Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy最新文献

{"title":"STIS: A novel approach for standardization of spectrometric instruments in fungal Raman spectroscopy","authors":"Hailong Feng,&nbsp;Mingyue Huang,&nbsp;Jing Liang,&nbsp;Xiaoxuan Xu,&nbsp;Bin Wang,&nbsp;Jing Xu","doi":"10.1016/j.saa.2026.127494","DOIUrl":"10.1016/j.saa.2026.127494","url":null,"abstract":"<div><div>More than 1.5 million annual deaths from invasive fungal infections underscore the demand for rapid and accurate diagnostics. Although single-cell Raman spectroscopy is a sensitive and label-free technique, its clinical translation is hindered by spectral inconsistencies between instruments. This work introduces a spectral transformer for instrument standardization (STIS), which replaces the localized linear approximations of traditional DS and PDS with a global self-attention mechanism. By encoding spectral position via embeddings and modeling full-range dependencies, STIS captures complex instrumental deviations without overfitting. Evaluated on Raman spectra from 47 clinical fungal strains, STIS markedly surpasses existing methods, raising the average correlation to 0.9897 and reducing the transfer error to 5.13%. Notably, consistent cross-device alignment is attained using only 10 standardization samples. With STIS calibration, slave instrument spectra achieve recognition accuracies of 95.74% (SVM) and 97.87% (CNN) on a held-out test set—An improvement exceeding 30% over uncalibrated data and clearly outperforming DS and PDS</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"351 ","pages":"Article 127494"},"PeriodicalIF":4.6,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146035684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced spectral modeling for bacterial strains: A MARS–PLS2 approach with Lasso regularization and baseline optimization","authors":"Sughra Sarwar,&nbsp;Tahir Mehmood,&nbsp;Mudassir Iqbal","doi":"10.1016/j.saa.2026.127506","DOIUrl":"10.1016/j.saa.2026.127506","url":null,"abstract":"<div><div>The natural characteristics of the infrared spectroscopic data are that it tends to distort the baseline, there is high-dimensionality and non-linear correlation that hinder reliable prediction of biochemical properties. To overcome these obstacles, this study introduces an integrated MARS–PLS2–Lasso framework that incorporates the effective baseline correction, non-linear regression, latent variable extraction, and sparse variable selection to promote the chemometric modeling accuracy and interpretability. Out of four baseline correction methods, viz. Asymmetric Least Squares (ALS), AirPLS, Polynomial fitting, and Wavelet baseline correction, the Wavelet method (sym8, Level 5) was found to be the most successful, in that it was able to represent local spectral variation with low-frequency noise. This technique achieved high predictive accuracy with RMSE = 0.2846–0.6857, MAE = 0.2371–0.5445 and MSE = 0.0810–0.4705 specifying both high model fit and minimal residual error across bacterial spectra. The Wavelet-corrected spectra revealed six key functional regions that contributed most significantly to bacterial differentiation: 720<!--> <!-->cm⁻¹ to 750<!--> <!-->cm⁻¹ (C–Cl stretching, C<img>H bending), 1000<!--> <!-->cm⁻¹ to 1300<!--> <!-->cm⁻¹ (C–O stretching, esters, carboxylic acids), 1500<!--> <!-->cm⁻¹ to 1650<!--> <!-->cm⁻¹ (C<img>C stretching), 1687<!--> <!-->cm⁻¹ to 1793<!--> <!-->cm⁻¹ (C<img>O stretching, conjugated carbonyls), 2771<!--> <!-->cm⁻¹ to 3143<!--> <!-->cm⁻¹ (C<img>H stretching, alkanes, alkenes), 3290<!--> <!-->cm⁻¹ to 3595<!--> <!-->cm⁻¹ (O–H and N<img>H stretching ). Vibrational domains of interest are biochemical components of lipids, proteins, amides and polysaccharides that determine the structural integrity and metabolic activity of bacteria. The proposed MARS–PLS2–Lasso model leverages Multivariate Adaptive Regression Splines (MARS) to capture nonlinear relationships through adaptive basis functions, while Partial Least Squares (PLS2) extracts latent components that maximize covariance between spectral predictors and multiple bacterial responses. Lasso regularization adds sparsity to the model and reduces the complexity of the model, as well as penalizes less interesting basis functions, which overfit the model. Such a combination is used to provide a reasonable approximation of the parameter even in high-dimensional spectral data. In general, MARS–PLS2–Lasso provides a sound, interpretable, and chemically consistent way of high dimensional infrared spectral modeling. It is highly predictive, less noisy and has a more adequate manner of interpreting spectral–biochemical interactions, and thus, a bright way of bacteria modeling, spectral diagnostics and further use in bio-analytical spectroscopy.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"351 ","pages":"Article 127506"},"PeriodicalIF":4.6,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146036096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Construction of BSA-CuNCs@UiO-66 nanoprobe based on MOF confinement effect and its ultrasensitive fluorescence sensing for creatinine","authors":"Lian-Lian Duan ,&nbsp;Wen-Jun Liu ,&nbsp;Rui Zhai ,&nbsp;Zhen-Guang Wang ,&nbsp;Hong-Yuan Yan ,&nbsp;Yun-Kai Lv PhD (Leading)","doi":"10.1016/j.saa.2026.127515","DOIUrl":"10.1016/j.saa.2026.127515","url":null,"abstract":"<div><div>This study employed a pore-confined synthesis strategy to achieve the in situ growth of bovine serum albumin-capped copper nanoclusters (BSA-CuNCs) within the UiO-66 framework (BSA-CuNCs@UiO-66). This nanocomposite enables highly sensitive and specific detection of creatinine (CR). Results demonstrated that the spatial confinement imposed by UiO-66 induced aggregation of the BSA-CuNCs and suppressed non-radiative transitions, leading to an approximately 10-fold enhancement in fluorescence intensity and a 11-fold increase in quantum yield. Leveraging the specific adsorption and enrichment capability of the UiO-66 framework toward CR, the BSA-CuNCs@UiO-66 fluorescence probe exhibited significant fluorescence quenching upon exposure to CR, achieving a detection range of 50–1000 nM and a detection limit of 30.81 nM. This work presented a novel confinement engineering strategy utilizing metal-organic frameworks (MOFs), establishing a new design paradigm for high-performance fluorescence probes with significant potential in bioanalytical applications.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"351 ","pages":"Article 127515"},"PeriodicalIF":4.6,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146055571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-wavelength emissive N-doped carbon dots as a fluorescent probe for sensitive detection of pyrophosphate and cellular imaging","authors":"Yingte Wang,&nbsp;Yijun Shen,&nbsp;Jiandang Xue,&nbsp;Lele Liu,&nbsp;Yawei Li","doi":"10.1016/j.saa.2026.127469","DOIUrl":"10.1016/j.saa.2026.127469","url":null,"abstract":"<div><div>Nitrogen-doped carbon dots (N-CDs) exhibiting long-wavelength fluorescence were successfully synthesized via a one-step hydrothermal method using neutral red and thiosemicarbazide as precursors, specifically to address limitations in pyrophosphate (P₂O₇⁴⁻, PPi) detection. As an essential adenosine triphosphate (ATP) hydrolysis byproduct and disease biomarker, PPi quantification remains challenged by costly instrumentation and complex procedures in conventional methods. The synthesized N-CDs demonstrated optimal excitation/emission at 520/600 nm with a quantum yield (QY) of 4.8%, enabling rapid (1 min response time), selective PPi detection through fluorescence quenching. Quantitative analysis revealed a linear detection range of 1.38–85.60 μmol/L (R² = 0.9983) and low detection limit of 0.42 μmol/L. Practical validation in milk samples yielded excellent recovery rates of 95.26–105.74% with ≤1.86% relative standard deviation, confirming reliability in complex matrices. Critically, the N-CDs' deep-tissue penetration capability facilitated real-time monitoring of intracellular PPi dynamics in HeLa cells, while maintaining high biocompatibility. This work establishes multi-element doped carbon dots as both a cost-effective analytical alternative and a versatile platform for biomedical imaging applications.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"351 ","pages":"Article 127469"},"PeriodicalIF":4.6,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146004691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An endoplasmic reticulum-targeting NIR fluorescent probe for viscosity imaging in vitro and vivo","authors":"Jian-Hua Tang ,&nbsp;Jing-Jing Yu ,&nbsp;Jun-Tao Niu ,&nbsp;Tong Han ,&nbsp;Jia-Le Cui ,&nbsp;Yi-Ran Di ,&nbsp;Ting Liang ,&nbsp;Yan-Fei Kang ,&nbsp;Hao-Jun Fan","doi":"10.1016/j.saa.2026.127471","DOIUrl":"10.1016/j.saa.2026.127471","url":null,"abstract":"<div><div>The endoplasmic reticulum <strong>(</strong>ER), a central organelle, play critical roles in protein synthesis, folding and detoxification. Viscosity within the ER lumen is recognized as an essential physical property for maintaining its normal functions, and its dysregulation has been associated with numerous diseases and aging processes. Thus, detecting change of viscosity was meaningful in ER. In this work, a near-infrared (NIR) fluorescent probe (<strong>BEQ-ER</strong>) with a classic D-π-A structure is designed to measure viscosity fluctuation in ER relying on twisted intramolecular charge transfer (TICT) mechanism. <strong>BEQ-ER</strong> exhibited strong fluorescence at 682 nm under conditions of high viscosity due to suppressed intramolecular rotation. Moreover, the image results showed <strong>BEQ-ER</strong> can precisely target ER with a colocalization coefficient of 0.964, and high viscosity was detected in cancer cells. Importantly, <strong>BEQ-ER</strong> was shown to selectively illuminate tumor tissues in 4 T1 tumor-bearing mice. Therefore, this work provided a valuable tool for investigating disease mechanisms and progression through real-time monitoring of ER viscosity.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"351 ","pages":"Article 127471"},"PeriodicalIF":4.6,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146032248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative and exploratory study of ATR and diffuse reflectance mid-infrared spectroscopy for coal property analysis","authors":"Yu Liu,&nbsp;Jing-Yan Li,&nbsp;Yu-Peng Xu,&nbsp;Pu Chen,&nbsp;Dan Liu,&nbsp;Xiao-Li Chu","doi":"10.1016/j.saa.2026.127467","DOIUrl":"10.1016/j.saa.2026.127467","url":null,"abstract":"<div><div>To evaluate mid-infrared sampling geometries for rapid coal analysis, attenuated total reflectance (ATR) and diffuse reflectance FTIR (DRF) were systematically compared, and multimodal fusion was explored. A total of 200 coal samples were analyzed for six key quality indices: ash, calorific value, volatile matter, fixed carbon, moisture, and sulfur. During data preprocessing, extended multiplicative scatter correction (EMSC) was applied to improve spectral stability, followed by correlation-based wavelength selection and cross-validated optimization of latent variables to construct partial least squares (PLS) regression models for each property. Notably, this study establishes a unified and reproducible benchmarking framework to disentangle sampling-geometry effects (surface-sensitive ATR and bulk-sensitive DRF) under strictly identical preprocessing, variable-selection, and cross-validation rules, and interprets the observed performance differences via chemically meaningful spectral contribution. In addition, we systematically benchmark three fusion levels (low/mid/high) within the same framework to clarify when multimodal integration is beneficial and when it is not. DRF achieved the most accurate ash prediction, whereas ATR performed better for volatile matter and moisture; calorific value and fixed carbon were comparable. Sulfur prediction remained challenging for both modalities. Low- and mid-level fusion showed no consistent synergistic gain, while high-level fusion improved prediction for five properties. Overall, the study provides actionable guidance for selecting FTIR modality and fusion strategy for practical coal quality assessment.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"351 ","pages":"Article 127467"},"PeriodicalIF":4.6,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detection of residual microbial biomarkers in bacterial cellulose using laser-induced fluorescence spectroscopy","authors":"Petr Larionov ,&nbsp;Nikolay Maslov ,&nbsp;Natalia Pogorelova ,&nbsp;Ilya Rozhin ,&nbsp;Natalya Sarnitskaya ,&nbsp;Vyacheslav Stupak ,&nbsp;Irina Kirilova ,&nbsp;Andrey Korytkin ,&nbsp;Ilya Digel","doi":"10.1016/j.saa.2026.127475","DOIUrl":"10.1016/j.saa.2026.127475","url":null,"abstract":"<div><div>Bacterial cellulose (BC) is a promising biomaterial for medical and biotechnological applications. However, microbial contaminants and their metabolic residues remain a critical limitation for its clinical use. Many of the BC purity tests are labor-intensive and time-consuming. This study investigates the feasibility of using laser-induced fluorescence (LIF) spectroscopy for monitoring microbial contamination in BC.</div><div>BC samples were obtained from a <em>Medusomyces gisevii</em> consortium and subjected to various purification protocols (alkaline, detergent and oxidative treatments). LIF spectra were recorded across 220–290 nm excitation wavelengths and analyzed chemometrically. For better interpretation of the results, the same samples were examined by laser scanning confocal microscopy (LSM).</div><div>The results reveal that both native and treated BC samples exhibit fluorescence features associated with tryptophan and tyrosine, indicative of microbial residues. Treatment with NaOH effectively reduced tryptophan-associated signals, while hydrogen peroxide diminished tyrosine-related fluorescence. None of the purification strategies completely eliminated these signals. A good correlation between the LIF and the more labor-consuming LSM data was observed. LIF showed the capability of rapid and reliable differentiation between treatment variants and provided spectral fingerprints linked to residual contamination. Future work may focus on standardizing LIF-based diagnostic protocols and integrating them into biotechnological workflows for contamination monitoring.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"351 ","pages":"Article 127475"},"PeriodicalIF":4.6,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interpretable machine learning prediction of biochar characteristics based on laser-Raman spectroscopy","authors":"Xing Hu,&nbsp;Dezhi Chen,&nbsp;Shihao Zhou,&nbsp;Jun Xu,&nbsp;Kai Xu,&nbsp;Long Jiang,&nbsp;Yi Wang,&nbsp;Sheng Su,&nbsp;Song Hu,&nbsp;Jun Xiang","doi":"10.1016/j.saa.2026.127474","DOIUrl":"10.1016/j.saa.2026.127474","url":null,"abstract":"<div><div>The precise detection of biochar characteristics serves as a critical determinant in both production process optimization and targeted application selection. In this study, interpretable machine learning prediction models based on Raman spectroscopy, including extreme gradient boosting, support vector regression, feedforward neural network, random forest, and ridge regression, were developed for accurately predicting the characteristics of biochar derived from six different biomass, across a pyrolysis temperature range of 350–1000 °C. Results demonstrated that the feedforward neural network achieved superior overall predictive performance for key biochar characteristics (R² = 0.89–0.95), including fixed carbon, volatile, H, O, atomic ratio of H/C and O/C. Highly accurate prediction of ash (R² = 0.95) was achieved by integrating the results of multibasic prediction of volatile matter and fixed carbon and establishing a quantitative relationship with ash. A tripartite analytical framework was developed to improve model interpretability by integrating CARS for spectral feature selection, SHAP analysis to quantify feature importance, and mechanistic correlation analysis of model predictions linking selected bands to biochar structure. The robustness of the models was evaluated through tests on various enhanced datasets, confirming their resilience under different perturbations. This approach, combining Raman spectroscopy with machine learning, offers a rapid and reliable means for predicting biochar characteristics, facilitating more efficient control of biomass pyrolysis processes, and supporting the development of online monitoring techniques.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"351 ","pages":"Article 127474"},"PeriodicalIF":4.6,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146036099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Online monitoring of Chinese herbal medicine production process toward lean six sigma: multimodal data fusion based on transformer architecture","authors":"Mintong Zhao ,&nbsp;Zhilong Tang ,&nbsp;Mingyang Zhou ,&nbsp;Xiaohan Zhang ,&nbsp;Xinyu Wang ,&nbsp;Xingchu Gong","doi":"10.1016/j.saa.2026.127507","DOIUrl":"10.1016/j.saa.2026.127507","url":null,"abstract":"<div><div>The manufacturing of Chinese medicines often faces challenges such as poor product consistency, high solvent consumption, and long processing times. The percolation process is a commonly used technique for extracting medicinal herbs. Significant variation in percolate concentration and low concentration near the endpoint make it difficult for existing online detection technologies to accurately determine target component concentrations. To address this, the study developed an online monitoring system integrating multi-modal sensors for physical quantity, image, and spectral data. Using Xiaochaihu capsules, real-time multimodal data were collected, including over 20,000 physical quantity points, 14,000 spectra, and 14,000 images. A Transformer-based framework, PMFormer, was proposed, with interpolation-based data augmentation to alleviate the “data-rich but label-scarce” problem. PMFormer achieved R² values of 0.96, 0.94, and 0.91 for 6-gingerol, 8-gingerol, and adenine, with RMSEs below 2.4, 0.4, and 1.8 μg/mL, respectively. A quantitative extraction control strategy was developed, determining the percolation endpoint when the accumulated total mass of collection (ATMC) met quality control limits. Validation showed improved consistency, reduced solvent use, and enhanced efficiency, aligning with Lean Six Sigma concepts. This study provides a reference for online monitoring of TCM percolation processes and demonstrates the potential of multimodal data fusion in pharmaceutical manufacturing.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"351 ","pages":"Article 127507"},"PeriodicalIF":4.6,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146088592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A mitochondria-targeted “turn-on” near-infrared fluorescent probe for imaging protein Sulfenic acids in live cells under oxidative stress","authors":"Zhixuan Feng ,&nbsp;Wenjing Liu ,&nbsp;Xiaojie Zhang ,&nbsp;Ping Li ,&nbsp;Libo Du ,&nbsp;Yan Cui","doi":"10.1016/j.saa.2026.127460","DOIUrl":"10.1016/j.saa.2026.127460","url":null,"abstract":"<div><div>Protein sulfenic acids (PSA) are crucial reactive species in oxidative stress, yet their transient nature and the complex cellular environment demand detection tools with high selectivity, sensitivity, and organelle-targeting capability. To address this, we report a novel near-infrared (NIR) turn-on fluorescent probe, HCA-CHD. This probe is rationally constructed with a cationic hemicyanine (HCA) dye as the NIR fluorophore and a 1,3-cyclohexanedione (CHD) moiety as the specific reaction site for PSA. The reaction with PSA forms a thioether linkage, which triggers a significant fluorescence enhancement. HCA-CHD exhibits a maximum absorption at 640 nm and, upon reaction, shows a strong turn-on fluorescence emission at 710 nm. Comprehensive characterization confirms its excellent reactivity, high selectivity, good stability, and inherent mitochondria-targeting ability. We successfully demonstrate the application of HCA-CHD for the highly sensitive and selective imaging of endogenous PSA in the mitochondria of live HeLa and MCF-7 cells, thus providing a powerful tool for investigating redox biology.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"351 ","pages":"Article 127460"},"PeriodicalIF":4.6,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145957741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}