Abnormally low or high blood iron levels are common health conditions worldwide and can seriously affect an individual’s overall well-being. A low-cost point-of-care technology that measures blood iron markers with a goal of both preventing and treating iron-related disorders represents a significant advancement in medical care delivery systems. Methods: A novel assay equipped with an accurate, storable, and robust dry sensor strip, as well as a smartphone mount and (iPhone) app is used to measure total iron in human serum. The sensor strip has a vertical flow design and is based on an optimized chemical reaction. The reaction strips iron ions from blood-transport proteins, reduces Fe(III) to Fe(II), and chelates Fe(II) with ferene, with the change indicated by a blue color on the strip. The smartphone mount is robust and controls the light source of the color reading App, which is calibrated to obtain output iron concentration results. The real serum samples are then used to assess iron concentrations from the new assay and validated through intra-laboratory and inter-laboratory experiments. The intra-laboratory validation uses an optimized iron detection assay with multi-well plate spectrophotometry. The inter-laboratory validation method is performed in a commercial testing facility (LabCorp). Results: The novel assay with the dry sensor strip and smartphone mount, and App is seen to be sensitive to iron detection with a dynamic range of 50 - 300 µg/dL, sensitivity of 0.00049 µg/dL, coefficient of variation (CV) of 10.5%, and an estimated detection limit of ~15 µg/dL These analytical specifications are useful for predicting iron deficiency and overloads. The optimized reference method has a sensitivity of 0.00093 µg/dL and CV of 2.2%. The correlation of serum iron concentrations (N=20) between the optimized reference method and the novel assay renders a slope of 0.95, and a regression coefficient of 0.98, suggesting that the new assay is accurate. Lastly, a spectrophotometric study of the iron detection reaction kinetics is seen to reveal the reaction order for iron and chelating agent. Conclusion: The new assay is able to provide accurate results in intra- and inter- laboratory validations and has promising features of both mobility and low-cost.

Extracellular Vesicles (EVs), particularly exosomes, are of considerable interest as tumor biomarkers since tumor-derived EVs contain a broad array of information about tumor pathophysiology including its metabolic and metastatic status. However, current EV based assays cannot distinguish between EV biomarker changes by altered secretion of EVs during diseased conditions like cancer, inflammation, etc. that express a constant level of a given biomarker, stable secretion of EVs with altered biomarker expression, or a combination of these two factors. This issue was addressed by developing a nanoparticle and dye-based fluorescent immunoassay that can distinguish among these possibilities by normalizing EV biomarker level(s) to EV abundance, revealing average expression levels of EV biomarker under observation. In this approach, EVs are captured from complex samples (e.g. serum), stained with a lipophilic dye and hybridized with antibody-conjugated quantum dot probes for specific EV surface biomarkers. EV dye signal is used to quantify EV abundance and normalize EV surface biomarker expression levels. EVs from malignant (PANC-1) and nonmalignant pancreatic cell lines (HPNE) exhibited similar staining, and probe-to-dye ratios did not change with EV abundance, allowing direct analysis of normalized EV biomarker expression without a separate EV quantification step. This EV biomarker normalization approach markedly improved the ability of serum levels of two pancreatic cancer biomarkers, EV EpCAM, and EV EphA2, to discriminate pancreatic cancer patients from nonmalignant control subjects. The streamlined workflow and robust results of this assay are suitable for rapid translation to clinical applications and its flexible design permits it to be rapidly adapted to quantitate other EV biomarkers by the simple swapping of the antibody-conjugated quantum dot probes for those that recognize a different disease-specific EV biomarker utilizing a workflow that is suitable for rapid clinical translation.

Mycobacterium tuberculosis is the primary bacteria responsible for tuberculosis, one of the most dangerous diseases, and top causes of death worldwide, as identified by the World Health Organization in a 2018 report. Diagnostic tools currently exist for identifying those who carry active or latent versions of the infection including chest radiographs, a Mantoux tuberculin skin test, or an acid-fast bacilli smear of sputum samples. These methods are standard in the medical community of high income countries, but pose challenges for lower-income regions of the world as well as vulnerable populations. The need for a rapid, inexpensive, and non-invasive method of tuberculosis detection is evident by the ten million that contracted and 1.6 million that died from TB in 2017 alone. In our study, we used a previously developed nanoplasmon-enhanced scattering technology combined with dark field microscopy in order to investigate the potential for a blood-based TB detection assay. Twenty-eight capture antibodies were screened using cell culture exosomes and human serum samples to identify candidates for a TB-derived exosome biomarker. Four antibodies demonstrated potential for distinguishing negative controls from positive controls in this study: anti-AG85, anti-AG85B, anti-SodA, anti-Ald. These capture antibodies displayed significant differences (p<0.05) for both cell culture exosomes and human serum samples on more than one occasion. The work is significant in its ability to distinguish potential capture antibody targets, and future experimentation may yield a technology ready for clinical settings to address the gap in current TB detection methods.

The optimization of a blood-based assay for diagnosing tuberculosis which has been developed and validated in Dr. Hu’s lab, at Arizona State University, is important for ensuring its successful translation to a resource-limited setting of the developing world. Tuberculosis is most prevalent in the developing world with Sub-Saharan Africa having the highest cases of HIV/TB coinfections. The implementation of a blood-based assay for diagnosing Tuberculosis in the sub-Saharan would significantly improve the diagnosis and treatment monitoring of tuberculosis thereby managing or eliminating the pandemic altogether. The World Health Organization has called for robust diagnostic technologies that would resolve the shortfalls of the current technologies which include GeneXpert, X-ray, and smear microscopy. The blood-based diagnostic methodology heavily relies on Mass-spectrometry, a technology which could be entirely novel and expensive to implement in most laboratories in the Sub-Saharan. Despite virtual challenges in implementing the technology, the assay has demonstrated high specificity and sensitivity to HIV/TB coinfected patients and children in comparison to the available TB diagnostic assays. This study endorses the Blood-based Mass Spectrometry assay as one of the promising technologies to effectively improve the diagnosis of TB. The performance of the assay on detecting TB antigens was tested using different methods and materials. In the end, the use of DBS and miniaturized mass spectrometers have been discussed as possible routes for translating the assay to the developing world