Archivio Istituzionale della Ricerca- Università del Piemonte Orientale
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Efficacy of a theoretical-practical course for the ultrasound measurement of the optic nerve diameter in different healthcare operators
No full textBackground The measurement of the optic nerve sheath diameter (ONSD) via ultrasound is a non-invasive technique to estimate intracranial pressure. Brief training has been shown to be effective in accurately teaching the ONSD technique in specialized healthcare providers. This study evaluates the ability of medical and nursing students, Intensive Care Unit (ICU) nurses, and ICU residents to perform ONSD measurements after a brief training. Methods Forty participants underwent a 4-h training session consisting of 30 min of lecture focusing on the key principles of the technique for ONSD measurement, followed by at least 20 measurements with an expert tutor. Thereafter, all participants assessed 5 ONSD measurements on healthy volunteers and their assessments were compared to those by the expert tutor. Results All participants successfully visualized the optic nerve and recorded similar values among groups (p > 0.05 for all comparisons). ICU nurse residents and medical students demonstrated a good accuracyof measurements, as defined by an upper and lower limits of agreement with the expert tutor not exceeding 0.5 mm in the Bland-Altman analysis. On the opposite, nurse students had the highest error rates and poor accuracy in ONSD assessment. Conclusions These findings highlight the feasibility of training medical students, ICU nurses and residents in ONSD measurement, opening the possibility of a wider application of this technique. After dedicated training, ONSD assessment and monitoring could be performed not only by specialists but also by other healthcare providers, including specialized nurses. This may serve as an additional tool for the rapid triage of patients, even in out-of-hospital settings
Integrating genome and transcriptome analysis to decipher balanced structural variants in unsolved cases of neurodevelopmental disorders
Get PDFIntroduction: Balanced chromosomal abnormalities (BCAs) are structural variations that can underlie a wide spectrum of neurodevelopmental disorders, often remaining undetected by conventional diagnostic approaches. Whole-genome sequencing (WGS) allows for base-pair resolution of structural variants across the entire genome, making it a powerful tool to detect cryptic chromosomal rearrangements and refine breakpoint mapping. RNA sequencing (RNA-Seq), by enabling the detection of gene expression changes and fusion transcripts, provides complementary functional insights into the consequences of genomic alterations. This study integrated WGS and RNA-Seq to precisely characterize the breakpoints and assess the functional impact of de novo BCAs in two unsolved cases of Neurodevelopmental Disorders. Materials and methods: Short read WGS was used to identify the chromosomal breakpoints and gene disruptions caused by BCAs. RNA-Seq on blood RNA was employed to detect differential gene expression and potential fusion transcripts of disrupted genes. Results: In the first case, the inversion inv(8) (p11.2q13) disrupted two genes at the breakpoints, namely, CHD7 and SLC20A2. These genes are in opposite orientations, and the inversion realigned them in the same direction, generating two novel fusion genes. Disruption of CHD7 confirmed the suspected diagnosis of CHARGE syndrome. The interruption of SLC20A2, commonly associated with neurological symptoms, prompted further clinical evaluation. RNA-Seq identified in-frame fusion transcripts from the chimeric genes in the blood, suggesting a potential deleterious phenotypic effect. In the second case, WGS revealed a balanced translocation t(17; 22) (q25; q13) that disrupted EP300 at 22q25, confirming Rubinstein-Taybi syndrome. The concurrent disruption of RBFOX3 at 17q13 suggested additional neurological implications, particularly related to epilepsy. Transcriptomic analysis demonstrated the monoallelic and significantly reduced expression of EP300. Conclusion: These findings highlight the crucial role of WGS in identifying disease-associated BCAs and underscore the complementary value of RNA-Seq in assessing their functional consequences. This integrated approach enhanced diagnostic accuracy and clinical management, paving the way for more comprehensive and personalized care in these two patients
Discordance in Patient and Physician's Perception of Disease Activity Among Idiopathic Inflammatory Myopathy Patients: Insights From the COVAD Study
No full textLocal Habitat Features, but Not Isolation, Shape Alpine Odonate Assemblages: Implications for Modelling and Conservation
Get PDFPrevalence of Urinary Tract Cancer in Patients with Obstructive Sleep Apnea: Data from the Vercelli Registry
No full textRice Adaptation to Abiotic Stresses Caused by Soil Inorganic Elements
Get PDFSoil contamination with toxic inorganic elements poses a major challenge to rice cultivation, affecting plant physiology, yield, and grain safety. While natural variation in tolerance exists among rice genotypes and related species, recent advances in genomics, breeding, and biotechnology offer new opportunities to enhance adaptation. This review synthesizes the current knowledge on the physiological effects of toxic elements and explores strategies to improve tolerance, from harnessing genetic diversity to genome editing and transgenic approaches. Attention is also paid to the role of microbiota in mitigating toxicity and reducing translocation to seeds, highlighting emerging solutions for sustainable rice production in contaminated environments
Neutrophil-to-Lymphocyte Ratio in the Alzheimer’s Disease Continuum
No full textAlzheimer’s disease (AD) is a neurodegenerative disorder defined clinically by progressive cognitive decline and memory impairment and pathologically by the accumulation of amyloid-beta plaques, tau neurofibrillary tangles, neuroinflammation, and immune system dysregulation. Peripheral biomarkers are gaining attention as valuable tools for elucidating neuroinflammatory mechanisms in the AD continuum, with potential implications for diagnosis and prognosis. Among these, the neutrophil-to-lymphocyte ratio (NLR) has emerged as a promising systemic inflammatory marker. NLR, a readily available and cost-effective parameter derived from routine blood tests, reflects the balance between innate and adaptive immune responses. Elevated NLR has been associated with AD and mild cognitive impairment (MCI), showing correlations with disease severity, amyloid burden, and neuroinflammation. Increased neutrophil counts may contribute to neurodegeneration through oxidative stress and pro-inflammatory cytokine release, while decreased lymphocyte levels suggest impaired adaptive immunity. However, despite growing evidence, the clinical utility of NLR in AD remains debated due to heterogeneity in study populations and confounding factors, such as comorbidities and medication effects. This review provides a comprehensive analysis of the association between NLR and AD throughout the disease continuum. Future research should prioritize longitudinal studies and integrative approaches that combine NLR with other inflammatory and neurodegenerative markers to enhance early diagnosis and personalized therapeutic strategies
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No full textAssessing patterns of authorship of low- and middle-income countries in global commercial clinical trials in oncology
Get PDFPoor authorship practices in global health research may be a sign of unequal partnerships. Previous studies have shown that authors from low- and middle-income countries (LMICs) are frequently underrepresented in publications from global research collaborations between LMICs and high-income countries (HICs). To the best of our knowledge, the patterns of authorship from LMICs in international industry-sponsored clinical research on breast, lung and colon cancer have not yet been investigated. Therefore, as a spin-off to broader research on globalization of commercial clinical trials in oncology, we conducted an analysis of authorship in the publications from completed industry-sponsored therapeutic trials in breast, lung and colon cancer (from phase I to IV) that involved LMICs. Only articles published in a peer-reviewed journal in English by March 30, 2024 were included. A total of 302 publications from 173 trials were analysed. 63% (n = 191) of them have at least one author from a middle-income country (MIC); 14% (n = 42) articles have the first author from a MIC; and 13% (n = 39) articles have the last author from a MIC. Conversely, 37% (n = 111) of articles had no author from MIC, including two trials conducted only in MICs. In conclusion, our study found an imbalance in authorship, suggestive of significant inequalities, in collaborative research in industry-sponsored clinical trials for breast, lung and colon cancer. Industry sponsors need to work towards greater equity in authorship when collaborating with researchers in (L)MICs, and oncology researchers and opinion leaders in HICs should actively advocate for greater fairness to their colleagues in (L)MICs
Adapting foundation models for rapid clinical response: intracerebral hemorrhage segmentation in emergency settings
No full textIntracerebral hemorrhage (ICH) is a medical emergency that demands rapid and accurate diagnosis for optimal patient management. Hemorrhagic lesions’ segmentation on CT scans is a necessary first step for acquiring quantitative imaging data that are becoming increasingly useful in the clinical setting. However, traditional manual segmentation is time-consuming and prone to inter-rater variability, creating a need for automated solutions. This study introduces a novel approach combining advanced deep learning models to segment extensive and morphologically variable ICH lesions in non-contrast CT scans. We propose a two-step methodology that begins with a user-defined loose bounding box around the lesion, followed by a fine-tuned YOLOv8-S object detection model to generate precise, slice-specific bounding boxes. These bounding boxes are then used to prompt the Medical Segment Anything Model for accurate lesion segmentation. Our pipeline achieves high segmentation accuracy with minimal supervision, demonstrating strong potential as a practical alternative to task-specific models. We evaluated the model on a dataset of 252 CT scans demonstrating high performance in segmentation accuracy and robustness. Finally, the resulting segmentation tool is integrated into a user-friendly web application prototype, offering clinicians a simple interface for lesion identification and radiomic quantification