Direct Capture and Early Detection of Lyme Disease Spirochete in Skin with a Microneedle Patch.

Borrelia burgdorferi sensu lato family of spirochetes causes Lyme disease (LD) in animals and humans. As geographic territory of ticks expands across the globe, surveillance measures are needed to measure transmission rates and provide early risk testing of suspected bites. The current standard testing of LD uses an indirect two-step serological assay that detects host immune reactivity. Early detection remains a challenge because the host antibody response develops several weeks after infection. A microneedle (MN) device was developed to sample interstitial fluid (ISF) and capture spirochetes directly from skin. After sampling, the MN patch is easily dissolved in water or TE buffer, and the presence of spirochete DNA is detected by PCR. Performance was tested by spiking porcine ear skin with inactivated Borrelia burgdorferi, which had an approximate recovery of 80% of spirochetes. With further development, this simple direct PCR method could be a transformative approach for early detection of the causative agent of Lyme disease and enable rapid treatment to patients when infection is early, and numbers of systemic spirochetes are low.

A multi-channel smartphone-based spectroscopic system for high-throughput biosensing in low-resource settings.

Primary healthcare centers (PHC) are the first point of contact for people in low-resource settings, and laboratory services play a critical role in early diagnosis of any disease. In recent years, several smartphone-based spectroscopic systems have been demonstrated to translate lab-confined healthcare applications into point-of-care environments to improve their accessibility. Due to constraints, such as the low availability of skilled personnel and consumables in a PHC, batch processing would be ideal for a large number of samples. Therefore, high-throughput and multi-channel detection is equally critical as affordability and portability. To date, most point-of-care systems are designed to perform a single type of analysis at a time. Herein, we introduce a smartphone-based spectroscopic system based on the use of line-beam illumination to achieve high-throughput sensing (15 channels simultaneously) within a 3d-printed microfluidic device. We also developed a smartphone application to process the spectral data and provide the results in real-time. Bland-Altman analysis revealed that the proposed device performs similarly to a laboratory spectrophotometer. The availability of the developed system will enable detection of multiple samples rapidly in low-resource settings with the existing limited manpower and infrastructures. The fast turnaround time may eventually help in timely diagnosis of patients during situations of high sample load, such as during disease outbreaks.

Recurrence monitoring for ovarian cancer using a cell phone-integrated paper device to measure the ovarian cancer biomarker HE4/CRE ratio in urine.

Ovarian cancer has a poor cure rate and rates of relapse are high. Current recurrence detection is limited by non-specific methods such as blood testing and ultrasound. Based on reports that human epididymis four (HE4) / creatinine (CRE) ratios found in urine are elevated in ovarian cancers, we have developed a paper-based device that combines lateral flow technology and cell phone analysis to quantitatively measure HE4/CRE. Surrogate samples were used to test the performance over clinically expected HE4/CRE ratios. For HE4/CRE ratios of 2 to 47, the percent error was found to be 16.0% on average whether measured by a flatbed scanner or cell phone. There was not a significant difference between the results from the cell phone or scanner. Based on published studies, error in this method was less than the difference required to detect recurrence. This promising new tool, with further development, could be used at home or in low-resource settings to provide timely detection of ovarian cancer recurrence.

Low-Cost, Volume-Controlled Dipstick Urinalysis for Home-Testing.

Dipstick urinalysis provides quick and affordable estimations of multiple physiological conditions but requires good technique and training to use accurately. Manual performance of dipstick urinalysis relies on good human color vision, proper lighting control, and error-prone, time-sensitive comparisons to chart colors. By automating the key steps in the dipstick urinalysis test, potential sources of error can be eliminated, allowing self-testing at home. We describe the steps necessary to create a customizable device to perform automated urinalysis testing in any environment. The device is cheap to manufacture and simple to assemble. We describe the key steps involved in customizing it for the dipstick of choice and for customizing a mobile phone app to analyze the results. We demonstrate its use to perform urinalysis and discuss the critical measurements and fabrication steps necessary to ensure robust operation. We then compare the proposed method to the dip-and-wipe method, the gold standard technique for dipstick urinalysis.