In this task, you are given an abstract of article. Your task is to generate title for this article. Preferred titles are under thirty words.

Example Input: AIMS patients with diabetes mellitus (DM) have high platelet reactivity and are at increased risk of ischaemic events and bleeding post-acute coronary syndromes (ACS). In the PLATelet inhibition and patient Outcomes (PLATO) trial, ticagrelor reduced the primary composite endpoint of cardiovascular death, myocardial infarction, or stroke, but with similar rates of major bleeding compared with clopidogrel. We aimed to investigate the outcome with ticagrelor vs. clopidogrel in patients with DM or poor glycaemic control.
METHODS AND RESULTS we analysed patients with pre-existing DM (n = 4662), including 1036 patients on insulin, those without DM (n = 13 951), and subgroups based on admission levels of haemoglobin A1c (HbA1c; n = 15 150). In patients with DM, the reduction in the primary composite endpoint (HR: 0.88, 95% CI: 0.76-1.03), all-cause mortality (HR: 0.82, 95% CI: 0.66-1.01), and stent thrombosis (HR: 0.65, 95% CI: 0.36-1.17) with no increase in major bleeding (HR: 0.95, 95% CI: 0.81-1.12) with ticagrelor was consistent with the overall cohort and without significant diabetes status-by-treatment interactions. There was no heterogeneity between patients with or without ongoing insulin treatment. ticagrelor reduced the primary endpoint, all-cause mortality, and stent thrombosis in patients with HbA1c above the median (HR: 0.80, 95% CI: 0.70-0.91; HR: 0.78, 95% CI: 0.65-0.93; and HR: 0.62, 95% CI: 0.39-1.00, respectively) with similar bleeding rates (HR: 0.98, 95% CI: 0.86-1.12).
CONCLUSION ticagrelor, when compared with clopidogrel, reduced ischaemic events in ACS patients irrespective of diabetic status and glycaemic control, without an increase in major bleeding events.
Example Output: Ticagrelor vs. clopidogrel in patients with acute coronary syndromes and diabetes: a substudy from the PLATelet inhibition and patient Outcomes (PLATO) trial

Example Input: Monocytes are primary targets for human CMV (HCMV) infection and are proposed to be responsible for hematogenous dissemination of the virus. Monocytes acquire different functional traits during polarization to the classical proinflammatory M1 macrophage or the alternative antiinflammatory M2 macrophage. We hypothesized that HCMV induced a proinflammatory M1 macrophage following infection to promote viral dissemination because, biologically, a proinflammatory state provides the tools to drive infected monocytes from the blood into the tissue. To test this hypothesis of monocyte conversion from a normal quiescent phenotype to an inflammatory phenotype, we used Affymetrix Microarray to acquire a transcriptional profile of infected monocytes at a time point our data emphasized is a key temporal regulatory point following infection. We found that HCMV significantly up-regulated 583 (5.2%) of the total genes and down-regulated 621 (5.5%) of the total genes>or=1.5-fold at 4 h postinfection. Further ontology analysis revealed that genes implicated in classical M1 macrophage activation were stimulated by HCMV infection. We found that 65% of genes strictly associated with M1 polarization were up-regulated, while only 4% of genes solely associated with M2 polarization were up-regulated. Analysis of the monocyte chemokinome at the transcriptional level showed that 44% of M1 and 33% of M2 macrophage chemokines were up-regulated. Proteomic analysis using chemokine Ab arrays confirmed the secretion of these chemotactic proteins from HCMV-infected monocytes. Overall, the results identify that the HCMV-infected monocyte transcriptome displayed a unique M1/M2 polarization signature that was skewed toward the classical M1 activation phenotype.
Example Output: Transcriptome analysis reveals human cytomegalovirus reprograms monocyte differentiation toward an M1 macrophage.

Example Input: This study aimed to compare the symptoms, unmet needs, and QoL reported by women at 6 months to <2 years and 2 to 5 years following surgery and adjuvant treatment for breast cancer. It also evaluated the relationships among symptoms, unmet needs, and QoL using structural equation modeling. In this study, 113 and 137 survivors following breast cancer treatment 6 months to <2 years and 2 to 5 years, respectively, completed the Memorial Symptom Assessment Scale, the Supportive Care Needs Survey-34, and the Medical Outcomes Study 12-item Short Form Health Survey version 2.0 during their medical follow-up. The mean numbers of symptoms and unmet needs were 5.43 and 3.0, respectively, for survivors at <2 years, and 5.24 and 2.42, respectively, for survivors at 2 to 5 years following treatment. The most common reported symptoms were related primarily to physical domains. No significant differences were found between the two survivor groups on the MSAS scores. Survivors at <2 years reported significantly higher scores in Psychological and Health Care System/Information needs (p < 0.01), and lower composite scores in physical and mental QoL (p < 0.05) than those at 2 to 5 years post-treatment. Significant direct and indirect effects were found of symptom burden through unmet needs on survivors' physical and mental QoL after adjustment for survival time, and the models showed a good fit. Results suggest that breast cancer survivors continue to endure many symptoms independent of the survivorship period. The unmet needs mediate the relationship between symptom burden and survivors' QoL.
Example Output:
Unmet needs mediate the relationship between symptoms and quality of life in breast cancer survivors