Background Post-stroke depression (PSD) is a mood disorder characterized by depression and anhedonia caused by stroke. Metabolomics identified metabolites associated with PSD, but previous studies are based on gas chromatography (GC)/mass spectrometry (MS). This study aimed to perform a liquid chromatography (LC)-MS-based metabolomics study of the plasma metabolite profiles between patients with PSD and controls. Methods This was a prospective study of patients with stroke enrolled between July and December 2017 at the Second Affiliated Hospital of Nanchang University. Patients were grouped as Hamilton Depression Rating Scale > 7 (PSD) or < 7 (controls). Metabonomics profiling of plasma sampled was conducted by LC-MS. By combining multivariable and univariable statistical analyses, significant differential metabolites between the two groups were screened. The threshold for significant differences was VIP ≥1 and P < 0.05. Log2FC is the logarithm of the mean ratio between the two groups. Results There were no significant difference with respect to age, NIHSS score, and MMSE between the two groups (all P > 0.05). There were six differential metabolites between the PSD and stroke groups, of which three metabolites were increased and three were decreased. Compared with the control group, p-chlorophenylalanine (Log2FC = 1.37, P = 0.03), phenylacetyl glutamine (Log2FC = 0.21, P = 0.048), and DHA (Log2FC = 0.77, P = 0.01) levels were higher in the PSD group, while betaine (trimethylglycine) (Log2FC = − 0.79, P = 0.04), palmitic acid (Log2FC = − 0.51, P = 0.001), and MHPG-SO4 (Log2FC = − 2.37, P = 0.045) were decreased. Conclusion Plasma metabolomics showed that amino acid metabolism (phenylacetyl glutamine, p-chlorophenylalanine, trimethylglycine), lipid metabolism (DHA, palmitic acid, trimethylglycine), and oxidative stress (DHA, palmitic acid, trimethylglycine) were associated with PSD. These results could help to reveal the pathophysiological mechanism of PSD and eventually identify treatment targets.

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Pre-eclampsia, characterized as defective uteroplacental vascularization, remains the major cause of maternal and fetal mortality and morbidity. Previous epidemiological studies demonstrated that cigarette smoking reduced the risk of pre-eclampsia. However, the molecular mechanism remains elusive. In the present study, it is demonstrated that a low dose of nicotine decreased soluble vascular endothelial growth factor receptor 1 (sFlt1) secretion in human trophoblast cells under hypoxic conditions. Nicotine was then observed to promote vascular endothelial growth factor (VEGF) secretion by reducing sFlt1 secretion and increasing VEGF mRNA transcription. Further data showed that nicotine enhanced hypoxia-mediated hypoxia-inducible factor-1α (HIF-1α) expression and HIF-1α small interfering RNA abrogated nicotine-induced VEGF secretion, indicating that HIF-1α may be responsible for nicotine-mediated VEGF transcription under hypoxic conditions. Moreover, conditioned medium from human trophoblast cells treated with nicotine under hypoxic conditions promoted the proliferation and tube formation capacity of human umbilical endothelial cells (HUVEC) by promoting VEGF secretion. These findings indicate that nicotine may promote VEGF secretion in human trophoblast cells under hypoxic conditions by reducing sFlt1 secretion and up-regulating VEGF transcription and improve the proliferation and tube formation of HUVEC cells, which may contribute to elucidate the protective effect of cigarette smoking against pre-eclampsia.

Background: Previous Resting-state functional magnetic resonance imaging (fMRI) studies have mainly focused on cerebral functional alteration in processing different emotional stimuli in patients with narcolepsy type 1 (NT1), but were short of exploration of characteristic brain activity and its remote interaction patterns. This study aimed to investigate the spontaneous blood oxygen fluctuations at rest and to elucidate the neural mechanisms underlying neuropsychiatric behavior. Method: A total of 18 unmedicated patients with NT1 and matched healthy individuals were recruited in a resting-state fMRI study. Magnetic resonance imaging (MRI) data were first analyzed using fractional low-frequency amplitude of low-frequency fluctuation (fALFF) to detect changes in local neural activity, and regions with group differences were taken as regions of interest (ROIs). Secondly, functional connectivity (FC) analysis was used to explore altered connectivity between ROIs and other areas. Lastly, the relationship between functional brain activity and neuropsychiatric behaviors was analyzed with correlation analysis. Results: fALFF analysis revealed enhanced neural activity in bilateral fusiform gyrus (FFG), right precentral gyrus, and left postcentral gyrus (PoCG) in the NT1 group. The patients indicated reduced activity in the bilateral temporal pole middle temporal gyrus (TPOmid), left caudate nucleus (CAU), left parahippocampus, left precuneus (PCUN), right amygdala, and right anterior cingulate and paracingulate gyri. ESS score was negatively correlated with fALFF in the right FFG. The NT1 group revealed decreased connectivity between left TPOmid and right PoCG, the bilateral middle frontal gyrus, left superior frontal gyrus, medial, and right supramarginal gyrus. Epworth Sleepiness Scale (ESS) was negatively correlated with FC of the left TPOmid with left putamen (PUT) in NT1. Compared with healthy controls (HCs), enhanced FC of the left CAU with right FFG was positively associated with MSLT-SOREMPs in patients. Furthermore, increased FC of the left PCUN with right PoCG was positively correlated with SDS score. Conclusions: We found that multiple functional activities related to the processing of emotional regulation and sensory information processing were abnormal, and some were related to clinical characteristics. fALFF in the left postcentral or right precentral gyrus may be used as a biomarker of narcolepsy, whereas fALFF in the right fusiform and the FC strength of the left temporal pole middle temporal gyrus with the putamen may be clinical indicators to assess the drowsiness severity of narcolepsy.