A Novel Approach for the Optimal Design of a Biosensor

Daphnia's phototaxis as an indicator in ecotoxicological studies: A review

Animal-based sensors have been increasingly applied to many water monitoring systems and ecological studies. One of the staple organisms used as living sensors for such systems is Daphnia. This organism has been extensively studied and, with time, used in many toxicological and pharmaceutical bioassays, often used for exploring the ecology of freshwater communities. One of its behaviours used for evaluating the state of the aquatic environment is phototaxis. A disruption in the predicted behaviour is interpreted as a sign of stress and forms the basis for further investigation. However, phototaxis is a result of complex processes counteracting and interacting with each other. Predator presence, food quality, body pigmentation and other factors can greatly affect the predicted phototactic response, hampering its reliability as a bioindicator. Therefore, a holistic approach and meticulous documentation of the methods are needed for the correct interpretation of this behavioural indicator. In this review, we present the current methods used for studying phototaxis, the factors affecting it and proposed ways to optimise the reliability of the results.

High-Sensitivity Liquid Dielectric Characterization Differential Sensor by 1-Bit Coding DGS

This paper presents two devices to detect the liquid dielectric characterization. The differential method was used to enhance the robustness and reduce tolerance. A basic sensor based on defected ground structure (DGS) was designed and the optimization for the squares of the DGS via adaptive genetic algorithm was applied to enhance the performance of the microwave sensor, which was shown by the difference of the two resonant frequencies. Furthermore, the electric field distribution was enhanced. Glass microcapillary tubes were used to hold samples to provide an environment of non-invasive. The optimized device exhibited the sensitivity of 0.076, which is more than 1.52 times than the basic structure. It could be considered a sensitive and robust sensor with quick response time for liquid dielectric characterization.

Detection of multiplex exosomal miRNAs for clinically accurate diagnosis of Alzheimer's disease using label-free plasmonic biosensor based on DNA-Assembled advanced plasmonic architecture

Alzheimer's disease (AD), the most common neurologic disorder, is characterized by progressive cognitive impairment. However, the low clinical significance of the currently used core AD biomarkers amyloid-beta and tau proteins remains a challenge. Recently, exosomes, found in human biological fluids, are gaining increasing attention because of their clinical significance in diagnosing of various diseases. In particular, blood-derived exosomal miRNAs are not only stable but also provide information regarding the different characteristics according to AD progression. However, quantitative and qualitative detection is difficult due to their characteristics, such as small size, low abundance, and high homology. Here, we present a DNA-assembled advanced plasmonic architecture (DAPA)-based plasmonic biosensor to accurately detect exosomal miRNAs in human serum. The designed nanoarchitecture possesses two narrow nanogaps that induce plasmon coupling; this significantly enhances its optical energy density, resulting in a 1.66-fold higher refractive-index (RI) sensitivity than nanorods at localized surface plasmon resonance (LSPR). Thus, the proposed biosensor is ultrasensitive and capable of selective single-nucleotide detection of exosomal miRNAs at the attomolar level. Furthermore, it identified AD patients from healthy controls by measuring the levels of exosomal miRNA-125b, miRNA-15a, and miRNA-361 in clinical serum samples. In particular, the combination of exosomal miRNA-125b and miRNA-361 showed the best diagnostic performance with a sensitivity of 91.67%, selectivity of 95.00%, and accuracy of 99.52%. These results demonstrate that our sensor can be clinically applied for AD diagnosis and has great potential to revolutionize the field of dementia research and treatment in the future.