{"title":"","authors":"Panagiota S. Filippou, and , Priyanka Dey*, ","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"24 7","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":3.8,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.jproteome.5c00088","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144548130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Juan C. Rojas Echeverri*, Sanja Milkovska-Stamenova, Ulf Wagner and Ralf Hoffmann,
{"title":"","authors":"Juan C. Rojas Echeverri*, Sanja Milkovska-Stamenova, Ulf Wagner and Ralf Hoffmann, ","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"24 7","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":3.8,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.jproteome.5c00093","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144548150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Agata N. Makar, Jocelyn Holkham, Sergio Lilla, Simon Wilkinson and Alexander von Kriegsheim*,
{"title":"","authors":"Agata N. Makar, Jocelyn Holkham, Sergio Lilla, Simon Wilkinson and Alexander von Kriegsheim*, ","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"24 7","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":3.8,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.jproteome.5c00268","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144548151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jean Lucas Kremer, Henrique Sanchez Ortega, Talita Souza-Siqueira, Claudia Blanes Angeli, Leo Kei Iwai, Giuseppe Palmisano and Claudimara Ferini Pacicco Lotfi*,
{"title":"","authors":"Jean Lucas Kremer, Henrique Sanchez Ortega, Talita Souza-Siqueira, Claudia Blanes Angeli, Leo Kei Iwai, Giuseppe Palmisano and Claudimara Ferini Pacicco Lotfi*, ","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"24 7","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":3.8,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.jproteome.5c00026","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144548153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Muhammad Salman Sajid, Rency S. Varghese, Alexander Kroemer and Habtom W. Ressom*,
{"title":"","authors":"Muhammad Salman Sajid, Rency S. Varghese, Alexander Kroemer and Habtom W. Ressom*, ","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":"24 7","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":3.8,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.jproteome.5c00231","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144548166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Circulating Proteomic Panels for Noninvasive Diagnosis and Prognostication of Thromboangiitis Obliterans.","authors":"Gang Fang, Yuan Fang, Lutong Yan, Bichen Ren, Jingyang Luan, Ziang Zuo, Lingwei Zou, Yuning Wang, Shiyang Gu, Tianyue Pan, Hao Liu, Xiaolang Jiang, Yige Lu, Lu Yu, Chenke Ding, Zheng Wei, Peng Liu, Weiguo Fu, Zhihui Dong","doi":"10.1021/acs.jproteome.4c01101","DOIUrl":"https://doi.org/10.1021/acs.jproteome.4c01101","url":null,"abstract":"<p><p>Thromboangiitis obliterans (TAO) is often diagnosed late and characterized by high amputation rates. TAO-specific early diagnostic and disease-staging biomarkers are urgently needed. A staged mass spectrometry (MS)-based discovery-verification-validation workflow was utilized in this study. Ten healthy controls (HCs) and 20 TAOs were included for data-independent acquisition (DIA)-MS quantitative proteomic analysis for the discovery cohort. The DIA-MS analysis acquired 842 identified proteins and 470 quantifiable proteins. Twenty-three candidate biomarkers were further quantified using targeted proteomics based on parallel monitoring reaction (PRM) analysis in the verification stage. A 9-protein and a 7-protein serum biomarker panels were built by machine learning to accurately distinguish TAOs from HCs and active TAOs (A-TAOs) from inactive TAOs. A combined prognostic panel consisting of serum proteins and clinical indicators was established, allowing for risk stratification of A-TAOs. During the validation stage, an independent prospective validation cohort was recruited to validate the proteomic panels based on the enzyme-linked immunosorbent assay analysis, demonstrating the stability and robustness of the predictive models. This study presented the serum proteomic landscape of a TAO cohort and provided novel insights into further biological research. Meanwhile, serum protein signatures have a great potential to improve the early diagnosis and risk stratification in TAOs.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144537422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nguyen Tran Nam Tien, Nguyen Thi Hai Yen, Nguyen Ky Phat, Nguyen Ky Anh, Nguyen Quang Thu, Cho Eunsu, Ho-Sook Kim, Vu Dinh Hoa, Duc Ninh Nguyen, Dong Hyun Kim, Jee Youn Oh, Nguyen Phuoc Long
{"title":"Multiomics and Machine Learning Identify Immunometabolic Biomarkers for Active Tuberculosis Diagnosis Against Nontuberculous Mycobacteria and Latent Tuberculosis Infection.","authors":"Nguyen Tran Nam Tien, Nguyen Thi Hai Yen, Nguyen Ky Phat, Nguyen Ky Anh, Nguyen Quang Thu, Cho Eunsu, Ho-Sook Kim, Vu Dinh Hoa, Duc Ninh Nguyen, Dong Hyun Kim, Jee Youn Oh, Nguyen Phuoc Long","doi":"10.1021/acs.jproteome.4c00989","DOIUrl":"https://doi.org/10.1021/acs.jproteome.4c00989","url":null,"abstract":"<p><p>This study utilized multiomics combined with a comprehensive machine learning-based predictive modeling approach to identify, validate, and prioritize circulating immunometabolic biomarkers in distinguishing tuberculosis (TB) from nontuberculous mycobacteria (NTM) infections, latent tuberculosis infection (LTBI), and other lung diseases (ODx). Functional omics data were collected from two discovery cohorts (76 patients in the TB-NTM cohort and 72 patients in the TB-LTBI-ODx cohort) and one validation cohort (68 TB patients and 30 LTBI patients). Mutiomics integrative analysis identified three plasma multiome biosignatures that could distinguish active TB from non-TB with promising performance, achieving area under the receiver operating characteristic curve (AUC) values of 0.70-0.90 across groups in both the discovery and validation cohorts. The lipid PC(14:0_22:6) emerged as the most important predictor for differentiating active TB from non-TB controls, consistently presenting at lower levels in the active TB group compared with its counterparts. Further validation using two independent external data sets demonstrated AUCs of 0.77-1.00, confirming the biomarkers' efficacy in distinguishing active TB from other non-TB groups. Our investigation highlights lipids as promising biomarkers for classifying TB, NTM, LTBI, and ODx. Rigorous validation further indicates PC(14:0_22:6) as a TB differential diagnostic biomarker candidate.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144537423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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