A model-based approach to investigating the relationship between glucose-insulin dynamics and dapagliflozin treatment effect in patients with type 2 diabetes.

AIMS: To develop a quantitative systems pharmacology model to describe the effect of dapagliflozin (a sodium-glucose co-transporter-2 [SGLT2] inhibitor) on glucose-insulin dynamics in type 2 diabetes mellitus (T2DM) patients, and to identify key determinants of treatment-mediated glycated haemoglobin (HbA1c) reduction. MATERIALS AND METHODS: Glycaemic control during dapagliflozin treatment was mechanistically characterized by integrating components representing dapagliflozin pharmacokinetics (PK), glucose-insulin homeostasis, renal glucose reabsorption, and HbA1c formation. The model was developed using PK variables, glucose, plasma insulin, and urinary glucose excretion (UGE) from a phase IIa dapagliflozin trial in patients with T2DM (NCT00162305). The model was used to predict dapagliflozin-induced HbA1c reduction; model predictions were compared to actual data from phase III trials (NCT00528879, NCT00683878, NCT00680745 and NCT00673231). RESULTS: The integrated glucose-insulin-dapagliflozin model successfully described plasma glucose and insulin levels, as well as UGE in response to oral glucose tolerance tests and meal intake. HbA1c reduction was also well predicted. The results show that dapagliflozin-mediated glycaemic control is anticorrelated to steady-state insulin concentration and insulin sensitivity. CONCLUSIONS: The developed model framework is the first to integrate SGLT2 inhibitor mechanism of action with both short-term glucose-insulin dynamics and long-term glucose control (HbA1c). The results suggest that dapagliflozin treatment is beneficial in patients with inadequate glycaemic control from insulin alone and this benefit increases as insulin control diminishes.

Profiling Subcellular Protein Phosphatase Responses to Coxsackievirus B3 Infection of Cardiomyocytes.

Cellular responses to stimuli involve dynamic and localized changes in protein kinases and phosphatases. Here, we report a generalized functional assay for high-throughput profiling of multiple protein phosphatases with subcellular resolution and apply it to analyze coxsackievirus B3 (CVB3) infection counteracted by interferon signaling. Using on-plate cell fractionation optimized for adherent cells, we isolate protein extracts containing active endogenous phosphatases from cell membranes, the cytoplasm, and the nucleus. The extracts contain all major classes of protein phosphatases and catalyze dephosphorylation of plate-bound phosphosubstrates in a microtiter format, with cellular activity quantified at the end point by phosphospecific ELISA. The platform is optimized for six phosphosubstrates (ERK2, JNK1, p38α, MK2, CREB, and STAT1) and measures specific activities from extracts of fewer than 50,000 cells. The assay was exploited to examine viral and antiviral signaling in AC16 cardiomyocytes, which we show can be engineered to serve as susceptible and permissive hosts for CVB3. Phosphatase responses were profiled in these cells by completing a full-factorial experiment for CVB3 infection and type I/II interferon signaling. Over 850 functional measurements revealed several independent, subcellular changes in specific phosphatase activities. During CVB3 infection, we found that type I interferon signaling increases subcellular JNK1 phosphatase activity, inhibiting nuclear JNK1 activity that otherwise promotes viral protein synthesis in the infected host cell. Our assay provides a high-throughput way to capture perturbations in important negative regulators of intracellular signal-transduction networks.

Variables that impact HPV test accuracy during vaginal self collection workflow for cervical cancer screening.

Vaginal self collection (SC) is safe and effective for human papillomavirus (HPV) testing and can increase cervical cancer screening coverage for underserved women. To better understand the impact of SC methodology on HPV test outcomes, empirical testing was conducted using different swab collection workflows. Deposition of the collection swab into resuspension buffer resulted in a 2.4-cycle reduction in threshold detection of human beta-hemoglobin during PCR when compared to "swirl-and-toss". In addition, reducing the swab resuspension volume from 10 mL to 3 mL resulted in a 2.6-cycle reduction in threshold detection of human beta-globin. A systematic literature search (01/01/2020 to 08/02/2023) of Ovid Medline and Embase, followed by data extraction and analysis, was conducted to further assess the impact of resuspension volume on performance following SC. HPV test performance for SC, relative to clinician collection (CC), was calculated for detection of cervical pre-cancer. Data were stratified by the resuspension volume ratio of SC to CC being either ≥ 1.0 or < 1.0. SC with a volume ratio of ≥ 1.0 and < 1.0 had a relative ≥ CIN2 sensitivity of 92.0 % (95 % CI: 88.0, 96.0) and 97.0 % (95 % CI: 94.0, 100), respectively. Taken together, these results suggest that SC conditions can be modified to optimize sample recovery and performance, as part of cervical cancer screening.

Three Modes of Viral Adaption by the Heart.

Viruses elicit long-term adaptive responses in the tissues they infect. Understanding viral adaptions in humans is difficult in organs such as the heart, where primary infected material is not routinely collected. In search of asymptomatic infections with accompanying host adaptions, we mined for cardio-pathogenic viruses in the unaligned reads of nearly one thousand human hearts profiled by RNA sequencing. Among virus-positive cases (~20%), we identified three robust adaptions in the host transcriptome related to inflammatory NFκB signaling and post-transcriptional regulation by the p38-MK2 pathway. The adaptions are not determined by the infecting virus, and they recur in infections of human or animal hearts and cultured cardiomyocytes. Adaptions switch states when NFκB or p38-MK2 are perturbed in cells engineered for chronic infection by the cardio-pathogenic virus, coxsackievirus B3. Stratifying viral responses into reversible adaptions adds a targetable systems-level simplification for infections of the heart and perhaps other organs.

Modeling the complete kinetics of coxsackievirus B3 reveals human determinants of host-cell feedback.

Complete kinetic models are pervasive in chemistry but lacking in biological systems. We encoded the complete kinetics of infection for coxsackievirus B3 (CVB3), a compact and fast-acting RNA virus. The model consists of separable, detailed modules describing viral binding-delivery, translation-replication, and encapsidation. Specific module activities are dampened by the type I interferon response to viral double-stranded RNAs (dsRNAs), which is itself disrupted by viral proteinases. The experimentally validated kinetics uncovered that cleavability of the dsRNA transducer mitochondrial antiviral signaling protein (MAVS) becomes a stronger determinant of viral outcomes when cells receive supplemental interferon after infection. Cleavability is naturally altered in humans by a common MAVS polymorphism, which removes a proteinase-targeted site but paradoxically elevates CVB3 infectivity. These observations are reconciled with a simple nonlinear model of MAVS regulation. Modeling complete kinetics is an attainable goal for small, rapidly infecting viruses and perhaps viral pathogens more broadly. A record of this paper's transparent peer review process is included in the Supplemental information.

Modeling chemotherapy-induced stress to identify rational combination therapies in the DNA damage response pathway.

Cells respond to DNA damage by activating complex signaling networks that decide cell fate, promoting not only DNA damage repair and survival but also cell death. We have developed a multiscale computational model that quantitatively links chemotherapy-induced DNA damage response signaling to cell fate. The computational model was trained and calibrated on extensive data from U2OS osteosarcoma cells, including the cell cycle distribution of the initial cell population, signaling data measured by Western blotting, and cell fate data in response to chemotherapy treatment measured by time-lapse microscopy. The resulting mechanistic model predicted the cellular responses to chemotherapy alone and in combination with targeted inhibitors of the DNA damage response pathway, which we confirmed experimentally. Computational models such as the one presented here can be used to understand the molecular basis that defines the complex interplay between cell survival and cell death and to rationally identify chemotherapy-potentiating drug combinations.

Characteristics That May Help in the Identification of Potentially Confusing Proprietary Drug Names.

PURPOSE: This study aimed to provide a descriptive analysis of characteristics that are common among drug name pairs involved in name confusion medication errors. METHODS: We evaluated drug name pairs that contained at least one proprietary name from the Institute for Safe Medication Practices (ISMP) List of Confused Drug Names. For each name pair, we analyzed whether the following characteristics were present: (1) the same first letter, (2) a shared letter string of at least 3 letters, and (3) similarity in the number of letters. Additionally, we obtained the combined Phonetic and Orthographic Computer Analysis (POCA) score. RESULTS: Ninety-nine percent of the drug name pairs reflected at least one of the 3 characteristics analyzed. Additionally, 75% of the names had a combined POCA score of ≥50%. CONCLUSIONS: This descriptive analysis provides some insight into characteristics that may be associated with name confusion, which should be considered when formulating and evaluating proposed proprietary drug names.