UNLABELLED: The ability to noninvasively measure endogenous pancreatic β-cell mass (BCM) would accelerate research on the pathophysiology of diabetes and revolutionize the preclinical development of new treatments, the clinical assessment of therapeutic efficacy, and the early diagnosis and subsequent monitoring of disease progression. The vesicular monoamine transporter type 2 (VMAT2) is coexpressed with insulin in β-cells and represents a promising target for BCM imaging. METHODS: We evaluated the VMAT2 radiotracer (18)F-fluoropropyl-dihydrotetrabenazine ((18)F-FP-(+)-DTBZ, also known as (18)F-AV-133) for quantitative PET of BCM in healthy control subjects and patients with type 1 diabetes mellitus. Standardized uptake value was calculated as the net tracer uptake in the pancreas normalized by injected dose and body weight. Total volume of distribution, the equilibrium ratio of tracer concentration in tissue relative to plasma, was estimated by kinetic modeling with arterial input functions. Binding potential, the steady-state ratio of specific binding to nondisplaceable uptake, was calculated using the renal cortex as a reference tissue devoid of specific VMAT2 binding. RESULTS: Mean pancreatic standardized uptake value, total volume of distribution, and binding potential were reduced by 38%, 20%, and 40%, respectively, in type 1 diabetes mellitus. The radiotracer binding parameters correlated with insulin secretion capacity as determined by arginine-stimulus tests. Group differences and correlations with β-cell function were enhanced for total pancreas binding parameters that accounted for tracer binding density and organ volume. CONCLUSION: These findings demonstrate that quantitative evaluation of islet β-cell density and aggregate BCM can be performed clinically with (18)F-FP-(+)-DTBZ PET.

The objective of this study was to test a comprehensive model of biologic (pubertal status), family (communication and conflict), and psychological influences (behavioral autonomy) on diabetes management and glycemic control in a sample of youth (N = 226) with type 1 diabetes recruited during late childhood/early adolescence (ages 9-11 years). The study design was a prospective, multisite, multi-method study involving prediction of diabetes management and glycemic control 1 year post-baseline. The primary outcome measures included diabetes management behaviors based on the Diabetes Self-Management Profile (DSMP) administered separately to mothers and youth and glycemic control measured by glycated hemoglobin (HbA1c) obtained by blood samples and analyzed by a central laboratory to ensure standardization. Our hypothesized predictive model received partial support based on structural equation modeling analyses. Family conflict predicted less adequate glycemic control 1 year later (p < 0.05). Higher conflict predicted less adequate diabetes management and less adequate glycemic control. More advanced pubertal status also predicted less adequate glycemic control, but behavioral autonomy did not. Family conflict is an important, potentially clinically significant influence on glycemic control that should be considered in primary and secondary prevention in the management of type 1 diabetes in youth.

Antibody class defines function in B cell immunity, but how class is propagated into B cell memory remains poorly understood. Here we demonstrate that memory B cell subsets unexpectedly diverged across antibody class through differences in the effects of major transcriptional regulators. Conditional genetic deletion of the gene encoding the transcription factor T-bet selectively blocked the formation and antigen-specific response of memory B cells expressing immunoglobulin G2a (IgG2a) in vivo. Cell-intrinsic expression of T-bet regulated expression of the transcription factor STAT1, steady-state cell survival and transcription of IgG2a-containing B cell antigen receptors (BCRs). In contrast, the transcription factor RORα and not T-bet was expressed in IgA(+) memory B cells, with evidence that knockdown of RORα mRNA expression and chemical inhibition of transcriptional activity also resulted in lower survival and BCR expression of IgA(+) memory B cells. Thus, divergent transcriptional regulators dynamically maintain subset integrity to promote specialized immune function in class-specific memory B cells.

Significant progress has been made in understanding pharmacokinetics (PK), pharmacodynamics (PD), as well as toxicity profiles of therapeutic proteins in animals and humans, which have been in commercial development for more than three decades. However, in the PK arena, many fundamental questions remain to be resolved. Investigative and bioanalytical tools need to be established to improve the translation of PK data from animals to humans, and from in vitro assays to in vivo readouts, which would ultimately lead to a higher success rate in drug development. In toxicology, it is known, in general, what studies are needed to safely develop therapeutic proteins, and what studies do not provide relevant information. One of the major complicating factors in nonclinical and clinical programs for therapeutic proteins is the impact of immunogenicity. In this review, we will highlight the emerging science and technology, as well as the challenges around the pharmacokinetic- and safety-related issues in drug development of mAbs and other therapeutic proteins.

Differential scanning fluorometry (DSF), also referred to as fluorescence thermal shift, is emerging as a convenient method to evaluate the stabilizing effect of small molecules on proteins of interest. However, its use in the mechanism of action studies has received far less attention. Herein, the ability of DSF to report on inhibitor mode of action was evaluated using glutathione S-transferase (GST) as a model enzyme that utilizes two distinct substrates and is known to be subject to a range of inhibition modes. Detailed investigation of the propensity of small molecule inhibitors to protect GST from thermal denaturation revealed that compounds with different inhibition modes displayed distinct thermal shift signatures when tested in the presence or absence of the enzyme's native co-substrate glutathione (GSH). Glutathione-competitive inhibitors produced dose-dependent thermal shift trendlines that converged at high compound concentrations. Inhibitors acting via the formation of glutathione conjugates induced a very pronounced stabilizing effect toward the protein only when GSH was present. Lastly, compounds known to act as noncompetitive inhibitors exhibited parallel concentration-dependent trends. Similar effects were observed with human GST isozymes A1-1 and M1-1. The results illustrate the potential of DSF as a tool to differentiate diverse classes of inhibitors based on simple analysis of co-substrate dependency of protein stabilization.

BACKGROUND: Oxidative stress has been implicated in the pathogenesis of a variety of diseases ranging from cancer to neurodegeneration, highlighting the need to identify chemicals that can induce this effect. The antioxidant response element (ARE) signaling pathway plays an important role in the amelioration of oxidative stress. Thus, assays that detect the up-regulation of this pathway could be useful for identifying chemicals that induce oxidative stress. OBJECTIVES: We used cell-based reporter methods and informatics tools to efficiently screen a large collection of environmental chemicals and identify compounds that induce oxidative stress. METHODS: We utilized two cell-based ARE assay reporters, β-lactamase and luciferase, to screen a U.S. National Toxicology Program 1,408-compound library (NTP 1408, which contains 1,340 unique compounds) for their ability to induce oxidative stress in HepG2 cells using quantitative high throughput screening (qHTS). RESULTS: Roughly 3% (34 of 1,340) of the unique compounds demonstrated activity across both cell-based assays. Based on biological activity and structure-activity relationship profiles, we selected 50 compounds for retesting in the two ARE assays and in an additional follow-up assay that employed a mutated ARE linked to β-lactamase. Using this strategy, we identified 30 compounds that demonstrated activity in the ARE-bla and ARE-luc assays and were able to determine structural features conferring compound activity across assays. CONCLUSIONS: Our results support the robustness of using two different cell-based approaches for identifying compounds that induce ARE signaling. Together, these methods are useful for prioritizing chemicals for further in-depth mechanism-based toxicity testing.

Community research and action projects undertaken by community-university partnerships can lead to contextually appropriate and sustainable community improvements in rural and urban localities. However, effective implementation is challenging and prone to failure when poorly executed. The current paper seeks to inform rural community-university partnership practice through consideration of first-person accounts from five stakeholders in the Rural Embedded Assistants for Community Health (REACH) Network. The REACH Network is a unique community-university partnership aimed at improving rural health services by identifying, implementing, and evaluating innovative health interventions delivered by local caregivers. The first-person accounts provide an insider's perspective on the nature of collaboration. The unique perspectives identify three critical challenges facing the REACH Network: trust, coordination, and sustainability. Through consideration of the challenges, we identified several strategies for success. We hope readers can learn their own lessons when considering the details of our partnership's efforts to improve the delivery infrastructure for rural healthcare.

BACKGROUND: Despite the increasing prevalence of type 2 diabetes in youth, there are few data to guide treatment. We compared the efficacy of three treatment regimens to achieve durable glycemic control in children and adolescents with recent-onset type 2 diabetes. METHODS: Eligible patients 10 to 17 years of age were treated with metformin (at a dose of 1000 mg twice daily) to attain a glycated hemoglobin level of less than 8% and were randomly assigned to continued treatment with metformin alone or to metformin combined with rosiglitazone (4 mg twice a day) or a lifestyle-intervention program focusing on weight loss through eating and activity behaviors. The primary outcome was loss of glycemic control, defined as a glycated hemoglobin level of at least 8% for 6 months or sustained metabolic decompensation requiring insulin. RESULTS: Of the 699 randomly assigned participants (mean duration of diagnosed type 2 diabetes, 7.8 months), 319 (45.6%) reached the primary outcome over an average follow-up of 3.86 years. Rates of failure were 51.7% (120 of 232 participants), 38.6% (90 of 233), and 46.6% (109 of 234) for metformin alone, metformin plus rosiglitazone, and metformin plus lifestyle intervention, respectively. Metformin plus rosiglitazone was superior to metformin alone (P=0.006); metformin plus lifestyle intervention was intermediate but not significantly different from metformin alone or metformin plus rosiglitazone. Prespecified analyses according to sex and race or ethnic group showed differences in sustained effectiveness, with metformin alone least effective in non-Hispanic black participants and metformin plus rosiglitazone most effective in girls. Serious adverse events were reported in 19.2% of participants. CONCLUSIONS: Monotherapy with metformin was associated with durable glycemic control in approximately half of children and adolescents with type 2 diabetes. The addition of rosiglitazone, but not an intensive lifestyle intervention, was superior to metformin alone. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases and others; TODAY ClinicalTrials.gov number, NCT00081328.).

The structural integrity of myelin formed by Schwann cells in the peripheral nervous system (PNS) is required for proper nerve conduction and is dependent on adequate expression of myelin genes including peripheral myelin protein 22 (PMP22). Consequently, excess PMP22 resulting from its genetic duplication and overexpression has been directly associated with the peripheral neuropathy called Charcot-Marie-Tooth disease type 1A (CMT1A), the most prevalent type of CMT. Here, in an attempt to identify transcriptional inhibitors with therapeutic value toward CMT1A, we developed a cross-validating pair of orthogonal reporter assays, firefly luciferase (FLuc) and β-lactamase (βLac), capable of recapitulating PMP22 expression, utilizing the intronic regulatory element of the human PMP22 gene. Each compound from a collection of approximately 3,000 approved drugs was tested at multiple titration points to achieve a pharmacological end point in a 1536-well plate quantitative high-throughput screen (qHTS) format. In conjunction with an independent counter-screen for cytotoxicity, the design of our orthogonal screen platform effectively contributed to selection and prioritization of active compounds, among which three drugs (fenretinide, olvanil, and bortezomib) exhibited marked reduction of endogenous Pmp22 mRNA and protein. Overall, the findings of this study provide a strategic approach to assay development for gene-dosage diseases such as CMT1A.

The limitations of traditional toxicity testing characterized by high-cost animal models with low-throughput readouts, inconsistent responses, ethical issues, and extrapolability to humans call for alternative strategies for chemical risk assessment. A new strategy using in vitro human cell-based assays has been designed to identify key toxicity pathways and molecular mechanisms leading to the prediction of an in vivo response. The emergence of quantitative high-throughput screening (qHTS) technology has proved to be an efficient way to decompose complex toxicological end points to specific pathways of targeted organs. In addition, qHTS has made a significant impact on computational toxicology in two aspects. First, the ease of mechanism of action identification brought about by in vitro assays has enhanced the simplicity and effectiveness of machine learning, and second, the high-throughput nature and high reproducibility of qHTS have greatly improved the data quality and increased the quantity of training datasets available for predictive model construction. In this review, the benefits of qHTS routinely used in the US Tox21 program will be highlighted. Quantitative structure-activity relationships models built on traditional in vivo data and new qHTS data will be compared and analyzed. In conjunction with the transition from the pilot phase to the production phase of the Tox21 program, more qHTS data will be made available that will enrich the data pool for predictive toxicology. It is perceivable that new in silico toxicity models based on high-quality qHTS data will achieve unprecedented reliability and robustness, thus becoming a valuable tool for risk assessment and drug discovery.