In this work, sensitive detection of dengue virus type 2 E-proteins (DENV-2 E-proteins) was performed in the range of 0.08 pM to 0.5 pM. The successful DENV detection at very low concentration is a matter of concern for targeting the early detection after the onset of dengue symptoms. Here, we developed a SPR sensor based on self-assembled monolayer/reduced graphene oxide-polyamidoamine dendrimer (SAM/NH₂rGO/PAMAM) thin film to detect DENV-2 E-proteins. Surface characterizations involving X-ray diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR) confirms the incorporation of NH₂rGO-PAMAM nanoparticles in the prepared sensor films. The specificity, sensitivity, binding affinity, and selectivity of the SPR sensor were then evaluated. Results indicated that the variation of the sensing layer due to different spin speed, time incubation, and concentration provided a better interaction between the analyte and sensing layer. The linear dependence of the SPR sensor showed good linearity (R² = 0.92) with the lowest detection of 0.08 pM DENV-2 E-proteins. By using the Langmuir model, the equilibrium association constant was obtained at very high value of 6.6844 TM⁻¹ (R² = 0.99). High selectivity of the SPR sensor towards DENV-2 E-proteins was achieved in the presence of other competitors.

Uric acid (UA), dopamine (DA) and ascorbic acid (AA) exist in the human body as protein metabolism, neurotransmitter and antioxidant, respectively. The abnormal levels of UA, DA and AA could lead to certain diseases and it could be measured and determined using electrochemical sensors. UA, DA and AA have close oxidation potentials and cause overlapping peaks in electrochemical measurements. Researchers have been working on electrode modification by using different materials to overcome those challenges and improve their selectivity, sensitivity and limit of detection. This review aims to highlight the performance of modified electrochemical sensors for detection of UA, DA and AA individually or simultaneously.

This paper unequivocally examines the production of carbon quantum dots from biomass waste, such as palm kernel shells and oyster shells, and their application in bioimaging. We also prepared carbon quantum dots from citric acid as a comparison.