Objective To explore the influnce on the endothelin-1 (ET-1) and clinical application value of continuous blood purification (CBP) on the treatment of severe craniocerebral injury with the neurogenic pulmonary edema (NPE).Methods All data about sixty patients with NPE were prospectively studied.These 60 patients were randomly (random number) divided into control group (n =30) and treatment group (n =30).In control group,patients were rapidly given with lowering intracranial pressure,mechanical ventilation,calming,antibiotic therapy and so on.In the treatment group,patients received CBP integrated with routine treatment.On admission and 72 h posttreatment,ET-1,static lung compliance and oxygenation index were observed.Time of mechanical ventilation support,incidence rates of multipal organ dysfunction syndrome (MODS) were compared between two groups.The paired t-test was used for the amount data within the group.Chi-square was used for the constitute ratio and incidence ratio of the each relevant information.P ＜ 0.05 was considered statistically significant.Results Compared to the control group,the level of ET-1 was decreased significantly in the treatment group [(48 ± 10) ng/L vs.(85 ± 14) ng/L] after 72 h post-treatment,while static lung compliance [(60.9 ± 2.3) mL/cmH2O vs.(31.4 ±4.8) mL/cmH2O] and oxygenation index [(317 ± 11) mmHg vs.(192 ± 14) mmHg] increased significantly (P ＜ 0.05).In treatment group and control group,the time of respirator intervention were [(6.0 ± 2.1) d vs.(11 ± 3.2) d],and the statistical significance was shown (P ＜ 0.05).Compared to the control group [56.7％ (17/30)],incidence rate of MODS [20.0％ (6/30)] was lower in treatment group (P ＜ 0.05).Conclusions CBP combined with routine treatment,which can remove ET-1 effectively,improve oxygenation,reduce the time of mechanical ventilation support and incidence rate of MODS.

Exosomes are nanoscale extracellular vesicle structures that communicate and exchange information between cells. They carry a variety of biologically active molecules whose compositions and contents vary according to the origin and recipient cells. Therefore, exosomes can be used as biomarkers. Neurodegenerative diseases are diseases with hidden onset, so early screening and accurate diagnosis is undoubtedly a reliable guarantee to reduce their mortality and increase the cure rate. Exosomes, as a research hotspot in recent years, have great potential for the diagnosis and treatment of diseases given their transport capacity and contents, and have significant advantages in abundance, stability, diversity and accessibility. The purpose of this paper is to discuss exosomes as potential candidates for early diagnosis of neurodegenerative diseases, and thus to elaborate new fields of their application, with a view to providing a richer perspective for clinical prediction and treatment.

Purpose/Significance To explore the changes,challenges,key application scenarios and future development directions of generative artificial intelligence(AI)represented by ChatGPT in the field of hospital management,and to provide references for the ap-plication of AI natural language processing(NLP)technology in the field of hospital management in China.Method/Process Through literature review and analysis,the changes and challenges brought about by the rapid development of generative AI in the field of hospital management are sorted out,its key application scenarios and future development directions in the field of hospital management are empha-sized and explored.Result/Conclusion AI has broad application prospects in the field of hospital management,and it should focus on exploring its practical application scenarios and strategic directions to provide reference and guidance for promoting the high-quality de-velopment of public hospitals.

The application of artificial intelligence(AI)in the medical field, particularly for predicting, diagnosing and treating retinal detachment(RD), has made remarkable achievements. This paper reviews the advancements in AI applications for RD across multiple dimensions, including predicting RD incidence, assessing surgical success rates, forecasting postoperative visual outcomes, and evaluating recurrence rates. In diagnostic support, AI technology has demonstrated significant value, especially in ophthalmic imaging, with applications in the intelligent analysis of ultra-wide-angle fundus photography, optical coherence tomography(OCT), ophthalmologic ultrasound images, and AI chatbots models. Furthermore, AI has proven uniquely beneficial in surgical decision-making, robotic-assisted surgical systems, and the assessment of surgical complications. This paper provides a comprehensive overview of the current state of AI applications in RD, underscoring its potential to address numerous challenges in clinical practice. It also explores existing limitations and offers insights into future directions for development in this field.

The application of artificial intelligence(AI)in the medical field, particularly for predicting, diagnosing and treating retinal detachment(RD), has made remarkable achievements. This paper reviews the advancements in AI applications for RD across multiple dimensions, including predicting RD incidence, assessing surgical success rates, forecasting postoperative visual outcomes, and evaluating recurrence rates. In diagnostic support, AI technology has demonstrated significant value, especially in ophthalmic imaging, with applications in the intelligent analysis of ultra-wide-angle fundus photography, optical coherence tomography(OCT), ophthalmologic ultrasound images, and AI chatbots models. Furthermore, AI has proven uniquely beneficial in surgical decision-making, robotic-assisted surgical systems, and the assessment of surgical complications. This paper provides a comprehensive overview of the current state of AI applications in RD, underscoring its potential to address numerous challenges in clinical practice. It also explores existing limitations and offers insights into future directions for development in this field.