In addition, the PE values of right dorsolateral prefrontal cortex were positively correlated to the ADHD index . These results suggest that complexity analysis of fNIRS signals could be a promising tool in diagnosing children with ADHD.Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in children. Neuroimaging studies have revealed abnormalities of neural activities in some brain regions, including the frontal cortex, striatum, cerebellum, and occipital cortex. Recently, some investigators have demonstrated that nonlinear complexity analysis of neural activity may provide a new index to indicate ADHD. In the present study, we used the permutation entropy (PE) to measure the complexity of functional near-infrared spectroscopy (fNIRS) signals in children with and without ADHD during a working memory task, it was aimed to investigate the relationship between the PE values and the cortical activations, and the different PE values between the children with and without ADHD. We found that PE values exhibited significantly negative correlation with the cortical activations ( It is estimated that about 5–8% of school-aged children are affected by ADHD4. Consequently, children with ADHD have difficulties controlling their behaviors or paying their attentions, which result in an adverse effect on academic performance and social function1. Furthermore, this disorder may increase a risk of other disorders which are not directly related to ADHD, such as antisocial disorders6. Therefore, it is important to explore valid biomarkers for earlier diagnosis and intervention.Attention-deficit/hyperactivity disorder (ADHD) is one of the most prevalent neurodevelopmental disorders, which is characterized by difficulty paying attention, excessive activity, and impulsivity. Generally, ADHD arises in childhood and frequently persists into adolescence and adulthood8, which has been considered as a core deficit in ADHD9. Some subsequent neuropsychological measures have proposed to detect working memory deficits in youth and adults with ADHD11. These impairments in ADHD include the performance on digit span, consonant trigrams and mental arithmetic12. N-back task is a common working memory paradigm, which has been used in many functional neuroimaging researches on ADHD. Functional magnetic resonance imaging (fMRI) data from ADHD adults showed significantly decreased activity in cerebellar and occipital regions and a trend toward decreased activation in prefrontal cortex compared to control subjects during a 2-back task12. Besides, the activation of parietal cortex was also decreased in ADHD patients during a verbal n-back task13. The study of electrophysiological activation during the visual n-back found that frontal theta event-related synchronization was significantly reduced in ADHD compared to control subjects, meanwhile, ADHD patients showed lower alpha event-related desynchronization and higher subsequent alpha event-related synchronization14. These studies indicate that n-back working memory tasks are associated with prefrontal function12.Working memory is defined as the temporary storage and manipulation of information15. The subjects need to wear a cap embedded with detector-emitter pairs of near-infrared light, meanwhile they are without the constraints of confined space. One detector-emitter pair generates one channel. This form makes fNIRS better to localize the neural signals than EEG. In addition, fNIRS is more low-cost and more robust to movement than fMRI. With its relatively low cost, portability, and high ecological validity, fNIRS is particularly suitable for investigating the brain function of children and patients with ADHD17.Recently functional near-infrared spectroscopy (fNIRS) has been applied in the neuroscience, which is a non-invasive optical imaging technique that can measure the concentration changes in oxygenated hemoglobin ([HbO]) and deoxygenated hemoglobin ([Hb]) associated with functional brain activity19. The Go-NoGo task requires individuals to inhibit prepotent response. During the NoGo block, ADHD children had a weaker increase in [HbO] over the prefrontal cortex compared to controls, which indicated that ADHD children were not activating the prefrontal cortex20. In working memory processes, adult patients with ADHD had a reduced lateral prefrontal activation during n-back task21. These studies consistently indicated hypoactivity in the prefrontal cortex in ADHD patients.Many previous studies of fNIRS about ADHD mainly focus on the abnormalities of brain activation during different experimental paradigms. In the studies of subjects performing a Stroop task, which requires the inhibition of competing response, controls had a significant increase in [HbO] over right dorsolateral prefrontal cortex, whereas the ADHD children did not22. Output neurophysiologic signals exhibit complex fluctuations both in spatial and temporal23, which reflect nonlinear dynamical processes24. Consequently, nonlinear analysis was applied to neurophysiologic signals for providing a novel understanding of the complexity of human brain activity and the physiological processes in either healthy or pathological populations26. Several complexity analysis methods were reviewed in Takahashi’s paper24. In the past few decades, novel nonlinear approaches based on entropy have been widely used to measure the complexity of physiological signals. In general, entropy methods describe the degree of underlying randomness of a random signal27. Random signal with large entropy has a high level of randomness, in contrast, random signal with small entropy corresponds a low level of randomness28. Entropy methods have been successfully applied in many areas, such as depth of anesthesia monitoring30, seizure prediction31, and mental disorders24. For example, in studies about ADHD, the sample entropy of EEG signals in the alpha frequency band decreased in ADHD children during a multi-source interference task22, and the adult patients with ADHD showed reduced sample entropy of fMRI signals in frontal and occipital regions during resting state32. These results were consistent with the hypothesis that there is a loss of complexity in the dynamics of many integrated physiological processes with disease34. However, sample entropy is heavily dependent on the data length and may result bias for short data sets35. Moreover, sample entropy is sensitive to parameter choices, especially the selection of similarity criterion36. Permutation entropy (PE) as an appropriate complexity measure for time series can overcome these issues37. PE statistically measures the different orders of neighboring relative values in the time series, rather than estimating the similarity like sample entropy. Therefore, it does not need to set the similarity criterion. According to the report of Bandt and Pompe, PE is robust to the choice of data length (128 samples are sufficient)37. Moreover, PE is a normalized value, which makes the comparison between different results more easily. Therefore, PE may provide a novel tool to investigate neural signals with ADHD.It is well known that the human brain is a complex nonlinear systemIn this study, our aim was to investigate the relationship between the complexity of fNIRS signals and the cortical activation, and the change of brain complexity in ADHD children and controls during an n-back task. To address these issues, we measured the fNIRS signals of both ADHD children and normal controls during a digital n-back task. We used the general linear model (GLM) to detect the activation areas in the both groups during the task. PE was applied to measure the complexity of fNIRS signals. Then, the differences between the PE values of the two groups were further statistically evaluated. Finally, Pearson’s correlation coefficient was used to test the relationship between the PE values and the cortical activations.39, the control and ADHD groups in this study showed poorer performances on the n-back task than those in previous studies. We think the difference of age may be the main reason why the subjects showed poorer performances in this study. The subjects in this study are younger than those in previous studies.The data of reaction time (RT) and accuracy (ACC) were listed in the Table t15 = 5.93, p = 0.001; t15 = 5.17, p = 0.006). We then performed a subtractive contrast (1-back minus 0-back) within each group. In the subtractive contrast, the control group had more significant activation in right DLPFC (channel 3) in 1-back condition than in 0-back condition , and positively correlated to the ADHD index .Significant difference in PE values was found in right DLPFC channel 3). Thus, we used the data of channel 3 in 1-back condition for the correlation analysis. The Pearson’s correlation coefficient was used to test the relationship between the PE values and the cortical activations, and the ADHD index. The results are shown in Fig. . Thus, wIn this study, we used PE to analyze the complexity of fNIRS signals in children with and without ADHD during a working memory task. We investigated the relationship between the complexity  and the activation patterns, and sought the differences in complexity between fNIRS signals acquired from children with and without ADHD during a working memory task.41. However, the disadvantage of AE and SE is that both of them require long, stationary and noiseless data42. Fortunately, PE as a new complexity statistical parameter does not have such limitations. This is because PE calculation just considers the order relation between the values of a time series instead of the values themselves. In addition, the value of PE is based on the distribution of ordinal patterns, PE is therefore less sensitive to noise embedded in fNIRS signals. Meanwhile, PE is conceptually simple, computationally efficient and artifact resistant. Therefore, PE is more suitable for application of complexity analysis to fNIRS signals.The application of complexity analysis to physiological signals has provided important information about cortical abnormalities in neuropsychiatric disorders that may not be apparent by linear analysis. In previous studies, approximate entropy (AE) and sample entropy (SE) have been used for complexity analysis of neural signals in ADHD39. Additionally, in the ADHD group, there are functional deficits of right DLPFC which is as the main neural correlate of the central executive43. The n-back tasks are classical executive function tests in that they require subjects to monitor stimulus and update information in working memory to generate appropriate responses44. In a meta-analysis, Smith et al. reported that an increasing demand on n-back tasks was associated with increasing DLPFC activity in healthy subjects45. As the review of Cubillo et al., there are deficits of executive functions in children and adults with ADHD46. Whether the structural studies or the functional imaging studies, indicated that the DLPFC which is an important region related to the executive functions differentiate ADHD patients from controls. Shallice et al. inferred that the executive function differences between ADHD patients and controls might be associated with a higher-level effort mechanism47.In the present study, we found that the control group significantly activated the right DLPFC and VLPFC in 1-back condition than in 0-back condition, and more strongly activated right DLPFC than the ADHD group. This indicates that greater working memory demands evoke greater activations in brain regions associated with working memory, including dorsolateral prefrontal cortex, inferior frontal junction48. As mentioned above, the ADHD children didn’t activate the right DLPFC due to the functional deficits. This makes the fNIRS signals from the right DLPFC not be modulated by the working memory task in ADHD children. That is to say, the fNIRS signals from the right DLPFC are more random during the working memory task in ADHD children. Therefore, the complexity of corresponding region in ADHD children is higher than that in controls. That is also why the cortical activations and PE values exhibited significantly negative correlation in right DLPFC.In our complexity analysis we found that the PE values of right DLPFC in ADHD children were significantly larger than those in controls. The global PE values of ADHD children were relatively increased during the working memory task. But they were not significantly different. Generally, if the signal is measured from an inactive region, it should contain more spontaneous brain activity, and thus its PE should reach a relatively high value. If the signal is measured from an active region, it should be more ordered, and thus has a smaller PE49. We inferred that there may be three main reasons. First, the fNIRS signals we used were recorded from prefrontal cortex and partial temporal cortex, while the signals previous studies used were recorded from the whole brain. According to the hypothesis that there is a loss of complexity in the dynamics of many integrated physiological processes with disease34, we think the complexity of other regions we did not measure should be lower in ADHD children compared to controls. Second, we used different neuroimaging modalities during different tasks. We recorded the fNIRS signals during an n-back task, while the previous studies recorded their fMRI or MEG signals at resting state. Third, our subjects are younger. The brain signal complexity of healthy subjects will increase with age50, while the brain signal complexity the ADHD patients will not increase due to the neurodevelopmental deficit. These factors combine to cause the results in previous studies different from this study.However, our results are different from some previous studies which reported relatively decreased complexity of brain activity in ADHD subjectsWe think there are two main advantages of PE analysis over traditional activation analysis. First, the PE analysis has the lower signal-noise-ratio requirements than the traditional activation analysis, because the PE analysis is less affected by the amplitude of the signals and less sensitive to the noise embedded in the signals. Second, PE analysis can be applied to both task state and resting state, while the traditional activation analysis can be just used during a task. In the future, we also hope to investigate the complexity of fNIRS signals during resting state in ADHD children. Note that, the two methods describe different physical phenomena. The PE analysis can not supersede the traditional activation analysis. The PE analysis of fNIRS signals just provides a new research perspective on the ADHD.Based on this study, we think there are several implications of the PE value. First, the negative correlation between PE value and activation level implies that the PE value may estimate the cortex activation degree during a cognitive task. Second, the difference of the PE values between ADHD group and control group implies that the PE value may be as a parameter of neurofeedback for rehabilitation of ADHD children. Third, the correlation between PE value and ADHD symptom severity implies that the PE value may serve as a potential candidate for neurophysiologic marker of ADHD.It should be noted that, the results presented in this study might be limited to children samples but not to other age groups. Hence, we should test our results on a larger sample, and consider the effect of age and gender in the further studies. Meanwhile, we just chose the empirical values as the parameters of PE calculation. We should systematically discuss the effect of parameters to PE calculation in the further studies. Furthermore, we also aim to evaluate and compare the complexity of the brain at resting state in the near future studies.To our knowledge, this is the first study to investigate the complexity of fNIRS signals in children with and without ADHD during a working memory task. We evaluated the complexity of brain by using the PE metric. It was found that the cortical activations and PE values exhibited significantly negative correlation, and the PE values of right DLPFC in ADHD children were significantly larger than those in controls. The results reveal that the right prefrontal complexity was changed in ADHD, and suggested that ADHD may be related to neural disconnection. Therefore, the complexity analysis based on PE may provide a new view to understand the neural mechanism of ADHD. Although there are some limitations in this study, we still suggest that the complexity analysis based on PE is a promising tool in diagnosing ADHD.Thirty-one children, consisted of fifteen with ADHD  and sixteen normal controls , participated in this study. Children with ADHD were recruited randomly from Capital Institute of Pediatrics’ Children’s Hospital and diagnosed by an experienced child psychiatrist using the diagnostic interview that assesses ADHD according to the DSM-V criteria. The severity of ADHD symptoms was assessed using the ADHD index from the Conners’ rating scales for parents. No ADHD children exhibited any complication such as neurological limitation, epilepsy, mental retardation, or genetic disorder. In addition, all the ADHD children were drug-naive. The controls were recruited from the local community and had no history of any mental or neurological disorders. The intelligence quotients (IQ) of all children were evaluated by means of the Chinese version of the Wechsler Intelligence Scale for Children-Revised (WISC-R). There were no significant differences between the groups in terms of age and IQ. The detailed demographic data of subjects were listed in Table Figure In this study, we used the ETG-4000  NIRS system working with two different wavelengths of near infrared light (695 nm and 830 nm) to measure the [HbO] and [Hb]. The sampling frequency was 10 Hz. We used a “3 × 11” measurement patch, which was placed on the head with regard to the relevant standard positions of international 10–20 system for EEG electrode placement. The middle inferior optode was placed over Fpz and inferior row of optodes was oriented in direction of T3 or T4 respectively Fig. . In this51, we divided these channels into nine regions as shown in Fig. We mapped fNIRS channels to the corresponding areas of a brain model. According to literature52. Because [HbO] signals can reflect changes in regional cerebral blood oxygenation and provide a better signal to noise ratio53, we only used [HbO] data in this study. The motion artifacts in [HbO] data were corrected using the empirical mode decomposition method54. To remove the high-frequency physiological noise and low-frequency baseline drift, a band-pass filter (4th order infinite impulse response Butterworth filter) between 0.01 to 0.3 Hz was applied to the [HbO] data. At last, the [HbO] data was down-sampled to 2 Hz.The [HbO] and [Hb] were calculated using the modified Beer-Lambert law55. In this study, we also employed GLM to analyze channel-wise hemodynamic responses in the cortex stimulated by the n-back task. GLM models the measured brain response as a linear combination of predicted responses due to variable stimulations plus an error term, which can be formulated as:y is the measured hemodynamic response ([HbO] in this study) at each channel, x0 and x1 are the predicted stimulation-evoked responses (0-back and 1-back) which are generated by convolving the task onset with the canonical hemodynamic response function, GLM analysis has been increasingly used to analyze fNIRS data in many studies to identify cortical areas significantly stimulated by given tasks37 as a quantitative complexity measure of a dynamical time series. With the PE method, a time series is first mapped to a sequence of order patterns based on comparison of neighboring values, and then PE is the statistical measure of relative frequencies of the different order patterns. Given a time series Permutation entropy was originally proposed by Bandt and PompeThe corresponding normalized entropy is defined as follows:The largest value of PE is 1, meaning the time series is random and the smallest value of PE is 0, meaning the time series is absolutely regular. That is, the larger the value of PE is, the more irregular or complex the time series is, and vice versa. The calculation of PE is dependent on the selection of embedding dimension 55 and SPM-fNIRS (https://www.nitrc.org/projects/spm_fnirs/). Last, we used the Pearson’s correlation coefficient to test the relationship between the PE values and the cortical activations, and the ADHD index.For the performance data, two-sample t-test was used for the between-group comparisons. In activation analysis, within-group analysis was performed using one-sample t-test for 0-back contrast, 1-back contrast and subtractive (1-back minus 0-back) contrast; between-group comparisons were completed using two-sample t-test. In PE analysis, the PE values in each condition (0-back and 1-back) were calculated channel by channel for each subject, and the two-sample t-test was performed to identify the significantly different regions between the two groups. Since there are 52 channels, we can calculate 52 values (beta or PE). The t-tests were performed repeatedly across 52 channels. The Bonferroni correction was then applied to correct for multiple comparisons. The p-value × 52 < 0.05 is considered as significant result. The p-value × 52 was reported in this study. The Beta-maps and the PE-maps for both groups were generated by a custom software based on NIRS-SPM


Because the developing brain of a child is vulnerable to environmental toxins, even very low concentration of neurotoxin can affect children’s neurodevelopment. Lead is a neurotoxic heavy metal which has the harmful effect on the striatal-frontal circuit of brain. This area of the brain is known to be closely related to attention deficit hyperactivity disorder (ADHD) pathophysiology. The primary objective of the present study was to investigate whether elevated blood lead concentration is a risk factor for ADHD. The secondary objective was to examine the association between blood lead concentration and symptom severity.We conducted a frequency-matched, hospital-based case-control study with 114 medically diagnosed ADHD cases and 114 controls. The participants were matched for age and sex. The diagnoses of ADHD were assessed with semi-structured diagnostic interviews. The participants completed the continuous performance test (CPT), and their parents completed the ADHD-rating scale (ADHD-RS). Blood lead concentrations were measured by using graphite furnace atomic absorption spectrometry featuring Zeeman background correction.p = 0.003). The log transformed total blood lead concentration was associated with a higher risk of ADHD . The analysis also revealed that the children with blood lead concentrations above 2.30 μg/dℓ were at a 2.5–fold  greater risk of having ADHD. After adjusting for covariates, our multivariate regression models indicated that blood lead concentrations were not significantly associated with ADHD-RS or CPT profiles among the ADHD cases.Children with ADHD exhibited blood lead concentrations that were significantly higher than those of the controls ( 1.90 ± 086 μg/dℓ vs. 1.59 ± 0.68 μg/dℓ, Even low blood lead concentrations are a risk factor for ADHD in children. This study warrants primary prevention policies to reduce the environmental lead burden. Future studies may be required to ascertain the effects of lead on symptom severity in ADHD. Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by persistent and developmentally inappropriate expressions of inattention, impulsivity, and hyperactivity. ADHD is the most common neurodevelopmental disorder in childhood, with a worldwide prevalence of approximately 5 % , 2. BothAmong the environmental factors that are suspected to be associated with ADHD, lead exposure has been implicated in the etiology of ADHD . Lead isPrevious studies have reported that even low levels (<5 μg/dℓ) of lead exposure are associated with inattention and hyperactivity/impulsivity, which are the two core symptom domains of ADHD –15. HoweAnother issue is whether blood lead concentrations are associated with symptom severity in ADHD. Previous population-based studies have reported inconsistent results regarding this issue . PopulatTherefore, this hospital-based case-control study was performed to assess the relationship between blood lead concentrations and ADHD. We defined ADHD cases using a semi-structured interview based on the diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition (DSM-IV) . We alsoThis study has two hypotheses. The primary hypothesis is that children with higher blood lead concentrations will be more likely to be diagnosed with ADHD. The secondary hypothesis is that blood lead concentrations will be associated with the symptom severity of ADHD.The present study was designed to frequency-match cases and controls in terms of age and sex. The study was conducted in four university hospitals  in Busan, Korea, from April to September 2013. All of the participants in this study were recruited in Busan.The ADHD cases met the following inclusion criteria: 1) diagnosis of ADHD by a child psychiatrist based on the DSM-IV [ diagnosiA total of 114 ADHD cases were recruited from child psychiatric clinics at two university hospitals (Donga-A and Inje University). A total of 202 age- and sex-matched controls were recruited from pediatric clinics at three university hospitals . Controls were selected from children with normal physical function, confirmed by pediatrician. After performing the frequency matching by age and sex, a total of 228 children  were ultimately selected.After the children and their legal guardian provided written informed consent to participate, we acquired information about demographic factors and the children’s medical and developmental histories from the self-administered questionnaires. The variables collected by questionnaires were age (year), sex, gestational age (weeks), birth weight (kilogram), parental education , parents' smoking behavior , and economic status .All children completed the computerized Continuous Performance Test (CPT), and their parents completed the ADHD Rating Scale-IV (ADHD-RS). Next, we conducted diagnostic interviews with each child and parent to confirm the diagnoses of ADHD. Subsequently, we collected blood samples from the children to analyze the blood lead concentrations. Ethical approval for this study was obtained from the Institutional Review Board of the National Cancer Center.The diagnoses of ADHD were confirmed based on a semi-structured interview. In the present study, the screening section and the ADHD supplement section of the Korean version of the Kiddie-Schedule for Affective Disorders and Schizophrenia Present and Lifetime Version (K-SADS-PL-K) were used to confirm the diagnoses of ADHD. The K-SADS-PL-K has good to excellent reliability and validity in the diagnosis of ADHD in children .The ADHD-RS is composed of 18 items and scored by a parent . This scAttention and inhibitory control were evaluated with the CPT, which was developed to assess attention and response inhibition in children over 5 year of age . Three sTo determine the levels of lead in the blood, blood samples were obtained from each child via venipuncture in the arm. The blood was drawn into EDTA-containing commercial evacuated tubes (Vacutainer®), and the collected samples were stored at -20 °C prior to analysis. Fifty-microliters aliquots of the blood samples were diluted with 950 μℓ of pretreatment buffer (containing Triton X-100 and ammonium phosphate). The lead levels were measured via graphite furnace atomic absorption spectrometry featuring Zeeman background correction . Commercial reference materials  were used for internal quality control. The method detection limit of blood lead in the present study was 0.076 μg/dℓ and the instrument detection limit was 0.042 μg/dℓ. The sample was analyzed in triplicate. The coefficient of variation was 4.62 % and the RSD (relative standard deviation) was 2.0 %. All analyses were carried out by Dong-A University Heavy Metal Exposure Environmental Health Center . To qualify for equipment assurance, we participated in the German External Quality Assessment Scheme operated by Friedrich-Alexander University.2 tests were used for the nominal variables, and independent t tests were used for the continuous variables.For the between-group comparisons of the demographic characteristics, Pearson’s χTo test our primary hypothesis, odds ratios (ORs) and 95 % confidence intervals (CIs) were estimated via multivariate logistic regression models using ADHD diagnosis as the dependent variable and the blood lead concentration as the independent variable. The lead concentrations were log-transformed to achieve a normal distribution. The lead levels were then categorized into lead concentration quartiles . We treated the blood lead concentration as both a continuous  and categorical (quartile) variable.To test our secondary hypothesis, we conducted multivariate linear regression analysis using ADHD-RS and CPT scores as the dependent variables and the lead concentrations as the independent variable. The regression coefficients were calculated only for the ADHD cases. The covariates considered in analytic models were sex, age, gestational age, birth weight, economic status, parental education, and parents’ smoking behavior.Statistical significance was evaluated using a two-sided design with alpha set to 0.05. Missing data were excluded from our analysis. All analyses were conducted using IBM SPSS Statistics .p = 0.01). Duration of education was shorter for parent of the ADHD case than for that of the control (p < 0.001). The overall scores for ADHD-RS and CPT, with the exception of response time, were significantly higher in the ADHD cases than in the controls  of the blood lead concentrations were 1.90 ± 0.86 μg/dℓ (range: 0.37–5.35 μg/dℓ) for the cases and 1.59 ± 0.68 μg/dℓ (range: 0.18–3.41 μg/dℓ) for the controls. The children with ADHD exhibited significantly higher blood lead concentrations than the controls with effect size (Cohen’s D) of 0.40 (p < 0.05). The analysis also revealed that the children with a blood lead concentrations above 2.30 μg/dℓ were at a 2.5–fold  greater risk of ADHD. The effect of lead concentrations below 2.30 μg/dℓ was not significant.Table After adjusting for the covariates, our multivariate regression models indicated that blood lead concentrations were not significantly associated with ADHD-RS or CPT profiles the ADHD cases Table .Table 4ATwo key findings emerged from the present study. First, even low blood lead exposure is also a potential risk factor of ADHD in children. Second, blood lead concentrations are not associated with the symptom severity of ADHD.In our study, increased ORs for ADHD were observed at low blood lead concentrations, particularly in the concentration range of 2.30–5.35 μg/dℓ. This result is in close agreement with that of Kim S. et al. , who docAnother main finding of the present study is that blood lead concentrations were not significantly associated with either of the symptom domains of ADHD after adjusting for the confounding factors. These findings contrast with those of Nigg et al. , who demOur results exhibited the negative association between blood lead concentration and CPT commission error, albeit not statistically significant. Some previous studies reported positive association , 28, butThe findings of this study must be interpreted within the limitations of the study. First, hospital-based design is subject to selection bias. Our controls recruited from pediatric clinics of three different hospitals. Thus controls in this study would not be representative of the general population. Second, although our study controlled for several covariates, we could not collect the information about intelligence quotients (IQs) and parental history of ADHD. IQ is potential confounder which affects child cognition and behavior. It is possible that IQ would confound ADHD symptoms or affect CPT performance. Although genetic heritability of ADHD is high, it is difficult to assess history of parental ADHD in this study. Diagnosis of ADHD is based on childhood symptoms. We acknowledged that parents could hardly remember inattention or hyperactivity symptoms in their childhood. Furthermore, in our society, ADHD has only in recent decades been recognized by public. Thus, even if they had clinical level of ADHD symptoms in childhood, they rarely have been diagnosed with ADHD. To obtain objective and reliable information of parental ADHD, collateral information from other family members or objective diagnostic tools for adult ADHD are required. Third, we used only a single measure of blood lead level, which limited our ability to investigate the temporal relationship between early life lead exposure and the onset of ADHD. Finally, as noted above, the ADHD treatment histories were omitted from our study.This hospital-based case-control study demonstrated that even low blood lead concentration is also a risk factor for ADHD in children. The environmental risk factors for ADHD have meaningful implications for prevention because they are easier to modify than genetic factors. The current consensus is that there is no safe threshold for neurotoxic lead exposure . The fin


This gene-environment interaction (GxE) has been previously tied to the processing of emotional stimuli, which is increasingly recognized to be a key factor in ADHD-related impairment. The executive control and default mode brain networks play an important role in the regulation of emotion processing, and altered connectivity of these networks has also been associated with ADHD. We therefore investigated whether resting-state connectivity of either of these networks mediates the relation of 5-HTTLPR and stress exposure with ADHD severity. Resting-state functional magnetic resonance imaging, genetic, and stress exposure questionnaire data was available for 425 adolescents and young adults (average age 17.2 years). We found that 5-HTTLPR S-allele carriers showed a more negative relation between stress exposure and connectivity of the executive control network than L-allele homozygotes, specifically in the pre/postcentral gyrus, striatum, and frontal pole. In the default mode network, we found a positive association between the GxE and supramarginal gyrus connectivity. Connectivity of either network did not significantly mediate the effect of this GxE on ADHD. Opposite effects of stress exposure on connectivity in the executive and default mode networks may contribute to findings that stress exposure is associated with lowered cognitive control and heightened levels of rumination and worrying, for S-allele carriers but not L-allele homozygotes. When combined, these effects on connectivity of both networks may relate to the emotional problems seen in individuals with ADHD.We recently reported that the The online version of this article (doi:10.1007/s11682-016-9633-3) contains supplementary material, which is available to authorized users. Numerous papers have reported that people carrying the short variant  of 5-HTTLPR have a stronger association between stress exposure and psychiatric disorders than people homozygous for the long variant of this gene  consisting of individuals with and without ADHD, thus enabling analysis within a wide range of ADHD severity, in accordance with the continuous distribution of ADHD within the population  study  and the medical ethical committee of the VU University Medical Center. All participants signed informed consent .After selection of those who met the inclusion criteria and had complete phenotypic and good quality rs-fMRI data available, our sample consisted of 425 participants from 255 families. This sample contained 161 participants with a full diagnosis of ADHD, 53 participants with subthreshold ADHD .Genotyping was performed as described in Brookes et al.  and in tAs a measure of socio-economic status, the highest successfully completed education level of the parents was recoded into a measure reflecting years of education. This scale contained nine levels, ranging from 0  to 17 (university) years of education Buis . The aveAll subjects were scanned with either a Siemens MAGNETOM Sonata 1.5 Tesla (at VU UMC in Amsterdam) or a Siemens MAGNETOM Avanto 1.5 Tesla (at Donders Centre for Cognitive Neuroimaging in Nijmegen) MRI scanner , using identical protocols. Functional images during rest were obtained using a gradient echo echo-planar imaging (GE-EPI) sequence . Participants were instructed to relax with their eyes open during the rs-fMRI scan, which lasted 8 minutes.Preprocessing consisted of removal of the first five volumes, primary head movement correction by realignment to the middle volume, global 4D mean intensity normalization and spatial smoothing with a 6 mm Gaussian kernel. We corrected for secondary effects of head motion by applying ICA-AROMA, a robust ICA-based strategy for automatic detection and removal of motion-related artifacts , as calculated by the root mean squared of the frame-wise displacement time series. Subsequently, 19 individuals were removed based on scan quality , and 18 due to incidental findings after visual inspection (e.g. enlarged ventricles or unexpected hypo-intensities), for our final sample size of n = 425.Starting out with 486 participants who had behavioral and rs-fMRI data available, we first excluded the top 5 % of participants with highest motion score , as previously reported in a sample from which the current sample is a subset , but not in L-allele homozygotes .The executive control network covers large portions of the medial frontal lobe, frontal pole, and basal ganglia. The corresponding brain map is displayed in the 5-HTTLPR genotype bilaterally in the precentral gyrus extending into the postcentral gyrus, right frontal pole, left thalamus and caudate nucleus


Attention Deficit / Hyperactivity Disorder (ADHD) and Chronic Tic Disorder (CTD) are two common and frequently co-existing disorders, probably following an additive model. But this is not yet clear for the basic sensory function of colour processing sensitive to dopaminergic functioning in the retina and higher cognitive functions like attention and interference control. The latter two reflect important aspects for psychoeducation and behavioural treatment approaches.Colour discrimination using the Farnsworth-Munsell 100-hue Test, sustained attention during the Frankfurt Attention Inventory (FAIR), and interference liability during Colour- and Counting-Stroop-Tests were assessed to further clarify the cognitive profile of the co-existence of ADHD and CTD. Altogether 69 children were classified into four groups: ADHD (N = 14), CTD (N = 20), ADHD+CTD (N = 20) and healthy Controls (N = 15) and compared in cognitive functioning in a 2×2-factorial statistical model.Difficulties with colour discrimination were associated with both ADHD and CTD factors following an additive model, but in ADHD these difficulties tended to be more pronounced on the blue-yellow axis. Attention problems were characteristic for ADHD but not CTD. Interference load was significant in both Colour- and Counting-Stroop-Tests and unrelated to colour discrimination. Compared to Controls, interference load in the Colour-Stroop was higher in pure ADHD and in pure CTD, but not in ADHD+CTD, following a sub-additive model. In contrast, interference load in the Counting-Stroop did not reveal ADHD or CTD effects.The co-existence of ADHD and CTD is characterized by additive as well as sub-additive performance impairments, suggesting that their co-existence may show simple additive characteristics of both disorders or a more complex interaction, depending on demand. The equivocal findings on interference control may indicate limited validity of the Stroop-Paradigm for clinical assessments. Attention Deficit / Hyperactivity Disorder (ADHD) and Chronic Tic Disorder (CTD) are considered as neurodevelopmental disorders DSM-V , and botADHD dysfunctions in dopaminergic fronto-striatal neuronal networks may play an important role in the development and retention of problems with inhibitory executive functions or cognitive control as one of its core deficits ),2>10.5% explained variance) with 80% power (1-β) and α set to 5%; considering also trends (α<10%) highlight almost medium effects (η2>8.4%).The available total sample of 69 participants permits the detection of large effects  in a noise-shielded room. Besides the main parameters for the current study, children also underwent standardized IQ-testing, tests of Spelling Abilities and Word Fluency , see Tab and a clColour discrimination as measured by the Farnsworth-Munsell 100 hue Test is frequently used in ophthalmological investigations [igations . The tesigations , but coligations  and possigations .Sustained attention was assessed with the Frankfurt Attention Inventory (FAIR). This 6-minute paper-and-pencil test requires marking two prespecified targets in a row of items with a line drawn continuously along each row. An example of the test procedure and a more detailed description is given in the Figure A in Interference Control was assessed with two conditions of a computerized single trial Stroop-Task: one condition used colours as targets (coloured bars or colour words printed in incongruent colours); and the other used quantities (squares or numbers printed in black) used as targets presented in neutral or incongruent stimuli , intra-individual reaction-time variability (RT-SD) and response accuracy (percentage of correct responses) were recorded for each condition.2 with part. η2>.01 considered as small, part. η2>.06 as medium and part. η2>.14 as large effects [The dependent variables were tested in a 2×2 factorial design with the between subject factors “ADHD” (children with vs. without ADHD) and “CTD” (children with vs. without CTD disorder). In the Farnsworth-Munsell 100hue Test, error-scores on the red-green and blue-yellow axes were analysed as repeated measures on within-subject factor “Axis”  and z-transformed numbers of correct responses . Main effects would thus indicate general performance differences; interactions with the speed-accuracy factor would indicate relative shifts in the trade-off.(69)>.92, p <.01), this total error score in addition with IQ  and age  were used as covariates in the general linear model of the speed-accuracy assessment, including the main and within-subject interaction effects with the covariates.The influence of colour perception was explored as following: since error scores on the blue-yellow and red-green axes are highly correlated with the total error score in the overall sample /3(number of hypotheses) = .033.In the following section we present the results of the 2×2 factorial design. If not otherwise stated, ADHD and CTD are thus regarded as factors. E.g. ADHD denotes children with pure ADHD and ADHD+CTD in comparison with Controls and pure CTD, whilst the CTD factor comprises the comparison of pure CTD and ADHD+CTD in comparison with Controls and pure ADHD groups. In case of significant interaction effects between ADHD and CTD, the four groups were compared in post-hoc tests to further clarify violations of the additive model of ADHD and CTD co-occurrence.>5.0, p <.03, part η2>.07), but problems regarding Hyperactivity, Conduct Problems and Total Problems were particularly present in the ADHD-only group > 7.4, p <.01, part η2>.11). Children with CTD were rated with higher scores for Emotional Symptoms  = 6.2, p = .02, part η2 = .09) while other comparisons revealed no differences <2.0, p>.17, part η2 <.03, see The parent-rated SDQ revealed problems in children with ADHD for all scales  = 22.6, p <.01, part η2 = .26) and CTD  = 36.5, p <.01, part η2 = .36) were additive  = 1.7, p = .20, part η2 <.03, see  = 15.2, p <.01, part η2 = .19), where children with ADHD tended to have more pronounced difficulties discriminating blue-yellow  = 3.1, p = .08, part η2 = .05, but impairments in ADHD were significant on both axes & CDT*Axis: F = 1.4, p = .25, part η2 = .02, see Table A in As reported previously , colour  = 3.5, p = .07, part η2 = .05, but significant for “Q” and “K”, both F>4.7, p< = .03, part η2 = .07, see Table A in  = 4.2, p = .05, part η2 = .06). However, with the exception of false alarms, these ADHD effects disappeared  or were diminished to a trend (Q) when controlling for IQ.Attention was measured with the FAIR including the performance parameter L (number of concentrated processed items during the 6 min assessment), quality  and continuity (K). Children with ADHD showed diminished attention on all three parameters <1, p = .93, part η2 <.01), and slower in incongruent compared to congruent trials  = 115.6, p <.01, part η2 = .64). A significant main effect CTD  = 7.2, p = .01, part η2 = .10) and an interaction CTD*Condition  = 4.6, p = .04, part η2 = .07) were further clarified with post hoc analyses of confidence intervals: children with CTD showed slower RTs in both conditions (p <.05), and tended to be slower in the colour Stroop (p <.10) while children without tics showed rather  the opposite pattern. No significant main effects or interactions with ADHD, and no interactions with Congruency were found <1.1, p>.30, part η2 <.02, see Table B in Overall, reaction-times were similar for both Stroop-Tests <1, p = .94, part η2 <.01), but lower in incongruent trials  = 75.3, p <.01, part η2 = .54). However, besides the interaction CTD*Condition  = 7.5, p <.01, part η2 = .10), there was also a three-way interaction Condition*ADHD*CTD  = 14.8, p <.01, part η2 = .19) was found. Moreover, there were also two- and four-way interactions involving Condition and Congruency  = 3.2, p = .08, part η2 = .05 and Condition*Congruency*ADHD*CTD: F = 7.0, p = .01, part η2 = .10): Post-hoc analyses separately for each Condition revealed significant Congruency effects in both Stroops >24.5, p <.01, part η2>.27) without any group differences in the Counting Stroop <1.1, p>.31, part η2 <.02), but for the classical Colour Stroop an interaction ADHD*TIC  = 9.9, p <.01, part η2 = .13, see Table B in Accuracy was similar in both Stroop conditions <1). Children with ADHD achieved lower speed-accuracy performance  = 11.3, p <.01, part η2 = .15)  whilst CTD and the interaction ADHD*CTD had no effect on general speed-accuracy in the Stroop-Tests <1.5, p>.23, part η2 <.02).For the performance analysis taking speed and accuracy as factors, the parameters were at first z-standardized separately for congruent and incongruent trials of each of the two single trial Stroop-Tests. Therefore, no main effects of the within-subject factors Speed-Accuracy (S_A), Condition and Interference remained in this comparison  = 8.3, p <.01, part η2 = .11), S_A*Condition*CTD  = 9.7, p <.01, part η2 = .13) and S_A*Condition*CTD*ADHD  = 7.3, p <.01, part η2 = .10). Separate analyses of the difference in the z-standardized reaction-times and accuracy rates revealed differences between the two tasks: for the Colour-Stroop, a main effect of CTD  = 15.0, p <.01, part η2 = .19) and an Interaction ADHD*CTD  = 4.3, p = .04, part η2 = .06) was present. Post-hoc tests showed that in the pure ADHD group speed was emphasized over accuracy  whilst in children with ADHD+CTD and as a tendency also in children with pure CTD disorder (p <.10) accuracy was accentuated. For the Counting-Stroop, no group differences in speed-accuracy trade-off were found <2.2, p>.14, part η2 <.03, see Figure C in Several interactions including speed-accuracy (S_A) reached significance: S_A*CTD  = 5.0, p = .03, part η2 = .07) which was further explored with the Congruency differences, separately for both Stroop-Tests. In accordance with the separate analyses of response speed and accuracy, the congruency effect in the Colour Stroop was larger in children with pure ADHD and pure CTD, and smallest in controls and children with comorbid ADHD+CTD, whilst in the Counting Stroop the Congruency effects on speed and accuracy combined did not differ between groups  initially entered as covariates; IQ was then dropped since it had no significant impact. = 8.5, p = .01, part. η2 = .12) and in children with better colour discrimination  = 6.1, p = .02, part. η2 = .09), as well a shift towards speed with ageing  = 3.6, p = .06, part. η2 = .05 & S_A: F = 3.2, p = .08, part. η2 = .05 –this is mainly due to faster RT, whilst accuracy remains unchanged with age). Importantly, total error score did not interact with the Congruency effect <1.2, p>.28). Moreover, with the exception of the strong ADHD main effect  = 3.6, p = .06, part. η2 = .05), all the significant effects from the speed-accuracy analysis above were replicated with Age and colour discrimination total error score covaried.This covariance analysis revealed better combined speed-accuracy performance in older children  permitted the detection of large effect sizes with a conventional α< 5% and a power of 80%, and close to medium effect size if trends α< 10% were also considered. Since impairments in ADHD are expected to be large, the current sample is adequate for detection, but as CTD and potential (sub-additive) ADHD*CTD interaction effects may be smaller, potential relevant effects may remain undetected even if trends were considered.The gender ratio was successfully matched, thus assessment of possible gender effects were beyond the scope of the current study, and conclusions can only be drawn regarding clinical referrals, which are predominantly boys.Psychopathological ratings obtained with the parent-rated SDQ revealed broad difficulties for children with ADHD. Children with CTD showed higher ratings of emotional problems, following an additive model. Sub-additive effects on Hyperactivity, Conduct Problems and also Total Problems may indicate that in children with co-existing ADHD+CTD psychopathological difficulties may follow ADHD, but may rather be compensated by the co-existing CTD . This maColour discrimination impairments of large effect size are present in ADHD and CTD following an additive model. This previously reported finding suggests that deficits in ADHD and CTD may simply add-up in children with co-existing ADHD+CTD, suggesting that ADHD+CTD may represent a simple combination of both disorders and no distinct clinical entity . This leAs expected from the retinal dopaminergic hypothesis , difficuThe current results also agree partly with findings in adults with ADHD, which showed higher total error scores in the FMT and particularly pronounced deficits along the blue spectrum, but with considerably lower (medium) effect size that detected in this study with children . One mayThe three main outcome variables of the FAIR  revealedDeficits with Cognitive Control in ADHD are a frequently reported finding in ADHD, and early cognitive theories suggest that in particular behavioural inhibition may be “the” core deficit of ADHD . This viResponse speed was generally slower in children with CTD, but no considerable differences regarding interference liability between groups were detected. On the other hand, important effects regarding accuracy were found for children with ADHD who performed less accurate in both Stroops. Besides these general accuracy effects, the Colour Stroop revealed larger Congruency effects on accuracy in both pure ADHD and CTD groups, whilst the Counting-Stroop did not. Importantly, this divergent finding was driven by larger congruency effects in Controls and comorbid ADHD+CTD, whilst both pure ADHD and CTD groups accuracy remained unchanged. One may speculate whether differences between colour naming and counting on the one hand and the mapping of the response to the respective button might have played a role.The current single-trial Stroop-Tests differentiate speed and accuracy as two aspects of task performance. The data revealed large Congruency effects in response speed and accuracy, for both Colour- and Counting-Stroops. combined analysis of both speed and accuracy in one statistical model revealed several important effects. First, in the Colour Stroop, children with ADHD showed (compared to controls) a significant shift towards response speed on the expense of accuracy, whilst in comparison children with CTD and also those with ADHD+CTD showed a shift towards more accurate responses. Hence, response style may be an important neuropsychological difference between ADHD (i.e. speed) and CTD (i.e. accuracy). However, as the current Stroop implementation revealed differences between groups not in response speed, but rather accuracy, these combined speed-accuracy analyses merely reflect accuracy findings. The missing of such differential trade-offs in the Counting Stroop must remain unexplained by our data.The Since at least the Colour-Stroop relies on colour processing, performance may be moderated by colour discrimination, and deficits as detected here in ADHD and CTD may compromise the interpretation. The current analysis of covariation indicated that colour discrimination had an unspecific impact on Stroop performance and may partly explain these unspecific performance problems in children with ADHD. A more recent study with adults suggest that exogenous covert attention (modulated by cue presentation) may has an impact on colour saturation discrimination, but this may not explain impairments in ADHD . But as The current study has limited statistical power, and as such potentially relevant small to medium sized effects may remain undetected. However, the detected attention difficulties in ADHD, additive colour discrimination deficits in ADHD and CTD, as well as the sub-additive effects on interference load in the Colour-Stroop, were in fact of medium to large size, suggesting that sample size was at least adequate for testing the current hypotheses, but a larger sample would nevertheless mean a stronger empirical basis for the interpretation of the results. Further comorbidities, with the exception of severe psychiatric (e.g. Autism Spectrum Disorder) or neurologic disorders that may mimic ADHD or CTD, were not considered in the current study. Another important limitation is our limited understanding of the equivocal interference effects, namely that Controls and children with ADHD+CTD showed difficulties in the Counting- that were not present in the Colour-Stroop, and the role of colour perception thereon. To our understanding, this predicament requires further research particularly on underlying brain activity before definitive conclusions can be drawn.The current study further elucidated the impact of ADHD and CTD and their co-existence on neuropsychological functions. The co-existence of ADHD and CTD may thus be characterized as a hybrid: Attention problems may be a part of lower general cognitive ability in ADHD and may be not a major issue in pure CTD. Colour discrimination deficits associated with dopaminergic dysfunctions may be independently associated with both ADHD and CTD, and may thus be particularly expressed in co-existing ADHD+CTD, following an additive model. Interference control assessed with parallel Stroop-Tests yielded equivocal effects that may not be clarified by colour discrimination deficits: while the Colour-Stroop showed impairments in children with ADHD and CTD, but not in comorbid ADHD+CTD, the parallel Counting-Stroop did not show performance deficits in patients.Taken together, ADHD and CTD are associated with neuropsychological deficits probably related to dopaminergic dysfunctions. Attention deficits were primarily associated with ADHD while colour discrimination deficits were driven by ADHD and CTD following an additive model. Equivocal findings regarding interference control may indicate limited validity of the Stroop-Paradigm for clinical assessments.S1 FileTable A gives mean scores and standard deviations of spelling ability and word fluency, Farnsworth-Munsell 100 hue error scores and scores from the FAIR attention test. Table B gives performance data (mean RT of correct responses and error-rates) from the Colour- and Counting-Stroop. Figure A gives example of the Frankfurt Attention Inventory (FAIR). Figure B illustrates the Stroop Response-Pad layout. Figure C gives confidence intervals from the analysis of inter-individual speed-accuracy tradeoff.(PDF)Click here for additional data file.


Olefin metathesis using ruthenium carbene complexes is a useful method in synthetic organic chemistry. Enyne metathesis is also catalyzed by these complexes and various carbo- and heterocycles could be synthesized from the corresponding enynes. Dienyne metathesis, cross enyne metathesis and ring-opening enyne metathesis have been further developed. Various complicated compounds, such as the natural products and the related biologically active substances, could be synthesized using these metatheses reactions. Skeletal reorganization using the transition metals and metallotropic rearrangement are also discussed. Introduction1. Ring-Closing Enyne Metathesis2. Ring-Closing Dienyne Metathesis3. Cross Enyne Metathesis4. Ring-Opening Enyne Metathesis5. Skeletal Reorganization Using Transition Metals6. Metallotropic RearrangementPerspectiveet al. found that molybdenum carbene complex 1a was effective for olefin metathesis anthraquinone skeleton. Utilization of this strategy, total synthesis of YM-181741, (+)-ochromycinone, (+)-rubiginone B have been accomplished ..73].An interesting acceleration effect of an allylic hydroxy group on ring-closing enyne metathesis has been demonstrated. Ring-closing enyne metathesis of terminal alkynes possessing an allylic hydroxy group proceeded smoothly. The synthesis of (+)-isofagomine with the aid of this efficient reaction has been demonstrated .86 having double and triple bonds at the appropriate positions in the carbon chain gave compound 87 in high yield in one step, although many processes were contained in this reaction as shown in Grubbs demonstrated the synthesis of various fused polycyclic compounds using tandem metathesis reaction. A steroidal skeleton could be constructed using tandem enyne metathesis. Treatment of polyenyne et al. -anthramycin.Synthesis of anthramycine derivative M and CM  77]. L-. L-99a walyst 1j ,21. The 100 using 1g followed by methylation gave bicyclic compound 101. Cross metathesis of 101 and methyl vinyl ketone in the presence of 1g afforded (-)-dihydroxanthatin (Morken and Evans succeeded in the synthesis of (-)-dihydroxanthatin using RCM and CM . Enyne manthatin .102 followed by desilylation gave lactone 104. The total synthesis of 8-epi-xanthatin was directly achieved by tandem RCM-CM of lactone 104 using 1h in the presence of an excess amount of methyl vinyl ketone in one step  furnished cross-coupling product 122 3 gave 138a and 138b. Protection of the hydroxyl group of 138a gave 139a, and then it was led to compound 140, which was already converted into (±)-guanacastepene A -erythrocarine was achieved by Mori using dienyne metathesis . Synthesrocarine . Hatakeyet al. succeeded in a diastereoselective total synthesis of (-)-securinine in an optically pure form by employing RCM of the corresponding dienyne 150 as a key step ..174 was 2Cl2 solution of alkyne 178a was stirred under an atmosphere of ethylene at room temperature in the presence of 1c, 1,3-diene 179a was obtained in 62% yield. It is interesting that, formally, the double bond of ethylene is cleaved and each methylene part of ethylene is introduced onto the alkyne carbon to produce 1,3-diene 179 -amphidinolide E, whose side chain was constructed using cross enyne metathesis ,114. Alkachieved .Recently, same group succeeded in the total synthesis of amphidinolide K using intramolecular cross enyne metathesis in the key step .214 was treated with molybdenum complex 215 to give macrocycle 216 in 84% yield. Then an intermolecular enyne metathesis of the resulting cycloalkyne 216 with ethene was used to set the vicinal exo-methylene branches. From this compound 217, amphidinolide V was synthesized. As the result, the absolute configuration of amphidinolide V was determined to be as 8R, 9S, 10S, 13R 2 as a catalyst (E-243a (E/Z=80/20) was carried out in the presence of [RuCl2(CO)3]2 under carbon monoxide, E-isomer 244a was produced predominantly. It is interesting that from Z-243a (E/Z=11/89), E-244a was formed. An E/Z mixture of 1,7-enyne 243b afforded only E-isomer of 244b in 86% yield.In 1994, Murai and Chatani reported skeletal reorganization of 1,6-enyne using 2 in toluene at 80 °C for 4 h to give tetracyclic compound 246 containing two cyclopropane rings in 84% yield. It is interesting to note that other transition-metal complexes, such as PtCl2, [Rh(OOCCF3)2]2, [IrCl(CO)3]n, and ReCl(CO)5 also showed catalytic activity for this very complex transformation.They speculated that complex reaction . To trapRh(II)-catalyzed skeletal reorganization of 1,6- and 1,7-enynes through electrophilic activation of alkynes was also reported ,140.2 -panaxytriol  shift of which gave ruthenium carbene complex 272. Cross metathesis of 272 and alkene 269 afforded compound 270. From this compound 270, -panaxytriol could be synthesized -tricholomenyn.Total synthesis of (+)-asperpentyn and (-)-tricholomenyn A have been accomplished by implementing this metathesis-based tandem reaction sequence as the key step . CompounSince the discovery of stable and isolable catalysts for metathesis by Schrock and Grubbs, a wide range of olefin metatheses have been reported, and olefin metathesis now plays an important role in natural product syntheses. Enyne metathesis, dienyne metathesis, cross enyne metathesis, and ROM of cycloalkene-yne have also been developed. Furthermore, skeletal reorganization using the transition metals or metallotropic rearrangement is a unique reaction. Novel procedures for the synthesis of the natural products and related compound, various complex molecules and macrocyclic compounds would be further developed using these various enyne metatheses. The retrosynthetic analysis of the natural products using these enyne metatheses would be completely different from that of the previous synthesis and the steps for the synthesis of these compounds would be shortened.


Background: Attention-deficit/hyperactivity disorder (ADHD) is a highly genetic neurodevelopmental disorder, and its dysregulation of gene expression involves microRNAs (miRNAs). The purpose of this study was to identify potential miRNAs biomarkers and then use these biomarkers to establish a diagnostic panel for ADHD.Design and methods: RNA samples from white blood cells (WBCs) of five ADHD patients and five healthy controls were combined to create one pooled patient library and one control library. We identified 20 candidate miRNAs with the next-generation sequencing (NGS) technique (Illumina). Blood samples were then collected from a Training Set (68 patients and 54 controls) and a Testing Set (20 patients and 20 controls) to identify the expression profiles of these miRNAs with real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). We used receiver operating characteristic (ROC) curves and the area under the curve (AUC) to evaluate both the specificity and sensitivity of the probability score yielded by the support vector machine (SVM) model.Results: We identified 13 miRNAs as potential ADHD biomarkers. The ΔCt values of these miRNAs in the Training Set were integrated to create a biomarker model using the SVM algorithm, which demonstrated good validity in differentiating ADHD patients from control subjects . The results of the blind testing showed that 85% of the subjects in the Testing Set were correctly classified using the SVM model alignment . The discriminative validity is not influenced by patients' age or gender, indicating both the robustness and the reliability of the SVM classification model.Conclusion: As measured in peripheral blood, miRNA-based biomarkers can aid in the differentiation of ADHD in clinical settings. Additional studies are needed in the future to clarify the ADHD-associated gene functions and biological mechanisms modulated by miRNAs. This dirategies .Genetic factors play an important role in the etiology of ADHD , and theMany animal studies have demonstrated that miRNA expression  or miRNA target genes  are associated with phenotypes of ADHD animal models –28. WithCurrently, no study has applied the NGS technique to identify miRNA biomarkers in order to assist with the differential diagnosis of ADHD. Although ADHD is a brain-based neurodevelopmental disorder, identifying miRNA expression in brain tissue of living is impossible in clinical settings. Relatively, detecting miRNA expression from peripheral blood is a feasible substituting method. Plasma and white blood cells (WBCs) have been suggested as biomarker sources and to identify circulating plasma-based miRNA biomarkers for neuropsychiatry diseases , 43. HowOur research protocol was approved by the Institutional Review Board (IRB) at Chang Gung Memorial Hospital in Taiwan. We obtained written informed consent from the parents or guardians of all the participating children in accordance with the Declaration of Helsinki. This study consisted of eligible patients with ADHD treated in the outpatient Department of Child Psychiatry at Chang Gung Children's Hospital in Taiwan and healthy control children from May 2015 to February 2017. The criteria for ADHD patients included the following: (a) a clinical diagnosis of ADHD by a senior child psychiatrist based on the criteria provided in the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) after structured interviews based on the Chinese version of the Schedule for Affective Disorders and Schizophrenia for School-Age Children, epidemiologic version (K-SADS-E) ; (b) ageThe healthy control subjects were children without ADHD, who were ethnically Han Chinese and between the ages of 6 and 16 years old within the same catchment area. The participants had to be children without any known major physical illnesses or any of the aforementioned major neuropsychiatric diseases.Figure We collected approximately 5 ml of whole blood from each subject with Vacutainer® Blood Collection Tubes . The collected whole blood samples were placed in a centrifuge  with the red blood cell (RBC) lysis buffer (RBCBioscience) added to remove the RBCs. Next, the RBC-free pellets were collected and processed with the mirVana miRNA isolation kit (Life technology) to extract total RNAs from the WBC. The blood samples in the same batch were processed in parallel. As a result, the whole procedures were finished in 4 h from initial blood drawing to final RNA harvesting. The integrity of the RNAs was determined using Agilent 2100 (Agilent Technologies). We excluded all samples with an RNA integrity number (RIN) less than 8.SRP140588.NGS is a highly sensitive technique to globally screen miRNA expression profiles. The RNA samples from the five ADHD patients and five healthy controls were evenly mixed to generate one pooled patient library and one control library, respectively. The two pooled RNA libraries were prepared with TruSeq Small RNA Preparation protocol (Illumina). Then, the prepared amplicon products were examined with high-sensitivity DNA 1000 kit of Bioanalyzer 2100 (Agilent) to confirm successful preparation. Next, the amplicon products were sequenced with a V3 150-cycle sequencing reagent on the MiSeq facility (Illumina) to generate 51-nt single-end reads. The generated NGS data were analyzed with miRSeq tool kit  with defWe employed real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) to determine the expression profiles of the 20 miRNAs in all the samples from the enrolled subjects. The RNA samples were first reverse transcribed into cDNAs with High-Capacity cDNA Reverse Transcription Kit  as the manufacturer's instructions. Then, we further used the TaqMan MicroRNA Transcription Kit  to prepare the RNA samples. The sequence and Assay ID for each miRNA kit are available in Supplementary Table A senior psychiatrist used the K-SADS-E diagnostic tool  to interp-values of < 0.05 were considered statistically significant.We analyzed data using the statistical software package SPSS, version 16.0  and the MedCalc software Version 15.11.4. Variables were presented as either the mean (standard deviation) or frequency. Two-tailed t-test or Mann-Whitney U test was utilized to determine the potential difference in age, clinical assessments, and miRNA expressions between the ADHD patients and healthy controls. The Multivariate Analysis of Covariance (MANCOVA) was used to examine whether age, sex, or intelligence quotient functioned as confounding factors in miRNA expression between ADHD patients and controls.We applied the Chi-square test or Fisher's exact test to compare gender distribution between the ADHD patients and the controls. An independent A support vector machine (SVM), a type of machine learning algorithm, can effectively handle binary classification problems and is suitable for disease diagnosis or prognosis applications , 51. A lWe further performed sensitivity analyses to test the robustness of our results. First, we combined all of the participants in the Training Set and Testing Set and categorized them into a younger group and an older group based on the median age of 108 months. We then used ROC analysis to examine whether the probability scores produced by the SVM model effectively differentiates patients from controls in both age groups. The ROC analysis was also applied to investigate the discriminative validity in boys and girls. Finally, we used Pearson correlation to estimate the relationships between the probability score and ADHD symptoms in all patients.p = 0.001) and younger (p = 0.047) and to have a lower intelligence quotient (p < 0.001), higher inattention scores (p < 0.001), and higher hyperactivity/impulsivity scores (p < 0.001) as rated by parents, teachers, or clinicians.Table The miRNA profiling data from the NGS technique is shown in Supplementary Table p < 0.05, Figure p-value < 0.1 .To examine the strength of this biomarker panel, an independent cohort that included 20 ADHD patients and 20 healthy control subject was recruited as the Testing Set to conduct a blind test. No significant differences were found in age, gender, or intelligence quotient between ADHD patients and controls Table . We detep < 0.001) and the younger group . Moreover, the gender-stratified analysis showed that the SVM model can still significantly differentiate patients and controls both in males  and in females . Lastly, we observed that the probability score yielded by the SVM was positively correlated to the inattentive symptoms rated by parents , teachers , or clinicians , as well as the hyperactivity/impulsivity symptoms rated by parents , teachers , or clinicians .As demonstrated in Figure p < 0.05, only let-7g-5p, miR-30e-5p, miR-223-3p, and miR-486-5p have predicted target gene data. We then generated a set of 2,510 non-redundant target genes, followed by pathway enrichment analysis with Partek Genomic Suite. As shown in Supplementary Table We are curious about the possible regulation roles of these biomarker miRNAs, we analyzed the pathways enriched by the biomarker miRNAs' predicted target genes by downloading their target genes from TargetScan 6.2. Of the nine miRNAs with To the best of our knowledge, this report is the first to use global screening technology (NGS) to explore candidate miRNA biomarkers for ADHD. Furthermore, we argue that this study is the foremost in providing evidence that combining differential expression levels of miRNAs in WBC may be helpful to differentiate patients with ADHD from healthy control subjects.ADHD is a highly genetic neurodevelopmental disorder . PreviouPrevious studies have indicated that several miRNAs  may be associated with ADHD , 37, 38.We must mention that the patients and controls in our Training Set were not matched in demographic characteristics. Ziats and Rennert  reportedp = 0.00031), which regulates synaptic transmission and controls neural network development (p < 0.05), only four of them had target gene data, included in pathway enrichment analysis. In other words, more than half miRNAs were missed which was the limitation of this study. In addition, for the miRNAs with p < 0.1, we did not have their target gene data so that they were also excluded in target gene enrichment analysis which was another limitation of this study.We are curious about the possible regulation roles of the biomarker miRNAs, and we identified 56 significant pathways enriched by 2,510 predicted target genes using Partek Genomic Suite. Of the significant pathways, we are especially interested in axon guidance pathway (elopment . The dyselopment . TherefoAmong the initial 2,510 genes, 35 were enriched in Axon Guidance pathway. And, six of them were co-regulated by equal to or more than two miRNAs, including SRGAP3, EPHA3, PLXNC1, RASA1, SEMA3A, and UNC5C. After examining the regulation route of Axon Guidance pathway, we found that these co-regulated genes usually played the critical roles, either the membrane receptor or the signal transduction hub. For example, UNC5C, PLXNC1, and EPHA3 encodes the proteins of membrane receptors responsible for transducing external stimuli into cells. SRGAP3 and SEMA3A function as irreplaceable intermediate of signal transduction. Such multiple-miRNA regulation phenomenon constitutes a sophisticated modulation mechanism.This study has several methodological issues and limitations that need to be mentioned. First, miRNA-related genetic variations have been reported to alter the expression levels of particular miRNAs . WhetherIn conclusion, this study is at the forefront of providing evidence that combining differentially expressed miRNAs can be applied to establish an objective and valid biomarker panel that can differentiate patients with ADHD from healthy control subjects. The miRNA-based biomarkers, as can be measured in peripheral blood, may assist in identifying ADHD in clinical settings. However, the findings of our study require further confirmation with a larger sample size and a cross ethnic validation. Future studies are needed to clarify the gene functions that are modulated by miRNAs and the biological mechanisms that underlie the ADHD pathophysiology.L-JW and S-CL participated in study design, patient recruitment, reviewing references, executed the statistical analysis, interpreting data, and drafting the manuscript. L-JW and S-CL are joint first authors and contribute equally to this manuscript. M-JL, M-CC, and W-JC participated in data collection and patient recruitment. S-YL drafted and revised the manuscript. C-WH provided technical and material support. L-HH participated in protocol development. H-CK participated in study design and revised the manuscript. All authors read and approved the final manuscript and contributed to the drafting and revising of the paper.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The current study aimed to investigate the effect of methylphenidate-Osmotic Release Oral SystemIn a single group off–on medication test design, narratives were obtained from 12 children with ADHD, aged 7–13 years, using wordless picture books. For microstructure, number of words, type–token ratio and mean length of utterance were derived from narrative samples using Systematic Analysis of Language Transcripts conventions. For macrostructure, the narratives were coded according to the Narrative Scoring Scheme, which includes seven narrative characteristics, as well as a composite score reflecting the child’s overall narrative ability.® resulted in a significant difference in certain aspects of language macrostructure: cohesion and overall narrative ability. Little effect was noted in microstructure elements.The administration of MPH-OROSWe observed a positive effect of stimulant medication on the macrostructure, but not on the microstructure, of narrative production. Although stimulant medication improves attention and concentration, it does not improve all aspects of language abilities in children with ADHD. Language difficulties associated with ADHD related to language content and use may be more responsive to stimulant medication than language form, which is likely to be affected by cascading effects of inattention, hyperactivity and impulsivity beginning very early in life and to progress over a more protracted period. Therefore, a combination of treatments is advocated to ensure that children with ADHD are successful in reaching their full potential. Attention-deficit hyperactivity disorder (ADHD) is a frequently occurring psychiatric condition in school-aged children with estimates of prevalence ranging from 3% to 5% , on language production processes in children with ADHD. In the current study, so as to circumvent the effect of comprehension skills on narrative production, an elicitation procedure was utilised that was less likely to result in performance that varies on the basis of memory or receptive language ability. Narrative elicitation did not involve listening to the story in advance, but rather previewing the wordless picture book prior to narrative production, allowing the processing of the entire story before planning and organising story components into a cohesive narrative. The current study sought to comprehensively measure microstructure and macrostructure elements of narration, employing a sensitive and specific scale of narrative production that rates the degree of development of story grammar elements rather than the mere presence or absence thereof  Is there an effect of MPH-OROS® medication on macrostructure language production elements  during story narration, as measured by NSS?The purpose of the current study was to extend prior work on the effects of a single medication, namely MPH-Osmotic Release Oral System , aged 7 and 13 years (mean age of 11.23 with a standard deviation of 2.28) with average or above average intelligence (mean of 96.42 with a standard deviation of 10.05), were selected from a private remedial school. See Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV), were included in this study. In addition, participants held a current prescription for MPH-OROS® for a minimum of 3 months prior to the commencement of the study with consent from parents to administer medication at school. Participants had a diagnosis of language impairment, as defined by at least one standard deviation below the mean for standard scores on any of the following test batteries: Clinical Evaluation of Language Fundamentals (CELF-4)   guidelines and software , lexical diversity (type–token ratio) and grammatical complexity (MLU). Macrostructure was defined using the NSS as introduction (provides the setting for the story and introduces main characters), character development , mental states (ability to use metacognitive verbs to describe thoughts and feelings), referencing , conflict resolution (highlights major conflicts and resolutions), cohesion  and conclusion (story is wrapped up using concluding statements)  was randomly chosen for agreement and reliability scoring. Narratives were re-transcribed in SALT and re-analysed using NSS both by the original transcriber as well as by the second transcriber.t-unit and 0.987 (0.996) for type–token ratio.Inter(intra)-rater agreements for the SALT microstructure transcript elements were determined using Pearson’s correlations. The results showed the following correlation coefficients: 1.00 (1.00) for number of words, 0.997 (1.00) for length of Krippendorff’s alpha values were calculated with ordinal scaling to determine inter-rater reliability of the NSS scores using 0.67 (acceptable) and 0.80 (adequate) benchmarks  and interquartile range (IQR), the difference between the third quartile and the first quartile, have been reported because of the skewed distribution of the data. These descriptive measures are more robust than averages and standard deviations as they are not influenced by outliers.Based on the small sample size and the skewed distribution of the differences between the on- and off-medication measurements, non-parametric tests were used. Inferential statistics were employed to determine the significance of results at a 5% level of significance. The Wilcoxon paired signed ranks test, a non-parametric equivalent of the paired p-value with 0.05/3 = 0.0167 for the families with three variables and the lowest p-value with 0.05/2 = 0.025 for the families with two variables). Because of the non-parametric analysis of results, and the comparison of medians, effect sizes were calculated using r-values  were not significant .Results for the first research question  during narrative production as measured by NSS. The p-value of 0.008, which is less than 0.05, indicates that MPH-OROS® elicited a statistically significant effect on the overall narrative performance . Using the Holm procedure for multiple comparisons, results showed that the medication has a significant influence on one of the seven independent macrostructure language production elements: cohesion. The p-value for cohesion was 0.020, indicating that MPH-OROS® elicited a significant effect on this component. Note that the improvement for conflict resolution failed to reach significance after the family-wise correction for multiple comparisons, p = 0.026; however, the effect size for this difference was -0.454, indicating a medium-to-large correlation  was noted in microstructure elements. Details regarding each of the questions will be discussed below.The purpose of this study was to investigate the effect of MPH-OROS® did not impact microstructure elements. These findings are in line with the results obtained by Francis et al.  while five were not . The improvement noted in cohesion may be indicative of the effect of MPH-OROS® on executive functions as this element may be more deeply rooted in one’s present ability to relate and organise events in relation to one another and perhaps less reliant on the modelling of story structure during previous language-learning opportunities.The second research question addressed the effect of medication on macrostructure language production elements during story narration as measured by NSS. An overall improvement in NSS total score was observed following MPH-OROS® showed a positive effect on the cohesion of narratives, supporting the theory that the language characteristics of individuals with ADHD can be attributed to executive dysfunction . Differentiation between ADHD subtypes would prove valuable as the effect of MPH-OROSIn addition, obtaining multiple narrative samples per participant would allow for a more accurate representation of an individual’s abilities as results would be less affected by external and internal factors. However, because of the nature of this study, it was necessary that material be similar with regard to theme, structural complexity, number of main characters and length so as to not exert an influence on the narratives produced. With limited material available to meet these criteria, it was only possible to obtain a single on- and off-medication narrative sample. Further, the repeated elicitation of narratives from the participants may have resulted in training effects and could be circumvented in future studies by making use of a crossover design or adjusting the period the period of time between on- and off-medication sampling.Developmental differences in narrative production, because of the wide age range of the study participants, may have impacted upon their narrative ability and could have subsequently influenced the results.Although reliability appeared low for the introduction component on the NSS, it is important to note that raw scores never differed by more than a single point (e.g. 2 [intermediate between immature and emergent] vs. 3 [emergent]). Scores within one point are considered consistent, given that the scale was constructed with clear anchors of 1, 3 and 5 (with intermediate scores of 2 and 4). In addition, the low scores can in part be attributed to the very small number of reliability transcripts. Rescoring 20% of the data translated into only five language samples, leaving little margin for error. With regard to the difference in points between scorers, no trends could be noted between transcriptions with regard to participant characteristics for the two transcripts with a scoring discrepancy. Transcripts were both 100% intelligible, and the book used to elicit the narratives differed between transcripts as did the presence or absence of medication. Reliability for conflict resolution was also low; however, again, scores never differed by more than a single point and scores were identical for four of five transcripts.One possible reason for differences between scorers may be based on the scorers’ interpretation of the descriptions of the criteria. For example, an emergent score (3 points) under the introduction category requires (1) Setting: ‘states general setting but provides no detail’, ‘descriptions or elements of setting are given intermittently through story’ and ‘may provide description of specific element of setting (e.g. the frog is in the jar)’ and (2) Characters: ‘characters of story are mentioned with no detail/description’. The immature (1 point) requires that the speaker ‘Launches into the story with no attempt to provide setting’ , which may be maximally informative in terms of the effects of stimulant medication on the spontaneous expressive language of children with ADHD.Frog, Where Are You?, A Boy, a Dog and a Frog  (Gagarina et al., The findings of this study have potential implications, both academically and socially. Children with ADHD are at risk for academic underachievement because of the primary symptoms associated with ADHD (Loe & Feldman, ® improves aspects of narrative ability in children with ADHD could be valuable information for clinicians and speech-language pathologists as this, if replicated, might prove beneficial when guiding parents in decision-making processes regarding medication as well as the ongoing necessity of speech-language therapy in children with ADHD.Therefore, because of the large role that narratives play in academic and social settings, it is evident that narrative inability in children with ADHD cannot be ignored by those professionals working with this population. The findings that MPH-OROS


A 5-year-old boy presented with mild autism and attention-deficit hyperactivity disorder (ADHD). Chromosomal microarray demonstrated a 1.7 Mb deletion at Xp22.31, which was consistent with X-linked ichthyosis (XLI). Further exam revealed dry, scaly skin on his abdomen and pretibial areas. Patients with mutations involving solely the STS gene or the recurrent ~2 Mb deletion may present with ADHD, whereas those with larger deletions including the NLGN4 gene can present with both ADHD and autism. However, our patient presented with mild autism in addition to ADHD despite having only the recurrent deletion without loss of NLGN4. Such neurological manifestations of XLI warrant attention as practical targets of clinical management. X-linked ichthyosis (XLI) is an X-linked recessive disorder with a prevalence of approximately 1 : 4,000, demonstrating dry, scaly skin due to a deficiency of the enzyme steroid sulfatase , 3.We present a case of XLI with ADHD and mild autism due to a recurrent ~2 Mb deletion which spared the NLGN4 gene.A 5-year-old boy  presented to Parkside Medical Group  for a neurological evaluation. His mother remembered being told that he might have intellectual disability based on blood tests and an amniocentesis; however, these test results were not available. Otherwise, the pregnancy history and delivery were normal. He weighed 6 lbs 10 oz (20th percentile) at birth, walked at 14 months, and said “mama” and “papa” at 8-9 months. During early childhood he did not want to be around other children. He adhered to routines; for example, when his father would change his favorite TV channel he would become very angry. He spoke Spanish and some English. He attended special education at a preschool level and he could count up to 100. However, he could not focus in school. He was diagnosed with ADHD and mild autism based on the DSM V criteria by a child psychologist six months prior to the neurology visit. He was started on amphetamine-dextroamphetamine ER 10 mg daily, which improved his behavior both at home and at school. He started participating more in group activities. On exam, he was found to have a high anterior hairline, a triangular face, a short chin, widely spaced eyes, prominent nasal bridge, and conical teeth . There wHere we present a case of XLI with 1.7 Mb deletion at Xp22.31 which included the STS gene, as well as 5 other genes. In addition to the classic features of XLI of dry, scaly skin , he alsoXLI was first described by Sedgwick in 1863 . XLI preIn our patient, chromosomal microarray revealed the recurrent ~2 Mb deletion, which included the following genes: STS, PUDP, MIR4767, VCX, PNPLA4, and MIR651. The significance of PUDP, MIR4767, and MIR651 is uncertain as there is not much known about the biological role of these genes. PUDP encodes a member of the haloacid dehalogenase-like (HAD) hydrolase superfamily; however, the encoded protein has no known biological function . There iKent et al.  reportedIn our patient, however, the recurrent ~2 Mb deletion  was sufficient to cause both mild autism and ADHD.Our case report highlights the importance of a neurological evaluation in XLI due to the association with ADHD and autism, especially those with the recurrent ~2 Mb deletions and those with larger deletions including NLGN4. In addition, we suggest that clinical cytogenetics laboratories which report these deletions should indicate the risk for the neurological manifestations in their interpretation, in addition to the skin manifestations and other clinical features. In conclusion, we hope to bring awareness of the neurological manifestations of XLI among neurologists and geneticists .Genomic DNA extraction and chromosomal microarray analysis were performed with the previously described methods . Informe