A novel nanoparticle-based fluorescent sandwich immunoassay for specific detection of Salmonella Typhimurium.

The diseases caused by foodborne pathogens have a serious impact on human health and social stability. Conventional detection methods can involve long assay times and complex pretreatment steps, making them unsuitable for rapid, large-scale analysis of food samples. We constructed a novel nano-fluorescence sandwich immunosorbent immunoassay (nano-FSIA) to rapidly detect Salmonella Typhimurium in food, based on strong covalent binding between streptavidin and biotin.

Quantitative analysis of respiratory viruses based on lab-on-a-chip platform.

The quantitative analysis of respiratory viruses is of great importance for rapid diagnosis, precision medicine, and prognosis. Several current quantitative analysis systems have been proposed and commercialized. Although they have been proven in trials, quantitative analyzes based on real samples are still complex, time-consuming, and expensive.

Highly sensitive digital detection of SARS-CoV-2 nucleocapsid protein through single-molecule counting.

Nucleocapsid protein (NP) is one of the structural proteins of SARS-CoV-2 which is stable, well-conserved, highly immunogenic, and abundantly expressed due to the host's adaptive immune response, making it a promising antigenic biomarker for the early and rapid identification and diagnosis of SARS-CoV-2. Traditional antigen analytical methods with NP as the detection marker often have insufficient sensitivity. To achieve rapid and highly sensitive detection of NP, we constructed a novel single-molecule (digital) fluorescence-linked immunosorbent assay (FLISA) based on streptavidin-modified transparent 96-well microplates.

Fabrication of planar monolayer microreactor array for visual statistical analysis and droplet-based digital quantitative analysis in situ.

Planar monolayer microreactor arrays (PMMRAs) make droplet-based numerical measurements and statistical analysis cheap and easy. However, PMMRAs are typically produced in complex microfluidic devices and, moreover, still requires stringent control to reduce droplet loss during heating. In this paper, a simple, reliable, and flexible method for fabricating PMMRAs in a 96-well plate is described in detail by using simple materials and low-cost equipment.

A self-contained and integrated microfluidic nano-detection system for the biosensing and analysis of molecular interactions.

Traditional detection methods have shortcomings such as time-consumption and requirement of large instruments, which cannot meet the demands for on-site detection or analysis. Silicon nanowire-field-effect transistor (SiNW-FET) biosensors have the advantages of high speed, high sensitivity, strong specificity, and ease of integration. However, SiNW-FET biosensors also have some demerits: they are too sensitive, environmental factors such as light, temperature, and pH easily cause interference, and their performance uniformity needs to be calibrated in advance.

Overview and Future Perspectives of Microfluidic Digital Recombinase Polymerase Amplification (dRPA).

Digital recombinase polymerase amplification (dRPA) aims to quantify the initial amount of nucleic acid by dividing nucleic acid and all reagents required for the RPA reaction evenly into numerous individual reaction units, such as chambers or droplets. dRPA turns out to be a prominent technique for quantifying the absolute quantity of target nucleic acid because of its advantages including low equipment requirements, short time consumption, as well as high sensitivity and specificity. dRPA combined with microfluidics are recognized as simple, various, and high-throughput nucleic acid quantization systems.

Test Article for automation purposes.

Digital recombinase polymerase amplification (dRPA) aims to quantify the initial amount of nucleic acid by dividing nucleic acid and all reagents required for the RPA reaction evenly into numerous individual reaction units, such as chambers or droplets. dRPA turns out to be a prominent technique for quantifying the absolute quantity of target nucleic acid because of its advantages including low equipment requirements, short time consumption, as well as high sensitivity and specificity. dRPA combined with microfluidics are recognized as simple, various, and high-throughput nucleic acid quantization systems.

Particle Self-Aligning, Focusing, and Electric Impedance Microcytometer Device for Label-Free Single Cell Morphology Discrimination and Yeast Budding Analysis.

Microfluidic electric impedance flow cytometry (IFC) devices have been applied in single cell analysis, such as cell counting, volume discrimination, cell viability, etc. A cell's shape provides specific information about cellular physiological and pathological conditions, especially in microorganisms such as yeast. In this study, the particle orientation focusing was theoretically analyzed and realized by hydrodynamics.

[Development of a microenvironment test chamber for airborne microbe research].

One of the most important environmental cleanliness indicators is airborne microbe. However, the particularity of clean operating environment and controlled experimental environment often leads to the limitation of the airborne microbe research. This paper designed and implemented a microenvironment test chamber for airborne microbe research in normal test conditions.

[Analysis and Optimization of the Temperature Retard between Sample and Air Based on Nucleic Acid Amplification System Heated by Air].

It is the main method for amplifying the specific gene to use the nucleic acid amplification system to accomplish polymerase chain reaction(PCR).The temperature retard between heat source and sample exists in the heating and cooling progresses of most nucleic acid amplification system.The retard would result in the problem that the sample would take a long time to reach the set temperature and the problem would reduce the speed of integrate reaction.

Prediction of protein subcellular location using a combined feature of sequence.

To understand the structure and function of a protein, an important task is to know where it occurs in the cell. Thus, a computational method for properly predicting the subcellular location of proteins would be significant in interpreting the original data produced by the large-scale genome sequencing projects. The present work tries to explore an effective method for extracting features from protein primary sequence and find a novel measurement of similarity among proteins for classifying a protein to its proper subcellular location.