Publications by authors named "M R Gottfried"
Article Synopsis
- This study analyzed data from 14,370 students in the Early Childhood Longitudinal Study-Kindergarten Class of 2011 to explore how student-teacher relationships impact various student outcomes from kindergarten to third grade.
- The findings revealed that both conflict and closeness in student-teacher relationships significantly influenced student outcomes over time, except for absenteeism, which was less consistently affected by conflict.
- The study noted that girls tended to have poorer social outcomes compared to boys due to experiencing more conflictual and less close relationships with their teachers.
We report on an articulated fossil boxfish (Tetraodontiformes, Ostraciidae) recently recovered from the Pliocene of the North Island of New Zealand. The specimen was collected from the Tangahoe Formation, a mid-Pliocene (c. 3.
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- Amivantamab-lazertinib demonstrated better progression-free survival (PFS) rates than osimertinib in patients with EGFR-mutant advanced non-small-cell lung cancer (NSCLC), particularly benefiting those with TP53 mutations and detectable circulating tumor DNA (ctDNA).
- A study involving 858 treatment-naive patients showed that amivantamab-lazertinib outperformed osimertinib in various high-risk subgroups, including individuals with baseline liver metastases and those who did not clear ctDNA during treatment.
- Results indicated significant improvements in median PFS for patients treated with amivantamab-lazertinib across multiple categories, showcasing its potential as a more effective option for managing advanced
Purpose: Current guidelines for the management of metastatic non-small cell lung cancer (NSCLC) without driver mutations recommend checkpoint immunotherapy with PD-1/PD-L1 inhibitors, either alone or in combination with chemotherapy. This approach fails to account for individual patient variability and host immune factors and often results in less-than-ideal outcomes. To address the limitations of the current guidelines, we developed and subsequently blindly validated a machine learning algorithm using pretreatment plasma proteomic profiles for personalized treatment decisions.
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