Substrate-Free Untagged Detection of miR393a Using an Ultrasensitive Electrochemical Biosensor

Machine learning provides specific detection of salt and drought stresses in cucumber based on miRNA characteristics

BACKGROUND

Specific detection of the type and severity of plant abiotic stresses helps prevent yield loss by considering timely actions. This study introduces a novel method to detect the type and severity of stress in cucumber plants under salinity and drought conditions. Various features, i.e., morphological (image textural features), physiological/biochemical (relative water content, chlorophyll, catalase activity, anthocyanins, phenol content, and proline), as well as miRNA characteristics (the concentration of miRNA-156a, miRNA-166i, miRNA-399g, and miRNA-477b) were extracted from plant leaves, and machine learning methods were used to predict the type and severity of stress by having these features. Support vector machine (SVM) with parameters optimized by genetic algorithm (GA) and particle swarm optimization (PSO) was used for machine learning.

RESULTS

The coefficient of determination of predicting the stress type and severity in plants under both stresses was 0.61, 0.82, and 0.99 using morphological, physiological/biochemical, and miRNA characteristics, respectively. This reveals machine learning methods optimized by metaheuristic optimization techniques can provide specific detection of salt and drought stresses in cucumber plants based on miRNA characteristics. Among the study miRNAs, miRNA-477b and miRNA-399g had the highest and lowest contribution to salt and drought stresses, respectively.

CONCLUSIONS

Comapred to conventional plant traits, miRNAs are more reliable features for providing us with valuable information about plant abiotic diseases at early stages. Using an electrochemical miRNA biosensor similar to one used in this work to measure the miRNA concentration in plant leaves and using a machine learning algorithm such as SVM enable farmers to detect the salt and drought stress at early stages in cucumber plants with very high accuracy.

MicroRNA Regulation in Infectious Diseases and Its Potential as a Biosensor in Future Aquaculture Industry: A Review

An infectious disease is the most apprehensive problem in aquaculture as it can lead to high mortality in aquatic organisms and massive economic loss. Even though significant progress has been accomplished in therapeutic, prevention, and diagnostic using several potential technologies, more robust inventions and breakthroughs should be achieved to control the spread of infectious diseases. MicroRNA (miRNA) is an endogenous small non-coding RNA that post-transcriptionally regulates the protein-coding genes. It involves various biological regulatory mechanisms in organisms such as cell differentiation, proliferation, immune responses, development, apoptosis, and others. Furthermore, an miRNA also acts as a mediator to either regulate host responses or enhance the replication of diseases during infection. Therefore, the emergence of miRNAs could be potential candidates for the establishment of diagnostic tools for numerous infectious diseases. Interestingly, studies have revealed that miRNAs can be used as biomarkers and biosensors to detect diseases, and can also be used to design vaccines to attenuate pathogens. This review provides an overview of miRNA biogenesis and specifically focuses on its regulation during infection in aquatic organisms, especially on the host immune responses and how miRNAs enhance the replication of pathogens in the organism. In addition to that, we explored the potential applications, including diagnostic methods and treatments, that can be employed in the aquaculture industry.

Chlorambucil-Loaded Graphene-Oxide-Based Nano-Vesicles for Cancer Therapy

In this study, the authors have designed biocompatible nano-vesicles using graphene oxide (GO) for the release of chlorambucil (CHL) drugs targeting cancerous cells. The GO sheets were first sulfonated and conjugated with folic acid (FA) molecules for controlled release and high loading efficiency of CHL. The chlorambucil (CHL) drug loading onto the functionalized GO surface was performed through π-π stacking and hydrophobic interactions with the aromatic planes of GO. The drug loading and "in vitro" release from the nano-vesicles at different pH were studied. The average particle size, absorption, and loading efficiency (%) of FA-conjugated GO sheets (CHL-GO) were observed to be 300 nm, 58%, and 77%, respectively. The drug release study at different pH (i.e., 7.4 and 5.5) showed a slight deceleration at pH 7.4 over pH 5.5. The amount of drug released was very small at pH 7.4 in the first hour which progressively increased to 24% after 8 h. The rate of drug release was faster at pH 5.5; initially, 16% to 27% in the first 3 h, and finally it reached 73% after 9 h. These observations indicate that the drug is released more rapidly at acidic pH with a larger amount of drug-loading ability. The rate of drug release from the CHL-loaded GO was 25% and 75% after 24 h. The biotoxicity study in terms of % cell viability of CHL-free and CHL-loaded GO against human cervical adenocarcinoma cell line was found to have lower cytotoxicity of CHL-loaded nano-vesicles (IC₅₀ = 18 μM) as compared to CHL-free (IC₅₀ = 8 μM). It is concluded that a high drug-loading efficiency and controlled release with excellent biotoxicity of CHL-GO offers an excellent application in the biomedical field.