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In this work, Au nanobowl (AuNB) arrays and the hybridization chain reaction (HCR) were utilized to develop a surface-enhanced Raman scattering (SERS) microfluidic chip for the ultrasensitive and simultaneous detection of squamous cell carcinoma antigen (SCCA) and cytokeratin 19 fragment antigen 21–1 (CYFRA21–1) in the serum of cervical cancer patients. Antibody-oligonucleotide conjugates were adopted as triggers, which initiated HCR by the hybridization between hairpin DNAs that were modified on Raman reporters-labeled Ag nanocubes, forming nicked double-stranded DNAs on AuNB arrays and leading to SERS signal amplification. Good linear response in the range of 10-12 – 10-6 g/mL, with an ultralow limit of detection for SCCA (0.08 pg/mL) and CYFRA21–1 (0.13 pg/mL), was achieved. Furthermore, the experiments demonstrated that the chip was feasible, time-efficient, and selective. The proposed chip was successfully applied to detect SCCA and CYFRA21–1 in clinical samples, and the results were consistent with those of enzyme-linked immunosorbent assay. Since most protein biomarkers in serum lack the corresponding aptamers, this method, which establishes antibody-oligonucleotide conjugates to trigger HCR, provides a general signal amplification technology for detecting protein biomarkers and exhibits good potential in clinical applications. • A SERS microfluidic chip based on AuNBs array and HCR was developed and employed for clinical detection. • Antibody-oligonucleotide conjugates were established to connect with targets and initiate HCR for signal amplification. • The assay possessed high sensitivity, with LODs as low as 0.08 pg/mL for SCCA and 0.13 pg/mL for CYFRA21-1. • The SERS microfluidic chip realized automatic flow by hydrophilic treatment and comb-like structure channels. [ABSTRACT FROM AUTHOR]

A novel rhodamine B-based sensor 1 consisting of a rhodamine B moiety linked to the amine end of a 1,4,7,10-tetraoxa-13-azacyclopentadecane was designed and synthesized. Sensor 1 exhibits a high selectivity for Fe 3+ in the presence of many other metal cations in a MeOH/H 2 O (1:1, v/v, pH = 7.4) solution. The binding analysis using a Job plot suggested that sensor 1 formed a 1:1 complex with Fe 3+ . The Fe 3+ binding ability of 1 was further demonstrated by DFT calculations. Fluorescence microscopy experiments demonstrated that sensor 1 can be used as a fluorescent probe for the detection of Fe 3+ in human liver cells (L-02) and rat neuronal cells (PC12). [ABSTRACT FROM AUTHOR]

Abstract: We have successfully introduced a novel strategy for the rational design of a fluorescence turn-on probe for iodide, which is a notorious fluorescence quencher due to the heavy atom effect. The strategy is based on the redox reaction between Cu2+ and iodide. The probe exhibited a 20-fold fluorescence enhancement in the presence of 4equiv. of iodide. The probe developed herein represents the first fluorescence amplified probe for iodide. We believe that it will find interesting use in environment. [Copyright &y& Elsevier]

Serum analysis is crucial for favourable prognosis of gastric cancer (GC) and for improving patient survival rates. However, it remains a challenge to develop an effective strategy to accurately identify differences in gastric cancer before and after treatment to guide efficacy evaluation. In this study, we combined surface-enhanced Raman scattering (SERS) with principal component analysis (PCA)-two-layer nearest neighbour (TLNN) to propose a promising serum analytical platform for label-free detection of cisplatin-treated GC mice. A microarray chip fabricated from Au nano-hexagon (AuNH) substrates was employed to measure the SERS spectra of the serum of GC mice at different treatment stages, and then a model for recognition of SERS spectra was constructed using a PCA-TLNN algorithm. The results revealed that the microarray chip exhibited superior portability, SERS activity, stability, and uniformity. Through PCA-TLNN, the GC mice at different treatment stages were successfully segregated, and several key spectral features for distinguishing different treatment stages were captured. The established PCA-TLNN model achieved satisfactory results, with an accuracy of over 97.5%, a sensitivity of over 90%, and a specificity of over 96.7%. Label-free serum SERS in combination with multivariate analysis could serve as a potential technique for the clinical diagnosis and staging of treatments. [Display omitted] • The novel microarray chip can realize rapid, sensitive, label-free and high-throughput detection of SERS spectra of serum. • PCA-TLNN successfully differentiated the SERS spectra of serum from cisplatin-treated GC mice at different stages. • The most prominent spectral features for distinguishing different treatment stages. • were captured in PCs loading plots. • PCA-TLNN was superior to traditional multivariate algorithm in accuracy, sensitivity and specificity. [ABSTRACT FROM AUTHOR]