Clustering Functional Magnetic Resonance Imaging Time Series in Glioblastoma Characterization: A Review of the Evolution, Applications, and Potentials.

In this paper, we discuss how the clustering analysis technique can be applied to analyze functional magnetic resonance imaging (fMRI) time-series data in the context of glioblastoma (GBM), a highly heterogeneous brain tumor. The precise characterization of GBM is challenging and requires advanced analytical approaches. We have synthesized the existing literature to provide an overview of how clustering algorithms can help identify unique patterns within the dynamics of GBM. Our review shows that the clustering of fMRI time series has great potential for improving the differentiation between various subtypes of GBM, which is pivotal for developing personalized therapeutic strategies. Moreover, this method proves to be effective in capturing temporal changes occurring in GBM, enhancing the monitoring of disease progression and response to treatment. By thoroughly examining and consolidating the current research, this paper contributes to the understanding of how clustering techniques applied to fMRI data can refine the characterization of GBM. This article emphasizes the importance of incorporating cutting-edge data analysis techniques into neuroimaging and neuro-oncology research. By providing a detailed perspective, this approach may guide future investigations and boost the development of tailored therapeutic strategies for GBM.

Impact of sleep disorders on behavioral issues in preschoolers with autism spectrum disorder.

Background: Sleep disorders are one of the most common problems in children with Autism Spectrum Disorder (ASD). However, they often tend to be underdiagnosed and incorrectly treated in clinical practice. This study aims to identify sleep disorders in preschool children with ASD and to explore their relationship with the core symptoms of autism, the child's developmental and cognitive level as well as the psychiatric comorbidities. Methods: We recruited 163 preschool children with a diagnosis of ASD. The Children's Sleep Habits Questionnaire (CSHQ) assessed sleep conditions. Multiple standardized tests were used to evaluate intellectual abilities, the presence of repetitive behaviors (through the Repetitive Behavior Scale-Revised), as well as the emotional-behavioral problems and the psychiatric comorbidities (through the Child Behavior Checklist -CBCL 11/2-5). Results: The results showed that poor disorders had consistently higher scores in all areas assessed by the CSHQ and on the CBCL across all domains. The correlational analysis showed that severe sleep disorders were associated with higher scores in internalizing, externalizing, and total problems at the CBCL syndromic scales, and in all DSM-oriented CBCL subscales. Moreover, we found that the association between sleep disorders and restricted and repetitive behaviors (RRBs) is explained by the anxiety-related symptoms. Conclusion: Based on these findings, the study recommends that screening for sleep problems followed by early intervention should constitute a routine part of clinical practice for children with ASD.

Advancements in Glioma Care: Focus on Emerging Neurosurgical Techniques.

BACKGROUND: Despite significant advances in understanding the molecular pathways of glioma, translating this knowledge into effective long-term solutions remains a challenge. Indeed, gliomas pose a significant challenge to neurosurgical oncology because of their diverse histopathological features, genetic heterogeneity, and clinical manifestations. Relevant sections: This study focuses on glioma complexity by reviewing recent advances in their management, also considering new classification systems and emerging neurosurgical techniques. To bridge the gap between new neurosurgical approaches and standards of care, the importance of molecular diagnosis and the use of techniques such as laser interstitial thermal therapy (LITT) and focused ultrasound (FUS) are emphasized, exploring how the integration of molecular knowledge with emerging neurosurgical approaches can personalize and improve the treatment of gliomas. CONCLUSIONS: The choice between LITT and FUS should be tailored to each case, considering factors such as tumor characteristics and patient health. LITT is favored for larger, complex tumors, while FUS is standard for smaller, deep-seated ones. Both techniques are equally effective for small and superficial tumors. Our study provides clear guidance for treating pediatric low-grade gliomas and highlights the crucial roles of LITT and FUS in managing high-grade gliomas in adults. This research sets the stage for improved patient care and future developments in the field of neurosurgery.

Differential Diagnosis in Children with Autistic Symptoms and Subthreshold ADOS Total Score: An Observational Study.

BACKGROUND: Children with autism spectrum disorder (ASD) share some symptoms with children with other neurodevelopmental disorders (ie, intellectual disability or communication disorders or language disorders). These similarities can make difficult to obtain an accurate diagnosis, which is essential to give targeted treatments to the patients. We aim to verify in our study if children with autistic traits who undergo to Autism Diagnostic Observation Schedule had specific clinical diagnosis. PATIENTS AND METHODS: We selected 73 children tested with ADOS-G or ADOS-2, for the presence of autistic symptoms. The whole sample did not reach the cut-off of ADOS and did not receive the ASD diagnosis, according to DSM-5. RESULTS: Results of this study showed that in order of frequency and early diagnosis, communication disorders (CD), mild intellectual disability (mID) and the attention deficit hyperactivity disorders (ADHD) represent the most common final clinical diagnosis in children with autistic traits. CONCLUSION: Our results showed as the CD was the common diagnosis of these children and that often associated with younger age. Moreover, analyses of ADOS domains and the difference of individual items between groups did not show the capacity to differentiate between different neurodevelopmental disorders in terms of differential diagnosis, and this confirms the need for integrating multiple sources of information during the diagnostic process.