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: The ability of p53 to induce apoptosis requires its sequence-specific DNA binding activity; however, the transactivation-deficient p53(Gln22-Ser23) can still induce apoptosis. Previously, we have shown that the region between residues 23 and 97 in p53 is necessary for such activity. In an effort to more precisely map a domain necessary for apoptosis within the N terminus, we found that deletion of the N-terminal 23 amino acids compromises, but does not abolish, p53 induction of apoptosis. Surprisingly, p53(Delta1-42), which lacks the N-terminal 42 amino acids and the previously defined activation domain, retains the ability to induce apoptosis to an even higher level than wild-type p53. A more extensive deletion, which eliminates the N-terminal 63 amino acids, renders p53 completely inert in mediating apoptosis. In addition, we found that both p53(Delta1-42) and p53(Gln22-Ser23) can activate a subset of cellular p53 targets. Furthermore, we showed that residues 53 and 54 are critical for the apoptotic and transcriptional activities of both p53(Delta1-42) and p53(Gln22-Ser23). Taken together, these data suggest that within residues 43-63 lie an apoptotic domain as well as another transcriptional activation domain. We therefore postulate that the apoptotic activity in p53(Gln22-Ser23) and p53(Delta1-42) is still transcription-dependent.
Example Output: Identification of a novel p53 functional domain that is necessary for mediating apoptosis.

Example Input: OBJECTIVE The Diabetes Prevention Program (DPP) is a 27-center randomized clinical trial designed to evaluate the safety and efficacy of interventions that may delay or prevent development of diabetes in people at increased risk for type 2 diabetes. RESEARCH DESIGN AND METHODS Eligibility requirements were age > or = 25 years, BMI > or = 24 kg/m2 (> or = 22 kg/m2 for Asian-Americans), and impaired glucose tolerance plus a fasting plasma glucose of 5.3-6.9 mmol/l (or < or = 6.9 mmol for American Indians). Randomization of participants into the DPP over 2.7 years ended in June 1999. Baseline data for the three treatment groups--intensive lifestyle modification, standard care plus metformin, and standard care plus placebo--are presented for the 3,234 participants who have been randomized.
RESULTS Of all participants , 55% were Caucasian, 20% were African-American, 16% were Hispanic, 5% were American Indian, and 4% were Asian-American. Their average age at entry was 51 +/- 10.7 years (mean +/- SD), and 67.7% were women. Moreover, 16% were < 40 years of age, and 20% were > or = 60 years of age. Of the women, 48% were postmenopausal. Men and women had similar frequencies of history of hypercholesterolemia (37 and 33%, respectively) or hypertension (29 and 26%, respectively). On the basis of fasting lipid determinations, 54% of men and 40% of women fit National Cholesterol Education Program criteria for abnormal lipid profiles. More men than women were current or former cigarette smokers or had a history of coronary heart disease. Furthermore, 66% of men and 71% of women had a first-degree relative with diabetes. Overall, BMI averaged 34.0 +/- 6.7 kg/m2 at baseline with 57% of the men and 73% of women having a BMI > or = 30 kg/m2. Average fasting plasma glucose (6.0 +/- 0.5 mmol/l) and HbA1c (5.9 +/- 0.5%) in men were comparable with values in women (5.9 +/- 0.4 mmol/l and 5.9 +/- 0.5%, respectively).
CONCLUSIONS The DPP has successfully randomized a large cohort of participants with a wide distribution of age, obesity, and ethnic and racial backgrounds who are at high risk for developing type 2 diabetes. The study will examine the effects of interventions on the development of diabetes.
Example Output: The Diabetes Prevention Program: baseline characteristics of the randomized cohort. The Diabetes Prevention Program Research Group.

Example Input: Autophagy is a process in which subcellular membranes undergo dynamic morphological changes that lead to the degradation of cellular proteins and cytoplasmic organelles. This process is an important cellular response to stress or starvation. Many studies have shed light on the importance of autophagy in cancer, but it is still unclear whether autophagy suppresses tumorigenesis or provides cancer cells with a rescue mechanism under unfavourable conditions. What is the present state of our knowledge about the role of autophagy in cancer development, and in response to therapy? And how can the autophagic process be manipulated to improve anticancer therapeutics?
Example Output:
The role of autophagy in cancer development and response to therapy