Analytical science advances最新文献

Homemade explosives (HMEs), commonly used in improvised explosive devices (IEDs), present a significant forensic challenge due to their chemical variability, accessibility and adaptability. Traditional forensic methodologies often struggle with environmental contamination, complex sample matrices and the non-specificity of precursor residues. Recent advances in analytical techniques and chemometric methods have enhanced the detection, classification and interpretation of explosive residues. Infrared (IR) spectroscopy and gas chromatography–mass spectrometry (GC–MS) have seen improvements in spectral resolution and real-time detection capabilities, allowing for more accurate differentiation of explosive precursors. Thermal analysis techniques, such as thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC), now provide refined kinetic modelling to assess the decomposition pathways of unstable energetic materials, improving forensic risk assessments. Additionally, x-ray diffraction (XRD) has contributed to forensic material sourcing by distinguishing between industrial-grade and improvised explosive formulations. Chemometric approaches, including principal component analysis (PCA), linear discriminant analysis (LDA) and partial least squares discriminant analysis (PLS-DA), have revolutionized forensic data analysis by improving classification accuracy and enabling automated identification of explosive components. Advanced machine learning models are being integrated with spectral datasets to enhance real-time decision-making in forensic laboratories and portable field devices. Despite these advancements, challenges remain in adapting laboratory-based techniques for field deployment, particularly in enhancing the sensitivity and robustness of portable analytical instruments. This review critically evaluates the latest developments in forensic analytical chemistry, highlighting strengths, limitations and emerging strategies to improve real-world HME detection and classification.

Abuse of xylazine is an immediate global public health concern. We report the distinct and measurable colour changes when xylazine is exposed to the Mandelin, Marquis and Mecke presumptive test reagents. The colour changes observed with xylazine are distinct from those of drugs that give colour changes from the same presumptive tests. To overcome the subjective limitations of determining spot test results by-eye, we applied image and video analyses to quantify the distinctive features of presumptive tests with xylazine and thus differentiate it from other illicit substances tested under the same conditions, including morphine, fentanyl, heroin and methamphetamine. Herein, experimental protocols utilising Kineticolor, a computer vision software, were developed to qualitatively and quantitatively study presumptive tests for xylazine detection. To the best of our knowledge, these findings represent the first presumptive test strategy towards specific, quantifiable and potentially field-ready detection of xylazine.

Cardiac troponin I (cTnI) is a crucial biological macromolecule found in the contractile apparatus of cardiac myocytes, exclusively expressed in cardiomyocytes. It is released into the bloodstream upon cardiac tissue injury, serving as a vital biomarker for the early detection of various heart diseases. Despite advancements in cTnI diagnostics and cardiovascular disease (CVD) detection, there is an ongoing need for more effective early diagnostic methods and innovative approaches. Current CVD diagnosis often relies on clinical signs and symptoms, supplemented by molecular imaging (MI) or biomarkers associated with CVD. However, challenges remain regarding the reliability, specificity and accuracy of analyses for myocardial infarction, particularly in its early stages. Emerging nanomaterial systems present promising solutions for enhancing diagnostic tools due to their unique physical and chemical properties. Various nanomaterials, such as gold nanoparticles, carbon nanotubes, quantum dots, lipids and polymer nanoparticles, are paving new pathways for cardiac disease detection. The advancements in nanomaterial science offer exciting opportunities for cardiac screening. This article provides a comprehensive overview of these advancements, categorizing research efforts focused on both optical and electrochemical platforms, thereby contributing to the evolution of cardiac screening methodologies and addressing the critical need for reliable early diagnostic solutions.

Natural products are essential in drug discovery and have diverse applications in biotechnology. Naturally derived compounds are widely recognized as lead candidates in conventional drug development. Molecular docking has become a valuable tool for predicting interactions between small molecules and drug targets, assisting medicinal chemists in designing compounds with potential pharmacological effects. This study aimed to investigate the phytoconstituents of the methanol extract of Boerhavia elegans stem through gas chromatography–mass spectrometry (GC–MS) analysis and to conduct molecular docking studies of active components against the BCL2 receptor protein. Liquid–liquid extractions were performed using n-hexane, chloroform and butanol, followed by GC–MS analysis of the extracts. Molecular docking studies were conducted on active components identified by GC–MS against the BCL2 receptor protein. GC–MS analysis identified 22 compounds in the extracts, with prominent compounds, including hexadecenoic acid, octadec-9-enoic acid, various benzene dicarboxylic acid esters, hexadecanoic acid derivatives, 13-docosenamide and stigmasterol. Molecular docking revealed that γ-sitosterol, α-sitosterol and campesterol exhibited the lowest binding scores, indicating high affinity. These findings support the traditional use of B. elegans stem in treating various ailments, and the molecular docking results provide insights into potential mechanisms of action of the identified compounds.

The introduction of ambient ionisation mass spectrometry (AIMS) is among the most important developments in analytical chemistry in recent years. Enabling the direct analysis of samples in their native state with neither sample preparation nor chromatographic separation provides chemical characterisation in a matter of seconds. Since its inception in the early 2000s, the field of ambient ionisation has continued to expand and develop, pushing the boundaries of analytical chemistry and finding utility across broad areas of scientific research. This annual review provides an overview of key developments and applications of AIMS throughout 2024. The introduction of novel ion sources, development of existing techniques for enhanced performance, and diverse applications across forensic science, food chemistry, disease detection and more highlight the expanding versatility and widespread adoption of ambient ionisation across the globe.

Protein phosphorylation introduces negative charges on the hydroxyl groups of serine, threonine, and tyrosine residues, reducing the ionization efficiency of phosphorylated peptides. The low abundance of phosphorylated peptides often diminishes their detection using mass spectrometry. To enhance the identification of the low-abundance peptides, an enrichment step was often used, which complicated the high-throughput analysis of phosphorylated proteomes. In this study, we developed a titanium dioxide surface-modified macroporous silicon encapsulated micropipette tips, loaded with trypsin, to integrate rapid enzymatic protein hydrolysis with selective enrichment and extraction of phosphorylated peptides within a microfluidic enzyme reactor. This streamlined approach simplified the protein sample preparation process, combining enzymatic hydrolysis, selective enrichment and separation while maintaining high efficiency. The method enabled comprehensive analysis of complex cancer cell line samples in 1–2 h. Successful detection of phosphorylated peptides from protein mixtures was achieved using matrix-assisted laser desorption/ionization-time-of-flight-mass spectrometry. This application may provide the potential for high-throughput phosphoproteomics and advance the study of protein modifications.

The present study is to develop a cost-effective, non-destructive and rapid method for quantification of syringyl/guaiacyl (S/G) ratio content in non-wood lignin, which is based on FT-NIR spectroscopic data and chemometric modelling techniques. The S/G ratio in 22 non-wood lignins was determined by wet chemical method. Then the same samples were run with FT-NIR, and the spectroscopic data were pre-processed with Savitzky–Golay (S–G) on their 1st and 2nd derivatives. As chemometric models, principal component regression (PCR) and partial least square regression (PLSR) were assessed for quantification of S/G ratio in non-wood lignin with raw and pre-treated FT-NIR spectral data. Finally, for quantification of S/G ratio, PLSR showed the best predictive results (R² = 99.90%) with FT-NIR data after treating them with S–G filtered with its derivatives and leverage correction. This rapid and cost-effective method is being proposed for the determination of S/G ratio in non-wood lignin.

Residual contamination by intravenous antineoplastic drugs on hospital surfaces remains a critical concern, as highlighted by numerous studies. This study presents a novel, rapid and highly sensitive analytical method for quantifying a wide range of antineoplastic drugs and detecting other potentially harmful molecules on wiped surfaces. Utilizing hydrophilic interaction liquid chromatography (HILIC) coupled with high-resolution spectrometry, the method combines the quantification of eight commonly used antineoplastic drugs: 5-fluorouracil, ifosfamide, cyclophosphamide, gemcitabine, doxorubicin, methotrexate, epirubicin and irinotecan, with the identification of unknown compounds offering a comprehensive solution for monitoring hospital surface contamination. While HILIC-MS/MS has been extensively applied in various matrices, its use for surface contamination monitoring in healthcare settings has been relatively underexplored. Chromatographic separation was achieved using gradient elution on an HILIC ZORBAX 120 column (150 mm × 2.1 mm, 4 µm), enabling rapid analysis within 8 min. The method demonstrated exceptional sensitivity, achieving limits of quantification below 0.04 ng/cm² for all targeted molecules. Applied to 28 surfaces in the day hospital of a medical oncology unit at a French hospital, the method revealed contamination on 22 surfaces with at least one antineoplastic drug. Additionally, unknown molecules, including a compound associated with cleaning detergents, were detected, highlighting the complexity of hospital surface contamination underscoring the ongoing risks faced by healthcare workers and patients. This innovative approach represents a significant advancement in analytical chemistry and hospital hygiene monitoring, providing a faster, more efficient and versatile alternative to traditional techniques, as it allows 5-FU quantification within the same run time with other molecules. By addressing critical gaps in current methodologies, this study offers valuable insights into occupational safety and supports efforts to reduce exposure risks for healthcare workers and patients. Further research is needed to identify the unknown molecules detected and fully assess their potential risks.

A specific device that combines (1) surface-enhanced Raman spectroscopy (SERS) and (2) superhydrophobic surfaces is developed to detect traces of analytes diluted at sub-femtomolar concentration in water solutions. The first step of the analysis consists in the evaporation of a drop of the solution on the device, designed to concentrate all the analytes on a central functionalized small area (80 µm diameter). This analytical zone is covered with Ag nanoparticles dedicated to enhance Raman signals. In a second step, this zone is scanned pixel by pixel to accumulate around 2200 Raman spectra. The third step is an algorithmic analysis of the pile of spectra to identify Raman peaks that are specific to the targeted molecules. We detail an original analysis method that allows (1) to select spectra that are significantly different from those obtained when a pure solvent is evaporated (control experiment), (2) to classify the spectra by a criterion of similarity and, finally, (3) to select the SERS spectra of the analytes. This method uses hierarchical correlation clustering techniques, the originality being to classify the different spectra on the basis of their peak positions, with all peaks being normalized at the same intensity and bandwidth. The method leads to a convincing identification of spectra of the targeted molecules (i.e. rhodamine B), down to atto-molar concentrations.

Stress is a significant issue among students, affecting both their mental and physical health. In this study, we investigated cortisol levels, a key biomarker for stress, in students at the United Arab Emirates University (UAEU) during their exam period. Using a sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) methodology we measured cortisol concentrations in hair and saliva samples and explored the potential correlation between exam-induced stress and cortisol levels. The results revealed an increase in cortisol levels during the exam period, with male students showing an average hair cortisol concentration of 150.625 pg/mg and female students displaying an average of 77.756 pg/mg. Salivary cortisol levels ranged from 0.002 to 9.189 ng/mL, with an overall average of 4.505 ng/mL. Statistical analysis revealed significant differences in cortisol levels between male and female students, underscoring the impact of exam-related stress on both acute and chronic stress markers. This study underscores the importance of addressing academic stress and suggests targeted strategies to mitigate its impact on student health ultimately fostering an environment encouraging both academic success and psychological well-being within the student community. Future research directions include exploring additional clinical parameters and expanding the study population to further understand the long-term effects of academic stress.