Analysis of gut microbiota in rheumatoid arthritis patients. Disease-related dysbiosis and modifications induced by etanercept

A certain number of studies were carried out to address the question of how dysbiosis could affect the onset and development of rheumatoid arthritis (RA), but little is known about the reciprocal influence between microbiota composition and immunosuppressive drugs, and how this interaction may have an impact on the clinical outcome. The aim of this study was to characterize the intestinal microbiota in a groups of RA patients treatment-naïve, under methotrexate, and/or etanercept (ETN). Correlations between the gut microbiota composition and validated immunological and clinical parameters of disease activity were also evaluated. In the current study, a 16S analysis was employed to explore the gut microbiota of 42 patients affected by RA and 10 healthy controls. Disease activity score on 28 joints (DAS-28), erythrocyte sedimentation rate, C-reactive protein, rheumatoid factor, anti-cyclic citrullinated peptides, and dietary and smoking habits were assessed. The composition of the gut microbiota in RA patients free of therapy is characterized by several abnormalities compared to healthy controls. Gut dysbiosis in RA patients is associated with different serological and clinical parameters; in particular, the phylum of Euryarchaeota was directly correlated to DAS and emerged as an independent risk factor. Patients under treatment with ETN present a partial restoration of a beneficial microbiota. The results of our study confirm that gut dysbiosis is a hallmark of the disease, and shows, for the first time, that the anti-tumor necrosis factor alpha (TNF-α) ETN is able to modify microbial communities, at least partially restoring a beneficial microbiota

Dopamine neuronal loss contributes to memory and reward dysfunction in a model of Alzheimer's disease

Alterations of the dopaminergic (DAergic) system are frequently reported in Alzheimer’s disease (AD) patients and are commonly linked to cognitive and non-cognitive symptoms. However, the cause of DAergic system dysfunction in AD remains to be elucidated. We investigated alterations of the midbrain DAergic system in the Tg2576 mouse model of AD, overexpressing a mutated human amyloid precursor protein (APPswe). Here, we found an age-dependent DAergic neuron loss in the ventral tegmental area (VTA) at pre-plaque stages, although substantia nigra pars compacta (SNpc) DAergic neurons were intact. The selective VTA DAergic neuron degeneration results in lower DA outflow in the hippocampus and nucleus accumbens (NAc) shell. The progression of DAergic cell death correlates with impairments in CA1 synaptic plasticity, memory performance and food reward processing. We conclude that in this mouse model of AD, degeneration of VTA DAergic neurons at pre-plaque stages contributes to memory deficits and dysfunction of reward processing

Phase I dose-escalation trial of the oral AKT inhibitor uprosertib in combination with the oral MEK1/MEK2 inhibitor trametinib in patients with solid tumors.

PurposeThis study aimed to determine the safety, tolerability, and recommended phase II doses of trametinib plus uprosertib (GSK2141795) in patients with solid tumors likely to be sensitive to MEK and/or AKT inhibition.MethodsThis was a phase I, open-label, dose-escalation, and dose-expansion study in patients with triple-negative breast cancer or BRAF-wild type advanced melanoma. The primary outcome of the expansion study was investigator-assessed response. Among 126 enrolled patients, 63 received continuous oral daily dosing of trametinib and uprosertib, 29 received various alternative dosing schedules, and 34 were enrolled into expansion cohorts. Doses tested in the expansion cohort were trametinib 1.5 mg once daily (QD) + uprosertib 50 mg QD.ResultsAdverse events (AEs) were consistent with those reported in monotherapy studies but occurred at lower doses and with greater severity. Diarrhea was the most common dose-limiting toxicity; diarrhea and rash were particularly difficult to tolerate. Overall, 59% and 6% of patients reported AEs with a maximum severity of grade 3 and 4, respectively. Poor tolerability prevented adequate delivery of uprosertib with trametinib at a concentration predicted to have clinical activity. The study was terminated early based on futility in the continuous-dosing expansion cohorts and a lack of pharmacological or therapeutic advantage with intermittent dosing. The objective response rate was < 5% (1 complete response, 5 partial responses).ConclusionsContinuous and intermittent dosing of trametinib in combination with uprosertib was not tolerated, and minimal clinical activity was observed in all schedules tested

Deep graph neural network for video-based facial pain expression assessment

Automatic pain assessment can be defined as the set of computer-aided technologies allowing to recognise pain status. Reliable and valid methods for pain assessment are of primary importance for the objective and continuous monitoring of pain in people who are unable to communicate verbally. In the present work, we propose a novel approach for the recognition of pain from the analysis of facial expression. More specifically, we evaluate the effectiveness of Graph Neural Network (GNN) architectures exploiting the inherent graph structure of a set of fiducial points automatically tracked on subject faces. Experiments carried over on the publicly available dataset BioVid, show how the proposed method reaches higher levels of accuracy when compared with baseline models on acted pain, while outmatching state of the art approaches on spontaneous pain

Essential versus accessory aspects of cell death: recommendations of the NCCD 2015

Cells exposed to extreme physicochemical or mechanical stimuli die in an uncontrollable manner, as a result of their immediate structural breakdown. Such an unavoidable variant of cellular demise is generally referred to as ‘accidental cell death’ (ACD). In most settings, however, cell death is initiated by a genetically encoded apparatus, correlating with the fact that its course can be altered by pharmacologic or genetic interventions. ‘Regulated cell death’ (RCD) can occur as part of physiologic programs or can be activated once adaptive responses to perturbations of the extracellular or intracellular microenvironment fail. The biochemical phenomena that accompany RCD may be harnessed to classify it into a few subtypes, which often (but not always) exhibit stereotyped morphologic features. Nonetheless, efficiently inhibiting the processes that are commonly thought to cause RCD, such as the activation of executioner caspases in the course of apoptosis, does not exert true cytoprotective effects in the mammalian system, but simply alters the kinetics of cellular demise as it shifts its morphologic and biochemical correlates. Conversely, bona fide cytoprotection can be achieved by inhibiting the transduction of lethal signals in the early phases of the process, when adaptive responses are still operational. Thus, the mechanisms that truly execute RCD may be less understood, less inhibitable and perhaps more homogeneous than previously thought. Here, the Nomenclature Committee on Cell Death formulates a set of recommendations to help scientists and researchers to discriminate between essential and accessory aspects of cell death

Trends, Applications, and Challenges in Human Attention Modelling

Human attention modelling has proven, in recent years, to be particularly useful not only for understanding the cognitive processes underlying visual exploration, but also for providing support to artificial intelligence models that aim to solve problems in various domains, including image and video processing, vision-and-language applications, and language modelling. This survey offers a reasoned overview of recent efforts to integrate human attention mechanisms into contemporary deep learning models and discusses future research directions and challenges. For a comprehensive overview of the ongoing research, refer to our dedicated repository available at https://github.com/aimagelab/awesome-human-visual-attention

On Using rPPG Signals for DeepFake Detection: A Cautionary Note

An experimental analysis is proposed concerning the use of physiological signals, specifically remote Photoplethysmography (rPPG), as a potential means for detecting Deepfakes (DF). The study investigates the effects of different variables, such as video compression and face swap quality, on rPPG information extracted from both original and forged videos. The experiments aim to understand the impact of face forgery procedures on remotely-estimated cardiac information, how this effect interacts with other variables, and how rPPG-based DF detection accuracy is affected by these quantities. Preliminary results suggest that cardiac information in some cases (e.g. uncompressed videos) may have a limited role in discriminating real videos from forged ones, but the effects of other physiological signals cannot be discounted. Surprisingly, heart rate related frequencies appear to deliver a significant contribution to the DF detection task in compressed videos