Culture-Free Quantification of Bacteria Using Digital Fluorescence Imaging in a Tunable Magnetic Capturing Cartridge for Onsite Food Testing.

Accurate, onsite detection of pathogenic bacteria from food matrices is required to rapidly respond to pathogen outbreaks. However, accurately detecting whole-cell bacteria in large sample volumes without an enrichment step remains a challenge. Therefore, bacterial samples must be concentrated, identified, and quantified. We developed a tunable magnetic capturing cartridge (TMCC) and combined it with a portable digital fluorescence reader for quick, onsite, quantitative detection of Staphylococcus aureus. The TMCC platform integrates an absorption pad impregnated with water-soluble polyvinyl alcohol (PVA) with an injection-molded polycarbonate (PC) plate that has a hard magnet on its back and an acrylonitrile-butadiene-styrene case. An S. aureus-specific antibody conjugated with magnetic nanoparticles was used to concentrate bacteria from a large-volume sample and capture bacteria within the TMCC. The retention time for capturing bacteria on the TMCC was adjusted by controlling the concentration and volume of the PVA solution. Concentrated bacterial samples bound to target-specific aptamer probes conjugated with quantum dots were loaded into the TMCC for a controlled time, followed by attachment of the bacteria to the PC plate and removal of unbound aptamer probes with wash buffer. The captured bacteria were quantified using a digital fluorescence reader equipped with an embedded program that automatically counts fluorescently tagged bacteria. The bacterial count made using the TMCC was comparable to a standard plate count (R2 = 0.9898), with assay sensitivity and specificity of 94.3 and 100%, respectively.

An Acquisition Method for Visible and Near Infrared Images from Single CMYG Color Filter Array-Based Sensor.

Near-infrared (NIR) images are very useful in many image processing applications, including banknote recognition, vein detection, and surveillance, to name a few. To acquire the NIR image together with visible range signals, an imaging device should be able to simultaneously capture NIR and visible range images. An implementation of such a system having separate sensors for NIR and visible light has practical shortcomings due to its size and hardware cost. To overcome this, a single sensor-based acquisition method is investigated in this paper. The proposed imaging system is equipped with a conventional color filter array of cyan, magenta, yellow, and green, and achieves signal separation by applying a proposed separation matrix which is derived by mathematical modeling of the signal acquisition structure. The elements of the separation matrix are calculated through color space conversion and experimental data. Subsequently, an additional denoising process is implemented to enhance the quality of the separated images. Experimental results show that the proposed method successfully separates the acquired mixed image of visible and near-infrared signals into individual red, green, and blue (RGB) and NIR images. The separation performance of the proposed method is compared to that of related work in terms of the average peak-signal-to-noise-ratio (PSNR) and color distance. The proposed method attains average PSNR value of 37.04 and 33.29 dB, respectively for the separated RGB and NIR images, which is respectively 6.72 and 2.55 dB higher than the work used for comparison.

A fully integrated bacterial pathogen detection system based on count-on-a-cartridge platform for rapid, ultrasensitive, highly accurate and culture-free assay.

Rapid, sensitive and accurate point-of-care-testing (POCT) of bacterial load from a variety of samples can help prevent human infections caused by pathogenic bacteria and mitigate their spreading. However, there is an unmet demand for a POCT device that can detect extremely low concentrations of bacteria in raw samples. Herein, we introduce the 'count-on-a-cartridge' (COC) platform for quantitation of the food-borne pathogenic bacteria Staphylococcus aureus. The system comprised of magnetic concentrator, sensing cartridge and fluorescent image reader with a built-in counting algorithm facilitated fluorescent microscopic bacterial enumeration in user-convenient manner with high sensitivity and accuracy within a couple of hours. The analytical performance of this assay is comparable to that of a standard plate count. The COC assay shows a sensitivity of 92.9% and specificity of 100% performed according to global microbiological criteria for S. aureus which is acceptable below 100 CFU/g in the food matrix. This culture-independent, rapid, ultrasensitive and highly accurate COC assay has great potential for places where prompt bacteria surveillance is in high demand.

A smartphone fluorescence imaging-based mobile biosensing system integrated with a passive fluidic control cartridge for minimal user intervention and high accuracy.

A key challenge for realizing mobile device-based on-the-spot environmental biodetection is that a biosensor integrated with a fluid handling sensor cartridge must have acceptable accuracy comparable to that of conventional standard analytical methods. Furthermore, the user interface must be easy to operate, technologically plausible, and concise. Herein, we introduced an advanced smartphone imaging-based fluorescence microscope designed for Hg2+ monitoring by utilizing a biosensor cartridge that reduced user intervention via time-sequenced passive fluid handling. The cartridge also employed a metal-nanostructured plastic substrate for complementing the fluorescence signal output; this helped the realization of high-accuracy detection, in which a ratiometric dual-wavelength detection method was applied. Using 30 samples of Hg2+-spiked wastewater, we showed that our device, which has a detection limit of ∼1 pM, can perform analytical assays accurately. The detection results from our method were in good linearity and agreement with those of conventional standard methods. We conclude that the integration of a simple-to-use biosensor cartridge, fluorescence signal-enhancing substrate, dual-wavelength detection, and quantitative image data processing on a smartphone has great potential to make any population accessible to small-molecule detection, which has been performed in centralized laboratories for environmental monitoring.