Study of Tumor Cells in the G0 or G1 Nerve Growth State

The cell cycle of such a subject has been thoroughly studied, yet here we are examining for the second time that we have entered a new phase; Biology always has new insights to show us. This data was amazing. This map is based on this beautiful circular pattern that we have identified as all the different stages of the cell cycle. Have a disease. When Placer and colleagues used the ccAF tool to analyze cell data for glioma tumors, we found that tumor cells were often in the G0 or G1 nerve growth state. With tumor aggression, fewer cells remain at rest in the G0 nerve state. This means that more cells are growing and growing in the tumor. Keywords: Cancer; Cells; Tissues; Tumors; Prevention; Prognosis; Diagnosis; Imaging; Screening, Treatment; Management

Epigenetic Regulation of Hematopoiesis and Acute Leukemia

The cell cycle of such a subject has been thoroughly studied, yet here we are examining for the second time that we have entered a new phase; Biology always has new insights to show us. This data was amazing. This map is based on this beautiful circular pattern that we have identified as all the different stages of the cell cycle. Have a disease. When Placer and colleagues used the ccAF tool to analyze cell data for glioma tumors, we found that tumor cells were often in the G0 or G1 nerve growth state. With tumor aggression, fewer cells remain at rest in the G0 nerve state. This means that more cells are growing and growing in the tumor. Keywords: Cancer; Cells; Tissues, Tumors; Prevention, Prognosis; Diagnosis; Imaging; Screening; Treatment; Management

Raman Spectroscopy and Machine Learning for IDH Genotyping of Unprocessed Glioma Biopsies

Isocitrate dehydrogenase (IDH) mutational status is pivotal in the management of gliomas. Patients with IDH-mutated (IDH-MUT) tumors have a better prognosis and benefit more from extended surgical resection than IDH wild-type (IDH-WT). Raman spectroscopy (RS) is a minimally invasive optical technique with great potential for intraoperative diagnosis. We evaluated the RS’s ability to characterize the IDH mutational status onto unprocessed glioma biopsies. We extracted 2073 Raman spectra from thirty-eight unprocessed samples. The classification performance was assessed using the eXtreme Gradient Boosted trees (XGB) and Support Vector Machine with Radial Basis Function kernel (RBF-SVM). Measured Raman spectra displayed differences between IDH-MUT and IDH-WT tumor tissue. From the 103 Raman shifts screened as input features, the cross-validation loop identified 52 shifts with the highest performance in the distinction of the two groups. Raman analysis showed differences in spectral features of lipids, collagen, DNA and cholesterol/phospholipids. We were able to distinguish between IDH-MUT and IDH-WT tumors with an accuracy and precision of 87%. RS is a valuable and accurate tool for characterizing the mutational status of IDH mutation in unprocessed glioma samples. This study improves RS knowledge for future personalized surgical strategy or in situ target therapies for glioma tumors.

Correlation between Stage and Histopathological Features and Clinical Outcomes in Patients with Glioma Tumors

BACKGROUND: Brain tumor incidence continues to increase during the last decade in several countries. Determining the response of intracranial tumors to treatment remains a major challenge in the field of neuro-oncology. Karnofsky Performance Status Scale (KPS) is a widely used method for assessing the functional status of a patient. AIM: This study aims to determine the relationship between stadium and histopathological features with clinical outcomes in patients with glioma tumors. METHODS: This was an observational analytic study with a retrospective approach at the H. Adam Malik General Hospital in Medan from September 2019 to September 2020. The study population was glioma patients. The research sample was 36 subjects taken consecutively. The independent variables of the study were stage and histopathological features, while the dependent variable of the study was KPS. Statistical analysis with Gamma test. RESULTS: Mean age was 38.11 ± 13.86 years. Most subjects were male, amounting to 20 subjects (55.6%). The most common type of glioma tumor was anaplastic astrocytoma, amounting to 8 subjects (22.2%). The highest tumor stage was a high-grade glioma, amounting to 19 subjects (52.8%), and the most histopathological features based on WHO criteria were WHO grade 3, totaling 13 subjects (36.1%). Most KPS is 80–100 with 19 subjects (52.8%). There is a significant correlation between the stage and histopathological features with KPS with a moderate correlation strength (p = 0.036; r = 0.598) (p = 0.024; r = 0.508) CONCLUSION: There is a significant correlation between stage and histopathological features with KPS with moderate correlation strength

A Gradient Discretisation Method for Anisotropic Reaction–Diffusion Models with Applications to the Dynamics of Brain Tumors

A gradient discretisation method (GDM) is an abstract setting that designs the unified convergence analysis of several numerical methods for partial differential equations and their corresponding models. In this paper, we study the GDM for anisotropic reaction–diffusion problems, based on a general reaction term, with Neumann boundary condition. With natural regularity assumptions on the exact solution, the framework enables us to provide proof of the existence of weak solutions for the problem, and to obtain a uniform-in-time convergence for the discrete solution and a strong convergence for its discrete gradient. It also allows us to apply non-conforming numerical schemes to the model on a generic grid (the non-conforming ℙ ⁢ 1 {\mathbb{P}1} finite element scheme and the hybrid mixed mimetic (HMM) methods). Numerical experiments using the HMM method are performed to assess the accuracy of the proposed scheme and to study the growth of glioma tumors in heterogeneous brain environment. The dynamics of their highly diffusive nature is also measured using the fraction anisotropic measure. The validity of the HMM is examined further using four different mesh types. The results indicate that the dynamics of the brain tumor is still captured by the HMM scheme, even in the event of a highly heterogeneous anisotropic case performed on the mesh with extreme distortions.

Differentiating Between Low- and High-grade Glioma Tumors Measuring Apparent Diffusion Coefficient Values in Various Regions of the Brain

Objectives: Our study aimed to apply the apparent diffusion coefficient (ADC) values to quantify the differences between low- and high-grade glioma tumors. Methods: We conducted a multicenter, retrospective study between September to December 2019. Magnetic resonance imaging (MRI) diffusion-weighted images (DWIs), and the pathologic findings of 56 patients with glioma tumors (low grade = 28 and high grade = 28) were assessed to measure the ADC values in the tumor center, tumor edema, boundary area between tumor with normal tissue, and inside the healthy hemisphere. These values were compared between the two groups, and cut-off values were calculated using the receiver operating characteristic curve. Results: We saw significant differences between the mean ADC values measured in the tumor center and edema between high- and low-grade tumors (p < 0.005). The ADC values in the boundary area between tumors with normal tissue and inside healthy hemisphere did not significantly differ in the groups. The ADC values at tumor center and edema were higher than 1.12 × 10-3 mm2/s (sensitivity = 100% and specificity = 96.0%) and 1.15 × 10-3 mm2/s (sensitivity = 75.0% and specificity = 64.0%), respectively, could be classified as low-grade tumors. Conclusions: The ADC values from the MRI DWIs in the tumor center and edema could be used as an appropriate method for investigating the differences between low- and high-grade glioma tumors. The ADC values in the boundary area and healthy tissues had no diagnostic values in grading the glioma tumors.

Silencing ZEB2 Induces Apoptosis and Reduces Viability in Glioblastoma Cell Lines

Background: Glioma is an aggressive type of brain tumor that originated from neuroglia cells, accounts for about 80% of all malignant brain tumors. Glioma aggressiveness has been associated with extreme cell proliferation, invasion of malignant cells, and resistance to chemotherapies. Due to resistance to common therapies, glioma affected patients’ survival has not been remarkably improved. ZEB2 (SIP1) is a critical transcriptional regulator with various functions during embryonic development and wound healing that has abnormal expression in different malignancies, including brain tumors. ZEB2 overexpression in brain tumors is attributed to an unfavorable state of the malignancy. Therefore, we aimed to investigate some functions of ZEB2 in two different glioblastoma U87 and U373 cell lines. Methods: In this study, we investigated the effect of ZEB2 knocking down on the apoptosis, cell cycle, cytotoxicity, scratch test of the two malignant brain tumor cell lines U87 and U373. Besides, we investigated possible proteins and microRNA, SMAD2, SMAD5, and miR-214, which interact with ZEB2 via in situ analysis. Then we evaluated candidate gene expression after ZEB2-specific knocking down. Results: We found that ZEB2 suppression induced apoptosis in U87 and U373 cell lines. Besides, it had cytotoxic effects on both cell lines and reduced cell migration. Cell cycle analysis showed cell cycle arrest in G0/G1 and apoptosis induction in U87 and U373 cell lines receptively. Also, we have found that SAMAD2/5 expression was reduced after ZEB2-siRNA transfection and miR-214 upregulated after transfection. Conclusions: In line with previous investigations, our results indicated a critical oncogenic role for ZEB2 overexpression in brain glioma tumors. These properties make ZEB2 an essential molecule for further studies in the treatment of glioma cancer.

Repercussion of palliative care on survival in patients with High-grade Glioma

Aim: To determine the influence of education in early neuro-palliative care, on the survival of patients diagnoses with high-grade glioma, to evaluate the overload associated with the care of such patients. Method: was an observational, cross-sectional, descriptive, and exploratory study in 52 patients and caregivers with High-grade glioma tumors as the pathological diagnosis, treated at the Institute of Neurology and Neurosurgery of Havana from January 2019 to January 2020. Results: The care provision system was in charge of family members in 51.9% of the patients, predominantly female in this task; 45 (86.7%), 42.2% of which maintained a labor relationship, with a mean age of 53.9 years. The Zarit test was applied in the 52 caregivers, intense overload was recorded in 33 (63.5%), mild in 10 (19.2%) and no overload in 9 (17.3%). Patients in whom their caregivers received education in palliative care at the time of HGG diagnosis had 57.1 more days of survival, unlike those who received it in the period of neurological deterioration (241.7 vs 184.6 days). Survival time was influenced by the record of caregiver burden. Conclusion: The overall survival life time was directly related to the caregiver's education in palliative care and the time it was received, early palliative care education, could influence prolonging life.