{"title":"评估异常子宫出血妇女子宫内膜组织病理学改变的凋亡生物标志物","authors":"Bellala Venkata Madhavi, Thallury Shirin Kamal, Bellala Ravi Shankar, Prathipaty Josephine Bindu","doi":"10.1111/jog.70059","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Aim</h3>\n \n <p>Abnormal uterine bleeding (AUB) is a common clinical challenge faced by women, often indicating underlying gynecological disorders, including endometrial pathologies. The evaluation of apoptotic biomarkers has gained attention as a potential method to elucidate the mechanisms driving these pathologies. AUB lacks precise diagnostic tools, with an insufficient understanding of apoptotic biomarkers' roles in endometrial changes, hindering effective management and targeted therapies for affected women.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>The objectives are to identify apoptotic biomarkers associated with endometrial histopathological changes, evaluate their diagnostic potential for abnormal uterine bleeding, and enhance understanding of underlying biological mechanisms in affected women. Analyzing healthcare data reveals patterns that inform clinical decisions and improve patient outcomes.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Content-based filtering technique combined with deep feedforward neural networks can uncover patterns in biomarkers, forecast histopathological outcomes, improve diagnostic accuracy, and tailor treatment strategies for women experiencing abnormal uterine bleeding. Findings show that in cycles under 21 days, 5% of patients experienced bleeding for 4 days, while 74% had 4–6 days of bleeding, and 21% bled for more than 6 days. This result was implemented using Python software.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>Future research could explore targeted therapies based on apoptotic biomarkers, enhancing diagnostic accuracy and personalized treatment strategies for women with abnormal uterine bleeding and associated endometrial histopathological changes.</p>\n </section>\n </div>","PeriodicalId":16593,"journal":{"name":"Journal of Obstetrics and Gynaecology Research","volume":"51 9","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluating apoptotic biomarkers with endometrial histopathological changes in women with abnormal uterine bleeding\",\"authors\":\"Bellala Venkata Madhavi, Thallury Shirin Kamal, Bellala Ravi Shankar, Prathipaty Josephine Bindu\",\"doi\":\"10.1111/jog.70059\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Aim</h3>\\n \\n <p>Abnormal uterine bleeding (AUB) is a common clinical challenge faced by women, often indicating underlying gynecological disorders, including endometrial pathologies. The evaluation of apoptotic biomarkers has gained attention as a potential method to elucidate the mechanisms driving these pathologies. AUB lacks precise diagnostic tools, with an insufficient understanding of apoptotic biomarkers' roles in endometrial changes, hindering effective management and targeted therapies for affected women.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>The objectives are to identify apoptotic biomarkers associated with endometrial histopathological changes, evaluate their diagnostic potential for abnormal uterine bleeding, and enhance understanding of underlying biological mechanisms in affected women. Analyzing healthcare data reveals patterns that inform clinical decisions and improve patient outcomes.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>Content-based filtering technique combined with deep feedforward neural networks can uncover patterns in biomarkers, forecast histopathological outcomes, improve diagnostic accuracy, and tailor treatment strategies for women experiencing abnormal uterine bleeding. Findings show that in cycles under 21 days, 5% of patients experienced bleeding for 4 days, while 74% had 4–6 days of bleeding, and 21% bled for more than 6 days. This result was implemented using Python software.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusions</h3>\\n \\n <p>Future research could explore targeted therapies based on apoptotic biomarkers, enhancing diagnostic accuracy and personalized treatment strategies for women with abnormal uterine bleeding and associated endometrial histopathological changes.</p>\\n </section>\\n </div>\",\"PeriodicalId\":16593,\"journal\":{\"name\":\"Journal of Obstetrics and Gynaecology Research\",\"volume\":\"51 9\",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2025-09-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Obstetrics and Gynaecology Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://obgyn.onlinelibrary.wiley.com/doi/10.1111/jog.70059\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"OBSTETRICS & GYNECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Obstetrics and Gynaecology Research","FirstCategoryId":"3","ListUrlMain":"https://obgyn.onlinelibrary.wiley.com/doi/10.1111/jog.70059","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"OBSTETRICS & GYNECOLOGY","Score":null,"Total":0}
Evaluating apoptotic biomarkers with endometrial histopathological changes in women with abnormal uterine bleeding
Aim
Abnormal uterine bleeding (AUB) is a common clinical challenge faced by women, often indicating underlying gynecological disorders, including endometrial pathologies. The evaluation of apoptotic biomarkers has gained attention as a potential method to elucidate the mechanisms driving these pathologies. AUB lacks precise diagnostic tools, with an insufficient understanding of apoptotic biomarkers' roles in endometrial changes, hindering effective management and targeted therapies for affected women.
Methods
The objectives are to identify apoptotic biomarkers associated with endometrial histopathological changes, evaluate their diagnostic potential for abnormal uterine bleeding, and enhance understanding of underlying biological mechanisms in affected women. Analyzing healthcare data reveals patterns that inform clinical decisions and improve patient outcomes.
Results
Content-based filtering technique combined with deep feedforward neural networks can uncover patterns in biomarkers, forecast histopathological outcomes, improve diagnostic accuracy, and tailor treatment strategies for women experiencing abnormal uterine bleeding. Findings show that in cycles under 21 days, 5% of patients experienced bleeding for 4 days, while 74% had 4–6 days of bleeding, and 21% bled for more than 6 days. This result was implemented using Python software.
Conclusions
Future research could explore targeted therapies based on apoptotic biomarkers, enhancing diagnostic accuracy and personalized treatment strategies for women with abnormal uterine bleeding and associated endometrial histopathological changes.
期刊介绍:
The Journal of Obstetrics and Gynaecology Research is the official Journal of the Asia and Oceania Federation of Obstetrics and Gynecology and of the Japan Society of Obstetrics and Gynecology, and aims to provide a medium for the publication of articles in the fields of obstetrics and gynecology.
The Journal publishes original research articles, case reports, review articles and letters to the editor. The Journal will give publication priority to original research articles over case reports. Accepted papers become the exclusive licence of the Journal. Manuscripts are peer reviewed by at least two referees and/or Associate Editors expert in the field of the submitted paper.