Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy最新文献

Molecules exhibiting aggregation-induced emission (AIE) characteristics have gained prominence fluorescence in aggregated state, offering distinct advantages compared to traditional fluorogenic probes. This study proposes a hydrazine modified tetrastyrene derivative (Q) with AIE enhancement effect, which is used for high selectivity and ultrasensitive recognition of Fe³⁺ and Cu²⁺ by constructing a new metal coordination supramolecular complex (Q-Fe/Cu). Quantitative analysis revealed detection limits (LODs) of 6.35 × 10^-9 M (Fe³⁺) and 4.37 × 10^-9 M (Cu²⁺). Significantly, the coordinated complex Q-Cu (formed through Cu²⁺ incorporation) achieved high sensitive CN^- quantification with a LOD of 6.89 × 10^-8 M. Meanwhile, Q-based test strips can serve as convenient and efficient reagent kits for detecting Fe³⁺ and Cu²⁺, while Q-Cu based test strips can detect CN^- in water. This supramolecular design strategy establishes a novel paradigm for sample ultrasensitive recognition through programmable coordination-driven assembly.

The creation of fluorescent probes with exceptional brightness holds the key to unlocking sensitive, reproducible, and reliable performance of fluorometry. Other than synthetizing novel fluorescent probes, enhancing the functionality of well-established, mass-produced existing probes is also very meaningful although thousands of organic small molecule fluorescent probes have been synthesized in recent years. Here, we demonstrate an unexpected and significant enhancement of brightness of Alizarin Red S (ARS)/PyB(OH)₂ (A/P) complexes, which we reported recently by coordination induced assembly with Al³⁺. A novel fluorescence turn-on method for Al³⁺ detection was developed based on the significant emission change. The introduction of Al³⁺ to the formed A/P/Al³⁺ ensembles make them highly suitable for constructing sensitive fluorescence methods because Al³⁺ provides recognition sites. The observed performance was rationalized through theoretical calculations, including HOMO-LUMO gaps and configuration changes. Thus, a highly sensitive sensing system for PPi and ALP was proposed. Unlike other Cu²⁺ or Cd²⁺ based ALP on-off assay, the proposed Al³⁺ based ALP assay allows off-on readout. In addition, the practicality of the proposed sensing system has been validated by detecting ALP in complex fetal bovine serum. The strategy can also be extended to enhance the brightness of other existing fluorescent probes, and related work is currently underway in our laboratory.

Surface-Enhanced Raman Spectroscopy (SERS) has long been a recognized method for the rapid and sensitive detection of low concentrations of analytes. Nevertheless, challenges still exist in the fabrication of practical, effective SERS substrates and the interpretation of complex SERS spectra. In this study, a machine learning (ML)-assisted SERS platform that is both scalable and practical is proposed. The SERS substrate, composed of silver nanoparticle-decorated nanofibers (AgNFs), was obtained by integrating nanoparticle-free reactive silver (Ag) ink into a nanofiber matrix containing polyvinylpyrrolidone (PVP) and poly (ethylene oxide) (PEO). The nanofibers served both as a mechanical scaffold and a nano-scale template, guiding the formation of homogeneously distributed Ag nanostructures throughout the substrate. This synergistic fiber-assisted growth produced a highly SERS-active substrate, resulting in an analytical enhancement factor (AEF) of 2.9 × 10⁷. This platform enabled detection of phenylalanine, proline, valine, alanine, and cysteine amino acids at concentrations as low as 0.3 μM. The results demonstrated a direct correlation between the analyte concentration and the SERS signal intensity, as evidenced by determination coefficients (R²) that exceeded 0.9. Furthermore, the spectral data were subjected to analysis using ML algorithms, thereby allowing for the classification of amino acids. The linear support vector machine (SVM) algorithm exhibited superior classification performance, with an accuracy rate of approximately 98%. The findings demonstrate the efficacy of the developed ML-enhanced SERS platform for detecting various analytes, as well as its advantageous properties of simplicity, scalability, reproducibility, and ultra-sensitive structure.

Microcystin-LR (MC-LR) could be largely released in water environment during the cyanobacterial blooms, endangering the health of plants, animals, and even humans. Numerous evidences had demonstrated a strong correlation between the toxicities of MC-LR and the oxidative stress induced by MC-LR. Hydrogen peroxide (H₂O₂) is one of the primary constituents of reactive oxygen species (ROS) and tends to be overproduced under oxidative stress. Therefore, detecting the changes in H₂O₂ levels in organisms exposed to MC-LR can serve as an indicator of MC-LR-induced oxidative damage. However, the studies of directly detecting H₂O₂ levels in organisms exposed to MC-LR are lacking. In this work, we developed a novel near-infrared probe, DSP-B, to detect H₂O₂ under MC-LR-induced oxidative stress in organisms. DSP-B exhibited high sensitivity and specificity to H₂O₂, and the detection ability of DSP-B to endogenous and exogenous H₂O₂ has also been validated. Then DSP-B was applied to detect the H₂O₂ level in cells and zebrafishes treated with MC-LR to elucidate the effect of oxidative stress caused by MC-LR. Moreover, DSP-B was utilized for tissue visualization imaging in MC-LR-poisoned loaches model, enabling the upregulation of H₂O₂ to be successfully observed. This study offers a novel strategy for analyzing the MC-LR-induced oxidative stress and demonstrates the potential of using probe for MC-LR toxicity research. This probe is expected to provide assistances in evaluating the risks and hazards of MC-LR exposure to organisms in the environment.

Paraquat (PQ) is the herbicide that has been proven to be harmful to humans and poses significant risks. Rapid and accurate determination of PQ in clinical practice would aid in the correct diagnosis and timely treatment of patients with PQ poisoning. This study aims to utilize surface-enhanced Raman spectroscopy (SERS) for the rapid and accurate detection of PQ in human plasma. Ag nanoparticles modified metal-organic framework (Ag-MOF) was prepared by sodium citrate reduction method as SERS substrate. The octahedral NH₂-MIL-88B(Fe) was selected as the MOF matrix due to its porous structure and excellent adsorption capacity, which enabled the adsorbed PQ to be brought closer to the "hot spots" generated by the local surface plasmon resonance (LSPR) of Ag. Consequently, the Ag-MOF exhibited good PQ detection performance, with limits of detection (LOD) as low as 3.36 × 10^-9 M (0.86 μg/L) and 4.98 × 10^-9 M (1.28 μg/L) for aqueous solutions and human plasma samples, respectively. Furthermore, the prepared Ag-MOF SERS substrate demonstrated good selectivity, reproducibility, and stability, providing a simple, rapid, and sensitive method for detecting PQ in human plasma. It is expected to be applied in clinical PQ detection.

Charge recombination, which causes photocurrent loss, is a critical factor limiting the performance of dye-sensitized solar cells (DSSCs). Introducing alkyl or alkoxy chains into molecular structures has been established as an effective strategy to mitigate this process. Therefore, this study systematically investigated the influence of alkoxy groups in triphenylamine (TPA) and alkyl/alkoxy phenyl groups in phenothiazine (PTZ) on DSSC performance using density functional theory (DFT). The photophysical and electrochemical properties of four molecules, TP-C₆, TP-PhOC₆, C₆O-TP-C₆, and C₆O-TP-PhOC₆, were computationally analyzed. Results show that the alkoxy phenyl groups in PTZ and the absence of alkoxy groups in TPA within TP-PhOC₆ enhance molecular planarity, induce redshifted absorption spectra, and improve charge transfer performance. Adsorption simulations further reveal that dye@TiO₂ system exhibits a reduced bandgap and redshifted absorption, thereby enhancing spectral response and facilitating electron injection. Moreover, the application of an external electric field is shown to significantly improve electron transfer, optical properties, and interfacial electron injection at the dye/TiO₂ interface. Photoelectric performance predictions confirm that TP-PhOC₆ achieves the highest power conversion efficiency (PCE) of 6.509%, attributed to its high short-circuit current density (J_sc = 11.96 mA cm^-2) and open-circuit voltage (V_oc = 0.650 V). In the molecular design, TPA was substituted with carbazole in the donor unit, and the benzene ring in the π bridge was replaced by thiophene. The thiophene substitution was found to broaden the light absorption range and enhance light-harvesting efficiency, resulting in a higher J_sc. Consequently, the designed molecule exhibits superior PCE compared to the experimental molecules. Theoretical simulations further validate the feasibility of developing high-performance DSSCs.

Melanoma remains one of the most aggressive and lethal cutaneous malignancies, underscoring the need for objective and label-free diagnostic methods that complement traditional histopathology. In this study, Laser-Induced Breakdown Spectroscopy (LIBS) and Raman spectroscopy were jointly applied to characterize formalin-fixed paraffin-embedded (FFPE) melanoma and normal human tissues, and the resulting spectra were modeled using an Extreme Learning Machine (ELM) under five activation functions. Model interpretability was achieved through SHapley Additive exPlanations (SHAP) analysis. Among the tested activation functions, the average test accuracies were achieved by sine for LIBS (92.43%) and sigmoid for Raman (74.41%) under stratified spectrum-wise cross-validation, while feature-level fusion achieved 77.88% average test accuracy with sigmoid. SHAP analysis revealed that K (∼766/769 nm) and Ca (∼422 nm) emission lines in LIBS and ∼ 3164 and ∼ 1163 cm^-1 bands in Raman were the dominant discriminative features, corresponding to ionic imbalance, calcium signaling dysregulation, as well as protein conformational changes (amide A/N-H stretching) and protein-lipid-associated C-C/C-N vibrational alterations characteristic of melanoma progression. These results establish a coherent and interpretable framework linking spectral signatures to biochemical mechanisms and demonstrate the potential of compact, multimodal, and mechanism-driven optical diagnostics for precise, transparent cancer assessment.

Heparin is a highly sulfated linear glycosaminoglycan with anticoagulant properties, and its excessive use may lead to many diseases. Therefore, developing sensitive detection techniques for precise detection of heparin is of utmost importance. Herein, we reported a novel peptide-based fluorescent probe (TPE-GRGRG) based on tetraphenylethylene (TPE)-labeled pentapeptide (Gly-Arg-Gly-Arg-Gly-NH₂) for the highly selective and outstanding sensitive detection of heparin. TPE-GRGRG exhibited a large Stokes shift (132 nm) and typical aggregation-induced emission (AIE) characteristics in DMSO/H₂O binary mixtures. TPE-GRGRG demonstrated a significant enhancement of fluorescence intensity in the presence of heparin with a response time of under 30 s and the limit of detection (LOD) as low as 0.30 nM. A series of characterizations revealed that TPE-GRGRG and heparin formed nanoaggregates via electrostatic interactions, including fluorescence spectroscopy, UV-Vis, FTIR, CD, zeta potential, DLS measurements and fluorescence lifetime analyses, which in turn restricted the intramolecular rotation and triggered the fluorescence enhancement. TPE-GRGRG enabled heparin detection over a wide pH range and exhibited good biocompatibility, and was successfully applied to image heparin in living cells and zebrafish larvae. Furthermore, this study established detection platforms based on swab tests for visual qualitative analysis and smartphone RGB analysis, thereby achieving portable and visual heparin monitoring with the LOD of 0.93 μM. Finally, heparin detection was achieved in 0.1% fetal bovine serum with the LOD of 1.46 nM. TPE-GRGRG offers a reliable strategy for point-of-care testing of heparin, holding potential application value in clinical diagnosis and biosensing.

Parkinson's disease (PD) diagnosis faces substantial challenges due to the lack of reliable biomarkers and the limitations of existing detection techniques. Exosomes, which carry biomolecular cargo reflective of disease pathology, are increasingly recognized as promising biomarkers because of their stable presence in biofluids and accessibility through minimally invasive methods. Surface-enhanced Raman spectroscopy (SERS) provides high sensitivity and rapid molecular fingerprinting, but its clinical translation is hindered by spectral variability and sample heterogeneity. To address these limitations, we developed a novel diagnostic approach by integrating serum exosome SERS with support vector machine (SVM) classification. Systematic evaluation of 27 distinct data preprocessing strategies confirmed that data preprocessing critically influences classification performance, and the optimized model successfully differentiated PD patients from normal controls (NC), achieving an accuracy of 0.85 (95% confidence interval [CI], 0.75-1.00) and an area under the receiver operating characteristic curve (AUC) of 0.85 (95% CI, 0.67-1.00), which was statistically significant as validated by permutation testing (p < 0.05). Comparative analysis with the diagnostic criteria of the Movement Disorder Society (MDS) demonstrated that our model outperforms several conventional MDS methods. Furthermore, this study revealed that the "coffee-ring" effect, which introduces sample heterogeneity during SERS measurements, substantially compromised reproducibility and predictive accuracy. Several post-processing strategies were implemented to mitigate the coffee-ring effect, and notably, one of these strategies achieved results comparable to those of the optimal model (AUC = 0.85, accuracy = 0.85). This demonstrates that such post-processing approaches can effectively suppress the influence of the "coffee-ring" effect. In addition, linear SVM feature importance mapping identified potential exosomal biomarkers, including proteins (S-S stretching, tryptophan), nucleic acids (adenine vibrations, CH₃/CH₂ twisting), lipids, and saccharides. Collectively, these findings highlight a promising strategy for clinical PD diagnosis by combining exosome-based SERS and machine learning, with biomarker identification and heterogeneity analysis further advancing diagnostic reliability and paving the way for practical clinical translation.

The extraction of mycotoxins from complex food matrices for immunoassay often requires organic solvents, which can compromise antibody integrity and detection sensitivity. This study aimed to investigate the tolerance patterns of an ochratoxin a (OTA)-specific nanobody in organic solvents, elucidating the relationship between its structural stability and functional activity. Direct competitive enzyme-linked immunosorbent assay, fluorescence spectroscopy, ultraviolet-visible absorption spectroscopy, Fourier transform infrared spectroscopy, and molecular docking were employed to systematically analyze the tolerance thresholds, antibody activity retention rates, and structural changes of the OTA nanobody in eight organic solvents.The results showed that the OTA nanobody exhibited higher tolerance in methanol, ethylene glycol, glycerol, acetone and dimethyl sulfoxide (thresholds of 40%-60%), while lower tolerance was observed in acetonitrile and dimethylformamide (thresholds of 20% and 10%, respectively). Results of antibody activity retention rate and spectral analysis showed that methanol induced minimal structural and functional damage to OTA nanobodies; acetone severely impaired the nanobodies' structure and activity with significant destruction of their core domain; acetonitrile might affect antibody activity and tolerance via a non-structural mechanism; dimethylformamide exerted a drastic conformational impact, leading to complete structural disorder, acute activity loss, and the poorest tolerance. Molecular docking results indicated that organic solvents primarily interacted with framework residues via hydrogen bonds, without occupying the core antigen-binding region. This study elucidates the tolerance mechanism of the OTA nanobody in organic solvents, providing a theoretical basis for its application in complex sample detection and the design of solvent-resistant mutants.