Lagenaria siceraria (Molina) Standley is a prominent food source as almost all its plant parts are edible. However, no studies have recorded the changes in shoots, peduncles and fruits during its growth. Hence, this study aimed to record changes in shoot traits and relate the peduncle to the fruit traits of L. siceraria landraces across different growth stages. Changes in shoots, peduncles and fruits during growth were compared within and among landraces using analysis of variance, correlation, principal component analysis, cluster analysis and heritability estimates. Almost all landraces had harvestable shoots at 42 days after sowing. Peduncles became shorter and wider as the fruits elongated. Shoots, peduncles and fruits correlated positively with each other. The informative principal components had a total variability of 84.488%, with a major contribution from shoot traits. The biplot and dendrogram clustered landraces with similar growth habits and the harvestable shoot and fruit attributes into three clusters, but KRI and NSRC formed singlets. Shoot width (60.2%) and peduncle length (55.2%) had high heritability estimates. The general low heritability estimates and genetic advances indicated the presence of non-additive gene action. This study is the first report on changes in harvested shoots and the relationship between peduncles and fruits during growth.  Lagenaria siceraria (Molina) Standley, commonly known as the bottle gourd, is a member of the Cucurbitaceae family , wh, wh13], L. siceraria accessions in India [Furthermore, PC2 was responsible for 24.681% of the variability and was associated with peduncle width, as well as the length, width and mass of fruits in the current study. In corresponding results for germplasm from India, the second principal component had an eigenvalue of 1.64 responsible for 12.64% of the variation in the featured fruit length and fruit width . The difin India . FurtherL. siceraria landraces (significantly correlated with PC1), followed by fruit traits (associated with PC2). However, previous studies indicate fruit traits as the most limiting characteristics that are responsible for variability among L. siceraria landraces [The current study indicates that shoot traits are principal determinants of variation among andraces ,53. The Although PC3 had the least variability percentage (1.457%), it clarified a contrast between the length (r = 0.850) and width (r = −0.672) of peduncles . This reL. siceraria landraces with similar root characteristics in Chile and Mozambique [L. siceraria landraces based on their morphological attributes, as facilitated by the biplot [The grouping of landraces with similar growth trends in shoots and fruits in a biplot  concurrezambique . This wae biplot . In the biplot , the groLandrace NSRC was also a singlet in the dendrogram, whereas KRI was grouped with NRC (cluster V). The association of KRI and NRC can be based on their rough fruit texture and small-sized fruits. Again, the grouping of landraces BG-19, BG-70 and NqSC in cluster II of the dendrogram relates to their association in the biplot (cluster III). Landraces in the third cluster of the dendrogram had longer peduncles at anthesis that had a quicker reduction rate within five days after anthesis. Cluster IV had a mixture of landraces with vigorous shoot growth (BG-26 and BG-31), high fruit abortion rates , and with big and heavier fruits .The higher genotypic variance and genotypic coefficient of variation than the environmental variance and environmental coefficient of variation in almost all traits, except for shoot width and peduncle length of harvested fruits , indicatThe high heritability values recorded in shoot width (60.5) and peduncle length of harvested fruits (55.2) suggest that the environment had a low impact on their expressions . HoweverLagenaria siceraria from different agro-climatic regions in Northern KwaZulu-Natal and Limpopo, South Africa were investigated (Eighteen landraces of stigated . Landracstigated . Landrac2 per pit) and placed below the seeds in 10–15 cm deep pits. Experimental plots were 3 m × 4 m in size, and seeds were spaced with an intra-row spacing of 1 m and an inter-row spacing of 2 m. Each plot had 20 plants with a net plot of 6 m2 having 6 plants. Each of the 18 landraces had 3 replicate plots, which resulted in 54 plots in total, bearing a total of 1080 plants. Weeding and insecticide applications were performed when necessary. The field was irrigated to field capacity for the duration of the experiment using a sprinkler system.The experiment adopted the randomized block design generated by R 4.2.1 software in the RStudio platform . Seeds wVegetative shoot tips were harvested when landraces were at a fourteen-true-leaf stage. Ten shoots were harvested for each plot per harvest. The shoot tip harvesting was conducted over 28 days at 7-day intervals, resulting in four data sets . Shoot tips were pruned at the third mature leaf from the apical bud. The harvested shoot tips of each harvesting period were used to determine the length, width, fresh and dry mass, as well as moisture content. The lengths (mm) of harvested shoot tips per plot were determined using a plastic measuring tape. The fresh mass (g) of the harvested shoots of each plot was determined using the Kern 3 kg analytical scale EWJ 3000-2. The harvested shoots were dried in an oven  at 65 °C until the constant dry mass was obtained. Thereafter, the shoot moisture content (%) was determined using the formula described by :(1)ShootPlants in the net plots were used to measure the peduncle and fruit traits of each landrace. Fruits were identified at anthesis (0 days after anthesis (0 DAA) and had their peduncle length (mm) measured from the leaf axil to the base of the inferior ovary using a plastic measuring tape. The peduncle width (mm) was measured using vernier calipers. Similarly, the length (mm) and width (mm) of the same developing fruits were measured using a plastic measuring tape and vernier calipers, respectively. Measurements of the length and width of peduncles and fruits were continued at 1, 2, 3, 4 and 5 DAA while fruits were still attached to the plants.A total of 5 fruits were also harvested in the net plot of each landrace at 7, 14, 21 and 28 DAA. Harvested fruits had their mass (kg) measured using the analytical weighing scale, as well as their length (mm) and width (mm) measured using vernier calipers. n = 10) were analyzed for each parameter per landrace. Means were separated using Tukey’s HSD test at a 5% significance level. Correlations and a principal component analysis (PCA) were implemented to determine multi-character variation. The ‘pairs. panels’ function in ‘psych’ R package  was used for analyzing the correlations within and among shoot, peduncle and fruit traits at different stages of growth (https://cran.r-project.org/web/packages/psych/) (accessed on 27 July 2022) [Data were subjected to ANOVA using the GenStat 15th edition, and 10 fruits (ly 2022) . A clustThe phenotypic, genotypic and environmental variances and coefficient of variation were calculated according to the formula described by  and cite2p = phenotypic variationδ2g = genotypic variationδx = grand mean of the character studied.2), expressed as the percentage of the ratio of the genotypic variance (δ2g) to the phenotypic variance (δ2p), according to [The estimation of heritability in the broad sense was conducted as follows: broad sense heritability  was estimated as per the formula provided by  and citeGA = expected genetic advance2p = phenotypic variationδ2g = genotypic variationδk = the standard selection differential at 5% selection intensity (k = 2.063).Lagenaria siceraria landraces. It is also the first record of the relationship between changes that occur in peduncle and fruit size during growth.Almost all landraces had harvestable shoots at 42 DAS, which could also be harvested at seven-day intervals, with few exceptions. Landraces BG-24, BG-27, BG-31, BG-100/GC, ESC, KRI and NRC had vigorous shoot growth, whereas DSI, KSC, KSP and NSRP had the largest and heaviest fruits. Peduncles became shorter and wider while the fruits elongated and widened from 0 to 5 DAA in all landraces. Shoot traits correlated positively with each other at all stages of growth. However, peduncle length had a negative correlation with peduncle width both in the correlation matrix and principal component analysis. Shoot traits were the main contributors to variability among landraces followed by fruit traits, based on the principal component analysis. The biplot and dendrogram grouped landraces according to shoot traits, fruit traits, as well as shoot regenerative rate and fruit abortion rate. The phenotypic variation in most traits depended on genetic differences. However, traits that were chiefly affected by environmental variability had higher heritability. All traits had low (<1) genetic advancement. This study recorded for the first time the ideal time to initiate (42–49 DAS) and progressively  harvest shoots from


Transcranial direct current stimulation (tDCS) could be a side-effect-free alternative to psychostimulants in attention-deficit/hyperactivity disorder (ADHD). Although there is limited evidence for clinical and cognitive effects, most studies were small, single-session and stimulated left dorsolateral prefrontal cortex (dlPFC). No sham-controlled study has stimulated the right inferior frontal cortex (rIFC), which is the most consistently under-functioning region in ADHD, with multiple anodal-tDCS sessions combined with cognitive training (CT) to enhance effects. Thus, we investigated the clinical and cognitive effects of multi-session anodal-tDCS over rIFC combined with CT in double-blind, randomised, sham-controlled trial .Fifty boys with ADHD (10–18 years) received 15 weekday sessions of anodal- or sham-tDCS over rIFC combined with CT . ANCOVA, adjusting for baseline measures, age and medication status, tested group differences in clinical and ADHD-relevant executive functions at posttreatment and after 6 months.ADHD-Rating Scale, Conners ADHD Index and adverse effects were significantly lower at post-treatment after sham relative to anodal tDCS. No other effects were significant.This rigorous and largest RCT of tDCS in adolescent boys with ADHD found no evidence of improved ADHD symptoms or cognitive performance following multi-session anodal tDCS over rIFC combined with CT. These findings extend limited meta-analytic evidence of cognitive and clinical effects in ADHD after 1–5 tDCS sessions over mainly left dlPFC. Given that tDCS is commercially and clinically available, the findings are important as they suggest that rIFC stimulation may not be indicated as a neurotherapy for cognitive or clinical remediation for ADHD. Attention-deficit/hyperactivity disorder (ADHD) is characterised by persisting, age-inappropriate and impairing symptoms of inattention and/or impulsivity-hyperactivity , generating subthreshold, polarity-dependent shifts in resting membrane potentials in underlying brain regions. The resulting net increase (predominantly under the anode) or decrease (predominantly under the cathode) in neuronal excitability leads to modulation of the neuronal network  studies is the underactivation of rIFC during tasks of cognitive control , 50 children and adolescents with ADHD were administered 15 consecutive weekday sessions of anodal or sham tDCS over rIFC combined with CT of EF typically impaired in ADHD. The primary outcome measures were parent-rated clinical symptoms and cognitive performance in an inhibition and a sustained-attention task. Secondary outcome measures were other clinical, safety and EF measures.Given some evidence of clinical and cognitive improvements with anodal tDCS over the dlPFC  and medication status (naïve and non-naïve) using Smith randomisation , double-blind, sham-controlled, parallel RCT compared multi-session anodal  Kaiser,  conducte Kaiser, .t score > 60)  were recruited from South London clinics, social media and parent support groups (February 2018–20). All participants had a clinical DSM-5 diagnosis of ADHD established by a clinician, and validated by the Schedule of Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime version  . To help avoid medication effects from masking tDCS effects, 14 of the 32 participants followed our optional request to abstain from psychostimulants at least 24 h before each assessment time point (range: 24–72 h), of which eight abstained only 24 h beforehand . A further seven participants abstained for trial duration (i.e. baseline to posttreatment). One participant stopped taking medication 3 months before follow-up.TM . ACTIVATETM games were played on an iPad Air 2 10.2″, the Stop task on a Dell XPS 15.6″ Touch Laptop  and visual-spatial working memory . Before each game, participants chose a game to play from three options; the ACTIVATETM programme tracked choices and constrained future options so that multiple EF were twice as likely to be trained as working memory  stop signal  with a 30 s fade-in/fade-out. For sham stimulation, only the 30 s fade-in/fade-out was administered  via a pair of 25 cmThe adult version of the Maudsley Attention and Response Suppression (MARS) task battery  Home Version  , the Wisconsin Card Sorting Task  for Go (GNG), Congruent (Simon) and Target (CPT) trials]; and (3) prematurity  .Three intercorrelated generic, task-independent EF were measured, which included: (1) general speed of information processing  (2); intrasubject response variability . To determine what drove this effect, exploratory simple effects analysis of subscales showed that the anodal v. sham tDCS group had higher scores at posttreatment on Inattention (p = 0.03) and Hyperactivity-Impulsivity subscales (p = 0.06), with the latter being lower for active v. sham tDCS at follow-up (p = 0.07) . Simple effects analysis showed significantly higher scores following anodal v. sham tDCS at posttreatment only  (There was only a significant time by group interaction for Conners 3-P ADHD Index (o 2.41)] .v. posttreatment or follow-up) across groups. In cognitive measures, both groups improved in GNG, Simon, Letter Fluency tasks (baseline v. posttreatment or follow-up); Speed of Processing (baseline v. posttreatment only); and CPT % Omissions and Commissions, Mackworth Clock % Omissions, WM, Response Variability, and Prematurity (baseline v. follow-up only) (online Supplementary Table S9). In clinical measures, both groups improved in ADHD-RS and Conners 3-P Index (baseline v. posttreatment or follow-up); and in ARI Parent and Child, WREMB-R, and CIS (baseline v. posttreatment only).Separate repeated-measures ANOVAs showed an effect of time .We also explored if outcome changes that showed a significant time effect across both groups from baseline to posttreatment or follow-up were correlated with changes in CT performance scores (week 3 minus week 1). No correlations were significant (online Supplementary Table S11).β = 0.2, s.e. = 0.12, t(46) = 1.7, p = 0.096], the simple effects showed a significantly reduced improvement for anodal tDCS v. sham in older participants , and an opposite but not significant pattern in younger children , indicating that older participants benefitted clinically less from anodal v. sham tDCS.Given that age was not matched between groups, we conducted a post-hoc moderation analysis Hayes, , predictv. sham tDCS at posttreatment , driven mainly by higher parent-ratings for ‘he seems more grumpy and irritable’, ‘has little appetite’ and ‘has more problems falling asleep’ (2(1) = 3.9, p = 0.28], participants  and borderline for parent guesses for anodal tDCS , thus blinding was overall successful.There were no significant group differences in ratings of mood, wakefulness, overall impression of tDCS and CT (online Supplementary Tables S12 and S13), and side effects . Adverse asleep’ . StimulaThis double-blind, sham-controlled RCT administered 15 sessions of anodal or sham tDCS over rIFC combined with CT in 50 boys with ADHD, and found no improvement in ADHD symptoms or cognitive performance. Although both groups improved in clinical and cognitive measures over time, anodal relative to sham tDCS was associated with higher primary (ADHD-RS) and secondary (Conners 3-P ADHD Index) clinical outcome measures. Side effects did not differ, but at posttreatment, adverse effects relating to mood, sleep and appetite were higher following anodal than sham tDCS.The lack of an observable clinical or cognitive effect extend previous meta-analytic evidence of no significant cognitive effects and limited evidence of clinical effects in ADHD with 1–5 anodal tDCS sessions over predominantly left dlPFC . Another limitation is that we could not test for weekly dose effects as ADHD symptoms were only measured at baseline, posttreatment and follow-up; yet weekly changes in CT performance did not show dose effects.Findings are not encouraging for the efficacy of multi-session tDCS of rIFC combined with CT in ADHD. However, there are limitations. Although our sample of 50 participants is the largest sample of any tDCS study in paediatric ADHD, recent meta-analyses report relatively small cognitive effects of tDCS in ADHD  measuring clinical, cognitive and possible non-targeted cognitive outcomes. Stimulating T4-Fz and F8-Cz intersection and F6 could potentially be more effective for improving inhibitory control and attention functions in ADHD.This rigorously conducted double-blind, randomised, sham-controlled trial of 15-weekday sessions of anodal tDCS over rIFC combined with CT in 50 boys with ADHD showed no clinical or cognitive improvement. Findings suggest that rIFC stimulation may not be indicated as a neurotherapy for cognitive or clinical remediation for ADHD.


Chaotic home environments may contribute to children's attention‐deficit hyperactivity disorder (ADHD) symptoms. However, ADHD genetic risk may also influence household chaos. This study investigated whether children in chaotic households had more ADHD symptoms, if mothers and children with higher ADHD genetic risk lived in more chaotic households, and the joint association of genetic risk and household chaos on the longitudinal course of ADHD symptoms across childhood.n = 880) and twins ; of these, n = 871 mothers and n = 1,925 children had information on children's ADHD and household chaos.Participants were mothers and children from the Environmental Risk (E‐Risk) Longitudinal Twin Study, a UK population‐representative birth cohort of 2,232 twins. Children's ADHD symptoms were assessed at ages 5, 7, 10 and 12 years. Household chaos was rated by research workers at ages 7, 10 and 12, and by mother's and twin's self‐report at age 12. Genome‐wide ADHD polygenic risk scores (PRS) were calculated for mothers (Children in more chaotic households had higher ADHD symptoms. Mothers and children with higher ADHD PRS lived in more chaotic households. Children's ADHD PRS was associated with household chaos over and above mother's PRS, suggesting evocative gene–environment correlation. Children in more chaotic households had higher baseline ADHD symptoms and a slower rate of decline in symptoms. However, sensitivity analyses estimated that gene–environment correlation accounted for a large proportion of the association of household chaos on ADHD symptoms.Children's ADHD genetic risk was independently associated with higher levels of household chaos, emphasising the active role of children in shaping their home environment. Our findings suggest that household chaos partly reflects children's genetic risk for ADHD, calling into question whether household chaos directly influences children's core ADHD symptoms. Our findings highlight the importance of considering parent and child genetic risk in relation to apparent environmental exposures. Children who grow up in chaotic households, characterised by lack of routine, excessive noise and instability, are more likely to experience adverse outcomes, including behaviour problems , these correlations can be examined in studies that include participant's genetic information. For example, recent research on gestational exposures found that mothers with higher ADHD PRS had more prenatal infections and acetaminophen use  Longitudinal Twin Study, a birth cohort of 2,232 British children drawn from a larger birth register of twins born in England and Wales in 1994–95 , 10 years (96%) and 12 years (96%). Home visits at ages 5–12 years included assessments with participants and their mother and were completed by trained research workers. Research workers had degrees in psychology, nursing or related disciplines, and received 1 month of intensive training as well as ongoing supervision by clinical researchers affiliated with the study. The Joint South London and Maudsley and the Institute of Psychiatry Research Ethics Committee approved each phase of the study. Parents gave written informed consent and twins gave assent between 5 and 12 years. At follow‐up, the study sample represents the full range of socioeconomic conditions in Great Britain, as reflected in the families' distribution on a neighbourhood‐level socioeconomic index .To create the combined age‐12 household chaos score, we standardised then averaged reports from research worker's impressions based on their observations during home visits with mothers, research worker's impressions based on their observations during home visits with twins, mother's self‐report and twin's self‐report. To create the total combined household chaos score, we averaged standardised chaos scales from ages 7, 10 and the combined age‐12 scale. Participants had to have information on household chaos from at least two ages to be included in the combined chaos score. The distribution of scores on the scales by age and rater is shown in Figure 48 Table . Correla56 Table . The staWe ascertained childhood ADHD symptoms on the basis of mother‐ and teacher reports of 18 symptoms (9 symptoms of inattention and 9 symptoms of hyperactivity/impulsivity) derived from DSM‐IV diagnostic criteria .We used Illumina Omni Express 24 BeadChip arrays  to assay common single‐nucleotide polymorphism (SNP) variation in the genomes of cohort members and their mothers. We imputed additional SNPs using IMPUTE2 software . We then performed clumping by retaining the SNP with the smallest p‐value from each LD block (excluding SNPs with r2 > .1 in 500‐kb windows) and then weighted SNPs by effect estimate. To control for possible population stratification, we conducted a principal components analysis using PLINK v1.9 . Figure Higher levels of household chaos were associated with children's ADHD symptoms at ages 7, 10 and 12, with a standard deviation increase in household chaos associated with about one additional symptom  and 10 . Mother's ADHD PRS was not associated with their own  or their children's  ratings of household chaos when children were age 12. Further adjusting for child's ADHD PRS . This suggests that, overall, there is no effect of mother's ADHD PRS on household chaos over and above child's PRS. One exception is age 10, when mothers with higher ADHD PRS were rated by research workers as having more chaotic households, adjusting for child's PRS .We found evidence of gene–environment correlation, with mother's ADHD PRS significantly associated with total combined household chaos , 10  and 12 . When children were 12, mothers of children with higher ADHD PRS also rated their households as more chaotic  and children with higher ADHD PRS rated their own homes as more chaotic . Adjusting for mother's ADHD PRS  providing evidence of evocative gene–environment correlation, that is children with higher ADHD genetic risk contribute to household chaos. Associations remained significant for research worker‐rated chaos at age 7, but not at ages 10 or 12. Mothers of children with higher ADHD PRS also rated their households as more chaotic when children were age 12, even accounting for mother's own PRS .Children with higher ADHD PRS had higher total combined household chaos . Mother's ADHD PRS was not associated with children's symptoms over and above the child's own PRS . This suggests a lack of genetic nurture; instead, mother's ADHD PRS is associated with children's ADHD symptoms via genes transmitted to their offspring rather than via the environments mothers create. While overall ADHD symptoms declined from age 5 to age 12, neither mother's nor child's ADHD PRS was associated with rate of change in ADHD symptoms .Longitudinal models of ADHD symptoms examining the role of ADHD PRS found that children with higher PRS had more symptoms across childhood, even after accounting for mother's PRS (Table p < .001), as well as slower rate of decline in symptoms  . Child's ADHD PRS also remained significantly associated with ADHD symptom level adjusting for household chaos . Results were similar examining hyperactivity/impulsivity and inattention symptoms separately; however, there was no association with ADHD PRS and inattention symptoms.Children living in more chaotic households had higher ADHD symptoms , but remained significant, suggesting that household chaos is an environmental risk factor for childhood ADHD. However, because PRS are known to underestimate the full extent of genetic influences, we then adjusted for a magnitude of gene–environment confounding reflecting more realistic levels of genetic influence. When adjusting for the SNP heritability of general population ADHD symptoms . Adjusting for SNP heritability estimated from case–control studies .We tested genetic confounding of associations between household chaos and childhood ADHD symptoms, accounting for different strengths of gene–environment confounding Figure . We firsWe found that children living in more chaotic households had higher ADHD symptoms across childhood. We also identified a significant contribution of child's ADHD genetic risk to levels of household chaos – over and above mother's ADHD genetic risk – suggesting evocative gene–environment correlation, such that children's genetic risk contributes to shaping their environments. Thus children with higher ADHD genetic risk are more likely to live in unpredictable, less organised, more chaotic households due at least in part to underlying genetic risk, most strongly from the genetic predisposition of the child. Studies examining environmental risk factors for ADHD that include participant genetic information should take into account the possibility of this kind of gene–environment correlation.Our findings regarding an effect of children's ADHD PRS on household chaos emphasise the active role children play in shaping the family environment. Adoption and twin studies have identified such evocative gene–environment correlations, such as child effects on mother's anxiety  to age 10  and to age 12 . While our goal was not to examine change in household chaos, supplemental analyses . However, there are also several limitations. First, we focus on ADHD genetic risk in mothers and their offspring, but we lack genetic information on fathers. Thus, we cannot directly consider a potentially important part of the household environment or analyse transmitted and untransmitted alleles (Kong et al., es Table  showing A wide range of environmental exposures have been associated with ADHD, from maternal smoking to children's TV viewing (Christakis, Zimmerman, DiGiuseppe, & McCarty, Table S1 Chaos measure items by rater.Table S2. Correlations between household chaos measures at each age by rater.Table S3. Correlations between household chaos measures at each age.Table S4. Association of mother's and child's ADHD PRS with household chaos as rated by study research workers from ages 7 to 12.Figure S1. Distributions of scores on household chaos measures by age and rater, and for total combined household chaos.Figure S2. Mean research worker rated household chaos from age 7 to 12 among those in the top quartile of child ADHD PRS and the bottom quartile of child ADHD PRS.Appendix S1. Methods supplement.Click here for additional data file.


In recent years, physical activity as a potential intervention for attention-deficit hyperactivity disorder (ADHD) became into the focus of researchers, however the results are conflicting.Our aim was to investigate the effect of acute moderate physical activity on executive functions requiring inhibition.The study included 50 treatment-naïve ADHD children, 50 medicated children with ADHD and 50 typically developing children, aged 6–12 years. To diagnose ADHD, we applied the Mini International Neuropsychiatric Interview for Children and Adolescents. To measure executive functions, the pediatric version of the Test of Attentional Performance (KiTAP) was used. Half of the children in each study group participated in a 20-minute, moderately intense exercise while watching a cartoon video. In the control intervention, the other half of the children from all three study groups watched the same cartoon video in a sitting position for 20 min.Regarding distractibility, flexibility and inhibition, physical activity had a significant positive effect on two of 10 parameters  in the treatment-naïve ADHD group.Our results suggest that moderate acute physical activity has some significant positive effects on certain executive function parameters among children with ADHD. Future studies should consider determining the optimal form, intensity, and duration of physical activity to become a potential adjunctive intervention for children diagnosed with ADHD.No significant relationships.


Bartonella spp. are responsible for cat scratch disease, Carrion’s disease, bacillary angiomatosis and trench fever. On the other hand, Bartonella vinsonii is rarely reported in the literature and there exist a few reports of systemic infection caused by Bartonella vinsonii in patients with acquired immunodeficiency syndrome. A 31-year-old male (diagnosed with AIDS six years ago) had persistent fever and ulceration in the right knee. The elevated levels of inflammatory markers suggested an infectious aetiology. Despite the negative findings of blood culture, metagenomic Next-Generation Sequencing of plasma detected Bartonella vinsonii. The polymerase chain reaction of whole blood and Sanger sequencing confirmed the mNGS findings. Immunohistochemical staining had later suggested bacillary angiomatosis, which was consistent with Bartonella infection. Following antibiotic treatment, the ulcers subsided significantly, but a high fever persisted. The patient died due to sudden respiratory failure.Bartonella species are fastidious, aerobic bacteria that are transmitted by blood-sucking arthropods.  Bartonella spp. are fastidious gram-negative bacilli that require an enriched culture medium (which contains haeme) and a high CO2 level for growth [Bartonella henselae is the most reported member of the Bartonella species, which are transmitted to humans through bites and scratches by cats [Bartonella vinsonii are rare and are typically carried by canines [Bartonella vinsonii subsp. berkhoffii infection that led to bacillary angiomatosis in a patient with AIDS, which was detected by mNGS and confirmed by PCR and pathological staining.r growth ,2. They r growth . Bartone by cats ,5. On th canines . Here weTreponema pallidum and was emaciated. The routine laboratory test results can be found in 12/L), platelet (5.0 × 109/L) and CD4+ T cell count (5 cells/µl) were significantly reduced. In addition, inflammatory markers, including CRP (94.25 mg/L) and PCT (4.98 ng/mL), were elevated. On the other hand, T-SPOT.TB, serum -β-D glucan test, galactomannan test and blood culture were all negative. Due to severe anaemia, the patient was given intravenous infusions of red blood cells. Moreover, lamivudine, dotiravir and tenofovir fumarate were administered as anti-HIV treatment. Meropenem was empirically used as a broad-spectrum antibiotic. The plasma samples were sent for mNGS testing (detailed methods can be found in one of our previous publications [Bartonella vinsonii (2352 reads), EBV (1 read) and CMV (1 read) (Bartonella vinsonii (3 reads) and EBV (1 read). Both mNGS tests returned results in less than 24 h (sequencing files were deposited into the NCBI SRA database and can be retrieved at https://www.ncbi.nlm.nih.gov/sra with accession number PRJNA821973). The subspecies of Bartonella vinsonii was berkhoffii as we detected 69 and 2 uniquely mapped reads from plasma and pleural effusion, respectively. To further confirm the microbiological findings, we designed primers that specifically targeted Bartonella vinsonii and performed PCR (forward 5’-GCAGGCATAACGAAGCACAT-3’ and reverse 5’-CCCAGCTGTCCATCATTCCA-3’) using total DNA extracted from 200 μL of whole blood . Peripheral blood collected from a healthy individual was used as a negative control. The PCR amplicons were then sent for Sanger sequencing. As expected, the patient sample, rather than the negative control, showed specific amplification of Bartonella vinsonii  was a farmer and owned a pet dog. Six years ago, the patient was diagnosed with acquired immunodeficiency syndrome (AIDS) and had since been taking HIV medicines irregularly. The CD4+ T cell count of the patient dropped from 500 to 95/mL (from June to December 2021). One month before admission, the patient noticed a red spot on the right knee, which progressed into a lump (ications ) on JanuBartonella vinsonii infection. Therefore, azithromycin, doxycycline and rifampin were used. The mass shrunk significantly, and the rash subsided . Meanwhile, HHV8, CK, and S100 were negative. These results suggested that the lesion was angiogenic and not likely to be a malignant tumour. Notably, Warthin-Starry staining was positive, which pointed to bacillary angiomatosis  and molecular tests. However, these tests are targeted and thus require a priori assumptions. On the other hand, mNGS can unbiasedly sequence all potential pathogens directly from clinical samples [Bartonella can cause a spectrum of clinical symptoms, including fever, hallucinations, weight loss, muscle fatigue, partial paralysis, endocarditis , neurops samples .Bartonella vinsonii subsp. berkhoffii. This finding was plausible as the patient owned a pet dog, which is known to carry and transmit Bartonella vinsonii [Bartonella spp. in AIDS patients was first reported in 1998, which described bacillary angiomatosis that was characterized by neovascular proliferation in the skin due to infections by Bartonella quintana and Bartonella henselae. Moreover, proliferative vascular diseases caused by Bartonella vinsonii subsp. berkhoffii have been reported [et al reported a 44-year-old HIV patient presented with a mass on the lateral side of the neck [Bartonella quintana. Unfortunately, in our case, an autopsy was not performed, and the exact cause of respiratory failure was not established. Although the patient also died in our case, we still wanted to point out the importance of a fast and accurate microbiological result in diagnosing and treating Bartonella infections.In this case, the patient was immunocompromised due to AIDS. An Infectious aetiology was suspected but with no backing from traditional microbiological tests. The tumour was also considered and therefore biopsies were taken for pathological examination. While waiting for the results, plasma mNGS reported vinsonii . The assvinsonii , while treported . In our reported . Owing tthe neck . Due to


The crystal structures of UO2 showed that the U–X bond strength follows U–O ≈ U–NH > U–S. Conditional stability constants (βX) of UO2 in ethanol were investigated to understand the effect of X on thermodynamic stability. The log βX decrease in the order of UO2 (log βNH = 10) > UO2 (log βO = 7.24) > UO2 (log βS = 5.2). This trend cannot be explained only by Pearson's Hard and Soft Acids and Bases (HSAB) principle, but rather follows the order of basicity of X. Theoretical calculations of UO2 suggested that the ionic character of U–X bonds decreases in the order of U–NH > U–O > U–S, while the covalency increases in the order U–O < U–NH < U–S. Redox potentials of all UO2 in DMSO were similar to each other regardless of the difference in X. Spectroelectrochemical measurements and DFT calculations revealed that the center U6+ of each UO2 undergoes one-electron reduction to afford the corresponding uranyl(v) complex. Consequently, the difference in X of UO2 affects the coordination of tBu,MeO–saldien–X2− with UO22+. However, the HSAB principle is not always prominent, but the Lewis basicity and balance between ionic and covalent characters of the U–X interactions are more relevant to determine the bond strengths.Uranyl( vi) complexes with pentadentate N2O2X1-donating ligands  are affected by the difference in X. In contrast, the X atom does not largely affect the redox behavior of the complexes.The U–X bond strength and thermodynamic stability of uranyl( The chemical separation of UO22+ from various aqueous systems such as feed solutions of spent nuclear fuels and even seawater is one of the important research topics in nuclear chemistry. In the usual sense, coordination chemistry provides very powerful tools for chemical separation. Hence, the complexation between UO22+ and organic ligands has been widely studied.1–13Uranium is the most important element in nuclear engineering. The chemistry of uranium plays important roles in nuclear fuel fabrication and spent fuel reprocessing. Under ambient conditions, uranium is most commonly present as a hexavalent uranyl and Cm(iii) from Ln(iii) on the basis of difference in coordinating affinities of these metal ions with soft-donor atoms incorporated in the designed ligands.17–20Pearson's Hard and Soft Acids and Bases (HSAB) principle is quite useful to describe preferential interactions between specific metal ions and coordinating atoms of ligands and to design organic molecules selectively coordinating with a target metal ion,22+ complexes having analogous coordination geometries. For this purpose, it is first necessary to choose a suitable ligand system. Previously, we reported UO22+ complexes with N3O2-pentadentate Schiff base ligands, UO2, shown in 21,22 Its NR moiety can be substituted with O or S to provide the similar UO22+ complexes, UO2 (UO2(LX), X = NH, O, S, 2(LX)  to discuss effects of X to the U–X bond strength and thermodynamic stability as well as redox chemistry of this class of UO22+ complexes.In this study, we discuss strengths of U–N, U–O and U–S interactions formed in UOtert-Butyl-5-methoxysalicylaldehyde was synthesized as reported elsewhere.23All reagents used were of reagent grade and used as received, if not specified. 3-tert-butyl-5-methoxysalicylaldehyde  in ethanol (2 mL) was added 2,2′-diaminodiethylamine . This solution was heated to reflux for 10 min. UO2(NO3)3·6H2O  dissolved in ethanol (2 mL) was dropwise added to the solution. A red precipitate was formed within several minutes, and the suspension was stirred at 60 °C for 1 h. After cooling to room temperature, a red precipitate was collected by filtration and rinsed with methanol. Recrystallization from CH2Cl2/ethanol yielded red crystals. Yield: 176 mg (48%). This compound was characterized by 1H NMR, IR and elemental analysis. 1H NMR : 1.71 3), 3.61  scale" fill="currentColor" stroke="none"><path d="M0 440 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z M0 280 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z"/></g></svg>N–CH2CH2–N or CN–CH2CH2–N), 3.83 , 4.07 , 4.26 , 4.50 , 6.86 , 7.32 , 9.38 . 1H NMR : 1.65 3), 3.40 , 3.75 , 4.02 , 4.49 , 6.51 , 7.04 , 7.14 , 9.57 . IR : 858 , 1636 . Elemental analysis (%) calcd for UO2(LNH) (C28H39N3O6U1): C, 44.74; H, 5.23; N, 5.59. Found: C 44.64; H, 5.29; N, 5.42. The obtained crystals were also suitable for the X-ray crystallography.To a solution of 3-tert-butyl-5-methoxysalicylaldehyde  in ethanol (3 mL) was added 2,2′-oxybis(ethylamine) . This solution was heated to reflux for 10 min. UO2(NO3)3·6H2O  dissolved in ethanol (2 mL) was dropwise added to the solution. A red precipitate was formed within several minutes, and the suspension was stirred at 60 °C for 1 h. After cooling to room temperature, a red precipitate was collected by filtration and rinsed with methanol. Recrystallization from CH2Cl2/ethanol yielded red microcrystals. Yield: 27.1 mg (30%). This compound was characterized by 1H NMR, IR and elemental analysis. 1H NMR : 1.71 3), 3.83 , 4.59 , 4.65 , 6.91 , 7.33 , 9.50 . 1H NMR : 1.64 3), 3.77 , 4.53 , 4.66 , 7.09 , 7.17 , 9.75 . IR : 883 , 1637 . Elemental analysis (%) calcd for UO2(LO) (C28H38N2O7U1): C, 44.68; H, 5.09; N, 3.72. Found: C 44.79; H, 5.21; N, 3.65. The crystals suitable for X-ray diffraction were obtained by recrystallization from pyridine/hexane.To a solution of 3-tert-butyl-5-methoxysalicylaldehyde  in ethanol (3 mL) was added 2,2′-thiobis(ethylamine) . This solution was heated to reflux for 10 min under Ar. UO2(NO3)3·6H2O  dissolved in ethanol (2 mL) was dropwise added to the solution under Ar. A dark red precipitate was formed within several minutes, and the suspension was stirred at 60 °C for 1 h. After cooling to room temperature, a red precipitate was collected by filtration quickly, and rinsed with deoxygenated ethanol. Recrystallization from CH2Cl2/ethanol yielded dark red plate crystals. Yield: 7.8 mg (8%). This compound was characterized by 1H NMR, IR and elemental analysis. 1H NMR : 1.70 3), 3.74 , 3.83 , 3.74 , 5.33 , 6.89 , 7.33 , 9.47 . 1H NMR : 1.64 3), 3.77 , 3.79 , 4.60 , 7.09 , 7.18 , 9.74 . IR : 880 , 1623 . Elemental analysis (%) calcd for UO2(LS)·0.5CH2Cl2 (C28H38N2O6S1U1·0.5CH2Cl2): C, 42.20; H, 4.85; N, 3.45. Found: C 42.24; H, 4.79; N, 3.40. The obtained crystals were also suitable for the X-ray crystallography.To a solution of 3-1H NMR spectra were recorded by using JEOL ECX-400 (1H: 399.78 MHz) NMR spectrometer. The chemical shifts of 1H NMR were referenced to TMS (δ = 0 ppm). The IR measurements were performed by JASCO FT/IR4700 equipped with a diamond ATR attachment. Elemental analyses were carried out by Yanaco MT-6 CHN elemental analyzer. Cyclic voltammetry (CV) measurements of UO2(LX) (1 mM) dissolved in DMSO containing 0.1 M tetra-n-butylammonium perchlorate (TBAP) were performed at 295 K under a dry Ar atmosphere by using BAS ALS660B electrochemical analyzer. A three-electrode system consisted of a Pt disk working electrode , a Pt wire counter electrode, and an Ag0/+ reference electrode (0.1 M TBAP + 1 mM AgNO3/CH3CN). A ferrocene/ferrocenium ion redox couple (Fc0/+) was taken as an external standard redox system. All samples were prepared under an inert Ar atmosphere. Dissolved oxygen gas in each sample solution was expelled by purging Ar gas for at least 10 min prior to starting the CV experiments. UV-vis-NIR spectroelectrochemical measurements in DMSO were performed with a JASCO V-770 spectrophotometer equipped with an optically transparent thin layer electrode (OTTLE) cell at 295 K.24–27 Its optical path length was 1.0 × 10−2 cm, which was calibrated spectrophotometrically.22 The three-electrode system was the same as that in the above electrochemical experiments with a replacement of the working electrode by a Pt gauze (80 mesh). The potential applied on OTTLE was controlled by BAS ALS660B. The absorption spectrum at each potential step was recorded after equilibration of the electrochemical reaction at the applied potential on the working electrode, which completed within 3 min. The sample solution in the OTTLE cell was prepared in a similar manner to that for the CV measurements.The 2(LNH)·(CH2Cl2), UO2(LO)·(C5H5N) and UO2(LS)·(CH2Cl2) were collected by a Rigaku XtaLAB mini II equipped with hybrid pixel array detector and graphite monochromated Mo Kα radiation (λ = 0.71073 Å). Each sample was mounted on a MiTeGen Dual Thickness MicroMounts, and located in the temperature-controlled N2 gas flow. Intensity data were collected by taking oscillation photographs. Reflection data were corrected for both Lorentz and polarization effects. The structures were solved by the direct method and refined anisotropically by the SHELX program suite28 for non-hydrogen atoms by full-matrix least-squares calculations. Each refinement was continued until all shifts were smaller than one-third of the standard deviations of the parameters involved. Hydrogen atoms were located at the calculated positions. All hydrogen atoms were constrained to ideal geometry with C–H = 0.95 Å. The thermal parameters of all hydrogen atoms were related to those of their parent atoms by U(H) = 1.2Ueq(C). All calculations were performed by using the Olex2 crystallographic software program package.29 Crystallographic data of all complexes were summarized in Table S1,2177295 (UO2(LO)·(C5H5N)), 2177296 (UO2(LNH)·(CH2Cl2)), and 2177297 (UO2(LS)·(CH2Cl2)).The X-ray diffraction data of the well-shaped single crystals of UO2LX  were prepared by mixing 3-tert-butyl-5-methoxysalicylaldehyde and the corresponding diamines in ethanol. The formation of H2LX  was checked by 1H NMR spectroscopy  was added as a H+ scavenger after the formation of UO2(LX). The total concentration of UO22+ was stepwise increased up to 0.12 mM (0 ≤ [UO22+]/[LX2−] ≤ 1.2) by adding a feed solution of UO2(NO3)3·6H2O (10 mM) in ethanol. The UV-vis absorption spectrum at each increment step was recorded by JASCO V-770 spectrophotometer. During the whole titration experiment, temperature of the sample solution was kept at 293 K in a thermostat cell holder equipped with the spectrophotometer. The obtained titration series of the UV-vis absorption spectra was analyzed by HypSpec (version 1.1.33)30 to determine conditional stability constants of UO2(LX)  under the presence of 0.4 mM NEt3 in ethanol.Sample solutions of H31 for characterization of UO2(LX) and the one-electron reduced complexes, [UO2(LX)]− . The atomic coordinates of UO2(LX) were taken from those experimentally-determined and were used for structure optimization. Hybrid DFT functional B3LYP32 was employed and solvent was modelled through a conductor-like polarized continuum model (CPCM) for DMSO (dielectric ε = 46.7).33 For uranium, Stuttgart-type small-core effective core potential (ECP) and corresponding basis set has been used.34 The most diffuse basis functions on uranium with the exponent 0.005  were omitted as in previous studies.35–39 The 6-311G(d) basis sets were used for other elements . Vibrational frequency calculations at the same level of theory confirmed that no imaginary frequency was found to be present. Single-point calculations for energetic analysis were performed using the same condition. NBO analysis were carried out by using the NBO 5.0 program.40 The molecular structures of [UO2(LX)]− were taken from those of UO2(LX) determined experimentally and were optimized after addition of a single negative charge and doublet spin degeneracy to assume the one-electron reduction using the same condition. The Mulliken spin-density plots were illustrated by GaussView 6.1.41Density functional theory (DFT) calculations were performed using Gaussian 16 program (Revision B.01)tert-butyl-5-methoxysalicylaldehyde and the corresponding diamine in ethanol, and further reacted with one equivalent of UO2(NO3)2·6H2O to afford UO2(LX). These complexes were yielded as red microcrystalline solids, which were recrystallized from appropriate solvent mixtures to obtain single crystals suitable for X-ray structure determination. The IR peaks of [OUO]2+ asymmetric stretching (ν3) and CN stretching (νNC) of UO2(LX) were observed at around 860–880 and 1630 cm−1, respectively. The elemental analysis for UO2(LX) well-agreed with the expected chemical formulae of them.Each ligand was synthesized through a condensation reaction between a 3-2(LX) were determined by single crystal X-ray diffraction (SCXRD). The resulting molecular structures of UO2(LX) are shown in 22+ in UO2(LX) is five-coordinated in its equatorial plane to give a pentagonal bipyramidal coordination geometry as expected in 22+ complexes.21,22The molecular structures of UOOax bond lengths of UO22+ in UO2(LX) (U(1)–O(1), U(1)–O(2)) are 1.78–1.79 Å, which is similar to those in UO22+ complexes reported previously.21,22 Herein, we introduced tert-butyl groups at the ortho-positions of the phenolate moieties in each system to control the structure of the ligand after coordination to UO22+. To avoid steric collision between these bulky groups in UO2(LX), two phenolate moieties are forced to be present in the opposite sides of the equatorial plane of UO22+  is 111°, which is close to the ideal value (109.5°) of the tetrahedral coordination around N, showing its sp3 character. Note that the N–H moiety in UO2(LNH) forms a hydrogen bond with the axial O of UO22+ of the neighboring complexes . Nevertheless, there seems to be little effect on the structure of this UO22+ complex, because the similar bond angles around N was also observed in UO2  and UO2(LS) are 120° and 98°. Moreover, the deviation of X from the mean planes defined by U1, N1, N2, O3, and O4 in UO2(LS) (0.489 Å) is larger than those of UO2(LNH) (0.261 Å) and UO2(LO) (0.116 Å). Such a difference would be related to the bonding nature and steric factor of these X atoms. However, it is difficult at this moment to clearly describe in detail how the hardness/softness of X affects such a structural trend. Hence, we decided to focus on the bond lengths around X as another structural parameter directly affected by the coordination strength.The bond angles around X are strongly affected by the difference in X. The mean bond angle of C(9)–N(3)–C(10), C(9)–N(3)–U(1) and C(10)–N(3)–U(1) in UO2(LX) complexes studied here, the bond lengths between U and the phenolic O (U(1)–O(3), U(1)–O(4)) are 2.23–2.24 Å regardless of difference in X. This is also the case for those between U and the imino N (U(1)–N(1), U(1)–N(2), 2.52–2.55 Å). In contrast, the U(1)–X bond lengths depend on X. The U(1)–N(3) distance of UO2(LNH) is 2.594(5) Å, which is slightly longer than the corresponding interaction in UO2(LO) (U(1)–O(5) = 2.581(3) Å). These bond lengths are commonly found in the previous reports.21,22 The U(1)–S(1) distance in UO2(LS) is significantly longer than the others. However, the U(1)–S(1) distance of UO2(LS) is still shorter than the sum of van der Waals radii of U and S (2.3 Å + 1.8 Å = 4.1 Å),42 suggesting that chemical bonding interaction is certainly present between U(1) and S(1) in this complex. Indeed, the U(1)–S(1) distance of UO2(LS) (2.981(2) Å) is close to the U–S bond lengths in UO22+–thioether complexes reported previously (2.96–3.02 Å).2,43,44 The observed structural parameters of the U–X interactions in UO2(Lx) are quite common in uranyl complexes having X atom coordination reported so far.2,21,22,43,44 Therefore, UO2(LX) studied here are suitable for exploring impacts of X in the coordination chemistry of UO22+.In the UORUX) derived from the sum of van der Waals radii and an actual bond length between U and X as shown in 45–47rU and rX, are van der Waals radii of U and X, respectively. dUX is the U–X bond length of UO2(LX) determined by SCXRD.45–47 Based on this definition, greater RUX implies weaker U–X bond (vice versa). As a result, RUX of UO2(LNH) is 0.665, which is close to that of UO2(LO) (0.670). This implies that the bond strengths of U(1)–N(3) in UO2(LNH) and U(1)–O(5) in UO2(LO) are similar to each other. In contrast, RUX of UO2(LS) is 0.727, which is significantly greater than those of UO2(LNH) and UO2(LO). Hence, the U(1)–S(1) bond strength of UO2(LS) is supposed to be weaker than the U–X ones in UO2(LNH) and UO2(LO). Consequently, the bond strength of U–X interactions follows U–O ≈ U–NH > U–S. As widely accepted in the HSAB principle, the hardness of X moiety follows O > NH > S.14,15 Therefore, the trend of U–X bond strengths of UO2(LX) cannot be explained only by the HSAB principle, while the bond strength of U(1)–S(1) of UO2(LS) is certainly weaker than others. Note that all RUX of UO2(LX) presented here are much smaller than those of noncovalent intermolecular interactions such as Cl⋯X and hydrogen bonds reported previously, where R = 0.98–0.80.45–47 Therefore, a coordination bond is certainly formed between U and X in each UO2(LX).It could be misleading to discuss the strengths of the U–X bonding interactions solely on the basis of the observed bond lengths, because the sizes of N, O and S are different from each other. The bond strengths between two atoms can be normalized by reduction in an interaction distance (2(LX) , the U–X bond strength depends on the difference in X. Therefore, there would also be some impact on the thermodynamic stability of UO2(LX). To confirm this issue, we investigated the complexation of UO22+ and LX2− in ethanol by spectrophotometric titration. 22+ and LX2− represented by CU/CL. Note that these titration experiments were conducted under the presence of 0.4 mM NEt3 employed as a H+ scavenger after the formation of UO2(LX).In the crystal structures of UOCU/CL. Simultaneously, the absorption intensity at 350 nm decreased. The isosbestic points were clearly observed, indicating that the complexation equilibrium between UO22+ and LX2− only takes place in each system. As shown in the insets of CU/CL = 1.0, indicating that UO2(LNH) and UO2(LO) are almost quantitatively formed. On the other hand, such a trend is equivocal for X = S ]/([UO22+][LX2−])) of UO2(LX)  in ethanol containing NEt3 (0.4 mM), the spectral series of 30 As a result, log βX of UO2(LX) for X = NH, O, and S are estimated to be 10 ± 1, 7.24 ± 0.02, and 5.2 ± 0.1, respectively. Since all the coordinating atoms except for X are common in the studied systems, the difference in log βX observed here can be ascribed to the difference in affinity of X with UO22+. As widely-accepted in the HSAB principle, the hardness of X atoms follows O > NH > S.14,15 However, log βX of UO2(LX) decrease in the order of UO2(LNH) > UO2(LO) > UO2(LS), which is difficult to be rationalized only by the HSAB principle. To understand this trend, we focus on difference in basicity of X in LX2−. The pKa values of protonated diethylamine ((CH3CH2)2NH2+), dimethyl ether ((CH3)2OH+), and dimethyl thioether ((CH3)2SH+) are 11.0 (ref. βX of UO2(LX) described above. Therefore, the basicity of X atom would also provide some contribution to the thermodynamic stability of UO2(LX). At this moment, it is still too early to verify linear free energy relationship between log βX and pKa.To estimate the conditional stability constants , we carried out DFT calculations of UO2(LX), followed by the natural bond orbital (NBO) analysis. The molecular structures of UO2(LX) were taken from those of UO2(LX) determined by X-ray crystallography, and were optimized with B3LYP method.32 The optimized structures of UO2(LX) are shown in Fig. S4,17,18,40 of center U and coordinating atoms in the optimized structures.To further elucidate the nature of U–X bonds in UO2(LNH) (−0.646) and O(5) in UO2(LO) (−0.565) have negative natural charges, indicating that the center U and X atoms interact electrostatically. In contrast, the natural charge of S(1) in UO2(LS) is positive (+0.326), implying that the electrostatic attraction between U and S is little expectable despite significant penetration between these atoms in UO2(LS) within the sum of van der Waals radii as described above. To provide a rationale for the U–S bonding interaction experimentally observed, bond orders of U–X interactions were estimated in terms of WBI. As a result, some covalency was detected in the U–S bond of UO2(LS) as pronounced by WBI = 0.471, which is significantly larger than those of the other U–X bonds (WBI = 0.277–0.345). Therefore, the bonding interaction between U and S of UO2(LS) is rather covalent, while it is somewhat weakened by the electrostatic repulsion between these positively charged atoms. The significant covalency of the U–S interaction compared with the electrostatic characters in U–NH and U–O would be a typical manifestation of the HSAB principle. In connection with this, N is usually considered to be softer than O, while the stability of UO2(LNH) is greater than UO2(LO) despite the hardness of UO22+. The stronger basicity of NH provides an additional effect to strengthen the U–NH bond compared with that of U–O.No significant differences were found in the natural charge on the axial and equatorial coordinating atoms except for X. Both N(3) in UO2(LX). Recently, we have reported that the redox potential of UO2 . To clarify this point, the electrochemical measurements of UO2(LX) in DMSO were carried out. 2(LX), where a couple of cathodic (Epc) and anodic peaks (Epc) has been observed. These redox waves are reproducible even in multiple scanned cyclic voltammograms recorded at the potential sweep rate (ν) of 100 mV s−1, indicating that the reduction product at Epc undergoes no successive reactions, and is fully reoxidized to UO2(LX) at Epa  tends to increase (111–490 mV) with increasing v from 50 mV s−1 to 500 mV s−1  are quasireversible. Even after careful survey of the DFT calculations described later, we, however, could not find any critical rationales for the differences in the electrochemical reversibility of these systems. Anyway, the peak potential separations  were also much greater than the theoretical value of a reversible system (59 mV). Therefore, all the systems studied here are regarded to be electrochemically irreversible. Although we do not have unequivocal explanation for the above points at this moment, solvation structures around these uranyl complexes could be largely modified through the electron transfer. Note that all the redox reactions are chemically reversible as demonstrated by occurrence of the isosbestic points in the spectroelectrochemical experiments shown in Do) of UO2(LNH), UO2(LO), and UO2(LS) in these systems at 295 K were estimated as 1.6 × 10−6, 1.8 × 10−6 and 8.1 × 10−7 cm2 s−1, respectively, where the redox reactions observed in 49 As summarized in Tables S4–S6,E°′ (=(Epc + Epa)/2) of each UO2(LX) is around −1.60 V vs. Fc0/+ with regardless of v, and also seems not to be largely affected by X. The E°′ value of UO2(LNH) well agrees with that of its analogue, UO2, we reported previously (−1.60 V vs. Fc0/+ in DMSO).21,22 Therefore, the coordinating LX2− would not have strong contribution to the redox events of UO2(LX). From these results, we assume that the redox centers of all UO2(LX) are the UO22+ moiety. However, cyclic voltammograms does not provide any detailed information about the reductant of UO2(LX). Hence, we carried out the spectroelectrochemical measurements and theoretical calculations to further understand the redox chemistry of UO2(LX).As mentioned above, X strongly affects the thermodynamic stability of UOsaldien)  is signia Fig. S6. The pean) in the reduction of UO2(LX), the spectroelectrochemical measurements were performed. The UV-vis-NIR spectra of each system were recorded at different potentials (E). 2(LX) around 30 000 and 20 000 cm−1 gradually decreased with decreasing E, while new absorption bands appeared around 25 000 and 15 000 cm−1. Moreover, isosbestic points were clearly observed, indicating that the redox equilibria of UO2(LX) only take place in the current potential ranges. Using the absorbance at 24 630 or 24 876 cm−1, the concentration ratio (CO/CR) between the oxidant (UO2(LX)) and its reductant at each E was calculated. The relationship between CO/CR and E should follow the Nernstian equation, E°′, R, T, and F are the formal potential, the gas constant (8.314 J mol−1 K−1), the absolute temperature, and the Faraday constant (96 485 C mol−1), respectively. The slope and intercept of the linear relationship between E and ln(CO/CR) (insets of n and E°′ of the redox reactions of UO2(LX). The estimated n values of UO2(LX) are close to unity (Table S72(LX) affords [UO2(LX)]−. The E°′ values estimated from the spectroelectrochemical measurements  and [UO2(LX)]− in DMSO were summarized in 2(LX) are quite similar to each other. All UO2(LX) showed characteristic bands around 28 000 and 24 000 cm−1. These absorption bands were also observed in UO22+ complexes with Schiff base ligands, and can be assigned to the π–π* transition bands of Schiff base ligands.21,22 Therefore, the difference in X leads to no significant differences in the electronic structures of UO2(LX).UV-vis-NIR spectra of UO2(LX)]− with different X commonly have the intense bands at around 25 000 cm−1 with ε ∼ 104 M−1 cm−1 and weak bands at 16 400, 14 500, 12 200 and 7200 cm−1 with ε ∼ 102 M−1 cm−1 (2(LNH)]− has a characteristic band at 5200 cm−1, although this absorption is not clearly observed in [UO2(LO)]− and [UO2(LS)]− .21,22 In accordance with TD-DFT calculation,21,22 the absorption band at 16 400 cm−1 is attributable to a metal-to-ligand charge transfer (MLCT) from a 5fδu orbital of the U5+ center to the π* orbital of the coordinating ligand. Finally, those at 14 500, 12 200 and 7200 cm−1 are ascribed to the f–f transitions arising from the 5f1 electron configuration of U5+.21,22,35 [UO2(LNH)]− only exhibited the absorption band at 5200 cm−1 attributable to another f–f transition,21,22,35 while this is not the case for the others studied here. As a matter of fact, this transition is not always clearly observable as we reported previously.22 To theoretically support occurrence of UVO2+ in each [UO2(LX)]−, we further performed DFT calculations of [UO2(LX)]−.Even after the reduction, [UOM−1 cm−1 . Note thO2(LS)]− . The abs2(LX)]− in DMSO were taken from those of UO2(LX) determined by the X-ray crystal structure and were optimized after addition of a single negative charge and doublet spin degeneracy to assume the one-electron reduction. The optimized structures of [UO2(LX)]− were shown in Fig. S10†Initially, the molecular structures of [UOOax bond lengths of [UO2(LX)]− are 1.86 Å, which are ca. 0.08 Å longer than those of the corresponding UO2(LX) determined by SCXRD (Oax bond lengths are very similar to those of the UVO2+ complexes with bis(phenolate) ligands (1.851(7)–1.868(8) Å).50 The U–O bond lengths between U atom and phenolic O of [UO2(LX)]− are ca. 0.15 Å longer than those of the corresponding UO2(LX) ]− is exclusively localized in the center U as shown in the Mulliken spin density surfaces ]−/0.The Uby SCXRD . These U UO2(LX) . These Usurfaces , clearly2 (UO2(LX); X = NH, O, S) were synthesized and structurally characterized to discuss impacts of the heteroatoms (X) to the coordination chemistry of UO22+. The crystal structures of UO2(LX) showed the five-coordinated UO22+ with LX2− in the equatorial plane. The UOax bond length of UO22+ and the bond length between U and phenolic O are not affected by the difference in X. On the other hand, the U–X bond length increases in the order of UO2(LO) < UO2(LNH) < UO2(LS). After taking into account the differences in the atomic size of X, the normalized U–X bond strength in UO2(LX) was found to follow U–O ≈ U–NH > U–S. While the U–O and U–NH bond strengths are similar to each other, the weaker U–S interaction can be explained by the HSAB principle. The logarithmic conditional stability constant (log βX) of UO2(LX) in ethanol containing 0.4 mM NEt3 decreases in the order of UO2(LNH) (log βNH = 10) > UO2(LO) (log βO = 7.24) > UO2(LS) (log βS = 5.2). This trend cannot be explained only by the HSAB principle, but rather follows the order of basicity of X. The theoretical calculations of UO2(LX) suggested that the ionic character of U–X bonds decreases in the order of U–NH > U–O > U–S. In contrast, the covalency increases as U–O < U–NH < U–S. No significant differences were found in the electrochemistry of UO2(LX) with different X in terms of E°′ and U-centered redox reaction. As demonstrated in this work, a UO22+-ligand bond strength does not always follow the HSAB principle, but is also affected by other factors such as Lewis basicity and balance between ionic and covalent interactions of donating atoms to the center metal. These points should be more carefully considered to design molecular structures of ligands suitable for hydrometallurgical separations of metal ions of interest.In this study, UOT. T. devised the main conceptual ideas, carried out all experiments, and wrote the manuscript in consultation with K. T. K. T. supervised this project, discussed all experimental results with T. T., and edited the manuscript. All authors have given approval to the final version of the manuscript.There are no conflicts to declare.RA-012-D2RA04639C-s001RA-012-D2RA04639C-s002


Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in childhood, which may be related to adverse childhood experiences (ACEs). Our study aims to explore the association between ACEs and subsequent ADHD, and analyze the potential moderators.Literature search was conducted by a combined computer‐assisted and manual method. Studies were included if they had reported the association between ACEs and subsequent ADHD. Overall estimates of odds ratios (ORs) were obtained using random‐effects meta‐analyses, meta‐regressions and further stratified analyses were conducted to examine potential moderator variables.Totals of 70 studies involving nearly 4 million participants from among 6,452 unique articles were included. In the primary analyses, ACEs were found to be associated with subsequent ADHD , and the negative effects of different forms of ACEs for ADHD were nonequivalent. Such as lived in the stepfamily, been adopted or fostered, and experienced sexual abuse were more deleterious than others. It was found that individuals who had experienced multiple ACEs or who are female were more vulnerable to ADHD.The findings provide critical evidence for understanding the association between ACEs and ADHD. ACEs could increase the susceptibility of ADHD, especially for individuals who ever experienced multiple ACEs and females. Moreover, the reference lists of potentially eligible articles and systematic review papers were hand‐searched. Medical subject headings and free text terms of ACEs, ADHD, and study design of interest were used. Searches were updated in June 2021, and example of search strategy in Ovid Medline was available in Appendix 2.3Original studies were included if they were cohort studies, case‐control studies, or cross‐sectional studies that were published in English and reported: (1) Dichotomous or continuous measurement of any form of ACEs. (2) Diagnosis of subsequent ADHD or ADD according to any standardized criteria, such as DSM‐III, DSM‐III‐R, DSM‐IV, DSM‐IV‐TR, DSM‐5, or ICD‐10; or diagnostic information for ADHD could be obtained from reliable records, like vaccine‐related records, clinic registers, hospital records, and the like; or self‐report and informed guardian‐reported diagnosis for ADHD made by a professional. (3) At least the effect estimates with 95% confidence intervals (95% CIs) or standard error (SE) were reported, including odds ratio (OR), relative risk (RR), or hazard ratio (HR). (4) A non‐ADHD control group or a nonexposed control group was set up in the original study.The following types of studies were excluded: (1) reported ADHD‐related symptoms, rather than any ADHD diagnosis; (2) studies in which did not specifically report any risk estimates for the outcome of our interest; (3) duplicate reporting on findings from the same population; (4) studies that did not provide detailed information, and the author did not give us feedback or could not provide detailed information to us. It is important to note that we also excluded these studies in which the diagnosis was only based on medication records. Since these studies may contribute to underestimating the diagnosis of ADHD or ADD as only about 60% of ADHD patients are treated with pharmacotherapy . A third researcher (Man Gao) checked the included literature.A validated Excel table in prestudy was used to extract relevant data from eligible studies by two trained researchers . For all studies, we extracted information on the name of the first author, year of publication, effect sizes, and moderator codes, all of which were checked by Weiguang Wang. Disagreements were solved by the reviewers’ consensus (with Xing Liao and Junhong Wang).As recommended by Cochrane Handbook of Systematic Reviews, the Newcastle‐Ottawa Quality Assessment Scale (NOS) was used for quality assessment of eligible cohort studies and case‐control studies, and an adapted version for cross‐sectional studies  and methodological factors  across eligible studies moderated the association between ACEs and subsequent ADHD. When high heterogeneous was observed and the number of included studies was not less than 10, targeted stratified analysis was performed if a moderator mediated the association. The funnel plot was used to evaluate the possible publication bias, and further with the Begg's tests as recommended , and HRs were similar to RRs , and high heterogeneity was observed (Q (69) = 1173.34, I2 = 94.1%, p < .05).Figure 4.2As shown in Appendices Specifically speaking, medium‐size association (1.50 ≤ OR < 3.00) were detected between exposure to physical abuse, sexual abuse, emotional abuse, childhood neglect, economic adversity, stepfamily/adoption/foster placement, familial criminality/incarceration, household substance abuse, household mental illness, family discord, bullying, or other violence and ADHD. Low‐size association (1.00 < OR < 1.50) between other forms of ACEs and ADHD, such as single parent/parental separation/divorce, familial death, domestic violence, discrimination, and accident/injury/illness trauma.4.3z = 5.011, p < .05), 1.99 , and 2.87, correspondingly.We pooled the results of studies that investigated the association between the number of ACEs exposed and ADHD, and the results were presented in Figure 4.4The influences of ACEs on the core symptoms and the type of ADHD was also analyzed to further reveal the association between ACEs and ADHD. The results of meta‐analysis showed that ACEs are associated with higher scores of ADHD symptom (the pooled effect sizes ranged from 0.20 to 5.96) and increased vulnerability to different subtypes of ADHD (the pooled ORs ranged from 1.44 to 2.12). The detailed results of meta‐analysis could be found in Appendices 4.5Significant heterogeneity was observed in meta‐analyses, except for the meta‐analyses for the association between sexual abuse, familial death, discrimination, or accident/injury/illness trauma, and ADHD. The Knapp–Hartung random‐effect meta‐regressions for moderators that mentioned above were conducted to explain variation in effect sizes, and the results were presented in Appendices 4.6p < .05).Substantial asymmetry was observed in the visual inspection of the funnel plots, and the evidence of substantial publication bias was identified by Begg's test in meta‐analysis for the association between all forms of common ACEs and ADHD. As shown in Figure 4.7Leave‐one‐out method sensitivity analyses revealed that no single study could independently significantly influence the pooled OR value of the association between all 17 forms of ACEs and the diagnosis of ADHD. However, González et al. , Ouyang Trim and fill method sensitivity analysis showed that no statistically significant changes in the results of meta‐analysis for all 17 forms of ACEs in relation to any ADHD diagnosis after filled the 35 possible missing studies, and the details of trim and fill method sensitivity analysis were presented in Figure 5To our knowledge, this is the first systematic review and meta‐analysis that comprehensively examined existing observational studies to assess the association between ACEs and ADHD. Following literature searches, we finally identified 64 published journal articles, including 70 independent studies involving nearly 4 million participants. It was found that individuals who experienced any form of ACEs had a 1.68‐fold increased vulnerability of ADHD, compared to those without a history of ACEs.Although we included observational studies that adjusted for potential confounders, significant heterogeneity was observed, which may pose risk of residual confounding. ADHD was revealed to have a high degree of genetic predisposition with gender difference and prevalence declines with age in the general population. We used the gender composition of the study population, the period for ADHD diagnosis, and the continent in which the studies were conducted as demographic moderators consequently. Despite thoroughly examining the potential mediation to influence the association between ACEs and ADHD, no evidence supported that the location of studies moderated the size of the obtained effects. In contrast, we found that individuals who had suffered ACEs in studies with a proportion of males below inferior quartile (IQ) were more likely to be diagnosed with ADHD, compared to those above IQ which calculated based on detailed data provided by included studies. This phenomenon may be correlated with sex differences in neurodevelopment and sensitivity to ACEs Bath,  and coulAdditionally, we attempted to trace and analyze the heterogeneity through independent meta‐regressions for methodological characteristics, including sample size, indicator of effect estimate, study design and type, measures of ACEs and ADHD, and study quality. Since the eligible studies varied widely in these respects, which may mediate the association between ACEs and ADHD. The findings of meta‐regressions did not support the hypothesis that study quality affects the association between ACEs and ADHD and confirm the mediating roles of these other methodological moderators mentioned above. Sample size may have a positive correlation effect on the association, as poor association between ACEs and ADHD was observed in the subgroup of studies with sample sizes below IQ. This finding reflects the limitations of small sample studies that the bias caused by sampling error and sensitivity of logOR to sample size restricts sharp inferences from small samples to large populations Lin, . The ranWe had examined the effects of 17 different forms of ACEs, since ACEs have a deleterious effect on health outcomes that is nonequivalent and specific, which means each form of childhood adversities has a specific effect on ADHD and some forms of ACEs are more harmful than others , No. 81774366.This study found that individuals exposed to any ACEs were more susceptible to ADHD than nonexposed individuals, and the negative effects of different forms of ACEs were nonequivalent, gender‐specific, and accumulative, which could provide critical evidence for understanding the association between ACEs and ADHD.There are no conflicts of interest arising from this research.APPENDIX 1: SEARCH STRATEGIES IN OVID MEDLINE(R)APPENDIX 2: CHARACTERISTICS OF THE INCLUDED COHORT STUDIESAPPENDIX 3: CHARACTERISTICS OF THE INCLUDED CASE‐CONTROL STUDIESAPPENDIX 4: CHARACTERISTICS OF THE INCLUDED CROSS‐SECTION STUDIESAPPENDIX 5: REFERENCES OF INCLUDED STUDIESAPPENDIX 6: RESULT OF META‐ANALYSIS FOR THE ASSOCIATION BETWEEN ACES AND ADHDAPPENDIX 7: FOREST PLOTS AND FUNNEL PLOTS OF META‐ANALYSIS FOR THE ASSOCIATION BETWEEN 17 FORMS OF COMMON ACES AND ADHDAPPENDIX 8: RESULT OF META‐ANALYSIS FOR THE ASSOCIATION BETWEEN NUMBER OF ACES AND ADHDAPPENDIX 9: META‐ANALYSIS FOR THE ASSOCIATION BETWEEN ACES AND ADHD SYMPTOMSAPPENDIX 10: META‐ANALYSIS FOR THE ASSOCIATION BETWEEN ACES AND TYPE OF ADHDAPPENDIX 11: META‐REGRESSION FOR MODERATOR ANALYSISAPPENDIX 12: STRATIFICATION ANALYSIS FOR POTENTIAL MODERATORSAPPENDIX 13: RESULTS OF TRIM AND FILL METHOD SENSITIVITY ANALYSISClick here for additional data file.


Emerging evidence points at substantial comorbidity between adult attention deficit hyperactivity disorder (ADHD) and cardiometabolic diseases, but our understanding of the comorbidity and how to manage cardiometabolic disease in adults with ADHD is limited. The ADHD Remote Technology study of cardiometabolic risk factors and medication adherence (ART-CARMA) project uses remote measurement technology to obtain real-world data from daily life to assess the extent to which ADHD medication treatment and physical activity, individually and jointly, may influence cardiometabolic risks in adults with ADHD. Our second main aim is to obtain valuable real-world data on adherence to pharmacological treatment and its predictors and correlates during daily life from adults with ADHD.ART-CARMA is a multi-site prospective cohort study within the EU-funded collaboration ‘TIMESPAN’ (Management of chronic cardiometabolic disease and treatment discontinuity in adult ADHD patients) that will recruit 300 adults from adult ADHD waiting lists. The participants will be monitored remotely over a period of 12 months that starts from pre-treatment initiation. Passive monitoring, which involves the participants wearing a wrist-worn device (EmbracePlus) and downloading the RADAR-base Passive App and the Empatica Care App on their smartphone, provides ongoing data collection on a wide range of variables, such as physical activity, sleep, pulse rate (PR) and pulse rate variability (PRV), systolic peaks, electrodermal activity (EDA), oxygen saturation (SpO2), peripheral temperature, smartphone usage including social connectivity, and the environment . By combining data across these variables measured, processes such as physical activity, sleep, autonomic arousal, and indicators of cardiovascular health can be captured. Active remote monitoring involves the participant completing tasks using a smartphone app , measuring their blood pressure and weight, or using a PC/laptop (cognitive tasks). The ART system is built on the RADAR-base mobile-health platform.The long-term goal is to use these data to improve the management of cardiometabolic disease in adults with ADHD, and to improve ADHD medication treatment adherence and the personalisation of treatment. Attention deficit hyperactivity disorder (ADHD) is a common psychiatric disorder, with a prevalence among adults of 2.5% . The disThe prevalence of ADHD medication use for adults has increased markedly during the last two decades –5. RandoPossible reasons for treatment discontinuity in adults with ADHD include lack of treatment response, adverse side effects and poor adherence behaviours (such as forgetting to take the medication). Although sub-optimal response is one of the most common reasons reported for ADHD medication discontinuation, few studies report on adherence and discontinuation results . A systeRemote measurement technology (RMT) offers new opportunities for collecting detailed, frequent, long-term, real-world data on clinical symptoms, functional and cognitive impairments, physiological measures, health behaviours (such as exercise and sleep) and measures of the environment on large sample sizes. The ADHD Remote Technology (‘ART’) assessment and monitoring system for adults with ADHD, developed by Kuntsi, Dobson and colleagues , 31 utilThis protocol describes the ADHD Remote Technology study of cardiometabolic risk factors and medication adherence (‘ART-CARMA’), which uses the ART system. ART-CARMA is a clinical study within the EU-funded collaboration ‘TIMESPAN’ (Management of chronic cardiometabolic disease and treatment discontinuity in adult ADHD patients), which unites a multidisciplinary team of 17 partners from academia, small and medium-sized enterprises (SMEs), patients and care providers. The main objective of TIMESPAN is to advance the management of adult ADHD and co-occurring cardiometabolic disease by improving the identification and treatment of individuals with these comorbidities. The wearable device included in ART-CARMA is the EmbracePlus developed by the SME partner Empatica . ART-CARThe ADHD Remote Technology (ART) system benefits from procedures developed in the RADAR-MDD study protocol ; a RMT sThe first main aim (objectives 1–3 below) is to obtain real-world data from the patient’s daily life on the extent to which ADHD medication treatment and physical activity, individually and jointly, may influence cardiometabolic risks in adults with ADHD. This will provide new insights into disease patterns and help improve the safety and effectiveness of pharmacological  and non-pharmacological  interventions for patients with ADHD and co-occurring cardiometabolic disease. The second main aim (objectives 4–6 below) is to obtain in vivo, real-world data from the patient’s daily life on adherence to pharmacological treatment and its predictors and correlates, over a remote monitoring period of 12 months that starts from pre-treatment initiation. The long-term goal is to use these data to improve the management of cardiometabolic disease in adults with ADHD, and to improve ADHD medication treatment adherence and the personalisation of treatment.Objective 1: Use RMT to identify real-world consequences of ADHD medication treatment on the following cardiometabolic risk (or protective) factors in adults with ADHD: changes in HR, blood pressure, weight, smoking, alcohol use, diet, sleep and physiological stress response.Objective 2: Use RMT to measure the potential contribution of physical activity to a reduction in these risk factors, independently and in combination with ADHD medication treatment.Objective 3: Use machine learning, applied to the full set of multimodal remote monitoring data from the 12-month period, to build prediction models of the cascade of effects that follow from the initiation of ADHD medication treatment. This allows us to go beyond objectives 1 and 2, to obtain insight into potential underlying mechanisms that are needed for developing algorithms for personalised treatment. The prediction models allow us to assess complex, temporal relationships between multiple measures.Objective 4: Use RMT to explore ADHD medication use patterns in adults with ADHD in the first year of starting ADHD medication treatment  and to quantify the extent of treatment adherence, non-adherence and treatment gaps.Objective 5: Use RMT to identify potential reasons for non-adherence, with a focus on adverse side effects , lack of treatment response (limited or no effect on ADHD symptoms and impairments) and poor adherence behaviours (e.g. forgetting to take or difficulties taking ADHD medication). We capture these time series data across the periods of pre-treatment, treatment initiation, titration and subsequent monitoring.Objective 6: Identify psychiatric comorbidities that predict treatment non-adherence or increase adverse effects. We will measure symptoms of autism spectrum disorder, antisocial behaviour, anxiety, depression and substance use.ART-CARMA has six specific objectives:ART-CARMA is a clinical study being undertaken as part of a larger body of work by the Management of chronic cardiometabolic disease and treatment discontinuity in adult ADHD patients (TIMESPAN ) researcART-CARMA is a prospective observational non-randomised, non-interventional study, using wearable technology and smartphone sensors, representing no change to the usual care or treatments of participants due to participation. There is no control comparison group, or randomised group allocation.Power calculations GPower 3.1) for a regression analysis with five predictors indicate that a sample size of 280 has 80% power  to detect a small effect size (f2) of 0.07. Published Monte-Carlo simulations that aimed to determine the necessary sample size to achieve stable estimates for correlations suggest that, in typical scenarios, a sample size of approx. 250 is required for stable estimates . These c for a reParticipants will be recruited over twenty-four months across two data collection sites of ART-CARMA at King’s College London (UK) and Vall d’Hebron Research Institute (Spain). In total, across the two sites, we will recruit 300 adults from adult ADHD clinic waiting lists, which enables an initial off-medication remote monitoring period and subsequent continuous remote monitoring following initiation of ADHD medication treatment. The schedule of events is available in Table Recruitment procedures will vary slightly across the two sites. Adults will be recruited who are on the waiting list and are not yet receiving ADHD medication. In the UK/British Isles, the clinical team will contact the individuals by their preferred method of contact  and will provide them with information about the study. If the patient is interested in taking part, the first baseline assessment with the research team will be scheduled. The participant information sheet and informed consent form will be sent to patients a minimum of 24 h before the baseline assessment. In Spain, individuals will be provided with information about the study on the day of their ADHD assessment. If the patient is interested in taking part, the baseline assessments will be completed on the same day. Written informed consent will be obtained.The baseline assessments will happen either in-person or virtually using Microsoft Teams depending on the site they have been recruited from. In the UK/British Isles, participants will be paid £30 at the point of enrolling in the study, and a further £5 for every completed outcome measure (paid at months 6 and 12). Participants will be paid an additional £30 at the end of the study period (month 12). In Spain, participants will not receive any financial compensation for their participation.The baseline assessments will take approximately four hours to complete. In Spain, the two in-person baseline assessment sessions will be completed in one day. In the UK/British Isles, the virtual baseline assessment sessions will be completed across two days, with approximately a week in between each session. Both the in-person and virtual baseline sessions will consist of (1) the Diagnostic Interview for ADHD in Adults (DIVA ) to confDuring the baseline session, the participants with ADHD will also be asked to identify a partner, a family member or a close friend who could complete informant-report versions of the active monitoring questionnaires on ADHD symptoms and impairment, and irritability, using the Research Electronic Data Capture (REDCap), a web-based platform. The research team will contact the partner, family member or close friend (via email or telephone) and invite him/her to complete the questionnaires every four weeks.The remote monitoring starts immediately following the research baseline assessment and will last for 12 months. The remote monitoring consists of both active and passive components, following procedures established for the wider ART research programme, and is linked to the RADAR-base mobile-health platform . Below iParticipants will be asked to download the RADAR-base Active App that requests the participant to complete questionnaires at specific intervals. Every day participants will be asked to complete a short questionnaire for medication use on whether the participant took their medication that day, with follow-on questions on type and dose of medication or why medication was not taken . Every week participants will be asked to report their medication use side effects using the CADDRA Patient ADHD Medication form . This foParticipants will also self-administer the two cognitive tasks of CPT/GNG and Fast task twice during the 12 months (months 6 and 12) on their home PC or laptop, without the researcher present. In addition, ratings on ADHD symptoms are obtained monthly also from a partner, a family member or a close friend of the individual with ADHD using web-based Redcap.Participants will be asked to download the RADAR-base passive remote monitoring app, configured for ART requirements , which wThe wearable device in ART-CARMA is the Empatica EmbracePlus . ParticiThe Care App collects data from the EmbracePlus and sends it to the Empatica Cloud, where it is stored. The data collected by the EmbracePlus is transferred to the Care App via Bluetooth®. The Care App then transmits the data to the Empatica Cloud via WiFi. To access and use the Care App, the participant has to scan the QR code or type in the participant ID/password provided by the research team. The login credentials generated by the research team via the Care Portal are unique and de-identified.Both the Passive App and the EmbracePlus require compatible smartphones to be used in ART-CARMA. The Passive App requires an Android smartphone and the EmbracePlus requires Bluetooth® 5.0. For participants who do not own a smartphone, we will provide a compatible Android smartphone for them. For participants who are using a non-Android or a non-compatible Android smartphone, we will not recruit them unless they agree to switch to a compatible Android smartphone as their only phone for the duration of the study. We will provide a compatible Android smartphone for them.The outcome measures are (i) the cardiometabolic risk factors  and (ii) daily medication use (adherence), adverse side effects and other reasons for non-adherence.To ensure a system which meets participants and researcher needs, there will be continued monitoring of the ART system throughout the data collection period, including participant adherence to wearable devices and smartphone, and completion of measures. At the study endpoint, we will offer post-participation qualitative interviews to participants. Interviews will be offered to all participants who completed to the study end-point and to those who dropped out during their 12-month study period.Participants will be contacted by telephone after one month of the baseline assessment to address any concerns or questions. Brief follow-up phone-calls will then be offered every three months to maintain engagement with participants throughout the course of the study and to remind participants of any upcoming assessments. Participants will be encouraged to live their lives as normal, responding to the Active App notifications when required. The research team will be able to review incoming data using the RADAR-base management portal and Empatica Research Portal. The research team may contact participants if there is a loss of data from a device. All contact with participants will be recorded as evidence of feasibility and acceptability of outcomes.At the end of the follow-up period, participants will receive a ‘debrief’ session, which will serve to collect end-point acceptability and usability outcomes, and to retrieve study materials . This will be done either over the phone or on Microsoft Teams with a member of the research team and will be audio-recorded using Microsoft Teams. Participants will also have an opportunity to view and discuss their own data.There may be several reasons for withdrawal from the study:Participant choosing to no longer participate: participants will be informed both in writing and verbally that participation is voluntary, that non-participation will not influence their medical care, and that they are free to withdraw from the study at any point without providing reasons.The research team may withdraw the participant in the event of inter-current illness, adverse event (AE), protocol violation, administrative or other reasons.In the case of participant self-withdrawal, all attempts will be made to follow up with the participant to establish cause of withdrawal, and to collect qualitative data regarding experience of participation. All data, including those from withdrawn participants, will be included in the final analysis. If a participant withdraws from the study prematurely, we will consider replacing the participant if resources allow and if recruitment is ongoing for the study.Descriptive statistics for demographics, attrition rate and number of participants using the remote assessment measurements without loss or damage and providing adequate data for the duration of the study period will be estimated. Using a survival model approach  and clusRegression and machine learning approaches will be used to investigate the changes in cardiometabolic factors measured by RMT (listed in Objective 1) following initiation of ADHD treatment. Data obtained from the accelerometer will be used to label days/part of the days with different gradation levels of activity levels and the duration of such activities on a per day basis. For Objective 2, Activity and derived features will be used to statistically test the effect of average activity level on cardiometabolic factors defined in Objective 1 with/without treatment. As well as typical statistical modelling approaches, this analysis will utilise both conventional machine learning methods including support vector machines and random forest in combination with feature selection and fusion approaches, as well as more contemporary deep learning methods (Objective 3).Actigraphy read-outs will also be used to derive sleep characteristics using Empatica’s proprietary, 2-step algorithm that automatically identifies sleep periods and within the determined sleep period classifies epochs as sleep or wake with a 1-minute granularity. Sleep data will be further analysed in relation to Active App data and outcome scales. Utilizing EmbracePlus’ sensor suite, sleep analyses can further be refined by looking at sleep and wake timing, wake bouts, sleep efficiency and fragmentation, activity level(s) over the day during wake (based on 3-axis accelerometers), several features of EDA during wake (gated with motion and temperature) and sleep (including sleep storm patterns). Empatica’s team is also able to post-process EmbracePlus’ sleep or rest data to obtain estimates of respiration and PR, controlling for several factors (movement artefact and compliance) in its processing –59. Raw,Medication use clustering will be analysed for details around behaviour and pattern of use in Objective 4 and extended in Objective 5 to look at specific predictors of use. Time-variant clustering will be used to define subgroups of medication use classes across time, including the probability of transitioning between classes using mixture latent Markov models.Machine learning will be implemented in order to build individualised prediction models for treatment response, symptom classification and stratification, and medication adherence (Objective 6). Based on previous work, different prediction models including Neural Processes model personalization and meta-learning techniques, developed for few-shot learning to individualize models, will be used .We have ensured the highest standards of data security are in place. All electronic data collected will be streamed to Amazon Elastic Kubernetes System (EKS) server where the RADAR-base platform will be deployed for data collection. Amazon EKS servers will be located in London (UK), adhering to General Data Protection Rules (GDPR). Access to RADAR-base stack on Amazon EKS is restricted to system administrators. Data will be placed within the secure network of King’s College and Rivest–Shamir–Adleman (RSA) asymmetric public key encryption will be applied to access. All the data will be stored anonymised and highly restricted access will be given to specific authorised researchers. Industry grade security will be used to secure data access. Authorised access to secure Storage Server using RSA encryption over Secure Shell (SSH-RSA), sFTP access, Access Control Lists (ACLs) and user-groups will be used to control object-level permissions in the storage for each user. EmbracePlus data collected by Empatica will be pseudonymised . Information sheet and consent forms provide details about how participants personal data is handled. Participants will also have the opportunity before giving sign consent to ask the research worker any questions regarding this. All the personal information will be handled according to GDPR and this will be explained in detail to the participants.Empatica Cloud is the cloud infrastructure where the pseudonymised data recorded by the EmbracePlus is collected and made accessible via web interfaces and data repositories. Data is securely stored and encrypted within an Amazon Web Services (AWS) S3 bucket located in the United States (N. Virginia), and then pulled to secure sFTP storage placed in KCL (with the same authorisation and access controls discussed above). Data is encrypted at rest and in transit. Access to this data is granted by a set of unique, secret keys provided by Empatica. The Empatica Portal is GDPR compliant and a Data Processing Agreement has already been established between the research parties and the participant information sheet and consent form includes information about the wearable sensor data.To maintain participant anonymity, their data will be pseudonymised. Their personal information will be stored separately in REDCap from information collected from the apps and wearable. Participant’s name will be replaced with a code, which will be randomly generated and a combination of a human readable ID , project name, and site location, and the information collected from the apps and wearable will only be associated with this code. Information from the wearable and smartphone apps will be encrypted (scrambled) so that only the research team can see it. Transfer of data between different components is secured using industry standards. Data extracted from the platform are also secure and private; only people who have rights can access it. Pseudonymised data will be securely stored on servers managed by the Institute of Psychiatry, Psychology and Neuroscience, KCL, and also on 3rd party servers, which can provide additional security and backup. These data will not be linked back to participants personal information. All details of how data is pseudonymised will be included in the Information Sheets and Informed Consent Forms.Using RMT, ART-CARMA will obtain real-world data on ADHD medication adherence and its predictors, and on the extent to which ADHD medication treatment and physical activity may influence cardiometabolic risks in adults with ADHD. Detailed digital phenotyping has not been captured in previous large real-world studies that have relied on health record databases.ART-CARMA benefits from the recent development of the ADHD Remote Technology (ART) system , 31, theThe long-term aim for ART-CARMA is to improve the management of cardiometabolic disease in adults with ADHD, and to improve ADHD medication treatment adherence and the personalisation of treatment. RMT uniquely has the potential, in the future, to offer the clinician easy and time-saving access to detailed data on symptoms and impairments during the titration process and subsequent long-term monitoring of treatment effects, which could help improve patient outcomes in a cost-effective way. Future personalised treatment could further involve personalised feedback using a clinical app.The project will improve our understanding of the feasibility and acceptability of long-term RMT data collection in adults with ADHD. Feedback from participants and thorough follow-up procedures will help identify challenges for long-term remote monitoring specifically for individuals with ADHD and inform on how to overcome barriers for future implementation of RMT procedures.