Introduction/Aims Ultrasound (US) studies have demonstrated patchy enlargement of spinal and peripheral nerves in Guillain‐Barré syndrome (GBS). However, whether ultrasound yields useful information for early classification of GBS has not been established. We aimed to evaluate nerve ultrasound in patients with GBS in northern China and compare the sonographic characteristics between demyelinating and axonal subtypes. Methods Between November 2018 and October 2019, 38 hospitalized GBS patients within 3 wk of disease onset and 40 healthy controls were enrolled. Ultrasonographic cross‐sectional areas (CSA) of the peripheral nerves, vagus nerve, and cervical nerve roots were prospectively recorded in GBS subtypes and controls. Results Ultrasonographic CSA exhibited significant enlargement in most patients' nerves compared with healthy controls, most prominent in cervical nerves. The CSA tended to be larger in acute inflammatory demyelinating polyneuropathy (AIDP) than in acute motor axonal neuropathy (AMAN)/acute motor and sensory axonal neuropathy (AMSAN), especially in cervical nerves (C5: 5.9 ± 1.6 mm2 vs. 7.0 ± 1.7 mm2, p = .042; C6: 10.5 ± 1.8 mm2 vs. 12.0 ± 2.1 mm2, p = .033). The chi‐squared test revealed significant differences in nerve enlargement in C5 (p < .001), C6 (p < .001), the proximal median nerve (p < .001), and the vagus nerve (p = .003) between GBS and controls. The vagus nerve was larger in patients with autonomic dysfunction than in patients without it (2.3 ± 1.0 mm2 vs. 1.4 ± 0.5 mm2, p = .003). Discussion The demyelinating subtype presented with more significant cervical nerve enlargement in GBS. Vagus nerve enlargement may be a useful marker for autonomic dysfunction.

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: Hypoxia-inducible factor-1 (HIF-1) is a heterodimer protein composed of an oxygen-regulated functional subunit, HIF-1α, and a structural subunit, HIF-1β, belonging to the basic helix-loop-helix family. Strict regulation of HIF-1 protein stability and subsequent transcriptional activity involves various molecular interactions and is primarily controlled by post-transcriptional modifications. Hypoxia, owing to impaired cerebral blood flow, has been implicated in a range of central nervous system (CNS) diseases by exerting a deleterious effect on brain function. As a master oxygen-sensitive transcription regulator, HIF-1 is responsible for upregulating a broad spectrum of target genes involved in glucose metabolism, angiogenesis, and erythropoiesis to generate the adaptive response to avoid or minimize hypoxic brain injury. However, prolonged, severe oxygen deprivation may directly contribute to the role-conversion of HIF-1, namely. From neuroprotection to the promotion of cell death. Currently, an increasing number of studies support the fact HIF-1 is involved in a variety of CNS-related diseases, such as intracranial atherosclerosis, stroke, and neurodegenerative diseases. This review article chiefly focuses on the effect of HIF-1 on the pathogenesis and mechanism of progression of numerous CNS-related disorders by mediating the expression of various downstream genes and extensive biological functional events. It presents robust evidence that HIF-1 may represent a potential therapeutic target for CNS-related diseases.

Posterior circulation cerebral infarction (PCCI) can lead to deceased infratentorial cerebral blood flow (CBF) and metabolism. Neural activity is closely related to regional cerebral blood flow both spatially and temporally. Transcranial Doppler (TCD) combined with quantitative electroencephalography (QEEG) is a technique that evaluates neurovascular coupling and involves synergy between the metabolic and vascular systems. This study aimed to monitor brain function using TCD-QEEG and estimate the efficacy of TCD-QEEG for predicting the prognosis of patients with PCCI. We used a TCD-QEEG recording system to perform quantitative brain function monitoring; we recorded the related clinical variables simultaneously. The data were analyzed using a Cox proportional hazards regression model. Receiver-operating characteristic (ROC) curve analysis was used to evaluate the cut-off for the diastolic flow velocity (VD) and (delta + theta)/(alpha + beta) ratio (DTABR). The area under the ROC curve (AUROC) was calculated to assess the predictive validity of the study variables. Forty patients (aged 63.7 ± 9.9 years; 30 men) were assessed. Mortality at 90 days was 40%. The TCD indicators of VD [hazard ratio (HR) 0.168, confidence interval (CI) 0.047–0.597, p = 0.006] and QEEG indicators of DTABR (HR 12.527, CI 1.637–95.846, p = 0.015) were the independent predictors of the clinical outcomes. The AUROC after combination of VD and DTABR was 0.896 and showed better predictive accuracy than the Glasgow Coma Scale score (0.75), VD (0.76), and DTABR (0.781; all p &lt; 0.05). TCD-QEEG provides a good understanding of the coupling mechanisms in the brain and can improve our ability to predict the prognosis of patients with PCCI.

Background: Posterior circulation cerebral infarction (PCCI) leads to decreased cerebral blood flow (CBF) and metabolism. Neural activity is closely related to regional CBF both spatially and temporally. Transcranial Doppler (TCD) combined with quantitative electroencephalography (QEEG) can evaluate neurovascular coupling and involves synergy between the metabolic and vascular systems. This study aimed to monitor brain function using TCD-QEEG and estimate its efficacy in predicting the prognosis of patients with PCCI.Methods: We used TCD-QEEG to perform quantitative brain function monitoring; we recorded the related clinical variables simultaneously. The data were analyzed using a Cox proportional hazards regression model. Receiver-operating characteristic (ROC) curve analysis was used to evaluate the cut-off for the diastolic flow velocity (VD) and (delta+theta)/(alpha+beta) ratio (DTABR). The area under the ROC curve (AUROC) was calculated to assess the predictive validity of the study variables. Results: Forty patients (aged 63.7±9.9 years; 30 men) were assessed. Mortality at 90 days was 40%. The TCD indicators of VD (hazards ratio [HR] 0.168, confidence interval [CI] 0.047–0.597, p=0.006), and QEEG indicators of DTABR (HR 12.527, CI 1.637–95.846, p=0.015) were the independent predictors of the clinical outcomes. The AUROC after the combination of VD and DTABR was 0.896 and showed better predictive accuracy than the Glasgow Coma Scale score (0.75), VD (0.76), and DTABR (0.781; all p<0.05).Conclusion: TCD-QEEG provides a good understanding of the coupling mechanisms in the brain and can improve our ability to predict the prognosis of patients with PCCI.