Two key brainstem neuron types were identified for heat defense, fever limiting, energy expenditure, and body weight control.

Background and purpose: Autonomic dysfunction is common after stroke, which is correlated with unfavorable outcome. Phase-rectified signal averaging is a newly developed technique for assessing cardiac autonomic function, by detecting sympathetic and vagal nerve activity separately through calculating acceleration capacity (AC) and deceleration capacity (DC) of heart rate. In this study, we used this technique for the first time to investigate the cardiac autonomic function of patients with acute hemispheric ischemic stroke.
Methods: A 24-hour Holter monitoring was performed in 63 patients with first-ever acute ischemic stroke in hemisphere and sinus rhythm, as well as in 50 controls with high risk of stroke. DC, AC, heart rate variability parameters, standard deviation of all normal-to-normal intervals (SDNN), and square root of the mean of the sum of the squares of differences between adjacent normal-to-normal intervals (RMSSD) were calculated. The National Institutes of Health Stroke Scale (NIHSS) was used to assess the severity of stroke. We analyzed the changes of DC, AC, SDNN, and RMSSD and also studied the correlations between these parameters and NIHSS scores.
Results: The R–R (R wave to R wave on electrocardiogram) intervals, DC, AC, and SDNN in the cerebral infarction group were lower than those in controls (P=0.003, P=0.002, P=0.006, and P=0.043), but the difference of RMSSD and the D-value and ratio between absolute value of AC (|AC|) and DC were not statistically significant compared with those in controls. The DC of the infarction group was significantly correlated with |AC|, SDNN, and RMSSD (r=0.857, r=0.619, and r=0.358; P=0.000, P=0.000, and P=0.004). Correlation analysis also showed that DC, |AC|, and SDNN were negatively correlated with NIHSS scores (r=-0.279, r=-0.266, and r=-0.319; P=0.027, P=0.035, and P=0.011). Conclusion: Both DC and AC of heart rate decreased in patients with hemispheric infarction, reflecting a decrease in both vagal and sympathetic modulation. Both DC and AC were correlated with the severity of stroke.

Purpose: To determine the associations between apolipoprotein E (APOE) genotypes and serum levels of glucose, total cholesterol, and triglycerides in a cognitively normal aging Han Chinese population. Methods: There were 1,003 cognitively normal aging subjects included in this study. APOE genotypes were analyzed and biochemical parameters were tested. All the subjects were divided into three groups according to APOE genotypes: (1) E2/2 or E2/3 (APOE E2); (2) E3/3 (APOE E3); and (3) E2/4, E3/4, or E4/4 (APOE E4). Correlations of serum levels of glucose, total cholesterol, and triglycerides with APOE genotypes were assessed. Results: E2, E3, and E4 allele frequencies were found to be 6.2%, 82.1%, and 11.7%, respectively. Serum levels of total cholesterol were higher in the APOE E4 group (P<0.05). A higher level of total cholesterol was associated with the E4 allele (adjusted odds ratio 1.689, 95% confidence interval 1.223–2.334, P<0.01). However, no association was found between APOE status and serum levels of glucose (adjusted odds ratio 0.981, 95% confidence interval 0.720–1.336, P=0.903) or total triglycerides (adjusted odds ratio 1.042, 95% confidence interval 0.759–1.429, P=0.800). Conclusion: A higher serum level of total cholesterol was significantly correlated with APOE E4 status in a cognitively normal, nondiabetic aging population. However, there was no correlation between APOE genotypes and serum levels of glucose or total triglycerides.

Induction of apoptosis is a strategy in the treatment of glioma, a malignant tumor with the highest prevalence in the brain. Sodium butyrate (NaB) induces apoptosis in glioma cells at pharmacological dosages (>2.5 mM), but the mechanism remains largely unknown beyond the mitochondrial potential drop. In this study, NaB was found to open the mitochondrial permeability transient pore (MPTP) to induce a proton leak in the mechanism of apoptosis. The MPTP opening led to collapse of mitochondrial potential and suppression of ATP production in the NaB-treated cells. Proton leak was increased in the mitochondria under the coupling and uncoupling conditions from the MPTP opening. The proton leak was associated with an elevation in the protein abundance of adenine nucleotide translocator 2 (ANT2) and was blocked by an ANT-specific inhibitor of bongkrekic acid (BA). These data suggest that the proton leak is induced by NaB for the mitochondrial potential drop in the induction of apoptosis. The mechanism may be related to activation of ANT2 in the MPTP complex.

Migraine seriously affects the physical and mental health of patients because of its recurrence and the hypersensitivity to the environment that it causes. However, the pathogenesis and pathophysiology of migraine are not fully understood. We addressed this issue in the present study using an autodynamic functional connectome model (A-DFCM) with twice-clustering to compare dynamic functional connectome patterns (DFCPs) from resting-state functional magnetic resonance imaging data from migraine patients and normal control subjects. We used automatic localization of segment points to improve the efficiency of the model, and intergroup differences and network metrics were analyzed to identify the neural mechanisms of migraine. Using the A-DFCM model, we identified 17 DFCPs—including 1 that was specific and 16 that were general—based on intergroup differences. The specific DFCP was closely associated with neuronal dysfunction in migraine, whereas the general DFCPs showed that the 2 groups had similar functional topology as well as differences in the brain resting state. An analysis of network metrics revealed the critical brain regions in the specific DFCP; these were not only distributed in brain areas related to pain such as Brodmann area 1/2/3, basal ganglia, and thalamus but also located in regions that have been implicated in migraine symptoms such as the occipital lobe. An analysis of the dissimilarities in general DFCPs between the 2 groups identified 6 brain areas belonging to the so-called pain matrix. Our findings provide insight into the neural mechanisms of migraine while also identifying neuroimaging biomarkers that can aid in the diagnosis or monitoring of migraine patients.