Three spectrophotometric quantitative analysis of bisoprolol fumarate and telmisartan in fixed-dose combination utilizing ratio spectra manipulation methods.

Hypertension is a chronic condition with multiple drug regimens. Limiting these medicines is critical to patient compliance. Therefore, bisoprolol and telmisartan were recently developed in a fixed-dose combination to control blood pressure. The UV absorption spectra of bisoprolol and telmisartan overlapped significantly. Thus, three spectrophotometric methods have been developed for simultaneous determination of bisoprolol and telmisartan without prior separation. Method A is ratio difference of ratio spectra (RD), which measures the amplitude difference between (210-224) nm for bisoprolol and between (255-365) nm for telmisartan. Method B, the first derivative of ratio spectra (1DD), measures amplitude signals at 232 and 243 nm for bisoprolol and telmisartan, respectively. Method C is the mean centering of ratio spectra (MC), which measures the mean-centered ratio spectra's values at 223 nm for bisoprolol and 245 nm for telmisartan. The applied methods showed good linearity 2-20 µg/mL for bisoprolol, 4-32 µg/mL for telmisartan, with sufficient accuracy and precision. The methods were sensitive, with LOD values of 0.243 µg/mL and 0.596 µg/mL in RD method, 0.313 µg/mL and 0.914 µg/mL in 1DD method, and 0.406 and 0.707 µg/mL in MC method for bisoprolol and telmisartan, respectively, the methods were validated per ICH criteria. The novel methods are precise and accurate and can be used for routine analysis and quality control of bisoprolol and telmisartan in pure and dosage form. Furthermore, the greenness of the approaches was evaluated using Analytical Greenness assessment (AGREE), and the suggested method received a high greenness score.

Detection and quantification of groundnut oil adulteration with machine learning using a comparative approach with NIRS and UV-VIS.

Groundnut oil is known as a good source of essential fatty acids which are significant in the physiological development of the human body. It has a distinctive fragrant making it ideal for cooking which contribute to its demand on the market. However, some groundnut oil producers have been suspected to produce groundnut oil by blending it with cheaper oils especially palm olein at different concentrations or by adding groundnut flavor to palm olein. Over the years, there have been several methods to detect adulteration in oils which are time-consuming and expensive. Near infrared (NIR) and ultraviolet-visible (UV-Vis) spectroscopies are cheap and rapid methods for oil adulteration. This present study aimed to apply NIR and UV-Vis in combination with chemometrics to develop models for prediction and quantification of groundnut oil adulteration. Using principal component analysis (PCA) scores, pure and prepared adulterated samples showed overlapping showing similarities between them. Linear discriminant analysis (LDA) models developed from NIR and UV-Vis gave an average cross-validation accuracy of 92.61% and 62.14% respectively for pure groundnut oil and adulterated samples with palm olein at 0, 1, 3, 5, 10, 20, 30, 40 and 50% v/v. With partial least squares regression free fatty acid, color parameters, peroxide and iodine values could be predicted with R2CV's up to 0.8799 and RMSECV's lower than 3 ml/100 ml for NIR spectra and R2CV's up to 0.81 and RMSECV's lower than 4 ml/100 ml for UV-Vis spectra. NIR spectra produced better models as compared to UV-Vis spectra.

Comparative Evaluation of UV-Vis Spectroscopy-Based Approaches for Hemoglobin Quantification: Method Selection and Practical Insights.

The growing demand for effective alternatives to red blood cells (RBCs) has spurred significant research into hemoglobin (Hb)-based oxygen carriers (HBOCs). Accurate characterization of HBOCs-including Hb content, encapsulation efficiency, and yield-is crucial for ensuring effective oxygen delivery, economic viability, and the prevention of adverse effects caused by free Hb. However, the choice of quantification methods for HBOCs is often driven more by tradition than by a thorough assessment of available options. This study meticulously compares various UV-vis spectroscopy-based methods for Hb quantification, focusing on their efficacy in measuring Hb extracted from bovine RBCs across different concentration levels. The findings identify the sodium lauryl sulfate Hb method as the preferred choice due to its specificity, ease of use, cost-effectiveness, and safety, particularly when compared to cyanmethemoglobin-based methods. Additionally, the study discusses the suitability of these methods for HBOC characterization, emphasizing the importance of considering carrier components and potential interferences by analyzing the absorbance spectrum before selecting a method. Overall, this study provides valuable insights into the selection of accurate and reliable Hb quantification methods, which are essential for rigorous HBOC characterization and advancements in medical research.

Functional and spectroscopic approaches to determining thermal limitations of Rieske oxygenases.

The biotechnological potential of Rieske Oxygenases (ROs) and their cognate reductases remains unmet, in part because these systems can be functionally short-lived. Here, we describe a set of experiments aimed at identifying both the functional and structural stability limitations of ROs, using terephthalate (TPA) dioxygenase (from Comamonas strain E6) as a model system. Successful expression and purification of a cofactor-complete, histidine-tagged TPA dioxygenase and reductase protein system requires induction with the Escherichia coli host at stationary phase as well as a chaperone inducing cold-shock and supplementation with additional iron, sulfur, and flavin. The relative stability of the Rieske cluster and mononuclear iron center can then be assessed using spectroscopic and functional measurements following dialysis in an iron chelating buffer. These experiments involve measurements of the overall lifetime of the system via total turnover number using both UV-Visible absorbance and HPLC analyses, as well specific activity as a function of temperature. Important methods for assessing the stability of these multi-cofactor, multi-protein dependent systems at multiple levels of structure (secondary to quaternary) include differential scanning calorimetry, circular dichroism, and metallospectroscopy. Results can be rationalized in terms of three-dimensional structures and bioinformatics. The experiments described here provide a roadmap to a detailed characterization of the limitations of ROs. With a few notable exceptions, these issues are not widely addressed in current literature.

A sensitive, rapid and cost-effective RP-HPLC-UV method for detection and quantification of bedaquiline in physiological fluid (pH 7.4).

Bedaquiline, a highly lipophilic molecule, is used in the treatment regimen of multi-drug resistant tuberculosis. A rare complication of pulmonary tuberculosis is tuberculous pericarditis. Ex vivo studies utilising animal pericardium can be used to investigate whether this drug is capable of diffusing across pericardial tissue into simulated pericardial fluid (pH 7.4) to indicate efficacy. For detection of bedaquiline in physiological fluid, a rapid, cost-effective and sensitive method is essential. The aim of this study was thus to develop and validate a simple and sensitive RP-HPLC-UV method for the detection and quantification of bedaquiline, encapsulated in a nanosystem, at pH 7.4 after permeation across excised pericardium. A HPLC Phenomenex Kinetex RPC18 column (150 × 4.6 mm, 5 µm) was utilized for analysis. The mobile phase consisted of 95 : 5 v/v (A : B), where (A) methanol : acetonitrile (85 : 15 v/v) : (B) triethylamine (1% v/v) : 0.15 mM KH2PO4 buffer (pH 7.4). Running conditions included the following: injection volume 20 µl, flow rate 1.0 ml min-1, detection wavelength 275 nm, 25 °C and running time of 5 min. Bedaquiline eluted as a single symmetrical peak at a retention time of 4.17 min. The method was found to be linear within the range of 1-50 µg ml-1 (R2 = 1). The limit of detection (LOD) and limit of quantification (LOQ) were found to be 0.05 µg ml-1 and 0.15 µg ml-1, respectively (signal-to-noise ratio method). All validation parameters were found to be within acceptable limits (RSD < 2%). The method was fast, reliable, accurate, reproducible, and transient for the detection of bedaquiline in simulated physiological fluid (pH 7.4). This method can thus be applied to easily detect bedaquiline in body fluids (pH 7.4) i.e. blood and pericardial fluid without the accuracy being impacted by ionisation factors of the molecule.

Determination of anamorelin concentration in human plasma using a simple high-performance liquid chromatography-ultraviolet detection method.

Anamorelin, a non-peptide ghrelin analog and growth hormone secretagogue, is a novel oral drug used to treat cancer cachexia. Patients with cancer cachexia frequently use several drugs and anamorelin is a substrate of cytochrome P450 (CYP) 3A4; therefore, drug-drug interactions with CYP3A4 inhibitors and inducers pose a clinical problem. In this study, we aimed to determine the concentration of anamorelin in human plasma using a simple high-performance liquid chromatography-ultraviolet (HPLC-UV)-based method. The analysis involved extracting a 200-µL plasma sample and protein precipitation using solid-phase extraction. Anamorelin was isocratically separated using a mobile phase consisting of 0.5% potassium dihydrogen phosphate (pH 4.5) and acetonitrile (61:39, v/v) on a Capcell Pack C18 MG II column (250 mm × 4.6 mm) at a flow rate of 1.0 mL/min and monitored at a detection wavelength of 220 nm. The calibration curve was linear within a plasma concentration range of 12.5-1,500 ng/mL, with a coefficient of determination of 0.9999. The intra- and inter-day coefficients of variation were 0.37-6.71% and 2.05-4.77%, respectively. The accuracy of the assay and recovery were 85.25-112.94% and > 86.58%, respectively. This proposed HPLC-UV method is simple and can be applied in clinical settings.

Rapid and accurate quantification of trypsin activity using integrated infrared and ultraviolet spectroscopy with data fusion techniques.

Proteases play a crucial role in industrial enzyme formulations, with activity fluctuations significantly impacting product quality and yield. Therefore, developing a method for precise and rapid detection of protease activity is paramount. This study aimed to develop a rapid and accurate method for quantifying trypsin activity using integrated infrared (IR) and ultraviolet (UV) spectroscopy combined with data fusion techniques. The developed method evaluates the enzymatic activity of trypsin under varying conditions, including temperature, pH, and ionic strength. By comparing different data fusion methods, the study identifies the optimal model for accurate enzyme activity prediction. The results demonstrated significant improvements in predictive performance using the feature-level data fusion approach. Additionally, substituting the spectral data of the samples in the validation sets into the best prediction model resulted in a minimal residual difference between predicted and true values, further verifying the model's accuracy and reliability. This innovative approach offers a practical solution for the efficient and precise quantification of enzyme activity, with broad applications in industrial processes.

HPTLC sequentially coupled to UV and SERS: A cost-effective tool for confirmative identification and quantitation of sildenafil in falsified herbal products.

The detection of falsified drugs usually requires multi-disciplinary analysis for confirmative identification. Among hyphenated techniques with high specificity detection, thin-layer chromatography coupled with surface-enhanced Raman spectroscopy (TLC-SERS) is an efficient choice, especially for herbal products with diversified matrix. In this study, HPTLC was coupled to two detection techniques: UV absorption and Raman scattering with silver colloid enhancement for the analysis of sildenafil adulterated in herbal products. With this approach, orthogonal UV and SERS spectral data was collected, so that confirmative results could be obtained within a single TLC analysis. How this approach helped to reduce chances of false positive or false negative results was also discussed. The HPTLC sequentially coupled to UV and SERS (HPTLC-UV-SERS) method was developed and validated parallelly on the UV and SERS signals. To improve the repeatability of the SERS signal, several analytical conditions were optimized, so that direct quantitation with TLC-SERS was feasible without chemometric data extrapolation. The determination was done with UV scanning at 304 nm for HPTLC and with SERS signal at 1580 cm-1 (excitation 633 nm). The TLC-SERS method had a detection limit of 1.65 ng/spot, 95 times lower than HPTLC method (157 ng/spot). The HPTLC-UV-SERS method was applied on 24 real herbal samples collected from the market, among which 3 real samples were positive to sildenafil, and quantitation results by UV and SERS were in consistency. Not only this method was proved feasible for practical applications, but the recommendations for TLC-SERS procedures could also be useful in TLC-SERS method development for other compounds.

Ppb-Level Ammonia Sensor for Exhaled Breath Diagnosis Based on UV-DOAS Combined with Spectral Reconstruction Fitting Neural Network.

Ammonia (NH3) in exhaled breath (EB) has been a biomarker for kidney function, and accurate measurement of NH3 is essential for early screening of kidney disease. In this work, we report an optical sensor that combines ultraviolet differential optical absorption spectroscopy (UV-DOAS) and spectral reconstruction fitting neural network (SRFNN) for detecting NH3 in EB. UV-DOAS is introduced to eliminate interference from slow change absorption in the EB spectrum while spectral reconstruction fitting is proposed for the first time to map the original spectra onto the sine function spectra by the principle of least absolute deviations. The sine function spectra are then fitted by the least-squares method to eliminate noise signals and the interference of exhaled nitric oxide. Finally, the neural network is built to enable the detection of NH3 in EB at parts per billion (ppb) level. The laboratory results show that the detection range is 9.50-12425.82 ppb, the mean absolute percentage error (MAPE) is 0.83%, and the detection accuracy is 0.42%. Experimental results prove that the sensor can detect breath NH3 and identify EB in simulated patients and healthy people. Our sensor will serve as a new and effective system for detecting breath NH3 with high accuracy and stability in the medical field.

Rapid, Simple and Low-Cost Analytical Method Development for Quantification of Eltrombopag Olamine in Tablet Dosage by UV Spectroscopy Method.

BACKGROUND: Eltrombopag Olamine is a drug used to treat thrombocytopenia, a disorder where blood platelet counts get lower and severe aplastic anemia. It serves as a thrombopoietin receptor agonist, which give rise to platelet production in the bone marrow. OBJECTIVES: The objective of this study is to develop a simple, specific, accurate, precise and economical Ultraviolet spectroscopy method to estimate the amount of Eltrombopag Olamine in bulk and tablet dosage form. METHODS: The developed method was performed using methanol for identification and physicochemical characterization of the drug. The validation parameters like linearity, precision, accuracy, robustness limits of detection and quantitation, and specificity were assessed as per ICH Q2 (R2). RESULTS: The maximum absorbance wavelength (λmax) of the drug was found at 247 nm in methanol. The linearity was found in the concentration range of 2-14 µg/ml with regression equation y = 0.0619x - 0.0123 and r² = 0.999. The standard addition method was used to determine the accuracy of the developed method. The result was found in the % recovery range of 98-99%. The precision was done on λmax with respect to the parameters such as repeatability, intraday, and interday. The method was found to be precise as the % RSD value was found to be <2%. The detection limit value (LOD) and quantitation limit value (LOQ) were 0.0524 µg/ml and 0.1588 µg/ml, respectively. CONCLUSION: The developed method is simple, economical, accurate and selective. The developed method was adaptable for the estimation of Eltrombopag Olamine analysis in pharmaceutical dosage form and routine quality control laboratory.

Determination of Aminoglycosides by Ion-Pair Liquid Chromatography with UV Detection: Application to Pharmaceutical Formulations and Human Serum Samples.

Aminoglycosides (AGs) represent a prominent class of antibiotics widely employed for the treatment of various bacterial infections. Their widespread use has led to the emergence of antibiotic-resistant strains of bacteria, highlighting the need for analytical methods that allow the simple and reliable determination of these drugs in pharmaceutical formulations and biological samples. In this study, a simple, robust and easy-to-use analytical method for the simultaneous determination of five common aminoglycosides was developed with the aim to be widely applicable in routine laboratories. With this purpose, different approaches based on liquid chromatography with direct UV spectrophotometric detection methods were investigated: on the one hand, the use of stationary phases based on hydrophilic interactions (HILIC); on the other hand, the use of reversed-phases in the presence of an ion-pairing reagent (IP-LC). The results obtained by HILIC did not allow for an effective separation of aminoglycosides suitable for subsequent spectrophotometric UV detection. However, the use of IP-LC with a C18 stationary phase and a mobile phase based on tetraborate buffer at pH 9.0 in the presence of octanesulfonate, as an ion-pair reagent, provided adequate separation for all five aminoglycosides while facilitating the use of UV spectrophotometric detection. The method thus developed, IP-LC-UV, was optimized and applied to the quality control of pharmaceutical formulations with two or more aminoglycosides. Furthermore, it is demonstrated here that this methodology is also suitable for more complex matrices, such as serum, which expands its field of application to therapeutic drug monitoring, which is crucial for aminoglycosides, with a therapeutic index ca. 50%.

Smart Chemometric-Assisted Spectrophotometric Approaches for Simultaneous Quantification of Tertiary Combination Recommended for COVID-19 Supportive Treatments With Their Greenness Assessment.

BACKGROUND: There is an increasing interest of the scientific community in developing innovative methodologies for their analysis needs within a green analytical chemistry framework. UV spectrophotometry is one of the most promising eco-friendly methods, which is integrated with advanced chemometric tools to enhance the selectivity of the analysis of complex mixtures with severe overlapped signals. OBJECTIVE: Simultaneous determination of a triple-combination of pseudoephedrine hydrochloride (PSE), carbinoxamine maleate (CRX), and paracetamol (PAR) using an artificial intelligence system and multivariate calibration methods. This combination has been recently recommended for COVID-19 home-treated patients as part of a symptomatic treatment. METHODS: Namely, the suggested models are artificial neural networks, partial least-squares, and principal component regression. The proposed algorithms were optimized and developed with the aid of a five-level, three-factor experimental design. RESULTS: The investigated methods were applied over the concentration range of 100-180 µg/mL, 18-16 µg/mL, and 4-12 µg/mL for PSE, CRX, and PAR, respectively. The models' validation results demonstrated excellent recoveries (around 98 to 102%), signaling the approaches' outstanding resolution capacity for the cited compounds in the presence of common excipients. The outcomes of the studied methods were statistically compared to the official approaches, and no significant difference was found. CONCLUSIONS: The suggested models were efficiently employed to determine the selected drugs in their combined tablets without any initial separation steps. The impact of these methods on the environment was evaluated via greenness tools: namely, the National Environmental Method Index, Raynie and Driver's green assessment method, Analytical Eco-Scale, Green Analytical Procedure Index, and Analytical Greenness Metric. HIGHLIGHTS: Green chemometric quality assessment of PSE, CRX, and PAR in their pure and pharmaceutical dosage forms. The established approaches are innovative, sustainable, smart, fast, selective, and cost-effective. These models are potential green nominees for routine analysis of the investigated mixture in quality control laboratories.

Efficient trihalomethane quantification in drinking water for minimally-equipped water treatment plants labs.

Chlorine is a common disinfectant used in water treatment. However, its reaction with organic matter can lead to the formation of harmful byproducts, such as trihalomethanes (THMs), which are potentially carcinogenic. To address this issue, the aim of this work was to enhance a colorimetric method capable of quantifying THMs in drinking water through UV/Vis Spectrophotometry, using cost-effective equipment, and validate this methodology for the first time according to established validation protocols. The method's innovation involved replacing the solvent pentane with the more common hexane, along with adjusting the heating ramp, elucidating the mechanisms involved in the process. This method involves the reaction between THMs, pyridine, and NaOH to produce a colored compound, which is then monitored through molecular absorption spectroscopy in the visible region. The method was thoroughly validated, achieving a limit of detection of 13.41 µg L-1 and a limit of quantification of 40.65 µg L-1. Recovery assays ranged from 86.1 % to 90.7 %, demonstrating high accuracy. The quality of the linear fit for the analytical curve exceeded R2 > 0.98. The method was applied to real samples, revealing concentrations ranging from 13.58 to 55.46 µg L-1, all way below the legal limit in Brazil (Maximum Contaminant Levels (MCL) = 100 µg L-1). This cost-effective and straightforward method is suitable for integration into water treatment plant laboratories.

Validation of a bioanalytical HPLC-UV method to quantify Α-Bisabolol in rat plasma applied to pharmacokinetic pilot study with the drug nanoemulsion.

α-Bisabolol (α-BIS) is a sesquiterpene alcohol present in chamomile essential oil [Chamomilla recutita (L.) Rauschert]. Despite its numerous pharmacological effects, its pharmacokinetics remain understudied. An analytical method capable of quantifying α-BIS in plasma is crucial to enable pharmacokinetic analysis. Presently, only one study has quantified it using mass spectrometry. Administering α-BIS requires a nanoemulsion for intravenous injection. This study aimed to develop and validate a bioanalytical method using high-performance liquid chromatography with an ultraviolet detector to quantify α-BIS in rat plasma. The method employed acetonitrile and ultrapure water (80:20, v/v) as the mobile phase, with a flow rate of 1 ml/min and concentrations ranging from 465 to 29.625 µg/ml. All US Food and Drug Administration-designated assays were successful, indicating the method's precision, accuracy, sensitivity and linearity in determining α-BIS in rat plasma. The developed nanoemulsion, assessed through dynamic light scattering analysis, the ensemble collection of particles and polydispersity index evaluation, proved safe and effective for intravenous administration. The pharmacokinetic parameters such as volume of distribution, clearance and half-life indicated that α-BIS tends to persist in the body. This study provides a foundation for further research to explore α-BIS's potential pharmaceutical applications in the future.

A (RP)UHPLC/UV analytical method to quantify dsRNA during the mRNA vaccine manufacturing process.

dsRNA is a product related impurity produced during the mRNA manufacturing process. The established immuno-based detection methods lack the flexibility and speed required to be applied throughout the manufacturing process. The RP-HPLC method developed outperforms these in terms of precision, broader detection range, LOD and LOQ, as well as in output variance. Using this method, dsRNA can be quantified in under 30 min for a single sample.

Detection of proteins with ascorbic acid-capped gold nanoparticles: a simple and highly sensitive colorimetric assay.

We report a simple and highly sensitive colorimetric method for the detection and quantification of proteins, based on the aggregation of ascorbic acid (AA) capped gold nanoparticles (AuNPs) by proteins. The interactions between our AuNPs and nine different proteins of various sizes and shapes (cytochrome C (12 kDa), lysozyme (14.3 kDa), myoglobin (17 kDa), human serum albumin (66 kDa), bovine serum albumin (66.4 kDa), human transferrin (80 kDa), aldolase (160 kDa), catalase (240 kDa), and human H-ferritin (500 kDa)) generated similar AuNPs-protein absorption spectra in a concentration-dependent manner in the range of 1-15 nM. Upon the addition of a protein, the UV-visible spectra of AuNPs-protein conjugates shifted from 524 nm for the AuNps alone to longer wavelength (600-750 nm) due to the presence of one of these proteins. This bathochromic shift is accompanied by a color change from a cherry red, to dark purple, and then light grey or colorless if excess protein has been added, indicating the formation of AuNPs-protein conjugates followed by protein-induced aggregation of the AuNPs. High-resolution transmission electron microscopy images revealed uniformly distributed spherical nanoparticles with an average size of 27.5 ± 15.2 nm, increasing in size to 39.6 ± 12.9 nm upon the addition of a protein, indicating the formation of AuNPs-protein conjugates in solution. A general mechanism for the protein-induced aggregation of our AuNPs is proposed. The consistent behavior observed with the nine proteins tested in our study suggests that our assay can be universally applied for the quantification of pure proteins in a solution, regardless of size, shape, or molecular weight.

An isocratic HPLC-UV analytical procedure for assessment of glutathione and its related substances.

Reduced glutathione (GSH) is an endogenous tripeptide antioxidant which plays a crucial role in a variety of physiological and pathological activities. Although GSH is not present in any FDA-approved drug product, GSH dietary supplement products and compounded GSH drugs are available to patients in the US. Several incidents of toxicity have occurred in recent years due to endotoxin or otherwise contaminated GSH in compounded drugs. Efficient and sensitive analytical methods are needed for assessing and ensuring the quality of GSH substance and associated drug or dietary supplement products. Impurities A (L-cysteinylglycine), B (cysteine), C (oxidized L-glutathione) and D (γ-L-glutamyl-L-cysteine) are the main related impurities for GSH drug substance which have been detected and quantified by capillary electrophoresis and qNMR analytical procedures. However, there are no reported HPLC methods for detecting or quantifying the three main related impurities A, B and D even though numerous HPLC analytical methods have been reported for analyzing GSH and impurity C. In this report, an isocratic HPLC-UV analytical procedure was developed and validated for separating and identifying GSH and related impurities A-D as well as a newly identified degradant, L-pyroglutamic acid (pGlu), within 10 minutes with resolution (RS) more than 3. The LOD and LOQ were determined to be 0.02 % w/w and 0.05 % w/w, respectively, for impurities A-D and pGlu. Importantly, the optimized HPLC analytical procedure for GSH assay does not have interference from impurities A, B and D, providing highly specific results compared to the commonly used iodine titration method. The newly validated analytical procedure was applied to assess different commercial GSH bulk substance samples. The results suggest that the analytical procedure described in this work is suitable for quality assessment of GSH samples.

Analysis of cassine and spectaline in the Senna spectabilis ethanolic extracts by capillary zone electrophoresis with indirect UV detection.

INTRODUCTION: 2,6-Disubstituted piperidin-3-ols are an important group of piperidine alkaloids found in species such as Senna spectabilis, whose main constituents include cassine and spectaline, compounds with relevant pharmacological activity. The analysis of these compounds is challenging due to the complexity of plant extracts and the absence of chromophores capable of absorbing ultraviolet (UV) radiation. OBJECTIVE: This paper presents a new analytical method to separate and quantify the non-UV-absorbing alkaloids present in ethanol extracts from S. spectabilis flowers using capillary zone electrophoresis (CZE) with indirect UV detection. METHODOLOGY: The optimized CZE method employs a background electrolyte containing 60 mM histidine (His), 15 mM α-cyclodextrin, 20% acetonitrile (ACN), and pH-adjusted to 4.7 with acetic acid (AcOH). RESULTS: The limit of detection (LOD) values was 10.2 and 13.9 mg L-1 for cassine and spectaline, respectively. For both analytes, the precision data were better than 2% of relative standard deviation (RSD) for migration times and peak areas. To evaluate the applicability of the developed method, ethanolic extracts from S. spectabilis flowers were prepared and analyzed. CONCLUSIONS: Thereby, the method proved to be efficient and complementary to conventional techniques, offering a cost-effective alternative in the quantification of the non-UV-absorbing piperidine alkaloids present in plant extracts.

Prediction of Vacuum Ultraviolet/Ultraviolet Gas-Phase Absorption Spectra Using Molecular Feature Representations and Machine Learning.

Ultraviolet (UV) absorption spectroscopy is a widely used tool for quantitative and qualitative analyses of chemical compounds. In the gas phase, vacuum UV (VUV) and UV absorption spectra are specific and diagnostic for many small molecules. An accurate prediction of VUV/UV absorption spectra can aid the characterization of new or unknown molecules in areas such as fuels, forensics, and pharmaceutical research. An alternative to quantum chemical spectral prediction is the use of artificial intelligence. Here, different molecular feature representation techniques were used and developed to encode chemical structures for testing three machine learning models to predict gas-phase VUV/UV absorption spectra. Structure data files (.sdf) and VUV/UV absorption spectra for 1397 volatile and semivolatile chemical compounds were used to train and test the models. New molecular features (termed ABOCH) were introduced to better capture pi-bonding, aromaticity, and halogenation. The incorporation of these new features benefited spectral prediction and demonstrated superior performance compared to computationally intensive molecular-based deep learning methods. Of the machine learning methods, the use of a Random Forest regressor returned the best accuracy score with the shortest training time. The developed machine learning prediction model also outperformed spectral predictions based on the time-dependent density functional theory.

Comparison of DeNovix, NanoDrop and Qubit for DNA quantification and impurity detection of bacterial DNA extracts.

Accurate DNA quantification is key for downstream application including library preparations for whole genome sequencing (WGS) and the quantification of standards for quantitative PCR. Two commonly used technologies for nucleic acid quantification are based on spectrometry, such as NanoDrop, and fluorometry, such as Qubit. The DS-11+ Series spectrophotometer/fluorometer (DeNovix) is a UV spectrophotometry-based instrument and is a relatively new spectrophotometric method but has not yet been compared to established platforms. Here, we compared three DNA quantification platforms, including two UV spectrophotometry-based techniques (DeNovix and NanoDrop) and one fluorometry-based approach (Qubit). We used genomic prokaryotic DNA extracted from Streptococcus pneumoniae using a Roche DNA extraction kit. We also evaluated purity assessment and effect of a single freeze-thaw cycle. Spectrophotometry-based methods reported 3 to 4-fold higher mean DNA concentrations compared to Qubit, both before and after freezing. The ratio of DNA concentrations assessed by spectrophotometry on the one hand, and Qubit on the other hand, was function of the A260/280. In case DNA was pure (A260/280 between 1.7 and 2.0), the ratio DeNovix or Nanodrop vs. Qubit was close or equal to 2, while this ratio showed an incline for DNA with increasing A260/280 values > 2.0. The A260/280 and A260/230 purity ratios exhibited negligible variation across spectrophotometric methods and freezing conditions. The comparison of DNA concentrations from before and after freezing revealed no statistically significant disparities for each technique. DeNovix exhibited the highest Spearman correlation coefficient (0.999), followed by NanoDrop (0.81), and Qubit (0.77). In summary, there is no difference between DeNovix and NanoDrop in estimated gDNA concentrations of S. pneumoniae, and the spectrophotometry methods estimated close or equal to 2 times higher concentrations compared to Qubit for pure DNA.