Proteoform identification is required to fully understand the biological diversity present in a sample. However, these identifications are often ambiguous because of the challenges in analyzing full length proteins by mass spectrometry. A five-level proteoform classification system was recently developed to delineate the ambiguity of proteoform identifications and to allow for comparisons across software platforms and acquisition methods. Widespread adoption of this system requires software tools to provide classification of the proteoform identifications. We describe here an implementation of the five-level classification system in the software program MetaMorpheus, which provides both bottom-up and top-down identifications. Additionally, we developed a stand-alone program called ProteoformClassifier that allows users to classify proteoform results from any search program, provided that the program writes output that includes the information necessary to evaluate proteoform ambiguity. This stand-alone program includes a small test file and database to evaluate if a given program provides sufficient information to evaluate ambiguity. If the program does not, then ProteoformClassifier provides meaningful feedback to assist developers with implementing the classification system. We tested currently available top-down software programs and found that none of them (other than MetaMorpheus) provided sufficient information regarding identification ambiguity to permit classification.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8764746 | PMC |
http://dx.doi.org/10.1021/acs.jproteome.1c00417 | DOI Listing |
Transfusion
January 2025
Infectious Disease Consultant, North Potomac, Maryland, USA.
Background: US blood donors are tested for syphilis because the bacterial agent is transfusion transmissible. Here we describe trends over an 11-year period of donations positive for recent and past syphilis infections, and donations classified as syphilis false positive (FP).
Methods: Data from January 1, 2013, to December 31, 2023 (11 years) were compiled for all American Red Cross blood donations to evaluate demographics/characteristics and longitudinal trends in donors testing syphilis reactive/positive.
Neurosurg Rev
January 2025
Hengyang Key Laboratory of Hemorrhagic Cerebrovascular Disease, Department of Neurosurgery, the Second Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, 421000, Hunan, China.
Patients with intracranial aneurysms (IA) undergoing endovascular treatment face varying risks and benefits when tirofiban is used for thromboprophylaxis during surgery. Currently, there is a lack of high-level evidence summarizing this information. This study aims to conduct a systematic review and meta-analysis to evaluate the efficacy and safety of tirofiban during endovascular treatment of IA.
View Article and Find Full Text PDFZ Gerontol Geriatr
January 2025
Geriatrie, Universität Witten-Herdecke, Alfred Herrhausenstraße 50, 58455, Witten, Germany.
Chronic obstructive pulmonary disease (COPD) is a frequent disease from which approximately 8% of individuals aged 40 years and above suffer. The prevalence increases up to fivefold as age advances. Following an introduction including the etiology, measurement, characteristic features and classification of COPD, this article presents the consensus recommendations of the German Working Group on Pneumology in Older Patients.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, National Clinical Research Center for Eye Disease, Shanghai, 200080, China.
The objectives of this study are to construct a deep convolutional neural network (DCNN) model to diagnose and classify meibomian gland dysfunction (MGD) based on the in vivo confocal microscope (IVCM) images and to evaluate the performance of the DCNN model and its auxiliary significance for clinical diagnosis and treatment. We extracted 6643 IVCM images from the three hospitals' IVCM database as the training set for the DCNN model and 1661 IVCM images from the other two hospitals' IVCM database as the test set to examine the performance of the model. Construction of the DCNN model was performed using DenseNet-169.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA.
Vision transformer (ViT)and convolutional neural networks (CNNs) each possess distinct strengths in medical imaging: ViT excels in capturing long-range dependencies through self-attention, while CNNs are adept at extracting local features via spatial convolution filters. While ViT may struggle with capturing detailed local spatial information, critical for tasks like anomaly detection in medical imaging, shallow CNNs often fail to effectively abstract global context. This study aims to explore and evaluate hybrid architectures that integrate ViT and CNN to leverage their complementary strengths for enhanced performance in medical vision tasks, such as segmentation, classification, reconstruction, and prediction.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!