Publications by authors named "V S Ramos"

Statement Of Problem: The angled screw channel (ASC) design has been well accepted for implant prostheses. However, investigation into the behavior of the ASC connection is sparse.

Purpose: The purpose of this in vitro study was to assess the effect of cyclic loading on the internal connection of an ASC system compared with straight access systems by measuring reverse torque values (RTVs) and using microcomputed tomography (µCT) imaging.

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Increased antibody affinity over time after vaccination, known as affinity maturation, is a prototypical feature of immune responses. Recent studies have shown that a diverse collection of B cells, producing antibodies with a wide spectrum of different affinities, is selected into the plasma cell (PC) pathway. How affinity-permissive selection enables PC affinity maturation remains unknown.

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Increased antibody affinity over time after vaccination, known as affinity maturation, is a prototypical feature of immune responses. Recent studies have shown that a diverse collection of B cells, producing antibodies with a wide spectrum of different affinities, are selected into the plasma cell (PC) pathway. How affinity-permissive selection enables PC affinity maturation remains unknown.

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Objective: To verify the temporal trend of neonatal mortality in the health regions of Pernambuco between 2000 and 2020.

Method: A time-series ecological study was conducted, analyzing the total neonatal mortality rate and its early and late components. For regression analysis, Joinpoint Regression was applied, trends were classified, and annual and average percentage changes were calculated for the period, with a significance level of 95%.

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(1) Background: Quasi-experimental design has been widely used in causal inference for health policy impact evaluation. However, due to the non-randomized treatment used, there is great potential for bias in the assessment of the results, which can be reduced by using propensity score (PS) methods. In this context, this article aims to map the literature concerning the use of machine learning (ML) algorithms for propensity score estimation.

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