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Surface-enhanced Raman scattering (SERS), as a rapid, reliable and non-destructive spectral detection technology, has made a series of breakthrough achievements in screening and pre-diagnosis of various cancerous tumors. In this paper, high-performance gold nanoparticles/785 porous silicon photonic crystals (Au NPs/785 PSi PhCs) active SERS substrates were specially designed for serum testing, and realized highly sensitive detection of serum from healthy people, patients with cervical cancer and breast cancer. Based on the SERS spectra of the three groups of serum, the significant differences between the healthy group and cancer group at 1030 cm−1 and 1051 cm−1 were analyzed, and the similar but different serum SERS spectra of cervical cancer and breast cancer patients were compared. In addition, the spectral difference detected by SERS technology combined with a multivariate statistical algorithm was used to distinguish three kinds of serum. The serum SERS spectral sensitive bands were extracted by recursive weighted partial least squares (rPLS), and the three classification diagnosis models were established by combining orthogonal partial least squares discriminant analysis (OPLS-DA), linear discriminant analysis (LDA) and principal component analysis support vector machine (PCA-SVM) for synchronous classification and discrimination of the three groups of serum. The diagnostic results showed that the overall screening accuracy of three models were 93.28%, 97.77% and 94.78%, respectively. These above results confirmed that the Au NPs/785 PSi PhCs can realize super-sensitive detection of serum, and the established diagnostic model has great potential for pre-diagnosis and simultaneous screening of cervical cancer and breast cancer. [ABSTRACT FROM AUTHOR]

Clopidol is one of the most widely used anti-coccidiosis drugs. Its residues in poultry products and the environment pose a serious threat to human health. In this work, microwave-assisted synthesis of magnetic ionic liquid/gold nanoparticles (MIL-Au NPs) as the SERS substrates were first designed for sensitive and reliable determination of clopidol residue in egg samples. The experiment shows that MIL(1-methyl-3-hexyl imidazole ferric tetrachloride ([C6mim]FeCl4)) and microwave play a key role in the dispersion and morphology of Au NPs. Under the optimal conditions, the as-prepared MIL-Au NPs were applied to the SERS detection of clopidol in methanol and egg solution and its detection limits can be as low as to 0.5 μg/kg (equal to 0.5 ppb) in both solutions. The standard curves with regression coefficients of 0.9298 and 0.93496 were constructed in the linear range of 100–1000 ppb and 0.5–50 ppb for clopidol in egg solutions. Moreover, satisfactory recoveries (97.5–103.2%) were obtained for egg samples. The developed SERS method provides a way for quantitation of clopidol and can be applied for the convenient, reliable, and highly sensitive detection of antibiotic residues in food and environment, which has great potential in food safety and biological monitoring. [ABSTRACT FROM AUTHOR]

Echinococcosis is a serious zoonotic parasitic disease that could be fatal without diagnosis and treatment in a timely manner. Herein, we present a rapid and label-free method for screening of echinococcosis using surface-enhanced Raman spectroscopy (SERS). Three groups of serum SERS spectra based on porous silicon/silver composites are obtained: one group from healthy volunteers (normal, n = 163) and two other groups from patients with pathologically confirmed echinococcosis (cystic echinococcosis (CE), n = 69 and alveolar echinococcosis (AE), n = 38). The derived characteristic spectrum was analyzed to explain differences between echinococcosis and healthy volunteers and a principal component analysis (PCA) was applied for classification. Raman spectra revealed that high sensitivity and specificity for echinococcosis diagnosis were associated with the contents of phenylalanine and tyrosine. In addition, Raman spectroscopy analysis identified two metabolites including phenylalanine and carotenoids that could distinguish three types of serum. Orthogonal partial least squares discriminant analysis (OPLS-DA) was successfully used as a discriminative model to classify echinococcosis with the highest sensitivity and specificity of 100% and 98.6%, respectively. Combination of serum metabolomics with SERS enabled accurate screening of echinococcosis patients. The results indicate that SERS-based serum profile analysis has the potential to be a valuable tool for the early diagnosis and screening of echinococcosis. [ABSTRACT FROM AUTHOR]