Embracing ChatGPT for Medical Education: Exploring Its Impact on Doctors and Medical Students.

ChatGPT (OpenAI), a cutting-edge natural language processing model, holds immense promise for revolutionizing medical education. With its remarkable performance in language-related tasks, ChatGPT offers personalized and efficient learning experiences for medical students and doctors. Through training, it enhances clinical reasoning and decision-making skills, leading to improved case analysis and diagnosis. The model facilitates simulated dialogues, intelligent tutoring, and automated question-answering, enabling the practical application of medical knowledge. However, integrating ChatGPT into medical education raises ethical and legal concerns. Safeguarding patient data and adhering to data protection regulations are critical. Transparent communication with students, physicians, and patients is essential to ensure their understanding of the technology's purpose and implications, as well as the potential risks and benefits. Maintaining a balance between personalized learning and face-to-face interactions is crucial to avoid hindering critical thinking and communication skills. Despite challenges, ChatGPT offers transformative opportunities. Integrating it with problem-based learning, team-based learning, and case-based learning methodologies can further enhance medical education. With proper regulation and supervision, ChatGPT can contribute to a well-rounded learning environment, nurturing skilled and knowledgeable medical professionals ready to tackle health care challenges. By emphasizing ethical considerations and human-centric approaches, ChatGPT's potential can be fully harnessed in medical education, benefiting both students and patients alike.

Rare and complex diseases in focus: ChatGPT's role in improving diagnosis and treatment.

Rare and complex diseases pose significant challenges to both patients and healthcare providers. These conditions often present with atypical symptoms, making diagnosis and treatment a formidable task. In recent years, artificial intelligence and natural language processing technologies have shown great promise in assisting medical professionals in diagnosing and managing such conditions. This paper explores the role of ChatGPT, an advanced artificial intelligence model, in improving the diagnosis and treatment of rare and complex diseases. By analyzing its potential applications, limitations, and ethical considerations, we demonstrate how ChatGPT can contribute to better patient outcomes and enhance the healthcare system's overall effectiveness.

Targeting proprotein convertase subtilisin/kexin type 9 (PCSK9): from bench to bedside.

Proprotein convertase subtilisin/kexin type 9 (PCSK9) has evolved as a pivotal enzyme in lipid metabolism and a revolutionary therapeutic target for hypercholesterolemia and its related cardiovascular diseases (CVD). This comprehensive review delineates the intricate roles and wide-ranging implications of PCSK9, extending beyond CVD to emphasize its significance in diverse physiological and pathological states, including liver diseases, infectious diseases, autoimmune disorders, and notably, cancer. Our exploration offers insights into the interaction between PCSK9 and low-density lipoprotein receptors (LDLRs), elucidating its substantial impact on cholesterol homeostasis and cardiovascular health. It also details the evolution of PCSK9-targeted therapies, translating foundational bench discoveries into bedside applications for optimized patient care. The advent and clinical approval of innovative PCSK9 inhibitory therapies (PCSK9-iTs), including three monoclonal antibodies (Evolocumab, Alirocumab, and Tafolecimab) and one small interfering RNA (siRNA, Inclisiran), have marked a significant breakthrough in cardiovascular medicine. These therapies have demonstrated unparalleled efficacy in mitigating hypercholesterolemia, reducing cardiovascular risks, and have showcased profound value in clinical applications, offering novel therapeutic avenues and a promising future in personalized medicine for cardiovascular disorders. Furthermore, emerging research, inclusive of our findings, unveils PCSK9's potential role as a pivotal indicator for cancer prognosis and its prospective application as a transformative target for cancer treatment. This review also highlights PCSK9's aberrant expression in various cancer forms, its association with cancer prognosis, and its crucial roles in carcinogenesis and cancer immunity. In conclusion, this synthesized review integrates existing knowledge and novel insights on PCSK9, providing a holistic perspective on its transformative impact in reshaping therapeutic paradigms across various disorders. It emphasizes the clinical value and effect of PCSK9-iT, underscoring its potential in advancing the landscape of biomedical research and its capabilities in heralding new eras in personalized medicine.

Innovating Healthcare: The Role of ChatGPT in Streamlining Hospital Workflow in the Future.

ChatGPT is revolutionizing hospital workflows by enhancing the precision and efficiency of tasks that were formerly the exclusive domain of healthcare professionals. Additionally, ChatGPT can aid in administrative duties, including appointment scheduling and billing, which enables healthcare professionals to allocate more time towards patient care. By shouldering some of these responsibilities, ChatGPT has the potential to advance the quality of patient care, streamline departmental efficiency, and lower healthcare costs. Nevertheless, it is crucial to strike a balance between the advantages of ChatGPT and the necessity of human interaction in healthcare to guarantee optimal patient care. While ChatGPT may assume some of the duties of physicians in particular medical domains, it cannot replace human doctors. Tackling the challenges and constraints associated with the integration of ChatGPT into the healthcare system is critical for its successful implementation.

Enhancing Diabetes Self-management and Education: A Critical Analysis of ChatGPT's Role.

ChatGPT, an advanced natural language processing model, holds significant promise in diabetes self-management and education. ChatGPT excels in providing personalized educational experiences by tailoring information to meet individual patient needs and preferences. It aids patients in developing self-management skills and strategies, fostering proactive disease management. Additionally, ChatGPT addresses healthcare access disparities by enabling patients to access educational resources irrespective of their geographic location or physical limitations. However, it is important to acknowledge and address the deficiencies of ChatGPT, such as its limited medical expertise, contextual understanding, and emotional support capabilities. Strategies for optimizing ChatGPT include regular training and updating, integration of healthcare professionals' expertise, improvement in contextual comprehension, and enhancing emotional support. By addressing these limitations and striking a balance between the benefits and limitations, ChatGPT can play a significant role in empowering patients to better understand and manage diabetes. Further research and development are needed to refine ChatGPT's capabilities and address ethical considerations, but its integration in patient education holds the potential to transform healthcare delivery and create a more informed and engaged patient population.

Chemoimmunotherapy combined with consolidative thoracic radiotherapy for extensive-stage small cell lung cancer: A systematic review and meta-analysis.

INTRODUCTION: This study aimed to evaluate the efficacy and safety of chemoimmunotherapy combined with consolidative thoracic radiation therapy (cTRT) in patients with extensive-stage small cell lung cancer (ES-SCLC). METHODS: A meta-analysis was conducted. PubMed, Embase, Web of Science, and the Cochrane Library were searched. The study was registered in PROSPERO (registration no. CRD42023410344). RESULTS: A total of 4677 studies were initially screened and 15 studies encompassing a total of 1033 patients were included. Chemoimmunotherapy combined with cTRT significantly improved survival (HR = 0.52, 95 % CI: 0.39, 0.68) with favorable 6-month (0.89, 95 % CI: 0.77, 1.00) and 1-year (0.77, 95 % CI: 0.72, 0.82) OS, without affecting ≥3 grade TRAEs (RR = 1.29, 95 % CI: 0.85, 1.98). Pooled 6-month and 1-year PFS were 0.67 (95 % CI: 0.47, 0.86) and 0.38 (95 % CI: 0.22, 0.55), respectively. Incidence of ≥3 grade TRAEs was 0.24 (95 % CI: 0.08, 0.39) and radiation pneumonitis was 0.03 (95 % CI: 0.01, 0.06). CONCLUSIONS: Chemoimmunotherapy combined with cTRT improves survival and shows favorable outcomes in ES-SCLC patients, with manageable adverse events. Further research with larger samples is needed to confirm these findings.

Efficacy, safety, and survival of neoadjuvant immunochemotherapy in operable non-small cell lung cancer: a systematic review and meta-analysis.

Background: Neoadjuvant immunochemotherapy may benefit patients with non-small cell lung cancer (NSCLC), but its impact requires further investigation. Methods: A meta-analysis was conducted. PubMed, Embase, Web of Science, and the Cochrane Library were searched. The study was registered in PROSPERO (registration no. CRD42022360893). Results: 60 studies of 3,632 patients were included. Comparing with neoadjuvant chemotherapy, neoadjuvant immunochemotherapy showed higher pCR (RR: 4.71, 95% CI: 3.69, 6.02), MPR (RR, 3.20, 95% CI: 2.75, 3.74), and ORR (RR, 1.46, 95% CI: 1.21, 1.77), fewer surgical complications (RR: 0.67, 95%CI: 0.48, 0.94), higher R0 resection rate (RR: 1.06, 95%CI: 1.03, 1.10, I2 = 52%), and longer 1-year and 2-year OS, without affecting TRAEs. For neoadjuvant immunochemotherapy in NSCLC, the pooled pCR rate was 0.35 (95% CI: 0.31, 0.39), MPR was 0.59 (95% CI: 0.54, 0.63), and ORR was 0.71 (95% CI: 0.66, 0.76). The pooled incidence of all grade TRAEs was 0.70 (95% CI: 0.60, 0.81), and that of >= grade 3 TRAEs was 0.24 (95% CI: 0.16, 0.32). The surgical complications rate was 0.13 (95% CI: 0.07, 0.18) and R0 resection rate was 0.98 (95% CI: 0.96, 0.99). The pooled 1-year OS was 0.97 (95%CI: 0.96, 0.99), and 2-year OS was 0.89 (95%CI: 0.83, 0.94). Patients with squamous cell carcinoma, stage III or higher PD-L1 performed better. Notably, no significant differences were observed in pCR, MPR, and ORR between 2 or more treatment cycles. Pembrolizumab-, or toripalimab-based neoadjuvant immunochemotherapy demonstrated superior efficacy and tolerable toxicity. Conclusion: According to our analysis, reliable efficacy, safety, and survival of neoadjuvant immunochemotherapy for operable NSCLC were demonstrated. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022360893, identifier CRD42022360893.

Cranial radiation therapy with hippocampus avoidance in lung cancer treatment: systematic review and meta-analysis.

Background: The role of cranial radiation therapy with hippocampus avoidance (HA-CRT) in neurocognitive function (NCF), brain metastasis (BM), and overall survival (OS) in lung cancer remains unclear. Methods: A meta-analysis was conducted to evaluate the impact of HA-CRT in lung cancer. Data from studies on hippocampal-avoidance prophylactic cranial irradiation (HA-PCI) and whole brain radiotherapy (HA-WBRT) were pooled. Results: A total of 14 studies, including 5 randomized controlled trials, were included. The focus of NCF was mainly via the Hopkins Verbal Learning Test-Revised or the Free and Cued Selective Reminding Test. At 6 months post-radiotherapy, the pooled proportion of participants with decline in the performance of total recall, delayed recall, and discrimination in neurocognitive tests were 0.22 (95% CI 0.15, 0.29), 0.20 (95% CI 0.13, 0.27), and 0.14 (95% CI 0.05, 0.24) respectively. After 12 months, the proportion were 0.16 (95% CI 0.08, 0.23), 0.10 (95% CI 0.04, 0.16), and 0.04 (95% CI 0, 0.09) respectively. For HA zone relapse, the RR of HA-CRT versus CRT was 2.72 (95% CI 0.53, 13.87), and for 2-year BM, it was 1.20 (95% CI 0.82, 1.75). Regarding HA-PCI in SCLC, the 1-year BM rate was 0.12 (95% CI 0.07, 0.17), and the 2-year BM rate was 0.20 (95% CI 0.16, 0.25). For HA-WBRT in NSCLC with BM, the 2-year intracranial progression rate was 0.38 (95% CI 0.13, 0.62). There was no significant difference in OS between HA-CRT and CRT. Conclusions: HA-CRT appears to be safe in lung cancer, but it may not outperform conventional CRT. Larger RCTs comparing HA-CRT and CRT are warranted. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022360890, identifier CRD42022360890.

A unique regulated cell death-related classification regarding prognosis and immune landscapes in non-small cell lung cancer.

Regulated cell death (RCD) contributes to reshaping the tumor immune microenvironment and participating in the progression of non-small cell lung cancer (NSCLC); however, related mechanisms have not been fully disclosed. Here, we identified 5 subclusters of NSCLC based on consensus clustering of 3429 RCD-associated genes in the TCGA database and depicted the genomic features and immune landscape of these clusters. Importantly, the clusters provided insights into recognizing tumor microenvironment (TME) and tumor responses to immunotherapy and chemotherapy. Further, we established and validated an RCD-Risk model based on RCD-associated genes, which strongly predicted the prognosis, TME, and immunotherapy outcomes in NSCLC patients. Notably, tissue microarray staining confirmed that the expression of LDLRAD3, a core gene in RCD-Risk model, correlated with poor survival. In conclusion, we developed a novel RCD classification system and RCD-Risk model of NSCLC, serving as a robust and promising predictor for prognosis and immunotherapy benefit of individual NSCLC patients.

MUC3A promotes the progression of colorectal cancer through the PI3K/Akt/mTOR pathway.

Mucin 3A (MUC3A) is overexpressed in colorectal cancer (CRC) and associated with poor prognosis, but the related mechanism remains unclear. Our study found that MUC3A promotes the progression of CRC by activating the PI3K/Akt/mTOR signaling pathway. Knockout of MUC3A significantly inhibited the proliferation of CRC cells and induced G1 phase arrest by upregulating p21 protein, an important cell cycle regulator. Moreover, knockout of MUC3A significantly inhibited invasion ability and enhanced the sensitivity to the chemotherapeutic agent 5-FU. Furthermore, we found that knockout of MUC3A repressed the PI3K/Akt/mTOR pathway through RNA-seq. Treatment with the PI3K/Akt/mTOR pathway inhibitor rapamycin successfully eliminated the difference in proliferation, invasion and chemoresistance between MUC3A knockout cells and control cells. Our study suggests that MUC3A is a potential oncogene that promotes the proliferation, invasion, and chemotherapy resistance of CRC. Moreover, CRC patients with high expression of MUC3A may benefit from rapamycin treatment.