ADHD prevalence estimates in Italian children and adolescents: A methodological issue

Abstract Background Attention deficit hyperactivity disorder (ADHD) is recognized as the most common, and most studied, developmental age disorder. Basic information, such as the most appropriate case definition and the best way to evaluate the disorder’s prevalence rate, however, remains an open issue. Methods A comprehensive meta-analysis on the epidemiology of ADHD in Italy, which was lacking from the literature, was therefore performed to attempt to estimate the actual prevalence rate of ADHD, highlighting conceptual and quantitative differences between clinical-diagnosis and survey-based symptoms studies. The Medline, Embase, and PsycINFO databases, and the grey literature, were searched up to January 2018. The review was laid out in three main sections: an overall prevalence estimate, an epidemiological profile of ADHD symptoms, and an attempt to define the actual rate of ADHD diagnosis, as emerged from Italian studies. Results A total of 15 unique studies were included. These contributed to estimating the prevalence of ADHD in 67,838 subjects aged 5–17, representing 9 of the 20 regions (45%) of Italy. Overall, the pooled prevalence of ADHD was 2.9% (range: 1.1–16.7%). When distinguishing studies based on case definition, however, we found an average prevalence estimate, based on symptoms criteria, of 5.9% (range: 1.4 to 16.7%) and a best-estimate prevalence rate of 1.4% (range: 1.1 to 3.1%). Conclusions Following the case definition for epidemiological studies of ADHD, counting only subjects with an ADHD diagnosis performed and confirmed by clinical assessment would reduce the wide variability in prevalence estimates, and, above all, would both describe the real rate of subjects suffering from ADHD disorder and avoid misdiagnosis

Detecting similarities among distant homologous proteins by comparison of domain flexibilities

Aim of this work is to assess the informativeness of protein dynamics in the detection of similarities among distant homologous proteins. To this end, an approach to perform large-scale comparisons of protein domain flexibilities is proposed. CONCOORD is confirmed as a reliable method for fast conformational sampling. The root mean square fluctuation of alpha carbon positions in the essential dynamics subspace is employed as a measure of local flexibility and a synthetic index of similarity is presented. The dynamics of a large collection of protein domains from ASTRAL/SCOP40 is analyzed and the possibility to identify relationships, at both the family and the superfamily levels, on the basis of the dynamical features is discussed. The obtained picture is in agreement with the SCOP classification, and furthermore suggests the presence of a distinguishable familiar trend in the flexibility profiles. The results support the complementarity of the dynamical and the structural information, suggesting that information from dynamics analysis can arise from functional similarities, often partially hidden by a static comparison. On the basis of this first test, flexibility annotation can be expected to help in automatically detecting functional similarities otherwise unrecoverable. © 2007 The Author(s)

Conformational and functional analysis of molecular dynamics trajectories by Self-Organising Maps

<p>Abstract</p> <p>Background</p> <p>Molecular dynamics (MD) simulations are powerful tools to investigate the conformational dynamics of proteins that is often a critical element of their function. Identification of functionally relevant conformations is generally done clustering the large ensemble of structures that are generated. Recently, Self-Organising Maps (SOMs) were reported performing more accurately and providing more consistent results than traditional clustering algorithms in various data mining problems. We present a novel strategy to analyse and compare conformational ensembles of protein domains using a two-level approach that combines SOMs and hierarchical clustering.</p> <p>Results</p> <p>The conformational dynamics of the α-spectrin SH3 protein domain and six single mutants were analysed by MD simulations. The Cα's Cartesian coordinates of conformations sampled in the essential space were used as input data vectors for SOM training, then complete linkage clustering was performed on the SOM prototype vectors. A specific protocol to optimize a SOM for structural ensembles was proposed: the optimal SOM was selected by means of a Taguchi experimental design plan applied to different data sets, and the optimal sampling rate of the MD trajectory was selected. The proposed two-level approach was applied to single trajectories of the SH3 domain independently as well as to groups of them at the same time. The results demonstrated the potential of this approach in the analysis of large ensembles of molecular structures: the possibility of producing a topological mapping of the conformational space in a simple 2D visualisation, as well as of effectively highlighting differences in the conformational dynamics directly related to biological functions.</p> <p>Conclusions</p> <p>The use of a two-level approach combining SOMs and hierarchical clustering for conformational analysis of structural ensembles of proteins was proposed. It can easily be extended to other study cases and to conformational ensembles from other sources.</p

Ginsenosides are novel naturally-occurring aryl hydrocarbon receptor ligands.

The aryl hydrocarbon receptor (AHR) is a ligand-dependent transcription factor that mediates many of the biological and toxicological actions of structurally diverse chemicals. In this study, we examined the ability of a series of ginsenosides extracted from ginseng, a traditional Chinese medicine, to bind to and activate/inhibit the AHR and AHR signal transduction. Utilizing a combination of ligand and DNA binding assays, molecular docking and reporter gene analysis, we demonstrated the ability of selected ginsenosides to directly bind to and activate the guinea pig cytosolic AHR, and to stimulate/inhibit AHR-dependent luciferase gene expression in a recombinant guinea pig cell line. Comparative studies revealed significant species differences in the ability of ginsenosides to stimulate AHR-dependent gene expression in guinea pig, rat, mouse and human cell lines. Not only did selected ginsenosides preferentially activate the AHR from one species and not others, mouse cell line was also significantly less responsive to these chemicals than rat and guinea pig cell lines, but the endogenous gene CYP1A1 could still be inducted in mouse cell line. Overall, the ability of these compounds to stimulate AHR signal transduction demonstrated that these ginsenosides are a new class of naturally occurring AHR agonists

In vitro toxicity and in silico docking analysis of two novel selective AH-receptor modulators

The mediator of dioxin toxicity, aryl hydrocarbon receptor (AHR), has also important physiological functions. Selective AHR modulators (SAHRMs) share some effects of dioxins, except for their marked toxicity. We recently characterised toxicologically two novel SAHRMs, prodrugs IMA-08401 and IMA-07101 in rats, demonstrating that they are far less deleterious than the most toxic AHR-agonist, TCDD. Here, we analysed the in vitro toxicity and in silico AHR binding of the respective active, deacetylated metabolites, IMA-06201 (N-ethyl-N-phenyl-5-chloro-1,2-dihydro-4-hydroxy-1-methyl-2-oxo-quinoline-3-carboxamide) and IMA-06504 (N-(4-trifluoromethylphenyl)-1,2-dihydro-4-hydroxy-5-methoxy-1-methyl-2-oxo-quinoline-3-carboxamide). In H4IIE rat hepatoma cells, IMA-06201 and IMA-06504 induced CYP1A1 with comparable potencies and efficacies to those of TCDD. They had little effect on cell viability as assessed by LDH leakage and MTT reduction assays, and were not mutagenic in the Ames test, but IMA-06504 elicited a maximally 2.7-fold increase in micronuclei. Molecular docking simulations showed that similar to TCDD, they occupy the central region of AHR ligand binding cavity. Hence, while showing low to negligible in vitro toxicity, these novel SAHRMs bind to the AHR qualitatively in a similar fashion to TCDD, and appear comparably powerful AHR agonists. Combined with our earlier results demonstrating that they seem considerably less toxic in vivo than TCDD, these compounds are thus highly interesting new SAHRMs.Peer reviewe

MEK1/2 regulate normal BCR and ABL1 tumor-suppressor functions to dictate ATO response in TKI-resistant Ph+ leukemia

Resistance to tyrosine kinase inhibitors (TKIs) remains a clinical challenge in Ph-positive variants of chronic myeloid leukemia. We provide mechanistic insights into a previously undisclosed MEK1/2/BCR::ABL1/BCR/ABL1-driven signaling loop that may determine the efficacy of arsenic trioxide (ATO) in TKI-resistant leukemic patients. We find that activated MEK1/2 assemble into a pentameric complex with BCR::ABL1, BCR and ABL1 to induce phosphorylation of BCR and BCR::ABL1 at Tyr360 and Tyr177, and ABL1, at Thr735 and Tyr412 residues thus provoking loss of BCR's tumor-suppression functions, enhanced oncogenic activity of BCR::ABL1, cytoplasmic retention of ABL1 and consequently drug resistance. Coherently, pharmacological blockade of MEK1/2 induces dissociation of the pentameric MEK1/2/BCR::ABL1/BCR/ABL1 complex and causes a concurrent BCRY360/Y177, BCR::ABL1Y360/Y177 and cytoplasmic ABL1Y412/T735 dephosphorylation thereby provoking the rescue of the BCR's anti-oncogenic activities, nuclear accumulation of ABL1 with tumor-suppressive functions and consequently, growth inhibition of the leukemic cells and an ATO sensitization via BCR-MYC and ABL1-p73 signaling axes activation. Additionally, the allosteric activation of nuclear ABL1 was consistently found to enhance the anti-leukemic effects of the MEK1/2 inhibitor Mirdametinib, which when combined with ATO, significantly prolonged the survival of mice bearing BCR::ABL1-T315I-induced leukemia. These findings highlight the therapeutic potential of MEK1/2-inhibitors/ATO combination for the treatment of TKI-resistant leukemia

Biomarker, Imaging, and Clinical Factors Associated With Overt and Covert Stroke in Patients With Atrial Fibrillation.

BACKGROUND Atrial fibrillation is a major risk factor for stroke and silent brain infarcts. We studied whether a multimodal approach offers additional insights to the CHA2DS2-VASc score in predicting stroke or new brain infarcts on magnetic resonance imaging (MRI) over a 2-year follow-up. METHODS Swiss-AF is a prospective, multicenter cohort study of patients with known atrial fibrillation. We included patients with available brain MRI both at enrollment and 2 years later. The dates of the baseline and follow-up visits ranged from March 2014 to November 2020. The primary outcome was assessed 2 years after baseline and was defined as a composite of clinically identified stroke or any new brain infarct on the 2-year MRI. We compared a multivariable logistic regression model including prespecified clinical, biomarker, and baseline MRI variables to the CHA2DS2-VASc score. RESULTS We included 1232 patients, 89.8% of them taking oral anticoagulants. The primary outcome occurred in 78 patients (6.3%). The following baseline variables were included in the final multivariate model and were significantly associated with the primary outcome: white matter lesion volume in milliliters (adjusted odds ratio [aOR], 1.91 [95% CI, 1.45-2.56]), NT-proBNP (N-terminal pro-B-type natriuretic peptide; aOR, 1.75 [95% CI, 1.20-2.63]), GDF-15 (growth differentiation factor-15; aOR, 1.68 [95% CI, 1.11-2.53]), serum creatinine (aOR, 1.50 [95% CI, 1.02-2.22]), IL (interleukin)-6 (aOR, 1.37 [95% CI, 1.00-1.86]), and hFABP (heart-type fatty acid-binding protein; aOR, 0.48 [95% CI, 0.31-0.73]). Overall performance and discrimination of the new model was superior to that of the CHA2DS2-VASc score (C statistic, 0.82 [95% CI, 0.77-0.87] versus 0.64 [95% CI, 0.58-0.70]). CONCLUSIONS In patients with atrial fibrillation, a model incorporating white matter lesion volume on baseline MRI and selected blood markers yielded new insights on residual stroke risk despite a high proportion of patients on oral anticoagulants. This may be relevant to develop further preventive measures

Serum S-100B adds incremental value for the prediction of symptomatic intracranial hemorrhage and brain edema after acute ischemic stroke

Background: Early identification of patients developing symptomatic intracranial hemorrhage and symptomatic brain edema after acute ischemic stroke is essential for clinical decision-making. Astroglial protein S-100B is a marker of blood-brain barrier disruption, which plays an important role in the formation of intracranial hemorrhage and brain edema. In this study, we assessed the prognostic value of serum S-100B for the development of these complications. Methods: Serum S-100B levels were measured within 24 h from symptom onset in 1749 consecutive acute ischemic stroke patients from the prospective, observational, multicenter BIOSIGNAL cohort study (mean age 72.0 years, 58.3% male). To determine symptomatic intracranial hemorrhage or symptomatic brain edema, follow-up neuroimaging was performed in all patients receiving reperfusion therapy or experiencing clinical worsening with an NIHSS increase of ⩾4. Results: Forty six patients (2.6%) developed symptomatic intracranial hemorrhage and 90 patients (5.2%) developed symptomatic brain edema. After adjustment for established risk factors, log$_{10}$S-100B levels remained independently associated with both symptomatic intracranial hemorrhage (OR 3.41, 95% CI 1.7–6.9, p = 0.001) and symptomatic brain edema (OR 4.08, 95% CI 2.3–7.1, p < 0.001) in multivariable logistic regression models. Adding S-100B to the clinical prediction model increased the AUC from 0.72 to 0.75 ( p = 0.001) for symptomatic intracranial hemorrhage and from 0.78 to 0.81 ( p < 0.0001) for symptomatic brain edema. Conclusions: Serum S-100B levels measured within 24 h after symptom onset are independently associated with the development of symptomatic intracranial hemorrhage and symptomatic brain edema in acute ischemic stroke patients. Thus, S-100B may be useful for early risk-stratification regarding stroke complications