Ulcerative colitis（UC） is a chronic non-specific inflammatory bowel disease characterized by inflammation and ulceration of the colonic mucosa and submucosa， and its complex pathogenesis involves immune abnormality， oxidative stress and other factors. The nuclear transcription factor E₂-related factor 2（Nrf2）， encoded by the Nfe212 gene， plays a central role in antioxidant responses. It not only activates various antioxidant response elements such as heme oxygenase-1（HO-1） and quinone oxidoreductase 1（NQO1）， but also enhances the activity of glutathione-S-transferase（GST） and superoxide dismutase 1（SOD1）， effectively eliminating reactive oxygen species（ROS） accumulated in the body， and mitigating oxidative stress-induced damage to intestinal mucosa. In addition， Nrf2 can reduce the release of inflammatory factors and infiltration of immune cells by regulating immune response， cell apoptosis and autophagy pathways， thereby alleviating intestinal inflammation and promoting the repair and regeneration of damaged mucosa. Based on this， this paper reviews the research progress of Chinese materia medica in the prevention and treatment of UC by modulating the Nrf2 signaling pathway. It deeply explores the physiological role of Nrf2， the molecular mechanism of activation， the protective effect in the pathological process of UC， and how active ingredients in Chinese materia medica regulate the Nrf2 signaling pathway through multiple pathways to exert their potential mechanisms. These studies have revealed in depth that Chinese materia medica can effectively combat oxidative stress by regulating the Nrf2 signaling pathway. It can also play a role in anti-inflammatory， promoting autophagy， inhibiting apoptosis， protecting the intestinal mucosal barrier， and promoting intestinal mucosal repair， providing new ideas and methods for the multi-faceted treatment of UC.

ObjectiveTo collate and compare the characteristics and differences in the methods for constructing animal models of different subtypes of gastroesophageal reflux disease （GERD） based on literature， providing a reference for researchers in this field regarding animal model construction. MethodsExperimental studies related to GERD including reflux esophagitis （RE）， nonerosive reflux disease （NERD） and Barrett's esophagus （BE） model construction from January 1， 2014 to January 27， 2024， were retrieved from databases such as CNKI， Wanfang， VIP， Web of Science， and Pubmed. Information on animal strains， genders， modeling methods including disease-syndrome combination models， modeling cycles were extracted； for studies with model evaluation， the methods of model evaluation were also extracted； then analyzing all those information. ResultsA total of 182 articles were included. SD rats were most frequently selected when inducing animal models of RE （88/148， 59.46%） and NERD （9/14， 64.29%）. For BE， C57BL/6 mice were most commonly used （11/20， 55.00%）. Male animals （RE： 111/135， 82.22%； NERD： 11/14， 78.57%； BE： 10/12， 83.33%） were the most common gender among the three subtypes. The key to constructing RE animal models lies in structural damage to the esophageal mucosal layer， gastric content reflux， or mixed reflux， among which forestomach ligation + incomplete pylorus ligation （42/158， 26.58%） was the most common modeling method； the key to constructing NERD animal models lies in micro-inflammation of the esophageal mucosa， visceral hypersensitivity， and emotional problems， and intraperitoneal injection of a mixed suspension of ovalbumin and aluminum hydroxide combined with acid perfusion in the lower esophagus （8/14， 57.14%） was the most common modeling method； the key to constructing BE animal models lies in long-term inflammatory stimulation of the esophageal mucosa and bile acid reflux， and constructing interleukin 2-interleukin 1β transgenic mice （7/25， 28.00%） was the most common modeling method. Adverse psychological stress was the most common method for inducing liver depression. ConclusionsThe construction key principles and methodologies for RE， NERD， and BE animal models exhibit significant differences. Researchers should select appropriate models based on subtype characteristics （e.g.， RE focusing on structural damage， NERD emphasizing visceral hypersensitivity）. Current studies show insufficient exploration of traditional Chinese medicine disease-syndrome combination models. Future research needs to optimize syndrome modeling approaches （e.g.， composite etiology simulation） and establish integrated Chinese-Western medicine evaluation systems to better support mechanistic investigations of traditional Chinese medicine.

ObjectiveTo investigate the changes of intestinal flora in children with food allergy and constipation by high-throughput sequencing， and to analyze the function of intestinal flora， to provide a basis for the prevention and treatment of food allergy and constipation in children. MethodsTotally 33 children with food allergy and constipation in Longgang District of Shenzhen were selected as the disease group （CPFA group）， another 59 healthy children of the same age were recruited as the HC group. Stool samples were collected and subjected to high-throughput sequencing of 16SrRNA genes， followed by bioinformatics analysis. Results① The species abundance of HC group was higher than that of CPFA group， and the diversity of intestinal microbial community was different between the two groups； ② At the phylum level， the relative abundance of Bacteroidota， Desulfobacterota in CPFA group was lower than that in HC group， and the relative abundance of Firmicutes， Actinobacteria and Proteobacteria in CPFA group was higher than that in HC Group（P< 0.05）； ③ At the genus level， the relative abundance of Bacteroids， Parabacteroides in the CPFA group was lower than that in the HC group， and the relative abundance of Bifidobacterium， Escherichia-Shigella and Veillonella in the CPFA group was higher than that in the HC group； ④ Functional analysis showed that there were significant differences in functional genes between the two groups. Compared with those in the HC group， the abundance of functional genes in valine， leucine and isoleucine biosynthesis， cysteine and methionine metabolism， fatty acid metabolism and Staphylococcus aureus infection were significantly increased in the CPFA group （P<0.05）. The abundance of functional pathways related to bile acid biosynthesis and retinol metabolism was significantly decreased （P<0.05）. ConclusionThere are differences in intestinal flora and function between children with CPFA and HC， which may help to explore the pathogenesis of food allergy and constipation， and provide a theoretical basis for new therapeutic interventions.

Objective To investigate the independent risk factors affecting the prognosis of chronic active antibody-mediated rejection (caAMR) after kidney transplantation. Methods A retrospective analysis was conducted on 61 patients who underwent renal biopsy and were diagnosed with caAMR. The patients were divided into caAMR group (n=41) and caAMR+TCMR group (n=20) based on the presence or absence of concurrent acute T cell-mediated rejection (TCMR). The patients were followed up for 3 years. The value of 24-hour urinary protein and estimated glomerular filtration rate (eGFR) at the time of biopsy in predicting graft loss was assessed using receiver operating characteristic (ROC) curves. The independent risk factors affecting caAMR prognosis were analyzed using the LASSO-Cox regression model. The correlation between grouping, outcomes, and Banff scores was compared using Spearman rank correlation matrix analysis. Kaplan-Meier analysis was used to evaluate the renal allograft survival rates of each subgroup. Results The 3-year renal allograft survival rates for the caAMR group and the caAMR+TCMR group were 83% and 79%, respectively. The area under the ROC curve (AUC) for predicting 3-year renal allograft loss was 0.83 ［95% confidence interval (CI) 0.70-0.97］ for eGFR and 0.78 (95% CI 0.61-0.96) for 24-hour urinary protein at the time of biopsy. LASSO-Cox regression analysis and Kaplan-Meier analysis showed that eGFR≤25.23 mL/(min·1.73 m²) and the presence of donor-specific antibody (DSA) against human leukocyte antigen (HLA) class I might be independent risk factors affecting renal allograft prognosis, with hazard ratios of 7.67 (95% CI 2.18-27.02) and 5.13 (95% CI 1.33-19.80), respectively. A strong correlation was found between the Banff chronic lesion indicators of renal interstitial fibrosis and tubular atrophy (P<0.05). Conclusions The presence of HLA class I DSA and eGFR≤25.23 mL/(min·1.73 m²) at the time of biopsy may be independent risk factors affecting the prognosis of caAMR.

ObjectiveTo investigate the correlation with cognitive function based on a new Kayser-Fleischer ring （K-F ring） grading method in Wilson’s disease （WD）. MethodsA total of 136 WD patients who were hospitalized in Encephalopathy Center， The First Affiliated Hospital of Anhui University of Chinese Medicine， from April 2022 to October 2023 were enrolled. All subjects underwent slit lamp examination， and the grade of K-F ring was determined according to the shape and extent of copper deposition in the cornea， whether it formed a ring or not， and whether there was a sunflower-like cloudy change in the lens. The patients were instructed to complete UWDRS， MoCA， and MMSE scale assessments， and these indicators were compared between patients with different K-F ring grades. An analysis of variance was used for comparison of normally distributed continuous data between multiple groups， and the least significant difference t-test （homogeneity of variance） or the Dunnett’s T3 test （heterogeneity of variance） was used for further multiple comparisons； the Kruskal-Wallis H test was used for comparison of non-normally distributed continuous data between multiple groups； the chi-square test was used for comparison of categorical data between groups. The Spearman correlation analysis was used to investigate the correlation of K-F ring grade with UWDRS， MoCA， and MMSE scores. ResultsAmong the 136 patients with WD， there were 40 patients with grade 4 K-F ring， accounting for the highest proportion of 29.4%， and 14 patients with grade 0 K-F ring， accounting for the lowest proportion of 10.3%， and there were 22 patients with grade 1 K-F ring （16.2%）， 19 with grade 2 K-F ring （14%）， 25 with grade 3 K-F ring （18.4%）， and 16 with grade 5 K-F ring （11.7%）. According to the different grades of K-F ring， there was a significant increase in UWDRS score （F=22.61， P<0.001） and significant reductions in MoCA and MMSE scores （F=16.40 and 13.80， both P<0.001）. The Spearman correlation analysis showed that K-F ring grade was positively correlated with UWDRS score （r=0.67， P<0.01） and was negatively correlated with MoCA and MMSE scores in WD patients （r=-0.59 and -0.57， both P<0.01）. ConclusionThe new K-F ring grading method can determine disease severity in WD patients to a certain degree and partially reflect cognitive function and activities of daily living in such patients.

OBJECTIVE To establish HPLC fingerprint for Jianpi hewei formula （JPHWF）， conduct chemical pattern recognition analysis， and determine the contents of seven components in the formula， aiming to provide a scientific basis for quality control and further research of JPHWF. METHODS Taking 15 batches of standard decoctions of JPHWF as samples， the HPLC fingerprint was established using the Similarity Evaluation System of TCM Chromatographic Fingerprint （2012 edition）. Subsequently， similarity evaluation， as well as identification and attribution analysis of chromatographic peaks， were conducted. Using the common peak areas from the 15 batches of samples as variables， chemical pattern recognition analyses were performed on the samples through hierarchical cluster analysis， principal component analysis， and orthogonal partial least squares-discriminant analysis. The contents of adenine， 5-hydroxymethylfurfural， tetrahydropalmatine， naringin， dehydrocorydaline， neohesperidin and glycyrrhizic acid in 15 batches of samples were determined by HPLC. RESULTS There were 19 common peaks in the characteristic chromatograms for 15 batches of samples with the similarities of more than 0.95. Results of chemical pattern recognition analysis showed that 15 batches of samples could be clustered into 3 categories， and 3 differential compounds were found [peak 7 （5- hydroxymethylfurfural）， peak 17 （neohesperidin）， and peak 15 （naringin）]. The 7 components were linearly good in the respective concentration ranges （R2≥0.999 4）； RSDs of precision， stability and repeatability tests were less than 2% （n＝6）； the average recovery rate of 98.95%-103.81%， RSD of 0.61%-2.75% （n＝6）； the contents of them were 0.031-0.106， 0.267-0.824， 0.089- 0.144， 1.344-2.091， 0.089-0.178， 1.328-2.028， 0.040-0.150 mg/g， respectively. CONCLUSIONS Established HPLC fingerprinting method coupled with multi-index content determination is validated to be accurate and reliable， and its combination with chemical pattern recognition analysis can be applied to the quality control of JPHWF.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

AIM:To analyze the clinical phenotypes and genotypes of children with incontinentia pigmenti(IP)and enhance clinicians' understanding of the condition.METHODS: A family with IP diagnosed in February 2020 at the ophthalmology department of People's Hospital of Ningxia Hui Autonomous Region was enrolled. The proband and family members underwent comprehensive systemic and ocular examinations. Peripheral venous blood was collected for DNA extraction, followed by whole-exome sequencing and MLPA assay to identify pathogenic variants. Corresponding treatments were administered based on the severity of fundus lesions, and ocular clinical features and therapeutic outcomes were monitored during follow-up.RESULTS: The child in this study was a female, aged 8 years, with typical skin changes and scarring alopecia and dental abnormalities at the time of initial consultation. The results of genetic testing suggested that the child carried a heterozygous deletion of exons 4-10 of the IKBKG gene chrX:153440010-153446570del. The child had asymmetric lesions in both eyes, with severe lesions in the left eye, atrophy of the eyeballs, and ocular B-ultrasound suggesting structural disturbances in the eye, and neovascularization was seen in the peripheral retina of the right eye, and the patient was given laser photocoagulation treatment for the right eye, and no progression of retinopathy was detected during follow-up.CONCLUSION:Children with IP have different ocular clinical phenotypes, and retinal vasculopathy is the main change. Early screening and timely and standardized treatment are crucial for children diagnosed with IP.

Medical imaging technology plays a crucial role in clinical diagnosis and treatment. Image compression technology provides robust technical support for the storage and transmission of massive medical imaging data, serving as an effective safeguard for hospital data backup and telemedicine. The technology holds broad application prospects in the medical field, enabling the processing of various imaging modalities, multidimensional imaging, and medical video imaging. This study elaborates on general image and video compression algorithms, the application of compression algorithms in the medical field, and the performance metrics of medical image compression, thereby providing critical technical support for enhancing clinical diagnostic efficiency and data management security.

OBJECTIVE To explore the practice and application effect of lean Six Sigma （LSS） management in the cost- benefit management of PIVAS operation in a tertiary comprehensive hospital （hereinafter referred to as “S Hospital”）， providing reference for the operation and management of PIVAS in hospitals. METHODS The five steps （define， measure， analyze， improve and control， i.e. DMAIC） of LSS management were implemented for PIVAS operation cost-benefit of S Hospital， and lean management was implemented for its cost-benefit management elements （human resource cost， medical and health material cost， and all-in-one parenteral nutrition preparation income）. Several intervention measures including personnel training and performance assessment， refined management system of consumables， and doctor’s advice package of full parenteral nutrition were developed. Finally， the overall improvement effect was evaluated by the total benefit， total cost and net benefit of PIVAS. The effects of human resource allocation optimization and improvement were evaluated by the work efficiency， work quality， job satisfaction， turnover rate and accumulated rest days. The effects of consumables cost management were evaluated by the amount of medical and health materials cost. The improvement effects of all-in-one parenteral nutrition preparation income were evaluated by the profit amount， quantity and the proportion of single bottle of parenteral nutrition. RESULTS After implementing DMAIC in S Hospital， the total benefit of PIVAS was increased from （471 366.50±9 201.5） yuan/month to （479 679.50±14 320.14） yuan/month （P＞ 0.05）， the total cost was decreased from （305 878.88±3 201.75） yuan/month to （294 610.59±5 007.33） yuan/month （P＜0.05）， and the net benefit of PIVAS was increased by 11.83% compared with that before the improvement. The work efficiency， work quality and job satisfaction of employees were significantly improved， the accumulated rest days were significantly reduced， and the turnover rate of third-party employees was reduced from 15.0% before the improvement to 7.5% after the improvement. The cost of medical and health materials significantly decreased from （67 826.42±2 812.76） yuan/month before improvement to （56 384.33±4 607.67） yuan/month after improvement （P＜0.05）. The quantity of all-in-one parenteral nutrition was significantly increased from （1 263.75±135.83） group/month before improvement to （2 061.25±89.04） group/month after improvement （P＜0.05）， and the proportion of users of single bottle of parenteral nutrition in total users decreased from 93.25% before improvement to 58.75% after improvement. The profit of all-in-one parenteral nutrition was 63.18% higher than that before implementing DMAIC. CONCLUSIONS The implementation of PIVAS operation cost-benefit management based on DMAIC is conducive to strengthening the cost control of PIVAS and promoting the healthy development of PIVAS.