While LLMs have shown remarkable advancements in general-purpose applications, their development for specialized fields like medicine remains limited. The complexity of medical knowledge and the scarcity of high-quality, domain-specific data make creating highly efficient medical LLMs challenging. Although models like GPT-4 and DeepseekR1 have demonstrated impressive capabilities across industries, their adaptation to the medical domain… →
Evaluation of the proarrhythmic potential of imetelstat, a novel oligonucleotide telomerase inhibitor, in nonclinical and clinical studies is presented. In vitro, imetelstat sodium ≤ 750 μg/mL and negative (vehicle) and positive (cisapride) controls were evaluated for hERG channel current inhibition. In vivo, cynomolgus monkeys received a single vehicle control or imetelstat sodium (5 mg/kg [2-h… →
CONCLUSIONS: Letrozole treatment produced an effective growth response, particularly in DCIS initially classified as luminal A. Study inclusion criteria of DCIS with at least 1% ER positive cells resulted in the inclusion of other subtypes that failed to respond. Treatment also induced both minor and major changes in intrinsic subtype based on PAM50 probabilities. Overall,… →
CONCLUSIONS: This confirms the effectiveness of proposed method and opens up further prospects for the updated function of the IAN following the BSSO. →
CONCLUSION: Preliminary evidence indicates that a two-session, patient-centred, peer-cofacilitated psychoeducational programme is feasible and well-received, with high ratings for satisfaction from outpatients and caregivers. CLINICLATRIALS. →
BACKGROUND: The discovery of cellular tumor networks in glioblastoma, with routes of malignant communication extending far beyond the detectable tumor margins, has highlighted the potential of supramarginal resection strategies. Retrospective data suggest that these approaches may improve long-term disease control. However, their application is limited by the proximity of critical brain regions and vasculature, posing… →
Mathematical Large Language Models (LLMs) have demonstrated strong problem-solving capabilities, but their reasoning ability is often constrained by pattern recognition rather than true conceptual understanding. Current models are heavily based on exposure to similar proofs as part of their training, confining their extrapolation to new mathematical problems. This constraint restricts LLMs from engaging in advanced… →