NIH funds multi-university study of new public health threat
Bibliographic record
Abstract
GRAND FORKS, N.D.—A distantly related cousin to the bacterium that causes Lyme disease is the focus of a new multi-university research study funded by the National Institutes of Health Institute of Allergy and Infectious Diseases. The grant brings together an expert team of microbiologists and tick researchers led by Principal Investigator Brian Stevenson, PhD, a professor at the University of Kentucky, and Coinvestigators Catherine A. Brissette , PhD, an assistant professor at the University of North Dakota School of Medicine and Health Sciences; and Jean Tsao, PhD, an associate professor at Michigan State University. Lyme disease is caused by a spiral-shaped bacterium known as Borrelia burgdorferi, which is the cause of more than 90 percent of all tick-borne diseases affecting humans in the United States. Estimates from the Centers for Disease Control and Prevention (CDC) suggest that 300,000 people each year are affected by Lyme disease. Lyme disease is a debilitating and significant public health problem that can result in arthritis, heart problems, and neurological impairment and disability. The focus of the new NIH grant is the Lyme disease bacterium’s distant cousin known as Borrelia miyamotoi (B. miyamotoi) ; it was first identified in ticks from Japan. People infected with B. miyamotoi may require hospitalization, with symptoms that include high fever, joint and muscle pain, and inflammation of the membranes that surround the spinal cord and the brain. Both bacteria are spread by black-legged, or deer, ticks, which are found in eastern North Dakota, eastern Manitoba, Minnesota, and Wisconsin. For deer ticks to acquire either type of bacteria, they must feed on the blood of an infected animal for several days. After which, the ticks can bite and then spread the disease to humans. However, Borrelia miyamotoi may be the more insidious of the two bacterial cousins. In addition to infecting ticks that feed on infected animals, B. miyamotoi can also be passed transovarially, that is, from the tick mother to its offspring by infecting the eggs in the tick’s ovaries—significantly multiplying the number of ticks that can spread the infection. But almost nothing is known about how or where in the tick the bacterium takes hold. “We are excited to be part of a dynamic research team on a newly recognized human pathogen,” Brissette said. “The first reports of Borrelia miyamotoi infection are only from 2011 in Russia, and we know almost nothing about this bacterium. For a microbiologist, there’s nothing more thrilling than being on the front lines of discovery.” Other researchers working on the study are PhD candidates Christina Savage, in the Stevenson lab; Brandee Stone, MS, in the Brissette lab; and Seungeun Han, DVM, in the Tsao lab. They will assist the principal and coinvestigators in a series of synergistic studies to expand the understanding of B. miyamotoi transmission and infection mechanisms, including where the bacterium resides within the tick, how fast the bacterium is transmitted once a tick begins feeding, how the bacterium evades host immune responses, and how transovarial transmission of B. miyamotoi affects human disease risk. “These results will help us understand the threat of this emerging pathogen to humans,” Brissette said.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.056 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".