A hundred fifteen patients (53 men and 62 women), aged 62.7 years ± 16 (standard deviation, SD), were studied. They represent a convenience sample of patients with balance disorders, recruited with a consecutive sampling method. Patient diagnosis was as follows: 22 hemiparesis (12 right, 10 left), 21 Parkinson’s disease, 15 neuromuscular diseases, 14 hereditary ataxia, 11 multiple sclerosis, 10 unspecific age-related balance disorders, 7 peripheral vestibular disorders, 6 traumatic brain injury, 4 diffuse encephalopathy, 3 cervical myelopathy and 2 CNS neoplasm. All subjects were inpatients referred to the Scientific Institute of Veruno for rehabilitation assessment and treatment. Inclusion criteria were: able to walk with or without a cane; absence of severe cognitive or communication impairments; ability to tolerate the balance tasks without fatigue. Prior to taking part in the study, all participants signed the informed consent that had been approved by the Central Ethics Committee of the ‘Salvatore Maugeri’ Foundation.
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Central Nervous System Neoplasms
Central Nervous System Neoplasms
Central Nervous System Neoplasms refer to a diverse group of tumors that originate in the brain, spinal cord, or surrounding structures.
These cancers can vary in aggressivness and may affect various neurological functions.
Prompt diagnosis and targeted treatment are crucial for managing these complex conditions.
PubCompare.ai's AI-driven platform can help streamline your research by providing access to the latest protocols, pre-prints, and patents, while offering intelligent comparison tools to identify the most promising approaches.
Optimise your Central Nervous System Neoplasms research and accelerate your discoveries with PubCompare.ai.
These cancers can vary in aggressivness and may affect various neurological functions.
Prompt diagnosis and targeted treatment are crucial for managing these complex conditions.
PubCompare.ai's AI-driven platform can help streamline your research by providing access to the latest protocols, pre-prints, and patents, while offering intelligent comparison tools to identify the most promising approaches.
Optimise your Central Nervous System Neoplasms research and accelerate your discoveries with PubCompare.ai.
Most cited protocols related to «Central Nervous System Neoplasms»
Ataxias, Hereditary
Canes
Central Nervous System Neoplasms
Cognition
Communicative Disorders
Diagnosis
Encephalopathies
Ethics Committees
Fatigue
Hemiparesis
Inpatient
Multiple Sclerosis
Neck
Neuromuscular Diseases
Patients
Rehabilitation
Spinal Cord Diseases
Traumatic Brain Injury
Vestibular Diseases
Woman
To compare our methylation-based classification of CNS tumours with described methylation classes of brain tumours by the Cancer Genome Atlas (TCGA) project, we downloaded the pre-processed methylation dataset described in Ceccarelli et al. 201618 including methylation data of 418 low grade glioma and 377 glioblastoma samples analysed by using the Illumina 450k array or 27k array platforms. To classify our samples according to the TCGA pan-glioma DNA methylation classification, we trained a Random Forest classifier on this dataset using the 1,300 CpG probe signature provided by the authors and using the default settings of the Random Forest algorithms implemented in the R package randomForest. The results of this classification for astrocytomas, oligodendrogliomas and glioblastomas are shown in Extended Data Figure 3d and are given on a case-by-case basis in Supplementary Table 2 and 4 .
Astrocytoma
Brain Neoplasm, Malignant
Central Nervous System Neoplasms
DNA Methylation
Genome
Glioblastoma
Glioblastoma Multiforme
Glioma
Malignant Neoplasms
Methylation
Neoplasms
Oligodendroglioma
Astrocytoma
Brain Neoplasm, Malignant
Central Nervous System Neoplasms
DNA Methylation
Genome
Glioblastoma
Glioblastoma Multiforme
Glioma
Malignant Neoplasms
Methylation
Neoplasms
Oligodendroglioma
Central Nervous System Neoplasms
Chromosomes
Copy Number Polymorphism
Crossbreeding
Diagnosis
DNA Library
DNA Methylation
Europeans
Formalin
Freezing
Gene Chips
Gene Deletion
Gene Expression
Genes
Genome
Genome, Human
Medulloblastoma
Methylation
Neoplasms
Neuropathologist
Paraffin
Paraffin Embedding
Patients
Tissues
All methylation data were generated using the Illumina HumanMethylation450 (450k) or MethylationEPIC (850k) array platforms. Unsupervised clustering of methylation array data from a previously established reference set of unambiguously diagnosed CNS tumors (“the reference cohort”) revealed clear formation of separate tumor groups. The “Classifier” tool was developed based on a random forest algorithm. The current version v11b4 of the Classifier is based on the analysis of 10,000 CpG sites present on both the 450k and the EPIC arrays. An in-depth description on the theoretical background and development of this tool is given elsewhere [6 (link)].
The error rate of the Classifier calculated by a cross-validation analysis of the reference cohort was estimated to be approximately 1%. However, for statistical reasons in this cross validation, the class prediction was defined as “class with highest score” and did not include the threshold of ≥ 0.9 as an additional requirement for a correct prediction (for further information on the threshold see below). Therefore, we assume that many of the cases constituting the 1% “technical” error rate would actually resolve as cases with a calibrated score below ≥ 0.9, and we have not yet identified cases with such a technical error scoring in our routine workup.
The same set of data generated by employing the Illumina 450k or Illumina 850k/EPIC arrays can be used to calculate copy-number alterations using the ‘conumee’ package for R (http://bioconductor.org/packages/conumee ).
The error rate of the Classifier calculated by a cross-validation analysis of the reference cohort was estimated to be approximately 1%. However, for statistical reasons in this cross validation, the class prediction was defined as “class with highest score” and did not include the threshold of ≥ 0.9 as an additional requirement for a correct prediction (for further information on the threshold see below). Therefore, we assume that many of the cases constituting the 1% “technical” error rate would actually resolve as cases with a calibrated score below ≥ 0.9, and we have not yet identified cases with such a technical error scoring in our routine workup.
The same set of data generated by employing the Illumina 450k or Illumina 850k/EPIC arrays can be used to calculate copy-number alterations using the ‘conumee’ package for R (
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Central Nervous System Neoplasms
Copy Number Polymorphism
Methylation
Neoplasms
Most recents protocols related to «Central Nervous System Neoplasms»
All paediatric patients (< 18 years old) diagnosed with a supratentorial CNS-PNET and registered in the Swedish Childhood Cancer Registry (SCCR) between the 1st of January 1984 and 31st of December 2015 were eligible for the study. We searched the registry for the diagnoses of supratentorial PNET, supratentorial Medulloblastoma or CNS-PNET. The SCCR is estimated to capture approximately 94% of all diagnosed CNS tumours in children (0–15 years old) in Sweden since 1984 (unpublished data).
In total 88 patients were identified in the registry and formalin-fixed paraffin-embedded (FFPE) tumour material was available for re-evaluation in 71 of them. Clinical data were obtained from the SCCR or from the patients´ records. For each patient, gender, age at diagnosis, tumour localisation, metastatic status according to Chang stage [16 (link)], date of diagnosis, treatment, date of progression and date of death, or last follow-up were collected. Cases were followed until death, or until the 1st of February 2022.
In total 88 patients were identified in the registry and formalin-fixed paraffin-embedded (FFPE) tumour material was available for re-evaluation in 71 of them. Clinical data were obtained from the SCCR or from the patients´ records. For each patient, gender, age at diagnosis, tumour localisation, metastatic status according to Chang stage [16 (link)], date of diagnosis, treatment, date of progression and date of death, or last follow-up were collected. Cases were followed until death, or until the 1st of February 2022.
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Central Nervous System Neoplasms
Child
Diagnosis
Disease Progression
Formalin
Gender
Malignant Neoplasms
Medulloblastoma
Neoplasms
Paraffin
Patients
The Stop & Shop Family Pediatric Neuro-Oncology Outcomes Clinic is a multidisciplinary clinic which provides ongoing care to survivors of childhood CNS tumors greater than two years from diagnosis. The care team include pediatric neuro-oncology, pediatric neurology, psychology, neuropsychology and education specialists.
Central Nervous System Neoplasms
Diagnosis
Neoplasms
Specialists
Survivors
We identified GBM patients with an age ≥ 65 years at the date of initial surgery, who had undergone microsurgical resection as primary treatment at two university hospitals between 02/2012 and 12/2016 (Center A) and 09/2006 to 06/2021 (Center B). Exclusion criteria were defined as emergency surgery, biopsy only, palliative care only as well as patients with known secondary GBMs. The two hospitals have a combined catchment area of approximately 2,250,000 inhabitants. Annual caseloads of glioma surgeries were approximated to be ~ 120 (Center A) and ~ 50 (Center B).
Histopathological grading was performed according to the WHO classification of tumors of the central nervous system valid at the time of diagnosis [25 (link), 26 (link)]. Clinical data extraction was performed from electronic medical records and included patient characteristics such as age, sex, preoperative Karnofsky Performance Scale (KPS), tumor location and leading symptoms.
All patients/legal guardians gave written informed consent prior to all surgical procedures and adjuvant treatments. The State Review Board approval was obtained for the retrospective GBM databases this study was conducted upon (IRB-Number 415-E/2247/2-2017).
Histopathological grading was performed according to the WHO classification of tumors of the central nervous system valid at the time of diagnosis [25 (link), 26 (link)]. Clinical data extraction was performed from electronic medical records and included patient characteristics such as age, sex, preoperative Karnofsky Performance Scale (KPS), tumor location and leading symptoms.
All patients/legal guardians gave written informed consent prior to all surgical procedures and adjuvant treatments. The State Review Board approval was obtained for the retrospective GBM databases this study was conducted upon (IRB-Number 415-E/2247/2-2017).
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Biopsy
Central Nervous System Neoplasms
Diagnosis
Emergencies
Glioma
Legal Guardians
Neoplasms by Site
Operative Surgical Procedures
Palliative Care
Patients
Pharmaceutical Adjuvants
Protocol full text hidden due to copyright restrictions
Open the protocol to access the free full text link
Central Nervous System Neoplasms
Diagnosis
Genes
Isocitrate Dehydrogenase (NAD+)
Methylation
MGMT protein, human
Mutation
O(6)-Methylguanine-DNA Methyltransferase
Patients
From February 2017 to August 2021, a total of 13 patients (15 operations) suspected of DLGG in the central lobe based on pre-operative MRI were successively treated with awake craniotomy. All the patients recruited had no severe pre-operative neurological deficits or mental disorientation.
Clinical, radiological and histopathological characteristics were collected during admission, including sex, age, symptoms, neurological deficits, Karnofsky performance scale, seizure attacks, tumor location, and pathological grades and subtypes were revised according to the WHO Classification of Tumors of the Central Nervous System, Fifth Edition (CNS 5). The regional ethics committee approved the procedures and all subjects provided their informed written consent prior to participation in this study.
Clinical, radiological and histopathological characteristics were collected during admission, including sex, age, symptoms, neurological deficits, Karnofsky performance scale, seizure attacks, tumor location, and pathological grades and subtypes were revised according to the WHO Classification of Tumors of the Central Nervous System, Fifth Edition (CNS 5). The regional ethics committee approved the procedures and all subjects provided their informed written consent prior to participation in this study.
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Central Nervous System Neoplasms
Craniotomy
Insula of Reil
Neoplasms by Site
Patients
Regional Ethics Committees
Seizures
X-Rays, Diagnostic
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The Infinium MethylationEPIC BeadChip array is a microarray-based technology designed to measure DNA methylation levels across the human genome. It is capable of analyzing over 850,000 methylation sites, covering 99% of RefSeq genes, with a focus on CpG islands and regulatory regions.
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More about "Central Nervous System Neoplasms"
Central Nervous System (CNS) Neoplasms refer to a diverse array of tumors that originate in the brain, spinal cord, or surrounding structures.
These cancerous growths can vary in their aggressiveness and may impact various neurological functions.
Prompt and accurate diagnosis, as well as targeted treatment approaches, are crucial for managing these complex conditions.
The Infinium MethylationEPIC BeadChip array and Infinium Methylation EPIC are powerful tools that can help researchers and clinicians better understand the epigenetic changes associated with CNS neoplasms.
The ABE419 and EZ DNA Methylation Kit can also be utilized to study DNA methylation patterns in these tumors.
FBS, or fetal bovine serum, is a commonly used supplement in cell culture media and may be relevant for in vitro studies of CNS neoplasms.
The HumanMethylation450 BeadChip array is another platform that can provide insights into the methylation profiles of these cancers.
The BenchMark XT and BenchMark ULTRA Immunostainers are automated systems that can be used for immunohistochemical analysis of tissue samples, potentially aiding in the diagnosis and characterization of CNS neoplasms.
Phosphohistone-H3 is a marker that can be used to assess cell proliferation, which may be relevant for understanding the biology of these tumors.
The iScan system is a high-throughput scanning platform that can be used for various genomic and epigenomic analyses, including those related to CNS neoplasms.
By leveraging the latest technologies and research insights, scientists and clinicians can optimize their investigations into Central Nervous System Neoplasms, leading to improved understanding, diagnosis, and treatment of these complex conditions.
PubCompare.ai's AI-driven platform can help streamline this process by providing access to the latest protocols, pre-prints, and patents, while offering intelligent comparison tools to identify the most promising approaches.
These cancerous growths can vary in their aggressiveness and may impact various neurological functions.
Prompt and accurate diagnosis, as well as targeted treatment approaches, are crucial for managing these complex conditions.
The Infinium MethylationEPIC BeadChip array and Infinium Methylation EPIC are powerful tools that can help researchers and clinicians better understand the epigenetic changes associated with CNS neoplasms.
The ABE419 and EZ DNA Methylation Kit can also be utilized to study DNA methylation patterns in these tumors.
FBS, or fetal bovine serum, is a commonly used supplement in cell culture media and may be relevant for in vitro studies of CNS neoplasms.
The HumanMethylation450 BeadChip array is another platform that can provide insights into the methylation profiles of these cancers.
The BenchMark XT and BenchMark ULTRA Immunostainers are automated systems that can be used for immunohistochemical analysis of tissue samples, potentially aiding in the diagnosis and characterization of CNS neoplasms.
Phosphohistone-H3 is a marker that can be used to assess cell proliferation, which may be relevant for understanding the biology of these tumors.
The iScan system is a high-throughput scanning platform that can be used for various genomic and epigenomic analyses, including those related to CNS neoplasms.
By leveraging the latest technologies and research insights, scientists and clinicians can optimize their investigations into Central Nervous System Neoplasms, leading to improved understanding, diagnosis, and treatment of these complex conditions.
PubCompare.ai's AI-driven platform can help streamline this process by providing access to the latest protocols, pre-prints, and patents, while offering intelligent comparison tools to identify the most promising approaches.