Unknown Concentration Research Articles

Coupling Pre- and Postnatal Infant Exposures with Physiologically Based Pharmacokinetic Modeling to Predict Cumulative Maternal Levetiracetam Exposure During Breastfeeding.

Although breastfeeding ensures optimal infant development and maternal health, mothers taking medications may abandon breastfeeding because of uncertainties regarding toxicity to infants. Current methods in predicting infant risk to maternal medication exposure do not account for breastfeeding-related variability or in utero exposure via the umbilical cord (UC). Previously, our workflow integrated variability in infant anatomy and physiology, breast milk intake volume, and drug concentrations in breast milk using physiologically based pharmacokinetic (PBPK) modeling. The upper area under the curve ratio (UAR) was then calculated to assess infant risk from maternal drug. Herein, we enhanced this workflow by coupling pre- and postnatal exposures to predict the overall levetiracetam exposure in breastfeeding infants. A published pediatric PBPK model of levetiracetam was used to simulate an infant population (n = 100). Daily infant doses were simulated using a weight-normalized milk intake model to calculate volumes ingested across age groups, alongside literature-derived or simulated milk concentrations across maternal doses to predict infant concentrations. Published UC concentrations were used to develop a cord-coupled neonatal model (CCM), which was integrated with the PBPK and milk intake models and evaluated by comparing observed and simulated infant blood concentrations using a 90% prediction interval (PI). UC concentration data from 14 mothers were used to develop the CCM. A total of 16 paired (known milk concentrations) and two unpaired (unknown milk concentrations) individual infant concentrations were identified for evaluating the model along with population values of 64 infants from two age groups (2-4 and 7-31days). The CCM improved the predictions overall compared with the original workflow, largely due to improvements for the youngest age group evaluated. Overall, 83% (10 of 12) of the individual infant plasma concentrations were successfully captured within the 90% PI for the paired, quantifiable (i.e. above the limit of quantification) evaluation datasets. After administration of a maternal dose of levetiracetam 2000mg, the calculated UAR ranged from 0.13 to 0.27 for the 95th percentile infants. To our knowledge, this is the first report to combine prenatal levetiracetam exposures from the UC and postnatal exposures from breastfeeding to predict overall infant drug exposure. The results indicate that infant exposure in infants aged 0-7 days may approach therapeutic levels of levetiracetam in the highest-risk infants (i.e. 95th percentile), with a low likelihood of adverse effects based on published clinical studies. This integrated modeling approach provides a more holistic analysis of neonatal exposures. It can be applied in future studies to derive the UAR of drugs administered during breastfeeding to identify infants at risk of potential toxicity.

Application of improved matrix dilution method in quantitative analysis of Ni-Co-Mn ternary precursor

Abstract When using energy-dispersive X-ray fluorescence (EDXRF) to analyze Ni-Co-Mn (NCM) samples, if the standard sample's concentration greatly differs from the unknown sample's concentration, the traditional matrix dilution method requires repeated dilution and measurement. This makes the process time-consuming and labor-intensive. This study proposes an improved matrix dilution method to reduce sample preparation and analysis. This method first establishes a functional relationship model between the dilution factor and the characteristic X-ray intensity. Then the characteristic X-ray intensity of the analyzed element can be calculated by this model, avoiding unnecessary dilution and measurement steps. To verify the effectiveness of this method, the dilution factors and characteristic X-ray intensities of the test samples were fitted using the established functional relationship. The fitting results showed that the fitting coefficients of determination of the Mn, Co, and Ni were all 0.999. Quantitative analysis was performed on the characteristic X-ray intensity fitting values and measured values of the test samples. The results showed that the quantitative results of the two were consistent. The average error of the three elements for both methods was 1.1% and 0.7%, respectively. It shows that through the established functional relationship, the characteristic X-ray intensity can be effectively calculated by the dilution factor. This method can be applied to samples with identical elements and proportions of target elements, but with different concentrations, using the same set of standard samples.

Rapid Microfluidic Biosensor for Point-of-Care Determination of Rheumatoid Arthritis via Anti-Cyclic Citrullinated Peptide Antibody Detection.

Rheumatoid arthritis (RA) is a chronic autoimmune disorder that causes extensive damage to multiple organs and tissues and has no known cure. This study introduces a microfluidic detection platform that combines a microfluidic reaction chip with a micro-spectrometer to accurately detect the anti-cyclic citrullinated peptide antibody (anti-CCP Ab) biomarker, commonly associated with arthritis. The surface of the microfluidic reaction chip is functionalized using streptavidin to enable the subsequent immobilization of biotinylated-labeled cyclic citrullinated peptide (biotin-CCP) molecules through a streptavidin-biotin reaction. The modified chip is then exposed to anti-CCP Ab, second antibody conjugated with horseradish peroxidase (HRP) (2nd Ab-HRP), 3,3',5,5'-tetramethylbenzidine (TMB), and a stop solution. Finally, the concentration of the anti-CCP Ab biomarker is determined by analyzing the optical density (OD) of the colorimetric reaction product at 450 nm using a micro-spectrometer. The detection platform demonstrated a strong correlation (R2 = 0.9966) between OD and anti-CCP Ab concentration. This was based on seven control samples with anti-CCP Ab concentrations ranging from 0.625 to 100 ng/mL. Moreover, for 30 artificial serum samples with unknown anti-CCP Ab concentrations, the biosensor achieves a correlation coefficient of (R2 = 0.9650). The proposed microfluidic detection platform offers a fast and effective method for accurately identifying and quantifying the anti-CCP Ab biomarker. Thus, it offers a valuable tool for the early diagnosis and monitoring of RA and its progression in point-of-care settings.

Versatile hybrid magnetic core silver-shell (Fe3O4@PEI@Ag) microspheres based SERS substrates for detection of organic dyes pollutant

In recent years, the development of highly sensitive and versatile substrates for Surface-Enhanced Raman Scattering (SERS) has become pivotal in environmental monitoring. This study introduces a hybrid SERS substrate designed to enhance the detection and discrimination of organic dyes in aqueous environments. In this report, we present silver shell magnetic core (Fe3O4@PEI@Ag) microspheres as a versatile SERS substrate for the detection and differentiation of organic dyes, specifically malachite green (MG), crystal violet (CV), Rhodamine 6G (R6G), and Safranin O (S.O), which are often overlooked water pollutants. The core-shell structure of Fe3O4@PEI@Ag microspheres have been synthesized via seed-mediated growth method. The microspheres, integrates a magnetic core of iron oxide (Fe3O4) through a polymeric layer of polyethyleneimine (PEI) with silver shell (Ag), are optimized to act as magnetic separator and show SERS activity. The SEM measurements confirm the spherical shape of grown nano-particles whereas magnetization experiments confirm the presence of magnetic cores as well non-magnetic layers coating in the end products. These microspheres with aluminium (Al) base combination demonstrate high SERS sensitivity with enhancement factor of 1 × 105, 5.6 × 106, 6.4 × 106, and 4.2 × 105 for MG, CV, R6G, and S.O respectively. The detection limits have been found in the range between 10–8–10–10 for all four dyes. A linear relationship between Raman intensity and concentrations of dyes make it suitable for quantitative analysis of unknown concentration. Principal component analysis (PCA), a multivariate analysis has been adopted to discrimination of dyes. These dyes have been effectively detected quantitative in tap water to express substrate's suitability in real-world application. Their dual functionality, as SERS-active substrate and as magnetic separator, enhances their utility in real-world applications such as organic contaminants in aquatic environments.

Conjunctival and Corneal Endothelium Profile in a Sample of Healthy Electronic Cigarette Smokers

Objective: Though e-cigarette is thought of as a healthy alternative way of smoking, the unknown nicotine concentration level and chemical compounds from the aerosol mist and flavourings are potentially harmful and may exert irritation or damage to the ocular surface. Thus, a cross-sectional study was conducted to identify the conjunctival and corneal endothelium profile among healthy e-cigarette smokers, and the relationship between smoking behaviour with the conjunctival and corneal endothelium profile. Material and Methods: Seventeen healthy e-cigarette smokers and 17 non-smokers were recruited for this study where their palpebral redness, bulbar redness, limbal redness, conjunctival roughness, central corneal thickness, endothelial cell density, and coefficient of variation of endothelium cell area were assessed using slit lamp biomicroscope and specular microscope. Results: There was a non-significant, higher mean rank observed in the total palpebral redness, total bulbar redness, total limbal redness, total conjunctival roughness, central corneal thickness, endothelial cell density, and coefficient of variation of the endothelium cell area in e-cigarette smokers compared to non-smokers (p-value>0.05). Only smoking frequency and total palpebral redness showed a statistically significant, positive, and fair correlation (r=0.349, p-value=0.043), while no other smoking behaviour showed a significant correlation (p-value<0.05). Conclusion: The use of e-cigarettes showed no significant impact on the conjunctival and corneal profile among the users, but further research with comprehensive evaluation is required in a larger sample size of more established e-cigarette smoking profiles.

Optical actinometry for number density measurements in low-pressure plasmas: Advantages, error sources, and method validation

Number density of plasma-generated atoms or molecules is an important parameter for both fundamental research and applications. It can be measured in a straightforward manner, using vacuum-ultraviolet absorption spectroscopy, which is mainly possible in laboratory conditions as it may require bulky equipment, such as lasers. By contrast, optical actinometry is an alternative approach that only uses spontaneous emission from the plasma. This technique relies on the so-called corona excitation and uses emission line ratios between the gases with unknown and known concentrations (called actinometer in the last case). As a result of using line ratios, the additional density calibration is not required if the excitation cross sections are known. This study discusses Ar-based actinometry in low-pressure (roughly <1 kPa) plasma discharges with an emphasis on multiple line ratios. The work is particularly focused on the method’s applicability, the choice of Ar cross sections, and potential error sources. The influence of the additional excitation mechanisms is analyzed based on both experiments and modeling. The optical transitions for F, O, H, N, and P atoms along with expressions for their number density are presented, not requiring high optical resolution for measurements. For the sake of method validation, it is shown that in low-pressure radiofrequency discharges, a nearly excellent agreement between the actinometry data and the calibrated measurements can be achieved by careful selection of optical transitions.

Calibration-Free Analysis with Chronoamperometry at Microelectrodes.

Analytical methods are crucial for monitoring and assessing the concentration of important chemicals, and there is now a growing demand for methodologies that allow miniaturization, require lower sample volumes, and enable real-time analysis in the field. Most electroanalytical techniques depend on calibrations or standards, and this has several limitations, ranging from matrix interference, to stability problems, time required, cost and waste. Therefore, strategies that do not require standards or calibration curves greatly interest the analytical chemistry community. Here, we propose a new quantification method that does not rely on calibration and is only based on a single chronoamperometric curve recorded with a microelectrode. We show that satisfactory analytical information is obtained with just one chronoamperometric experiment that only takes a few seconds. We propose different data treatments to determine the unknown concentration, we consider the experimental conditions and instrument parameters, we report how parallel reactions affect the results, and we recommend procedures to implement the method in autonomous sensors. We also show that the concentration of several species can be derived if their E° values are sufficiently far apart or the sum of all concentrations if the E° values are too close. The proposed method was validated with a model redox system then further evaluated by determining ascorbic acid concentrations in standard solutions and food supplements, and paracetamol in a pain killer. The results for ascorbic acid were compared with those obtained by coulometry, and a good agreement was found, with a maximum deviation ca. 10.8%. The approach was also successfully applied to ascorbic acid quantification in solutions with different viscosity using ethylene glycol as a thickener.

Employing a switching valve to automate external standard calibration in inductively coupled plasma optical emission spectrometry

The traditional external standard calibration method (EC) is automated and simplified using a four-port switching valve (SV4) and a multi-signal approach that enables the generation of several calibration points from a single calibration solution. The SV4-EC method is applied to inductively coupled plasma optical emission spectrometry (ICP-OES) and is based on gradient dilution taking place within the instrument's sample introduction tubing. Both the calibration solution and the samples are diluted by a blank solution containing an internal standard species. Forty-five dilution points are collected over time while the solutions are mixed. Instrument responses from the calibration solution are then plotted against those from the samples, and the slope of the calibration curve is used to determine the unknown analyte concentrations in the samples. The method is used to determine Ba, Co, Cr, Cu, Fe, Mn, Ni, V and Zn in coconut water, creek water, green tea, mouthwash, soft drink, vinegar, and vodka. Limits of detection are in the 0.0002–0.009 mg L−1 (n = 10) range, with precision on the order of 0.4 %–3 % RSD. Analyte percent recoveries from a 0.5 mg L−1 spike are in the ranges of 88.4 %–111 %, 88.9 %–111 %, and 88.0 %–111 % for EC, SV4-EC, and the internal-standard-corrected method (SV4-EC/Sc), respectively. No statistically significant difference is observed between EC and SV4-EC recoveries for any of the sample matrices evaluated. Comparable results between EC and SV4-EC were also found for the analysis of two certified reference materials, Bovine Liver and Oyster Tissue. Based on a single calibration solution, the SV4-EC method requires caution when preparing the calibration standard to minimize measurement bias.

Inference on the common mean direction of several Fisher-von Mises-Langevin populations with unknown concentration parameters

The problem of combining information from several samples for estimating or testing a common mean for normal populations has been extensively studied in the statistical literature. In this paper, we take up this problem in the context of the common mean direction of several Fisher-von Mises-Langevin (FvML) distributions. The concentration parameters are taken to be unknown and heterogeneous. A non-iterative combined estimator is proposed and is seen to have substantially better risk performance than individual sample mean directions and a grand mean direction in a simulation study. Further, a test based on this non-iterative estimator is proposed, and nonparametric bootstrap and permutation resampling methods are developed for its implementation. Two more alternative tests are proposed and their implementation is carried out using nonparametric bootstrap resampling. A detailed simulation study shows that these test procedures achieve the nominal size and have good power performance. An ‘R’ package is developed for the implementation of the tests. A real data set is considered for illustrating the procedures.

Interplay of Kinetic and Thermodynamic Factors in the Stationary Composition of Vapor-Liquid-Solid IIIVxV1-x Nanowires.

Compositional control over vapor-liquid-solid III-V ternary nanowires based on group V intermix (VLS IIIVxV1-x NWs) is complicated by the presence of a catalyst droplet with extremely low and hence undetectable concentrations of group V atoms. The liquid-solid and vapor-solid distributions of IIIVxV1-x NWs at a given temperature are influenced by the kinetic parameters (supersaturation and diffusion coefficients in liquid, V/III flux ratio in vapor), temperature and thermodynamic constants. We analyze the interplay of the kinetic and thermodynamic factors influencing the compositions of VLS IIIVxV1-x NWs and derive a new vapor-solid distribution that contains only one parameter of liquid, the ratio of the diffusion coefficients of dissimilar group V atoms. The unknown concentrations of group V atoms in liquid have no influence on the NW composition at high enough levels of supersaturation in liquid. The simple analytic shape of this vapor-solid distribution is regulated by the total V/III flux ratio in vapor. Calculating the temperature-dependent desorption rates, we show that the purely kinetic regime of the liquid-solid growth occurs for VLS IIIVxV1-x NWs in a wide range of conditions. The model fits the data well on the vapor-solid distributions of VLS InPxAs1-x and GaPxAs1-x NWs and can be used for understanding and controlling the compositions of any VLS IIIVxV1-x NWs, as well as modeling the compositional profiles across NW heterostructures in different material systems.

Occurrence, Concentration, and Distribution of 35 PFASs and Their Precursors Retained in 20 Stormwater Biofilters.

Current knowledge about the fate and transport behaviors of per- and polyfluoroalkyl substances (PFASs) in urban stormwater biofilter facilities is very limited. C5-14,16 perfluoroalkyl carboxylic acids [perfluorinated carboxylic acids (PFCAs)], C4,8,10 perfluoroalkanesulfonic acids (PFSAs), methyl-perfluorooctane sulfonamide acetic acid (MeFOSAA, a PFSA precursor), and unknown C6-8 PFCA and perfluorooctanesulfonic acid precursors were frequently found in bioretention media and forebay sediments at Σ35PFAS concentrations of <0.03-19 and 0.064-16 μg/kg-DW, respectively. Unknown C6-8 PFCA precursor concentrations were up to ten times higher than the corresponding PFCAs, especially at forebays and biofilters' top layer. No significant trend could be attributed to PFAS and precursor concentrations versus depth of filter media, though PFAS concentrations were 2-3 times higher in the upper layers on average (significant difference between the upper (0-5 cm) and deepest (35-50 cm) layer). PFASs had a similar spatial concentration distribution in each filter media (no clear difference between short- and long-chain PFASs). Commercial land use and organic matter were important factors explaining the concentration variations among the biofilters and between the sampling depths, respectively. Given the comparable PFAS accumulations in deeper and superficial layers and possible increased mobility after precursor biotransformation, designing shallow-depth, nonamended sand biofilters or maintaining only the top layer may be insufficient for stormwater PFAS management.

Extended Kalman filter for quantifying hydrogen leaks in PEM fuel cells by estimating oxygen concentration

Hydrogen transfer leaks are one of the most important life-limiting faults in polymer electrolyte membrane fuel cells (PEMFCs). Hydrogen transfer leaks result in a reduction in the amount of oxygen available in the cathode (air) channel, with large leaks resulting in oxygen starvation and hydrogen emission. This paper aims to develop an adaptive extended Kalman filter (EKF) to estimate the unknown oxygen concentration, which is then used to infer hydrogen leaks. To this end, the paper first develops the lumped model of the fuel cell from a pseudo-2D model of a fuel cell. Next, a (non-adaptive) EKF is developed to estimate the fuel cell states under both normal and oxygen-starved conditions. The adaptive EKF is then implemented by adding the unknown hydrogen leak to the list of estimated states. Finally, the paper demonstrates the efficacy of the proposed adaptive EKF by using it to accurately estimate unknown hydrogen leaks in a high-fidelity virtual fuel cell under excessively noisy conditions.

A new spectral simulating method based on near-infrared hyperspectral imaging for evaluation of antibiotic mycelia residues in protein feeds

Antibiotic mycelia residues (AMRs) contain antibiotic residues. If AMRs are ingested in excess by livestock, it may cause health problems. To address the current problem of unknown pixel-scale adulteration concentration in NIR-HSI, this paper innovatively proposes a new spectral simulation method for the evaluation of AMRs in protein feeds. Four common protein feeds (soybean meal (SM), distillers dried grains with solubles (DDGS), cottonseed meal (CM), and nucleotide residue (NR)) and oxytetracycline residue (OR) were selected as study materials. The first step of the method is to simulate the spectra of pixels with different adulteration concentrations using a linear mixing model (LMM). Then, a pixel-scale OR quantitative model was developed based on the simulated pixel spectra combined with local PLS based on global PLS scores (LPLS-S) (which solves the problem of nonlinear distribution of the prediction results due to the 0%-100% content of the correction set). Finally, the model was used to quantitatively predict the OR content of each pixel in hyperspectral image. The average value of each pixel was calculated as the OR content of that sample. The implementation of this method can effectively overcome the inability of PLS-DA to achieve qualitative identification of OR in 2%-20% adulterated samples. In compared to the PLS model built by averaging the spectra over the region of interest, this method utilizes the precise information of each pixel, thereby enhancing the accuracy of the detection of adulterated samples. The results demonstrate that the combination of the method of simulated spectroscopy and LPLS-S provides a novel method for the detection and analysis of illegal feed additives by NIR-HSI.

A method for estimating the outer exposure of dairy cows to deoxynivalenol (DON) and zearalenone (ZEN) as a precondition for risk assessment based on inner exposure with toxin residue levels in blood and urine as indicators

DON and ZEN residues in the blood and urine of dairy cows can be used to predict the outer exposure to DON and ZEN expressed per kilogram diet for a risk evaluation based on comparisons to critical dietary concentrations. This method was used to evaluate the exposure of dairy cows from 12 farms located in Brandenburg, Germany, fed rations with unknown DON and ZEN concentrations (N = 244). The corresponding diet concentrations predicted by different methods from analyzed blood and urine samples varied significantly amongst farms from 0 to 1.6 mg/kg for DON and 0 to 3.0 mg/kg for ZEN at a reference dry matter content of 88% but independently of lactational state (post-partum vs. early lactation). This significant variation was noticed below the critical dietary DON concentration of 5 mg/kg, while the ZEN concentration in one farm exceeded the critical ZEN level of 0.5 mg/kg markedly. Predicted DON concentrations of rations increased with the proportion of maize silage, while the high ZEN concentration found in one farm was most likely related to a higher proportion of sugar beet pulp supposedly highly contaminated by ZEN. Exceeding the critical dietary ZEN concentration and significant variations in DON contents below the critical level was not related to performance, reproductive performance, and health-related traits of cows. For a more consistent evaluation of possible associations between the inner exposure of cows to DON and ZEN, more frequent longitudinal observations of both mycotoxin residue levels and performance and health traits are required.

Is redox zonation an appropriate method for determining the stage of natural remediation in deep contaminated groundwater?

Groundwater contamination resulting from petroleum development poses a significant threat to drinking water sources, especially in developing countries. In situ natural remediation methods, including microbiological processes, have gained popularity for the reduction of groundwater contaminants. However, assessing the stage of remediation in deep contaminated groundwater is challenging and costly due to the complexity of diverse geological conditions and unknown initial concentrations of contaminants. This research proposes that redox zonation may be a more convenient and comprehensive indicator than the concentration of contaminants for determining the stage of natural remediation in deep groundwater. The combination of sequencing microbial composition using the high-throughput 16S rRNA gene and function predicted by FAPROTAX is a useful approach to determining the redox conditions of different contaminated groundwater. The sulfate-reducing environment, represented by Desulfobacteraceae, Peptococcaceae, Desulfovibrionaceae, and Desulfohalobiaceae could be used as characteristic early stages of remediation for produced water contamination in wells with high concentrations of SO42−, benzene, and salinity. The nitrate-reducing environment, enriched with microorganisms related to denitrification, sulfur-oxidizing, and methanophilic microorganisms could be indicative of the mid stages of in situ bioremediation. The oxygen reduction environment, enriched with oligotrophic and pathogenic Sphingomonadaceae, Caulobacteraceae, Syntrophaceae, Legionellales, Moraxellaceae, and Coxiellaceae, could be indicative of the late stages of remediation. This comprehensive approach could provide valuable insights into the process of natural remediation and facilitate improved environmental management in areas of deep contaminated groundwater.

Concentration Enrichment in a Dissolving Microdroplet: Accessing Sub-nanomolar Electroanalysis.

Droplet evaporation has previously been used as a concentration enrichment strategy; however, the measurement technique of choice requires quantification in rather large volumes. Electrochemistry has recently emerged as a method to robustly probe volumes even down to the attoliter (10-18 L) level. We present a concentration enrichment strategy based on the dissolution of a microdroplet placed on the surface of a Au ultramicroelectrode (radius ∼ 6.25 μm). By precisely positioning a 1,2-dichloroethane microdroplet onto the ultramicroelectrode with a microinjector, we are able to track the droplet's behavior optically and electrochemically. Because the droplet spontaneously dissolves over time, given the relative solubility of 1,2-dichloroethane in the water continuous phase, the change in volume with time enriches the concentration of the redox probe (Cp2*(Fe)II) in the droplet. We demonstrate robust electrochemical detection down to sub-nM (800 pM) concentrations of Cp2*(Fe)II. For this droplet, 800 pM constitutes only about 106 molecules. We extend the strategy in a single-blind study to determine unknown concentrations, emphasizing the promise of the new methodology. These results take voltammetric quantification easily to the sub-μM regime.

Therapeutic drug monitoring of vancomycin in surgical patients using a validated HPLC method.

Vancomycin is being used for the treatment of a variety of infections caused by methicillin resistant Staphylococcus aureus and methicillin susceptible Staphylococcus aureus. Therapeutic drug monitoring (TDM) is highly recommended for ensuring the safe and effective therapy with vancomycin. A reliable and cost-effective bioanalytical method is required for TDM as well as pharmacokinetic studies of vancomycin. A selective, sensitive, and cost effective HPLC method was developed and validated for quantification of vancomycin concentrations in human plasma. The mobile phase was a mixture of buffer (50 mM ammonium dihydrogen phosphate, pH 2.4) and acetonitrile 88 : 12 v/v. The separation was carried on C18 column (125 × 4.6 mm, particle size 5 µm) with isocratic flow rate of 0.370 mL/min at room temperature with UV detection at 215 nm. The method was validated for sensitivity, accuracy, and precision as well as stability of vancomycin in human plasma by following European Medicine Agency (EMA) guideline. Therapeutic drug monitoring of vancomycin was performed by quantifying the trough concentrations of vancomycin in 65 human plasma samples after administration of therapeutically relevant dose. The developed method was sensitive enough to quantify vancomycin concentrations as low as 0.25 mg/L in human plasma. Moreover, the method was proved accurate and precise in terms of quantifying the unknown concentration of vancomycin. The evaluation of short-term, long-term, and freeze-thaw stability proved the stability of vancomycin in human plasma. The TDM of vancomycin by using this method showed that 39 (60%) samples were within the target trough concentration range (TTCR), i.e. 10 - 20 mg/L, while 23 samples (35.4%) were below the TTCR, and 3 samples (4.6%) were above this range. The developed method is sensitive and cost effective for quantification of vancomycin in human plasma. The results of sample analysis shows that the developed method can be used reliably for TDM of vancomycin.

Theoretical and Experimental Determinations of the Hydrophilic–Lipophilic Balance (HLB) of Representative Oils and Lecithins

The hydrophilic–lipophilic balance (HLB) is a valuable parameter used to determine the relative hydrophobicity of a compound based on its chemical structure. This semi-empirical parameter has been instrumental in formulating oil-in-water and water-in-oil emulsions using well-characterized ingredients with known HLB values. However, recent trends toward the use of minimally processed “virgin” oils of therapeutic or nutritional value may render the reported “required HLB” values inaccurate. Minimally processed oils can contain numerous compounds at varying or unknown concentrations, rendering the HLB value incalculable. Factors such as regional source, growing season, and processing method contribute to the variability in oil composition. Furthermore, the solubilization of lipophilic bioactives in oils can significantly alter the HLB of the oil phase in a concentration-dependent manner. This complicates the formulation of emulsions, as the HLB values of both the oil phase and emulsifiers must be closely matched to achieve stable formulations. This study presents a simple and efficient experimental method to determine an HLB value of a complex ingredient without resorting to lengthy Design-of-Experiment (DoE) matrices and trial-and-error approaches. The optimal HLB of a formulation can be determined from a series of experiments in which two well-characterized surfactants of known HLB values are mixed at varying proportions with an unknown oil phase, where the HLB of the oil is considered to match the HLB value of the surfactants combined at the proportion at which nanoemulsions with the smallest, most stable oil droplets are formed. Similarly, when the HLB values of the oil phase and other contributing components are precisely known, the unknown HLB of a complex natural surfactant can be calculated. These calculations assist in formulating emulsions efficiently and effectively by ensuring optimal compatibility among all the components.

Statistical Inference in Circular Structural Model and Fitting Circles to Noisy Data

It is well known that commonly used algorithms for circle fitting perform poorly when sampling distribution of the points is not symmetric with respect to the circle center, for example, when the points are sampled from a circle arc. To overcome this difficulty we introduce and study a parametric circular structural model. In this model the points on the circumference are assumed to be sampled according to the von Mises distribution with unknown concentration and mean direction parameters. We develop maximum likelihood and method of moments estimators of the circle center and radius, and study their statistical properties. In particular, we show that the proposed maximum likelihood estimator is asymptotically normal and efficient. We also develop a test of uniformity for the sampling distribution along the circle. Based on the derived theoretical results we propose a numerically stable circle fitting algorithm, investigate its accuracy in a simulation study, and illustrate its behavior in a real data example. Supplementary materials for this article are available online.

DNA-based assay for calorimetric determination of protein concentrations in pure or mixed solutions.

It was recently reported that values of the transition heat capacities, as measured by differential scanning calorimetry, for two globular proteins and a short DNA hairpin in NaCl buffer are essentially equivalent, at equal concentrations (mg/mL). To validate the broad applicability of this phenomenon, additional evidence for this equivalence is presented that reveals it does not depend on DNA sequence, buffer salt, or transition temperature (Tm). Based on the equivalence of transition heat capacities, a calorimetric method was devised to determine protein concentrations in pure and complex solutions. The scheme uses direct comparisons between the thermodynamic stability of a short DNA hairpin standard of known concentration, and thermodynamic stability of protein solutions of unknown concentrations. Sequences of two DNA hairpins were designed to confer a near 20°C difference in their Tm values. In all cases, evaluated protein concentrations determined from the DNA standard curves agreed with the UV-Vis concentration for monomeric proteins. For multimeric proteins evaluated concentrations were greater than determined by UV-Vis suggesting the calorimetric approach can also be an indicator of molecular stoichiometry.