In this task, you are given a passage which has a question and the context. You have to generate an answer to the question based on the information present in the context.

Ex Input:
Context: Sepsis from burn injuries can result from colonisation of burn wounds, especially in large surface area burns. Reducing bacterial infection will reduce morbidity and mortality, and mortality for severe burns can be as high as 15\xa0%. There are various quantitative and semi-quantitative techniques to monitor bacterial load on wounds. In the UK, burn wounds are typically monitored for the presence or absence of bacteria through the collection and culture of swabs, but no absolute count is obtained. Quantitative burn wound culture provides a measure of bacterial count and is gaining increased popularity in some countries. It is however more resource intensive, and evidence for its utility appears to be inconsistent. This systematic review therefore aims to assess the evidence on the utility and reliability of different quantitative microbiology techniques in terms of diagnosing or predicting clinical outcomes.', 'Standard systematic review methods aimed at minimising bias will be employed for study identification, selection and data extraction. Bibliographic databases and ongoing trial registers will be searched and conference abstracts screened. Studies will be eligible if they are prospective studies or systematic reviews of burn patients (any age) for whom quantitative microbiology has been performed, whether it is compared to another method. Quality assessment will be based on quality assessment tools for diagnostic and prognostic studies and tailored to the review as necessary. Synthesis is likely to be primarily narrative, but meta-analysis may be considered where clinical and methodological homogeneity exists.\Question: Do protocol for a systematic review of quantitative burn wound microbiology in the management of burns patients?

Ex Output:
Given the increasing use of quantitative methods, this is a timely systematic review, which will attempt to clarify the evidence base. As far as the authors are aware, it will be the first to address this topic.


Ex Input:
Context: Intraflagellar transport (IFT) is a motility process operating between the ciliary/flagellar (interchangeable terms) membrane and the microtubular axoneme of motile and sensory cilia. Multipolypeptide IFT particles, composed of complexes A and B, carry flagellar precursors to their assembly site at the flagellar tip (anterograde) powered by kinesin, and turnover products from the tip back to the cytoplasm (retrograde) driven by cytoplasmic dynein. IFT is essential for the assembly and maintenance of almost all eukaryotic cilia and flagella, and mutations affecting either the IFT motors or the IFT particle polypeptides result in the inability to assemble normal flagella or in defects in the sensory functions of cilia.', 'We found that the IFT complex B polypeptide, IFT27, is a Rab-like small G protein. Reduction of the level of IFT27 by RNA interference reduces the levels of other complex A and B proteins, suggesting that this protein is instrumental in maintaining the stability of both IFT complexes. Furthermore, in addition to its role in flagellar assembly, IFT27 is unique among IFT polypeptides in that its partial knockdown results in defects in cytokinesis and elongation of the cell cycle and a more complete knockdown is lethal.\Question: Is intraflagellar transport protein 27 a small G protein involved in cell-cycle control?

Ex Output:
IFT27, a small G protein, is one of a growing number of flagellar proteins that are now known to have a role in cell-cycle control.


Ex Input:
Context: T2 Lesion Volume (T2LV) has been an important biomarker for multiple sclerosis (MS). Current methods available to quantify lesions from MR images generally require manual adjustments or multiple images with different contrasts. Further, implementations are often not easily or openly accessible.', 'We created a fully unsupervised, single T2 FLAIR image T2LV quantification package based on the popular open-source imaging toolkit FSL.', 'By scripting various processing tools in FSL, we developed an image processing pipeline that distinguishes normal brain tissue from CSF and lesions. We validated our method by hierarchical multiple regression (HMR) with a preliminary study to see if our T2LVs correlate with clinical disability measures in MS when controlled for other variables.', 'Pearson correlations between T2LV and Expanded Disability Status Scale (EDSS: r = 0.344, P = 0.013), Six-Minute Walk (6MW: r = -0.513, P = 0.000), Timed 25-Foot Walk (T25FW: r = -0.438, P = .000), and Symbol Digit Modalities Test (SDMT: r = -0.499, P = 0.000) were all significant. Partial correlations controlling for age were significant between T2LV and 6MW (r = -0.433, P = 0.002), T25FW (r = -0.392, P = 0.004), and SDMT (r = -0.450, P = 0.001). In HMR, T2LV explained significant additional variance in 6MW (R(2) change = 0.082, P = 0.020), after controlling for confounding variables such as age, white matter volume (WMV), and gray matter volume (GMV).\Question: Does fully automated open-source lesion mapping of T2-FLAIR images with FSL correlate with clinical disability in MS?

Ex Output:

Our T2LV quantification software produces T2LVs from a single FLAIR image that correlate with physical disability in MS and is freely available as open-source software.