Maligno Francisco, Páscoa Ricardo N M J, Gomes Pedro S
Faculty of Dental Medicine, University of Porto, Porto, Portugal.
LAQV/REQUIMTE, Department of Chemical Sciences, Faculty of Pharmacy, University of Porto, Porto, Portugal.
Clin Oral Investig. 2025 May 20;29(6):305. doi: 10.1007/s00784-025-06382-6.
This proof-of-concept study aimed to compare the biochemical composition of gingival crevicular fluid (GCF) and peri-implant crevicular fluid (PICF) under healthy conditions, through mid-infrared (MIR) spectroscopy.
Using a split-mouth design, GCF and PICF samples were collected from 12 participants and analyzed through MIR spectroscopy. Advanced chemometric models, including partial least squares-discriminant analysis, k-nearest neighbors, and support vector machine discriminant analysis, were applied to explore potential biochemical differences between the biofluids.
No cluster formation was observed with PCA, indicating a high degree of similarity between groups. The PLS-DA model didn't effectively discriminate between GCF and PICF with prediction rates of 62.5% (10/16) for calibration, 37.5% (6/16) for cross-validation, and 50% (4/8) for validation. The k-NN model, using k = 3 neighbors showed 25% (4/16) correct classification rates during calibration and a validation set accuracy of 50%. SVM-DA analysis showed a correct prediction rate of 37.5% (6/16) for calibration and 50% for cross-validation 50% (8/16) and 50% (4/8) in the validation phase. Nonetheless, subtle spectral differences were observed in spectral regions R1 (3982-2652 cm⁻) and R4 (1180-922 cm⁻), suggesting a slightly increased lipidic content and the presence of ethers and glycosidic bonds linked to carbohydrates, in PICF.
The lack of significant biochemical differences between GCF and PICF under healthy conditions, as determined by MIR spectroscopy, suggests that implant-related changes in PICF composition are negligible.
The demonstrated biochemical similarity between GCF and PICF under healthy conditions reinforces the potential of PICF as a reliable biofluid for diagnostic applications, including monitoring oral and systemic health biomarkers, without significant influence from implant-related factors.
本概念验证研究旨在通过中红外（MIR）光谱法比较健康状态下龈沟液（GCF）和种植体周龈沟液（PICF）的生化成分。
采用双侧对照设计，从12名参与者中收集GCF和PICF样本，并通过MIR光谱法进行分析。应用先进的化学计量模型，包括偏最小二乘判别分析、k近邻算法和支持向量机判别分析，以探索生物流体之间潜在的生化差异。
主成分分析（PCA）未观察到聚类形成，表明各组之间具有高度相似性。偏最小二乘判别分析（PLS-DA）模型未能有效区分GCF和PICF，在校准阶段预测率为62.5%（10/16），交叉验证阶段为37.5%（6/16），验证阶段为50%（4/8）。使用k = 3个近邻的k近邻算法（k-NN）模型在校准期间显示出25%（4/16）的正确分类率，验证集准确率为50%。支持向量机判别分析（SVM-DA）在校准阶段的正确预测率为37.5%（6/16），交叉验证阶段为50%（8/16），验证阶段为50%（4/8）。尽管如此，在光谱区域R1（3982 - 2652 cm⁻）和R4（1180 - 922 cm⁻）观察到细微的光谱差异，表明PICF中脂质含量略有增加，并且存在与碳水化合物相关的醚键和糖苷键。
MIR光谱法测定结果表明，健康状态下GCF和PICF之间缺乏显著的生化差异，这表明种植体相关的PICF成分变化可忽略不计。
健康状态下GCF和PICF之间已证实的生化相似性强化了PICF作为一种可靠生物流体用于诊断应用的潜力，包括监测口腔和全身健康生物标志物，且不受种植体相关因素的显著影响。
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