Leveraging technological advances to assess dyadic visual cognition during infancy in high- and low-resource settings.

Caregiver-infant interactions shape infants' early visual experience; however, there is limited work from low-and middle-income countries (LMIC) in characterizing the visual cognitive dynamics of these interactions. Here, we present an innovative dyadic visual cognition pipeline using machine learning methods which captures, processes, and analyses the visual dynamics of caregiver-infant interactions across cultures. We undertake two studies to examine its application in both low (rural India) and high (urban UK) resource settings. Study 1 develops and validates the pipeline to process caregiver-infant interaction data captured using head-mounted cameras and eye-trackers. We use face detection and object recognition networks and validate these tools using 12 caregiver-infant dyads (4 dyads from a 6-month-old UK cohort, 4 dyads from a 6-month-old India cohort, and 4 dyads from a 9-month-old India cohort). Results show robust and accurate face and toy detection, as well as a high percent agreement between processed and manually coded dyadic interactions. Study 2 applied the pipeline to a larger data set (25 6-month-olds from the UK, 31 6-month-olds from India, and 37 9-month-olds from India) with the aim of comparing the visual dynamics of caregiver-infant interaction across the two cultural settings. Results show remarkable correspondence between key measures of visual exploration across cultures, including longer mean look durations during infant-led joint attention episodes. In addition, we found several differences across cultures. Most notably, infants in the UK had a higher proportion of infant-led joint attention episodes consistent with a child-centered view of parenting common in western middle-class families. In summary, the pipeline we report provides an objective assessment tool to quantify the visual dynamics of caregiver-infant interaction across high- and low-resource settings.

Infant milk formula, produced by membrane filtration, promotes mucus production in the upper small intestine of young pigs.

Human breast milk promotes maturation of the infant gastrointestinal barrier, including the promotion of mucus production. In the quest to produce next generation infant milk formula (IMF), we have produced IMF by membrane filtration (MEM-IMF). With a higher quantity of native whey protein, MEM-IMF more closely mimics human breast milk than IMF produced using conventional heat treatment (HT-IMF). After a 4-week dietary intervention in young pigs, animals fed a MEM-IMF diet had a higher number of goblet cells, acidic mucus and mucin-2 in the jejunum compared to pigs fed HT-IMF (P < 0.05). In the duodenum, MEM-IMF fed pigs had increased trypsin activity in the gut lumen, increased mRNA transcript levels of claudin 1 in the mucosal scrapings and increased lactase activity in brush border membrane vesicles than those pigs fed HT-IMF (P < 0.05). In conclusion, MEM-IMF is superior to HT-IMF in the promotion of mucus production in the young gut.