Background: Elastomeric pumps (elastic balls into which analgesics or antibiotics can be inserted) push medicines through a catheter to a nerve or blood vessel. Since elastomeric pumps are small and need no power sour...Background: Elastomeric pumps (elastic balls into which analgesics or antibiotics can be inserted) push medicines through a catheter to a nerve or blood vessel. Since elastomeric pumps are small and need no power source, they fit easily into a pocket during infusion, allowing patient mobility. Elastomeric pumps are widely used and widely studied experimentally, but they have well-known problems, such as maintaining reliable flow rates and avoiding toxicity or other peak-and-trough effects. Objectives: Our research objective is to develop a realistic theoretical model of an elastomeric pump, analyze its flow rates, determine its toxicity conditions, and otherwise improve its operation. We believe this is the first such theoretical model of an elastomeric pump consisting of an elastic, medicine-filled ball attached to a horizontal catheter. Method: Our method is to model the system as a quasi-Poiseuille flow driven by the pressure drop generated by the elastic sphere. We construct an engineering model of the pressure exerted by an elastic sphere and match it to a solution of the one-dimensional radial Navier-Stokes equation that describes flow through a horizontal, cylindrical tube. Results: Our results are that the model accurately reproduces flow rates obtained in clinical studies. We also discover that the flow rate has an unavoidable maximum, which we call the “toxicity bump”, when the radius of the sphere approaches its terminal, unstretched value—an effect that has been observed experimentally. Conclusions: We conclude that by choosing the properties of an elastomeric pump, the toxicity bump can be restricted to less than 10% of the earlier, relatively constant flow rate. Our model also produces a relation between the length of time that the analgesic fluid infuses and the physical properties of the fluid, of the elastomeric sphere and the tube, and of the blood vessel into which the analgesic infuses. From these, we conclude that elastomeric pumps can be designed, using our simple model, to control infusion times while avoiding toxicity effects.展开更多
The application of Raman spectroscopic techniques combined with multivariate chemometrics signal processing promise new means for the rapid multidimensional analysis of metabolites non-destructively, with little or no...The application of Raman spectroscopic techniques combined with multivariate chemometrics signal processing promise new means for the rapid multidimensional analysis of metabolites non-destructively, with little or no sample preparation and little sensitivity to water. However, Rayleigh scattering, fluorescence and uncontrolled variance present substantial challenges for the accurate quantitative analysis of metabolites at physiological levels in bio- logically varying samples. Effective strategies include the application of chemometrics pretreatments for reducing Raman spectral interference. However, the arbitrary application of individual or combined pretreatment procedures can significantly alter the outcome of a measurement, thereby complicating spectral analysis. This paper evaluates and compares six signal pretreatment methods for correcting the baseline variances, together with three variable se- lection methods for eliminating uninformative variables, all within the context of multivariate calibration models based on partial least squares (PLS) regression. Raman spectra of 90 artificial bio-fluid samples with eight urine metabolites at near-physiological concentrations were used to test these models. The combination of multiplicative scatter correction (MSC), continuous wavelet transform (CWT), randomization test (RT) and PLS modeling pre- sented the best performance for all the metabolites. The correlation coefficient (R) between predicted and prepared concentration reached as high as 0.96.展开更多
文摘Background: Elastomeric pumps (elastic balls into which analgesics or antibiotics can be inserted) push medicines through a catheter to a nerve or blood vessel. Since elastomeric pumps are small and need no power source, they fit easily into a pocket during infusion, allowing patient mobility. Elastomeric pumps are widely used and widely studied experimentally, but they have well-known problems, such as maintaining reliable flow rates and avoiding toxicity or other peak-and-trough effects. Objectives: Our research objective is to develop a realistic theoretical model of an elastomeric pump, analyze its flow rates, determine its toxicity conditions, and otherwise improve its operation. We believe this is the first such theoretical model of an elastomeric pump consisting of an elastic, medicine-filled ball attached to a horizontal catheter. Method: Our method is to model the system as a quasi-Poiseuille flow driven by the pressure drop generated by the elastic sphere. We construct an engineering model of the pressure exerted by an elastic sphere and match it to a solution of the one-dimensional radial Navier-Stokes equation that describes flow through a horizontal, cylindrical tube. Results: Our results are that the model accurately reproduces flow rates obtained in clinical studies. We also discover that the flow rate has an unavoidable maximum, which we call the “toxicity bump”, when the radius of the sphere approaches its terminal, unstretched value—an effect that has been observed experimentally. Conclusions: We conclude that by choosing the properties of an elastomeric pump, the toxicity bump can be restricted to less than 10% of the earlier, relatively constant flow rate. Our model also produces a relation between the length of time that the analgesic fluid infuses and the physical properties of the fluid, of the elastomeric sphere and the tube, and of the blood vessel into which the analgesic infuses. From these, we conclude that elastomeric pumps can be designed, using our simple model, to control infusion times while avoiding toxicity effects.
基金Project supported by the National Natural Science Foundation of China (No. 20835002), and International Science and Technology Cooperation Program of the Ministry of Science and Technology (MOST) of China (No. 2008DFA32250), as well as the British Columbia Innovation Council and the Natural Sciences and Engineering Research Council of Canada.
文摘The application of Raman spectroscopic techniques combined with multivariate chemometrics signal processing promise new means for the rapid multidimensional analysis of metabolites non-destructively, with little or no sample preparation and little sensitivity to water. However, Rayleigh scattering, fluorescence and uncontrolled variance present substantial challenges for the accurate quantitative analysis of metabolites at physiological levels in bio- logically varying samples. Effective strategies include the application of chemometrics pretreatments for reducing Raman spectral interference. However, the arbitrary application of individual or combined pretreatment procedures can significantly alter the outcome of a measurement, thereby complicating spectral analysis. This paper evaluates and compares six signal pretreatment methods for correcting the baseline variances, together with three variable se- lection methods for eliminating uninformative variables, all within the context of multivariate calibration models based on partial least squares (PLS) regression. Raman spectra of 90 artificial bio-fluid samples with eight urine metabolites at near-physiological concentrations were used to test these models. The combination of multiplicative scatter correction (MSC), continuous wavelet transform (CWT), randomization test (RT) and PLS modeling pre- sented the best performance for all the metabolites. The correlation coefficient (R) between predicted and prepared concentration reached as high as 0.96.