Recent studies have shown that some inflammatory markers are associated with the prognosis of solid tumors. This study aims to evaluate the prognosis of glioma patients with or without adjuvant treatment using the systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), and platelet-lymphocyte ratio (PLR).All patients who were diagnosed with gliomas at the first and second affiliated hospital of Guangxi Medical University between 2011 and 2020 were included in this study. The optimal cutoff value of SII, NLR, and PLR was determined by X-tile software program. We stratified patients into several groups and evaluated the progression-free survival (PFS) and overall survival (OS) of SII, NLR, and PLR during the period of pre-surgical, con-chemoradiotherapy, and post-treatments. Multivariate Cox regression analyses were performed to detect the relationships between OS, PFS, and prognostic variables.A total of 67 gliomas patients were enrolled in the study. The cutoff values of SII, NLR, and PLR were 781.5 × 109/L, 2.9 × 109/L, and 123.2 × 109/L, respectively. Patients who are pre-SII < 781.5 × 109/L had better PFS (P = .027), but no difference in OS. In addition, patients who had low pre-NLR (<2.9 × 109/L) meant better OS and PFS. PLR after adjuvant treatments (post-PLR) was significantly higher than pre-PLR (P = .035). Multivariate analyses revealed that pre-SII, pre-NLR were independent prognostic factors for OS (pre-SII: HR 1.002, 95% CI: 1.000-1.005, P = .030 and pre-PLR: HR 0.983, 95% CI: 0.973-0.994, P = .001), while pre-PLR was an independent factor for PFS (HR 0.989, 95% CI: 0.979-1.000, P = .041).High pre-SII or high pre-NLR could be prognostic markers to identify glioma patients who had a poor prognosis.
To investigate the immune cell infiltration status in glioblastoma multiforme (GBM) and construct a novel prognostic risk model that can predict patients' prognosis.The Cancer Genome Atlas (TCGA) database was used to obtain RNA-sequence information and relevant clinical data. We performed Pearson correlation, univariate Cox regression to screen m6A-related prognostic lncRNA. GMB patients' samples were separated into different clusters through the ConsensusClusterPlus package. The risk score model was established through LASSO regression analysis. Besides, KEGG pathway enrichment analysis was implemented. CIBERSORT algorithm was used to analyze the difference of 22 types of immune cell infiltration in different cluster of GBM patient. Cox regression analyses were used to verify the independence of the model and correlation analysis was performed to demonstrate the link between our model and clinical characteristics of GBM patients. Experiments were used to validate the differential expression of the model lncRNA in patients with different prognosis.17 lncRNA related to prognosis were screened from 1021 m6A-related lncRNAs. Further, four m6A-related lncRNAs that were significantly correlated with GBM prognosis were selected to establish our prognostic risk model, which had excellent accuracy and can independently predict the prognosis of GBM patients. The infiltration fractions of T regulatory cells, T cells CD4 memory activated and neutrophils were positively associated with risk score, which suggested a significant relationship between the model and tumor immune microenvironment.The m6A-related RNA risk model offered potential for identifying biomarkers of therapy and predicting prognosis of GBM patients.
The rabbit brain model is commonly applied in neuroscience, including basic science, neuro medicine, and neural network, etc. The rabbit brain is more suitable than the mouse one for a microscopic neuroanatomy atlas study due to its suitable size and shape. Lateral ventricles are essential landmarks that enable a three-dimensional structure understanding of the rabbit cerebrum. Knowledge about how the nervous structures outside the neural tube amplify and contort around the lateral ventricles would help in the understanding of the rabbit cerebrum's three-dimensional organization. Ten rabbits were used in this study. After fixation for at least two weeks, rabbits' heads were dissected and micro-operative anatomy photographs were taken using the stereomicroscope camera. All figures were divided into three parts: lateral ventricles body; choroid fissure and the thalamus-cerebrum space; partition and connection between the left and right lateral ventricles. Under the stereoscopic microscope, it can be observed that: rabbit cerebrum left and right lateral ventricles were wrapped by the grey and white matter layers; hippocampal formation, relatively older cortical structures in the cerebrum, coiled inward by newer cortex; the curly edges of the cortex made the choroid fissure, namely the potential opening between the lateral ventricles (left and right) and cerebrum surface. The three-dimensional structure atlas also showed cortex folding and coil and that cortex with the hippocampal formation was centered in the thalamus, while the thalamus was in a direct extension relationship with the cortex-hippocampus formation. The relationship between the thalamus and the cortex-hippocampus formation should be noticed in neural network research as it suggests that the thalamus may be at the core of the cerebrum network. If we could have a correct understanding of rabbit cerebrum three-dimensional structure via microscopic anatomical atlas under the microscope before the section research, we would be able to assembly the local neural network structures in the brain constructed by section research into a complete cerebrum network properly.
A Fe-doped NiMoO 4 pre-catalyst with lattice defects induced by NH 3 treatment shows bulk and rapid reconstruction to distorted γ-Ni(Fe)OOH with improved intrinsic activity for water oxidation.
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