BACKGROUND:Magnetic nanomaterials,as a hot topic in the biomedical field in recent years,are often used to enhance the targeted delivery of drugs to the affected area.OBJECTIVE:To investigate the effects of magnetic nano drug carriers on skeletal muscle injury markers and inflammatory responses in rats with sports injuries.METHODS:Magnetic nanoparticles were prepared.A total of 88 male SD rats were randomly divided into a blank group(n=8),an injury control group(n=32),a Yunnan Baiyao group(n=24),and a magnetic nano-drug carrier group(n=24)by using a random number table method.The latter three groups were modeled with exercise-induced muscle injury(treadmill slope of-16°,running speed of 16 m/min,and training time of 120 min).Immediately after exercise,after verifying the success of the model,Yunnan Baiyao patch was applied to the gastrocnemius muscle of the rats in the Yunnan Baiyao group.Yunnan Baiyao patch loaded with magnetic nanoparticles was applied to the gastrocnemius muscle of the rats in the magnetic nano-drug carrier group.At 24,48,and 120 hours after exercise,blood was drawn from the abdominal aorta of rats to detect the activities of creatine kinase and lactate dehydrogenase,as well as the levels of myoglobin,interleukin-6,and tumor necrosis factor-α.Hematoxylin-eosin staining was used to observe the infiltration of inflammatory cells in the gastrocnemius muscle.RESULTS AND CONCLUSION:(1)Compared with the blank group,the levels of myoglobin,creatine kinase,lactate dehydrogenase and tumor necrosis factorα in the injury control group at 24,48 and 120 hours after exercise were increased(P＜0.05),and the level of interleukin 6 at 24 and 120 hours after exercise was increased(P＜0.05).Compared with the injury control group,the level of myoglobin in the Yunnan Baiyao group at 24 and 48 hours after exercise was decreased(P＜0.05),the activities of creatine kinase and lactate dehydrogenase at 24,48 and 120 hours were decreased(P＜0.05),and the levels of interleukin 6 and tumor necrosis factor α at 120 hours after exercise were decreased(P＜0.05).Compared with the Yunnan Baiyao group,the level of myoglobin in the magnetic nano-drug carrier group at 24 and 48 hours after exercise was decreased(P＜0.05),the activities of creatine kinase and tumor necrosis factor α at 48 and 120 hours after exercise were decreased(P＜0.05),and the lactate dehydrogenase activity was reduced(P＜0.05).(2)Hematoxylin-eosin staining showed that a large number of inflammatory cells infiltrated in the muscle fibers of the injury control group 24 hours after exercise,and then the inflammatory cell infiltration gradually decreased,and the local damaged muscle fibers began to regenerate 120 hours after exercise.A large number of inflammatory cells infiltrated in the muscle fibers of the Yunnan Baiyao group and the magnetic nano-drug carrier group 24 hours after exercise,and then the inflammatory cell infiltration gradually decreased,and the damaged muscle fibers were regenerating 120 hours after exercise,and there was no significant difference from the blank group.(3)The results show that Yunnan Baiyao patch combined with magnetic nanoparticles can accelerate the recovery of exercise-induced muscle injury in rats,and the effect is better than that of Yunnan Baiyao alone.

BACKGROUND:Rapid and accurate segmentation of brain tissue in medical images is of great significance for three-dimensional biomechanical modeling and diagnosis of craniocerebral injuries.Currently,artificial intelligence(AI)-based baseline models exhibit excellent generalization capabilities on large-scale datasets.However,due to the specificity and complexity of craniocerebral tissues,these models have certain limitations in their application to craniocerebral tissue segmentation.Additionally,the scarcity of craniocerebral tissue samples makes it difficult for baseline models to achieve precise segmentation results through fine-tuning.OBJECTIVE:To construct a craniocerebral tissue segmentation model based on texture feature retrieval enhancement to improve segmentation accuracy under a small number of samples.METHODS:Segment Anything in Medical Images(MedSAM)model was selected as the basic framework,and texture features were combined with deep learning to build a brain tissue segmentation model based on texture feature retrieval enhancement(DP-MedSAM).Dice Coefficient and mean intersection over union(MIoU)were selected to evaluate the efficiency of image segmentation results.In comparison with the original MedSAM model,the ablation experiment systematically evaluated the influence of key components on the model performance.The sensitivities of MedSAM,the Segment Anything Model(SAM)for medical image segmentation(SAM-Med2D)and DP-MedSAM in the mandible,left optic nerve,and left parotid gland were compared.RESULTS AND CONCLUSION:(1)By verifying the impact of the number of point prompts on segmentation results on the HaN-Seg dataset,the experimental results indicated that the optimal Dice score was achieved with the addition of three points.(2)DP-MedSAM demonstrated performance improvements compared with MedSAM and SAM-Med2D on two datasets(HaN and Public Domain Database for Computational Anatomy).Especially on the Public Domain Database for Computational Anatomy dataset,in terms of the MIoU metric,DP-MedSAM outperformed MedSAM by 6.59％and SAM-Med2D by 37.35％;in terms of the Dice metric,DP-MedSAM outperformed MedSAM and SAM-Med2D by 4.34％and 25.32％,respectively.(3)The ablation experiment results showed that removing the texture feature extraction module in the DP-MedSAM model,relying solely on original image features,led to a significant decrease in results on the test set.Furthermore,removing the vector cache database and its retrieval enhancement function from the model,which deprived the ability of the model to perform similarity retrieval using an external knowledge base,further reduced model performance.(4)Under conditions of limited data resources,the DP-MedSAM model outperformed the other two models in all evaluation metrics.The DP-MedSAM model performed excellently when processing simple and moderately difficult samples,demonstrating a clear advantage over the other two models and indicating good generalization ability.Processing the fine structures of difficult samples placed higher demands on the model's segmentation capabilities.Although the performance of the DP-MedSAM model declined slightly,it still outperformed the other two models.(5)This study proposes an innovative craniocerebral tissue segmentation model,DP-MedSAM,which improves the baseline model's performance in capturing local details and global structural information in medical images by introducing target region texture feature extraction.Through vector similarity retrieval technology,DP-MedSAM can retrieve the feature vector most similar to the current target region from a pre-constructed vector database,providing more precise guiding information for the segmentation process.

BACKGROUND:3D-printed bone tissue engineering scaffolds have obvious advantages in the research and clinical treatment of bone defect repair.As one of the important raw materials for 3D printed bone scaffolds,poly-L-lactic acid has a great potential for application in performing bone defect repair,but clinical patients with different bone defect causative factors have different requirements for the comprehensive performance of poly-L-lactic acid bone scaffolds.OBJECTIVE:To summarize and review the development of 3D printing technology and poly-L-lactic acid scaffolds and the design strategies chosen for scaffolds for bone repair in the setting of bone diseases such as osteomyelitis,bone tumor,osteonecrosis,and osteoporosis.METHODS:Literature from CNKI,WanFang,PubMed,Science Direct,and Web of Science databases were searched and screened from 1994 to 2024.Search terms were"3D printing,polylactic acid,bone tissue engineering scaffold,osteomyelitis,bone tumor,osteonecrosis,osteoporosis,bone defect"in Chinese and English.The screened 62 articles were systematically summarized and analyzed.RESULTS AND CONCLUSION:(1)Poly-L-lactic acid is considered to be an ideal raw material for artificial bone scaffold design due to its non-toxicity,processability,biocompatibility,and ability to self-degrade in the human environment.The application of 3D printing technology has enabled poly-L-lactic acid bone scaffolds to meet the multilayered and porous structural design requirements of biomimetic artificial bone repair materials,and to optimize the mechanical properties for better bone repair.(2)According to different bone disease microenvironments,timely adjustment of the functional design of poly-L-lactic acid scaffolds is important for the comprehensive osteogenic efficacy of the scaffolds.The article discusses the application of poly-L-lactic acid scaffolds in bone disease environments such as osteomyelitis,bone tumor,osteonecrosis,and osteoporosis,and highlights the importance of rationally grasping the timing of bone disease treatment and bone tissue regeneration for bone defects caused by different bone diseases.(3)Although poly-L-lactic acid scaffolds show potential in bone repair,there are still some problems,such as the need to further optimize the structural design of the scaffolds to fit new bone regeneration,enhance the bioactivity of the scaffolds,and take into account other functions(e.g.,antimicrobial,anti-tumor,and anti-osteoporosis)in order to adapt to the needs of bone tissue repair in different pathological environments.

BACKGROUND:Magnetic nanomaterials,as a hot topic in the biomedical field in recent years,are often used to enhance the targeted delivery of drugs to the affected area.OBJECTIVE:To investigate the effects of magnetic nano drug carriers on skeletal muscle injury markers and inflammatory responses in rats with sports injuries.METHODS:Magnetic nanoparticles were prepared.A total of 88 male SD rats were randomly divided into a blank group(n=8),an injury control group(n=32),a Yunnan Baiyao group(n=24),and a magnetic nano-drug carrier group(n=24)by using a random number table method.The latter three groups were modeled with exercise-induced muscle injury(treadmill slope of-16°,running speed of 16 m/min,and training time of 120 min).Immediately after exercise,after verifying the success of the model,Yunnan Baiyao patch was applied to the gastrocnemius muscle of the rats in the Yunnan Baiyao group.Yunnan Baiyao patch loaded with magnetic nanoparticles was applied to the gastrocnemius muscle of the rats in the magnetic nano-drug carrier group.At 24,48,and 120 hours after exercise,blood was drawn from the abdominal aorta of rats to detect the activities of creatine kinase and lactate dehydrogenase,as well as the levels of myoglobin,interleukin-6,and tumor necrosis factor-α.Hematoxylin-eosin staining was used to observe the infiltration of inflammatory cells in the gastrocnemius muscle.RESULTS AND CONCLUSION:(1)Compared with the blank group,the levels of myoglobin,creatine kinase,lactate dehydrogenase and tumor necrosis factorα in the injury control group at 24,48 and 120 hours after exercise were increased(P＜0.05),and the level of interleukin 6 at 24 and 120 hours after exercise was increased(P＜0.05).Compared with the injury control group,the level of myoglobin in the Yunnan Baiyao group at 24 and 48 hours after exercise was decreased(P＜0.05),the activities of creatine kinase and lactate dehydrogenase at 24,48 and 120 hours were decreased(P＜0.05),and the levels of interleukin 6 and tumor necrosis factor α at 120 hours after exercise were decreased(P＜0.05).Compared with the Yunnan Baiyao group,the level of myoglobin in the magnetic nano-drug carrier group at 24 and 48 hours after exercise was decreased(P＜0.05),the activities of creatine kinase and tumor necrosis factor α at 48 and 120 hours after exercise were decreased(P＜0.05),and the lactate dehydrogenase activity was reduced(P＜0.05).(2)Hematoxylin-eosin staining showed that a large number of inflammatory cells infiltrated in the muscle fibers of the injury control group 24 hours after exercise,and then the inflammatory cell infiltration gradually decreased,and the local damaged muscle fibers began to regenerate 120 hours after exercise.A large number of inflammatory cells infiltrated in the muscle fibers of the Yunnan Baiyao group and the magnetic nano-drug carrier group 24 hours after exercise,and then the inflammatory cell infiltration gradually decreased,and the damaged muscle fibers were regenerating 120 hours after exercise,and there was no significant difference from the blank group.(3)The results show that Yunnan Baiyao patch combined with magnetic nanoparticles can accelerate the recovery of exercise-induced muscle injury in rats,and the effect is better than that of Yunnan Baiyao alone.

BACKGROUND:Rapid and accurate segmentation of brain tissue in medical images is of great significance for three-dimensional biomechanical modeling and diagnosis of craniocerebral injuries.Currently,artificial intelligence(AI)-based baseline models exhibit excellent generalization capabilities on large-scale datasets.However,due to the specificity and complexity of craniocerebral tissues,these models have certain limitations in their application to craniocerebral tissue segmentation.Additionally,the scarcity of craniocerebral tissue samples makes it difficult for baseline models to achieve precise segmentation results through fine-tuning.OBJECTIVE:To construct a craniocerebral tissue segmentation model based on texture feature retrieval enhancement to improve segmentation accuracy under a small number of samples.METHODS:Segment Anything in Medical Images(MedSAM)model was selected as the basic framework,and texture features were combined with deep learning to build a brain tissue segmentation model based on texture feature retrieval enhancement(DP-MedSAM).Dice Coefficient and mean intersection over union(MIoU)were selected to evaluate the efficiency of image segmentation results.In comparison with the original MedSAM model,the ablation experiment systematically evaluated the influence of key components on the model performance.The sensitivities of MedSAM,the Segment Anything Model(SAM)for medical image segmentation(SAM-Med2D)and DP-MedSAM in the mandible,left optic nerve,and left parotid gland were compared.RESULTS AND CONCLUSION:(1)By verifying the impact of the number of point prompts on segmentation results on the HaN-Seg dataset,the experimental results indicated that the optimal Dice score was achieved with the addition of three points.(2)DP-MedSAM demonstrated performance improvements compared with MedSAM and SAM-Med2D on two datasets(HaN and Public Domain Database for Computational Anatomy).Especially on the Public Domain Database for Computational Anatomy dataset,in terms of the MIoU metric,DP-MedSAM outperformed MedSAM by 6.59％and SAM-Med2D by 37.35％;in terms of the Dice metric,DP-MedSAM outperformed MedSAM and SAM-Med2D by 4.34％and 25.32％,respectively.(3)The ablation experiment results showed that removing the texture feature extraction module in the DP-MedSAM model,relying solely on original image features,led to a significant decrease in results on the test set.Furthermore,removing the vector cache database and its retrieval enhancement function from the model,which deprived the ability of the model to perform similarity retrieval using an external knowledge base,further reduced model performance.(4)Under conditions of limited data resources,the DP-MedSAM model outperformed the other two models in all evaluation metrics.The DP-MedSAM model performed excellently when processing simple and moderately difficult samples,demonstrating a clear advantage over the other two models and indicating good generalization ability.Processing the fine structures of difficult samples placed higher demands on the model's segmentation capabilities.Although the performance of the DP-MedSAM model declined slightly,it still outperformed the other two models.(5)This study proposes an innovative craniocerebral tissue segmentation model,DP-MedSAM,which improves the baseline model's performance in capturing local details and global structural information in medical images by introducing target region texture feature extraction.Through vector similarity retrieval technology,DP-MedSAM can retrieve the feature vector most similar to the current target region from a pre-constructed vector database,providing more precise guiding information for the segmentation process.

BACKGROUND:3D-printed bone tissue engineering scaffolds have obvious advantages in the research and clinical treatment of bone defect repair.As one of the important raw materials for 3D printed bone scaffolds,poly-L-lactic acid has a great potential for application in performing bone defect repair,but clinical patients with different bone defect causative factors have different requirements for the comprehensive performance of poly-L-lactic acid bone scaffolds.OBJECTIVE:To summarize and review the development of 3D printing technology and poly-L-lactic acid scaffolds and the design strategies chosen for scaffolds for bone repair in the setting of bone diseases such as osteomyelitis,bone tumor,osteonecrosis,and osteoporosis.METHODS:Literature from CNKI,WanFang,PubMed,Science Direct,and Web of Science databases were searched and screened from 1994 to 2024.Search terms were"3D printing,polylactic acid,bone tissue engineering scaffold,osteomyelitis,bone tumor,osteonecrosis,osteoporosis,bone defect"in Chinese and English.The screened 62 articles were systematically summarized and analyzed.RESULTS AND CONCLUSION:(1)Poly-L-lactic acid is considered to be an ideal raw material for artificial bone scaffold design due to its non-toxicity,processability,biocompatibility,and ability to self-degrade in the human environment.The application of 3D printing technology has enabled poly-L-lactic acid bone scaffolds to meet the multilayered and porous structural design requirements of biomimetic artificial bone repair materials,and to optimize the mechanical properties for better bone repair.(2)According to different bone disease microenvironments,timely adjustment of the functional design of poly-L-lactic acid scaffolds is important for the comprehensive osteogenic efficacy of the scaffolds.The article discusses the application of poly-L-lactic acid scaffolds in bone disease environments such as osteomyelitis,bone tumor,osteonecrosis,and osteoporosis,and highlights the importance of rationally grasping the timing of bone disease treatment and bone tissue regeneration for bone defects caused by different bone diseases.(3)Although poly-L-lactic acid scaffolds show potential in bone repair,there are still some problems,such as the need to further optimize the structural design of the scaffolds to fit new bone regeneration,enhance the bioactivity of the scaffolds,and take into account other functions(e.g.,antimicrobial,anti-tumor,and anti-osteoporosis)in order to adapt to the needs of bone tissue repair in different pathological environments.

OBJECTIVE To investigate the effects of subanesthetic dose of esketamine on postoperative anxiety and recovery in patients undergoing laparoscopic cholecystectomy. METHODS A total of 200 patients scheduled for laparoscopic cholecystectomy at Suzhou Ninth Hospital Affiliated to Soochow University from January 2023 to December 2024 were randomly assigned to control group （n＝100） and observation group （n＝100）. One minute before the initiation of anesthesia， patients in the control group received intravenous injections of Propofol emulsion injection， Sufentanil citrate injection， and Succinylcholine chloride injection. On this basis， patients in the observation group received an intravenous injection of Esketamine hydrochloride injection. The anxiety status of patients in both groups was compared， along with their general intraoperative conditions （including sufentanil dosage， duration of pneumoperitoneum， operative time， anesthesia time， and extubation time）， postoperative recovery， incidence of adverse reactions， and the need for dezocine rescue analgesia. Heart rate and mean arterial pressure， entropy index （state entropy and response entropy）， inflammatory marker levels [interleukin-6 （IL-6） and C-reactive protein （CRP）]， numerical rating scale （NRS） for pain intensity were compared between the two groups at different time points. RESULTS No significant differences were found between the two groups in pneumoperitoneum duration， operative time， anesthesia time，extubation time， incidence of postoperative dry mouth， entropy index or length of stay in the post-anesthesia care unit （P＞0.05）. Compared with the control group， the observation group showed significantly lower postoperative STAI-S scores， reduced intraoperative sufentanil consumption， decreased incidence of postoperative nausea， vomiting， and shivering， the need for dezocine rescue analgesia， as well as lower plasma IL-6 and CRP levels at 24 h after surgery， and NRS （P＜0.05）. The heart rate and mean arterial pressure of patients in the observation group at the start of surgery， end of surgery， and during extubation were all significantly higher than those in the control group （P＜0.05）. CONCLUSIONS Subanesthetic dose of esketamine can effectively alleviate postoperative anxiety， reduce intraoperative opioid consumption， suppress postoperative inflammatory response， relieve postoperative pain， and promote recovery in patients undergoing laparoscopic cholecystectomy.

ObjectiveTo establish a mouse model of rheumatoid arthritis with interstitial lung disease （RA-ILD） in DBA/1 mice using Porphyromonas gingivalis （Pg） infection combined with collagen-induced arthritis （CIA）， and to comprehensively evaluate pathological characteristics in joints， lungs， and serum. MethodsForty DBA/1 mice were randomly divided into four groups， i.e.， Control， Pg infection （Pg）， CIA， and Pg infection combined with CIA （Pg+CIA）， with 10 mice in each group. Arthritis clinical symptoms were evaluated by recording arthritis incidence and clinical scores. Micro-CT scanning was used to assess knee joint pathology. Histopathological changes and collagen deposition in knee joints and lung tissues were analyzed using hematoxylin-eosin （HE） and Masson staining. Immunohistochemistry was performed to detect protein expression of α-smooth muscle actin （α-SMA）， typeⅠ collagen （ColⅠ）， and fibronectin （FN） in lung tissues. Real-time quantitative polymerase chain reaction（Real-time PCR）was used to measure mRNA expression levels of α-SMA， ColⅠ， FN， tumor necrosis factor-α （TNF-α）， interleukin-6 （IL-6）， and IL-1β in lung tissues. Enzyme-linked immunosorbent assay （ELISA） was used to detect serum levels of Pg， cyclic citrullinated peptide （CCP）， and immunoglobulin G （IgG）. ResultsJoint lesions： The CIA and Pg+CIA groups showed 100% arthritis incidence， with evident joint redness， swelling， and deformity. The number of affected limbs was 27 and 28， and clinical scores were 68 and 70， respectively. No obvious clinical symptoms were observed in the Pg group. Histopathological and imaging analyses showed severe joint lesions in the CIA and Pg+CIA groups， with significantly increased histopathological scores， bone mineral density， bone volume fraction， trabecular thickness， and trabecular number compared to the Control group （P<0.01）. No obvious joint pathology was observed in the Pg group. Lung lesions： The Pg+CIA group exhibited marked alveolar inflammation， interstitial inflammatory cell infiltration， and alveolar wall thickening， with pronounced blue staining of collagen fibers. Histopathological scores and collagen area ratios were significantly higher than those of the Control， Pg， and CIA groups （P<0.05）. Lung protein and mRNA expression levels of α-SMA， ColⅠ， and FN were markedly increased， and mRNA levels of IL-6， TNF-α， and IL-1β were significantly elevated compared to the Control group （P<0.05）. Serology： The Pg+CIA group showed significantly higher levels of CCP， Pg， and IgG compared with the Control， Pg， and CIA groups （P<0.05）. ConclusionDBA/1 mice subjected to Pg infection combined with CIA exhibited pronounced symptoms and pathological features of RA-ILD， along with elevated serum anti-CCP antibody levels. This model represents a novel RA-ILD mouse model， providing a valuable experimental tool for investigating RA-ILD pathogenesis and developing new therapeutics， and serves as a basis for establishing anti-cyclic citrullinated peptide antibody （ACPA）-positive RA-ILD animal models.

Colorectal cancer （CRC） is one of the most common cancers， with its incidence ranking high among cancers. It stands as the second leading cause of cancer-related death worldwide. In the early stages， CRC lacks specific symptoms， and most patients are diagnosed at advanced stages， making it a major research focus in the field of gastrointestinal tumors. Currently， clinical CRC treatments face several common challenges， including high surgical risks， frequent metastasis and recurrence， drug resistance， and significant side effects from chemotherapy and radiation therapy. With the development and application of traditional Chinese medicine （TCM）， it has been found that TCM and its active ingredients can effectively inhibit CRC cell proliferation， invasion， migration， and angiogenesis， and promote apoptosis and autophagy， thereby slowing the progression of CRC. This has become a key focus of CRC treatment research. Salvia Miltiorrhiza has multiple pharmacological effects， including activating blood circulation to dispel blood stasis， unlocking meridians to relieve pain， clearing heat to calm irritability， and cooling blood to reduce abscesses. It contains a variety of chemical components， including diterpenoids， phenolic acids， flavonoids， polysaccharides， nitrogen-containing compounds， steroids， and lactone compounds. This review summarized the molecular mechanisms of Salvia miltiorrhiza and its active ingredients in the treatment of CRC. It is found that these ingredients exert anti-CRC effects through various molecular mechanisms， including cell cycle arrest， promotion of apoptosis， inhibition of cell invasion and migration， induction of autophagy， suppression of tumor angiogenesis， and remodeling of the tumor microenvironment. The review aims to provide new insights for the drug development and clinical application of Salvia miltiorrhiza in CRC treatment.

Neurocritical care involves complex pathophysiological mechanisms, and its incidence is higher, injuries are more severe, and treatment is more challenging in high-altitude environments. This consensus, based on the latest domestic and international evidence-based medical data, establishes a standardized, goal-oriented framework for neurocritical care management applicable in high-altitude regions and nationwide. The consensus was developed following international standards for evidence quality assessment and underwent two rounds of Delphi expert consultation, resulting in 32 recommendation statements covering three parts: management systems, monitoring and assessment, and core strategies. Key updates include: advocating for the establishment of independent neurocritical care units and implementing precise tiered diagnosis and treatment based on the "Five Differences in Critical Care" concept; constructing a "trinity" multimodal brain monitoring system centered on cerebral blood flow, cerebral oxygenation, and brain function, emphasizing routine bedside transcranial Doppler ultrasound, cerebral oximetry, and continuous electroencephalography monitoring; shifting management strategies from mild hypothermia therapy to targeted temperature management, and defining the "446" target management pathway for the supercritical stage; emphasizing the assessment of static and dynamic cerebrovascular autoregulation functions through multimodal methods to achieve individualized optimal mean arterial pressure management; elevating cerebrospinal fluid management goals to the level of "glymphatic system" function maintenance; implementing a multidisciplinary collaborative, whole-process management model focusing on patients' long-term neurological functional outcomes; de-escalation criteria include multidimensional indicators such as recovery of brain structure, restoration of cerebrovascular autoregulation, improvement in cerebrospinal fluid dynamics, and reduction in biomarker levels; and integrating cutting-edge technologies like artificial intelligence into post-critical care management and rehabilitation planning. This consensus systematically integrates the entire process of neurocritical care management, reflecting the modern connotation of goal-oriented, dynamic, and multimodal integration in neurocritical care medicine. It aims to adapt to new trends such as deepening understanding of pathophysiological mechanisms, the integration of medicine and engineering, and the empowerment of artificial intelligence, thereby further advancing the discipline of critical care medicine.