ObjectiveTo investigate the correlation between sleep patterns and myopia progression among younger school-age children at a primary school in Changning District of Shanghai, based on the data from the Shanghai Students’ Common Diseases and Health Influencing Factors Monitoring System and a sleep-specific survey, so as to provide data support for myopia prevention and control in this age group. MethodsOne primary school was selected from the common diseases and health influencing factors monitoring system for students in Changning District, Shanghai. A total of 230 first-grade students were included in the study. Myopia and refractive parameters were examined, and sleep patterns were investigated. General demographic characteristics and myopia-related behavior data of the students were also collected. Sleep patterns were evaluated in terms of sleep duration, sleep efficiency, and sleep quality, with the latter assessed using the Chinese version of the Children’s Sleep Habits Questionnaire (CSHQ). Multiple linear regression and binary logistic regression models were used to analyze the association between sleep patterns and myopia progression among these students. ResultsThe results of the regression analyses revealed that the total CSHQ score of the students at baseline survey was (48.85±7.15) points. Their sleep efficiency was (94.49±8.48)%, sleep duration was (9.58±0.93) hours, and the proportion of those with insufficient sleep (<10 hours) was 78.26%. At baseline survey, students’ higher daytime sleepiness scores were associated with lower spherical equivalent (SE) ( β=-0.18, 95%CI: -0.31 to -0.04) and an increased risk of axial length (AL) / corneal radius (CR) ratio >3 (OR=1.52, 95%CI: 1.00 to 2.29), whereas longer sleep duration and higher sleep efficiency were associated with higher SE (β=0.18, 95%CI: 0.05 to 0.32; β=0.17, 95%CI: 0.04 to 0.31, respectively), shorter (AL) (β=-0.15, 95%CI: -0.27 to -0.03; β=-0.13, 95%CI: -0.25 to 0, respectively) and a reduced risk of AL /CR>3 (OR=0.70, 95%CI: 0.51 to 0.96; OR=0.73, 95%CI: 0.53 to 0.99, respectively). At baseline survey, children’s higher propensity for sleep problems (OR=1.70, 95%CI: 1.04 to 2.78), sleep resistance (OR=2.26, 95%CI: 1.36 to 3.75), and sleep anxiety scores (OR=2.15, 95%CI: 1.33 to 3.48) were all associated with an increased risk of AL/CR >3 at follow-up (all P<0.05). Furthermore, higher sleep anxiety scores predicted prolonged AL at follow-up (β=0.03, 95%CI: 0 to 0.05). According to the mixed-effects model, higher daytime sleepiness scores and prolonged sleep duration were independently linked to reduced right-eye SE (β=-0.05, 95%CI: -0.10 to 0, P<0.05) and shorter right-eye AL (β=-0.05, 95%CI: -0.10 to 0, P<0.05). ConclusionIn this school in Shanghai, there are problems of insufficient and poor-quality sleep among young children. Sleep problems such as sleep resistance, delayed sleep onset, sleep anxiety, and daytime sleepiness among children may accelerate the risk of myopia progression, while longer sleep duration and higher sleep efficiency may serve as protective factors against the occurrence and development of myopia.

Intestinal fibrosis is a significant clinical challenge in inflammatory bowel diseases, but no effective anti-fibrotic therapy is currently available. Glucagon receptor (GCGR) and glucagon-like peptide 1 receptor (GLP1R) are both peptide hormone receptors involved in energy metabolism of epithelial cells. However, their role in intestinal fibrosis and the underlying mechanisms remain largely unexplored. Herein GCGR and GLP1R were found to be reduced in the stenotic ileum of patients with Crohn's disease as well as in the fibrotic colon of mice with chronic colitis. The downregulation of GCGR and GLP1R led to the accumulation of the metabolic byproduct lactate, resulting in histone H3K9 lactylation and exacerbated intestinal fibrosis through epithelial-to-mesenchymal transition (EMT). Dual activating GCGR and GLP1R by peptide 1907B reduced the H3K9 lactylation in epithelial cells and ameliorated intestinal fibrosis in vivo. We uncovered the role of GCGR/GLP1R in regulating EMT involved in intestinal fibrosis via histone lactylation. Simultaneously activating GCGR/GLP1R with the novel dual agonist peptide 1907B holds promise as a treatment strategy for alleviating intestinal fibrosis.

Objective:To investigate the clinical characteristics and survival outcomes of patients with nasopharyngeal carcinoma (NPC) complicated by multiple primary malignancies (MPCs) in a real-world setting.Methods:A retrospective study was performed on 238 NPC patients with MPCs who received radical radiotherapy at Fujian Cancer Hospital between January 1st, 2004 and December 31st, 2023. The primary endpoints were overall survival (OS) and cumulative survival rate. Survival analysis was conducted using the Kaplan-Meier method with log-rank / Breslow tests, and univariate analysis of prognostic factors was performed using the Cox proportional hazards model.Results:A total of 246 primary malignant tumors were identified in 238 patients, involving 12 organ systems and 39 tumor types. The most common coexisting malignancies occurred in the respiratory and intrathoracic organs [25.2% (62/246)], followed by digestive organ malignancies [22.8% (56/246)], malignancies of the lip, oral cavity, and pharynx [22.8% (56/246)], and thyroid and other endocrine gland malignancies [15.4% (38/246)]. The median OS was 186 months, and the 3-, 5-, and 10-year cumulative survival rates were 90.84%, 85.25%, and 69.45%, respectively. Poorer survival was associated with male sex, age>48 years at onset, locally advanced disease (stage IVA), synchronous MPCs and/or digestive system malignancies, fewer total cycles of chemotherapy, and lack of concurrent or adjuvant chemotherapy.Conclusions:In patients with NPC, MPCs most frequently involve the respiratory system, digestive system, and head and neck organs (including the thyroid). Male sex, older age, locally advanced primary NPC, synchronous and/or digestive system MPCs, fewer chemotherapy cycles, and lach of concurrent or adjuvant chemotherapy were significantly associated with poorer prognosis.

Background: The global rise in visual impairment, driven by population aging, the increasing prevalence of lifestyle-related chronic diseases, and environmental factors, has made it a critical public health concern, highlighting the urgent need for effective preventive strategies and eye health maintenance. Cuscutae Semen (CS), a traditional Chinese herbal medicine long regarded for its vision-enhancing properties, has been widely used to support ocular health. However, its underlying molecular mechanisms and bioactive constituents remain poorly understood, limiting its modernization and broader clinical application. Objective: This study aims to investigate the restorative effects of CS on visual impairment, elucidate its underlying mechanisms, and identify potential active components. Methods: A zebrafish model of visual impairment was established using mepanipyrim to simulate retinal structural damage and visual dysfunction. The therapeutic effects of CS were systematically evaluated through behavioral analyses and histomorphological observations. To elucidate the underlying mechanisms, an integrated approach was employed, combining transcriptome sequencing (RNA-seq), reverse transcription quantitative polymerase chain reaction validation, and immunofluorescence staining to identify critical genes and pathways involved. Furthermore, macroporous resin column chromatography was employed for the fractionation and screening of potential active components. Results: CS treatment significantly alleviated mepanipyrim-induced ocular abnormalities in zebrafish, restoring approximately 82% of the observed morphological defects. Behavioral assessments revealed that CS-treated zebrafish exhibited markedly increased swimming speed and distance, indicating enhanced visual light sensitivity. Histopathological analysis demonstrated that CS effectively repaired the structure of retinal cell layers. RNA-seq revealed that CS broadly reversed mepanipyrim-induced gene expression disturbances, suggesting a restorative effect on transcriptomic homeostasis. Gene Ontology enrichment analysis identified the phototransduction pathway as a key mediator of CS’s therapeutic effects. This was further supported by reverse transcription quantitative polymerase chain reaction validation of critical genes and immunofluorescence staining, which confirmed the restored expression of Pde6a and Gnat2, key proteins involved in photic signal transmission. Active component screening indicated that high-polar constituents, including chlorogenic acid, may constitute one of the major bioactive fractions responsible for the observed therapeutic effects. Conclusion: This study provides evidence of the vision-protective effects of CS in a zebrafish model, demonstrating that its therapeutic mechanism involves modulation of the phototransduction pathway. Chlorogenic acid was identified as one of the key bioactive constituents contributing to this effect. These findings not only provide scientific validation for the traditional use of CS in ocular protection but also present promising therapeutic prospects for the prevention and treatment of visual impairment.

Purpose To explore the value of machine learning models based on synthetic MRI,dynamic contrast-enhanced MRI(DCE-MRI)and diffusion weighted imaging(DWI)parameters in identifying molecular subtypes of breast cancer.Materials and Methods A retrospective analysis was conducted on the data of 292 patients who underwent synthetic MRI,DCE-MRI and DWI examinations from September 2020 to September 2024 in Ningxia Medical University General Hospital before surgery and were pathologically confirmed to have breast cancer postoperatively.Patients were randomly divided into training and test sets using a ratio of 7:3.Multiple parameters were obtained from the synthetic MRI,DCE-MRI and DWI images.Variance analysis were used to screen the characteristic parameters among molecular subtype groups.Five machine learning models were established based on the selected characteristic parameters,and receiver operating characteristic curves were plotted to calculate the area under the curve among the molecular subtype groups.Results The support vector machine model exhibited the highest overall performance,with an area under the curve of 0.972,accuracy of 82.5％,specificity of 94.76％and sensitivity of 82.14％in the test set.This model's area under the curve values for differentiating luminal A,luminal B,human epidermal growth factor receptor-2 overexpression,and triple-negative groups in the training set were 0.979,0.925,0.971 and 0.982,respectively;in the test set,the area under the curve values were 0.973,0.873,0.956 and 0.955,respectively.Conclusion Machine learning models based on multimodal MRI parameters can assist clinicians in preoperatively determining the molecular subtypes of breast cancer and the support vector machine model shows relatively high comprehensive performance.

Purpose To explore the value of machine learning models based on synthetic MRI,dynamic contrast-enhanced MRI(DCE-MRI)and diffusion weighted imaging(DWI)parameters in identifying molecular subtypes of breast cancer.Materials and Methods A retrospective analysis was conducted on the data of 292 patients who underwent synthetic MRI,DCE-MRI and DWI examinations from September 2020 to September 2024 in Ningxia Medical University General Hospital before surgery and were pathologically confirmed to have breast cancer postoperatively.Patients were randomly divided into training and test sets using a ratio of 7:3.Multiple parameters were obtained from the synthetic MRI,DCE-MRI and DWI images.Variance analysis were used to screen the characteristic parameters among molecular subtype groups.Five machine learning models were established based on the selected characteristic parameters,and receiver operating characteristic curves were plotted to calculate the area under the curve among the molecular subtype groups.Results The support vector machine model exhibited the highest overall performance,with an area under the curve of 0.972,accuracy of 82.5％,specificity of 94.76％and sensitivity of 82.14％in the test set.This model's area under the curve values for differentiating luminal A,luminal B,human epidermal growth factor receptor-2 overexpression,and triple-negative groups in the training set were 0.979,0.925,0.971 and 0.982,respectively;in the test set,the area under the curve values were 0.973,0.873,0.956 and 0.955,respectively.Conclusion Machine learning models based on multimodal MRI parameters can assist clinicians in preoperatively determining the molecular subtypes of breast cancer and the support vector machine model shows relatively high comprehensive performance.

Objective:To investigate the clinical characteristics and survival outcomes of patients with nasopharyngeal carcinoma (NPC) complicated by multiple primary malignancies (MPCs) in a real-world setting.Methods:A retrospective study was performed on 238 NPC patients with MPCs who received radical radiotherapy at Fujian Cancer Hospital between January 1st, 2004 and December 31st, 2023. The primary endpoints were overall survival (OS) and cumulative survival rate. Survival analysis was conducted using the Kaplan-Meier method with log-rank / Breslow tests, and univariate analysis of prognostic factors was performed using the Cox proportional hazards model.Results:A total of 246 primary malignant tumors were identified in 238 patients, involving 12 organ systems and 39 tumor types. The most common coexisting malignancies occurred in the respiratory and intrathoracic organs [25.2% (62/246)], followed by digestive organ malignancies [22.8% (56/246)], malignancies of the lip, oral cavity, and pharynx [22.8% (56/246)], and thyroid and other endocrine gland malignancies [15.4% (38/246)]. The median OS was 186 months, and the 3-, 5-, and 10-year cumulative survival rates were 90.84%, 85.25%, and 69.45%, respectively. Poorer survival was associated with male sex, age>48 years at onset, locally advanced disease (stage IVA), synchronous MPCs and/or digestive system malignancies, fewer total cycles of chemotherapy, and lack of concurrent or adjuvant chemotherapy.Conclusions:In patients with NPC, MPCs most frequently involve the respiratory system, digestive system, and head and neck organs (including the thyroid). Male sex, older age, locally advanced primary NPC, synchronous and/or digestive system MPCs, fewer chemotherapy cycles, and lach of concurrent or adjuvant chemotherapy were significantly associated with poorer prognosis.

Purpose To explore the predictive value of nomogram model for invasive breast cancer with axillary lymph node metastasis.Materials and Methods Retrospective analysis was made on 122 patients suspected to be breast cancer in the General Hospital of Ningxia Medical University from September 2020 to March 2022.According to whether there was axillary lymph node metastasis,all subjects were divided into 57 patients in the metastasis group and 65 patients in the non-metastasis group.All lesions were pathologically confirmed by surgery.The two groups received synthesis of magnetic resonance imaging(syMRI),dynamic contrast enhancement magnetic resonance imaging(DCE-MRI)and diffusion weighted imaging(DWI)scans.The syMRI parameters[including T1,T2,proton density(PD)],DCE-MRI time signal intensity curve,apparent diffusion coefficient(ADC)value of breast lesions were measured.Compared the difference of parameters between the two groups,and screened the independent risk factors of invasive breast cancer with axillary lymph node metastasis.Results Logistic regression results showed that Ki-67(OR=2.971,95%CI 1.306-6.762,P=0.009),lesion size(OR=1.652,95%CI 1.067-2.556,P=0.024),ADCratio(OR=1.685,95%CI 1.014-2.801,P=0.044),T2ratio(OR=3.015,95%CI 1.433-6.340,P=0.003),PDratio(OR=2.782,95%CI 1.471-5.262,P=0.002)were independent risk factors for invasive breast cancer with axillary lymph node metastasis.The comparison of the five models showed that the Logistic regression model had the best performance,with the area under curve of 0.729(95%CI 0.621-0.789),the accuracy,specificity and sensitivity were 70.65%,62.79%and 77.55%,respectively.The accuracy of the nomogram model was tested,and C-index=0.844,the accuracy of the nomogram model established was good,cut-off risk was 0.468,and the cut-off score was 143.50,which means that when the total score exceeds 143.50,the risk of axillary lymph node metastasis would be higher than 46.8%.Conclusion Nomogram model has a good predictive ability for invasive breast cancer patients with axillary lymph node metastasis.

Objective To establish an ideal modeling method for diarrhea predominant irritable bowel syndrome(IBS-D)with anxiely and depression in rats,and to provide a basis for the clinical study of IBS-D.Methods 60 rats were used in this study.(1)At first,20 rats were randomly divided into blank,3%acetic acid enema,4%acetic acid enema,and 5%acetic acid enema groups.After the modeling and observation period,the diarrhea status and the degree of colon injury caused by different modeling concentrations were observed by diarrhea related index and colon histopathology.(2)After the optimal modeling concentration was assessed,40 rats were randomly divided into control(a),acetic acid enema(b),acetic acid+binding(c),and acetic acid+binding+tail clip(d)groups and correspondingly treated for 8 days.After the treatments,the general condition,diarrhea-related index,open field test(OFT)score,and colonic histopathology of rats were evaluated.Results(1)Compared with the blank group,the fecal trait score of 4%acetic acid enema group was increased on days 1 to 3 after intervention(P＜0.001),and gradually decreased on days 4 to 7 after intervention.After 1 week,there was no significant difference between the fecal trait score and that of the blank group(P＞0.05).Body weight was lower(P＜0.01),fecal water content was higher(P＜0.001).Compared with blank group,body weight of the 5%acetic acid enema group was decreased(P＜0.001),the fecal trait score and diarrhea index were increased(P＜0.01).No significant difference was found between 3%acetic acid enema and blank groups.The pathological colon tissue showed that,compared with the blank group,the mucosal structure of the 4%acetic acid enema group was complete with a small amount of inflammatory cell infiltration,and the pathological tissue score showed no significant difference(P＞0.05),whereas the 5%acetic acid enema had a medium to large amount of inflammatory cell infiltration,and the pathological tissue score was increased(P＜0.01).(2)Compared with group a,group b had lower body weight(P＜0.001),and higher fecal trait score,fecal water content and diarrhea index(P＜0.01).Compared with a and b groups,the body weight of c and d groups was lower(P＜0.001),the fecal traits score,fecal water content,and diarrhea index were increased(P＜0.01),and the colon running time was decreased(P＜0.01).Compared with group c,Fecal water content in group D was higher(P＜0.001).In the OFT score,compared with a and b groups,the OFT distance,standing times,and upright times in c and d groups were lower(P＜0.05).Compared with c,the OFT distance,standing times,and upright times in d group were lower(P＜0.05).The pathological tissue of colon showed that the mucosal structure of the four groups was complete,and there were different degrees of inflammatory cell infiltration.The pathological tissue scores of groups c and d were higher than those of groups a and b(P＜0.05).Conclusions The 4%acetic acid concentration is appropriate for IBS-D modeling.After superposition and binding,the IBS-D diarrhea and internal hypersensitivity characteristic state can be better simulated.After superposition of a tail clip,the IBS-D model of liver stagnation and spleen deficiency can be established successfully.

Purpose To investigate the abnormal brain development in fetuses with isolated mild to moderate ventriculomegaly(VM)during the second and third trimesters of pregnancy by using semi-quantitative fetal total maturation score(fTMS).Materials and Methods A retrospective analysis was performed on 45 normal fetuses and 78 abnormal fetuses who underwent fetal MRI in the General Hospital of Ningxia Medical University from January 2018 to October 2022.fTMS was used to score all images.Linear regression was used to assess the relationship between fTMS and gestational age between normal and abnormal fetuses and to analyze the differences between fetuses with isolated mild and moderate VM and controls.Results In the control group,fetal fTMS was significantly positively correlated with gestational age(r=0.939,P<0.05).The linear regression equation between fTMS(Y)and gestational age(X)was as follows:Y=-28.1+1.25X.In the mild and moderate isolated VM groups,fTMS was positively correlated with gestational age(r=0.945,0.906,P<0.05).The linear regression equations of fTMS(Y)and gestational age(X)were:Y=-28.46+1.24X,Y=-25.57+1.13X.The average fTMS of healthy fetus,mild VM and moderate VM were(10.55±4.25)points,(10.13+4.08)points and(9.22±3.77)points,respectively.There was no significant difference in fTMS between the 49 fetuses with mild isolated VM and the control group(t=1.651,P>0.05).There was significant difference in fTMS between the 29 fetuses with moderate isolated VM and the control group(t=2.306,P<0.05).Conclusion fTMS is suitable for routine clinical use and sensitive to differences in brain maturation between fetuses with isolated moderate VM and healthy controls.