LC HCAL Absorber And Active Media Comparisons Using a Particle-Flow Algorithm

We compared Stainless Steel (SS) to Tungsten (W) as absorber for the HCAL in simulation using single particles (pions) and a Particle-Flow Algorithm applied to e{sup +}e{sup -} -> Z -> qqbar events. We then used the PFA to evaluate the performance characteristics of a LC HCAL using W absorber and comparing scintillator and RPC as active media. The W/Scintillator HCAL performs better than the SS/Scintillator version due to finer {lambda}{sub I} sampling and narrower showers in the dense absorber. The W/Scintillator HCAL performs better than the W/RPC HCAL except in the number of unused hits in the PFA. Since this represents the confusion term in the PFA response, additional tuning and optimization of a W/RPC HCAL might significantly improve this HCAL configuration

Histopathologic findings in malignant peripheral nerve sheath tumor predict response to radiotherapy and overall survival

BACKGROUND: Malignant peripheral nerve sheath tumor (MPNST) is an aggressive and poorly understood malignant neoplasm. Even in the setting of multimodal therapy, the clinical course of MPNST is frequently marked by metastatic conversion and poor overall prognosis, with optimal treatment paradigms for this rare tumor unknown. METHODS: We reviewed the medical records and histopathology of 54 consecutive patients who were treated at University of California San Francisco between 1990 and 2018. RESULTS: Our cohort consisted of 24 male and 30 female patients (median age 38 years). Fédération Nationale des Centres de Lutte Contre Le Cancer (FNCLCC) sarcoma grading criteria segregated patients into groups with differences in overall survival (OS) ( CONCLUSIONS: Our results lend support to the FNCLCC sarcoma grading criteria as a prognostic scheme for MPNST, although few cases of grade 1 were included. Further, we identify increased Ki-67 labeling as a strong predictor of poor OS from MPNST. Finally, we identify a subset of MPNSTs with a predictive immunohistochemical profile that has improved local control with adjuvant radiotherapy. These data provide insights into the grading and therapy for patients with MPNST, although further studies are needed for independent validation

The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe

The preponderance of matter over antimatter in the early Universe, the dynamics of the supernova bursts that produced the heavy elements necessary for life and whether protons eventually decay --- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our Universe, its current state and its eventual fate. The Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed plan for a world-class experiment dedicated to addressing these questions. LBNE is conceived around three central components: (1) a new, high-intensity neutrino source generated from a megawatt-class proton accelerator at Fermi National Accelerator Laboratory, (2) a near neutrino detector just downstream of the source, and (3) a massive liquid argon time-projection chamber deployed as a far detector deep underground at the Sanford Underground Research Facility. This facility, located at the site of the former Homestake Mine in Lead, South Dakota, is approximately 1,300 km from the neutrino source at Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino charge-parity symmetry violation and mass ordering effects. This ambitious yet cost-effective design incorporates scalability and flexibility and can accommodate a variety of upgrades and contributions. With its exceptional combination of experimental configuration, technical capabilities, and potential for transformative discoveries, LBNE promises to be a vital facility for the field of particle physics worldwide, providing physicists from around the globe with opportunities to collaborate in a twenty to thirty year program of exciting science. In this document we provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess.Comment: Major update of previous version. This is the reference document for LBNE science program and current status. Chapters 1, 3, and 9 provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess. 288 pages, 116 figure

Targeted Gene Expression Profiling Predicts Meningioma Outcomes and Radiotherapy Responses

Surgery is the mainstay of treatment for meningioma, the most common primary intracranial tumor, but improvements in meningioma risk stratification are needed and indications for postoperative radiotherapy are controversial. Here we develop a targeted gene expression biomarker that predicts meningioma outcomes and radiotherapy responses. Using a discovery cohort of 173 meningiomas, we developed a 34-gene expression risk score and performed clinical and analytical validation of this biomarker on independent meningiomas from 12 institutions across 3 continents (N = 1,856), including 103 meningiomas from a prospective clinical trial. The gene expression biomarker improved discrimination of outcomes compared with all other systems tested (N = 9) in the clinical validation cohort for local recurrence (5-year area under the curve (AUC) 0.81) and overall survival (5-year AUC 0.80). The increase in AUC compared with the standard of care, World Health Organization 2021 grade, was 0.11 for local recurrence (95% confidence interval 0.07 to 0.17, P \u3c 0.001). The gene expression biomarker identified meningiomas benefiting from postoperative radiotherapy (hazard ratio 0.54, 95% confidence interval 0.37 to 0.78, P = 0.0001) and suggested postoperative management could be refined for 29.8% of patients. In sum, our results identify a targeted gene expression biomarker that improves discrimination of meningioma outcomes, including prediction of postoperative radiotherapy responses