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The lateral-flow immunoassay (LFA) is an inexpensive point-of-care (POC) paper-based diagnostic device with the potential to rapidly detect disease biomarkers in resource-poor settings. Although LFA is inexpensive, easy to use, and requires no laboratory equipment, it is limited by its sensitivity, which remains inferior to that of gold standard laboratory-based assays. Our group is the only one to have previously utilized various aqueous two-phase systems (ATPSs) to enhance LFA detection. In those studies, the sample was concentrated by an ATPS in a test tube and could only be applied to LFA after it had been extracted manually. Here, we bypass the extraction step by seamlessly integrating a polyethylene glycol-potassium phosphate ATPS with downstream LFA detection in a simple, inexpensive, power-free, and portable all-in-one diagnostic device. We discovered a new phenomenon in which the target biomarkers simultaneously concentrate as the ATPS solution flows through the paper membranes, and our device features a 3-D paper well that was designed to exploit this phenomenon. Studies with this device, which were performed at room temperature in under 25 min, demonstrated a 10-fold improvement in the detection limit of a model protein, transferrin. Our next-generation LFA technology is rapid, affordable, easy-to-use, and can be applied to existing LFA products, thereby providing a new platform for revolutionizing the current state of disease diagnosis in resource-poor settings.

Pathogen transmission by mosquitoes is tightly linked to blood feeding which, in turn, is required for egg development. Studies of these processes would greatly benefit from genetic methods, such as the binary Gal4/UAS system. The latter has been well established for model organisms, but its availability is limited for mosquitoes. The objective of this study was to develop the blood-meal-activated, gut-specific Gal4/UAS system for the yellow-fever mosquito Aedes aegypti and utilize it to investigate the regulation of gut-specific gene expression. A 1.1-kb, 5(') upstream region of the carboxypeptidase A (CP) gene was used to genetically engineer the CP-Gal4 driver mosquito line. The CP-Gal4 specifically activated the Enhanced Green Fluorescent Protein (EGFP) reporter only after blood feeding in the gut of the CP-Gal4 > UAS-EGFP female Ae. aegypti. We used this system to study the regulation of CP gene expression. In vitro treatments with either amino acids (AAs) or insulin stimulated expression of the CP-Gal4 > UAS-EGFP transgene; no effect was observed with 20-hydroxyecdysone (20E) treatments. The transgene activation by AAs and insulin was blocked by rapamycin, the inhibitor of the Target-of-Rapamycin (TOR) kinase. RNA interference (RNAi) silence of the insulin receptor (IR) reduced the expression of the CP-Gal4 > UAS-EGFP transgene. Thus, in vitro and in vivo experiments have revealed that insulin and TOR pathways control expression of the digestive enzyme CP. In contrast, 20E, the major regulator of post-blood-meal vitellogenic events in female mosquitoes, has no role in regulating the expression of this gene. This novel CP-Gal4/UAS system permits functional testing of midgut-specific genes that are involved in blood digestion and interaction with pathogens in Ae. aegypti mosquitoes.

Introduction/Objective: The KidneyIntelX is a multiplex, bioprognostic, immunoassay consisting of 3 plasma biomarkers and clinical variables that uses machine learning to predict a patient's risk for a progressive decline in kidney function over 5 years. We report the 1-year pre- and post-test clinical impact on care management, eGFR slope, and A1C along with engagement of population health clinical pharmacists and patient coordinators to promote a program of sustainable kidney, metabolic, and cardiac health. Methods: The KidneyIntelX in vitro prognostic test was previously validated for patients with type 2 diabetes and diabetic kidney disease (DKD) to predict kidney function decline within 5 years was introduced into the RWE study (NCT04802395) across the Health System as part of a population health chronic disease management program from [November 2020 to April 2023]. Pre- and post-test patients with a minimum of 12 months of follow-up post KidneyIntelX were assessed across all aspects of the program. Results: A total of 5348 patients with DKD had a KidneyIntelX assay. The median age was 68 years old, 52% were female, 27% self-identified as Black, and 89% had hypertension. The median baseline eGFR was 62 ml/min/1.73 m2, urine albumin-creatinine ratio was 54 mg/g, and A1C was 7.3%. The KidneyIntelX risk level was low in 49%, intermediate in 40%, and high in 11% of cases. New prescriptions for SGLT2i, GLP-1 RA, or referral to a specialist were noted in 19%, 33%, and 43% among low-, intermediate-, and high-risk patients, respectively. The median A1C decreased from 8.2% pre-test to 7.5% post-test in the high-risk group (P <.001). UACR levels in the intermediate-risk patients with albuminuria were reduced by 20%, and in a subgroup treated with new scripts for SGLT2i, UACR levels were lowered by approximately 50%. The median eGFR slope improved from −7.08 ml/min/1.73 m2/year to −4.27 ml/min/1.73 m2/year in high-risk patients (P =.0003), −2.65 to −1.04 in intermediate risk, and −3.26 ml/min/1.73 m2/year to +0.45 ml/min/1.73 m2/year in patients with low-risk (P <.001). Conclusions: Deployment and risk stratification by KidneyIntelX was associated with an escalation in action taken to optimize cardio-kidney-metabolic health including medications and specialist referrals. Glycemic control and kidney function trajectories improved post-KidneyIntelX testing, with the greatest improvements observed in those scored as high-risk. [ABSTRACT FROM AUTHOR]

Introduction and Objective: The lack of precision to identify patients with early-stage diabetic kidney disease (DKD) at near-term risk for progressive decline in kidney function results in poor disease management often leading to kidney failure requiring unplanned dialysis. The KidneyIntelX is a multiplex, bioprognostic, immunoassay consisting of 3 plasma biomarkers and clinical variables that uses machine learning to generate a risk score for progressive decline in kidney function over 5-year in adults with early-stage DKD. Our objective was to assess the impact of KidneyIntelX on management and outcomes in a Health System in the real-world evidence (RWE) study. Methods: KidneyIntelX was introduced into a large metropolitan Health System via a population health-defined approved care pathway for patients with stages 1 to 3 DKD between [November 2020 to March 2022]. Decision impact on visit frequency, medication management, specialist referral, and selected lab values was assessed. We performed an interim analysis in patients through 6-months post-test date to evaluate the impact of risk level with clinical decision-making and outcomes. Results: A total of 1686 patients were enrolled in the RWE study and underwent KidneyIntelX testing and subsequent care pathway management. The median age was 68 years, 52% were female, 26% self-identified as Black, and 94% had hypertension. The median baseline eGFR was 59 ml/minute/1.73 m2, urine albumincreatinine ratio was 69 mg/g, and HbA1c was 7.7%. After testing, a clinical encounter in the first month occurred in 13%, 43%, and 53% of low-risk, intermediate-risk, and high-risk patients, respectively and 46%, 61%, and 71% had at least 1 action taken within the first 6 months. High-risk patients were more likely to be placed on SGLT2 inhibitors (OR = 4.56; 95% CI 3.00-6.91 vs low-risk), and more likely to be referred to a specialist such as a nephrologist, endocrinologist, or dietician (OR = 2.49; 95% CI 1.53-4.01) compared to low-risk patients. Conclusions: The combination of KidneyIntelX, clinical guidelines and educational support resulted in changes in clinical management by clinicians. After testing, there was an increase in visit frequency, referrals for disease management, and introduction to guideline-recommended medications. These differed by risk category, indicating an impact of KidneyIntelX risk stratification on clinical care. [ABSTRACT FROM AUTHOR]

Decitabine, a cancer therapeutic that inhibits DNA methyl-ation, produces variable antitumor response rates in patients with solid tumors that might be leveraged clinically with identification of a predictive biomarker. In this study, we profiled the response of human ovarian, melanoma, and breast cancer cells treated with decitabine, finding that RAS/MEK/ERK pathway activation and DNMT1 expression correlated with cytotoxic activity. Further, we showed that KRAS genomic status predicted decitabine sensitivity in low-grade and high-grade serous ovarian cancer cells. Pretreatment with decitabine decreased the cytotoxic activity of MEK inhibitors in KRAS-mutant ovarian cancer cells, with reciprocal downregulation of DNMT1 and MEK/ERK phosphorylation. In parallel with these responses, decitabine also upregulated the proapoptotic BCL-2 family member BNIP3, which is known to be regulated by MEK and ERK, and heightened the activity of proapoptotic small-molecule navitoclax, a BCL-2 family inhibitor. In a xenograft model of KRAS-mutant ovarian cancer, combining decitabine and navitoclax heightened antitumor activity beyond administration of either compound alone. Our results define the RAS/MEK/DNMT1 pathway as a determinant of sensitivity to DNA methyltransferase inhibition, specifically implicating KRAS status as a biomarker of drug response in ovarian cancer. [ABSTRACT FROM AUTHOR]

Summary: The high rate of clinical response to protein-kinase-targeting drugs matched to cancer patients with specific genomic alterations has prompted efforts to use cancer cell line (CCL) profiling to identify additional biomarkers of small-molecule sensitivities. We have quantitatively measured the sensitivity of 242 genomically characterized CCLs to an Informer Set of 354 small molecules that target many nodes in cell circuitry, uncovering protein dependencies that: (1) associate with specific cancer-genomic alterations and (2) can be targeted by small molecules. We have created the Cancer Therapeutics Response Portal (http://www.broadinstitute.org/ctrp) to enable users to correlate genetic features to sensitivity in individual lineages and control for confounding factors of CCL profiling. We report a candidate dependency, associating activating mutations in the oncogene β-catenin with sensitivity to the Bcl-2 family antagonist, navitoclax. The resource can be used to develop novel therapeutic hypotheses and to accelerate discovery of drugs matched to patients by their cancer genotype and lineage. [Copyright &y& Elsevier]