AIM: To compare and analyze the efficacy of femtosecond laser-assisted in situ keratomileusis(FS-LASIK)with small incision lenticule extraction(SMILE)in the treatment of moderate myopia.METHODS:Retrospective study. A total of 100 patients(100 eyes)with moderate myopia admitted to our hospital from August 2022 to October 2024 were selected(all the data of the right eye were taken for study). The 52 cases in FS-LASIK group received FS-LASIK, while the 48 cases in SMILE group received SMILE. The patients were followed up for 6 mo, the visual recovery, spherical equivalent, corneal curvature, corneal Q value, central corneal thickness, corneal volume, high-order aberrations, corneal biomechanical parameters and incidence of complications were compared between the two groups.RESULTS: At 3 and 6 mo after surgery, the uncorrected visual acuity(UCVA)and spherical equivalent of both groups increased compared to before surgery(all P<0.05). At 6 mo after surgery, both groups showed a decrease in corneal curvature, central corneal thickness, and corneal volume, with the FS-LASIK group having a lower corneal volume; both groups showed a great increase in Q values, with the FS-LASIK group having a higher Q value(all P<0.001); the total high-order aberration, spherical aberration, and trefoil aberration all increased in both groups, with higher values observed in the FS-LASIK group(all P<0.001); the integrated radius(IR), inverse concave radius(ICR)and deformation amplitude ratio 2(DAR2)were all increased, while the stiffness parameter at first applanation(SP-A1), the highest concavity radius(HC-Radius)and the ambrosio's relational thickness to the horizontal profile(ARTh)were all decreased in both groups(all P<0.001). There was no statistical difference in the incidence of complications between two groups(P>0.05).CONCLUSION: Both FS-LASIK and SMILE can help improve the visual quality of patients with moderate myopia, and their early postoperative corneal morphological changes have their own characteristics. In addition, patients who receive FS-LASIK have larger corneal Q value and high-order aberrations after surgery.

Pituitary adenoma is a common intracranial tumor, and endoscopic endonasal surgery has become one of its primary treatment modalities. Intraoperative magnetic resonance imaging (iMRI) technology can provide surgeons with real-time imaging during surgery, significantly enhancing surgical precision and safety. This case report retrospectively analyzes a case of recurrent pituitary adenoma treated at the Department of Neurosurgery, Huashan Hospital, Fudan University. During endoscopic endonasal surgery, the iMRI revealed residual tumor tissue located above the scar from previous surgery. With the aid of neuronavigation, the surgeon precisely identified and incised the proliferative fibrous tissue that had been misidentified as the diaphragma sellae, successfully removing the concealed tumor and achieving gross total resection. Postoperatively, the patient experienced marked improvement in visual acuity, preserved normal pituitary function, and had no cerebrospinal fluid leakage. Based on this case and relevant literature, this paper discusses the advantages of iMRI in endoscopic endonasal surgery and its potential to improve patient outcomes, aiming to provide reference and guidance for clinical practice.

Objective To explore the application of artificial intelligence (AI) in the standardized training of thoracic surgery residents, specifically in enhancing clinical skills and anatomical understanding through AI-assisted lung nodule identification and lung segment anatomy teaching. Methods Thoracic surgery residents undergoing standardized training at Peking Union Medical College Hospital from September 2023 to September 2024 were selected. They were randomly assigned to a trial group and a control group using a random number table. The trial group used AI-assisted three-dimensional reconstruction technology for lung nodule identification, while the control group used conventional chest CT images. After basic teaching and self-practice, the ability to identify lung nodules on the same patient CT images was evaluated, and feedback was collected through questionnaires. Results A total of 72 residents participated in the study, including 30 (41.7%) males and 42 (58.3%) females, with an average age of (24.0±3.0) years. The trial group showed significantly better overall diagnostic accuracy for lung nodules (91.9% vs. 73.3%) and lung segment identification (100.0% vs. 83.70%) compared to the control group, and the reading time was significantly shorter [ (118.5±10.5) s vs. (332.1±20.2) s, P<0.01]. Questionnaire results indicated that 94.4% of the residents had a positive attitude toward AI technology, and 91.7% believed that it improved diagnostic accuracy. Conclusion AI-assisted teaching significantly improves thoracic surgery residents’ ability to read images and clinical thinking, providing a new direction for the reform of standardized training.

Objective:To explore the molecular epidemiological characteristics of human metapneumovirus (HMPV) in children with acute respiratory infection (ARI) in Beijing from 2023 to 2024.Methods:In the longitudinal study, 9 834 children with ARI were enrolled from August 2023 to December 2024, including the influenza-like illness (ILI) group from emergency and outpatient department receiving influenza virus (Flu) and HMPV test and the ARI inpatient group for 13 common respiratory pathogen screening test including HMPV, Flu, respiratory syncytial virus, and so on. All respiratory samples positive with HMPV were genotyped by amplifying and sequencing of G gene and further phylogenetic analysis. The χ2 test and Wilcoxon rank-sum test were used to compare the positive rate and basic clinical data of the 2 groups. Results:Among 9 834 enrolled patient, there were 5 276 male and 4 558 female children, with age 5.4 (1.9, 8.2) years. In ILI group of 1 460 patients, there were 83 cases (5.7%) positive for HMPV, with the age 4.9 (3.6, 6.6) years and children under 6.0 years old 59 cases (71.1%). Among 8 374 ARI inpatients, there were 256 cases (3.1%) positive for HMPV, with age 3.5 (1.3, 6.4) years and children under 6.0 years old 188 cases (73.4%). The HMPV positive rate and the age of children positive for HMPV in ARI inpatient group were significantly lower than that in ILI group (both P<0.001). In December, 2024, the HMPV positive rates of ILI and ARI inpatient group (21.3% (17/80), 15.0% (47/314)) were significantly higher than the total positive rates of each group (both P<0.001). Among 279 subtyped specimens, there were 155 cases (55.6%) belonging to genotype A and 124 cases (44.4%) belonging to genotype B. Sub-lineage A2.2.2 containing 111nt-insertions was predominate one in 2023 with positive ratio 89.2% (91/102), and B2 was predominate in 2024 with positive ratio 64.4% (114/177). Conclusions:From 2023 to 2024, the positive rate of HMPV in the ILI group was higher than that in the ARI inpatient group, suggesting a common epidemic of HMPV infection. Children positive for HMPV in the ARI inpatient group were younger than that in the ILI group. A severe epidemic of HMPV was observed in the winter of 2024, which requires attention. Sub-lineage A2.2.2 with 111nt-duplicate insertions and B2 were the predominant epidemic strains in 2023 and 2024, respectively.

Objective:To explore the related risk factors of neonatal necrotizing enterocolitis (NEC) by constructing and comparing nine regression models.Methods:All NEC patients admitted to the neonatal internal medicine department, neonatal surgery department, and neonatal intensive care unit of Shanxi Provincial Children's Hospital (Shanxi Provincial Maternity and Child Health Center) from 2020 to 2022 were included as the case group. A control group consisted of children admitted during the same period based on the inclusion and exclusion criteria. The NEC data collected were used for feature selection by using the Boruta algorithm. Logistic regression, multi-decision tree gradient boosting, efficient gradient one-sided sampling, random forest, decision tree, gradient boosting decision tree (GBDT), neural network, support vector machine, and K-nearest neighbor models were constructed. The optimal model was selected through rigorous comparison and Shap explainable analysis was performed on the GBDT model.Results:Thirteen key factors were identified through screening for nine regression models construction. After strict comparison and analysis, the GBDT model showed higher stability compared with other eight regression models. In the validation set, the area under the receiver operating characteristic curve of the GBDT model was 0.958, with an accuracy of 0.925, and sensitivity and specificity of 0.827 and 0.950, respectively. Shap explainable analysis on the GBDT model revealed that suffering from anemia, non-invasive ventilator use, procalcitonin use, premature birth, and low birth weight increased the risk for NEC, while breastfeeding and probiotics decreased the risk for NEC.Conclusion:This study identified the risk factors and protective factors for NEC by using the GBDT model, which provided evidnce for the prevention and treatment of NEC.

Objective To construct and verify a risk prediction model of emergence agitation in patients undergoing thoracoscopic radical resection of lung cancer,and to screen the optimal model by using machine learning algorithm,so as to provide references for clinical formulation of a nursing risk management plan.Methods The convenience sampling method was used to retrospectively select 476 patients who underwent thoracoscopic radical resection of lung cancer in a tertiary hospital in Hangzhou,Zhejiang Province from January to December 2023 as a construction group.Logistic regression,decision tree,random forest and naive Bayesian model were constructed by SPSS 29.0 and R 4.3.0 software.The prediction performance of each model was compared by accuracy,precision,recall,F1 score and area under the receiver operating characteristic curve,and the optimal model was screened.From January to June 2024,204 patients in the unit were prospectively selected as the research subjects of an external validation group.The discrimination and calibration of the optimal model were evaluated by AUC value and calibration curve.Results A total of 680 patients completed the survey.All 4 models showed that multimodal analgesia,thoracic drainage tube type,pain score,tracheal intubation type,state anxiety and catheter indwelling time were the influencing factors of emergence agitation in patients undergoing thoracoscopic radical resection of lung cancer(P＜0.05).The 4 risk prediction models showed that the random forest prediction model had the best comprehensive performance.The external verification results showed that the AUC value was 0.913,and the calibration curve fitted well with the 45° ideal line.Conclusion Among the 4 risk prediction models,the random forest prediction model has the best performance,which is more suitable for the assessment of the risk of emergence agitation in patients undergoing thoracoscopic radical resection of lung cancer,and has good generalization and clinical application value.

To summarize the nursing experience of a patient who underwent an abandoned liver transplantation combined with associating liver partition and portal vein ligation for staged hepatectomy.The main points of nursing included the establishment of a multidisciplinary team before surgery to ensure the smooth progress of the surgery,intraoperative preservation of the abandoned liver and healthcare collaboration for precise portal vein pressure monitoring,postoperative implementation of capacity management for ensuring perfusion of abandoned liver,dynamic monitoring of abandoned liver hyperplasia and prevention of small liver syndrome,individualized immune management and prevention of acute rejection reactions,nutritional support and exercise rehabilitation,strengthening protection and isolation strategies to comprehensively reduce the risk of infection.After treatment and nursing,the patient was discharged on the 28th of surgery.

Approximately 30%-40% of epilepsy patients do not respond well to adequate anti-seizure medications (ASMs), a condition known as pharmacoresistant epilepsy. The management of pharmacoresistant epilepsy remains an intractable issue in the clinic. Its early prediction is important for prevention and diagnosis. However, it still lacks effective predictors and approaches. Here, a classical model of pharmacoresistant temporal lobe epilepsy (TLE) was established to screen pharmacoresistant and pharmaco-responsive individuals by applying phenytoin to amygdaloid-kindled rats. Ictal electroencephalograms (EEGs) recorded before phenytoin treatment were analyzed. Based on ictal EEGs from pharmacoresistant and pharmaco-responsive rats, a convolutional neural network predictive model was constructed to predict pharmacoresistance, and achieved 78% prediction accuracy. We further found the ictal EEGs from pharmacoresistant rats have a lower gamma-band power, which was verified in seizure EEGs from pharmacoresistant TLE patients. Prospectively, therapies targeting the subiculum in those predicted as "pharmacoresistant" individual rats significantly reduced the subsequent occurrence of pharmacoresistance. These results demonstrate a new methodology to predict whether TLE individuals become resistant to ASMs in a classic pharmacoresistant TLE model. This may be of translational importance for the precise management of pharmacoresistant TLE.
Epilepsy, Temporal Lobe/diagnosis* ; Animals ; Drug Resistant Epilepsy/drug therapy* ; Electroencephalography/methods* ; Rats ; Anticonvulsants/pharmacology* ; Neural Networks, Computer ; Male ; Humans ; Phenytoin/pharmacology* ; Adult ; Disease Models, Animal ; Female ; Rats, Sprague-Dawley ; Young Adult ; Convolutional Neural Networks

The incomplete degradation of tumour cells by macrophages (Mϕ) is a contributing factor to tumour progression and metastasis, and the degradation function of Mϕ is mediated through phagosomes and lysosomes. In our preliminary experiments, we found that overactivation of NADPH oxidase 2 (NOX2) reduced the ability of Mϕ to degrade engulfed tumour cells. Above this, we screened out liquiritin from Glycyrrhiza uralensis Fisch, which can significantly inhibit NOX2 activity and inhibit tumours, to elucidate that suppressing NOX2 can enhance the ability of Mϕ to degrade tumour cells. We found that the tumour environment could activate the NOX2 activity in Mϕ phagosomes, causing Mϕ to produce excessive reactive oxygen species (ROS), thus prohibiting the formation of phagolysosomes before degradation. Conversely, inhibiting NOX2 in Mϕ by liquiritin can reduce ROS and promote phagosome-lysosome fusion, therefore improving the enzymatic degradation of tumour cells after phagocytosis, and subsequently promote T cell activity by presenting antigens. We further confirmed that liquiritin down-regulated the expression of the NOX2 specific membrane component protein gp91 phox, blocking its binding to the NOX2 cytoplasmic component proteins p67 phox and p47 phox, thereby inhibiting the activity of NOX2. This study elucidates the specific mechanism by which Mϕ cannot degrade tumour cells after phagocytosis, and indicates that liquiritin can promote the ability of Mϕ to degrade tumour cells by suppressing NOX2.