Cerebrovascular response to CO2 during moderate-intensity exercise measured by performing transcranial Doppler Ultrasonography

Previous studies demonstrated that cerebral blood flow (CBF) changes during dynamic exercise and a physiological basis for this observation may be explained by the tight control of CBF by arterial carbon dioxide tension (PaCO?). This study examined whether the steady state of the middle cerebral artery blood flow velocity (MCAVmean) and PaCO?could be observed during constant work rate cycling exercise and to investigate the cerebrovascular reactivity (CVR) to CO?. Seven young volunteers performed a 10-min exercise session with constant workload using a cycle ergometer, with intensities corresponding to the level below the lactate threshold. Respiratory gas analysis and MCAVmean were measured simultaneously using the transcranial Doppler (TCD) method. PaCO?was estimated (ePaCO?) using the end-tidal pressure of CO?(PETCO?) and the tidal volume (VT). On-transient phase II of VO?and the corresponding responses of MCAVmean and ePaCO? were investigated simultaneously with the monoexponential model. Since the responses in ΔMCAVmean or ePaCO?had the overshoot phase within 3min in some cases, analysis for the fitted curves of the monoexponential model was performed during the first 5 min as well as during the total 10 min. CVR to CO?during the dynamic cyclic exercise was 5.33 % mmHg-1 and 4.78 % mmHg?1 in the 5-min and the 10-min analysis, respectively. In the 5-min and the 10-min analysis, CVR to CO?significantly correlated with the exercise intensity during the 10-min bout (r2 = 0.89 and 0.75, respectively). During the on-transient phase of dynamic exercise, CBF would be influenced by PaCO?and other factors such as the neuronal activation and cardiac output would also be involved in changing CBF

Long-Term Clinical Consequences of Intense, Uninterrupted Endurance Training in Olympic Athletes

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Guideline for Hereditary Angioedema (HAE) 2010 by the Japanese Association for Complement Research - Secondary Publication

ABSTRACTThis guideline was provided by the Japanese Association for Complement Research targeting clinicians for making an accurate diagnosis of hereditary angioedema (HAE), and for prompt treatment of the HAE patient in Japan. This is a 2010 year version and will be updated according to any pertinent medical advancements

PIG-S and PIG-T, essential for GPI anchor attachment to proteins, form a complex with GAA1 and GPI8

Many eukaryotic cell surface proteins are anchored to the plasma membrane via glycosylphosphatidylinositol (GPI). The GPI transamidase mediates GPI anchoring in the endoplasmic reticulum, by replacing a protein’s C-terminal GPI attachment signal peptide with a pre-assembled GPI. During this transamidation reaction, the GPI transamidase forms a carbonyl intermediate with a substrate protein. It was known that the GPI transamidase is a complex containing GAA1 and GPI8. Here, we report two new components of this enzyme: PIG-S and PIG-T. To determine roles for PIG-S and PIG-T, we disrupted these genes in mouse F9 cells by homologous recombination. PIG-S and PIG-T knockout cells were defective in transfer of GPI to proteins, particularly in formation of the carbonyl intermediates. We also demonstrate that PIG-S and PIG-T form a protein complex with GAA1 and GPI8, and that PIG-T maintains the complex by stabilizing the expression of GAA1 and GPI8. Saccharomyces cerevisiae Gpi16p (YHR188C) and Gpi17p (YDR434W) are orthologues of PIG-T and PIG-S, respectively

Modeling of Longitudinal Changes in Left Ventricular Dimensions among Female Adolescent Runners

<div><p>Purpose</p><p>Left ventricular (LV) enlargement has been linked to sudden cardiac death among young athletes. This study aimed to model the effect of long-term incessant endurance training on LV dimensions in female adolescent runners.</p><p>Methods</p><p>Japanese female adolescent competitive distance runners (<i>n</i> = 36, age: 15 years, height: 158.1 ± 4.6 cm, weight: 44.7 ± 6.1 kg, percent body fat: 17.0 ± 5.2%) underwent echocardiography and underwater weighing every 6 months for 3 years. Since the measurement occasions varied across subjects, multilevel analysis was used for curvilinear modeling of changes in running performance (velocities in 1500 m and 3000 m track race), maximal oxygen uptake (VO₂max), body composition, and LV dimensions.</p><p>Results</p><p>Initially, LV end-diastolic dimension (LVEDd) and LV mass were 47.0 ± 3.0 mm and 122.6 ± 15.7 g, respectively. Running performance and VO₂max improved along with the training duration. The trends of changes in fat-free mass (FFM) and LVEDd were similarly best described by quadratic polynomials. LVEDd did not change over time in the model including FFM as a covariate. Increases in LV wall thicknesses were minimal and independent of FFM. LV mass increased according to a quadratic polynomial trend even after adjusting for FFM.</p><p>Conclusions</p><p>FFM was an important factor determining changes in LVEDd and LV mass. Although running performance and VO₂max were improved by continued endurance training, further LV cavity enlargement hardly occurred beyond FFM gain in these adolescent female runners, who already demonstrated a large LVEDd.</p></div

Changes in running velocities for 1500 m and 3000 m races.

<p>The cubic polynomial curves determined by multilevel analysis to best describe the trajectories of running velocities for 1500 m (V₁₅₀₀, solid line) and 3000 m (V₃₀₀₀, dotted line) track races over time among adolescent female distance runners. Closed and open circles represent the records of individual 1500 m and 3000 m races, respectively. X in the model equations denotes Time (day). All unadjusted estimates; <i>p</i> < 0.05 and <i>p</i> < 0.001, respectively.</p

The trajectories of changes in fat-free mass (FFM), left ventricular end-diastolic dimension (LVEDd), and left ventricular mass (LV mass) among adolescent female distance runners.

<p>Occasion of measurement (T_measure) is numbered from 0 (baseline) with a 1-unit increase representing 6 months. Open circles represent individual data. X in the polynomials denotes T_measure.</p