Objective : To investigate the brain microvascular tissue block culture method for extracting primary rat brain microvascular endothelial cells and identify its effect. Methods : Brain tissue from 4-week-old Sprague Dawley rats was screened, pre-digested and solidified to obtain brain microvascular segments. These segments were subsequently placed in a CO2incubator for primary culture. The target cells were identified by cell morphology and immunocytochemical staining for factor Ⅷ-related antigen. Results : After a 48-hour culture periodin vitro, the short spindle cells crawled out from around the brain microvascular segments. After 72 hours, island-like cell culsters formed. After 96 hours the clusters fused and the cells formed a typical monolayer, cobble stone-like, and mosaic arrangement. Factor Ⅷ-related antigen immunocytochemical staining showed that the cytoplasm of the cells appeared brown-red, indicating positive expression; DAB stained the nucleus, showing blue-dark. Conclusion The brain microvascular tissue block culture method can isolate and culture primary rat brain microvascular endothelial cells.

Objective: To explore the relationship between visual acuity and physical fitness of university freshmen, so as to provide reference for myopia prevention and control for freshmen. Methods: From October to November 2022, 2 160 college freshman without majoring in public safety administration, selected from Guangxi Police College in 2022 by using the stratified cluster random sampling method, were reviewed for the results of visual acuity test and physical fitness scores. The physical fitness indices were evaluated by using the Z scores of physical fitness test scores, and the strength of association between the level of physical fitness index and myopia was analyzed by using Logistic regression model. Results: Among 2 160 college freshman without majoring in public safety administration, 917 (42.5%) students were diagnosed screening myopia, including 66 (3.1%) cases of high myopia, 383 (17.7%) cases of moderate myopia and 468 (21.7%) cases of mild myopia. The differences in the distribution of visual acuity tests among students with different physical fitness indices, body mass index, and gender were statistically significant ( Z/H=54.50, 49.53, 15.51, P <0.01). Low level and low middle level physical fitness indices were associated with screening myopia among freshmen[ OR (95% CI )=2.81(1.93-4.08),1.87(1.38-2.54)], and low level physical fitness indexes were associated with high myopia [ OR (95% CI )=7.22(2.33-22.32)] ( P <0.01). Conclusions Screening myopia among college freshman without majoring in public safety administration is related to physical fitness, and low level and low middle level physical fitness index are risk factors for myopia. Improving the level of physical fitness might be effective in preventing myopia.

ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Young female early breast cancer (≤ 40 years) treatment presents unique challenges due to its aggressive features. Using data from the Taiwan Cancer Registry (2007–2017), this study investigated its clinical characteristics, treatment patterns, and prognostic factors. The proportion of young female breast cancer declined from 12% to 8% during the study period.Triple-negative (TN) breast cancer was more prevalent in younger patients, while hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative subtypes increased with age. Stages II and III were observed more frequently in older patients, whereas extremely young patients (20–29 years) exhibited compromised overall and recurrencefree survival. Subtype analysis revealed worse outcomes for TN and hormone receptornegative/human epidermal growth factor receptor 2-positive (HER2+) cases. Treatment patterns showed that targeted therapy was more commonly administered to younger patients with HER2+, while endocrine therapy was used less frequently for HR+ cases, reflecting tolerability and treatment compliance challenges. Future research should focus on optimizing therapeutic strategies and addressing long-term survivorship to enhance care for young women with breast cancer.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Objective To investigate the prevalence of common diseases among primary and secondary school students in Yichang City from 2019 to 2022, and to provide a scientific basis for formulating effective intervention measures in the future. Methods By random cluster sampling , 7 schools in urban areas and 5 schools in suburban counties were selected to screen common diseases such as myopia, dental caries, obesity and abnormal spinal curvature. Descriptive epidemiological methods were employed for statistical analysis. Results A total of 17 023 primary and secondary school students were screened from 2019 to 2022. The overall detection rate of common diseases from high to low was myopia (54.12%), caries (36.75%), overweight (15.17%), obesity (11.88%), malnutrition (5.80%), and abnormal spinal curvature (3.49%). The detection rates of myopia and abnormal curvature of the spine showed an increasing trend with years and school stages, while the detection rates of malnutrition and dental caries showed a decreasing trend with years and school stages. The detection rates of overweight and obesity showed no trend difference with years, and the detection rates of obesity showed a decreasing trend with school stages. The rates of myopia, overweight and obesity were higher in urban areas than those in suburban counties, and the rate of dental caries was higher in suburban counties than that in urban areas. The prevalence of overweight, obesity, and malnutrition in boys was higher than that in girls. The prevalence of myopia and dental caries in girls was higher than that in boys. The above differences were statistically significant (all P<0.05). Conclusion Myopia, dental caries, obesity, and abnormal curvature of the spine are the current focus of the prevention and treatment of common diseases in students. There are great differences between different regions, school stages, and genders. The ^“tripartite linkage^” of schools, families, and communities should be achieved with the joint efforts of the education and health departments to actively take targeted intervention measures to reduce the prevalence.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Definitive treatment of lung cancer with radiotherapy is challenging, as respiratory motion and anatomical changes can increase the risk of severe off-target effects during radiotherapy. Online adaptive radiotherapy (ART) is an evolving approach that enables timely modification of a treatment plan during the interfraction of radiotherapy, in response to physiologic or anatomic variations, aiming to improve the dose distribution for precise targeting and delivery in lung cancer patients. The effectiveness of online ART depends on the seamless integration of multiple components: sufficient quality of linear accelerator-integrated imaging guidance, deformable image registration, automatic recontouring, and efficient quality assurance and workflow. This review summarizes the present status of online ART for lung cancer, including key technologies, as well as the challenges and areas of active research in this field.
Humans ; Lung Neoplasms/radiotherapy* ; Radiotherapy Planning, Computer-Assisted/methods*

Background/Aims: Anti-reflux mucosal ablation (ARMA) is a promising endoscopic intervention for proton pump inhibitor (PPI)-dependent gastroesophageal reflux disease (GERD). However, the effect of ARMA on esophageal motility remains unclear. Methods: Twenty patients with PPI-dependent GERD receiving ARMA were prospectively enrolled. Comprehensive self-report symptom questionnaires, endoscopy, 24-hour impedance-pH monitoring, and high-resolution impedance manometry were performed and analyzed before and 3 months after ARMA. Results: All ARMA procedures were performed successfully. Symptom scores, including GerdQ (11.16 ± 2.67 to 9.11 ± 2.64, P = 0.026) and reflux symptom index (11.63 ± 5.62 to 6.11 ± 3.86, P = 0.001), improved significantly, while 13 patients (65%) reported discontinuation of PPI. Total acid exposure time (5.84 ± 4.63% to 2.83 ± 3.41%, P = 0.024) and number of reflux episodes (73.05 ± 19.34 to 37.55 ± 22.71, P < 0.001) decreased significantly after ARMA. Improved esophagogastric junction (EGJ) barrier function, including increased lower esophageal sphincter resting pressure (13.89 ± 10.78 mmHg to 21.68 ± 11.5 mmHg, P = 0.034), 4-second integrated relaxation pressure (5.75 ± 6.42 mmHg to 9.99 ± 5.89 mmHg, P = 0.020), and EGJ-contractile integral(16.42 ± 16.93 mmHg · cm to 31.95 ± 21.25 mmHg · cm, P = 0.016), were observed. Esophageal body contractility also increased significantly (distal contractile integral, 966.85 ± 845.84 mmHg · s · cm to 1198.8 ± 811.74 mmHg · s · cm, P = 0.023). Patients with symptom improvement had better pre-AMRA esophageal body contractility. Conclusions ARMA effectively improves symptoms and reflux burden, EGJ barrier function, and esophageal body contractility in patients with PPIdependent GERD during short-term evaluation. Longer follow-up to clarify the sustainability of ARMA is needed.