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.

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.