Metabolic dysfunction-associated fatty liver disease （MAFLD） has become one of the most prevalent chronic liver diseases worldwide， posing a serious challenge to public health. In this context， the integration of artificial intelligence （AI）， especially intelligent diagnosis and treatment and digital health interventions based on machine learning， can break through the limitations of traditional methods， realize efficient screening of multi-dimensional data such as key genes， biomarkers， and biochemical metabolites， and achieve revolutionary breakthroughs in risk prediction， subtype identification， and therapeutic effect assessment for MAFLD. This article systematically reviews the ground-breaking application of machine learning models in driving the innovation of clinical diagnosis and precise risk prediction of MAFLD， conducts a comprehensive comparative analysis of digital health practice cases of MAFLD in China and globally， and deeply analyzes their advantages and limitations in terms of research subjects， interventions， and management team. Studies have shown that the deep integration of digital health and long-term management of MAFLD is becoming the key engine driving the transformation of disease management modes towards an intelligent， individualized， and precise era， but there are various ethical and technical issues that need to be addressed urgently.

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.

Objective To investigate the interaction relationship among symptoms in middle-aged patients during the recovery period of stroke and explore its correlation with rehabilitation confidence,providing a reference for the implementation of precise rehabilitation nursing.Methods A cross-sectional study was conducted,and 365 middle-aged patients in the recovery period of stroke who were hospitalized in 4 tertiary general hospitals in Wuhan from April 20 to August 31,2024 were conveniently selected as the subjects of the investigation.Data were collected using the General Information Questionnaire,Stroke Symptom Experience Scale,and Confidence after Stroke Measure Questionnaire.Symptom network analysis was conducted using R software,and a network structure model of symptoms-rehabilitation confidence was constructed;meanwhile,the stability of the network structure was evaluated.Results Finally,350 middle-aged stroke patients in the recovery period were included.The most common symptom was"limb weakness"(81.1％).Symptom network analysis showed that"limited limb movement"was the core symptom(rs=1.118).The symptoms strongly associated with recovery confidence were"limited physical movement","annoyance at not being able to do what you want to do"and"slow reaction times".Stability tests suggest that the model results are all good.Conclusion Symptoms of middle-aged patients in the recovery period after stroke are interrelated,and the mechanisms by which different symptoms affect rehabilitation confidence are also different.It is recommended that healthcare professionals prioritize interventions based on core symptoms and inter-symptom relationships in order to accurately enhance patient outcomes and improve recovery outcomes.

Objective:This study aimed to identify key genes in endothelial cell (EC) associated with the pathogenesis and progression of human venous malformations (VMs) through bioinformatics analysis, providing potential biomarkers for early screening and targeted therapy of VMs.Methods:A case-control study was conducted using surgically resected tissue specimens from VMs patients at the Third Affiliated Hospital of Zhengzhou University (from September 2021 to September 2023), with malformed venous tissues as the experimental group and distal normal venous tissues as controls. Single-nucleus RNA sequencing (snRNA-seq) was performed on paired experimental and control samples from four VM patients. High-dimensional weighted gene co-expression network analysis (hdWGCNA), combined with gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), and protein-protein interaction (PPI) network analysis, identified critical genes. Validation experiments included 15 additional VM cases and controls using reverse transcription quantitative polymerase chain reaction (RT-qPCR), immunohistochemistry (IHC), and Western blot.Results:A total of 55 430 nuclei were captured using snRNA-seq, with 30 391 nuclei from the experimental group and 25 039 nuclei from the control group. Cluster analysis identified 22 distinct cell populations, which were annotated into 8 cell types. hdWGCNA revealed four modules associated with invasion, which were enriched in angiogenesis, integrin signaling, and cell adhesion according to GO analysis. KEGG pathway analysis indicated that the PI3K-AKT signaling pathway and focal adhesion are key regulatory mechanisms. PPI network analysis combined with cytoscape identified EGFL7, TEK, and FLT1 as key genes. RT-qPCR results demonstrated that the relative mRNA expression levels of these three genes in the experimental group (6.66±2.31, 1.86±0.62, 3.49±0.58) were significantly higher than those in the control group (1.05±0.14, 1.00±0.14, 1.06±0.25), with statistically significant differences ( t=9.37, 4.27, 11.20, P<0.05). Immunohistochemical analysis showed that the relative protein expression levels of these three genes in the cytoplasm of the experimental group (0.84±0.15, 0.68±0.14, 0.85±0.12) were also significantly higher than those in the control group (0.19±0.05, 0.23±0.06, 0.30±0.05), with statistically significant differences ( t=16.62, 5.93, 11.68, P<0.05). Western blot analysis confirmed that the relative protein expression levels of these three genes in the experimental group (0.35±0.04, 0.36±0.09, 0.31±0.04) were significantly higher than those in the control group (0.19±0.01, 0.13±0.02, 0.14±0.04), with statistically significant differences ( t=7.05, 4.61, 5.93, P<0.05). Conclusion:EGFL7, FLT1, and TEK in EC may play crucial roles in the occurrence and invasion of VMs.

Spine fracture and dislocation are common traumatic spinal conditions that often require surgical intervention due to compromised spinal stability. Surgical approaches include anterior, posterior, and combined anterior-posterior spinal procedures. According to the specific surgical requirements, patients may be placed in the prone position or repositioned between prone and supine positions during surgery. Intraoperative repositioning has become an essential step in patient positioning. However, during repositioning, patients with spinal fracture and dislocation are at increased risk for complications such as hemodynamic instability, nerve injury, and pressure injuries to the skin and soft tissue. Notably, due to the instability of the spinal cord, even minor manipulations can further exacerbate the damage, potentially leading to severe outcomes like paraplegia. Although the current clinical guidelines provide instructive recommendations for standard position, there remains no specific protocols for intraoperative repositioning in patients with spine fracture and dislocation. With a concern for the lack of clinical studies on positioning techniques, risk prevention, and operational norms for special patients, no applicable guidelines or standards are available. A consensus was required to provide clinical reference, meet the requirements of surgical treatment, and minimize the safety risks of patients caused by improper placement of positions. Professional Committee of Operating Room Nursing of Shaanxi Nursing Association organized experts in nursing management and operating room nursing from major hospitals across China to formulate Expert consensus on intraoperative repositioning for patients with spinal fracture and dislocation ( version 2025). The consensus provides 11 recommendations covering pre-repositioning preparation, intraoperative maneuvers, and post-repositioning observation, aiming to provide references for clinical standardization of the intraoperative repositioning process and protection of patients′ safety.

Objective:To investigate the underlying mechanism behind the significant reduction in intracellular virus loads after respiratory syncytial virus (RSV) and influenza viruses infect respiratory epithelial cells overexpressing the chemokine (C-C motif) receptor 1 (CCR1).Methods:A549 cells were infected with respiratory syncytial virus (RSV), influenza A viruses (H1N1, H3N2), or influenza B virus (FluB), and the expression of chemokine (C-C motif) ligand 5 (CCL5) and CCR1 were detected by qRT-PCR, ELISA, and Western blot. After overexpressing or knocking down CCR1 in A549 cells, these cells were infected with RSV, H1N1, H3N2, or FluB, and the expression of CCR1, heat shock protein 90 (HSP90), cyclin-dependent kinase 1 (CDK1), and viral proteins were detected by qRT-PCR and Western blot. After stimulating CCR1-overexpressed A549 cells with CCL5, Western blot was used to detect the expression of HSP90 and CDK1, and co-immunoprecipitation was used to detect the interaction between HSP90 and CCR1. CCR1 -/- mice were infected with RSV, H1N1, or H3N2 to observe the changes in the expression of HSP90, CDK1, and viral proteins with Western blot, and the inflammation in lung tissues with HE staining. One-way analysis of variance and t test were used for statistical analysis. Results:RSV, H1N1, H3N2, and FluB infections induced high expression of CCL5 in A549 cells ( P<0.05), but the expression of CCR1 showed an overall downward trend. After activating its receptor CCR1, CCL5 inhibited the replication of RSV and influenza viruses by suppressing the activity of HSP90 ( P<0.05). The experiments conducted on CCR1 -/- mice confirmed that the enhanced activity of HSP90 facilitated the replication of RSV and influenza viruses. Conclusion:RSV and influenza viruses may reduce the binding of CCL5 to CCR1 by downregulating the expression of CCR1 in respiratory epithelial cells, thereby weakening the inhibitory effect of CCR1 on HSP90 activity, which enables them to evade host immune defense.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

ObjectiveTo monitor the real-time changes in ammonia concentration in the laboratory animal facility environment before, during, and after the air conditioning system stops supplying air, so as to provide a basis and reference for developing emergency plans for the shutdown of the air conditioning system. MethodsThe laboratory animal facilities of the Wuhan Institute of Biological Products were used as the research object. Ammonia concentration detectors were used to monitor ammonia concentration continuously in the environment of conventional rabbit production facility, SPF hamster production facility, and SPF guinea pig experimental facility before and after the passive shutdown due to repairs and active maintenance shutdown of the air conditioning system, as well as the time for the ammonia concentration to return to daily levels after resuming air supply. ResultsUnder both shutdown modes of the air conditioning system, the trend of ammonia concentration changes in different laboratory animal facilities was consistent, showing a rapid increase after shutdown and a rapid decrease after resuming air supply. Under active maintenance shutdown, the maximum ammonia concentrations in the conventional rabbit production facilities, SPF hamster production facilities, and SPF guinea pig experimental facilities were 9.81 mg/m³, 14.27 mg/m³, and 6.98 mg/m³, respectively. Within 12 minutes after resuming air supply, ammonia concentration could return to normal daily levels. Under passive long-term shutdown, ammonia concentration value was positively correlated with the duration of air supply suspension. As the shutdown duration increased, ammonia concentration continued to increase. The maximum ammonia concentration values in the three facilities occurred at 88 minutes (38.06 mg/m³), 40 minutes (18.43 mg/m³), and 34 minutes (15.61 mg/m³) after air supply suspension, respectively.Within 11 minutes after resuming air supply, ammonia concentration could return to normal daily levels. ConclusionShutdown of the air conditioning system causes a rapid increase in ammonia concentration in laboratory animal facilities, and the rise in ammonia concentration is positively correlated with the duration of air supply suspension. Therefore, when an emergency shutdown of the air-conditioning system is required due to maintenance or other reasons, backup fans should be provided in accordance with the requirements of GB 50447-2008 "Architectural and Technical Code for Laboratory Animal Facilities". Older facilities should make adequate preparations and develop a scientifically sound emergency plan.

Objective: To investigate the therapeutic effect of patchouli alcohol on mice with lung-heat syndrome based on the phosphoinositide 3-kinase(PI3K)/protein kinase B(Akt)/nuclear factor-kappa B(NF-κB) signaling pathway. Methods: First, network pharmacology was used to predict the potential targets of patchouli alcohol in the treatment of lung-heat syndrome, and a "component-disease-key target" network was constructed for pathway analysis. Then, 40 BALB/c mice were assigned to the normal, lung-heat model, honeysuckle, and low-dose and high-dose patchouli alcohol groups. All groups, except the blank group, were intranasally infected with 50 μL (103 TCID50) of influenza virus solution. After two hours of infection, mice were treated once a day for seven consecutive days. The therapeutic mechanism of patchouli alcohol was explored by measuring pulmonary inflammatory factors, the PI3K/Akt/NF-κB pathway, hypothalamic fever markers (PGE2, cAMP, cGMP levels), rectal temperature, and tissue energy metabolism. Results: Network pharmacology identified 135 target genes related to patchouli alcohol and lung-heat syndrome, with the key targets being STAT3, H1F1A, and NF-κB1. In animal experiments, patchouli alcohol significantly alleviated influenza virus-induced lung inflammatory damage in mice with lung-heat syndrome, inhibited the expression of TNF-α and IL-6 in lung tissues(P<0.01), and suppressed the activation of the PI3K/Akt/NF-κB pathway. It also reduced hypothalamic levels of PGE2 and cAMP(P<0.01), suppressed the increase in rectal temperature, significantly decreased liver glycogen and pyruvate levels(P<0.01), and increased the activities of SDH, LDH, and Na+ -K+ -ATPase in the liver(P<0.01) Conclusion Patchouli alcohol improves the symptoms of lung-heat syndrome in mice by inhibiting the activation of the PI3K/Akt/NF-κB pathway, reducing proinflammatory cytokines and inflammatory damage, and regulating hypothalamic fever markers and energy metabolism.

Objective To explore risk factors for cardiac valve calcification (CVC) in maintenance hemodialysis (MHD) patients and evaluate its impact on cardiovascular events and mortality. Methods Retrospective selection of 223 patients with MHD admitted to the Department of Nephrology of Jinshan Hospital, Fudan University from June 30, 2019 to June 30, 2024, and enrollment completed within one week of June 30, 2019. Patients were divided into CVC and non-CVC groups. Baseline data and 5-year follow-up data were collected. The binary logistic regression analysis was performed to explore the risk factors for CVC. Kaplan-Meier survival curve was used to analyze the survival rate of patients. Cox proportional hazard regression model was applied to evaluate the impact of CVC on the survival rates of MHD patients. Results Totally, 223 MHD patients with an average age of (58.4±13.5) years and an average dialysis duration of (64.0±55.4) months were involved. Among them, 136(61.0%) were males, 117(52.5%) were complicated with CVC. Age, dialysis duration, diabetic kidney disease (DKD), the serum corrected total calcium and phosphate, intact parathyroid hormone (iPTH), high-sensitive C-reactive protein (hsCRP), and homocysteine (Hcy) were independent related factors for CVC (P＜0.05). Both all-cause mortality (46.6% vs 28.7%) and cardiovascular mortality (33.3% vs 16.0%) were significantly higher in the CVC group than those in the non-CVC group (P＜0.01). Conclusions Age, dialysis duration, the primary disease, calcium and phosphate, and inflammation- and nutrition-related serum indicators are associated with CVC in MHD patients. CVC significantly increases mortality risk of MHD patients.