Publications by authors named "A Aroldi"
Background: Anaplastic lymphoma kinase (ALK) plays a role in the development of lymphoma, lung cancer and neuroblastoma. While tyrosine kinase inhibitors (TKIs) have improved treatment outcomes, relapse remains a challenge due to on-target mutations and off-target resistance mechanisms. ALK-positive (ALK+) tumors can evade the immune system, partly through tumor-associated macrophages (TAMs) that facilitate immune escape.
View Article and Find Full Text PDFBackground: Unstable hemoglobins are caused by single amino acid substitutions in the HBB gene, often affecting key histidine residues, leading to protein destabilization and hemolytic crises. In contrast, long HBB variants, exceeding 20 bp, are rare and associated with a β-thalassemia phenotype due to disrupted α-β chain interactions. We describe a family wherein four of six members carry a novel 23-amino-acid in-frame duplication of HBB (c.
View Article and Find Full Text PDFPolycythemia Vera (PV) is typically caused by V617F or exon 12 JAK2 mutations. Little is known about Polycythemia cases where no JAK2 variants can be detected, and no other causes identified. This condition is defined as idiopathic erythrocytosis (IE).
View Article and Find Full Text PDFArticle Synopsis
- SETBP1 mutations are associated with various clonal myeloid disorders, but their role in initiating leukemia is uncertain, as they usually occur later in the progression of the disease.
- Researchers created a mouse model with SETBP1 mutations in blood-forming tissue, which resulted in significant changes in cell differentiation and the development of a serious myeloid neoplasm.
- In a study of triple-negative primary myelofibrosis patients, two groups were identified—those with SETBP1 mutations, who experienced more aggressive disease, and those without mutations, suggesting that SETBP1 mutations may act earlier in some clonal disorders than previously thought.
In a first-of-its-kind study, we assessed the capabilities of large language models (LLMs) in making complex decisions in haematopoietic stem cell transplantation. The evaluation was conducted not only for Generative Pre-trained Transformer 4 (GPT-4) but also conducted on other artificial intelligence models: PaLm 2 and Llama-2. Using detailed haematological histories that include both clinical, molecular and donor data, we conducted a triple-blind survey to compare LLMs to haematology residents.
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