Characterization of the competing role of surface-contact and shear stress on platelet activation in the setting of blood contacting devices.

Supraphysiological shear stress and surface-contact are recognized as driving mechanisms of platelet activation (PA) in blood contacting devices (BCDs). However, the competing role of these mechanisms in triggering thrombogenic events is poorly understood. Here, we characterized the dynamics of PA in response to the combined effect of shear stress and material exposure. Human platelets were stimulated with different levels of shear stress (500, 750, 1000 dynes/cm2) over a range of exposure times (10, 20, and 30 min) within capillary tubes made of various polymeric materials. Polyethylene (PE), polytetrafluoroethylene (PTFE), ethylene tetrafluoroethylene (ETFE), and polyether ether ketone (PEEK), used for BCDs fabrication, were investigated as compared to glass and thromboresistant Sigma™-coated glass. PA was quantified using the Platelet Activity State assay. Our results indicate that mechanical stimulation and polymer surface-contact both significantly contribute to PA. Notably, the contribution of the mechanical stimulus ranges between +36% and +43%, while that associated with polymer surface-contact ranges from +48% to +59%, depending on the exposure time. In more detail, our results indicate that: (i) PA increases with increasing shear stress magnitude; (ii) PA has a non-linear, time-dependent relationship to exposure time; (iii) PA is largely influenced by biomaterials, with PE and PEEK having respectively the lowest and highest prothrombotic potential; (iv) the effects of polymer surface-contact and shear stress are not correlated and can be studied separately. Our results suggest the importance of incorporating the evaluation of platelet activation driven by the combined effect of shear stress and polymer surface-contact for the comprehensive assessment, and eventually minimization, of BCDs thrombogenic potential.

A statistical assessment of micropollutants occurrence, time trend, fate and human health risk using left-censored water quality data.

In recent years, the presence of micropollutants in drinking water has become an issue of growing global concern. Due to their low concentrations, monitoring databases are usually rich in censored data (e.g. samples with concentrations reported below the limit of quantification, LOQ) which are typically eliminated or replaced with a value arbitrarily chosen between 0 and LOQ. These conventional methods have some limitations and can lead to erroneous conclusions on: presence of micropollutants in the source water, treatment efficiencies, produced water quality and associated human health risk. In this work, an advanced approach, based on Maximum Likelihood Estimation method for left-censored data (MLELC), was applied on monitoring data of 19 contaminants (metals, volatile organic compounds, pesticides and perfluorinated compounds) in 5362 groundwater (GW) and 12,344 drinking water (DW) samples, collected from 2012 to 2017 in 28 drinking water treatment plants in an urbanized area. This study demonstrates the benefits of MLELC method, especially for high percentages of censored data. Data are used to build statistical distributions which can be effectively used for several applications, such as the time trend evaluation of GW micropollutant concentrations and the estimation of treatment removal efficiency, highlighting the adequacy or the need for an upgrade. Moreover, the MLELC method has been applied to assess the human health risk associated with micropollutants, indicating the high discrepancy in the estimations obtained with conventional methods, whose results do not follow precautionary or sustainability criteria.

A Novel Multiparametric Score for the Detection and Grading of Prosthetic Mitral Valve Obstruction in Cases With Different Disc Motion Abnormalities.

Prosthetic mechanical valves are the elective choice in mitral valve (MV) replacement, because of their reliability and easiness of implantation. However, these prostheses can suffer from complications, the major one being prosthetic mitral valve thrombosis (PMVT). In these cases, transthoracic doppler echocardiogram (TDE) is the standard diagnostic workup for diagnosis of valve malfunction. The American Society of Echocardiography (ASE) indicates the possible TDE-derived indexes, which can help in identifying insurgence of MV replacement complications. Unfortunately, in some cases, it is not possible to detect PMVT based on these criteria. In these cases, we speak of Doppler silent thrombosis and only more accurate and invasive analyses, such as fluoroscopy, allow for a correct diagnosis. In this work, computational fluid dynamic models were implemented to simulate valve fluid dynamics in different clinical scenarios in order to improve the reliability of PMVT diagnosis based on TDE. In detail, seven mechanical valve configurations, associated to different potential thrombotic conditions (symmetric and asymmetric stenosis), were designed and tested using five pathologic transmitral velocity profile, extracted from real TDE images; to obtain the flow rate profiles, each TDE velocity profile was scaled to yield a mean flow rate (MFR) of 4, 5 and 6 L/min, respectively. As a result, 105 (7 × 5 × 3) synthetic cases, accounting for different velocity profiles, MFRs and valve configurations, were simulated. TDE-derived indexes were calculated according to the ASE guidelines that were extracted. Advanced statistical methods were applied to propose a new diagnostic algorithm for detecting PMVT. Our results showed that there isn't any significant difference between symmetric and asymmetric stenosis, probe location and flow rate waveform and confirmed that the single modality diagnostic is not able to predict thrombosis in a relevant number of cases, referable to mild and mild-severe stenosis cases. To overcome the problem, a novel multi-parametric discrete score based on the designed diagnostic algorithm was attained and tested; the percentage of stenosis (POS) was predicted with an accuracy rate of 90.5%. Even more interestingly, the error rate of 9.5% is related to four false positive cases corresponding to mild stenosis (POS = 15%) which were erroneously classified as mild-severe stenosis. No false negatives were obtained. Our results suggest that a reliable estimation must take into account the mean flow rate as well as the transmitral velocity profile in order to provide a correct diagnosis.