Investigating the flow dynamics in the obstructed and stented ureter by means of a biomimetic artificial model.

Double-J stenting is the most common clinical method employed to restore the upper urinary tract drainage, in the presence of a ureteric obstruction. After implant, stents provide an immediate pain relief by decreasing the pressure in the renal pelvis (P). However, their long-term usage can cause infections and encrustations, due to bacterial colonization and crystal deposition on the stent surface, respectively. The performance of double-J stents - and in general of all ureteric stents - is thought to depend significantly on urine flow field within the stented ureter. However very little fundamental research about the role played by fluid dynamic parameters on stent functionality has been conducted so far. These parameters are often difficult to assess in-vivo, requiring the implementation of laborious and expensive experimental protocols. The aim of the present work was therefore to develop an artificial model of the ureter (i.e. ureter model, UM) to mimic the fluid dynamic environment in a stented ureter. The UM was designed to reflect the geometry of pig ureters, and to investigate the values of fluid dynamic viscosity (?), volumetric flow rate (Q) and severity of ureteric obstruction (OB%) which may cause critical pressures in the renal pelvis. The distributed obstruction derived by the sole stent insertion was also quantified. In addition, flow visualisation experiments and computational simulations were performed in order to further characterise the flow field in the UM. Unique characteristics of the flow dynamics in the obstructed and stented ureter have been revealed with using the developed UM

Investigating the flow dynamics in the obstructed and stented ureter by means of a biomimetic artificial model

Double-J stenting is the most common clinical method employed to restore the upper urinary tract drainage, in the presence of a ureteric obstruction. After implant, stents provide an immediate pain relief by decreasing the pressure in the renal pelvis (P). However, their long-term usage can cause infections and encrustations, due to bacterial colonization and crystal deposition on the stent surface, respectively. The performance of double-J stents - and in general of all ureteric stents - is thought to depend significantly on urine flow field within the stented ureter. However very little fundamental research about the role played by fluid dynamic parameters on stent functionality has been conducted so far. These parameters are often difficult to assess in-vivo, requiring the implementation of laborious and expensive experimental protocols. The aim of the present work was therefore to develop an artificial model of the ureter (i.e. ureter model, UM) to mimic the fluid dynamic environment in a stented ureter. The UM was designed to reflect the geometry of pig ureters, and to investigate the values of fluid dynamic viscosity (μ), volumetric flow rate (Q ) and severity of ureteric obstruction (OB%) which may cause critical pressures in the renal pelvis. The distributed obstruction derived by the sole stent insertion was also quantified. In addition, flow visualisation experiments and computational simulations were performed in order to further characterise the flow field in the UM. Unique characteristics of the flow dynamics in the obstructed and stented ureter have been revealed with using the developed UM

Probabilistic Forecasting for Oil Producing Wells Using Seq2seq Augmented Model

Time series forecasting is a challenging problem in the field of data mining. Deterministic forecasting has shown limitations in the field. Therefore, researchers are now more inclined towards probabilistic forecasting, which has shown a clear advantage by providing more reliable models. In this paper, we utilize seq2seq machine learning models in order to estimate prediction intervals (PIs) for a large oil production dataset. To evaluate the proposed models, Prediction Interval Coverage Probability (PICP), Prediction Interval Normalized Average Width (PINAW), and Coverage Width-based Criterion (CWC) metrics are used. Our results show that the proposed model can reliably estimate PIs for production forecasting

An artificial model for studying fluid dynamics in the obstructed and stented ureter

Fluid dynamics in the obstructed and stented ureter represents a non-trivial subject of investigation since, after stent placement, the urine can flow either through the stent lumen or in the extra-luminal space located between the stent wall and the ureteric inner wall. Fluid dynamic investigations can help understanding the phenomena behind stent failure (e.g. stent occlusions due to bacterial colonization and encrustations), which may cause kidney damage due to the associated high pressures generated in the renal pelvis. In this work a microfluidic-based transparent device (ureter model, UM) has been developed to simulate the fluid dynamic environment in a stented ureter. UM geometry has been designed from measurements on pig ureters. Pressure in the renal pelvis compartment has been measured against three variables: fluid viscosity (?), volumetric flow rate (Q) and level of obstruction (OB%). The measurements allowed a quantification of the critical combination of ?, Q and OB% values which may lead to critical pressure levels in the kidney. Moreover, an example showing the possibility of applying particle image velocimetry (PIV) technology to the developed microfluidic device is provided

Cancer as a risk factor for urinary tract calculi: a retrospective cohort study using 'The Health Improvement Network' : Cancer and urinary tract calculi.

PURPOSE Urolithiasis is a common condition that poses significant morbidity to patients. There are similarities in the development of certain cancers and urinary tract calculi (UTC), however, little is known about their temporal relationship. This study aims to identify if cancer is a risk factor for the development of UTC. METHODS A population-based retrospective cohort study was conducted for the period 1st January 1990 to 1st May 2016. 124,901 exposed patients identified using clinical codes with newly diagnosed cancer were matched to 476,203 unexposed controls by age, gender, BMI, and general practice. The main outcome measure was the risk of developing UTC described by hazard ratios. RESULTS There were 512 incident UTC events in the cancer group compared to 1787 in the unexposed controls. This translated to an adjusted hazard ratio of 1.26 (95% CI 1.14-1.39; p < 0.001). A sub-analysis assessing cancer-specific effects demonstrated increased risks for 10 out of 12 common cancers, most significantly in bladder, colorectal and prostate cancer. CONCLUSION This study demonstrated a 26% increased risk of UTC in cancer patients suggesting wider recognition of this risk amongst clinicians could improve diagnosis and prevention of UTC, as well as encourage further research exploring this association

Renal pelvic pressure <i>vs</i> urine properties and severity of obstruction.

<p>Renal pelvic pressure (<i>P</i>) in the ureteric model increases linearly with A) flow rate (<i>Q</i> in ml/min) and B) severity of obstruction in the upper UM (OB%, calculated using Eq. 1). Fixed values of OB% = 100 and <i>Q</i> = 20 ml/min were considered for the experimental data reported in A) and B), respectively. The fluid dynamic viscosity is equal to 1 cP. The equation of the least square regression line, the R-squared values and error bars are reported (N = 3). The slope of regression line in panel A represents the hydraulic resistance of the system. The horizontal red line indicates the critical value of renal pelvic pressure (<i>P</i> = 20 cmH₂O).</p

Severity of UM obstruction induced solely by stent insertion.

<p>Severity of obstruction (OB_i%) calculated along the longitudinal coordinate of the UM (<i>D_0–15</i>, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0087433#pone-0087433-g004" target="_blank">Figure 4</a> for reference) introduced by the double-J stent only (absence of plastic sphere). For the calculations, Eq. 4 was considered. UPJ and VUJ indicate the urteropelvic and vesicureteric junctions, respectively.</p

Fabrication of the ureter model.

<p>A) Phases of ureter model (UM) fabrication. The male mold (MM) was inserted coaxially into a plastic hallow cylinder. A mixture of PDMS and curing agent was poured into the cylinder and cured at 80°C for 1 hr. The MM was then extracted from the cylinder and the resulting ureter model was further cured at 100°C for 30 min. B) Final UM with double-J stent (blue colour) placed inside. C) Particular of the terminal part of UM, in proximity to the vesico-ureter junction (VUJ). Note the presence of side holes and a curling “J” end of the stent.</p

Schematic of the computational domain and boundary conditions.

<p>A) Schematic representation of the two-dimensional computational domain. Colours correspond to different boundary conditions: red wall boundary; green outflow; light blue velocity inlet. B) Summary of the geometrical characteristics of the computational domain, and boundary conditions applied to each individual edge.</p