Rapid, simple, and reliable detection of toxics at trace level is of great significance for public health. Surface‐enhanced Raman spectroscopy (SERS) as a powerful vibrational spectroscopic technique for molecules probing provides great advantages in trace detection; however, the low reproducibility of SERS signals from spot to spot and substrate to substrate remains a great challenge restricting its real applications. Here, we report a facile method for reproducibly preparing highly uniform self‐assembled monolayers of gold nanostars (Au NSs SAM) as SERS substrates using the classic Langmuir–Blodgett technique and introduced a statistical method to explore the signal reproducibility by t test. Our results show that the Au NSs SAM substrates fabricated in the same batch and different batches generated constant SERS signals without statistical differences and could detect dye molecules CV, R6G, and RhB in solution at concentrations as low as 10−8, 10−8, and 10−7 M, respectively. We then applied the Au NSs SAM for trace detection of Tetracycline (TC), one of the most widespread antibiotics entering the food chain and threatening the ecological balance. A detection limit of 0.05 μg/ml was achieved, with a linear response between SERS signal and TC concentration in the range of 0.05–10 μg/ml. Overall, this uniform Au NSs SAM could be reproducibly fabricated to provide a reliable platform for trace detection of TC residues or other toxics in water and is expected to have broad applications in different fields including environmental monitoring, food security, and so on.
BackgroundACYP1 plays important physiological and metabolic roles in glycolysis and membrane ion pump activity by catalyzing acyl phosphate hydrolysis. ACYP1 is related to tumorigenesis and progression and poor prognosis in gastrointestinal cancer. However, its pancancer roles and mechanisms are unclear. Our study aimed to understand the ACYP1 expression signature and prognostic value across cancers and investigate immune infiltration patterns in liver hepatocellular carcinoma (LIHC) and verify them in LIHC samples.MethodsTranscriptional expression profiles of ACYP1 across cancers were analyzed using Oncomine and TIMER. The prognostic value of ACYP1 was assessed across PrognoScan, Kaplan—Meier Plotter, and GEPIA. Significant pathways associated with ACYP1 in LIHC were obtained via Gene Set Enrichment Analysis. The correlation between ACYP1 expression and immune infiltration in LIHC was investigated using TIMER. We validated ACYP1 expression, prognostic value, and association with immune cells in tumor tissues by immunohistochemistry and flow cytometry.ResultsACYP1 was overexpressed across cancers. High expression of ACYP1 correlated with a poor prognosis in most tumor types, especially in LIHC. ACYP1 was significantly implicated in immune and metabolic related pathways. High ACYP1 expression showed significant correlations with the abundances of Th2 cells, Tregs, macrophages, dendritic cells, and myeloid-derived suppressor cells in LIHC. LIHC patients with high ACYP1 expression showed significantly shorter overall survival and relapse-free survival rates concomitant with increased infiltration of CD4+ T cells. Mouse subcutaneous tumors with ACYP1 overexpression exhibited significantly accelerated tumor progression with increased aggregation of CD4+ T cells.ConclusionOverall, ACYP1 may serve as a vital prognostic biomarker and play an immunoregulatory role in LIHC.
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