1.Current Research Status,Challenges,Differentiation and Treatment Strategies of Traditional Chinese Medicine for Gastroesophageal Reflux Disease
Fengyun WANG ; Mi LYU ; Bingduo ZHOU ; Beihua ZHANG ; Yi WANG ; Tingting XU ; Cong HE ; Xiaokang WANG ; Xin LIU ; Yang WANG ; Kaiyue HUANG ; Lusi XU ; Xudong TANG
Journal of Traditional Chinese Medicine 2026;67(4):392-396
This article systematically reviews the current research status as well as diagnosis and treatment strategies of traditional Chinese medicine (TCM) for gastroesophageal reflux disease (GERD). Studies demonstrate that TCM, based on the "disease-syndrome combination" approach, exhibits multi-target advantages in alleviating symptoms of various GERD subtypes, promoting mucosal repair, regulating emotions, and facilitating the reduction of western medication. To address clinical challenges such as symptom overlap and limited therapeutic efficacy, strategies have been proposed including "treating different diseases with the same method" and integrated regulation based on viscera correlation. Future efforts should focus on elucidating the mechanisms of compound prescriptions, promoting TCM drug development under the "three-combination" evaluation framework that integrates TCM theory, human experience and clinical trial evidence, and optimizing integrated traditional and western medicine models to enhance GERD management.
2.Improving microclimate standards in primary and secondary school classrooms to promote student health
ZHANG Fengyun, WU Ming, LIU Mingfa, YANG Dongling, LUO Chunyan
Chinese Journal of School Health 2026;47(2):153-157
Abstract
The study examines the development and application of microclimate standards for primary and secondary school classrooms, so as to ensure and promote the healthy growth of primary and secondary school students. The paper systematically reviews relevant domestic and international standards, analyzes the problems and shortcomings arising from their practical application and proposes effective countermeasures, in order to provide robust references aimed at optimizing the classroom environment in primary and secondary schools for student health, as well as offering practical support to advance the construction of a healthy China.
3.Investigation on the microclimate of primary and secondary school classrooms in five provinces and municipalities of China in winter
Chinese Journal of School Health 2026;47(2):158-162
Objective:
To understand the microclimate in primary and secondary school classrooms for the study period during the winter heating season, so as to provide a reference for the revision and improvement of relevant health standards.
Methods:
In December 2024, stratified random sampling was used to select 30 primary and secondary schools and 180 classrooms from the northern regions with centralized heating (Liaoning Province, Tianjin City) and the southern regions without centralized heating (Shanghai City, Anhui Province, and Jiangxi Province). Indoor temperature, relative humidity, wind speed, CO 2 and other indicators were measured on site. Variance analysis, t-test, Mann-Whitney U test and Kruskal-Wallis H test were used to analyze the differences in the microclimate of classrooms among regions and urban and rural differences.
Results:
The average temperature in the middle of the classrooms tested on site was (16.47±4.72)℃, and the variance analysis showed that the difference between the regions was statistically significant ( F=27.80, P <0.01). Among them, Tianjin had the highest average temperature of (20.43± 2.12 )℃, followed by Liaoning (19.03±2.23)℃, Shanghai (15.33±5.32)℃, Anhui (12.79±1.74)℃, and Jiangxi (11.69± 1.68 )℃. Horizontal temperature difference was 0.90 (0.50, 1.60)℃, the vertical temperature difference was 0.20 (0.10,0.60)℃, the average relative humidity was (44.39±16.16)%, the wind speed was 0.03(0.01,0.11)m/s, and the differences among different provinces and cities were statistically significant ( H/F =40.62, 82.69, 95.06, 55.28, all P <0.01). The average CO 2 volume concentration in urban areas of Tianjin, Liaoning, and Shanghai was 0.21(0.16,0.30)%, and there was no statistically significant difference ( H=4.65, P =0.10). There were grade differences in relative humidity ( F =3.71, 6.21) and CO 2 ( H =14.72, 12.92) in the north and the south (all P <0.05). In addition, the temperature, relative humidity, wind speed and CO 2 in the middle of the classroom were 42.8%, 67.8%, 100.0% and 22.2% respectively.
Conclusions
The temperature in the middle of the classroom in the non centralized heating area is lower than the standard, the relative humidity of classroom in the centralized heating area is lower than the standard,and the CO 2 in the classroom in winter is lower than the standard. It is recommended to install heating facilities in schools with low temperatures to increase the temperature and increase the frequency of ventilation in classrooms or adopt mechanical ventilation strategies to reduce CO 2 volume concentration.
4.Indoor environment management and CO 2 volume concentration of primary and secondary school classrooms in winter across three provinces and municipalities of China
Chinese Journal of School Health 2026;47(2):163-167
Objective:
To evaluate the classroom environmental management and CO 2 volume concentration in primary and secondary schools from Liaoning, Tianjin, and Shanghai, thereby providing a scientific basis for developing targeted strategies to improve classroom air quality.
Methods:
From December 16 to 26, 2024, by using stratified random cluster sampling method, the questionnaire survey was conducted in 72 primary and secondary schools (24 each of primary, junior high, and regular high schools) across Liaoning, Tianjin and Shanghai. Information on heating, ventilation and other classroom environmental management was collected. Additionally, 108 classrooms were selected for on site microclimate measurements, including temperature, humidity, wind speed and CO 2 volume concentration. Univariate analysis and multiple linear regression models were employed to explore related factors of classroom CO 2 volume concentration.
Results:
Among the three provinces/municipalities, 20.8% of schools regularly monitored the microclimate. The overall compliance rate for classroom CO 2 volume concentration was 17.6%. Multiple linear regression analysis showed that CO 2 volume concentration in regular and junior high school classrooms were higher than in primary school classrooms ( β=0.067, 0.046, 95%CI =0.036-0.099, 0.013-0.080); classrooms ventilated regularly in the morning and afternoon had higher CO 2 volume concentration than those ventilated during every break between classes ( β=0.043, 95%CI = 0.007- 0.080); both temperature ( β=0.010, 95%CI =0.004-0.016) and humidity ( β=0.003, 95%CI =0.002-0.004) were positively correlated with CO 2 volume concentration (all P <0.05).
Conclusions
Excessive CO 2 volume concentration in primary and secondary school classrooms is a prominent issue, and ventilation frequency is a key intervenable factor for controlling CO 2 levels. It is recommended to promote ventilation during every break between classes as a core management measure and to emphasize air quality supervision in regular high school classrooms.
5.Compatibility and comfort assessment of school desks and chairs in three cities in China
Chinese Journal of School Health 2025;46(3):321-324
Objective:
To understand the subjective and objective comfort evaluations of students from different age groups on desks and chairs, so as to provide reference for standardized allocation and use of desks and chairs.
Methods:
From January to April 2024, a total of 2 446 students were selected from 26 schools in 13 districts (counties/cities) in Shanghai, Tianjin, and Wuxi from Jiangsu Province by using cluster random method, including students in kindergartens, primary schools, junior high schools,senior high schools, colleges and universities. Standardized procedures were used to measure the height and weight of participants, and the matching desks and chairs models were selected according to the height. The subjective comfort of students on matching desks and chairs was investigated, and their objective comfort was evaluated by using a self designed questionnaire. The χ 2 test was used to analyze the differences of subjective perception and objective evaluation in comfort between different types of desks and chairs.
Results:
About 84.1% of the students subjectively thought that large desks and small chairs were very comfortable or relatively comfortable, followed by large desks and chairs (75.7%), and the proportion of small desks and chairs was the lowest among the three types (46.2%), and the difference was statistically significant ( χ 2=722.46, P <0.01). The reporting rates of primary school, junior high school and senior high school students who subjectively considered large desks and chairs to be very comfortable/relatively comfortable were higher than that of other types of desks and chairs, and the differences were statistically significant ( χ 2=297.49, 252.82, 343.67, P <0.01). However, there was no significant difference in the subjective comfort evaluation of different types of desks and chairs among kindergarten children ( χ 2=3.21, P >0.05), and 66.3% of the students in colleges and universities felt very comfortable/relatively comfortable when they used the matching standard desks and chairs. The objective evaluation results of the comfort for the three types of desks and chairs were consistent with the subjective evaluation, but the proportions of the objective evaluation as very comfortable/relatively comfortable were higher than that of the subjective evaluation ( χ 2=20.76- 813.47, P <0.01).
Conclusions
Large desks and chairs, as well as large desks with small chairs are perceived comfortable, while small desks and chairs are perceived less comfortable. It is recommended to match the large desks and chairs or large desks and small chairs that are suitable for them according to the "standard", to promote physical and mental health of students.
6.Comfort assessment of school desks and chairs ergonomics among students with different body types
Chinese Journal of School Health 2025;46(3):325-329
Objective:
To investigate the differences in the comfort of desks and chairs furniture among students with different body types according to the standard, so as to provide a reference for guiding students with overweight and obesity to choose the correct study furniture and revising the standards.
Methods:
From January to April 2024, 2 443 students from 26 schools in 13 districts (counties/cities) in Shanghai, Tianjin, and Jiangsu Province were selected by the cluster random sampling method to conduct physical examination. The subjective and objective evaluations of the comfort of height matched desks and chairs were investigated. The students were divided into non overweight, overweight, and obesity groups according to relevant criteria, and stratified analysis was performed. The χ 2 test was used to analyze differences in the comfort evaluations of desks and chairs among students with different body types.
Results:
Among the 2 443 students surveyed, 16.7% and 12.6% were respectively classified as overweight and obese. All students assigned the highest comfort ratings to large desks and small chairs (84.1%), and consistency was observed between students subjective and objective evaluations. The reporting rate of samll desks and chairs of obesity students subjective evaluation was lower (36.8%) than that of overweight and non overweight/obesity students (52.1%, 48.0%) ( χ 2=14.63, P <0.01). The overweight and obese group of primary school students had a worse evaluation of the comfort of large desks and chairs and small desks and chairs than those of the non overweight and obese groups( χ 2=15.78, 7.63, P <0.05). Among high school students, the overweight and obese group had worse evaluation of the comfort of large desks and chairs, as well as large desks and small chairs, than those of the non-overweight and obese groups( χ 2=9.62, 11.77, P <0.05). The objective evaluations revealed low compliance ratings on the posture of the thighs and calves for naturally forming an angle greater than 90° (55.6%), and headroom height under the table (50.3%) with small desks and chairs ( χ 2=94.05, 166.47, P <0.05).
Conclusions
Compared with non overweight/obese students, students with overweight and obese students report poor comfort evaluations of height matched desks and chairs. Revision of the standard should consider the body types of students, and evaluations of the comfort of desks and chairs furniture by students with overweight and obesity should be improved.
7.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
8.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
9.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
10.Analysis of Animal Model Construction Methods of Different Subtypes of Gastroesophageal Reflux Disease Based on Literature
Mi LYU ; Kaiyue HUANG ; Xiaokang WANG ; Yuqian WANG ; Xiyun QIAO ; Lin LYU ; Hui CHE ; Shan LIU ; Fengyun WANG
Journal of Traditional Chinese Medicine 2025;66(13):1386-1394
ObjectiveTo collate and compare the characteristics and differences in the methods for constructing animal models of different subtypes of gastroesophageal reflux disease (GERD) based on literature, providing a reference for researchers in this field regarding animal model construction. MethodsExperimental studies related to GERD including reflux esophagitis (RE), nonerosive reflux disease (NERD) and Barrett's esophagus (BE) model construction from January 1, 2014 to January 27, 2024, were retrieved from databases such as CNKI, Wanfang, VIP, Web of Science, and Pubmed. Information on animal strains, genders, modeling methods including disease-syndrome combination models, modeling cycles were extracted; for studies with model evaluation, the methods of model evaluation were also extracted; then analyzing all those information. ResultsA total of 182 articles were included. SD rats were most frequently selected when inducing animal models of RE (88/148, 59.46%) and NERD (9/14, 64.29%). For BE, C57BL/6 mice were most commonly used (11/20, 55.00%). Male animals (RE: 111/135, 82.22%; NERD: 11/14, 78.57%; BE: 10/12, 83.33%) were the most common gender among the three subtypes. The key to constructing RE animal models lies in structural damage to the esophageal mucosal layer, gastric content reflux, or mixed reflux, among which forestomach ligation + incomplete pylorus ligation (42/158, 26.58%) was the most common modeling method; the key to constructing NERD animal models lies in micro-inflammation of the esophageal mucosa, visceral hypersensitivity, and emotional problems, and intraperitoneal injection of a mixed suspension of ovalbumin and aluminum hydroxide combined with acid perfusion in the lower esophagus (8/14, 57.14%) was the most common modeling method; the key to constructing BE animal models lies in long-term inflammatory stimulation of the esophageal mucosa and bile acid reflux, and constructing interleukin 2-interleukin 1β transgenic mice (7/25, 28.00%) was the most common modeling method. Adverse psychological stress was the most common method for inducing liver depression. ConclusionsThe construction key principles and methodologies for RE, NERD, and BE animal models exhibit significant differences. Researchers should select appropriate models based on subtype characteristics (e.g., RE focusing on structural damage, NERD emphasizing visceral hypersensitivity). Current studies show insufficient exploration of traditional Chinese medicine disease-syndrome combination models. Future research needs to optimize syndrome modeling approaches (e.g., composite etiology simulation) and establish integrated Chinese-Western medicine evaluation systems to better support mechanistic investigations of traditional Chinese medicine.


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