The Relationship Between Screen Use and preschoolers' Social-Emotional Problems Among Highly Educated Migrant Families: A One-Year Follow-Up Study.

Introduction: The present study investigated the relationship between screen use and social-emotional problems in preschoolers aged 46 to 72 months from migrant families.

Methods: The parents of 427 children completed the Ages and Stages Questionnaire: Social Emotional II (ASQ: SE II) and the survey on screen use at two time points (T1 and T2) with one-year interval.

Results: There were no significant changes in preschoolers' social-emotional problems and screen use over one year.

Social-emotional problems in 3-to 5-year-old children: a cross-sectional study of highly educated migrants in a Chinese urban area.

Background: Previous research has primarily examined the mental well-being of children from labor migrant families, yet there is a lack of understanding regarding the mental well-being of children from highly educated migrant backgrounds. This study investigated the social-emotional problems of 3-5-year-olds from highly educated migrant families residing in an urban area of China, as well as explored potential differences in demographic variables.

Methods: A cross-sectional study was conducted in Qiantang District, Hangzhou, China, with 1,494 (53.

Association between parents' concerns about eating and sleeping problems and social-emotional development in Chinese children aged 3 to 6 years.

Background: Parents' parenting beliefs have a major influence on their children's eating and sleeping problems and emotional socialization. However, the relationship between parent's concerns about eating or sleeping problems and social-emotional development is unclear.

Methods: We used a convenience sampling method to investigate 997 parents of preschool children aged 3 to 6 in Hangzhou, China, and asked them to complete the "Ages & Stages Questionnaire: Social-Emotional (2nd Edition)" (ASQ: SE-2) and the Survey of Concerns about Children's Eating and Sleeping Problems.

The predictive value of machine learning for mortality risk in patients with acute coronary syndromes: a systematic review and meta-analysis.

Background: Acute coronary syndromes (ACS) are the leading cause of global death. Optimizing mortality risk prediction and early identification of high-risk patients is essential for developing targeted prevention strategies. Many researchers have built machine learning (ML) models to predict the mortality risk in ACS patients.

Enhanced Ca handling in thioglycolate-elicited peritoneal macrophages.

In macrophage biology, resident peritoneal macrophages (RPMs) and thioglycolate-elicited peritoneal macrophages (TGPMs) have been traditionally utilized as primary cultured models. RPMs and TGPMs exhibit distinct morphological, functional and metabolic characteristics, although it remains unclear how cellular Ca handling differs between them. In our Fura-2 Ca imaging, TGPMs displayed elevated resting Ca levels, increased store Ca contents and facilitated store-operated Ca entry (SOCE) compared with RPMs.