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Bacterial infections in marine fishes are linked to mass mortality issues; hence, rapid detection of an infection can contribute to achieving a faster diagnosis using point-of-care testing. There has been substantial interest in identifying diagnostic biomarkers that can be detected in major organs to predict bacterial infections. Aspartate was identified as an important biomarker for bacterial infection diagnosis in olive flounder (Paralichthys olivaceus) fish. To determine aspartate levels, an amperometric biosensor was designed based on bi-enzymes, namely, glutamate oxidase (GluOx) and aspartate transaminase (AST), which were physisorbed on copolymer reduced graphene oxide (P-rGO), referred to as enzyme nanosheets (GluOx-ASTENs). The GluOx-ASTENs were drop casted onto a Prussian blue electrodeposited screen-printed carbon electrode (PB/SPCE). The proposed biosensor was optimized by operating variables including the enzyme loading amount, coreactant (α-ketoglutarate) concentration, and pH. Under optimal conditions, the biosensor displayed the maximum current responses within 10 s at the low applied potential of −0.10 V vs. the internal Ag/AgCl reference. The biosensor exhibited a linear response from 1.0 to 2.0 mM of aspartate concentrations with a sensitivity of 0.8 µA mM−1 cm−2 and a lower detection limit of approximately 500 µM. Moreover, the biosensor possessed high reproducibility, good selectivity, and efficient storage stability. [ABSTRACT FROM AUTHOR]

Glutamate (GLU) is a primary excitatory neurotransmitter, and its dysregulation is associated with several neurodegenerative disorders. A major challenge in GLU estimation is the existence of other biomolecules in the brain that could directly get oxidized at the electrode. Hence, highly selective electroenzymatic biosensors that enable rapid estimation of GLU are needed. Initially, a copolymer, poly(2-dimethylaminoethyl methacrylate- styrene) was synthesized through reversible addition-fragmentation chain transfer polymerization to noncovalently functionalize reduced graphene oxide (rGO), named DS–rGO. Glutamate oxidase macromolecule immobilized DS–rGO formed enzyme nanosheets, which was drop-coated over Prussian blue electrodeposited disposable electrodes to fabricate the GLU biosensor. The interconnectivity between the enzyme nanosheets and the Prussian blue endows the biosensor with enhanced conductivity and electrochemical activity. The biosensor exhibited a linearity: 3.25–250 μM; sensitivity: 3.96 μA mM−1 cm−2, and a limit of detection: 0.96 μM for GLU in the Neurobasal Medium. The biosensor was applied to an in vitro primary rat cortical model to discriminate GLU levels in Neurobasal Medium, before and after KCl mediated depolarization, which provides new insights for elucidating neuronal functioning in the brain. Amperometric biosensor for detecting GLU in the in vitro model of primary rat cortical neurons before and after KCl mediated depolarization. [Display omitted] [ABSTRACT FROM AUTHOR]

Bacterial infections in fish farms increase mass mortality and rapid detection of infection can help prevent its widespread. Lactate is an important biomarker for early diagnosis of bacterial infections in farmed olive flounder (Paralichthys olivaceus). To determine the lactate levels, we designed a disposable amperometric biosensor based on Prussian blue nanozyme and lactate oxidase (LOX) entrapped in copolymer-reduced graphene oxide (P-rGO) on screen-printed carbon electrodes. Because LOX is inherently unstable, P-rGO nanosheets were utilized as a base matrix to immobilize it. After optimization in terms of enzyme loading, operating potential, and pH, the biosensor displayed maximum current responses within 5 s at the applied potential of –0.1 V vs. internal Ag/AgCl. The biosensor had Langmuir-type response in the lactate concentration range from 10 µM to 1.6 mM, a dynamic linear response range of 10–100 µM, a sensitivity of 15.9 µA mM−1 cm−2, and a lower detection limit of 3.1 µM (S/N = 3). Additionally, the biosensor featured high reproducibility, good selectivity, and stability till four weeks. Its practical applicability was tested in olive flounder infected by Streptococcus parauberis against the uninfected control. The results were satisfactory compared to those of a standard colorimetric assay kit, validating our method. [ABSTRACT FROM AUTHOR]

A new disposable amperometric biosensor for sarcosine (Sar, a biomarker for prostate cancer) was designed based on screen-printed carbon electrodes, Prussian blue, polymer dispersed reduced graphene oxide (P-rGO) nanosheets, and sarcosine oxidase (SOx). Poly(sodium 4-styrenesulfonate- r -LAHEMA) denoted as PSSL was newly synthesized as dispersant for rGO. The P-rGO was utilized for SOx immobilization, the sulfonate and disulfide functionalities in PSSL enable physical adsorption of SOx and its bioactivity and stability properties were improved. The biosensor was optimized by various enzyme concentration, applied potential, and operating pH. Under the optimized conditions, the biosensor exhibited maximum current responses within 5 s at an applied potential of −0.1 V vs. integrated Ag/AgCl reference electrode. The biosensor had a dynamic linear range of 10–400 μM, with a sensitivity of 9.04 μA mM−1 cm−2 and a low detection limit of 0.66 μM (S/N = 3). Additionally, the biosensor possesses strong anti-interference capability, high reproducibility, and storage stability over 3 weeks. Furthermore, its clinical applicability was tested in urine samples from both prostate cancer patients and healthy control, and the analytical recoveries were satisfactory. Therefore, this biosensor has significant potential in the rapid and non-invasive point-of-care testing for prostate cancer diagnosis. [Display omitted] • A new polymer dispersant synthesized to disperse reduced graphene oxide (P-rGO). • P-rGO and Prussian blue utilized for amperometric sarcosine biosensor. • SOxENs prepared using P-rGO and sarcosine oxidase (SOx). • High selectivity against major interferents in human urine. • The designed biosensor is more suitable for non-invasive prostate cancer diagnosis. [ABSTRACT FROM AUTHOR]