Publications by authors named "G Dolci"
Bridging the gap between cortical morphometric remodeling and gene expression can help to clarify the effects of the selective brain accumulation of Amyloid-β (Aβ) and tau proteins occurring in the Alzheimer's disease (AD). To this aim, we derived morphometric similarity (MS) networks from 126 Aβ- and tau-positive (Aβ+/tau+) and 172 Aβ-/tau- subjects, and we investigated the association between group-wise regional MS differences and transcriptional correlates thanks to an imaging transcriptomics approach grounded in the Allen Human Brain Atlas (AHBA). The expressed gene with the highest correlation with MS alterations was , a gene related to Aβ homeostasis.
View Article and Find Full Text PDFMultiple techniques exist for the preoperative localization of small, deeply located solid or subsolid pulmonary nodules to guide limited thoracoscopic resection. This study aims to conduct a multi-institutional comparison of three different tomography-guided tracers' methods. A retrospective multicenter cross-sectional study was conducted.
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- A study on perioperative antibiotic prophylaxis (PAP) in lung transplant recipients over a 20-year period revealed significant variation in practices among different centers.
- The research enrolled 111 lung transplant recipients, finding that most received combination therapy, while the median duration for PAP was 10 days.
- However, the study concluded that there was no significant difference in preventing early post-operative infections (EPOIs) between combination and single-agent therapies, and duration of PAP also did not impact EPOI rates.
This study evaluated the fate of food delivery boxes when subjected to biological treatments, reproducing at the lab-scale the conditions of full-scale plants. Four paper-based boxes were composted: two made of paper only, one coupled with polylactic acid (PLA), and one with a barrier coating. One paper only box and the box with PLA were also investigated for their anaerobic degradability with biochemical methane potential (BMP) and semi-continuous tests.
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- Alzheimer's disease (AD) is a common form of dementia causing progressive cognitive decline, with a precursor stage called Mild Cognitive Impairment (MCI) that can either worsen or remain stable.
- Researchers used structural and functional MRI data and included genetic factors (Single Nucleotide Polymorphisms) to develop a novel deep learning model aimed at detecting AD and predicting MCI progression, filling in missing data through Cycle Generative Adversarial Networks.
- The model achieved impressive accuracy rates—92.6% for distinguishing between cognitively normal individuals and AD, and 71.1% for predicting MCI progression—while identifying critical brain regions and connectivity patterns associated with the disease.