Objective To investigate the changes in the gut microflora(GM)composition and metabo-lites in children with allergic rhinitis(AR)based on high-throughput sequencing technology.Methods From December 2023 to May 2024,11 preschool children with allergic rhinitis(AR)who visited the pediatric outpa-tient department of Shantou University Medical College Longgang Maternal and Child Health Hospital Clini-cal College(Longgang District Maternal and Child Health Hospital)were selected as the AR group,and 21 healthy children of the same age who underwent physical examinations in the child health care department during the same period were selected as the control group.Fecal samples were collected from both groups,and DNA was extracted and amplified.High-throughput sequencing technology was used to analyze the composi-tion of gut microbial genes,and the differences in gut microbiota composition and metabolites between the two groups were compared.Results Compared with the control group,the AR group had a higher Shannon index,with a significant increase in the abundance of Proteobacteria and Saccharibacteria.The relative abundance of Veillonella,Enterococcus,Escherichia coli/Shigella,Haemophilus,and Streptococcus was significantly high-er,while the relative abundance of Lachnospira,Anaerostipes,Enterobacteriaceae,Anaerobacterium,and Eu-bacterium was significantly lower(P＜0.05).There were statistically significant differences in the principal components of GM metabolites between the two groups(P＜0.05).A total of 2 540 different metabolites were identified,of which 1 185 metabolites were significantly increased,20 metabolites were significantly de-creased,and 1 335 metabolites showed no significant changes.Variable importance in projection(VIP)analy-sis revealed 30 significantly different metabolites.Compared with the control group,2 fecal metabolites were significantly downregulated in the AR group,specifically 3-furanmethanol glucoside and membrane heptosyl A.Conclusion The gut microbiota of preschool children with AR has undergone significant changes,which are related to inflammation and immune function.

Objective To analyze clinical characteristics affecting survival outcomes in gastric adenocarcinoma(GAC)patients with second primary malignancies(SPM)and construct a predictive model with a web-based calculator.Methods Patients diagnosed with GAC between January 2010 and December 2017 in the SEER database(n=24 085)were analyzed,comparing non-SPM(n=22 963)and SPM cohorts(n=1 122).SPM patients were randomized(3:1)into training(n=842)and internal validation cohorts(n=280).Univariate/multivariate Cox regression identified prognostic factors for model construction.Model performance was evaluated via ROC curves,calibration plots,and decision curve analysis(DCA).A web-based calculator was deployed using DynNom(https://kunma697.shinyapps.io/dynnomapp-1/).External validation used 192 SPM patients diagnosed at Yantai Yuhuangding Hospital(2010-2017).Results χ2 tests revealed SPM patients had higher age(56.3%),earlier T-stage(T1:29.2%;T2:10.5%),predominant gastric cardia involvement(43.7%),fewer distant metastases(12.3%),and higher rates of radiotherapy(32.5%)and surgery(77.2%)vs.non-SPM(P<0.05).Cox analyses identified GAC primary site,T-stage,SEER stage,radiotherapy/surgery history,plus SPM grade/stage/treatment history as significant predictors(P<0.05).AUCs in the training cohort were 0.771(95%CI:0.722～0.820),0.839(95%CI:0.796～0.882),and 0.836(95%CI:0.792～0.879)for 1-/3-/5-year survival;internal validation showed 0.751(95%CI:0.700～0.801),0.746(95%CI:0.695～0.797),and 0.772(95%CI:0.723～0.821);external validation yielded 0.713(95%CI:0.648～0.778),0.805(95%CI:0.749～0.861),and 0.851(95%CI:0.801～0.901).Calibration indicated high prediction-actuality concordance;DCA confirmed clinical utility.Conclusion The model and web calculator incorporating GAC/SPM characteristics effectively predict SPM patient prognosis.

Objective To investigate the changes of blood lipid and glycosylated hemoglobin (HbA1c) levels in obese type 2 diabetes (T2DM) patients and their relationship with insulin resistance (Homa-IR). Methods A total of 120 cases of T2DM newly diagnosed in Motuo County, Tibet from February to October 2022 were selected as the observation group. According to BMI, the patients were divided into diabetes normal weight group (46 cases), overweight group (43 cases) and obesity group (31 cases); 145 healthy subjects were selected as the control group. The levels of HbA1c, fasting blood glucose (FPG), fasting insulin (FINS), serum total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL-C), and low-density lipoprotein (LDL-C) were detected in the study subjects, and Homa-IR and Homa-β indices were calculated. The height, weight, and abdominal circumference were measured. The differences in the levels of the above indicators between the observation group patients and the control group, as well as among various subgroups within the observation group were compared. The influencing factors of Homa-IR in obese T2DM patients were analyzed. Results Compared with the control group, a significant increase in BMI, abdominal circumference, blood pressure, HbA1c, FBG, FINS, TC, TG, LDL-C, UA, visceral fat area, and the levels of Home-IR and Home-β was found in the observation group (all P<0.05). There were significant differences in BMI, abdominal circumference, and the levels of FINS, Homa IR, Homa-β, and HbA1c in diabetes patients with different BMI (all P<0.05). Correlation analysis showed that TG levels in obese T2DM patients in the observation group were significantly correlated with HbA1c (r=0.396, P=0.027), Homa-IR (r=0.405, P=0.024), and Home-β (r=-0.401, P=0.025); LDL-C was significantly correlated with Homa-IR (r=0.411, P=0.022) and Homa-β (r=-0.412, P=0.021); HbA1c was significantly positively correlated with BMI (r=0.371, P=0.040). Conclusion Insulin resistance is closely related to TG, LDL-C, and BMI in obese T2DM patients from the Motuo ethnic minority of Tibet, suggesting that these factors may play a role in the occurrence of T2DM.

OBJECTIVE To study effects of Jinshui Liujun decoction(JLD) on pulmonary water metabolism and TNF-α/NF-κB signaling pathway in asthmatic mice. METHODS After 1 week of acclimatization, 10 mice were randomly selected by body weight as a blank control group, and the rest of the mice were sensitized by intraperitoneal and subcutaneous injections of ovalbumin sensitizing solution on the 1st, 8th, and 15th day of the experiment. On the 22nd day, they were randomly divided into model control group, positive control group and JLD low, medium and high dose(4.1, 8.2, 16.4 g·kg−1) group, and replicated the asthma mouse model by inhaling nebulized excitation solution(1% ovalbumin) once every other day for 2 consecutive weeks, and at the same time, were given atomized excitation solution(1% ovalbumin) every other day for two weeks to replicate the asthmatic mouse model, and were given the test drug by gavage daily. The effects of JLD on the behavior, lung wet-dry weight ratio, AQP1, AQP5, TNF-α, NF-κB, and NF-κB mRNA expression in asthmatic mice were observed. RESULTS JLD reduced the number of animals with asthma attacks, alleviated asthma symptoms, decreased the lung index and lung wet-to-dry weight ratio, increased the expression level of AQP1 and AQP5 in lung tissues, reduced the content of TNF-α in bronchoalveolar lavage fluid and lung tissues, and down-regulated the expression level of NF-κB and its genes in lung tissues(P<0.05 or P<0.01). CONCLUSION JLD has an anti-asthma effect and its mechanism of action is partially due to its inhibition of the TNF-α/NF-κB signaling pathway, upregulation of AQP1 and AQP5, and improvement of pulmonary water metabolism.

In recent years, the detection rate and incidence of thyroid diseases are on the rise. Thyroid nodule (TN) is a common thyroid disease that can be divided into benign nodules and malignant nodules. Genetic factors, physiqu, inflammation, and other factors can all lead to TN. In this article, the factors affecting the occurrence and development of TN were analyzed and summarized to provide a basis for scientific prevention and treatment of TN, clinical research, and patient health guidance.

Objective To generate and identify the Itgbl1(integrin beta-like)promoter-driven Cre knock-in mouse line.Methods Itgbll-Cre knock-in mice were generated using clustered regularly interspaced short palindromic repeats(CRISPR)/CRISPR-associated protein 9(Cas9)gene editing.The Itgbl1-Cre mice were crossed with the Cre reporter ROSALSL-tdTomato)mice to detect the expression profile of Cre activity.The tdTomato expression pattern across tissues and cell-specific markers were used to identify the cell types of Itgbl1-expressing cells and their progeny.Results and Conclusion tdTomato was specifically expressed in mucous acinar cells of the sublingual gland,pancreatic islet cells,and gastric endocrine cells.In addition,tdTomato expression was also found in some of the neurons of the retina and brain,as well as in a few cells in the serosal layer of the intestine,articular cartilage,periosteum,and bone marrow.The first Itgbl1-Cre recombinase transgenic mouse line was established,which can specifically label the mucous acinar cells of the sublingual gland.

Microplastics pollution has attracted worldwide attention. Compared with the status quo of microplastics pollution in marine environment and other major rivers and lakes, the relevant data of the Yellow River basin is relatively inadequate. The abundance, types, and spatial distribution characteristics of microplastic pollution in the sediments and surface water of the Yellow River basin were reviewed. Meanwhile, the status of microplastic pollution in the national central city and Yellow River Delta wetland was discussed, and the corresponding prevention and control measures were put forward. The results showed that the spatial distribution of microplastics pollution in sediments and surface water of the Yellow River basin increased from upstream to downstream, especially in the Yellow River Delta wetland. There are obvious differences between the types of microplastics in sediment and surface water in the Yellow River basin, which is mainly related to the materials of microplastics. Compared with similar regions in China, the microplastics pollution levels in national key cities and national wetland parks in the Yellow River basin are in the medium to high degree, which should be taken seriously. Plastics exposure through various ways will cause serious impact on aquaculture and human health in the Yellow River beach area. To control microplastic pollution in the Yellow River basin, it is necessary to improve the relevant production standards, laws and regulations, and improve the capacity of biodegradable microplastics and the degradation capacity of plastic wastes.
Humans ; Microplastics ; Plastics ; Water Pollutants, Chemical/analysis* ; Environmental Monitoring/methods* ; Water ; China

Objective:To investigate surgical treatment of carotid artery diseases in neck tumor surgery. Methods:A retrospective analysis of the clinical data on carotid artery treatment was conducted in the five cases of neck tumor surgeries treated at Department of Surgical Oncology, the First Peoples Hospital of Lanzhou from March 2010 to May 2020. Surgical methods, including carotid artery resection and ligation, tumor-involved artery resection and vascular reconstruction, and tumor peeling and carotid rupture repairing were used, respectively. Results:Five cases were successfully operated on. One case of carotid artery ligation was followed by intermittent dizziness and decreased contra-lateral limb strength after the surgery. The remaining patients exhibited no neurological complications. A patient with cervical low-grade myofibroblastoma developed into lung metastases 8 months after the surgery. Another patient with cervical lymph node metastases in papillary thyroid cancer developed into lung metastases 24 months after the surgery. Conclusion:Currently, surgical methods for clinical treatment of diseased carotid arteries include carotid artery resection and ligation, simple tumor peeling, tumor invasion artery resection and vascular reconstruction, and interventional therapy. Each surgical method has its own advantages and disadvantages. Therefore, the choice of treatment depends on the patient's specific conditions, physician's clinical experience, and the equipment available.
Humans ; Retrospective Studies ; Carotid Arteries/pathology* ; Head and Neck Neoplasms/pathology* ; Thyroid Neoplasms/surgery* ; Lung Neoplasms/pathology*

Hepatocellular carcinoma (HCC) is the most common liver malignancy, where HCC segmentation and prediction of the degree of pathological differentiation are two important tasks in surgical treatment and prognosis evaluation. Existing methods usually solve these two problems independently without considering the correlation of the two tasks. In this paper, we propose a multi-task learning model that aims to accomplish the segmentation task and classification task simultaneously. The model consists of a segmentation subnet and a classification subnet. A multi-scale feature fusion method is proposed in the classification subnet to improve the classification accuracy, and a boundary-aware attention is designed in the segmentation subnet to solve the problem of tumor over-segmentation. A dynamic weighted average multi-task loss is used to make the model achieve optimal performance in both tasks simultaneously. The experimental results of this method on 295 HCC patients are superior to other multi-task learning methods, with a Dice similarity coefficient (Dice) of (83.9 ± 0.88)% on the segmentation task, while the average recall is (86.08 ± 0.83)% and an F1 score is (80.05 ± 1.7)% on the classification task. The results show that the multi-task learning method proposed in this paper can perform the classification task and segmentation task well at the same time, which can provide theoretical reference for clinical diagnosis and treatment of HCC patients.
Humans ; Carcinoma, Hepatocellular ; Liver Neoplasms ; Learning

Objective:Based on the concept of outcomes-based education (OBE), aiming to improve students' medical mathematical modeling ability, the teaching design and practice of mathematical modeling module for the course Medical Advanced Mathematics are carried out and the direction of improvement is defined. Methods:Taking infectious disease model as an example, teaching practice was carried out, and then questionnaires from 44 students were collected for feedback opinions. Statistical description, Mann-Whitney U test, one-way ANOVA and Scheffe method, as well as chi-square test and z-test were used to analyze data. Results:The results showed that 90.91% of the students were interested in the subject of the course, and 65.91% of the students thought that this mode significantly improved the learning effect. In this course, there was no significant difference in the learning initiative of students on the two levels of being or not being interested in the course topic, but it had a significant impact on their mastery of knowledge points and their willingness to continue to carry out flipped classroom.Conclusion:The teaching mode is generally effective, but it needs to be further improved in three aspects: emphasizing modeling and downplaying computation, enhancing students' participation and strengthening the classroom learning effect.