Focused Ultrasound-Modulated Glomerular Ultrafiltration Assessed by Functional Changes in Renal Arteries

This study demonstrates the feasibility of using focused ultrasound (FUS) to modulate glomerular ultrafiltration by renal artery sonication and determine if protein-creatinine ratios are estimated through vascular parameters. All animal experiments were approved by our Animal Care and Use Committee. The renal arteries of Sprague-Dawley rats were surgically exposed and sonicated at various acoustic power levels using a FUS transducer with a resonant frequency of 1 MHz. The mean peak systolic velocity (PSV) of the blood flow was measured by Doppler ultrasound imaging. Urinary protein-creatinine ratios were calculated during the experiments. Histological examination of renal arteries and whole kidneys was performed. The PSV, pulsatility index, and resistance index of blood flow significantly increased in the arteries after FUS sonication without microbubbles (p<0.05). The change in normalized protein-creatinine ratios significantly increased with increasing acoustic power, but such was not observed when microbubbles were administered. Furthermore, no histological changes were observed in the hematoxylin- and eosin-stained sections. Glomerular ultrafiltration is regulated temporarily by renal artery sonication without microbubbles. Monitoring vascular parameters are useful in estimating the normalized change in protein-creatinine ratios.     

Bacterial Communities of Three Saline Meromictic Lakes in Central Asia

Meromictic lakes located in landlocked steppes of central Asia (~2500 km inland) have unique geophysiochemical characteristics compared to other meromictic lakes. To characterize their bacteria and elucidate relationships between those bacteria and surrounding environments, water samples were collected from three saline meromictic lakes (Lakes Shira, Shunet and Oigon) in the border between Siberia and the West Mongolia, near the center of Asia. Based on in-depth tag pyrosequencing, bacterial communities were highly variable and dissimilar among lakes and between oxic and anoxic layers within individual lakes. Proteobacteria, Bacteroidetes, Cyanobacteria, Actinobacteria and Firmicutes were the most abundant phyla, whereas three genera of purple sulfur bacteria (a novel genus, Thiocapsa and Halochromatium) were predominant bacterial components in the anoxic layer of Lake Shira (~20.6% of relative abundance), Lake Shunet (~27.1%) and Lake Oigon (~9.25%), respectively. However, few known green sulfur bacteria were detected. Notably, 3.94% of all sequencing reads were classified into 19 candidate divisions, which was especially high (23.12%) in the anoxic layer of Lake Shunet. Furthermore, several hydro-parameters (temperature, pH, dissolved oxygen, H₂S and salinity) were associated (P< 0.05) with variations in dominant bacterial groups. In conclusion, based on highly variable bacterial composition in water layers or lakes, we inferred that the meromictic ecosystem was characterized by high diversity and heterogenous niches.     

Spatial distribution of filament elasticity determines the migratory behaviors of a cell

Any cellular response leading to morphological changes is highly tuned to balance the force generated from structural reorganization, provided by actin cytoskeleton. Actin filaments serve as the backbone of intracellular force, and transduce external mechanical signal via focal adhesion complex into the cell. During migration, cells not only undergo molecular changes but also rapid mechanical modulation. Here we focus on determining, the role of spatial distribution of mechanical changes of actin filaments in epithelial, mesenchymal, fibrotic and cancer cells with non-migration, directional migration, and non-directional migration behaviors using the atomic force microscopy. We found 1) non-migratory cells only generated one type of filament elasticity, 2) cells generating spatially distributed two types of filament elasticity showed directional migration, and 3) pathologic cells that autonomously generated two types of filament elasticity without spatial distribution were actively migrating non-directionally. The demonstration of spatial regulation of filament elasticity of different cell types at the nano-scale highlights the coupling of cytoskeletal function with physical characters at the sub-cellular level, and provides new research directions for migration related disease.     

Preclinical pharmacokinetics of MHAA4549A,a human monoclonal antibody to influenza A virus,and the prediction of its efficacious clinical dose for the treatment of patients hospitalized with influenza A

MHAA4549A is a human immunoglobulin G1 (IgG1) monoclonal antibody that binds to a highly conserved epitope on the stalk of influenza A hemagglutinin and blocks the hemagglutinin-mediated membrane fusion in the endosome, neutralizing all known human influenza A strains. Pharmacokinetics (PK) of MHAA4549A and its related antibodies were determined in DBA/2J and Balb-c mice at 5 mg/kg and in cynomolgus monkeys at 5 and 100 mg/kg as a single intravenous dose. Serum samples were analyzed for antibody concentrations using an ELISA and the PK was evaluated using WinNonlin software. Human PK profiles were projected based on the PK in monkeys using species-invariant time method. The human efficacious dose projection was based on in vivo nonclinical pharmacological active doses, exposure in mouse infection models and expected human PK. The PK profiles of MHAA4549A and its related antibody showed a linear bi-exponential disposition in mice and cynomolgus monkeys. In mice, clearance and half-life ranged from 5.77 to 9.98 mL/day/kg and 10.2 to 5.76 days, respectively. In cynomolgus monkeys, clearance and half-life ranged from 4.33 to 4.34 mL/day/kg and 11.3 to 11.9 days, respectively. The predicted clearance in humans was ～2.60 mL/day/kg. A single intravenous dose ranging from 15 to 45 mg/kg was predicted to achieve efficacious exposure in humans. In conclusion, the PK of MHAA4549A was as expected for a human IgG1 monoclonal antibody that lacks known endogenous host targets. The predicted clearance and projected efficacious doses in humans for MHAA4549A have been verified in a Phase 1 study and Phase 2a study, respectively.     

Frequency of Lost to Follow-Up and Associated Factors for Patients with Rheumatic Diseases

Objective

To determine the frequency of lost to follow-up (LTFU) in the setting of usual care for outpatients with rheumatic diseases including RA, SLE, AS, and Ps/PsA, to explore the associated demographic factors, and to investigate the reasons for being LTFU from the original medical care.

Methods

Patients registered between May 2011 and January 2014 at the rheumatology outpatient department of a medical center were included. Those who did not attend their scheduled appointment were defined as LTFU. Univariate and multivariate logistic regression were used to analyze the factors for being LTFU.

Results

A total of 781 patients were enrolled, including 406 patients with RA, 174 with SLE, 136 with AS, and 65 with Ps/PsA. The frequency of LTFU was 23.9%, 25.9%, 35.3%, and 35.4%, respectively. The frequency of LTFU was significantly different between the four rheumatic diseases (p = 0.028). In multivariate logistic regression analysis, an older age increased being LTFU in the patients with RA (OR 1.02; 95% CI 1.00–1.04; p = 0.033), but reduced being LTFU in those with Ps/PsA (OR 0.96; 95% CI 0.92–0.99; p = 0.021). Female patients with SLE and Ps/PsA were more likely to be LTFU, although this did not reach statistical significance (p = 0.056 and 0.071, respectively). The most common reason for being LTFU was moving to other district hospitals from the original medical center due to convenience for the patients with RA and SLE, and stopping medication due to minimal symptoms for the patients with AS and Ps/PsA.

Conclusions

The frequency of LTFU in patients with rheumatic diseases is high. Associated demographic factors included older age in RA, female gender in SLE and Ps/PsA, and younger age in Ps/PsA, with various reasons for being LTFU. Recognizing these associated factors and reasons for being LTFU may help to improve the attendance of patients and the quality of medical care.     

Shape-Related Toxicity of Titanium Dioxide Nanofibres

Titanium dioxide (TiO₂) nanofibres are a novel fibrous nanomaterial with increasing applications in a variety of fields. While the biological effects of TiO₂ nanoparticles have been extensively studied, the toxicological characterization of TiO₂ nanofibres is far from being complete. In this study, we evaluated the toxicity of commercially available anatase TiO₂ nanofibres using TiO₂ nanoparticles (NP) and crocidolite asbestos as non-fibrous or fibrous benchmark materials. The evaluated endpoints were cell viability, haemolysis, macrophage activation, trans-epithelial electrical resistance (an indicator of the epithelial barrier competence), ROS production and oxidative stress as well as the morphology of exposed cells. The results showed that TiO₂ nanofibres caused a cell-specific, dose-dependent decrease of cell viability, with larger effects on alveolar epithelial cells than on macrophages. The observed effects were comparable to those of crocidolite, while TiO₂ NP did not decrease cell viability. TiO₂ nanofibres were also found endowed with a marked haemolytic activity, at levels significantly higher than those observed with TiO₂ nanoparticles or crocidolite. Moreover, TiO₂ nanofibres and crocidolite, but not TiO₂ nanoparticles, caused a significant decrease of the trans-epithelial electrical resistance of airway cell monolayers. SEM images demonstrated that the interaction with nanofibres and crocidolite caused cell shape perturbation with the longest fibres incompletely or not phagocytosed. The expression of several pro-inflammatory markers, such as NO production and the induction of Nos2 and Ptgs2, was significantly increased by TiO₂ nanofibres, as well as by TiO₂ nanoparticles and crocidolite. This study indicates that TiO₂ nanofibres had significant toxic effects and, for most endpoints with the exception of pro-inflammatory changes, are more bio-active than TiO₂ nanoparticles, showing the relevance of shape in determining the toxicity of nanomaterials. Given that several toxic effects of TiO₂ nanofibres appear comparable to those observed with crocidolite, the possibility that they exert length dependent toxicity in vivo seems worthy of further investigation.     

Longitudinal analytical approaches to genetic data

Background

Longitudinal phenotypic data provides a rich potential resource for genetic studies which may allow for greater understanding of variants and their covariates over time. Herein, we review 3 longitudinal analytical approaches from the Genetic Analysis Workshop 19 (GAW19). These contributions investigated both genome-wide association (GWA) and whole genome sequence (WGS) data from odd numbered chromosomes on up to 4 time points for blood pressure–related phenotypes. The statistical models used included generalized estimating equations (GEEs), latent class growth modeling (LCGM), linear mixed-effect (LME), and variance components (VC). The goal of these analyses was to test statistical approaches that use repeat measurements to increase genetic signal for variant identification.

Results

Two analytical methods were applied to the GAW19: GWA using real phenotypic data, and one approach to WGS using 200 simulated replicates. The first GWA approach applied a GEE-based model to identify gene-based associations with 4 derived hypertension phenotypes. This GEE model identified 1 significant locus, GRM7, which passed multiple test corrections for 2 hypertension-derived traits. The second GWA approach employed the LME to estimate genetic associations with systolic blood pressure (SBP) change trajectories identified using LCGM. This LCGM method identified 5 SBP trajectories and association analyses identified a genome-wide significant locus, near ATOX1 (p?=?1.0E^?8). Finally, a third VC-based model using WGS and simulated SBP phenotypes that constrained the β coefficient for a genetic variant across each time point was calculated and compared to an unconstrained approach. This constrained VC approach demonstrated increased power for WGS variants of moderate effect, but when larger genetic effects were present, averaging across time points was as effective.

Conclusion

In this paper, we summarize 3 GAW19 contributions applying novel statistical methods and testing previously proposed techniques under alternative conditions for longitudinal genetic association. We conclude that these approaches when appropriately applied have the potential to: (a) increase statistical power; (b) decrease trait heterogeneity and standard error; (c) decrease computational burden in WGS; and (d) have the potential to identify genetic variants influencing subphenotypes important for understanding disease progression.