In Utero Exposure to Environmental Tobacco Smoke Increases Neuroinflammation in Offspring

The embryonic stage is the most vulnerable period for congenital abnormalities. Due to its prolonged developmental course, the central nervous system (CNS) is susceptible to numerous genetic, epigenetic, and environmental influences. During embryo implantation, the CNS is more vulnerable to external influences such as environmental tobacco smoke (ETS), increasing the risk for delayed fetal growth, sudden infant death syndrome, and immune system abnormalities. This study aimed to evaluate the effects of in utero exposure to ETS on neuroinflammation in the offspring of pregnant mice challenged or not with lipopolysaccharide (LPS). After the confirmation of mating by the presence of the vaginal plug until offspring birth, pregnant C57BL/6 mice were exposed to either 3R4F cigarettes smoke (Kentucky University) or compressed air, twice a day (1h each), for 21 days. Enhanced glial cell and mixed cell cultures were prepared from 3-day-old mouse pups. After cell maturation, both cells were stimulated with LPS or saline. To inhibit microglia activation, minocycline was added to the mixed cell culture media 24 h before LPS challenge. To verify the influence of in utero exposure to ETS on the development of neuroinflammatory events in adulthood, a different set of 8-week-old animals was submitted to the Autoimmune Experimental Encephalomyelitis (EAE) model. The results indicate that cells from LPS-challenged pups exposed to ETS in utero presented high levels of proinflammatory cytokines such as interleukin 6 (IL-6) and tumor necrosis factor-alpha (TNFα) and decreased cell viability. Such a proinflammatory environment could modulate fetal programming by an increase in microglia and astrocytes miRNA155. This scenario may lead to the more severe EAE observed in pups exposed to ETS in utero.

Infant urinary metabolomic profile in a fatal acute methadone intoxication

A case report suspicious for a Sudden Infant Death Syndrome is here described. Pathological findings were consistent with an acute respiratory failure while toxicological analysis revealed an elevated blood methadone concentration. Death was then ascribed to an acute methadone intoxication. In addition to the routinary approach, the urinary sample collected at autopsy was investigated with a 1H NMR metabolomic approach and the identified metabolomic profile was challenged with the urinary metabolomic profiles previously obtained from 10 newborns who experienced perinatal asphyxia and 16 healthy control newborns. Intriguingly, the urinary profile of the methadone intoxicated infant was very similar to those belonging to the perinatal asphyxia newborns, especially to those belonging to the newborns characterised by the worst outcome. The results offer several hints on a shared metabolic derangement between different mechanisms of asphyxia/hypoxia. To the best of the authors’ knowledge, this is the first report of the use of a metabolomic approach in a pathological case, in which metabolomics offers useful additional information regarding the mechanism and the cause of death.

Medullary Serotonergic Binding Deficits and Hippocampal Abnormalities in Sudden Infant Death Syndrome: One or Two Entities?

Sudden infant death syndrome (SIDS) is understood as a syndrome that presents with the common phenotype of sudden death but involves heterogenous biological causes. Many pathological findings have been consistently reported in SIDS, notably in areas of the brain known to play a role in autonomic control and arousal. Our laboratory has reported abnormalities in SIDS cases in medullary serotonin (5-HT) receptor 1A and within the dentate gyrus of the hippocampus. Unknown, however, is whether the medullary and hippocampal abnormalities coexist in the same SIDS cases, supporting a biological relationship of one abnormality with the other. In this study, we begin with an analysis of medullary 5-HT1A binding, as determined by receptor ligand autoradiography, in a combined cohort of published and unpublished SIDS (n = 86) and control (n = 22) cases. We report 5-HT1A binding abnormalities consistent with previously reported data, including lower age-adjusted mean binding in SIDS and age vs. diagnosis interactions. Utilizing this combined cohort of cases, we identified 41 SIDS cases with overlapping medullary 5-HT1A binding data and hippocampal assessment and statistically addressed the relationship between abnormalities at each site. Within this SIDS analytic cohort, we defined abnormal (low) medullary 5-HT1A binding as within the lowest quartile of binding adjusted for age and we examined three specific hippocampal findings previously identified as significantly more prevalent in SIDS compared to controls (granular cell bilamination, clusters of immature cells in the subgranular layer, and single ectopic cells in the molecular layer of the dentate gyrus). Our data did not find a strong statistical relationship between low medullary 5-HT1A binding and the presence of any of the hippocampal abnormalities examined. It did, however, identify a subset of SIDS (~25%) with both low medullary 5-HT1A binding and hippocampal abnormalities. The subset of SIDS cases with both low medullary 5-HT1A binding and single ectopic cells in the molecular layer was associated with prenatal smoking (p = 0.02), suggesting a role for the exposure in development of the two abnormalities. Overall, our data present novel information on the relationship between neuropathogical abnormalities in SIDS and support the heterogenous nature and overall complexity of SIDS pathogenesis.

Risk Factors for Sudden Infant Death in North Carolina

Background: Sudden infant death syndrome (SIDS) is the sudden, unexplained death of infants <1 year old. SIDS remains a leading cause of death in US infants. We aim to identify associations between SIDS and race/ethnicity, birth weight/gestational age, and socioeconomic/environmental factors in North Carolina (NC) to help identify infants at risk for SIDS.Methods and Results: In this IRB-approved study, infant mortality 2007–2016 and death certificate-linked natality 2007–2014 were obtained from the NC Department of Health and Human Services. General, NC natality statistics 2007–2016 were obtained from CDC Wonder. Association between SIDS/total infant death and covariates (below) were calculated. Total infant mortality decreased 2007–2016 by an average of 14 deaths/100,000 live births per year, while SIDS incidence remained constant. Risk ratios of SIDS/total infant deaths, standardized to Non-Hispanic White, were 1.76/2.41 for Non-Hispanic Black and 0.49/0.97 for Hispanic infants. Increased SIDS risk was significantly and independently associated with male infant sex, Non-Hispanic Black maternal race/ethnicity, young maternal age, low prenatal care, gestational age <39 weeks, birthweight <2500 g, low maternal education, and maternal tobacco use (p < 0.01). Maternal previous children now deceased also trended toward association with increased SIDS risk.Conclusions: A thorough SIDS risk assessment should include maternal, socioeconomic, and environmental risk factors as these are associated with SIDS in our population.

Memory-Efficient AI Algorithm for Infant Sleeping Death Syndrome Detection in Smart Buildings

Artificial intelligence (AI) is fundamentally transforming smart buildings by increasing energy efficiency and operational productivity, improving life experience, and providing better healthcare services. Sudden Infant Death Syndrome (SIDS) is an unexpected and unexplained death of infants under one year old. Previous research reports that sleeping on the back can significantly reduce the risk of SIDS. Existing sensor-based wearable or touchable monitors have serious drawbacks such as inconvenience and false alarm, so they are not attractive in monitoring infant sleeping postures. Several recent studies use a camera, portable electronics, and AI algorithm to monitor the sleep postures of infants. However, there are two major bottlenecks that prevent AI from detecting potential baby sleeping hazards in smart buildings. In order to overcome these bottlenecks, in this work, we create a complete dataset containing 10,240 day and night vision samples, and use post-training weight quantization to solve the huge memory demand problem. Experimental results verify the effectiveness and benefits of our proposed idea. Compared with the state-of-the-art AI algorithms in the literature, the proposed method reduces memory footprint by at least 89%, while achieving a similar high detection accuracy of about 90%. Our proposed AI algorithm only requires 6.4 MB of memory space, while other existing AI algorithms for sleep posture detection require 58.2 MB to 275 MB of memory space. This comparison shows that the memory is reduced by at least 9 times without sacrificing the detection accuracy. Therefore, our proposed memory-efficient AI algorithm has great potential to be deployed and to run on edge devices, such as micro-controllers and Raspberry Pi, which have low memory footprint, limited power budget, and constrained computing resources.

Are SIDS, SUDC and SUDEP the different masks of the same great mystery?

The cases of sudden, unexpected child death against the background of relative clinical well-being, i.e., in the absence of apparent reasons take a special place in the structure of infant mortality. Sudden Infant Death Syndrome (SIDS), which is recognized as one of the leading causes of postnatal infant mortality in most developed countries, is the most common cause of unexpected out-ofhospital death of a child. Today SIDS remains one of the most mysterious problems in medicine. The lack of identifiable mechanisms causing SIDS has led to a large number of theories about the mechanisms responsible for death due to this syndrome. Also, sudden unexplained death in childhood (SUDC), which is the unexplained death of children over one- year-old, is currently distinguished among cases of unexpected death. The main clinical features of SUDC include: more common in boys; death occurs at night time, children are found in the early morning in a prone position, face down; children often have convulsions, including febrile ones in the clinical symptom complex during life. Several authors have noted that in some cases, the death due to SUDC resembles Sudden Death in Epilepsy (SUDEP), which is the leading cause of death in epilepsy. To date, it has already been shown that SUDEP is one of the forms of canalopathies characteristic of young children and it is associated with a high risk of sudden death. The mechanisms of thanatogenesis in SUDEP remain unknown. SIDS, SUDC, and SUDEP are a series of fatal syndromes united by multifactorial pathophysiological mechanisms, the causes of which are not fully understood. In fact, these syndromes represent a catastrophic multisystem failure, which is caused by an extremely unfavorable combination of autonomic, respiratory and cardiogenic disorders.