Extracting meaningful features from time series analysis of plasma analytes in clinical research
Blank, P.; Golding, A. E.; Morales, I.; Waters, H.; Mekhedov, E.; Bezrukov, L.; Wachter, R. D.; Mikhailenko, I.; Brown, R. H.; Bonnemann, C.; Demidowich, A.; Jain, M.; Yanovski, J. A.; Zimmerberg, J.
Show abstract
While absolute blood biomarkers have long guided diagnosis, their rate of change often provides greater diagnostic value. For the Limb Girdle Muscular Dystrophies studied here, increased muscle weakness is associated with abnormal sarcolemma repair. Time course analyses were made to changes in muscle-derived plasma enzymes after modest physical activity of ambulatory inpatients. Blood samples at 20 selected time points at variable intervals were obtained at rest, and before and after routine morning activities and motor function testing. After these activities, plasma enzyme levels increased in a similar way, suggesting damage and leakage from skeletal muscle. The levels then decreased in a similar way, suggesting that muscle cells stopped leaking and enzymes were subsequently cleared from the blood. The complex temporal changes were modeled using both continuous time and data features to reduce the number of parameters required to describe the irregularly sampled, interrupted, time series data. Unlike individuals with cardiac muscle ischemia or following intense exercise, there was no extended post-injury rising phase of enzyme levels. In contradistinction, levels fell once activity ceased. Time series analyses of blood biomarkers most likely provide an assay and index of sarcolemma fragility and by extension skeletal muscle damage.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- A randomized placebo-controlled clinical trial of Nicotinamide Riboside and Pterostilbene supplementation in experimental muscle injury in elderly subjects 92%
- Immunoresolvents Support Skeletal Myofiber Regeneration via Actions on Myeloid and Muscle Stem Cells 89%
- Temporal regulation of TAK1 to counteract muscular dystrophy 89%
Similar papers in this journal
- Multi-scale machine learning model predicts muscle and functional disease progression in FSHD 91%
- A Metabolomics Approach for Early Prediction of Vincristine-Induced Peripheral Neuropathy 90%
- Gait signature changes with walking speed are similar among able-bodied young adults despite persistent individual-specific differences 90%
Similar papers in this journal
- High-resolution mass spectrometry-based non-targeted metabolomic discovery of disease and glucocorticoid biomarkers in an animal model of muscular dystrophy 92%
- Towards development of a statistical framework to evaluate myotonic dystrophy type 1 mRNA biomarkers in the context of a clinical trial 92%
- Muscle fiber hypertrophy in response to 6 weeks of high-volume resistance training in trained young men is largely attributed to sarcoplasmic hypertrophy 90%
Similar papers in this journal
Similar papers in this journal
- Young Adults Recruit Similar Motor Modules Across Walking, Turning, and Chair Transfers 91%
- RNA sequencing on muscle biopsy from a 5-week bedrest study reveals the effect of exercise and potential interactions with dorsal root ganglion neurons 90%
- Intermuscular Adipose Tissue And Muscle Function In Patients On Maintenance Hemodialysis 89%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.