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A coumarin-based fluorescent ligand, 4-hydroxy-2-oxo-2H-chromene-3-carbaldehyde (HCC), was synthesized and evaluated for the selective detection of tryptophan (Trp) among the nine essential amino acids. The probe exhibited remarkable selectivity toward Trp through an excited-state intramolecular proton transfer (ESIPT) mechanism facilitated by intramolecular hydrogen transfer. Upon interaction with Trp, HCC forms an HCC-Trp complex (HCP), which undergoes a transient tautomeric transformation between enol (E) and keto (K) forms via an excited-state intramolecular proton transfer (ESIPT) process. This results in an approximately 11-fold enhancement in fluorescence intensity at 385 nm, accompanied by a bathochromic shift in both the absorption and emission spectra. The probe HCC exhibited a low detection limit of 1.53 μM and a binding constant of 1.6 × 10⁴ M^-1 towards Trp. The sensing behaviour and binding mechanism were systematically confirmed using UV-Vis and fluorescence spectroscopy, ¹H NMR, mass spectrometry, Job's plot analysis, and density functional theory (DFT) calculations. Additionally, HCC exhibited notable binding affinity toward biomacromolecules such as calf thymus DNA (ct-DNA), bovine serum albumin (BSA), and pig liver esterase (PLE), supported by spectroscopic studies and molecular docking analysis. The binding constant for ct-DNA, BSA and PLE was found to be 5.7 × 10⁴ M^-1, 5.6 × 10⁴ M^-1 and 1.19 × 10⁵ M^-1, respectively. Fluorescence imaging experiments further confirmed the applicability of HCC for detecting Trp in biological samples along with in vitro anticancer studies. Thus, this study demonstrates that a simple coumarin-based small-molecule probe can selectively recognize tryptophan through an ESIPT-driven mechanism. The probe HCC exhibits high sensitivity, strong binding affinity, and compatibility with biological systems, enabling fluorescence-based detection and imaging of Trp. The findings highlight the potential of HCC as a multifunctional probe for biochemical sensing and provide a promising platform for developing small-molecule fluorophores for amino acid recognition.

The prolonged or excessive use of berberine (Ber) can induce drug resistance and adverse reactions, necessitating the development of simple, sensitive, and rapid on-site detection methods. In contrast to conventional sequence truncation, we rationally extended the stem region of the aptamer to elevate its melting temperature, complemented by loop-region base mutagenesis. The obtained aptamer (BBRE7M9) exhibits substantially enhanced thermal stability, which is 6 °C and 10 °C higher than those of BBR38S-3A10C and BBR4S3, respectively. Its dissociation equilibrium constant remained stable at 1.42-1.86 μM across 22-40 °C. Circular dichroism, molecular docking, site-directed mutagenesis, and displacement assays collectively indicated that Ber binds within a hydrophobic minor groove constituted by C8, A9, T10, T17, and T18. This confined microenvironment restricts intramolecular motions and suppresses non-radiative transitions, triggering a fluorescence turn-on response. Upon integration with a smartphone-based portable dark-box platform, the sensor exhibited a linear response over 0-800 nM with a detection limit of 53.9 nM and satisfactory selectivity. This stem-elongation approach demonstrates a practical route to enhancing aptamer thermal stability, and the mechanistic elucidation of the key binding sites provides a structural basis for designing berberine-aptamer-based turn-on fluorescent probes. More broadly, this strategy may also serve as a reference for optimizing other aptamer sensors that suffer from similar temperature-induced signal attenuation.

Transmission X-ray microscopy combined with X-ray absorption near-edge structure (TXM-XANES) spectroscopy enables nanoscale chemical state imaging of transition metal oxides, yet the low signal-to-noise ratio (SNR) of single-pixel spectra undermines the reliability of conventional edge-energy (E₀) quantification. Herein, we present an analytical framework based on white-line peak fitting that integrates skewed Gaussian fitting for precise peak extraction, area normalization for spectral standardization, and average spectrum analysis for chemical state referencing. Compared with the E₀ method, our approach reduces the full width at half maximum (FWHM) of the energy distribution to one-third (0.28 eV versus 0.83 eV) and achieves an average coefficient of determination (R²) of 0.997 across the entire particle, confirming superior accuracy under low-SNR conditions. Using a high-nickel Ni90 cathode as a model system, we establish a linear correlation between white-line peak energy and cell voltage. In battery cycling, 45 nm chemical-state mapping reveals interparticle reaction heterogeneity, improved uniformity after the first activation cycle, and a non-radial reaction pattern with spatially random heterogeneity originating from intragranular defects rather than Li⁺ diffusion limitations. These observations are consistent with a kinetically trapped state model in which some regions remain inactive during the first charge, gradually overcome the activation barrier, and homogenize, though the activation is not fully reversible. This strategy enhances the quantitative fidelity and throughput of nanoscale chemical-state imaging and offers an efficient analytical route for operando studies of battery materials and heterogeneous systems.

Surface-enhanced Raman scattering (SERS) enables real-time analysis of volatile organic compounds (VOCs) and other gaseous molecules using portable Raman devices, offering faster measurements compared to GC-MS. To facilitate this, numerous solid SERS substrates have been developed and applied across multiple fields. However, they often require complex fabrication due to poor adsorption of gases onto solid surfaces leading to high production costs and inconsistencies in sensitivity and reproducibility. In contrast, colloidal nanoparticles are less expensive to produce and established facile synthesis methods help their broader implementation. In this study a simple approach has been conceptualised whereby gaseous analytes are bubbled directly into colloidal nanoparticles. This was achieved by pumping air into a flask containing the volatile analyte, which in turn was bubbled into a vial containing colloidal nanoparticles and measured with a portable Raman spectrometer. Initially, 3-mercapto-hexanol (3MH) was successfully measured using this method. 3MH was chosen due to the method originally being developed to measure thiols associated to underarm odour. Subsequently, 3MH was used to optimize the air flow rate by testing at eight different flow rates. The results demonstrated that flow rate influenced the timing of analyte spectral appearance as seen by the rate of change in peak height at 634 cm^-1 for 3MH, with the most reproducible results observed at 50 mL min^-1. The technique was further evaluated with two other analytes: 2-methyl-3-mercapto-pentanol (2M3MP) and indole. The latter needed the addition of an aggregating agent (NaCl) to the nanoparticles. These findings indicate that this approach offers a promising alternative for detecting gaseous analytes using colloidal nanoparticles.

The relentless pursuit of rapid, ultrasensitive, and real-time analytical tools has positioned evanescent wave-based biosensors at the forefront of modern diagnostics. These platforms, which exploit the surface-confined electromagnetic field generated during total internal reflection, enable label-free, highly sensitive detection of biomolecular interactions. This review critically examines the recent advances in evanescent-wave-based analytical approaches for nanobiosensing, providing a comprehensive overview of the current research landscape and future perspectives. We delve into the predominant analytical platforms, including Surface Plasmon Resonance (SPR), Localized Surface Plasmon Resonance (LSPR), and various optical waveguide and fiber-optic configurations. A central focus is placed on the synergistic integration of nanomaterials, such as metallic nanoparticles, graphene and other 2D materials, and quantum dots, to enhance analytical performance through signal amplification and novel surface functionalities. Furthermore, we highlight current trends shaping the field's trajectory, including convergence with microfluidics to create Lab-on-a-Chip (LOC) systems for point-of-care (POC) applications, the deployment of machine learning for advanced data interpretation, and the development of portable, smartphone-integrated readers. Finally, the review addresses the persistent analytical challenges, including matrix effects, nonspecific binding, and manufacturing scalability, and provides a forward-looking perspective on the emerging materials and technologies poised to overcome these hurdles and redefine the future of bioanalytical science.

As insulin is the core regulatory hormone maintaining blood glucose stability, its abnormal secretion is often associated with diseases such as diabetes. In order to break away from the dependence on the traditional insulin detection technology involving expensive instruments and complex operations, we present a cucurbit[7]uril (CB[7])/gold nanoparticle (AuNP) self-assembly mediated chemiluminescence resonance energy transfer immunoassay (CRETIA) for insulin detection. The AuNP@CB[7] self-assembly serves two critical roles: the biorecognition element for capturing insulin from complex samples via host-guest interaction and the catalyst for the chemiluminescent reaction due to the enzyme-like activity of AuNPs. Upon introducing the energy acceptor antibody (Ab)-graphene oxide (GO) nanosheets, the presence of insulin leads to the formation of AuNP@CB[7]/insulin/Ab-GO nanosheet complexes, in which the AuNP and GO nanosheets are in close proximity, resulting in significant quenching of the chemiluminescence signal. Under optimized conditions, a satisfactory linear relationship was obtained in the range of 10-5000 pg mL^-1, with a limit of detection (LOD) of 2.51 pg mL^-1. The proposed CRETIA involves no use of natural enzyme or tedious washing and separation steps, thereby providing a robust tool for rapid detection of insulin.