Prolonged pregnancy: evaluating gestation-specific risks of fetal and infant mortality

Objective To evaluate gestation-specific risks of stillbirth, neonatal and post-neonatal mortality.
Design Retrospective analysis of 171,527 notified births (1989–1991) and subsequent infant survival at one year, from community child health records.
Setting Notifications from maternity units in the North East Thames Region, London.
Main outcome measures The incidence of births, stillbirths, neonatal and post-neonatal deaths at each gestation after 28 completed weeks. Mortality rates per 1000 total or live births and per 1000 ongoing pregnancies at each gestation were calculated.
Results The rates of stillbirth at term (2.3 per 1000 total births) and post-term (1.9 per 1000 total births) were similar. When calculated per 1000 ongoing pregnancies, the rate of stillbirth increased six-fold from 0.35 per 1000 ongoing pregnancies at 37 weeks to 2.12 per 1000 ongoing pregnancies at 43 weeks of gestation. Neonatal and post-neonatal mortality rates fell significantly with advancing gestation, from 15 1.4 and 31.7 per 1000 live births at 28 weeks, to reach a nadir at 41 weeks of gestation (0.7 and 1.3 per 1000 live births, respectively), increasing thereafter in prolonged gestation to 1.6 and 2.1 per 1000 live births at 43 weeks of gestation. When calculated per 1000 ongoing pregnancies, the overall risk of pregnancy loss (stillbirth + infant mortality) increased eight-fold from 0.7 per 1000 ongoing pregnancies at 37 weeks to 5.8 per 1000 ongoing pregnancies at 43 weeks of gestation.
Conclusion The risks of prolonged gestation on pregnancy are better reflected by calculating fetal and infant losses per 1000 ongoing pregnancies. There is a significant increase in the risk of stillbirth, neonatal and post-neonatal mortality in prolonged pregnancy. This study provides accurate data on gestation-specific risks of pregnancy loss, enabling pregnant women and their carers to judge the appropriateness of obstetric intervention.     

Incidence of urinary incontinence and constipation during pregnancy and postpartum: survey of current findings at the Rotunda Lying-in Hospital

Objective To assess the impact of pregnancy upon continence and constipation.
Design A questionnaire survey.
Setting Maternity wards in the Rotunda Lying In Hospital, Dublin, Republic of Ireland.
Population 7771 women who were delivered of liveborn infants.
Methods Questionnaires were delivered and collected by physiotherapy staff as part of routine postnatal care.
Results Analysis of data using χ² tests showed significant differences between three parity groups [primigravidae, multigravidae (2–4) and multigravidae (5+)] for symptoms of both urinary incontinence (  χ²= 119.54  , df = 2, P = 0.000) and constipation (  χ²= 12.53  , df = 3, P = 0.002); the incidence of both constipation and urinary incontinence increased with parity.
Conclusion The results of this survey have emphasised the relation between parity and postpartum incontinence which stresses the importance of early diagnosis and intervention.     

Orange Fanta versus orange fruit: A novel measure of nutrition knowledge in Malawi

This paper introduces a novel survey instrument to identify distinct components of nutrition knowledge and test for links between knowledge and dietary choices in Southern Malawi. Our first aim is to distinguish respondents' familiarity with recommended behaviours, such as when to start breastfeeding or introduce solid foods, from respondents' factual knowledge about mechanisms, such as whether biscuits or papaya and orange fruit or orange Fanta contribute more to future health. We find knowledge of nutrition behaviours to be strongly associated with more schooling, older age, and being female, whereas knowledge of mechanisms is associated only with training and employment as a health professional. We then test whether this expanded definition of nutrition knowledge is associated with dietary intake when controlling for other factors and find no significant links in these data. Results point to the need for knowledge surveys and public health behaviour‐change campaigns to address the kinds of information that might have the most influence on actual behaviour, potentially including the mechanisms involved in food composition, food safety, and disease transmission.     

Understanding the Driving Forces That Trigger Mutations in SARS-CoV-2: Mutational Energetics and the Role of Arginine Blockers in COVID-19 Therapy

SARS-CoV-2 is a global challenge due to its ability to mutate into variants that spread more rapidly than the wild-type virus. Because the molecular biology of this virus has been studied in such great detail, it represents an archetypal paradigm for research into new antiviral drug therapies. The rapid evolution of SARS-CoV-2 in the human population is driven, in part, by mutations in the receptor-binding domain (RBD) of the spike (S-) protein, some of which enable tighter binding to angiotensin-converting enzyme (ACE2). More stable RBD-ACE2 association is coupled with accelerated hydrolysis of furin and 3CLpro cleavage sites that augment infection. Non-RBD and non-interfacial mutations assist the S-protein in adopting thermodynamically favorable conformations for stronger binding. The driving forces of key mutations for Alpha, Beta, Gamma, Delta, Kappa, Lambda and Omicron variants, which stabilize the RBD-ACE2 complex, are investigated by free-energy computational approaches, as well as equilibrium and steered molecular dynamic simulations. Considered also are the structural hydropathy traits of the residues in the interface between SARS-CoV-2 RBD and ACE2 protein. Salt bridges and π-π interactions are critical forces that create stronger complexes between the RBD and ACE2. The trend of mutations is the replacement of non-polar hydrophobic interactions with polar hydrophilic interactions, which enhance binding of RBD with ACE2. However, this is not always the case, as conformational landscapes also contribute to a stronger binding. Arginine, the most polar and hydrophilic among the natural amino acids, is the most aggressive mutant amino acid for stronger binding. Arginine blockers, such as traditional sartans that bear anionic tetrazoles and carboxylates, may be ideal candidate drugs for retarding viral infection by weakening S-protein RBD binding to ACE2 and discouraging hydrolysis of cleavage sites. Based on our computational results it is suggested that a new generation of “supersartans”, called “bisartans”, bearing two anionic biphenyl-tetrazole pharmacophores, are superior to carboxylates in terms of their interactions with viral targets, suggesting their potential as drugs in the treatment of COVID-19. In Brief: This in silico study reviews our understanding of molecular driving forces that trigger mutations in the SARS-CoV-2 virus. It also reports further studies on a new class of “supersartans” referred to herein as “bisartans”, bearing two anionic biphenyltetrazole moieties that show potential in models for blocking critical amino acids of mutants, such as arginine, in the Delta variant. Bisartans may also act at other targets essential for viral infection and replication (i.e., ACE2, furin cleavage site and 3CLpro), rendering them potential new drugs for additional experimentation and translation to human clinical trials.     

Undifferentiated carcinoma with osteoclastic giant cells (UCOCGC) of the pancreas associated with the familial atypical multiple mole melanoma syndrome (FAMMM)

The familial atypical multiple mole melanoma (FAMMM) syndrome is caused by a germline mutation of p16. More than 90% of the sporadic pancreatic carcinomas contain genetic alterations that inactivate p16. Patients with the FAMMM syndrome have an increased risk of developing pancreatic cancer. Ductal adenocarcinoma is the most common cancer of the pancreas and the one encountered in patients with FAMMM syndrome. Undifferentiated carcinoma with osteoclastic giant cells, also referred to as UCOCGC of the pancreas, is a rare variant of pancreatic cancer. An UCOCGC of the pancreas associated with FAMMM syndrome is described in this report. Molecular analysis confirmed a germline p16-Leiden deletion in the UCOCGC, accompanied by somatic loss of heterozygosity of the second p16 allele, and absence of p16 protein expression in the neoplastic cells. It is the first case reported and it provides additional evidence that UCOCGC can be considered as a variant of conventional ductal adenocarcinoma of the pancreas.     

On the Utility of ToxCast-Based Predictive Models to Evaluate Potential Metabolic Disruption by Environmental Chemicals

Background: Research suggests environmental contaminants can impact metabolic health; however, high costs prohibit in vivo screening of putative metabolic disruptors. High-throughput screening programs, such as ToxCast, hold promise to reduce testing gaps and prioritize higher-order (in vivo) testing.Objectives: We sought to a) examine the concordance of in vitro testing in 3T3-L1 cells to a targeted literature review for 38 semivolatile environmental chemicals, and b) assess the predictive utility of various expert models using ToxCast data against the set of 38 reference chemicals.Methods: Using a set of 38 chemicals with previously published results in 3T3-L1 cells, we performed a metabolism-targeted literature review to determine consensus activity determinations. To assess ToxCast predictive utility, we used two published ToxPi models: a) the 8-Slice model published by Janesick et al. (2016) and b) the 5-Slice model published by Auerbach et al. (2016). We examined the performance of the two models against the Janesick in vitro results and our own 38-chemical reference set. We further evaluated the predictive performance of various modifications to these models using cytotoxicity filtering approaches and validated our best-performing model with new chemical testing in 3T3-L1 cells.Results: The literature review revealed relevant publications for 30 out of the 38 chemicals (the remaining 8 chemicals were only examined in our previous 3T3-L1 testing). We observed a balanced accuracy (average of sensitivity and specificity) of 0.86 comparing our previous in vitro results to the literature-derived calls. ToxPi models provided balanced accuracies ranging from 0.55 to 0.88, depending on the model specifications and reference set. Validation chemical testing correctly predicted 29 of 30 chemicals as per 3T3-L1 testing, suggesting good adipogenic prediction performance for our best adapted model.Discussion: Using the most recent ToxCast data and an updated ToxPi model, we found ToxCast performed similarly to that of our own 3T3-L1 testing in predicting consensus calls. Furthermore, we provide the full ranked list of largely untested chemicals with ToxPi scores that predict adipogenic activity and that require further investigation. https://doi.org/10.1289/EHP6779