Publications by authors named "F Montani"

Immune checkpoint inhibitors (ICIs) improve outcomes in advanced melanoma, but many patients are refractory or experience relapse. The gut microbiota modulates antitumor responses. However, inconsistent baseline predictors point to heterogeneity in responses and inadequacy of cross-sectional data.

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The processes involved in encoding and decoding signals in the human brain are a continually studied topic, as neuronal information flow involves complex nonlinear dynamics. This study examines awake human intracranial electroencephalography (iEEG) data from normal brain regions to explore how biological sex influences these dynamics. The iEEG data were analyzed using permutation entropy and statistical complexity in the time domain and power spectrum calculations in the frequency domain.

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Metabolic plasticity is a hallmark of cancer, and metabolic alterations represent a promising therapeutic target. Since cellular metabolism is controlled by membrane traffic at multiple levels, we investigated the involvement of TBC1 domain-containing proteins (TBC1Ds) in the regulation of cancer metabolism. These proteins are characterized by the presence of a RAB-GAP domain, the TBC1 domain, and typically function as attenuators of RABs, the master switches of membrane traffic.

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Scale-free brain activity, linked with learning, the integration of different time scales, and the formation of mental models, is correlated with a metastable cognitive basis. The spectral slope, a key aspect of scale-free dynamics, was proposed as a potential indicator to distinguish between different sleep stages. Studies suggest that brain networks maintain a consistent scale-free structure across wakefulness, anesthesia, and recovery.

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Article Synopsis
  • * A 54-gene signature, known as PETsign, correlates with FDG uptake and provides independent prognostic information for patients with luminal breast cancers, the most common subtype.
  • * Findings suggest that PETsign reflects metabolic properties of breast cancer cells, predicting higher glucose dependency and involvement of specific signaling pathways, making it useful for improving clinical decisions in treatment.
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