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Timing of initiation of oral anticoagulants in patients with acute ischemic stroke and atrial fibrillation comparing posterior and anterior circulation strokes

Background: The aim of this study in patients with acute posterior ischemic stroke (PS) and atrial fibrillation (AF) were to evaluate the risks of recurrent ischemic event and severe bleeding and these risks in relation with oral anticoagulant therapy (OAT) and its timing. Methods: Patients with PS were prospectively included; the outcome events of these patients were compared with those of patients with anterior stroke (AS) which were taken from previous registries. The primary outcome was the composite of: stroke recurrence, TIA, symptomatic systemic embolism, symptomatic cerebral bleeding and major extracranial bleeding occurring within 90 days from acute stroke. Results: A total of 2,470 patients were available for the analysis: 473 (19.1%) with PS and 1,997 (80.9%) AS. Over 90 days, 213 (8.6%) primary outcome events were recorded: 175 (8.7%) in patients with AS and 38 (8.0%) in those with PS. In patients who initiated OAT within 2 days, the primary outcome occurred in 5 out of 95 patients (5.3%) with PS compared to 21 out of 373 patients (4.3%) with AS (OR 1.07; 95% CI 0.39-2.94). In patients who initiated OAT between days 3 and 7, the primary outcome occurred in 3 out of 103 patients (2.9%) with PS compared to 26 out of 490 patients (5.3%) with AS (OR 0.54; 95% CI 0.16-1.80). Conclusions: Patients with posterior or anterior stroke and AF appear to have similar risks of ischemic or hemorrhagic events at 90 days with no difference concerning the timing of initiation of OAT

Probabilistic data association Kalman filter for multi-channel phase unwrapping

Within this manuscript a novel Multi-channel InSAR phase unwrapping method is proposed. The approach implements an Extended Kalman Filter for jointly unwrap the phase and regularize the result. The novelty of the methodology consists in the probabilistic data association step that has been implemented in order to improve the robustness of EKF for PhU. Encouraging results on simulated dataset are reported

Constipation distinguishes different clinical-biochemical patterns in de novo Parkinson's disease

Introduction: Prodromal constipation (PC) at Parkinson's disease (PD) onset may mark a distinct neurodegen-erative trajectory; accordingly, presenting phenotype, biochemical signature, and progression of PD patients with PC (PD + PC) might differ from those without (PDwoPC). We compared the clinical-biochemical profile of de novo PD patients with and without PC, and the respective mid-term progression, to establish the grouping effect of PC. Methods: Motor and non-motor scores were collected at diagnosis in n = 57 PD + PC patients and n = 73 PDwoPC. Paired CSF biomarkers (alpha-synuclein, amyloid and tau peptides, lactate, CSF/serum albumin ratio or AR) were assessed into a smaller sample and n = 46 controls. Clinical progression was estimated as Hoehn and Yahr stage (HY) and levodopa equivalent daily dose (LEDD) change 2.06 +/- 1.35 years after diagnosis. Results: At onset, PD + PC patients had higher HY and MDS-UPDRS-part III scores, and higher CSF AR. PDwoPC had higher Non-Motor Symptoms Scale domain-2 score, and lower CSF alpha-synuclein level. At follow-up, PD + PC had greater LEDD. Conclusions: PC identifies a group of de novo patients with more severe motor impairment, possible blood brain barrier disruption, and greater dopaminergic requirement at mid-term; conversely, de novo PDwoPC patients had prominent fatigue, and pronounced central synucleinopathy

Role of cardiac magnetic resonance in the differential diagnosis between arrhythmogenic cardiomyopathy with left ventricular involvement and previous infectious myocarditis

Aims: Arrhythmogenic cardiomyopathy with left ventricular involvement (ACM-LV), particularly in case of isolated left ventricular involvement (i.e. left dominant arrhythmogenic cardiomyopathy, LDAC) and previous infectious myocarditis (pIM) may have overlapping clinical and cardiac magnetic resonance (CMR) features. To date, there are no validated CMR criteria for the differential diagnosis between these conditions. The present study aimed to identify CMR characteristics to distinguish ACM-LV from pIM. Methods and results: This observational, retrospective, single-centre study included 30 pIM patients and 30 ACM-LV patients. In ACM-LV patients CMR was performed at diagnosis; in patients with pIM, CMR was performed six months after acute infection. CMR analysis included quantitative assessment of left ventricle (LV) volumes, systolic function and wall thicknesses, qualitative and quantitative assessment of late gadolinium enhancement (LGE) sequences. Compared with pIM, ACM-LV patients showed slightly larger LV volumes, more frequent regional wall motion anomalies and reduced wall thicknesses. ACM-LV patients had higher amounts of LV LGE and extension. Notably, the LDAC subgroup had the highest amount of LV LGE. LV LGE amount > 15 g and a LV LGE percentage > 30% of LV mass discriminated ACM-LV from pIM with a 100% specificity. LGE segmental distribution was superimposable among the groups, except for septal segments that were more frequently involved in ACM-LV and LDAC patients. Conclusions: A great extension of LV LGE (a cut-off of LGE >15 g and a percentage above 30% of LV LGE in relation to total myocardial mass) discriminates ACM-LV from pIM with extremely high specificity

MUC1 Expression Affects the Immunoflogosis in Renal Cell Carcinoma Microenvironment through Complement System Activation and Immune Infiltrate Modulation

Mucin1 (MUC1), a glycoprotein associated with an aggressive cancer phenotype and chemoresistance, is aberrantly overexpressed in a subset of clear cell renal cell carcinoma (ccRCC). Recent studies suggest that MUC1 plays a role in modulating cancer cell metabolism, but its role in regulating immunoflogosis in the tumor microenvironment remains poorly understood. In a previous study, we showed that pentraxin-3 (PTX3) can affect the immunoflogosis in the ccRCC microenvironment by activating the classical pathway of the complement system (C1q) and releasing proangiogenic factors (C3a, C5a). In this scenario, we evaluated the PTX3 expression and analyzed the potential role of complement system activation on tumor site and immune microenvironment modulation, stratifying samples in tumors with high (MUC1H) versus tumors with low MUC1 expression (MUC1L). We found that PTX3 tissue expression was significantly higher in MUC1H ccRCC. In addition, C1q deposition and the expressions of CD59, C3aR, and C5aR were extensively present in MUC1H ccRCC tissue samples and colocalized with PTX3. Finally, MUC1 expression was associated with an increased number of infiltrating mast cells, M2-macrophage, and IDO1+ cells, and a reduced number of CD8+ T cells. Taken together, our results suggest that expression of MUC1 can modulate the immunoflogosis in the ccRCC microenvironment by activating the classical pathway of the complement system and regulating the immune infiltrate, promoting an immune-silent microenvironment

Olfactory Neuron Prokineticin-2 as a Potential Target in Parkinson's Disease

Objective The objective of this study was to outline the dynamics of prokineticin-2 pathway in relation to clinical-pathological features of Parkinson's disease by examining olfactory neurons of patients. Methods Thirty-eight patients (26 de novo, newly diagnosed) and 31 sex/age-matched healthy controls underwent noninvasive mucosa brushing for olfactory neurons collection, and standard clinical assessment. Gene expression levels of prokineticin-2, prokineticin-2 receptors type 1 and 2, and prokineticin-2-long peptide were measured in olfactory neurons by real-time polymerase chain reaction (PCR); moreover, the prokineticin-2 protein and alpha-synuclein species (total and oligomeric) were quantified by immunofluorescence staining. Results Prokineticin-2 expression was significantly increased in Parkinson's disease. De novo patients had higher prokineticin-2 levels, directly correlated with Movement Disorder Society-Sponsored Revision of the Unified Parkinson Disease Rating Scale (MDS-UPDRS) part III motor score. In addition, oligomeric alpha-synuclein was higher in Parkinson's disease and directly correlated with prokineticin-2 protein levels. Total alpha-synuclein did not differ between patients and controls. Interpretation Prokineticin-2 is a chemokine showing neuroprotective effects in experimental models of Parkinson's disease, but translational proof of its role in patients is still lacking. Here, we used olfactory neurons as the ideal tissue to analyze molecular stages of neurodegeneration in vivo, providing unprecedented evidence that the prokineticin-2 pathway is activated in patients with Parkinson's disease. Specifically, prokineticin-2 expression in olfactory neurons was higher at early disease stages, proportional to motor severity, and associated with oligomeric alpha-synuclein accumulation. These data, consistently with preclinical findings, support prokineticin-2 as a candidate target in Parkinson's disease, and validate reliability of olfactory neurons to reflect pathological changes of the disease. ANN NEUROL 202

Predictive Machine Learning Models and Survival Analysis for COVID-19 Prognosis Based on Hematochemical Parameters

The coronavirus disease 2019 (COVID-19) pandemic has affected hundreds of millions of individuals and caused millions of deaths worldwide. Predicting the clinical course of the disease is of pivotal importance to manage patients. Several studies have found hematochemical alterations in COVID-19 patients, such as inflammatory markers. We retrospectively analyzed the anamnestic data and laboratory parameters of 303 patients diagnosed with COVID-19 who were admitted to the Polyclinic Hospital of Bari during the first phase of the COVID-19 global pandemic. After the pre-processing phase, we performed a survival analysis with Kaplan–Meier curves and Cox Regression, with the aim to discover the most unfavorable predictors. The target outcomes were mortality or admission to the intensive care unit (ICU). Different machine learning models were also compared to realize a robust classifier relying on a low number of strongly significant factors to estimate the risk of death or admission to ICU. From the survival analysis, it emerged that the most significant laboratory parameters for both outcomes was C-reactive protein min; HR=17.963 (95% CI 6.548–49.277, p < 0.001) for death, HR=1.789 (95% CI 1.000–3.200, p = 0.050) for admission to ICU. The second most important parameter was Erythrocytes max; HR=1.765 (95% CI 1.141–2.729, p < 0.05) for death, HR=1.481 (95% CI 0.895–2.452, p = 0.127) for admission to ICU. The best model for predicting the risk of death was the decision tree, which resulted in ROC-AUC of 89.66%, whereas the best model for predicting the admission to ICU was support vector machine, which had ROC-AUC of 95.07%. The hematochemical predictors identified in this study can be utilized as a strong prognostic signature to characterize the severity of the disease in COVID-19 patients