Iron-regulatory proteins secure iron availability in cardiomyocytes to prevent heart failure

Results

Reduced iron content, IRE binding activity, and transferrin receptor expression in the failing human heart

library(math)

labels(data) <- c("non-failing heart (NF)", "failing heart (F)")
library(reticulate)
np <- import("numpy", convert=FALSE)
(x <- np$arange(1, 9)$reshape(2L, 2L))
## [[  99.   52.]
##   [  96.   40.]
##   [  100.   38.]
##   [  105.   18.]
##   [ np.nan.   11.]
##   [ np.nan.  5.]
##   [ np.nan.  42.]
##   [ np.nan.  55.]
##   [ np.nan  53.]
##   [ np.nan  39.]
##   [ np.nan.  42.]
##   [ np.nan  50.]
##   [ 23.  24.]]


df = pd.DataFrame.from_records(data, columns=labels)
tt = ttest_ind(df['non-failing heart (NF)'], 
               df['failing heart (F)'], 
               equal_var=False, nan_policy='omit')

pvalue = tt.pvalue

glue('pvalue', math.ceil(pvalue * 1000.0) / 1000.0)
pvalue <- 0.00152894

Consistent with previous reports {cite}maeder2011,leszek2012 iron concentration was significantly lower in LV tissue samples from patients with advanced heart failure than in LV tissue samples from unused donor hearts. As shown by electrophoretic mobility shift assays, IRE binding activity was significantly (p < formatC(pvalue,3,format="f") ) reduced in failing hearts (most pronounced in patients with ischemic cardiomyopathy) ({ref}Figure 1<fig1>). Protein expression levels of the transferrin receptor were significantly lower in failing hearts than in the controls.

import numpy as np
import matplotlib.pyplot as plt

n = 256
X = np.linspace(-np.pi,np.pi,n,endpoint=True)
Y = np.sin(2*X)

fig, ax = plt.subplots( nrows=1, ncols=1 )
ax.plot (X, Y+1, color='blue', alpha=1.00)
ax.plot (X, Y-1, color='blue', alpha=1.00)
#plt.show()
fig.savefig('foo.png', bbox_inches='tight')
print "finished"