153 research outputs found
Recommended from our members
Near infrared spectrometric investigation of lactate in a varying pH buffer
Lactic acidosis is commonly observed in various disease states in critical care and can be adopted as a hemodynamic biomarker, as well as a target for therapy. pH is the main biomarker for the diagnosis of acid–base disorders and is currently measured utilizing invasive blood sampling techniques. Therefore, there is a need for a non-invasive and continuous technology for the measurement of pH and lactate levels. In this work, near infrared spectroscopy is explored as a technique for investigating lactic acidosis. In-vitro studies on 20 isotonic phosphate buffer solutions of varying pH with constant lactate concentration (2 mmol/L) were performed. The whole near infrared spectrum (800–2600 nm) was then divided into four parts for analysis: (a) water absorption peaks, (b) 1000–1250 nm, (c) 1700–1760 nm, and (d) 2200–2400 nm. The water absorption peaks showed a linear variation with the changes in pH in the spectra. The range from 1700–1760 nm showed good correlation with calculated values for lactate ionization, with the changes in pH. However, the region from 2200–2400 nm showed a reverse correlation with respect to the concentration changes of lactate and a distinction could be made from pH 6–7 and 7–8. This study successfully identifies wavelengths (1233 nm, 1710 nm, 1750 nm, 2205 nm, 2319 nm, and 2341 nm) which can be directly correlated to lactic acidosis. Knowledge from this study will contribute toward the development of lactate-based pH monitoring optical sensor for critical care
Knowledgezoom for java: A concept-based exam study tool with a zoomable open student model
This paper presents our attempt to develop a personalized exam preparation tool for Java/OOP classes based on a fine-grained concept model of Java knowledge. Our goal was to explore two most popular student model-based approaches: open student modeling and problem sequencing. The result of our work is a Java exam preparation tool, Knowledge Zoom. The tool combines an open concept-level student model component, Knowledge Explorer and a concept-based sequencing component, Knowledge Maximizer into a single interface. This paper presents both components of Knowledge Zoom, reports results of its evaluation, and discusses lessons learned. © 2013 IEEE
Recommended from our members
In vitro quantification of lactate in Phosphate Buffer Saline (PBS) samples.
Continuous measurement of lactate levels in the blood is a prerequisite in intensive care patients who are susceptible to sepsis due to their suppressed immune system and increased metabolic demand. Currently, there exists no noninvasive tool for continuous measurement of lactate in clinical practice. The current mode of measurement is based on arterial blood gas analyzers which require sampling of arterial blood. In this work, we propose the use of Near Infra-Red (NIR) spectroscopy together with multivariate models as a means to non-invasively predict the concentration of lactate in the blood. As the first step towards this objective, we examined the possibility of accurately predicting concentrations of sodium lactate (NaLac) from the NIR spectra of 37 isotonic phosphate buffer saline (PBS) samples containing NaLac ranging from 0 to 20 mmol/L. NIR spectra of PBS samples were collected using the Lambda 1050 dual beam spectrometer over a spectral range of 800 - 2600 nm with a quartz cell of 1 mm optical path. Estimates and calibration of the lactate concentration with the NIR spectra were made using Partial Least-Squares (PLS) regression analysis and leave-one-out cross-validation on filtered spectra. The regression analysis showed a correlation coefficient of 0.977 and a standard error of 0.89 mmol/L between the predicted and prepared samples. The results suggest that NIR spectroscopy together with multivariate models can be a valuable tool for non-invasive assessment of blood lactate concentrations
Recommended from our members
Comparison of wavelength selection methods for in-vitro estimation of lactate: a new unconstrained, genetic algorithm-based wavelength selection
Biochemical and medical literature establish lactate as a fundamental biomarker that can shed light on the energy consumption dynamics of the body at cellular and physiological levels. It is therefore, not surprising that it has been linked to many critical conditions ranging from the morbidity and mortality of critically ill patients to the diagnosis and prognosis of acute ischemic stroke, septic shock, lung injuries, insulin resistance in diabetic patients, and cancer. Currently, the gold standard for the measurement of lactate requires blood sampling. The invasive and costly nature of this procedure severely limits its application outside intensive care units. Optical sensors can provide a non-invasive, inexpensive, easy-to-use, continuous alternative to blood sampling. Previous efforts to achieve this have shown significant potential, but have been inconclusive. A measure that has been previously overlooked in this context, is the use of variable selection methods to identify regions of the optical spectrum that are most sensitive to and representative of the concentration of lactate. In this study, several wavelength selection methods are investigated and a new genetic algorithm-based wavelength selection method is proposed. This study shows that the development of more accurate and parsimonious models for optical estimation of lactate is possible. Unlike many existing methods, the proposed method does not impose additional locality constraints on the spectral features and therefore helps provide a much more granular interpretation of wavelength importance
Recommended from our members
Near Infrared Spectrometric Investigations on the behaviour of Lactate
In patients with life-threatening illnesses, the metabolic production and disposal of lactate are impaired, which leads to a build-up of blood lactate. In critical care units, the changes in lactate levels are measured through intermittent, invasive, blood sampling and in vitro assay. Continuous monitoring is lacking, yet such monitoring could allow early assessment of severity and prognosis to guide therapy. Currently, there is no routine means to measure lactate levels continuously, particularly non-invasively. The motivation of this study was to understand the interaction of lactate with light in the Near Infra Red (NIR) region of the electromagnetic spectrum. This was to create an opportunity to explore the possibility of a non-invasive sensing technology to monitor lactate continuously.
In vitro studies were performed using solution samples with varying concentration levels of sodium lactate in isotonic Phosphate Buffer Solution (PBS) at constant pH (7.4). These samples were prepared using stoichiometric solution compositions and spectra for each sample were taken using a state-of-the-art spectrometer in the NIR region. The spectra were then analysed qualitatively by 2D correlation analysis, which identified the regions of interest. Further analysis of these regions using linear regression at four randomly selected wavelengths showed bathochromic shifts, which, moreover, showed systematic variation correlating with lactate concentration
Comparison of a Genetic Algorithm Variable Selection and Interval Partial Least Squares for quantitative analysis of lactate in PBS
Blood lactate is an important biomarker that has been linked to morbidity and mortality of critically ill patients, acute ischemic stroke, septic shock, lung injuries, insulin resistance in diabetic patients, and cancer. Currently, the clinical measurement of blood lactate is done by collecting intermittent blood samples. Therefore, noninvasive, optical measurement of this significant biomarker would lead to a big leap in healthcare. This study, presents a quantitative analysis of the optical properties of lactate. The benefits of wavelength selection for the development of accurate, robust, and interpretable predictive models have been highlighted in the literature. Additionally, there is an obvious, time- and cost-saving benefit to focusing on narrower segments of the electromagnetic spectrum in practical applications. To this end, a dataset consisting of 47 spectra of Na-lactate and Phosphate Buffer Solution (PBS) was produced using a Fourier transform infrared spectrometer, and subsequently, a comparative study of the application of a genetic algorithm-based wavelength selection and two interval selection methods was carried out. The high accuracy of predictions using the developed models underlines the potential for optical measurement of lactate. Moreover, an interesting finding is the emergence of local features in the proposed genetic algorithm, while, unlike the investigated interval selection methods, no explicit constraints on the locality of features was imposed. Finally, the proposed genetic algorithm suggests the formation of α-hydroxy-esters methyl lactate in the solutions while the other investigated methods fail to indicate this
Recommended from our members
The efficacy of support vector machines in modelling deviations from the Beer-Lambert law for optical measurement of lactate
Lactate is an important biomarker with a significant diagnostic and prognostic ability in relation to life-threatening conditions and diseases such as sepsis, diabetes, cancer, pulmonary and kidney diseases, to name a few. The gold standard method for the measurement of lactate relies on blood sampling, which due to its invasive nature, limits the ability of clinicians in frequent monitoring of patients' lactate levels. Evidence suggests that the optical measurement of lactate holds promise as an alternative to blood sampling. However, achieving this aim requires better understanding of the optical behavior of lactate. The present study investigates the potential deviations of absorbance from the Beer-Lambert law in high concentrations of lactate. To this end, a number of nonlinear models namely support vector machines with quadratic, cubic and quartic kernels and radial basis function kernel are compared with the linear principal component regression and linear support vector machine. Interestingly, it is shown that even in extremely high concentrations of lactate (600 mmol/L) in a phosphate buffer solution, the linear models surpass the performance of the other models
Recommended from our members
Near Infrared and Aquaphotomic analysis of water absorption in lactate containing media
Increased concentrations of lactate levels in blood are often seen in patients with life-threatening cellular hypoperfusion or infections. State-of-the-art techniques used in clinical practice for measuring serum lactate concentrations rely on intermittent blood sampling and do not permit continuous monitoring of this all important parameter in critical care environments.In recent years, Near Infrared (NIR) Spectroscopy has been established as a possible alternative to existing methods that can mitigate these constraints and be used for non-invasive continuous monitoring of lactate. Nevertheless, the dominant absorption of -OH overtone bands of water in the NIR presents a challenge and complicates the accurate detection of other absorbers such as lactate. For this reason, comprehensive analysis of the -OH overtone bands with systematic lactate concentration changes is essential. This paper reports on the analysis of NIR spectra of two aqueous systems of varying concentrations of lactate in saline and whole blood using the principles of Aquaphotomics.The results show distinctive conformational and structural differences in lactate-water binding, which arise due to the molecular interactions of bonds present in respective solvents
Identification and Quantitative Determination of Lactate Using Optical Spectroscopy—Towards a Noninvasive Tool for Early Recognition of Sepsis
Uninterrupted monitoring of serum lactate levels is a prerequisite in the critical care of patients prone to sepsis, cardiogenic shock, cardiac arrest, or severe lung disease. Yet there exists no device to continuously measure blood lactate in clinical practice. Optical spectroscopy together with multivariate analysis is proposed as a viable noninvasive tool for estimation of lactate in blood. As an initial step towards this goal, we inspected the plausibility of predicting the concentration of sodium lactate (NaLac) from the UV/visible, near-infrared (NIR), and mid-infrared (MIR) spectra of 37 isotonic phosphate-buffered saline (PBS) samples containing NaLac ranging from 0 to 20 mmol/L. UV/visible (300–800 nm) and NIR (800–2600 nm) spectra of PBS samples were collected using the PerkinElmer Lambda 1050 dual-beam spectrophotometer, while MIR (4000–500 cm−1) spectra were collected using the Spectrum two FTIR spectrometer. Absorption bands in the spectra of all three regions were identified and functional groups were assigned. The concentration of lactate in samples was predicted using the Partial Least-Squares (PLS) regression analysis and leave-one-out cross-validation. The regression analysis showed a correlation coefficient (R2) of 0.926, 0.977, and 0.992 for UV/visible, NIR, and MIR spectra, respectively, between the predicted and reference samples. The RMSECV of UV/visible, NIR, and MIR spectra was 1.59, 0.89, and 0.49 mmol/L, respectively. The results indicate that optical spectroscopy together with multivariate models can achieve a superior technique in assessing lactate concentrations
Recommended from our members
Comparison of a Genetic Algorithm Variable Selection and Interval Partial Least Squares for quantitative analysis of lactate in PBS
Blood lactate is an important biomarker that has been linked to morbidity and mortality of critically ill patients, acute ischemic stroke, septic shock, lung injuries, insulin resistance in diabetic patients, and cancer. Currently, the clinical measurement of blood lactate is done by collecting intermittent blood samples. Therefore, noninvasive, optical measurement of this significant biomarker would lead to a big leap in healthcare. This study, presents a quantitative analysis of the optical properties of lactate. The benefits of wavelength selection for the development of accurate, robust, and interpretable predictive models have been highlighted in the literature. Additionally, there is an obvious, time- and cost-saving benefit to focusing on narrower segments of the electromagnetic spectrum in practical applications. To this end, a dataset consisting of 47 spectra of Na-lactate and Phosphate Buffer Solution (PBS) was produced using a Fourier transform infrared spectrometer, and subsequently, a comparative study of the application of a genetic algorithm-based wavelength selection and two interval selection methods was carried out. The high accuracy of predictions using the developed models underlines the potential for optical measurement of lactate. Moreover, an interesting finding is the emergence of local features in the proposed genetic algorithm, while, unlike the investigated interval selection methods, no explicit constraints on the locality of features was imposed. Finally, the proposed genetic algorithm suggests the formation of α-hydroxy-esters methyl lactate in the solutions while the other investigated methods fail to indicate this
- …