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The soluble epoxide hydrolase (sEH) is possibly both a marker for and target of numerous diseases. Herein, we describe a homogeneous mix-and-read assay for the detection of human sEH based on using split-luciferase detection coupled with anti-sEH nanobodies. Selective anti-sEH nanobodies were individually fused with NanoLuc Binary Technology (NanoBiT), which consists of a large and small portion of NanoLuc (LgBiT and SmBiT, respectively). Different orientations of the LgBiT and SmBiT-nanobody fusions were expressed and investigated for their ability to reform the active NanoLuc in the presence of the sEH. After optimization, the linear range of the assay could reach 3 orders of magnitude with a limit of detection (LOD) of 1.4 ng/mL. The assay has a high sensitivity to human sEH and reached a similar detection limit to our previously reported conventional nanobody-based ELISA. The procedure of the assay was faster (30 min total) and easy to operate, providing a more flexible and simple way to monitor human sEH levels in biological samples. In general, the immunoassay proposed here offers a more efficient detection and quantification approach that can be easily adapted to numerous macromolecules.

Elemental impurities contained in a drug product create a risk for patients. Potential toxic elemental impurities are defined and classified in the Guideline for Elemental Impurities Q3D(R1). Among the finished product dosage forms, parenteral products could be critical for elemental impurities because elemental impurities go directly into systemic circulation. One of the most frequently used methods to determine elemental impurities is inductively coupled plasma–mass spectrometry (ICP–MS). In this study we aimed to develop and validate an ICP-MS method for the determination of 24 elemental impurities in micafungin powder for infusion manufactured in our own facility. Results showed that correlation coefficients of calibration curves were found higher than 0.99 for all elements in the determined ranges and all validation parameters were achieved successfully. With this method, all 24 elemental impurities can be tracked throughout the shelf life of the product. [ABSTRACT FROM AUTHOR]

In this tutorial review, we provide a guiding reference on the good practice in building calibration and correlation experiments, and we explain how the results should be evaluated and interpreted. The review centers on calibration experiments where the relationship between response and concentration is expected to be linear, although certain of the described principles of good practice can be applied to non-linear systems, as well. Furthermore, it gives prominence to the meaning and correct interpretation of some of the statistical terms commonly associated with calibration and regression. To reach a mutual understanding in this significant field, we present, through a practical example, a step-by-step procedure, which deals with typical challenges related to linearity and outlier assessment, calculation of the associated error of the predicted concentration, and limits of detection. The utilization of regression lines to compare analytical methods is also elaborated. The results of regression and correlation data are acquired by implementing the Excel spreadsheet of Microsoft, being perhaps one of the most widely used user-friendly software in education and research. [ABSTRACT FROM AUTHOR]

Simple Summary: Digestibility is a crucial factor for assessing feed costs for dairy cattle. Rapid analysis of fecal composition is necessary to obtain accurate data on digestive efficiency. Traditional wet chemical analysis methods are time-consuming; therefore, the potential of near-infrared reflectance spectroscopy technique was explored for assessing fecal chemical components in dairy cattle. The technique has been widely used to predict the nutritional contents of raw materials and complete feeds. In the present study, near-infrared reflectance spectroscopy could successfully predict the chemical composition of dairy cattle feces, thereby reducing analysis time and workload. Traditional methods for determining the chemical composition of cattle feces are uneconomical. In contrast, near-infrared reflectance spectroscopy (NIRS) has emerged as a successful technique for assessing chemical compositions. Therefore, in this study, the feasibility of NIRS in terms of predicting fecal chemical composition was explored. Cattle fecal samples were subjected to chemical analysis using conventional wet chemistry techniques and a NIRS spectrometer. The resulting fecal spectra were used to construct predictive equations to estimate the chemical composition of the feces in both cows and calves. The coefficients of determination for calibration (RSQ) were employed to evaluate the calibration of the predictive equations. Calibration results for cows (dry matter [DM], RSQ = 0.98; crude protein [CP], RSQ = 0.93; ether extract [EE], RSQ = 0.91; neutral detergent fiber [NDF], RSQ = 0.82; acid detergent fiber [ADF], RSQ = 0.89; ash, RSQ = 0.84) and calves (DM, RSQ = 0.92; CP, RSQ = 0.89; EE, RSQ = 0.77; NDF, RSQ = 0.76; ADF, RSQ = 0.92; ash, RSQ = 0.97) demonstrated that NIRS is a cost-effective and efficient alternative for assessing the chemical composition of dairy cattle feces. This provides a new method for rapidly predicting fecal chemical content in cows and calves. [ABSTRACT FROM AUTHOR]

A novel Eu(tta)3([4,4′-(t-bu)2-2,2′-bpy)] complex (tta-thenoyltrifluoroacetone), a ratiometric luminescent-based optical sensor for the quantitative determination of aluminum ion, is synthesized and characterized using XRD and 1H NMR. The XRD data reveal the slightly distorted octahedral structure. The complex displays a bright red emission at 613 nm in methanol which is characteristic of europium (III) complexes. Upon the addition of Al3+ ions, the red emission disappears, and a new blue emission at 398 nm emerges, manifesting the ratiometric nature of the complex. The turn-off of the red emission and turn-on of the blue emission are attributed to Eu-Al trans-metalation, as supported by Raman data that show the emergence of Al-O vibrations at 418, 495, and 608 cm−1 concomitant with the disappearance of Eu-O and Eu-N bond vibrations. Most aluminum sensors are known to suffer from interferences from other metals including Cu2+, Co2+, and Cd2+. However, the sensor reported here is tested for 11 common cations and shows no interference on sensitivity. To the best of our knowledge, this is the first known Eu-based luminescence sensor that successfully exhibited the ability to detect aluminum ions in ppb levels in aqueous environments. The calculated Al3+ binding constant is 2.496 × 103 ± 172. The complex shows a linear relationship in the range of 0–47.6 ppb (1.76 × 10−6 M) Al3+ and the limit of detection (LOD) is 4.79 ppb (1.77 × 10−7 M) in MeOH. ICP-OES is used for validation of the sensor complex in water and then it was used for quantitative detection of Al3+ ions in water as a real-life application. The complex can accurately detect Al3+ ions in the range of 4.97–24.9 ppb (1.84 × 10−7 M–9.2 × 10−7 M) with an LOD of 8.11 ppb (2.99 × 10−7 M). Considering that the aluminum ion serves no recognized function within the human body, its accumulation can lead to severe neurological disorders, including Parkinson’s and Alzheimer’s diseases. With the LOD value significantly lower than the WHO-recommended maximum permissible level of 200 ppb for aluminum in drinking water, even without high-power laser-aided signal enhancement, the sensor shows promise for detecting trace amounts of aluminum contamination in water. Therefore, it can significantly aid in the monitoring of even the smallest aluminum ion contamination in drinking water, industrial effluents, and natural water bodies.

In all ultrasonic material evaluation methods, transducers and sensors play a key role of mechanoelectrical conversion. Their transduction characteristics must be known quantitatively in designing and implementing successful structural health monitoring (SHM) systems. Yet, their calibration and verification have lagged behind most other aspects of SHM system development. This study aims to extend recent advances in quantifying the transmission and receiving sensitivities to normally incident longitudinal waves of ultrasonic transducers and acoustic emission sensors. This paper covers extending the range of detection to lower frequencies, expanding to areal and multiple sensing methods and examining transducer loading effects. Using the refined transmission characteristics, the receiving sensitivities of transducers and sensors were reexamined under the conditions representing their actual usage. Results confirm that the interfacial wave transmission is governed by wave propagation theory and that the receiving sensitivity of resonant acoustic emission sensors peaks at antiresonance.

There are few wearable sensors suitable for daily monitoring of wrist and finger movements for hand-related healthcare applications. Here, we describe the development and validation of a novel algorithm for magnetically counting hand movements. We implemented the algorithm on a wristband that senses magnetic field changes produced by movement of a magnetic ring worn on the finger (the "Manumeter"). The "HAND" (Hand Activity estimated by Nonlinear Detection) algorithm assigns a "HAND count" by thresholding the real-time change in magnetic field created by wrist and/or finger movement. We optimized thresholds to achieve a HAND count accuracy of ~85% without requiring subject-specific calibration. Then, we validated the algorithm in a dexterity-impaired population by showing that HAND counts strongly correlate with clinical assessments of upper extremity (UE) function after stroke. Finally, we used HAND counts to test a recent hypothesis in stroke rehabilitation that real-world UE hand use increases only for stroke survivors who achieve a threshold level of UE functional capability. For 29 stroke survivors, HAND counts measured at home did not increase until the participants' Box and Blocks Test scores exceeded ~50% normal. These results show that a threshold-based magnetometry approach can non-obtrusively quantify hand movements without calibration and also verify a key concept of real-world hand use after stroke.

There are few wearable sensors suitable for daily monitoring of wrist and finger movements for hand-related healthcare applications. Here, we describe the development and validation of a novel algorithm for magnetically counting hand movements. We implemented the algorithm on a wristband that senses magnetic field changes produced by movement of a magnetic ring worn on the finger (the "Manumeter"). The "HAND" (Hand Activity estimated by Nonlinear Detection) algorithm assigns a "HAND count" by thresholding the real-time change in magnetic field created by wrist and/or finger movement. We optimized thresholds to achieve a HAND count accuracy of ~85% without requiring subject-specific calibration. Then, we validated the algorithm in a dexterity-impaired population by showing that HAND counts strongly correlate with clinical assessments of upper extremity (UE) function after stroke. Finally, we used HAND counts to test a recent hypothesis in stroke rehabilitation that real-world UE hand use increases only for stroke survivors who achieve a threshold level of UE functional capability. For 29 stroke survivors, HAND counts measured at home did not increase until the participants' Box and Blocks Test scores exceeded ~50% normal. These results show that a threshold-based magnetometry approach can non-obtrusively quantify hand movements without calibration and also verify a key concept of real-world hand use after stroke.

Calcium fluoride formed by the reaction between ammonium bifluoride and calcium chloride was investigated as a dominating matrix for quantitative analysis by laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). Transformation from a solid sample to the calcium fluoride-based matrix permitted quantitative analysis based on calibration standards made from elemental standards. A low abundance stable calcium isotope, i.e. 44Ca+, was monitored as the internal standard for quantitative analysis by LA-ICP-MS. Correlation coefficient factors for multiple elements were obtained with values over 0.999. The results for multiple elements in a certified reference material of soil (NIST SRM 2710a) agreed with the certified values in the range of expanded uncertainty, indicating the present method was valid for quantitation of elements in solid samples.

Assessment of the adequacy of a proposed linear calibration curve is necessarily subjective in chemical analysis. If the outlier points in calibration are not identified and discarded, the constructed model will not have much validity and does not warrant the accuracy and precision of prediction step. Recognizing of influential points, outlier data, and discarding them is one of the steps in data processing that has been considered in various sciences. The outlier points can arise from (I) bad design of calibration set and (II) gross error in doing experiments. Therefore, we aimed to extract a map that recognizes the following issues: (A) the existence of data with high regression coverage that is far from the rest and will strongly affect the accuracy of the calibration equation, high leverage points; (B) large error in the experimental process: The recorded signal does not match the desired concentration; and (C) points with a concentration lower than the limit of quantification, which is calculated by considering the standard error of regression instead of the standard deviation of blank. The efficiency of the proposed roadmap will be reviewed, and this will give a new perspective on the calibration equation to avoid common mistakes in analytical chemistry. To achieve the above goal, visual and statistically significant tests will be used and all tests will be performed in a simple Microsoft Excel environment. [ABSTRACT FROM AUTHOR]

Acoustic emission (AE) sensors and ultrasonic transducers were characterized for the detection of Rayleigh waves (RW). Small aperture reference sensors were characterized first using the fracture of glass capillary tubes in combination with a theoretical displacement calculation, which utilized finite element method (FEM) and was verified by laser interferometer. For the calibration of 18 commercial sensors and two piezoceramic disks, a 90° angle beam transducer was used to generate RW pulses on an aluminum transfer block. By a substitution method, RW receiving sensitivity of a sensor under test was determined over the range of frequency from 22 kHz to 2 MHz. Results were compared to the sensitivities to normally incident waves (NW) and to other guided waves (GW). It was found that (1) NW sensitivities are always higher than RW sensitivities, (2) differences between NW and RW receiving sensitivities are dependent on frequency and sensor size, (3) most sensors show comparable RW and GW receiving sensitivities, especially those of commonly used AE sensors, and (4) the receiving sensitivities of small aperture (1 mm diameter) sensors behave differently from larger sensors.

Individual perspiration level indicates a person's physical status as well as their comfort level. Therefore, continuous perspiration level measurement enables people to monitor these conditions for applications including fitness assessment, athlete physical status monitoring, and patient/elderly care. Prior work on perspiration (sweat) sensing required the user either to be static or to wear the adhesive sensor directly on the skin, which limits users' mobility and comfort. In this paper, we present a novel conductive thread-based textile sensor that measures an individual's on-cloth sweat quantity. The sensor consists of three conductive threads. Each conductive thread is surrounded by a braided cotton cover. An additional braided cotton cover is placed outside the three conductive threads, holding them in a position that is stable for measurement. the sensor can be embedded at various locations on a person's clothing. When the person sweats, the cotton braids absorb the sweat and change the conductivity (resistance) between conductive threads. We used a voltage dividing circuit to measure this resistance as the sensor output (DC). We then conducted a sensor calibration to map this measured voltage to the quantity of electrolyte solution (with the same density as sweat) applied to the sensor. We used this sensor to measure individuals' perspiration quantity and infer their perceived perspiration levels. The system is able to limit the average prediction error to 0.4 levels when compared to five pre-defined perceived perspiration levels.

The coefficient of correlation (r) and the coefficient of determination (R 2 or r 2) have long been used in analytical chemistry, bioanalysis and forensic toxicology as figures demonstrating linearity of the calibration data in method validation. We clarify here what these two figures are and why they should not be used for this purpose in the context of model fitting for prediction. R 2 evaluates whether the data are better explained by the regression model used than by no model at all (i.e. a flat line of slope = 0 and intercept |$\bar y$|⁠), and to what degree. Hopefully, in the context of calibration curves, the fact that a linear regression better explains the data than no model at all should not be a point of contention. Upon closer examination, a series of restrictions appear in the interpretation of these coefficients. They cannot indicate whether the dataset at hand is linear or not, because they assume that the regression model used is an adequate model for the data. For the same reason, they cannot disprove the existence of another functional relationship in the data. By definition, they are influenced by the variability of the data. The slope of the calibration curve will also change their value. Finally, when heteroscedastic data are analyzed, the coefficients will be influenced by calibration levels spacing within the dynamic range, unless a weighted version of the equations is used. With these considerations in mind, we suggest to stop using r and R 2 as figures of merit to demonstrate linearity of calibration curves in method validations. Of course, this does not preclude their use in other contexts. Alternative paths for evaluation of linearity and calibration model validity are summarily presented. [ABSTRACT FROM AUTHOR]

Hyperspectral remote sensing is known to suffer from wavelength bands blocked by atmospheric gases. Short-wave infrared hyperspectral imaging at in situ installations is shown to be affected by water vapour even if the pathlength of light through air is only hundreds of centimetres. This impact is especially noticeable with large variations of relative humidity, the coefficient of variation reaching 5 % in our test case. Using repeated calibrations of imaging system at the same relative humidity as in the measurement, we were able to reduce the coefficient of variation to 1 %. The measurement variations are also shown to induce significant error in material classification. Polymer type identification was selected as the test case for material classification. The measurement variations due to the change in relative humidity are shown to result in 20 % classification error at its minimum. With repeated calibrations or by eliminating the most affected wavelength bands from measurements, we were able to reduce the classification error to less than 1 %. Such improvement of measurement and classification precision may be important for industrial applications such as waste sorting, polymer classification etc.

Calibration transfer is an essential activity in analytical chemistry in order to avoid a complete recalibration. Currently, the most popular calibration transfer methods, such as piecewise direct standardization and dynamic orthogonal projection, require a certain amount of standard or reference samples to guarantee their effectiveness. To achieve higher efficiency, it is desirable to perform the transfer with as few reference samples as possible. To this end, we propose a new calibration transfer method by using a calibration database from a master instrument (source domain) and only one spectrum with known properties from a slave instrument (target domain). We first generate a counterpart of this spectrum in the source domain by a multivariate Gaussian kernel. Then, we train a filter to make the response function of the slave instrument equivalent to that of the master instrument. To avoid the need for labels from the target domain, we also propose an unsupervised way to implement our method. Compared with several state-of-the-art methods, the results on one simulated dataset and two real-world datasets demonstrate the effectiveness of our method. Traditionally, the demand for certain amounts of reference samples during calibration transfer is cumbersome. Our approach, which requires only one reference sample, makes the transfer process simple and fast. In addition, we provide an alternative for performing unsupervised calibration transfer. As such, the proposed method is a promising tool for calibration transfer. [Display omitted] • A new calibration transfer method is introduced, which requires only one spectrum from target domain. • The calibration transfer method can be conducted in an unsupervised way. • A multivariate Gaussian kernel is introduced to generate a virtual sample in source domain. • Results from simulated and real-world datasets demonstrate the effectiveness of our method. [ABSTRACT FROM AUTHOR]

The article offers information on production method of Molnupiravir. It mentions It is freely soluble in methanol R, soluble in dehydrated ethanol R, sparingly soluble in acetonitrile R and water R; and also mentions Molnupiravir should be kept in tightly closed containers, protected from moisture, as it is slightly hygroscopic and exhibits polymorphism.

Currently, the use of time of flight (TOF)-mass spectrometry (MS) in quantitative analysis of small molecules is rare. Recently, the quantitative performance of TOF mass analyzers has improved due to the advancements in TOF technology. We evaluated a Q-TOF-MS in different modes, i.e., Q-TOF-full scan (Q-TOF-FS), Q-TOF-enhanced-full scan (Q-TOF-En-FS), MS(E), Q-TOF-targeted (Q-TOF-TGT), Q-TOF-enhanced-targeted (Q-TOF-En-TGT), and compared their quantitative performance against a unit resolution LC-MS-MS (tandem quadrupole) platform. The five modes were investigated for sensitivity, linearity, signal-to-noise ratio, recovery and precision using 11-nor-9-carboxy-Δ(9)-tetrahydrocannabinol (THC-COOH) as a model compound in electrospray ionization (ESI) with negative polarity. Preliminary studies indicated that Q-TOF-FS mode was the least linear and precise; hence, it was eliminated from further investigation. Total imprecision in remaining four modes was 0.99) and linearity (range, 5-455 ng/mL) for THC-COOH analysis when compared with LC-MS-MS. We also investigated the performance of the same four modes using methamphetamine in positive ESI. Quantitative data obtained by Q-TOF-En-TGT and MS(E), using both positive and negative ESI, suggest that these modes performed better than the other modes. While unit resolution LC-MS-MS remains the optimal technique for quantification, our data showed that Q-TOF-MS can also be used to quantify small molecules in complex biological specimens.

Recommendations are given for metrological terminology in analytical chemistry. Analytical chemistry is defined, and concepts related to laboratory practice are termed and defined. Recommendations are given concerning the terminology of quality assurance in analytical chemistry. Terms draw on the extensive quality literature, particularly from ISO. [ABSTRACT FROM AUTHOR]

This paper demonstrates an automated computer vision system for outdoor tree crop enumeration in a seedling nursery. The complete system incorporates both hardware components (including an embedded microcontroller, an odometry encoder, and an uncalibrated digital color camera) and software algorithms (including microcontroller algorithms and the proposed algorithm for tree crop enumeration) required to obtain robust performance in a natural outdoor environment. The enumeration system uses a three-step image analysis process based upon: (1) an orthographic plant projection method integrating a perspective transform with automatic parameter estimation; (2) a plant counting method based on projection histograms; and (3) a double-counting avoidance method based on a homography transform. Experimental results demonstrate the ability to count large numbers of plants automatically with no human effort. Results show that, for tree seedlings having a height up to 40 cm and a within-row tree spacing of approximately 10 cm, the algorithms successfully estimated the number of plants with an average accuracy of 95.2% for trees within a single image and 98% for counting of the whole plant population in a large sequence of images.

This work uses digital images, near-infrared (NIR) spectra, data fusion, and multivariate calibration to develop fast, non-laborious, and cheap methods for determining moisture and total protein and phosphorus contents in powdered chicken egg samples. These analyzed samples were obtained after breaking, homogenizing, lyophilizing, and pulverizing whole chicken eggs. Digital images were captured employing a scanner, while NIR spectra were recorded using benchtop and portable spectrometers. The proposed multivariate calibration methods were better in terms of correlation coefficient (r) and ratio performance deviation of prediction (RPD) for predicting total protein content using digital images (r = 0.995 and RPD = 9.55) than those obtained by benchtop and portable NIR spectra. On the other hand, in predicting moisture (r = 0.974 and RPD = 4.35) and total phosphorus content (r = 0.98 and RPD = 4.3), the benchtop NIR produced better results. The analytical performance of data fusion methods was slightly poorer than the best methods using preprocessed NIR spectra or digital images separately. Therefore, these proposed methods proved to be a good alternative tool for destructive chemical analysis, given that powdered chicken egg samples could be analyzed without using chemicals and without generating waste harmful to health and the environment, following the basic principles of Green Chemistry. [Display omitted] • Development of digital images and NIR chemometrics methods for chicken egg analysis. • Determination of the quality parameters in lyophilized chicken eggs. • Successful determination of moisture, and total protein and phosphorus contents. • Valuable alternative to standard reference methods for routine analyses. [ABSTRACT FROM AUTHOR]

• The risk of bisphenols (BPA, BPF, and BPS) in thermal papers and canned food samples was assessed. • A method for determining bisphenols based on HPLC-DAD was developed and validated. • An integrated calibration method was modified and supported by the H-point standard addition method to compensate interference effects. • BPA concentration in canned food products was exceeded. • Risk factors connected to the receipts (BPF and BPS) proved harmful to cashiers due to long exposure time. The most crucial purpose of the measurement is to obtain a reliable result that reflects the actual qualitative and/or quantitative features of the tested material. The overriding goal of analytical chemistry is to obtain accurate results after compensating of various interference effects as well as non-linear calibration dependence. A new approach based on an integrated calibration method (ICM) supported by H-point standard addition method (HPSAM) has been used to improve the quality of analytical results. The proposed methodological approach was extended using the step-by-step dilution procedure, and five measurement conditions were used to eliminate multiplicative, additive, and non-linear interferences. On this basis, a set of estimations is obtained to improve the quality of the analytical results. The analytical usefulness of the proposed approach was tested on the example of the determination of three compounds from the group of bisphenols (BPs) using the chromatographic technique - HPLC-DAD (high-performance liquid chromatography with diode array detection). Compared to the reference method - fluorescence spectroscopy - the obtained results were characterized by excellent accuracy (RE=3 % in most cases). The developed methodology allowed to carry out a risk assessment on BPA, BPF, and BPS present in samples of shop receipts and canned food. Store clerks have been shown to be particularly vulnerable to PBF and BPS in receipts due to skin permeation (exposure factors were equal to 308.97 µg/g for BPF and 181.89 µg/g for BPS). Consumers should also pay close attention to the BPA found in canned food samples (the average concentration was equal to 20.61 µg/mL, and the tolerable daily intake was exceeded over 165.000 times). The analytical method and the methodological approach were evaluated using the RGB model and the AGREE approach - it was shown that the method can be successfully used for other analytical purposes (the method is White) and is environmentally friendly (Significance=0.63). [ABSTRACT FROM AUTHOR]

To support the development of a dynamic in vitro human pharmacokinetic/pharmacodynamic simulation model for biofilm-mediated infections and study stability of meropenem, an LC-MS/MS method for the determination of meropenem in Luria Bertani (LB) media was developed and validated in an API2000 LC-MS/MS system. A partial validation was also performed in M9 media. Sample aliquots of 100μL (or 25μL for M9 media) were mixed with the internal standard (IS) ceftazidime and filtered. The filtrate was directly injected onto a C8 column eluted with ammonium formate (10mM, pH 4) and acetonitrile (0.1% formic acid) in a gradient mode. ESI(+) and MRM with ion pair m/z 384→68 for meropenem and m/z 547→468 for the IS were used for quantification. The calibration curve concentration range was 50 to 25,000ng/mL. The recovery was over 98%. In LB media, significant signal suppression was observed throughout the time period of detection when compared with mobile phase solvents, but the matrix effect was compensated well with the IS. In M9 media, much less signal suppression was observed. The method is simple, fast, and reliable. Using the method, stability of meropenem in LB and M9 media were tested. No significant degradation was observed for at least 8h in both LB media (37°C) and M9 media (30°C), but more than 15% degradation was observed overnight (∼20h). The method was transferred to an API5000 LC-MS/MS system using meropenem-d6 as the IS.

Measurement of proteasome activity is fast becoming a commonly used assay in many laboratories. The most common method to measure proteasome activity involves measuring the release of fluorescent tags from peptide substrates in black microplates. Comparisons of black plates used for measuring fluorescence with different properties show that the microplate properties significantly affect the measured activities of the proteasome. The microplate that gave the highest reading of trypsin-like activity of the purified 20S proteasome gave the lowest reading of chymotrypsin-like activity of the 20S proteasome. Plates with medium binding surfaces from two different companies showed an approximately 2-fold difference in caspase-like activity for purified 20S proteasomes. Even standard curves generated using free 7-amino-4-methylcoumarin (AMC) were affected by the microplate used. As such, significantly different proteasome activities, as measured in nmol AMC released/mg/min, were obtained for purified 20S proteasomes as well as crude heart and liver samples when using different microplates. The naturally occurring molecule betulinic acid activated the chymotrypsin-like proteasome activity in three different plates but did not affect the proteasome activity in the nonbinding surface microplate. These findings suggest that the type of proteasome activity being measured and sample type are important when selecting a microplate.

A simple, specific, accurate and economic reverse phase liquid chromatographic method was developed for the estimation of Sofosbuvir in all polymorphic form. Mobile phase contain acetonitrile and 0.05M ammonium acetate (pH 7.6) in ratio of 50:50 (v/v). A logarithmic calibration curve was plotted from 10 µg/mL to 60 µg/mL (r = 0.9989) for sofosbuvir, with the limit of detection (LOD) and the limit of quantification (LOQ) of 0.245 μg/mL and 0.816 μg/mL, respectively. The developed method was highly validated and practiced for the assurance of sofosbuvir raw materials with acceptable and non-objectionable accuracy and precision results (recovery 99–102%, RSD

Partial least square (PLS) analysis is the most favourite tool in chemometrics to develop calibration models. PLS technique allows us to decipher even the complex systems by analysing all the variables instead of looking at them one at a time. PLS technique not only capture the maximum variation associated with predictor (i.e. spectra) and predicted (i.e. concentration) variables but also maximises the correlation between them. The present article describes the working scheme of the PLS algorithm. It also describes important technical details that need to be considered for developing a parsimonious and robust calibration model. [ABSTRACT FROM AUTHOR]

Featured Application: This review will offer a global overview of the chemometric approaches most commonly used in the field of spectroscopy-based food analysis and authentication. Three different scenarios will be surveyed: data exploration, calibration and classification. Basic and simple descriptions of the main multivariate techniques exploited in such a domain along with a comprehensive outline of their most recent and interesting applications will be provided. In the last decades, spectroscopic techniques have played an increasingly crucial role in analytical chemistry, due to the numerous advantages they offer. Several of these techniques (e.g., Near-InfraRed—NIR—or Fourier Transform InfraRed—FT-IR—spectroscopy) are considered particularly valuable because, by means of suitable equipment, they enable a fast and non-destructive sample characterization. This aspect, together with the possibility of easily developing devices for on- and in-line applications, has recently favored the diffusion of such approaches especially in the context of foodstuff quality control. Nevertheless, the complex nature of the signal yielded by spectroscopy instrumentation (regardless of the spectral range investigated) inevitably calls for the use of multivariate chemometric strategies for its accurate assessment and interpretation. This review aims at providing a comprehensive overview of some of the chemometric tools most commonly exploited for spectroscopy-based foodstuff analysis and authentication. More in detail, three different scenarios will be surveyed here: data exploration, calibration and classification. The main methodologies suited to addressing each one of these different tasks will be outlined and examples illustrating their use will be provided alongside their description. [ABSTRACT FROM AUTHOR]

Quantitative nuclear magnetic resonance (qNMR) is an analytical technique that offers numerous advantages in pharmaceutical applications including minimum sample preparation and rapid data collection times with no need for response factor corrections, being a powerful tool for assaying drug content in both drug discovery and early drug development. In the present work, we have applied qNMR, using both the internal standard and the electronic reference to access in vivo concentrations 2 calibration methods, to assess the purity of RI76, a novel antifungal drug candidate. NMR acquisition and processing parameters were optimized in order to obtain spectra with intense, well‐resolved signals of completely relaxed nuclei. The analytical method was validated following current guidelines, demonstrating selectivity, linearity, accuracy, precision, and robustness. The calibration approaches were statistically compared, and no significant difference was observed when comparing the obtained results and their dispersion in terms of relative standard deviation. The proposed qNMR method may, therefore, be used for both qualitative and quantitative assessments of RI76 in early drug development and for characterization of this compound. [ABSTRACT FROM AUTHOR]

A review is presented of recent multi-way calibration protocols involving three-, four- and five-way data. A brief description of the various data structures and processing models is shown, with emphasis on model selection based on the matching between the data structure and the physicochemical model assumptions. Calibration research works are then discussed, classified according to the type of measured instrumental data and model/algorithm selection. Image 1 • Recent multi-way calibration protocols are reviewed. • The relationship between data structures and chemometric models is detailed. • Second-, third- and fourth-order data generation is discussed. • Implications to green analytical chemistry are underlined. [ABSTRACT FROM AUTHOR]

[Display omitted] • PFCE2: an updated parameter-free calibration enhancement (PFCE) for NIR data. • PFCE2 improves robustness with two novel constraints on model coefficients. • PFCE2 enhances efficiency and versatility with a multitask learning method. • PFCE2 tackles scenarios of calibration transfer, maintenance, and enhancement. Near-infrared (NIR) spectroscopy is a widely used technique for chemical analysis, but it has faced challenges of calibration transfer, maintenance, and enhancement among different instruments and conditions. The parameter-free calibration enhancement (PFCE) framework was developed to address these challenges with non-supervised (NS), semi-supervised (SS), and full-supervised (FS) methods. This study presented PFCE2, an updated version of the PFCE framework that incorporates two new constraints and a new method to improve the robustness and efficiency of calibration enhancement. First, normalized L2 and L1 constraints were introduced to replace the correlation coefficient (Corr) constraint used in the original PFCE. These constraints preserve the parameter-free feature of PFCE and impose smoothness or sparsity on the model coefficients. Second, multitask PFCE (MT-PFCE) was proposed within the framework to address the calibration enhancement among multiple instruments, enabling the framework to be versatile for all possible calibration transfer situations. Demonstrations conducted on three NIR datasets of tablets, plant leaves, and corn showed that the PFCE methods with the new L2 and L1 constraints can result in more accurate and robust predictions than the Corr constraint, especially when the standard sample size is small. Moreover, MT-PFCE could refine all models in the involved scenarios at once, leading to significant enhancement in model performance, compared to the original PFCE method with the same data requirements. Finally, the applicable situations of the PFCE framework and other analogous calibration transfer methods were summarized, facilitating users to choose suitable methods for their application. The source codes written in both MATLAB and Python are available at https://github.com/JinZhangLab/PFCE and https://pypi.org/project/pynir/ , respectively. [ABSTRACT FROM AUTHOR]