Robert A. Lodder

Mechanisms contributing to angiotensin II regulation of body weight.

Previous studies in our laboratory have implicated adipose tissue as a potential site for local angiotensin II (ANG II) synthesis. However, functions of ANG II in adipose tissue and the impact of ANG II on body weight regulation are not well defined. To study the effect of ANG II on body weight, a chronic ANG II infusion model was used. In study 1, a low dose of ANG II (175 ng.kg-1.min-1) was infused into rats for 14 days. Plasma ANG II levels were not elevated after 14 days of infusion. ANG II-infused rats did not gain weight over the 14-day protocol and exhibited a lower body weight than controls on day 8. Food intake was not altered, but water intake was increased in ANG II-infused rats. Blood pressure gradually increased to significantly elevated levels by day 14. Thermal infrared imaging demonstrated an increase in abdominal surface temperature. Measurement of organ mass demonstrated site-specific reductions in white adipose tissue mass after ANG II infusion. In study 2, the dose-response relationship for ANG II infusion (200, 350, and 500 ng.kg-1.min-1) was determined. Body weight (decrease), blood pressure (increase), white adipose mass (decrease), plasma ANG II levels (increase), and plasma leptin levels (decrease) were altered in a dose-related manner after ANG II infusion. In study 3, the effect of ANG II infusion (350 ng.kg-1.min-1) was examined in rats treated with the vasodilator hydralazine. Hydralazine treatment normalized blood pressure in ANG II-infused rats. The effect of ANG II to decrease body weight was augmented in hydralazine-treated rats. These results demonstrate that low levels of ANG II infusion regulate body weight through mechanisms related to increased peripheral metabolism and independent of elevations in blood pressure.

Near-Infrared Spectroscopic Determination of Residual Moisture in Lyophilized Sucrose Through Intact Glass Vials

A rapid, noninvasive, and nondestructive method for determining moisture in sealed freeze-drying vials is described. The method, based on near-infrared spectrometry, used a novel fiber-optic diffuse-reflectance probe to make remote reflectance measurements from 1100 to 2500 nm through the bottom of glass vials. The correlation of the method to results obtained by Karl Fischer analysis was good (r2 = 0.97). The moisture content of sucrose, a common cryoprotectant, was determined with an error of 0.27% using a single sample scan.

Biological and Medical Applications of Near-Infrared Spectrometry

Near-infrared spectrometry is being applied in the solution of problems in many areas of biomedical and pharmaceutical research, including cardiovascular radiology, brain imaging, formulation, quality/process control, and even clinical trials. The technique can also play a role in the biotechnology industry in the nondestructive analysis of small quantities of expensive materials. This report first defines near-IR spectrometry and imaging and then describes its application to atherosclerosis and stroke research. New developments in near-IR optics and instrumentation that make effective biomedical near-IR spectrometry possible are related, and, finally, new computational research results in parallel supercomputing for near-IR imaging are described. Together, instrumentation, optics, and computing combine to poise biomedical near-IR spectrometry for great advances as it enters the next century.

Analysis of Intact Tablets by Near-Infrared Reflectance Spectrometry

A typical pharmaceutical tablet is too small for analysis in an ordinary NIRA instrument. An intact tablet will not begin to fill a solid-sample holder designed for use with a powdered sample. Grinding the sample is likewise unproductive, as a single tablet also does not provide enough powder for the sample cup. Potential NIRA applications such as the detection of product tampering and even routine quality control are unnecessarily complicated by this grinding requirement. A method of analyzing single, intact tablets using a double-reflecting aluminum sample holder is described in this report. The integrity of the sample is preserved during the analysis, allowing the tablet to be sold or consumed after the procedure.

Detection of Subpopulations in Near-Infrared Reflectance Analysis:

In typical near-infrared multivariate statistical analyses, samples with similar spectra produce points that cluster in a certain region of spectral hyperspace. These clusters can vary significantly in shape and size due to variation in sample packings, particle-size distributions, component concentrations, and drift with time. These factors, when combined with discriminant analysis using simple distance metrics, produce a test in which a result that places a particular point inside a particular cluster does not necessarily mean that the point is actually a member of the cluster. Instead, the point may be a member of a new, slightly different cluster that overlaps the first. A new cluster can be created by factors like low-level contamination or instrumental drift. An extention added to part of the BEAST (Bootstrap Error-Adjusted Single-sample Technique) can be used to set nonparametric probability-density contours inside spectral clusters as well as outside, and when multiple points begin to appear in a certain region of cluster-hyperspace the perturbation of these density contours can be detected at an assigned significance level. The detection of false samples both within and beyond 3 SDs of the center of the training set is possible with this method. This procedure is shown to be effective for contaminant levels of a few hundred ppm in an over-the-counter drug capsule, and is shown to function with as few as one or two wavelengths, suggesting its application to very simple process sensors.

Acoustic-Resonance Spectrometry as a Process Analytical Technology for Rapid and Accurate Tablet Identification

This research was performed to test the hypothesis that acoustic-resonance spectrometry (ARS) is able to rapidly and accurately differentiate tablets of similar size and shape. The US Food and Drug Administration frequently orders recalls of tablets because of labeling problems (eg, the wrong tablet appears in a bottle). A high-throughput, nondestructive method of online analysis and label comparison before shipping could obviate the need for recall or disposal of a batch of mislabeled drugs, thus saving a company considerable expense and preventing a major safety risk. ARS is accurate and precise as well as inexpensive and nondestructive, and the sensor, is constructed from readily available parts, suggesting utility as a process analytical technology (PAT). To test the classification ability of ARS, 5 common household tablets of similar size and shape were chosen for analysis (aspirin, ibuprofen, acetaminophen, vitamin C, and vitamin B12). The measures of successful tablet identification were intertablet distances in nonparametric multidimensional standard deviations (MSDs) greater than, 3 and intratablet MSDs less than 3, as calculated from an extended bootstrap erroradjusted single sample technique. The average intertablet MSD was 65.64, while the average intratablet MSD from cross-validation was 1.91. Tablet mass (r2=0.977), thickness (r2=0.977), and density (r2=0.900) were measured very accurately from the AR spectra, each with less than 10% error. Tablets were identified correctly with only 250 ms data collection time. These results demonstrate that ARS effectively identified and characterized the 5 types of tablets and could potentially serve as a rapid high-throughput online pharmaceutical sensor.

Spectrophotometric prediction of the dissolution rate of carbamazepine tablets

A near-infrared (IR) spectrophotometer, integrating optics, and parallel-vector supercomputer are employed to develop a mathematical model that predicts the dissolution rate of individual intact tablets from near-IR spectra (r2 = 0.985). Each tablet can be analyzed nondestructively by the spectrophotometer in less than 1 min. The model permits hundreds of near-IR wavelengths to be used in the determination of dissolution rate, leading to increased accuracy.

Advances and Perspectives in Near-Infrared Spectrophotometry

Abstract Near-infrared spectrophotometric analysis is a rapid technique that typically uses the reflectance of a solid sample at several wavelengths to determine the samples composition. A computerized modeling process is generally used to correct for background and sample-matrix interferences. The modeling process employs a training set of samples to, in effect, “teach” the computer to recognize relationships between minute spectral features and sample composition. The contents of the training-set samples must be determined initially by some other reference method before applying the near-IR technique. The model developed from near-IR spectra and reference values gives the sample composition using a number of linear equations. Each of these equations expresses a particular component concentration as a weighted sum of the signals observed at a number of near-IR wavelengths. Instruments used for near-IR spectrophotometry can be as simple as a filter photometer or a grating monochromator. The broad spectra...

Determination of Extent of Formaldehyde-Induced Crosslinking in Hard Gelatin Capsules by Near-Infrared Spectrophotometry

AbstractPurpose. To predict the degree of crosslinking from formaldehyde-stressed hard gelatin capsules (HGCs) using near-infrared spectrophotometry (NIR). Methods. HGCs were exposed to a 150 ppb atmosphere of formaldehyde for 2.25,4.60,9.42, 16.0 and 24.0 hours. The capsules were filled with fresh amoxicillin, placed in a 90° conical reflector cone, and scanned in a NIR spectrophotometer. Principal component regression (PCR) was employed to analyze the spectra of the intact capsules. Dissolution profiles were then obtained for each experimental group. Results. The dissolution of amoxicillin from the capsules at pH 1.2 was found to decrease with increasing time of exposure to the formaldehyde atmosphere. A set of principal components (PCs) was formed by a linear combination of the absorbance values at each wavelength scanned. A good correlation was established (r2 = 0.963) when PC values from the NIR spectra of the HGCs were regressed against percentage of amoxicillin dissolved at 45 minutes, at pH 1.2. Water content of the capsules was found to be the largest determinant in the variation between HGC spectra at each exposure time. Conclusions. NIR spectrophotometry, combined with PCR, was successful at not only predicting dissolution of HGCs exposed to formaldehyde, but also at determining which wavelengths contributed most to spectral variation of these stressed HGCs.

Molecular Factor Computing for Predictive Spectroscopy

PurposeThe concept of molecular factor computing (MFC)-based predictive spectroscopy was demonstrated here with quantitative analysis of ethanol-in-water mixtures in a MFC-based prototype instrument. MethodsMolecular computing of vectors for transformation matrices enabled spectra to be represented in a desired coordinate system. New coordinate systems were selected to reduce the dimensionality of the spectral hyperspace and simplify the mechanical/electrical/computational construction of a new MFC spectrometer employing transmission MFC filters. A library search algorithm was developed to calculate the chemical constituents of the MFC filters. The prototype instrument was used to collect data from 39 ethanol-in-water mixtures (range 0–14%). For each sample, four different voltage outputs from the detector (forming two factor scores) were measured by using four different MFC filters. Twenty samples were used to calibrate the instrument and build a multivariate linear regression prediction model, and the remaining samples were used to validate the predictive ability of the model.Results In engineering simulations, four MFC filters gave an adequate calibration model (r2 = 0.995, RMSEC = 0.229%, RMSECV = 0.339%, p = 0.05 by f test). This result is slightly better than a corresponding PCR calibration model based on corrected transmission spectra (r2 = 0.993, RMSEC = 0.359%, RMSECV = 0.551%, p = 0.05 by f test). The first actual MFC prototype gave an RMSECV = 0.735%.ConclusionMFC was a viable alternative to conventional spectrometry with the potential to be more simply implemented and more rapid and accurate.