Primal world beliefs (“primals”) capture understanding of general characteristics of the world, such as whether the world is “Good,” “Safe,” and “Enticing.” In a new study, researchers analyzed responses from children, mothers, fathers and then later, young adults in Colombia, Italy, Jordan, Kenya, Philippines, Sweden, Thailand, and the United States to learn about their world beliefs. 

In a new study, researchers analyzed responses from children, mothers, fathers and then later, young adults in Colombia, Italy, Jordan, Kenya, Philippines, Sweden, Thailand, and the United States to learn about their world beliefs. 

This research was featured in a new Child Development article with authors from Duke University (United States), the University of Miami (United States), the Eunice Kennedy Shriver National Institute of Child Health and Human Development (United States), UNICEF (United States), the Institute for Fiscal Studies (United Kingdom), University of Macau (China), the University of Pennsylvania (United States), University of Massachusetts Amherst (United States), Università di Roma “La Sapienza” (Italy), University West (Sweden), Chiang Mai University (Thailand), Maseno University (Kenya), Temple University (United States),  King Abdulaziz University (Saudi Arabia), Universidad de San Buenaventura (Colombia), and Ateneo de Manila University (Philippines). 

The study was led by Dr. Jennifer Lansford, SRCD’s incoming President and Research Professor in the Duke University Sanford School of Public Policy and Director of the Center for Child and Family Policy. This is the first longitudinal and multi-country study of primal world beliefs advancing understanding of how beliefs about the world are related to experiences in childhood and adolescence. The findings showed that parental warmth during childhood and adolescence led to “Good,” “Safe,” and “Enticing” world beliefs.

Dr. Pushkar Lele received a National Institute of General Medical Sciences research grant to investigate how bacteria sense their mechanical environment. 

Researchers at Tulane University have identified a potential new way to treat idiopathic pulmonary fibrosis (IPF), a deadly and currently incurable lung disease that affects more than 3 million people worldwide.

Genome editing has advanced at a rapid pace with promising results for treating genetic conditions—but there is always room for improvement. A new paper by investigators from Mass General Brigham published in Nature showcases the power of scalable protein engineering combined with machine learning to boost progress in the field of gene and cell therapy. In their study, authors developed a machine learning algorithm—known as PAMmla—that can predict the properties of about 64 million genome editing enzymes. The work could help reduce off-target effects and improve editing safety, enhance editing efficiency, and enable researchers to predict customized enzymes for new therapeutic targets.  Their results are published in Nature.