Owing to the aging of the rural population in the hilly and mountainous areas of Japan, mowing on narrow ridges and steep slopes is done manually by the elderly—individuals over 65 years of age. Studies have shown that many accidents that occurred during mowing were caused by workers’ unstable posture, especially when mowing on steep surfaces where there is a high risk of falling. It is necessary to analyze the body movements of mowing workers to elucidate the elements related to the risk of falls. Therefore, in this study, based on a high-precision motion-capture device and a series of experiments with elderly, skilled mowing workers, we focused on the movements of mowing. We sought to identify effective and safe mowing patterns and the factors that lead to the risk of falls. In various mowing styles, compared to the stride (S) and downward (D) mowing patterns, the basic (B) and moving (M) patterns were the most efficient; however, the risk of falls was also the highest among these patterns. While mowing, workers need to pay more attention to their arm strength and take appropriate measures to reduce the risk of falls according to their age and physique. The results can be used as data for the development of fall-detection systems and offer useful insights for the training of new mowing workers. In the hilly and mountainous areas of Japan, mowing is done using manually operated machines because of the steep gradients of many terraced rice fields . For exaAccording to related surveys , approxiWith the continuous development of sensors and Internet of Things (IoT) technologies, most human activities, including body movements , eye movAccording to relevant studies  and relaStudies show that it is very important and necessary to identify the dangerous postures and find effective and safe ways for older people to work on slope mowing. However, the research to date has mainly focused on the analysis of falls in older adults at home, and not much research has been done using motion-capture devices. Therefore, based on a series of experiments by experienced elderly mowing workers using a high-precision motion-capture device (Xsens MVN), this study focuses on the issues of mowing movements on slopes, and aims to identify effective and safe mowing patterns.Four experienced mowing workers participated in this experiment; they were required to perform normal mowing work. All study participants provided informed consent, and the study design was approved by the ethics review board. The Xsens MVN device and 4 k cameras were used to record the entire mowing actions of the workers for analysis. We also aimed to analyze possible factors influencing the risk of falls while mowing. The results can be accumulated as data for the development of future fall-detection systems and offer useful insights for the training of new mowing workers.This paper is an extension of the international conference paper  we publiAccording to the Agricultural Work Safety Information Center of Japan, mowing is one of the most accident-prone agricultural activities in Japan . AccidenFalls in the elderly are associated with reduced postural stability and delayed motor response , which mConsequently, fall prevention in elderly behavior analysis is an active field of study. The survey by Letts et al. on factors affecting the risk of falls in the elderly showed that home hazards such as falls and fires appear to be a significant risk factor in older community-dwelling adults .Several articles analyzed the movements of the elderly, such as the possible relationship between their gaits and falls. For example, through a gait experiment with 597 adults aged 70 years and older, Verghese et al. examined the relationship between speed and six other gait markers and the incidence of falls . To veriThere are many comparative studies between older and younger adults. For instance, to examine differences in postural stability and the speed of response between young adults, older adults at low risk of falls, and older adults at high risk of falls, Tucker et al. analyzed their voluntary postural sway movements. They showed that both fall-risk groups had a slower reaction and movement time than the younger group; and that people at high risk of falls had slower reaction and movement times and increased non-target center amplitude during casual swaying . ExploriMany studies use sensors to collect and analyze data from the elderly. For example, Howcroft et al. developed a fall-risk prediction model for the elderly based on gait data and expected fall occurrence from wearable sensors . Sun et Motion-capture devices are one of the important means to analyze human motion, and such devices are used in many fields, such as sports and medical fields. They have been used to analyze the movements of athletes in many studies. Noiumkar et al. studied golf swing in a game using a motion-capture device called mechanical MOCAP system . CockcroOther studies have also applied motion-capture devices to the medical field. For instance, to assess hand rehabilitation, Li et al. provided a simple and intuitive optical motion-capture system, showing a clear and accurate model of hand movements . To provIn addition to the research that focused on the use of camera-based motion-capture devices, several studies have applied motion-capture devices to human motion analysis in open environments. For example, Burget et al. compared the similarities and differences between subjects performing hand-coordination tasks by asking healthy subjects and patients with Parkinson’s disease to use an acceleration sensor-based motion-capture device .Many studies have focused on the analysis of athletes’ movement. For instance, by having athletes wear a Wi-Fi-based inertial sensing module on their wrist, Abdallah et al. presented a new wearable IoT device capable of monitoring athletes’ movements in real-time . Ivanov Studies show that it is very important and necessary to identify the dangerous postures and find effective and safe ways for older people to work on slope mowing. However, the research to date has mainly focused on the analysis of falls in older adults at home, and not much research has been done using motion-capture devices. Therefore, in this study, we focus on the analysis of body movements of skilled mowing workers by motion-capture devices to confirm the safe and effective mowing postures to prevent falls.Based on related works and our previous studies ,12, to iIn this study, the high-precision motion-capture device Xsens MVN  was usedIn contrast to traditional motion-capture devices, which are based on video camera and 17-joint models, the Xsems MVN device can collect information on 23 joints including spinal segments T12, T8, L5, and L3, and toes as XML files with high precision. The details of collectible joint data are shown in All joint data collected using the motion-capture device have corresponding 3D coordinates. Based on these, many joint angles can be calculated to represent the posture of the subject. As shown in A, B, and C represent the joints around the subject’s knee and have coordinates such as A , B , and C . Therefore, from point A, two vectors can be calculated as Equations (1) and (2).As shown in Then, according to these two vectors, the angle of the knee As the motion-capture device Xsens MVN can provide the coordinate metadata of each joint directly, it is only necessary to use the device in actual mowing practice to obtain the required data.As shown in Therefore, based on the collected body movements data and the mentioned joint angle calculation method, four variables were calculated for analysis, including the joint angle variation, the standard deviation of waist angle variation, and the moving distance of movement by hands.As the movement of the user’s wrists, knees, ankles, and other joints is linear in each target analysis range, we calculate the angle variation of each joint as the characteristic quantity.Because the waist angle variation is not linear in the analysis, the standard deviation was calculated to describe the magnitude of its vibration as the characteristic quantity. The waist is close to the center of gravity of the subject while mowing; hence, the size of the vibration may predict the risk of a fall .As the subjects use their hands to push the mower during the mowing process, the distance of the movement of the hands is usually proportional to the amount of effort they exert; we use the Euclidean formula to calculate the distance of the hands as the characteristic quantity. The distance of the movement of the hands is determined by calculating the coordinate distances of all adjacent frames and adding them, as shown in Equations (4) and (5).i as an example, the coordinates of the hand before i and after i are assumed to be A  and B , respectively. Therefore, the moving distance A to B will be:Taking point In our data, each frame has a duration of 4 ms; hence, if the target analysis range of one “cutting” action consists of n points, the moving distance of the hand will be:Therefore, as shown in In our previous study , we condBased on the experiments conducted in previous studies ,12, to oThe area has a large slope angle (slope depth is over 10 m) and the weeds grow so tall that a normal mower robot cannot operate on the area. It requires the mowing worker to make several horizontal trips back and forth to cut the grass manually.Four experienced mowing workers participated in this experiment. Each participant was over 65 years old and had 10 or more years of slope-mowing experience. The details of the experimental subjects are shown in All subjects in the experiment used the most common type of mower shown in All subjects were right-handed and the mowers they used were specifically designed for right-handed people. Moreover, no participants had any cognitive disorder problems, and they were in good health and had normal vision.To increase the authenticity of the collected data, the subjects were not given any special instructions during the data-collection phase; they were only required to perform the usual mowing work. With confirmation that these additional devices did not interfere with the normal activities of the subjects, all subjects in the trial were equipped with Xsens MVN motion-capture devices. Additional interviews were conducted at the end of all experiments to determine the details could not be obtained visually. In addition to the data collected through the motion-capture device, the movements of the subjects were recorded in real time by the 4k camera on the side and compared to the collected motion data later.The experiment was completed in September 2020, and a supplementary experiment was carried out in September 2021. A total of 627 sets of mowing movements on slopes were collected for analysis. To make the 3D model more accurate, we also collected additional physical and personal data of the subjects as shown in Through experimental correlation image  analysis and interviews with subjects, we found that the classic mowing action on slopes can be divided into four different patterns. As shown in Basic mowing action refers to the mowing action performed on the weeds in front of the subject while standing naturally with both feet. Stride mowing action refers to the mowing action where the subject takes a large stride with one foot in order to maintain stability.Moving mowing motion refers to the mowing action when the subject moves his or her position to perform the mowing task better. Stride and moving motions are both performed while mowing weeds in front of the subject. Finally, downward mowing motion refers to the mowing motion performed to the weeds below the subject, with the subject’s feet in their natural state. As per the mowing operation trajectory shown in Through basic statistics, as shown in Based on the chi-square analysis of the data, we learned that target variables do not conform to the normal distribution. Therefore, to distinguish the similarities and differences between these patterns, the Kruskal–Wallis one-way ANOVA is used to analyze the difference between the characteristic quantities of these types of actions.As shown in We will discuss the similarities and differences of each of the post hoc results in three parts, including the upper body, lower body, and the waist vibration and mowing distance of hands.Through post-event questionnaires and interviews, we learned that in slope mowing, the body joint movements determine how the worker exerts his or her force and technique. As the way of mowing involves lifting the mower and exerting the force diagonally downward from right to left, the movement of the worker’s left and right hands and feet are different. As shown in Therefore, for the upper-body joints, the results of post hoc analysis show that although there is significant difference in almost all movements between the four patterns, similarity also appears in some measures.As shown in The right and left wrists need to be discussed separately. Through our investigation, the right hand is mainly responsible for pushing the mower to move, whereas the left hand is more responsible for lifting the mower.For the right wrist, similarities are observed between the patterns of the B–M, B–S, and S–M pairs. Pattern S has a higher level than others in the angle variation. One possible explanation is that the right hand of the worker is primarily responsible for pushing the mower during mowing, especially when mowing downward, in which it requires more force to push the mower because the workers need to change the way they hold the control lever.For the left wrist, similarities are observed between the patterns of B–D and S–D. Pattern M has a higher level than others in the angle variation. A possible explanation is that the worker needs to exert more force on the left hand to lift the mower when moving with pattern M.As shown in It is important to note that because of the characteristics of the pattern M, which is different from the other three patterns, only the data of M  are listed and not compared and discussed in this paper. The comparison results of the other three patterns are as follows.For the right knee and ankle, similarities are observed between the patterns of the B–S, B–D, and S–D pairs. As the standard pattern for mowing on a slope is to stand firmly with the right foot in front and the left foot at the back, the results mean that in all patterns, the right foot may be primarily responsible for maintaining balance and not for exerting force for mowing.For the left knee, the similarity is observed between the pattern B–D, and for the left ankle, the similarity is observed between the patterns B–D and S–D, that each of the values of the S pattern is smaller than the others. The possible explanation is that the left foot, as the weight-bearing foot, does not change much in terms of force under pattern B and D, but in pattern S, owing to the forward shift of the center of gravity, its weight-bearing force is partially reduced.Lastly, for the post hoc results for waist vibration and moving distance of hands, as shown in For waist vibration and the moving distance of right hand and left hand, the analysis results show that similarities are observed between the patterns of the B-M and S-D pairs, which are similar to the results of the upper-body elbow analysis. If the explanation regarding the elbows’ angle variation (workers output more power in B and M patterns) is correct, this means that the output of greater force is subject to a greater risk of falling. The results of the moving distance by both hands corroborate this hypothesis.Based on the analysis for different patterns of mowing on slopes, the results of the Kruskal–Wallis one-way ANOVA and related post hoc analysis show that among the four patterns, the B pattern has the highest number and, like the M pattern, allows workers to mow with maximum effort. Workers in the S and D patterns have to use slightly less force to mow to maintain balance. Therefore, if the conditions allow, the B and M patterns are recommended to use to increase efficiency when mowing on slopes. However, the results also show that when using the B and M patterns for mowing, workers need to be aware of falls, as higher efficiency means higher risk.From the conclusion of Thus, in the stepwise regression, the STDwaist, which represents the vibration of the waist joint, was set as the dependent variable, and the other measures were set as the independent variables.To meet the conditions of stepwise regression analysis, after correlation pretreatment, as shown in p-value < 0.01).As shown in In terms of the magnitude of influence with the direction positive, the biggest two are the angle variation of the left elbow and right elbow, which mean that the force exerted while mowing is mainly by the angle variation of the joint of the worker’s elbow; the greater the angle variation, the greater the power output. However, sometimes it also means a higher waist vibration, which may cause a fall while mowing on the slope. Positive effects were also observed on the left wrist that may suggest that the force of holding the mower in the left hand also affects the vibration in the waist and further affects the possibility of falling. The results are consistent with those discussed in The results show that in addition to the left and right elbow and left wrist, arm span and age also play a significant role as influencing factors. The effects are bigger, but the direction of the effects is negative.The results of arm span analysis mean that the longer a person’s arm span, the less vibration their waist has while mowing. As the length of a person’s arms is often proportional to his physical size, this means that a worker who is not sufficiently strong may have to exert more effort to mow the grass, and may face a higher risk of falling while mowing on a slope.Contrary to expectations, the results on the effect of workers’ age showed that elder workers had more stable waists while mowing on slopes. Because the experimental subjects had similar mowing experiences, one possible explanation is that older workers were more concerned with their body balance during work. This means that without physical limitations, workers over the age of 65 may have a safer body motion for slope mowing.Based on the analysis of falling risk of elderly workers when mowing on slopes, the results of stepwise regression analysis are as follows. To reduce the possibility of falling while mowing, workers need to pay attention to the use of arm strength and take appropriate measures to reduce the risk of falls according to their age and physique.To identify the most effective and safe mowing patterns and the possible influence factors of fall risk while mowing on slopes, in this study a series of experiments were conducted to collect data and analyze the body movements of workers during mowing.Based on 627 sets of motion data collected from four elderly workers, the Kruskal–Wallis one-way ANOVA and the related post hoc analysis show significant differences in all the measures among the mowing patterns B, S, D, and M. At the same time, the patterns B and M have higher efficiency when mowing on slopes, but also carry a higher risk of falling.The results of stepwise regression indicate that a relatively old worker with a healthy physique may have a safer mowing motion on the slope. To reduce the risk of falling, the workers need to pay attention to their arms when cutting grass on a slope. The results can be used as data for the development of future fall-detection systems and offer useful insights for the training of new mowing workers.Due to the risk of mowing on steep slopes, more subjects over the age of 65 could not be invited to join the related experiments. The discussion in this paper assumes that workers with more than 20 years of mowing experience will have safer and more efficient postures than novices.In future work, we plan to break down the mowing action in terms of frequency, consider more human-related data such as mowing workers’ eye movements and invite more workers with different characteristics  to conduct experiments. We are also considering the use of deep-learning technology to predict the workers’ risk of falling.


Background: Few studies have examined if maternal allergic disease is associated with an offspring's neurodevelopment. We hypothesized that Th-2 biased maternal immune function assessed as total serum immunoglobulin (Ig) E is associated with attention deficit hyperactivity disorder (ADHD).Methods: Data are from the Wayne County Health, Environment, Allergy, and Asthma Longitudinal Study (WHEALS), a racially and socioeconomically diverse birth cohort in metropolitan Detroit, Michigan. Maternal total IgE was measured prenatally and at 1-month postpartum. Child total IgE was assessed at birth, 6 months, and 2 years of age. ADHD diagnosis was based on the parental report at the 10–12-year study visits or medical chart abstraction. Total IgE was log2 transformed. Poisson regression models with robust error variance were used to calculate the risk ratios (RR). Inverse probability weighting was used to correct for potential bias due to a loss to follow-up and non-response.Results: Of the 636 maternal-child pairs in the analysis, 513 children were neurotypical and 123 had ADHD. Maternal prenatal total IgE was significantly associated with ADHD even after adjustment for potential confounders . Maternal and child IgE measures were positively and significantly correlated, but child total IgE was not associated with ADHD at any time point.Conclusions: Maternal prenatal IgE may influence neurodevelopment, but additional studies are needed to confirm and expand these findings. Neurodevelopmental disorders, such as autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD), have risen in prevalence over the last 15–20 years. Current estimates suggest that one in 59 children are affected with ASD and 9% of children are affected with ADHD . Interesin utero  recruited pregnant women with due dates from September 2003 through December 2007, and who were seeing a practitioner at one of five clinics in the Henry Ford Health System to establish a birth cohort , 24. AllOf the 1,258 maternal-child pairs in the WHEALS cohort, 1,201 had a maternal total IgE measurement at either the prenatal visit or 1-month postpartum visit. Of those, 651 maternal-child pairs were followed through 10 years of age and had information on neurodevelopmental outcomes. Seven children with a sensory processing disorder, but not ADHD, and eight children with ASD, but not ADHD, were removed prior to the analysis, leaving a total of 636 maternal-child pairs in the final analytic sample.Blood was collected from mothers during the prenatal visit and at the 1-month postpartum home visit, while blood was collected from children at birth , 6-months, 1-year, and 2-years. Total IgE (IU/mL) was measured in all blood samples with the Pharmacia UniCAP system  using the manufacturer's standard protocols. Further details on the total IgE measurement have been previously published .At the age 10–12-year visit, the caregiver (95% the mother) reported if the child had ever been diagnosed with ADHD, ASD, Asperger's syndrome, or a sensory processing disorder. A question about Asperger's syndrome was asked separately since children may have been diagnosed prior to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). Caregiver report of a “suspect” diagnosis was also classified as positive for the primary analysis.A subset of 325 WHEALS children who had received care from the Henry Ford Health System providers had their medical records abstracted for additional health information, including ADHD diagnoses. Caregiver report of ADHD diagnosis was validated within this subset using the kappa (κ) statistic to evaluate agreement. Landis and Koch . Given tChildren with ADHD were compared to children who were considered neurotypical (NT) because they did not have a caregiver-reported neurodevelopmental diagnosis. Other neurodevelopmental disorders were not evaluated as a separate outcome due to the small sample sizes. To evaluate the robustness of the results, two sensitivity analyses were performed in addition to the primary analysis of all ADHD cases relative to NT: (1) ADHD cases with a “suspect” parental diagnosis but no chart abstracted diagnosis were removed, and (2) ADHD cases with a comorbid ASD diagnosis  were removed.2) at the first prenatal care visit  were calculated. Although the first measured BMI in pregnancy and self-reported prepregnancy BMI have been shown to be highly correlated in other studies  were collected at the prenatal interview. Maternal prenatal care records were abstracted to obtain prescription antibiotic and antifungal use . Height  studies , the firp = probability of inclusion, then IPW = 1/p for included children and IPW = 1/(1-p) for excluded children. Covariate balance was assessed using the standardized differences (difference in means or proportions divided by standard error) before and after weighting, with imbalance defined as absolute value >0.20.In order to describe the differences in children included and excluded from the analyses and to describe differences by ADHD status, analysis of variance was used for continuous covariates while chi-square tests were used for categorical covariates . For descriptive purposes, total IgE measurements were first compared on the untransformed IU/mL scale, with between group differences evaluated using the Wilcoxon rank sum test. In order to have meaningful coefficients in regression models (described further in the Results), total IgE measurements were log2-transformed prior to model inclusion. The log2 transformation was also used to examine Pearson correlations between total IgE measurements in order to meet normality assumptions. a priori specified as potential effect modifiers and were tested using multiplicative interaction terms.To evaluate the association between maternal total IgE  and ADHD in offspring, risk ratios (RR) were obtained from Poisson regression models using a robust error variance . In all mianalyze procedure was used to pool estimates.Because there was covariate missingness in the analytic dataset, multiple imputation was performed in addition to a complete-case analysis. A total of 20 imputed datasets were calculated using all exposure variables, the outcome of interest, confounders, and the IPW for loss to follow-up. The SAS procedure MI  with the fully conditional specification algorithm was used to generate imputed datasets; imputation quality was assessed via trace plots and variance information . The SASp < 0.05). Included mothers were also older on average and less likely to smoke or be exposed to tobacco smoke during pregnancy; included children on average also weighed more at birth. Standardized differences of these associations were as large as 0.75; however, after weighting the subjects by their IPW for loss to follow-up, no significant associations were found, and the absolute value of all standardized differences were <0.20 (maximum = 0.04), which suggested that balance was achieved in these covariates between the included and excluded subjects after weighting.Among the 636 maternal-child pairs included in the analysis, 123 (19.1%) were diagnosed with ADHD and 513 (79.7%) were NT. Ten children had both ADHD and ASD. The comparison of children included and excluded from analyses are shown in p < 0.05). Specifically, relative to NT children, children with ADHD had mothers with higher prenatal BMIs, were more likely to use prenatal prescription antifungals and more likely to have a self-reported history of hay fever or allergic rhinitis and asthma. Children with ADHD were more likely to be male and on average had earlier gestational ages at delivery. Of these characteristics, only prenatal antifungal use and child sex were also significantly associated with maternal total IgE ; similarly, for each 2-fold increase in the maternal 1-month total IgE, the risk of ADHD increased by 8% . After adjusting for covariates in a complete-case analysis, both maternal prenatal  and 1-month  IgE remained statistically significantly associated with ADHD. However, only maternal prenatal IgE remained statistically significant in the multiple imputation estimates . In the first sensitivity analysis removing seven children who had a “suspect” ADHD diagnosis, results for the maternal prenatal IgE were effectively unchanged . Results were again consistent in the second sensitivity analysis where we repeated the analysis after removing 10 children who had both ASD and ADHD. Specifically, effect estimates with prenatal IgE were not impacted and again remained statistically significantly associated with ADHD . In both sensitivity analyses, there remained no association between the 1-month postpartum IgE and ADHD. Additionally, child sex and breastfeeding status at 1-month did not significantly modify any of the associations between maternal IgE and ADHD .r = 0.91), within the child at all time points , and between mother and child at all time points . Consistent with what we observed in p = 0.38).The correlations between maternal and child total IgE measurements are shown in The findings from this study suggest that maternal IgE during pregnancy influences the risk of ADHD in an offspring. Specifically, higher levels of maternal prenatal total IgE were associated with a statistically significant increased risk of ADHD diagnosis in the offspring, which remained after covariate adjustment. Child IgE throughout the first 2 years of life was not associated with ADHD. These findings are significant because they highlight maternal prenatal total IgE level as an important potential marker of risk of ADHD. To our knowledge, few studies have examined prenatal exposure to immunoglobulins generally and risk of ADHD or other neurodevelopmental disorders such as ASD. While results of other studies are not directly comparable to the findings presented here, inferences may be drawn from similar work on other neurodevelopmental outcomes. Grether et al. studied maternal prenatal total IgG and total IgM and found no association with the risk of ASD . HoweverFurthermore, previous studies suggested that maternal IgE is correlated with infant IgE , 34. In While this study does not specifically examine the mechanisms by which IgE (or the immune functions marked by IgE levels) may influence ADHD risk, we hypothesized that fetal neurodevelopment is influenced by maternal prenatal immune function. The concept of a link between the pattern of maternal prenatal immune function and ASD or ADHD has been discussed , 32, 38,N = 56) , thus, we are unable to assess the changes in the total IgE during pregnancy. One previous study suggested that maternal total IgE changes differently during pregnancy in mothers with and without sensitization and allergic symptoms, but that study was small (N = 56) . In the N = 56) . AdditioIn summary, we found that maternal prenatal total IgE, but not early life or childhood levels of IgE, is associated with an increased risk of ADHD. This finding suggests that the prenatal period is an important window of exposure for risk of ADHD and, as such, might be a critical time period in which interventions to prevent these outcomes may be successful.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.All participants provided written, informed consent and study protocols were approved by the Henry Ford Health System Institutional Review Board; at the age 10–12 year visit, children provided written informed assent.JS conceptualized and designed the study and drafted the initial manuscript. AS conducted the statistical analysis and drafted the initial manuscript. All authors contributed in revising and editing the manuscript, and approved the final version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The ISCT was generated through three phases comprising (i) the molecular characterization of drugs and pathologies, (ii) the generation of adult and children virtual populations (vPOPs) totaling 2,600 individuals and the creation of physiologically based pharmacokinetic (PBPK) and quantitative systems pharmacology (QSP) models, and (iii) data analysis with artificial intelligence methods. The characteristics of our vPOPs were in close agreement with real reference populations extracted from clinical trials, as did our PBPK models with in vivo parameters. The mechanisms of action of LDX and MPH were obtained from QSP models combining PBPK modeling of dosing schemes and systems biology-based modeling technology, i.e., therapeutic performance mapping system. The step-by-step process described here to undertake a head-to-head ISCT would allow obtaining mechanistic conclusions that could be extrapolated or used for predictions to a certain extent at the clinical level. Altogether, these computational techniques are proven an excellent tool for hypothesis-generation and would help reach a personalized medicine.Regulatory agencies encourage computer modeling and simulation to reduce the time and cost of clinical trials. Although still not classified in formal guidelines, system biology-based models represent a powerful tool for generating hypotheses with great molecular detail. Herein, we have applied a mechanistic head-to-head  Although the concept emerged in the early 2000s  approaches to optimize randomized clinical trials . CM&S aply 2000s , the terly 2000s . In addily 2000s .One of the most promising computational tools encompassing these concepts is systems biology or systems medicine , 7–9. DuAttention-deficit/hyperactivity disorder (ADHD) is a complex ailment with a prevalence in children ranging from 6 to 10% . Besides® in the US and Elvanse ® in Europe) and the development of extended-release formulations . Although a pediatric clinical trial analyzing LDX and MPH is currently ongoing (ADHD management comprises pharmacologic and non-pharmacologic treatments. Medications include stimulant [amphetamines and methylphenidate (MPH)] and non-stimulant drugs , with the former being recommended as first-line treatment . Several ongoing , 31, the® vs. Concerta® in the pediatric-adolescent population and Elvanse® vs. Medikinet® retard in the adult population) using a crossover–like design. The objective of this ISCT was to model the efficacies of the two drugs and compare them in a virtual head-to-head setting. Additionally, we describe an approach to measure and compare the output results in terms of efficacy of the two medications, the molecular mechanisms triggered, and the response to ADHD management in a diverse population of virtual patients, including patients with the most common psychiatric comorbidities.We present here the methods of the Therapeutic Performance Mapping System (TPMS) technology, which allow the generation of virtual patients and PBPK and systems biology-based models with the purpose of performing ISCTs. To demonstrate the applicability of the method, we used as case-study a mechanistic head-to-head ISCT between LDX and MPH  were generated: adult (>18 years old) and pediatric-adolescent (6–17 years old) vPOPs. As reference demographic and comorbidity parameters to generate the VPOPs, the following studies were used: NCT00730249  (MPH) anAdditionally, standard population distribution data was used to fill incomplete demographic parameters. For adults, ESS Round 7  was usedAll virtual patients created had ADHD, and specific branches for the different comorbidities were also generated, as previously described . ADHD anSince data on treated and non-treated patients is not available, we considered that a number of patients large enough to discriminate among ADHD patients and healthy individuals would also be large enough to detect efficacy-associated changes for each drug. Therefore, to generate enough patients and ensure having sufficient statistical power when performing data analyses, the sample size approach described below was carried out. Because TPMS' drug efficacy outcomes are based on predicted protein activity , this methodology was based on experimental measures that can relate to protein activity variability, particularly gene expression.k-fold cross-validation (k = 10)  experiments  and then(k = 10) . FinallyFor the present ADHD study-case, RNAseq records from the entry GSE159104  were selThe two populations, adult and pediatric-adolescent, were segmented into nine arms each  to facilitate the simulation and the analysis. One arm accounted for ADHD without any comorbidity, while the eight additional arms contained patients with ADHD and one, or a combination, of comorbid psychiatric conditions.in silico nature, the files containing the models of each virtual patient could be cloned; thus, no wash-out period was needed.Each of the arms accounting for comorbidities had 100 patients, while arms related to ADHD alone consisted of 500 patients, with the aim of maximizing the number of patients with different demographical characteristics. Consequently, a total of 2,600 patients were included in the simulation: 1,300 adults  and 1,30According to their population group, the patients included in the ISCT were treated with different formulations and doses of LDX and MPH in a two-period crossover-like study design. For all patients, the same initial state was used at each period, hence carryover effect was assumed zero. Dosage, molecular target profile, and pharmacokinetic information were needed for the QSP modeling herein proposed.®) 70 mg and children with LDX 50 mg. Different doses and types of modified release systems for MPH were considered in the simulation, corresponding to different commercial formulations: (i) for adults, Medikinet® 60 mg with modified-release , based in multiarticular beads that combine 50% immediate and 50% extended-release  with a 22% of the total amount available for immediate release   .The molecular target profile identification was performed through a review of official regulatory sources , drug-target–dedicated databases ; and (ii) standard population distributions, retrieved from populational studies. For the present ADHD study-case, the recruitment of each vPOP was based on the demographical parametric descriptors defined in section Population Definition—Virtual Patients'  minus the original tSignal.An unsupervised clustering strategy was applied to obtain groups of two to seven clusters of MoAs to evaluate the molecular variability of the generated models. The two (adults and children-adolescents) complete sets of 1,000 QSP ADHD patient mechanistic models (500 for LDX and 500 for MPH) were evaluated separately, taking into account the final activation values of the ADHD protein effectors modulated by both drugs. Clusters were obtained using K means algorithm . The cluOnly aggregated patient data from published clinical trials were used in the current project –90, 98. All simulations described in this project were executed in the Anaxomics' cloud computing, which integrates more than 800 computational threads in machines with 64 Gigabytes of RAM. Software, databases, and tools are the property of Anaxomics Biotech.The characteristics of adult and pediatric-adolescent vPOPs of ADHD patients were generated from the proportions of demographic characteristics reported in the corresponding clinical trials. Additionally, eight subpopulations with different comorbidities  were created using the same method for both populations to evaluate the impact of comorbidities on the drugs' efficacy. The characteristics of our modeled vPOPs can be found in TPMS-derived MoA models were subjected to sensitivity SOBOL analysis to evaluate whether the variation of molecular parameters would affect the models' response and to identify key molecules. The sensitivity evaluation was carried out for a range of values  for each protein. Although these models have about 5000 parameters, less than a third of them showed a real impact (difference >15%) on the output, which was less notorious in MPH (max difference ~17%) than in LDX (max difference ~32%)  and child  . PBPK moAfter the process of optimizing by trimming, 83 proteins (out of 86) were included in the pediatric-adolescent ADHD definition (ρ = −0.81) and 66 proteins (out of 86) in the adult ADHD definition (ρ = −0.79). The resulting molecular definitions found after optimizing the model-derived efficacy measures for each conditions' clinical efficacy can be found in Supplementary Table G in The MoA of LDX and MPH in our populations of interest, inferred from QSP models, were obtained by combining PBPK models of the dosing schemes of these drugs and TPMS technology, which modeled the MoA of both drugs in ADHD. The simulation analyzed the whole available data on pathologies, drugs, and the population. The mean accuracy values obtained in mechanistic models for ADHD virtual patients were: 91.63% (adults treated with LDX), 91.71% (adults treated with MPH), 91.68% (children-adolescents treated with LDX), and 91.69% (children-adolescents treated with MPH). Thus, for each patient, activation/inhibition patterns of all proteins associated with the MoA of LDX and MPH were obtained. Drugs' efficacy on ADHD measured over each virtual patient was exclusively estimated using the above mentioned tSignal formula (Equation 1), which summed up the activity values of ADHD effector proteins. The tSignal formula was applied to the list of ADHD effector proteins optimized to fit clinical observations and provided high accuracy QSP models for the whole set of 1,300 patients comprising adults and children.The ADHD population was subjected to clustering analysis to explore molecular variability within the LDX and MPH mechanistic models. The optimal number of clusters for adults was four different clusters, whereas three main clusters were identified for children, according to Hopkins statistics , Silhouette index , and Jaccard Bootstrap index . These results reflected drug-independent patient intrinsic variability since they clustered in a non–drug-dependent manner . Clusterp-value = 2.515e-08) and children-adolescents . In adults, cluster 4 showed the highest mean tSignal , while cluster 2 was the one presenting the lowest . In children-adolescents, the tSignal of cluster 1 was significantly higher  and that of cluster 3 was significantly lower  than the rest (Student's T-test). To further characterize the clusters, we performed an ANOVA analysis to identify potential differences on the demographic characteristics within the clusters. In the overall analysis, only weight was significantly different  in adults , and no differences were found in children-adolescents. When comparing each cluster against the rest in adults, we found that BMI, weight, and gender ratio were significantly lower in cluster 4, while weight was slightly higher in cluster 2. In children- adolescents, BMI and weight were significantly lower in cluster 1, while weight was slightly higher in cluster 3  and PKC . The pleiotropic nature of these proteins and their involvement in several signaling processes could explain their potential impact in the sensitivity of mechanistic models. However, a detailed evaluation of each drug mechanistic model should provide further knowledge on the key proteins involved.QSP model clustering analysis indicated the presence of several response patterns, not clearly defined by drug treatment. The protein activity-based unsupervised clustering was somehow associated to response level, and PCA analysis revealed some relevant proteins that could be exerting this effect, including: dopamine signaling-related AKT proteins , neurotrin silico cloning of data from individual type 1 diabetes patients to improve algorithms for closed-loop insulin delivery systems has been reported in 12 and 47 virtual patients in studies that aimed to tackle the challenging problem of inter- and intra-subject variability . However, other consequences of these characteristics at the ADHD pathophysiology level were not considered, because of the absence of (i) clear molecular information to include in the ADHD definitions for each patient profile, and (ii) reliable sources of information to properly model these characteristics at the molecular level. This limitation could prevent the modeling and detection of relevant results regarding these characteristics, such as age-related neurodevelopment , 129, dip-values for age and weight were close to the significance threshold. These parameters proved to be more difficult to fit in pediatric than in adult virtual populations. While clinical trials only report average weight and age, general pediatric population weight distributions obtained from growth information (p > 0.1 or even p > 0.2) during the randomization procedure might ensure obtaining a fitter population, especially regarding the pediatric case. In this specific scenario, as the case-study objective for the generation of the ISCT was a head-to-head between LDX and MPH using the exact same population, this bias was not expected to significantly affect the results. TPMS-based models are not an exception either  that has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant Agreement No. 765158.This study was funded by Takeda. Public funders provided support for some of the authors' salaries: GJ has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant Agreement No. 765912. VJ is part of a project (COSMIC; JRG-C has served as speaker for Takeda and Shire and has received research funding from Shire. JQ has served as speaker and/or on scientific advisory boards for Takeda, Janssen, and Rubio. GJ, VJ, and JM are full-time employees at Anaxomics Biotech. VM, TP-R, and CM are full-time employees at Takeda. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Attention-Deficit / Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder, characterized by varying severity in attention deficit and hyperactivity. Studies have shown deficiencies in the serum level of magnesium and vitamin D in people with ADHD. The aim of this study is to determine the effect of vitamin D and magnesium supplementation on mental health in children with ADHD.n = 33) or placebos (n = 33) for 8-weeks. Strengths and difficulties questionnaire was used to evaluate children’s mental health at baseline and the end of the study.We conducted a randomized, double blind, placebo-controlled clinical trial of 66 children with ADHD. Participants were randomly allocated to receive both vitamin D  plus magnesium (6 mg/kg/day) supplements (p = 0.001), conduct problems (p = 0.002), peer problems (p = 0.001), prosocial score (p = 0.007), total difficulties (p = 0.001), externalizing score (p = 0.001), and internalizing score (p = 0.001) compared with children treated with the placebo.After eight weeks of intervention, the serum levels of 25-hydroxy-vitamin D3 and magnesium increased significantly in the intervention group compared with the control group. Also, children receiving vitamin D plus magnesium showed a significant reduction in emotional problems  and magnesium (6 mg/kg/day) co-supplementation for a duration of 8-weeks could improve the behavioral function and mental health of children with ADHD. However, further well-designed studies with a larger sample size are needed.IRCT2016030326886N1. Attention-Deficit / Hyperactivity Disorder (ADHD) is characterized by varying severity in attention deficit and hyperactivity and is related to neurodevelopmental disorders. The prevalence of ADHD has been increasing over the past decades . ADHD isIn general, the risk factors for ADHD include smoking, alcohol and substance abuse and maternal stress during pregnancy. Moreover low birth weight, preterm delivery, contaminants such as organophosphates, polychlorinated biphenyls, lead, artificial dye ores and low socio-economic status of the family  are alsoADHD is a common neurodevelopmental disorder with associated vitamin and mineral deficiency. Nutrient deficiencies have not been shown to cause ADHD in children, but studies in children with ADHA have shown deficiencies in some nutrients such as magnesium and vitamin D , 13. Evin = 33). Ethical approval was provided by the Ethics Committee of Isfahan University of Medical Sciences, Isfahan, Iran. The study is registered with the Iranian Registry of Clinical Trials with number; IRCT2016030326886N1.The present study is an 8-week double-blind, randomized controlled trial conducted based on the CONSORT guidelines . During 3 less than 30 ng/dL  were selected based on the inclusion and exclusion criteria. From the 66 patients included at baseline, all participants completed the study , normal weight (19.5 < BMI ≤ 25 kg/m2), over weight (25 < BMI ≤ 30 kg/m2) and obese (BMI>30 kg/m2). Moreover, the baseline levels of 25-OH-vitamin D and magnesium were not different between the intervention and control groups , peer problem (P = 0.006), total difficulties (P = 0.009) and internalizing (P = 0.003) was significant. Peer ploblem was a significant effect on all covariates, externalizing was significant in all covariates except age and finally internalizing was significant in age and sex. The effect size of Cohen’s d showed that the mean differences, which are significant, also have larger effect effects. The effect sizes related to interventions in the precision of model for internalizing (14%), peer problem (12.2%) and total difficulties (11.2%) were more than others. Among the effect sizes written for the different models in Table The effect of co-supplementation of vitamin D and magnesium on the components of SDQ with and without adjusting for age, sex, BMI and Ritalin dose are shown in Table problem 1.2% and tThe adjusted mean for the SDQ component in gender and groups was summerised in Table To the best of our knowledge, the present study is one of the few studies to examine the effect of vitamin D, and magnesium supplementation in Iranian children with ADHD. The results showed that vitamin D and magnesium supplements could decrease emotional, peer problems, total difficulties and internalizing scores compared to placebo. However, these supplementations did not have a significant effect on conduct problem, prosocial, externlising and hyperactivity scores. Also, the intervention showed a lower mean for the SDQ components in girls compared to boys.ADHD is a common psychiatric disorder among children influenced by genetics and environmental factors . ADHD has three symptoms, including impulsivity, hyperactivity, and lack of attention , 33. RecOne study showed that serum magnesium levels in people with ADHD were significantly lower than in the general population as well as in laboratory references. Therefore, given the role of magnesium in the nervous system, it is likely that magnesium supplementation within this patient population can help improve symptoms , 43. SimIn a previously published manuscript from this study, children’s behavioral problems were examined with Conners’ Parent Rating Scale-48 (CPRS-48), the results of which indicated improved behavior . In contOur study had several limitations. First, we investigated the combined effect of magnesium and vitamin D, and the effect of each supplement was not studied separately. Second, our sample size was relatively small. Future studies should be designed to determine both the combined and individual effect of these micronutrients on people with ADHD in a larger population. Third, the dietary intakes of magnesium and vitamin D as essential cofounders were not assessed. Fourth, the duration of follow-up was short, so long-term effects are unknown. Finally, participants with low serum levels of these two micronutrients were included in the study, so it is unclear whether supplementation can be effective in patients with ADHD who are not deficient.Vitamin D  and magnesium (6 mg/kg/day) co-supplementation for a duration of 8-weeks could improve the behavioral function and mental health in children with ADHD affected with low serum level of vitamin D and magnesium. However, further well-designed studies with larger sample sizes are needed to validate our findings and determine whether vitamin D and magnesium deficiency are the results of ADHD or whether they are risk factors for this disorder.


Objective: This article aims to assess whether individual differences in reward sensitivity can be used to predict which children with attention-deficit/hyperactivity disorder (ADHD) will benefit most from behavioral interventions that include reinforcement. Methods: A 12-week behavioral intervention was offered to 21 children with ADHD and their parents. Reward sensitivity was assessed prior to the intervention using a combination of psychological and physiological measures. ADHD symptoms were assessed pre- and posttreatment using the Strengths and Weaknesses of ADHD and Normal behavior (SWAN) rating scale. Results: Lower scores on one of the questionnaire scales were associated with greater pre/posttreatment differences in ADHD symptoms. Conclusion: We found that pre/posttreatment change was associated with one measure of parent-rated reward sensitivity. Children with low impulsive negative behavior toward gaining reward improved most during treatment. This result suggests that aspects of reward-related behaviors in ADHD may be useful to predict the effectiveness of treatment. Behavioral interventions are recommended for the treatment of children with attention-deficit/hyperactivity disorder ADHD; . These iSensitivity to reward and reinforcement has been reported to be changed in children with ADHD compared with typically developing children. Both in behavioral data and in neuropsychological and imaging data, differences have been found at the group level , 2010. CBased on this information, recommendations for clinical practice are that children with an ADHD diagnosis may benefit most from immediate reward and need more frequent and consistent reinforcement than typically developing children for reward to be effective , 2011. TDiagnostic and Statistical Manual of Mental Disorders, 5th ed.; DSM-5; individual reward processing to predict the effectiveness of behavioral interventions for individual children. In addition, to test the construct validity of our reward sensitivity measures, we assessed correlations between the various measurement modalities.Despite the integration of these clinical recommendations, the utility of research findings has been limited in clinical practice, likely due to the highly heterogeneous nature of ADHD. Although at the group level ADHD has been linked to changes in reward sensitivity, these findings may not be relevant to all children with ADHD, due to large inter-individual differences  and Altrecht Center for Mental Healthcare . Data were collected at the UMC Utrecht.Scoring with ADHD) treatment program  met full inclusion criteria for this study; 18 boys and three girls. We used DISC-IV scores to further classify participants. Children met criteria for the following DSM-IV subtypes: 13 combined type, one inattentive type, and seven hyperactive/impulsive type. We classified 12 participants as having comorbid oppositional defiant disorder (ODD), two of whom also met criteria for conduct disorder (CD). Nine participants were not receiving any psychopharmacological treatment, five were taking methylphenidate, one participant was receiving atomoxetine and the remaining six participants were taking other medication. Parents of one participant did not complete the posttreatment questionnaires. Consequently, the main outcome measures could not be computed for this participant and we excluded these data from all analyses.Scoring with ADHD). This is a group-based behavioral therapy program for children with ADHD and their parents, that incorporates all major components of typical behavioral child/parent interventions in ADHD  rating scale  administWe operationalized reward sensitivity using three modalities. Behaviorally, using a questionnaire, neuropsychologically, using two neuropsychological tasks and psychophysiologically, using heart rate measures. We used these measures to capture a variety of indices of reward-sensitivity and to assess preliminarily which of these modalities was most predictive of pre/posttreatment change.We used the Dutch translation of the Sensitivity to Punishment and Sensitivity to Reward Questionnaire for children SPSRQ-C;  as a parWe used two neuropsychological tasks to probe different aspects of reward processing. The Hungry Donkey Task HDT;  is a comThe Spongers task is a child-friendly version of the Monetary Incentive Delay Task (MID), where reward frequency and magnitude are experimenter-controlled . This taHungryDonkey-Baseline, HRVSpongers-Baseline, HRVSpongers80%−Spongers20%, AHRHungryDonkey-Baseline, AHRSpongers-Baseline, AHRSpongers80%−Spongers20%.The measurement of physiological responses to reinforcement have a long history in research of disruptive disorders . They hat tests to compare parent-rated symptoms of ADHD before and after treatment.We tested all variables for missing values, normality of distribution (using the Shapiro-Wilk test) and outliers (using an interquartile range larger than three). Two participants missed a question on the pretreatment SWAN questionnaire and three participants missed a question on the posttreatment SWAN questionnaire. We omitted these scores when computing average scale scores. The majority of the data was normally distributed and included no univariate outliers. For some measures, we ran regression analyses with non-normally distributed data, and additionally tested these using spearman correlations. This was the case for the SPSRQ-C scales Reward Sensitivity and Drive, the percentage advantageous doors in the HDT, and the HRV data. Since the nonparametric analyses for these measures did not differ meaningfully from the parametric ones, we report only the parametric analyses. To assess pre/posttreatment change we used paired samples Hungry Donkey-Baseline, HRVSpongers-Baseline, and HRVSpongers80%−Spongers20%. In exploratory, post hoc analyses we entered a number of additional reward sensitivity variables. We entered heart rate measures  and two additional factors of the SPSRQ-C questionnaire  as predictor variables.We tested for associations between reward sensitivity measured prior to treatment and pre/posttreatment change in ADHD symptoms. To do so, we used linear regression with SWAN change scores as outcome variables  and reward sensitivity measures as predictor variables. Primary predictor variables included: the SPSRQ-C subscales Reward Sensitivity, Impulsivity/Fun Seeking and Drive; the HDT percentage advantageous doors, Spongers RegB_20_2, Spongers RegB_80_2, HRVsupplementary material.To assist hypothesis-generation for future research, we tested associations between the reward sensitivity measures in different modalities, using correlational analyses. Further information on these analyses can be found in the We ran sensitivity checks for the influence of IQ and baseline heart rate on our main analyses. As some of the original heart rate data sets included temporary signal losses, we assessed whether the quality of heart rate data influenced the results. We did this by entering a dummy variable of heart rate data quality (complete data sets vs. incomplete data sets) in the regression analyses with significant results. We found no evidence of these measures affecting our outcome and therefore reported our results without them.M = −.60, SD = 1.01) and less hyperactive  after treatment, than they did before treatment, M = −1.29, SD = .78 and M = −1.47, SD = .67 respectively; t(19) = −3.59, p < .05 and t(19) = −3.29, p < .05.Values of pre- and posttreatment measurements of the SWAN questionnaire can be found in β = −.809, t(20) = −2.717, p = .014, and the SWAN Total Scale, β = −.665, t(20) = −2,551, p = .020; see r = .54 and r = .52, respectively). This means that hyperactive behavior was more likely to diminish during treatment in children with low parental ratings on the impulsivity/fun seeking scale. The impulsivity scale consists of four slightly divergent items that focus on gaining social status through unfair means, not being able to resist the temptation to do forbidden things, showing risky behavior to get a reward and not doing things you enjoy so as to not be rejected or criticized. We found no relationship between pre/posttreatment change in ADHD symptoms and task performance, heart rate variability or the other SPSRQ-C subscales. In an exploratory, post hoc regression analyses we found no relationship between pre/posttreatment change in ADHD symptoms and heart rate measures  or the two additional SPSRQ-C sub-scales. Results of these regression analyses can be found in We found that pre/posttreatment change was associated with one scale of the parent-rated reward sensitivity questionnaire. Lower scores on the SPSRQ-C Impulsivity/Fun seeking scale were associated with larger change scores on both the SWAN Hyperactivity Scale,  −.809, t0 = −2.71supplementary materials.In correlations between variables of the same modalities, we found different heart rate measures to be highly positively intercorrelated, with only a few significant correlations in the questionnaire and task data. Across modalities, measures of reward sensitivity mostly did not correlate. Further information on these correlations is provided in the The aim of this pilot study was to assess whether reward sensitivity, as assessed a-priori, can predict pre/posttreatment differences in core ADHD symptoms in the context of a behavioral intervention using reward contingencies. Our treatment was a reward contingency assisted behavioral intervention incorporating evidence-based elements of typical behavioral interventions. We hypothesized that those children with ADHD who had the greatest sensitivity to reward, would benefit most from the behavioral intervention. To test this hypothesis, we collected reward sensitivity data from different modalities; a questionnaire, two neuropsychological tasks and heart rate measurements, and assessed their predictive relationship with pre/posttreatment differences in parental ratings of ADHD symptoms. Children showed improvement overall, as parents rated their children less inattentive and hyperactive after treatment. These findings are in line with previous research that has shown that behavioral interventions are moderately effective . ChildreThe name of the scale “impulsivity/fun seeking”, was introduced during previous iterations of factor analyses of the SPSRQ-C , but perAlthough the association between impulsive negative behaviors to gain reward and the effectiveness of treatment is promising, these results should be interpreted with caution. First, in view of the exploratory nature of our study, we chose not to correct for multiple testing. This increases the likelihood of false positive findings. Moreover, both measures were based on parental ratings. The lens through which parents view and rate their children may affect outcome as questionnaire data completed by the same rater are not entirely independent. This phenomenon has been called common method variance . Its impsupplementary material.In addition to the matters discussed above, there is the initial value-problem: those children who show the most severe symptoms on pretreatment measures may be most likely to improve, whereas children with milder symptoms may show less improvement. We carried out additional analyses where we defined treatment outcome simply as posttreatment SWAN scores. These analyses showed similar results to the ones in the main paper, although two additional regression analyses reached statistical significance: the SPSRQ-C Impulsivity/Fun Seeking scale was associated not only with the posttreatment SWAN Hyperactivity Scale, but also with the posttreatment SWAN Attention Scale. Furthermore, we found that differences in heart rate variability between the Spongers 80% condition and the Spongers 20% condition were associated with the posttreatment SWAN Hyperactivity scale. Detailed information on these analyses can be found in the All our measures of reward sensitivity have previously been used successfully in research on reward sensitivity. The SPSRQ-C-questionnaire is the most ecologically valid measure, commonly used in research on reward sensitivity. It has been shown to differentiate between typically developing children and children with an ADHD diagnosis . Our twoWe found no evidence for the predictive value of heart rate measures or neuropsychological task performance on pre/posttreatment change. Other studies have previously tried to identify and quantify clinically relevant biomarkers of reward sensitivity . To dateThis study was setup as a pilot study and accordingly, we included only a small number of participants. As such, our power to detect more subtle differences in reward sensitivity was limited. Furthermore, we used a single-arm design and lacked a control condition for pre/posttreatment change. Therefore, it is difficult to discern if pre/posttreatment differences are due to the behavioral intervention or whether other factors played a role. Due to the small-scale design of our study, we did not assess the impact of psychopharmacological treatment on the relationship between reward sensitivity and treatment outcome. This may be an important factor to study more thoroughly in future studies.In this pilot study, we made a first attempt to connect the extensive neuroscientific literature on reward processing in children with ADHD to clinical practice. We found that pre/posttreatment change was associated with one specific aspect of parent-rated pretreatment reward sensitivity. This result suggests that children with low impulsive negative behavior to gain reward, may benefit most from a behavioral intervention using reward contingencies. This preliminary finding is promising in that it suggests individual neuropsychological profiles in ADHD may perhaps be applicable for predicting the effectiveness of treatments. However, this is a small pilot study and larger studies are warranted before translating these findings to everyday clinical practice.Click here for additional data file.Supplemental material, Supplement_material for Which Child Will Benefit From a Behavioral Intervention for ADHD? A Pilot Study to Predict Intervention Efficacy From Individual Reward Sensitivity by Myrte J. M. van Langen, Branko M. van Hulst, Miriam Douma, Maarten Steffers, Nicolle M. H. van de Wiel, Els van den Ban, Sarah Durston and Patrick de Zeeuw in Journal of Attention Disorders


Background: Dietary habits were investigated as environmental risk factors for Attention-Deficit/Hyperactivity Disorder (ADHD). However, no previous studies explored the effects of dietary factors on modifying the role of genetic factors on ADHD. Methods: Based on a Swedish population-based twin study with 1518 twin pairs aged 20–47 years, we tested whether the importance of genetic and environmental effects on ADHD varied as a function of dietary habits. Self-reported dietary habits and ADHD symptoms were collected. Twin methods were used to test the degree to which high-sugar and unhealthy food intake moderated the genetic and environmental influences on ADHD symptoms. Results: In middle-aged adults, genetic influences on inattention symptoms were statistically significantly higher among individuals with higher levels of high-sugar  and unhealthy food intake , compared with those with lower levels of consumption of high-sugar  and unhealthy foods . Similar patterns were also found for the associations between hyperactivity/impulsivity and high-sugar/unhealthy food intake, even though the moderation effects were not statistically significant. Conclusion The present study suggests that genetic factors play a more prominent role in individual differences of ADHD symptoms in the presence of the high consumption of sugar and unhealthy foods. Future longitudinal studies with multiple assessments of ADHD and dietary habits are needed to replicate our findings. Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder characterized by developmentally excessive inattention–disorganization and hyperactivity–impulsivity symptoms . AlthougA key framework for understanding the complex contribution of both genetic and environmental influences on ADHD is gene–environment interactions (G × E), that is, the importance of genetic factors may be dependent on key environmental factors . StudiesAs suggested by available studies, genetic risk variants associated with ADHD seem to have a stronger impact on the presence of unfavourable environmental conditions . EmerginSeveral studies used a candidate gene  approach to explore G × E interactions in ADHD ,23,24. HThe purpose of the present study was to study how dietary habits influence the magnitude of genetic and environmental contributions to ADHD in adults, considering the inattentive and hyperactive/impulsive symptom dimensions separately. Based on previous literature, we hypothesized that genetic factors associated with ADHD were more likely to cause the disorder among adults with unhealthier food habits, as compared to adults with healthier food habits.Data were collected from participants in the Study of Twin Adults: Genes and Environment (STAGE), which only includes twins born in Sweden between 1959 and 1985 . In the Self-reported ADHD symptoms: were obtained via an 18-item questionnaire derived from the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV), with two subscales reflecting the inattentive and hyperactive/impulsive symptom dimensions [mensions . Both inmensions . As suggmensions , in thisFood habits: were assessed by a food frequency questionnaire (FFQ) with 94 food items. For each food item, the participants reported their average consumption frequency over the past year by selecting one of the following frequencies: never, 1–3 times/month, 1–2 times/week, 3–4 times/week, 5–6 times/week, 1 time/day, 2 times/day, 3 times/day. The frequency for each food item was converted into number of servings per day. Consistent with a previous study [us study , high-suTwin data can be used to estimate the genetic and environmental contributions to variation in a trait by comparing the similarity between monozygotic twins  and dizygotic twins . In the additive model, total phenotypic variance of a trait can be broken down into three components: A—additive genetic influences, or narrow-sense heritability; C—shared environmental influences, which are common to both twins in a pair and make them similar; and E—non-shared environmental influences, which impact the twins individually, and also include random measurement errors .Intra-class correlations were calculated for MZ and DZ twins by ADHD symptom dimensions and each dietary habit group. For our primary analyses, we first standardized the log-transformed ADHD symptoms to have means of 0 and standard deviations of 1. Age and sex were included as covariates on the mean of the phenotype. Second, we estimated the variance of ADHD by A, C and E components. We then excluded C component to test if the AE model was not statistically significantly different from the full ACE model , if so, AE models were used in further analyses.Next, we expanded our analyses by evaluating whether dietary habits moderated the aetiology of ADHD using the ‘extended univariate G × E’ model , which eTo test the gene–environment interaction hypotheses, we determined whether the moderation paths significantly improved the fit of the full ACE/AE moderation model using a negative two times the log-likelihood value (−2lnL) statistic. First, a global test of moderation was conducted by constraining the moderation effects on all of the components to be zero. Second, to test whether the moderation was driven by specific pathways, we then fitted a series of nested models, dropping moderation of the mean components, the variance components and all moderation separately and assessing the change in fit. If dropping moderation paths statistically and significantly reduced model fit (indicated by a significant chi-square χ2 statistic), then the result supported the hypothesis that the environmental variable moderated the heritability of ADHD symptoms. Otherwise, if the model fit was not significantly worse with moderator paths excluded, then dietary habits did not modify the heritability of ADHD symptoms .All analyses were performed by using the structural equation modelling in the statistical software R version 3.6.1, with the OpenMx package (2.14.11).Descriptive statistics for the study population are presented in Next, to address our main research question, we tested the significance of the moderation between ADHD symptoms and dietary habits by dropping parameters from the best-fitting AE models. To our knowledge, this is the first twin study to test whether two dietary habits, high-sugar food and unhealthy food, moderate the heritability of ADHD symptoms. We found that in middle-aged adults, dietary habits significantly moderated genetic and non-shared environmental contributions to ADHD symptomatology. Specifically, genetic influences on ADHD symptoms increased at higher levels of high-sugar and unhealthy food intake but were lower when consuming less of these diets. By contrast, non-shared environmental contributions to ADHD symptoms were highest at lower levels of high-sugar and unhealthy food intake and decreased as these dietary consumptions increased. Such findings thus serve to not only illuminate the origins of ADHD, but also provide important empirical support the diathesis–stress model of G × E .There are several potential explanations for how dietary factors moderate the influence of genetic and environmental effects on ADHD. Firstly, the field of nutrigenomics has yielded valuable information on how dietary and nutrition influences an individual’s genetic composition and gene expression ,37. ResuSome limitations of the study warrant discussion. Firstly, the current sample was underpowered for examining G × E effects separately by sex and age. Even though we found stable phenotypic and genetic associations between ADHD symptoms and dietary habits across age, sex and SES groups, and we also adjusted for age and sex in the G × E modelling, the future examination of sex and age differences in aetiological mechanisms, including G × E effects, remains important. Second, we examined ADHD symptoms dimensionally by using self-reported data. Given that self-reports among adults typically underestimate the presence of ADHD symptoms and also generate lower heritability estimates compared to reports from other informants  , future The present study showed that the heritability of ADHD symptoms was higher with a high consumption of high-sugar and unhealthy foods, a finding that supports the diathesis–stress model. The finding provides further insights into a better understanding of mechanisms underlying ADHD, as well as directions for genome-wide G × E studies. Future longitudinal studies with multiple assessments of ADHD and dietary habits are still needed to replicate our findings.


Pseudomonas is a diverse genus of Gammaproteobacteria with increasing novel species exhibiting versatile trains including antimicrobial and insecticidal activity, as well as plant growth–promoting, which make them well suited as biocontrol agents of some pathogens. Here we isolated strain 1257 that exhibited strong antagonistic activity against two pathovars of Xanthomonas oryzae, especially X. oryzae pv. oryzicola (Xoc) responsible for the bacterial leaf streak (BLS) in rice. The phylogenetic, genomic, physiological, and biochemical characteristics support that strain 1257 is a representative of a novel Pseudomonas species that is most closely related to the entomopathogenic bacterium Pseudomonas entomophila. We propose to name it Pseudomonas oryziphila sp. nov. Comparative genomics analyses showed that P. oryziphila 1257 possesses most of the central metabolic genes of two closely related strains P. entomophila L48 and Pseudomonas mosselii CFML 90-83, as well as a set of genes encoding the type IV pilus system, suggesting its versatile metabolism and motility properties. Some features, such as insecticidal toxins, phosphate solubilization, indole-3-acetic acid, and phenylacetic acid degradation, were disclosed. Genome-wide random mutagenesis revealed that the non-ribosomal peptide catalyzed by LgrD may be a major active compound of P. oryziphila 1257 against Xoc RS105, as well as the critical role of the carbamoyl phosphate and the pentose phosphate pathway that control the biosynthesis of this target compound. Our findings demonstrate that 1257 could effectively inhibit the growth and migration of Xoc in rice tissue to prevent the BLS disease. To our knowledge, this is the first report of a novel Pseudomonas species that displays a strong antibacterial activity against Xoc. The results suggest that the P. oryziphila strain could be a promising biological control agent for BLS. Pseudomonas species are gram-negative bacteria that are ubiquitous in soil, water, animals, and plant rhizosphere , siderophores, and volatile organic compounds (VOCs)  . Phenazis (VOCs) . TherefoXanthomonas. Pseudomonas entomophila is an entomopathogenic bacterium that is able to kill Drosophila larvae and adults. Its entomopathogenic property and hemolytic activity have been associated with insecticidal toxins and cyclic lipopeptides , a causative agent of citrus canker , and X. oryzae pv. oryzicola (Xoc)  . The P. activity . WhetherXoc can infect the host rice causing bacterial leaf streak (BLS) that has gradually become the fourth major disease on rice in some rice-growing regions in southern China, resulting in a yield reduction of 10–30% in some severe cases  or nutrient broth (NB) medium at 28°C (Escherichia coli DH5α and EC100D were grown in Luria–Bertani (LB) medium at 37°C. Rice seeds (Yuanfengzhao) were provided by Dr. Youlun Xiao from the Institute of Plant Protection, Hunan Academy of Agricultural Sciences. Antibiotics were used at the following final concentrations (μg mL–1) as required: rifampicin (Rif), 75; kanamycin (Km), 25; gentamicin (Gm), 10; and spectinomycin (Sp), 25.The bacterial strains and plasmids are listed in  at 28°C ; Escheri–3, 10–4, and 10–5 in sterilized water. The Xoc RS105 was used as an indicator, through inhibiting its growth to screen biocontrol strains. A 100-μL diluted solution was plated onto NA agar plates containing RS105. The plates were incubated at 28°C for 2 days. Colonies with antagonistic activity were transferred and purified and then were further confirmed by the Oxford Cup method. The inhibition zones were measured by Kirby–Bauer (KB) test method. Each inhibitory phenotype was repeated in triplicate. The antagonistic bacterial isolates were collected and stored at -80°C with glycerol . Strain 1257 was isolated from the rhizosphere soil of cabbage collected on September 27, 2017 from Cungu village in Zhuanghang town, Fengxian District, Shanghai, China.The rhizosphere soil samples from healthy plants were collected from 23 provinces in China. Briefly, a 10-g soil sample with several steel balls was added to a triangular conical flask with 90-mL sterilized water and then was shaken for 20 min at 28°C, 200 revolutions/min (rpm). A 1-mL suspension was diluted to three gradients of 10P. oryziphila 1257 was examined using Xanthomonas strains, non-Xanthomonas strains, and some fungal pathogen strains listed in 600 = 2.0 using NB medium, and then the 200 μL solutions were added into the NA medium plates. A 50 μL (OD600 = 2.0) P. oryziphila 1257 solution was added into the Oxford Cup. The inhibition zones were measured using KB method and sterile water as the negative control. Three biological replicates were performed. The antifungal activity of P. oryziphila 1257 was further studied by confrontation–culture plating method according to the reported protocols.The antimicrobial activity of 16S rRNA gene sequence was amplified using universal primers of 27F and 1492R (2+ Plus) (20 mM), 4 μL of dNTP mixture (10 mM), 1 μL of each primer (10 μM), 1 μL of genomic DNA template (30–50 ng/μL), and 0.25 μL of Ex Taq DNA polymerase , with double-distilled water up to 50 μL. The polymerase chain reaction (PCR) amplifications were performed according to the following parameters: initial denaturation at 95°C for 8 min and then 32 cycles of 30 s of denaturation at 95°C, 30 s of annealing at 55°C, and 1.5 min of extension at 72°C, and a final extension at 72°C for 10 min. The 1,500-bp fragment was purified and sequenced in BioSune Biotech . The complete DNA sequence was used for blast search in the National Center for Biotechnology Information (NCBI) database. The multilocus sequence analysis (MLSA) phylogenetic tree was established and performed. The genome sequences for the other 15 representative Pseudomonas species were obtained from the NCBI database. The nucleotide sequences of 10 housekeeping genes 16Sr RNA, aroE, dnaA, guaA, gyrB, mutL, ppsA, pyrC, recA, and rpoB were aligned using Muscle (version 3.8.425), and the unreliable comparison points were removed using Gblock (version 0.91b) to ensure that these sequences were suitable for phylogenetic analysis. A maximum likelihood–based phylogenetic method was performed with MEGE 7.0 software, with 1,000 bootstrap replicates; the internodes of branches indicated the percentage ; DNA quality and integrity were determined by using a Qubit Flurometer  and a NanoDrop Spectrophotometer . The whole genome was sequenced using the Pacific Biosciences platform and the Illumina Miseq platform at Personalbio . The complete genome sequence of P. oryziphila 1257 was deposited in GenBank under accession number CP034338.1.The genomic DNA of P. oryziphila 1257, P. entomophila L48, and P. mosselii CFML 90-83 were filtered to remove low-quality sequences based on length and percent stop codons in FASTA format. Then these proteomes were compared to each other based on an all-versus-all BLASTP alignment with an E value of 1e-10, I (Inflation) of 1.5 and at 70% identity. The BLASTP results are retrieved with the MCL program for clustering to construct gene families using OrthoMCL software (version 2.0.8). At last, through the Perl 5.8, DBI libraries to organize and count above clustering results were included.For comparative analyses of the orthologous and exclusive genes between 1257 and the other two closest genomes, the protein sequences of P. oryziphila 1257, P. entomophila L48, and P. mosselii CFML 90-83 by using Mauve software (version 2.3.1) with default parameters  assay was used for detecting the siderophore production according to the published methods . Three sP. oryziphila 1257 competent cell with 1 μL of the EZ-Tn5 < R6Kγori/KAN-2 > Tnp transposome. The electroporated cells were immediately recovered with LB medium to the electroporation cuvette to 1-mL final volume. The medium was mixed gently by a pipette, transferred to a tube, and incubated on a 28°C shaker for 2 h to facilitate the cell outgrowth. Each 200 μL of the cells was plated on four plates containing Km and incubated at 28°C for 2 days. The colonies were moved individually to the NA agar medium containing Xoc RS105 and Km to screen the mutants that exhibited absolutely losing, apparently and partially attenuated antagonistic activity against Xoc RS105.Random mutagenesis was performed by electroporation of EcoRI and then were self-ligated by mixing 8 μL of the digested DNA with 1 μL of ligation buffer and 1 μL of T4 DNA ligase . The mixture was incubated at 22°C for 12 h and then inactivated at 70°C for 10 min. An aliquot of 5 μL of the ligation mixture was used to transform E. coli EC100D pir+ electrocompetent cells and then were plated on LB plates containing Km. Colonies were screened by amplified with the primers Tn5-F and Tn5-R in The genomic DNA from chosen mutants was digested by lgrD, carA, carB, purF, and serC genes were amplified by PCR with primers listed in -lgrD by XbaI and HindIII digestion resulting in pML-carA and pML-carB by BamHI and XbaI digestion, resulting in pML-serC by BamHI and SacI digestion, as well as resulting in pML-purF by HindIII and SacI digestion. Correct recombinant plasmids were confirmed by PCR using the primers pML123-F and pML123-R listed in Here we selected five mutants of 100-12, 56-11, 62-42, 62-27, and 92-23 to complement. Briefly, the open reading frame sequences with the promoter regions of Xoc RS105 (OD600 = 0.6) by needle injection. 1257 treatment (1257-Tre) meant that rice leaves were sprayed with 1257 (OD600 = 1.0) 12 h after inoculation with Xoc RS105 suspension. 1257 preventive treatment (1257-Pre) indicated that rice leaves were sprayed with 1257 12 h before inoculation with Xoc RS105 suspension. Three independent experiments were performed. The BLS disease severity under all treatments was investigated after 15 ays. For biocontrol assays in greenhouse, three leaves from 2-week-old Yuanfengzao were inoculated with Xoc RS105-Gus (OD600 = 0.6) by needleless syringe. The 1257-Tre and 1257-Pre indicated that rice leaves were injected with 1257 at 3 h after and before inoculation with Xoc RS105-Gus suspension, respectively. Three pots were injected in one leaf. Two independent experiments were performed. The BLS disease severity under all treatments was observed after 1, 3, 5, and 7 days. The inhibitory percentages (IPs) were calculated by the formula: IP = (1-lesions length of treatment/lesions length of control) × 100. The IP was calculated by using three technical replicates per assay. Student t test was used for significance (p < 0.05), and the statistical results were treated by GraphPad Prism 8 version.For biocontrol assays in rice fields, 10 leaves from the highly susceptible rice cultivar Yuanfengzao at booting stage were inoculated with Xoc RS105-Gus strains including staining and quantitative detection for each treatment in greenhouse was conducted as our previous methods (The β-glucuronidase (GUS) activity of  methods .Xoc wild-type strain RS105 from the 248 rhizosphere soil samples collected from 23 provinces in China. Among these isolates, we found that one strain, 1257, strongly inhibited Xoc RS105 (with an inhibition zone > 40 mm) and other eight Xoc strains isolated from Chinese major rice-growing regions . The antifungal activity assays showed that 1257 displayed no any inhibitory effect on five fungal pathogens including Magnaporthe oryzae, Fusarium graminearum, Fusarium oxysporum, Botrytis cinerea, and Phytophthora capsici (data not shown). These results suggest that 1257 exhibits specific inhibitory activity against Xoc and Xoo, two pathovars of X. oryzae.To screen beneficial bacterial resources to control BLS, we attained 223 bacterial isolates that displayed evident antibacterial activity against the  regions . We foun strains . Furtheruglandis , and no 16S rRNA gene sequence of 1257 was amplified and aligned with the 16S rRNA gene sequences that have been deposited in the NCBI database. The BLAST analysis indicated that 1257 belongs to the Pseudomonas genus; however, the 16S rRNA gene sequence of 1257 exhibited more than 99% similarity with the corresponding sequences of P. entomophila L48 (99.54% similarity) and P. mosselii CFMT90-83 (99.48% similarity). To define the phylogenetic status of 1257, we sequenced the complete genome of 1257  using MLSA showed that 1257 located in a separate branch with the type strains of P. entomophila L48 and P. mosselii CFMT90-83 as its nearest neighbors  value between 1257 and P. entomophila L48 was 34.10%, and the DDH value between 1257 and P. mosselii CFML 90-83 was 34.70%. These two values were less than the accepted species threshold of 70%. Together, these results suggested that 1257 is a novel species within the Pseudomonas genus, which is closely related to P. entomophila and P. mosselii species.Further, we conducted an ANI analysis between 1257 and other 15 sequenced different species in the phylogenetic tree. All ANI values (ANIb and ANIm) between 1257 and individual species of the genus are in the range of 73.77 to 89.13% , which iP. entomophila L48 and P. mosselii CFML 90-83 were attained from the previous studies -glucuronic acid, and 2,3-butanediol. 1257 displayed the same as P. entomophila L48 in urease activity and in the ability to use L-fucose, psicose, α-ketobutyric acid, and dimethyl succinate as carbon sources. 1257 differed from P. entomophila L48 in the capacity to use glycogen, which is negative for 1257 and P. mosselii CFML 90-83. Combined with the antagonistic phenotypes that P. entomophila L48 exhibited similar antibacterial activity against Xoc RS105 with 1257, but P. mosselii CFML 90-83 displayed no inhibitory effect on Xoc RS105 .Synthetically considering the phylogenetic, genomic, physiological, and biochemical characteristics, we propose strain 1257 as a representative of a novel P. oryziphila 1257 is composed of a circular chromosome of 6,049,604 base pairs , the tricarboxylic acid cycle (TCA), and the Entner–Doudoroff (ED) pathway. We found no gene encoding a 6-phosphofructokinase present in the P. oryziphila 1257 genome. This is consistent with P. entomophila metabolism  were found in the genome of P. oryziphila 1257 , pilO (chr_orf 05631), and pilS (chr_orf 05634), are involved in encoding type IVB pilus biosynthesis protein. Only seven T4P homologous genes in P. oryziphila 1257 were identified in the genome of P. entomophila L48, whereas 17 T4P orthologous genes were found in the genome of P. mosselii CFML 90-83  was found in the genome of P. oryziphila 1257, but one gene encoding the T3SS effector HopPmaJ (T3SE) was found in P. oryziphila 1257, which is in agreement with the previous report in P. entomophila  but not the genes associated for the biosynthesis of 2,4-DAPG, phenazines, pyoluteorin, pyrrolnitrin, pyochelin, pyocyanine, and xantholysinABCD. We also detected several genes or gene clusters involved in plant–bacteria interactions in the genomes of P. oryziphila 1257, including the iacR gene involvement in the indole-3-acetic acid (IAA) degradation pathway, the paa gene involved in the phenylacetic acid (PAA) degradation pathway, indicating that P. oryziphila 1257 might help to balance the delicate IAA and PAA equilibrium in the rhizosphere. A unique acoABC operon involved in the biosynthesis of acetoin that has been known as one kind of VOC promoting plant growth was detected in the genome of P. oryziphila 1257. Similar to P. entomophila and P. mosselii, P. oryziphila also possesses the pyrroloquinoline quinone (PPQ) biosynthesis genes pqqE, pqqD, and pqqB, which were predicted to participate in phosphate solubilization. These results suggested that P. oryziphila 1257 may have the potential to promote plant growth.Some potential second metabolites including toxins, antibiotics, and cyclic lipopeptides were found and are listed in omophila . Anotheromophila , which eP. oryziphila 1257 contains eight candidate gene clusters encoding a dipeptide N-acetylglutaminylglutamine amidc (NAGGN), four non-ribosomal peptide synthetase (NRPS), and two ribosomally synthesized antimicrobial peptides, and a pigment of the aryl polyene (APE) type  ions from the surrounding environment  type . The NAGosa PAO1 . The twoironment . The genML 90-83 . Blast cmosselii . CombineXoc RS105. However, these attempts indicated that the active substance may be a strong polar compound. To elucidate the antibacterial mechanism of 1257, we used the transposon mutagenesis based on the EZ-Tn5 < R6Kγori/KAN-2 > Tnp transposome system to screen functional genes associated with antibacterial active compounds. Among the 10,080 mutants, we screened 30 mutants that exhibited absolutely lacking, apparently or partially attenuated antagonistic activity toward Xoc RS105 , a precursor of arginine and pyrimidines metabolism. ArgG encoded by the argG gene is an argininosuccinate synthetase responsible for producing argininosuccinic acid from aspartate. The sdhA gene encodes a subunit A of succinate dehydrogenase that is a key enzyme in the TCA cycle. The six pur genes encoded PurF, PurD, PurL, PurM, PurC, and PurK, which are metabolic enzymes in the PPP, converting ribose-5P from the glycolytic pathway (PP) into 5-carboxyamino-1-(5-phospho-D-ribosyl) imidazole (CPR). Together, these analyses indicated that CP and CPR may be the important precursors for synthesis of the activate compounds and also provided some important evidences for further identification of the target compounds.To define the biological process involved by the function genes mentioned previously, we exerted a Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis . The cardnaK encoding a chaperone protein foldase Dnak that enable the RNA polymerase to sustain bacterial life in response to the stringent response (sohB gene encoding a periplasmic serine protease (ClpP class) and rRNA2 gene encoding the 23s_rRNA, respectively, resulted in partially impaired antagonistic activity of the mutants against Xoc RS105, indicating that posttranscriptional mechanisms may be involved in the modulation of genes associated with biosynthesis of active compounds.Three independent insertions have been shown in response . AnothergntR and lgrD genes that located in the NRPS 4 cluster exhibiting 40% similarity with the L-2-amino-4-methoxy-trans-3-butenoic acid (AMB) biosynthetic gene cluster from P. aeruginosa PAO1 by the antiSMASH analysis. However, the gntR gene encodes a GntR family transcriptional regulator, and the lgrD gene encodes a non-ribosomal peptide synthethase of linear gramicidin synthase subunit D. The gntR and lgrD insertion mutants  exhibited significantly reduced antibacterial activity against Xoc RS105 when compared with the wild-type P. oryziphila 1257, whereas the complemented strain of lgrD insertion mutant nearly restored the antibacterial activity to the wild-type levels , rice leaves sprayed with 1257 12 h after inoculation with Xoc RS105 suspension (1257-Tre) and rice leaves sprayed with 1257 12 h before inoculation with Xoc RS105 suspension (1257-Pre). We fist tested the appropriate concentration of 1257 and found that 1257 as OD600 of 1.0 did not influence the morphology and growth of the rice plants during 15 days in our field trial experiment. Therefore, we used this concentration in all our biocontrol assays. The BLS disease severity under all treatments was investigated after 15 days. Compared with the control treatment, the 1257-Tre and 1257-Pre treatments significantly reduced the severity of BLS in paddy fields with relative control efficiencies of 53.9 and 39.7%, respectively  including pilA encoding the major pilin protein   (pilQ genes encoding the outer membrane (OM) pore complex PilQ1 or PilQ2; other genes such as pilD encoding a pre-pilin peptidase PilD; pilS encoding one of the two-component system PilS  ; the pilnd PilC) ; the piltem PilS ; and thetem PilS . These fPseudomonas species are largely dependent on its secondary metabolites such as toxins, lipopeptides, polyketides, fatty acids, and phenazines  but not the genes associated for the biosynthesis of 2,4-DAPG, phenazines, pyoluteorin, pyrrolnitrin, pyochelin, pyocyanine, and xantholysinABCD. Xantholysins, a family of lipodepsipeptides produced by some P. putida and P. soli strains, exhibits Xanthomonas-inhibitory activity, including Xoo-antagonistic activity  and the paa gene (PAA degradation pathway) in the genomes of P. oryziphila 1257, indicating that P. oryziphila 1257 might help to balance the delicate IAA and PAA equilibrium in the rhizosphere. The acoABC operon putatively participated in the biosynthesis of acetoin, one kind of VOC promoting plant growth  and stability of P. oryziphila 1257. We are trying to improve the stress tolerance of P. oryziphila 1257 through fermentation techniques such as microcapsule bacterial agent to improve its biocontrol effect. Some studies showed that phenazine-1-carboxylic acid (PCA) from Pseudomonas species is very effective against Xoo and Xoc  is an effective biological control agent for BLS, providing a new microbial resource for biological control of bacterial diseases caused by X. oryzae.In summary, we have reported the identification of a novel species, The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/RY and SL designed the research. GC supervised the study. YL, YY, and YF analyzed the data and performed part of the biocontrol experiments. RY and LZ wrote the manuscript. RY, SL, YL, YY, YF, LZ, and GC critically revised the manuscript and approved the final version. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.