Erratum: Author correction to 'Real-time SERS monitoring anticancer drug release along with SERS/MR imaging for pH-sensitive chemo-phototherapy' [Acta Pharm Sin B 13 (2023) 1303-1317].

[This corrects the article DOI: 10.1016/j.apsb.2022.08.024.].

Well-Ordered Au Nanoarray for Sensitive and Reproducible Detection of Hepatocellular Carcinoma-Associated miRNA via CHA-Assisted SERS/Fluorescence Dual-Mode Sensing.

Ultra-sensitive detection of cancer-related biomarkers in serum is of great significance for early diagnosis, treatment, prognosis, and staging of cancer. In this work, we proposed a surface-enhanced Raman scattering and fluorescence (SERS/FL) dual-mode biosensor for hepatocellular carcinoma (HCC)-related miRNA (miR-224) detection using the composition of well-arranged Au nanoarrays (Au NAs) substrate coupled with the target-catalyzed hairpin assembly (CHA) strategy. The hot spots densely and uniformly distributed on the Au array offers considerably enhanced and reproducible SERS signals, along with their wide and open surface to facilitate miR-224 adsorption. By this sensing strategy, the target miR-224 can be detected in a wide linear range (1 fM to 1 nM) with a limit of detection of 0.34 fM in the SERS mode and 0.39 fM in the FL mode. Meanwhile, this biosensor with exceptional specificity and anti-interference ability can discriminate target miR-224 from other interference miRNAs. Practical analysis of human blood samples also demonstrated considerable reliability and repeatability of our developed strategy. Furthermore, this biosensor can distinguish HCC cancer subjects from normal ones and monitor HCC patients before and after hepatectomy as well as guide the distinct Barcelona clinic liver cancer (BCLC) stages. Overall, benefiting from a well-arranged Au nanoarray, CHA amplification strategy, and SERS/metal enhanced fluorescence effect, this established biosensor opens new avenues for the early prediction, warning, monitoring, and staging of HCC.

Real-time SERS monitoring anticancer drug release along with SERS/MR imaging for pH-sensitive chemo-phototherapy.

In situ and real-time monitoring of responsive drug release is critical for the assessment of pharmacodynamics in chemotherapy. In this study, a novel pH-responsive nanosystem is proposed for real-time monitoring of drug release and chemo-phototherapy by surface-enhanced Raman spectroscopy (SERS). The Fe3O4@Au@Ag nanoparticles (NPs) deposited graphene oxide (GO) nanocomposites with a high SERS activity and stability are synthesized and labeled with a Raman reporter 4-mercaptophenylboronic acid (4-MPBA) to form SERS probes (GO-Fe3O4@Au@Ag-MPBA). Furthermore, doxorubicin (DOX) is attached to SERS probes through a pH-responsive linker boronic ester (GO-Fe3O4@Au@Ag-MPBA-DOX), accompanying the 4-MPBA signal change in SERS. After the entry into tumor, the breakage of boronic ester in the acidic environment gives rise to the release of DOX and the recovery of 4-MPBA SERS signal. Thus, the DOX dynamic release can be monitored by the real-time changes of 4-MPBA SERS spectra. Additionally, the strong T2 magnetic resonance (MR) signal and NIR photothermal transduction efficiency of the nanocomposites make it available for MR imaging and photothermal therapy (PTT). Altogether, this GO-Fe3O4@Au@Ag-MPBA-DOX can simultaneously fulfill the synergistic combination of cancer cell targeting, pH-sensitive drug release, SERS-traceable detection and MR imaging, endowing it great potential for SERS/MR imaging-guided efficient chemo-phototherapy on cancer treatment.

Logistic regression analysis of ultrasound findings in predicting the malignant and benign phyllodes tumor of breast.

OBJECTIVE: To evaluate ultrasound characteristics in the prediction of malignant and benign phyllodes tumor of the breast (PTB) by using Logistic regression analysis. METHODS: 79 lesions diagnosed as PTB by pathology were analyzed retrospectively. The ultrasound features of PTB were recorded and compared between benign and malignant tumors by using single factor and multiple stepwise Logistic regression analysis. Moreover, the Logistic regression model for malignancy prediction was also established. RESULTS: There were 79 patients with PTB, including 39 benign PTBs and 40 malignant PTBs (33 borderline PTBs and 7 malignant PTBs by pathologic classification). The area under the ROC curve (AUC) of lesion size and age were 0.737 and 0.850 respectively. There were significant differences in age, lesion size, shape, internal echo, liquefaction, and blood flow between malignant and benign PTBs by using single-factor analysis (P<0.05). Age, internal echo, and liquefaction were significant features by using Logistic regression analysis. The corresponding regression equation In (p/(1 - p) = -3.676+2.919 internal echo +3.029 liquefaction +4.346 age). CONCLUSION: Internal echo, age, and liquefaction are independent ultrasound characteristics in predicting the malignancy of PTBs.