David Erickson

Abstract Purpose: Breast cancer, the most common malignancy among women globally, demands precise molecular subtyping to guide effective treatment. However, in low- and middle-income countries (LMICs), limited access to diagnostic resources hinders timely interventions. We developed a triplex lateral flow immunoassay (LFIA) capable of simultaneously quantifying progesterone receptor (PR), estrogen receptor (ER), and human epidermal growth factor receptor 2 (HER2) to address these diagnostic challenges with a portable and cost-effective solution. Methods: The triplex LFIA incorporates europium-streptavidin fluorescence for enhanced sensitivity and specificity, coupled with an incubation pad to improve antigen-antibody interactions. Detection limits of PR, ER, and HER2 were established as 32 pM, 76 pM, and 25 pM, respectively. Comparative analysis with enzyme-linked immunosorbent assay (ELISA) validated the assay’s accuracy and clinical utility. A Portable Rapid Onsite Versatile Image-based Detection System (PROVIDS) was developed for real-time quantitative biomarker analysis. Results: The LFIA demonstrated high sensitivity, specificity (cross-reactivity <5%), and strong correlation with ELISA (R2 > 0.95). The platform’s performance aligns with clinical thresholds, distinguishing breast cancer subtypes across biomarker profiles. PROVIDS-enabled analysis ensures quantitative readouts, achieving point-of-care compatibility. While its laboratory performance is promising, further field validation is required to assess its operational impact in LMICs. Conclusion: The triplex LFIA represents a significant step toward accessible molecular subtyping in resource-limited settings. With its innovative design and promising laboratory performance, this platform holds potential to address diagnostic disparities in LMICs and improve timely breast cancer care upon further validation. Citation Format: Wenting Gao, Iftak Hussain, Thea Nikolaou, Clement Adebamowo, David Erickson. Point-of-Care Technologies for Molecular Subtyping of Breast Cancer in Low- and Middle-Income Countries [abstract]. In: Proceedings of the 13th Annual Symposium on Global Cancer Research; 2025 Sep 16. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2025;34(12_Suppl):Abstract nr 83.

0.9347). It performed even better when the analysis was applied directly to the raw signal data without additional pre-processing steps such as artifact filtering. This suggests that the AI model is more generalizable to new data and is able to discriminate KS-present and KS-absent samples better than traditional methods.

Kaposi sarcoma (KS) is an endothelial cancer caused by the Kaposi sarcoma-associated herpesvirus (KSHV), and it remains one of the most frequently diagnosed and fatal cancers in sub-Saharan Africa. Achieving timely and accurate diagnosis for KS is a critical challenge in sub-Saharan Africa, where access to histopathology is limited and clinical diagnosis is often erroneous. Previously, a point-of-care device was developed to quantify KSHV DNA and demonstrated promising performance, achieving 97% sensitivity and 92% specificity at a 26-minute threshold in a training set of patients from several Ugandan clinics. Herein, 421 skin biopsies from a different, test set of patients identified later in calendar time at the same clinical sites were examined using the same methodology. Using the previously defined cutoff threshold, the test achieved similarly high sensitivity (95%) and specificity (90%), confirming the robustness of the threshold-based assay across both clinical settings and time. This multi-site, temporally distinct validation supports the further development of a nucleic acid–based KS diagnostic test and holds strong potential for improving early KS diagnosis access in high-burden, resource-limited regions.

The point-of-care diagnostic kit for molecular subtyping of breast cancer (PoCBreCa) exemplifies innovation in breast cancer diagnostics, offering a multiplex lateral-flow immunoassay for rapid molecular subtyping at the point of care in low- and middle-income countries (LMIC). By leveraging cell lysates from fine-needle aspirates and biopsies, PoCBreCa kit aims to swiftly quantify pivotal breast cancer-related biomarkers: estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) in under 70 minutes, vastly outpacing the weeks-long timeline and cost of traditional immunohistochemistry while maintaining high analytical sensitivity and specificity. The analysis generates images that are captured and analyzed by the PROVIDS reader system that we developed. PROVIDS is powered by a mobile platform, interprets the captured images, and identifies breast cancer subtypes instantly, facilitating rapid clinical decisions. The cost, objectivity, ease of use, and immediacy of result delivery are paramount in regions where healthcare resources are limited. These characteristics enable prompt and appropriate therapeutic interventions, thereby optimizing patient management, prediction, and prognostication in the challenging healthcare landscape of LMICs.

BACKGROUND: Kaposi sarcoma (KS) is a cancer of viral origin (Kaposi sarcoma-associated herpesvirus; KSHV) for which the detection of KSHV DNA is an attractive target for a rapid, automatable diagnostic test. We previously demonstrated favorable diagnostic accuracy using loop-mediated isothermal amplification (LAMP) to quantitate KSHV DNA in lesional skin biopsies, though extracting DNA from the punch biopsies was the time-limiting step. Herein, we describe the development of a biopsy processing tool called Slicer to enable rapid nucleic acid testing in addition to traditional histopathological interpretation. METHODS: Slicer divides skin punch biopsies into two ½-cylinders and a thin, cross-sectional slice. The thin slice enables a previously demonstrated, equipment-free alkaline extraction termed ColdSHOT while the remaining ½-cylinders are available for histopathological diagnosis and additional molecular testing as needed. Slicer prototypes were used on skin punch biopsies collected from patients in Uganda who were referred for clinical suspicion of KS. RESULTS: For 27 patient samples, the combination of Slicer and ColdSHOT sample processing with LAMP testing resulted in qualitative KSHV DNA detection that was fully concordant with US-based histopathological diagnoses. Additional analysis demonstrated compatibility of Slicer and ColdSHOT with qPCR for KSHV DNA quantitation. CONCLUSIONS: These results warrant further investigation using a larger set of skin biopsies and indicate that the Slicer and ColdSHOT could enable accurate KS diagnosis within a few hours of biopsy collection with minimal equipment.

The growing cancer burden and suboptimal diagnostic capacity in low- and middle-income countries calls for urgent innovation in diagnostic solutions. Point-of-care technologies (POCTs) offer a transformative approach to decentralizing cancer diagnostics by providing rapid, affordable, and scalable testing in resource-constrained settings. Recent advancements, including loop-mediated isothermal amplification and multiplexed lateral flow immunoassay, enable high-sensitivity detection of cancer biomarkers without the need for complex laboratory infrastructure. Additionally, noninvasive imaging tools, such as optical coherence tomography and fluorescence-guided microscopy, offer portable and cost-effective solutions for early cancer detection in settings with limited health care services. These innovations are complemented by the integration of artificial intelligence, which improves diagnostic accuracy and reduces reliance on highly trained personnel. However, significant infrastructure and logistical challenges persist, including resource constraints, unreliable electricity, and insufficient cold-chain logistics, which limit diagnostic precision and accessibility. This review discusses recent advances in POCTs for oncology and examines how public-private partnerships and multisector collaborations can address key implementation barriers. By prioritizing inclusivity, cross-sector collaboration, and targeted investments, POCTs can sustainably narrow global disparities in cancer diagnosis and treatment.

e17164 Background: Prostate cancer (PC) is the most common cancer among men in the U.S. Compared to Caucasians, Black men have a higher PC incidence, are diagnosed at a younger age, and have a higher PC specific mortality. The reasons for this disparity are multi-faceted and include genetic and socioeconomic factors including access to care. Recent PSA screening guidelines recommend screening in Black men from the age of 40. However, studies suggest uptake of this PSA screening recommendation is very low. Development of a low-cost and rapid screening tool that could be performed in the community could increase PSA testing among Black men. Methods: We developed a total PSA (tPSA) POC lateral flow assay test strip that utilizes immunochromatography to yield different signal intensities based on tPSA concentrations and uses a commercial portable strip reader (Cube) to quantify PSA based on the ratio of signal intensity of test and control line (TC ratio). In an IRB approved study, men undergoing standard PSA testing with a PSA 0.1-20 ng/ml enrolled on protocol after providing informed consent. 50 µL of fingerstick collected blood was mixed with 150 µL of buffer (PBS 1X, 1% BSA, 1% Tween-20) and 100 µL deposited in the chip well and the TC ratio read at 20 min and correlated with a venous blood drawn PSA measured in a CLIA lab. Spearman correlation coefficient was used to assess the correlation between the values of the two tests, and a receiver-operating characteristic curve (ROC) analysis was performed to find the optimal cutoff of TC test to maximize its Sensitivity and Specificity using Youden’s index with a PSA test (dichotomized at 4) as the gold standard. Results: PSA values were plotted against the TC values in a scatter plot from 30 men. The Spearman correlation coefficient between fingerstick and venous PSA was 0.89 (95% CI: 0.78, 0.96). Using a dichotomized approach where a PSA < 4 was Negative, >4 Positive, a ROC analysis demonstrated an AUC of 0.98 (95% confidence interval [CI]: 0.94, 1), with a sensitivity of 85% (95% CI: 62.1% - 96.8%), and specificity of 100% (95% CI: 69.2% - NA). A second cohort of 23 men using a different batch of POC test strips similarly demonstrated an AUC of 0.97 (95% CI: 0.93, 1) with a sensitivity of 86.7% (95% CI: 59.5% - 98.3%), and specificity of 100% (95% CI: 63.1% - NA). Conclusions: Our data show that a PSA POC test is feasible and accurate as a screening test to detect PSA > 4 ng/ml. Patients with positive tests may be referred to the appropriate healthcare provider for further evaluation. PSA POC testing is an alternative and convenient low-cost method to test for elevated PSA in a community setting and improve access to care. This will be further tested by utilizing the device for PSA screening in the community at barbershops.

Importance: Advanced-stage disease at the time of diagnosis, with resultant high mortality, is among the most urgent issues for HIV-related Kaposi sarcoma (KS) in sub-Saharan Africa. Lack of access to skilled clinical personnel and histopathologic technology in the region contribute to diagnostic delays and advanced stage at diagnosis. Accordingly, new paradigms for KS diagnosis are needed. Objective: To evaluate the accuracy of artificial intelligence (AI)-based interpretation of digital surface images of skin lesions to diagnose KS among dark-skinned patients in Uganda. Design: Cross-sectional study of consecutive participants referred to skin biopsy services in Uganda because of clinical suspicion of KS. Lesions were photographed using a digital camera, and punch biopsies were obtained. Histopathologic interpretation was considered the gold standard. Using training (∼70% of images) and validation (∼10% of images) sets, we developed a prediction model using a rule-based combination of YOLO (You Only Look Once) version 5 and 8 object detection classifiers. Setting: Free-of-charge skin biopsy services. Participants: Consecutive sample of 482 individuals were evaluated due to clinical suspicion of KS. Main Outcomes: Sensitivity, specificity, positive and negative predictive value (with accompanying 95% confidence intervals) of the AI-based prediction model in a test set (∼20% of images). The accuracy of a dermatologist's visual interpretation of images was also described. Results: 472 participants (1385 images) were evaluable. Of these, 36% were female, median age was 34 years, and 94% had HIV; 332 had KS, and 140 had no KS by histopathology. In the test set, the AI-derived prediction model achieved 89% sensitivity (85%-94%) and 51% specificity (40%-61%) for diagnosing KS; positive predictive value was 81% (75%-86%) and negative predictive value was 67% (55%-78%). A dermatologist evaluating the same images, with emphasis on sensitivity, achieved sensitivity of 93% (89%-96%) and specificity of 19% (11%-28%). Conclusions and Relevance: Among dark-skinned patients in Uganda with skin lesions suspicious for KS, evaluation of digital surface images by an AI-based prediction model produced moderate accuracy for diagnosing KS. While currently inadequate for clinical use, this inaugural assessment is sufficiently promising to justify evaluation of larger datasets and evolving technologies to determine if accuracy can be improved. Key Points: In sub-Saharan Africa, where incidence and mortality from KS is high and delayed diagnosis is common due to limited specialized personnel and technical supplies, AI-based prediction models built on digital images taken of suspicious lesions may someday hasten KS diagnoses.

PURPOSE: Immunohistochemical staining for the antigen of Kaposi sarcoma (KS)-associated herpesvirus, latency-associated nuclear antigen (LANA), is helpful in diagnosing KS. A challenge lies in distinguishing anti-LANA-positive cells from morphologically similar brown counterparts. This work aims to develop an automated framework for localization and quantification of LANA positivity in whole-slide images (WSI) of skin biopsies. METHODS: The proposed framework leverages weakly supervised multiple-instance learning (MIL) to reduce false-positive predictions. A novel morphology-based slide aggregation method is introduced to improve accuracy. The framework generates interpretable heatmaps for cell localization and provides quantitative values for the percentage of positive tiles. The framework was trained and tested with a KS pathology data set prepared from skin biopsies of KS-suspected patients in Uganda. RESULTS: The developed MIL framework achieved an area under the receiver operating characteristic curve of 0.99, with a sensitivity of 98.15% and specificity of 96.00% in predicting anti-LANA-positive WSIs in a test data set. CONCLUSION: The framework shows promise for the automated detection of LANA in skin biopsies, offering a reliable and accurate tool for identifying anti-LANA-positive cells. This method may be especially impactful in resource-limited areas that lack trained pathologists, potentially improving diagnostic capabilities in settings with limited access to expert analysis.

Point-of-care (POC) testing has revolutionized diagnostics by providing rapid, accessible solutions outside traditional laboratory settings. However, many POC systems lack the sensitivity or multiplexing capability required for complex diseases. This study introduces an LED-based fluorescence reader designed for POC applications, enabling multiplex detection of lupus nephritis (LN) biomarkers using a biomarker microarray (BMA) slide. The reader integrates an LED excitation source, neutral density (ND) filters for precise intensity control, and onboard image processing with Gaussian smoothing and centroid thresholding to enhance signal detection and localization. Five LN biomarkers (VSIG4, OPN, VCAM1, ALCAM, and TNFRSF1B) were assessed, and performance was validated against a Genepix laser-based scanner. The LED reader demonstrated strong correlation coefficients (r = 0.96-0.98) with the Genepix system for both standard curves and patient samples, achieving robust signal-to-noise ratios and reproducibility across all biomarkers. The multiplex format reduced sample volume and allowed simultaneous analysis of multiple biomarkers. These results highlight the reader's potential to bridge the gap between laboratory-grade precision and POC accessibility. By combining portability, cost-effectiveness, and high analytical performance, this fluorescence reader provides a practical solution for POC diagnostics, particularly in resource-limited settings, improving the feasibility of routine monitoring and early intervention for diseases requiring comprehensive biomarker analysis.

copies per mL, whereas AuNP-based LFAs met the defined TPP threshold. Both CNB- and AuNP-LFA formats also met the WHO TPP acceptable targets for time to result, number of user steps and target use setting. These results indicate that CNBs can provide superior analytical sensitivity relative to 40 nm AuNPs and may support more sensitive, visually interpreted LFAs without the need for specialized test strip readers.

Loop-mediated isothermal amplification (LAMP) has gained particular attention for point-of-care (POC) applications due to its advantages over traditional nucleic acid testing approaches. However, a prevailing limitation of LAMP in POC applications is nucleic acid extraction from the sample prior to analysis. This is particularly true for complex samples such as submillimeter skin biopsies where lysis and digestion involve intricate and lengthy procedures. The objective of this study was to compare alternative methodologies against the spin-column laboratory standard and evaluate them based on the World Health Organization ASSURED criteria for POC testing. Four methods-magnetic bead extraction, alkaline extraction, proteinase K-heat inactivation extraction, and boiling method extraction-were optimized utilizing porcine skin submillimeter punch biopsies and subsequently validated on human skin. Results show that both alkaline extraction and proteinase K-heat inactivation produce DNA yields equivalent to or higher than the spin-column method in porcine and human skin. When evaluated against the ASSURED criteria, both methods demonstrated low complexity while being highly scalable and readily accessible. Overall, this comparative study established a robust framework for selecting DNA extraction methods for submillimeter skin biopsies in POC applications. It also underscored the performance of the alkaline extraction method based on the ASSURED criteria, providing equivalent DNA yields to laboratory standards with reduced complexity and potential for cost-effective scalability.

Abstract Immunohistochemical (IHC) staining for the antigen of Kaposi sarcoma-associated herpesvirus (KSHV), latency-associated nuclear antigen (LANA), is helpful in diagnosing Kaposi sarcoma (KS). A challenge, however, lies in distinguishing anti-LANA-positive cells from morphologically similar brown counterparts. In this work, we demonstrate a framework for automated localization and quantification of LANA positivity in whole slide images (WSI) of skin biopsies, leveraging weakly supervised multiple instance learning (MIL) while reducing false positive predictions by introducing a novel morphology-based slide aggregation method. Our framework generates interpretable heatmaps, offering insights into precise anti-LANA-positive cell localization within WSIs and a quantitative value for the percentage of positive tiles, which may assist with histological subtyping. We trained and tested our framework with an anti-LANA-stained KS pathology dataset prepared by pathologists in the United States from skin biopsies of KS-suspected patients investigated in Uganda. We achieved an area under the receiver operating characteristic curve (AUC) of 0.99 with a sensitivity and specificity of 98.15% and 96.00% in predicting anti-LANA-positive WSIs in a test dataset. We believe that the framework can provide promise for automated detection of LANA in skin biopsies, which may be especially impactful in resource-limited areas that lack trained pathologists.

Kaposi's sarcoma (KS) is a cancer affecting skin and internal organs for which the Kaposi's sarcoma associated herpesvirus (KSHV) is a necessary cause. Previous work has pursued KS diagnosis by quantifying KSHV DNA in skin biopsies using a point-of-care (POC) device which performs quantitative loop-mediated isothermal amplification (LAMP). These previous studies revealed that extracting DNA from patient biopsies was the rate limiting step in an otherwise rapid process. In this study, a simplified, POC-compatible alkaline DNA extraction, ColdSHOT, was optimized for 0.75 mm human skin punch biopsies. The optimized ColdSHOT extraction consistently produced 40,000+ copies of DNA per 5 µl reaction from 3 mg samples-a yield comparable to standard spin column extractions-within 1 h without significant equipment. The DNA yield was estimated sufficient for KSHV detection from KS-positive patient biopsies, and the LAMP assay was not affected by non-target tissue in the unpurified samples. Furthermore, the yields achieved via ColdSHOT were robust to sample storage in phosphate-buffered saline (PBS) or Tris-EDTA (TE) buffer prior to DNA extraction, and the DNA sample was stable after extraction. The results presented in this study indicate that the ColdSHOT DNA extraction could be implemented to simplify and accelerate the LAMP-based diagnosis of Kaposi's sarcoma using submillimeter biopsy samples.

Quantification of SARS-CoV-2 RNA copies in wastewater can be used to estimate COVID-19 prevalence in communities. While such results are important for mitigating disease spread, SARS-CoV-2 measurements require sophisticated equipment and trained personnel, for which a centralized laboratory is necessary. This significantly impacts the time to result, defeating its purpose as an early warning detection tool. The objective of this study was to evaluate a field portable device (called MINI) for detecting SARS-CoV-2 viral loads in wastewater using real-time reverse transcriptase loop-mediated isothermal amplification (real-time RT-LAMP). The device was tested using wastewater samples collected from buildings (with 430 to 1430 inhabitants) that had known COVID-19-positive cases. Results show comparable performance of RT-LAMP against reverse transcriptase polymerase chain reaction (RT-qPCR) when detecting SARS-CoV-2 copies in wastewater. Both RT-LAMP and RT-qPCR detected SARS-CoV-2 in wastewater from buildings with at least three positive individuals within a 6-day time frame prior to diagnosis. The large 96-well throughput provided by MINI provided scalability to multi-building detection. The portability of the MINI device enabled decentralized on-site detection, significantly reducing the time to result. The overall findings support the use of RT-LAMP within the MINI configuration as an early detection system for COVID-19 infection using wastewater collected at the building scale.

Our objectives were to develop and evaluate an integrated system consisting of a lateral-flow immunoassay ( LFIA ) and an electronic portable imaging device for determination of pregnancy status of cows based on plasma concentrations of pregnancy-specific protein B ( PSPB ). Experiment 1 was conducted to test the performance of the LFIA for PSPB ( PSPB-LFIA ) whereas experiment 2 was conducted to evaluate the performance of the integrated system including both the LFIA and imaging device. The PSPB-LFIA strips were made of nitrocellulose membrane with polystreptavidin, anti-mouse antibody, Europium-anti-PSPB conjugates, and biotin-PSPB. After adding buffer and plasma in a 96-well plate, strips were dipped to initiate flow and were read in a fluorescence microscope to estimate PSPB concentrations based on the test-to-control line signal (T/C ratio). The T/C ratio of standards was linearly associated with PSPB (R 2 = 0.99 in both experiments) concentrations. To test the ability to identify pregnant cows of the PSPB-LFIA only or the integrated system, plasma samples were collected and transrectal ultrasonography ( TUS ) was conducted 29 to 35 d post AI in lactating Holstein cows (Experiment 1: n=83; Experiment 2: n=205). A cow was considered pregnant ( Preg ) if concentrations of PSPB in plasma obtained by ELISA were ≥2 ng/mL or if an embryo was visible by TUS. In Experiment 1, the accuracy of the PSPB-LFIA compared with ELISA was 92.7% (91.2% Se; 96.1% Sp; 98.1% PPV; 83.3% NPV) and compared with TUS was 90.4% (100% Se; 78.9% Sp; 84.9% PPV; 100% NPV). The agreement between LFIA and ELISA (kappa = 0.84; 95%CI 0.71–0.96) or LFIA and TUS (kappa = 0.80; 95%CI 0.67–0.93) as methods to classify cows as Preg or Non-Preg was high. In Experiment 2, the accuracy of the PSPB-LFIA compared with ELISA was 96.1% (93.8% Se; 100% Sp; 100% PPV; 90.5% NPV) and compared with TUS was 92.2% (99.0% Se; 84.7% Sp; 87.6% PPV; 98.8% NPV). The agreement between LFIA and ELISA (kappa = 0.92; 95%CI 0.86–0.97) or LFIA and TUS (kappa = 0.84; 95%CI 0.77–0.92) as methods to classify cows as Preg or Non-Preg was high. We conclude that a system integrating a fluorescence-based LFIA and an optical reader was effective for classifying cows as pregnant or not pregnant based on estimations of plasma concentrations of PSPB. This novel system serves as a platform for further development of on-farm pregnancy testing tools based on measurement of biomarkers of pregnancy in bodily fluids of cattle.

BACKGROUND: Major depressive disorder (MDD) is a common, often recurrent condition and a significant driver of healthcare costs. People with MDD often receive pharmacological therapy as the first-line treatment, but the majority of people require more than one medication trial to find one that relieves symptoms without causing intolerable side effects. There is an acute need for more effective interventions to improve patients' remission and quality of life and reduce the condition's economic burden on the healthcare system. Pharmacogenomic (PGx) testing could deliver these objectives, using genomic information to guide prescribing decisions. With an already complex and multifaceted care pathway for MDD, future evaluations of new treatment options require a flexible analytic infrastructure encompassing the entire care pathway. Individual-level simulation models are ideally suited for this purpose. We sought to develop an economic simulation model to assess the effectiveness and cost effectiveness of PGx testing for individuals with major depression. Additionally, the model serves as an analytic infrastructure, simulating the entire patient pathway for those with MDD. METHODS AND ANALYSIS: Key stakeholders, including patient partners, clinical experts, researchers, and modelers, designed and developed a discrete-time microsimulation model of the clinical pathways of adults with MDD in British Columbia (BC), including all publicly-funded treatment options and multiple treatment steps. The Simulation Model of Major Depression (SiMMDep) was coded with a modular approach to enhance flexibility. The model was populated using multiple original data analyses conducted with BC administrative data, a systematic review, and an expert panel. The model accommodates newly diagnosed and prevalent adult patients with MDD in BC, with and without PGx-guided treatment. SiMMDep comprises over 1500 parameters in eight modules: entry cohort, demographics, disease progression, treatment, adverse events, hospitalization, costs and quality-adjusted life-years (payoff), and mortality. The model predicts health outcomes and estimates costs from a health system perspective. In addition, the model can incorporate interactive decision nodes to address different implementation strategies for PGx testing (or other interventions) along the clinical pathway. We conducted various forms of model validation (face, internal, and cross-validity) to ensure the correct functioning and expected results of SiMMDep. CONCLUSION: SiMMDep is Canada's first medication-specific, discrete-time microsimulation model for the treatment of MDD. With patient partner collaboration guiding its development, it incorporates realistic care journeys. SiMMDep synthesizes existing information and incorporates provincially-specific data to predict the benefits and costs associated with PGx testing. These predictions estimate the effectiveness, cost-effectiveness, resource utilization, and health gains of PGx testing compared with the current standard of care. However, the flexible analytic infrastructure can be adapted to support other policy questions and facilitate the rapid synthesis of new data for a broader search for efficiency improvements in the clinical field of depression.

279 Background: Screening for prostate cancer (PC) reduces PC-specific deaths. African American (AA) individuals have a ~2-fold higher risk of developing and dying from PC and may benefit from screening at a younger age. To increase access to PC screening for high-risk communities, we developed a portable, rapid point of care (POC) PSA test that quantifies PSA from FS blood in 20 minutes. We present preliminary data for our POC test. Methods: We developed a lateral flow immunoassay test strip 1 combined with the Cube Reader (Chembio Diagnostics GmbH) to quantify PSA from FS blood. These measurements were compared on the same day with standard venous blood PSA as measured with the Siemens Centaur Chemiluminescent Immunoassay. Following informed consent, 50 µL of FS blood was mixed with 80 µL of buffer (PBS 1X with 1% Tween-20) and loaded onto the test strip. This ratio was found to be effective for adequate sample flow on the test strip. Eligible patients (pts) were undergoing standard of care PSA testing and had a recent PSA <20 ng/mL (to resemble a screening population). Pts with and without PC were included. Colorimetric signal intensities of the Test (T) and Control (C) lines were measured at 20 min with the Cube Reader. A scatter plot and Pearson correlation coefficient between the T/C ratios and the PSA results from venous blood were obtained for a group of 42 preliminary pts. A cohort of 30 pts additionally had 200 µL of FS blood (the minimum sufficient quantity) collected for serum analysis via the Centaur assay. This was done to evaluate for any unexpected variability between laboratory-based capillary and venous PSA results, and to test the feasibility of measuring PSA in the lab with a small volume of blood. Results: In these preliminary results, the 30 pts who had PSA measured from capillary and venous sera via the Centaur assay showed a correlation coefficient of 0.99. In the cohort of 42 pts who had PSA T/C ratios measured with the test strip, the correlation with venous PSA was 0.9. This encompassed a PSA range of 0.3-19.6 ng/mL with one outlier of 179 ng/mL. Based on a preliminary calibration curve from a small sample of 21 pts, the sensitivity and specificity of the POC test to detect a PSA >4 ng/mL was 100% (95% CI: 71.51-100) and 90% (95% CI: 55.50-99.75), respectively, in the 0.3-10 ng/mL detection range. Nineteen percent (8/42) of pts were AA. Conclusions: Serum from capillary and venous blood shows a strong correlation when measured via a standard laboratory assay. In addition, a rapid POC PSA test using a PSA test strip is easy to administer and preliminary data suggest a good correlation with standard venous PSA testing. The development of such a test may improve access to PC screening for high-risk individuals. Continued optimization and validation of our POC test is ongoing. 1. Curr Res Biotechnol 2021;3:288-299. Clinical trial information: N/A.

BACKGROUND: Pharmacogenomic testing to identify variations in genes that influence metabolism of antidepressant medications can enhance efficacy and reduce adverse effects of pharmacotherapy for major depressive disorder. We sought to establish the cost-effectiveness of implementing pharmacogenomic testing to guide prescription of antidepressants. METHODS: We developed a discrete-time microsimulation model of care pathways for major depressive disorder in British Columbia, Canada, to evaluate the effectiveness and cost-effectiveness of pharmacogenomic testing from the public payer's perspective over 20 years. The model included unique patient characteristics (e.g., metabolizer phenotypes) and used estimates derived from systematic reviews, analyses of administrative data (2015-2020) and expert judgment. We estimated incremental costs, life-years and quality-adjusted life-years (QALYs) for a representative cohort of patients with major depressive disorder in BC. RESULTS: Pharmacogenomic testing, if implemented in BC for adult patients with moderate-severe major depressive disorder, was predicted to save the health system $956 million ($4926 per patient) and bring health gains of 0.064 life-years and 0.381 QALYs per patient (12 436 life-years and 74 023 QALYs overall over 20 yr). These savings were mainly driven by slowing or avoiding the transition to refractory (treatment-resistant) depression. Pharmacogenomic-guided care was associated with 37% fewer patients with refractory depression over 20 years. Sensitivity analyses estimated that costs of pharmacogenomic testing would be offset within about 2 years of implementation. INTERPRETATION: Pharmacogenomic testing to guide antidepressant use was estimated to yield population health gains while substantially reducing health system costs. These findings suggest that pharmacogenomic testing offers health systems an opportunity for a major value-promoting investment.

Technologies for automating animal management and monitoring tasks can improve efficiency and productivity of livestock production. We developed the e-Synch system for automated control and monitoring the estrous cycle of cattle through intravaginal hormone delivery and sensing. Thus, our objective was to evaluate luteinizing hormone (LH) concentrations after intravaginal instillation of the Gonadotropin-releasing hormone (GnRH) analogue Gonadorelin with the e-Synch system. This system consists of an intravaginal electronically controlled automated hormone delivery and sensing device integrated with an IoT platform. Lactating Holstein cows with their estrous cycle synchronized were used in two experiments (Exp). In Exp 1, at 48 h after induction of luteolysis, cows (n=5-6 per group) were randomized to receive 100 µg of Gonadorelin through intramuscular (i.m.) injection, 100 µg of Gonadorelin in a 2 mL solution delivered with e-Synch, and an empty e-Synch device. In Exp 2, at 48 h after induction of luteolysis cows (n=6-7 per group) were randomized to receive 100 µg of Gonadorelin i.m., or an intravaginal treatment with e-Synch consisting of 100 or 1,000 µg of Gonadorelin in 2 or 10 mL of solution containing 10% citric acid as absorption enhancer. Circulating concentrations of LH were analyzed with linear mixed models with or without repeated measurements. In Exp 1, cows in the i.m. Gonadorelin treatment had a surge of LH whereas cows in the other two treatments did not have a surge of LH for up to 8 h after treatment. In Exp 2, the 1,000 µg dose of Gonadorelin elicited more LH release than the 100 µg dose, regardless of solution quantity. The overall LH response as determined by area under the curve, mean, and maximum LH concentrations was similar between cows receiving 1,000 µg of Gonadorelin delivered with e-Synch and 100 μg of Gonadorelin i.m. Increasing volume of solution for delivering the same dose of Gonadorelin partially increased LH release only for the 100 µg dose. We conclude that the e-Synch system could be used to automatically release Gonadorelin in a dose and volume that induces a surge of LH of similar magnitude than after i.m. injection of 100 μg of Gonadorelin. Also, the dose of Gonadorelin delivered by e-Synch is more critical than the volume of solution used.

The objective of this manuscript was to present the e-Synch system, integrating an intravaginal electronically controlled hormone delivery and sensing device with an IoT platform for remote programming and monitoring. Secondary objectives were to demonstrate system functionality and cow responses to e-Synch. External components of e-Synch include a 3D-printed case with retention wings, a flexible wideband antenna, and silicone membrane for pressure balancing. Internal components include a central control board, battery, wireless charging coil, and two silicone hormone reservoirs connected to individual peristaltic pumps. An accelerometer and a high-accuracy temperature sensor are integrated in the custom printed circuit board (PCB). The IoT platform includes a gateway consisting of Raspberry PI 3 and a CC1352 radiofrequency module that collects sensor data at 915 mHz. Data is transferred to the Google Cloud utilizing the IoT Core service through TCP/IP, and then is pulled by the Pub/Sub service. After routing to a BigQuery table by the Dataflow service, data visualization is provided by Data Studio. Drug delivery protocols are selected using an IOS device app that connects to e-Synch through Bluetooth. Experiments with lactating Holsteins cows were conducted to demonstrate proof-of-concept system functionality and evaluate cow responses. Despite unstable communication and signal discontinuity because of signal strength attenuation by body tissue, devices (n=6) communicated with the IoT platform in 89% (24/27) of use instances. Temperature and accelerometer data were received for at least one 15 min period during an 8 h insertion period from all devices that communicated with the IoT platform. Variation in accelerometer data (± 8.565 m/s 2 ) was consistent with cow activity during experimentation and mean vaginal temperature of 39.1 °C (range 38.6 to 39.5 °C) demonstrated sensor functionality. Hormone release was confirmed in all instances of device use except for one. Cow behavior evaluated through signs of discomfort and pain, and tail raising scores was mostly unaltered by e-Synch. Vaginal integrity and mucus scores also remained unaltered during and after device insertion. In conclusion, the e-Synch device integrated with a controlling app and IoT platform might be used to automate intravaginal hormone delivery and sensing for controlling the estrous cycle of cattle.

A plurality of photonic crystal resonator optical trapping apparatuses and a plurality optical trapping methods using the plurality of photonic crystal resonator optical trapping apparatuses include located and formed over a substrate a photonic waveguide that is coupled (i.e., either separately coupled or integrally coupled) with a photonic crystal resonator. In a particular embodiment, the photonic waveguide and the photonic crystal resonator comprise a monocrystalline silicon (or other) photonic material absent any chemical functionalization. In another particular embodiment, the photonic waveguide and the photonic crystal resonator comprise a silicon nitride material which when actuating the photonic crystal resonator optical trapping apparatus with a 1064 nanometer resonant photonic radiation wavelength (or other resonant photonic radiation wavelength in a range from about 700 to about 1200 nanometers) provides no appreciable heating of an aqueous sample fluid that is analyzed by the photonic crystal resonator optical trapping apparatus.

Kaposi's sarcoma (KS) is an endothelial cancer caused by the Kaposi's sarcoma-associated herpesvirus (KSHV) and is one of the most common cancers in sub-Saharan Africa. In limited-resource settings, traditional pathology infrastructure is often insufficient for timely diagnosis, leading to frequent diagnoses at advanced-stage disease where survival is poor. In this study, we investigate molecular diagnosis of KS performed in a point-of-care device to circumvent the limited infrastructure for traditional diagnosis. Using 506 mucocutaneous biopsies collected from patients at three HIV clinics in Uganda, we achieved 97% sensitivity, 92% specificity, and 96% accuracy compared to gold standard U.S.-based pathology. The results presented in this manuscript show that LAMP-based quantification of KSHV DNA extracted from KS-suspected biopsies has the potential to serve as a successful diagnostic for the disease and that diagnosis may be accurately achieved using a point-of-care device, reducing the barriers to obtaining KS diagnosis while increasing diagnostic accuracy.

Aflatoxins (AFs) are naturally occurring mycotoxins known to cause a considerable threat to food safety and affect animal and health. Rapid and reliable analytical methods are crucial for preventing AF contamination in the global food supply chain. Many conventional AF detection methods involve complex sample preparation steps, lengthy analysis times, and multiple handling stages which lead to delays in obtaining results, in addition to being unaffordable in many settings with resource constraints. Herein, we demonstrate the proof of concept of a competitive immunochromatographic (IC) strip test for quantification of total AF using commercially available antibodies and a low-cost portable CubeTM analyzer. We conducted preliminary testing of our point-of-need (PON) AF detection method with corn samples and results indicated a good agreement when compared with gold standard HPLC method. Furthermore, a detection range of 5–50 ppb with detection time of 5 min, makes this technology suitable for rapid testing and meets the regulatory requirements for AF detection in food samples. We also demonstrate the real-time data sharing capabilities of the reader to a proof-of-concept centralized and cloud-based AF databank, that we developed to provide timely monitoring for different parts of food systems. It is critical for the test data to be easily accessible within a food systems dashboard to enable early warning, data-driven decision-making, rapid interventions, and improve overall coordination between various stakeholders within the food system.