Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy最新文献_第4页

MoistureVision: Rapid non-destructive prediction of cotton seed moisture using hyperspectral imaging and machine learning 使用高光谱成像和机器学习对棉籽水分进行快速无损预测

IF 4.6 2区化学 Q1 SPECTROSCOPY

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Pub Date : 2026-05-05 Epub Date: 2026-01-24 DOI: 10.1016/j.saa.2026.127511

Hao Li , Qiao Liu , Zhiguo Han , Tao Lu , Zeyu Li

Rapid, non-destructive and accurate prediction of cotton seed moisture content is important for assessing seed vigour and improving storage capacity. In this study, a prediction approach for cotton seed moisture content was developed based on machine learning (ML) and hyperspectral imaging. Using the cultivar Jinken 1161 as the experimental material, spectral data in the range of 935–1720 nm were acquired. Outliers were removed using the Isolation Forest algorithm, and the samples were divided into calibration and prediction sets using the spectral–physicochemical value coordinate algorithm. The raw spectra were pre-processed using four methods, including Savitzky–Golay (SG) smoothing and standard normal variate transformation, before constructing traditional ML models [partial least square regression and multiple linear regression (MLR)] and deep learning (DL) models [convolutional neural network and long short-term memory network]. To reduce data redundancy and improve computational efficiency, feature wavelengths related to moisture content were selected using the successive projection algorithm and the least absolute shrinkage and selection operator (LASSO). Comparative analysis of different algorithmic combinations identified the optimal model, which was subsequently applied to hyperspectral images for pixel-wise prediction. This application enabled visualisation of the spatial distribution of moisture within individual cotton seeds. The results showed that, given the current sample size, ML models outperformed DL models. The SG–LASSO–MLR model achieved the best performance, with a prediction correlation coefficient (R2 p), root mean square error of prediction and residual predictive deviation of 0.9557, 0.908 and 4.77, respectively. These findings provide a feasible and effective technical solution for rapid and non-destructive detection of cotton seed moisture content. These outcomes offer valuable insights for seed quality evaluation and intelligent crop monitoring.

快速、无损、准确地预测棉花种子水分含量对评价种子活力和提高种子贮量具有重要意义。本文提出了一种基于机器学习和高光谱成像技术的棉花种子水分预测方法。以金根1161为实验材料，获得了935 ~ 1720 nm范围内的光谱数据。使用隔离森林算法去除异常值，并使用光谱-理化值坐标算法将样本划分为校准集和预测集。在构建传统的ML模型（偏最小二乘回归和多元线性回归（MLR））和深度学习（DL）模型（卷积神经网络和长短期记忆网络）之前，使用Savitzky-Golay （SG）平滑和标准正态变量变换等4种方法对原始光谱进行预处理。为了减少数据冗余，提高计算效率，采用逐次投影算法和最小绝对收缩选择算子（LASSO）选择与水分含量相关的特征波长。通过对不同算法组合的比较分析，确定了最优模型，并将其应用于高光谱图像的逐像素预测。这个应用程序使单个棉花种子内水分的空间分布可视化。结果表明，给定当前的样本量，ML模型优于DL模型。SG-LASSO-MLR模型表现最佳，预测相关系数（R2 p）、预测均方根误差和残差预测偏差分别为0.9557、0.908和4.77。研究结果为棉籽水分快速无损检测提供了可行有效的技术方案。这些结果为种子质量评价和作物智能监测提供了有价值的见解。

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引用次数: 0

Ratiometric naphthalimide-based fluorescent probes for highly selective detection of carboxylesterase activity 基于萘酰亚胺的比例荧光探针用于高选择性检测羧酸酯酶活性。

IF 4.6 2区化学 Q1 SPECTROSCOPY

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Pub Date : 2026-05-05 Epub Date: 2026-02-04 DOI: 10.1016/j.saa.2026.127548

Jizhen Shang , Yidian Zheng , Yan Zhang , Jiahui He , Peixi Wu , Jiaxun He , Han Zhao , Qidong Wang , Shuai Li , Yuchun Qiao , Hua Wang

Carboxylesterase (CES) is a key Phase I metabolic enzyme, and the accurate assessment of its activity is essential for studies in drug metabolism, toxicology, and disease diagnosis. However, many existing fluorescent probes suffer from cross-reactivity with homologous enzymes such as acetylcholinesterase (AChE) and butyrylcholinesterase (BChE). In this study, we designed carbamate as a CES-specific hydrolyzable moiety and conjugated it to the highly photostable naphthalimide fluorophore NIOH via either chlorinated or non-chlorinated self-immolative linkers, thereby developing two ratiometric fluorescent probes, NI-Cl and NI-W. Both probes exhibited negligible responses to AChE and BChE while enabling selective and sensitive ratiometric detection of CES. NI-Cl demonstrated an exceptionally low detection limit of 0.038 U/mL, and NI-W also showed strong performance with a detection limit of 0.048 U/mL. Importantly, NI-Cl successfully visualized endogenous CES activity in different live cells, providing a robust tool for elucidating the physiological and pathological roles of CES.

羧酸酯酶（Carboxylesterase， CES）是一种关键的I期代谢酶，其活性的准确评估对药物代谢、毒理学和疾病诊断的研究至关重要。然而，许多现有的荧光探针与同源酶如乙酰胆碱酯酶（AChE）和丁基胆碱酯酶（BChE）存在交叉反应性。在本研究中，我们将氨基甲酸酯设计为ces特异性水解片段，并通过氯化或非氯化自溶连接剂将其与高度光稳定的萘酰亚胺荧光基团NIOH结合，从而开发了NI-Cl和NI-W两种比例荧光探针。两种探针对AChE和BChE的反应都可以忽略不计，同时能够选择性和敏感地检测CES。NI-Cl的检出限极低，为0.038 U/mL， NI-W的检出限也很好，为0.048 U/mL。重要的是，NI-Cl成功地可视化了不同活细胞中的内源性CES活性，为阐明CES的生理和病理作用提供了强有力的工具。

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引用次数: 0

Corrigendum to “A new strategy for skeletal muscle wound age estimation using machine learning and ATR-FTIR spectroscopy: Eliminating early postmortem interference” [Spectrochim. Acta Part A: Mol. Biomol. Spectrosc. 344 (2026) 126748] “使用机器学习和ATR-FTIR光谱估计骨骼肌伤口年龄的新策略：消除早期死后干扰”的勘误表[Spectrochim]。Acta A Part: Mol. Biomol。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: 2026-02-10 DOI: 10.1016/j.saa.2025.127278

Xuehong Qian , Shisheng Zhu , Qiang Chen , Yingfan Li , Yao Fu , Bi Wei , Tao Huang , Jing Ma , Sihao Wang , Zhong Zhang , Yue Zhao , Shixiong Deng , Kai Yu

引用次数: 0

A hyperspectral co-design framework guided by occlusion sensitivity for early mould detection in bamboo 基于遮挡敏感性的高光谱协同设计框架在竹材霉菌早期检测中的应用。

IF 4.6 2区化学 Q1 SPECTROSCOPY

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Pub Date : 2026-05-05 Epub Date: 2026-02-02 DOI: 10.1016/j.saa.2026.127546

Ziruan Lin , Zhiyu Ma , Xuan Chu , Han Fu , Hongyu Wei , Hongli Liu

Schizostachyum funghomii McClure is a bamboo species vital to traditional craftsmanship. However, it is highly susceptible to mould, which degrades material quality and poses health risks from mycotoxins. While hyperspectral imaging (HSI) combined with deep learning (DL) offers a promising detection method, yet aligning feature selection with model design remains a challenge. This study introduces a co-design engineering framework that leverages Occlusion Sensitivity (OS) analysis to integrate model optimization and feature selection. The framework was implemented in two stages. First, OS analysis served as a diagnostic tool, revealing that baseline networks over-relied on spatial textures. This diagnosis informed the targeted architectural refinement of a ResNet model into a lightweight version (ResNet-HS). By shifting focus from spatial patterns toward core spectral features, ResNet-HS improved validation accuracy on full-spectrum data from 87.04% to 95.06%. Second, an OS-guided algorithm was developed to select characteristic wavelengths based on their direct contribution to model decisions. A concise set of seven wavelengths was identified. The final lightweight model, using only these bands, achieved a validation accuracy of 90.74%, maintaining robust performance despite a 97% reduction in spectral data. This result exceeded a CARS-SPA-based model (87.65% with 14 bands) and was comparable to a PCA Loading-based model (91.36% with 12 bands). By transforming OS into an active co-optimization engine, this research establishes an integrated framework for developing hyperspectral systems that balance accuracy, efficiency, and interpretability.

裂竹（Schizostachyum funghomii McClure）是传统工艺中至关重要的竹种。然而，它极易受到霉菌的影响，这会降低材料质量，并造成真菌毒素带来的健康风险。虽然高光谱成像（HSI）与深度学习（DL）相结合提供了一种很有前途的检测方法，但将特征选择与模型设计相结合仍然是一个挑战。本研究引入了一个协同设计工程框架，该框架利用遮挡敏感性（OS）分析来集成模型优化和特征选择。该框架分两个阶段实施。首先，OS分析作为诊断工具，揭示了基线网络对空间纹理的过度依赖。这一诊断为ResNet模型的目标架构改进提供了信息，使其成为轻量级版本（ResNet- hs）。通过将焦点从空间格局转向核心光谱特征，ResNet-HS将全光谱数据的验证精度从87.04%提高到95.06%。其次，开发了一种os引导算法，根据特征波长对模型决策的直接贡献来选择特征波长。确定了一组简洁的七个波长。最终的轻量化模型，仅使用这些波段，实现了90.74%的验证精度，尽管光谱数据减少了97%，但仍保持了稳健的性能。该结果超过了基于cars - spa的模型（87.65%，14个波段），与基于PCA加载的模型（91.36%，12个波段）相当。通过将操作系统转换为主动协同优化引擎，本研究建立了一个集成框架，用于开发平衡精度、效率和可解释性的高光谱系统。

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引用次数: 0

“On–off–on” fluorescent probe based on g-C3N4 quantum dots for sequential detection of Ag+ and glutathione 基于g-C3N4量子点的“开关-开关”荧光探针用于银+和谷胱甘肽的顺序检测。

IF 4.6 2区化学 Q1 SPECTROSCOPY

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Pub Date : 2026-05-05 Epub Date: 2026-01-26 DOI: 10.1016/j.saa.2026.127528

Ya Zou , Mei Chen , Qingzhi Liu , Kezhen Qi , Jieli He

This study reports the successful synthesis of graphitic carbon nitride quantum dots (g-C₃N₄ QDs) that demonstrate remarkable fluorescence properties and excellent dispersion through a hydrothermal method. Leveraging the specific fluorescence quenching effect of Ag⁺ on g-C₃N₄ QDs together with the strong chelating affinity of glutathione (GSH) for Ag⁺, a novel “on–off–on” fluorescence sensing platform was developed to enable sequential and highly sensitive detection of both Ag⁺ and GSH. This probe exhibited outstanding sensitivity, anti-interference ability, and selectivity with detection limits of 0.0114 μM for Ag⁺ and 0.3916 μM for GSH. Mechanistic studies revealed that the fluorescence “off” state was mainly governed by a photoinduced electron-transfer (PET) effect, with additional contributions from the internal filtering effect (IFE). Conversely, the fluorescence “on” state was restored when GSH coordinated with Ag⁺, thereby blocking the PET pathway and recovering the intrinsic fluorescence of g-C₃N₄ QDs. Furthermore, spiked-recovery experiments in real water and serum samples yielded satisfactory results, demonstrating the sensor's strong practical applicability and providing a reliable analytical approach for environmental monitoring and biomedical analysis.

本研究报道了用水热法成功合成了具有显著荧光特性和良好分散性能的石墨化氮化碳量子点（g-C3N4 QDs）。利用Ag+对g-C3N4量子点的特异性荧光猝灭效应以及谷胱甘肽（GSH）对Ag+的强螯合亲和力，开发了一种新型的“开-关-开”荧光传感平台，实现了Ag+和GSH的序列和高灵敏度检测。该探针对Ag+和GSH的检出限分别为0.0114 μM和0.3916 μM，具有良好的灵敏度、抗干扰能力和选择性。机理研究表明，荧光“关闭”状态主要由光诱导电子转移（PET）效应控制，内部过滤效应（IFE）也有额外的贡献。相反，当GSH与Ag+配合时，恢复荧光“on”状态，从而阻断PET途径，恢复g-C₃N₄QDs的固有荧光。此外，在真实的水和血清样品中进行了峰值回收实验，取得了满意的结果，证明了该传感器具有较强的实用性，为环境监测和生物医学分析提供了可靠的分析方法。

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引用次数: 0

Rational design of a fluorescent turn-on probe synergistically responsive to viscosity and polarity for rapid detection of total polar materials in edible oil 一种对粘度和极性协同响应的荧光开启探针的合理设计用于食用油中总极性物质的快速检测。

IF 4.6 2区化学 Q1 SPECTROSCOPY

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Pub Date : 2026-05-05 Epub Date: 2026-02-04 DOI: 10.1016/j.saa.2026.127545

Kehong Jiang , Jiayi Shi , Lingbo Qu , Yuanqiang Sun

Total polar materials (TPM) in edible oils consist primarily of degradation products formed through oxidation, hydrolysis, and polymerization during processing or storage. These polar components adversely affect the oil's functional performance, storage stability, and nutritional quality. Leveraging the dual positive correlation between TPM content and the microenvironmental polarity and viscosity of frying oil, a fluorescent probe was designed that exhibited a synergistic enhancement in fluorescence in response to increases in both polarity and viscosity. As the viscosity and polarity increased, the probe exhibited a distinct “off−on” fluorescence response, demonstrating a strong correlation with both factors. This probe was successfully employed to determine the TPM content in frying oils. In experiments using soybean oil (TPM range: 1.1–29.3%) and salad oil (TPM range: 0.1–27.5%), the fluorescence intensity demonstrated excellent linear correlations with TPM content, achieving correlation coefficients of 0.9967 and 0.9940, respectively. These results confirm the probe's capability for quantitative detection. Furthermore, the probe was validated with commercially available oil samples, accurately determining TPM levels even in complex unknown matrices. This demonstrates its potential as a tool for rapid preliminary screening of edible oil quality. This study provides valuable insights and lays the foundation for the development of highly sensitive and efficient dual-response fluorescent probes that target polarity and viscosity.

食用油中的总极性物质（TPM）主要由加工或储存过程中氧化、水解和聚合形成的降解产物组成。这些极性成分对油的功能性能、储存稳定性和营养品质产生不利影响。利用TPM含量与煎炸油微环境极性和粘度之间的双重正相关关系，设计了一种荧光探针，该探针在极性和粘度增加的同时表现出荧光的协同增强。随着粘度和极性的增加，探针表现出明显的“off-on”荧光响应，表明与这两个因素有很强的相关性。该探针成功地测定了煎炸油中TPM的含量。在大豆油（TPM范围：1.1 ~ 29.3%）和色拉油（TPM范围：0.1 ~ 27.5%）的实验中，荧光强度与TPM含量表现出良好的线性相关性，相关系数分别为0.9967和0.9940。这些结果证实了探针定量检测的能力。此外，该探针用市售的油样进行了验证，即使在复杂的未知矩阵中也能准确地确定TPM水平。这表明了它作为一种快速初步筛选食用油质量的工具的潜力。该研究为开发高灵敏度、高效的极性和粘度双响应荧光探针提供了有价值的见解，并奠定了基础。

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引用次数: 0

Non-invasive detection of gastric cancer biomarker 4-HBA via a ZIF/CDs-based fluorescent sensor 基于ZIF/ cds的荧光传感器无创检测胃癌生物标志物4-HBA

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.2026.127530

Rui Jie , Xiaochen Zhu , Haiyan Qi , Tao Jing , Jun Li , Yunpeng Zhao , Jinzhi Yu , Chenyu Qi

Urine analysis has become an increasingly valuable tool in modern medical diagnostics due to its non-invasive nature. In this study, we report the development of a novel fluorescent sensor based on ZIF-8 and CDs embedded in a molecularly imprinted polymer matrix (ZIF/CDs@MIPs) for the selective and sensitive detection of 4-hydroxybenzoic acid (4-HBA), a potential gastric cancer biomarker. The integration of ZIF-8 enhanced the sensor's surface area, structural stability, and fluorescence performance. Optimization experiments revealed that a ZIF-8 concentration of 400 mg/L yielded the highest quenching efficiency. The sensor exhibited excellent fluorescence stability under varying pH, ionic strength, and UV exposure. A detailed analysis of the quenching mechanism indicated that dynamic quenching and electron transfer were involved in 4-HBA detection. The sensor showed strong selectivity for 4-HBA over common interferents, with a low detection limit of 0.68 μmol/L and a good linear response in the 0–100 μmol/L range. Application in real urine samples demonstrated high recovery rates (97.71–106.16%) and low relative standard deviations (0.80–2.95%), confirming its reliability and accuracy. These findings highlight the potential of ZIF/CDs@MIPs as a practical and non-invasive fluorescence sensing platform for biomarker monitoring in clinical diagnostics, especially for early gastric cancer detection.

尿液分析因其非侵入性而成为现代医学诊断中越来越有价值的工具。在这项研究中，我们报道了一种基于ZIF-8和CDs嵌入分子印迹聚合物基质（ZIF/CDs@MIPs）的新型荧光传感器的开发，用于选择性和敏感检测4-羟基苯甲酸（4-HBA），这是一种潜在的胃癌生物标志物。ZIF-8的集成增强了传感器的表面积、结构稳定性和荧光性能。优化实验表明，ZIF-8浓度为400 mg/L时淬火效率最高。该传感器在不同的pH值、离子强度和紫外线照射下均表现出优异的荧光稳定性。对4-HBA的猝灭机理进行了详细的分析，表明4-HBA的检测涉及动态猝灭和电子转移。该传感器对4-HBA干扰具有较强的选择性，检测限为0.68 μmol/L，在0 ~ 100 μmol/L范围内具有良好的线性响应。在实际尿样中应用，回收率高（97.71 ~ 106.16%），相对标准偏差低（0.80 ~ 2.95%），验证了该方法的可靠性和准确性。这些发现突出了ZIF/CDs@MIPs作为一种实用的、无创的荧光传感平台在临床诊断中监测生物标志物的潜力，特别是在早期胃癌检测中。

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引用次数: 0

A robust xanthylium-based near-infrared fluorescent probe for viscosity imaging in inflammatory and hepatic injury mice models 一种健壮的基于黄嘌呤的近红外荧光探针，用于炎症和肝损伤小鼠模型的粘度成像

IF 4.6 2区化学 Q1 SPECTROSCOPY

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Pub Date : 2026-05-05 Epub Date: 2026-01-23 DOI: 10.1016/j.saa.2026.127504

Lele Yan , Xiaoyuan Sun , Zhuobin Shang , Zhenming Dong , Xiaoqing Yan , Yu Wang , Shaomin Shuang

As the principal organ for the metabolism and detoxification of both exogenous and endogenous substances, the liver demonstrates heightened vulnerability to the onset of hepatic pathologies. Aberrant viscosity, acting as a potential biomarker, exhibits a significant correlation with liver diseases such as fatty liver, hepatic fibrosis, and liver injury. Therefore, real-time monitoring of viscosity fluctuations in animal models of liver disease is essential for related pathological investigations. Here, we report a novel viscosity-sensitive fluorescent probe (DJXP) with NIR excitation at 736 nm and emission at 809 nm, characterized by a large Stokes shift (67 nm), a broad operational pH range, high selectivity and excellent biocompatibility. DJXP enabled the visualization of viscosity changes in ICR mice induced by the antifungal drug nystatin, as determined by fluorescence imaging analysis. Furthermore, DJXP was employed to monitor elevated viscosity in mouse models of both lipopolysaccharide (LPS)-induced inflammation and rotenone-induced acute hepatic injury, demonstrating promising potential for the non-invasive detection and diagnosis of hepatic pathologies associated with altered viscosity.

作为外源性和内源性物质的代谢和解毒的主要器官，肝脏对肝脏病变的发病表现出高度的脆弱性。异常黏度作为一种潜在的生物标志物，与脂肪肝、肝纤维化和肝损伤等肝脏疾病有显著相关性。因此，实时监测肝脏疾病动物模型的粘度波动对相关病理研究至关重要。在这里，我们报道了一种新型的粘度敏感荧光探针（DJXP），其近红外激发波长为736 nm，发射波长为809 nm，具有大的Stokes位移（67 nm），宽的工作pH范围，高选择性和优异的生物相容性。通过荧光成像分析，DJXP可以可视化抗真菌药物制霉菌素诱导的ICR小鼠黏度变化。此外，DJXP被用于监测脂多糖（LPS）诱导的炎症和鱼藤酮诱导的急性肝损伤小鼠模型的粘度升高，显示出与粘度改变相关的肝脏病变的无创检测和诊断的潜力。

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引用次数: 0

Imaging mitochondrial hydrogen sulfide in multicellular spheroids using a near-infrared iridium(III) complex 使用近红外铱（III）配合物成像多细胞球体中的线粒体硫化氢。

IF 4.6 2区化学 Q1 SPECTROSCOPY

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Pub Date : 2026-05-05 Epub Date: 2026-01-21 DOI: 10.1016/j.saa.2026.127496

Zhifeng Mao , Liuqi Ye , Fahui Hu , Xiaolei Wu , Daniel Shiu-Hin Chan , Chun-Yuen Wong , Jin-Biao Liu , Chung-Hang Leung , Wanhe Wang

Abnormal levels of hydrogen sulfide (H₂S) have been linked to multiple diseases, including neurological disorders, cardiovascular diseases, and cancers. Mitochondria play a central role in H₂S metabolism, and dysregulation of H₂S within mitochondria is emerging as a key factor in mitochondrial dysfunction. To explore the role of mitochondrial H₂S in live cells, a near-infrared (NIR) iridium(III) complex-based luminescence probe was constructed for the selective and sensitive detection of endogenous mitochondrial H₂S. Complex 1 exhibits a distinct luminescent response to H₂S. Upon exposure to H₂S, the nitro group in complex 1 is reduced to an amine group for triggering a 1,6-elimination reaction, resulting in luminescence quenching. The probe exhibits high-performance detection with low detection limit of 0.96 μM and exceptional specificity in aqueous buffer. Confocal imaging in living HeLa cells confirmed the probe's ability to detect both exogenous and endogenous H₂S. Additionally, the probe specifically localizes to mitochondria, enabling effective bioimaging of mitochondrial H₂S in multicellular spheroids (MCSs). Notably, this study presents the first luminescence probe for mitochondrial H₂S based on a NIR iridium(III) complex. These findings demonstrate that complex 1 is a promising tool for exploring the biological functions and pathological roles of subcellular H₂S in diseases.

硫化氢（H2S）水平异常与多种疾病有关，包括神经系统疾病、心血管疾病和癌症。线粒体在H2S代谢中起着核心作用，线粒体内H2S的失调是线粒体功能障碍的关键因素。为了探索线粒体H2S在活细胞中的作用，构建了一种近红外（NIR）铱（III）配合物发光探针，用于选择性和敏感检测内源性线粒体H2S。配合物1对H2S表现出明显的发光响应。当接触H2S时，配合物1中的硝基被还原为胺基，引发1,6-消除反应，导致发光猝灭。该探针具有良好的检测性能，检测限为0.96 μM，在水溶液缓冲液中具有良好的特异性。活HeLa细胞的共聚焦成像证实了探针检测外源性和内源性H2S的能力。此外，该探针特异性定位于线粒体，能够有效地对多细胞球体（mcs）中的线粒体H2S进行生物成像。值得注意的是，本研究首次提出了基于近红外铱（III）配合物的线粒体H2S发光探针。这些发现表明，复合体1是探索亚细胞H2S在疾病中的生物学功能和病理作用的一个很有前途的工具。

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引用次数: 0

Raman and SERS analytical platform with machine learning for classifying wild type p53 and hotspot mutants R175H and R273H 基于机器学习的Raman和SERS分析平台对野生型p53和热点突变体R175H和R273H进行分类。

IF 4.6 2区化学 Q1 SPECTROSCOPY

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Pub Date : 2026-05-05 Epub Date: 2026-01-25 DOI: 10.1016/j.saa.2026.127522

Karen Hernández-Vidales , Juan A. Muñoz Castillo , Selene R. Islas , Andrés Rodríguez-Rodríguez , Vanesa Olivares-Illana , José M. Saniger

The development of analytical approaches capable of detecting subtle protein conformational changes is of significant interest in biomedicine, particularly for disease diagnostics and biomolecular characterization. In this work, the tumor suppressor p53 protein was selected as a model system to evaluate an analytical platform based on Raman spectroscopy combined with surface-enhanced Raman spectroscopy (SERS) and supervised machine learning for the classification of closely related protein variants.

Label-free Raman and SERS spectra of recombinant wild-type p53 and its hotspot mutants R175H and R273H were acquired on bare Al and Al coated with gold nanospheres, gold nanorods, and silver nanoparticles. Principal Component Analysis (PCA) revealed distinct spectral fingerprints among the p53 variants, with relevant contributions in the amide III and CH stretching regions, indicating subtle conformational differences. Supervised classification was performed using several machine learning algorithms under a nested, group-disjoint cross-validation protocol (holding out entire acquisition lines) to account for within-line spectral correlation. Among tested models, a linear Support Vector Machine (Linear-SVM) achieved the highest performance, reaching an accuracy of 92.9 ± 6.9% on AuNS@Al substrates.

These results demonstrate that the integration of optimized nanostructured SERS substrates, Raman spectroscopy, and machine learning constitutes a robust analytical platform for the structural classification of wild-type and mutant p53 proteins. The proposed approach provides a versatile framework for studying conformational changes in biomolecules of biomedical relevance and supports its potential application in cancer biomarker detection and protein misfolding studies.

能够检测细微蛋白质构象变化的分析方法的发展对生物医学，特别是疾病诊断和生物分子表征具有重要意义。在这项工作中，选择肿瘤抑制蛋白p53作为模型系统，评估基于拉曼光谱结合表面增强拉曼光谱（SERS）和监督机器学习的分析平台，以分类密切相关的蛋白质变体。重组野生型p53及其热点突变体R175H和R273H在裸铝和包被金纳米球、金纳米棒和银纳米颗粒的铝上获得了无标记拉曼和SERS光谱。主成分分析（PCA）揭示了p53变体之间不同的光谱指纹图谱，在酰胺III和CH拉伸区有相关贡献，表明了微妙的构象差异。在嵌套的、组分离的交叉验证协议（保留整个采集线）下，使用几种机器学习算法进行监督分类，以解释线内光谱相关性。在测试的模型中，线性支持向量机（linear - svm）达到了最高的性能，在AuNS@Al基板上达到了92.9±6.9%的精度。这些结果表明，优化的纳米结构SERS底物、拉曼光谱和机器学习的集成构成了野生型和突变型p53蛋白结构分类的强大分析平台。该方法为研究生物医学相关生物分子的构象变化提供了一个通用的框架，并支持其在癌症生物标志物检测和蛋白质错误折叠研究中的潜在应用。

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引用次数: 0