SusD-like protein from the human gut bacterium Bacteroides thetaiotaomicron
Bibliographic record
Abstract
Nutritional research is continually demonstrating the strong interaction between the human colon microbiota and a healthy digestive system 1. It has been shown that this intestinal microbial population can influence our state of health including our metabolism, nutrient production and absorption, and the development of our immune system2. These symbiotic organisms have an important role in the metabolism of human dietary carbohydrates and exist by utilizing these sugars, which are not readily digested by upstream human enzymatic mechanisms. The ability of these microbes to utilize these sugars can also impact digestive disease states that include obesity, irritable bowel disorder, colonic cancer and Type 2 diabetes3. A dominant member of this environment is the bacterium Bacteroides thetaiotaomicron and has been characterized at efficiently utilizing carbohydrates in the colon. This symbiont has been shown to have a large repertoire of proteins and enzymes that have been predicted to be strongly involved in the capture and degradation of dietary sugars. In this study we focused on assessing the impact of a specific SusD-like protein on the utilization of dietary sugars. Biochemical evidence, as well as preliminary structural data provides support that this carbohydrate binding protein is capable of binding various dietary sugars. These interactions enable this bacterium to capture sugars derived from the colon and provide an available substrate for membrane bound glycoside hydrolases. The information gathered in this study can shed light on a part of digestion that is unclear at this point in time and create a connection between diet composition and its affect on a dominant member of the gut microbiota.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".