***TASK***
the task is to simplify the input abstract of a biomedical literature

***INPUT***
the input is the abstract of a biomedical literature

***OUTPUT***
the output is the simplified abstract for the input abstract of a biomedical literature
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Input: Functionally analogous enzymes are those that catalyze similar reactions on similar substrates but do not share common ancestry, providing a window on the different structural strategies nature has used to evolve required catalysts. Identification and use of this information to improve reaction classification and computational annotation of enzymes newly discovered in the genome projects would benefit from systematic determination of reaction similarities. Here, we quantified similarity in bond changes for overall reactions and catalytic mechanisms for 95 pairs of functionally analogous enzymes (non-homologous enzymes with identical first three numbers of their EC codes) from the MACiE database. Similarity of overall reactions was computed by comparing the sets of bond changes in the transformations from substrates to products. For similarity of mechanisms, sets of bond changes occurring in each mechanistic step were compared; these similarities were then used to guide global and local alignments of mechanistic steps. Using this metric, only 44% of pairs of functionally analogous enzymes in the dataset had significantly similar overall reactions. For these enzymes, convergence to the same mechanism occurred in 33% of cases, with most pairs having at least one identical mechanistic step. Using our metric, overall reaction similarity serves as an upper bound for mechanistic similarity in functional analogs. For example, the four carbon-oxygen lyases acting on phosphates (EC 4.2.3) show neither significant overall reaction similarity nor significant mechanistic similarity. By contrast, the three carboxylic-ester hydrolases (EC 3.1.1) catalyze overall reactions with identical bond changes and have converged to almost identical mechanisms. The large proportion of enzyme pairs that do not show significant overall reaction similarity (56%) suggests that at least for the functionally analogous enzymes studied here, more stringent criteria could be used to refine definitions of EC sub-subclasses for improved discrimination in their classification of enzyme reactions. The results also indicate that mechanistic convergence of reaction steps is widespread, suggesting that quantitative measurement of mechanistic similarity can inform approaches for functional annotation.
Output:  When species evolve, their genes duplicate and diverge to allow for adaptation of their functional repertoires to the changing environment. In this scenario, unrelated genes can convergently evolve to produce proteins with the same molecular function, termed “functionally analogous.” A quantitative determination of the reaction similarities among functionally analogous enzymes could provide insight about the different structural solutions nature has used to evolve similar catalysts. Bond changes between substrates and products, and between successive reaction intermediates, were used to compare the reactions catalyzed and the mechanisms of catalysis for 95 pairs of functionally analogous enzymes. Less than half of the reactions catalyzed by unrelated enzymes, but defined as similar by the Enzyme Commission (EC) classification, are similar in terms of bond changes, suggesting that this classification often fails to capture quantitative differences between many enzyme reactions. Furthermore, we addressed for the first time whether the chemical mechanisms by which similar overall reactions are achieved in functional analogs are also similar. We conclude that convergence of reaction is often accompanied by convergence of chemical mechanism. These results will be useful for classifying enzymes, guiding functional annotation of newly determined enzyme sequences and structures and for informing the engineering of enzymes with new functions.

Input:  Human African trypanosomiasis is fatal without treatment. The long post-treatment follow-up (24 months) required to assess cure complicates patient management and is a major obstacle in the development of new therapies. We analyzed individual patient data from 12 programs conducted by Médecins Sans Frontières in Uganda, Sudan, Angola, Central African Republic, Republic of Congo and Democratic Republic of Congo searching for early efficacy indicators.
Patients analyzed had confirmed second-stage disease with complete follow-up and confirmed outcome (cure or relapse), and had CSF leucocytes counts (CSFLC) performed at 6 months post-treatment. We excluded patients with uncertain efficacy outcome: incomplete follow-up, death, relapse diagnosed with CSFLC below 50/µL and no trypanosomes. We analyzed the 6-month CSFLC via receiver-operator-characteristic curves. For each cut-off value we calculated sensitivity, specificity and likelihood ratios (LR+ and LR−). We assessed the association of the optimal cut-off with the probability of relapsing via random-intercept logistic regression. We also explored two-step (6 and 12 months) composite algorithms using the CSFLC.
The most accurate cut-off to predict outcome was 10 leucocytes/µL (n = 1822, 76.2% sensitivity, 80.4% specificity, 3.89 LR+, 0.29 LR−). Multivariate analysis confirmed its association with outcome (odds ratio = 17.2). The best algorithm established cure at 6 months with < = 5 leucocytes/µL and relapse with > = 50 leucocytes/µL; patients between these values were discriminated at 12 months by a 20 leucocytes/µL cut-off (n = 2190, 87.4% sensitivity, 97.7% specificity, 37.84 LR+, 0.13 LR−).
The 6-month CSFLC can predict outcome with some limitations. Two-step algorithms enhance the accuracy but impose 12-month follow-up for some patients. For early estimation of efficacy in clinical trials and for individual patients in the field, several options exist that can be used according to priorities.


Output:

Because Human African trypanosomiasis is fatal, it is crucial for the patient to determine if curative treatment has been effective. Unfortunately this is not possible without a 24-month laboratory follow-up, which is problematic and largely unaccomplished in the field reality. Studies that assessed early indicators have used small cohorts, yielding limited statistical power plus potential bias because of including patients with equivocal outcome. We tackled this problem by pooling a large dataset which allowed for selecting cases providing strictly unequivocal information, still numerous enough to produce sound statistical evidence. We studied predictors based on the CSF leucocytes count, a laboratory technique already available in the field, evaluating their predictive power at 6 and 12 months post-treatment. We found a predictor at 6 months (10 leucocytes/µL of CSF) that has sub-optimal accuracy but may be valuable in some particular situations, plus two-step algorithms at 6 and 12 months that offer sufficient confidence to shorten the patients' follow-up. Until better biomarkers are identified, these findings represent a significant advance for this neglected disease. Benefits are foreseen both for patients and for overburdened treatment facilities. In addition, research for new treatments can be accelerated by using early predictors.
