Identification of core genes of craniopharyngioma angiogenesis based on single-cell nuclear transcriptome sequencing.

This study aimed to explore the core genes of craniopharyngioma angiogenesis for targeted vascular therapy based on single-cell nuclear transcriptome sequencing. For single-cell nuclear transcriptome sequencing, we collected six samples from the tumor center and adjacent hypothalamic tumor tissues from three patients with craniopharyngioma, as well as four normal brain tissues based on Gene Expression Omnibus. We screened genes with differential up-regulation between vascular endothelial cells of craniopharyngioma and those of normal brain tissues, performed GO and KEGG analysis, constructed the protein-protein interaction network, and selected key genes verified using immunofluorescence. After data cleaning and quality control, 623 craniopharyngioma endothelial cells and 439 healthy brain endothelial cells were obtained. Compared with normal brain endothelial cells, craniopharyngioma endothelial cells were screened for 394 differentially up-expressed genes (DEGs). GO and KEGG results showed that DEGs probably modulated endothelial cells, adherens junction, focal adhesion, migration, actin cytoskeleton, and invasion via the PI3K-AKT, Rap1, Ras, Wnt, and Hippo pathways. The core genes screened were CTNNB1, PTK2, ITGB1, STAT3, FYN, HIF1A, VCL, SMAD3, PECAM1, FOS, and CDH5. This study obtained possible anti-angiogenic genes in craniopharyngioma. Our results shed novel insights into molecular mechanisms and craniopharyngioma treatment.

Cumulative summation analysis of learning curve for endoscopic endonasal transsphenoidal resection of craniopharyngiomas.

Background: To evaluate the cumulative summation (CUSUM) analysis of the learning curve for Endoscopic Endonasal Transsphenoidal resection of craniopharyngioma (EETC). Methods: Retrospectively analyzed the clinical data of 113 patients who underwent EETC by the same neurosurgery team of the first affiliated Hospital of Nanchang University from June 2012 to November 2020. The learning curve was created by the CUSUM method and analyzed, which was divided into two groups: the learning stage and stable stage based on the learning curve trend. The median operation time and minimum surgical case number was calculated and the operation time and postoperative complications were compared between the two groups. Results: The median operation time was 318 min. The best fitting curve equation was y = 227.72 + 49.06x + 0.14x2 - 0.05x3, R2 = 0.949, (p < 0.001). The minimum number of surgical cases was 65. Between the two groups, the operation time decreased from 360.8 ± 106.4 min in the learning group to 281.6 ± 69.9 min in the stable group (p < 0.05). The incidence of postoperative complications (intracranial infection, cerebrospinal fluid rhinorrhea, and diabetes insipidus) was significantly reduced (p < 0.05). Conclusion: The CUSUM learning curve of craniopharyngioma resection via endoscope endonasal transsphenoidal approach could better describe the learning process for a neurosurgeon. The frequency of surgery could be a good factor for strengthening the learning effect and help to shorten the learning time. After 65 cases of EETC, the surgical skills can reach a stable stage, the operation time is obviously shortened, and the postoperative complications are significantly reduced.

MicroRNA-146a inhibition promotes total neurite outgrowth and suppresses cell apoptosis, inflammation, and STAT1/MYC pathway in PC12 and cortical neuron cellular Alzheimer's disease models.

This study aimed to explore the effect of microRNA (miR)-146a inhibition on regulating cell apoptosis, total neurite outgrowth, inflammation, and STAT1/MYC pathway in Alzheimer's disease (AD). PC12 and cortical neuron cellular AD models were constructed by Aß1-42 insult. For the former model, nerve growth factor (NGF) stimulation was previously conducted. miR-146a inhibitor and negative-control (NC) inhibitor were transfected into the two cellular AD models, and then cells were named miR-inhibitor group and NC-inhibitor group, respectively. After transfection, cell apoptosis, total neurite outgrowth, supernatant inflammation cytokines, and STAT1/MYC pathway were detected. miR-146a expression was similar between PC12 cellular AD model and control cells (NGF-stimulated PC12 cells), while miR-146a expression was increased in cortical neuron cellular AD model compared with control cells (rat embryo primary cortical neurons). In both PC12 and cortical neuron cellular AD models, miR-146a expression was reduced in miR-inhibitor group compared with NC-inhibitor group after transfection. Furthermore, cell apoptosis was attenuated, while total neurite outgrowth was elevated in miR-inhibitor group compared with NC-inhibitor group. As for supernatant inflammatory cytokines, tumor necrosis factor-α, interleukin (IL)-1ß, IL-6, and IL-17 levels were lower in miR-inhibitor group than in NC-inhibitor group. Additionally, STAT1 and c-Myc mRNA and protein expressions were attenuated in miR-inhibitor group compared with NC-inhibitor group. In conclusion, miR-146a potentially represented a viable therapeutic target for AD.

MicroRNA-146a inhibition promotes total neurite outgrowth and suppresses cell apoptosis, inflammation, and STAT1/MYC pathway in PC12 and cortical neuron cellular Alzheimer's disease models

This study aimed to explore the effect of microRNA (miR)-146a inhibition on regulating cell apoptosis, total neurite outgrowth, inflammation, and STAT1/MYC pathway in Alzheimer's disease (AD). PC12 and cortical neuron cellular AD models were constructed by Aβ1-42 insult. For the former model, nerve growth factor (NGF) stimulation was previously conducted. miR-146a inhibitor and negative-control (NC) inhibitor were transfected into the two cellular AD models, and then cells were named miR-inhibitor group and NC-inhibitor group, respectively. After transfection, cell apoptosis, total neurite outgrowth, supernatant inflammation cytokines, and STAT1/MYC pathway were detected. miR-146a expression was similar between PC12 cellular AD model and control cells (NGF-stimulated PC12 cells), while miR-146a expression was increased in cortical neuron cellular AD model compared with control cells (rat embryo primary cortical neurons). In both PC12 and cortical neuron cellular AD models, miR-146a expression was reduced in miR-inhibitor group compared with NC-inhibitor group after transfection. Furthermore, cell apoptosis was attenuated, while total neurite outgrowth was elevated in miR-inhibitor group compared with NC-inhibitor group. As for supernatant inflammatory cytokines, tumor necrosis factor-α, interleukin (IL)-1β, IL-6, and IL-17 levels were lower in miR-inhibitor group than in NC-inhibitor group. Additionally, STAT1 and c-Myc mRNA and protein expressions were attenuated in miR-inhibitor group compared with NC-inhibitor group. In conclusion, miR-146a potentially represented a viable therapeutic target for AD.