Niven R. Narain

Development and characterization of phospholipid-stabilized submicron aqueous dispersions of coenzyme Q10 presenting continuous vibrating-mesh nebulization performance

Abstract Coenzyme Q10 (CoQ10) is a poorly-water soluble compound that is being investigated for the treatment of carcinomas. The aim of this research was to develop a suitable formulation for pulmonary delivery of this anticancer agent. An appropriate selection of excipients (phospholipids) and a suitable device (Aeroneb Pro® vibrating-mesh nebulizer) were selected initially after reviewing the literature. After characterization of the bulk drug, a feasible manufacturing process was selected to obtain small particle size dispersions of CoQ10. Following selection of an appropriate process, the parameters affecting drug particle size were studied. Using LD and gravimetrical analysis, nebulization was evaluated to assess the performance of the inhalation system triad: drug–excipients–device. CoQ10 powder studied was crystalline with a melting point approximately at 51 °C and with a particle size of 30 µm. Microfluidization was found to be a suitable method to prepare submicron drug particles in aqueous dispersions. Increasing microfluidization processing to more than 50 passes did not provide further particle downsizing for both soya phosphatidylcholine (lecithin) and dipalmitoyl phosphatidylcholine (DPPC) dispersions of CoQ10, presenting Z-average values of approximately 130 and 70 nm, respectively. Nebulization performance of lecithin-stabilized CoQ10 dispersions varied according to number of passes in the microfluidizer. Formulations processed with 10 passes presented steadier nebulization over time and different rheological behavior compared to those processed with 30 or 50 passes. In conclusion, aqueous dispersions of CoQ10 were adequately produced using a microfluidizer with characteristics that were suitable for pulmonary delivery with an Aeroneb Pro® nebulizer. Furthermore, the rheology of these dispersions appeared to play a significant role in the aerosol generation from the active vibrating-mesh nebulizer used.

Intrinsic Properties of Brown and White Adipocytes Have Differential Effects on Macrophage Inflammatory Responses

Obesity is marked by chronic, low-grade inflammation. Here, we examined whether intrinsic differences between white and brown adipocytes influence the inflammatory status of macrophages. White and brown adipocytes were characterized by transcriptional regulation of UCP-1, PGC1α, PGC1β, and CIDEA and their level of IL-6 secretion. The inflammatory profile of PMA-differentiated U937 and THP-1 macrophages, in resting state and after stimulation with LPS/IFN-gamma and IL-4, was assessed by measuring IL-6 secretion and transcriptional regulation of a panel of inflammatory genes after mono- or indirect coculture with white and brown adipocytes. White adipocyte monocultures show increased IL-6 secretion compared to brown adipocytes. White adipocytes cocultured with U937 and THP-1 macrophages induced a greater increase in IL-6 secretion compared to brown adipocytes cocultured with both macrophages. White adipocytes cocultured with macrophages increased inflammatory gene expression in both types. In contrast, macrophages cocultured with brown adipocytes induced downregulation or no alterations in inflammatory gene expression. The effects of adipocytes on macrophages appear to be independent of stimulation state. Brown adipocytes exhibit an intrinsic ability to dampen inflammatory profile of macrophages, while white adipocytes enhance it. These data suggest that brown adipocytes may be less prone to adipose tissue inflammation that is associated with obesity.

Non-obvious correlations to disease management unraveled by Bayesian artificial intelligence analyses of CMS data

OBJECTIVE Given the availability of extensive digitized healthcare data from medical records, claims and prescription information, it is now possible to use hypothesis-free, data-driven approaches to mine medical databases for novel insight. The goal of this analysis was to demonstrate the use of artificial intelligence based methods such as Bayesian networks to open up opportunities for creation of new knowledge in management of chronic conditions. MATERIALS AND METHODS Hospital level Medicare claims data containing discharge numbers for most common diagnoses were analyzed in a hypothesis-free manner using Bayesian networks learning methodology. RESULTS While many interactions identified between discharge rates of diagnoses using this data set are supported by current medical knowledge, a novel interaction linking asthma and renal failure was discovered. This interaction is non-obvious and had not been looked at by the research and clinical communities in epidemiological or clinical data. A plausible pharmacological explanation of this link is proposed together with a verification of the risk significance by conventional statistical analysis. CONCLUSION Potential clinical and molecular pathways defining the relationship between commonly used asthma medications and renal disease are discussed. The study underscores the need for further epidemiological research to validate this novel hypothesis. Validation will lead to advancement in clinical treatment of asthma & bronchitis, thereby, improving patient outcomes and leading to long term cost savings. In summary, this study demonstrates that application of advanced artificial intelligence methods in healthcare has the potential to enhance the quality of care by discovering non-obvious, clinically relevant relationships and enabling timely care intervention.

Lipidomic Adaptations in White and Brown Adipose Tissue in Response to Exercise Demonstrate Molecular Species-Specific Remodeling

Exercise improves whole-body metabolic health through adaptations to various tissues, including adipose tissue, but the effects of exercise training on the lipidome of white adipose tissue (WAT) and brown adipose tissue (BAT) are unknown. Here, we utilize MS/MSALL shotgun lipidomics to determine the molecular signatures of exercise-induced adaptations to subcutaneous WAT (scWAT) and BAT. Three weeks of exercise training decrease specific molecular species of phosphatidic acid (PA), phosphatidylcholines (PC), phosphatidylethanolamines (PE), and phosphatidylserines (PS) in scWAT and increase specific molecular species of PC and PE in BAT. Exercise also decreases most triacylglycerols (TAGs) in scWAT and BAT. In summary, exercise-induced changes to the scWAT and BAT lipidome are highly specific to certain molecular lipid species, indicating that changes in tissue lipid content reflect selective remodeling in scWAT and BAT of both phospholipids and glycerol lipids in response to exercise training, thus providing a comprehensive resource for future studies of lipid metabolism pathways.

Monoacylglycerol Analysis Using MS/MSALL Quadruple Time of Flight Mass Spectrometry

Monoacylglycerols (MAGs) are structural and bioactive metabolites critical for biological function. Development of facile tools for measuring MAG are essential to understand its role in different diseases and various pathways. A data-independent acquisition method, MS/MSALL, using electrospray ionization (ESI) coupled quadrupole time of flight mass spectrometry (MS), was utilized for the structural identification and quantitative analysis of individual MAG molecular species. Compared with other acylglycerols, diacylglycerols (DAG) and triacylglycerols (TAG), MAG characteristically presented as a dominant protonated ion, [M + H]+, and under low collision energy as fatty acid-like fragments due to the neutral loss of the glycerol head group. At low concentrations (<10 pmol/µL), where lipid-lipid interactions are rare, there was a strong linear correlation between ion abundance and MAG concentration. Moreover, using the MS/MSALL method the major MAG species from human plasma and mouse brown and white adipose tissues were quantified in less than 6 min. Collectively, these results demonstrate that MS/MSALL analysis of MAG is an enabling strategy for the direct identification and quantitative analysis of low level MAG species from biological samples with high throughput and sensitivity.

Identification of Filamin-A and -B as potential biomarkers for prostate cancer

Aim: A novel strategy for prostate cancer (PrCa) biomarker discovery is described. Materials & methods: In vitro perturbation biology, proteomics and Bayesian causal analysis identified biomarkers that were validated in in vitro models and clinical specimens. Results: Filamin-B (FLNB) and Keratin-19 were identified as biomarkers. Filamin-A (FLNA) was found to be causally linked to FLNB. Characterization of the biomarkers in a panel of cells revealed differential mRNA expression and regulation. Moreover, FLNA and FLNB were detected in the conditioned media of cells. Last, in patients without PrCa, FLNA and FLNB blood levels were positively correlated, while in patients with adenocarcinoma the relationship is dysregulated. Conclusion: These data support the strategy and the potential use of the biomarkers for PrCa.

Regulation of Human Adipose Tissue Activation, Gallbladder Size, and Bile Acid Metabolism by a β3-Adrenergic Receptor Agonist

β3-adrenergic receptor (AR) agonists are approved to treat only overactive bladder. However, rodent studies suggest that these drugs could have other beneficial effects on human metabolism. We performed tissue receptor profiling and showed that the human β3-AR mRNA is also highly expressed in gallbladder and brown adipose tissue (BAT). We next studied the clinical implications of this distribution in 12 healthy men given one-time randomized doses of placebo, the approved dose of 50 mg, and 200 mg of the β3-AR agonist mirabegron. There was a more-than-dose-proportional increase in BAT metabolic activity as measured by [18F]-2-fluoro-D-2-deoxy-d-glucose positron emission tomography/computed tomography (medians 0.0 vs. 18.2 vs. 305.6 mL ⋅ mean standardized uptake value [SUVmean] ⋅ g/mL). Only the 200-mg dose elevated both nonesterified fatty acids (68%) and resting energy expenditure (5.8%). Previously undescribed increases in gallbladder size (35%) and reductions in conjugated bile acids were also discovered. Therefore, besides urinary bladder relaxation, the human β3-AR contributes to white adipose tissue lipolysis, BAT thermogenesis, gallbladder relaxation, and bile acid metabolism. This physiology should be considered in the development of more selective β3-AR agonists to treat obesity-related complications.

Clinical metabolomics: a pivotal tool for companion diagnostic development and precision medicine

Translation of companion diagnostic (CDx) development into a personalized clinical application remains a challenging task. It requires integration of multidimensional molecular and clinical data into patient-centric models. Family history, clinical history, and physical examination are mandatory for the interpretation of laboratory results. The inclusion of metabolomics data into the molecular architecture of the patient analyses allows for a more robust biological narrative. To empower broad spectrum utility in population health, adherence to protocol standardization and data accuracy will enable more predictive outcomes. A transformative evolution in healthcare has been galvanized, engaging patient and population biology for theranostic drug development. Theranostics employs diagnostic testing to select a targeted therapy for individuals. This approach serves as the catalyst for implementing mainstream precision medicine. Precision medicine focuses on identifying effective quantitative approaches aligning single-agent or combinational regimens based on genetics; demographics; socioeconomic status; ethnicity; gender; and environmental, metabolic, and lifestyle factors of the patient. For implementation, two essential guiding principles should be followed for CDx development. First, identification of valid biomarker panels which define positive or negative treatment outcomes, as well as adverse event risk factors for an individual or a population. Second, a reproducible method is required for detecting the biomarker panel in the population. This scheme aligns the intervention and the selectionmethod for CDx development in precisionmedicine. The FDA defines CDx as a tool or imaging device that provides information essential for the safe and effective use of a corresponding treatment [1]. This approach demands patient stratification, i.e. identifying populations which are more likely to benefit from the therapy. In the past, drug development began with preclinical studies and progressed toward NDA submission. However, CDx development also includes individual biomarker (or panel development) and advances toward regulatory submission and CDx launch, which is often in addition to the therapeutic launch. The impact of CDx implementation as a method for the development of new drugs is profound. Preferably, CDx incorporation should be early in the drug development process, although it can also occur at later stages of clinical development. In the era of precision medicine, a novel panel of diagnostic markers can change the economics of drug development as well as the economics of the market size significantly, depending on whether the biomarker panel is labeled as a CDx or a complementary diagnostic [2]. These processes are all dependent on the path of the specific drug in CDx development, and the regulatory and compliance decisions enacted upon in pivotal clinical studies. Additional processes are guided by population selection based on diagnostic cutoff points and determination of the evasive zones’ positive and negative predictive assessment. The complexity of CDx development, particularly in parallel to a new drug development course, requires coordination across several cross-functional units and potentially also across organizations. Incorporating CDx into drug development infuses a more precise and accurate approach to matching patient populations to effective therapeutics. Moreover, in reimbursement environments that are leaning toward outcome-based models, CDx may emerge as the cardinal tool for clinical focus and revenue forecasting [3].

Reduced expression of collagen VI alpha 3 (COL6A3) confers resistance to inflammation-induced MCP1 expression in adipocytes

Collagen VI alpha 3 (COL6A3) is associated with insulin resistance and adipose tissue inflammation. In this study, the role of COL6A3 in human adipocyte function was characterized.

Development of Aqueous Dispersions of Coenzyme Q10 for Pulmonary Delivery and the Dynamics of Active Vibrating-Mesh Aerosolization.

Coenzyme Q10 (CoQ10) is a poorly-water soluble compound that is being investigated for the treatment of carcinomas. The aim of this study was to investigate the feasibility of preparing phospholipid-stabilized dispersions of the anticancer agent for continuous pulmonary delivery using a vibrating-mesh nebulizer. We determined the physicochemical properties (drug particle size distribution in dispersion, zeta potential, surface tension, and rheology) and compared the aerosolization profiles (nebulization performance, aerodynamic drug deposition and total emitted dose) of dispersions of CoQ10 prepared with different phospholipids. The hydrodynamic sizes of the drug particles in dispersion were primarily in the submicron range, but formulations with drug particle sizes greater than the aperture size of the nebulizer presented superior aerosolization profiles. At high shear rates, certain formulations presented increased shear-thickening behavior, which was connected to a decrease in mass and drug output over time, and with decreased aerodynamic and geometric sizes. Other formulations presented shear-thinning behavior and showed similarly high drug depositions. In this investigation, we found that dispersed formulations of CoQ10 presented different in vitro performance for pulmonary delivery based on their rheological behavior. In conclusion, this characterization methodology provides an innovative approach to screen formulations of poorly-water soluble compounds for continuous (no clogging) active vibrating-mesh nebulization.