Abdominal subcutaneous and visceral adipocyte size, lipolysis and inflammation relate to insulin resistance in male obese humans.

Obesity is associated with a disturbed adipose tissue (AT) function characterized by adipocyte hypertrophy, an impaired lipolysis and pro-inflammatory phenotype, which contributes to insulin resistance (IR). We investigated whether AT phenotype in different AT depots of obese individuals with and without type 2 diabetes mellitus (T2DM) is associated with whole-body IR. Subcutaneous (SC) and visceral (V) AT biopsies from 18 lean, 17 obese and 8 obese T2DM men were collected. AT phenotype was characterized by ex vivo measurement of basal and stimulated lipolysis (mature adipocytes), adipocyte size distribution (AT tissue sections) and AT immune cells (flow cytometry). In VAT, mean adipocyte size, CD45+ leukocytes and M1 macrophages were significantly increased in both obese groups compared to lean individuals. In SCAT, despite adipocyte hypertrophy, no significant differences in immune cell populations between groups were found. In SCAT, multiple linear regression analysis showed that none of the AT phenotype markers independently contributed to HOMA-IR while in VAT, mean adipocyte size was significantly related to HOMA-IR. In conclusion, beside adipocyte hypertrophy in VAT, M1 macrophage- or B-cell-mediated inflammation, may contribute to IR, while inflammation in hypertrophic SCAT does not seem to play a major role in IR.

Key Factors Affecting Reproductive Success of Thoroughbred Mares and Stallions on a Commercial Stud Farm.

To evaluate factors contributing to fertility of thoroughbred mares, data from 3743 oestrous periods of 2385 mares were collected on a large thoroughbred farm in Ireland. Fourteen stallions (mean age 8.3 years; range 4-15 years) had bred 2385 mares (mean age 9.4 years; range 3-24 years). Maiden mares accounted for 12%, mares with a foal at foot for 64%, and barren, slipped or rested mares for 24% of the total. The mean pregnancy rate per cycle was 67.8% (68.6% in year 1 and 66.9% in year 2). Backward stepwise multivariable logistic regression analysis was utilized to develop two models to evaluate mare factors, including mare age, reproductive status, month of foaling, dystocia, month of cover, foal heat, cycle number, treatments, walk-in status and stallion factors including stallion identity, stallion age, shuttle status, time elapsed between covers and high stallion usage on the per cycle pregnancy rate and pregnancy loss. Old age (p < 0.001) and cover within 20 days post-partum (p < 0.003) were associated with lowered pregnancy rates. High mare age (p < 0.05) and barren, slipped or rested reproductive status (p = 0.05) increased the likelihood of pregnancy loss. Uterine inflammation or infection, if appropriately treated, did not affect fertility. Only high usage of stallions (used more than 21 times in previous week) was associated with lowered (p = 0.009) pregnancy rates. However, shuttle stallions were more likely to have increased (p = 0.035) pregnancy survival, perhaps reflecting a bias in stallion selection. In conclusion, mare age exerted the greatest influence on fertility; nonetheless, thoroughbreds can be effectively managed to achieve high reproductive performance in a commercial setting.

Impact of sewer condition on urban flooding: an uncertainty analysis based on field observations and Monte Carlo simulations on full hydrodynamic models.

In-sewer defects are directly responsible for affecting the performance of sewer systems. Notwithstanding the impact of the condition of the assets on serviceability, sewer performance is usually assessed assuming the absence of in-sewer defects. This leads to an overestimation of serviceability. This paper presents the results of a study in two research catchments on the impact of in-sewer defects on urban pluvial flooding at network level. Impacts are assessed using Monte Carlo simulations with a full hydrodynamic model of the sewer system. The studied defects include root intrusion, surface damage, attached and settled deposits, and sedimentation. These defects are based on field observations and translated to two model parameters (roughness and sedimentation). The calculation results demonstrate that the return period of flooding, number of flooded locations and flooded volumes are substantially affected by in-sewer defects. Irrespective of the type of sewer system, the impact of sedimentation is much larger than the impact of roughness. Further research will focus on comparing calculated and measured behaviour in one of the research catchments.