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: Environmental conditions (eg, latitude) play a critical role in the susceptibility and severity of many autoimmune disorders, including multiple sclerosis (MS). Here, we investigated the mechanisms underlying the beneficial effects of immune regulatory processes induced in the skin by moderate ultraviolet B (UVB) radiation on central nervous system (CNS) autoimmunity.', 'Effects of UVB light were analyzed in a murine model of CNS autoimmunity (experimental autoimmune encephalomyelitis). Additionally, patients with relapsing-remitting MS were treated with narrowband UVB phototherapy. Immunomodulatory effects were examined in skin biopsies, serum samples, and immune cells of the peripheral blood.', 'Regulatory T cells (Tregs), which are induced locally in the skin-draining lymph nodes in response to UVB exposure, connect the cutaneous immune response to CNS immunity by migration to the sites of inflammation (blood, spleen, CNS). Here, they attenuate the inflammatory response and ameliorate disease symptoms. Treg-inducing tolerogenic dendritic cells (DCs) were further necessary for induction of this systemic immune regulation by UVB radiation, because ablation of Langerhans cells abolished the UVB-induced phenotype. MS patients treated with UVB phototherapy showed an increase in induced Tregs and tolerogenic DCs accompanied by the downregulation of the T-cell effector cytokine interleukin 21. The treatment further induced elevated serum levels of vitamin D.\Question: Does ultraviolet B light attenuate the systemic immune response in central nervous system autoimmunity?
Example Output: Local UVB radiation of the skin influences systemic immune reactions and attenuates systemic autoimmunity via the induction of skin-derived tolerogenic DCs and Tregs. Our data could have implications for the understanding or therapeutic modulation of environmental factors that influence immune tolerance.

Example Input: Context: Efforts to improve outcomes from acute kidney injury (AKI) have focussed on timely diagnosis and effective delivery of basic patient care. Electronic alerts (e-alerts) for AKI have attracted interest as a tool to facilitate this. Initial feasibility has already been demonstrated; this review will discuss recent advances in alert methodology, implementation beyond single centres and reported effect on outcomes.', 'On-going descriptions of e-alerts highlight increasing variation in both detection algorithms and alert processes. In England, this is being addressed by national rollout of a standardized detection algorithm; recent data have shown this to have good diagnostic performance. In critical care, fully automated detection systems incorporating both serum creatinine and urine output criteria have been developed. A recent randomized trial of e-alerts has also been reported, in which isolated use of a text message e-alert did not affect either clinician behaviour or patient outcome.\Question: Does recent developments in electronic alert for acute kidney injury?
Example Output: As e-alerts gain popularity, consideration must be given to both the method of AKI detection and the method by which results are communicated to end-users; these aspects influence the degree of these systems' effectiveness. This approach should be coupled to further work to study the effect on patient outcomes of those interventions that have been demonstrated to influence clinician behaviour.

Example Input: Context: We aimed to evaluate risk factors for ventilator-associated pneumonia (VAP) due to Acinetobacter baumannii (AbVAP) in critically ill patients.', 'This was a prospective observational study conducted in an intensive care unit (ICU) of a district hospital (6 beds). Consecutive patients were eligible for enrolment if they required mechanical ventilation for >48 hours and hospitalization for >72 hours. Clinical, microbiological, and laboratory parameters were assessed as risk factors for AbVAP by univariate and multivariate analysis.', '193 patients were included in the study. Overall, VAP incidence was 23.8% and AbVAP, 11.4%. Previous hospitalization of another patient with Acinetobacter baumannii infection was the only independent risk factor for AbVAP (OR (95% CI) 12.016 (2.282-19.521) P < 0.001). ICU stay (25 17 versus 12 9P < 0.001), the incidence of other infections (OR (95% CI) 9.485 (1.640-10.466) P = 0.002) (urinary tract infection, catheter related infection, and bacteremia), or sepsis (OR (95% CI) 10.400 (3.749-10.466) P < 0.001) were significantly increased in patients with AbVAP compared to patients without VAP; no difference was found with respect to ICU mortality.\Question: Is acinetobacter baumannii infection in prior ICU bed occupants an independent risk factor for subsequent cases of ventilator-associated pneumonia?
Example Output:
ICU admission or the hospitalization of patients infected by Acinetobacter baumannii increases the risk of AbVAP by subsequent patients.