation of DAPs as molar sums within their respective subgroups (ΣDMP and ΣDEP) rather than evaluating the six DAPs individually follows usual practice as multiple DAPs can result from metabolism of the same parent compound ,56.Maternal age at delivery (years), child sex at birth , and birth year  were obtained from the MBRN. Maternal education , financial difficulty experienced in the past 12 months , marital status , parity , maternal smoking during pregnancy , maternal drinking during pregnancy , maternal exposure to pesticides in the past 6 months , paternal exposure to pesticides in the past 6 months , residing on a farm or detached home (home not attached to another home such as in an apartment complex or condominium) during pregnancy , and season of urine collection  were obtained from the maternal questionnaire administered at 17 weeks’ gestation. Maternal history of depression (yes/no) was also collected from this questionnaire using a dichotomized version of the lifetime history (LTH) of major depression (MD) assessment . Raw frum = 20). MICE is sometimes referred to as fully conditional specification, where missing values are imputed from conditional models. To apply this approach, a random value was selected from an appropriate distribution (representative of the data), conditional on the outcome, exposure, and other covariates. Summary estimates from the combined generated datasets were derived using Rubin’s rules for imputation [Descriptive statistics were generated for all variables. Spearman correlations between ΣDMP and ΣDEP were calculated. Missing covariate data can be found in putation ,61,62,63We used adjusted logistic regression models to estimate associations between prenatal ΣDEP and ΣDMP exposure and offspring ADHD. Functional form assessment of ΣDMP and ΣDEP using Akaike Information Criterion identified OP tertiles as the most appropriate descriptor of OP exposure.Potential confounders were identified from the literature and their relationships were examined using a direct acyclic graph (DAG) . The minTwo sensitivity analyses were performed. To determine the impact of imputation, primary models were rerun without imputing data . To evaluate the impact of adjusting for the other OP molar sum, models were rerun without mutually adjusting for the other metabolite class.Characteristics of the study population can be seen in Specific-gravity and non-specific-gravity adjusted OP metabolite distributions are in We observed no association between ΣDMP or ΣDEP and offspring ADHD, either overall or within sex-specific strata . AlthougIn this nested case-control study of prenatal ΣDMP and ΣDEP exposure at 17 weeks’ gestation and offspring ADHD, we observed no evidence of increased odds of ADHD in relation to increased exposure either overall or within strata of child sex. Despite adjusting for prenatal consumption of raw fruit and vegetables, higher exposure to ΣDMP and ΣDEP metabolites tended to be associated with slightly reduced odds of ADHD, however the confidence intervals were wide and included the null.Although the bulk of the literature on prenatal OP exposure and offspring ADHD is mixed, the results from our study are consistent with five previous studies that did not observe associations with ADHD or ADHD-like behaviors ,37,40,70Conversely, other studies have found associations of prenatal OP exposure with offspring ADHD symptoms and executive dysfunction ,35,39,41Although interactions with child sex have been reported for prenatal OP exposure and ADHD in some studies, we did not observe evidence of multiplicative EMM in our study. This finding is consistent with four other studies on prenatal OP exposure and ADHD or ADHD-like symptoms that explored EMM by child sex ,38,39,40A reason for discrepancies in the literature may be the challenges inherent in measurement of ADHD or ADHD-like symptoms, which may be magnified in the earliest age groups. The majority of prenatal OP-ADHD studies focused on symptoms in the preschool period ,37,38,40The OP-ADHD literature is also challenged by numerous study-specific differences regarding the nature of exposure to OP parent compounds in the individual populations, which are difficult to differentiate based on non-specific dialkylphosphate biomarkers. Half of the studies on prenatal OP exposure and ADHD were conducted in the US and more than a quarter of agricultural pesticides used in the US are currently banned in the EU, including many OPs ,43,75. BOur study has many strengths. This was an efficient nested case-control study within a large and representative population-based cohort that contained an extensive amount of questionnaire data covering important covariates, such as maternal ADHD symptoms and prenatal dietary intake of fruits and vegetables. As a result, we were able to account for important confounding pathways that have been rarely addressed in prior studies. Maternal ADHD has the potential to confound the association between prenatal OP exposure and offspring ADHD through socioeconomic and behavioral pathways ,81,82,83Although there are many strengths of our study, there are also some limitations. Because MoBa only collected one urine sample during pregnancy, we can only assess exposure at ~17 weeks’ gestation. OPs are quickly metabolized with estimated half-lives between a few hours to several days  and haveIn summary, despite a robust body of evidence linking prenatal OP exposure with adverse neurodevelopmental impacts ,32 inclu


Appropriate and timely administration of intravenous fluids to patients with sepsis-induced hypotension is one of the mainstays of sepsis management in the emergency department (ED), however, fluid resuscitation remains an ongoing challenge in ED. Our study has been undertaken with two specific aims: firstly, for patients with sepsis, to identify factors associated with receiving intravenous fluids while in the ED; and, secondly to identify determinants associated with the actual time to fluid administration.We conducted a retrospective multicentre cohort study of adult ED presentations between October 2018 and May 2019 in four metropolitan hospitals in Western Sydney, Australia. Patients meeting pre-specified criteria for sepsis and septic shock and treated with antibiotics within the first 24 h of presentation were included. Multivariable models were used to identify factors associated with fluid administration in sepsis.p < 0.001); lower systolic blood pressure , p < 0.001); presenting to smaller hospital  and a Clinical Rapid Response alert activated , p < 0.001). Patients with Triage Category 1 received fluids 101.22 min earlier (95% CI (59.3 to131.2), p < 0.001) and those with Category 2 received fluids 43.58 min earlier (95% CI (9.6 to 63.1), p < 0.001) compared to patients with Triage Category 3–5. Other factors associated with receiving fluids earlier included septic shock (-49.37 min (95% CI (-86.4 to -12.4), p < 0.001)); each mmol/L increase in serum lactate levels , p < 0.001) and presenting to smaller hospitals , p < 0.001).Four thousand one hundred forty-six patients met the inclusion criteria, among these 2,300 (55.5%) patients with sepsis received intravenous fluids in ED. The median time to fluid administration from the time of diagnosis of sepsis was 1.6 h (Interquartile Range (IQR) 0.5 to 3.8), and the median volume of fluids administered was 1,100 mL (IQR 750 to 2058). Factors associated with patients receiving fluids were younger age (Odds Ratio (OR) 1.05, 95% Confidence Interval (CI (1.03 to 1.07), Younger age, greater severity of sepsis, and presenting to a smaller hospital increased the probability of receiving fluids and receiving it earlier. Recognition of these factors may assist in effective implementation of sepsis management guidelines which should translate into better patient outcomes. Future studies are needed to identify other associated factors that we have not explored. Sepsis resulting from a dysregulated immune response to infection can progress to septic shock subsequently resulting in organ failure and death . It is oSeveral recommendations have since been advocated by the Surviving Sepsis Campaign including the administration of at least 30 mL/kg of crystalloid fluids within the first 3 h; administration of intravenous antibiotics within the first hour and measurement of serum lactate , 6. FluiWe conducted a multicentre retrospective observational study as part of the Sydney Multicentre Emergency Department Sepsis Archive from four EDs in Western Sydney, Australia with a combined 200,000 ED visits per year. Two of these were larger tertiary level hospitals and two of them were smaller secondary level hospitals. The study period for this project was between October 2018 and May 2019, after the introduction of an electronic fluid management record at each site. All the participating EDs used the Sepsis Pathway as part of the Sepsis Kills Program  with recData included encounters from all adult presentations (over 16 years of age) who presented to the participating EDs. Sepsis was defined as those who met the suspected infection criteria for Sepsis 3 definition . Septic p-values for final models are presented. All potential covariates were included in the initial model, and the final model was developed using a stepwise  approach, and the overall model fit was assessed using Akaike Information Criterion (AIC), the Area Under the Receiver Operator Curve (AUC) for the adjusted and final models which are also presented [p-value of 0.10 as a cut-off, no interaction terms were identified as significant. For these linear multivariable models, the overall fit of the model was assessed using an adjusted R2.All analysis was performed using R statistical language software . Descriptive summaries were produced for: (1) all presentations with sepsis; (2) the subset of these patients who received intravenous fluids; (3) patients who did not receive intravenous fluids; and (4) patients receiving intravenous fluids, categorised by the time of first intravenous fluid administration . Multivariable logistic regression models were used to identify factors associated with receiving intravenous fluid, both crude (univariate) and adjusted estimates of effect are presented as Odds Ratios (OR), 95% confidence intervals (95% CI), and only resented . To explFrom the initial 556,652 ED presentation records, 4146 patients met the inclusion criteria for sepsis . A similar distribution of women and men who did and did-not receive fluids (p = 0.60) was found. Patients receiving fluids weighed less , and had a similar number of documented comorbidities  0.60 (1.19) and 0.76 (1.40) respectively, p = 0.005). Patient subgroup receiving fluids had a greater proportion of Triage Category 1 ( Immediate Simultaneous Assessment and Treatment) [p < 0.001) compared to Triage Category 3 ( Assessment and treatment start within 30 min); Category 4 (Assessment and treatment start within 60 min); and Category 5 (Assessment and treatment start within 120 min), a higher mSOFA , higher median lactate and lower median systolic blood pressure . Subgroup receiving fluids had significantly higher proportion of septic shock patients . Sepsis patients presenting to a smaller compared to larger hospital EDs were more likely to receive fluids . Similarly, patient characteristics based on time to fluid administration categories are presented in Table Characteristics of patients who received fluids and did not receive fluids are presented in Table eatment)  and Catep < 0.001); lower systolic blood pressure , p < 0.001); presenting to a smaller compared to a larger hospital ED ; and a Clinical Rapid Response alert activated , p < 0.001).The factors associated with patients with sepsis receiving intravenous fluids compared to not receiving fluids are presented in Table p < 0.001) and 43.58 min earlier (95% CI (9.6 to 63.1), p < 0.001) respectively compared with those triaged as a less urgent Triage Category 3, 4 or 5. Patients with septic shock received intravenous fluids 49.37 min earlier (95% CI (12.4 to 86.4), p < 0.001) compared with those with no signs of septic shock. Each one mmol/L increase in serum lactate level , p < 0.001) showed statistically significant association with reduced time to fluids. Patients presenting to smaller secondary hospitals received their first intravenous fluids 74.61 min earlier (95% CI (55.3 to 94.0), p < 0.001) than those who presented to larger tertiary hospitals. Factors such as documented immunosuppressant therapy at the time of presentation , p = 0.186) and mSOFA score, for each unit increase , p = 0.524) showed no association with reduction in time to fluids. While these factors were associated with early administration of intravenous fluids, some factors were associated with delayed fluid administration.Several factors were found to be associated with the time to intravenous fluids. Triage Category 1 and 2 were associated with receiving fluids 101.22 min earlier (95% CI (59.3 to 131.2), p < 0.001). Other factors associated with delays in receiving fluids included the systolic blood pressure with each 5 mmHg increase being associated with 15.13 min delay (95% CR (1.45 to 28.81), p < 0.001). Each hour increase in the time to intravenous antibiotics administration was associated with 2.25 min fluid delay (95% CI (1.4 to 3.1), p < 0.001) (Table Each 5-year increase in age was associated with a 4.9 min delay in receiving fluids (95% CI (2.5 to 7.3), Our study has found that on average just over half of the patients presenting to the ED with sepsis received fluids which is less than optimal, and the average time to first fluids was 1.6 h. Unlike other elements of the Surviving Sepsis Campaign bundle, studies have scarcely explored factors associated with intravenous fluid administration . Our stuThe proportion of patients who received fluids in this study is similar to previous retrospective studies , 17. TheOn exploring the factors associated with receiving versus not receiving intravenous fluids, patients who were younger were more likely to receive fluids and increasing age was associated with delayed intravenous fluid administration. This finding is similar to previous studies reporting clinicians’ hesitancy to prescribe fluids in the older population  despite In line with our expectations, a higher proportion of patients with more severe clinical signs of sepsis received intravenous fluids and they were also more likely to receive fluids early. This is most likely associated with indication bias where sicker patients were more likely to be recognised and treated earlier. Recognisable features of illness severity that showed association in this study include signs of septic shock, low systolic blood pressure, and increasing lactate level. Patients who were on immunosuppressants who were more likely to develop severe infections also received fluids earlier. These findings suggest the possibility that clinicians predominantly rely on clinical judgement while administering fluids. While the importance of clinical judgement cannot be disputed, the fact that clinician factors such as inexperience, failure to recognise sepsis, clinical reliance on development of explicit signs of hypotension that have been reported previously as barriers to timely intravenous fluid initiation in sepsis cannot be ignored , 17, 26.Nearly half of the patients with sepsis in this study did not receive intravenous fluids in the ED within the first 24 h. This finding should be interpreted with caution as the study is subject to the limitations of retrospective analysis of information retrieved from eMR and we are unable to associate individual factors such as “Not for Resuscitation” orders, fluid restriction status and any other relevant clinical indications that might potentially contribute to patients not receiving fluids. Nevertheless, the significant proportion of patients who meet the criteria for sepsis or septic shock yet not receiving fluids warrant further exploration in future studies.While among those who received fluids, a total of about 68% of patients received fluids within the first three hours, the others received fluids later. While administration of intravenous fluids within the first 30 min  and largContrary to our expectations and previous study findings , other pThe only non-patient related factor that showed significant association with both the likelihood of receiving fluids and receiving fluids early was presentation to smaller secondary hospitals. While this may be attributed to the characteristics of the tertiary settings which are typically overcrowded resulting in delays in fluid resuscitation , 8, it iThe estimates obtained from our modelling of the timing of fluid administration appear to make clinical sense. For example, using the results from the final model to predict the time to fluid, it was estimated that a young adult patient presenting to a participating smaller ED with sepsis triaged as a Category 2, and a systolic blood pressure of 90 mmHg, lactate more than 2 mmol/L is predicted to receive intravenous fluids 2.4 h earlier than a patient who does not have these characteristics. Recognising these factors influencing fluid administration can be of relevance to clinical practice.The results of this study need to be considered in the context of some potential weaknesses. Despite the large database allowing relevant inference about clinical practice, this was a retrospective observational study and therefore, there is a possibility of unaccounted confounders and causality cannot be established. Although our study included four different hospitals within a single local health district, the findings may not reflect the situation of all EDs in Australia. Some data was missing due to incomplete or data entry errors in the eMR which could potentially have an inclusion bias. Some potentially relevant information such as experience level of the clinician, time of first contact with the medical officer, time of first contact with the nurse after triage etc. could not be retrieved. In addition, the Charlson Co-morbidity Score used in this study was derived using data from admission records, and any detail recorded in medical assessment could not be retrieved potentially impacting the accuracy of the calculated score. The eMR may not have included all interventions performed, for instance information regarding pre-hospital fluid administration were not available. Furthermore, there was a lack of information about other potential causes of hypotension. However, the data extraction process with the electronic time stamps allowed recovery of the majority of potentially relevant variables.Importantly, even though our study has identified several factors associated with who and when individuals presenting with sepsis received fluids in ED, there may be a number of factors we may have missed. They may be factors not routinely captured in patient records such as organisational culture, perceptions and knowledge related issues. Further investigation of other associated factors using qualitative and mixed approaches is essential to obtain a deeper understanding of the facilitators and barriers.Our study has found that on average just over half of patients presenting to the ED with sepsis received fluids, and the average time to first fluids was 1.6 h. Lower age, lower triage category and the presence of more severe clinical signs of sepsis increased the probability of receiving fluids and reduced the time to first fluids. Recognising these patient and non-patient related factors will assist in designing and implementing quality performance improvement initiatives. Awareness of these factors can influence clinician decision making in ED practice environment. Any improvement in sepsis care practice will result in mortality benefits for patients. However, other factors we haven’t explored may determine why and when sepsis patients receive fluids in the ED. Further studies are required to establish a comprehensive understanding of the subjective factors associated with patients receiving early intravenous fluid administration in the emergency department.


Attention Deficit Hyperactivity Disorder (ADHD) is the most prevalent childhood neurodevelopmental disorder. It shares some genetic risk with Autism Spectrum Disorder (ASD), and the conditions often occur together. Both are potentially associated with abnormal glutamate and GABA neurotransmission, which can be modelled by measuring the synaptic activity in the retina with an electroretinogram (ERG). Reduction of retinal responses in ASD has been reported, but little is known about retinal activity in ADHD. In this study, we compared the light-adapted ERGs of individuals with ADHD, ASD and controls to investigate whether retinal responses differ between these neurodevelopmental conditions.−2. The time-to-peak and amplitude of the a- and b-waves and the parameters of the Photopic Negative Response (PhNR) were compared amongst the three groups of participants, using generalised estimating equations.Full field light-adapted ERGs were recorded from 15 ADHD, 57 ASD (without ADHD) and 59 control participants, aged from 5.4 to 27.3 years old. A Troland protocol was used with a random series of nine flash strengths from −0.367 to 1.204 log photopic cd.s.m−2 flash strength (p < .0001), at which the b-wave amplitude in ASD was significantly lower than that in the controls. Using this measure, ADHD could be distinguished from ASD with an area under the curve of 0.88.Statistically significant elevations of the ERG b-wave amplitudes, PhNR responses and faster timings of the b-wave time-to-peak were found in those with ADHD compared with both the control and ASD groups. The greatest elevation in the b-wave amplitudes associated with ADHD were observed at 1.204 log phot cd.s.mThe ERG b-wave amplitude appears to be a distinctive differential feature for both ADHD and ASD, which produced a reversed pattern of b-wave responses. These findings imply imbalances between glutamate and GABA neurotransmission which primarily regulate the b-wave formation. Abnormalities in the b-wave amplitude could provisionally serve as a biomarker for both neurodevelopmental conditions.The online version contains supplementary material available at 10.1186/s11689-022-09440-2. Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental condition and one of the most common mental disorders in children and adolescents , affectiAutism Spectrum Disorder (ASD) is also a neurodevelopmental disorder characterised by persistent deficits in co-occurring impairments of social reciprocity and social communication, repetitive patterns of behaviour and atypical responses to sensory input or unusual interests in aspects of the environment , 14. BotThe eye and neural retina provide a window to the neurobiology of the brain and have been of growing interest to those studying neurodegenerative and psychiatric disorders –27. The Light entering the eye causes retinal cell membranes to hyperpolarise and depolarise at different times. The net signal can be recorded at the front of the eye as the electroretinogram (ERG) waveform. This can be observed as a voltage change over time following the onset of a light flash see Fig. . The ERGThe ERG is increasingly being used to distinguish between psychiatric conditions, such as schizophrenia from bipolar disorder, and to investigate the effects of drug treatment in conditions such as depression –41. In cIn this study, we investigated whether the LA-ERG waveform is different in ADHD individuals compared to ASD and control individuals.Fifteen individuals with ADHD  and fifty-seven participants with ASD (13.7 ± 4.8 years) were recruited. Clinical evaluations were made by specialist paediatric psychiatrists and clinical psychologists in clinics for children with neurodevelopmental disorders at London’s Great Ormond Street Hospital for Children and at local clinics in the UK and South Australia. Diagnostic assessments were supported by parental interviews  , school Male participants predominated in both groups: ADHD (53%) and ASD (75%). All had normal range intelligence: mean full-scale IQ 92.9 ± 14.2 in ADHD and 100.5 ± 19.4 in ASD. ADHD severity scores were based on the ICD-10 Research Diagnostic Criteria and calculated from measures of hyperactivity, impulsivity and inattention provided by parents/carers and schoolteachers for both ADHD and ASD participants. ADHD severity scores range from 0 (no symptoms) to 6; the mean ADHD severity scores in the ADHD and ASD groups were 3.9 ± 0.8 and 2.0 ± 0.7, respectively  in all three groups, and the study was reviewed by the appropriate Institutional Ethics Committees.−2 white background with an average of 60 trials to obtain the waveform with repeated recordings for both eyes. The nine randomised flash strengths were then followed by the ISCEV standard flash 3.0 cd.s.m−2 on a 30-cd.m−2 white background presented at 2 Hz with 30 samples averaged, to generate the waveform. This custom protocol was programmed in the RETeval , which was used for all recordings, using a self-adhesive skin electrode positioned 2–3 mm below the participant’s lower eyelid in accordance with the manufacturer’s recommendation. The RETeval automatically stopped recording if pupil tracking was lost  standard . A custoils, see , 56.TablData were analysed via generalised estimating equations (GEEs). GEEs are non-likelihood models akin to linear mixed-effects models (LMM) in that they deal with clustered data in cases of repeated measures . GEEs alFS•G were significant were further assessed via QIC by retaining significant variables signalled in the full model but leaving out ‘ethnicity’  influenced any of the dependent variables. This analysis was performed via robust linear models. The resulting models were examined via type III ANOVA. If a significant interaction was not present, then the main effects were not analysed further.In all models, ‘participants’ as random effects were entered as the vector which identifies clusters, whilst the covariates listed in Table Gb) and maximal saturated amplitude (Vbmax), respectively [The change of b-wave amplitude with flash strength was plotted as the photopic hill and analysed using a mathematical modelling of combinations of a Gaussian function that represents the OFF-pathway and a logistic function that represents ON-pathway contributions according to its parameter maximal Gaussian amplitude (ectively . As backB2), flash strength (I), semi-saturation flash strength (σ), and Gb and Vbmax of each group were generated using non-linear curve-fitting in OriginPro 2019 following the photopic hill equation which was inputted as a customised equation in the Fitting Function Builder. The parameters between the groups were compared by one-way ANOVA. The correlation plot network between the ERG measures and the cohort phenotypes was produced in Origin 2021b.All the five parameter values, including the measures of the width of the Gaussian curve .A ificance . All R cFS•G) of flash strength and the groups demonstrated a statistically significant differences on three variables  that these were b-wave amplitude (p = 7.8 × 10−7), b-wave time (p = 1.4 × 10−8) and the p72 amplitude (p = .001).GEE was performed in this analysis to compare all the ERG parameters in repeated measures amongst the ADHD, control and ASD groups. Additional file The finding showed a noticeable elevation of the b-wave amplitude in the ADHD group compared to the control and ASD groups, whereas the ASD b-wave amplitude was reduced compared to comparison control. Figure p-values < .005). The photopic hill in Fig. Vbmax, p < .00001) and maximal Gaussian amplitude  in ADHD compared to the other groups  , which the b-time-to-peak of ADHD was 30.6 ± 1.1 ms, compared to 30.8 ± 1.1 ms in Control and 31.2 ± 1.8 ms in the ASD group.In all groups, the b-wave time-to-peak gets later as the flash strength increases. The b-wave time-to-peak differed only at some flash strengths by pairwise comparisons amongst the groups , 0.398 (p = .0011), 0.477 (p < .001), 1.114 (p = 6.21 × 10−5) and 1.204 log cd.s.m−2 (p = .003) amongst the groups. The p72 amplitudes of ADHD subjects were significantly higher than the other two groups at flash strengths − 0.119 and 1.114 log phot cd.s.m−2. The p72 amplitudes of ADHD, Control and ASD at 1.114 log phot cd.s.m−2 were − 10.6 ± 6.3 μV, − 7.3 ± 3.6 μV and − 7.5 ± 4.5 μV, respectively. However, the PhNR parameters did not distinguish ASD from the control group with no significant differences between these groups (p > .24).Variable differences between the ADHD group and the other groups were found in the PhNR p72 amplitude. Figure p = .07), a-wave amplitude (p = .17), Tmin (p = .03), PhNRmin (p = .01), p-ratio (p = .01) and w-ratio (p = .02). Additional file For the other ERG measures, no significant differences were observed in each parameter between the ADHD and the other groups in the multiple comparisons, including a-wave time-to-peak . Additional file Direct measurements of the ERGs before and after taking the medication methylphenidate in five ADHD participants did not reveal significant interactions between flash strength and ADHD medication nor other parameters  compared to the OFF-pathway (p = .0038).Larger b-wave amplitudes in ADHD could be explained by a lower signal threshold in response to a light flash, and the observation is compatible with other findings of an increase in retinal neuronal noise or non-stimulus driven neuronal activity in ADHD , 46. EleA significantly larger PhNR p72 amplitude was observed in the ADHD than in the control group at the higher flash strengths. In contrast, there were no significant differences in any of the PhNR parameters between the ASD and control groups. This finding had previously been reported  and confSeveral studies have examined the signalling interactions between dopamine and glutamate in ADHD , 86, 87.Measuring the severity of ASD and ADHD from a combination of parental/school reports and observation, we did not find any significant association with either b-wave amplitudes or PhNR parameters. Nor did we find any association between these variables and other ERG measures. ERG parameters were independent of both ASD and ADHD severity as well as measures of intelligence, although there was a stronger relationship between the ERG parameters and the ADHD phenotypes.The sample of children with ADHD was small, in part because of our stringency to exclude any participant with associated ASD traits. Replication studies with a larger ADHD sample size across a wider age range could identify the age at which ERG abnormalities emerge, and track their development over time, especially in later adolescence and early adulthood. Collecting a complete set of phenotypic data in all three groups will improve the understanding of the relationship between the ERG measures and the phenotypes. The relationship between ADHD symptoms and biological sex is known to be complex, with evidence that in girls, the phenotype is more inattentive in character and thus clinically elusive . A largeThis study was the first to present the observation, from a robust light-adapted ERG measure, that increases in b-wave amplitude can distinguish children with ADHD from those with ASD and typical controls. The observation of a diametrically opposite pattern of b-wave response in the two conditions implies a biomarker exists that correlates with their clinical characteristics. Consequently, the ERG waveform appears to be a physiological marker that could potentially support their differential diagnosis. Whilst the biological significance of the retinal response requires further investigation, our findings imply the differentiation between the clinically related conditions ASD and ADHD could lie in the balance between the activities of glutamatergic and GABAergic neurotransmitter systems.Additional file 1: Table S1. Comorbidities and medications. Fig. S1. Iris colour index. Table S2. Generalised estimating equations analysis of all the variables. Table S3. Pairwise comparisons between groups. Table S4. The b-wave amplitude, b-time-to-peak and p72 values. Fig. S2. Summary of the ERG measures. Table S5. The effects of ADHD medications. Fig. S3. The effects of ADHD medications on ERG measures. Table S6. Correlations of the ERG measures and phenotypes. Fig. S4. Correlation plot network. Fig. S5. ROC Curve. Table S7. Comparisons of AUC, Cut-off point, Specificity and Sensitivity.