Least-squares Linear Regression Analysis Research Articles

X-ray stress analysis with a 2D detector. Part 2. Goniometer alignment

The use of 2D detectors for stress/strain analysis enables new strategies for data acquisition and treatment to be devised, thus enabling faster measurements to be performed, including stress mapping without goniometer rotations. These advantages were developed in Part 1 of this work [François (2023). J. Appl. Cryst. 56, 48–60], but they imply the occurrence of additional alignment issues that need to be addressed carefully. The aim of this second part is to describe the misalignment errors geometrically using the general formalism introduced in Part 1. Under the assumption that the defects of the equipment are small, closed-form analytical expressions are provided for each type of error. It is found that the trigonometric functions describing each defect are independent. Thus, it becomes possible to identify and quantify the type of error from measurements performed on a stress-free sample such as a powder specimen. This is achieved by a linear least-squares regression analysis on the measured peak positions for various values of the goniometric angles. The proposed method is then applied to an example.

Application of High-Performance Liquid Chromatography Combined with Fluorescence Detector and Dispersive Liquid-Liquid Microextraction to Quantification of Selected Bisphenols in Human Amniotic Fluid Samples.

Bisphenol A (BPA) is a widely produced chemical worldwide found in numerous everyday products. Its endocrine-disrupting properties and omnipresence have aroused concern and led to several restrictions on its use. These restrictions and growing public awareness about the toxicity of BPA have resulted in market products labeled "BPA-free", with BPAs often being replaced by other bisphenols. This is why constant biomonitoring of bisphenol levels in various body fluids and tissues is essential. In this study, we propose the use of simple, cost-effective high-performance liquid chromatography coupled with the fluorescence detector (HPLC-FLD) method for the determination of simultaneously selected bisphenols in amniotic fluid. For the sample preparation, a fast, simple, and "green" dispersive liquid-liquid microextraction (DLLME) method was used, achieving mean recovery values in the range of 80.9-115.9% with relative standard deviations below 12% for all analytes. Limits of quantification (LOQs) determined in the amniotic fluid matrix ranged from 6.17 to 22.72 ng/mL and were obtained from a calibration curve constructed using least-squares linear regression analysis for all cases. The presented sample preparation procedure can be easily adopted for LC-MS analysis.

Heat Release Rate Characterization of NFPA 1403 Compliant Training Fuels

When using solid fuels for live fire training, NFPA 1403: Standard on Live Fire Training Evolutions requires that the materials be wood based. While the standard offers guidance on the type of fuels that are permissible for use in training, it offers little in the way of quantitative methods of selecting an appropriately sized fuel package. In order to examine the effects of fuel mass and orientation on heat release behavior, free burn heat release rate (HRR) experiments were conducted on twenty-one wood-based training fuel packages and twelve comparison furniture items. Training fuel packages demonstrated peak HRRs ranging from 1.0 MW to 3.6 MW, with the total energy release between 210 MJ and 1615 MJ. The furniture items exhibited peak HRRs between 0.9 MW and 3.7 MW, with the total energy release between 180 MJ and 995 MJ. A least-squares linear regression analysis indicated a good linear fit between total energy release and fuel mass burned among the training fuel packages (R^2 = 0.98), suggesting that the effective heat of combustion is approximately constant at 14.2 MJ/kg. Generally, peak HRR increased as initial fuel mass increased, although the relationship was more variable, with the peak HRRs of similarly sized training fuel packages varying by nearly 1 MW. The results indicated that while total energy release was dependent largely on the initial fuel mass, peak HRR and peak burning duration were also dependent on the orientation and type of fuel in the fuel package. Wood-based training fuel packages were capable of producing peak HRRs comparable to individual items of furniture, although the total energy release was typically higher for the training fuel packages compared to corresponding furniture items.

Novel methodology on direct extraction of the strength information from cementitious materials using piezo-sensor based electromechanical impedance (EMI) method

It is critical to develop an accurate non-destructive testing (NDT) methods to evaluate the real-time concrete strength gain due to the fast pace of construction. Among the NDTs for concrete strength monitoring, piezoelectric materials based electromechanical impedance (EMI) method has attracted much attention recently. Some statistical approaches are proposed for impedance signal processing, such as root mean square deviation (RMSD) and mean absolute percentage deviation (MAPD). However, these methods require the baseline value for calculation, which is not convenient, particularly for the very early strength gain monitoring. In this study, three features extracted directly from phase angle spectrum, including resonant frequency of the first local phase angle peak (PARF), local phase angle peak value (PA), and the corresponding width of half-prominence (HPW) are employed as indicators to monitor the strength gain process. Among these three indicators, the first peak of phase angle resonant frequency (PARF) is found the most reliable. The PARF index can directly be obtained from the impedance spectrum without baseline calculation. Five types of different cement mortar with various water-to-cement ratios from 0.38 to 0.46 were prepared. The EMI test and conventional cubic testing (ASTM 109) were conducted concurrently at a very early age (4th to 8th hour) and an early age (1st, 3rd, and 7th day). To examine the correlation between the compressive strength obtained and the EMI-PARF indices, a linear least-squares regression analysis was performed. Furthermore, the finite element analysis (FEA) was conducted to discuss the relationship between the features obtained from the phase angle spectrum and the stiffness of the host structure. The PARF index exhibits a high correlation with the mechanical properties of cementitious materials. Both experiments and FEA results ascertain that piezoelectric-based EMI coupled with the PARF index is a reliable method for in-place strength gain evaluation of cementitious materials.

Methodology to derive well-calibrated thermometers: a new glass-composition geothermometer for olivine-bearing glassy samples at one atmosphere

This work describes the methodology used to develop a new glass-composition geothermometer by multiple linear least-squares regression analysis of experimental data available in literature. The geothermometer is applicable to natural olivine-bearing glassy samples quenched at one atmosphere. The calibration data set includes a total of 543 anhydrous experiments performed at one atmosphere which produced olivine coexisting with glass (± other phases). The accuracy of the geothermometer has been verified using an independent set of randomly selected one atmosphere anhydrous experimental samples external to the calibration data set. The new proposed equation reads: T(°C) = 1054.1±6.5 + (1458.0±23.5)(XMgO)liq – (267.1±45.8)(XCaO)liq + (116.3±30.9)(XNa2O + XK2O)liq, where the terms such as (XMgO)liq represent the cation fraction of MgO in the liquid. The new geothermometer is able to reproduce the calibration temperatures within a standard error of estimate (SEE) of ±23° C and to predict the temperatures for the test data set with a SEE of ±25° C. The proposed equation, when compared to previous models, gives the lowest systematic error. Moreover, we mathematically demonstrate that the comparison of the slope and the intercept parameters of the regression line against the 1:1 line leads to correct evaluation of the model only when a regression of observed or measured (in the y-axis as dependent variable) vs. predicted or calculated (in the x-axis as independent variable) is used.

Involvement of NO in Antinociception of NSAIDS in Murine Formalin Hind Paw Assay.

There are different animal models to evaluate pain among them the formalin hind paw assay which is widely used since some of its events appear to be similar to the clinical pain of humans. The assay in which a dilute solution of formalin is injected into the dorsal hindpaw of a murine produces two 'phases' of pain behavior separated by a inactive period. The early phase (Phase I) is probably due to direct activation of nociceptors and the second phase (Phase II) is due to ongoing inflammatory input and central sensitization. Mice were used to determine the potency antinociceptive of piroxicam (1,3,10,and 30 mg/kg), parecoxib (0.3, 1,3,10 and 30 mg/kg), dexketoprofen (3,10,30 and 100 mg/kg) and ketoprofen (3,10,30 and 100 mg/kg). Dose-response for each NSAIDs were created before and after 5 mg/kg of L-NAME i.p. or 5 mg/kg i.p. of 7-nitroindazole. A least-squares linear regression analysis of the log dose-response curves allowed the calculation of the dose that produced 50% of antinociception (ED50) for each drug. The ED50 demonstrated the following rank order of potency, in the phase I: piroxicam > dexketoprofen > ketoprofen > parecoxib and in the phase II: piroxicam > ketoprofen > parecoxib > dexketoprofen. Pretreatment of the mice with L-NAME or 7-nitroindazol induced a significant increase of the analgesic power of the NSAIDs, with a significant reduction of the ED50. It is suggested that NO may be involved in both phases of the trial, which means that nitric oxide regulates the bioactivity of NSAIDs.

Prediction of the diet nutrients digestibility of dairy cows using Gaussian process regression

In order to effectively evaluate the diet nutritional value of dairy cows, it is essential to accurately predict the diet nutrients digestibility (DND). Conventional predicting DND methods are usually based on the least squares linear regression analysis (LS-LRA), which often relies on a large amount of training samples to accomplish reliable predictions. However,in real-world applications, it is often extremely difficult, costly and time-consuming to obtain a large number of measured samples, especially for the DND prediction of dairy cows. This paper applies a Gaussian process regression (GPR) technique to predict the DND indicators of dairy cows in small samples. To evaluate prediction accuracy effectively, we compared the GPR technique with the LS-LRA, radial basis function artificial neural network (RBF-ANN), support vector regression (SVR) and least squares support vector regression (LS-SVR) methods, using the required sample data obtained from actual digestion experiments. The prediction results indicate that the GPR technique is superior to other conventional methods (especially the LS-LRA method) in predicting the main DND indicators of dairy cows such as dry matter digestibility (DMD), organic matter digestibility (OMD), neutral detergent fiber (NDFD), acid detergent fiber (ADFD), and crude protein digestibility (CPD). It is worth mentioning that the developed GPR-based prediction technique is more suitable for the prediction problems with small samples, which is often the case in the prediction of DND indicators of dairy cows, and then more coincide with actual needs.

Renewed Explosive Phreatomagmatic Activity at Poás Volcano, Costa Rica in April 2017

Phreatic and phreatomagmatic eruptions at volcanoes often present no short term precursory activity, making them a challenge to forecast. Poas volcano, Costa Rica, exhibits cyclic activity with phreatic and some phreatomagmatic eruptions separated by times of quiescence. The latest phreatomagmatic stage began in March 2017 with increases in crater lake temperatures, SO2 flux, and the rate of seismicity, as well as accelerated ground inflation near the active crater. On 23 April 2017 at 04:12 UTC, a large phreatomagmatic eruption occurred at Poas, sending blocks up to 1 m in length to distances greater than 1 km. Hindsight analysis revealed a precursory seismic sequence from 25 March to 22 April of similar seismic events (in terms of their frequency and waveform characteristics). Fourteen families of similar seismic events (containing >10 events per family) were identified during this precursory sequence, totaling over 1300 events. An acceleration within the dominant family of LF (low frequency) waveforms was identified, suggesting that a forecast for the onset of the eruption may have been possible using the Failure Forecast Method (FFM). However, no confidence could be placed in the forecast generated, reiterating that not all accelerating trends are suitable for analysis using the FFM, in particular in conjunction with a least-squares linear regression. Our residual analysis further supports the concept that using a least-squares linear regression analysis is not appropriate with this dataset, and allows us to eliminate commonly used forecasting parameters for this scenario. However, the identification of different families of similar seismicity allows us to determine that magmatic fluid on its way to the surface initially became stalled beneath a chilled margin or hydrothermal seal, before catastrophically failing in a large phreatomagmatic eruption. Additionally, we note that 24 hours prior to the large phreatomagmatic eruption, all LF families became inactive, which could have been falsely interpreted in real time as the waning of activity. Our results suggest that identifying families of seismicity offers unique opportunities to better understand ongoing processes at depth, and to challenge conventional forecasting techniques.

An EELS signal-from-background separation algorithm for spectral line-scan/image quantification

Background removal is an important step in the quantitative analysis of electron energy-loss structure. Existing methods usually require an energy-loss region outside the fine structure in order to estimate the background. This paper describes a method for signal-from-background separation that is based on subspace division. The linear space is divided into two subspaces. The signal is recovered from a linear subspace containing no background information, and the other subspace containing the background is discarded. This method does not rely on any signal outside the energy-loss range of interest and should be very helpful for multiple linear least-squares (MLLS) regression analysis on experimental signals with little or no available smooth pre-edge region or with overlapping pre-edge features. Use of the algorithm is demonstrated with several practical applications, including closely overlapping core-loss spectra and zero-loss peak removal. Tests based on experimental data indicate that the algorithm has similar or better performance relative to conventional pre-edge power-law fitting methods in applications such as MLLS regression for electron energy-loss near-edge structure.

Optimization of cellulose nanocrystal length and surface charge density through phosphoric acid hydrolysis.

Cellulose nanocrystals (CNCs) are emerging nanomaterials with a large range of potential applications. CNCs are typically produced through acid hydrolysis with sulfuric acid; however, phosphoric acid has the advantage of generating CNCs with higher thermal stability. This paper presents a design of experiments approach to optimize the hydrolysis of CNCs from cotton with phosphoric acid. Hydrolysis time, temperature and acid concentration were varied across nine experiments and a linear least-squares regression analysis was applied to understand the effects of these parameters on CNC properties. In all but one case, rod-shaped nanoparticles with a high degree of crystallinity and thermal stability were produced. A statistical model was generated to predict CNC length, and trends in phosphate content and zeta potential were elucidated. The CNC length could be tuned over a relatively large range (238-475 nm) and the polydispersity could be narrowed most effectively by increasing the hydrolysis temperature and acid concentration. The CNC phosphate content was most affected by hydrolysis temperature and time; however, the charge density and colloidal stability were considered low compared with sulfuric acid hydrolysed CNCs. This study provides insight into weak acid hydrolysis and proposes 'design rules' for CNCs with improved size uniformity and charge density.This article is part of a discussion meeting issue 'New horizons for cellulose nanotechnology'.

Contemporary Trends in Utilization and Perioperative Outcomes of Percutaneous Nephrolithotomy in the United States from 2003 to 2014.

To investigate the contemporary trends and perioperative outcomes of percutaneous nephrolithotomy (PCNL) by using a population-based cohort. Using the Premier Healthcare Database, we identified 225,321 patients in whom kidney/ureteral calculi were diagnosed and who underwent PCNL at 447 different hospitals across the United States from 2003 to 2014. Outcomes included 90-day postoperative complications (as classified by the Clavien-Dindo system), prolonged hospital length of stay, operating room time, blood transfusions, and direct hospital costs. Temporal trends were quantified by estimated annual percentage change (EAPC) by using least-squares linear regression analysis. Multivariable logistic regression was performed to identify predictors of outcomes. PCNL utilization rates initially increased from 6.7% (2003) to 8.9% (2008) (EAPC: +5.60%, p = 0.02), before plateauing at 9.0% (2008-2011), and finally declining to 7.2% in 2014 (EAPC: -4.37%, p = 0.02). Overall (Clavien ≥1) and major complication (Clavien ≥3) rates rose significantly (EAPC: +12.2% and +16.4%, respectively, both p < 0.001). Overall/major complication and blood transfusion rates were 23.1%/4.8% and 3.3%, respectively. Median operating room time and 90-day costs were 221 minutes (interquartile range [IQR] 4) and $12,734 (IQR $9419), respectively. Significant predictors of overall complications include higher Charlson comorbidity index (CCI) (CCI ≥2: odds ratio [OR] 2.08, p < 0.001) and more recent year of surgery (2007-2010: OR 3.20, 2011-2014: OR 4.39, both p < 0.001). Higher surgeon volume was significantly associated with decreased overall (OR 0.992, p < 0.001) and major (OR 0.991, p = 0.01) complications. Our contemporary analysis shows a decrease in the utilization of PCNL in recent years, along with an increase in complication rates. Numerous patient, hospital, and surgical characteristics affect complication rates.

Degree of Geochemical Similarity (DOGS): a simple statistical method to quantify and map affinity between samples from multi-element geochemical data sets

ABSTRACTThe 42 element, 1190 sample Mobile Metal Ion subset of the National Geochemical Survey of Australia database was used to develop and illustrate the concept of Degree of Geochemical Similarity of soil samples. Element concentrations were unified to parts per million units and log(10)-transformed. The degree of similarity of pairs of samples of known provenance in the Yilgarn Craton was obtained using least-squares linear regression analysis and demonstrated that the method successfully assessed the degree of similarity of soils related to granitoid and greenstone lithologies. Exploratory Data Analysis symbol maps of all remaining samples in the database against various reference samples were used to obtain correlation maps not only for granitoid- and greenstone-related soil types but also to distinguish between, for example, samples derived from marine vs regolith carbonate. Likewise, the distribution of soil samples having a geochemical fingerprint similar to mineralised provinces (e.g. Mount Isa) can be mapped, and this can be used as a first-order prospection tool.

Simple radiometric method for accurately quantitating epitope densities of hapten-protein conjugates with sulfhydryl linkages.

Control of small molecule hapten epitope densities on antigenic carrier proteins is essential for development and testing of optimal conditions for vaccines. Yet, accurate determination of epitope density can be extremely difficult to accomplish, especially with the use of small haptens, large molecular weight carrier proteins, and limited amounts of protein. Here we report a simple radiometric method that uses 14C-labeled cystine to measure hapten epitope densities during sulfhydryl conjugation of haptens to maleimide activated carrier proteins. The method was developed using a (+)-methamphetamine (METH)-like hapten with a sulfhydryl terminus, and two prototype maleimide activated carrier proteins, bovine serum albumin (BSA) and immunocyanin monomers of keyhole limpet hemocyanin. The method was validated by immunochemical analysis of the hapten–BSA conjugates, and least-squares linear regression analysis of epitope density values determined by the new radiometric method versus values determined by matrix-assisted laser desorption/ionization mass spectrometry. Results showed that radiometric epitope density values correlated extremely well with the mass spectrometrically derived values (r2 = 0.98, y = 0.98x + 0.91). This convenient and simple method could be useful during several stages of vaccine development including the optimization and monitoring of conditions for hapten–protein conjugations, and choosing the most effective epitope densities for conjugate vaccines.

Clumped isotope signatures in modern brachiopod carbonate

We present a temperature to Δ47 relationship for naturally occurring modern brachiopods, which was established using a suite of thirteen brachiopod specimens from twelve sampling localities that span a mean annual seawater temperature range of −0.8 to 29.0°C. Sample locations and depths were selected to maximize the range of temperatures covered by the calibration while minimizing the seasonal temperature variability impacting the samples. Linear least-squares regression analysis yields the following relationship expressed using the Ghosh et al. (2006) reference frame:Δ47=0.0478±0.0099⋅106/T2+0.1164±0.1203n=13;R2=0.91;95%CI.This equation lies within the 95% confidence interval of the original relationship determined using synthetic calcite (Ghosh et al., 2006), but is in better agreement with the newly revised calibration of Zaarur et al. (2013). However, despite this broad agreement, our equation has a shallower slope than the equations for synthetic calcites, and yields temperatures at the warm end of the calibration temperature range (Δ47=0.640‰) that are as much as 3.1°C offset from those predicted using the equation of Zaarur et al. (2013). On the other hand, our new equation has a steeper slope than the Henkes et al. (2013) equation for modern brachiopods and mollusks. This finding is consistent with the hypothesis that differences in the protocols employed by laboratories that use different temperatures of phosphoric acid digestion cause the observed discrepancies between the Δ47 values reported by various laboratories.

Kinetics of thermal degradation of renewably prepared amines useful for flue gas treatment

N-ethylmonoethanolamine (EMEA) and N-N-diethylmonoethanolamine (DEMEA) can be prepared from renewable resources and appear to be commercially attractive solvents for post-combustion CO2 capture by absorption/stripping process. In this paper, the thermal degradation of these renewably prepared amines was studied at 423 K and compared with other amines such as monoethanolamine, diethanolamine, triethanolamine, and N-methyl diethanolamine. Furthermore, an investigation of the kinetics of thermal degradation of aqueous EMEA and DEMEA was conducted by using a 600 ml high-temperature high-pressure reactor in the temperature range of 393 to 423 K and amine concentration range of 1 to 3 kmol m−3, respectively. Estimation of the active solvent content of the reaction mixture samples obtained during the degradation experiments was performed using a gas chromatograph (GC) equipped with a Flame Ionization Detector (FID) and a Tenax GC column. The obtained results indicate that the rate of thermal degradation of both aqueous EMEA and DEMEA increases with the increase in the initial amine concentration and temperature. Additionally, the degradation reaction was observed to be first order with respect to the initial amine concentration. Two intrinsic kinetic power law models were formulated to describe the kinetics of the thermal degradation of aqueous EMEA and DEMEA and the kinetic parameters were predicted by using the linear least-squares regression analysis. The kinetic rate constants for the thermal degradation of these renewably prepared amines were determined (both experimentally and by the models) and on the basis of their temperature dependency, the activation energy for the degradation reaction was estimated. This work represents the first attempt towards obtaining the intrinsic kinetic data for thermal degradation of aqueous EMEA and DEMEA and formulating a kinetic model that fits the data based on the initial rate of degradation.

Changes in Dark Chocolate Volatiles during Storage

Chocolate storage is critical to the quality of the final product. Inadequate storage, especially with temperature fluctuations, may lead to a change in crystal structure, which may eventually cause fat bloom. Bloom is the main cause of quality loss in the chocolate industry. The impact of various storage conditions on the flavor quality of dark chocolate was determined. Dark chocolate was stored in different conditions leading to either fat or sugar bloom and analyzed at 0, 4, and 8 weeks of storage. Changes in chocolate flavor were determined by volatile analysis and descriptive sensory evaluation. Results were analyzed by analysis of variance (ANOVA), cluster analysis, principal component analysis (PCA), and linear partial least-squares regression analysis (PLS). Volatile concentration and loss were significantly affected by storage conditions. Chocolates stored at high temperature were the most visually and texturally compromised, but volatile concentrations were affected the least, whereas samples stored at ambient, frozen, and high relative humidity conditions had significant volatile loss during storage. It was determined that high-temperature storage caused a change in crystal state due to the polymorphic shift to form VI, leading to an increase in sample hardness. Decreased solid fat content (SFC) during high-temperature storage increased instrumentally determined volatile retention, although no difference was detected in chocolate flavor during sensory analysis, possibly due to instrumental and sensory sampling techniques. When all instrumental and sensory data had been taken into account, the storage condition that had the least impact on texture, surface roughness, grain size, lipid polymorphism, fat bloom formation, volatile concentrations, and sensory attributes was storage at constant temperature and 75% relative humidity.

Simultaneous field and R mapping to quantify liver iron content using autoregressive moving average modeling

To investigate the use of a complex multigradient echo (mGRE) acquisition and an autoregressive moving average (ARMA) model for simultaneous susceptibility and R 2 measurements for the assessment of liver iron content (LIC) in patients with iron overload. Fifty magnetic resonance imaging (MRI) exams with magnitude and phase mGRE images were processed using the ARMA model, which provides fat-separated field maps, R 2 maps, and T(1) -W imaging. The LIC was calculated by measuring the susceptibility between the liver and the right transverse abdominal muscle from the field maps. The relationship between LIC derived from susceptibility measurements and LIC from R 2 measurements was determined using linear least-squares regression analysis. LIC measured from R 2 is highly correlated to the LIC with the susceptibility method (mg/g dry = 8.99 ± 0.15 × [mg Fe/mL of wet liver] -2.38 ± 0.29, R(2) = 0.94). The field inhomogeneity in the liver is correlated with R 2 (R(2) = 0.85). By using the ARMA model on complex mGRE images, both susceptibility and R 2-based LIC measurements can be made simultaneously. The susceptibility measurement can be used to help verify R 2 measurements in the assessment of iron overload.

Abstract C31: DMBA-induced skin tumors in HPV16 E7 transgenic mice are affected by bovine α-lactalbumin made lethal to tumor cells (BAMLET)

Abstract Background and Purpose: Human papillomavirus Type 16 (HPV16) infection is necessary but not alone a sufficient causal risk factor for cervical and other anogenital cancers and nearly 25% of head and neck malignancies (1, 2). HPV16 E7 is one of the important oncoproteins that promotes carcinogenesis. Most treatments for cervical precancers are ablative and few therapeutic drugs are available. Human α-Lactalbumin Made Lethal to Tumor Cells (HAMLET), a complex of Human α-Lactalbumin and oleic acid shows promise for treating skin papillomas by differentially inducing apoptosis in transformed cells without adverse effects on normal cells. Bovine α-Lactalbumin Made Lethal to Tumor Cells (BAMLET) has been shown to be biologically equivalent to HAMLET (3) and in vitro studies suggest BAMLET and HAMLET show similar cytotoxic effects in tumor cell lines (4). Further, in vitro studies suggest both a dose- and time-dependent response to BAMLET treatment (3–6). To determine the effect of BAMLET on tumor number, size and histological characteristics in vivo, we compared two groups of BAMLET-treated with normal saline (NS)-treated HPV16 E7 transgenic C57/BL6 mice (TG) and syngeneic mice receiving chemical carcinogen DMBA topically to induce skin tumor. Methods: For 56 TG and syngeneic mice, in six treatment groups, 100nmol/200μl DMBA was applied topically on the dorsal thoracic flank for up to 20 weeks. BAMLET, 0.7 mM, was applied daily for 7d before and either 11d (18d BAMLET) or up to 23 weeks (24w BAMLET) following DMBA initiation. As a comparison, NS was similarly applied to 10 TG and syngeneic mice for a total of 24 weeks. A series of bivariate zero-inflated repeated-measures Poisson (ZIP) models predicted the number of papillomas based on TG/syngeneic groupings, and treatment group. The fully adjusted model evaluated the effect of the TG, treatment group and duration, and time on study for predicting the number of tumors. Least-squares linear regression (LSLR) was used to estimate the effect of treatment on average tumor size at censoring or death, controlling for the effect of gender, among the transgenic mice. Results: On average, papillomas developed after 9 weeks of DMBA treatment. Analyses showed TG-mice developed more tumors than did syngeneic mice (p&amp;lt;0.0001), controlling for the effect of time on study (p&amp;lt;0.0001). In the fully adjusted analyses, the number of tumors was most affected by the TG (p&amp;lt;0.0001) and time on study (p&amp;lt;0.0001), but treatment showed no effect: 18d (p=0.9) and 24w (p=0.8) vs. normal saline (NS). Among transgenic mice, time on study was shorter than for syngeneic comparators and was a proxy indicator across treatment groups, confounding the ZIP analyses. Among transgenic mice, BAMLET treatment predicted average tumor size at censoring or death in the LSLR analysis. Specifically, among transgenic mice, the average tumor size was greatest for the 18d (μ=0.24 cm, p=0.003) and 24w BAMLET-treated (μ=0.20 cm, p=0.03) mice when compared to NS-treated controls (μ=0.12 cm). Discussion and Conclusion: These preliminary data suggest the effect of the transgene is strong on the number of tumors the result from DMBA treatment and on survival. This strong effect suggests we lack the power to detect an effect of BAMLET in transgenic mice. However, some data herein suggest BAMLET may increase average tumor size among HPV16-E7 transgenic mice. In light of positive findings in human clinical studies using the human analogue, HAMLET, understanding whether the effects of α-Lactalbumins and oleic acid complexes are modulated by HPV E6, E7, or E6/E7 oncogenes warrants further exploration. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the Second AACR International Conference on Frontiers in Basic Cancer Research; 2011 Sep 14-18; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2011;71(18 Suppl):Abstract nr C31.

Evaluation of a Fully Automated Method for the Determination of Sirolimus

Background Sirolimus (SRL) is a macrocyclic lactone, indicated for prevention of organ rejection after kidney transplantation. Therapeutic drug monitoring of this agent constitutes an important part to immunosuppressive treatment because of its narrow window of therapeutic efficacy. Routine methods include manual pretreatment of samples. The aim of this study was to evaluate the performance characteristics of an automated immunoassay that does not require manual pretreatment to quantify SRL in whole blood on the Dimension analyzer. Methods We examined 50 whole blood samples collected routinely from kidney transplant patients treated with SRL. The samples were analyzed simultaneously by an immunoassay on an IMx analyzer (reference method), which requires manual pretreatment step versus a totally automated immunoassay on the Dimension analyzer, which does not require this pretreatment. Results The Dimension SRL assay had a functional sensitivity of ≤2.4 ng/mL. Total imprecision was 15.6% at a concentration of 2.8 ng/mL; 10% at 7.9 ng/mL; and 5.2% at 18.4 ng/mL. Least-squares linear regression analysis yielded an r-value of 0.973 with the following equation: SRL-D = 1 .204*SRL-IMx − 0 .251 . Bland-Altman comparison showed a mean positive difference of 1.38 ng/mL (95% confidence interval, −1.10 to 3.82), namely, 17.2% for SRL Dimension. The Dimension assay to monitor SRL concentrations was an acceptable method for routine clinical use, with total assay imprecision (%CV) ranging from 10.0% to 5.2% within and above the therapeutic concentration range, respectively. Conclusion SRL IMx and Sirolimus Dimension methods show a good correlation ( r = 0.973), but the SRL Dimension method demonstrated a positive average difference of 17.2% compared with the IMx method. The Dimension assay to monitor whole blood SRL concentration does not require a manual pretreatment step, reducing turnaround time and making this method an attractive alternative for SRL analysis.

Hippocampal volumes are important predictors for memory function in elderly women

BackgroundNormal aging involves a decline in cognitive function that has been shown to correlate with volumetric change in the hippocampus, and with genetic variability in the APOE-gene. In the present study we utilize 3D MR imaging, genetic analysis and assessment of verbal memory function to investigate relationships between these factors in a sample of 170 healthy volunteers (age range 46–77 years).MethodsBrain morphometric analysis was performed with the automated segmentation work-flow implemented in FreeSurfer. Genetic analysis of the APOE genotype was determined with polymerase chain reaction (PCR) on DNA from whole-blood. All individuals were subjected to extensive neuropsychological testing, including the California Verbal Learning Test-II (CVLT). To obtain robust and easily interpretable relationships between explanatory variables and verbal memory function we applied the recent method of conditional inference trees in addition to scatterplot matrices and simple pairwise linear least-squares regression analysis.ResultsAPOE genotype had no significant impact on the CVLT results (scores on long delay free recall, CVLT-LD) or the ICV-normalized hippocampal volumes. Hippocampal volumes were found to decrease with age and a right-larger-than-left hippocampal asymmetry was also found. These findings are in accordance with previous studies. CVLT-LD score was shown to correlate with hippocampal volume. Multivariate conditional inference analysis showed that gender and left hippocampal volume largely dominated predictive values for CVLT-LD scores in our sample. Left hippocampal volume dominated predictive values for females but not for males. APOE genotype did not alter the model significantly, and age was only partly influencing the results.ConclusionGender and left hippocampal volumes are main predictors for verbal memory function in normal aging. APOE genotype did not affect the results in any part of our analysis.