Objective:To investigate the role of calcium-binding protein S100A9 in acute lung injury induced by hepatic ischemia-reperfusion (HIR) in mice, and to explore its relationship with nuclear factor erythroid 2-related factor 2 (Nrf2).Methods:A total of 12 specific pathogen-free (SPF) male wild-type (WT) and 12 S100A9 knockout (S100A9 KO) C57BL/6J mice aged 6~8 weeks and weighing 20-25 g were randomly divided into four groups using a random number table: WT+Sham group, S100A9 KO+Sham group, WT+HIR group, and S100A9 KO+HIR group ( n=6 per group). The HIR model was established by clamping the portal vein and hepatic artery of the left and median liver lobes for 60 minutes followed by reperfusion. At 6 hours post-reperfusion, mice were anesthetized again, and blood samples were collected from the inferior vena cava. Both lungs were harvested. The lung wet-to-dry (W/D) weight ratio was measured. Hematoxylin and eosin (HE) staining was used to assess histopathological changes and calculate lung injury scores. The levels of inflammatory markers—S100A9, tumor necrosis factor-α (TNF-α), and interleukin-6 (IL-6) —as well as oxidative stress indicators including myeloperoxidase (MPO), reactive oxygen species (ROS), malondialdehyde (MDA), and superoxide dismutase (SOD) in serum and lung tissue were measured. Western blotting was used to assess the expression levels of nuclear and cytoplasmic Nrf2, and cytoplasmic HO-1. Results:Compared with the WT+Sham group, both the WT+HIR and S100A9 KO+HIR groups showed significantly increased lung injury scores, W/D ratio, TNF-α, IL-6, ROS, MPO, and MDA levels (all P<0.05). Compared with the WT+HIR group, the S100A9 KO+HIR group exhibited significantly reduced levels of these indicators (all P<0.05). Moreover, the S100A9 KO+HIR group showed elevated nuclear Nrf2 expression and decreased cytoplasmic Nrf2 expression, accompanied by increased expression of HO-1, Gclm, Gclc, and Nqo1 (all P<0.05). Conclusion:Upregulation of S100A9 is involved in the development of HIR-induced acute lung injury, possibly through inhibition of Nrf2 nuclear translocation.

Collagen-based materials, renowned for their biocompatibility and minimal immunogenicity, serve as exemplary substrates in a myriad of biomedical applications. Collagen-based micro/nanogels, in particular, are valued for their increased surface area, tunable degradation rates, and ability to facilitate targeted drug delivery, making them instrumental in advanced therapeutics and tissue engineering endeavors. Although extensive reviews on micro/nanogels exist, they tend to cover a wide range of biomaterials and lack a specific focus on collagen-based materials. The current review offers an in-depth look into the manufacturing technologies, drug release mechanisms, and biomedical applications of collagen-based micro/nanogels to address this gap. First, we provide an overview of the synthetic strategies that allow the precise control of the size, shape, and mechanical strength of these collagen-based micro/nanogels by controlling the degree of cross-linking of the materials. These properties are crucial for their performance in biomedical applications. We then highlight the environmental responsiveness of these collagen-based micro/nanogels, particularly their sensitivity to enzymes and pH, which enables controlled drug release under various pathological conditions. The discussion then expands to include their applications in cancer therapy, antimicrobial treatments, bone tissue repair, and imaging diagnosis, emphasizing their versatility and potential in these critical areas. The challenges and future perspectives of collagen-based micro/nanogels in the field are discussed at the end of the review, with an emphasis on the translation to clinical practice. This comprehensive review serves as a valuable resource for researchers, clinicians, and scientists alike, providing insights into the current state and future directions of collagen-based micro/nanogel research and development.
Collagen/chemistry* ; Drug Delivery Systems/methods* ; Humans ; Tissue Engineering/methods* ; Animals ; Biocompatible Materials/chemistry*

To address the challenges faced by current brain midline segmentation techniques, such as insufficient accuracy and poor segmentation continuity, this paper proposes a deep learning network model based on a two-stage framework. On the first stage of the model, prior knowledge of the feature consistency of adjacent brain midline slices under normal and pathological conditions is utilized. Associated midline slices are selected through slice similarity analysis, and a novel feature weighting strategy is adopted to collaboratively fuse the overall change characteristics and spatial information of these associated slices, thereby enhancing the feature representation of the brain midline in the intracranial region. On the second stage, the optimal path search strategy for the brain midline is employed based on the network output probability map, which effectively addresses the problem of discontinuous midline segmentation. The method proposed in this paper achieved satisfactory results on the CQ500 dataset provided by the Center for Advanced Research in Imaging, Neurosciences and Genomics, New Delhi, India. The Dice similarity coefficient (DSC), Hausdorff distance (HD), average symmetric surface distance (ASSD), and normalized surface Dice (NSD) were 67.38 ± 10.49, 24.22 ± 24.84, 1.33 ± 1.83, and 0.82 ± 0.09, respectively. The experimental results demonstrate that the proposed method can fully utilize the prior knowledge of medical images to effectively achieve accurate segmentation of the brain midline, providing valuable assistance for subsequent identification of the brain midline by clinicians.
Humans ; Brain/diagnostic imaging* ; Deep Learning ; Image Processing, Computer-Assisted/methods* ; Algorithms ; Magnetic Resonance Imaging/methods* ; Neural Networks, Computer

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Objective:To assess the predictive performance of a nomogram model integrating endoscopic ultrasound（EUS）radiomic features with clinical variables for distinguishing early esophageal squamous cell carcinoma（ESCC）from non-cancerous lesions.Methods:Clinical and imaging data from 454 patients who underwent EUS for suspected esophageal malignancies were retrospectively collected in the First Affiliated Hospital of Nanjing Medical University（training cohort， n = 323）and Dongyang People's Hospital（external validation cohort， n = 131）from January 2020 to November 2023. Independent clinical predictors of early ESCC were identified using univariable and multivariable Logistic regression analyses to establish a clinical model. Pearson correlation and Least Absolute Shrinkage and Selection Operator（LASSO）algorithms were used to construct a radiomics model. A combined model integrating radiomics scores and clinical predictors was developed and visualized as a nomogram. The predictive performance of each model was assessed using the area under the ROC curve（AUC），and calibration curves were used to evaluate the model's fitting capability. Results:The training set and validation set indicated that there were statistically significant differences in age，smoking history and lesion location between the early ESCC group and the non-cancerous lesion change group（all P < 0.05）. According to univariate and multivariate Logistic regression analysis，age（ OR = 1.039，95% CI = 1.003–1.077， P = 0.036）and smoking（ OR = 2.358，95% CI = 1.270 - 4.376， P = 0.007）were identified as independent predictors and used to develop the clinical model，with AUCs of 0.608 and 0.694 in the training and validation cohorts，respectively. Fourteen optimal radiomic features were selected to construct the radiomics model，with AUCs of 0.881 and 0.807 in the training and validation cohorts，respectively. The combined nomogram model demonstrated superior predictive performance with AUCs of 0.893 and 0.830，sensitivities of 82.5% and 79.1%，and specificities of 82.2% and 81.3% in the training and validation cohorts，respectively. Conclusions:The EUS-based nomogram model demonstrates optimal predictive performance and can serve as a non-invasive tool to assist endoscopists in distinguishing early ESCC from non-cancerous lesions.

Objective To systematically sort out the current situation of animal model construction and evaluation of damp-heat syndrome of spleen and stomach under the pattern of combining disease and evidence,references for optimizing the standardized research of this syndrome were provided.Methods The references in the past 20 years from CNKI,Wanfang,VIP,PubMed and other databases were searched to summarize and analyze the modeling ideas,evaluation systems and problems of the animal models of spleen-stomach damp-heat syndrome.Results Most of the existing models used high-fat and high-sugar feeds combined with hot and humid environment exposure,compound pathogenic microbial infection or chemical stimulation to construct the combined disease and evidence model.The model validity was evaluated by macroscopic signs,gastrointestinal function indexes,inflammatory factors,and intestinal bacterial flora,etc.However,there were still problems of insufficient stability of the model,and inconsistencies in the criteria for evaluation of the evidence.Conclusion The combination of disease and evidence model can better simulate the clinical characteristics of spleen and stomach damp-heat syndrome,but it is necessary to strengthen the construction of multimodal evaluation system and molecular mechanism research.The standardization of animal models can be promoted through the integration of multidisciplinary technology,which can provide a more accurate method for the modernization of traditional Chinese medicine research.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Objective:To assess the predictive performance of a nomogram model integrating endoscopic ultrasound（EUS）radiomic features with clinical variables for distinguishing early esophageal squamous cell carcinoma（ESCC）from non-cancerous lesions.Methods:Clinical and imaging data from 454 patients who underwent EUS for suspected esophageal malignancies were retrospectively collected in the First Affiliated Hospital of Nanjing Medical University（training cohort， n = 323）and Dongyang People's Hospital（external validation cohort， n = 131）from January 2020 to November 2023. Independent clinical predictors of early ESCC were identified using univariable and multivariable Logistic regression analyses to establish a clinical model. Pearson correlation and Least Absolute Shrinkage and Selection Operator（LASSO）algorithms were used to construct a radiomics model. A combined model integrating radiomics scores and clinical predictors was developed and visualized as a nomogram. The predictive performance of each model was assessed using the area under the ROC curve（AUC），and calibration curves were used to evaluate the model's fitting capability. Results:The training set and validation set indicated that there were statistically significant differences in age，smoking history and lesion location between the early ESCC group and the non-cancerous lesion change group（all P < 0.05）. According to univariate and multivariate Logistic regression analysis，age（ OR = 1.039，95% CI = 1.003–1.077， P = 0.036）and smoking（ OR = 2.358，95% CI = 1.270 - 4.376， P = 0.007）were identified as independent predictors and used to develop the clinical model，with AUCs of 0.608 and 0.694 in the training and validation cohorts，respectively. Fourteen optimal radiomic features were selected to construct the radiomics model，with AUCs of 0.881 and 0.807 in the training and validation cohorts，respectively. The combined nomogram model demonstrated superior predictive performance with AUCs of 0.893 and 0.830，sensitivities of 82.5% and 79.1%，and specificities of 82.2% and 81.3% in the training and validation cohorts，respectively. Conclusions:The EUS-based nomogram model demonstrates optimal predictive performance and can serve as a non-invasive tool to assist endoscopists in distinguishing early ESCC from non-cancerous lesions.

Objective:To investigate the role of calcium-binding protein S100A9 in acute lung injury induced by hepatic ischemia-reperfusion (HIR) in mice, and to explore its relationship with nuclear factor erythroid 2-related factor 2 (Nrf2).Methods:A total of 12 specific pathogen-free (SPF) male wild-type (WT) and 12 S100A9 knockout (S100A9 KO) C57BL/6J mice aged 6~8 weeks and weighing 20-25 g were randomly divided into four groups using a random number table: WT+Sham group, S100A9 KO+Sham group, WT+HIR group, and S100A9 KO+HIR group ( n=6 per group). The HIR model was established by clamping the portal vein and hepatic artery of the left and median liver lobes for 60 minutes followed by reperfusion. At 6 hours post-reperfusion, mice were anesthetized again, and blood samples were collected from the inferior vena cava. Both lungs were harvested. The lung wet-to-dry (W/D) weight ratio was measured. Hematoxylin and eosin (HE) staining was used to assess histopathological changes and calculate lung injury scores. The levels of inflammatory markers—S100A9, tumor necrosis factor-α (TNF-α), and interleukin-6 (IL-6) —as well as oxidative stress indicators including myeloperoxidase (MPO), reactive oxygen species (ROS), malondialdehyde (MDA), and superoxide dismutase (SOD) in serum and lung tissue were measured. Western blotting was used to assess the expression levels of nuclear and cytoplasmic Nrf2, and cytoplasmic HO-1. Results:Compared with the WT+Sham group, both the WT+HIR and S100A9 KO+HIR groups showed significantly increased lung injury scores, W/D ratio, TNF-α, IL-6, ROS, MPO, and MDA levels (all P<0.05). Compared with the WT+HIR group, the S100A9 KO+HIR group exhibited significantly reduced levels of these indicators (all P<0.05). Moreover, the S100A9 KO+HIR group showed elevated nuclear Nrf2 expression and decreased cytoplasmic Nrf2 expression, accompanied by increased expression of HO-1, Gclm, Gclc, and Nqo1 (all P<0.05). Conclusion:Upregulation of S100A9 is involved in the development of HIR-induced acute lung injury, possibly through inhibition of Nrf2 nuclear translocation.

Objective To search,evaluate and summarise the best evidence on pre-rehabilitation before surgery for elderly patients with hip fracture so as to provide an evidence-based basis for further standardisation in clinical practice.Methods Based on the"6S Pyramid"evidence model,desktop searches were conducted across databases and websites including Medlive,BMJ Best Practice,UpToDate,the World Health Organization,the Guidelines International Network(GIN),British National Institute for Health and Care Excellence(NICE),American National Guideline Clearinghouse(NGC),Canadian Medical Association:Clinical Practice Guidelines Infobase(CMA),Scottish Intercollegiate Guidelines Network(SIGN),the Registered Nurses'Association of Ontario(RNAO),American College of Sports Medicine(ACSM),American Academy of Orthopaedic Surgeons(AAOS),European Society for Clinical Nutrition and Metabolism(ESPEN),American Society for Parenteral and Enteral Nutrition(ASPEN),the Enhanced Recovery After Surgery Society(ERASS),Cochrane Library,Joanna Briggs Institute,PubMed,CINAHL,Web of Science,Embase,Scopus,Science Direct,CNKI,Wanfang Data,Vip,and SinoMed.The research targeted evidence on pre-rehabilitation in elderly patients with hip-fracture before surgery,encompassing clinical decisions,guidelines,evidence summaries,best practices,expert consensus,systematic reviews and randomized controlled trials(RCTs).The search items spanned from the inception of database to 31st December,2023.Two researchers trained with evidence-based knowledge evaluated the quality of the included literature and extracted and summarised the evidence.Results A total of 14 documents were included,consisting of 2 clinical decisions,4 guidelines,1 best practice,4 expert consensus and 3 systematic reviews.Evidence was summarised into 7 domains from 25 pieces of evidence:multidisciplinary management,preoperative assessment,preoperative health education,multi-modal analgesia,nutritional management,exercise intervention and assessment and prevention of complication risks.Conclusion The best evidence summarised in this study provides a basis for pre-rehabilitation in elderly patients with hip fracture before surgery.Nurses should adapt the findings to specific contexts,standardise the preoperative rehabilitation procedures,and improve clinical outcomes for the patients.