Analytical Science Advances

Triglycerides (TGs) are one of the main components of the glycerolipid family. Their main task in cells is to store excess fatty acids. TG energy storage is mainly concentrated in adipocytes. TGs and free fatty acids constitute the majority (57.5%) of the skin surface lipids (SSLs). TGs are essential for the formation of the skin water barrier. This work is the second part of a global study that aims to evaluate the effect of solar radiations on SSLs using vibrational spectroscopy. In the first part of this work, a stepwise characterization of free fatty acids was performed, and different spectral descriptors were used to follow the different structural modifications during the photo‐oxidation process, that is hydrogen abstraction, formation of hydroperoxides and peroxyl radicals as primary oxidation products and the formation of aldehydes, ketones, alcohol as secondary products. In this second part, the photo‐oxidation of TGs was evaluated using Raman spectroscopy. A decrease in the CH2/CH3 stretching bands ratio that confirmed the hydrogen abstraction, an increase in the 1165/1740 cm−1 ((δ(OH) and υ(C–O))/ν(C=O) (ester)) ratio indicated the formation of secondary oxidation products such as hydroperoxides. And finally, an increase in the 1725/1740 cm−1 (υ(C=O) (ald.)/υ(C=O) (ester)) ratio and the trans ν(C=C)/cis ν(C=C) ratio highlighted the formation of aldehydes, alcohols, ketone, trans secondary products and others.

Biofluid proteomics is a sensitive and high throughput technique that provides vast amounts of molecular data for biomarker discovery. More recently, dried blood spots (DBS) have gained traction as a stable, noninvasive, and relatively cheap source of proteomic data for biomarker identification in disease and injury. Snake envenomation is responsible for significant morbidity and mortality worldwide; however, much remains unknown about the systemic molecular response to envenomation and acquiring biological samples for analysis is a major hurdle. In this study, we utilized DBS acquired from a case of lethal rattlesnake envenomation to determine the feasibility of discovering biomarkers associated with human envenomation. We identified proteins that were either unique or upregulated in envenomated blood compared to non‐envenomated blood and evaluated if physiological response pathways and protein markers that correspond to the observed syndromes triggered by envenomation could be detected. We demonstrate that DBS provide useful proteomic information on the systemic processes that resulted from envenomation in this case and find evidence for a massive and systemic inflammatory cascade, combined with coagulation dysregulation, complement system activation, hypoxia response activation, and apoptosis. We also detected potential markers indicative of lethal anaphylaxis, cardiac arrest, and brain death. Ultimately, DBS proteomics has the potential to provide stable and sensitive molecular data on envenomation syndromes and response pathways, which is particularly relevant in low‐resource areas which may lack the materials for biofluid processing and storage.

IL‐1β is a essential molecule in inflammatory signalling pathways and plays an essential role in inflammatory diseases. Accordingly, the development of monoclonal antibodies (mAbs) that target IL‐1β has become the focus of developing new anti‐inflammatory drugs. The successful clinical application of therapeutic antibodies is dependent on good quality control, which is based on accurate bioactivity determination. The aim of this work was to develop an elegant and accurate reporter gene assay to determine the bioactivity of anti‐IL‐1β antibody drugs. The D10‐G4‐1 cell line with a naturally high expression of IL‐1 receptor was selected as the effector cell, and the plasmid containing luciferase reporter gene with NF‐κB as a regulatory element was transfected into D10‐G4‐1 cells. After a period of pressure screening, a monoclonal cell line with good reactivity and stable expression of reporter gene was finally screened out. Stimulation of this cell line via IL‐1β addition increased the expression of the luciferase gene by activating the NF‐κB signalling pathway, with the addition of luciferase substrate, which can be quantified by relative luminescence units. When anti‐IL‐1β antibodies are present in the system, the expression of luciferase gene is inhibited, which demonstrates the bioactivity of anti‐IL‐1β antibodies. Detailed methodological optimization and comprehensive methodological validation were followed to establish a reporter gene assay for the bioactivity of anti‐IL‐1β antibodies.

Ambient pollution correlated to fine particulate matter (PM2.5) is a worldwide environmental issue as it is highly associated with human health and eco‐environmental safety. A significant part regarding the toxicity of PM2.5 is attributed to its bonded contaminants. Appreciable efforts have been performed to study the occurrence, exposure, and toxicological properties of chemicals of emerging concerns in PM2.5. Recent works indicated a broad environmental transformation of emerging contaminants in the atmospheric environment and highlighted the significance of PM2.5 bonded transformation products, which may exhibit higher environmental concentrations and toxicities compared to their parent compounds. Among these studies, mass spectrometry has been widely applied for the analysis of transformation products of emerging contaminants in PM2.5 on the aspects of suspect/non‐target screening, structure elucidation, concentration profiling, and toxicity determination. This review describes key mass spectrometry‐based analytical strategies and applications for determining transformation products in PM2.5 and presents outlooks for their analysis.

Metabolomics and lipidomics techniques are capable of comprehensively measuring hundreds to thousands of small molecules in single analytical runs and have been used to characterize responses to exercise traditionally using venipuncture‐produced liquid samples. Advanced microsampling devices offer an alternative by circumventing the requirement to maintain frozen samples. This approach combines a microneedle puncture for blood draw with microfluidic sample collection onto a dried carrier and has thus far been employed for targeted measurements of a few analytes. To demonstrate the utility of advanced dried microsampling to characterize metabolomic and lipidomic changes during exercise, we obtained samples before and after a 2‐mile run from twelve (8 male, 4 female) healthy volunteers with various ranges in activity levels. Results highlighted significant changes in whole blood levels of several metabolites associated with energy (glycolysis and Tricarboxylic Acid cycle) and redox (Pentose Phosphate Pathway) metabolism. Lipid changes during this same period were individualized and less uniform. Sex‐based differences in response to running highlighted reliance on carbohydrate or fat substrate utilization in males or females, respectively. The results presented herein illustrate the ability of this approach to monitor circulating metabolome and lipidome profiles from field sampled blood in response to exercise.

Hydrophobic interaction chromatography (HIC) is a chromatographic technique that mainly targets the separation of biomolecules (intact proteins, monoclonal antibodies, etc.) based on the difference in surface hydrophobicity while applying non‐denaturing conditions. This protocol paper provides guidelines for setting‐up robust HIC analysis and considers the instrument configuration, mobile‐phase and sample preparation, as well as chromatographic conditions and settings. The separation of a mixture of intact proteins and monoclonal antibodies is demonstrated by applying conventional HIC conditions, that is, using a mildly hydrophobic (C4) stationary phase in combination with an inverse ammonium sulphate gradient dissolved in aqueous phosphate buffer. The effect of sample‐preparation conditions on sample breakthroughs is presented. Finally, good run‐to‐run repeatability (relative standard deviation < 2%) is demonstrated for five different columns obtained from three different column lots, considering chromatographic retention, peak width, peak area and column pressure.

As a rather recent PhD graduate and still an “early career researcher”, the author wondered what to write about that would be interesting for a young scientist. The answer came while overhearing students in the break room stating, “I wish I had known all that before starting my PhD that would have made everything easier!” – An experience many researchers are very familiar with. From simple tricks for laboratory work to choosing the right software or planning the next career steps, this was a reoccurring theme during the career of the author, who will try to give a short personal overview for young researchers, especially in the analytics and/or natural products field. These topics and lists represent a personal opinion and are neither meant to be all‐encompassing nor of course might differ from the experiences of other researchers.

In the treatment of organophosphate poisoning atropine sulphate monohydrate (AT) and obidoxime dichloride (OB) play a vital role. Currently, the Austrian Armed Forces use the DOUBLEPEN OA two‐chamber autoinjector (ChemProtect) to administer these two drugs. The autoinjector is a part of military standard equipment as a “Basic CBRN‐First Aid Kit” and contains OB and AT with a declared concentration of 220 mg/2 ml and 2 mg/2 ml, respectively. Especially in the two‐chamber autoinjectors, it is highly possible that not all the content of the antidote solution is administered when the autoinjector is triggered. The purpose of the study was to analyze one hundred DOUBLEPEN OA autoinjectors from two different production batches (1707068 and 1707067) for volume loss, drug content and uniformity of dosage unit. Uniformity of dosage units, assessed by the content uniformity method (Chapter 2.9.40 of the European Pharmacopeia), requires the calculation of an acceptable value to quantify the uniformity of the drug product. An acceptance value for the first 10 dosage units of 15.0% or below is considered acceptable. The loss of volume was calculated by determining the density and mass of the solution after triggering the autoinjector. A quantitative high‐performance liquid chromatography method has been developed and in‐house validated for the determination of the content of two drugs. According to International Council for Harmonisation guidelines, the analytical method was proven to be accurate and repeatable. The obtained results show that the average loss of volume after injection was 5%, and the average content of OB and AT for batch 1707068, was 216.5 and 1.9 mg, while for batch 1707067 it was 224.2 and 2.0 mg, respectively. Although the loss of volume and content were observed, the calculated acceptance value for both production batches met the requirements of uniformity of dosage unit by the European Pharmacopeia.

As Scientists, our main role is performing solid, cutting-edge science, to promote our understanding of this world and make new discoveries. However, the accumulating knowledge is meant to be shared with others to allow progress and application for the greater good. Therefore, communication of science is just as important. The rapid developments in technologies and the multidisciplinary approach of science today, is sometimes challenging for explain to heterogeneous audience, both scientific and non-scientific. My postdoc mentor once told me: “try to explain it to your grandmother”. Unfortunately, by that time, I no longer had a living grandma to talk to, but I imagined this conversation in my head every time I had so simplify a complex idea – not for dummies, as often termed- but for well-experienced people just not in my field, like "Grannies".

Cell‐free biosynthesis is emerging as a very attractive alternative for the production of market‐relevant molecules. The free combination of enzymes, regardless of where they are isolated from, raises the possibility to build more efficient synthetic routes but at the same time leads to higher complexity regarding the analysis of the different enzymatic steps. Here we present an analytical method for the real‐time analysis of acyl‐CoA blocks forming and consuming during multi‐step catalyses. We focused on malonyl‐Coenzyme A and acetyl‐CoA, which are the most used acyl‐CoA units for carbon chain elongations. By employing capillary electrophoresis, we could detect the decrease of educts and the formation of products in a time‐resolved fashion.

We measured Raman spectra of N2 fluids obtained at 0.1–25 MPa at room temperature. The 14N15N peak in the Raman spectrum of a low‐pressure N2 fluid is difficult to detect because of the prevalence of a group of peaks attributed to rotational vibration of 14N2. The Raman peaks of 14N15N and 14N2 of N2 fluid at 25 MPa were acquired at various exposure times. The mean values and standard deviations of the peak height ratios and peak area ones of 14N15N and 14N2 were examined for each time. The standard deviations of the peak height ratios and peak area ones were 2.2% and 1.9%, respectively, for 20 spectra acquired with peak height of 1 million counts of 14N2. The uncertainties are about two times higher than those predicted from the noise of a CCD. Improvement of the pixel resolution can enhance the precision of the nitrogen isotope ratios by Raman spectroscopy.

Inorganic arsenic is a carcinogen repeatedly found in water and foods threatening global human health. Prior work applied the Gutzeit method and X‐ray fluorescence spectroscopy to quantify inorganic arsenic based on a harmful chemical, i.e., mercury bromide, to capture the arsine gas. In this project, we explored silver nitrate as an alternative to mercury bromide for the capture and detection of inorganic arsenic. To compare the performance of mercury bromide and silver nitrate, two standard curves were established in the range from 0 to 33.3 µg/L after optimization of reaction conditions such as the quantity of reagents and reaction time. Our result shows silver nitrate‐based standard curve had a lower limit of detection and limit of quantification at 1.02 µg/L and 3.40 µg/L, respectively, as compared to the one built upon mercury bromide that has limit of detection of 4.86 µg/L and limit of quantification of 16.2 µg/L. The relative higher sensitivity when using silver nitrate was contributed by the less interfering elements for X‐ray fluorescence analysis and thus lower background signals. A commercial apple juice was studied for matrix inference, and the results show 85%–99% recoveries and 7.4%–24.5% relative standard deviation. In conclusion, we demonstrated silver nitrate is a better choice in terms of safety restrictions and detection capability at lower inorganic arsenic concentrations.

In molecular design, material design, process design, and process control, it is important not only to construct a model with high predictive ability between explanatory features x and objective features y using a dataset but also to interpret the constructed model. An index of feature importance in x is permutation feature importance (PFI), which can be combined with any regressors and classifiers. However, the PFI becomes unstable when the number of samples is low because it is necessary to divide a dataset into training and validation data when calculating it. Additionally, when there are strongly correlated features in x, the PFI of these features is estimated to be low. Hence, a cross‐validated PFI (CVPFI) method is proposed. CVPFI can be calculated stably, even with a small number of samples, because model construction and feature evaluation are repeated based on cross‐validation. Furthermore, by considering the absolute correlation coefficients between the features, the feature importance can be evaluated appropriately even when there are strongly correlated features in x. Case studies using numerical simulation data and actual compound data showed that the feature importance can be evaluated appropriately using CVPFI compared to PFI. This is possible when the number of samples is low, when linear and nonlinear relationships are mixed between x and y when there are strong correlations between features in x, and when quantised and biased features exist in x. Python codes for CVPFI are available at https://github.com/hkaneko1985/dcekit.

Neospora caninum is an obligate intracellular protozoan parasite of the phylum Alveolata (subphylum Apicomplexa) which has not been studied extensively in a biochemical context. N. caninum is a primary cause of reproductive disorders causing mummification and abortion not only in cattle but also in other small ruminant species resulting in a substantial economic impact on the livestock industry. In canids, which are the final hosts of N. caninum, clinical disease includes neuromuscular symptoms, ataxia, and ascending paralysis. Fatal outcomes of neosporosis have also been reported depending on the host species, age and immune status, however, its zoonotic potential is still uncertain. Therefore, N. caninum should be thoroughly investigated. Matrix‐assisted laser desorption/ionisation (MALDI) mass spectrometry (MS) and MS imaging (MSI) were used, combined with high‐performance liquid chromatography (HPLC) to investigate these intracellular parasites. The aim of this study was to identify molecular biomarkers for N. caninum tachyzoite‐infected host cells and to further clarify their functions. By atmospheric‐pressure scanning microprobe MALDI MS(I), sections of N. caninum‐infected and non‐infected host cell pellets were examined in order to determine potential markers. In vivo, N. caninum infects different types of nucleated cells, such as endothelial cells which represent a highly immunoreactive cell type. Therefore, primary bovine umbilical vein endothelial cells were here used as a suitable infection system. For comparison, the permanent MARC‐145 cell line was used as an additional, simplified in vitro cell culture model. HPLC‐tandem MS (HPLC‐MS/MS) experiments combined with database search were employed for structural verification of markers. The statistically relevant biomarkers found by MS and identified by HPLC‐MS/MS measurements were partly also found in infected monolayers. Marker signals were imaged in cell layers of N. caninum‐infected and non‐infected host cells at 5 µm lateral resolution.

Bioactive peptides with a molecular mass between 2 and 10 kDa represent an important class of substances banned in elite sports, which has been recognized with an increasing number and variety of substances by anti-doping organizations. Also, the annually renewed list of prohibited substances of the World Anti-Doping Agency (WADA) explicitly mentions more and more of these peptides, and efficient testing procedures are required. Even under simplified sample preparation conditions, liquid chromatography coupled to high-resolution mass spectrometry (with resolution properties > 100,000 full width at half maximum) offers suitable conditions for this task and can therefore be used as an initial testing procedure. In contrast to urine, blood analysis essentially relies on the detection of intact peptide hormones, and the expected concentrations are commonly higher in blood samples than in urine. This facilitates the analysis, and a generic sample preparation by means of mixed-mode solid-phase extraction could be realized in this study. Co-extraction and analysis of several different peptides such as insulins (human, lispro, aspart, glulisine, tresiba, detemir, glargine, bovine insulin and porcine insulin), growth hormone releasing hormones (sermorelin, CJC-1295 and tesamorelin), insulin-like growth factors (long-R3-IGF-I, R3-IGF-I and Des1-3-IGF-I) and mechano growth factors (human MGF and MGF-Goldspink) with criteria that fulfil the requirements of the WADA documents (TD2022 MRPL) for doping controls. The proof of principle was shown by the analysis of post administration samples after treatment with synthetic insulin analogues.

The copper slags collected during the excavation of the Early Harappan period site at Kunal in northern India were studied to understand the advancement of smelting technology and the achieved smelting temperature in the furnace by undertaking archaeometallurgical characterisation of the slags. In this research, two types of slags such as slag with glassy appearance and granulated slag were selected for the study. The microscopic structure and distribution of slag components were investigated using optical microscopy and phase determination was done by X‐ray diffraction (XRD). Chemical characterization of the slags was conducted using scanning electron microscopy–energy‐dispersive X‐ray spectroscopy, X‐ray fluorescence analysis (XRF) and inductively coupled plasma–mass spectrometry to build a complete chemical profile of the slags. Fayalite and magnetite were the dominant phases in the glassy slag; however, the granulated slag showed the dominance of calcite as secondary phase which reflected the dolomitic stoichiometry of the slag. The presence of dominant fayalite mineral phase as detected by XRD and higher concentration of iron as detected by XRF indicated the reducing environment during the smelting process. In this study, the absence of sulphur is reported which is unique to the ancient copper slag.

Analytic methods development, like many other disciplines, relies on experimentation and data analysis. Determining the contribution of a paper or report on a study incorporating data analysis is typically left to the reviewer's experience and good sense, without reliance on structured guidelines. This is amplified by the growing role of machine learning driven analysis, where results are based on computer intensive algorithm applications. The evaluation of a predictive model where cross validation was used to fit its parameters adds challenges to the evaluation of regression models, where the estimates can be easily reproduced. This lack of structure to support reviews increases uncertainty and variability in reviews. In this paper, aspects of statistical assessment are considered. We provide checklists for reviewers of applied statistics work with a focus on analytic method development. The checklist covers six aspects relevant to a review of statistical analysis, namely: (1) study design, (2) algorithmic and inferential methods in frequentism analysis, (3) Bayesian methods in Bayesian analysis (if relevant), (4) selective inference aspects, (5) severe testing properties and (6) presentation of findings. We provide a brief overview of these elements providing references for a more elaborate treatment. The robustness analysis of an analytical method is used to illustrate how an improvement can be achieved in response to questions in the checklist. The paper is aimed at both engineers and seasoned researchers.

The objective of this study is to develop an adaptive software sensor technique that can predict objective process variables for a target grade in a plant while also considering information related to various other grades. We use a dataset of the target grade as the target domain and those of the other grades as source domains to perform transfer learning. Multiple models or sub‐models are constructed by setting a source domain for each grade and changing the number of samples used as the source domain. Furthermore, to prevent the negative transfer, the use of a source domain is automatically judged. In this study, we constructed sub‐models using the locally weighted partial least squares approach as an adaptive soft sensor technique. The values of an objective variable were predicted with ensemble learning using sub‐models. The effectiveness of the proposed method was verified using a dataset measured in an actual incineration plant, and the proposed method was able to accurately predict the product quality even when the plant was operated in five grades and when a new grade was produced.

Tolinapant (ASTX660), a pan‐selective inhibitor of apoptosis protein antagonist with dual cIAP/XIAP activity, was identified as a clinical candidate in preclinical efficacy, pharmacokinetic and safety studies. In order to assess tolinapant in first‐in‐human Phase I/II clinical trials, a validated bioanalytical method was required to determine plasma pharmacokinetics. Tolinapant and d4‐tolinapant were extracted from human plasma using liquid‐liquid extraction. Separation chromatography was performed on a Acquity BEH C18 1.7 µM, 50 mm × 2.1 mm i.d. column, using a mobile phase of 0.1% formic acid in water and 0.1% formic acid in acetonitrile. Mass spectrometry detection was performed by positive turbo ion spray ionisation, in multiple reaction monitoring mode. The method was validated according to the US Food and Drug Administration (FDA) guidelines. The method has a quantifiable linear range of 1–500 ng/mL (r2 = 0.999). The intra‐ and inter‐day coefficients of variation were < 11.4%. Dilution QC samples agreed with prepared concentrations, with a precision of 1.5% and accuracy of 101%. Tolinapant mean recoveries ranged from 85.1–94.4 % with negligible matrix effects. A highly sensitive and selective LC‐MS/MS bioanalytical method was developed and validated. The method was successfully applied in Phase 1/2 clinical trials to determine the human pharmacokinetic profile of tolinapant.

Biomimetic chromatography is the name of the High Performance Liquid Chromatography (HPLC) methods that apply stationary phases containing proteins and phospholipids that can mimic the biological environment where drug molecules distribute. The applied mobile phases are aqueous organic with a pH of 7.4 to imitate physiological conditions that would be encountered in the human body. The calibrated retention of molecules on biomimetic stationary phases reveals a compound's affinity to proteins and phospholipids, which can be used to model the biological and environmental fate of molecules. This technology, when standardised, enables the prediction of in vivo partition and distribution behaviour of compounds and aids the selection of the best compounds for further studies to become a drug molecule. Applying biomimetic chromatographic measurements helps reduce the number of animal experiments during the drug discovery process. New biomimetic stationary phases, such as sphingomyelin and phosphatidylethanolamine, widen the application to the modelling of blood–brain barrier distribution and lung tissue binding. Recently, the measured properties have also been used to predict toxicity, such as phospholipidosis and cardiotoxicity. The aquatic toxicity of drugs and pesticides can be predicted using biomimetic chromatographic data. Biomimetic chromatographic separation methods may also be extended in the future to predict protein and receptor binding kinetics. The development of new biomimetic stationary phases and new prediction models will further accelerate the widespread application of this analytical method.

The first oligonucleotide therapeutic was approved by the Food and Drug Administration in 1998, and since then, 12 nucleic acids have been commercialised as medicines. To be approved, the oligonucleotides need to be identified and characterised as well as its related impurities. Different methods exist, but the most commonly used is ion‐pairing reversed‐phase liquid chromatography with tandem mass spectrometry. The separation obtained depends on the mobile phase and column used. Other methods have been developed, notably by using hydrophilic interaction chromatography and two‐dimensional high performance liquid chromatography. Furthermore, ion‐pairing reversed‐phase high performance liquid chromatography ultra‐violet spectroscopy detection and mass spectrometry has been optimised for the analysis of methylated nucleobases due to the utilisation of this modification in the drugs. This review covers the recent advancements in the analysis and characterisation of oligonucleotides in 2021 by high performance liquid chromatography mass spectrometry, notably by hydrophilic interaction chromatography and two‐dimensional liquid chromatography but also the different parameters that influence the analysis by ion‐pairing reversed‐phase high performance liquid chromatography, the characterisation of methylated nucleobases, and the recent software developed for oligonucleotides.

Non‐target screening of trace organic compounds complements routine monitoring of water bodies. So‐called features need to be extracted from the raw data that preferably represent a chemical compound. Relevant features need to be prioritized and further be interpreted, for instance by identifying them. Finally, quantitative data is required to assess the risks of a detected compound. This review presents recent and noteworthy contributions to the processing of non‐target screening (NTS) data, prioritization of features as well as (semi‐) quantitative methods that do not require analytical standards. The focus lies on environmental water samples measured by liquid chromatography, electrospray ionization and high‐resolution mass spectrometry. Examples for fully‐integrated data processing workflows are given with options for parameter optimization and choosing between different feature extraction algorithms to increase feature coverage. The regions of interest‐multivariate curve resolution method is reviewed which combines a data compression alternative with chemometric feature extraction. Furthermore, prioritization strategies based on a confined chemical space for annotation, guidance by targeted analysis and signal intensity are presented. Exploiting the retention time (RT) as diagnostic evidence for NTS investigations is highlighted by discussing RT indexing and prediction using quantitative structure‐retention relationship models. Finally, a seminal technology for quantitative NTS is discussed without the need for analytical standards based on predicting ionization efficiencies.

Amniocentesis is the process of retrieving the nutrient‐rich amniotic fluid (AF) that encompasses the growing fetus in order to diagnose fetal diseases and developmental disorders. Currently, it is only performed on pregnant persons at risk and is invasive with the potential for infection and in some cases, miscarriage. A non‐invasive alternative is needed and could be developed using magnetic resonance spectroscopy (MRS). To develop such MRS sequences, ample testing and training are needed and could be most efficiently conducted on a phantom. We propose a protocol for creating such a synthetic AF phantom for MRS testing and optimization. The proposed AF is validated using nuclear magnetic resonance (NMR) proving it produces spectra comparable to those in the literature. The results from this study can aid in developing a non‐invasive fetal diagnostic tool to replace amniocentesis.

Optimization of dye decolourization for wastewater and power production are explored in dual‐chamber microbial fuel cells (MFCs) with TiO2/CdS photocathodes. The rapid reduction of azo dye methylene blue (MB) and power production were enhanced with TiO2/CdS photocathode under illumination. The analysis of electrochemical impedance spectra indicated that the photocatalysis of TiO2/CdS accelerated the electron transfer process of photoelectrode reduction. Moreover, the UV‐visible light spectrophotometer showed that the maximum degradation of the MFCs was 98.25%, which illustrated that MB may be cleaved by photoelectrons generated by light irradiation on the illuminated TiO2/CdS photocathode. Finally, the power production of MFCs in this work promoted reductive decolourization of the dye MB solution.

Ambient ionization mass spectrometry (AIMS) has revolutionized the field of analytical chemistry, enabling the rapid, direct analysis of samples in their native state. Since the inception of AIMS almost 20 years ago, the analytical community has driven the further development of this suite of techniques, motivated by the plentiful advantages offered in addition to traditional mass spectrometry. Workflows can be simplified through the elimination of sample preparation, analysis times can be significantly reduced and analysis remote from the traditional laboratory space has become a real possibility. As such, the interest in AIMS has rapidly spread through analytical communities worldwide, and AIMS techniques are increasingly being integrated with standard laboratory operations. This annual review covers applications of AIMS techniques throughout 2021, with a specific focus on AIMS applications in a number of key fields of research including disease diagnostics, forensics and security, food safety testing and environmental sciences. While some new techniques are introduced, the focus in AIMS research is increasingly shifting from the development of novel techniques toward efforts to improve existing AIMS techniques, particularly in terms of reproducibility, quantification and ease‐of‐use.

This review focuses on the development and applications of organic polymer monoliths, with special attention to the literature published in 2021. The latest protocols in the preparation of polymer monoliths are discussed. In particular, tailored surface modification using nanomaterials, the development of chiral stationary phases and development of stationary phases for capillary electrochromatography are reviewed. Furthermore, the optimization of pore forming solvents composition is also discussed. Finally, the use of monolithic stationary phases in sample treatment using solid‐phase extraction and enrichment methods, molecularly imprinted polymers and enzymatic reactors is mentioned.

As the human population grows, the anthropogenic impacts from various agricultural and industrial processes produce unwanted contaminants in the environment. The accurate, sensitive and rapid detection of such contaminants is vital for human health and safety. Surface‐enhanced Raman spectroscopy (SERS) is a valuable analytical tool with wide applications in environmental contaminant monitoring. The aim of this review is to summarize recent advancements within SERS research as it applies to environmental detection, with a focus on research published or accessible from January 2021 through December 2021 including early‐access publications. Our goal is to provide a wide breadth of information that can be used to provide background knowledge of the field, as well as inform and encourage further development of SERS techniques in protecting environmental quality and safety. Specifically, we highlight the characteristics of effective SERS nanosubstrates, and explore methods for the SERS detection of inorganic, organic, and biological contaminants including heavy metals, pharmaceuticals, plastic particles, synthetic dyes, pesticides, viruses, bacteria and mycotoxins. We also discuss the current limitations of SERS technologies in environmental detection and propose several avenues for future investigation. We encourage researchers to fill in the identified gaps so that SERS can be implemented in a real‐world environment more effectively and efficiently, ultimately providing reliable and timely data to help and make science‐based strategies and policies to protect environmental safety and public health.

Methanogenic archaea (methanogens) are microorganisms that can synthesize methane. They are found in diverse environments ranging from paddy fields to animal digestive tracts to deep‐sea hydrothermal vents. Investigating their distribution and physiological activity is crucial for the detailed analysis of the dynamics of greenhouse gas generation and the search for the environmental limits of life. In methanogens, cobamide cofactors (vitamin B12 analogs) play a key role in methane synthesis and carbon fixation, thus serving as a marker compound that metabolically characterizes them. Here, we report on resonance Raman detection of cobamides in methanogenic cells without destroying cells and provide structural insights into those cobamides. We succeeded in detecting cobamides in four representative methanogens Methanosarcina mazei, Methanosarcina barkeri, Methanopyrus kandleri, and Methanocaldococcus jannaschii. The former two are mesophilic, cytochrome‐containing methanogens, whereas the latter two are hyperthermophilic, non‐cytochrome‐containing methanogens. The 532 nm‐excited Raman spectra of single or multiple cells of the four species all showed resonance Raman bands of cobamides arising mainly from the corrin ring, with the most intense one at ∼1500 cm−1. We envision that resonance Raman microspectroscopy could be useful for in situ, nondestructive identification of methanogenic cells that produce high levels of cobamides.

An increasing number of adverse analytical findings (AAFs) in routine doping controls has been suspected and debated to presumably result from intimate contact with bodily fluids (including ejaculate), potentially facilitating the transfer of prohibited substances. More precisely, the possibility of prohibited drugs being present in ejaculate and introduced by sexual intercourse into the vagina of an athlete and, subsequently, into doping control urine samples, was discussed. Two testing strategies to determine trace amounts of semenogelin I, a major and specific constituent of semen, were assessed as to their applicability to urine samples. First, the testing protocol of a lateral flow immunochromatographic test directed against semenogelin was adapted. Second, a liquid chromatography/tandem mass spectrometry (LC‐MS/MS)‐based method was established, employing solid‐phase extraction of urine, trypsinization of the retained protein content, and subsequent detection of semenogelin I‐specific peptides. Sensitivity, specificity, and reproducibility, but also recovery, linearity, precision, and identification capability of the approaches were assessed. Both assays were used to determine the analyte stability in urine (at 3 µL/mL) at room temperature, +4°C, and ‐20°C, and authentic urine samples collected either after (self‐reported) celibacy or sexual intercourse were subjected to the established assays for proof‐of‐concept. No signals for semenogelin were observed in either assay when analyzing blank urine specimens, demonstrating the methods’ specificity. Limits of detection were estimated with 1 µL and 10 nL of ejaculate per mL of urine for the immunochromatographic and the mass spectrometric approach, respectively, and figures of merit for the latter assay further included intra‐ and interday imprecision (4.5‐10.7% and 3.8‐21.6%), recovery (44%), and linearity within the working range of 0‐100 nL/mL. Spiked urine tested positive for semenogelin under all storage conditions up to 12 weeks, and specimens collected after sexual intercourse were found to contain trace amounts of semenogelin up to 55‐72 h. Probing for the presence of semenogelin in human urine by immunological and chromatographic‐mass spectrometric methods in the context of sports drug testing

The simultaneous analysis of a broad range of polar ionogenic metabolites using capillary electrophoresis‐mass spectrometry (CE‐MS) can be challenging, as two different analytical methods are often required, that is, one for cations and one for anions. Even though CE‐MS has shown to be an effective method for cationic metabolite profiling, the analysis of small anionic metabolites often results in relatively low sensitivity and poor repeatability. In this work, a novel derivatization strategy based on trimethylmethaneaminophenacetyl bromide was developed to enable CE‐MS analysis of carboxylic acid metabolites using normal CE polarity (i.e., cathode in the outlet) and detection by mass spectrometry in positive ionization mode. Optimization of derivatization conditions was performed using a response surface methodology after which the optimized method (incubation time 50 min, temperature 90°C, and pH 10) was used for the analysis of carboxylic acid metabolites in extracts from HepG2 cells. For selected metabolites, detection limits were down to 8.2 nM, and intraday relative standard deviation values for replicates (n = 3) for peak areas were below 21.5%. Metabolites related to glycolysis, tricarboxylic acid cycle, and anaerobic respiration pathways were quantified in 250,000 cell lysates, and could still be detected in extracts from only 25,000 HepG2 cell lysates (∼70 cell lysates injected).

This tutorial review focuses on analytical challenges encountered with the liquid chromatography‐tandem mass spectrometry determination of 25‐hydroxyvitamin D, which is currently still considered the metabolite that is most representative of vitamin D status. It describes how multiple binding states of circulating 25‐hydroxyvitamin D (phase II metabolites, epimers, free/bioavailable/protein‐bound species) can influence the accuracy of the analytical determination. It also summarizes important chemical species that can inadvertently contribute to vitamin D status and thus cause systematic errors. These interfering endogenous and exogenous compounds might be isomers of vitamin D, constitutional isomers or isobars and the article outlines techniques to eliminate or minimize these interferences, including chromatographic separations, ion mobility spectrometry, and high‐resolution mass spectrometry.

Zinc oxide (ZnO) and graphene oxide (GO) nanoparticles, silver/zinc zeolite (Ag/Zn‐Ze), and graphene oxide‐silver (GO‐Ag) nanocomposites were synthesized and characterized with X‐ray powder Diffraction, Field Emission Scanning Electron Microscope and Fourier Transform‐Infrared Spectroscopy. The antibacterial efficacy of these nanoparticles was evaluated against E. coli. by shake flask method and plate culture method for different concentrations. For 105 cells/mL initial bacterial concentration, minimum inhibitory concentration (MIC) were <160, <320, <320, and >1280 μg/mL, and antibacterial concentration at which 50% cells are inhibited (IC50) were 47, 90, 78, and 250 μg/mL for Ag/Zn‐Ze, GO, GO‐Ag, and ZnO, respectively. Therefore, the shake flask method showed that for all nanoparticle concentrations, Ag/Zn‐Ze, and GO‐Ag exhibited greater inhibition efficacy, which was also highly dependent on initial bacterial concentration. However, in case of the plate culture method, similar range of inhibition capacity was found for Ag/Zn‐Ze, GO‐Ag, and ZnO, whereas GO showed lower potency to inhibit E. coli. In addition, GO‐Ag nanocomposite exhibited more efficacy than Ag/Zn‐Ze when the antibacterial surface was prepared with those. However, Ag/Zn‐Ze showed no toxicity on Vero cells, whereas GO‐Ag exhibited severe toxicity at higher concentrations. This study establishes GO‐Ag and Ag/Zn‐Ze as potent antimicrobial agents; however, their application dosage should carefully be chosen based on cytotoxic effects of GO‐Ag in case of any possible physiological interaction.

Metabolomics is the comprehensive study of the metabolome and its alterations within biological fluids and tissues. Over the years, applications of metabolomics have been explored in several areas, including personalised medicine in diseases, metabolome‐wide association studies (MWAS), pharmacometabolomics and in combination with other branches of omics such as proteomics, transcriptomics and genomics. Mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy are the major analytical techniques widely employed in metabolomics. In addition, MS is coupled with chromatography techniques like gas chromatography (GC) and liquid chromatography (LC) to separate metabolites before analysis. These analytical techniques have made possible identification and quantification of large numbers of metabolites, encompassing characterization of diseases and facilitating a systematic and rational therapeutic strategy based on metabolic patterns. In recent years, the metabolomics approach has been used to obtain a deeper insight into the underlying biochemistry of neurodegenerative disorders and the discovery of biomarkers of clinical implications. The current review mainly focuses on an Indian perspective of metabolomics for the identification of metabolites and metabolic alterations serving as potential diagnostic biomarkers for neurological diseases including acute spinal cord injury, amyotrophic lateral sclerosis, tethered cord syndrome, spina bifida, stroke, Parkinson's disease, glioblastoma and neurological disorders with inborn errors of metabolism.

Mosquito‐borne pathogens, including malaria, Zika, dengue, and chikungunya continue to be a major public health concern globally. Based on the understanding that only older female mosquitoes are infectious and represent a risk to human health, scientists have sought to age‐grade mosquitoes for decades. To date, however, no reliable, cost‐effective and practical methods exist to age older mosquitoes despite the tremendous epidemiological value of this approach. This study is the first attempt to develop a surface‐enhanced Raman spectroscopic (SERS) method to age mosquitoes. The water extracts of Aedes aegypti mosquitoes aged 0–22 days were mixed with silver nanoparticles. The SERS spectra, which were analysed by principal component analysis and partial least square (PLS), demonstrated the capability of this approach to predict the calendar age of mosquitoes between 0 and 22 days with the coefficient of correlation (R) = 0.994 and 0.990 for PLS model calibration and validation, respectively. Spectral analysis with both SERS and infrared spectroscopy revealed the key biological sources leading to changes in spectra allowing mosquito age‐grading is adenine‐containing compounds and proteins. In addition, we evaluated the impact of two arthropod‐borne pathogen deactivating pre‐treatments (bleach and ethanol) on the discrimination capability of the SERS approach. The result shows the ethanol treatment has the potential to enhance the discrimination capability and the safety of the approach. This study represents the first step towards developing the SERS approach as a quick, reliable and field‐deployable method for mosquito age‐grading, which would significantly improve the effectiveness of vector‐borne disease monitoring and prevention.

Under different concentrations of the base potassium deuteroxide KOD, the progress of reactions, such as enolization, D‐substitution, isomerization, and conformational changes of diketopiperazine cyclo(L‐Pro‐L‐Xxx) and cyclo(D‐Pro‐L‐Xxx) (Xxx = Phe, Tyr) in D2O solution, was investigated by 1H nuclear magnetic resonance (NMR). Cyclo(L‐Pro‐L‐Xxx) is mostly isomerized to cyclo(D‐Pro‐L‐Xxx) in D2O solution, whereas cyclo(D‐Pro‐L‐Xxx) is only slightly isomerized to cyclo(L‐Pro‐L‐Xxx) even under stronger basic conditions. After adding a deuterated organic solvent (CD3COCD3, CD3SOCD3 or CD3OD) to a D2O solution of cyclo(L‐Pro‐L‐Xxx), cyclo(D‐Pro‐L‐Xxx), or increasing the temperature of the D2O solution, CH‐π interaction between H9 and the benzene ring of cyclo (D‐Pro‐L‐Xxx) was stronger than that between H8α and the benzene ring of cyclo(L‐Pro‐L‐Xxx).

Pharmaco‐metabolomics uses metabolic phenotypes for the prediction of inter‐individual variations in drug response and helps in understanding the mechanisms of drug action. The field has made significant progress over the last 14 years with numerous studies providing clinical evidence for personalised medicine. However, discovered pharmaco‐metabolomic biomarkers are not yet translated into clinics due to a lack of large‐scale validation. Integration of targeted and untargeted metabolomics workflows into pharmacokinetic analysis and drug development can advance the field from bench to bedside. Also, Indian pharmaceutical research and its bioanalytical infrastructure are in a position to take on these opportunities by addressing challenges such as appropriate training and regulatory compliance.

Medicinal plant metabolomics has emerged as a goldmine for the natural product chemists. It provides a pool of bioactive phytoconstituents leading to accelerated novel discoveries and the elucidation of a variety of biosynthetic pathways. Further, it also acts as an innovative tool for herbal medicine's scientific validation and quality assurance. This review highlights different strategies and analytical techniques employed in the practice of metabolomics. Further, it also discusses several other applications and advantages of metabolomics in the area of natural product chemistry. Additional examples of integrating metabolomics with multivariate data analysis techniques for some Indian medicinal plants are also reviewed. Recent technical advances in mass spectrometry‐based hyphenated techniques, nuclear magnetic resonance‐based techniques, and comprehensive hyphenated technologies for phytometabolite profiling studies have also been reviewed. Mass Spectral Imaging (MSI) has been presented as a highly promising method for high precision in situ spatiotemporal monitoring of phytometabolites. We conclude by introducing GNPS (Global Natural Products Social Molecular Networking) as an emerging platform to make social networks of related molecules, to explore data and to annotate more metabolites, and expand the networks to novel “predictive” metabolites that can be validated.