An accumulating amount of evidence supports the hypothesis that various brain disorders are in fact disconnection syndromes or network diseases, which disrupt brain networks that support multiple perceptual and cognitive functions.
A reduction in water mobility due to the increased cellularity is associated to malignant lesions, with diffusion parameters being helpful for lesion characterization. On the other hand, by evaluating diffusion directionality, it is possible to infer on white matter pathways and on the structural connectivity between different brain regions. The same approach is applied to estimate orientation of muscular fibres in the body.
Currently, diagnosis and therapy strategies for cancer patients strongly relies on cell- or tissue-based visual assessment of tumor markers. However, in most clinical, pathology and research centers the criteria used for their visual classification is merely qualitative and thus strongly operator-dependent.
Cerebrovascular diseases represent one of the most prevalent subsets of all cardiovascular diseases, the number one cause of mortality worldwide. In particular, ample evidence exists indicating that cerebral small vessel disease (SVD) is the most prevalent neurological disorder, underlying multiple neurological conditions such as stroke and dementia.
Fast acquisition approaches for quantitative evaluation of T2 and T2*-weighted images are needed to investigate brain iron deposits in movement disorders such as Parkinson’s Disease and Essential Tremor.
Non-additive speckle wide sense multiplicative (pseudo) noise is present in a multitude of imaging modalities, involving coherent radiation such as Synthetic Aperture Radar (SAR), LASER, Optical Coherence Tomography (OCT) and Ultrasound (US).
The gold standard technique for mapping myocardium fibrosis is MRI with late gadolinium enhancement (LGE). Despite providing quantitative measurements, LGE analysis is subject-dependent and so objective T1 measurements are actively being researched.
Emotional and cognitive objective evaluation the subjects is essential both in the identification and characterization of common disorders, such as fatigue, stress and sleep disorders, as in the diagnosis of more severe neurological, psychological and psychiatric conditions such as MCI, ALS, Alzheimer, depression, anxiety, attention deficit and Schizophrenia.
Recently we surveyed the dark-proteome, i.e., regions of proteins never observed by experimental structure determination and inaccessible to homology modelling. Surprisingly, we found that most of the dark proteome could not be accounted for by conventional explanations (e.g., intrinsic disorder, transmembrane domains, and compositional bias), and that nearly half of the dark proteome comprised dark proteins, in which the entire sequence lacked similarity to any known structure. In this project we keep the dark secretes of the proteome at the Dark Dark Proteome Database (DPD) however we share some of our secrets through associated web services that provide access to updated information about the dark proteome.