Colorimetric Sensor Array for White Wine Tasting.

A colorimetric sensor array was developed to characterize and quantify the taste of white wines. A charge-coupled device (CCD) camera captured images of the sensor array from 23 different white wine samples, and the change in the R, G, B color components from the control were analyzed by principal component analysis. Additionally, high performance liquid chromatography (HPLC) was used to analyze the chemical components of each wine sample responsible for its taste. A two-dimensional score plot was created with 23 data points. It revealed clusters created from the same type of grape, and trends of sweetness, sourness, and astringency were mapped. An artificial neural network model was developed to predict the degree of sweetness, sourness, and astringency of the white wines. The coefficients of determination (R2) for the HPLC results and the sweetness, sourness, and astringency were 0.96, 0.95, and 0.83, respectively. This research could provide a simple and low-cost but sensitive taste prediction system, and, by helping consumer selection, will be able to have a positive effect on the wine industry.

Smartphone-Based Paper Microfluidic Immunoassay of Salmonella and E. coli.

Previous studies from our lab have created a simple procedure for single-cell count of bacteria on a paper chip platform using optical detection from a smartphone. The procedure and steps employed are outlined along with the lessons learned and details of certain steps and how the design was optimized. Smartphone optical detection is easy to use, low cost, and potentially field deployable, which can be useful for early and rapid detection of pathogens. Smartphone imaging of a paper microfluidic chip preloaded with antibody-conjugated particles provides an adaptable platform for detection of different bacterial targets. The paper microfluidic chip was fabricated with a multichannel design. Each channel was preloaded with either a negative control of bovine serum albumin (BSA) conjugated particles, anti-Salmonella Typhimurium-conjugated particles with varying amounts (to cover different ranges of assay), or anti-Escherichia coli-conjugated particles. Samples were introduced to the paper microfluidic chip using pipetting. Antigens of Salmonella Typhimurium traveled through the channel by capillary action confined within the paper fibers surrounded by the hydrophobic barrier. The paper channel was observed to act as a filter for unwanted particles and contaminants found in field samples. Serial dilutions of known concentrations of bacterial targets were also tested using this procedure to construct a standard curve prior to the assays. The antibody-conjugated particles were able to immunoagglutinate which was quantified through evaluation of Mie scatter intensity. This Mie scattering was quantified in images taken with a smartphone at an optimized angle and distance. Mie scatter simulation provided a method of optimizing the experimental setup and could translate easily to other types of target sample matrices. A smartphone application was developed to help the user position the smartphone optimally in relation to the paper microfluidic chip. The application integrated both image capturing capability and a simple image processing algorithm that calculated bacteria concentrations. The detection limit was at a single-cell level with a total assay time ranging from 90 to less than 60 s depending on the target.

Smartphone Detection of UV LED-Enhanced Particle Immunoassay on Paper Microfluidics.

Use of a smartphone as an optical detector for paper microfluidic devices has recently gained substantial attention due to its simplicity, ease of use, and handheld capability. Utilization of a UV light source enhances the optical signal intensities, especially for the particle immunoagglutination assay that has typically used visible or ambient light. Such enhancement is essential for true assimilation of assays to field deployable and point-of-care applications by greatly reducing the effects by independent environmental factors. This work is the first demonstration of using a UV LED (UVA) to enhance the Mie scatter signals from the particle immunoagglutination assay on the paper microfluidic devices and subsequent smartphone detection. Smartphone's CMOS camera can recognize the UVA scatter from the paper microfluidic channels efficiently in its green channel. For an Escherichia coli assay, the normalized signal intensities increased up to 50% from the negative signal with UV LED, compared with the 4% to 7% with ambient light. Detection limit was 10 colony-forming units/mL. Similar results were obtained in the presence of 10% human whole blood.

Multi-Normalization and Interpolation Protocol to Improve Norovirus Immunoagglutination Assay from Paper Microfluidics with Smartphone Detection.

Norovirus (NoV) is one of the leading causes of acute gastroenteritis, affecting 685 million people per year around the world. The best preventive measure is to screen water for possible NoV contamination, not from infected humans, preferably using rapid and field-deployable diagnostic methods. While enzyme immunoassays (EIAs) can be used for such detection, the low infectious dose as well as the generally inferior sensitivity and low titer of available NoV antibodies render critical challenges in using EIAs toward NoV detection. In this work, we demonstrated smartphone-based Mie scatter detection of NoV with immunoagglutinated latex particles on paper microfluidic chips. Using only three different concentrations of anti-NoV-conjugated particles, we were able to construct a single standard curve that covered seven orders of magnitude of NoV antigen concentrations. Multiple normalization steps and interpolation procedures were developed to estimate the optimum amount of antibody-conjugated particles that matched to the target NoV concentration. A very low detection limit of 10 pg/mL was achieved without using any concentration or enrichment steps. This method can also be adapted for detection of any other virus pathogens whose antibodies possess low sensitivity and low antibody titer.

Smartphone-based, sensitive µPAD detection of urinary tract infection and gonorrhea.

The presence of bacteria in urine can be used to monitor the onset or prognosis of urinary tract infection (UTI) and some sexually-transmitted diseases (STDs), such as gonorrhea. Typically, bacteria's presence in urine is confirmed by culturing samples overnight on agar plates, followed by a microscopic examination. Additionally, the presence of Escherichia coli in a urine sample can be indirectly confirmed through assaying for nitrite (generated by reducing nitrate in urine), however this is not sufficiently specific and sensitive. Species/strains identification of bacteria in a urine sample provides insight to appropriate antibiotic treatment options. In this work, a microfluidic paper analytical device (µPAD) was designed and fabricated for evaluating UTI (E. coli) and STD (Neisseria gonorrhoeae) from human urine samples. Anti-E. coli or anti-N. gonorrhoeae antibodies were conjugated to submicron particles then pre-loaded and dried in the center of each paper microfluidic channel. Human urine samples (undiluted) spiked with E. coli or N. gonorrhoeae were incubated for 5 min with 1% Tween 80. The bacteria-spiked urine samples were then introduced to the inlet of paper microfluidic channel, which flowed through the channel by capillary force. Data confirms that proteins were not filtered by µPAD, which is essential for this assay. Urobilin, the component responsible for the yellow appearance of urine and green fluorescence emission, was filtered by µPAD, resulting in significantly minimized false-positive signals. This filtration was simultaneously made during the µPAD assay and no pretreatment/purification step was necessary. Antibody-conjugated particles were immunoagglutinated at the center of the paper channel. The extent of immunoagglutination was quantified by angle-specific Mie scatter under ambient lighting conditions, utilizing a smartphone camera as a detector. The total µPAD assay time was less than 30s. The detection limit was 10 CFU/mL for both E. coli and N. gonorrhoeae, while commercially available gonorrhea rapid kit showed a detection limit of 10(6) CFU/mL. A commercially available nitrite assay test strip also had a detection limit of 10(6) CFU/mL, but this method is not antibody-based and thus not sufficiently specific. By optimizing the particle concentration, we were also able to extend the linear range of the assay up to 10(7) CFU/mL. The proposed prototype will serve as a low-cost, point-of-care, sensitive urinalysis biosensor to monitor UTI and gonorrhea from human urine.

Rapid and reagentless detection of microbial contamination within meat utilizing a smartphone-based biosensor.

A smartphone-utilized biosensor was developed for detecting microbial spoilage on ground beef, without using antibodies, microbeads or any other reagents, towards a preliminary screening tool for microbial contamination on meat products, and potentially towards wound infection. Escherichia coli K12 solutions (10(1)-10(8) CFU/mL) were added to ground beef products to simulate microbial spoilage. An 880 nm near infrared LED was irradiated perpendicular to the surface of ground beef, and the scatter signals at various angles were evaluated utilizing the gyro sensor and the digital camera of a smartphone. The angle that maximized the Mie scatter varied by the E. coli concentration: 15° for 10(8) CFU/mL, 30° for 10(4) CFU/mL, and 45° for 10 CFU/mL, etc. SEM and fluorescence microscopy experiments revealed that the antigens and cell fragments from E. coli bonded preferably to the fat particles within meat, and the size and morphologies of such aggregates varied by the E. coli concentration.

Smartphone-based optofluidic lab-on-a-chip for detecting pathogens from blood.

A novel smartphone-based detection device was created to detect infectious pathogens directly from diluted (10%) human whole blood. The model pathogen was histidine-rich protein 2 (HRP-2), an antigen specific to Plasmodium falciparum (malaria). Anti-HRP-2-conjugated submicrobeads were mixed with HRP-2-infused 10% blood in a lab-on-a-chip device. The white LED flash and the digital camera of the smartphone were used as light source and detector, which delivered light to and from the bead and blood mixture via optofluidic channels in the lab-on-a-chip. The optofluidic channels were angled at 45 degrees to capture the Mie scatter from the sample. Considering the absorption and scattering characteristics of blood (red/infrared preferred) and the Mie scatter simulations for microbead immunoagglutination (UV preferred), blue detection showed the best results. The detection limit was 1 pg/mL in 10% blood. The linear range was from 1 pg/mL to 10 ng/mL. A handheld device, easily attachable to a single smartphone, was finally designed and fabricated using optical mirrors and lenses and successfully detected the HRP-2 from 10% blood. The total assay time was approximately 10 min. The proposed device can potentially be used for detecting a wide range of blood infection with high sensitivity.

Enhanced nucleic acid amplification with blood in situ by wire-guided droplet manipulation (WDM).

There are many challenges facing the use of molecular biology to provide pertinent information in a timely, cost effective manner. Wire-guided droplet manipulation (WDM) is an emerging format for conducting molecular biology with unique characteristics to address these challenges. To demonstrate the use of WDM, an apparatus was designed and assembled to automate polymerase chain reaction (PCR) on a reprogrammable platform. WDM minimizes thermal resistance by convective heat transfer to a constantly moving droplet in direct contact with heated silicone oil. PCR amplification of the GAPDH gene was demonstrated at a speed of 8.67 s/cycle. Conventional PCR was shown to be inhibited by the presence of blood. WDM PCR utilizes molecular partitioning of nucleic acids and other PCR reagents from blood components, within the water-in-oil droplet, to increase PCR reaction efficiency with blood in situ. The ability to amplify nucleic acids in the presence of blood simplifies pre-treatment protocols towards true point-of-care diagnostic use. The 16s rRNA hypervariable regions V3 and V6 were amplified from Klebsiella pneumoniae genomic DNA with blood in situ. The detection limit of WDM PCR was 1 ng/µL or 10(5)genomes/µL with blood in situ. The application of WDM for rapid, automated detection of bacterial DNA from whole blood may have an enormous impact on the clinical diagnosis of infections in bloodstream or chronic wound/ulcer, and patient safety and morbidity.

Cell-phone-based measurement of TSH using Mie scatter optimized lateral flow assays.

Semi-quantitative thyr oid stimulating hormone (TSH) lateral flow immunochromatographic assays (LFA) are used to screen for serum TSH concentration >5 mIUL(-1) (hypothyroidism). The LFA format, however, is unable to measure TSH in the normal range or detect suppressed levels of TSH (<0.4 mIU L(-1); hyperthyroidism). In fact, it does not provide quantitative TSH values at all. Obtaining quantitative TSH results, especially in the low concentration range, has until now required the use of centralized clinical laboratories which require specimen transport, specialized equipment and personnel, and result in increased cost and delays in the timely reporting of important clinical results. We have conducted a series of experiments to develop and validate an optical system and image analysis algorithm based upon a cell phone platform. It is able to provide point-of-care quantitative TSH results with a high level of sensitivity and reproducibility comparable to that of a clinical laboratory-based third-generation TSH immunoassay. Our research approach uses the methodology of the optimized Rayleigh/Mie scatter detection by taking into consideration the optical characteristics of a nitrocellulose membrane and gold nanoparticles on an LFA for quantifying TSH levels. Using a miniature spectrometer, LED light source, and optical fibers on a rotating benchtop apparatus, the light intensity from different angles of incident light and angles of detection to the LFA were measured. The optimum angles were found that the minimized Mie scattering from nitrocellulose membrane, consequently maximizes the Rayleigh scatter detection from the gold nanoparticles in the LFA bands. Using the results from the benchtop apparatus, a cell-phone-based apparatus was designed which utilized the embedded flash in the cell phone camera as the light source, piped the light with an optical fiber from the flash through a collimating lens to illuminate the LFA. Quantification of TSH was performed in an iOS application directly on the phone and verified using the code written in MATLAB. The limit of detection of the system was determined to be 0.31 mIU L(-1) (never achieved before on an LFA format), below the commonly accepted minimum concentration of 0.4 mIU L(-1) indicating clinical significance of hyperthyroidism. The system was further evaluated using human serum showing an accurate and reproducible platform for rapid and point-of-care quantification of TSH using a cell phone.

Smartphone quantifies Salmonella from paper microfluidics.

Smartphone-based optical detection is a potentially easy-to-use, handheld, true point-of-care diagnostic tool for the early and rapid detection of pathogens. Paper microfluidics is a low-cost, field-deployable, and easy-to-use alternative to conventional microfluidic devices. Most paper-based microfluidic assays typically utilize dyes or enzyme-substrate binding, while bacterial detection on paper microfluidics is rare. We demonstrate a novel application of smartphone-based detection of Salmonella on paper microfluidics. Each paper microfluidic channel was pre-loaded with anti-Salmonella Typhimurium and anti-Escherichia coli conjugated submicroparticles. Dipping the paper microfluidic device into the Salmonella solutions led to the antibody-conjugated particles that were still confined within the paper fibers to immunoagglutinate. The extent of immunoagglutination was quantified by evaluating Mie scattering from the digital images taken at an optimized angle and distance with a smartphone. A smartphone application was designed and programmed to allow the user to position the smartphone at an optimized angle and distance from the paper microfluidic device, and a simple image processing algorithm was implemented to calculate and display the bacterial concentration on the smartphone. The detection limit was single-cell-level and the total assay time was less than one minute.