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.

Example Input: Context: Natural disasters expose entire communities to stress and trauma, leading to increased risk for psychiatric symptoms. Yet, the majority of exposed individuals are resilient, highlighting the importance of identifying underlying factors that contribute to outcomes.', "The current study was part of a larger prospective study of children in Long Island, New York (n = 260). At age 9, children viewed unpleasant and pleasant images while the late positive potential (LPP), an event-related potential component that reflects sustained attention toward salient information, was measured. Following the event-related potential assessment, Hurricane Sandy, the second costliest hurricane in United States history, hit the region. Eight weeks after the hurricane, mothers reported on exposure to hurricane-related stress and children's internalizing and externalizing symptoms. Symptoms were reassessed 8 months after the hurricane.", 'The LPP predicted both internalizing and externalizing symptoms after accounting for prehurricane symptomatology and interacted with stress to predict externalizing symptoms. Among children exposed to higher levels of hurricane-related stress, enhanced neural reactivity to unpleasant images predicted greater externalizing symptoms 8 weeks after the disaster, while greater neural reactivity to pleasant images predicted lower externalizing symptoms. Moreover, interactions between the LPP and stress continued to predict externalizing symptoms 8 months after the hurricane.\Question: Does neural Reactivity to Emotional Stimuli Prospectively predict the Impact of a Natural Disaster on Psychiatric Symptoms in Children?
Example Output: Results indicate that heightened neural reactivity and attention toward unpleasant information, as measured by the LPP, predispose children to psychiatric symptoms when exposed to higher levels of stress related to natural disasters, while greater reactivity to and processing of pleasant information may be a protective factor.

Example Input: Context: Apicomplexan parasites actively release transmembrane (TM) adhesive proteins involved in host cell attachment and invasion. Rhomboids, a family of intramembrane serine proteases, cleave these secreted adhesive proteins within their TM domains as an essential step in completing the invasion process. In Cryptosporidium parvum, the activity of rhomboids in cleaving microneme proteins (MICs) has not been reported. In the present study, the interaction between C. parvum rhomboids (CpROM1 and CpROM4) and C. parvum microneme proteins (CpGP900 and CpTRAP-C1) was investigated using yeast two-hybrid assay and co-immunoprecipitation assays.', 'Our study demonstrated that CpROM1 protein could interact with CpGP900 protein in co-transformed AH109 yeasts. Analysis of these proteins in co-transfected mammalian cells showed that the cleavage product of the CpGP900 protein was detected in the co-transfected cells. As control, CpGP900 only was transfected into cells and no cleavage was observed. The results suggested that CpGP900 protein was the substrate of CpROM1. Moreover, CpROM1 and CpROM4 could not cleave CpTRAP-C1 protein, which is the substrate of T. gondii rhomboid 2.\Question: Does cryptosporidium parvum rhomboid1 have an activity in microneme protein CpGP900 cleavage?
Example Output: Our results showed that CpROM1 is an active protease that is involved in microneme protein CpGP900 cleavage, which lay the foundation for further research on the mechanisms of C. parvum invasion.

Example Input: Context: In multiple sclerosis (MS), cerebral gray matter (GM) atrophy correlates more strongly than white matter (WM) atrophy with disability. The corresponding relationships in the spinal cord (SC) are unknown due to technical limitations in assessing SC GM atrophy. Using phase-sensitive inversion recovery (PSIR) magnetic resonance imaging, we determined the association of the SC GM and SC WM areas with MS disability and disease type.', 'A total of 113 MS patients and 20 healthy controls were examined at 3T with a PSIR sequence acquired at the C2/C3 disk level. Two independent, clinically masked readers measured the cord WM and GM areas. Correlations between cord areas and Expanded Disability Status Score (EDSS) were determined. Differences in areas between groups were assessed with age and sex as covariates.', 'Relapsing MS (RMS) patients showed smaller SC GM areas than age- and sex-matched controls (p = 0.008) without significant differences in SC WM areas. Progressive MS patients showed smaller SC GM and SC WM areas compared to RMS patients (all p ≤ 0.004). SC GM, SC WM, and whole cord areas inversely correlated with EDSS (rho: -0.60, -0.32, -0.42, respectively; all p ≤ 0.001). The SC GM area was the strongest correlate of disability in multivariate models including brain GM and WM volumes, fluid-attenuated inversion recovery lesion load, T1 lesion load, SC WM area, number of SC T2 lesions, age, sex, and disease duration. Brain and spinal GM independently contributed to EDSS.\Question: Does spinal cord gray matter atrophy correlate with multiple sclerosis disability?
Example Output:
SC GM atrophy is detectable in vivo in the absence of WM atrophy in RMS. It is more pronounced in progressive MS than RMS and contributes more to patient disability than SC WM or brain GM atrophy.