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: To study the healing effect of recombinant human epidermal growth factor (hEGF) on diabetic foot ulcers.', 'A total of 127 consecutive patients were screened and 61 diabetic subjects were recruited into this double-blind randomized controlled study. Predetermined criteria were used for diagnosis and classification of the diabetic wound. The patients were randomized into three groups. All patients attended our Diabetes Ambulatory Care Center every other week for joint consultation with the diabetologist and the podiatrist. Group 1 (control) was treated with Actovegin 5% cream (Actovegin), group 2 with Actovegin plus 0.02% (wt/wt) hEGF, and group 3 with Actovegin plus 0.04% (wt/wt) hEGF. The study end point was the complete closure of the wound. Failure to heal was arbitrarily defined as incomplete healing after 12 weeks.', 'Final data were obtained from 61 patients randomly assigned into three groups. The mean ages of the patients, wound sizes, wound duration, metabolic measurements, and comorbidities were comparable within groups, except that group 3 had more female patients. Mean follow-up for the patients was 24 weeks. Data were cutoff at 12 weeks, and results were analyzed by intention to treat. After 12 weeks, in group 1 (control) eight patients had complete healing, two patients underwent toe amputation, and nine had nonhealing ulcers. In group 2 (0.02% [wt/wt] hEGF) 12 patients experienced wound healing, 2 had toe amputations, and 7 had nonhealing ulcers. Some 20 of 21 patients in group 3 (0.04% [wt/wt] hEGF) showed complete wound healing. Healing rates were 42.10, 57.14, and 95% for the control, 0.02% (wt/wt) hEGF, and 0.04% (wt/wt) hEGF groups, respectively. Kaplan-Meier survival analysis suggested that application of cream with 0.04% (wt/wt) hEGF caused more ulcers to heal by 12 weeks and increased the rate of healing compared with the other treatments (log-rank test, P = 0.0003).
Example Output: 1

Example Input: Human hepatocellular carcinoma (HCC) heterogeneity promotes recurrence and resistance to therapies. Recent studies have reported that HCC may be derived not only from adult hepatocytes and hepatoblasts but also hepatic stem/progenitors. In this context, HepaRG cells may represent a suitable cellular model to study stem/progenitor cancer cells and the retrodifferentiation of tumor-derived hepatocyte-like cells. Indeed, they differentiate into hepatocyte- and biliary-like cells. Moreover, tumor-derived HepaRG hepatocyte-like cells (HepaRG-tdHep) differentiate into both hepatocyte- and biliary-like cells through a hepatic progenitor. In this study we report the mechanisms and molecular effectors involved in the retrodifferentiation of HepaRG-tdHep into bipotent progenitors. Gene expression profiling was used to identify genomic changes during the retrodifferentiation of HepaRG-tdHep into progenitors. We demonstrated that gene expression signatures related to a poor-prognosis HCC subclass, proliferative progenitors, or embryonic stem cells were significantly enriched in HepaRG progenitors derived from HepaRG-tdHep. HepaRG-tdHep retrodifferentiation is mediated by crosstalk between transforming growth factor beta 1 (TGFβ1) and inflammatory cytokine pathways (e.g., tumor necrosis factor alpha [TNFα] and interleukin 6 [IL6]). Signatures related to TNFα, IL6, and TGFβ activation pathways are induced within the first hour of retrodifferentiation. Moreover, specific activation or inhibition of these signaling pathways allowed us to determine that TNFα and IL6 contribute to the loss of hepatic-specific marker expression and that TGFβ1 induces an epithelial-to-mesenchymal transition of HepaRG-tdHep. Interestingly, the retrodifferentiation process is blocked by the histone deacetylase inhibitor trichostatin A, opening new therapeutic opportunities.
Example Output: 0

Example Input: The purpose of this research study was to identify factors that are associated with receiving care in a medical home for children with special health care needs (CSHCN) and to identify how these factors vary among different socioeconomic levels.', 'Data were obtained from the National Survey of Children with Special Health Care Needs, 2000-2002. Access to a medical home was derived using an algorithm. This survey analysis also included demographic characteristics, geographical location of household, severity of condition, and social factors. Multiple logistic regression models were constructed for socioeconomic status (SES) levels defined by federal poverty level (FPL): <133%; 133-199%; 200-299%; > or =300%.', 'Age group was significant in all but the 200-299% of FPL stratum. Severity of condition was significant in all strata. Race was significant in all but the > or =300% stratum. Maternal education was borderline significant in the lowest and highest strata. Insurance type/status was significant in all but the 133-199% of FPL stratum. Geographical location was significant in the lowest and highest strata. The language of the interview was only significant in the lowest stratum. The relationship of the respondent to the child was significant in the middle two strata. The total number of adults in the household was significant in the highest stratum, and the total number of children in the household was significant in the 200-299% of FPL stratum.
Example Output:
1