ObjectiveTo systematically evaluate the application of narrative education in undergraduate nursing teaching， to understand the current application status of narrative education， and to provide a theoretical basis for the subsequent establishment of a sound narrative education system. MethodsA systematic search was conducted for studies published in Chinese and English databases on applying narrative education to undergraduate nursing teaching， with the search period ranging from database inception to February 23， 2025. Literature was screened， and relevant information was extracted. A rigorous quality evaluation was conducted on the included studies， and a descriptive analysis was performed on their content. ResultsA total of 20 papers were included， involving 3，180 research subjects， all of whom were undergraduate nursing students. The results of descriptive analysis showed that the teaching model of narrative education primarily encompassed reading narrative works， watching films and videos， performing narrative scenarios， and writing reflective journals. The course setting and content covered pre-teaching preparation and in-teaching implementation. The evaluation of teaching effectiveness included the evaluation of teachers’ teaching methods （student evaluation/self-evaluation） and the evaluation of students’ learning effectiveness （course grade evaluation/humanistic care scale/empathy scale assessment， and others）. ConclusionNarrative education combines abstract concepts with concrete clinical situations， which not only enriches students’ learning experiences but also enhances their humanistic literacy. Meanwhile， it provides teachers with opportunities to develop their narrative teaching skills， which requires them to possess profound professional knowledge and employ narrative techniques to guide students in reflection and critical thinking， thereby improving teaching quality and learning outcomes. Future efforts should consistently deepen the connotation research of narrative education and build a systematic nursing education system.

Recent studies have indicated that the expression of ubiquitin-specific protease 51 (USP51), a novel deubiquitinating enzyme (DUB) that mediates protein degradation as part of the ubiquitin‒proteasome system (UPS), is associated with tumor progression and therapeutic resistance in multiple malignancies. However, the underlying mechanisms and signaling networks involved in USP51-mediated regulation of malignant phenotypes remain largely unknown. The present study provides evidence of USP51's functions as the prominent DUB in chemoresistant triple-negative breast cancer (TNBC) cells. At the molecular level, ectopic expression of USP51 stabilized the 78 kDa Glucose-Regulated Protein (GRP78) protein through deubiquitination, thereby increasing its expression and localization on the cell surface. Furthermore, the upregulation of cell surface GRP78 increased the activity of ATP binding cassette subfamily B member 1 (ABCB1), the main efflux pump of doxorubicin (DOX), ultimately decreasing its accumulation in TNBC cells and promoting the development of drug resistance both in vitro and in vivo. Clinically, we found significant correlations among USP51, GRP78, and ABCB1 expression in TNBC patients with chemoresistance. Elevated USP51, GRP78, and ABCB1 levels were also strongly associated with a poor patient prognosis. Importantly, we revealed an alternative intervention for specific pharmacological targeting of USP51 for TNBC cell chemosensitization. In conclusion, these findings collectively indicate that the USP51/GRP78/ABCB1 network is a key contributor to the malignant progression and chemotherapeutic resistance of TNBC cells, underscoring the pivotal role of USP51 as a novel therapeutic target for cancer management.

The trillions of commensal microorganisms living in the gut lumen profoundly influence the physiology and pathophysiology of the liver through a unique gut-liver axis. Disruptions in the gut microbial communities, arising from environmental and genetic factors, can lead to altered microbial metabolism, impaired intestinal barrier and translocation of microbial components to the liver. These alterations collaboratively contribute to the pathogenesis of liver disease, and their continuous impact throughout the disease course plays a critical role in hepatocarcinogenesis. Persistent inflammatory responses, metabolic rearrangements and suppressed immunosurveillance induced by microbial products underlie the pro-carcinogenic mechanisms of gut microbiota. Meanwhile, intrahepatic microbiota derived from the gut also emerges as a novel player in the development and progression of liver cancer. In this review, we first discuss the causes of gut dysbiosis in liver disease, and then specify the pivotal role of gut microbiota in the malignant progression from chronic liver diseases to hepatobiliary cancers. We also delve into the cellular and molecular interactions between microbes and liver cancer microenvironment, aiming to decipher the underlying mechanism for the malignant transition processes. At last, we summarize the current progress in the clinical implications of gut microbiota for liver cancer, shedding light on microbiota-based strategies for liver cancer prevention, diagnosis and therapy.

Objective:To develop a deep learning model based on 3D super-resolution reconstruction technology and to analyze its feasibility and effectiveness in predicting paraglottic space invasion in hypopharyngeal cancer.Methods:A retrospective study was conducted involving 382 patients with hypopharyngeal squamous cell carcinoma treated at Qilu Hospital of Shandong University between January 2014 and December 2020. The cohort included 364 males and 18 females, with a mean age of 62±7 years. Patients were divided into a training set ( n=300) and a test set ( n=82) based on enrollment time. A generative adversarial network was used to perform 3D super-resolution reconstruction on contrast-enhanced CT images, improving spatial resolution by 16 times. A 2.5D deep learning strategy was employed to construct Resnet-NR and Resnet-SR models based on conventional and super-resolution images, respectively, to predict whether the paraglottic space was invaded. Model performance was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC). A multi-reader multi-case study was conducted to assess the impact of the artificial intelligence (AI) model on clinicians′ diagnostic capabilities. Results:The super-resolution model Resnet-SR achieved the highest accuracy in both the training set (AUC=0.87, 95% CI: 0.84-0.90) and the test set (AUC=0.88, 95% CI: 0.81-0.96), significantly outperforming traditional clinical indicators (T stage, N stage, tumor diameter, and pathological differentiation degree) (AUC range: 0.55-0.70, all P<0.05). In comparison, the conventional-resolution model Resnet-NR achieved AUCs of 0.81 (95% CI: 0.77-0.84, P=0.005) and 0.80 (95% CI: 0.71-0.89, P=0.184) in the training and test sets, respectively. Using Resnet-SR to assist clinical decision-making improved the diagnostic accuracy of junior physicians (AUC=0.793 without AI assistance vs. AUC=0.871 with AI assistance, P=0.012) and significantly reduced diagnosis time for clinicians of all experience levels (86.5 s without AI assistance vs. 82.5 s with AI assistance, t=2.01, P=0.032). Conclusion:This study successfully develops a deep learning model based on 3D super-resolution reconstruction technology, which can assist in preoperative prediction of paraglottic space invasion in hypopharyngeal cancer. The AI-assisted tool improves diagnostic accuracy for junior physicians and enhances diagnostic efficiency for clinicians across all experience levels.

Objective:To analyze the research trends and hotspots of bupivacaine liposomes from 1994 to 2023 using bibliometrics.Methods:A comprehensive search was conducted for the literature related to bupivacaine liposomes in the Web of Science Core Collection from 1994 to 2023. The CiteSpace software was used to conduct an in-depth analysis of the included literature data, including publication year, country, institution, author, journal, cited references, keywords, etc.Results:A total of 875 papers related to bupivacaine liposomes were included. The research and development of bupivacaine liposomes were divided into 3 stages: slow development (1994-2011), a sharp rise (2011-2021), and stabilization (2021-2023). The United States was in a leading position in terms of the number of publications, centrality, and author cooperation, and Harvard University had the largest number of publications. de Paula E had the most publications, Bramlett K had the highest number of citations, and Boogaerts J had the highest centrality of publications. Journals such as Anesthesia and Analgesia made significant contributions to this field. The most cited references focused on the infiltration of wounds and the periprosthetic injection of bupivacaine liposomes. The keyword analysis showed that local anesthetics, postoperative pain, etc. were commonly used keywords, and enhanced recovery after surgery was an emerging hotspot. Conclusions:Bupivacaine liposomes show good application prospects in the field of peripheral nerve block due to their unique pharmacological properties and safety characteristics and are expected to prolong the duration of postoperative analgesia. However, there is a difference between the actual effect and the expectation, and more clinical trials are needed to evaluate the curative effect, providing a more solid and reliable theoretical basis and practical guidance for clinical practice.

Objective:To develop and validate a deep learning-based multimodal model integrating clinical and radiomic features for predicting acute kidney injury（AKI）risk after partial nephrectomy.Methods:A retrospective analysis was conducted on 416 patients who underwent partial nephrectomy at Zhongshan Hospital，Fudan University from January 2023 to January 2025. The cohort included 100 AKI patients［defined by a ≥ 25% reduction in postoperative evaluated glomerular filtration rate（eGFR）within 48 hours sustained for >24 hours］and 316 non-AKI patients（1∶3 ratio，randomly matched with 16 additional cases for redundancy）. Clinical and radiomic features were extracted from preoperative contrast-enhanced CT scans using PyRadiomics. Demographics included 259 males and 158 females，with a median age of 57（49，65）years，body mass index of（24.1 ± 3.3）kg/m2，preoperative eGFR of（88.5 ± 18.3）ml/（min·1.73 m2），postoperative eGFR（48-hour）of（76.0 ± 21.9）ml/（min·1.73 m2），Zhongshan Score（ZSscore）of 7.34 ± 2.01，and R.E.N.A.L. score of 7.50 ± 1.71. All tumors were T 1a stage. Patients were divided into training（n = 312）and test（n = 104）sets（3∶1 ratio）. A clinical model was constructed via multivariate logistic regression，while radiomic and combined（clinical + radiomic）models utilized an artificial neural network（ANN）with 1 input layer，5 hidden layers，1 output layer，and 10 5 training epochs. Model performance was evaluated by using receiver operating characteristic（ROC）curves and area under the curve（AUC），and was compared to the Martini model. Feature contributions were interpreted via SHapley Additive exPlanations（SHAP）. Results:In the test set，the results of multivariate logistic regression showed that patient’s weight，preoperative eGFR，R.E.N.A.L. score，surgical approach，and operation time were risk factors for AKI（ P < 0.05）. The AUC of the clinical feature prediction model constructed based on the above factors was 0.852（95% CI 0.775?0.929）. In the test set，the AUC of the Martini model was 0.725（95% CI 0.565?0.791）. The radiomic model，trained on 1 315 imaging features，achieved an AUC of 0.898（95% CI 0.804?0.993）with 94.2%（98/104）accuracy. The combined clinical and radiomic model，integrating 1 315 radiomic features and clinical features，demonstrated superior performance with an AUC of 0.946（95% CI 0.887?1.000）and 96.2%（100/104）accuracy，outperforming both the clinical model（ P = 0.03）and the Martini model（ P < 0.01）. SHAP analysis identified the top five predictors in the combined model：ZSscore（SHAP value：0.78），long-run low gray-level emphasis（SHAP value：0.61），run-length non-uniformity（SHAP value：0.58），size-zone non-uniformity（SHAP value：0.46），and gray-level co-occurrence matrix joint energy（SHAP value：0.36）. Conclusions:The deep learning-based multimodal model integrating clinical and radiomic features accurately predicts AKI risk after partial nephrectomy，offering a novel strategy for preoperative risk stratification and personalized intervention.

Objective:To analyze the iodine nutrition status and its related factors among adults aged 18 years and above in Zhejiang Province in 2022.Methods:A multistage stratified sampling method was used to select 4 320 adults aged 18 years and above from 16 on-site survey sites in Zhejiang Province for the study. A questionnaire was used to investigate the general demographic information and personal dietary characteristics of the study participants. Household edible salt and urine samples were collected to detect salt iodine content and urinary iodine level by using direct titration and cerium arsenate-catalyzed spectrophotometry, respectively, to evaluate the iodine nutritional status according to the standard. The multiple-ordered logistic regression model was used to analyze the factors influencing the urinary iodine concentration.Results:The age of the 4 320 study participants was (51.19±15.33) years, with males accounting for 44.44% (1 920). About 40.16% of adults (1 735) were from coastal areas and 56.37% (2 435) from urban areas. The salt iodine content, M ( Q1, Q3), of the 4 320 household edible salt samples was 21.10 (0.00, 24.16) mg/kg, including 1 662 non-iodized salt samples, 182 unqualified iodized salt samples and 2 476 qualified iodized salt samples. The rate of iodized salt coverage was 61.53%, and the rate of qualified iodized salt consumption was 57.31%. There was a statistically significant difference in the proportion of qualified iodized salt in adult households among different regions ( P<0.001), with the proportion of non-iodized salt gradually decreasing from coastal to inland areas ( χ 2trend=618.458, P<0.001). The urinary iodine concentration M ( Q1, Q3) was 137.60 (86.85, 210.60) μg/L in 4 320 adult urine samples, with the urinary iodine levels of<100, 100-199, 200-299, and≥300 μg/L accounting for 31.64% (1 367), 40.56% (1 752), 17.66% (763), and 10.14% (438), respectively. There was a nonlinear positive correlation between household salt iodine content and urinary iodine level in adults aged 18 years and above by using the χ 2 test for trend ( χ 2regression=231.10, P<0.001 and χ 2skew=28.81, P<0.001). Urinary iodine concentrations were higher in men than in women ( P=0.029) and higher in adults in rural areas than in urban areas ( P<0.001). There were statistically significant differences in the distribution of iodine nutritional status among adults of different ages, regions, and urban and rural areas (all P<0.001). The proportion of those with urinary iodine levels<100 μg/L gradually increased with age ( χ 2trend=37.493, P<0.001), and gradually decreased from coastal areas to inland areas ( χ 2trend=71.381, P<0.001). The results of the multiple-ordered logistic regression model analysis showed that compared with adults aged 18 to 44 years and male adults, those aged 45 to 59 years and female adults had lower urinary iodine levels, with OR (95% CI) of 0.75 (0.68-0.83) and 0.85 (0.76-0.95), respectively. Compared with adults in coastal and urban adults, those in sub-coastal, inland and rural adults had higher levels of urinary iodine, with OR (95% CI) of 1.89 (1.63-2.19), 2.02 (1.72-2.37) and 1.46 (1.28-1.66), respectively. Conclusion:The overall iodine nutrition level of adults aged 18 years and above in Zhejiang Province in 2022 is generally appropriate. However, there is a potential risk of iodine deficiency among adults in coastal areas.

Objective:To explore the relationship between intestinal bacterial overgrowth (SIBO) and ulcerative colitis (UC).Methods:From December 2023 to June 2024, 85 patients with UC from the Gastroenterology Department of the Luquan branch of the Second Hospital of Hebei Medical University were enrolled. The lactulose hydrogen-methane breath test was performed to assess the prevalence of SIBO. Clinical data, including basic information, clinical manifestations, endoscopic manifestations, inflammatory indicators, current medication regimen, and past medical history, were collected. Furthermore, the body mass index (BMI), modified Mayo score, and patient-reported outcome (PRO2) score were calculated to evaluate disease activity in each patient. The Student′s t-test, Chi-square test, non-parametric test, and multiple logistic regression were used to analyze the data and explore the relationship between SIBO and UC. Results:The incidence of abdominal pain and bloating in patients who were SIBO positive with UC was higher than in those who were SIBO negative [abdominal pain: 50.0%(10/20) vs. 23.1%(15/65), χ2=5.34, P=0.021; abdominal distension: 40.0% (8/20) vs. 13.8% (9/65), χ2=5.01, P=0.025]; the difference was statistically significant ( P<0.05). Patients who were SIBO positive with UC were more likely to develop hypoproteinemia and anemia than those who were SIBO negative [hypoproteinemia: 50.0% (10/20) vs. 15.4% (10/65), χ2=8.35, P=0.004; anemia: 35.0% (7/20) vs. 9.2% (6/65), χ2=5.98, P=0.014]; the difference was statistically significant ( P<0.05). In the intestinal methanogen overgrowth (IMO) positive group, the number of patients with UC with 1-2 stool times/day was higher, and the distribution of stool times between the IMO positive and IMO negative groups was significantly different ( χ2=6.45, P=0.040). Furthermore, combined hypoproteinemia and anemia were risk factors for SIBO in patients with UC (hypoproteinemia OR=4.331, 95% CI 1.117-16.799, P=0.034; anemia OR=5.515, 95% CI 1.231-24.700, P=0.026). Conclusions:We observed a clinical overlap between SIBO and UC. SIBO could be targeted to optimize the treatment of patients with UC in the future.

Alzheimer′s disease (AD) is one of the most common neurodegenerative diseases. As the global population ages, incidence, morbidity and mortality of AD have increased significantly. The core pathological features of AD include β-amyloid (Aβ) deposition and phosphorylated tau aggregation, resulting in neuronal damage, abnormal mental behavior, and cognitive decline. In recent years, research breakthroughs have not only deepened the Aβ cascade hypothesis and the pathological theory of tau protein, but also made important progress in the fields of neuroimmune regulation, "microbiota-gut-brain" axis, genetic factors, especially the ApoEε4 allele. At the same time, AD has been continuously enriched in blood, cerebrospinal fluid and imaging markers, and sensitivity of markers has been improved and detection tends to be non-invasive. Therapeutic strategies for AD include traditional drugs, novel drugs targeting Aβ/tau protein, and non-pharmacological interventions such as cognitive training, non-invasive brain stimulation and exercise. This review systematically expounds the pathological mechanism, biomarkers, and treatment strategies of AD, aiming to provide a scientific basis for the establishment of a biomarker-based precision diagnosis and treatment paradigm.

Objective:To investigate the follow-up colonoscopy of patients after colorectal adenoma (CRA) resection, so as to improve colonoscopy quality and reduce missed CRA diagnosis.Methods:A total of 189 patients after CRA resection who underwent follow-up colonoscopy from October 2020 to October 2021 were consecutively recruited. The effect of bowel preparation was evaluated by the Boston bowel preparation scale (BBPS). The location, the number, and gross morphology of adenomas during CRA resection and two colonoscopies during 1 year follow-up after the resection were recorded, and their correlation with major clinicopathologic features were analyzed, and the missed CRA in follow-up colonoscopy were also analyzed.Results:The BBPS scores of the right colon, transverse colon, left colon and total colon in 189 patients who underwent CRA resection were 1.93±0.42, 2.53±0.52, 2.77±0.45, and 7.22±1.03 points at the 1-year follow-up colonoscopy and 2.08±0.35, 2.70±0.46, 2.81±0.40, and 7.57±0.84 points at the time of CRA resection. Except for the left colon segment ( χ 2=0.98, P>0.05), the differences in other colon segments were significantly different ( P<0.05). At the time of CRA resection, 62, 66, 210 and 338 CRAs were detected in the right colon, transverse colon, left colon and total colon segments, respectively. At the 1-year follow-up colonoscopy, 21, 38, 49 and 108 CRAs were missed in the corresponding colon segments and total colon, respectively. CRA missed diagnosis was related to patient age (≥60 years accounting for 54.2%), gender (males accounting for 81.9%), adenoma location (predominantly in the left colon comprising 36.2%) and gross morphology (flat types representing 72.3%) ( P<0.05), but not related to being vegetarian, history of cholecystectomy or appendectomy, smoking or alcohol consumption, number of adenomas or pathological type ( P>0.05). Conclusion:The missed diagnosis of CRA in patients after CRA resection primarily involves the flat type adenomas, which is associated with the age, gender, adenoma location within the colon and the gross morphology.