RESUMO
Introduction: Artificial intelligence (AI) is revolutionizing medical workflows, with self-learning systems like ChatGPT showing promise in therapy recommendations. Our study evaluated ChatGPT's performance in suggesting treatments for 30 breast cancer cases. AI's role in healthcare is expanding, particularly with tools like ChatGPT becoming accessible. However, understanding its limitations is vital for safe implementation. Material and Methods: We used 30 breast cancer cases from our medical board, assessing ChatGPT's suggestions. The input was standardized, incorporating relevant patient details and treatment options. ChatGPT's output was evaluated by oncologists based on a given questionnaire. Results: Treatment recommendations by ChatGPT were overall rated sufficient with minor limitations by the oncologists. The HER2 treatment category was the best-rated therapy option, with the most accurate recommendations. Primary cases received more accurate recommendations, especially regarding chemotherapy. Conclusions: While ChatGPT demonstrated potential, difficulties were shown in intricate cases and postoperative scenarios. Challenges arose in offering chronological treatment sequences and partially lacked precision. Refining inputs, addressing ethical intricacies, and ensuring chronological treatment suggestions are essential. Ongoing research is vital to improving AI's accuracy, balancing AI-driven suggestions with expert insights and ensuring safe and reliable AI integration into patient care.
Assuntos
Neoplasias da Mama , Humanos , Feminino , Neoplasias da Mama/tratamento farmacológico , Neoplasias da Mama/terapia , Inteligência Artificial , Ginecologia/métodosRESUMO
Infections with influenza A viruses (IAV) cause seasonal epidemics and global pandemics. The majority of these infections remain asymptomatic, especially among children below five years of age. Importantly, this is a time, when immunological imprinting takes place. Whether early-life infections with IAV affect the development of antimicrobial immunity is unknown. Using a preclinical mouse model, we demonstrate here that silent neonatal influenza infections have a remote beneficial impact on the later control of systemic juvenile-onset and adult-onset infections with an unrelated pathogen, Staphylococcus aureus, due to improved pathogen clearance and clinical resolution. Strategic vaccination with a live attenuated IAV vaccine elicited a similar protection phenotype. Mechanistically, the IAV priming effect primarily targets antimicrobial functions of the developing innate immune system including increased antimicrobial plasma activity and enhanced phagocyte functions and antigen-presenting properties at mucosal sites. Our results suggest a long-term benefit from an exposure to IAV during the neonatal phase, which might be exploited by strategic vaccination against influenza early in life to enforce the host's resistance to later bacterial infections.
Assuntos
Anti-Infecciosos , Vírus da Influenza A , Vacinas contra Influenza , Influenza Humana , Animais , Camundongos , HumanosRESUMO
Primary or secondary immunodeficiencies are characterized by disruption of cellular and humoral immunity. Respiratory infections are a major cause of morbidity and mortality among immunodeficient or immunocompromised patients, with Staphylococcus aureus being a common offending organism. We propose here an adoptive macrophage transfer approach aiming to enhance impaired pulmonary immunity against S aureus. Our studies, using human-induced pluripotent stem cell-derived macrophages (iMφs), demonstrate efficient antimicrobial potential against methicillin-sensitive and methicillin-resistant clinical isolates of S aureus. Using an S aureus airway infection model in immunodeficient mice, we demonstrate that the adoptive transfer of iMφs is able to reduce the bacterial load more than 10-fold within 20 hours. This effect was associated with reduced granulocyte infiltration and less damage in lung tissue of transplanted animals. Whole transcriptome analysis of iMφs compared with monocyte-derived macrophages indicates a more profound upregulation of inflammatory genes early after infection and faster normalization 24 hours postinfection. Our data demonstrate high therapeutic efficacy of iMφ-based immunotherapy against S aureus infections and offer an alternative treatment strategy for immunodeficient or immunocompromised patients.