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.

ObjectiveTo investigate the effects of metformin on the immune functions of immature dendritic cells （imDCs） and the underlying mechanisms. MethodsMouse bone marrow-derived imDCs were treated with different concentrations of metformin. The working concentration and treatment time of metformin in this study were determined based on the results of cell apoptosis and cell viability assays. The effects of metformin on the phagocytic capacity of imDCs was evaluated using an antigen endocytosis assay. The expression of cluster of differentiation 205 （CD205）， the polymerization of filamentous actin （F-actin）， and the underlying regulatory mechanisms were investigated through flow cytometry， laser confocal fluorescence microscopy， and Western blot. ResultsThe working concentrations of metformin were 1， 2， 4 mmol/L for 24 h determined by the apoptosis and cell viability assays.Metformin significantly suppressed the phagocytic capacity of imDCs， down-regulated the expression of the mannose receptor CD205 on the cell surface， which was closely associated with phagocytic function； metformin inhibited the RhoA-ROCK1-LIMK1-Cofilin signaling pathway， which inhibited the polymerization of F-actin and disturbed its dynamic remodeling of imDCs. ConclusionMetformin can inhibit the expression of CD205 and disrupt the remodeling of F-actin， thereby suppressing the antigen-capturing capacity of imDCs.

Objective To explore the feasibility of constructing a three-classification bone status screening radiomics model on chest CT images.Methods A total of 371 patients who underwent both chest and abdominal plain CT examinations were retrospec-tively selected and randomly divided into training set(296 cases)and test set(75 cases)in a ratio of 8︰2.Additionally,110 patients were included as external validation set using the same criteria.The 120 kVp abdominal images were transmitted to a quantitative compu-ted tomography(QCT)post-processing workstation to measure the bone mineral density(BMD)of the L1-L2 vertebral bodies.Patients were classified into osteoporosis(OP)group(BMD<80 mg/cm3),osteopenia group(80 mg/cm3≤BMD≤120 mg/cm3)and normal bone mass group(BMD>120 mg/cm3)based on QCT BMD results.The automatic segmentation model was used to segment T10-T12 vertebral trabecular bone on chest CT images and the radiomics models based on random forest(RF)and logistic regres-sion(LR)was established to evaluate BMD,enabling it to simultaneously distinguish OP,osteopenia,and normal bone mass.The diag-nostic performance of the two models were evaluated using metrics such as the area under the curve(AUC),sensitivity and specificity.The DeLong test was used to compare the differences between the two models.Results In the test set,the AUC for differentiating normal bone mass were 0.948 and 0.877 for the RF and LR models,respectively;the AUC for differentiating OP were 0.942 and 0.836,respectively;and the AUC for differentiating osteopenia were 0.871 and 0.688,respectively.The performance comparison results of the models showed that there was no statistically significant difference in AUC(0.966 vs 0.907,P>0.05)between RF model and LR model in the external validation set for distinguishing OP,while there was a statistically significant difference in AUC for distinguishing osteopenia(0.895 vs 0.749,P=0.009)and normal bone mass(0.975 vs 0.906,P=0.023).The RF model performance was superior to the LR model.Conclusion The radiomics model developed based on chest plain CT can be used for opportunistic OP screening with good diagnostic efficacy,and the the model based on the RF classifier outperforms the LR model.

Objective:To explore the application value of the double-low technique of auto-prescription technique combined with iterative reconstruction algorithm in CT pulmonary angiography (CTPA).Methods:A total of 86 patients who were clinically suspected of having pulmonary embolism and underwent CTPA examination in the First Affiliated Hospital of Dalian Medical University were prospectively collected and randomly assigned to a control group ( n = 45) and an observation group ( n = 41) according to the random number table method. In the control group, a tube voltage of 120 kVp was used with a standard iodine contrast agent dose of 60 ml, and images were reconstructed using the 40% adaptive statistical iterative reconstruction algorithm (ASIR-V). In the observation group, the tube voltage was set by auto-prescription technique, and 0.4 ml/kg of personalized low iodine contrast agent was used. Images were reconstructed with 40%, 60%, and 80% ASIR-V, respectively, and designated as observation 1, observation 2, and observation 3 respectively. The volume CT dose index (CTDI vol), dose-length product (DLP), and effective dose ( E) were recorded and compared among the four groups. The CT values and standard deviation (SD) of the main pulmonary artery, left and right pulmonary arteries, as well as the left and right pulmonary lobe arteries were measured, and the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of these arteries were calculated. Additionally, the SD value at the contrast medium concentration in the superior vena cava was measured, and the artifact index (AI) was subsequently calculated. Two observers independently assessed the visibility of the pulmonary arteries, image noise, and sclerosis artifacts in the superior vena cava using a blinded method. Results:The E in the observation group was 3.28 (2.08, 3.93) mSv, which was significantly lower than that in the control group [5.03 (4.86, 5.20)] mSv, and the difference was statistically significant ( Z = 174.00, P < 0.05). The contrast agent dosage in the observation group was 28 (25, 30) ml, which was lower than that in the control group (60 ml), and the difference was statistically significant ( Z = 0, P < 0.05). The CT values for the main pulmonary artery and the left and right pulmonary lobe arteries in the observation group were higher than those in the control group, and the differences were all statistically significant ( t = -3.65 to -3.89, P < 0.05). The SNR and CNR of the observation groups 2 and 3 were greater than those of the control group ( t = -9.20 to -2.98, P < 0.05). The consistency of subjective evaluations between the two observers was good ( Kappa = 0.729 - 0.879, P < 0.05). There was no statistically significant difference in the subjective score of pulmonary artery visibility between the control and observation group ( P > 0.05). The subjective scores for image noise in observation group 2 and group 3 were higher than those in the control group ( U =598.50, 654.00, P < 0.05). The presence of artifacts due to sclerosis in the superior vena cava was significantly lower in the observation group compared to the control group ( χ2 = 46.09, P < 0.001). Conclusions:The combination of auto-prescription technique with ASIR-V reconstruction algorithm and low contrast agent imaging protocol can reduce the radiation dose and contrast agent dose without compromising image quality, and enable personalized double low CTPA imaging.

Objective:To investigate the role and mechanism of negative pressure wound therapy (NPWT) in a rabbit full-thickness wound model using non-targeted metabolomics.Methods:Eighteen male New Zealand rabbits (11-12 weeks old) were used. Two symmetrical circular full-thickness skin defects were created on the back of each rabbit. The animals were randomly divided into three groups: Control group (no treatment), Saline group (debridement with saline irrigation), and NPWT+ Saline group (saline debridement followed by 2 h of NPWT at -125 mm Hg once daily for two weeks). Wound healing was documented on days 0, 3, 7, 10, and 14. The wound healing rate was calculated as (original area-unhealed area)/original area × 100%. Histopathological changes were evaluated via hematoxylin and eosin (HE) staining. Metabolomic profiling of wound tissues was performed using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Differential metabolites were identified, and pathway enrichment analysis was conducted. Oxidative stress markers, including superoxide dismutase (SOD) and catalase (CAT) activities and malondialdehyde (MDA) content, were measured using commercial kits. Data were analyzed using SPSS 20.0. One-way ANOVA with Tukey’s HSD test or Welch’s ANOVA with Games-Howell test was applied as appropriate.Results:On days 3, 10, and 14, the wound healing rate in the NPWT+ Saline group was significantly higher than that in the Control and Saline groups ( P<0.05). On day 7, the NPWT+ Saline group showed a significantly higher healing rate than the Saline group ( P<0.01), but no significant difference compared with the Control group ( P>0.05). HE staining on day 7 revealed enhanced epithelialization, thicker granulation tissue, higher microvessel density, and more abundant, well-organized collagen in the NPWT+ Saline group. By day 14, all groups had formed relatively continuous epithelial structures. Non-targeted metabolomics identified riboflavin and spermidine as differential metabolites. Pathway analysis highlighted riboflavin metabolism and glutathione metabolism as the most significantly enriched pathways. Compared with the Control and Saline groups, the NPWT+ Saline group exhibited significantly increased CAT and SOD activities ( P<0.05) and decreased MDA content ( P<0.01), indicating reduced oxidative stress. Conclusion:NPWT may promote wound healing by elevating riboflavin and spermidine levels, thereby modulating riboflavin and glutathione metabolism and regulating local redox reactions.

Objective To explore the application value of Auto-prescription combined with low-dose contrast and adaptive statisti-cal iterative reconstruction-Veo(ASIR-V)algorithm in the computed tomography angiography(CTA)of thoracodorsal artery(TDA).Methods A total of 100 patients who underwent TDA CTA examination were prospectively selected.A tube voltage of 120 kVp and contrast agent of 1.5 mL/kg were used for group A(50 cases),and images were reconstructed with 40％ post-set ASIR-V.The Auto-prescription for tube voltage and contrast agent of 1.2 mL/kg were used for group B(50 cases),while images were reconstruc-ted with 40％,60％,and 80％ post-set ASIR-V,labeled as subgroups B1 to B3.The objective and subjective evaluation results of the images were compared between and within groups.Results Group A had an effective dose(ED)of 2.98(2.65,4.03)mSv,while group B had an ED of 1.92(1.44,3.33)mSv.The iodine intake in group B was lower than that in group A,and the CT value of the axillary artery in group B was significantly higher than that in group A(P＜0.001).With the increased of ASIR-V level in group B,the signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)of the images gradually increased(P＜0.05).In terms of subjec-tive scores on axial images,both subgroups B2 and B3 were superior to group A(P＜0.001);with the increased of ASIR-V level in group B,subjective scores of axial images increased first and then decreased,among which subjective score of subgroup B2 was the highest and the differences were statistically significant(P＜0.001).In terms of subjective scores on three-dimensional image quality,subgroups B1 to B3 were superior to group A(P＜0.001).Conclusion The use of Auto-prescription combined with low-dose con-trast and 60％ ASIR-V can significantly optimize the display of TDA,and reduce the radiation dose and contrast agent dose to a certain extent.

In recent years, hybrid brain-computer interfaces (BCIs) have gained significant attention due to their demonstrated advantages in increasing the number of targets and enhancing robustness of the systems. However, Existing studies usually construct BCI systems using intense auditory stimulation and strong central visual stimulation, which lead to poor user experience and indicate a need for improving system comfort. Studies have proved that the use of peripheral visual stimulation and lower intensity of auditory stimulation can effectively boost the user's comfort. Therefore, this study used high-frequency peripheral visual stimulation and 40-dB weak auditory stimulation to elicit steady-state visual evoked potential (SSVEP) and auditory steady-state response (ASSR) signals, building a high-comfort hybrid BCI based on weak audio-visual evoked responses. This system coded 40 targets via 20 high-frequency visual stimulation frequencies and two auditory stimulation frequencies, improving the coding efficiency of BCI systems. Results showed that the hybrid system's averaged classification accuracy was (78.00 ± 12.18) %, and the information transfer rate (ITR) could reached 27.47 bits/min. This study offers new ideas for the design of hybrid BCI paradigm based on imperceptible stimulation.
Brain-Computer Interfaces ; Humans ; Evoked Potentials, Visual/physiology* ; Acoustic Stimulation ; Photic Stimulation ; Electroencephalography ; Evoked Potentials, Auditory/physiology* ; Adult

Objective To explore the application value of deep learning image reconstruction(DLIR)algorithm combined with a large reconstruction matrix in lung nodules screening using low-dose computed tomography(LDCT)of the chest.Methods Patients who underwent LDCT scans were prospectively enrolled.The control group(group A)used the iterative reconstruction(IR)algorithm(Karl)with a reconstruction level of Karl 5,reconstructed images of 512×512(group A1)matrix,and 1 024 × 1 024(group A2)matrix.The experimental group employed DLIR combined with 512×512(group B)matrix and 1 024 × 1 024(group C)matrix for image reconstruction at levels 1-5,which were recorded as groups B1-5 and groups C1-5.The CT values and standard deviation(SD)values of the lung parenchyma and tracheal air were measured,and the signal-to-noise ratio(SNR)was calculated.The overall lung image quality was scored on a Likert 5-point scale,and the subgroup with the best lung image quality was selected.The lung nodule detec-tion rate and clarity were compared with group A1.Results Under the same reconstruction matrix,the CT values of the tracheal air and lung parenchyma in the experimental group showed no significant difference compared to the control group,while the SD values were lower and SNR were higher(P＜0.05).Within groups B and C,as the DLIR level increased,the SD values of the tracheal air and lung paren-chyma gradually decreased,and SNR gradually improved(P＜0.05).Subjective scores for the image quality in groups B and C initially increased and then decreased,with group B3 and group C4 showed the best image quality.No difference was observed in objective eval-uation between the two groups,but the subjective image quality score of group C4 was superior to group B3(P＜0.05).Subjective eval-uation of lung nodule display in group C4 was better than in group A1(P＜0.05).Conclusion DLIR algorithm combined with a large reconstruction matrix is feasible for lung nodules screening in chest LDCT,reducing image noise while improving lung nodules clarity,demonstrating significant clinical value.

Objective To evaluate the efficacy,safety and economy of vonoprazan in the treatment of post-endoscopic submucosal dissection(ESD)ulcer by rapid health technology assessment method,and to provide reference for clinical treatment decision.Methods PubMed,Cochrane Library,Embase,ScienceDirect,CNKI,WanFang Data databases and the official website of health technology assessment(HTA)agency were electronically searched to collect HTA reports,systematic reviews/Meta-analysis and pharmacoeconomic studies of vonoprazan in the treatment of post-ESD ulcer from inception to July 31,2024.Two researchers independently screened literature,extracted data,and comprehensively analyzed the results of the included literature on the basis of literature quality evaluation.Results A total of 8 studies were included,all were systematic reviews/Meta-analysis.In terms of effectiveness,compared with proton pump inhibitors(PPI),vonoprazan significantly increased the overall ulcer healing rate after ESD and more rapid reduction of ulcer area(P<0.05).The results of subgroup analysis showed that there was no significant difference in ulcer healing rate between vonoprazan and PPI treatment at 4 or 8 weeks after ESD(P>0.05).Vonoprazan significantly increased the rate of postoperative ulcer reduction in H.pylori positive patients compared with PPI(P<0.05).In terms of safety,compared with PPI,vonoprazan reduced the incidence of overall adverse events rate(P<0.05).The difference in the incidence of delayed bleeding and ulcer perforation between vonoprazan and PPIs showed no statistically significant difference.(P>0.05).Conclusion Vonoprazan demonstrated favorable efficacy and safety in the treatment of ESD ulcers,and further economic studies are warranted.

Objective To explore the feasibility of constructing a three-classification bone status screening radiomics model on chest CT images.Methods A total of 371 patients who underwent both chest and abdominal plain CT examinations were retrospec-tively selected and randomly divided into training set(296 cases)and test set(75 cases)in a ratio of 8︰2.Additionally,110 patients were included as external validation set using the same criteria.The 120 kVp abdominal images were transmitted to a quantitative compu-ted tomography(QCT)post-processing workstation to measure the bone mineral density(BMD)of the L1-L2 vertebral bodies.Patients were classified into osteoporosis(OP)group(BMD<80 mg/cm3),osteopenia group(80 mg/cm3≤BMD≤120 mg/cm3)and normal bone mass group(BMD>120 mg/cm3)based on QCT BMD results.The automatic segmentation model was used to segment T10-T12 vertebral trabecular bone on chest CT images and the radiomics models based on random forest(RF)and logistic regres-sion(LR)was established to evaluate BMD,enabling it to simultaneously distinguish OP,osteopenia,and normal bone mass.The diag-nostic performance of the two models were evaluated using metrics such as the area under the curve(AUC),sensitivity and specificity.The DeLong test was used to compare the differences between the two models.Results In the test set,the AUC for differentiating normal bone mass were 0.948 and 0.877 for the RF and LR models,respectively;the AUC for differentiating OP were 0.942 and 0.836,respectively;and the AUC for differentiating osteopenia were 0.871 and 0.688,respectively.The performance comparison results of the models showed that there was no statistically significant difference in AUC(0.966 vs 0.907,P>0.05)between RF model and LR model in the external validation set for distinguishing OP,while there was a statistically significant difference in AUC for distinguishing osteopenia(0.895 vs 0.749,P=0.009)and normal bone mass(0.975 vs 0.906,P=0.023).The RF model performance was superior to the LR model.Conclusion The radiomics model developed based on chest plain CT can be used for opportunistic OP screening with good diagnostic efficacy,and the the model based on the RF classifier outperforms the LR model.