MetaWise: Combined Feature Selection and Weighting Method to Link the Serum Metabolome to Treatment Response and Survival in Glioblastoma.

Glioblastoma (GBM) is a highly malignant and devastating brain cancer characterized by its ability to rapidly and aggressively grow, infiltrating brain tissue, with nearly universal recurrence after the standard of care (SOC), which comprises maximal safe resection followed by chemoirradiation (CRT). The metabolic triggers leading to the reprogramming of tumor behavior and resistance are an area increasingly studied in relation to the tumor molecular features associated with outcome. There are currently no metabolomic biomarkers for GBM.

Correction: Tasci et al. RadWise: A Rank-Based Hybrid Feature Weighting and Selection Method for Proteomic Categorization of Chemoirradiation in Patients with Glioblastoma. 2023, , 2672.

In the original publication [...

Serum CD133-Associated Proteins Identified by Machine Learning Are Connected to Neural Development, Cancer Pathways, and 12-Month Survival in Glioblastoma.

Glioma is the most prevalent type of primary central nervous system cancer, while glioblastoma (GBM) is its most aggressive variant, with a median survival of only 15 months when treated with maximal surgical resection followed by chemoradiation therapy (CRT). CD133 is a potentially significant GBM biomarker. However, current clinical biomarker studies rely on invasive tissue samples.

Diagnosing Progression in Glioblastoma-Tackling a Neuro-Oncology Problem Using Artificial-Intelligence-Derived Volumetric Change over Time on Magnetic Resonance Imaging to Examine Progression-Free Survival in Glioblastoma.

Glioblastoma (GBM) is the most aggressive and the most common primary brain tumor, defined by nearly uniform rapid progression despite the current standard of care involving maximal surgical resection followed by radiation therapy (RT) and temozolomide (TMZ) or concurrent chemoirradiation (CRT), with an overall survival (OS) of less than 30% at 2 years. The diagnosis of tumor progression in the clinic is based on clinical assessment and the interpretation of MRI of the brain using Response Assessment in Neuro-Oncology (RANO) criteria, which suffers from several limitations including a paucity of precise measures of progression. Given that imaging is the primary modality that generates the most quantitative data capable of capturing change over time in the standard of care for GBM, this renders it pivotal in optimizing and advancing response criteria, particularly given the lack of biomarkers in this space.

MGMT ProFWise: Unlocking a New Application for Combined Feature Selection and the Rank-Based Weighting Method to Link MGMT Methylation Status to Serum Protein Expression in Patients with Glioblastoma.

Glioblastoma (GBM) is a fatal brain tumor with limited treatment options. O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation status is the central molecular biomarker linked to both the response to temozolomide, the standard chemotherapy drug employed for GBM, and to patient survival. However, MGMT status is captured on tumor tissue which, given the difficulty in acquisition, limits the use of this molecular feature for treatment monitoring.

Advances in the field of developing biomarkers for re-irradiation: a how-to guide to small, powerful data sets and artificial intelligence.

Introduction: Patient selection remains challenging as the clinical use of re-irradiation (re-RT) increases. Re-RT data is limited to retrospective studies and small prospective single-institution reports, resulting in small, heterogenous data sets. Validated prognostic and predictive biomarkers are derived from large-volume studies with long-term follow-up.

Corrigendum: Glioblastoma survival is associated with distinct proteomic alteration signatures post chemoirradiation in a large-scale proteomic panel.

[This corrects the article DOI: 10.3389/fonc.2023.

GradWise: A Novel Application of a Rank-Based Weighted Hybrid Filter and Embedded Feature Selection Method for Glioma Grading with Clinical and Molecular Characteristics.

Glioma grading plays a pivotal role in guiding treatment decisions, predicting patient outcomes, facilitating clinical trial participation and research, and tailoring treatment strategies. Current glioma grading in the clinic is based on tissue acquired at the time of resection, with tumor aggressiveness assessed from tumor morphology and molecular features. The increased emphasis on molecular characteristics as a guide for management and prognosis estimation underscores is driven by the need for accurate and standardized grading systems that integrate molecular and clinical information in the grading process and carry the expectation of the exposure of molecular markers that go beyond prognosis to increase understanding of tumor biology as a means of identifying druggable targets.

An Overview of CD133 as a Functional Unit of Prognosis and Treatment Resistance in Glioblastoma.

Biomarkers for resistance in Glioblastoma multiforme (GBM) are lacking, and progress in the clinic has been slow to arrive. CD133 (prominin-1) is a membrane-bound glycoprotein on the surface of cancer stem cells (CSCs) that has been associated with poor prognosis, therapy resistance, and tumor recurrence in GBM. Due to its connection to CSCs, to which tumor resistance and recurrence have been partially attributed in GBM, there is a growing field of research revolving around the potential role of CD133 in each of these processes.

Glioblastoma survival is associated with distinct proteomic alteration signatures post chemoirradiation in a large-scale proteomic panel.

Background: Glioblastomas (GBM) are rapidly progressive, nearly uniformly fatal brain tumors. Proteomic analysis represents an opportunity for noninvasive GBM classification and biological understanding of treatment response.

Purpose: We analyzed differential proteomic expression pre vs.

Evaluation of donor-derived bacterial infections in lung transplant recipients.

Background: This study aims to evaluate the etiology and outcomes of donor-derived bacterial infections in patients undergoing lung transplantation.

Methods: Between January 2013 and December 2017, a total of 71 lung transplant recipients (56 males, 15 females; median age: 43.3 years) were retrospectively analyzed.

RadWise: A Rank-Based Hybrid Feature Weighting and Selection Method for Proteomic Categorization of Chemoirradiation in Patients with Glioblastoma.

Glioblastomas (GBM) are rapidly growing, aggressive, nearly uniformly fatal, and the most common primary type of brain cancer. They exhibit significant heterogeneity and resistance to treatment, limiting the ability to analyze dynamic biological behavior that drives response and resistance, which are central to advancing outcomes in glioblastoma. Analysis of the proteome aimed at signal change over time provides a potential opportunity for non-invasive classification and examination of the response to treatment by identifying protein biomarkers associated with interventions.

Cost Matrix of Molecular Pathology in Glioma-Towards AI-Driven Rational Molecular Testing and Precision Care for the Future.

Gliomas are the most common and aggressive primary brain tumors. Gliomas carry a poor prognosis because of the tumor's resistance to radiation and chemotherapy leading to nearly universal recurrence. Recent advances in large-scale genomic research have allowed for the development of more targeted therapies to treat glioma.

Hierarchical Voting-Based Feature Selection and Ensemble Learning Model Scheme for Glioma Grading with Clinical and Molecular Characteristics.

Determining the aggressiveness of gliomas, termed grading, is a critical step toward treatment optimization to increase the survival rate and decrease treatment toxicity for patients. Streamlined grading using molecular information has the potential to facilitate decision making in the clinic and aid in treatment planning. In recent years, molecular markers have increasingly gained importance in the classification of tumors.

The Next Frontier in Health Disparities-A Closer Look at Exploring Sex Differences in Glioma Data and Omics Analysis, from Bench to Bedside and Back.

Sex differences are increasingly being explored and reported in oncology, and glioma is no exception. As potentially meaningful sex differences are uncovered, existing gender-derived disparities mirror data generated in retrospective and prospective trials, real-world large-scale data sets, and bench work involving animals and cell lines. The resulting disparities at the data level are wide-ranging, potentially resulting in both adverse outcomes and failure to identify and exploit therapeutic benefits.

Bias and Class Imbalance in Oncologic Data-Towards Inclusive and Transferrable AI in Large Scale Oncology Data Sets.

Recent technological developments have led to an increase in the size and types of data in the medical field derived from multiple platforms such as proteomic, genomic, imaging, and clinical data. Many machine learning models have been developed to support precision/personalized medicine initiatives such as computer-aided detection, diagnosis, prognosis, and treatment planning by using large-scale medical data. Bias and class imbalance represent two of the most pressing challenges for machine learning-based problems, particularly in medical (e.

COVID-19: the new cause of dyspnoea as a result of reduced lung and peripheral muscle performance.

This study aimed to evaluate the cardiopulmonary function and impairment of exercise endurance in patients with COVID-19 after 3 months of the second wave of the pandemic in Turkey. A total of 51 consecutive COVID-19 survivors, mostly healthcare providers, still working in the emergency room and intensive care units of the hospital after the second wave of Covid 19 pandemia were included in this study. Cardiopulmonary exercise stress test was performed.

A voting-based ensemble deep learning method focusing on image augmentation and preprocessing variations for tuberculosis detection.

Tuberculosis (TB) is known as a potentially dangerous and infectious disease that affects mostly lungs worldwide. The detection and treatment of TB at an early stage are critical for preventing the disease and decreasing the risk of mortality and transmission of it to others. Nowadays, as the most common medical imaging technique, chest radiography (CXR) is useful for determining thoracic diseases.

Follow-up strategy with long-term veno-venous extracorporeal membrane oxygenation support for complicated severe acute respiratory distress related to COVID-19 and recovery of the lungs.

Novel coronavirus-2019 (COVID-19) pandemic has affected all over the world, leading to viral pneumonia-complicating severe acute respiratory distress syndrome and death. Although there is no proven definitive treatment yet, physicians use some assistive methods based on the previous epidemic viral acute respiratory distress syndrome experiences. Extracorporeal membrane oxygenation is one of them.

Lung transplantation for non-cystic fibrosis bronchiectasis in Turkey: An initial institutional experience.

Background/objective: Lung transplantation is a well-established treatment in patients who have bronchiectasis with diffuse involvement, and with a progressive decline in respiratory function despite maximal medical therapy. We have aimed to present pre-transplantation factors and our results of lung transplantation for non-cystic fibrosis bronchiectasis.

Methods: Patients who underwent lung transplantation for non-cystic fibrosis bronchiectasis between the dates of December 2016 and July 2019 were included.

Lung Transplantation for Cystic Fibrosis in Turkey: First Report.

Objectives: Lung transplant is the most important treatment approach that improves the life expectancy and quality of life for patients with cystic fibrosis with end-stage lung disease. In this study, we retros-pectively analyzed patients with cystic fibrosis who were referred to our lung transplant program in Turkey.

Materials And Methods: We evaluated 14 patients with cystic fibrosis who were referred to our lung transplant clinic between December 2016 and December 2019.

Extracorporeal membrane oxygenation as a bridge to lung transplantation in a Turkish lung transplantation program: our initial experience.

Lung transplantation is a life-saving treatment for patients with end-stage lung disease. Although the number of lung transplants has increased over the years, the number of available donor lungs has not increased at the same rate, leading to the death of transplant candidates on waiting lists. In this paper, we presented our initial experience with the use of extracorporeal membrane oxygenation (ECMO) as a bridge to lung transplantation.

Anticoagulant-induced breast hematoma.

Warfarin is the most commonly used oral anticoagulant and is widely prescribed to prevent thromboembolic events. Warfarin-dependent spontaneous breast hematoma is a very rare complication. Presently described is rare case of warfarin-induced breast hematoma.

Lung transplantation in Turkey: lessons from surgeons and pulmonologists.

Background/aim: In order to actualize an efficient lung transplantation program, it is necessary to determine priorities and set up strategies. This study aimed to estimate the present situation in Turkey by determining the level of interest and knowledge of pulmonologists and thoracic surgeons regarding lung transplantation.

Materials And Methods: A questionnaire was prepared to establish the level of interest and knowledge of physicians on lung transplantation.