Prostate cancer (PC) is the sixth most common cancer type in the world, which causes approximately 10% of total cancer fatalities. The detection of protein biomarkers in body fluids is the key topic for the diagnosis and prognosis of PC. Highly sensitive screening of PC is the most effective approach for reducing mortality. Thus, there are a growing number of literature that recognizes the importance of new technologies for early diagnosis of PC. Graphene is playing an important role in the biosensor field with remarkable physical, optical, electrochemical and magnetic properties. Many recent studies demonstrated the potential of graphene materials for sensitive detection of protein biomarkers. In this review, the graphene-based biosensors toward PC analysis are mainly discussed in two groups: Firstly, novel biosensor interfaces were constructed through the modification of graphene materials onto sensor surfaces. Secondly, ingenious signal amplification strategies were developed using graphene materials as catalysts or carriers. Graphene-based biosensors have exhibited remarkable performance with high sensitivities, wide detection ranges, and long-term stabilities.

Pb(II) can cause serious damaging effects to human health, and thus, the study of Pb²⁺ detection methods to sensitively and selectively monitor Pb(II) pollution has significant importance. In this work, we have developed a label-free fluorescence sensing strategy based on a Pb(II) DNAzyme cleavage and the ThT/G-quadruplex complex. In the presence of Pb(II), a G-rich tail was cut and released from the substrate strand, which then would form a G-quadruplex structure by combination with ThT dye. The fluorescence signal increase was then measured for sensitive Pb(II) quantification with a limit of detection of 0.06 nM. Our sensor also demonstrated high selectivity against six different metal ions, which is very important for the analysis of complex samples.

The accuracy and metrology traceability of DNA quantification is becoming a critical theme in many fields, including diagnosis, forensic analysis, microorganism detection etc. Thus the research of DNA reference materials (RMs) and consistency of DNA quantification methods has attracted considerable research interest. In this work, we developed 3 plasmid candidate RMs, containing 3 target genes of Escherichia coli O157:H7 (E. coli O157:H7) and other Shiga toxin-producing Escherichia coli (STEC): stx1, stx2, and fliC (h7) respectively. Comprehensive investigation of the plasmid RMs was performed for their sequence, purity, homogeneity and stability, and then the concentration was quantified by three different methods: ultraviolet spectrophotometer (UV), high resolution inductively coupled plasma mass spectrometry (HR-ICP-MS) and digital PCR. As a routinely applied method for DNA analysis, UV was utilized for the quantification (OD260) and purity analysis for the plasmids. HR-ICP-MS quantified the plasmid DNA through analysing the phosphorus in DNA molecules. Digital PCR distributed the DNA samples onto a microarray chip containing thousands of reaction chambers, and quantified the DNA copy numbers by analysing the number of positive signals without any calibration curves needed. Based on the high purification of the DNA reference materials and the optimization of dPCR analysis, we successfully achieved good consistency between UV, HR-ICP-MS and dPCR, with relative deviations lower than 10 %. We then performed the co-quantification of 3 DNA RMs with three different methods together, and the uncertainties of their concentration were evaluated. Finally, the certified values and expanded uncertainties for 3 DNA RMs (pFliC, pStx1 and pStx2) were (1.60 ± 0.10) × 1010 copies/μL, (1.53 ± 0.10) × 1010 copies/μL and (1.70 ± 0.11) × 1010 copies/μL respectively.

Intracellular enzyme cascades are essential for various biological processes, and mimicking their functions in artificial systems has attracted significant research attention. However, achieving convenient and efficient spatial organization of enzymes on interfaces remains a critical challenge. In this work, we designed a simple single-DNA scaffold using triblock polyA single-stranded DNA for the arrangement of coupled enzymes. The scaffold was assembled onto a gold electrode through the affinity of polyA-Au, and two enzymes (glucose oxidase and horseradish peroxidase) were captured through hybridization. The molecular distance between the enzymes was regulated by changing the length of the polyA fragment. As a proof of concept, a glucose biosensor was constructed based on the enzyme cascade amplification. The biosensor exhibited excellent detection capability for glucose in human serum samples with a limit of detection of 1.6 μM. Additionally, a trienzyme cascade reaction was successfully activated, demonstrating the potential scalability of our approach for multienzyme reactions. This study provides a promising platform for the development of easy-to-operate, highly efficient, and versatile enzyme cascade systems using DNA scaffolds.

The discrimination and recognition of biological targets, such as proteins, cells, and bacteria, are of utmost importance in various fields of biological research and production. These include areas like biological medicine, clinical diagnosis, and microbiology analysis. In order to efficiently and cost-effectively identify a specific target from a wide range of possibilities, researchers have developed a technique called differential sensing. Unlike traditional “lock-and-key” sensors that rely on specific interactions between receptors and analytes, differential sensing makes use of cross-reactive receptors. These sensors offer less specificity but can cross-react with a wide range of analytes to produce a large amount of data. Many pattern recognition strategies have been developed and have shown promising results in identifying complex analytes. To create advanced sensor arrays for higher analysis efficiency and larger recognizing range, various nanomaterials have been utilized as sensing probes. These nanomaterials possess distinct molecular affinities, optical/electrical properties, and biological compatibility, and are conveniently functionalized. In this review, our focus is on recently reported optical sensor arrays that utilize nanomaterials to discriminate bioanalytes, including proteins, cells, and bacteria.