Pub Date : 2024-07-15DOI: 10.3389/fmed.2024.1370396
Yuqing Chen, Peng Guo, Lihong Chen, Dalin He
Since the patients suffering from female lower genital tract diseases are getting younger and younger and the human papilloma virus (HPV) infection is becoming more widespread, the novel non-invasive precise modalities of diagnosis and therapy are required to remain structures of the organ and tissue, and fertility as well, by which the less damage to normal tissue and fewer adverse effects are able to be achieved. In all nucleated mammalian cells, 5-Aminolevulinic acid (5-ALA) is an amino acid that occurs spontaneously, which further synthesizes in the heme biosynthetic pathway into protoporphyrin IX (PpIX) as a porphyrin precursor and photosensitizing agent. Exogenous 5-ALA avoids the rate-limiting step in the process, causing PpIX buildup in tumor tissues. This tumor-selective PpIX distribution after 5-ALA application has been used successfully for tumor photodynamic diagnosis (PDD) and photodynamic therapy (PDT). Several ALA-based drugs have been used for ALA-PDD and ALA-PDT in treating many (pre)cancerous diseases, including the female lower genital tract diseases, yet the ALA-induced fluorescent theranostics is needed to be explored further. In this paper, we are going to review the studies of the mechanisms and applications mainly on ALA-mediated photodynamic reactions and its effectiveness in treating female lower genital tract diseases.
由于女性下生殖道疾病患者越来越年轻化，人类乳头瘤病毒（HPV）感染也越来越普遍，因此需要新型非侵入性的精确诊断和治疗方法来保持器官和组织的结构以及生育能力，从而减少对正常组织的损伤和不良影响。在所有有核哺乳动物细胞中，5-氨基乙酰丙酸（5-ALA）是一种自发产生的氨基酸，它在血红素生物合成途径中进一步合成原卟啉 IX（PpIX），是一种卟啉前体和光敏剂。外源性 5-ALA 避免了这一过程中的限速步骤，导致 PpIX 在肿瘤组织中积聚。应用 5-ALA 后的这种肿瘤选择性 PpIX 分布已成功用于肿瘤光动力诊断（PDD）和光动力疗法（PDT）。一些基于 ALA 的药物已被用于 ALA-PDD 和 ALA-PDT 治疗包括女性下生殖道疾病在内的多种（癌前）疾病，但 ALA 诱导的荧光疗法仍有待进一步探索。本文将主要回顾 ALA 介导的光动力反应及其在治疗女性下生殖道疾病方面的机制和应用研究。
{"title":"5-aminolevulinic acid induced photodynamic reactions in diagnosis and therapy for female lower genital tract diseases","authors":"Yuqing Chen, Peng Guo, Lihong Chen, Dalin He","doi":"10.3389/fmed.2024.1370396","DOIUrl":"https://doi.org/10.3389/fmed.2024.1370396","url":null,"abstract":"Since the patients suffering from female lower genital tract diseases are getting younger and younger and the human papilloma virus (HPV) infection is becoming more widespread, the novel non-invasive precise modalities of diagnosis and therapy are required to remain structures of the organ and tissue, and fertility as well, by which the less damage to normal tissue and fewer adverse effects are able to be achieved. In all nucleated mammalian cells, 5-Aminolevulinic acid (5-ALA) is an amino acid that occurs spontaneously, which further synthesizes in the heme biosynthetic pathway into protoporphyrin IX (PpIX) as a porphyrin precursor and photosensitizing agent. Exogenous 5-ALA avoids the rate-limiting step in the process, causing PpIX buildup in tumor tissues. This tumor-selective PpIX distribution after 5-ALA application has been used successfully for tumor photodynamic diagnosis (PDD) and photodynamic therapy (PDT). Several ALA-based drugs have been used for ALA-PDD and ALA-PDT in treating many (pre)cancerous diseases, including the female lower genital tract diseases, yet the ALA-induced fluorescent theranostics is needed to be explored further. In this paper, we are going to review the studies of the mechanisms and applications mainly on ALA-mediated photodynamic reactions and its effectiveness in treating female lower genital tract diseases.","PeriodicalId":502302,"journal":{"name":"Frontiers in Medicine","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141647812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-15DOI: 10.3389/fmed.2024.1384676
Anfal Hussain Mahmoud, Iman M. Talaat, Abdelaziz Tlili, R. Hamoudi
Congenital Anomalies of the Kidney and Urinary Tract (CAKUT) refer to a range of conditions that affect the kidney and urinary tract. These anomalies can be severe, such as kidney agenesis, or milder, such as vesicoureteral reflux. CAKUT affects over 1% of live births and accounts for 40–50% of cases of chronic kidney failure in children. The pathogenesis of CAKUT is caused by various environmental, genetic, and epigenetic factors that disrupt normal nephrogenesis. Environmental factors that can lead to CAKUT include maternal diabetes, obesity, malnutrition, alcohol consumption, or medications affecting kidneys development. Genetic factors can cause an imbalance in the metanephros and the ureteric bud interaction. Defects in specific genes such as PAX2, TBX18, NRIP1, REX, SIX2, BMP4, and chromosome 17 cause CAKUT. Over 50 genes have been identified as the root cause of this condition, with monogenetic variants causing up to 20% of all cases. CAKUTs can be diagnosed through fetal ultrasonography, but some anomalies may remain undetected. GWASs, Next Generation Sequencing for targeted and whole exome DNA sequencing may provide additional diagnostic methods. This review article highlights some the leading factors that cause CAKUT, which adversely affects kidney development and urinary tract function.
{"title":"Congenital anomalies of the kidney and urinary tract","authors":"Anfal Hussain Mahmoud, Iman M. Talaat, Abdelaziz Tlili, R. Hamoudi","doi":"10.3389/fmed.2024.1384676","DOIUrl":"https://doi.org/10.3389/fmed.2024.1384676","url":null,"abstract":"Congenital Anomalies of the Kidney and Urinary Tract (CAKUT) refer to a range of conditions that affect the kidney and urinary tract. These anomalies can be severe, such as kidney agenesis, or milder, such as vesicoureteral reflux. CAKUT affects over 1% of live births and accounts for 40–50% of cases of chronic kidney failure in children. The pathogenesis of CAKUT is caused by various environmental, genetic, and epigenetic factors that disrupt normal nephrogenesis. Environmental factors that can lead to CAKUT include maternal diabetes, obesity, malnutrition, alcohol consumption, or medications affecting kidneys development. Genetic factors can cause an imbalance in the metanephros and the ureteric bud interaction. Defects in specific genes such as PAX2, TBX18, NRIP1, REX, SIX2, BMP4, and chromosome 17 cause CAKUT. Over 50 genes have been identified as the root cause of this condition, with monogenetic variants causing up to 20% of all cases. CAKUTs can be diagnosed through fetal ultrasonography, but some anomalies may remain undetected. GWASs, Next Generation Sequencing for targeted and whole exome DNA sequencing may provide additional diagnostic methods. This review article highlights some the leading factors that cause CAKUT, which adversely affects kidney development and urinary tract function.","PeriodicalId":502302,"journal":{"name":"Frontiers in Medicine","volume":"114 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141646776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-12DOI: 10.3389/fmed.2024.1440572
Manrong Yu, Liqin Jiang, Jinhui Dai, Maria Liu
{"title":"Editorial: Spotlight on the relationship between visual experience and myopia","authors":"Manrong Yu, Liqin Jiang, Jinhui Dai, Maria Liu","doi":"10.3389/fmed.2024.1440572","DOIUrl":"https://doi.org/10.3389/fmed.2024.1440572","url":null,"abstract":"","PeriodicalId":502302,"journal":{"name":"Frontiers in Medicine","volume":"53 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141653066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-10DOI: 10.3389/fmed.2024.1455227
Carmelo Caldarella, M. Bauckneht, Ramin Sadeghi
{"title":"Editorial: Case reports in PET imaging 2023","authors":"Carmelo Caldarella, M. Bauckneht, Ramin Sadeghi","doi":"10.3389/fmed.2024.1455227","DOIUrl":"https://doi.org/10.3389/fmed.2024.1455227","url":null,"abstract":"","PeriodicalId":502302,"journal":{"name":"Frontiers in Medicine","volume":"36 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141661887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-09DOI: 10.3389/fmed.2024.1455319
{"title":"Erratum: Artificial intelligence based data curation: enabling a patient-centric European health data space","authors":"","doi":"10.3389/fmed.2024.1455319","DOIUrl":"https://doi.org/10.3389/fmed.2024.1455319","url":null,"abstract":"","PeriodicalId":502302,"journal":{"name":"Frontiers in Medicine","volume":"78 14","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141664693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Type 1 diabetes mellitus (T1DM) is frequently associated with various infections, including mycoses; however, the direct link between T1DM and fungal infections remains under-researched. This study utilizes a Mendelian randomization (MR) approach to investigate the potential causal relationship between T1DM and mycoses.Genetic variants associated with T1DM were sourced from the European Bioinformatics Institute database, while those related to fungal infections such as candidiasis, pneumocystosis, and aspergillosis were obtained from the Finngen database, focusing on European populations. The primary analysis was conducted using the inverse variance weighted (IVW) method, with additional insight from Mendelian randomization Egger regression (MR-Egger). Extensive sensitivity analyses assessed the robustness, diversity, and potential horizontal pleiotropy of our findings. Multivariable Mendelian randomization (MVMR) was employed to adjust for confounders, using both MVMR-IVW and MVMR-Egger to evaluate heterogeneity and pleiotropy.Genetically, the odds of developing candidiasis increased by 5% in individuals with T1DM, as determined by the IVW method (OR = 1.05; 95% CI 1.02–1.07, p = 0.0001), with a Bonferroni-adjusted p-value of 0.008. Sensitivity analyses indicated no significant issues with heterogeneity or pleiotropy. Adjustments for confounders such as body mass index, glycated hemoglobin levels, and white blood cell counts further supported these findings (OR = 1.08; 95% CI:1.03–1.13, p = 0.0006). Additional adjustments for immune cell counts, including CD4 and CD8 T cells and natural killer cells, also demonstrated significant results (OR = 1.04; 95% CI: 1.02–1.06, p = 0.0002). No causal associations were found between T1DM and other fungal infections like aspergillosis or pneumocystosis.This MR study suggests a genetic predisposition for increased susceptibility to candidiasis in individuals with T1DM. However, no causal links were established between T1DM and other mycoses, including aspergillosis and pneumocystosis.
1型糖尿病（T1DM）经常与包括真菌病在内的各种感染有关；然而，对T1DM与真菌感染之间的直接联系的研究仍然不足。与 T1DM 相关的基因变异来自欧洲生物信息研究所数据库，而与念珠菌病、肺囊肿病和曲霉菌病等真菌感染相关的基因变异则来自芬根数据库，重点研究欧洲人群。主要分析采用反方差加权法（IVW）进行，并从孟德尔随机化艾格回归（MR-Egger）中获得更多信息。广泛的敏感性分析评估了我们研究结果的稳健性、多样性和潜在的横向多义性。采用多变量孟德尔随机化（MVMR）调整混杂因素，同时使用MVMR-IVW和MVMR-Egger评估异质性和多义性。根据IVW方法确定，T1DM患者患念珠菌病的遗传几率增加了5%（OR = 1.05; 95% CI 1.02-1.07, p = 0.0001），Bonferroni调整后的P值为0.008。敏感性分析表明，异质性或多义性没有明显问题。对体重指数、糖化血红蛋白水平和白细胞计数等混杂因素的调整进一步支持了这些研究结果（OR = 1.08; 95% CI:1.03-1.13, p = 0.0006）。对包括 CD4 和 CD8 T 细胞以及自然杀伤细胞在内的免疫细胞计数的额外调整也显示出显著的结果（OR = 1.04；95% CI：1.02-1.06，p = 0.0002）。这项磁共振研究表明，T1DM 患者对念珠菌病的遗传易感性增加。然而，T1DM与曲霉菌病和肺囊肿病等其他真菌感染之间并没有因果关系。
{"title":"Causal relationship between type 1 diabetes mellitus and mycoses: a Mendelian randomization study","authors":"Xiaolan Chen, Chen Chen, Mingyan Wu, Shanmei Wang, Hongbin Jiang, Zhe Li, Yuetian Yu, Bing Li","doi":"10.3389/fmed.2024.1408297","DOIUrl":"https://doi.org/10.3389/fmed.2024.1408297","url":null,"abstract":"Type 1 diabetes mellitus (T1DM) is frequently associated with various infections, including mycoses; however, the direct link between T1DM and fungal infections remains under-researched. This study utilizes a Mendelian randomization (MR) approach to investigate the potential causal relationship between T1DM and mycoses.Genetic variants associated with T1DM were sourced from the European Bioinformatics Institute database, while those related to fungal infections such as candidiasis, pneumocystosis, and aspergillosis were obtained from the Finngen database, focusing on European populations. The primary analysis was conducted using the inverse variance weighted (IVW) method, with additional insight from Mendelian randomization Egger regression (MR-Egger). Extensive sensitivity analyses assessed the robustness, diversity, and potential horizontal pleiotropy of our findings. Multivariable Mendelian randomization (MVMR) was employed to adjust for confounders, using both MVMR-IVW and MVMR-Egger to evaluate heterogeneity and pleiotropy.Genetically, the odds of developing candidiasis increased by 5% in individuals with T1DM, as determined by the IVW method (OR = 1.05; 95% CI 1.02–1.07, p = 0.0001), with a Bonferroni-adjusted p-value of 0.008. Sensitivity analyses indicated no significant issues with heterogeneity or pleiotropy. Adjustments for confounders such as body mass index, glycated hemoglobin levels, and white blood cell counts further supported these findings (OR = 1.08; 95% CI:1.03–1.13, p = 0.0006). Additional adjustments for immune cell counts, including CD4 and CD8 T cells and natural killer cells, also demonstrated significant results (OR = 1.04; 95% CI: 1.02–1.06, p = 0.0002). No causal associations were found between T1DM and other fungal infections like aspergillosis or pneumocystosis.This MR study suggests a genetic predisposition for increased susceptibility to candidiasis in individuals with T1DM. However, no causal links were established between T1DM and other mycoses, including aspergillosis and pneumocystosis.","PeriodicalId":502302,"journal":{"name":"Frontiers in Medicine","volume":"108 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141342439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-14DOI: 10.3389/fmed.2024.1402768
Yifei Lin, Qingquan Chen, Tebin Chen
As machine learning progresses, techniques such as neural networks, decision trees, and support vector machines are being increasingly applied in the medical domain, especially for tasks involving large datasets, such as cell detection, recognition, classification, and visualization. Within the domain of bone marrow cell morphology analysis, deep learning offers substantial benefits due to its robustness, ability for automatic feature learning, and strong image characterization capabilities. Deep neural networks are a machine learning paradigm specifically tailored for image processing applications. Artificial intelligence serves as a potent tool in supporting the diagnostic process of clinical bone marrow cell morphology. Despite the potential of artificial intelligence to augment clinical diagnostics in this domain, manual analysis of bone marrow cell morphology remains the gold standard and an indispensable tool for identifying, diagnosing, and assessing the efficacy of hematologic disorders. However, the traditional manual approach is not without limitations and shortcomings, necessitating, the exploration of automated solutions for examining and analyzing bone marrow cytomorphology. This review provides a multidimensional account of six bone marrow cell morphology processes: automated bone marrow cell morphology detection, automated bone marrow cell morphology segmentation, automated bone marrow cell morphology identification, automated bone marrow cell morphology classification, automated bone marrow cell morphology enumeration, and automated bone marrow cell morphology diagnosis. Highlighting the attractiveness and potential of machine learning systems based on bone marrow cell morphology, the review synthesizes current research and recent advances in the application of machine learning in this field. The objective of this review is to offer recommendations to hematologists for selecting the most suitable machine learning algorithms to automate bone marrow cell morphology examinations, enabling swift and precise analysis of bone marrow cytopathic trends for early disease identification and diagnosis. Furthermore, the review endeavors to delineate potential future research avenues for machine learning-based applications in bone marrow cell morphology analysis.
{"title":"Recent advancements in machine learning for bone marrow cell morphology analysis","authors":"Yifei Lin, Qingquan Chen, Tebin Chen","doi":"10.3389/fmed.2024.1402768","DOIUrl":"https://doi.org/10.3389/fmed.2024.1402768","url":null,"abstract":"As machine learning progresses, techniques such as neural networks, decision trees, and support vector machines are being increasingly applied in the medical domain, especially for tasks involving large datasets, such as cell detection, recognition, classification, and visualization. Within the domain of bone marrow cell morphology analysis, deep learning offers substantial benefits due to its robustness, ability for automatic feature learning, and strong image characterization capabilities. Deep neural networks are a machine learning paradigm specifically tailored for image processing applications. Artificial intelligence serves as a potent tool in supporting the diagnostic process of clinical bone marrow cell morphology. Despite the potential of artificial intelligence to augment clinical diagnostics in this domain, manual analysis of bone marrow cell morphology remains the gold standard and an indispensable tool for identifying, diagnosing, and assessing the efficacy of hematologic disorders. However, the traditional manual approach is not without limitations and shortcomings, necessitating, the exploration of automated solutions for examining and analyzing bone marrow cytomorphology. This review provides a multidimensional account of six bone marrow cell morphology processes: automated bone marrow cell morphology detection, automated bone marrow cell morphology segmentation, automated bone marrow cell morphology identification, automated bone marrow cell morphology classification, automated bone marrow cell morphology enumeration, and automated bone marrow cell morphology diagnosis. Highlighting the attractiveness and potential of machine learning systems based on bone marrow cell morphology, the review synthesizes current research and recent advances in the application of machine learning in this field. The objective of this review is to offer recommendations to hematologists for selecting the most suitable machine learning algorithms to automate bone marrow cell morphology examinations, enabling swift and precise analysis of bone marrow cytopathic trends for early disease identification and diagnosis. Furthermore, the review endeavors to delineate potential future research avenues for machine learning-based applications in bone marrow cell morphology analysis.","PeriodicalId":502302,"journal":{"name":"Frontiers in Medicine","volume":"55 34","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141339258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-14DOI: 10.3389/fmed.2024.1407830
Kai Zhao, Yiming Liu, M. Jing, Wenhan Cai, Jiamei Jin, Zirui Zhu, Leilei Shen, Jiaxin Wen, Zhiqiang Xue
We aimed to assess the impact of myasthenia gravis (MG) on the long-term prognosis in patients with thymoma after surgery and identify related prognostic factors or predictors.This retrospective observational study included 509 patients with thymoma (thymoma combined with MG [MG group] and thymoma alone [non-MG group]). Propensity score matching was performed to obtain comparable subsets of 96 patients in each group. A comparative analysis was conducted on various parameters.Before matching, the 10-year survival and recurrence-free survival rates in both groups were 93.8 and 98.4%, and 85.9 and 93.4%, respectively, with no statistically significant difference observed in the survival curves between the groups (p > 0.05). After propensity score matching, 96 matched pairs of patients from both groups were created. The 10-year survival and recurrence-free survival rates in these matched pairs were 96.9 and 97.7%, and 86.9 and 91.1%, respectively, with no statistical significance in the survival curves between the groups (p > 0.05). Univariate analysis of patients with thymoma postoperatively revealed that the World Health Organization histopathological classification, Masaoka–Koga stage, Tumor Node Metastasis stage, resection status, and postoperative adjuvant therapy were potentially associated with tumor recurrence after thymoma surgery. Multivariate analysis demonstrated that the Masaoka–Koga stage and postoperative adjuvant therapy independently predicted the risk of recurrence in patients with thymoma after surgery.There was no difference in prognosis in patients with thymoma with or without MG. The Masaoka–Koga stage has emerged as an independent prognostic factor affecting recurrence-free survival in patients with thymoma, while postoperative adjuvant therapy represents a poor prognostic factor.
{"title":"Long-term prognosis in patients with thymoma combined with myasthenia gravis: a propensity score-matching analysis","authors":"Kai Zhao, Yiming Liu, M. Jing, Wenhan Cai, Jiamei Jin, Zirui Zhu, Leilei Shen, Jiaxin Wen, Zhiqiang Xue","doi":"10.3389/fmed.2024.1407830","DOIUrl":"https://doi.org/10.3389/fmed.2024.1407830","url":null,"abstract":"We aimed to assess the impact of myasthenia gravis (MG) on the long-term prognosis in patients with thymoma after surgery and identify related prognostic factors or predictors.This retrospective observational study included 509 patients with thymoma (thymoma combined with MG [MG group] and thymoma alone [non-MG group]). Propensity score matching was performed to obtain comparable subsets of 96 patients in each group. A comparative analysis was conducted on various parameters.Before matching, the 10-year survival and recurrence-free survival rates in both groups were 93.8 and 98.4%, and 85.9 and 93.4%, respectively, with no statistically significant difference observed in the survival curves between the groups (p > 0.05). After propensity score matching, 96 matched pairs of patients from both groups were created. The 10-year survival and recurrence-free survival rates in these matched pairs were 96.9 and 97.7%, and 86.9 and 91.1%, respectively, with no statistical significance in the survival curves between the groups (p > 0.05). Univariate analysis of patients with thymoma postoperatively revealed that the World Health Organization histopathological classification, Masaoka–Koga stage, Tumor Node Metastasis stage, resection status, and postoperative adjuvant therapy were potentially associated with tumor recurrence after thymoma surgery. Multivariate analysis demonstrated that the Masaoka–Koga stage and postoperative adjuvant therapy independently predicted the risk of recurrence in patients with thymoma after surgery.There was no difference in prognosis in patients with thymoma with or without MG. The Masaoka–Koga stage has emerged as an independent prognostic factor affecting recurrence-free survival in patients with thymoma, while postoperative adjuvant therapy represents a poor prognostic factor.","PeriodicalId":502302,"journal":{"name":"Frontiers in Medicine","volume":"111 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141342491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-14DOI: 10.3389/fmed.2024.1368977
Yanjiang Liu, Tao Zhang, Kejian Pan, He Wei
Intestinal fibrosis is a common complication of chronic intestinal diseases with the characteristics of fibroblast proliferation and extracellular matrix deposition after chronic inflammation, leading to lumen narrowing, structural and functional damage to the intestines, and life inconvenience for the patients. However, anti-inflammatory drugs are currently generally not effective in overcoming intestinal fibrosis making surgery the main treatment method. The development of intestinal fibrosis is a slow process and its onset may be the result of the combined action of inflammatory cells, local cytokines, and intestinal stromal cells. The aim of this study is to elucidate the pathogenesis [e.g., extracellular matrix (ECM), cytokines and chemokines, epithelial-mesenchymal transition (EMT), differentiation of fibroblast to myofibroblast and intestinal microbiota] underlying the development of intestinal fibrosis and to explore therapeutic advances (such as regulating ECM, cytokines, chemokines, EMT, differentiation of fibroblast to myofibroblast and targeting TGF-β) based on the pathogenesis in order to gain new insights into the prevention and treatment of intestinal fibrosis.
{"title":"Mechanisms and therapeutic research progress in intestinal fibrosis","authors":"Yanjiang Liu, Tao Zhang, Kejian Pan, He Wei","doi":"10.3389/fmed.2024.1368977","DOIUrl":"https://doi.org/10.3389/fmed.2024.1368977","url":null,"abstract":"Intestinal fibrosis is a common complication of chronic intestinal diseases with the characteristics of fibroblast proliferation and extracellular matrix deposition after chronic inflammation, leading to lumen narrowing, structural and functional damage to the intestines, and life inconvenience for the patients. However, anti-inflammatory drugs are currently generally not effective in overcoming intestinal fibrosis making surgery the main treatment method. The development of intestinal fibrosis is a slow process and its onset may be the result of the combined action of inflammatory cells, local cytokines, and intestinal stromal cells. The aim of this study is to elucidate the pathogenesis [e.g., extracellular matrix (ECM), cytokines and chemokines, epithelial-mesenchymal transition (EMT), differentiation of fibroblast to myofibroblast and intestinal microbiota] underlying the development of intestinal fibrosis and to explore therapeutic advances (such as regulating ECM, cytokines, chemokines, EMT, differentiation of fibroblast to myofibroblast and targeting TGF-β) based on the pathogenesis in order to gain new insights into the prevention and treatment of intestinal fibrosis.","PeriodicalId":502302,"journal":{"name":"Frontiers in Medicine","volume":"28 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141342583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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