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  1. Article ; Online: A national pharmacovigilance study of haematological adverse drug reactions to clozapine vs other second-generation antipsychotics in Italy.

    Bertoli, Sara / Casetta, Cecilia / Giordano, Barbara / D'Agostino, Armando

    Schizophrenia research

    2023  Volume 257, Page(s) 25–26

    MeSH term(s) Humans ; Antipsychotic Agents/adverse effects ; Clozapine/adverse effects ; Pharmacovigilance ; Olanzapine ; Drug-Related Side Effects and Adverse Reactions ; Italy
    Chemical Substances Antipsychotic Agents ; Clozapine (J60AR2IKIC) ; Olanzapine (N7U69T4SZR)
    Language English
    Publishing date 2023-05-25
    Publishing country Netherlands
    Document type Letter
    ZDB-ID 639422-x
    ISSN 1573-2509 ; 0920-9964
    ISSN (online) 1573-2509
    ISSN 0920-9964
    DOI 10.1016/j.schres.2023.05.009
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  2. Article ; Online: Reply to 'Delirium, sleep, COVID-19 and melatonin'.

    D'Agostino, Armando / Zambrelli, Elena

    Sleep medicine

    2020  Volume 75, Page(s) 543

    MeSH term(s) Betacoronavirus ; COVID-19 ; Coronavirus Infections ; Delirium ; Humans ; Melatonin ; Pandemics ; Pneumonia, Viral ; SARS-CoV-2
    Chemical Substances Melatonin (JL5DK93RCL)
    Keywords covid19
    Language English
    Publishing date 2020-05-25
    Publishing country Netherlands
    Document type Letter ; Comment
    ZDB-ID 2012041-2
    ISSN 1878-5506 ; 1389-9457
    ISSN (online) 1878-5506
    ISSN 1389-9457
    DOI 10.1016/j.sleep.2020.05.027
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  3. Article ; Online: Impact of a single webinar intervention on attitudes towards mental illness in undergraduate students.

    Ferrara, Paolo / Ruta, Federico / D'Agostino, Armando / Destrebecq, Anne / Terzoni, Stefano

    Acta bio-medica : Atenei Parmensis

    2023  Volume 94, Issue 5, Page(s) e2023254

    MeSH term(s) Humans ; Mental Disorders/therapy ; Students ; Attitude of Health Personnel ; Students, Medical ; Students, Nursing
    Language English
    Publishing date 2023-10-17
    Publishing country Italy
    Document type Letter
    ZDB-ID 2114240-3
    ISSN 2531-6745 ; 0392-4203
    ISSN (online) 2531-6745
    ISSN 0392-4203
    DOI 10.23750/abm.v94i5.14296
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    Zs.B 925: Show issues Location:
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  4. Article: Cortico-thalamic development and disease: From cells, to circuits, to schizophrenia.

    Angulo Salavarria, Marilyn M / Dell'Amico, Claudia / D'Agostino, Armando / Conti, Luciano / Onorati, Marco

    Frontiers in neuroanatomy

    2023  Volume 17, Page(s) 1130797

    Abstract: The human brain is the most complex structure generated during development. Unveiling the ontogenesis and the intrinsic organization of specific neural networks may represent a key to understanding the physio-pathological aspects of different brain areas. ...

    Abstract The human brain is the most complex structure generated during development. Unveiling the ontogenesis and the intrinsic organization of specific neural networks may represent a key to understanding the physio-pathological aspects of different brain areas. The cortico-thalamic and thalamo-cortical (CT-TC) circuits process and modulate essential tasks such as wakefulness, sleep and memory, and their alterations may result in neurodevelopmental and psychiatric disorders. These pathologies are reported to affect specific neural populations but may also broadly alter physiological connections and thus dysregulate brain network generation, communication, and function. More specifically, the CT-TC system is reported to be severely affected in disorders impacting superior brain functions, such as schizophrenia (SCZ), bipolar disorder, autism spectrum disorders or epilepsy. In this review, the focus will be on CT development, and the models exploited to uncover and comprehend its molecular and cellular mechanisms. In parallel to animal models, still fundamental to unveil human neural network establishment, advanced
    Language English
    Publishing date 2023-03-02
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2452969-2
    ISSN 1662-5129
    ISSN 1662-5129
    DOI 10.3389/fnana.2023.1130797
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  5. Article ; Online: Early identification of risk for eating disorders in Italian secondary school students: a cross-sectional study.

    Gjini, Enkeleda / Terzoni, Stefano / Carelli, Lara / Ruta, Federico / Melillo, Nicole / Bertelli, Sara / Gambini, Orsola / D'Agostino, Armando / Ferrara, Paolo

    Rivista di psichiatria

    2024  Volume 59, Issue 1, Page(s) 13–19

    Abstract: Aim: Eating disorders are major illnesses that primarily affect adolescents and young adults and seriously threaten public health. Early identification of at-risk individuals and timely initiation of treatment is crucial to improve outcomes. The Inside ... ...

    Abstract Aim: Eating disorders are major illnesses that primarily affect adolescents and young adults and seriously threaten public health. Early identification of at-risk individuals and timely initiation of treatment is crucial to improve outcomes. The Inside Out Institute Screener (IOI-S) is a rapid self-administration screening tool for high-risk and early-stage eating disorders. This study aimed to investigate the risk of having an eating disorder in a sample of Italian students by testing the Italian version of the IOI-S.
    Methods: A multicentre cross-sectional study was conducted in a population of students aged 12-19 years; validity and reliability of the IOI-Sita were investigated.
    Results: Four-hundred and ninety-one (81.97%) students were enrolled, 24.85% of whom were found to be at "very high risk" of an eating disorder, according to IOI-Sita. Younger (p<0.001) and female (p<0.001) students had higher risk scores. The EFA confirmed the original monodimensional structure of the tool, S-CVI=0.95%. The Content Validity Index of the scale (S-CVI) was 0.95, ω coefficient was 0.927.
    Discussion and conclusions: This research confirms the need to screen for eating disorders in Italian youth adequately; the psychometric properties of the IOI-Sita confirm it as a valid and reliable tool for screening high-risk and early-stage eating disorders.
    MeSH term(s) Adolescent ; Young Adult ; Humans ; Female ; Cross-Sectional Studies ; Reproducibility of Results ; Surveys and Questionnaires ; Feeding and Eating Disorders/diagnosis ; Feeding and Eating Disorders/epidemiology ; Psychometrics ; Students ; Italy/epidemiology ; Schools
    Language English
    Publishing date 2024-02-19
    Publishing country Italy
    Document type Journal Article
    ZDB-ID 205570-3
    ISSN 2038-2502 ; 0035-6484
    ISSN (online) 2038-2502
    ISSN 0035-6484
    DOI 10.1708/4205.41944
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    Zs.B 1521: Show issues Location:
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  6. Article ; Online: Proof-of-concept evidence for high-density EEG investigation of sleep slow wave traveling in First-Episode Psychosis.

    Castelnovo, Anna / Casetta, Cecilia / Cavallotti, Simone / Marcatili, Matteo / Del Fabro, Lorenzo / Canevini, Maria Paola / Sarasso, Simone / D'Agostino, Armando

    Scientific reports

    2024  Volume 14, Issue 1, Page(s) 6826

    Abstract: Schizophrenia is thought to reflect aberrant connectivity within cortico-cortical and reentrant thalamo-cortical loops, which physiologically integrate and coordinate the function of multiple cortical and subcortical structures. Despite extensive ... ...

    Abstract Schizophrenia is thought to reflect aberrant connectivity within cortico-cortical and reentrant thalamo-cortical loops, which physiologically integrate and coordinate the function of multiple cortical and subcortical structures. Despite extensive research, reliable biomarkers of such "dys-connectivity" remain to be identified at the onset of psychosis, and before exposure to antipsychotic drugs. Because slow waves travel across the brain during sleep, they represent an ideal paradigm to study pathological conditions affecting brain connectivity. Here, we provide proof-of-concept evidence for a novel approach to investigate slow wave traveling properties in First-Episode Psychosis (FEP) with high-density electroencephalography (EEG). Whole-night sleep recordings of 5 drug-naïve FEP and 5 age- and gender-matched healthy control subjects were obtained with a 256-channel EEG system. One patient was re-recorded after 6 months and 3 years of continuous clozapine treatment. Slow wave detection and traveling properties were obtained with an open-source toolbox. Slow wave density and slow wave traveled distance (measured as the line of longest displacement) were significantly lower in patients (p < 0.05). In the patient who was tested longitudinally during effective clozapine treatment, slow wave density normalized, while traveling distance only partially recovered. These preliminary findings suggest that slow wave traveling could be employed in larger samples to detect cortical "dys-connectivity" at psychosis onset.
    MeSH term(s) Humans ; Clozapine ; Electroencephalography ; Sleep/physiology ; Psychotic Disorders ; Schizophrenia/drug therapy
    Chemical Substances Clozapine (J60AR2IKIC)
    Language English
    Publishing date 2024-03-21
    Publishing country England
    Document type Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-024-57476-2
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  7. Article ; Online: Machine learning methods to predict outcomes of pharmacological treatment in psychosis.

    Del Fabro, Lorenzo / Bondi, Elena / Serio, Francesca / Maggioni, Eleonora / D'Agostino, Armando / Brambilla, Paolo

    Translational psychiatry

    2023  Volume 13, Issue 1, Page(s) 75

    Abstract: In recent years, machine learning (ML) has been a promising approach in the research of treatment outcome prediction in psychosis. In this study, we reviewed ML studies using different neuroimaging, neurophysiological, genetic, and clinical features to ... ...

    Abstract In recent years, machine learning (ML) has been a promising approach in the research of treatment outcome prediction in psychosis. In this study, we reviewed ML studies using different neuroimaging, neurophysiological, genetic, and clinical features to predict antipsychotic treatment outcomes in patients at different stages of schizophrenia. Literature available on PubMed until March 2022 was reviewed. Overall, 28 studies were included, among them 23 using a single-modality approach and 5 combining data from multiple modalities. The majority of included studies considered structural and functional neuroimaging biomarkers as predictive features used in ML models. Specifically, functional magnetic resonance imaging (fMRI) features contributed to antipsychotic treatment response prediction of psychosis with good accuracies. Additionally, several studies found that ML models based on clinical features might present adequate predictive ability. Importantly, by examining the additive effects of combining features, the predictive value might be improved by applying multimodal ML approaches. However, most of the included studies presented several limitations, such as small sample sizes and a lack of replication tests. Moreover, considerable clinical and analytical heterogeneity among included studies posed a challenge in synthesizing findings and generating robust overall conclusions. Despite the complexity and heterogeneity of methodology, prognostic features, clinical presentation, and treatment approaches, studies included in this review suggest that ML tools may have the potential to predict treatment outcomes of psychosis accurately. Future studies need to focus on refining feature characterization, validating prediction models, and evaluate their translation in real-world clinical practice.
    MeSH term(s) Humans ; Antipsychotic Agents/therapeutic use ; Psychotic Disorders/diagnostic imaging ; Psychotic Disorders/drug therapy ; Functional Neuroimaging ; Machine Learning ; Neuroimaging
    Chemical Substances Antipsychotic Agents
    Language English
    Publishing date 2023-03-02
    Publishing country United States
    Document type Journal Article ; Review ; Research Support, Non-U.S. Gov't
    ZDB-ID 2609311-X
    ISSN 2158-3188 ; 2158-3188
    ISSN (online) 2158-3188
    ISSN 2158-3188
    DOI 10.1038/s41398-023-02371-z
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  8. Article ; Online: Correction to: The Impact of Lithium on Brain Function in Bipolar Disorder: An Updated Review of Functional Magnetic Resonance Imaging Studies.

    Bergamelli, Emilio / Del Fabro, Lorenzo / Delvecchio, Giuseppe / D'Agostino, Armando / Brambilla, Paolo

    CNS drugs

    2022  Volume 36, Issue 11, Page(s) 1241

    Language English
    Publishing date 2022-10-07
    Publishing country New Zealand
    Document type Published Erratum
    ZDB-ID 1203800-3
    ISSN 1179-1934 ; 1172-7047
    ISSN (online) 1179-1934
    ISSN 1172-7047
    DOI 10.1007/s40263-022-00962-w
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  10. Article ; Online: Reply to ‘Delirium, sleep, COVID-19 and melatonin’

    D'Agostino, Armando / Zambrelli, Elena

    Sleep Medicine

    2020  Volume 75, Page(s) 543

    Keywords General Medicine ; covid19
    Language English
    Publisher Elsevier BV
    Publishing country us
    Document type Article ; Online
    ZDB-ID 2012041-2
    ISSN 1878-5506 ; 1389-9457
    ISSN (online) 1878-5506
    ISSN 1389-9457
    DOI 10.1016/j.sleep.2020.05.027
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