A high performance thin layer chromatography (HPTLC) method for the quality assessment of agarwood (Aquilaria malaccensis) oil from Northeast India

The high-value agarwood oil, largely used in perfumery is generally graded by the traditional method of sensorial assessment. The compositional complexity and variation made its quality control challenging. Besides, non-volatile contaminants and adulterants are the bottlenecks in gas-chromatographic detection. Herein, a HPTLC based technique was developed for the quality assessment of agarwood oil from Northeast India. A 'marker band' (anisylacetone and oxygenated sesquiterpene rich) on HPTLC profile, containing major peaks of the oil and characteristic agarwood aroma was quantified to assess the quality. The developed method was validated in terms of specificity, linearity, sensitivity, recovery and precision. The application of the method in test samples of three different grades indicated a positive correlation between 'marker band' quantity and oil quality. Its abundance in the superior grade oil was >50% and <20% in poor grade. It can be an efficient analytical tool for the quality assessment and grading of agarwood oil.

Enhancing Odor Analysis with Gas Chromatography-Olfactometry (GC-O): Recent Breakthroughs and Challenges

Gas chromatography-olfactometry (GC-O) has made significant advancements in recent years, with breakthroughs in its applications and the identification of its limitations. This technology is widely used for analyzing complex odor patterns. The review begins by explaining the principles of GC-O, including sample preparation, separation methods, and olfactory evaluation techniques. It then explores the diverse range of applications where GC-O has found success, such as food and beverage industries, environmental monitoring, perfume and aroma development, and forensic analysis. One of the major breakthroughs in GC-O analysis is the improvement in separation power and resolution of odorants. Techniques like rapid GC, comprehensive two-dimensional GC, and multidimensional GC have enhanced the identification and quantification of odor-active chemicals. However, GC-O also has limitations. These include the challenges in detecting and quantifying trace odorants, dealing with matrix effects, and ensuring the repeatability and consistency of results across laboratories. The review examines these limitations closely and discusses potential solutions and future directions for improvement in GC-O analysis. Overall, this review presents a comprehensive overview of the recent advances in GC-O, covering breakthroughs, applications, and limitations. It aims to promote the wider usage of GC-O analysis in odor analysis and related industries. Researchers, practitioners, and anyone interested in leveraging the capabilities of GC-O in analyzing complex odor patterns will find this review a valuable resource. The article highlights the potential of GC-O and encourages further research and development in the field.

A stability-indicating method development and validation for the determination of related substances in novel synthetic decapeptide by HPLC

In the present scenario, peptide is an emerging field of research having vast therapeutic applications. Diverse impurities may rise from various stages of the synthesis process and storage of the peptides. Because these contaminants may have an impact on the therapeutic safety and effectiveness of peptides in their approaching applications, they must be identified and carefully monitored. Considering the pharmaceutical importance of the extent of peptides, we were motivated to synthesize a decapeptide and establish a novel gradient reversed-phase high-performance liquid chromatography (RP-HPLC) method for its analysis along with efficient separation of its six related impurities. Different buffers, organic modifiers, and columns were used in the tests for good separation of these impurities. To establish a stability-indicating method, a stress study was also conducted. The International Conference on Harmonization (ICH) guidelines have been followed for validation of the developed analytical method. The validated method revealed sufficient accuracy, specificity, linearity, robustness, precision, and high sensitivity for its intended use. The proposed method could be appropriate for routine analysis and stability assessment of the decapeptide, which might be useful for further scientific investigation.

Development and Validation of Novel HPLC Methods for Quantitative Determination of Vitamin D3 in Tablet Dosage Form

In the present work, an efficient isocratic HPLC method was developed for the precise and accurate estimation of vitamin D3 in tablet form. The chromatographic conditions comprised an L3 silica column (5 µm in particle size, 4.6 mm × 250 mm) with a mobile phase n-hexane/ethyl acetate (85:15 v/v) with a flow rate of 2.0 mL/min and a detection wavelength of 292 nm. The new methodology was validated for accuracy, precision, specificity, robustness, and quantification limits according to an official monograph of USP/BP and ICH guidelines. The peak areas of the six replicates of the homogeneous sample were recorded. The mean value obtained was 67,301, and the relative standard deviation (RSD) was 0.1741. The linearity and range were in the acceptable bounds, i.e., 0.999, which was calculated using regression line analysis. The results show that the method is truly acceptable as the RSD, as the flow rate was 0.81%, while for the mobile phase composition, it was 0.72%, which lies in the acceptable range. The limit of detection (LOD) and the limit of quantification (LOQ) values were 0.0539 µg/mL and 0.1633 µg/mL, respectively. The % RSD of the intra and inter-day precision of the method was deemed acceptable according to the international commission for harmonization guidelines. The developed method has potential to be used for the detection and quantification of vitamin D3 during routine analysis for tablets in dosage form.

Novel LC-MS/MS Method for Simultaneous Determination of Monoamine Neurotransmitters and Metabolites in Human Samples

For the simultaneous determination of monoamine neurotransmitters (NTs) like dopamine, serotonin, noradrenaline, and epinephrine, and their metabolites (metanephrine, normetanephrine, 3-methoxytyramine, vanillylmandelic acid, 3,4-dihydroxyphenylacetic acid, homovanillic acid, and 5-hydroxyindoleacetic acid), a robust liquid chromatography method coupled with tandem mass spectrometry (LC-MS/MS) was introduced as the analytical method. This analytical method proved to be accurate for the simultaneous measurement of the amounts of 11 NTs and their metabolites in biological samples. The method proved to be more efficient and better than the previously reported method in terms of precision, recovery, sample requirement, and extraction procedure. The reported method requires only 100 μL of blood and 200 μL of urine, and the extraction procedure requires acetonitrile precipitation, filtration, drying, and reconstitution in water. The separation of all analytes was performed on an C18 column (4.6 mm × 150 mm and 1.8 μm). A 10 min gradient elution program with a mobile phase consisting of phase A (0.2% formic acid in water) and phase B (methanol) was used. The positive ionization mode was used for the detection of all analytes in multiple reaction monitoring (MRM). The proposed method was validated with an internal standard and yielded lower limits of detection and quantification ranges of 0.0182-0.0797 ng/mL and 0.0553-0.2415 ng/mL, respectively, with a good linearity (R2) between 0.9959 and 0.9994. The recoveries ranged from 73.37% to 116.63% in blood and from 80.9% to 115.33% in urine. For the NTs and metabolites, the intra- and interday % CV were 0.24-9.36 and 0.85-9.67, respectively. The developed LC-MS/MS method was successfully used for the determination of trace amounts of endogenous compounds in human blood and urine samples.

Liquid chromatography-tandem mass spectrometry determination of bumetanide in human plasma and application to a clinical pharmacokinetic study

Determining a drug's bioavailability and bioequivalence is important for developing and approving a drug product. The procedure supports applications for generic drug products and novel therapeutic substances, makes important decisions regarding safety and efficacy, and measures a drug's concentration in biological matrices. This study aimed to develop and validate a specific, simple, sensitive, and accurate method using liquid chromatography-tandem mass spectrometry (LC-MS) for measuring bumetanide (BUM) in human plasma. Chromatographic separation was achieved using a Hypurity C18 column (4.6 × 50 mm, 5 μm) under isocratic conditions, and LC-MS detected positive ionization acquisition modes. Protonated precursor to product ion transitions were observed at m/z 365.08 → 240.10 and 370.04 → 244.52 for BUM and internal standard, respectively. The linear range of BUM in plasma samples was 3.490-401.192 ng/mL. The inter-precision value ranged from 1.76% to 4.75%. The inter-accuracy value ranged from 96.46% to 99.95%. The method was adequately validated per the U.S. Food and Drug Administration guidelines, and the results were within permissible bounds. The Cmax and Tmax values were ~53.097 ± 13.537 ng/mL and 1.25 (0.67-5.00) h, respectively. The new approach showed satisfactory results for studying BUM in human plasma with potential use in pharmacokinetic and bioequivalence investigations.

Does the Quantification of Δ9-Tetrahydrocannabinolic Acid A in Serum/Plasma Provide Any Additional Information About Consumption Pattern from Drivers Under the Influence of Cannabis?

Introduction: Δ9-tetrahydrocannabinolic acid A (THCA-A) is one of the main ingredients of cannabis plants and is converted to the psychoactive substance Δ9-tetrahydrocannabinol (THC) by decarboxylation during heating above ∼90°C. During the consumption of cannabis, a varying proportion of THCA-A is absorbed into the body. Therefore, the quantification of THCA-A in serum/plasma might provide additional information on consumption behavior in driving under the influence of cannabis cases. Materials and Methods: In this study, an already established gas-chromatography mass-spectrometry (GC-MS) method for the quantification of THC, 11-OH-THC, and THC-COOH in serum and plasma samples was extended to include THCA-A. This validated method was then applied to 1228 routinely achieved serum/plasma samples from drivers suspected of cannabis consumption in Western Saxony. Two different grouping systems for chronic/occasional consumption, one system for acute/subacute consumption, Huestis formulas, and the cannabis influence factor (CIF) were used for evaluation. Results: Method validation showed appropriate results for forensic toxicological routine analysis. Limit of detection and lower limit of quantification (LLOQ) for THCA-A were 0.3 and 1.0 ng/mL, respectively. Reproducibility was <11% and accuracy ranged between 104% and 107%. THCA-A was stable in native samples at least for 2 weeks at room temperature or 4°C as well as 1 month at -20°C. Freeze-thaw stability for three cycles and processed sample stability over 3 days was proven. A total of 865 cases with a THC concentration above the German analytical cutoff of 1 ng/mL as well as the analytical LLOQs of 0.9 and 2.5 ng/mL for 11-OH-THC and THC-COOH, respectively, were included in further statistical analysis. In 407 (47.1%) of these samples, THCA-A was quantifiable. Different statistical analyses indicated a correlation between THCA-A and THC concentrations in cases of chronic and acute consumption. In addition, an increase of chronic and acute cases with increasing THCA-A concentrations was observed. However, no correlation between THCA-A and CIF was found. Discussion: These data show that THCA-A might be an additional indicative marker to provide information about consumption frequency and acuteness. Additional studies with known consumption frequencies and times are required to verify these findings.

GC-MS/MS analysis of synthetic cannabinoids 5F-MDMB-PICA and 5F-CUMYL-PICA in forensic cases

Aim: Validate a method to quantify 1-(5-fluoropentyl)-N-(2-phenylpropan-2-yl)-1H-indole-3-carboxamide (5F-CUMYL-PICA) and methyl 2-[[1-(5-fluoropentyl) indole-3-carbonyl] amino]-3,3-dimethyl-butanoate (5F-MDMB-PICA) in blood samples using GC-MS/MS. Materials & methods: A solid-phase extraction (SPE) method has been developed to quantify 5F-MDMB-PICA and 5F-CUMYL-PICA in authentic human blood samples. Results & conclusion: The limit of detection (LOD) was 0.1 and 0.11 ng/ml for 5F-CUMYL-PICA and 5F-MDMB-PICA, respectively, while the limit of quantification (LOQ) was 0.50 ng/ml for both two compounds. Recovery was 91.40, 82.54 and 85.10% for SPE, supported liquid extraction (SLE) and ISOLUTE C18; matrix effects 15, 24 and 22.5% for SPE, SLE and ISOLUTE C18; accuracy was 2.4-5.5 and 3.9-7.3% for SPE, SLE and ISOLUTE C18, while precision was 4.6-7.7 and 6.4-8.3% for SPE, SLE and ISOLUTE C18, respectively. The concentrations of 5F-CUMYL-PICA and 5F-MDMB-PICA in the authentic human blood samples were 2.18 and 3.07 ng/ml, respectively. The validated method was successfully used in supporting the quantification of analytes in blood.

Efficient retrosynthetic planning with MCTS exploration enhanced A* search

Retrosynthetic planning, which aims to identify synthetic pathways for target molecules from starting materials, is a fundamental problem in synthetic chemistry. Computer-aided retrosynthesis has made significant progress, in which heuristic search algorithms, including Monte Carlo Tree Search (MCTS) and A* search, have played a crucial role. However, unreliable guiding heuristics often cause search failure due to insufficient exploration. Conversely, excessive exploration also prevents the search from reaching the optimal solution. In this paper, MCTS exploration enhanced A* (MEEA*) search is proposed to incorporate the exploratory behavior of MCTS into A* by providing a look-ahead search. Path consistency is adopted as a regularization to improve the generalization performance of heuristics. Extensive experimental results on 10 molecule datasets demonstrate the effectiveness of MEEA*. Especially, on the widely used United States Patent and Trademark Office (USPTO) benchmark, MEEA* achieves a 100.0% success rate. Moreover, for natural products, MEEA* successfully identifies bio-retrosynthetic pathways for 97.68% test compounds.

Development of an Untargeted LC-MS Metabolomics Method with Postcolumn Infusion for Matrix Effect Monitoring in Plasma and Feces

Untargeted metabolomics based on reverse phase LC-MS (RPLC-MS) plays a crucial role in biomarker discovery across physiological and disease states. Standardizing the development process of untargeted methods requires paying attention to critical factors that are under discussed or easily overlooked, such as injection parameters, performance assessment, and matrix effect evaluation. In this study, we developed an untargeted metabolomics method for plasma and fecal samples with the optimization and evaluation of these factors. Our results showed that optimizing the reconstitution solvent and sample injection amount was critical for achieving the balance between metabolites coverage and signal linearity. Method validation with representative stable isotopically labeled standards (SILs) provided insights into the analytical performance evaluation of our method. To tackle the issue of the matrix effect, we implemented a postcolumn infusion (PCI) approach to monitor the overall absolute matrix effect (AME) and relative matrix effect (RME). The monitoring revealed distinct AME and RME profiles in plasma and feces. Comparing RME data obtained for SILs through postextraction spiking with those monitored using PCI compounds demonstrated the comparability of these two methods for RME assessment. Therefore, we applied the PCI approach to predict the RME of 305 target compounds covered in our in-house library and found that targets detected in the negative polarity were more vulnerable to the RME, regardless of the sample matrix. Given the value of this PCI approach in identifying the strengths and weaknesses of our method in terms of the matrix effect, we recommend implementing a PCI approach during method development and applying it routinely in untargeted metabolomics.

A comprehensive approach for evaluating the virucidal performance of domestic laundry detergents under practical conditions

AIMS

We aimed to develop a method to assess the virucidal performance of domestic laundry in a lab-scale washing machine (Rotawash) based on EN 17658.

METHODS AND RESULTS

For method development, virus recovery was investigated after drying on cotton carriers for three test viruses murine norovirus (MNV), modified vaccinia virus Ankara (MVA), and bovine coronavirus (BCoV), followed by washing simulations in flasks and Rotawash. MNV and MVA demonstrated sufficient recovery from carriers after drying and washing (up to 40°C and 60 min). BCoV exhibited lower recovery, indicating less relevance as a test virus. Rotawash efficacy tests conducted with MNV, a resistant, non-enveloped virus, showed limited efficacy of a bleach-free detergent, aligning with results from a domestic washing machine. Rotawash washes achieved higher reductions in infectious virus titers than suspension tests, indicating the role of washing mechanics in virus removal.

CONCLUSIONS

This study established a practical method to test the virucidal efficacy of laundry detergents in Rotawash, simulating domestic washing.

A novel, high-performance, low-volume, rapid luciferase immunoprecipitation system (LIPS) assay to detect autoantibodies to zinc transporter 8

BACKGROUND

Zinc transporter 8 autoantibodies (ZnT8A) are thought to appear close to type 1 diabetes (T1D) onset and can identify high-risk multiple (≥2) autoantibody positive individuals. Radiobinding assays (RBA) are widely used for ZnT8A measurement but have limited sustainability. We sought to develop a novel, high-performance, non-radioactive luciferase immunoprecipitation system (LIPS) assay to replace RBA.

METHODS

A custom dual C-terminal ZnT8 (aa268-369; R325/W325) heterodimeric antigen, tagged with a NanoluciferaseTM (Nluc-ZnT8) reporter, and LIPS assay was developed. Assay performance was evaluated by testing sera from new onset T1D (n = 573), healthy schoolchildren (n = 521), and selected first-degree relatives (FDRs) from the Bart's Oxford family study (n = 617; 164 progressed to diabetes).

RESULTS

In new-onset T1D, ZnT8A levels by LIPS strongly correlated with RBA (Spearman's r = 0.89; P < 0.0001), and positivity was highly concordant (94.3%). At a high specificity (95%), LIPS and RBA had comparable assay performance [LIPS pROC-AUC(95) 0.032 (95% CI: 0.029-0.036); RBA pROC-AUC(95) 0.031 (95% CI: 0.028-0.034); P = 0.376]. Overall, FDRs found positive by LIPS or RBA had a comparable 20-year diabetes risk (52.6% and 59.7%, respectively), but LIPS positivity further stratified T1D risk in FDRs positive for at least one other islet autoantibody detected by RBA (P = 0.0346).

CONCLUSION

This novel, high-performance, cheaper, quicker, higher throughput, low blood volume Nluc-ZnT8 LIPS assay is a safe, non-radioactive alternative to RBA with enhanced sensitivity and ability to discriminate T1D progressors. This method offers an advanced approach to current strategies to screen the general population for T1D risk for immunotherapy trials and to reduce rates of diabetic ketoacidosis at diagnosis.

Comparison of colorimetric, spectroscopic and electrochemical techniques for quantification of hydrogen sulfide

Background: Hydrogen sulfide (H2S), an endogenous gasotransmitter, has potential applications in several conditions. However, its quantification in simulated physiological solutions is a major challenge due to its gaseous nature and other physicochemical properties. Aim: This study was designed to compare four commonly used H2S detection and quantification methods in aqueous solutions. Methods: The four techniques compared were one colorimetric, one chromatographic and two electrochemical methods. Results: Colorimetric and chromatographic methods quantified H2S in millimolar and micromole ranges, respectively. The electrochemical methods quantified H2S in the nanomole and picomole ranges and were less time-consuming. Conclusion: The H2S quantification method should be selected based on the specific requirements of a research project in terms of sensitivity, response time and cost-effectiveness.

Time-lapse confocal microscopy to study in vitro Streptococcus mutans surface colonization

The cariogenicity of Streptococcus mutans relates to its ability to form biofilms on dental surfaces. The aim of this work was to develop a flowcell system compatible with time-lapse confocal microscopy to compare the adhesion and accumulation of S. mutans cells on surfaces in unsupplemented media against media containing sucrose or sucralose (a non-metabolized sweetener) over a short period of time. Fluorescent S. mutans 3209/pVMCherry was suspended in unsupplemented media or media supplemented with 1% sucrose or 1% sucralose and passed through a 3D-printed flowcell system. Flowcells were imaged over 60 minutes using a confocal microscope. Image analysis was performed, including a newly developed object-movement-based method to measure biomass adhesion. Streptococcus mutans 3209/pVMCherry grown in 1% sucrose-supplemented media formed small, dense, relatively immobile clumps in the flowcell system measured by biovolume, surface area, and median object centroid movement. Sucralose-supplemented and un-supplemented media yielded large, loose, mobile aggregates. Architectural metrics and per-object movement were significantly different (P < 0.05) when comparing sucrose-supplemented media to either unsupplemented or sucralose-supplemented media. These results demonstrate the utility of a flowcell system compatible with time-lapse confocal microscopy and image analysis when studying initial biofilm formation and adhesion under different nutritional conditions.

Combining stochastic resetting with Metadynamics to speed-up molecular dynamics simulations

Metadynamics is a powerful method to accelerate molecular dynamics simulations, but its efficiency critically depends on the identification of collective variables that capture the slow modes of the process. Unfortunately, collective variables are usually not known a priori and finding them can be very challenging. We recently presented a collective variables-free approach to enhanced sampling using stochastic resetting. Here, we combine the two methods, showing that it can lead to greater acceleration than either of them separately. We also demonstrate that resetting Metadynamics simulations performed with suboptimal collective variables can lead to speedups comparable with those obtained with optimal collective variables. Therefore, applying stochastic resetting can be an alternative to the challenging task of improving suboptimal collective variables, at almost no additional computational cost. Finally, we propose a method to extract unbiased mean first-passage times from Metadynamics simulations with resetting, resulting in an improved tradeoff between speedup and accuracy. This work enables combining stochastic resetting with other enhanced sampling methods to accelerate a broad range of molecular simulations.

Towards a transferable fermionic neural wavefunction for molecules

Deep neural networks have become a highly accurate and powerful wavefunction ansatz in combination with variational Monte Carlo methods for solving the electronic Schrödinger equation. However, despite their success and favorable scaling, these methods are still computationally too costly for wide adoption. A significant obstacle is the requirement to optimize the wavefunction from scratch for each new system, thus requiring long optimization. In this work, we propose a neural network ansatz, which effectively maps uncorrelated, computationally cheap Hartree-Fock orbitals, to correlated, high-accuracy neural network orbitals. This ansatz is inherently capable of learning a single wavefunction across multiple compounds and geometries, as we demonstrate by successfully transferring a wavefunction model pre-trained on smaller fragments to larger compounds. Furthermore, we provide ample experimental evidence to support the idea that extensive pre-training of such a generalized wavefunction model across different compounds and geometries could lead to a foundation wavefunction model. Such a model could yield high-accuracy ab-initio energies using only minimal computational effort for fine-tuning and evaluation of observables.

Concepts and principles for new rapid simple liquid chromatography method for quantification of antioxidants resveratrol, vitamin E, and coenzyme Q10 in capsules with high-performance liquid chromatography with a photo-diode array detector

Principles and problems in the development of simultaneous liquid chromatography (LC) analytical methods for potent antioxidative molecules resveratrol, tocopherol, and coenzyme Q10 in capsules, have been investigated and systematically compared and summarized. For these purposes, experiments within the full polarity spectrum of LC techniques. were tested and recorded. The whole range of polarities included: Alkyl C18 bonded reversed phase, phenyl, cyanopropyl, diol, and the most polar base silica-filled column matrixes have been used. The summarized results concluded that all mentioned LC techniques could be used for the determination of the mentioned group of the three analytes with different run characteristics and efficiency. These successes could be achieved after careful analyses of molecular physicochemical data of analytes. They are especially organic solubilities. The ultraviolet spectral absorption characteristics of each analyte and the mobile phase constituents for appropriate separation were very important to be known. The ultimate targets were the development method with the isocratic mode of separation yielding symmetrical peak shapes for the best sensitivity and accuracy, with the shortest run time and best reproducibility. From an analytical point of view important for LC, the three analytes have quite distinct characteristics that contribute to successful method development. These features are their organic solvent and water solubility, molecular polarities, and ultraviolet-absorption characteristics, like spectra and absorptivities. All these mentioned parameters were taken into account for solving complications appearing in the development of rapid LC methods for the simultaneous determination of three antioxidant molecules.

LC-MS/MS methods for direct measurement of sepiapterin and tetrahydrobiopterin in human plasma and clinical applications

Aim: Tetrahydrobiopterin (BH4), a natural cofactor of aromatic amino acid hydroxylases, and sepiapterin, a natural precursor of BH4, are endogenously present in human plasma. This is the first report on methods for direct quantification of sepiapterin and BH4 in human plasma by LC-MS/MS for pharmacokinetic assessment. Materials & methods: The analytes in plasma were harvested from blood that were treated with 10% ascorbic acid (AA) to a final concentration of 1% AA. Results & conclusion: The quantification methods were validated for calibration ranges of 0.75-500 ng/ml and 0.5-500 ng/ml for sepiapterin and BH4, respectively. Quantification of analytes was challenging due to their susceptibility to redox reactions. The validated methods were utilized successfully to support clinical development of sepiapterin.

Assessment of biomarker stability and assay performance parameters for medical diagnosis: a case study of diagnosis of major depressive disorder

Aim: Assessing the stability profiles and assay performance of 24 biomarker assays in 32 biomarker/body fluid combinations identified as relevant for prediction of major depressive disorder. Materials & methods: Combinations were tested for stability and assay performance with ELISA at different storage and freeze-thaw conditions in pooled samples of 40 patients. Results: Stability and assay performance issues were found in almost all cases except three biomarkers in urine and three in serum. Conclusion: This study shows that, to produce reliable measurement data, assessments of stability and assay performance are essential. In development, other quality assurance parameters might be implemented to increase the level of measurement reliability by increasing assay performance control.

A rapid, sensitive method for clinical monitoring of ketamine and norketamine by ultra-high-performance reverse-phase liquid chromatography tandem mass spectrometry

BACKGROUND

Ketamine is an NMDAR antagonist with aggregating use across many areas of medicine. P450 enzymes heavily metabolise ketamine, where norketamine is a first pass formed metabolite following initial N-demethylation. Serum ketamine monitoring is becoming increasingly important, requiring a sensitive method with a robust lower limit of quantitation.

METHODS

Samples were prepared using protein precipitation or solid phase extraction. Ion suppression was investigated to optimise sample preparation technique, followed by reverse-phase chromatography coupled with tandem mass spectrometry to analyse extractions using a Waters Xevo TQ-S Micro and associated Acquity chromatography systems. Performance characteristics were analysed to validate the assay.

RESULTS

Ketamine and norketamine retention times were 1.28 and 1.23 min, respectively. Ketamine and norketamine precursor ions fragmented into 2 distinguishable product ions (238.14 > 207.18/125.06 and 224.1 > 178.96/124.86). Performance characteristics include an assay recovery of 103.7% (ketamine) and 96.3% (norketamine), lower limit of quantitation 36.2 µg/L (ketamine) and 38.9 µg/L (norketamine), and intra-assay imprecision ≤ 7.04% on average.

CONCLUSIONS

A robust and reproducible assay with limited sample preparation has been designed and validated. The linearity of the assay covers all ranges of interest reported in the literature. Ion suppression was clearly reduced via use of solid phase extraction. The method will form the basis of ketamine monitoring and providing valuable patient information on tolerance and metabolism.

Development and Application of an Atomic Absorption Spectrometry-Based Method to Quantify Magnesium in Leaves of Dioscorea polystachya

The Chinese yam (Dioscorea polystachya, DP) is known for the nutritional value of its tuber. Nevertheless, DP also has promising pharmacological properties. Compared with the tuber, the leaves of DP are still very little studied. However, it may be possible to draw conclusions about the plant quality based on the coloration of the leaves. Magnesium, as a component of chlorophyll, seems to play a role. Therefore, the aim of this research work was to develop an atomic absorption spectrometry-based method for the analysis of magnesium (285.2125 nm) in leaf extracts of DP following the graphite furnace sub-technique. The optimization of the pyrolysis and atomization temperatures resulted in 1500 °C and 1800 °C, respectively. The general presence of flavonoids in the extracts was detected and could explain the high pyrolysis temperature due to the potential complexation of magnesium. The elaborated method had linearity in a range of 1-10 µg L-1 (R2 = 0.9975). The limits of detection and quantification amounted to 0.23 µg L-1 and 2.00 µg L-1, respectively. The characteristic mass was 0.027 pg, and the recovery was 96.7-102.0%. Finally, the method was applied to extracts prepared from differently colored leaves of DP. Similar magnesium contents were obtained for extracts made of dried and fresh leaves. It is often assumed that the yellowing of the leaves is associated with reduced magnesium content. However, the results indicated that yellow leaves are not due to lower magnesium levels. This stimulates the future analysis of DP leaves considering other essential minerals such as molybdenum or manganese.

Fast free energy estimates from λ-dynamics with bias-updated Gibbs sampling

Relative binding free energy calculations have become an integral computational tool for lead optimization in structure-based drug design. Classical alchemical methods, including free energy perturbation or thermodynamic integration, compute relative free energy differences by transforming one molecule into another. However, these methods have high operational costs due to the need to perform many pairwise perturbations independently. To reduce costs and accelerate molecular design workflows, we present a method called λ-dynamics with bias-updated Gibbs sampling. This method uses dynamic biases to continuously sample between multiple ligand analogues collectively within a single simulation. We show that many relative binding free energies can be determined quickly with this approach without compromising accuracy. For five benchmark systems, agreement to experiment is high, with root mean square errors near or below 1.0 kcal mol-1. Free energy results are consistent with other computational approaches and within statistical noise of both methods (0.4 kcal mol-1 or less). Notably, large efficiency gains over thermodynamic integration of 18-66-fold for small perturbations and 100-200-fold for whole aromatic ring substitutions are observed. The rapid determination of relative binding free energies will enable larger chemical spaces to be more readily explored and structure-based drug design to be accelerated.

Validated HPLC-UV method for amphotericin B quantification in a critical patient receiving AmBisome and treated with extracorporeal replacement therapies

Amphotericin B (AMB) is a polyene macrolide antifungal agent used for treating invasive fungal infections. Liposomal AMB is a lipid dosage form, available as AmBisome, which reduces the toxicity of the drug. A simple HPLC-UV method was developed for the determination of AMB in plasma to study its pharmacokinetic profile in a critical patient receiving AmBisome and treated with extracorporeal replacement therapies. Sample preparation was performed using plasma deproteinization and drug release from liposome by the addition of acetonitrile (ACN)/zinc sulfate and ultrasonication. Chromatographic separation was performed using a C18 column and a mobile phase consisting of phosphate buffer (pH 3.0)/ACN (65/35, v/v). The UV detector was set at 407 nm. The total run time analysis was 23 min. The method was validated according to the standard guidelines and applied to study the pharmacokinetics of AMB in a critical patient. The total run time analysis obtained was shorter than that of the previously reported methods, being useful for therapeutic drug monitoring or pharmacokinetic profile research.

Development of Visible Spectrophotometric Methods for the Determination of Tricyclic Antidepressants Based on Formation of Molecular Complexes with p-Benzoquinones

Tricyclic antidepressants are commonly employed in the management of major depressive disorders. The present work describes two visible (VIS) spectrophotometric techniques that utilize the formation of charge transfer complexes between four antidepressant compounds, namely, amitriptyline hydrochloride (AMI), imipramine hydrochloride (IMI), clomipramine hydrochloride (CLO), and trimipramine maleate (TRI) acting as electron donors and two p-benzoquinones, namely, p-chloranilic acid (pCA) and 2,3-dichloro-5,6-dicyano-1,4-benzoquinone (DDQ), serving as electron acceptors. The stoichiometry of the compounds produced exhibited a consistent 1:1 ratio in all instances, as established by Job's method. Molar absorptivities, equilibrium association constants, and several other spectroscopic properties were determined for all complexes. The developed spectrophotometric techniques were validated intra-laboratory and successfully applied for quantitative assessment of the four antidepressant active ingredients in several commercial pharmaceutical formulations. The methods are relatively simple, fast, and use readily available laboratory instrumentation, making them easily applicable by most quality control laboratories worldwide.

Data-driven discovery of electrocatalysts for CO2 reduction using active motifs-based machine learning

The electrochemical carbon dioxide reduction reaction (CO2RR) is an attractive approach for mitigating CO2 emissions and generating value-added products. Consequently, discovery of promising CO2RR catalysts has become a crucial task, and machine learning (ML) has been utilized to accelerate catalyst discovery. However, current ML approaches are limited to exploring narrow chemical spaces and provide only fragmentary catalytic activity, even though CO2RR produces various chemicals. Here, by merging pre-developed ML model and a CO2RR selectivity map, we establish high-throughput virtual screening strategy to suggest active and selective catalysts for CO2RR without being limited to a database. Further, this strategy can provide guidance on stoichiometry and morphology of the catalyst to researchers. We predict the activity and selectivity of 465 metallic catalysts toward four expected reaction products. During this process, we discover previously unreported and promising behavior of Cu-Ga and Cu-Pd alloys. These findings are then validated through experimental methods.

Valbenazine isomers and enantiomer determination by chiral normal phase liquid chromatography

A novel, simple, specific, rapid, enantioselective normal phase chiral high-performance liquid chromatographic method with amylose-based Chiral Pak IG-3(250 × 4.6 mM) 3.0 μM column was developed and validated for separation and quantification of isomers and enantiomer of Valbenazine. The mobile phase composed of n-Heptane, isopropyl alcohol, dichloromethane, ethanol, and diethylamine in the ratio of 70:10:15:5:0.1 (V/V/V/VV) with a gradient flow rate was applied. The injection volume was 10 μl, and detection was carried out using a photodiode array detector at 282 nM. The column compartment was set at 35°C. The resolution between the enantiomer and isomers was found to be more than 2.0. The method was linear over the concentration range of limit of quantitation to 250% for isomers and enantiomers. The method was found to be robust with column temperature. The proposed chiral method is applicable for the determination of isomers and enantiomer of Valibenazine and was successfully used in the quality control of bulk drug manufacturing and pharmaceuticals.

A Reliable and Simple Method for the Production of Viable Pycnidiospores of the Pine Pathogen Diplodia sapinea and a Spore-Based Infection Assay on Scots Pine

Diplodia sapinea is a globally distributed opportunistic fungal pathogen of conifers that causes severe production losses in forestry. The fungus frequently colonizes pine trees as an endophyte without causing visible symptoms but can become pathogenic when the host plant is weakened by stress, such as drought or heat. Forest damage might therefore further increase due to the effects of climate change. The future development of control strategies depends on a better understanding of the fungus' biology, which requires experimental methods for its investigation in the laboratory. An efficient, standardized protocol for the production and storage of highly viable pycnidiospores was developed, and a spore-based infection method was devised. We compared infection rates of dormant and actively growing, wounded, or nonwounded Scots pine seedlings inoculated with in vitro-produced spores and mycelium from agar-plugs. Spores were a much more efficient inoculum for causing disease symptoms on wounded plants than the conventional agar plug. The application of spores on nonwounded plants lead to high rates of asymptomatic infection, suggesting endophytic fungal development. These methods enable standardized spore infection and virulence assays and promote D. sapinea as a model organism for studying the switch from endophytic to pathogenic life styles of forest pathogens.

Using enhanced development tools offered by analytical Quality by Design to support switching of a quality control method

Quality by Design (QbD) principles play an increasingly important role in the pharmaceutical industry. Here, we used an analytical QbD (AQbD) approach to develop a capillary electrophoresis sodium dodecyl sulfate under reducing conditions (rCE-SDS), with the aim of replacing SDS-polyacrylamide gel electrophoresis (SDS-PAGE) as release and stability test method for a commercialized monoclonal antibody product. Method development started with defining analytical method performance requirements as part of an analytical target profile, followed by a systematic risk assessment of method input parameters and their relation to defined method outputs. Based on this, design of experiments studies were performed to identify a method operable design region (MODR). The MODR could be leveraged to improve method robustness. In a bridging study, it was demonstrated that the rCE-SDS method is more sensitive than the legacy SDS-PAGE method, and a conversion factor could be established to compensate for an off-set due to the higher sensitivity, without losing the correlation to the historical data acquired with the former method. Overall, systematic application of analytical Quality by Design principles for designing and developing a new analytical method helped to elucidate the complex dependency of method outputs on its input parameters. The link of the method to product quality attributes and the definition of method performance requirements were found to be most relevant for derisking the analytical method switch, regarding impact on the control strategy.

Knowledge-driven design of solid-electrolyte interphases on lithium metal via multiscale modelling

Due to its high energy density, lithium metal is a promising electrode for future energy storage. However, its practical capacity, cyclability and safety heavily depend on controlling its reactivity in contact with liquid electrolytes, which leads to the formation of a solid electrolyte interphase (SEI). In particular, there is a lack of fundamental mechanistic understanding of how the electrolyte composition impacts the SEI formation and its governing processes. Here, we present an in-depth model-based analysis of the initial SEI formation on lithium metal in a carbonate-based electrolyte. Thereby we reach for significantly larger length and time scales than comparable molecular dynamic studies. Our multiscale kinetic Monte Carlo/continuum model shows a layered, mostly inorganic SEI consisting of LiF on top of Li2CO3 and Li after 1 µs. Its formation is traced back to a complex interplay of various electrolyte and salt decomposition processes. We further reveal that low local Li+ concentrations result in a more mosaic-like, partly organic SEI and that a faster passivation of the lithium metal surface can be achieved by increasing the salt concentration. Based on this we suggest design strategies for SEI on lithium metal and make an important step towards knowledge-driven SEI engineering.

Detection and Quantification of Bisphenol A in Surface Water Using Absorbance-Transmittance and Fluorescence Excitation-Emission Matrices (A-TEEM) Coupled with Multiway Techniques

In the present protocol, we determined the presence and concentrations of bisphenol A (BPA) spiked in surface water samples using EEM fluorescence spectroscopy in conjunction with modelling using partial least squares (PLS) and parallel factor (PARAFAC). PARAFAC modelling of the EEM fluorescence data obtained from surface water samples contaminated with BPA unraveled four fluorophores including BPA. The best outcomes were obtained for BPA concentration (R2 = 0.996; standard deviation to prediction error's root mean square ratio (RPD) = 3.41; and a Pearson's r value of 0.998). With these values of R2 and Pearson's r, the PLS model showed a strong correlation between the predicted and measured BPA concentrations. The detection and quantification limits of the method were 3.512 and 11.708 micro molar (µM), respectively. In conclusion, BPA can be precisely detected and its concentration in surface water predicted using the PARAFAC and PLS models developed in this study and fluorescence EEM data collected from BPA-contaminated water. It is necessary to spatially relate surface water contamination data with other datasets in order to connect drinking water quality issues with health, environmental restoration, and environmental justice concerns.

Machine learning electronic structure methods based on the one-electron reduced density matrix

The theorems of density functional theory (DFT) establish bijective maps between the local external potential of a many-body system and its electron density, wavefunction and, therefore, one-particle reduced density matrix. Building on this foundation, we show that machine learning models based on the one-electron reduced density matrix can be used to generate surrogate electronic structure methods. We generate surrogates of local and hybrid DFT, Hartree-Fock and full configuration interaction theories for systems ranging from small molecules such as water to more complex compounds like benzene and propanol. The surrogate models use the one-electron reduced density matrix as the central quantity to be learned. From the predicted density matrices, we show that either standard quantum chemistry or a second machine-learning model can be used to compute molecular observables, energies, and atomic forces. The surrogate models can generate essentially anything that a standard electronic structure method can, ranging from band gaps and Kohn-Sham orbitals to energy-conserving ab-initio molecular dynamics simulations and infrared spectra, which account for anharmonicity and thermal effects, without the need to employ computationally expensive algorithms such as self-consistent field theory. The algorithms are packaged in an efficient and easy to use Python code, QMLearn, accessible on popular platforms.

Accelerating the prediction of CO2 capture at low partial pressures in metal-organic frameworks using new machine learning descriptors

Metal-Organic frameworks (MOFs) have been considered for various gas storage and separation applications. Theoretically, there are an infinite number of MOFs that can be created; however, a finite amount of resources are available to evaluate each one. Computational methods can be adapted to expedite the process of evaluation. In the context of CO2 capture, this paper investigates the method of screening MOFs using machine learning trained on molecular simulation data. New descriptors are introduced to aid this process. Using all descriptors, it is shown that machine learning can predict the CO2 adsorption, with an R2 of above 0.9. The introduced Effective Point Charge (EPoCh) descriptors, which assign values to frameworks' partial charges based on the expected CO2 uptake of an equivalent point charge in isolation, are shown to be the second most important group of descriptors, behind the Henry coefficient. Furthermore, the EPoCh descriptors are hundreds of thousands of times faster to obtain compared with the Henry coefficient, and they achieve similar results when identifying top candidates for CO2 capture using pseudo-classification predictions.

Lyso-phosphatidylethanol detected by LC-MS/MS as a potential new marker for alcohol consumption

Alcohol biomarkers are able to reflect the degree of recent or long-term alcohol consumption, covering different windows of detection. Phosphatidylethanols (PEths) are an emerging group of direct alcohol biomarkers that are widely applied in clinical and forensic applications. Their quantification can provide insight into an individual's drinking behaviour. Here, we present a new sub-class of yet unknown PEth species, LysoPEths, which are structurally related to PEth, but miss one fatty acyl chain. LysoPEths can be either a degradation product of PEth or a product of transesterification of lyso-phosphatidylcholine (LysoPC) with ethanol. To set up an analytical method, LysoPEth 16:0 was synthesised from PC 16:0/18:1 and characterised by LC-MS/MS, using an enzymatic method: phospholipase D (PLD), followed by phospholipase A2 (PLA2). Then, an LC-MS/MS method in MRM mode for LysoPEth 16:0 with additional LysoPEth species (LysoPEth 18:1, LysoPEth 18:2, and LysoPEth 20:4) and PEth 16:0/20:4 was developed. By incubation of freshly sampled venous blood of a teetotaller with ethanol at different concentrations, the formation of LysoPEth in parallel to PEth was investigated. With increasing ethanol concentrations, LysoPEth 16:0 was formed besides the known PEth species (PEth 16:0/18:1, PEth 16:0/18:2) for up to 72 h with LysoPEth concentrations being about three times lower than PEth concentrations. Storage of ethanol-free PEth-positive blood of an alcohol consumer at 37 °C showed that LysoPEth 16:0 concentrations increased, while PEth 16:0/18:1 concentrations decreased in the first 24 h for frozen/thawed blood, however not for freshly collected blood. Furthermore, LysoPEth 16:0 was detected in venous as well as lyophilised blood from clinical and forensic case work alongside with PEth 16:0/18:1, 16:0/18:2, and other PEth and LysoPEth species (PEth 16:0/20:4, LysoPEth 18:1, LysoPEth 18:2, and LysoPEth 20:4). LysoPEth 16:0 concentrations were found to be in linear correlation with PEth 16:0/18:1 (r2 = 0.75).

Development and validation of a sensitive ultra-high-performance liquid chromatography-tandem mass spectrometry method for quantitative analysis of bambermycin in livestock and aquatic products: Implications for food safety control and regulatory enforcement

A sensitive and accurate analytical method was developed and validated to detect bambermycin, a commonly used antibiotic in animal feed and livestock. The presence of bambermycin residues in food products can pose health risks to consumers, emphasizing the need for a sensitive and accurate analytical method. A reversed-phase analytical column was utilized with a mobile phase comprising 0.005 mol/L ammonium acetate in 5% acetonitrile (A) and 0.005 mol/L ammonium acetate in 95% acetonitrile (B) to achieve effective chromatographic separation. Quantitative determination of bambermycin in various samples, including beef, pork, chicken, milk, eggs, flatfish, eel, and shrimp, was performed using ultra-high-performance liquid chromatography-tandem mass spectrometry. Sample extraction involved a mixture of methanol and a 25% ammonium hydroxide solution, followed by low-temperature purification and phospholipid removal utilizing a Phree cartridge. The method exhibited a satisfactory recovery rate ranging from 69% to 100%. Validation results demonstrated the reliability, robustness, and accuracy of the method, exhibiting good linearity, precision, and recovery. This validated method can be applied for routine analysis of bambermycin residues, assisting in the development of effective monitoring and control measures to ensure the safety of livestock and aquatic products.

[Assessment of Direct (COVID-19-Related) and Collateral, Psychosocial Pandemic Consequences for Vulnerable Groups by the Example of Serious Mental Illness]

The indirect pandemic consequences could by far exceed the direct effects of SARS-CoV-2 in terms of costs, morbidity, and mortality. This essay includes a proposed method (matrix) to visualize virus-related and psychosocial risks for different populations side by side in a systematic and concise manner. COVID-19-related and psychosocial vulnerability, stressors, direct and indirect consequences are derived on a theoretical and empirical basis. An exemplary quantification of the matrix for the vulnerable group of people with severe mental illness revealed a very high risk for severe COVID-19 consequences, as well as a pronounced risk for psychosocial collateral effects. The proposed approach could be further discussed for a risk-graded pandemic management, crisis recovery, and future preparedness to adequately address psychosocial collateral effects and better identify and protect vulnerable groups in this regard.

A Reliable Method for Determining the Degree of Orientation of Fibrous Foods Using Laser Transmission and Computer Vision

The degree of organised alignment of fibre structures, referred to as the degree of orientation, significantly influences the textural properties and consumer acceptance of fibrous foods. To develop a new method to quantitatively characterise the fibre structure of such foods, a laser transmission imaging system is constructed to capture the laser beam spot on a sample, and the resulting image undergoes a series of image processing steps that use computer vision to translate the light and dark variations of the original images into distinct ellipses. The results show that the degree of orientation can be reasonably calculated from the ellipse obtained by fitting the outermost isopixel points. To validate the reliability of the newly developed method, we determine the degree of orientation of typical fibrous foods (extruded beef jerky, pork jerky, chicken jerky, and duck jerky). The ranking of the measured orientation agrees with the results of pseudocolour maps and micrographs, confirming the ability of the method to distinguish different fibrous foods. Furthermore, the relatively small coefficients of variation and the strong positive correlation between the degree of organisation and the degree of orientation confirm the reliability of this newly developed method.

Testing of Different Digestion Solutions on Tissue Samples and the Effects of Used Potassium Hydroxide Solution on Polystyrene Microspheres

Microplastic particles are ubiquitous in our environment, having entered the air, the water, the soil, and ultimately our food chain. Owing to their small size, these particles can potentially enter the bloodstream and accumulate in the organs. To detect microplastics using existing methods, they must first be isolated. The aim of this study was to develop a non-destructive method for efficiently and affordably isolating plastic particles. We investigated the digestion of kidney, lung, liver, and brain samples from pigs. Kidney samples were analyzed using light microscopy after incubation with proteinase K, pepsin/pancreatin, and 10% potassium hydroxide (KOH) solution. Various KOH:tissue ratios were employed for the digestion of lung, liver, and brain samples. Additionally, we examined the effect of 10% KOH solution on added polystyrene microplastics using scanning electron microscopy. Our findings revealed that a 10% KOH solution is the most suitable for dissolving diverse organ samples, while enzymatic methods require further refinement. Moreover, we demonstrated that commonly used 1 µm polystyrene particles remain unaffected by 10% KOH solution even after 76 h of incubation. Digestion by KOH offers a simple and cost-effective approach for processing organ samples and holds potential for isolating plastic particles from meat products.

A high performance thin layer chromatography (HPTLC) method for the quality assessment of citronella oil: application in commercial sample analysis

Citronella oil, extracted from Cymbopogon species (winterianus and nardus) is a commercially valuable essential oil used in personal-care products and insect repellents. Routine analysis in gas chromatography is incapable of detecting high-boiling adulterants therein. In this study, an HPTLC technique was developed for the absolute quantification of citronellal (characteristic chemical marker) and triglyceride (main constituent of vegetable oil adulterant) in citronella oil for its quality assessment. It was validated in terms of specificity, linearity, sensitivity, accuracy and precision. Further, the developed method was employed to quantify citronellal and triglyceride in twenty commercial samples. The results showed a wide variation in citronellal content (trace to 30.65% w/w) and could differentiate its two chemotypes. Also, it revealed the possibility of vegetable oil adulteration through the detection and quantification of triglyceride in selected samples. It can be a simple and rapid technique for the quality control of citronella oil.

A quantum chemical interaction energy dataset for accurately modeling protein-ligand interactions

Fast and accurate calculation of intermolecular interaction energies is desirable for understanding many chemical and biological processes, including the binding of small molecules to proteins. The Splinter ["Symmetry-adapted perturbation theory (SAPT0) protein-ligand interaction"] dataset has been created to facilitate the development and improvement of methods for performing such calculations. Molecular fragments representing commonly found substructures in proteins and small-molecule ligands were paired into >9000 unique dimers, assembled into numerous configurations using an approach designed to adequately cover the breadth of the dimers' potential energy surfaces while enhancing sampling in favorable regions. ~1.5 million configurations of these dimers were randomly generated, and a structurally diverse subset of these were minimized to obtain an additional ~80 thousand local and global minima. For all >1.6 million configurations, SAPT0 calculations were performed with two basis sets to complete the dataset. It is expected that Splinter will be a useful benchmark dataset for training and testing various methods for the calculation of intermolecular interaction energies.

Strategies for capillary electrophoresis: Method development and validation for pharmaceutical and biological applications-Updated and completely revised edition

This review is in support of the development of selective, precise, fast, and validated capillary electrophoresis (CE) methods. It follows up a similar article from 1998, Wätzig H, Degenhardt M, Kunkel A. "Strategies for capillary electrophoresis: method development and validation for pharmaceutical and biological applications," pointing out which fundamentals are still valid and at the same time showing the enormous achievements in the last 25 years. The structures of both reviews are widely similar, in order to facilitate their simultaneous use. Focusing on pharmaceutical and biological applications, the successful use of CE is now demonstrated by more than 600 carefully selected references. Many of those are recent reviews; therefore, a significant overview about the field is provided. There are extra sections about sample pretreatment related to CE and microchip CE, and a completely revised section about method development for protein analytes and biomolecules in general. The general strategies for method development are summed up with regard to selectivity, efficiency, precision, analysis time, limit of detection, sample pretreatment requirements, and validation.

Evaluating the Impact of Hair Care Product Exposure on Hair Follicle and Scalp Health

Human hair follicles traverse the epidermis and dermis, and are comprised of specialised cells including dermal papilla cells (DPCs). DPCs play a critical role in the development and growth of both hair and follicle structure. While exposure of DPCs to undiluted exogenous compounds is unlikely, exposure to diluted compounds is possible should dermal penetration occur. The goal of this study was to evaluate the impact on hair and scalp health following application of a hair care product. Due to the lack of standardised and validated test systems for evaluating hair follicle health, the HairSkin® model, which uses intact human scalp samples, was adapted to evaluate hair follicle and scalp health. Similarly, the Franz diffusion cell assay and matrix-assisted laser desorption ionisation-Fourier transform ion cyclotron resonance (MALDI-FTICR) were adapted to evaluate dermal penetration. The results of this study demonstrate that application of the hair care product does not result in appreciable dermal penetration, suggesting that DPCs are unlikely to be exposed to undiluted product. Additionally, hair follicle health was not impacted following product application. While this study is exploratory, these results suggest that the combination of test systems utilised herein provides valuable insight and warrants further development and validation.

LC-MS/MS Method Development and Validation for Determination of Favipiravir Pure and Tablet Dosage Forms

Objectives

Analytical method development and validation for determination of favipiravir (FVPR) in pure and tablet dosage forms by liquid chromatography with tandem mass spectrometry/mass spectrometry (LC-MS/MS) technique.

Materials and Methods

A simple LC-MS/MS method was developed for determination of a new antiviral drug, FVPR in pharmaceutical formulations. The stationary phase employed was a Shim pack GISS, C18 (100 mm × 2.1 mm, 1.9 μm) column and mobile phase used in pump A was 10.0 mM ammonium acetate and in pump B methanol was used. The gradient program was used with fixed mobile phase flow rate at 0.4 mL min-1. Total run time was 5.0 min. The proposed method was validated according to International Conference on Harmonization (ICH) guidelines. The established method found better outcomes.

Results

The linearity graph was found in the range of 50-200 μg/mL and the correlation coefficient value (R2) obtained was found to be 1.0. The limit of detection (LOD) and limit of quantification (LOQ) were 4.044 μg/mL and 12.253 μg/mL, respectively. Tremendous recovery outcomes were observed and found to be 101%, 99.0%, and 99.5% for FVPR at 150% upper, 100% middle, and 50% lower concentrations, respectively.

Conclusion

All outcomes obtained comply with ICH guidelines. The developed method was simple, unique, accurate, robust, precise, and reproducible for determination of FVPR in tablet formulation. The method is novel and could be adopted in formulation industry.

Exploring the Impact of Organic Solvent Quality and Unusual Adduct Formation during LC-MS-Based Lipidomic Profiling

Liquid chromatography-mass spectrometry (LC-MS) is the key technique for analyzing complex lipids in biological samples. Various LC-MS modes are used for lipid separation, including different stationary phases, mobile-phase solvents, and modifiers. Quality control in lipidomics analysis is crucial to ensuring the generated data's reliability, reproducibility, and accuracy. While several quality control measures are commonly discussed, the impact of organic solvent quality during LC-MS analysis is often overlooked. Additionally, the annotation of complex lipids remains prone to biases, leading to potential misidentifications and incomplete characterization of lipid species. In this study, we investigate how LC-MS-grade isopropanol from different vendors may influence the quality of the mobile phase used in LC-MS-based untargeted lipidomic profiling of biological samples. Furthermore, we report the occurrence of an unusual, yet highly abundant, ethylamine adduct [M+46.0651]+ that may form for specific lipid subclasses during LC-MS analysis in positive electrospray ionization mode when acetonitrile is part of the mobile phase, potentially leading to lipid misidentification. These findings emphasize the importance of considering solvent quality in LC-MS analysis and highlight challenges in lipid annotation.

Minimizing non-radiative decay in molecular aggregates through control of excitonic coupling

The widely known "Energy Gap Law" (EGL) predicts a monotonically exponential increase in the non-radiative decay rate (knr) as the energy gap narrows, which hinders the development of near-infrared (NIR) emissive molecular materials. Recently, several experiments proposed that the exciton delocalization in molecular aggregates could counteract EGL to facilitate NIR emission. In this work, the nearly exact time-dependent density matrix renormalization group (TD-DMRG) method is developed to evaluate the non-radiative decay rate for exciton-phonon coupled molecular aggregates. Systematical numerical simulations show, by increasing the excitonic coupling, knr will first decrease, then reach a minimum, and finally start to increase to follow EGL, which is an overall result of two opposite effects of a smaller energy gap and a smaller effective electron-phonon coupling. This anomalous non-monotonic behavior is found robust in a number of models, including dimer, one-dimensional chain, and two-dimensional square lattice. The optimal excitonic coupling strength that gives the minimum knr is about half of the monomer reorganization energy and is also influenced by system size, dimensionality, and temperature.

Development and validation of a QuEChERS-LC-MS/MS method for determination of multiple mycotoxins in maize and sorghum from Botswana

Climatic conditions such as drought, high temperatures, and pre-harvest rainfalls promote the occurrence of mycotoxins in grains. Contamination of staple food sources such as maize and sorghum means that many populations are at risk of being poisoned by mycotoxins. Hence the need for sensitive methods for their simultaneous analysis. Herein, a quick, easy, cheap, effective, rugged, and safe liquid chromatography tandem mass spectrometry (QuEChERS-LC-MS/MS) method for the simultaneous determination of ten mycotoxins in maize and sorghum is presented. The QuEChERS extraction procedure was optimized to maximize extraction recovery and minimize matrix effects while using relatively small quantities of organic solvents and acids. This method was validated according to Commission Implementing Regulation (EU) 2021/808, Commission Regulation (EC) No 1881/2006, and Regulation (EC) no. 401/2006. The developed method met the specified requirements. Recoveries of 80.77% to 109.83% and CVs below 15% were obtained. The correlation coefficient values (R2) were all above 0.98, and low limits of quantification ranging from 0.53 to 89.28 µg/Kg were recorded. The method was applied to 10 maize and 10 sorghum samples collected from markets in Botswana. Half of the samples had detectable mycotoxins, Aflatoxins, Fumonisins, T2-toxin, HT2-toxin, and Zearalenone. Two maize samples had levels of aflatoxin B1 above the maximum permitted level (2.55, 4.07 µg/Kg). These findings point to the necessity of more stringent monitoring of mycotoxins, particularly AFB1 in maize, as well as the value of regular assessment using LC-MS/MS.

HILIC UPLC/ QTof MS Method Development for the Quantification of AGEs Inhibitors - Trouble Shooting Protocol

OBJECTIVE

The paper reports an attempt to develop and validate a HILIC UPLC/ QTof MS method for quantifying N-ε-carboxymethyl-L-lysine (CML) in vitro, testing N-ε-carboxy[D2]methyl-L-lysine (d2-CML), and N-ε-carboxy[4,4,5,5-D4]methyl-L-lysine (d4-CML) as internal standards.

METHOD

During the method development, several challenging questions occurred that hindered the successful completion of the method. The study emphasizes the impact of issues, generally overlooked in the development of similar analytical protocols. For instance, the use of glassware and plasticware was critical for the accurate quantification of CML. Moreover, the origin of atypical variation in the response of the deuterated internal standards, though widely used in other experimental procedures, was investigated.

RESULT

A narrative description of the systematic approach used to address the various drawbacks during the analytical method development and validation is presented.

CONCLUSION

Reporting those findings can be considered beneficial while bringing an insightful notion about critical factors and potential interferences. Therefore, some conclusion and ideas can be drawn from these trouble-shooting questions, which might help other researchers to develop more reliable bioanalytical methods, or to raise their awareness of stumbling blocks along the way.

Development of a Long-Term Sampling Method for Determination of NMHCs in Indoor Air

Vapor intrusion is detrimental for indoor air quality. One of the most common sources of vapor intrusion is soil contaminated with petroleum hydrocarbons. To evaluate the long-term risk from individual exposure to hydrocarbons it is necessary to measure quantitively and reliably an average concentration level of individual pollutants on a monthly or yearly basis. Temporal variability of vapor intrusion from hydrocarbons poses a significant challenge to determination of average exposure and there is a need for reliable long-term integrative sampling. To this end, an analytical method for determination of 10 selected nonmethane hydrocarbons (NMHCs), including hexane, heptane, octane, decane, benzene, toluene, ethyl-benzene, m,p-xylene, o-xylene, and naphthalene, sampled on active triple-bed tubes filled with Carbograph 2, Carbograph 1, and Carboxen 1003 adsorbents was developed and validated. Extensive laboratory studies proved the absence of breakthrough at 50% HR and ambient temperature for experiments lasting up to 28 days and established a safe sampling time/volume of 20 days/114 L when sampling at a low flow rate of around 4 mL min^-1. In addition, the developed method includes detailed uncertainty calculations for determination of concentrations. Finally, the method was tested by measuring NMHC concentrations in indoor air at a former industrial site during a 2-month-long field campaign in Lyon. The results of the field campaign suggest that 4-week integrated concentration measurements can be achieved by using active sampling on triple-bed tubes at 4.5 mL min^-1.

[Development of a widely-targeted metabolomics method based on gas chromatography-mass spectrometry]

Gas chromatography-mass spectrometry (GC-MS) detectors are widely used detection instruments owing to their distinct advantages over other analytical techniques, including lower sample consumption, higher sensitivity, faster analysis speed, and simultaneous separation and analysis. Metabolomics is an important component of system physiology that concerns systematic studies of the metabolite spectrum in one or more biological systems, such as cells, tissues, organs, body fluids, and organisms. Unfortunately, conventional GC-MS detectors also feature low scan rates, high ion loss rates, and a narrow concentration detection range, which limit their applications in the field of metabolomics. Therefore, establishing a GC-MS-based metabolomic analysis method with wide coverage is of great importance. In this research, a widely-targeted metabolomics method based on GC-MS is proposed. This method combines the universality of untargeted metabolomics with the accuracy of targeted metabolomics to realize the qualitative and semi-quantitative detection of numerous metabolites. It does not require a self-built database and exhibits high sensitivity, good repeatability, and strong support for a wide range of metabolic substances. The proposed method was used to establish the relationship between the retention time of straight-chain fatty acid methyl esters (FAMEs) and their retention index (RI) in the FiehnLib database based on the metabolite information stored in this database. We obtained a linear relationship that could be described by the equation y=40878x-47530, r²=0.9999. We then calculated the retention times of metabolites in the FiehnLib database under the experimental conditions based on their RI. In this way, the effects of significant variations in peak retention times owing to differences in the chromatographic column, temperature, carrier gas flow rate, and so on can be avoided. The retention time of a substance fluctuates within a certain threshold because of variations in instrument performance, matrix interference, and other factors. As such, the retention time threshold of the substance must be determined. In this paper, the retention time threshold was set to 0.15 min to avoid instrument fluctuations. The optimal scan interval was optimized to 0.20 s (possible values=0.10, 0.15, 0.20, 0.25, and 0.30 s) because longer sampling periods can lead to spectral data loss and reductions in the resolution of adjacent chromatographic peaks, whereas shorter sampling periods can result in deterioration of the signal-to-noise ratio of the collected signals. The metabolite quantification ions were optimized to avoid the interference of quantification ion peak accumulation in the case of similar peak times, and a selected ion monitoring (SIM) method table was constructed for 611 metabolites, covering 65% of the metabolic pathways in the KEGG (Kyoto Encyclopedia of Genes and Genomes). The developed method covered 39 pathways, including glycolysis, the tricarboxylic acid cycle, purine metabolism, pyrimidine metabolism, amino acid metabolism, and biosynthesis. Compared with the full-scan untargeted GC-MS method, the widely-targeted GC-MS method demonstrated a 20%-30% increase in the number of metabolites detected, as well as a 15%-20% increase in signal-to-noise ratio. The results of stability tests showed that 84% of the intraday relative standard deviations (RSDs) of metabolite retention times were less than 2% and 91% of that were less than 3%; moreover, 54% of the interday RSDs of metabolite retention times were less than 2% and 76% of that were less than 3%. The detection and analysis results of common biological samples confirmed that the proposed method greatly improved the quantity and signal-to-noise ratio of the detected metabolites and is applicable to substances that are thermally stable, volatile, or volatile after derivation and have relative molecular masses lower than 600. Thus, the widely-targeted GC-MS method can expand the application scope of GC-MS in metabolomics.

Progress in high-resolution isotope-ratio analysis of tree rings using laser ablation

Stable isotope ratio analysis of tree rings has been widely and successfully applied in recent decades for climatic and environmental reconstructions. These studies were mostly conducted at an annual resolution, considering one measurement per tree ring, often focusing on latewood. However, much more information could be retrieved with high-resolution intra-annual isotope studies, based on the fact that the wood cells and the corresponding organic matter are continuously laid down during the growing season. Such studies are still relatively rare, but have a unique potential for reconstructing seasonal climate variations or short-term changes in physiological plant properties, like water-use efficiency. The reason for this research gap is mostly technical, as on the one hand sub-annual, manual splitting of rings is very tedious, while on the other hand automated laser ablation for high-resolution analyses is not yet well established and available. Here, we give an update on the current status of laser ablation research for analysis of the carbon isotope ratio (δ13C) of wood, describe an easy-to-use laser ablation system, its operation and discuss practical issues related to tree core preparation, including cellulose extraction. The results show that routine analysis with up to 100 laser shot-derived δ13C-values daily and good precision and accuracy (ca. 0.1‰) comparable to conventional combustion in an elemental analyzer are possible. Measurements on resin-extracted wood is recommended as most efficient, but laser ablation is also possible on cellulose extracted wood pieces. Considering the straightforward sample preparation, the technique is therefore ripe for wide-spread application. With this work, we hope to stimulate future progress in the promising field of high-resolution environmental reconstruction using laser ablation.

Validation of a Novel RP-HPLC Technique for Simultaneous Estimation of Lignocaine Hydrochloride and Tibezonium Iodide: Greenness Estimation Using AGREE Penalties

Herein, we reported an HPLC method for the simultaneous determination of tibezonium iodide (TBN) and lignocaine hydrochloride (LGN). The method was developed according to the International Conference for Harmonization guidelines (ICH) Q2R1 using Agilent^® 1260 with a mobile phase consisting of acetonitrile and phosphate buffer (pH 4.5) in a volumetric ratio of 70:30 and flowing through a C₈ Agilent^® column at 1 mL/min. The results revealed that TBN and LGN peaks were isolated at 4.20 and 2.33 min, respectively, with a resolution of 2.59. The accuracy of TBN and LGN was calculated to be 100.01 ± 1.72% and 99.05 ± 0.65% at 100% concentration, respectively. Similarly, the respective precision was 100.03 ± 1.61% and 99.05 ± 0.48%. The repeatability for TBN and LGN was found to be 99.05 ± 0.48% and 99.19 ± 1.72%, respectively, indicating that the method was precise. The respective regression co-efficient (r²) for TBN and LGN was found to be 0.9995 and 0.9992. Moreover, the LOD and LOQ values for TBN were 0.012 and 0.037 µg/mL, respectively, while for LGN, they were 0.115 and 0.384 µg/mL, respectively. The calculated greenness of the method for ecological safety was found to be 0.83, depicting a green contour on the AGREE scale. No interfering peaks were found when the analyte was estimated in dosage form and in volunteers' saliva, depicting the specificity of the method. Conclusively, a robust, fast, accurate, precise and specific method was successfully validated to estimate TBN and LGN.