{'fraction_non_alphanumeric': 0.026198439241917504, 'fraction_numerical': 0.002787068004459309, 'mean_word_length': 5.799242424242424, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Relationships and distinctions in iron-regulatory networks responding to interrelated signals.

Specialized cDNA-based microarrays (IronChips) were developed to investigate complex physiological gene-regulatory patterns in iron metabolism. Approximately 115 human cDNAs were strategically selected to represent genes involved either in iron metabolism or in interlinked pathways (eg, oxidative stress, nitric oxide [NO] metabolism, or copper metabolism), and were immobilized on glass slides. HeLa cells were treated with iron donors or iron chelators, or were subjected to oxidative stress (H(2)O(2)) or NO (sodium nitroprusside). In addition, we generated a stable transgenic HeLa cell line expressing the HFE gene under an inducible promoter. Gene-response patterns were recorded for all of these interrelated experimental stimuli, and analyzed for common and distinct responses that define signal-specific regulatory patterns. The resulting regulatory patterns reveal and define degrees of relationship between distinct signals. Remarkably, the gene responses elicited by the altered expression of the hemochromatosis protein HFE and by pharmacological iron chelation exhibit the highest degree of relatedness, both for iron-regulatory protein (IRP) and non-IRP target genes. This finding suggests that HFE expression directly affects the intracellular chelatable iron pool in the transgenic cell line. Furthermore, cells treated with the iron donors hemin or ferric ammonium citrate display response patterns that permit the identification of the iron-loaded state in both cases, and the discrimination between the sources of iron loading. These findings also demonstrate the broad utility of gene-expression profiling with the IronChip to study iron metabolism and related human diseases.