Disparities in medical recommendations from AI-based chatbots across different countries/regions.

This study explores disparities and opportunities in healthcare information provided by AI chatbots. We focused on recommendations for adjuvant therapy in endometrial cancer, analyzing responses across four regions (Indonesia, Nigeria, Taiwan, USA) and three platforms (Bard, Bing, ChatGPT-3.5). Utilizing previously published cases, we asked identical questions to chatbots from each location within a 24-h window. Responses were evaluated in a double-blinded manner on relevance, clarity, depth, focus, and coherence by ten experts in endometrial cancer. Our analysis revealed significant variations across different countries/regions (p < 0.001). Interestingly, Bing's responses in Nigeria consistently outperformed others (p < 0.05), excelling in all evaluation criteria (p < 0.001). Bard also performed better in Nigeria compared to other regions (p < 0.05), consistently surpassing them across all categories (p < 0.001, with relevance reaching p < 0.01). Notably, Bard's overall scores were significantly higher than those of ChatGPT-3.5 and Bing in all locations (p < 0.001). These findings highlight disparities and opportunities in the quality of AI-powered healthcare information based on user location and platform. This emphasizes the necessity for more research and development to guarantee equal access to trustworthy medical information through AI technologies.

Targeting HSF1 for cancer treatment: mechanisms and inhibitor development.

Heat Shock Factor 1 (HSF1) is a master regulator of heat shock responsive signaling. In addition to playing critical roles in cellular heat shock response, emerging evidence suggests that HSF1 also regulates a non-heat shock responsive transcriptional network to handle metabolic, chemical, and genetic stress. The function of HSF1 in cellular transformation and cancer development has been extensively studied in recent years. Due to important roles for HSF1 for coping with various stressful cellular states, research on HSF1 has been very active. New functions and molecular mechanisms underlying these functions have been continuously discovered, providing new targets for novel cancer treatment strategies. In this article, we review the essential roles and mechanisms of HSF1 action in cancer cells, focusing more on recently discovered functions and their underlying mechanisms to reflect the new advances in cancer biology. In addition, we emphasize new advances with regard to HSF1 inhibitors for cancer drug development.

Accuracy of screening methods of COVID-19 in pregnancy: a cohort study.

BACKGROUND: All pregnant women in labor should be universally screened for Coronavirus Disease 2019 (COVID-19) during pandemic periods using reverse transcriptase polymerase chain reaction (RT-PCR) test. In many low-middle income countries, screening method was developed as an initial examination because of limited availability of RT-PCR tests. This study aims to evaluate the screening methods of COVID-19 accuracy in pregnant women. METHODS: We recruited all pregnant women with suspicion of COVID-19 from April to August 2020 at Airlangga University Hospital, Surabaya, Indonesia. The participant was divided into two groups based on RT-PCR results: COVID-19 and non-COVID-19 group. The proportion of positive signs and symptoms, rapid antibody test, abnormal findings in chest X-ray, and neutrophil to lymphocyte ratio (NLR) value were then compared between both groups. The sensitivity, specificity, positive predictive value (PPV), negative predictive values (NPV), and diagnostic accuracy (DOR) were calculated. RESULTS: A total 141 pregnant women with suspected COVID-19 cases were recruited for this study. This consist of 62 COVID-19 cases (43.9%) and 79 non-COVID-19 pregnant women (56.1%). The sensitivity, specificity, PPV, NPV, and diagnostic accuracy of each parameter are as follow: clinical sign and symptoms (24.19%, 75.95%, 3.92%, 96.11%, 65.87%), rapid antibody test (72.73%, 35.06%, 4.35%, 96.94%, 36.53%), chest X-ray (40.68%, 59.45%, 3.92%, 96.11%, 58.76%), and NLR >5.8 (41.38%, 72%, 5.66%, 96.80%, 70.81%). CONCLUSIONS: The use of combined screening methods can classify pregnant women with high-risk COVID-19 before definitively diagnosed with RT-PCR. This practice will help to reduce RT-PCR need in a limited resources country.