With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

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.

Objective To explore the effect of remote ischemic preconditioning (RIPC) on preoperative heart rate variability in patients with heart valves. Methods Patients scheduled to undergo on-pump cardiac valve surgery in the Department of Cardiovascular Surgery, General Hospital of Northern Theater Command, between January and July 2022 were initially enrolled. Eligible patients were randomly assigned at a 1 : 1 ratio to either the RIPC group or the control group. Relevant indicators of heart rate variability [standard deviation of NN interval (SDNN), standard deviation of mean value of NN interval in every five minutes (SDANN), mean square root of difference between consecutive NN intervals (RMSSD), percentage of adjacent RR interval>50 ms (PNN50), low frequency (LF) component, high frequency (HF) component and LF/HF] at 8 hours in the morning on the surgical day between two groups were compared. Results A total of 118 patients were initially assessed. After screening, 58 patients were excluded, and 60 patients provided written informed consent and were enrolled in the trial, with 30 allocated to the RIPC group and 30 to the control group. Seven patients in the control group and 5 patients in the RIPC group were subsequently excluded due to missing heart rate variability data resulting from cancelled operations. Finally, 23 patients in the control group and 25 patients in the RIPC group were included in the analysis. There was no statistical difference in baseline characteristics between the two groups, and there was no significant difference in heart rate variability 24 hours before intervention (P>0.05). After the intervention measures were taken, the comparison of the results of heart rate variability at 8 hours on the day of operation showed that SDNN and SDANN of patients in the RIPC group were higher than those in the control group, with statistical differences (P<0.05). Conclusion RIPC can stabilize the preoperative heart rate variability of patients undergoing cardiac valve surgery.

Background and aims The mechanism of cholestatic liver injury (CLI) is unclear, and effective therapies are lacking. While peroxisome proliferator-activated receptor alpha (PPARα) agonists show potential hepatoprotective effect and pyroptosis is implicated in hepatocellular damage, how PPARα activation mitigates lithocholic acid (LCA)-induced pyroptosis remains unknown. Methods The hepatoprotective effect of PPARα agonists was evaluated in a mouse model of intrahepatic cholestasis induced by LCA. Liver injury was assessed via serum biochemistry, hematoxylin and eosin and TUNEL staining, and electron microscopy. Pyroptosis pathways were analyzed using real-time quantitative polymerase chain reaction, Western blot, and co-immunoprecipitation. Results Combined morphological, histopathological, and biochemical analyses confirmed that PPARα activation protects against CLI. Compared with LCA treatment alone, PPARα activation significantly attenuated the elevation of serum lactate dehydrogenase (LDH), the increased TUNEL-positive cells, and the formation of hepatocyte membrane pores. Mechanistically, PPARα activation suppressed both NOD-like receptor protein 3 (NLRP3) inflammasome-mediated pyroptosis and apoptosis protease-activating factor-1 (APAF-1)/CASPASE-3/GSDME-mediated pyroptosis. Furthermore, PPARα agonist pretreatment inhibited activation of the nuclear factor-kappa B (NF-κB) and forkhead box O1 (FOXO1) signaling pathways. Conclusions PPARα protects against LCA-induced CLI by inhibiting both NLRP3 inflammasome-mediated pyroptosis associated with NF-κB and APAF-1/CASPASE-3/GSDME-mediated pyroptosis associated with the FOXO1 signaling pathway.

Skeletal muscle atrophy refers to a pathological condition characterized by muscle fiber atrophy as well as decreased muscle mass and muscle strength induced by various predisposing factors. It falls under the category of “flaccidity syndrome” in traditional Chinese medicine， and its pathogenesis is mainly associated with disturbed protein homeostasis， mitochondrial dysfunction and oxidative stress injury. Active ingredients of traditional Chinese medicine exerts synergistic regulatory effects via multiple pathways， thus possessing unique advantages in the clinical prevention and treatment of skeletal muscle atrophy. This paper reviews the mechanisms by which active ingredients of traditional Chinese medicine alleviate skeletal muscle atrophy. Existing studies have demonstrated that such active ingredients can ameliorate skeletal muscle atrophy through multiple approaches： regulating protein metabolic balance （geniposide， matrine， schisandrin A， etc.） and oxidative stress （astragaloside Ⅳ， Gastrodia elata polysaccharide， Angelica sinensis polysaccharide， etc.）， improving mitochondrial function （parthenolide， berberine， curcumin， etc.）， facilitating myogenesis and myogenic differentiation （cucurbitacin Ⅱb， saikosaponin A， saikosaponin D， etc.）， suppressing inflammatory response （ursolic acid， triptolide， emodin， etc.）， ameliorating insulin resistance （akebiasaponin D， etc.）. In the future， active ingredients of traditional Chinese medicine are expected to achieve breakthroughs in clinical treatment for skeletal muscle atrophy， providing novel ideas and strategies for the prevention and treatment of degenerative disorders.

Objective: To analyze the demographic evolution of China over the forthcoming decade (2026-2035) and to systematically evaluate its potential implications for voluntary blood donation practices and the equilibrium of clinical blood supply and demand. Methods: Leveraging comprehensive blood collection and utilization data from 2021 to 2025 at the national, provincial (Shandong), and municipal (Zibo) levels, we identified and examined critical determinants influencing blood management systems. The DeepSeek-V3.2 large language model was deployed to project future population age structures, and to generate quantitative estimates for hospitalization volumes, clinical blood requirements, available blood supply, and donation frequencies for the target years 2030 and 2035, thereby furnishing an evidence base for strategic planning and priority-setting. Results: DeepSeek-derived projections indicate that the proportion of China's population aged 60 years and above will surpass 27% (370 million/1 380 million) by 2030 and exceed 30% (400 million/1 350 million) by 2035, signaling a marked acceleration in population aging. This demographic shift is projected to reduce the proportion of the national population eligible to donate blood from 59.2% (835 million out of 1.41 billion) to 52% (710 million out of 1.36 billion), while the demand for blood is expected to increase by 87.8% relative to 2024, rising from 26.927 million units to 50.56 million units. Sustaining blood supply-demand balance will necessitate progressive annual increases in donation rates. Under prevailing policy frameworks, the required blood donation rate among the eligible population in Shandong Province would need to rise by 122.57% by 2035 [from 20.07‰ (1.1641 million person-times/58 million people) to 44.67‰ (2.189 million person-times/49 million people)] to potentially satisfy projected clinical requirements. Conclusion: By integrating DeepSeek-V3.2, AI predictive models, and blood donation incentive measures, it is possible to monitor population demographics, forecast clinical blood demand, manage blood supplies, and ensure the long-term sustainability of clinical blood availability. It must be acknowledged, however, that the present analysis is constrained by a limited data foundation (comprising only five annual observation points); accordingly, the projections should be interpreted as directional trend indicators or methodological illustrations rather than definitive quantitative forecasts.

Objective To evaluate the application effect of modified jejunostomy in thoracoscopic Ivor-Lewis esophagectomy. Methods A retrospective analysis of patients who underwent Ivor-Lewis esophagectomy for middle and lower esophageal cancer from 2017 to 2023 in Department of Cardiothoracic Surgery, Anqing Municipal Hospital was performed. The patients from 2017 to 2020 receiving "C+I" in the upper jejunum according to the "C+I" model, with fistula fixed with only two purse-string sutures and the abdominal wall were allocated into a group A. The patients from 2021 to 2023, on the basis of "C+I" suture, with the jejunum and abdominal wall fixed with 3-0 absorbable thread for 1-2 needles at the proximal or distal end of the fistula 10-15 mm, and the upper jejunum and abdominal wall fixed into "curtain" were allocated into a group B. The operation time, jejunostomy time, postoperative pathological stage, and enteral nutrition-related complications such as the incidence of incomplete intestinal obstruction, closed loop intestinal obstruction and intestinal volvulus requiring secondary surgery, skin redness and swelling of intestinal fluid leakage, stoma tube blockage, and accidental extubation were compared between the two groups. Results A total of 243 patients were enrolled in this study. The group A consisted of 118 patients (72 males, 46 females) with a mean age of (64.58±6.30) years. The group B consisted of 125 patients (76 males, 49 females) with a mean age of (65.11±6.81) years. All patients successfully underwent thoracoscopic Ivor-Lewis esophagectomy without perioperative mortality. There were no statistical differences between the two groups in operative time, jejunostomy creation time, or the rate of feeding tube occlusion (P>0.05). However, statistical differences were observed in the incidence of incomplete intestinal obstruction (P=0.035) and closed-loop intestinal obstruction requiring reoperation (P=0.017). The incidence of complications at the stoma site, such as intestinal fluid leakage and redness/swelling, was significantly higher in the group A (n=36) than that in the group B (n=7) (P<0.001). Conclusion The modified jejunostomy can significantly reduce the incomplete intestinal obstruction, closed loop intestinal obstruction and secondary operation rate after "C+I" jejunostomy, and significantly improve the leakage of intestinal fluid at the stoma and the injury of surrounding skin and soft tissue. Improvements in certain technologies reduce operational difficulties.

This paper summarizes Professor HAN Mingxiang's clinical experience in the use of Zeqi （Euphorbia HelioscopiaL.）. It is believed that Zeqi （Euphorbia HelioscopiaL.） has the effects of promoting qi， relieving water retention and swelling， resolving phlegm， stopping cough， dissipating masses， activating blood， removing stasis， and detoxifying. In clinical practice， Zeqi （Euphorbia HelioscopiaL.） is flexibly applied in the treatment of skin diseases， respiratory diseases， tumors， etc. For instance， in treating psoriasis with the pathogenesis of damp-heat toxin， a compound prescription of Zeqi Decoction （泽漆汤） is formulated. For bronchial asthma with kidney deficiency and water retention， Zeqi Decoction is commonly combined with Wuling Powder （五苓散） in adjusted doses. For lung nodules with a combination of deficiency， phlegm， stasis， and toxin， a Lung Nodule Prescription is proposed. For advanced lung cancer with both qi and yin deficiency and toxin accumulation， Qiyu Sanlong Decoction （芪玉三龙汤） is suggested， and for cancer-related ascites with qi deficiency and water retention， Wuling Powder combined with Zeqi （Euphorbia HelioscopiaL.）is chosen.

Objective To propose a lung artery segmentation method that integrates shape and position prior knowledge, aiming to solve the issues of inaccurate segmentation caused by the high similarity and small size differences between the lung arteries and surrounding tissues in CT images. Methods Based on the three-dimensional U-Net network architecture and relying on the PARSE 2022 database image data, shape and position prior knowledge was introduced to design feature extraction and fusion strategies to enhance the ability of lung artery segmentation. The data of the patients were divided into three groups: a training set, a validation set, and a test set. The performance metrics for evaluating the model included Dice Similarity Coefficient (DSC), sensitivity, accuracy, and Hausdorff distance (HD95). Results The study included lung artery imaging data from 203 patients, including 100 patients in the training set, 30 patients in the validation set, and 73 patients in the test set. Through the backbone network, a rough segmentation of the lung arteries was performed to obtain a complete vascular structure; the branch network integrating shape and position information was used to extract features of small pulmonary arteries, reducing interference from the pulmonary artery trunk and left and right pulmonary arteries. Experimental results showed that the segmentation model based on shape and position prior knowledge had a higher DSC (82.81%±3.20% vs. 80.47%±3.17% vs. 80.36%±3.43%), sensitivity (85.30%±8.04% vs. 80.95%±6.89% vs. 82.82%±7.29%), and accuracy (81.63%±7.53% vs. 81.19%±8.35% vs. 79.36%±8.98%) compared to traditional three-dimensional U-Net and V-Net methods. HD95 could reach (9.52±4.29) mm, which was 6.05 mm shorter than traditional methods, showing excellent performance in segmentation boundaries. Conclusion The lung artery segmentation method based on shape and position prior knowledge can achieve precise segmentation of lung artery vessels and has potential application value in tasks such as bronchoscopy or percutaneous puncture surgery navigation.