Uncovering precision phenotype-biomarker associations in traumatic brain injury using topological data analysis

Background: Traumatic brain injury (TBI) is a complex disorder that is traditionally stratified based on clinical signs and symptoms. Recent imaging and molecular biomarker innovations provide unprecedented opportunities for improved TBI precision medicine, incorporating patho-anatomical and molecular mechanisms. Complete integration of these diverse data for TBI diagnosis and patient stratification remains an unmet challenge. Methods and findings: The Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) Pilot multicenter study enrolled 586 acute TBI patients and collected diverse common data elements (TBI-CDEs) across the study population, including imaging, genetics, and clinical outcomes. We then applied topology-based data-driven discovery to identify natural subgroups of patients, based on the TBI-CDEs collected. Our hypothesis was two-fold: 1) A machine learning tool known as topological data analysis (TDA) would reveal data-driven patterns in patient outcomes to identify candidate biomarkers of recovery, and 2) TDA-identified biomarkers would significantly predict patient outcome recovery after TBI using more traditional methods of univariate statistical tests. TDA algorithms organized and mapped the data of TBI patients in multidimensional space, identifying a subset of mild TBI patients with a specific multivariate phenotype associated with unfavorable outcome at 3 and 6 months after injury. Further analyses revealed that this patient subset had high rates of post-traumatic stress disorder (PTSD), and enrichment in several distinct genetic polymorphisms associated with cellular responses to stress and DNA damage (PARP1), and in striatal dopamine processing (ANKK1, COMT, DRD2). Conclusions: TDA identified a unique diagnostic subgroup of patients with unfavorable outcome after mild TBI that were significantly predicted by the presence of specific genetic polymorphisms. Machine learning methods such as TDA may provide a robust method for patient stratification and treatment planning targeting identified biomarkers in future clinical trials in TBI patients

Apolipoprotein E epsilon 4 (APOE-ε4) genotype is associated with decreased 6-month verbal memory performance after mild traumatic brain injury

Introduction: The apolipoprotein E (APOE) ε4 allele associates with memory impairment in neurodegenerative diseases. Its association with memory after mild traumatic brain injury (mTBI) is unclear. Methods: mTBI patients (Glasgow Coma Scale score 13–15, no neurosurgical intervention, extracranial Abbreviated Injury Scale score ≤1) aged ≥18 years with APOE genotyping results were extracted from the Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot) study. Cohorts determined by APOE-ε4(+/−) were assessed for associations with 6-month verbal memory, measured by California Verbal Learning Test, Second Edition (CVLT-II) subscales: Immediate Recall Trials 1–5 (IRT), Short-Delay Free Recall (SDFR), Short-Delay Cued Recall (SDCR), Long-Delay F

P-A Measurements in the 48-Ca(p,n)48-Sc Reaction at 135 MeV

This research was sponsored by the National Science Foundation Grant NSF PHY-931478

Search for a State at E_x = 2.6MeV in 20-Na via the 20-Ne(p,n)20-Na Reaction and Possible Breakout from the Hot CNO Cycle

This research was sponsored by the National Science Foundation Grant NSF PHY-931478

Fragmentation of High-spin Stretched States in the (p,n) Reaction on 36-Ar and 40-Ca

This research was sponsored by the National Science Foundation Grant NSF PHY-931478

High-Spin Stretched States in Nuclei Excited via (p,n) Reactions

This research was sponsored by the National Science Foundation Grant NSF PHY 87-1440

Calibration of a Neutron Polarimeter

This research was sponsored by the National Science Foundation Grant NSF PHY-931478

Clinical assessment on days 1–14 for the characterization of traumatic brain injury: recommendations from the 2024 NINDS traumatic brain injury classification and nomenclature initiative clinical/symptoms working group

The current classification of traumatic brain injury (TBI) primarily uses the Glasgow Coma Scale (GCS) to categorize injuries as mild (GCS 13-15), moderate (GCS 9-12), or severe (GCS ≤8). However, this system is unsatisfactory, as it overlooks variations in injury severity, clinical needs, and prognosis. A recent report by the National Academies of Sciences, Engineering, and Medicine (USA) recommended updating the classification system, leading to a workshop in 2024 by the National Institute of Neurological Disorders and Stroke. This resulted in the development of a new clinical, biomarker, imaging, and modifier (CBI-M) framework, with input from six working groups, including the Clinical/Symptoms Working Group (CSWG). The CSWG included both clinical and non-clinical experts and was informed by individuals with lived experience of TBI and public consultation. The CSWG primarily focused on acute clinical assessment of TBI in hospital settings, with discussion and recommendations based on pragmatic expert reviews of literature. Key areas reviewed included: assessment of neurological status; performance-based assessment tools; age and frailty, pre-existing comorbidities, and prior medication; extracranial injuries; neuroworsening; early physiological insults; and physiological monitoring in critical care. This article reports their discussions and recommendations. The CSWG concluded that the GCS remains central to TBI characterization but must include detailed scoring of eye, verbal, and motor components, with identification of confounding factors and clear documentation of non-assessable components. Pupillary reactivity should be documented in all patients, but recorded separately from the GCS, rather than as an integrated GCS-Pupils score. At ceiling scores on the GCS (14/15), history of loss of consciousness (LoC) and the presence and duration of post-traumatic amnesia should be recorded using validated tools, and acute symptoms documented in patients with a GCS verbal score of 4/5 using standardized rating scales. Additional variables to consider for a more complete characterization of TBI include injury mechanism, acute physiological insults and seizures; and biopsychosocial-environmental factors (comorbidities, age, frailty, socioeconomic status, education, and employment). The CSWG recommended that, for a complete characterization of TBI, disease progression/resolution should be monitored over 14 days. While there was a good basis for the recommendations listed above, evidence for the use of other variables is still emerging. These include: detailed documentation of neurological deficits, vestibulo-oculomotor dysfunction, cognition, mental health symptoms, and (for hospitalized patients) data-driven integrated measures of physiological status and therapy intensity. These recommendations are based on expert consensus due to limited high-quality evidence. Further research is needed to validate and refine these guidelines, ensuring they can be effectively integrated into the CBI-M framework and clinical practice

The MeerKAT Galaxy Cluster Legacy Survey: I. Survey overview and highlights

Please abstract in the article.The South African Radio Astronomy Observatory (SARAO), the National Research Foundation (NRF), the National Radio Astronomy Observatory, US National Science Foundation, the South African Research Chairs Initiative of the DSI/NRF, the SARAO HCD programme, the South African Research Chairs Initiative of the Department of Science and Innovation.http://www.aanda.orghj2022Physic