Delirium is a common cause and complication of hospitalization in the elderly and is associated with higher risk of future dementia and progression of existing dementia, of which 70% is Alzheimer's disease (AD). AD and delirium, which are known to be aggravated by one another, represent significant societal challenges, especially in light of the absence of effective treatments. The intricate biological mechanisms have led to numerous clinical trial setbacks and likely contribute to the limited efficacy of existing therapeutics. Artificial intelligence (AI) presents a promising avenue for overcoming these hurdles by deploying algorithms to uncover hidden patterns across diverse data types. This review explores the pivotal role of AI in revolutionizing drug discovery for AD and delirium from target identification to the development of small molecule and protein-based therapies. Recent advances in deep learning, particularly in accurate protein structure prediction, are facilitating novel approaches to drug design and expediting the discovery pipeline for biological and small molecule therapeutics. This review concludes with an appraisal of current achievements and limitations, and touches on prospects for the use of AI in advancing drug discovery in AD and delirium, emphasizing its transformative potential in addressing these two and possibly other neurodegenerative conditions.

Non-small cell lung cancer (NSCLC) accounts for the majority of lung cancer cases and remains the leading cause of cancer-related mortality worldwide. Firstly, this review explores the limitations of conventional therapies, chemotherapy, radiotherapy, and surgery, focusing on the development of drug resistance and significant toxicity that often hinder their efficacy. Thereafter, advancements in targeted therapies, such as immune checkpoint inhibitors (ICIs) and tyrosine kinase inhibitors (TKIs), are discussed, highlighting their impact on improving outcomes for patients with specific genetic mutations, including c-ros oncogene 1 receptor tyrosine kinase (ROS1), anaplastic lymphoma kinase (ALK), and epidermal growth factor receptor (EGFR). Additionally, the emergence of novel immunotherapies and phytochemicals is examined, emphasizing their potential to overcome therapeutic resistance, particularly in advanced-stage diseases. The review also delves into the role of next-generation sequencing (NGS) in enabling personalized treatment approaches and explores the clinical potential of innovative agents, such as bispecific T-cell engagers (BiTEs) and antibody-drug conjugates (ADCs). Finally, we address the socioeconomic barriers that limit the accessibility of these therapies in low-resource settings and propose future research directions aimed at improving the long-term efficacy and accessibility of these treatments.

OBJECTIVE To evaluate the use of antibiotics after coronary artery bypass.METHODS Forty patients were assigned into two groups,vancomycin group and cefradine group.Each included 20 patients.We compared the infection cases,cost of hospitalization,and cost of medicine after CABG.RESULTS There were no difference of(infection) between two groups,the cost of hospitalization was fewer in cefradine group.(CONCLUSIONS) The short-term use of cefradine after CABG could achieve the goals of preventing infection of CABG,and save medical resources.

Objective: To investigate the safety of transgenic human lung adenocarcinoma cell line SPC-A-1/IL-2 as tumor vaccine. Methods: IL-2 gene was introduced into human lung adenocarcinoma cell line SPC-A-1 and was expressed stably on the basis of the construction of retroviral packing cell line PA317/pLIL-2SN.The mutagenesis of both the DNA and supernatant of SPC-A-1/IL-2 in the and in vitro was tested by means of genetic toxicological techniques.Results:The result indicated that mutagenesis of both the DNA and the supernatant of transgenic cell SPC-A-1/IL-2 was not observed. Conclusion: The initial experiment suggested that the application of transgenic cell SPC-A-l/IL-2 as tumor vaccine was bisically safe and reliable.