Controlled Nutrient Delivery to Pancreatic Islets Using Polydopamine-Coated Mesoporous Silica Nanoparticles.

In this study, we designed a nanoscale platform for sustained amino acid delivery to support transplanted pancreatic islets. The platform features mesoporous silica nanoparticles (MSNPs) loaded with glutamine (G), an essential amino acid required for islet survival and function, and coated with polydopamine (PD). We investigated various PD concentrations (0.

Drug Integrating Amphiphilic Nano-Assemblies: 2. Spatiotemporal Distribution within Inflammation Sites.

The need for chronic systemic immunosuppression, which is associated with unavoidable side-effects, greatly limits the applicability of allogeneic cell transplantation for regenerative medicine applications including pancreatic islet cell transplantation to restore insulin production in type 1 diabetes (T1D). Cell transplantation in confined sites enables the localized delivery of anti-inflammatory and immunomodulatory drugs to prevent graft loss by innate and adaptive immunity, providing an opportunity to achieve local effects while minimizing unwanted systemic side effects. Nanoparticles can provide the means to achieve the needed localized and sustained drug delivery either by graft targeting or co-implantation.

Supervised Parametric Learning in the Identification of Composite Biomarker Signatures of Type 1 Diabetes in Integrated Parallel Multi-Omics Datasets.

Background: Type 1 diabetes (T1D) is a devastating autoimmune disease, and its rising prevalence in the United States and around the world presents a critical problem in public health. While some treatment options exist for patients already diagnosed, individuals considered at risk for developing T1D and who are still in the early stages of their disease pathogenesis without symptoms have no options for any preventive intervention. This is because of the uncertainty in determining their risk level and in predicting with high confidence who will progress, or not, to clinical diagnosis.

A Composite Biomarker Signature of Type 1 Diabetes Risk Identified via Augmentation of Parallel Multi-Omics Data from a Small Cohort.

Background: Biomarkers of early pathogenesis of type 1 diabetes (T1D) are crucial to enable effective prevention measures in at-risk populations before significant damage occurs to their insulin producing beta-cell mass. We recently introduced the concept of integrated parallel multi-omics and employed a novel data augmentation approach which identified promising candidate biomarkers from a small cohort of high-risk T1D subjects. We now validate selected biomarkers to generate a potential composite signature of T1D risk.

Quantitative receptor model for responses that are left- or right-shifted versus occupancy (are more or less concentration sensitive): the SABRE approach.

Simple one-to three-parameter models routinely used to fit typical dose-response curves and calculate EC values using the Hill or Clark equation cannot provide the full picture connecting measured response to receptor occupancy, which can be quite complex due to the interplay between partial agonism and (pathway-dependent) signal amplification. The recently introduced SABRE quantitative receptor model is the first one that explicitly includes a parameter for signal amplification () in addition to those for binding affinity ( ), receptor-activation efficacy (), constitutive activity ( ), and steepness of response (Hill slope, ). It can provide a unified framework to fit complex cases, where fractional response and occupancy do not match, as well as simple ones, where parameters constrained to specific values can be used (e.

Quantification of receptor binding from response data obtained at different receptor levels: a simple individual sigmoid fitting and a unified SABRE approach.

Methods that allow quantification of receptor binding (occupancy) by measuring response (effect) data only are of interest as they can be used to allow characterization of binding properties (e.g., dissociation constant, K) without having to perform explicit ligand binding experiments that require different setups (e.

Exploring Computational Data Amplification and Imputation for the Discovery of Type 1 Diabetes (T1D) Biomarkers from Limited Human Datasets.

Background: Type 1 diabetes (T1D) is a devastating disease with serious health complications. Early T1D biomarkers that could enable timely detection and prevention before the onset of clinical symptoms are paramount but currently unavailable. Despite their promise, omics approaches have so far failed to deliver such biomarkers, likely due to the fragmented nature of information obtained through the single omics approach.

Broad-Spectrum Small-Molecule Inhibitors of the SARS-CoV-2 Spike-ACE2 Protein-Protein Interaction from a Chemical Space of Privileged Protein Binders.

Therapeutically useful small-molecule inhibitors (SMIs) of protein−protein interactions (PPIs) initiating the cell attachment and entry of viruses could provide novel alternative antivirals that act via mechanisms similar to that of neutralizing antibodies but retain the advantages of small-molecule drugs such as oral bioavailability and low likelihood of immunogenicity. From screening our library, which is focused around the chemical space of organic dyes to provide good protein binders, we have identified several promising SMIs of the SARS-CoV-2 spike—ACE2 interaction, which is needed for the attachment and cell entry of this coronavirus behind the COVID-19 pandemic. They included organic dyes, such as Congo red, direct violet 1, and Evans blue, which seem to be promiscuous PPI inhibitors, as well as novel drug-like compounds (e.

Methylene Blue Is a Nonspecific Protein-Protein Interaction Inhibitor with Potential for Repurposing as an Antiviral for COVID-19.

We have previously identified methylene blue, a tricyclic phenothiazine dye approved for clinical use for the treatment of methemoglobinemia and for other medical applications as a small-molecule inhibitor of the protein-protein interaction (PPI) between the spike protein of the SARS-CoV-2 coronavirus and ACE2, the first critical step of the attachment and entry of this coronavirus responsible for the COVID-19 pandemic. Here, we show that methylene blue concentration dependently inhibits this PPI for the spike protein of the original strain as well as for those of variants of concern such as the D614G mutant and delta (B.1.

RNA aptamers specific for transmembrane p24 trafficking protein 6 and Clusterin for the targeted delivery of imaging reagents and RNA therapeutics to human β cells.

The ability to detect and target β cells in vivo can substantially refine how diabetes is studied and treated. However, the lack of specific probes still hampers a precise characterization of human β cell mass and the delivery of therapeutics in clinical settings. Here, we report the identification of two RNA aptamers that specifically and selectively recognize mouse and human β cells.

Cdc42 GTPase-activating proteins (GAPs) regulate generational inheritance of cell polarity and cell shape in fission yeast.

The highly conserved small GTPase Cdc42 regulates polarized cell growth and morphogenesis from yeast to humans. We previously reported that Cdc42 activation exhibits oscillatory dynamics at cell tips of cells. Mathematical modeling suggests that this dynamic behavior enables a variety of symmetric and asymmetric Cdc42 activation distributions to coexist in cell populations.

Small-Molecule Inhibitors of the Coronavirus Spike: ACE2 Protein-Protein Interaction as Blockers of Viral Attachment and Entry for SARS-CoV-2.

Inhibitors of the protein-protein interaction (PPI) between the SARS-CoV-2 spike protein and human ACE2 (hACE2), which acts as a ligand-receptor pair that initiates the viral attachment and cellular entry of this coronavirus causing the ongoing COVID-19 pandemic, are of considerable interest as potential antiviral agents. While blockade of such PPIs with small molecules is more challenging than that with antibodies, small-molecule inhibitors (SMIs) might offer alternatives that are less strain- and mutation-sensitive, suitable for oral or inhaled administration, and more controllable/less immunogenic. Here, we report the identification of SMIs of this PPI by screening our compound library focused around the chemical space of organic dyes.

Parallel Multi-Omics in High-Risk Subjects for the Identification of Integrated Biomarker Signatures of Type 1 Diabetes.

Background: Biomarkers are crucial for detecting early type-1 diabetes (T1D) and preventing significant β-cell loss before the onset of clinical symptoms. Here, we present proof-of-concept studies to demonstrate the potential for identifying integrated biomarker signature(s) of T1D using parallel multi-omics.

Methods: Blood from human subjects at high risk for T1D (and healthy controls; = 4 + 4) was subjected to parallel unlabeled proteomics, metabolomics, lipidomics, and transcriptomics.

Methylene Blue Inhibits the SARS-CoV-2 Spike-ACE2 Protein-Protein Interaction-a Mechanism that can Contribute to its Antiviral Activity Against COVID-19.

Due to our interest in the chemical space of organic dyes to identify potential small-molecule inhibitors (SMIs) for protein-protein interactions (PPIs), we initiated a screen of such compounds to assess their inhibitory activity against the interaction between SARS-CoV-2 spike protein and its cognate receptor ACE2, which is the first critical step initiating the viral attachment and entry of this coronavirus responsible for the ongoing COVID-19 pandemic. As part of this, we found that methylene blue, a tricyclic phenothiazine compound approved by the FDA for the treatment of methemoglobinemia and used for other medical applications (including the inactivation of viruses in blood products prior to transfusion when activated by light), inhibits this interaction. We confirmed that it does so in a concentration-dependent manner with a low micromolar half-maximal inhibitory concentration (IC = 3 μM) in our protein-based ELISA-type setup, while chloroquine, siramesine, and suramin showed no inhibitory activity in this assay.

Growth hormone-releasing hormone agonists ameliorate chronic kidney disease-induced heart failure with preserved ejection fraction.

Therapies for heart failure with preserved ejection fraction (HFpEF) are lacking. Growth hormone-releasing hormone agonists (GHRH-As) have salutary effects in ischemic and nonischemic heart failure animal models. Accordingly, we hypothesized that GHRH-A treatment ameliorates chronic kidney disease (CKD)-induced HFpEF in a large-animal model.

Drug-Integrating Amphiphilic Nanomaterial Assemblies: 1. Spatiotemporal control of cyclosporine delivery and activity using nanomicelles and nanofibrils.

Immunomodulatory therapies are limited by unavoidable side effects as well as poor solubility, stability, and pharmacokinetic properties. Nanomaterial-based drug delivery may overcome these limitations by increasing drug solubility, site-targeting, and duration of action. Here, we prepared innovative drug-integrating amphiphilic nanomaterial assemblies (DIANA) with tunable hydrophobicity, size, and morphology, and we evaluated their ability to deliver cyclosporine A (CsA) for immunomodulatory applications.

A Collagen Based Cryogel Bioscaffold that Generates Oxygen for Islet Transplantation.

The aim of this work was to develop, characterize and test a novel 3D bioscaffold matrix which can accommodate pancreatic islets and provide them with a continuous, controlled and steady source of oxygen to prevent hypoxia-induced damage following transplantation. Hence, we made a collagen based cryogel bioscaffold which incorporated calcium peroxide (CPO) into its matrix. The optimal concentration of CPO integrated into bioscaffolds was 0.

Controlled Nutrient Delivery to Pancreatic Islets Using Polydopamine-Coated Mesoporous Silica Nanoparticles.

In the present study, we created a nanoscale platform that can deliver nutrients to pancreatic islets in a controlled manner. Our platform consists of a mesoporous silica nanoparticle (MSNP), which can be loaded with glutamine (G: an essential amino acid required for islet survival and function). To control the release of G, MSNPs were coated with a polydopamine (PD) layer.

A single unified model for fitting simple to complex receptor response data.

The fitting of complex receptor-response data where fractional response and occupancy do not match is challenging. They encompass important cases including (a) the presence of "receptor reserve" and/or partial agonism, (b) multiple responses assessed at different vantage points along a pathway, (c) responses that are different along diverging downstream pathways (biased agonism), and (d) constitutive activity. For these, simple models such as the well-known Clark or Hill equations cannot be used.

Longitudinal proteomics analysis in the immediate microenvironment of islet allografts during progression of rejection.

The applicability and benefits of pancreatic islet transplantation are limited due to various issues including the need to avoid immune-mediated rejection. Here, we used our experimental platform of allogeneic islet transplant in the anterior chamber of the eye (ACE-platform) to longitudinally monitor the progress of rejection in mice and obtain aqueous humor samples representative of the microenvironment of the graft for accurately-timed proteomic analyses. LC-MS/MS-based proteomics performed on such mass-limited samples (~5 μL) identified a total of 1296 proteins.

The Effect of Recovery Warm-up Time Following Cold Storage on the Dynamic Glucose-stimulated Insulin Secretion of Isolated Human Islets.

Standardized islet characterization assays that can provide results in a timely manner are essential for successful islet cell transplantation. A critical component of islet cell quality is β-cell function, and perifusion-based assessments of dynamic glucose-stimulated insulin secretion (GSIS) are the most informative method to assess this, as they provide the most complex in vitro evaluation of GSIS. However, protocols used vary considerably among centers and investigators as they often use different low- and high-glucose concentrations, exposure-times, flow-rates, oxygen concentrations, islet numbers, analytical methods, measurement units, and instruments, which result in different readouts and make comparisons across platforms difficult.