Article
Radiology, Nuclear Medicine & Medical Imaging
Jordana Phillips, Janeiro U. Achibiri, Geunwon Kim, Liza M. Quintana, Rashmi J. Mehta, Tejas S. Mehta
Summary: The purpose of this paper is to characterize true and false positive findings on contrast-enhanced mammography (CEM) and correlate enhancement pattern and method of detection with pathology outcomes.
ACADEMIC RADIOLOGY
(2022)
Article
Chemistry, Analytical
Shuang Tan, Shunling Li, Congkui Tang, Xiongfei Bai, Xin Ran, Qing Qu, Lei Li, Long Yang
Summary: In this work, a fluorescent switch regulated by black phosphorus (BP) nanosheets was developed to improve the accuracy and regenerability of beta-amyloid(1-42) oligomer detection. The fluorescent switch, under the regulation of BP nanosheets, enabled the rapid and stable recognition of A beta using nitrogen-doped carbon nanodots, with a wide sensing range and low detection limit.
Article
Radiology, Nuclear Medicine & Medical Imaging
Tali Amir, Molly P. Hogan, Stefanie Jacobs, Varadan Sevilimedu, Janice Sung, Maxine S. Jochelson
Summary: This study compared imaging characteristics of false-positive and true-positive findings on contrast-enhanced digital mammography (CEDM). The results showed that lesions present on both low-energy and iodine images were more likely to be true-positive, especially when the mammographic finding was an asymmetry or calcification. Additionally, calcifications with associated enhancement had a high malignancy rate.
AMERICAN JOURNAL OF ROENTGENOLOGY
(2022)
Article
Biochemical Research Methods
Lei Wang, Shao-Hua Shi, Hui Li, Xiang-Xiang Zeng, Su-You Liu, Zhao-Qian Liu, Ya-Feng Deng, Ai-Ping Lu, Ting-Jun Hou, Dong-Sheng Cao
Summary: Machine learning-based scoring functions (MLSFs) have gained popularity due to their potential superior screening performance compared to classical scoring functions. However, little is known about the information of negative data used in constructing MLSFs, and existing databases often contain biased putative inactive molecules. In this study, we propose an easy-to-use method called AMLSF that combines active learning and MLSF to improve the quality of inactive sets and reduce false positive rate. Our results demonstrate that AMLSF outperforms the control models in terms of identifying active molecules and reducing false positives.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Behavioral Sciences
Ravi Bansal, Bradley S. Peterson
Summary: The GDSS procedure combines voxelwise p-values with probabilities computed from the local geometry, providing greater statistical power than other multiple comparison procedures, especially in small imaging cohorts. Moreover, the study findings indicate that increasing sample size decreases effect sizes, suggesting that sample size calculations from small studies may underestimate the number of participants required in larger studies. It is also recommended to present both effect size maps and p-value maps for correct interpretation of findings.
BRAIN AND BEHAVIOR
(2023)
Review
Chemistry, Analytical
So-Hee Kim, So-Young Lee, Unji Kim, Se-Wook Oh
Summary: This review outlines several techniques for reducing false-positive LAMP results before and after amplification. Organic additives or pullulan can be used to decrease nonspecific amplification before amplification. Uracil-DNA-glycosylase and the hot-start effect with gold nanoparticles can eliminate carry-over contamination and reduce nonspecific amplification after amplification. The use of guide RNA and colorimetric change in DNAzyme can accurately confirm amplification results.
ANALYTICA CHIMICA ACTA
(2023)
Article
Neurosciences
David Steinbart, Siti N. Yaakub, Mirja Steinbrenner, Lynn S. Guldin, Martin Holtkamp, Simon S. Keller, Bernd Weber, Theodor Rueber, Rolf Heckemann, Maria Ilyas-Feldmann, Alexander Hammers
Summary: This study proposes a manual segmentation protocol and an automatic segmentation method to investigate the relationship between the piriform cortex and memory as well as epilepsy. The results show differences in the volumes of the piriform cortex in healthy individuals, temporal lobe epilepsy patients, and Alzheimer's disease patients, providing a new biomarker for early diagnosis.
HUMAN BRAIN MAPPING
(2023)
Article
Oncology
Yifei Li, Jinzhao Liu, Zihang Xu, Jiuyan Shang, Si Wu, Meng Zhang, Yueping Liu
Summary: This study analyzed the clinicopathological characteristics and prognostic factors of IMPC with lymph node metastasis (LNM) and constructed a prognostic nomogram. The nomogram showed high predictive accuracy and clinical utility in both internal and external validation cohorts.
FRONTIERS IN ONCOLOGY
(2023)
Article
Engineering, Biomedical
Xingqi Meng, Yanjun Peng, Yanfei Guo
Summary: This paper proposes a novel method for lymph node detection using nonorthogonal multi-union 2D slices to decompose candidate CT images and reduce false positives. Additionally, an adaptive multi-scale network is designed to optimize classification results by learning features of different scale images and redistributing convolution kernel weights. The proposed methods outperform existing approaches in sensitivity on two datasets, achieving sensitivities of 78%, 86% and 94%, 96% in mediastinum and abdomen respectively.
BIOCYBERNETICS AND BIOMEDICAL ENGINEERING
(2021)
Article
Oncology
Anastasia Constantinidou, Yiola Marcou, Michael S. Toss, Timothy Simmons, Ryan Bernhisel, Elisha Hughes, Braden Probst, Stephanie Meek, Eleni Kakouri, Georgios Georgiou, Ioanna Zouvani, Gabriella Savvidou, Vanessa Kuhl, Jennifer Doedt, Susanne Wagner, Alexander Gutin, Thomas P. Slavin, Jerry S. Lanchbury, Ralf Kronenwett, Ian O. Ellas, Emad A. Rakha
Summary: This study evaluated the performance of EndoPredict in premenopausal women with breast cancer, and found that the EP molecular score and EPclin score are associated with distant recurrence-free survival in breast cancer patients.
CLINICAL CANCER RESEARCH
(2022)
Article
Cardiac & Cardiovascular Systems
Simon Winther, Samuel Emil Schmidt, Laust Dupont Rasmussen, Luis Eduardo Juarez Orozco, Flemming Hald Steffensen, Hans Erik Botker, Juhani Knuuti, Morten Bottcher
Summary: The study validated the new 2019-ESC-PTP model's superiority and calibration in predicting obstructive coronary artery stenosis compared to previously recommended models.
EUROPEAN HEART JOURNAL
(2021)
Article
Psychology, Multidisciplinary
Hazzaa M. Al-Hazzaa, Shaima A. Alothman, Nada M. Albawardi, Abdullah F. Alghannam, Alaa A. Almasud
Summary: The aim of this study was to develop a multi-item Arabic SB questionnaire (ASBQ) to assess sedentary behavior and its association with social, environmental, and health outcomes. ASBQ showed excellent content validity and reliability in a diverse sample of Saudi adolescents and adults.
BEHAVIORAL SCIENCES
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Mark M. Hammer, Andetta R. Hunsaker
Summary: This study evaluates the impact of strategies for reducing false-positive results for intermediate-size nodules on lung cancer screening CT. Classifying intermediate-size nodules with triangular, polygonal, or ovoid shape in any subpleural location as category 2 and using volume-based measurements improve specificity without decreased sensitivity.
AMERICAN JOURNAL OF ROENTGENOLOGY
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Suyoung Yun, Ji Eun Park, Nakyoung Kim, Seo Young Park, Ho Sung Kim
Summary: The study developed a deep learning method for brain metastasis detection, which incorporates both gradient- and turbo spin-echo contrast-enhanced MRI. The performance of this method was evaluated in comparison with human readers and deep learning using gradient-echo-based imaging only. The results showed that the dual-enhanced deep learning method achieved similar sensitivity to human readers and reduced overestimation compared to the gradient-echo deep learning method.
EUROPEAN RADIOLOGY
(2023)
Article
Anesthesiology
Zachary Chuang, Janet Martin, Jordan Shapiro, Derek Nguyen, Penelope Neocleous, Philip M. Jones
Summary: This study aimed to determine the statistical significance and false positive risk in randomized controlled trials (RCTs) in leading anesthesiology journals. The results revealed that if the P-value threshold was lowered from 0.05 to 0.005, 42% of primary outcomes would lose statistical significance.
BRITISH JOURNAL OF ANAESTHESIA
(2022)
Editorial Material
Clinical Neurology
R. J. E. Armstrong, J. Downer, N. Evans, P. Anslow, G. C. Ebers
Article
Pharmacology & Pharmacy
Marius Thomas, Bjoern Bornkamp, Katja Ickstadt
Summary: An important task in drug development is to identify patients who respond better or worse to an experimental treatment, by finding predictive covariates that influence treatment effect. In dose-finding trials, a Bayesian hierarchical dose-response model is proposed to investigate treatment effect heterogeneity, with the use of shrinkage priors to prevent overfitting. By considering dependent modeling of prognostic and predictive effects, the approach aims to better distinguish between these two types of effects.
PHARMACEUTICAL STATISTICS
(2022)
Article
Obstetrics & Gynecology
Laura D. Benz, Peter K. Bode, Simone Brandt, Beate Grass, Cornelia Hagmann, Rabia Liamlahi, Bernhard Frey, Ulrike Held, Barbara Brotschi
Summary: This study did not demonstrate an association between placental findings and neurodevelopmental outcome at 18-24 months of age in cooled neonates with HIE.
JOURNAL OF PERINATAL MEDICINE
(2022)
Editorial Material
Mathematical & Computational Biology
Marissa LeBlanc, Corina S. Rueegg, Nural Bekiroglu, Tonya M. Esterhuizen, Morten W. Fagerland, Ragnhild S. Falk, Kathrine F. Froslie, Erika Graf, Georg Heinze, Ulrike Held, Rene Holst, Theis Lange, Madhu Mazumdar, Ida H. Myrberg, Martin Posch, Jamie C. Sergeant, Werner Vach, Eric A. Vance, HaraldWeedon-Fekjaer, Manuela Zucknick
STATISTICS IN MEDICINE
(2022)
Article
Mathematical & Computational Biology
Priska Heinz, Pedro David Wendel-Garcia, Ulrike Held
Summary: This study evaluated the impact of propensity score matching algorithms in medical research and found that different algorithms have different effects on matching results and treatment effect estimates. The choice of matching algorithm and reporting quality in practical applications still need improvement.
BIOMETRICAL JOURNAL
(2022)
Article
Rheumatology
Alexandru Garaiman, Klaus Steigmiller, Catherine Gebhard, Carina Mihai, Rucsandra Dobrota, Cosimo Bruni, Marco Matucci-Cerinic, Joerg Henes, Jeska De Vries-Bouwstra, Vanessa Smith, Andrea Doria, Yannick Allanore, Lorenzo Dagna, Branimir Anic, Carlomaurizio Montecucco, Otylia Kowal-Bielecka, Mickael Martin, Yoshiya Tanaka, Anna-Maria Hoffmann-Vold, Ulrike Held, Oliver Distler, Mike Oliver Becker
Summary: The DU-VASC model was developed and validated to assist in decision-making for the management of digital ulcers in patients with systemic sclerosis. The model showed that PI treatment was the most important predictor associated with reduced occurrence of digital ulcers.
Article
Pediatrics
Celine Steger, Maria Feldmann, Julia Borns, Cornelia Hagmann, Beatrice Latal, Ulrike Held, Andras Jakab, Ruth O'Gorman Tuura, Walter Knirsch
Summary: Reduced white matter NAA/Cho ratios in neonates undergoing cardiac surgery for congenital heart defects may indicate delayed brain maturation. Further research is needed to understand the clinical impact of altered metabolites on brain development and outcome.
PEDIATRIC RESEARCH
(2023)
Article
Biochemical Research Methods
Jonas Kupschus, Stefan Janssen, Andreas Hoek, Jan Kuska, Jonathan Rathjens, Carsten Sonntag, Katja Ickstadt, Lisa Budzinski, Hyun-Dong Chang, Andrea Rossi, Charlotte Esser, Katrin Hochrath
Summary: Short-read 16S rRNA gene sequencing is the main technology for profiling microbial communities in different habitats. Flow cytometry can quickly profile the microbiota of various sources. FlowSoFine is an open-source analyzing tool that enables the comparison of cytometric fingerprints of microbial communities from different sources.
Review
Health Care Sciences & Services
Sarah Friedrich, Andreas Groll, Katja Ickstadt, Thomas Kneib, Markus Pauly, Joerg Rahnenfuhrer, Tim Friede
Summary: This article reviews regularization approaches in data science for overcoming overfitting and improving prediction, and discusses their limited application in medical research. The authors suggest increased use of regularization approaches in medicine, despite the added complexity they bring to analyses. Proper investments in computing facilities and educational resources can help overcome these challenges.
STATISTICAL METHODS IN MEDICAL RESEARCH
(2023)
Article
Hematology
Davide Voci, Andrea Gotschi, Ulrike Held, Roland Bingisser, Giuseppe Colucci, Daniel Duerschmied, Riccardo M. Fumagalli, Bernhard Gerber, Barbara Hasse, Dagmar I. Keller, Stavros V. Konstantinides, Francois Mach, Silvana K. Rampini, Marc Righini, Helia Robert-Ebadi, Thomas Rosemann, Stephanie Roth-Zetzsche, Tim Sebastian, Noemi R. Simon, David Spirk, Stefan Stortecky, Lukas Vaisnora, Nils Kucher, Stefano Barco
Summary: The benefits of early thromboprophylaxis in symptomatic COVID-19 outpatients remain unclear. This study presents the 90-day results from the OVID phase III trial, which showed that early thromboprophylaxis with enoxaparin did not improve the course of COVID-19 in terms of hospitalization, death, or resolution of symptoms.
THROMBOSIS RESEARCH
(2023)
Article
Environmental Sciences
S. M. Seyedpour, C. Henning, P. Kirmizakis, S. Herbrandt, K. Ickstadt, R. Doherty, T. Ricken
Summary: In order to improve the usefulness of groundwater flow models, it is necessary to reduce uncertainty associated with major parameters like permeability. A coupled Random Field and extended Theory of Porous Media (eTPM) simulation is used to develop a robust model that reduces uncertainty and is validated with a physical sandbox experiment. The results show that random field realizations of permeability can strongly affect contaminant arrival time compared to a homogenous parameter model.
Article
Cardiac & Cardiovascular Systems
Bettina Reich, Sabrina Schwan, Kristina Heye, Thushiha Logeswaran, Andreas Hahn, Andrea Goetschi, Ulrike Held, Kristina Wetterling, Celine Steger, Raimund Kottke, Beatrice Latal, Walter Knirsch
Summary: This study evaluated the long-term effects on brain growth in children with univentricular congenital heart disease. The results showed that these children had impaired neurodevelopmental outcomes and structural brain lesions during school age.
EUROPEAN JOURNAL OF CARDIO-THORACIC SURGERY
(2023)
Review
Clinical Neurology
Ilona Stefanos-Yakoub, Kevin Wingeier, Ulrike Held, Beatrice Latal, Elaine Wirrell, Mary Lou Smith, Georgia Ramantani
Summary: In addition to seizure freedom, pediatric epilepsy surgery aims to stabilize and potentially optimize cognitive development. The study conducted a systematic review and meta-analysis to evaluate the changes in intelligence or developmental quotients (IQ/DQ) before and after surgery in children with focal lesional epilepsy. The findings suggest stabilization of intellectual and developmental functioning at long-term follow-up. Cessation of antiseizure medication after achieving seizure freedom may further optimize intellectual and developmental trajectories in affected children.
Article
Computer Science, Interdisciplinary Applications
Frank Weber, Katja Ickstadt, Aenne Glass
Summary: This article introduces the R package shinybrms, which provides a graphical user interface for fitting Bayesian regression models. The authors hope that this package can increase the popularity of Bayesian regression models in applied research, data analysis, and teaching.
Article
Chemistry, Multidisciplinary
Silvia Chines, Christiane Ehrt, Marco Potowski, Felix Biesenkamp, Lars Gruetzbach, Susanne Brunner, Frederik van den Broek, Shilpa Bali, Katja Ickstadt, Andreas Brunschweiger
Summary: To support compound synthesis design, we developed Reaction Navigator, a tool that can process and cluster a large amount of reaction data, helping users select suitable reactions for synthesis according to their needs. It has been successfully applied to DEL synthesis and mapping of reaction space under different reaction conditions.