AIM:To observe the morphological and structural changes of foveal cone photoreceptors in patients with age-related macular degeneration(ARMD)using adaptive optics scanning laser ophthalmoscopy(AOSLO)and to evaluate its application value in ARMD.METHODS:This was a retrospective cross-sectional study. Patients with ARMD who visited the Department of Ophthalmology, Army Medical Center of PLA, Army Medical University, and underwent AOSLO examination between September 2025 and October 2025 were enrolled as the experimental group(ARMD group). Age-matched individuals who underwent AOSLO examination during the same period and had either age-related cataract or pseudophakia with a normal macular region were selected as the control group(CON group). The AOSLO device was used to image a 2.4°×2.4° area of the fovea, and parameters including parafoveal cone photoreceptor density(PCPD), average inter-cell spacing, cell dispersion, and cell regularity were analyzed.RESULTS:A total of 53 participants(66 eyes)were included, comprising 24 patients(33 eyes)in the ARMD group [comprising 6 participants(6 eyes)in the intermediate ARMD group and 22 participants(27 eyes)in the late ARMD group(4 participants had one eye in the intermediate group and the other in the late ARMD group)], and 29 participants(33 eyes)in the CON group. The ARMD group included 13 males and 11 females, with a mean age of 69.36±9.79 y. The control group included 17 males and 12 females, with a mean age of 64.64±10.31 y. Compared to the CON group, the ARMD group exhibited significantly lower PCPD(31635±4887 vs 38524±3578 cells/mm2, P<0.01)and cell regularity(95.16%±0.75% vs 96.07%±0.67%, P<0.01), along with significantly greater average inter-cell spacing(4.43±0.26 vs 4.22±0.23 μm, P<0.01)and cell dispersion(20.23%±2.72% vs 16.47%±1.85%, P<0.01). Subgroup analysis within the ARMD group revealed that PCPD was significantly lower in the late ARMD subgroup(30831±4826 cells/mm2)compared to the intermediate ARMD subgroup(35254±3534 cells/mm2, P<0.05).CONCLUSION:Photoreceptor pathology in ARMD patients, as assessed by AOSLO, is characterized by decreased PCPD and cell regularity, as well as increased inter-cell spacing and dispersion. These structural alterations are closely associated with photoreceptor cell lesions. AOSLO, as a non-invasive and quantitative imaging modality, demonstrates promising application prospects in the clinical diagnosis of ARMD.

ObjectiveZheng’s San Qi San (ZSQS) power, a classic traditional Chinese medicine (TCM) formula, is used for treating soft tissue injuries involving muscles, tendons, and ligaments. However, its underlying therapeutic mechanisms remain unclear. This study aimed to screen and identify pharmaceutically active ingredients and their candidate biomolecule targets, and further elucidate the molecular mechanism of ZSQS in the treatment of skeletal muscle injury. MethodsNetwork pharmacology was employed to construct “ZSQS-component-target”, “protein-protein interaction (PPI)” and “active ingredient-core protein-pathway” networks to predict the key active ingredients and potential core targets of ZSQS for skeletal muscle injury. The predicted results were then validated via microarray data from the GEO database. Molecular docking was then performed to assess the binding ability between the screened active ingredients of ZSQS and the candidate core targets. Moreover, liquid chromatography-mass spectrometry (LC-MS) was used for qualitative and quantitative analysis to verify the active components of the drug and ZSQS serum. Finally, an animal model of eccentric exercise-induced skeletal muscle injury and a myotube cell model of oxidative stress-induced injury were established to validate the effects of ZSQS and its interventional effects on the biological functions of critical targets, thereby demonstrating the potential therapeutic mechanism of ZSQS. ResultsAmong the 111 active components identified in ZSQS and their corresponding 204 targets related to the skeletal muscle injury repair process, 14 core targets (including AKT1) and 4 core active components (quercetin, luteolin, kaempferol, and β‑sitosterol) were screened out, while the corresponding metabolites of quercetin, luteolin and kaempferol were detected in the ZSQS serum. Among these targets, 5 candidate genes (IL-6, CASP3, HIF1A, STAT3, and JUN) overlapped with the differential expression screening results with GEO data, and IL-6 was confirmed to be enriched in the PI3K/AKT pathway. Combined with the prediction results of the AKT expression levels, these findings suggest that the phosphorylation level of AKT1 plays a core role in the therapeutic mechanism of ZSQS. Molecular docking analysis further revealed that the PH domain of AKT1 had high binding energy with all 4 core active components, as verified by LC-MS. Finally, animal model studies have shown the promoting effect of ZSQS administration on skeletal muscle injury repair and its possible antioxidant damage mechanism. Cell model studies further demonstrated that ZSQS-containing serum, core active ingredient combination therapy, and quercetin monomer could increase the phosphorylation level of AKT, promote the nuclear translocation of Nrf2, upregulate the expression of downstream antioxidant enzymes (SOD, GPx, and GR), and inhibit the expression of inflammatory factors (IL-6 and TNF-α), thereby alleviating oxidative stress and the inflammatory response. ConclusionZSQS alleviates skeletal muscle injury mainly by activating the AKT/Nrf2 signaling pathway, enhancing cellular antioxidant and anti-inflammatory capabilities. The results of this study provide a scientific basis for the clinical application and modernized development of ZSQS.

Objective: To evaluate the intervention effect of school based salt reduction health education, so as to provide a scientific basis for constructing a more effective and sustainable salt reduction intervention model for children. Methods: According to a randomized controlled trial design, in June 2022, probability proportional to size sampling was used to select 501 second grade students (248 in the control group and 253 in the intervention group) from 10 primary schools in Zhenjiang (intervention group) and 10 primary schools in Yangzhou (control group), Jiangsu Province. An one year school based salt reduction health education intervention was implemented. This included 20 online and 8 offline health education sessions, monitoring of salt consumption in the canteen, and the establishment of a salt reduction environment on campus. The control group received no additional salt reduction interventions. A questionnaire survey and 24 hour urinary sodium test were conducted before and after the intervention. The difference in differences method was used to evaluate the intervention effect. Results: After the intervention, the intervention group showed significant net intervention effects in knowledge aspects, including knowing that primary school students consume less salt than adults ( OR=3.55,95%CI =1.69-7.47), daily salt intake of primary school students ( OR=6.64,95%CI =3.71-11.87), long term high salt intake leading to hypertension ( OR=6.83,95%CI =3.93-11.91), low salt intake not causing hair graying ( OR= 1.66 ,95%CI =1.00-2.75), salt content in food labels ( OR=4.56,95%CI =2.63-7.91), and common high salt foods ( OR=3.39,95%CI =1.87-6.14) (all P <0.05). In terms of attitude, the net intervention effect for having a positive attitude toward using less salt in home cooking was significantly increased ( OR=1.88,95%CI =1.13-3.12, P <0.05). There were no statistically significant net intervention effects for salt reduction related behaviors (all P >0.05). There was no statistically significant difference in the changes of 24 hour urinary sodium between the intervention group and the control group before and after intervention ( P >0.05). Conclusions School based salt reduction health education effectively improves students salt reduction knowledge and attitudes but has a limited effect on behavior change. The home-school collaboration should be strengthened, and the dietary environment should be optimized simultaneously.

Patients with lung cancer experience a heavy symptom burden during the perioperative period, which seriously affects their recovery and quality of life. Traditional symptom management models rely mainly on scheduled ward rounds during hospitalization and outpatient follow-up after discharge. However, they have limitations such as delayed symptom recognition, lack of post-discharge monitoring, and non-quantitative symptom assessment, which often lead to delayed interventions and low patient satisfaction. In recent years, the symptom management model based on electronic patient-reported outcomes (ePRO) has been increasingly valued in clinical practice. Existing high-level evidence from both domestic and international studies indicates that, through proactive monitoring, real-time alerts, and remote interventions, this model enables dynamic and continuous symptom management and helps improve patient recovery and healthcare experience. As a supplement to routine medical care, the ePRO-based symptom management model aims to enhance the quality of care rather than replace existing medical processes. To promote the standardized application of this model in perioperative lung cancer care, this consensus integrates domestic and international evidence. After multiple rounds of voting by more than 50 experts, it formulates 12 consensus statements covering the three core components, symptom monitoring, alerting, and intervention, to provide scientific and practical recommendations for clinical practice.

Objective:To investigate the clinical value of enhanced magnetic resonance imaging (MRI)-based deep learning model in preoperative prediction of proliferative hepatocellular carcinoma (HCC).Methods:The retrospective cohort study was conducted. The clinical data of 906 HCC patients who were admitted to The First Affiliated Hospital of Army Medical University and The Second Affiliated Hospital of Chongqing Medical University from May 2017 to October 2022 were collected. There were 769 males and 137 females, aged (53.2±10.9)years. Of the 906 patients, 815 cases who were admitted to The First Affiliated Hospital of Army Medical University were divided into the training set of 634 patients and the internal validation set of 181 patients using a random number table method with a ratio of 8:2, and 91 patients who were admitted to The Second Affiliated Hospital of Chongqing Medical University were divided into the external validation set. The training set was used to construct the prediction model, while the validation set was used to validate the prediction model. Observation indicators: (1) analysis of factors influencing the pathological classification of HCC patients; (2) deep learning imaging features of HCC patients; (3) evaluation of the efficacy of prediction model for proliferative HCC; (4) validation of the prediction model for proliferative HCC; (5) prognosis of HCC patients. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Multivariate analysis was conducted using the binary Logistic regression model. The model perfor-mance was evaluated through five-fold cross-validation, and receiver operating characteristic (ROC) curve was plotted to assess the diagnostic value of the model based on the area under curve (AUC), sensitivity, and specificity. The Delong test was used to compare the diagnostic performance of models. The Hosmer-Lemeshow test was employed to evaluate the calibration of models. The optimal cutoff value of the prediction model was determined by the maximum Youden index, with the value >0.175 indicating high-risk patients and value ≤0.175 indicating low-risk patients.The Kaplan-Meier method was used to calculate the survival rate and the Log-rank test was used for survival analysis. Results:(1) Analysis of factors influencing the pathological classification of HCC patients. Of 634 patients in the training set, there were 190 cases of proliferative HCC and 444 cases of non-proliferative HCC. Results of multivariate analysis showed that alpha fetoprotein (AFP) ≥400 μg/L and tumor diameter >5 cm were independent risk factors for pathological type of HCC as proli-ferative [ odds ratio=1.73, 1.88, 95% confidence interval ( CI) as 1.19-2.50, 1.30-2.71, P<0.05]. (2) Deep learning imaging features of HCC patients. In the training set of 634 patients, the probability predicted by MRI-based deep learning model was 84.8%(30.5%,95.4%) for proliferative HCC and 5.8%(3.2%,12.5%) for non-proliferative HCC, showing a significant difference between them ( Z=-16.01, P<0.05). (3) Evaluation of the efficacy of prediction model for proliferative HCC. In the training set, the AUC of clinical prediction model for proliferative HCC was 0.63(95% CI as 0.59-0.68, P<0.05), with sensitivity of 54.74% and specificity of 64.19%. The AUC of MRI-based deep learning prediction model was 0.90(95% CI as 0.87-0.93, P<0.05), with sensitivity of 80.53% and specificity of 86.94%. The AUC of combined MRI-based deep learning with clinical prediction model was 0.90 (95% CI as 0.87-0.93, P<0.05), with sensitivity of 83.16% and specificity of 86.04%. Results of Delong test showed that there was a significant difference between the combined MRI-based deep learning with clinical prediction model and the clinical prediction model ( P<0.05), and there was no signifi-cant difference between the combined MRI-based deep learning with clinical prediction model and the MRI-based deep learning prediction model ( P>0.05). Results of Hosmer-Lemeshow test showed good calibration for the clinical prediction model, the MRI-based deep learning prediction model and the combined MRI-based deep learning with clinical prediction model ( χ2=0.84, 6.38, 3.93, P>0.05), indicating that the predicted probabilities of these three prediction models matched the actual risk well. (4) Validation of the prediction model for proliferative HCC. Results of validation of the prediction model in internal validation set showed the AUC of MRI-based deep learning prediction model for proliferative HCC was 0.84(95% CI as 0.77-0.91, P<0.05), with sensitivity of 82.35% and specificity of 77.69%. Results of validation of the prediction model in external validation set showed the AUC of MRI-based deep learning prediction model for proliferative HCC was 0.81(95% CI as 0.71-0.92, P<0.05), with sensitivity of 70.00% and specificity of 81.69%. (5) Prognosis of HCC patients. Of the 906 patients, the 1-, 3-, and 5-year recurrence-free survival rates for 645 proliferative HCC patients were 56.9%, 31.4%, and 29.1%, respectively, and the 1-, 3-, and 5-year recurrence-free survival rates for 261 non-proliferative HCC patients were 88.8%, 68.6%, and 56.0%, respectively. There were significant differences in recurrence-free survival time between proliferative HCC and non-proliferative HCC patients of the training set, internal validation set and external validation set ( P<0.05). The 1-, 3-, 5-year recurrence-free survival rates for 331 high-risk HCC patients were 64.6%, 50.4%, 43.6%, versus 88.5%, 71.9%, 62.7% for 575 low-risk HCC patients. There were significant differences in recurrence-free survival time between high-risk HCC patients and low-risk HCC patients of the training set, internal validation set and external validation set ( P<0.05). Conclusion:The MRI-based deep learning model can effectively predict proliferative HCC and recurrence-free survival of patients before the surgery.

Objective To explore the safety of establishing the veno-arterial extracorporeal membrane oxygenation(VA-ECMO)pipeline through percutaneous puncture and the effectiveness of high-risk percutaneous coronary intervention(HR-PCI)under VA-ECMO assistance.Methods In this single-center retrospective study,patients who underwent HR-PCI assisted by VA-ECMO at Wuhan Asian Heart Hospital from December 2022 to December 2023 were included.The primary endpoint was the safety of establishing the VA-ECMO pipeline through percutaneous puncture,mainly characterized by extracorporeal membrane oxygenation(ECMO)-related complications,including severe bleeding/hematoma at the wound,arteriovenous fistula,pseudoaneurysm,peripheral arterial dissection,etc.The secondary endpoint was the effectiveness of HR-PCI under VA-ECMO assistance,defined as major adverse cardiovascular and cerebrovascular events(MACCE)at 6-month follow-up,including the composite events of all-cause death,non-fatal myocardial infarction,repeat revascularization,and ischemic stroke.Results Among the 189 patients included in the study,15(7.9％)had severe bleeding/hematoma at the puncture wound caused by VA-ECMO,8(4.2％)had wound infection,1(0.5％)had arteriovenous fistula,4(2.1％)had pseudoaneurysm,3(1.6％)had peripheral arterial dissection,8(4.2％)had systemic embolism,8(4.2％)had acute kidney injury,3(1.6％)had acute neurological injury,and 1(0.5％)died.percutaneous coronary intervention(PCI)was successful in 182 cases(96.3％),and a total of 36 cases(19.0％)had PCI-related complications.164 patients completed 6-month follow-up,among which 4(2.4％)had all-cause death,11(6.7％)had non-fatal myocardial infarction,11(6.7％)had unplanned repeat revascularization,and 2(1.2％)had the composite event of ischemic stroke.Conclusions Ultrasound-guided percutaneous puncture for establishing the VA-ECMO pipeline has high safety,and HR-PCI patients assisted by VA-ECMO have good short-term effects.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To investigate the impact of pre-treatment TPMT and NUDT15 genotyping on medication selection, tolerability and discontinuation rates of azathioprine or 6-mercaptopurine therapy in children with inflammatory bowel disease (IBD).Methods:A retrospective cohort study was conducted on 181 children with IBD who were scheduled for azathioprine or 6-mercaptopurine therapy at the Department of Gastroenterology, Children′s Hospital, Zhejiang University School of Medicine between January 2010 and January 2023. Among them, 168 children who received treatment were divided into a genotyped group and non-genotyped group based on pre-treatment TPMT and NUDT15 genotyping. The incidence of drug-related adverse reactions was compared between the two groups. The impact of genotyping on medication selection and discontinuation rates was analyzed. Chi-square test or Fisher exact test were used for intergroup comparisons. Logistic regression analysis was used to control the confounding factors. Firth Logistic regression analysis was applied for data with complete separation. The probability of discontinuation was assessed using survival analysis with Cox proportional hazards modeling.Results:Among the 181 children with IBD, 13 did not receive azathioprine or 6-mercaptopurine due to genetic variants, while the remaining 168 underwent the therapy (154 cases of Crohn′s disease and 14 cases ulcerative colitis; 108 males and 60 females). Excluding the 13 untreated cases, 77 children underwent TPMT and NUDT15 genotyping were assigned to the genotyped group, and the remaining 91 to the non-genotyped group. Adverse reactions included myelosupression (26 cases,15.5%), hepatotoxicity (18 cases,10.7%), gastrointestinal disturbance (25 cases,14.9%), alopecia (12 cases,7.1%), fever (3 cases,1.8%), rash (2 cases,1.2%), and pancreatitis (1 case,0.6%). The incidence of overall adverse reactions was significantly higher in the non-genotyped group compared to that of the genotyped group (40.7% (37/91) vs. 26.0% (20/77), P<0.05). Specifically, the non-genotyped group had a higher rate of gastrointestinal reactions compared to the genotyped group (24.2% (22/91) vs. 3.3% (3/77), P<0.01). Cox regression analysis revealed that non-genotyped group had a higher risk of treatment discontinuation due to the adverse reactions ( HR=1.47, 95% CI 0.65-3.30). Conclusion:Pre-treatment genotyping of TPMT and NUDT15 variants can help guide the selection of clinical drugs, reduce the incidence of drug-related adverse reactions and enhance tolerability of azathioprine or 6-mercaptopurine therapy in IBD children.

Objective:To evaluate the efficacy of the flipped classroom combined with 3D body anatomy software in the teaching of ultrasound-guided transversus thoracic muscle plane block.Methods:In this randomized controlled trial, 100 second-year resident physicians from the Department of Anesthesiology and Perioperative Medicine at our hospital, male or female, aged 22-26 yr, who rotated during January 2023 to January 2025, were selected and divided into 2 groups ( n=50 each) using a table of random numbers: experimental group and control group. Experimental group employed the teaching model of flipped classroom combined with 3D body anatomy software, while control group used the traditional teaching model. The scores of theoretical assessment, accuracy rate of ultrasound image identification, scores of procedural skills, success rates of clinical procedure, teaching satisfaction, and success rates of clinical translation after 1 month follow-up were compared between two groups. Results:Compared with control group, the scores of theoretical assessment, accuracy rate of ultrasound image identification, scores of procedural skills, success rates of clinical procedure, teaching satisfaction, and success rates of clinical translation after 1 month follow-up were significantly increased in experimental group ( P<0.05). Conclusions:The combination of flipped classroom and 3D body anatomy software is more effective than the traditional teaching methods when used for teaching of ultrasound-guided transversus thoracic muscle plane block.