Bibliographic record
Abstract
Current Opinion in Neurology was launched in 1988. It is one of a successful series of review journals whose unique format is designed to provide a systematic and critical assessment of the literature as presented in the many primary journals. The field of neurology is divided into 14 sections that are reviewed once a year. Each section is assigned a Section Editor, a leading authority in the area, who identifies the most important topics at that time. Here we are pleased to introduce the Journal's Section Editors for this issue. SECTION EDITORS S. Thomas CarmichaelS. Thomas CarmichaelS. Thomas Carmichael is a Neurologist and Neuroscientist in the Department of Neurology at the David Geffen School of Medicine at UCLA, USA. Dr Carmichael is Professor and Vice Chair in the Department, with active laboratory and clinical interests in stroke and neurorehabilitation and how the brain repairs from injury. He received his M.D. and Ph.D. degrees from Washington University School of Medicine, USA, in 1993 and 1994, and completed a neurology residency at Washington University School of Medicine, serving as Chief Resident. Dr Carmichael was a Howard Hughes Medical Institute postdoctoral fellow at UCLA from 1998 to 2001. He has been on the UCLA faculty since 2001. Dr Carmichael's laboratory studies the molecular and cellular mechanisms of neural repair after stroke and other forms of brain injury. This research focuses on the processes of axonal sprouting and neural stem cell and progenitor responses after stroke, and on neural stem cell transplantation. Dr Carmichael is an attending physician on the Neurorehabilitation and Stroke clinical services at UCLA. Dr Carmichael has published important papers on stroke recovery that have defined mechanisms of plasticity and repair. These include the fact that the stroke produces stunned circuits that limit recovery, but can be restored to normal functioning with newly applied experimental drugs. His work has identified a novel brain “growth program” that is activated by stroke and leads to the formation of new connections. These studies have also identified how this growth program changes with age, and how specific molecules in the aged brain block the formation of new connections and of recovery. This and other work has led to new directions in stroke therapeutics, including therapies with stem cell and tissue engineering applications. Dr Carmichael is in the midst of stroke stem cell development applications with the FDA and with biotechnology companies. Jean-François DémonetJean-François DémonetJean-François Démonet was trained as an MD and neurologist at Toulouse University, France. He complemented his training in neuropsychology at Montreal University, Canada. As an INSERM research fellow, he performed studies of language imaging using PET in London, UK, in the group of Prof. R. Frackowiak and obtained his PhD. Dr Démonet has co-founded a task force, the GRECO, that succeeded in the adaptation and standardization in French of a number of tests used in clinical neuropsychology. Dr Démonet has headed a master program in neuropsychology throughout France. Aside from classical neuropsychological studies, Dr Demonet's research work involves various brain mapping methods (PET, fMRI, ERPs, MEG, intracranial EEG recording, direct electrical cortical mapping) to explore how the brain correlates language and memory functions; these studies are conducted either in normal subjects or in patients suffering from diverse brain disorders, such as aphasia, agnosia, dyslexia, epilepsy and neurodegenerative disorders. Some of these works took place in recent Europe-wide collaborative networks such as the FP6 ‘Neurodys’ and the ‘Pharmacog’ IMI project. Studies were focused mainly on the sublexical and lexical processes especially in speech comprehension and written language production, showing the segregation of phonology-related versus semantics-related neural systems, in respectively dorsal and ventral neocortical pathways. More recent works highlighted the crucial role of the superior premotor cortex in handwriting as well as the importance of neural oscillations in conscious perception of script. From 1995 to 2011, Dr Démonet has been Directeur de Recherche in a French INSERM laboratory (Inserm UMR 825, Toulouse). He then joined again Prof. R. Frackowiak and his team of the Department of Clinical Neurosciences in Lausanne University Hospital (CHUV), Switzerland, as Professor of Neurology, a position supported by the Leenaards Foundation. He is the head of the Leenaards Memory Centre, an unprecedented multi-disciplinary centre putting together clinical care and translational research approaches to ageing-brain cognitive diseases. Monika E. HegiMonika E. HegiMonika Hegi is Associate Professor for Experimental and Translational Neuro-Oncology at the University of Lausanne, Switzerland. She has earned her doctoral degree in natural sciences at the Federal Institute of Technology in Zurich (ETHZ, 1989), Switzerland, and pursued post-doctoral training in molecular toxicology and molecular carcinogenesis at the National Institute of Environmental Health Sciences (NIEHS), NIH, Research Triangle Park, NC, USA, from 1989 to 1993. Since 1998 she directs the laboratory of Brain Tumor Biology and Genetics of the Service of Neurosurgery in the Department of Clinical Neurosciences at the University Hospital Lausanne. The research focus is to bridge basic and translational cancer research, aiming at identifying new targets and predictive factors for response to therapy and outcome. These efforts are in close collaboration with international cooperative clinical trials groups, in particular the Brain Tumor Group of the European Organisation for Research and Treatment of Cancer (EORTC), where she is coordinator for translational research. Analyzing molecular profiles established from tumors of patient enrolled in clinical trials has identified several molecular factors for treatment resistance, among them a stem cell related gene expression signature. Clinically most relevant, however, was the demonstration of a predictive value of epigenetic silencing of the repair gene MGMT, by promoter methylation, for benefit from the alkylating agent temozolomide in phase II and III trials for newly diagnosed glioblastoma. This has led to a paradigm change in the field, and the MGMT methylation status is now used as biomarker for stratification or patient selection in most clinical trials for glioma and for treatment decisions in particular for elderly glioblastoma patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".