AIM: To detect the distribution and expression of vascular endothelial growth factor(VEGF)in radiation retinopathy(RR)through fluorescence targeted imaging.METHODS:Covalent binding of fluorescein FITC with VEGF antibody ranibizumab to prepare targeted fluorescent imaging probe ranibizumab-FITC. SD rats were randomly divided into three groups based on the principle of weight balance: a normal control group(Con group), a low-dose radiation group(10 Gy group), and a high-dose radiation group(30 Gy group). Medical linear accelerators and lead blocks were used to locally irradiate the rat eyeballs for modeling. Western blot and qRT-PCR were used to detect the expression levels of VEGF-A in each group and to screen for appropriate modeling dose. The inverted fluorescence microscope and the confocal microscope were used to observe the distribution of VEGF and imaging probes in the retinas of control and RR model group rats, and to verify the effectiveness of targeted probes.RESULTS:The expression level of VEGF-A in the retina of rats in the high-dose radiation group(30 Gy group)was higher than that in the normal control group(Con group). In early RR, VEGF expression was observed to be associated with microaneurysms and abnormal microvessels in the retina. VEGF accumulation was observed at the site of capillary wall damage. When retinal capillary endothelial damage occurred, targeted probes gathered on the outer surface of the vessel wall.CONCLUSION:The expression level of VEGF in the retina of RR model rats is elevated, and fluorescent targeted molecular imaging probes can detect the spatial distribution of VEGF at the microvascular lesions in the retina of RR rats.

ObjectiveAngelicae Sinensis Radix， a commonly used medicinal herb with both medicinal and edible properties， is frequently adulterated in the market， severely affecting the clinical efficacy of preparations. While qualitative identification techniques for adulterants and counterfeits are now relatively mature， quantitative detection methods for adulterated processed products remain unexplored. Quantitative detection research of Angelicae Sinensis Radix and its primary closely related adulterant， "Tu Danggui" （Angelica gigas）， was conducted to establish a herbal quantitative molecular detection （Herb-Q） method for Angelicae Sinensis Radix and its processed products， providing a model for the establishment of quantitative detection technologies for Angelicae Sinensis Radix and related health products. MethodsThe specific single-nucleotide polymorphism （SNP） loci of Angelicae Sinensis Radix and Angelica gigas Nakai were screened based on the complete chloroplast genome sequence. The specific SNP loci of Angelicae Sinensis Radix were selected for quantitative methodological investigations （linearity， limit of quantification， limit of detection， and reproducibility） by mixing the powder of the herbs with different adulteration ratios. Huoxue Zhitong powder with three distinct adulteration ratios （15%， 25%， and 35%） was utilized to ascertain the precision of the Herb-Q method for the quantitative detection of Chinese patent medicines containing Angelicae Sinensis Radix. ResultsBy comparing the 123 chloroplast genome sequences of Angelicae Sinensis Radix， based on the principles of intraspecies conservation， interspecies specificity， and meeting the requirements of pyrophosphate high-throughput sequencing， it was determined that 9 674^th locus （A/G） in the chloroplast genome sequence NC_042826.1 and 38 592^nd locus （T/C） in the chloroplast genome sequence NC_029393.1 could be the exclusive molecular identification loci of Angelicae Sinensis Radix and Angelica gigas Nakai， respectively. The linear relationship R² of the Herb-Q method established by selecting the specific 9 674^th locus （A/G） of Angelicae Sinensis Radix was 0.997 4 （R²>0.99）， indicating an excellent linear relationship. The limits of quantification and detection were established at 2.0%， exhibiting excellent reproducibility ［relative standard deviation（RSD）<2.0%］. The established quantitative system based on the Herb-Q method detected the adulteration amount of counterfeit A. gigas in the Huoxue Zhitong powder， with an average deviation of 1.3% for three molecular quantitative replicates. ConclusionThis research demonstrates that the Herb-Q quantitative detection method established based on the 9 674^th locus （A/G） in the chloroplast genome sequence NC_042826.1 of Angelicae Sinensis Radix has good applicability， objectivity， and accuracy for Angelicae Sinensis Radix and A. gigas， and its processed products. This method has the capacity to provide technical support for the quantitative detection of commercially available Angelicae Sinensis Radix derivatives， including traditional Chinese medicinal preparations， dietary supplements， and nutraceuticals.

ObjectiveAngelicae Sinensis Radix， a commonly used medicinal herb with both medicinal and edible properties， is frequently adulterated in the market， severely affecting the clinical efficacy of preparations. While qualitative identification techniques for adulterants and counterfeits are now relatively mature， quantitative detection methods for adulterated processed products remain unexplored. Quantitative detection research of Angelicae Sinensis Radix and its primary closely related adulterant， "Tu Danggui" （Angelica gigas）， was conducted to establish a herbal quantitative molecular detection （Herb-Q） method for Angelicae Sinensis Radix and its processed products， providing a model for the establishment of quantitative detection technologies for Angelicae Sinensis Radix and related health products. MethodsThe specific single-nucleotide polymorphism （SNP） loci of Angelicae Sinensis Radix and Angelica gigas Nakai were screened based on the complete chloroplast genome sequence. The specific SNP loci of Angelicae Sinensis Radix were selected for quantitative methodological investigations （linearity， limit of quantification， limit of detection， and reproducibility） by mixing the powder of the herbs with different adulteration ratios. Huoxue Zhitong powder with three distinct adulteration ratios （15%， 25%， and 35%） was utilized to ascertain the precision of the Herb-Q method for the quantitative detection of Chinese patent medicines containing Angelicae Sinensis Radix. ResultsBy comparing the 123 chloroplast genome sequences of Angelicae Sinensis Radix， based on the principles of intraspecies conservation， interspecies specificity， and meeting the requirements of pyrophosphate high-throughput sequencing， it was determined that 9 674^th locus （A/G） in the chloroplast genome sequence NC_042826.1 and 38 592^nd locus （T/C） in the chloroplast genome sequence NC_029393.1 could be the exclusive molecular identification loci of Angelicae Sinensis Radix and Angelica gigas Nakai， respectively. The linear relationship R² of the Herb-Q method established by selecting the specific 9 674^th locus （A/G） of Angelicae Sinensis Radix was 0.997 4 （R²>0.99）， indicating an excellent linear relationship. The limits of quantification and detection were established at 2.0%， exhibiting excellent reproducibility ［relative standard deviation（RSD）<2.0%］. The established quantitative system based on the Herb-Q method detected the adulteration amount of counterfeit A. gigas in the Huoxue Zhitong powder， with an average deviation of 1.3% for three molecular quantitative replicates. ConclusionThis research demonstrates that the Herb-Q quantitative detection method established based on the 9 674^th locus （A/G） in the chloroplast genome sequence NC_042826.1 of Angelicae Sinensis Radix has good applicability， objectivity， and accuracy for Angelicae Sinensis Radix and A. gigas， and its processed products. This method has the capacity to provide technical support for the quantitative detection of commercially available Angelicae Sinensis Radix derivatives， including traditional Chinese medicinal preparations， dietary supplements， and nutraceuticals.

OBJECTIVE:Disorders in iron metabolism increase the risk of type 2 diabetes mellitus.Hepcidin play an important role in maintaining iron homeostasis in the body,but its level increases with increased inflammation.Changes in hepcidin and iron homeostasis and the extent of their association with inflammation in people with and without type 2 diabetes mellitus are unknown.Meta-analysis was used to evaluate the effect of inflammation on serum hepcidin and iron metabolism related parameters in patients with type 2 diabetes mellitus.METHODS:CNKI,PubMed,Web of Science and EBSCOhost databases were searched by computer to collect observational studies related to inflammatory index and hepcidin in patients with type 2 diabetes mellitus.The search time was from September 1,2000 to September 30,2024.Three researchers independently screened the literature,extracted data and evaluated the quality of the included literature.Meta-analysis was performed by Review Manager 5.3,Stata 17.0 and GraphPad Prism 8.0.2 software.RESULTS:A total of 15 articles(17 studies)involving 3 159 participants,including 1 357 patients with type 2 diabetes mellitus,were included.Meta-analysis results showed that compared with the control group,patients with type 2 diabetes mellitus had higher levels of serum hepcidin[standardized mean difference(SMD)=0.35,95％confidence interval(CI)(0.05,0.65),P＜0.05],serum ferritin(SMD=0.49,95％CI(0.21,0.78),P＜0.01)and serum transferrin(SMD=0.19,95％CI(0.00,0.37),P＜0.05).Subgroup analysis results indicated that inflammation had a significant effect on serum hepcidin(SMD=0.76,95％CI(0.17,1.34),P＜0.05)and serum ferritin(SMD=0.77,95％CI(0.06,1.47),P＜0.05)in patients with type 2 diabetes mellitus.CONCLUSION:Hepcidin concentration is positively correlated with type 2 diabetes mellitus.Inflammation is one of the risk factors of type 2 diabetes mellitus.Early prevention of inflammation has certain significance in preventing iron metabolism disorder in patients with type 2 diabetes mellitus.

OBJECTIVE:Disorders in iron metabolism increase the risk of type 2 diabetes mellitus.Hepcidin play an important role in maintaining iron homeostasis in the body,but its level increases with increased inflammation.Changes in hepcidin and iron homeostasis and the extent of their association with inflammation in people with and without type 2 diabetes mellitus are unknown.Meta-analysis was used to evaluate the effect of inflammation on serum hepcidin and iron metabolism related parameters in patients with type 2 diabetes mellitus.METHODS:CNKI,PubMed,Web of Science and EBSCOhost databases were searched by computer to collect observational studies related to inflammatory index and hepcidin in patients with type 2 diabetes mellitus.The search time was from September 1,2000 to September 30,2024.Three researchers independently screened the literature,extracted data and evaluated the quality of the included literature.Meta-analysis was performed by Review Manager 5.3,Stata 17.0 and GraphPad Prism 8.0.2 software.RESULTS:A total of 15 articles(17 studies)involving 3 159 participants,including 1 357 patients with type 2 diabetes mellitus,were included.Meta-analysis results showed that compared with the control group,patients with type 2 diabetes mellitus had higher levels of serum hepcidin[standardized mean difference(SMD)=0.35,95％confidence interval(CI)(0.05,0.65),P＜0.05],serum ferritin(SMD=0.49,95％CI(0.21,0.78),P＜0.01)and serum transferrin(SMD=0.19,95％CI(0.00,0.37),P＜0.05).Subgroup analysis results indicated that inflammation had a significant effect on serum hepcidin(SMD=0.76,95％CI(0.17,1.34),P＜0.05)and serum ferritin(SMD=0.77,95％CI(0.06,1.47),P＜0.05)in patients with type 2 diabetes mellitus.CONCLUSION:Hepcidin concentration is positively correlated with type 2 diabetes mellitus.Inflammation is one of the risk factors of type 2 diabetes mellitus.Early prevention of inflammation has certain significance in preventing iron metabolism disorder in patients with type 2 diabetes mellitus.

Recurrent syncopal episodes associated with head and neck lymphoma are rarely reported. Through a typical case study, this article analyzes the clinical features of patients with neck lymphoma presenting with syncope as the initial symptom, aiming to improve understanding of this type of disease. By reviewing the clinical data of this patient with neck masses admitted for recurrent syncope in June 2023 and integrating findings with relevant literature, the clinical characteristics of this patient population is presented. The first symptoms of lymphoma presenting as syncope are relatively rare and often lead to misdiagnosis. Diagnosis is mainly based on pathological and immunohistochemical analysis.
Humans ; Head and Neck Neoplasms/diagnosis* ; Lymphoma/diagnosis* ; Recurrence ; Syncope/etiology* ; Young Adult ; Diagnostic Errors

Objective:To develop an artificial intelligence (AI)-based automatic scoring model for magnetic resonance imaging-detected extramural vascular invasion (AI-mrEMVI) and evaluate its performance and prognostic value in patients with rectal cancer.Methods:In this multicenter retrospective cohort study, a total of 2 501 rectal cancer patients from seven centers between November 2012 and December 2020 were included and divided into completely independent training ( n=1 830) and validation ( n=671) cohorts. A nnUNet-based AI-mrEMVI scoring model was constructed. Manual mrEMVI scores assigned by two radiologists served as the reference standard for accessing the accuracy of the AI-mrEMVI scoring. Kaplan-Meier survival analysis and Cox regression were used to evaluate the prognostic stratification ability of the AI-mrEMVI scores. The concordance index (C-index) was calculated to evaluate prognostic performance. Results:In the validation cohort, the manual mrEMVI scores were 0-2 in 425 patients (63.3%), 3 in 89 (13.4%), and 4 in 157 (23.4%). The AI-mrEMVI model identified 0-2 in 375 patients (55.9%), 3 in 95 (14.2%), and 4 in 201 (30.0%), with an overall accuracy of 81.1% (544/671, 95% CI 77.9%-84.0%). The 3-year disease-free survival (DFS) rates for patients with AI-mrEMVI scores of 0-2, 3, and 4 were 85.2%, 70.0%, and 58.2%, respectively, and the 5-year overall survival (OS) rates were 87.2%, 81.6%, and 62.6%, respectively (DFS: χ2=48.74, P<0.001; OS: χ2=30.04, P<0.001). Multivariable Cox regression showed that for DFS, AI-mrEMVI scores of 3 and 4 were associated with hazard ratios ( HR) of 1.75 (95% CI 1.11-2.77, P=0.016) and 2.65 (95% CI 1.86-3.78, P<0.001), respectively. For OS, an AI-mrEMVI score of 4 was associated with an HR of 2.56 (95% CI 1.62-4.03, P<0.001). The C-index values of the AI-mrEMVI scoring model for predicting DFS and OS were 0.647 (95% CI 0.608-0.686) and 0.650 (95% CI 0.598-0.702), respectively. Conclusion:The proposed AI-mrEMVI automatic scoring model demonstrated high diagnostic accuracy and performed favorably in predicting DFS and OS prognostic risk in patients with rectal cancer.

Objective:To identify the relevant factors for the first-course remission of acute myeloid leukemia (AML) and to develop a predictive model as well as assess its predictive capability.Methods:Clinical data of 749 patients newly diagnosed with AML admitted to the Department of Hematology, the First Affiliated Hospital, Zhejiang University, School of Medicine from January 1, 2019, to April 30, 2023, were collected and randomly divided into training and validation sets. Multivariate logistic regression analysis was conducted to determine variables associated with complete remission in the first course of induction therapy, and a predictive model was established based on these variables. The receiver operating characteristic (ROC) curve of the predictive model was plotted, and the area under the curve (AUC) was calculated.Results:The indicators predicting the first remission course included peripheral blood white blood cell count during onset, CBF::MYH11 fusion gene, CEBPA bZIP region mutation, myelodysplastic syndrome-related gene mutation, and induction chemotherapy regimen selection as independent factors for the first remission course. The model’s area under the training and validation curves was 0.738 (95% CI: 0.696-0.780) and 0.726 (95% CI: 0.650-0.801), respectively. The Hosmer-Lemeshow test results yielded P-values of 0.993 and 0.335, respectively. Conclusion:In this study, the developed model demonstrates a strong predictive capability for the efficacy of the first course of patients with AML, providing valuable guidance to clinicians in assessing patient prognosis and selecting appropriate treatment strategies.

Objective:To develop and validate a diagnostic model for pancreatic benign and malignant tumors using radiomics technology.Methods:A retrospective analysis was conducted on the clinical data of 113 patients with pancreatic tumors who underwent surgical treatment at the Hepatobiliary and Pancreatic Surgery Departments of the Second Hospital and the First Hospital of Hebei Medical University from January 2020 to December 2022. There were 59 male and 54 female patients, aged (55.3±16.8) years. Preoperative enhanced thin-slice computed tomography (CT) data and postoperative pathological diagnosis results were collected. Data from 74 patients at the Second Hospital were selected, and according to the random classification principle of 7∶3, the data of 52 patients were determined as the training set for model construction, while the remaining 22 patients' data served as the internal validation set. Data from 39 patients at the First Hospital of Hebei Medical University were used as the external validation set to assess the generali-zability of the established model. The region of interest in the lesions on CT images was analyzed using three-dimensional radiomics feature extraction, and the top 5 features were selected using feature selection methods. Radiomics models were established for the selected features using 17 classifiers. The performance of the models was evaluated using the area under curve (AUC) of the receiver operating characteristic (ROC).Results:Two hundred and fifty-five models were established with 15 feature selection methods and 17 classifiers. 7 models with the AUC greater than 0.7 were selected, among which the best one was LASSO-K neighbors classifier model, constructed using the LASSO feature selection method and the k-nearest neighbors algorithm, achieving AUC values of 0.933 (95% CI: 0.859-0.984) in the training set, 0.973 (95% CI: 0.896-1.000) in the validation set, and 0.774 (95% CI: 0.624-0.908) in the external validation set, with satisfactoryclassification and generalization ability. Conclusion:The radiomics-based diagnostic model for pancreatic benign and malignant tumors can effectively distinguish the benignancy and malignancy of tumors. The LASSO-K neighbors classifier model demonstrated high accuracy and reliability in this study.

Objective: To understand the influenza vaccination rate and related factors of children in Xiqing District of Tianjin, so as to provide a scientific basis for improving the influenza vaccination coverage rate among children. Methods: A stratified random cluster sampling method was employed to select junior high school students and below students from 15 schools in five directions(east, west, south, north, midland) in Xiqing District, Tianjin, involving 13 075 students. A questionnaire survey was conducted among parents of students to analyze the influenza vaccination rate of children in 2023-2024 flu season (October to March of the following year). A binary Logistic regression model was used to analyze the factors affecting influenza vaccination. Results: The influenza vaccination rate was 16.66% for children in Xiqing District of Tianjin, in 2023-2024 flu season, among them, the vaccination rate in kindergartens was the highest (28.86%), followed by primary schools (18.87%) and junior high schools (12.61%). Binary Logistic regression analysis showed that having received the influenza vaccine during the 2020-2022 ( OR=10.55, 95%CI =9.48-11.73), parents awareness of influenza related knowledge ( OR=1.38, 95%CI =1.24-1.54), kindergarten children ( OR= 2.33 , 95%CI =1.91-2.83), primary school students ( OR=1.26, 95%CI =1.12-1.42), parents with a postgraduate degree or above ( OR=1.62, 95%CI =1.13-2.31), and a monthly average family income of 10 000-<20 000 yuan ( OR=1.67, 95%CI = 1.41- 1.99) were positive correlation factors with influenza vaccination of children ( P <0.05). Among parents of children who have not received the flu vaccine, 61.61% fully accepted flu vaccination or accepted but still considered. The most popular way for parents to obtain flu knowledge was flu prevention and control information from professional institutions during the flu season ( 77.38 %). Conclusions The influenza vaccination rate among kindergarten, as well as primary and junior high school students in Xiqing District of Tianjin is low. Promotion of influenza vaccination among children and increase the vaccination rate of influenza among children might help reduce the risk of campus flu outbreak.