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.

[EX Q]: Context: Diabetic cardiomyopathy (DCM) is associated with suppressed autophagy and augmented apoptosis in the heart although the interplay between the two remains elusive. The ability of mammalian sterile 20-like kinase 1 to regulate both autophagy and apoptosis prompted us to investigate it as a possible candidate in the progression of DCM.', 'Wild-type, Mst1 (also known as Stk4) transgenic and Mst1-knockout mice were challenged with streptozotocin to induce experimental diabetes. In addition, cultured neonatal mouse cardiomyocytes were subjected to simulated diabetes to probe mechanisms.', 'Mst1 knockout alleviated while Mst1 overexpression aggravated cardiac dysfunction in diabetes. Diabetic Mst1 transgenic mice exhibited decreased LC3 expression and enhanced protein aggregation. In contrast, typical autophagosomes were observed in diabetic Mst1-knockout mice with increased LC3 expression and reduced protein aggregation. Mst1 downregulation promoted autophagic flux as demonstrated by increased LC3-II and decreased p62 expression in the presence of bafilomycin A1. Furthermore, Mst1 overexpression increased, while Mst1 knockout decreased, cardiomyocyte apoptosis both in vivo and in vitro. Co-immunoprecipitation assays showed that Mst1 overexpression promoted Beclin1 binding to B cell lymphoma 2 (Bcl-2) and induced dissociation of Bcl-2 from Bax in diabetic mice. Conversely, Mst1 knockout disrupted the Beclin1-Bcl-2 complex and enhanced the interaction between Bcl-2 and Bax.\Question: Does mST1 coordinately regulate autophagy and apoptosis in diabetic cardiomyopathy in mice?
[EX A]: Mst1 knockout restores autophagy and protects against apoptosis in cardiomyocytes, en route to the rescue against DCM.

[EX Q]: Context: Both obesity and type 2 diabetes are among the risk factors for breast cancer development. Combined effect of these metabolic abnormalities on breast cancer risk however, has not been examined in premenopausal women. We tested this association in type 2 diabetic women, categorized as obese, overweight and normal body weight groups based on BMI.', 'A total of 101 subjects were included in this study. Serum levels of IL-6, TNF-alpha, C reactive protein, leptin, TGF-alpha, adiponectin and insulin were measured by ELISA. Data were logarithmically transformed for variables not normally distributed. Analysis of variance with post-hoc Bonferroni was applied to compare the data between the groups. Simple and partial correlation coefficients between the variables were determined and a stepwise multiple linear regression analysis was performed to determine the relationships between the variables of interest.', 'Significantly increased levels of IL-6, C reactive protein, leptin and significantly decreased levels of adiponectin were found in obese group, while the levels of TNF-alpha and TGF-alpha were unaltered. A positive correlation between waist circumference and IL-6 was found in obese group. Similarly, C reactive protein, waist and hip circumferences were linearly correlated with BMI in obese group. Stepwise multiple linear regression analysis revealed several significant predictors for breast cancer risk.\Question: Do combined effects of obesity and type 2 diabetes contribute to increased breast cancer risk in premenopausal women?
[EX A]: Obesity and type 2 diabetes, owing to their effects on adipocytokines and inflammatory mediators, contribute to increased breast cancer risk in premenopausal women. This study emphasizes healthy life style and better management of these metabolic disorders to avoid the pathogenesis of breast cancer and of other chronic diseases.

[EX Q]: Context: The aim of this study was to examine the utility of a hierarchical algorithm incorporating codes from the International Classification of Functioning, Disability and Health--ICF (WHO, 2001) and the International Statistical Classification of Diseases-ICD (WHO, 1994) to classify reasons for eligibility of young children in early intervention.', 'The database for this study was a nationally representative enrollment sample of more than 5,500 children in a longitudinal study of early intervention. Reasons for eligibility were reviewed and matched to the closest ICF or ICD codes under one of four major categories (Body Functions/Structures, Activities/Participation, Health Conditions, and Environmental Factors).', 'The average number of reasons for eligibility provided per child was 1.5, resulting in a population summary exceeding 100%. A total of 305 ICF and ICD codes were used with most (77%) of the children having codes in the category of Body Function/Structures. Forty-one percent of the sample had codes of Health Conditions, whereas the proportions with codes in the Activities/Partipication and Environmental Categories were 10 and 5%, respectively.\Question: Do iCF and ICD codes provide a standard language of disability in young children?
[EX A]:
The results demonstrate that ICD and ICF can be jointly used as a common language to document disability characteristics of children in early intervention.