Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy最新文献_第2页

Label-free serum SERS combined with RFE-GBDT algorithm for non-invasive screening of liver cancer 无标签血清SERS联合RFE-GBDT算法无创筛查肝癌。

IF 4.6 2区化学 Q1 SPECTROSCOPY

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Pub Date : 2026-05-05 Epub Date: 2026-02-05 DOI: 10.1016/j.saa.2026.127552

Jingjing Gao , Tianyi Lv , Xianqiong Gong , Xingen Gao , Wei Qiao , Fuqiang Wang , Junzheng Wu , Juqiang Lin

Early diagnosis of liver cancer is crucial for developing clinical treatment strategies and improving patient survival rates. However, current diagnostic methods are often invasive, complex, and time-consuming, making them unsuitable for early screening in practical settings. Therefore, there is an urgent need to develop efficient and convenient non-invasive diagnostic techniques. This study presents a non-invasive optical diagnostic approach based on surface-enhanced Raman spectroscopy (SERS) and a deep learning algorithm for liver cancer staging identification and auxiliary screening. We systematically collected high-quality SERS spectral data from serum samples of patients with different stages of liver cancer (T1, T2, T3), hepatitis B (HBV), and healthy controls (Normal). Recursive feature elimination (RFE) was employed for feature selection, eliminating redundant spectral bands and retaining features highly relevant to classification, which significantly enhanced the model's discriminative ability. The selected features were input then into a gradient boosting decision tree (GBDT) model. Through residual iterative optimization, the model effectively captured nonlinear feature interactions, and key spectral bands were interpreted using the local interpretable model-agnostic explanations (LIME) algorithm. Compared to other commonly used classifiers such as logistic regression (LR) and random forest (RF), the RFE-GBDT model demonstrated superior performance in liver cancer staging tasks, achieving an accuracy of 92.68% in the five-class classification. The results indicate that the integration of SERS technology with the RFE-GBDT algorithm holds promise as an efficient and non-invasive auxiliary tool for the early diagnosis of liver cancer.

肝癌的早期诊断对于制定临床治疗策略和提高患者生存率至关重要。然而，目前的诊断方法往往是侵入性的、复杂的和耗时的，使得它们不适合在实际环境中进行早期筛查。因此，迫切需要开发高效、便捷的无创诊断技术。本研究提出了一种基于表面增强拉曼光谱（SERS）和深度学习算法的无创光学诊断方法，用于肝癌分期识别和辅助筛查。我们系统地收集了不同分期肝癌（T1、T2、T3）、乙型肝炎（HBV）和健康对照（Normal）患者血清样本的高质量SERS谱数据。采用递归特征消除（RFE）进行特征选择，剔除冗余的光谱波段，保留与分类高度相关的特征，显著增强了模型的判别能力。然后将选择的特征输入到梯度增强决策树（GBDT）模型中。通过残差迭代优化，模型有效捕获非线性特征相互作用，并采用局部可解释模型不可知解释（LIME）算法对关键光谱波段进行解释。与其他常用的分类器如logistic回归（LR）和随机森林（RF）相比，RFE-GBDT模型在肝癌分期任务中表现出优越的性能，在五类分类中达到92.68%的准确率。结果表明，SERS技术与RFE-GBDT算法的结合有望成为肝癌早期诊断的一种高效、无创的辅助工具。

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引用次数: 0

Ag nanoclusters as nanozyme for detection of Hg2+ based on aggregation enhanced peroxidase-like activity 基于聚合增强过氧化物酶样活性的Ag纳米团簇作为检测Hg2+的纳米酶。

IF 4.6 2区化学 Q1 SPECTROSCOPY

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Pub Date : 2026-05-05 Epub Date: 2026-02-05 DOI: 10.1016/j.saa.2026.127562

Cuifeng Jiang, Yong Zhu, Wanting Han

In this study, lysine protected silver nanoclusters (Lys-AgNCs) were prepared and the mimetic property was systematically investigated. The nanoclusters displayed oxidase-like and peroxidase-like activity for the catalytic oxidation of 3, 3′, 5, 5′-tetramethylbenzidine (TMB). Interestingly, the nanozyme property could be tuned by adjusting the pH or temperature. In the low pH (3.6–4.2), oxidase-like activity is predominant. In the high pH(4.2–5.4), peroxidase- like activity is the main activity. In the lower temperature (20–40 °C), oxidase-like activity is predominant. Importantly, the Lys-AgNCs showed stronger affinity for TMB. The activation energy of Lys-AgNCs was lower than bare Ag nanoclusters, indicating a faster reaction rate. In addition, a detection method for Hg²⁺ was designed based on the aggregation enhanced peroxidase-like activity of lysine-Ag nanocluster with limit of detection (LOD) of 0.004 μM. The sensing assay exhibited excellent selectivity owing to the specific interaction between lysine and Hg²⁺ and can be used in tap water with an acceptable recovery rate. Considering the cost-effective of this method, it is proposed to be used in practical application.

本研究制备了赖氨酸保护银纳米团簇（lys - agnc），并对其模拟性能进行了系统的研究。纳米团簇对3,3 ',5,5 '-四甲基联苯胺（TMB）具有类似氧化酶和过氧化物酶的催化氧化活性。有趣的是，纳米酶的性质可以通过调节pH值或温度来调节。在低pH（3.6-4.2）条件下，氧化酶样活性占优势。在高pH（4.2 ~ 5.4）条件下，过氧化物酶样活性为主要活性。在较低温度下（20-40℃），氧化酶样活性占优势。重要的是，Lys-AgNCs对TMB具有更强的亲和力。Lys-AgNCs的活化能低于裸Ag纳米团簇，反应速度更快。此外，设计了一种基于赖氨酸-银纳米簇聚集增强过氧化物酶样活性的Hg2+检测方法，检测限（LOD）为0.004 μM。由于赖氨酸与Hg2+的特异性相互作用，该检测方法具有良好的选择性，可用于自来水中，回收率可接受。考虑到该方法的成本效益，建议在实际应用中推广应用。

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引用次数: 0

Accurate classification of ependymomas and medulloblastomas using Raman spectroscopy and pilot transcriptomic profiling 利用拉曼光谱和中导转录组谱准确分类室管膜瘤和髓母细胞瘤。

IF 4.6 2区化学 Q1 SPECTROSCOPY

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Pub Date : 2026-05-05 Epub Date: 2026-01-28 DOI: 10.1016/j.saa.2026.127532

Yuki Kawamoto , Yoshiko Okita , Kenta Temma , Toshiki Kubo , Yasuaki Kumamoto , Yasuhiro Fujii , Keisuke Nishimoto , Reina Utsugi , Chisato Yokota , Ryuichi Hirayama , Noriyuki Kijima , Khoo Hui Ming , Naoki Tani , Satoru Oshino , Naoki Kagawa , Daisuke Motooka , Katsumasa Fujita , Haruhiko Kishima

Raman spectroscopy enabled accurate discrimination of posterior fossa ependymomas and medulloblastomas in both frozen and formalin-fixed, paraffin-embedded (FFPE) specimens in this retrospective study. We acquired Raman spectra (532 nm excitation) from frozen and FFPE tissues to evaluate a principal component analysis–support vector machine classifier by using fivefold cross-validation. We also performed a pilot spatial transcriptomics analysis on three FFPE sections by using the 10× Genomics Xenium In Situ v2 FFPE workflow. In total, 34 specimens (21 frozen and 13 FFPE) were analyzed, and the classification models achieved >90% accuracy in distinguishing ependymomas from medulloblastomas under spectrum-level fivefold cross-validation, suggesting discriminative biochemical differences, whereas patient-level performance requires further validation in larger cohorts. Ependymomas had higher lipid-associated Raman bands (1084, 1128, and 1654 cm⁻¹), whereas medulloblastomas exhibited higher deoxyhemoglobin-related Raman bands (1356, 1548, and 1604 cm⁻¹). Compared with normal controls, tumor tissues had increased carotenoid-related Raman bands and reduced lipid-associated Raman bands. The observed spectral differences are consistent with differences in lipid-associated composition and the heme/oxygenation-related tissue context, and pilot transcriptomic profiling provided qualitative biological context related to lipid metabolism and angiogenesis. These findings support Raman spectroscopy as a label-free spectroscopic technique that may complement conventional diagnostics and aid surgical and therapeutic decision-making. Larger, prospective studies are warranted to further evaluate the clinical generalizability and intraoperative translation of our results.

在这项回顾性研究中，拉曼光谱能够准确区分冷冻和福尔马林固定石蜡包埋（FFPE）标本中的后窝室管膜瘤和成神经管细胞瘤。我们从冷冻和FFPE组织中获取拉曼光谱（532 nm激发），通过五倍交叉验证来评估主成分分析-支持向量机分类器。我们还使用10x Genomics Xenium In Situ v2 FFPE工作流程对三个FFPE切片进行了试验性空间转录组学分析。总共分析了34个标本（21个冷冻标本和13个FFPE标本），在光谱水平的五倍交叉验证下，分类模型在区分室管膜瘤和髓母细胞瘤方面达到了约90%的准确率，这表明存在区别性的生化差异，而患者水平的表现需要在更大的队列中进一步验证。室管膜瘤具有较高的脂质相关拉曼带（1084、1128和1654 cm-1），而髓母细胞瘤具有较高的脱氧血红蛋白相关拉曼带（1356、1548和1604 cm-1）。与正常对照相比，肿瘤组织中类胡萝卜素相关拉曼带增加，脂质相关拉曼带减少。观察到的光谱差异与脂质相关成分和血红素/氧相关组织背景的差异一致，初步转录组谱分析提供了与脂质代谢和血管生成相关的定性生物学背景。这些发现支持拉曼光谱作为一种无标签的光谱技术，可以补充传统的诊断和辅助手术和治疗决策。需要更大规模的前瞻性研究来进一步评估我们的结果的临床通用性和术中翻译。

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引用次数: 0

Application of FTIR and PCA-LR metabolites recognition for bergamot essential oil authentication FTIR和PCA-LR代谢物识别在佛手柑精油鉴别中的应用。

IF 4.6 2区化学 Q1 SPECTROSCOPY

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Pub Date : 2026-05-05 Epub Date: 2026-02-06 DOI: 10.1016/j.saa.2026.127561

Laura Manin , Giuseppe Oliva , Maria Giovanna Bianco , Md. Maruf Hossain , Srećko Valić , Syed K. Islam , Filippo Laganà , Antonino S. Fiorillo , Salvatore A. Pullano

A rapid method using FTIR-ATR spectroscopy combined with PCA and a classification model was applied to distinguish between natural, synthetic, and adulterated Bergamot essential oil (BEO). Synthetic BEOs are often composed of specific alcohols such as ethanol and dipropylene glycol (DPG), which are used to dilute synthetic metabolites like limonene, linalyl acetate, and linalool. Synthetic BEOs exhibited a distinct peak at 1340 cm⁻¹, linked to CH bending of alcohols or methyl group deformation in artificial esters like linalyl acetate, a peak that is absent in natural BEOs. Additionally, an absorption band between 3600 and 3100 cm⁻¹ indicated the presence of DPG and synthetic ethanol, a byproduct of synthetic linalyl acetate. These findings were validated by comparison with NMR spectroscopy for metabolite recognition. A logistic regression (LR) model using PCA was applied to 369 samples, achieving an overall accuracy of 0.976 ± 0.016 through five-fold cross-validation (CV).

采用FTIR-ATR光谱法结合主成分分析和分类模型对天然佛手柑精油（BEO）、合成佛手柑精油（BEO）和掺假佛手柑精油（BEO）进行快速鉴别。合成beo通常由乙醇和二丙二醇（DPG）等特定醇组成，用于稀释合成代谢物，如柠檬烯、醋酸芳樟醇和芳樟醇。合成beo在1340 cm-1处有一个明显的峰，这与醇的CH弯曲或醋酸芳樟酯等人造酯的甲基变形有关，而天然beo中没有这个峰。此外，3600 ~ 3100 cm-1之间的吸收带表明存在DPG和合成乙醇（合成乙酸芳樟酯的副产物）。这些发现是通过核磁共振光谱的代谢物识别的比较验证。采用主成分分析（PCA）建立logistic回归（LR）模型对369份样本进行分析，经5倍交叉验证（CV），总体准确率为0.976±0.016。

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引用次数: 0

Mercaptophenylboronic acid-modified double-layer PEI-Au magnetic probes: an ultrasensitive SERS biosensor for broad-spectrum bacterial capture and specific detection in clinical urine samples 巯基苯硼酸修饰双层PEI-Au磁探针：用于临床尿液样品广谱细菌捕获和特异性检测的超灵敏SERS生物传感器。

IF 4.6 2区化学 Q1 SPECTROSCOPY

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Pub Date : 2026-05-05 Epub Date: 2026-02-02 DOI: 10.1016/j.saa.2026.127544

Siyun Cheng , Jin Chen , Xiaodan Cheng , Shihui Zhu , Han Shen , Ping Yang , Rui Xiao

Accurate identification of uropathogens is critical for guiding effective antibiotic treatment. In this study, we developed a surface-enhanced Raman spectroscopy (SERS) biosensor for rapid and sensitive detection of urinary pathogens. The system combines 4-mercaptophenylboronic acid (MPBA)-modified magnetic gold-shell beads (MSAuS@MPBA) for broad-spectrum bacterial capture with 5,5′-dithiobis(2-nitrobenzoic acid) (DTNB)- and antibody-functionalized gold nanoflowers (AuNFs@Ab) as SERS tags. A double-layer polyethyleneimine (PEI)-assisted 3 nm gold seed design was introduced to fabricate hierarchical rough surfaces on MSAuS@MPBA, significantly enhancing SERS signal generation through localized electromagnetic hotspots. The MSAuS@MPBA achieved capture efficiencies exceeding 87.52% for Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus (S. aureus). Using S. aureus as a model pathogen, the sandwich-type biosensor (MSAuS@MPBA/bacteria/AuNFs@Ab) exhibited a limit of detection (LOD) of 7 CFU mL⁻¹, a wide linear range (10¹–10⁶ CFU mL⁻¹, R² = 0.991), excellent specificity against five interfering urinary tract infection (UTI) bacteria, repeatability (RSD < 6.25%), and robust anti-matrix interference in urine and blood. Clinical validation using urine from UTI patients demonstrated high recovery rates (89.11–116.32%), confirming the sensor's practical applicability. This streamlined (∼50 min), ultrasensitive platform provides a clinically translatable method for point-of-care detection of urinary pathogens.

准确识别尿路病原体对指导有效的抗生素治疗至关重要。在这项研究中，我们开发了一种表面增强拉曼光谱（SERS）生物传感器，用于快速灵敏地检测泌尿系统病原体。该系统结合了4-巯基苯基硼酸（MPBA）修饰的磁性金壳珠（MSAuS@MPBA），用于广谱细菌捕获，5,5'-二硫比斯（2-硝基苯甲酸）（DTNB）和抗体功能化的金纳米花（AuNFs@Ab）作为SERS标记。采用双层聚乙烯亚胺（PEI）辅助的3nm金粒设计，在MSAuS@MPBA上制备了分层粗糙表面，通过局部电磁热点显著增强了SERS信号的产生。MSAuS@MPBA对大肠杆菌、铜绿假单胞菌和金黄色葡萄球菌（S. aureus）的捕获效率超过87.52%。以金黄色葡萄球菌为模型病原菌，夹心式生物传感器（MSAuS@MPBA/bacteria/AuNFs@Ab）的检出限（LOD）为7 CFU mL-1，线性范围宽（101 ~ 106 CFU mL-1, R2 = 0.991），对5种干扰性尿路感染（UTI）细菌具有良好的特异性，重复性好（RSD）

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引用次数: 0

Diagnosis of Systemic Lupus Erythematosus (SLE) and Lupus Nephritis (LN) based on a Raman-Metabolomics multimodal re-annotated segment hierarchical fusion model 基于拉曼-代谢组学多模态重新注释段分层融合模型诊断系统性红斑狼疮（SLE）和狼疮肾炎（LN）

IF 4.6 2区化学 Q1 SPECTROSCOPY

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Pub Date : 2026-05-05 Epub Date: 2026-01-12 DOI: 10.1016/j.saa.2025.127355

Wentao Qin , Ziyang Zhang , Xinya Chen , Wu Xu , Qianxi Xu , Chen Chen

Significant advances have been achieved in the field of Computer-Aided Diagnosis (CAD) for Systemic Lupus Erythematosus (SLE) and Lupus Nephritis (LN), particularly in the field of multimodal fusion diagnosis. The integration of Raman spectroscopy and metabolomics presents a promising direction for disease diagnosis; however, current Metabolomics-Raman fusion models still encounter challenges such as inadequate interpretability and inefficient utilization of inter-modal interaction information. To address these issues, this study proposes a dedicated multimodal fusion framework for Metabolomics-Raman data, encompassing a Metabolite-Raman re-annotation segmentation method and a Multimodal Segment Hierarchical Fusion Model (MSHFM) constructed based on this method. Through the screening of differential metabolites and the analysis of their superclasses, a mapping relationship was constructed that directly links molecular vibration modes (as identified by Raman spectral wavenumbers) to metabolic superclasses. This approach facilitates metabolically meaningful spectral segmentation, overcoming the limitations of traditional physical partitioning. The MSHFM excavates the correlations between spectral segments and differential metabolites through the Cross-Attention Pre-fusion Module (CAPM), and realizes hierarchical fusion and feature enhancement via the Sample-level Adaptive Multimodal Segment Fusion Module (Slam-SFM). The classification accuracies on the SLE-LN and HC-SLE datasets reach 93.33% and 100%, respectively. We identified key biomarkers such as uric acid and prostaglandin E1 by analyzing the Metabolomics-Raman association patterns using the attention mechanism, which provides an interpretable new method and potential biomarkers for the diagnosis and mechanistic research of SLE and LN.

系统性红斑狼疮（SLE）和狼疮肾炎（LN）的计算机辅助诊断（CAD）取得了重大进展，特别是在多模态融合诊断领域。拉曼光谱与代谢组学的结合为疾病诊断提供了一个有前景的方向；然而，目前的代谢组学-拉曼融合模型仍然面临着诸如可解释性不足和模式间相互作用信息利用效率低下等挑战。为了解决这些问题，本研究提出了代谢组学-拉曼数据的专用多模态融合框架，包括代谢组学-拉曼重新注释分割方法和基于该方法构建的多模态段分层融合模型（MSHFM）。通过对差异代谢产物的筛选及其超类的分析，构建了将分子振动模式（通过拉曼光谱波数识别）与代谢超类直接联系起来的映射关系。这种方法有助于代谢有意义的光谱分割，克服了传统物理分割的局限性。MSHFM通过交叉注意预融合模块（Cross-Attention Pre-fusion Module， CAPM）挖掘光谱片段与差异代谢物之间的相关性，并通过样本级自适应多模态片段融合模块（Slam-SFM）实现分层融合和特征增强。在SLE-LN和HC-SLE数据集上的分类准确率分别达到93.33%和100%。我们利用注意机制分析代谢组学-拉曼关联模式，确定了尿酸和前列腺素E1等关键生物标志物，为SLE和LN的诊断和机制研究提供了一种可解释的新方法和潜在的生物标志物。

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引用次数: 0

Low-cost highlighter nanoparticles for highly efficient multistep excitation energy transfer 用于高效多步激发态能量转移的低成本荧光纳米颗粒。

IF 4.6 2区化学 Q1 SPECTROSCOPY

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Pub Date : 2026-05-05 Epub Date: 2026-01-24 DOI: 10.1016/j.saa.2026.127477

Jonathan Piard , Ilaria Degano , Clément Doré , Jean-Frédéric Audibert , Chloé Grazon , Clémence Allain , Loïc Bertrand

Efficient excitation energy transfer (EET) is essential for energy harvesting, optoelectronics, luminescence bioimaging and photothermal medicine. Recent advances in optimised multistep EET systems have expanded the potential of these applications, offering large Stokes shifts, long-range energy transfer, and a broader tuning range for excitation and emission. However, the energy transfer efficiency of these systems rarely exceeds 90%, suggesting room for further improvement. Seeking low-cost solutions to this global problem, we show that a worldwide commercial orange highlighter ink produces both direct and multistep EET with near-unity efficiency (94.4%) among the highest recorded in the literature. We reveal that this efficiency results from a stable monodisperse dispersion of dye-loaded polymer nanoparticles in a water–glycerol medium. We identified the main dyes involved, elucidated the two-step energy transfer sequence, and demonstrated that orange highlighter particle dispersions can serve as an efficient water–ethanol sensor through monitoring variations in EET efficiency. This work presents a low-cost and readily available material exhibiting exceptionally high multistep EET efficiency, offering broad application potential.

高效激发能转移（EET）在能量收集、光电子学、发光生物成像和光热医学中是必不可少的。优化的多步EET系统的最新进展扩大了这些应用的潜力，提供了大的斯托克斯位移，远程能量转移，以及更广泛的激励和发射调谐范围。然而，这些系统的能量传递效率很少超过90%，这表明有进一步提高的空间。为了寻找解决这一全球性问题的低成本方案，我们展示了一种世界范围内的商用橙色荧光笔墨水，可以产生直接和多步EET，其效率接近统一（94.4%），是文献中记录的最高效率之一。我们发现，这种效率的结果是稳定的单分散分散的染料负载的聚合物纳米颗粒分散在水-甘油介质。我们确定了所涉及的主要染料，阐明了两步能量转移序列，并通过监测EET效率的变化证明了橙色荧光笔颗粒分散体可以作为有效的水-乙醇传感器。这项工作提出了一种低成本和容易获得的材料，具有非常高的多步EET效率，具有广泛的应用潜力。

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引用次数: 0

A dual-mode sensing platform based on bifunctional iron-doped carbon dots for sarcosine detection 基于双功能掺杂铁碳点的肌氨酸检测双模传感平台。

IF 4.6 2区化学 Q1 SPECTROSCOPY

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Pub Date : 2026-05-05 Epub Date: 2026-02-02 DOI: 10.1016/j.saa.2026.127542

Lei Wang , Weiping Liu , Sikai Wang , Dan Qiu , Guoqi Zhang , Yan Zhao

Sarcosine (SA) serves as a crucial biomarker for the diagnosis of prostate cancer, and its concentration in the body fluids of patients is strongly correlated with disease progression. Therefore, it is highly significant to develop a sensitive method for SA detection. In this study, iron-doped carbon dots (Fe-CDs) exhibiting peroxidase-like activity and bright yellow-green fluorescence were synthesized. A dual-mode sensing platform for the detection of SA was subsequently constructed based on the as-prepared Fe-CDs. Under the catalysis of sarcosine oxidase, SA underwent an oxidative reaction with molecular oxygen to produce formaldehyde and hydrogen peroxide (H₂O₂). The H₂O₂ was then decomposed by Fe-CDs with peroxidase-like activity, generating reactive oxygen species (ROS), which subsequently oxidized the colorless substrate N, N-diethyl-p-phenylenediamine sulfate (DPD) into pink-colored oxidized DPD (oxDPD). The resulting oxDPD displayed characteristic absorption peaks at 512 nm and 551 nm and concurrently quenched the fluorescence of Fe-CDs at 525 nm via fluorescence resonance energy transfer. Consequently, sensitive and quantitative detection of SA can be achieved by monitoring the reduction in fluorescence intensity and the corresponding increase in absorbance. This method demonstrates a detection limit of 0.023 μM and a linear range of 0.05–120 μM in the fluorescence mode, and a detection limit of 0.17 μM with a linear range of 1–50 μM in the colorimetric mode. Furthermore, this sensing platform was successfully applied to the quantitative detection of SA in human urine samples, with spiked recovery rates of 96.0%–109.2% for fluorescence and 91.0%–107.4% for colorimetry, highlighting its considerable potential for applications in disease diagnosis.

sarcos （SA）是诊断前列腺癌的重要生物标志物，其在患者体液中的浓度与疾病进展密切相关。因此，开发一种灵敏的SA检测方法具有重要意义。本研究合成了具有过氧化物酶样活性和亮黄绿色荧光的铁掺杂碳点（Fe-CDs）。随后，基于制备的Fe-CDs构建了SA检测的双模传感平台。在肌氨酸氧化酶的催化下，SA与分子氧发生氧化反应，生成甲醛和过氧化氢（H2O2）。H2O2被具有过氧化物酶样活性的Fe-CDs分解，生成活性氧（ROS），随后将无色底物N， N-二乙基-对苯二胺硫酸盐（DPD）氧化成粉红色的氧化DPD （oxDPD）。得到的氧化dpd在512 nm和551 nm处显示出特征吸收峰，并通过荧光共振能量转移同时在525 nm处淬灭Fe-CDs的荧光。因此，可以通过监测荧光强度的降低和相应的吸光度的增加来实现对SA的敏感和定量检测。在荧光模式下，检测限为0.023 μM，线性范围为0.05 ~ 120 μM；在比色模式下，检测限为0.17 μM，线性范围为1 ~ 50 μM。此外，该传感平台成功应用于人尿中SA的定量检测，荧光加峰回收率为96.0% ~ 109.2%，比色加峰回收率为91.0% ~ 107.4%，在疾病诊断中具有较大的应用潜力。

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引用次数: 0

Corrigendum to “An hMAO-B-activatable mitochondrial binding fluorescent probe in live-cell via enzyme-anchored and charge-driven dual targeting” [Spectrochim. Acta Part A Mol. Biomol. Spectrosc. 351 (2026) 127464] “通过酶锚定和电荷驱动的双重靶向在活细胞中激活hmao - b可激活的线粒体结合荧光探针”的更正[Spectrochim]。生物化学学报（A部分）光谱学学报，2004,26(3):357 - 357。

IF 4.6 2区化学 Q1 SPECTROSCOPY

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Pub Date : 2026-05-05 Epub Date: 2026-02-07 DOI: 10.1016/j.saa.2026.127533

Siqi Li , Lin Ma , Rong Lin , Xiongwang Li , Xinyi Yao , Yufei Hu , Jia-Jia Lang , Zhonghua Yuan , Pengbing Mi

引用次数: 0

Label-free Raman spectroscopy combined with artificial intelligence for functional subtyping of human sperm and prediction of embryo development outcomes 无标签拉曼光谱结合人工智能用于人类精子的功能分型和胚胎发育结果预测

IF 4.6 2区化学 Q1 SPECTROSCOPY

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Pub Date : 2026-05-05 Epub Date: 2026-01-19 DOI: 10.1016/j.saa.2026.127498

Boying Gao , Ning Zhang , Dexi Bi , Haijing Zhao , Yuqin Zhu , Wenfeng Zeng , Yan Nie , Jianing Chen , Nengyong Ouyang

Raman spectroscopy delivers label-free, non-destructive, single-cell measurements and directly senses intrinsic biochemical signals of nucleic acids, proteins, and lipids. Conventional semen analysis offers limited prognostic power for assisted reproductive technology (ART). We developed a single-cell, label-free Raman workflow integrated with artificial intelligence (AI) to assess sperm functional status and predict outcomes of ART. Spectra from sperm of thirty-one ART patients were processed to extract diagnostically informative bands spanning nucleic acids, proteins, lipids, and glycogen. Spectral analysis resolved two robust spectral subpopulations. The subpopulation exhibiting higher chromatin integrity, more favorable protein conformation, and better membrane lipid dynamics molecular features was associated with better outcomes, higher two-pronuclear (2PN) fertilization rate (76.08% vs 50.17%, P = 0.044), high-quality embryo rate (40.53% vs 17.57%, P = 0.010), and blastocyst formation (59% vs 9%, P < 0.001). Among evaluated classifiers, a gated recurrent unit (GRU) model showed the best predictive performance (accuracy 94%, sensitivity 94%, AUC 0.98). This Raman–AI assay enables objective, non-invasive stratification of sperm quality and clinically relevant prognosis, offering an analytically rigorous tool to guide precise sperm selection in ART.

拉曼光谱提供无标签，非破坏性的单细胞测量，并直接感知核酸，蛋白质和脂质的内在生化信号。传统精液分析对辅助生殖技术（ART）的预测能力有限。我们开发了一种与人工智能（AI）相结合的单细胞无标签拉曼工作流程，以评估精子功能状态并预测ART的结果。对31例ART患者的精子光谱进行处理，提取诊断信息带，包括核酸、蛋白质、脂质和糖原。光谱分析解决了两个稳健的光谱亚群。具有更高染色质完整性、更有利的蛋白质构象和更好的膜脂动力学分子特征的亚群与更好的结局、更高的双原核（2PN）受精率（76.08%对50.17%,P = 0.044）、高质量胚胎率（40.53%对17.57%,P = 0.010）和囊胚形成（59%对9%，P < 0.001）相关。在评估的分类器中，门控循环单元（GRU）模型表现出最佳的预测性能（准确率94%，灵敏度94%，AUC 0.98）。这种拉曼-人工智能检测能够客观、无创地对精子质量和临床相关预后进行分层，为指导抗逆转录病毒治疗中精确的精子选择提供了一种严谨的分析工具。

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