Future research directions to improve fistula maturation and reduce access failure

With the increasing prevalence of end stage renal disease there is a growing need for hemodialysis. Arteriovenous fistulae (AVF) are the preferred type of vascular access for hemodialysis but maturation and failure continue to present significant barriers to successful fistula use. AVF maturation integrates outward remodeling with vessel wall thickening in response to drastic hemodynamic changes, in the setting of uremia, systemic inflammation, oxidative stress and preexistent vascular pathology. AVF can fail due to both failure to mature adequately to support hemodialysis, as well as development of neointimal hyperplasia (NIH) that narrows the AVF lumen, typically near the fistula anastomosis. Failure due to NIH involves vascular cell activation and migration and extracellular matrix remodeling with complex interactions of growth factors, adhesion molecules, inflammatory mediators, and chemokines, all of which result in maladaptive remodeling. Different strategies have been proposed to prevent and treat AVF failure, based on current understanding of the modes and pathology of access failure; these approaches range from appropriate patient selection and use of alternative surgical strategies for fistula creation, to the use of novel interventional techniques or drugs to treat failing fistulae. Effective treatments to prevent or treat AVF failure requires a multidisciplinary approach involving nephrologists, vascular surgeons and interventional radiologists, allowing careful patient selection and the use of tailored systemic or localized interventions to improve patient-specific outcomes. This review provides contemporary information on the underlying mechanisms of AVF maturation and failure and discusses the broad spectrum of options that can be tailored for specific therapy

The Noncommutative Harmonic Oscillator based in Simplectic Representation of Galilei Group

In this work we study symplectic unitary representations for the Galilei group. As a consequence the Schr\"odinger equation is derived in phase space. The formalism is based on the non-commutative structure of the star-product, and using the group theory approach as a guide a physical consistent theory in phase space is constructed. The state is described by a quasi-probability amplitude that is in association with the Wigner function. The 3D harmonic oscillator and the noncommutative oscillator are studied in phase space as an application, and the Wigner function associated to both cases are determined.Comment: 7 pages,no figure

Ramucirumab in combination with pembrolizumab in treatment-naïve advanced gastric or gej adenocarcinoma: Safety and antitumor activity from the phase 1a/b jvdf trial

Ramucirumab (anti-VEGFR2) plus pembrolizumab (anti-PD1) demonstrated promising antitumor activity and tolerability among patients with previously treated advanced cancers, supporting growing evidence that combination therapies modulating the tumor microenvironment may expand the spectrum of patients who respond to checkpoint inhibitors. Here we present the results of this combination in first-line patients with metastatic G/GEJ cancer. Twenty-eight patients (≥18 years) with no prior systemic chemotherapy in the advanced/metastatic setting received ramucirumab (8 mg/kg days 1 and 8) plus pembrolizumab (200 mg day 1) every 3 weeks as part of JVDF phase 1a/b study. The primary endpoint was safety. Secondary endpoints included progression-free survival (PFS), objective response rate (ORR), and overall survival (OS). Tumors were PD-L1-positive (combined positive score ≥ 1) in 19 and-negative in 6 patients. Eighteen patients experienced grade 3 treatment-related adverse events, most commonly hypertension (14%) and elevated alanine/aspartate aminotransferase (11% each), with no grade 4 or 5 reported. The ORR was 25% (PD-L1-positive, 32%; PD-L1-negative, 17%) with duration of response not reached. PFS was 5.6 months (PD-L1-positive, 8.6 months; PD-L1-negative, 4.3 months), and OS 14.6 months (PD-L1-positive, 17.3 months; PD-L1-negative, 11.3 months). Acknowledging study design limitations, ramucirumab plus pembrolizumab had encouraging durable clinical activity with no unexpected toxicities in treatment-naïve biomarker-unselected metastatic G/GEJ cancer, and improved outcomes in patients with PD-L1-positive tumors

Predicting progression of mild cognitive impairment to dementia using neuropsychological data: a supervised learning approach using time windows

Background: Predicting progression from a stage of Mild Cognitive Impairment to dementia is a major pursuit in current research. It is broadly accepted that cognition declines with a continuum between MCI and dementia. As such, cohorts of MCI patients are usually heterogeneous, containing patients at different stages of the neurodegenerative process. This hampers the prognostic task. Nevertheless, when learning prognostic models, most studies use the entire cohort of MCI patients regardless of their disease stages. In this paper, we propose a Time Windows approach to predict conversion to dementia, learning with patients stratified using time windows, thus fine-tuning the prognosis regarding the time to conversion. Methods: In the proposed Time Windows approach, we grouped patients based on the clinical information of whether they converted (converter MCI) or remained MCI (stable MCI) within a specific time window. We tested time windows of 2, 3, 4 and 5 years. We developed a prognostic model for each time window using clinical and neuropsychological data and compared this approach with the commonly used in the literature, where all patients are used to learn the models, named as First Last approach. This enables to move from the traditional question "Will a MCI patient convert to dementia somewhere in the future" to the question "Will a MCI patient convert to dementia in a specific time window". Results: The proposed Time Windows approach outperformed the First Last approach. The results showed that we can predict conversion to dementia as early as 5 years before the event with an AUC of 0.88 in the cross-validation set and 0.76 in an independent validation set. Conclusions: Prognostic models using time windows have higher performance when predicting progression from MCI to dementia, when compared to the prognostic approach commonly used in the literature. Furthermore, the proposed Time Windows approach is more relevant from a clinical point of view, predicting conversion within a temporal interval rather than sometime in the future and allowing clinicians to timely adjust treatments and clinical appointments.FCT under the Neuroclinomics2 project [PTDC/EEI-SII/1937/2014, SFRH/BD/95846/2013]; INESC-ID plurianual [UID/CEC/50021/2013]; LASIGE Research Unit [UID/CEC/00408/2013

Covid-19 Dynamic Monitoring and Real-Time Spatio-Temporal Forecasting

Background: Periodically, humanity is often faced with new and emerging viruses that can be a significant global threat. It has already been over a century post—the Spanish Flu pandemic, and we are witnessing a new type of coronavirus, the SARS-CoV-2, which is responsible for Covid-19. It emerged from the city of Wuhan (China) in December 2019, and within a few months, the virus propagated itself globally now resulting more than 50 million cases with over 1 million deaths. The high infection rates coupled with dynamic population movement demands for tools, especially within a Brazilian context, that will support health managers to develop policies for controlling and combating the new virus. / Methods: In this work, we propose a tool for real-time spatio-temporal analysis using a machine learning approach. The COVID-SGIS system brings together routinely collected health data on Covid-19 distributed across public health systems in Brazil, as well as taking to under consideration the geographic and time-dependent features of Covid-19 so as to make spatio-temporal predictions. The data are sub-divided by federative unit and municipality. In our case study, we made spatio-temporal predictions of the distribution of cases and deaths in Brazil and in each federative unit. Four regression methods were investigated: linear regression, support vector machines (polynomial kernels and RBF), multilayer perceptrons, and random forests. We use the percentage RMSE and the correlation coefficient as quality metrics. / Results: For qualitative evaluation, we made spatio-temporal predictions for the period from 25 to 27 May 2020. Considering qualitatively and quantitatively the case of the State of Pernambuco and Brazil as a whole, linear regression presented the best prediction results (thematic maps with good data distribution, correlation coefficient >0.99 and RMSE (%) <4% for Pernambuco and around 5% for Brazil) with low training time: [0.00; 0.04 ms], CI 95%. / Conclusion: Spatio-temporal analysis provided a broader assessment of those in the regions where the accumulated confirmed cases of Covid-19 were concentrated. It was possible to differentiate in the thematic maps the regions with the highest concentration of cases from the regions with low concentration and regions in the transition range. This approach is fundamental to support health managers and epidemiologists to elaborate policies and plans to control the Covid-19 pandemics

The submarine volcano eruption at the island of El Hierro: physical-chemical perturbation and biological response

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Association between IgM Anti-Herpes Simplex Virus and Plasma Amyloid-Beta Levels

OBJECTIVE: Herpes simplex virus (HSV) reactivation has been identified as a possible risk factor for Alzheimer's disease (AD) and plasma amyloid-beta (Aβ) levels might be considered as possible biomarkers of the risk of AD. The aim of our study was to investigate the association between anti-HSV antibodies and plasma Aβ levels. METHODS: The study sample consisted of 1222 subjects (73.9 y in mean) from the Three-City cohort. IgM and IgG anti-HSV antibodies were quantified using an ELISA kit, and plasma levels of Aβ(1-40) and Aβ(1-42) were measured using an xMAP-based assay technology. Cross-sectional analyses of the associations between anti-HSV antibodies and plasma Aβ levels were performed by multi-linear regression. RESULTS: After adjustment for study center, age, sex, education, and apolipoprotein E-e4 polymorphism, plasma Aβ(1-42) and Aβ(1-40) levels were specifically inversely associated with anti-HSV IgM levels (β = -20.7, P=0.001 and β = -92.4, P=0.007, respectively). In a sub-sample with information on CLU- and CR1-linked SNPs genotyping (n=754), additional adjustment for CR1 or CLU markers did not modify these associations (adjustment for CR1 rs6656401, β = -25.6, P=0.002 for Aβ(1-42) and β = -132.7, P=0.002 for Aβ(1-40;) adjustment for CLU rs2279590, β = -25.6, P=0.002 for Aβ(1-42) and β = -134.8, P=0.002 for Aβ(1-40)). No association between the plasma Aβ(1-42)-to-Aβ(1-40) ratio and anti-HSV IgM or IgG were evidenced. CONCLUSION: High anti-HSV IgM levels, markers of HSV reactivation, are associated with lower plasma Aβ(1-40) and Aβ(1-42) levels, which suggest a possible involvement of the virus in the alterations of the APP processing and potentially in the pathogenesis of AD in human