This article provides a systematic interpretation and review of the Society of Critical Care Medicine 2024 Guidelines on Adult ICU Design. Developed based on the Grading of Recommendations Assessment, Development and Evaluation methodology, the guideline address five core themes: ICU layout, room design, infection control, infrastructure, and staff spaces, and put forward 17 evidence-based recommendations, including 5 good practice statements. This article briefly introduces the guideline development methods and evidence characteristics, and focuses on summarizing key recommendations, including high-visibility layouts, single-bed ward settings, natural lighting and noise reduction strategies, integrated infection prevention and control design, remote monitoring, and flexible capacity expansion capabilities. Furthermore, it delves into the applicability and localized implementation pathways within China's healthcare environment, analyzing limitations in terms of evidence quality, specialty applicability, and cost-effectiveness. Furthermore, by integrating the Chinese Guidelines for the Construction and Development of Critical Care Medicine (2025 Edition) and current domestic practices, the article proposes tiered and phased implementation recommendations. This article aims to provide domestic healthcare institutions with a scientific reference that balances international cutting-edge concepts with China's real-world conditions for the construction and renovation of ICUs, thereby promoting the development of intensive care environments centered on patient safety, healthcare worker well-being, and infection control.

Objective To introduce the calculation of the DISO index in multi-dimensional data ranking for disease surveillance, and evaluate its applicability. Methods Using the data from the quality supervision and inspection of infectious disease reporting in Jingzhou City in a certain year as an example, the DISO index was used to rank 16 investigated medical institutions and compared with the TOPSIS method. The consistency between the two evaluation results was analyzed using Spearman correlation. Then, The DISO index from different medical institutions was used to evaluate the ranking of 8 counties (cities, districts). The evaluation indicators for the supervision and inspection included six items: report rate, timely report rate, completeness of report card filling, accuracy of report card filling, consistency rate with network information report, and completeness of valid ID number filling. Results Among the 16 medical institutions, 8 institutions had all six evaluation indicators at 100%. Using the two methods to rank the 16 medical institutions, the two methods showed that the 8 medical institutions with all six evaluation indicators at 100% were ranked first. There was a strong correlation between the rankings of the 16 medical institutions using the two methods (r_s=0.992, P=0.000). The three counties (cities, districts) with all six evaluation indicators at 100% were all ranked first, while country G was ranked seventh and country E was ranked eighth. Conclusion The results of the DISO index and the TOPSIS method were similar in one-dimensional ranking. DISO can be used for multi-dimensional ranking of disease surveillance data and deserves to be promoted and applied.

Objective:To evaluate the anti-reflux effect of digestive tract reconstruction using esophageal-tubular gastric asymmetric anastomosis after radical resection of esophageal and esophagogastric junction cancer.Methods:The main steps were as follows:(1)oblique incision of the lower esophagus;(2)curved incision of the tubular anterior gastric wall;(3)the lower end of the esophagus was anastomosed to the tubular gastric incision with a 90-degree torsion; (4)The anterior wall of the anastomosis was reinforced with a transverse-inverted suture,the posterior wall with a folded suture,and the corners of the gastric stump were buried with sutures.The anastomosis operation time,postoperative complications and postoperative hospital stay were recorded;the reconstructed structure and anti-reflux effect of the anastomosis were observed by digestive tract radiography,gastroscopy and follow-up investigation.Results:The Department of Gastrointestinal and Thoracic Surgery of Huaian First People's Hospital, affiliated to Nanjing Medical University, treated 5 patients of esophagogastric junction cancer and 20 esophageal cancer cases between August 2022 and November 2024, including 19 men and 6 women, with a mean age of (66.7±7.4) years. The mean anastomosis time was (35.4±5.9) minutes, the intraoperative blood loss was (117.6±33.4) ml and the mean postoperative hospital stay was(16.6±5.2) days, with no complications such as anastomotic leakage and bleeding. Postoperative digestive tract radiography (Trendelenburg position)showed that all the patients had no contrast reflux,gastroscopy showed no signs of reflux esophagitis and bile reflux gastritis, the anastomosis showed an inverted whiskers valve-like structure. The median follow-up time was (16.8±6.3) months, and all patients had no reflux symptoms such as acid reflux and belching,and no acid suppressive medication was needed.Conclusion:The esophageal-tubular gastric asymmetric anastomosis is a safe and effective antireflux reconstruction technique.

Objective To investigate the safety parameters of the air-powered electrocautery hook and its advantages in laparoscopic surgery.Methods In pressure trauma experiments,21 healthy New Zealand White Rabbits were randomly divided into three groups.In each group,three sites(liver,intestine,and kidney)were selected from each rabbit,and the air-powered electrocautery hook was used under laparoscopy to apply pressure and time gradients in a cross-combination manner.The three groups of experimental rabbits were dissected at three time points:immediately after application,3 d post-application,and 7 d post-application.Pathological sections were prepared from the corresponding treated sites,and the extent of injury was assessed.In rabbit renal capsule removal experiment,another 20 healthy New Zealand White Rabbits were randomly divided into 2 groups.Renal capsule removal was performed by using an air-powered electrosurgical hook and a conventional electrosurgical hook,respectively,to compare the two groups in terms of surgical time,intraoperative bleeding volume,intraoperative complications,and the number of times of wiping speculum.Results In pressure trauma experiment,except for the intestinal tract at 3 seconds(P=0.060),the histopathological scores under 0.3 MPa pressure were significantly higher than those under 0.1 MPa(P<0.05)and 0.2 MPa(P<0.05)in all the tissues.In the tissue sampling groups at 3 d and 7 d post-surgery,no tissue damage was observed in any tissue at any time point under 0.1 MPa pressure.In rabbit renal capsule removal experiment,the aerodynamic electrocautery group had less intraoperative bleeding volume than the conventional electrocautery group[(2.9±0.5)ml vs.(3.4±0.5)ml,t=-2.280,P=0.035].There were no significant differences between the two groups in terms of surgical time,intraoperative complication rates,and the number of times of wiping speculum(P>0.05).Conclusions The safe pressure range for using the air-powered electrosurgical hook on the surfaces of the kidney and intestinal tract is within 0.2 MPa.Within the safe pressure range,blowing on tissue for 6 seconds or less is relatively safe.Using the air-powered electrosurgical hook in surgeries requiring the separation of loose connective tissue can reduce intraoperative bleeding.

Objective To develop and validate a deep learning-based segmentation model for low-dose cervical spine X-ray,aiming to address the insufficient segmentation accuracy in low-dose protocols while balancing radiation protection and diagnostic accuracy.Methods A total of 1 363 patients cervical spine X-ray images data were collected.A dose-attenuation mathematical simulation sys-tem was constructed to generate 14 122 dynamic low-dose cervical spine images incorporating quantum noise,contrast degradation,and blur artifacts.A neural network model was developed for automated segmentation of low-dose cervical spine X-ray using this dataset.Results Within the dose range of 50%to 7.5%,the average reults of automatic segmentation by the neural network model and manual segmentation for each group were as follows:50%dose group,intersection over union(IoU)=0.98 vs 0.93(P=0.707)and Dice coefficient(Dice)=0.99 vs 0.96(P=0.749);10%dose group,IoU=0.97 vs 0.87(P=0.201)and Dice=0.99 vs 0.93(P=0.219);7.5%dose group,IoU=0.97 vs 0.67(P<0.01)and Dice=0.98 vs 0.80(P<0.01).Conclusion The developed deep learning model achieved robust cervical spine segmentation(IoU>0.96,Dice>0.98)below diagnostic dose thresholds[peak signal-to-noise ratio(PSNR)<38 dB,structural similarity index(SSIM)<0.65].Under ultra-low-dose conditions(PSNR=27.710 dB,SSIM=0.274),it demonstrated a 44.78%IoU improvement and 22.5%Dice improvement over manual segmentation.This model enables minimal radia-tion exposure while preserving diagnostic performance,confirming its theoretical feasibility for low-dose X-ray image analysis and clinical research potential.

Objective To develop and validate a deep learning-based segmentation model for low-dose cervical spine X-ray,aiming to address the insufficient segmentation accuracy in low-dose protocols while balancing radiation protection and diagnostic accuracy.Methods A total of 1 363 patients cervical spine X-ray images data were collected.A dose-attenuation mathematical simulation sys-tem was constructed to generate 14 122 dynamic low-dose cervical spine images incorporating quantum noise,contrast degradation,and blur artifacts.A neural network model was developed for automated segmentation of low-dose cervical spine X-ray using this dataset.Results Within the dose range of 50%to 7.5%,the average reults of automatic segmentation by the neural network model and manual segmentation for each group were as follows:50%dose group,intersection over union(IoU)=0.98 vs 0.93(P=0.707)and Dice coefficient(Dice)=0.99 vs 0.96(P=0.749);10%dose group,IoU=0.97 vs 0.87(P=0.201)and Dice=0.99 vs 0.93(P=0.219);7.5%dose group,IoU=0.97 vs 0.67(P<0.01)and Dice=0.98 vs 0.80(P<0.01).Conclusion The developed deep learning model achieved robust cervical spine segmentation(IoU>0.96,Dice>0.98)below diagnostic dose thresholds[peak signal-to-noise ratio(PSNR)<38 dB,structural similarity index(SSIM)<0.65].Under ultra-low-dose conditions(PSNR=27.710 dB,SSIM=0.274),it demonstrated a 44.78%IoU improvement and 22.5%Dice improvement over manual segmentation.This model enables minimal radia-tion exposure while preserving diagnostic performance,confirming its theoretical feasibility for low-dose X-ray image analysis and clinical research potential.

Objective To explore the role and mechanism of RNA m6A methyltransferase Wilms'tumor 1-associated protein(WTAP)in epithelial-mesenchymal transition(EMT)of glioblastoma cells and its association with transcription factor JUNB.Methods(1)Based on the Cancer Genome Atlas(TCGA)and Genotype-Tissue Expression(GTEx)databases,the expression levels of transforming growth factor β(TGF-β),WTAP,and JUNB in glioblastoma multiforme(GBM)and normal brain tissues were analyzed,as well as their diagnostic and prognostic values for GBM.The correlation of TGF-β,WTAP,and JUNB with gliomas of different WHO grades was analyzed using the Chinese Glioma Genome Atlas(CGGA)database.Spearman correlation analysis was performed to assess the correlation between TGF-β and m6A methyltransferases.(2)An EMT model was established in human astrocytoma U87-MG cells through TGF-β1 induction.qRT-PCR and Western blotting were employed to detect the expression levels of WTAP,JUNB,matrix metalloproteinase 2(MMP2),and N-cadherin.The migration capacity of U87-MG cells was evaluated by wound-healing and Transwell assays.An m6A RNA methylation quantification kit(colorimetric)was used to detect RNA m6A methylation modification levels.A stable cell line with low expression of WTAP was constructed to investigate the effects of WTAP knockdown on the migration ability of U87-MG cells,as well as the expression of JUNB.(3)A protein-protein interaction network was constructed using STRING database and GeneMANIA database,followed by gene ontology(GO)and KEGG pathway enrichment analyses to explore the biological processes,molecular functions,cellular components,and signaling pathways potentially involved in TGF-β/WTAP/JUNB.Gene set enrichment analysis(GSEA)was performed on JUNB-related genes to investigate their potential downstream signaling pathways.Results(1)The expression levels of TGF-β,WTAP,and JUNB were significantly higher in GBM(P<0.001),positively correlated with WHO grades of glioma(P<0.001).Glioma patients with high expression of all three genes had shorter overall and disease-free survival(P<0.001).Spearman analysis showed that the expression of TGF-β in GBM was positively correlated with WTAP(r=0.175,P=0.023),but no significant correlation with other m6A methyltransferases(P>0.05).(2)After TGF-β1 treatment,the level of m6A methylation modification of total RNA in U87-MG cells significantly increased(P<0.001).Wound-healing assay and Transwell assay results showed that the migration ability of U87-MG cells was significantly increased after TGF-β1 treatment(P<0.01),while WTAP knockdown significantly reduced the migration ability of U87-MG cells(P<0.01).qRT-PCR and Western blotting results showed that the mRNA and protein expression levels of WTAP,N-Cadherin,MMP2,and JUNB in U87-MG cells were significantly increased after 48 h of TGF-β1 induction(P<0.001),while WTAP knockdown significantly reduced the mRNA and protein expression of JUNB(P<0.001).(3)The TGF-β/WTAP/JUNB-related protein-protein interaction network was constructed,which was primary involved in mRNA modification and EMT.GSEA results showed that JUNB-related signaling pathways were closely associated with glioma malignant progression.Conclusions TGF-β,WTAP,and JUNB are all associated with GBM malignant progression and poor patient prognosis.TGF-β may enhance total RNA m6A modification by promoting the expression of m6A methyltransferase WTAP,and WTAP subsquentaly upregulates transcription factor JUNB,thereby promoting EMT and malignant progression of GBM.

Objective:To construct a risk prediction model of hyperuricemia (HUA) for community-dwelling residents.Methods:This cross-sectional study was conducted from March to November 2020. A total of 1 967 residents in the Nanzhai community of Taiyuan city were selected by stratified sampling method as study subjects, among whom 1 555 (80%) subjects served as the training set and the remaining 412 (20%) as the validation set. Blood uric acid was measured in all subjects and level>420 mmol/L was defined as HUA. The risk factors of HUA were determined with multivariate logistic regression analysis, and a risk prediction model was constructed. The Hosmer-Lemeshow goodness-of-fit test and the receiver operating characteristic (ROC) curve were used to evaluate the predictive performance of the model.Results:Among the 1 555 residents in the training set, HUA was detected in 285 cases (18.3%). The detection rate in men was significantly higher than that in women [29.8% (220/739) vs. 8.0% (65/816), χ 2=123.17, P<0.05]. Compared to non-HUA group, the waist circumference and BMI, and the proportion of smoking, drinking, staying up late, and prevalence of hypertension and dyslipidemia were significant higher in HUA group. There was significant difference in the frequency of drinking tea, coffee, milk, and eating fruits, as well as the amount of beverages consumed between the two groups ( P<0.05). Multivariate logistic regression analysis showed that high BMI ( OR=1.132, 95 %CI:1.070-1.197, P<0.001), coffee consumption ( OR=1.337, 95 %CI:1.027-1.742, P=0.032), and dyslipidemia ( OR=1.479, 95 %CI:1.049-2.086, P=0.025) were risk factors of HUA, while female sex ( OR=0.213, 95 %CI:0.146-0.390, P<0.001) was protective factor of HUA. When all factors were included in the logistic regression model, gender, BMI, coffee consumption, beverage intake, sodium salt intake, sleep quality, and dyslipidemia ( OR=0.213, 1.113, 1.353, 0.788, 1.320, 0.788, 1.651) were important components of the HUA prediction model. By substituting the constant, these factors, and the regression coefficients into the logistic regression equation, the Logit(P) formula was obtained: Logit(P)=-1.530-1.547×gender+0.107×BMI+0.303×coffee consumption frequency-0.238×sodium salt intake+0.278×beverage intake-0.238×sleep quality+0.502×dyslipidemia. The ROC curve showed an area under the curve ( AUC) of 0.750. The Hosmer-Lemeshow goodness-of-fit test: P=0.632, indicating a satisfactory fit. When the formula was applied to the validation set for internal validation, the AUC was 0.745. Conclusion:The occurrence of HUA is influenced by multiple factors. The prediction model constructed in this study has good prediction performance,which may be used to predict the risk of HUA in primary care settings for community-dwelling residents.

ObjectiveTraditional Chinese medicine (TCM) constitutes a valuable cultural heritage and an important source of antitumor compounds. Poria (Poria cocos (Schw.) Wolf), the dried sclerotium of a polyporaceae fungus, was first documented in Shennong’s Classic of Materia Medica and has been used therapeutically and dietarily in China for millennia. Traditionally recognized for its diuretic, spleen-tonifying, and sedative properties, modern pharmacological studies confirm that Poria exhibits antioxidant, anti-inflammatory, antibacterial, and antitumor activities. Pachymic acid (PA; a triterpenoid with the chemical structure 3β-acetyloxy-16α-hydroxy-lanosta-8,24(31)-dien-21-oic acid), isolated from Poria, is a principal bioactive constituent. Emerging evidence indicates PA exerts antitumor effects through multiple mechanisms, though these remain incompletely characterized. Neuroblastoma (NB), a highly malignant pediatric extracranial solid tumor accounting for 15% of childhood cancer deaths, urgently requires safer therapeutics due to the limitations of current treatments. Although PA shows multi-mechanistic antitumor potential, its efficacy against NB remains uncharacterized. This study systematically investigated the potential molecular targets and mechanisms underlying the anti-NB effects of PA by integrating network pharmacology-based target prediction with experimental validation of multi-target interactions through molecular docking, dynamic simulations, and in vitro assays, aimed to establish a novel perspective on PA’s antitumor activity and explore its potential clinical implications for NB treatment by integrating computational predictions with biological assays. MethodsThis study employed network pharmacology to identify potential targets of PA in NB, followed by validation using molecular docking, molecular dynamics (MD) simulations, MM/PBSA free energy analysis, RT-qPCR and Western blot experiments. Network pharmacology analysis included target screening via TCMSP, GeneCards, DisGeNET, SwissTargetPrediction, SuperPred, and PharmMapper. Subsequently, potential targets were predicted by intersecting the results from these databases via Venn analysis. Following target prediction, topological analysis was performed to identify key targets using Cytoscape software. Molecular docking was conducted using AutoDock Vina, with the binding pocket defined based on crystal structures. MD simulations were performed for 100 ns using GROMACS, and RMSD, RMSF, SASA, and hydrogen bonding dynamics were analyzed. MM/PBSA calculations were carried out to estimate the binding free energy of each protein-ligand complex. In vitro validation included RT-qPCR and Western blot, with GAPDH used as an internal control. ResultsThe CCK-8 assay demonstrated a concentration-dependent inhibitory effect of PA on NB cell viability. GO analysis suggested that the anti-NB activity of PA might involve cellular response to chemical stress, vesicle lumen, and protein tyrosine kinase activity. KEGG pathway enrichment analysis suggested that the anti-NB activity of PA might involve the PI3K/AKT, MAPK, and Ras signaling pathways. Molecular docking and MD simulations revealed stable binding interactions between PA and the core target proteins AKT1, EGFR, SRC, and HSP90AA1. RT-qPCR and Western blot analyses further confirmed that PA treatment significantly decreased the mRNA and protein expression of AKT1, EGFR, and SRC while increasing the HSP90AA1 mRNA and protein levels. ConclusionIt was suggested that PA may exert its anti-NB effects by inhibiting AKT1, EGFR, and SRC expression, potentially modulating the PI3K/AKT signaling pathway. These findings provide crucial evidence supporting PA’s development as a therapeutic candidate for NB.

Combined with elastic network model(ENM),the perturbation response scanning(PRS)has emerged as a robust technique for pinpointing allosteric interactions within proteins.Here,we proposed the PRS analysis of drug-target networks(DTNs),which could provide a promising avenue in network medicine.We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework,for drug repurposing of multiple sclerosis(MS).First,the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes.Then,based on topological analysis and functional annotation,the neurotransmission module was identified as the"therapeutic module"of MS.Further,perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis,giving a list of repurposable drugs for MS.Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of se-rotonin 2B receptor(HTR2B).Finally,we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex.These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS.As a useful systematic method,our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.