Specific Analytes Research Articles

The Proteomics Standards Initiative Standardized Formats for Spectral Libraries and Fragment Ion Peak Annotations: mzSpecLib and mzPAF.

Mass spectral libraries are collections of reference spectra, usually associated with specific analytes from which the spectra were generated, that are used for further downstream analysis of new spectra. There are many different formats used for encoding spectral libraries, but none have undergone a standardization process to ensure broad applicability to many applications. As part of the Human Proteome Organization Proteomics Standards Initiative (PSI), we have developed a standardized format for encoding spectral libraries, called mzSpecLib (https://psidev.info/mzSpecLib). It is primarily a data model that flexibly encodes metadata about the library entries using the extensible PSI-MS controlled vocabulary and can be encoded in and converted between different serialization formats. We have also developed a standardized data model and serialization for fragment ion peak annotations, called mzPAF (https://psidev.info/mzPAF). It is defined as a separate standard, since it may be used for other applications besides spectral libraries. The mzSpecLib and mzPAF standards are compatible with existing PSI standards such as ProForma 2.0 and the Universal Spectrum Identifier. The mzSpecLib and mzPAF standards have been primarily defined for peptides in proteomics applications with basic small molecule support. They could be extended in the future to other fields that need to encode spectral libraries for nonpeptidic analytes.

Towards the Development of an Optical Biosensor for the Detection of Human Blood for Forensic Analysis

Blood is a common biological fluid in forensic investigations, offering significant evidential value. Currently employed presumptive blood tests often lack specificity and are sample destructive, which can compromise downstream analysis. Within this study, the development of an optical biosensor for detecting human red blood cells (RBCs) has been explored to address such limitations. Aptamer-based biosensors, termed aptasensors, offer a promising alternative due to their high specificity and affinity for target analytes. Aptamers are short, single-stranded DNA or RNA sequences that form stable three-dimensional structures, allowing them to bind to specific targets selectively. A nanoflare design has been employed within this work, consisting of a quenching gold nanoparticle (AuNP), DNA aptamer sequences, and complementary fluorophore-labelled flares operating through a fluorescence resonance energy transfer (FRET) mechanism. In the presence of RBCs, the aptamer–flare complex is disrupted, restoring fluorescence and indicating the presence of blood. Two aptamers, N1 and BB1, with a demonstrated binding affinity to RBCs, were selected for inclusion within the nanoflare. This study aimed to optimise three features of the design: aptamer conjugation to AuNPs, aptamer hybridisation to complementary flares, and flare displacement in the presence of RBCs. Fluorescence restoration was achieved with both the N1 and BB1 nanoflares, demonstrating the potential for a functional biosensor to be utilised within the forensic workflow. It is hoped that introducing such an aptasensor could enhance the forensic workflow. This aptasensor could replace current tests with a specific and sensitive reagent that can be used for real-time detection, improving the standard of forensic blood analysis.

Optical Biosensors for Detection of Cancer Biomarkers: Current and Future Perspectives.

Optical biosensors are emerging as a promising technique for the sensitive and accurate detection of cancer biomarkers, enabling significant advancements in the field of early diagnosis. This study elaborates on the latest developments in optical biosensors designed for detecting cancer biomarkers, highlighting their vital significance in early cancer diagnosis. When combined with targeted nanoparticles, the bio-fluids can help in the molecular stage diagnosis of cancer. This enhances the discrimination of disease from the normal subjects drastically. The optical sensor methods that are involved in the disease diagnosis and imaging of cancer taken for the present review are surface plasmon resonance, localized surface plasmon resonance, fluorescence resonance energy transfer, surface-enhanced Raman spectroscopy and colorimetric sensing. The article meticulously describes the specific biomarkers and analytes that optical biosensors target. Beyond elucidating the underlying principles and applications, this article furnishes an overview of recent breakthroughs and emerging trends in the field. This encompasses the evolution of innovative nanomaterials and nanostructures designed to augment sensitivity and the incorporation of microfluidics for facilitating point-of-care testing, thereby charting a course towards prospective advancements.

The First N,O-Chelated Diphenylboron-Based Fluorescent Probe for Peroxynitrite and Its Bioimaging Applications

Peroxynitrite (ONOO−) is a reactive oxygen species (ROS) that takes part in the oxidation-reduction homeostasis while at the same time being responsible for activating numerous pathological pathways. Accordingly, monitoring the dynamic changes in ONOO− concentration has attracted a great deal of attention, undoubtedly prompting the development of appropriate fluorescent chemosensors. Herein, we developed a novel N,O-chelated diphenylboron-based fluorescent probe (DPB) for ONOO− featuring high selectivity, a quick response time (2.0 min), and a low detection limit (55 nM). DPB incorporates tetra-coordinated boron in the center of the fluorogenic core and a three-coordinated boron from the pinacolphenylboronate fragment, which acts as the recognition site for ONOO−. As confirmed by HR-MS and 1H NMR, the interaction of DPB with ONOO− led to an oxidative cleavage of pinacolphenylboronate moiety to produce strongly emissive derivative DPB-OH. The fluorescence enhancement is likely a result of a substantial deactivation of non-radiative decay due to the replacement of the bulky pinacolphenylboronate moiety with a compact hydroxyl group. Importantly, DPB probe exhibits negligible cytotoxicity and favorable biocompatibility allowing for an efficient tracking of ONOO− in living cells and zebrafish. Overall, the current study does not only represents the first N,O-chelated diphenylboron-based fluorescent probe for a specific analyte, but also serves as a guideline for designing more potent fluorescent probes based on the chemistry of boron chelates.

Influence of Carbon-Nitride Dot-Emitting Species and Evolution on Fluorescence-Based Sensing and Differentiation.

Carbon dots have attracted widespread interest for sensing applications based on their low cost, ease of synthesis, and robust optical properties. We investigate structure-function evolution on multiemitter fluorescence patterns for model carbon-nitride dots (CNDs) and their implications on trace-level sensing. Hydrothermally synthesized CNDs with different reaction times were used to determine how specific functionalities and their corresponding fluorescence signatures respond upon the addition of trace-level analytes. Archetype explosives molecules were chosen as a testbed due to similarities in substituent groups or inductive properties (i.e., electron withdrawing), and solution-based assays were performed using ratiometric fluorescence excitation-emission mapping (EEM). Analyte-specific quenching and enhancement responses were observed in EEM landscapes that varied with the CND reaction time. We then used self-organizing map models to examine EEM feature clustering with specific analytes. The results reveal that interactions between carbon-nitride frameworks and molecular-like species dictate response characteristics that may be harnessed to tailor sensor development for specific applications.

A novel application of hydrophilic interaction liquid chromatography for the identification of compounds with intramolecular hydrogen bonds

The incorporation of intramolecular hydrogen bonds (IMHB) into small molecules constitutes an interesting optimization strategy to afford potential drug candidates with enhanced solubility as well as permeability and consequently improved bioavailability (if metabolic stability is high). Common methods to assess IMHB rely on spectroscopic or diffraction techniques, which, however, have limited throughput when screening for hit compounds in early phases of drug discovery. Inspired by literature findings using supercritical fluid chromatography (SFC) as an indirect method for IMHB identification in a screening context, we aimed at developing a secondary chromatographic methodology taking advantage of commonly used HPLC-MS instrumentation. In this work, we explored hydrophilic interaction liquid chromatography (HILIC) and developed a method for discriminating compounds based on their hydrogen bonding features. By quantifying retention of different matched molecular pairs (MMP) and using information about their low energy conformations from quantum-mechanical calculations, we defined a hydrogen bonding-driven adsorption (kads) chromatographic parameter to assess a compound’s propensity to forming IMHB. In addition to the MMP analysis, we found that the kads parameter allows for the differentiation of analytes forming IMHB regardless of the comparison with control compounds.

A-123 Comparative Assessment of Unmanned High-Speed Aerial Vehicles in Medical Logistics: Blood Sample Transportation Amidst Weather Variability

Abstract Background Drones, as an innovative technology, hold transformative potential in the field of medical logistics, especially in the transportation of sensitive medical materials like blood samples. This study aimed to assess and compare the impact of high-speed drone transportation with conventional car transportation on the integrity and preanalytics of blood samples, taking into account various blood materials and analytes. Methods Blood samples, including EDTA whole blood, serum, and plasma anticoagulated with Citrate and Lithium-Heparin transported as whole blood, were subjected to transportation via both drone and car. Drone flights were tested under diverse weather conditions (ranging between 4 and 20 degrees Celsius), and results were compared to samples stored without transportation. The maximum drone speed exceeded 100 km/h. A total of 28 analytes were tested on Serum, 20 on EDTA, 26 on Lithium-Heparin, and 5 on Citrate blood. Statistical analyses were performed using Passing Bablok and Bland-Altman methods. Results For Serum samples, the correlation coefficient (r) ranged from 0.830 to 1.000, and slopes varied from 0.913 to 1.111. Five analytes (total bilirubin, Calcium, Ferritin, Kalium, and Sodium) exhibited discrepancies between the negative control and the transported sample, with r lower than 0.800, slopes not between 0.8 and 1.2, and mean (%) not between +/- 10%. However, no significant differences were noted between drone and car transportation. Similar patterns emerged for EDTA, Lithium-Heparin, and Citrate samples, with r ranging from 0.829 to 0.997, 0.939 to 0.998, and 0.830 to 1.000, respectively. Slopes ranged from 0.956 to 1.051, 0.938 to 1.085, and 0.913 to 1.111. Despite identifying a few discrepancies in specific analytes, no significant differences were observed between transportation methods. Conclusions n comparison to transportation by car, drone transportation of blood samples did not lead to alterations in concentrations of commonly used analytes. Notably, instances of differences before and after transportation were attributed to the transportation process itself rather than the mode of transportation. This suggests that the use of drones for medical sample transport can be deemed comparable to, if not superior to, traditional car transportation methods.

A-122 Evaluation of the Performance of the BD MiniDraw™ Capillary Blood Collection System Under Various Transport Conditions

Abstract Background Specimen transport is a vital component of the preanalytical phase. External factors such as temperature fluctuations, vibrations, shock, and prolonged transport times may negatively impact specimen integrity and compromise test results. A study was performed to evaluate the effects of temperature extremes and simulated transportation on specimen quality in the BD MiniDraw™ Capillary Blood Collection System with BD MiniDraw™ H&H and SST™ Capillary Blood Collection Tubes (BD MiniDraw™ H&H, BD MiniDraw™ SST™). The BD MiniDraw™ Capillary Blood Collection System enables capillary blood collection by trained healthcare workers in non-traditional settings (i.e., retail pharmacies and clinics). Methods Sixteen adult participants were enrolled from the on-site Associate Sample Collection Program. Venous blood was collected via venipuncture into reference comparator and no-additive tubes. Venous blood from no-additive tubes was then pooled into a secondary container for aliquoting into BD MiniDraw™ SST™ and MiniDraw™ H&H tubes. Thirty tubes per tube type were separated into 6 groups with storage and simulated transport conditions conducted in accordance with ASTM D7386-16 and ASTM D4169-22, as applicable: Group 1a: No transport, 2-8°C storage uncontrolled humidity, 49-52-hour storage; Group 1b: Air/road transport, 2-8°C storage uncontrolled humidity, 49-52-hour storage; Group 2a: No transport, 20-24°C storage, uncontrolled humidity, 5-7-hour storage; Group 2b: Road transport, 20-24°C storage, uncontrolled humidity, 5-7-hour storage; Group 3a: Road transport, 38-40°C storage, 90% relative humidity, 5-7-hour storage; Group 3b: Air/road transport, 38-40°C storage, 90% relative humidity, 49-52-hour storage Following clotting, centrifugation, and storage for the BD MiniDraw™ SST™ tubes, testing was performed for selected chemistry analytes (Albumin, Alanine Aminotransferase (ALT), Alkaline Phosphatase (ALKP), Blood Urea Nitrogen, Chloride, Calcium, Cholesterol, Creatinine, High Density Lipoprotein (HDL), Low Density Lipoprotein (LDL), Sodium, Total Bilirubin (TBIL), Total Protein, Triglycerides) on the Siemens Atellica® Solution. Testing was performed for hemoglobin/hematocrit on the Sysmex XN-1000 in the BD MiniDraw™ H&H Tubes. Visual quality (barrier formation, hemolysis) and tube integrity (physical damage, blood leakage, cap removal, tube fit into adaptor) were also evaluated. Mean biases and confidence intervals within the specific analyte clinical acceptance limit for each group comparison was considered clinically equivalent. Results Clinical equivalence was demonstrated for all analytes for each group comparison except ALKP, ALT, HDL, LDL, TBIL and hematocrit for the extreme transport/storage conditions for Group 3b versus Group 3a. Complete barrier formation with acceptable visual hemolysis was noted in all specimens post transport. Tube integrity was maintained post transport as well. Conclusions Analytes were not impacted across a wide range of temperature and transport conditions. However, exposing samples to extreme high temperature, high humidity conditions may affect analyte performance. This reiterates the importance of monitoring conditions to ensure accurate test results. No impact to visual observations of sample quality and tube physical integrity was noted at different storage and transportation extremes.

A-219 Method Intercomparison Study between Atellica Solution® and CI® Analyzers for Total Cholesterol and Triglycerides

Abstract Background Method intercomparison is an essential requirement that every Laboratory must perform when considering a method or instrument change for a specific analyte. Objective verify if the results of two analytical techniques (Total Cholesterol and Triglycerides) measured by Atellica Solution® and CI® analyzers (Siemens Healthineers) are interchangeable. Methods 40 patient samples were selected for each assay, with results distributed across the entire measurement range and analyzed by both instruments. Estatistical program Method Validator was used. To determine the degree of agreement between both instruments, Bland-Altman difference analysis and Passing-Bablok regression were performed. Statistics are expressed with their 95% confidence intervals. Results Total Cholesterol: After analyzing Bland-Altman differences, a systematic error was found as the mean difference between the results obtained by Atellica Solution® and CI 1900® was 13.8 with a 95% CI that does not include the null value. Regarding Passing Bablok analysis, a constant systematic difference was observed as the confidence interval of the intercept does not include the zero value, and also a proportional difference based on the 95% CI of the slope that does not include the value 1.• Triglycerides: After analyzing the Bland-Altman differences, a systematic error was found as the mean difference between the results obtained by Atellica Solution® and CI 1900® was -15.6, with higher results in Atellica Solution®. Regarding the Passing Bablok analysis, constant systematic differences were observed as the confidence interval of the intercept does not include the zero value, and also proportional differences based on the slope, whose 95% CI does not include the value 1 Conclusions It´s concluded that Atellica Solution® and CI® analyzers are not interchangeable for Total Cholesterol and Triglycerides assays due to the presence of a constant systematic error. To use them on both instruments, it would be advisable to modify the reference values for both methods.

B-010 Intercomparison Study of Methods between Atellica Solution® and CI® Analyzers for Sodium, Potassium, and Chloride

Abstract Background Method verification is an essential analysis routinely conducted in accredited Clinical Laboratories whenever a change of method or instrument for a specific analyte is desired. Objectives The aim of the study is to verify that the results measured by the Atellica Solution® analyzer (Siemens) and the new CI® analyzer (Siemens) for Sodium, Potassium, and Chloride are interchangeable. Methods To conduct the intercomparison study of Sodium, Potassium, and Chloride, the techniques were properly calibrated and controlled on both analyzers. For each assay, 40 patient samples were selected, covering the entire measurement range, and analyzed by both instruments. To determine the degree of agreement between the instruments, a Bland Altman analysis of mean differences and a Passing Bablok regression were performed. Statistics are expressed with their 95% confidence intervals (CI). The evaluation of results was carried out using the statistical program Method Validator. Results In both the Bland-Altman and Passing Bablok regression analyses, a slight constant systematic error was detected for all three assays, as the 95% confidence interval of the observed mean difference and the 95% confidence interval of the intercept of the regression line do not include zero. No systematic proportional differences were observed based on the slope, as the 95% confidence interval includes the value one Conclusions The small constant systematic differences found in the analyses should be re-evaluated after performing a new calibration of the methods. In none of the cases are the differences clinically significant, as they do not exceed the total error established in our quality specification. Therefore, it can be concluded that the Atellica Solution® and CI 1900® analyzers are interchangeable for Sodium, Potassium, and Chloride assays

Statistically sound identification of compounds by low-resolution GC-MS: Identification of tear agents in tear gas sprays

Gas-chromatography hyphenated with low-resolution mass spectrometry is a very flexible tool for the cost-effective identification and quantification of volatile compounds in complex matrices. In some analytical fields, criteria for the agreement between retention time and mass spectra of the analyte in calibrators and samples are defined based on the general understanding of the performance of these parameters. However, since this harmonization is not based on experimental performance observed for specific GC-MS conditions and analyte it leads to false identifications. This research proposes a novel and robust tool for defining statistically sound criteria for the identification of compounds by GC-MS and LC-MS using experimental data. The Monte Carlo Method (MCM) simulation of the correlated abundance of characteristic ions of analyte mass spectrum allows simulating the abundance ratio difference of the analyte in a calibrator and sample used for statistically sound identifications. The Cholesky decomposition of the covariance matrix of ion abundances for MCM simulations allows the reliable use of many ion abundance ratios in identifications. The developed methodology was implemented in a user-friendly Excel spreadsheet and applied to the identification of tear gas agents in tear gas sprays. Criteria defined by SANTE for identifying pesticide residues in foodstuffs were compared with the developed tool. The cross-validation of computational and SANTE tools allowed concluding that the statistical control of retention time and mass spectra performs according to the defined confidence level. On the other hand, the SANTE criteria can produce up to 92% false identifications for being too strict considering signal dispersion.

Fast identification of Baijius based on organic acid response colorimetric sensor array

Herein, a simple colorimetric sensor array sensitive to organic acids was designed by gold (Au) and silver (Ag) nanoparticles modified with four different compounds for the identification of 16 famous Baijius containing different organic acids. In detail, the sensing mechanism of the colorimetric sensor array was based on the charge transfer between the nanoparticle surface protectant and H+, which reduced the electrostatic force between the nanoparticles, leading to the aggregation and color change of the nanoparticles. The unique color change of the colorimetric array before and after the reaction was used as a unique fingerprint profile for each specific analyte, which can be identified by the naked eye. The generated digital database was analyzed using pattern recognition methods, including principal component analysis (PCA), hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA). All Baijius can be easily identified by fingerprint mapping or PCA scoring maps. 32 blind samples were tested by LDA and 30 samples were correctly classified. The HCA results showed that all samples were correctly classified and even very similar 1 % dilutions of the Baijiu can be easily distinguished, demonstrating the potential of the constructed colorimetric sensor array technology for quality control applications of Baijius and other beverages.

Applications of machine learning coupled with computer vision, electronic nose and untargeted analysis for food quality control

Application of artificial intelligence in food quality control has been a new trend, bringing a complete change to the traditional way of food quality control, helping to shorten analysis and detection time and carrying out real time analysis due to nondestructive sample preparation, simpler operations because of using of sensors, collecting a large amount of information thanks to taking all measurement data... This article provides a preliminary view of identification, discrimination and classification of food samples based on using machine learning and deep learning models coupled with analytical data obtained from spectral measurements, using sensors instead of the nose (electronic- nose), camera and image analysis (computer vision) for food quality control purposes such as determining food freshness, authenticating origin as well as detecting adulteration of foods. The published studies show that the application of machine learning models especially in rapid analysis and sample-free analysis has great potential as an alternative to targeted analysis methods with specific analytes in samples.

Microextraction of steroidal hormones from urine samples using natural deep eutectic solvents: insights into chemical interactions using molecular dynamics simulations.

Natural deep eutectic solvents (NADES) are gaining significant attention in analytical chemistry due to attractive physico-chemical properties associated with sustainable aspects. They have been successfully evaluated in different fields, and applications in sample preparation have increased in the last years. However, there is a limited knowledge related to chemical interactions and mechanism of intermolecular action with specific analytes. In this regard, for the first time, this study exploited a computational investigation using molecular dynamics (MD) predictions combined with experimental data for the extraction/determination of steroidal hormones (estriol, β-estradiol, and estrone) in urine samples using NADES. The ultrasound-assisted liquid-liquid microextraction (UALLME) approach followed by high-performance liquid chromatography with diode array detection (HPLC-DAD) was employed using menthol:decanoic acid as extraction solvent. Experimental parameters were optimized through multivariate strategies, with the best conditions consisting of 3min of extraction, 150 μL of NADES, and 3mL of sample (tenfold diluted). According to molecular dynamics predictions confirmed by experimental data, a molar ratio that permitted the highest efficiency consisted of menthol:decanoic acid 2:1 v/v. Importantly, computational simulations revealed that van der Waals interactions were the most significant contributor to the interaction energy of analytes-NADES. Using the optimized conditions, limits of detection (LOD) ranged from 3 and 8μg L-1, and precision (n = 3) varied from 8 to 19%. Intraday precision was evaluated at 3 concentrations: low (LOQ according to each analyte), medium (100μg L-1), and high (750μg L-1). Accuracy was successfully assessed through recoveries that ranged from 82 to 98%. In this case, molecular dynamics simulations proved to be an important tool for in-depth investigations of interaction mechanisms of DES with different analytes.

Fabrication of Three-Dimensional Dendritic Ag Nanostructures: A SERS Substrate for Non-Invasive Detection.

This paper discusses the fabrication of three-dimensional dendritic Ag nanostructures, showcasing pronounced Localized Surface Plasmon Resonance (LSPR) effects. These nanostructures, employed in surface-enhanced Raman scattering (SERS), function as sensors for lactic acid in artificial sweat. The dendritic structures of the silver nanoparticles (AgNPs) create an effective SERS substrate, with additional hotspots at branch junctures enhancing LSPR. We achieve differential LSPR effects by varying the distribution and spacing of branches and the overall morphology. Adjustments to electrodeposition parameters, such as current and plating solution protective agents on an anodized aluminum oxide (AAO) base, allow for precise control over LSPR intensities. By pre-depositing AgNPs, the electron transmission paths during electrodeposition are modified, which leads to optimized dendritic morphology and enhanced LSPR effects. Parameter optimization produces elongated rods with main and secondary branches, covered with uniformly sized, densely packed, non-overlapping spherical AgNPs. This configuration enhances the LSPR effect by generating additional hotspots beyond the branch tips. Fine-tuning the electrodeposition parameters improved the AgNPs' morphology, achieving uniform particle distribution and optimal spacing. Compared to non-SERS substrates, our structure amplified the Raman signal for lactic acid detection by five orders of magnitude. This method can effectively tailor SERS substrates for specific analytes and laser-based detection.

Dual-Purpose Aptamer-Based Sensors for Real-Time, Multiplexable Monitoring of Metabolites in Cell Culture Media.

The availability of high-frequency, real-time measurements of the concentrations of specific metabolites in cell culture systems will enable a deeper understanding of cellular metabolism and facilitate the application of good laboratory practice standards in cell culture protocols. However, currently available approaches to this end either are constrained to single-time-point and single-parameter measurements or are limited in the range of detectable analytes. Electrochemical aptamer-based (EAB) biosensors have demonstrated utility in real-time monitoring of analytes in vivo in blood and tissues. Here, we characterize a pH-sensing capability of EAB sensors that is independent of the specific target analyte of the aptamer sequence. We applied this dual-purpose EAB to the continuous measurement of pH and phenylalanine in several in vitro cell culture settings. The miniature EAB sensor that we developed exhibits rapid response times, good stability, high repeatability, and biologically relevant sensitivity. We also developed and characterized a leak-free reference electrode that mitigates the potential cytotoxic effects of silver ions released from conventional reference electrodes. Using the resulting dual-purpose sensor, we performed hourly measurements of pH and phenylalanine concentrations in the medium superfusing cultured epithelial tumor cell lines (A549, MDA-MB-23) and a human fibroblast cell line (MRC-5) for periods of up to 72 h. Our scalable technology may be multiplexed for high-throughput monitoring of pH and multiple analytes in support of the broad metabolic qualification of microphysiological systems.

Enantioselective Molecular Detection by Surface Enhanced Raman Scattering at Chiral Gold Helicoids on Grating Surfaces.

Distinct advantages of surface enhanced Raman scattering (SERS) in molecular detection can benefit the enantioselective discrimination of specific molecular configurations. However, many of the recent methods still lack versatility and require customized anchors to chemically interact with the studied analyte. In this work, we propose the utilization of helicoid-shaped chiral gold nanoparticles arranged in an ordered array on a gold grating surface for enantioselective SERS recognition. This arrangement ensured a homogeneous distribution of chiral plasmonic hot spots and facilitated the enhancement of the SERS response of targeted analytes through plasmon coupling between gold helicoid multimers (formed in the grating valleys) and adjacent regions of the gold grating. Naproxen enantiomers (R(+) and S(-)) were employed as model compounds, revealing a clear dependence of their SERS response on the chirality of the gold helicoids. Additionally, propranolol and penicillamine enantiomers were used to validate the universality of the proposed approach. Finally, numerical simulations were conducted to elucidate the roles of intensified local electric field and optical helicity density on the SERS signal intensity and on the chirality of the nanoparticles and enantiomers. Unlike previously reported methods, our approach relies on the excitation of a chiral plasmonic near-field and its interaction with the chiral environment of analyte molecules, obviating the need for the enantioselective entrapment of targeted molecules. Moreover, our method is not limited to specific analyte classes and can be applied to a broad range of chiral molecules.

Modulation of triplet quantum coherence by guest-induced structural changes in a flexible metal-organic framework

Quantum sensing has the potential to improve the sensitivity of chemical sensing by exploiting the characteristics of qubits, which are sensitive to the external environment. Modulation of quantum coherence by target analytes can be a useful tool for quantum sensing. Using molecular qubits is expected to provide excellent sensitivity due to the proximity of the sensor to the target analyte. However, many molecular qubits are used at cryogenic temperatures, and how to make molecular qubits respond to specific analytes remains unclear. Here, we propose a material design in which the coherence time changes in response to a variety of analytes at room temperature. We used the photoexcited triplet, which can be initialized at room temperature, as qubits and introduce them to a metal–organic framework that can flexibly change its pore structure in response to guest adsorption. By changing the local molecular density around the triplet qubits by adsorption of a specific analyte, the mobility of the triplet qubit can be changed, and the coherence time can be made responsive.

Advancements in optical biosensing techniques: From fundamentals to future prospects

Optical biosensors that consist of a light source, optical elements, and a photodetector are used to detect chemical and biological species and pollutants. This Tutorial discusses the fundamental details of optical biosensing techniques that include materials, working principle, components, sensor configurations, parameters, and future prospects. Optical biosensing techniques include plasmonic [surface plasmon resonance (SPR) and localized SPR], fluorescence, luminescence, Raman scattering, colorimetric, and interferometric methods. Bioreceptor elements play a significant role in detecting the specific analyte that can be synthetic or natural. Surface functionalization techniques to bind the bioreceptor elements on the surface, to control the bioreceptor orientation, have been discussed in detail. The possibility of integration of techniques on a chip, to develop wearable, implantable sensors, and the associated challenges have been fully demonstrated. This Tutorial provides valuable insights into the present state and future directions of optical biosensors for various applications.

Biotin-Modified PEGylated Protein-Stabilized gold Nanoclusters: A strategy for selective and efficient intracellular transport of glucose oxidase for glucose detection

Although bovine serum albumin-stabilized gold nanoclusters (BSA-AuNCs) have various applications in biological environments., limited research has been carried out on their potential for intracellular delivery of enzymes and highly selective intracellular detection of specific analytes. We developed biotin-capped polyethylene glycol (PEG)-functionalized bovine serum albumin-stabilized gold nanoclusters (biotin-AuNCs) for enhanced optical properties and bioimaging applications. Biotin-AuNCs exhibited superior performance to BSA-AuNCs, with higher quantum yield (∼14 %), improved photostability, and enhanced resistance to trypsin digestion. These nanoclusters enabled selective imaging of biotin receptor-positive cells such as HeLa and MCF-7, while forming nanocomposites (GOx-AuNCs) with avidin-glucose oxidase (GOx) for intracellular glucose detection. The GOx-AuNCs showed selective imaging capabilities and facilitated glucose sensing through GOx-catalyzed H2O2 production, leading to fluorescence quenching of the biotin-AuNCs. This method provided a reliable indicator for intracellular glucose levels, establishing a linear calibration curve between GOx-AuNC-labeled cells’ luminescence intensity and intracellular glucose concentration. Additionally, we developed dual-emission probes by modifying red-emitting GOx-AuNCs with green-emitting BDP-FL for ratiometric imaging of intracellular glucose concentration, enhancing glucose sensing precision in biological environments.