Given a passage classify if the passage has a definite objective/aim/goal or not. Output '1' if the passage has a defininte objective/aim/goal and output '0' if the passage does not have a definite objective/aim/goal.

Example Input: Dexamethasone (Dex)-induced spontaneous tendon rupture and decreased self-repair capability is very common in clinical practice. The metaplasia of adipose tissue in the ruptured tendon indicates that Dex may induce tendon stem cells (TSCs) to differentiate into adipocytes, but the mechanism remains unclear. In the present study, we used in vitro methods to investigate the effects of Dex on rat TSC differentiation and the molecular mechanisms underlying this process.', 'First, we used qPCR and Western blotting to detect the expression of the adipogenic differentiation markers aP2 and C/EBPα after treating the TSCs with Dex. Oil red staining was used to confirm that high concentration Dex promoted adipogenic differentiation of rat TSCs. Next, we used qPCR and Western blotting to detect the effect of a high concentration of dexamethasone on molecules related to the canonical WNT/β-catenin pathway in TSCs.', 'Treating rat TSCs with Dex promoted the synthesis of the inhibitory molecule dickkopf1 (DKK1) at the mRNA and protein levels. Western blotting results further showed that Dex downregulated the cellular signaling molecule phosphorylated glycogen synthase kinase-3β (P-GSK-3 β (ser9)), upregulated P-GSK-3β (tyr216), and downregulated the pivotal signaling molecule β-catenin. Furthermore, DKK1 knockdown attenuated Dex-induced inhibition of the canonical WNT/β-catenin pathway and of the adipogenic differentiation of TSCs. Lithium chloride (LiCl, a GSK-3β inhibitor) reduced Dex-induced inhibition of the classical WNT/β-catenin pathway in TSCs and of the differentiation of TSCs to adipocytes.
Example Output: 1

Example Input: In RA, conflicting results have been described on the association between genotypes of the complement factor mannose-binding lectin (MBL) and disease susceptibility and severity. This might be due to underpowerment of previous research work and the fact that no confirmation cohorts were used. Therefore a different approach is warranted.', 'MBL2 gene polymorphisms were determined in two RA cohorts (378 and 261 cases) and 648 controls. Considering MBL polymorphisms, cases and controls were categorized in groups of high, intermediate and low MBL production. The total sample size allows detection of a potential association between RA susceptibility and MBL groups with an odds ratio of 1.37 (alpha < 0.05; 1-beta > 0.8). Disease severity as defined by the need for anti-TNF therapy was also analysed for possible associations with MBL groups.', 'There was no difference in the frequencies between MBL genotypes of RA cases and controls that are associated with high (cases 54.4%, controls 57.0%), intermediate (cases 28.9%, controls 27.5%) or low (cases 16.7%, controls 15.5%) MBL production. Furthermore, there was no association between MBL groups and disease severity.
Example Output: 1

Example Input: Obesity has been described as a predictor of cardiovascular mortality, and some studies have reported an association with obesity and increased aortic stiffness. Other studies have not identified obesity to be an independent risk factor. Therefore, the purpose of our study was to determine the association between aortic stiffness and obesity in the Brazilian population.', 'A cross-sectional study recruited 1,662 individuals aged 25-64 years from the population of Vitória, Brazil following the guidelines of the MONICA-WHO Project. Anthropometric, clinical, and hemodynamic measurements and analyses of aortic stiffness (using carotid-femoral pulse wave velocity <PWV) were obtained in 1,608 subjects.', 'PWV correlated positively with age, systolic blood pressure (SBP), diastolic blood pressure (DBP), mean blood pressure, heart rate (HR), body mass index (BMI), waist circumference (WC), cholesterol levels, triglyceride levels, and blood glucose levels. A multivariate regression analysis demonstrated that the mean BP (β = 0.405, P < 0.01), age (β = 0.314, P < 0.01), HR (β = 0.107, P < 0.01), BMI (β = -103, P < 0.01), and blood glucose levels (β = 0.093, P < 0.01) explained nearly 37% of the PWV variability. A multivariate regression analysis using the WC instead of the BMI failed to reveal any significant effect of this parameter on the PWV.
Example Output:
0