T Cells Development Is Different between Thymus from Normal and Intrauterine Growth Restricted Pig Fetus at Different Gestational Stage

This experiment was conducted to evaluate the development of T cells in intrauterine growth retarded (IUGR) piglets at different gestational stages, and tentatively explore the relationship between T cells development and the Notch signaling pathway. A total of 18 crossbred (Landrace×Large white) primiparous sows were mated at similar weights and estruses and euthanized at d 60, 90 and 110 of gestation with six replicates for each time point. One IUGR and one normal fetus were picked from each litter. The T-cell subsets, mRNA expression of Delta-like1, Delta-like4, Jagged1, and Notch2 genes in the thymus were investigated. Compared to normal piglets, CD3+CD4−CD8+ cells in IUGR fetuses at d 90 was 0.13% lower (p<0.05). At d 110 of gestation CD8+ T cells in IUGR fetuses was 0.19% lower (p<0.05). The percentage of CD8+ T cells was 3.14% lower (p<0.05) of the total T cells in IUGR pigs at d 60. The abundance of Notch2 and Delta-like4 mRNA at d 110 was 20.93% higher and 0.77% (p<0.05) lower, and Delta-like1 mRNA at d 90 was 0.19% (p<0.05) higher compared to normal pigs. These results suggested that normal fetuses had a greater proportion of T-cell subsets at earlier gestation periods, and the Notch signaling pathway was likely partially responsible for these differences to some degree

Correlation Analysis between Polysomnography Diagnostic Indices and Heart Rate Variability Parameters among Patients with Obstructive Sleep Apnea Hypopnea Syndrome

<div><p>Heart rate variability (HRV) can reflect the changes in the autonomic nervous system (ANS) that are affected by apnea or hypopnea events among patients with obstructive sleep apnea hypopnea syndrome (OSAHS). To evaluate the possibility of using HRV to screen for OSAHS, we investigated the relationship between HRV and polysomnography (PSG) diagnostic indices using electrocardiography (ECG) and PSG data from 25 patients with OSAHS and 27 healthy participants. We evaluated the relationship between various PSG diagnostic indices (including the apnea hypopnea index [AHI], micro-arousal index [MI], oxygen desaturation index [ODI]) and heart rate variability (HRV) parameters using Spearman’s correlation analysis. Moreover, we used multiple linear regression analyses to construct linear models for the AHI, MI, and ODI. In our analysis, the AHI was significantly associated with relative powers of very low frequency (VLF [%]) (r = 0.641, P = 0.001), relative powers of high frequency (HF [%]) (r = -0.586, P = 0.002), ratio between low frequency and high frequency powers (LF/HF) (r = 0.545, P = 0.049), normalized powers of low frequency (LF [n.u.]) (r = 0.506, P = 0.004), and normalized powers of high frequency (HF [n.u.]) (r = -0.506, P = 0.010) among patients with OSAHS. The MI was significantly related to standard deviation of RR intervals (SDNN) (r = 0.550, P = 0.031), VLF [%] (r = 0.626, P = 0.001), HF [%] (r = -0.632, P = 0.001), LF/HF (r = 0.591, P = 0.011), LF [n.u.] (r = 0.553, P = 0.004), HF [n.u.] (r = -0.553, P = 0.004), and absolute powers of very low frequency (VLF [abs]) (r = 0.525, P = 0.007) among patients with OSAHS. The ODI was significantly correlated with VLF [%] (r = 0.617, P = 0.001), HF [%] (r = -0.574, P = 0.003), LF [n.u.] (r = 0.510, P = 0.012), and HF [n.u.] (r = -0.510, P = 0.012) among patients with OSAHS. The linear models for the PSG diagnostic indices were AHI = -38.357+1.318VLF [%], MI = -13.389+11.297LF/HF+0.266SDNN, and ODI = -55.588+1.715VLF [%]. However, the PSG diagnostic indices were not related to the HRV parameters among healthy participants. Our analysis suggests that HRV parameters are powerful tools to screen for OSAHS patients in place of PSG monitoring.</p></div

The time domain and frequency domain parameters.

<p>The time domain and frequency domain parameters.</p

The correlations between the frequency domain parameters and the MI.

<p>The correlations between the frequency domain parameters and the MI.</p

The correlations between the frequency domain parameters and the AHI.

<p>The correlations between the frequency domain parameters and the AHI.</p

The correlation between the frequency domain parameters and ODI.

<p>The correlation between the frequency domain parameters and ODI.</p

The relationship between the frequency domain parameters and the AHI with regard to the OSAHS group.

<p>(A) Scatterplot of VLF [%] with AHI; (B) Scatterplot of HF [%] with AHI; (C) Scatterplot of LF/HF with AHI; (D) Scatterplot of LF [n.u.] with AHI; (E) Scatterplot of HF [n.u.] with AHI.</p

The relationship between the frequency domain parameters and the ODI with regard to the OSAHS group.

<p>(A) Scatterplot of VLF [%] with ODI; (B) Scatterplot of HF [%] with ODI; (C) Scatterplot of LF [n.u.] with ODI; (D) Scatterplot of HF [n.u.] with ODI.</p

Correlations between the time domain parameters and the AHI, MI, and ODI with regard to controls.

<p>Correlations between the time domain parameters and the AHI, MI, and ODI with regard to controls.</p