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A report on the Stem Cell EuroConference, Paris, France, 9-10 December 2004

The role of dietary sodium intake on the modulation of T helper 17 cells and regulatory T cells in patients with rheumatoid arthritis and systemic lupus erythematosus

We aimed at investigating whether the frequency and function of T helper 17 (Th17) and regulatory T cells (Treg) are affected by a restriction of dietary sodium intake in patients with rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). We enrolled RA and SLE patients not receiving drugs known to increase urinary sodium excretion. Patients underwent a dietary regimen starting with a restricted daily sodium intake followed by a normal-sodium daily intake. The timepoints were identified at baseline (T0), after 3 weeks of low-sodium dietary regimen (T3), after 2 weeks of normal-sodium dietary regimen (T5). On these visits, we measured the 24-hour urinary sodium excretion, the frequency and function of Th17 and Treg cells in the peripheral blood, the serum levels of cytokines. Analysis of urinary sodium excretion confirmed adherence to the dietary regimen. In RA patients, a trend toward a reduction in the frequencies of Th17 cells over the low-sodium dietary regimen followed by an increase at T5 was observed, while Treg cells exhibited the opposite trend. SLE patients showed a progressive reduction in the percentage of Th17 cells that reached a significance at T5 compared to T0 (p = 0.01) and an increase in the percentage of Treg cells following the low-sodium dietary regimen at both T1 and T3 compared to T0 (p = 0.04 and p = 0.02, respectively). No significant apoptosis or proliferation modulation was found. In RA patients, we found a reduction at T5 compared to T0 in serum levels of both TGFβ (p = 0.0016) and IL-9 (p = 0.0007); serum IL-9 levels were also reduced in SLE patients at T5 with respect to T0 (p = 0.03). This is the first study investigating the effects of dietary sodium intake on adaptive immunity. Based on the results, we hypothesize that a restricted sodium dietary intake may dampen the inflammatory response in RA and SLE patients

Hypertension and emergency medicine: an update

The objective of this paper is to evaluate the correct management of hypertension in emergency departments. Studies were identified searching PubMed up to April 30, 2012, combining the terms 'HYPERTENSIVE EMERGENCY' and 'HYPERTENSIVE URGENCY'. The search strategy was limited to English and Italian language papers on adult and pediatric patients. Hypertensive crises are commonly found in emergency departments. A range of pharmacological options are available in this setting, but each physician should tailor theoretical principles to the individual patient according to his or her clinical parameters

Increased Vascular Endothelial Growth Factor Serum Concentrations May Help to Identify Patients with Onset of Type 1 Diabetes during Childhood at Risk for Developing Persistent Microalbuminuria

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Outcome Prediction for SARS-CoV-2 Patients Using Machine Learning Modeling of Clinical, Radiological, and Radiomic Features Derived from Chest CT Images

Featured Application The present study demonstrates that semi-automatic segmentation enables the identification of regions of interest affected by SARS-CoV-2 infection for the extraction of prognostic features from chest CT scans without suffering from the inter-operator variability typical of segmentation, hence offering a valuable and informative second opinion. Machine Learning methods allow identification of the prognostic features potentially reusable for the early detection and management of other similar diseases. (1) Background: Chest Computed Tomography (CT) has been proposed as a non-invasive method for confirming the diagnosis of SARS-CoV-2 patients using radiomic features (RFs) and baseline clinical data. The performance of Machine Learning (ML) methods using RFs derived from semi-automatically segmented lungs in chest CT images was investigated regarding the ability to predict the mortality of SARS-CoV-2 patients. (2) Methods: A total of 179 RFs extracted from 436 chest CT images of SARS-CoV-2 patients, and 8 clinical and 6 radiological variables, were used to train and evaluate three ML methods (Least Absolute Shrinkage and Selection Operator [LASSO] regularized regression, Random Forest Classifier [RFC], and the Fully connected Neural Network [FcNN]) for their ability to predict mortality using the Area Under the Curve (AUC) of Receiver Operator characteristic (ROC) Curves. These three groups of variables were used separately and together as input for constructing and comparing the final performance of ML models. (3) Results: All the ML models using only RFs achieved an informative level regarding predictive ability, outperforming radiological assessment, without however reaching the performance obtained with ML based on clinical variables. The LASSO regularized regression and the FcNN performed equally, both being superior to the RFC. (4) Conclusions: Radiomic features based on semi-automatically segmented CT images and ML approaches can aid in identifying patients with a high risk of mortality, allowing a fast, objective, and generalizable method for improving prognostic assessment by providing a second expert opinion that outperforms human evaluation

In Vitro Modeling of Tumor-Immune System Interaction.

Immunotherapy has emerged during the past two decades as an innovative and successful form of cancer treatment. However, frequently, mechanisms of actions are still unclear, predictive markers are insufficiently characterized, and preclinical assays for innovative treatments are poorly reliable. In this context, the analysis of tumor/immune system interaction plays key roles, but may be unreliably mirrored by in vivo experimental models and standard bidimensional culture systems. Tridimensional cultures of tumor cells have been developed to bridge the gap between in vitro and in vivo systems. Interestingly, defined aspects of the interaction of cells from adaptive and innate immune systems and tumor cells may also be mirrored by 3D cultures. Here we review in vitro models of cancer/immune cell interaction and we propose that updated technologies might help develop innovative treatments, identify biologicals of potential clinical relevance, and select patients eligible for immunotherapy treatments

Stepwise reprogramming of liver cells to a pancreas progenitor state by the transcriptional regulator Tgif2

The development of a successful lineage reprogramming strategy of liver to pancreas holds promises for the treatment and potential cure of diabetes. The liver is an ideal tissue source for generating pancreatic cells, because of its close developmental origin with the pancreas and its regenerative ability. Yet, the molecular bases of hepatic and pancreatic cellular plasticity are still poorly understood. Here, we report that the TALE homeoprotein TGIF2 acts as a developmental regulator of the pancreas versus liver fate decision and is sufficient to elicit liver-to-pancreas fate conversion both ex vivo and in vivo. Hepatocytes expressing Tgif2 undergo extensive transcriptional remodelling, which represses the original hepatic identity and, over time, induces a pancreatic progenitor-like phenotype. Consistently, in vivo forced expression of Tgif2 activates pancreatic progenitor genes in adult mouse hepatocytes. This study uncovers the reprogramming activity of TGIF2 and suggests a stepwise reprogramming paradigm, whereby a ‘lineage-restricted’ dedifferentiation step precedes the identity switch

High sleep fragmentation parallels poor subjective sleep quality during the third wave of the Covid-19 pandemic: An actigraphic study

Studies on sleep during the Covid-19 pandemic have mostly been conducted during the first wave of contagion (spring 2020). To follow up on two Italian studies addressing subjective sleep features during the second wave (autumn 2020), here we assess sleep during the third wave (spring 2021) in a sample of healthy adults from Campania (Southern Italy). Actigraphic data (on 2 nights) and the Pittsburgh Sleep Quality Index were collected from 82 participants (40 F, mean age: 32.5 ± 11.5 years) from 11 March to 18 April 2021, when Campania was classified as a "red zone", i.e. it was subjected to strict restrictions, only slightly looser than those characterizing the first national lockdown (spring 2020). Although objective sleep duration and architecture appeared in the normal range, the presence of disrupted sleep was indexed by a relevant degree of sleep fragmentation (number of awakenings ≥ 1 min: 12.7 ± 6.12; number of awakenings ≥ 5 min: 3.04 ± 1.52), paralleled by poor subjective sleep quality (Pittsburgh Sleep Quality Index global score: 5.77 ± 2.58). These data suggest that the relevant subjective sleep impairments reported during the first wave could have relied on subtle sleep disruptions that were undetected by the few objective sleep studies from the same period. Taken together with sleep data on previous phases of the pandemic, our findings show that the detrimental effects on sleep determined by the initial pandemic outbreak have not abated across the subsequent waves of contagion, and highlight the need for interventions addressing sleep health in global emergencies

Evaluation of renal function in clinical practice: the basics

The evaluation of renal function in Internal Medicine plays an important role in the staging and prognosis of chronic kidney disease, but also for the daily clinical activity (for example, dosage of drugs). This review describes the options for estimating renal function that are currently in use, underlining limits and indications