Development Of Analytical Methods Research Articles

A comprehensive review of analytical strategies for validating RP-HPLC methods of aceclofenac and thiocolchicoside in bulk drug and formulation

This comprehensive review explores the analytical method development and validation of Aceclofenac and Thiocolchicoside bulk drugs and formulations using Reverse Phase High-Performance Liquid Chromatography (RP-HPLC). Aceclofenac, a nonsteroidal anti-inflammatory drug (NSAID), and Thiocolchicoside, a muscle relaxant, are commonly co-formulated for the treatment of pain and inflammation. The review discusses the principles and strategies involved in RP-HPLC method development, emphasizing factors such as stationary phase selection, mobile phase composition, and detection wavelength optimization. Furthermore, it highlights the importance of method validation in pharmaceutical analysis, covering parameters such as specificity, linearity, accuracy, precision, robustness, and system suitability. The literature review section examines previous studies on RP-HPLC methods developed for Aceclofenac and Thiocolchicoside, summarizing key findings and comparing different methodologies. Challenges and limitations encountered during method development and validation are discussed, along with recent advances in RP-HPLC methodology. Finally, the review outlines future research directions and potential applications of RP-HPLC in studying the pharmacokinetics and bioavailability of Aceclofenac and Thiocolchicoside formulations.

Analytical Method Development and Validation Based on Simple Color Reactions and Microwave Plasma–Atomic Emission Spectrometry (MP-AES) for the Detection of Adulteration in Teff Injera (Ethiopian Flatbread)

Analytical Method Development and Validation Based on Simple Color Reactions and Microwave Plasma–Atomic Emission Spectrometry (MP-AES) for the Detection of Adulteration in Teff Injera (Ethiopian Flatbread)

Development of analytical methods and method validation for the qualitative and quantitative determination of Carboxymethyl Cellulose (CMC) in yogurt and ayran

This study presents the development and validation of analytical methods for the qualitative and quantitative determination of Carboxymethyl Cellulose (CMC) in yogurt and ayran. The methods were evaluated for their detection limit (LOD), quantification limit (LOQ), and method detection limit (MDL) across multiple samples, demonstrating robust sensitivity with MDL and LOD values of 0.03% for both yogurt and ayran. Recovery studies showed high accuracy, with recovery rates between 98% and 100%, and consistent recovery within the acceptable range of 97–103%, reinforcing the methods' reliability. The quantitative analysis exhibited strong repeatability and reproducibility, with low relative standard deviations (RSDr and RSDR), confirming minimal intra-day and inter-day variability. The calibration curves for CMC analysis demonstrated excellent linearity with high coefficients of determination (R2 = 0.9985 for yogurt and 0.9951 for ayran), ensuring accurate quantification over a wide concentration range. Measurement uncertainty analysis further validated the methods' precision and accuracy, showing low relative uncertainties for trueness, repeatability, and reproducibility. Robustness evaluations indicated that the methods maintained consistent recovery rates despite variations in pH, heating time, and sample quantity, highlighting their reliability under different conditions. For qualitative analysis, the visual images method showed exceptional performance with perfect sensitivity and specificity, accurately identifying all positive and negative samples without any false positives or negatives. This high level of accuracy makes the visual images method a valuable tool for ensuring product safety and compliance with quality standards in the dairy industry. Overall, the validated analytical methods for CMC detection in yogurt and ayran demonstrated high precision, accuracy, and reliability, making them essential for quality control and regulatory compliance in dairy production.

Greenness appraisal and spectrophotometric estimation of carvedilol in pharmaceutical formulations and study kinetic parameters

Numerous studies have established that carvedilol acts as a vasodilator and is effective in managing hypertension. Consequently, this research focuses on the development and validation of analytical methods for the quantification of carvedilol. Various techniques, including UV/Vis spectrophotometric methods, have been investigated alongside innovative, straightforward, accurate, and sensitive approaches. In this study, we established a method based on the interaction between carvedilol and alizarin yellow dye in an aqueous medium, allowing for a reaction time of 20 min for completion. Upon conclusion of the reaction, a purple-colored product is formed, which exhibits maximum absorption at a wavelength of 536 nm. This method adheres to Beer's law within the concentration range of 10–50 µg/mL, with a molar absorptivity of 2.560×103 L·mol−1·cm−1, a Sandel index of 0.158 µg. cm−2, the detection limit of 0.4190 µg/mL, and the quantitative limit is 1.2698 µg/mL. The recovery rate was determined to be 100.7010 %, and the relative standard deviation did not exceed 1.3094 %. The method was applied to estimate the concentration of carvedilol in its pharmaceutical formulation in tablet form CARVEDISAM. Additionally, the kinetics of the resulting complex were studied, revealing that the kinetics are of first order. To assess the environmental impact of contemporary UV spectrophotometric methods, the Green Analytical Greenness Metric (AGREE) software and the Green Analytical System Index (GAPI) were utilized to evaluate the greenness profile. The developed UV method is more sustainable and environmentally friendly.

Carboxy-PEG-thiol functionalized gold nanoparticle conjugates for the detection of SARS-CoV-2: Detection tools and analytical method development

Addressing the need for accessible SARS-CoV-2 testing, carboxy-PEG 12-thiol functionalized gold nanoparticles conjugates were developed for rapid point-of-care (POC) detection against SARS-CoV-2 spike protein, pseudo-SARS-CoV-2, and authentic Beta SARS-CoV-2 virus particles. These conjugates leverage gold nanoparticles (AuNPs) as signal transducers, cross-linked to either angiotensin-converting enzyme 2 (ACE2) or SARS-CoV-2 spike protein receptor-binding domain (RBD) antibodies as bioreceptors and showed a distinct color shift from pink to blue. To assess their POC feasibility, the conjugates were integrated into facemasks and breathalyzers, wherein aerosolized SARS-CoV-2 antigens were successfully detected, producing a color change within 10 and 30 minutes for the breathalyzer and facemask prototypes, respectively. Furthermore, we explored quantitative analysis using varying concentrations of SARS-CoV-2 spike protein. Both conjugates demonstrated a linear relationship between blue color intensity and virus concentration, with linear ranges of 0.08–0.6 ng/mL and 0.04–0.5 ng/mL, respectively. Low limits of detection and quantification were also achieved. They exhibited specificity, responding solely to SARS-CoV-2 even in complex matrices containing diverse proteins, including the SARS-CoV-1 spike protein. Precision tests yielded coefficient of variations below 2 %, showcasing their remarkable reproducibility. This work presents a promising approach for rapid, sensitive, and specific POC detection of SARS-CoV-2 paving the way for improved pandemic response and management.

Tetrodotoxin and the state-of-the-art progress of its associated analytical methods

Tetrodotoxin (TTX), which is found in various marine organisms, including pufferfish, shellfish, shrimp, crab, marine gastropods, and gobies, is an effective marine toxin and the cause of many seafood poisoning incidents. Owing to its toxicity and threat to public health, the development of simple, rapid, and efficient analytical methods to detect TTX in various food matrices has garnered increasing interest worldwide. Herein, we reviewed the structure and properties, origin and sources, toxicity and poisoning, and relevant legislative measures of TTX. Additionally, we have mainly reviewed the state-of-the-art progress of analytical methods for TTX detection in the past five years, such as bioassays, immunoassays, instrumental analysis, and biosensors, and summarized their advantages and limitations. Furthermore, this review provides an in-depth discussion of the most advanced biosensors, including cell-based biosensors, immunosensors, and aptasensors. Overall, this study provides useful insights into the future development and wide application of biosensors for TTX detection.

Identification of Major Interfering Substances for Heavy Metal Determination in Northern Sea Areas of Sri Lanka

This study investigated the physicochemical characteristics of seawater from five locations along the northern Sri Lankan coast, encompassing areas with varying degrees of anthropogenic activity. The analysis revealed significant variations in several parameters, potentially influenced by human influences. The results reveal significant variations in several parameters. For instance, turbidity levels varied from 1.88 NTU in Thalaiyadi to 13.3 NTU in Pannai, with Pannai, Myliddy, and Kakkaithivu exceeding the recommended limit of 5 NTU. Total suspended solids (TSS) ranged from 3 mg/L in Thalaiyadi to 83 mg/L in Pannai, surpassing the recommended limit of 30 mg/L. Electrical conductivity (EC) ranged from 45,700 µS/cm in Nainathivu to 49,500 µS/cm in Pannai, exceeding the typical seawater range. Nitrate levels ranged from 10.4 mg/L in Thalaiyadi to 19.1 mg/L in Myliddy. Major cations such as calcium (361 mg/L to 417 mg/L), magnesium (1,222 mg/L to 1,327 mg/L), and sodium (10,140 mg/L to 10,530 mg/L) also showed significant differences across locations. These findings highlight the need for continuous monitoring and effective management strategies to mitigate the negative impacts of anthropogenic activities on these coastal ecosystems. Furthermore, the complex seawater matrix presents challenges for heavy metal determination using Graphite Furnace Atomic Absorption Spectroscopy (GFAAS) due to spectral interferences from major cations, non-specific matrix effects, and interferences from organic matter, turbidity, and suspended solids. Careful consideration of these factors through background correction techniques, matrix modifiers, sample pre-treatment, and optimization of analysis parameters is crucial for accurate heavy metal determination in these environments. This study contributes to a better understanding of the environmental conditions and emphasizes the need for further research on heavy metal contamination and the development of robust analytical methods tailored to address the challenges posed by the complex seawater matrix in northern Sri Lanka.

Synthesis of Carbon Dots from Peltophorum Pterocarpum Flowers for Selective Fluorescence Detection of Carbendazim.

In this study, carbon dots (CDs) were synthesized from Peltophorum pterocarpum flowers as the precursor material using the hydrothermal method. The fluorescence emission spectra of the resulting Peltophorum pterocarpum CDs (PP-CDs) exhibited excitation-independent behavior, showing the fluorescence emission peak at 410 nm when excited at 330 nm. This method is simple, rapid and well consistent with the green chemistry and sustainable analytical method development. The as-synthesized PP-CDs acted as a promising fluorescent probe for detecting carbendazim (CBZ) via aggregation-induced emission mechanism, showing a linear response to CBZ concentrations ranging from 1 to 30 μM, with a detection limit of 5.41 nM. This method was successfully applied to quantify CBZ in food samples, achieving excellent recoveries of 99% with a relative standard deviation (RSD) of less than 2%.

Extractable Perfluoroalkyl Carboxylic Acids and Sulfonates in Food Contact Materials: Development of a Simple Analytical Method with Ultrasonic Extraction, Dispersive Sorbent Clean-Up, and LC-MS/MS Quantification

Extractable Perfluoroalkyl Carboxylic Acids and Sulfonates in Food Contact Materials: Development of a Simple Analytical Method with Ultrasonic Extraction, Dispersive Sorbent Clean-Up, and LC-MS/MS Quantification

Identification of chemical components of large-leaf yellow tea by ultra performance liquid chromatography-quadrupole time-of-flight mass spectrometry

Large-leaf yellow tea, a slightly fermented yellow tea that is unique to China, has a stronger hypoglycemic effect than other tea varieties, such as green and black tea. Research on large-leaf yellow tea has focused on its hypoglycemic effect owing to the lack of comprehensive techniques to characterize its chemical components; thus, its development and further promotion are limited. Therefore, the development of a reliable analytical method to fully characterize the chemical components of large-leaf yellow tea is urgently required. In this study, a reliable strategy based on the data-acquisition technology of ultra performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q TOF/MS) was established to rapidly screen and analyze the main chemical components of large-leaf yellow tea by combining the information of neutral loss groups and characteristic fragment ions. The chromatographic separation experiments were performed on a Waters ACQUITY UPLC BEH C18 column (100 mm×2.1 mm, 1.7 μm) with gradient elution using 0.1% formic acid aqueous solution and acetonitrile as the mobile phases. The flow rate was 0.2 mL/min, the sample volume was 2 μL, and the column temperature was 35 ℃. The mass spectral information of the components in a large-leaf yellow tea solution was collected using the full-information tandem MS (MSE) technique in positive and negative ion modes. The specific chemical components of large-leaf yellow tea was identified as follows. First, a self-established database of tea chemical components was constructed based on the literature. The mass spectral cleavage pathways of different types of compounds in large-leaf yellow tea were then sorted using reference substances, and the characteristics of the fragment ions and neutral loss groups were summarized. The precise mass-to-charge ratio of the target chemical components were then obtained based on the mass spectral information. Finally, the structures of the compounds in large-leaf yellow tea were confirmed based on their chromatographic retention times, mass spectral cleavage pathways, characteristic fragment ions, and neutral loss groups. A total of 87 chemical components, including 10 catechins, 32 flavonoids, 16 phenolic acids, 12 tannins, 6 theaflavins, and 11 compounds in other classes, were identified in large-leaf yellow tea. Representative compounds of various classes, including gallocatechin gallate, quercetin, vitexin, gallic acid, chlorogenic acid, 1,3,6-tri-O-galloyl-β-D-glucose, and theaflavin, were selected, and their characteristic fragment ions and neutral loss groups were investigated in detail to reveal the cleavage pathways of different types of compounds in large-leaf yellow tea. The UPLC-Q TOF/MS method established in this study can comprehensively identify the main chemical components of large-leaf yellow tea in a simple, highly sensitive, stable, and reliable manner. This study provides a scientific basis and data support for the discovery of functional ingredients and quality evaluation of large-leaf yellow tea.

A 96-position platform for magnetic sorbent-based dispersive microextraction: application to the determination of tetrahydrocannabinol and cannabidiol in saliva of cannabis smokers

BackgroundIn order to obtain sustainable analytical methods, it is essential to develop kinetically efficient sample preparation strategies in which equilibria are reached faster, as dispersive extraction techniques. In addition, the higher the reduction in size the higher number of extraction vessels can be located and thus the higher number of samples can be simultaneously treated. All this increases sample throughput, and contributes to the reduction of chemical waste, and energy and sample consumption. In this sense, multiposition extraction platforms are smart strategies to achieve these goals, but they are scarcely developed for dispersive extraction techniques. ResultsTaking miniaturized stir bar sorptive dispersive microextraction (mSBSDME) as a starting point, a 96-position extraction platform has been developed using a 96-position stirring plate and a tailor-designed 3D-printed support for locating the miniaturized extraction vessels, achieving a high-throughput miniaturized sample preparation strategy. In order to show the applicability of this novel platform, the determination of Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD) in human saliva has been carried out and applied to samples collected after the consumption of marijuana and legal CBD-rich cannabis. Only 100 μL of saliva were needed for the analysis and good analytical features in terms of linearity (at least up to 500 ng mL−1), limits of detection (0.7 and 2.8 ng mL−1 for THC and CBD, respectively), and precision (RSD ≤14%) were achieved. SignificanceThe miniaturization of the vessel allows the use of small volumes of sample (i.e., a few microliters) and the treatment of 96 samples in parallel, being the first proposal for carrying out dispersive sorbent-based microextraction under the concept of 96-well format. Additionally, this new workflow contributes to the development of analytical methods that meet the three pillars of sustainability, i.e., greenness and easily affordable in terms of economics and applicability.

Development of analytical method for determination of 1,3-dimethylamylamine in sports nutrition and bodybuilding supplements using pH-switchable deep eutectic solvents followed by high-performance liquid chromatography-diode array detector.

In this work, an easy, safe, simple, and efficient pH-switchable deep eutectic solvents (DESs)-based liquid phase microextraction followed by high-performance liquid chromatography-diode array detector analysis was developed for the determination of 1,3-dimethylamylamine (DMAA). The switchability of the obtained DESs was investigated by changing the pH. Then the best-selected DES was characterized and the application of the selected DES in the extraction of DMAA from sports nutrition and bodybuilding supplements was investigated. The DES synthesized from l-menthol: oleic acid in a molar ratio of 1:2 had the highest efficiency in the extraction of the target compound. Under the optimum conditions, (50µL of DES, 100µL of 4mol/L KOH, 100µL of 4mol/L HCl, extraction time of 40 s and without salt addition) the calibration graph was linear in the range of 0.05-100µg/kg and limit of detection was 0.02µg/kg. The relative standard deviations including intra-day and inter-day for 10.0µg/kg of DMAA in real samples were 2.7% (n=7) and 5.3% (n=7), respectively. The enrichment factor and percentage extraction recovery of the method were 283 and 85%, respectively. The relative recoveries for DMAA in different samples were in the range of 90%-109%.

An ultrasensitive and specific fluorescence split-aptasensor for VEGF165 detection based on nicking enzyme-assisted 3D DNA walker coupling with CRISPR-Cas12a

The overexpression of vascular endothelial growth factor 165 (VEGF165) in cancer cells plays a pivotal role in promoting tumor metastasis by facilitating their excessively rapid proliferation and division. Hence, the development of analytical methods possessing high sensitivity and resistance to interference is imperative for the detection of VEGF165. Various types of aptasensors have been devised for VEGF165 detection; however, the performance of these biosensors can be influenced by non-target signals caused by conformational changes in unbound aptamers. The paper shows the creation of a precise and sensitive fluorescence biosensor designed to detect VEGF165 by using a VEGF165-specific split aptamer. Additionally, this biosensor employs nicking enzyme-assisted DNA walker coupling with CRISPR-Cas12a to achieve dual-signal amplification. The VEGF165 calibration curve shows a detection limit of 268 fM and has a broad linear range from 5 to 4000 nM. The fluorometric biosensor was utilized to detect VEGF165 in human serum and cellular homogenate samples, yielding good outcomes. The innovative design serves as proof of concept and demonstrates significant potential in detecting various targets.

Development and validation of a green analytical method for determining fourteen bisphenols in bee pollen by ultra-high-performance liquid chromatography-tandem mass spectrometry

A new analytical method was developed and validated to determine fourteen bisphenols (A, B, C, E, F, M, P, S, Z, AF, AP, BP, FL, PH) in bee pollen using ultra-high-performance liquid chromatography-tandem mass spectrometry. Two different sample treatments were proposed and evaluated: one based on the QuEChERS (quick, easy, cheap, effective, rugged & safe) approach and the other utilizing microextraction with a supramolecular solvent (SUPRAS). In both cases, average analyte recovery ranged between 71 % and 114 %, and the matrix effect was between −45 % and +5 %, although it was not significant when using the QuEChERS-based method (<±20 %). The environmental impact of both sample treatments was assessed using different analytical metrics, with both procedures classified as environmentally friendly, though slightly better results were obtained for SUPRAS. The method was fully validated, showing that the QuEChERS approach had better overall performance, particularly regarding sensitivity and matrix effect. Consequently, the QuEChERS methodology was applied to determine bisphenols in thirty bee pollen samples from different Spanish regions. Residues of three bisphenols (M, P, and S) were detected, although only bisphenol S was quantified in several samples at low concentration levels (<7 μg kg−1), which is below the established specific migration limit (SML; 50 μg kg−1). However, regarding human health, the estimated daily intake, target hazard quotient, and hazard index assessed were higher than acceptable limits, suggesting a potential risk for human consumers.

Analytical Methods for the Determination of Pharmaceuticals and Personal Care Products in Solid and Liquid Environmental Matrices: A Review.

Among the various compounds regarded as emerging contaminants (ECs), pharmaceuticals and personal care products (PPCPs) are of particular concern. Their continuous release into the environment has a negative global impact on human life. This review summarizes the sources, occurrence, persistence, consequences of exposure, and toxicity of PPCPs, and evaluates the various analytical methods used in the identification and quantification of PPCPs in a variety of solid and liquid environmental matrices. The current techniques of choice for the analysis of PPCPs are state-of-the-art liquid chromatography coupled to mass spectrometry (LC-MS) or tandem mass spectrometry (LC-MS2). However, the complexity of the environmental matrices and the trace levels of micropollutants necessitate the use of advanced sample treatments before these instrumental analyses. Solid-phase extraction (SPE) with different sorbents is now the predominant method used for the extraction of PPCPs from environmental samples. This review also addresses the ongoing analytical method challenges, including sample clean-up and matrix effects, focusing on the occurrence, sample preparation, and analytical methods presently available for the determination of environmental residues of PPCPs. Continuous development of innovative analytical methods is essential for overcoming existing limitations and ensuring the consistency and diversity of analytical methods used in investigations of environmental multi-class compounds.

Racial capitalism and firearm violence: Developing a theoretical framework for firearm violence research examining structural racism

Despite the early promise of centering structural racism in explanatory models of firearm violence, there are noticeable gaps in what's been produced thus far; in particular, a deeper and more serious engagement with long-standing theories of racism is needed to further enrich our understanding of how structural inequalities produce unequal burdens of firearm-related harms. Thus, building on theories and concepts from a range of academic fields and Black philosophical perspectives, we developed a theoretical framework to help explain the role of place-based structural racism on firearm violence disparities. A central component of our framework is the concept racial capitalism, which contends that racial exploitation and the accumulation of assets depend on and reinforce one another. In this article, we present our framework and highlight how two processes related to racial capitalism—racialized dispossession and racialized spatial stigma—are connected with geographic disparities in firearm violence. We also present the results of an ecological cross-sectional study that reveals a potential key association between racial capitalism and firearm violence disparities on the neighborhood-level. We used a structural intersectionality approach and descriptive epidemiological methods to highlight and quantitatively describe spatial firearm violence disparities that could potentially be linked to the varying exposure of two dimensions of racial capitalism—historical redlining and contemporary racialized subprime mortgage lending. We found that sustained disadvantaged census tracts (tracts that were historically redlined and experienced higher contemporary subprime lending) experienced the highest burden of firearm violence in Baltimore City between 2015 and 2019. Our research suggests that racial capitalism could potentially be a root cause of firearm violence disparities. A theoretical framework based on racial capitalism can inform the development and usage of indicators and analytic methods for racism-related firearm violence research. Moreover, this framework can identify factors to prioritize in equity-based violence prevention policies and programs.

M2PSC: Multilingual sentiment analysis using improved multi-attention based Deep Learning model

Sentiment analysis, which involves determining the emotional polarity positivity, negativity, or neutrality in the source texts, is a crucial task. Multilingual sentiment analysis techniques were developed to analyze data in several languages; a notable deficiency of resources in multilingual sentiment analysis is one of the primary issues. Furthermore, the developed methods for multilingual sentiment analysis have some limitations such as data dependency, reliability, robustness, and computational complexity. To tackle these shortcomings, this research proposed a multilingual improved multi-attention Deep Learning model (M2PSC-DL), which leverages the advantages of the Bi-directional Long Short Term Memory (BiLSTM) classifier with improved attention mechanisms. The Multi-metric graph embedding technique encodes the data to provide more contextual information representation. Additionally, the combination of improved Positional Spatial Channel (SPC) attention increases the capability of the model to extract relevant features in the training process which leads to getting accurate results in sentiment analysis tasks. Furthermore, the research proposed an improved sigmoid activation for solving the vanishing gradient issues that help the model avoid gradient saturations. The validation results demonstrate that the M2PSC-DL model attains 96.26% accuracy, 96.06% precision, and 96.18% recall for the XED dataset which is far better than the traditional methods.

Analytical Method Development and Validation of Simultaneous Estimation of Pure and Tablet Dosage Form by RP-HPLC

The aim of this analytical research is to establish and validate the RP-HPLC (Reverse Phase High Performance Liquid Chromatography) method for concurrently quantifying Montelukast Sodium, Fexofenadine Hydrochloride, and Acebrophylline in a pharmaceutical formulation. The method utilized Rosagiline mesylate as an internal standard, employing a Shim-Pack Solar C18 Column (4.6 x 150 mm, 5 µm) as the stationary phase and a mobile phase composed of acetonitrile, methanol, and 10 mM Na2HPO4 buffer (50:30:20 % v/v/v, pH 5.5). The flow rate was maintained at 1.0 mL/min, and detection occurred at 210 nm. Validation followed ICH guidelines. The linear concentration ranges were 5-30 µg/ml, 10-60 µg/ml, and 10-100 µg/ml at 210 nm for Montelukast Sodium, Fexofenadine Hydrochloride, and Acebrophylline, respectively. Retention times were 7.643 min, 2.117 min, 3.863 min, and 3.050 min for Montelukast sodium, Fexofenadine Hydrochloride, Acebrophylline, and Rosagiline mesylate respectively. The RP-HPLC analysis of marketed formulations yielded concentrations within the ranges of 98.3–100.9%, 99.46–101.23%, and 99.82–101.74% for Montelukast sodium, Fexofenadine Hydrochloride, and Acebrophylline, respectively. Recovery fell within the range of 95.81-101.35% for both drugs. The proposed method has been validated as per ICH guidelines and successfully applied to the estimation of Montelukast, Fexofenadine and Acebrophylline in their combined tablet dosage form.

Development and Validation of Analytical Method for Simultaneous Estimation of Dapagliflozin Propanediol Monohydrate and Sitagliptin Phosphate Monohydrate in Tablet Dosage Form

Development and Validation of Analytical Method for Simultaneous Estimation of Dapagliflozin Propanediol Monohydrate and Sitagliptin Phosphate Monohydrate in Tablet Dosage Form

Development and assessment of analytic methods to improve the measurement of cognition in longitudinal studies of aging through the use of substudies with comprehensive neuropsychological testing.

The Health and Retirement Study International Partner Surveys (HRS IPS) have rich longitudinal data, but the brevity of cognitive batteries is a limitation. We used data from a substudy of the English Longitudinal Study of Ageing (ELSA) administering detailed cognitive assessments with the Harmonized Cognitive Assessment Protocol (ELSA-HCAP) (N=1273) to inform approaches for estimating cognition in ELSA (N=11,213). We compared two novel approaches: confirmatory factor analysis (CFA)- and regression-based prediction. Compared to estimates from the full HCAP battery, estimated cognitive functioning derived using regression models or CFA had high correlations (regression: r=0.85 [95% confidence interval [CI]: 0.83 to 0.87]; CFA: r=0.83 [95% CI: 0.81 to 0.85]) and reasonable mean squared error (regression: 0.25 [0.22 to 0.27]; CFA: 0.29 [0.26 to 0.32]) in held-out data. The use of additional items from waves 7 to 9 improved performance. Both approaches are recommended for future research; the similarity in approaches may be due to the brevity of available cognitive assessments in ELSA. Estimates of cognitive functioning informed by English Longitudinal Study of Ageing-Harmonized Cognitive Assessment Protocol (ELSA-HCAP) data had an adequate performance. Standard errors were smaller for associations with example risks when using measures informed by ELSA-HCAP. Performance was better when including additional cognitive measures available in waves 7 to 9. Conceptual advantages to the confirmatory factor analysis (CFA) approach were not important in practice due to the brevity of the ELSA cognitive battery.