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Children
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Updates on Child Neuropsychiatry
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Updates on Child Neuropsychiatry

A special issue of Children (ISSN 2227-9067). This special issue belongs to the section "Child Neurology".

Deadline for manuscript submissions: 10 January 2025 | Viewed by 2431

Special Issue Editors

Prof. Dr. Stefano Pallanti

E-Mail Website1 Website2
Guest Editor
Istituto di Neuroscienze (IN-CNR), Via Lamarmora 24, Florence, Italy
Interests: neurodevelopmental disorders; autism spectrum disorders; attention-deficit/hyperactivity disorder (ADHD); neuroimmunology; Pediatric Autoimmune Neuropsychiatric Disorders Associated with Streptococcal Infections (PANDAS); obsessive-compulsive and related disorders; depressive and bipolar disorders; substance and behavioral addictions; anxiety; schizophrenia; neuromodulation in neurodevelopmental and psychiatric disorders
Special Issues, Collections and Topics in MDPI journals
Dr. Luana Salerno

E-Mail Website
Guest Editor
Istituto di Neuroscienze (IN-CNR), Via Lamarmora 24, Florence, Italy
Interests: neurodevelopmental disorders; autism spectrum disorders; attention-deficit/hyperactivity disorder (ADHD); specific learning disorders; pediatric autoimmune neuropsychiatric disorders; psychiatric disorders; substance and behavioral addictions

Special Issue Information

Dear Colleagues,

Neurodevelopmental disorders (NDDs) comprise a group of complex and heterogeneous disorders that affect the growth and development of the brain and are often associated with impairments in cognitive and motor functions, communication, and adaptive behavior.

Multiple risk factors have been associated with NDDs, including genetic, environmental, infectious, and even traumatic factors, with evidence supporting the possibility of an interaction with each other.

NDDs are a public health challenge not only because of the complexity and heterogeneity of the etiology along with their high prevalence, but also because they show a high comorbidity with other neuropsychiatric conditions. Indeed, the co-existence of other disorders—including obsessive–compulsive and related disorders, attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, and pediatric autoimmune neuropsychiatric disorders associated with streptococcal infections (PANDAS) or pediatric acute-onset neuropsychiatric syndrome (PANS)—and sharing of symptoms across disorders (sometimes referred to as comorbidity) is the rule rather than the exception in child psychiatry. Inadequate knowledge of their clinical presentation can lead to a misdiagnosis and, therefore, an inappropriate treatment approach.

Considering the success and popularity of the Special Issue "Child Neuropsychiatry" previously published in the journal Children (https://www.mdpi.com/journal/children/special_issues/child_neuropsychiatry), we are pleased to now release a Second Issue aiming to gather papers that will provide researchers and clinicians with the most up-to-date information on the etiopathogenesis of these disorders and therapeutic strategies for patients as well as examine both the specificities within these disorders and their common transdiagnostic mechanisms to help to redefine their limits, propose new treatments, identify therapeutic targets, and assess treatment efficacy.

Prof. Dr. Stefano Pallanti
Dr. Luana Salerno
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Children is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • child
  • adolescent
  • neurodevelopmental disorders
  • impulsivity
  • inattention
  • comorbid disorders
  • diagnosis
  • treatment approaches
  • management approaches
  • neuromodulation

Published Papers (2 papers)

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Research

11 pages, 1297 KiB  
Article
Nutritional Assessment of Children and Adolescents with Atypical Anorexia Nervosa: A Preliminary Longitudinal Investigation Using the 24-h Dietary Recall
by Beatrice Valeriani, Jacopo Pruccoli, Francesca Chiavarino, Maria Letizia Petio and Antonia Parmeggiani
Children 2024, 11(4), 427; https://doi.org/10.3390/children11040427 - 03 Apr 2024
Viewed by 491
Abstract
Background: Atypical Anorexia Nervosa (AAN) is a Feeding and Eating Disorder characterized by fear of gaining weight and body image disturbance, in the absence of significantly low body weight. AAN may present specific clinical and psychopathological features. Nonetheless, the literature lacks data concerning [...] Read more.
Background: Atypical Anorexia Nervosa (AAN) is a Feeding and Eating Disorder characterized by fear of gaining weight and body image disturbance, in the absence of significantly low body weight. AAN may present specific clinical and psychopathological features. Nonetheless, the literature lacks data concerning the nutritional characteristics and body composition of children and adolescents with AAN and their variation over time. Methods: Case series, including 17 children and adolescents with AAN. All the patients were assessed at the first evaluation (T0) with a standardized dietary assessment (24 h Dietary Recall, 24 hDR). Nutritional data were compared with European dietary reference values (DRVs). Body composition parameters (weight, fat mass, fat-free mass) and their changes over time at two (T1) and six (T2) months were collected as well, using a Bioelectrical impedance analysis (Wunder WBA300 with four poles and foot contact; impedance frequency 50 kHz 500 μA; impedance measurement range 200~1000 Ω/0.1 Ω). Results: The included individuals presented eating behaviors oriented towards significantly low daily energy intake (p < 0.001) compared with DRVs set by the European Food Safety Authority (EFSA) (with low carbohydrates and fats), and increased proteins (p < 0.001). A longer latency before observation (illness duration before observation) correlated with a negative change in weight. Body composition parameters were described, with no significant changes across the six-month outpatient assessment. Discussion: This is the first research to systematically assess the body composition and nutritional features of a group of individuals with AAN in the developmental age. Further research should assess the effect of targeted treatment interventions on body composition and nutritional features. Full article
(This article belongs to the Special Issue Updates on Child Neuropsychiatry)
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17 pages, 3923 KiB  
Article
Detection of ASD Children through Deep-Learning Application of fMRI
by Min Feng and Juncai Xu
Children 2023, 10(10), 1654; https://doi.org/10.3390/children10101654 - 05 Oct 2023
Cited by 3 | Viewed by 1386
Abstract
Autism spectrum disorder (ASD) necessitates prompt diagnostic scrutiny to enable immediate, targeted interventions. This study unveils an advanced convolutional-neural-network (CNN) algorithm that was meticulously engineered to examine resting-state functional magnetic resonance imaging (fMRI) for early ASD detection in pediatric cohorts. The CNN architecture [...] Read more.
Autism spectrum disorder (ASD) necessitates prompt diagnostic scrutiny to enable immediate, targeted interventions. This study unveils an advanced convolutional-neural-network (CNN) algorithm that was meticulously engineered to examine resting-state functional magnetic resonance imaging (fMRI) for early ASD detection in pediatric cohorts. The CNN architecture amalgamates convolutional, pooling, batch-normalization, dropout, and fully connected layers, optimized for high-dimensional data interpretation. Rigorous preprocessing yielded 22,176 two-dimensional echo planar samples from 126 subjects (56 ASD, 70 controls) who were sourced from the Autism Brain Imaging Data Exchange (ABIDE I) repository. The model, trained on 17,740 samples across 50 epochs, demonstrated unparalleled diagnostic metrics—accuracy of 99.39%, recall of 98.80%, precision of 99.85%, and an F1 score of 99.32%—and thereby eclipsed extant computational methodologies. Feature map analyses substantiated the model’s hierarchical feature extraction capabilities. This research elucidates a deep learning framework for computer-assisted ASD screening via fMRI, with transformative implications for early diagnosis and intervention. Full article
(This article belongs to the Special Issue Updates on Child Neuropsychiatry)
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