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Mixed connective tissue disease was first described as a new autoimmune rheumatic disease in 1972 based on the claim of a distinct clinical picture associated with anti-RNP antibody positivity. Subsequently, this new entity has divided opinions in the rheumatology community. We have reviewed recent cohort studies with more than 100 patients, comparing the clinical and immunological features, treatment, prognosis and evolution to well-defined autoimmune rheumatic diseases. We also reviewed clinical features of undifferentiated autoimmune rheumatic diseases based on the most recent studies. After gathering and reviewing these data, we discuss whether the designation “mixed connective tissue disease” should be maintained.

Body fluids of cancer patients have attracted increasing attention in biomedical research within the last 15 years since—as so-called liquid biopsies—they represent a non-invasive source of clinically exploitable biomarkers, including circulating tumor cells (CTCs) and cell-free tumor DNA (ctDNA). Assessment of CTCs in peripheral blood from solid cancer patients has proven useful for detection of subclinical disease which otherwise remains invisible for current staging techniques. Based on results from large cohort studies in breast and colon cancer, diagnostic tests for enumeration of CTCs have been developed which can be used for tumor staging, prognosis, and post-treatment surveillance. Circulating plasma DNA derived from Epstein–Barr or human papilloma viruses has been established as a sensitive and highly specific biomarker for early cancer detection and disease monitoring. More recently, first studies have been initiated for studying the diagnostic value of mutant variants in plasma-derived ctDNA for treatment selection, response assessment and early detection of treatment failure.Advanced Head and Neck Squamous Cell Carcinoma (HNSCC) represents a malignancy associated with locoregionally advanced stage at presentation, dismal prognosis and little improvement in treatment outcome over the past decade, especially for patients with metastatic disease. HNSCC patients might therefore benefit from incorporation of liquid biopsy-based assays in clinical management. In the following chapters, I will summarize current evidence of the diagnostic value of liquid biopsies in HNSCC and give examples of potential clinical applications.

We propose a Generative Adversarial Network (GAN) model named Disease Evolution Predictor GAN (DEP-GAN) to predict the evolution (i.e., progression and regression) of White Matter Hyperintensities (WMH) in small vessel disease. In this study, the evolution of WMH is represented by the “Disease Evolution Map” (DEM) produced by subtracting irregularity map (IM) images from two time points: baseline and follow-up. DEP-GAN uses two discriminators (critics) to enforce anatomically realistic follow-up image and DEM. To simulate the non-deterministic and unknown parameters involved in WMH evolution, we propose modulating an array of random noises to the DEP-GAN’s generator which forces the model to imitate a wider spectrum of alternatives in the results. Our study shows that the use of two critics and random noises modulation in the proposed DEP-GAN improves its performance predicting the evolution of WMH in small vessel disease. DEP-GAN is able to estimate WMH volume in the follow-up year with mean (std) estimation error of −1.91 (12.12) ml and predict WMH evolution with mean rate of \(72.01\%\) accuracy (i.e., \(88.69\%\) and \(23.92\%\) better than Wasserstein GAN).

The objective of this work is to respond to the question: can quantitative electroencephalography (EEG) distinguish among Alzheimer’s Disease (AD) patients, mild cognitive impaired (MCI) subjects and elderly healthy controls? In other words, are there nonlinear indexes extracted from raw EEG data that are able to manifest the background difference among EEG? The response we give here is that a synthetic index of entropic complexity (Permutation Entropy, PE) as well as a measure of compressibility of the EEG can be used to discriminate among classes of subjects. An experimental database has been analyzed to make these measurements and the results we achieved are encouraging also in terms of disease evolution. Indeed, it is clearly shown that the condition of MCI has intermediate properties with respect to the analyzed markers: thus, these markers could in principle be used to evaluate the probability of transition from MCI to mild AD.