The field of biomedical research relies on the knowledge of binding interactions between various proteins of interest to create novel molecular targets for therapeutic purposes. While many of these interactions remain a mystery, knowledge of these properties and interactions could have significant medical applications in terms of understanding cell signaling and immunological defenses. Furthermore, there is evidence that machine learning and peptide microarrays can be used to make reliable predictions of where proteins could interact with each other without the definitive knowledge of the interactions. In this case, a neural network was used to predict the unknown binding interactions of TNFR2 onto LT-ɑ and TRAF2, and PD-L1 onto CD80, based off of the binding data from a sampling of protein-peptide interactions on a microarray. The accuracy and reliability of these predictions would rely on future research to confirm the interactions of these proteins, but the knowledge from these methods and predictions could have a future impact with regards to rational and structure-based drug design.
Level of education had little impact on whether or not women received the nutrition packet. Of those women with no education, 63.1% received the packet. Of those with any education, 63.9% got the packet.
In contrast, distance was strongly correlated with whether or not women received the packet. For example, of the women living within 200 meters of the health center, 93.2% received a nutrition packet. Of the women living between 250 meters and one kilometer of the health center, 68.4% received a nutrition packet. Of the women living over one kilometer from the health center, only 25% received a nutrition packet. The relationship between uptake of packets and women’s perception of distance to the health center was also explored. Out of 50 women who did not receive the packet, all of the women who said there was no health center in their village did live more than one kilometer from a health center. Of the women who lived between 250 meters and one kilometer from the health center, 40% felt it was too far. Of the women who lived more than a kilometer from the health center, 66.7% felt it was too far and 29.6% said there was no health center in their village. Again, it does not appear that ‘too far’ is just a default reason for women, but that actual distance, more so than education, is a major contributing factor in their ability to take the nutrition packet. These findings suggest that improving access to supplemental nutrition packets at the village level may increase uptake by the women.