Review
Multidisciplinary Sciences
Yafei Guo, Lixia Yang, Shuran Shao, Nanjun Zhang, Yimin Hua, Kaiyu Zhou, Fan Ma, Xiaoliang Liu
Summary: This case report describes a severe Mycoplasma pneumoniae pneumonia patient who developed coronary artery dilation (CAD). It emphasizes the importance for physicians to consider the possibility of CAD in patients with MP infection, not limited to Kawasaki disease.
Article
Public, Environmental & Occupational Health
Kerstin D. Rosenberger, Lam Phung Khanh, Frank Tobian, Ngoun Chanpheaktra, Varun Kumar, Lucy Chai See Lum, Jameela Sathar, Ernesto Pleite's Sandoval, Gabriela M. Maron, Ida Safitri Laksono, Yodi Mahendradhata, Malabika Sarker, Ridwanur Rahman, Andrea Caprara, Bruno Souza Benevides, Ernesto T. A. Marques, Tereza Magalhaes, Patricia Brasil, Guilherme Amaral Calvet, Adriana Tami, Sarah E. Bethencourt, Tam Dong Thi Hoai, Kieu Nguyen Tan Thanh, Ngoc Tran Van, Nam Nguyen Tran, Viet Do Chau, Sophie Yacoub, Kinh Nguyen Van, Maria G. Guzman, Pedro A. Martinez, Quyen Nguyen Than Ha, Cameron P. Simmons, Bridget A. Wills, Ronald B. Geskus, Thomas Jaenisch
Summary: This study aimed to improve the early diagnosis of dengue, especially in resource-limited settings where distinguishing dengue from other febrile illnesses is crucial. The study found that platelet count and white blood cell count were strongly associated with dengue, and the importance of serial measurements over time was highlighted.
LANCET GLOBAL HEALTH
(2023)
Article
Multidisciplinary Sciences
Xin Guo, Jinwen Liao, Xue Fan, Mingguo Xu
Summary: We developed a diagnostic predictive model to differentiate Kawasaki disease (KD) from other febrile diseases using eosinophil-to-lymphocyte ratio (ELR) and other biomarkers. The results showed that ELR was significantly increased in patients with KD. The prediction model constructed with ELR and other indicators had good diagnostic performance.
SCIENTIFIC REPORTS
(2023)
Article
Rheumatology
Kailey E. Brodeur, Meng Liu, Daniel Ibanez, Mareike J. de Groot, Liang Chen, Yan Du, Eman Seyal, Raquel Laza-Briviesca, Annette Baker, Joyce C. Chang, Margaret H. Chang, Megan Day-Lewis, Fatma Dedeoglu, Audrey Dionne, Sarah D. de Ferranti, Kevin G. Friedman, Olha Halyabar, Mindy S. Lo, Esra Meidan, Robert P. Sundel, Lauren A. Henderson, Peter A. Nigrovic, Jane W. Newburger, Mary Beth Son, Pui Y. Lee
Summary: In this study, the researchers identified key diagnostic markers for distinguishing Kawasaki disease (KD) from other pediatric inflammatory diseases. They found that elevated levels of IL-17 family cytokines were a hallmark of KD and could help differentiate KD from its clinical mimics.
ARTHRITIS & RHEUMATOLOGY
(2023)
Article
Pediatrics
Rumeysa Yalcinkaya, Fatma Nur Oz, Turkan Aydin Teke, Ayse Kaman, Sevgi Yasar Durmus, Utku Arman Orun, Gonul Tanir
Summary: Diagnosing Kawasaki disease in infants is challenging, but lower MPV and albumin levels may serve as supportive parameters to differentiate it from other febrile conditions.
JOURNAL OF PEDIATRIC RESEARCH
(2022)
Article
Medicine, General & Internal
Chih-Min Tsai, Chun-Hung Richard Lin, Ho-Chang Kuo, Fu-Jen Cheng, Hong-Ren Yu, Tsung-Chi Hung, Chuan-Sheng Hung, Chih-Ming Huang, Yu-Cheng Chu, Ying-Hsien Huang
Summary: Early recognition of Kawasaki disease is crucial for appropriate treatment to prevent cardiac complications. This study developed a machine learning model using objective parameters to differentiate Kawasaki disease from other febrile illnesses. The model showed excellent performance in distinguishing Kawasaki disease with high sensitivity, specificity, and accuracy.
Article
Immunology
Ho-Chang Kuo, Shiying Hao, Bo Jin, C. James Chou, Zhi Han, Ling-Sai Chang, Ying-Hsien Huang, Kuoyuan Hwa, John C. Whitin, Karl G. Sylvester, Charitha D. Reddy, Henry Chubb, Scott R. Ceresnak, John T. Kanegaye, Adriana H. Tremoulet, Jane C. Burns, Doff McElhinney, Harvey J. Cohen, Xuefeng B. Ling
Summary: This study validates the applicability of our algorithm in Taiwan, showing high sensitivity and positive predictive value.
FRONTIERS IN IMMUNOLOGY
(2022)
Article
Chemistry, Physical
Shiyue Yang, Graeme M. Day
Summary: The QR-BH method combines the low-discrepancy sampling of QR sequences with the BH efficiency in locating low energy structures, allowing for faster location of low energy structures while efficiently locating higher energy structures important for identifying important polymorphs.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2021)
Article
Public, Environmental & Occupational Health
Patrick Gerardin, Olivier Maillard, Lea Bruneau, Frederic Accot, Florian Legrand, Patrice Poubeau, Rodolphe Manaquin, Fanny Andry, Antoine Bertolotti, Cecile Levin
Summary: This cohort study developed two scores to differentiate COVID-19 and dengue from other febrile illnesses. These scores, validated through multinomial logistic regression and bootstrapping, showed high accuracy and reliability in predicting the respective diseases. The study concluded that the COVIDENGUE scores were effective in distinguishing COVID-19 and dengue from other febrile illnesses in a co-epidemic setting at a SARS-CoV-2 testing center.
TRAVEL MEDICINE AND INFECTIOUS DISEASE
(2022)
Article
Public, Environmental & Occupational Health
Daniel Camprubi-Ferrer, Ludovico Cobuccio, Steven Van Den Broucke, Leire Balerdi-Sarasola, Blaise Genton, Emmanuel Bottieau, Jessica Navero-Castillejos, Miguel J. Martinez, Corinne Jay, Anne Grange, Stephanie Borland, Mike Vaughn, Natalia Rodriguez-Valero, Alex Almuedo-Riera, Valerie D'Acremont, Carme Subira, Tessa de Alba, Angeline Cruz, Marjan Van Esbroeck, Crystal Smith, Ashley Hillman, Brandon Hanberg, Rob Trauscht, Nerissa Spampanato, Jose Munoz
Summary: This study evaluated a prototype panel of a multiplex nucleic acid amplification test (NAAT) in detecting different relevant pathogens in returning travelers with fever. The results showed that the prototype panel had high sensitivity and specificity in diagnosing malaria, dengue, and chikungunya, but had lower sensitivity for Zika virus and other important travel-related bacterial infections.
JOURNAL OF TRAVEL MEDICINE
(2023)
Article
Mathematics
Jose Antonio Roldan-Nofuentes, Saad Bouh Regad
Summary: This article compares the average kappa coefficients of two binary diagnostic tests in situations of partial disease verification. Computational methods such as the EM algorithm and the SEM algorithm are applied to estimate parameters and variances-covariances. Simulation experiments show that the proposed method has good asymptotic behavior for hypothesis tests.
Review
Infectious Diseases
Dylan Kain, Dale A. Jechel, Rochelle G. Melvin, Farah Jazuli, Michael Klowak, Jordan Mah, Arghavan Omidi, Ruwandi Kariyawasam, Stefanie Klowak, Andrea K. Boggild
Summary: The purpose of this review was to identify hematological patterns that can help frontline clinicians diagnose dengue fever. The study found that thrombocytopenia, neutropenia, and lymphopenia were common features in dengue patients during acute illness, with the combination of these three characteristics showing a 30-fold higher likelihood in dengue patients compared to those with other febrile illnesses. This suggests that these hematological patterns can guide early diagnostic and treatment approaches for patients suspected of having dengue fever.
CURRENT INFECTIOUS DISEASE REPORTS
(2021)
Article
Chemistry, Medicinal
Andrew J. Hoover, Martin Spale, Brian Lahue, Danny A. Bitton
Summary: To address recurring issues in drug discovery, a new open-source application called Matcher has been developed for matched molecular pair (MMP) analysis, which helps understand the relationship between chemical structure and function. Matcher provides novel search algorithms, automated querying-to-visualization, and requires no programming expertise. It enables users to have unprecedented control over MMP transformations and access various data representations with a few clicks, leading to confident and accelerated decision making.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Biochemistry & Molecular Biology
Vasileios C. Pezoulas, Costas Papaloukas, Maeva Veyssiere, Andreas Goules, Athanasios G. Tzioufas, Vassili Soumelis, Dimitrios Fotiadis
Summary: A computational workflow was developed to cluster Kawasaki disease patients and identify candidate diagnostic biomarker genes. Five novel genes were discovered as potential biomarkers for Kawasaki disease diagnosis. Training classifiers on these genes showed improved accuracy, sensitivity, and specificity compared to known genes.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2021)
Article
Engineering, Electrical & Electronic
Erik Leitinger, Alexander Venus, Bryan Teague, Florian Meyer
Summary: Multipath-based SLAM is an emerging paradigm for accurate indoor localization. Existing methods have limitations in accuracy and speed due to ignoring geometric constraints between different paths. This paper introduces an improved statistical model and estimation method that utilize multiple virtual anchors (MVA) for statistical modeling and ray-tracing (RT) for checking path availability, resulting in significant improvements in estimation accuracy.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2023)
Article
Obstetrics & Gynecology
Mohammad S. Ghaemi, Adi L. Tarca, Roberto Romero, Natalie Stanley, Ramin Fallahzadeh, Athena Tanada, Anthony Culos, Kazuo Ando, Xiaoyuan Han, Yair J. Blumenfeld, Maurice L. Druzin, Yasser Y. El-Sayed, Ronald S. Gibbs, Virginia D. Winn, Kevin Contrepois, Xuefeng B. Ling, Ronald J. Wong, Gary M. Shaw, David K. Stevenson, Brice Gaudilliere, Nima Aghaeepour, Martin S. Angst
Summary: The study aimed to examine proteomic signatures predictive of preeclampsia in two cohorts of pregnant women and found that the models derived in each cohort failed validation in the other. Proteomic models predicting gestational age, however, were readily validated across both cohorts, indicating the need for diverse and large patient populations in omic studies of syndromes like preeclampsia.
JOURNAL OF MATERNAL-FETAL & NEONATAL MEDICINE
(2022)
Meeting Abstract
Oncology
Sheeno P. Thyparambil, Xiurui Zhu, Yani Zhang, Hui Sun, Junjie Peng, Sanjun Cai, Yaqi Li, Chen Fu, Pingping Bao, Shiying Hao, Zhen Li, Yun Ding, Xiaoming Yao, Wei-Li Liao, Robert Heaton, Zhi Han, Lu Tian, James Schilling, Karl G. Sylvester, Xuefeng Ling
JOURNAL OF CLINICAL ONCOLOGY
(2022)
Article
Hematology
Chor-Cheung Frankie Tam, Yap-Hang Chan, Yuen-Kwun Wong, Zhen Li, Xiurui Zhu, Kuo-Jung Su, Anindita Ganguly, Kuoyuan Hwa, Xuefeng B. Ling, Hung-Fat Tse
Summary: This study compared the effects of ticagrelor and aspirin monotherapy on vascular endothelial function in patients with prior acute coronary syndrome. The results showed that ticagrelor significantly improved brachial flow-mediated dilation compared with aspirin, but had no significant effect on platelet activation markers and endothelial progenitor cell count. The analysis of multi-omics pathways also found associations between ticagrelor treatment and changes in metabolism and lipid levels.
ARTERIOSCLEROSIS THROMBOSIS AND VASCULAR BIOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Linmin Zhu, Qianyang Huang, Xiao Li, Bo Jin, Yun Ding, C. James Chou, Kuo-Jung Su, Yani Zhang, Xingguo Chen, Kuo Yuan Hwa, Sheeno Thyparambil, Weili Liao, Zhi Han, Richard Mortensen, Yi Jin, Zhen Li, James Schilling, Zhen Li, Karl G. Sylvester, Xuguo Sun, Xuefeng B. Ling
Summary: This study focused on discovering serum metabolic biomarkers of diabetes through mass spectrometry metabolomics, and demonstrated that these markers effectively differentiate diabetes or pre-diabetes (Pre-T2DM) patients from healthy controls.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2022)
Article
Cardiac & Cardiovascular Systems
Lindsay A. Edwards, Fei Feng, Mehreen Iqbal, Yong Fu, Amy Sanyahumbi, Shiying Hao, Doff B. McElhinney, X. Bruce Ling, Craig Sable, Jiajia Luo
Summary: In this study, a machine learning model was developed to identify mitral regurgitation (MR) on echocardiography. The model achieved high accuracy and F1 score in classifying the view and detecting MR. This is a promising step towards machine learning-based diagnosis of valvular heart disease in pediatric echocardiography.
JOURNAL OF THE AMERICAN SOCIETY OF ECHOCARDIOGRAPHY
(2023)
Article
Immunology
Ho-Chang Kuo, Shiying Hao, Bo Jin, C. James Chou, Zhi Han, Ling-Sai Chang, Ying-Hsien Huang, Kuoyuan Hwa, John C. Whitin, Karl G. Sylvester, Charitha D. Reddy, Henry Chubb, Scott R. Ceresnak, John T. Kanegaye, Adriana H. Tremoulet, Jane C. Burns, Doff McElhinney, Harvey J. Cohen, Xuefeng B. Ling
Summary: This study validates the applicability of our algorithm in Taiwan, showing high sensitivity and positive predictive value.
FRONTIERS IN IMMUNOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Ivana Maric, Kevin Contrepois, Mira N. Moufarrej, Ina A. Stelzer, Dorien Feyaerts, Xiaoyuan Han, Andy Tang, Natalie Stanley, Ronald J. Wong, Gavin M. Traber, Mathew Ellenberger, Alan L. Chang, Ramin Fallahzadeh, Huda Nassar, Martin Becker, Maria Xenochristou, Camilo Espinosa, Davide De Francesco, Mohammad S. Ghaemi, Elizabeth K. Costello, Anthony Culos, Xuefeng B. Ling, Karl G. Sylvester, Gary L. Darmstadt, Virginia D. Winn, Gary M. Shaw, David A. Relman, Stephen R. Quake, Martin S. Angst, Michael P. Snyder, David K. Stevenson, Brice Gaudilliere, Nima Aghaeepour
Summary: We developed machine-learning models to predict preeclampsia during early pregnancy using omics datasets. Our model based on urine metabolites achieved high accuracy and was validated on an independent cohort. Integration of multiomics data and immune cytometry data revealed novel associations and improved prediction accuracy. These findings provide a basis for a simple, early diagnostic test for preeclampsia.
Article
Biochemistry & Molecular Biology
Yaqi Zhang, Karl G. G. Sylvester, Bo Jin, Ronald J. J. Wong, James Schilling, C. James Chou, Zhi Han, Ruben Y. Y. Luo, Lu Tian, Subhashini Ladella, Lihong Mo, Ivana Maric, Yair J. J. Blumenfeld, Gary L. L. Darmstadt, Gary M. M. Shaw, David K. K. Stevenson, John C. C. Whitin, Harvey J. J. Cohen, Doff B. B. McElhinney, Xuefeng B. B. Ling
Summary: This study identified seven metabolomic biomarkers in urine samples collected from 60 pregnant women, using liquid chromatography mass spectrometry (LCMS/MS). A predictive model based on these biomarkers was developed using the XGBoost algorithm and showed good performance in identifying individuals at risk of developing preeclampsia.
Article
Oncology
Linfeng Chen, Qiming Tang, Keying Zhang, Qianyang Huang, Yun Ding, Bo Jin, Szumam Liu, Kuoyuan Hwa, C. James Chou, Yani Zhang, Sheeno Thyparambil, Weili Liao, Zhi Han, Richard Mortensen, James Schilling, Zhen Li, Robert Heaton, Lu Tian, Harvey J. Cohen, Karl G. Sylvester, Rebecca C. Arent, Xinyang Zhao, Doff B. Mcelhinney, Yumei Wu, Wenpei Bai, Xuefeng B. Ling
Summary: This study explores the potential use of metabolic changes as biomarkers for assessing ovarian cancer. The research identifies key gene expression pathways and proposes symmetric dimethylarginine (SDMA) and arginine as potential liquid biopsy biomarkers for ovarian cancer assessment.
Correction
Oncology
Scott R. Ceresnak, Yaqi Zhang, Xuefeng B. Ling, Kuo Jung Su, Qiming Tang, Bo Jin, James Schilling, C. James Chou, Zhi Han, Brendan J. Floyd, John C. Whitin, Kuo Yuan Hwa, Karl G. Sylvester, Henry Chubb, Ruben Y. Luo, Lu Tian, Harvey J. Cohen, Doff B. Mcelhinney
BIOMARKER RESEARCH
(2023)
Letter
Oncology
Scott R. Ceresnak, Yaqi Zhang, Xuefeng B. Ling, Kuo Jung Su, Qiming Tang, Bo Jin, James Schilling, C. James Chou, Zhi Han, Brendan J. Floyd, John C. Whitin, Kuo Yuan Hwa, Karl G. Sylvester, Henry Chubb, Ruben Y. Luo, Lu Tian, Harvey J. Cohen, Doff B. Mcelhinney
Summary: This study aimed to evaluate the feasibility of using dried blood spot (DBS) for screening and classifying congenital heart disease (CHD). The study analyzed metabolites in DBS samples to identify metabolic abnormalities in CHD patients and discovered potential biomarkers for CHD assessment and subtype classification. The study demonstrated for the first time that it is feasible to validate metabolite profiling results using long-term stored DBS samples.
BIOMARKER RESEARCH
(2023)
Article
Medical Informatics
Jonathan Y. Lam, Chisato Shimizu, Adriana H. Tremoulet, Emelia Bainto, Samantha C. Roberts, Nipha Sivilay, Michael A. Gardiner, John T. Kanegaye, Alexander H. Hogan, Juan C. Salazar, Sindhu Mohandas, Jacqueline R. Szmuszkovicz, Simran Mahanta, Audrey Dionne, Jane W. Newburger, Emily Ansusinha, Roberta L. DeBiasi, Shiying Hao, Xuefeng B. Ling, Harvey J. Cohen, Shamim Nemati, Jane C. Burns
Summary: This study aimed to develop and validate an artificial intelligence algorithm that can distinguish between MIS-C, Kawasaki disease, and other similar febrile illnesses to assist in the diagnosis of patients in the emergency department and acute care setting.
LANCET DIGITAL HEALTH
(2022)
Article
Nutrition & Dietetics
Chengyin Ye, Jinghua Wu, Jonathan D. Reiss, Tiffany J. Sinclair, David K. Stevenson, Gary M. Shaw, Donald H. Chace, Reese H. Clark, Lawrence S. Prince, Xuefeng Bruce Ling, Karl G. Sylvester
Summary: By studying the metabolic patterns during the development of bronchopulmonary dysplasia (BPD) in premature infants, this research identified 27 metabolic variables associated with BPD. The findings have implications for the prevention and management of BPD.