Pioglitazone Improves Fat Distribution,the Adipokine Profile and Hepatic Insulin Sensitivity in Non-Diabetic End-Stage Renal Disease Subjects on Maintenance Dialysis: A Randomized Cross-Over Pilot Study

Background

Fat redistribution, increased inflammation and insulin resistance are prevalent in non-diabetic subjects treated with maintenance dialysis. The aim of this study was to test whether pioglitazone, a powerful insulin sensitizer, alters body fat distribution and adipokine secretion in these subjects and whether it is associated with improved insulin sensitivity.

Trial Design

This was a double blind cross-over study with 16 weeks of pioglitazone 45 mg vs placebo involving 12 subjects.

Methods

At the end of each phase, body composition (anthropometric measurements, dual energy X-ray absorptometry (DEXA), abdominal CT), hepatic and muscle insulin sensitivity (2-step hyperinsulinemic euglycemic clamp with 2H2-glucose) were measured and fasting blood adipokines and cardiometabolic risk markers were monitored.

Results

Four months treatment with pioglitazone had no effect on total body weight or total fat but decreased the visceral/sub-cutaneous adipose tissue ratio by 16% and decreased the leptin/adiponectin (L/A) ratio from 3.63×10⁻³ to 0.76×10⁻³. This was associated with a 20% increase in hepatic insulin sensitivity without changes in muscle insulin sensitivity, a 12% increase in HDL cholesterol and a 50% decrease in CRP.

Conclusions/Limitations

Pioglitazone significantly changes the visceral-subcutaneous fat distribution and plasma L/A ratio in non diabetic subjects on maintenance dialysis. This was associated with improved hepatic insulin sensitivity and a reduction of cardio-metabolic risk markers. Whether these effects may improve the outcome of non diabetic end-stage renal disease subjects on maintenance dialysis still needs further evaluation.

Trial Registration

ClinicalTrial.gov {"type":"clinical-trial","attrs":{"text":"NCT01253928","term_id":"NCT01253928"}}NCT01253928     

In-depth molecular and phenotypic characterization in a rice insertion line library facilitates gene identification through reverse and forward genetics approaches

We report here the molecular and phenotypic features of a library of 31,562 insertion lines generated in the model japonica cultivar Nipponbare of rice (Oryza sativa L.), called Oryza Tag Line (OTL). Sixteen thousand eight hundred and fourteen T-DNA and 12,410 Tos17 discrete insertion sites have been characterized in these lines. We estimate that 8686 predicted gene intervals--i.e. one-fourth to one-fifth of the estimated rice nontransposable element gene complement--are interrupted by sequence-indexed T-DNA (6563 genes) and/or Tos17 (2755 genes) inserts. Six hundred and forty-three genes are interrupted by both T-DNA and Tos17 inserts. High quality of the sequence indexation of the T2 seed samples was ascertained by several approaches. Field evaluation under agronomic conditions of 27,832 OTL has revealed that 18.2% exhibit at least one morphophysiological alteration in the T1 progeny plants. Screening 10,000 lines for altered response to inoculation by the fungal pathogen Magnaporthe oryzae allowed to observe 71 lines (0.7%) developing spontaneous lesions simulating disease mutants and 43 lines (0.4%) exhibiting an enhanced disease resistance or susceptibility. We show here that at least 3.5% (four of 114) of these alterations are tagged by the mutagens. The presence of allelic series of sequence-indexed mutations in a gene among OTL that exhibit a convergent phenotype clearly increases the chance of establishing a linkage between alterations and inserts. This convergence approach is illustrated by the identification of the rice ortholog of AtPHO2, the disruption of which causes a lesion-mimic phenotype owing to an over-accumulation of phosphate, in nine lines bearing allelic insertions.     

Traffic instabilities in self-organized pedestrian crowds

In human crowds as well as in many animal societies, local interactions among individuals often give rise to self-organized collective organizations that offer functional benefits to the group. For instance, flows of pedestrians moving in opposite directions spontaneously segregate into lanes of uniform walking directions. This phenomenon is often referred to as a smart collective pattern, as it increases the traffic efficiency with no need of external control. However, the functional benefits of this emergent organization have never been experimentally measured, and the underlying behavioral mechanisms are poorly understood. In this work, we have studied this phenomenon under controlled laboratory conditions. We found that the traffic segregation exhibits structural instabilities characterized by the alternation of organized and disorganized states, where the lifetime of well-organized clusters of pedestrians follow a stretched exponential relaxation process. Further analysis show that the inter-pedestrian variability of comfortable walking speeds is a key variable at the origin of the observed traffic perturbations. We show that the collective benefit of the emerging pattern is maximized when all pedestrians walk at the average speed of the group. In practice, however, local interactions between slow- and fast-walking pedestrians trigger global breakdowns of organization, which reduce the collective and the individual payoff provided by the traffic segregation. This work is a step ahead toward the understanding of traffic self-organization in crowds, which turns out to be modulated by complex behavioral mechanisms that do not always maximize the group's benefits. The quantitative understanding of crowd behaviors opens the way for designing bottom-up management strategies bound to promote the emergence of efficient collective behaviors in crowds.