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BackgroundOxidative stress has been implicated in numerous birth outcomes, including spontaneous preterm birth. However, the relationship with presentation at delivery has been less well studied. We assessed the relationship between oxidative stress biomarkers and gestational duration with a focus on spontaneous presentation for delivery.MethodsOur sample included 740 women from a multi-center prospective cohort study, recruited from 2010 to 2012. Resultant measures of oxidative stress in pregnancy prostaglandin F2α (PGF2α), 8-iso-prostaglandin F2α (8-iso-PGF2α), and the primary 8-iso-PGF2α metabolite were measured in third trimester urine samples. Information on presentation for delivery was abstracted from medical records. We examined associations with preterm birth using adjusted logistic models. Time to event (overall delivery and spontaneous delivery) was examined using adjusted accelerated failure time models.ResultsThe 8-iso-PGF2α metabolite was associated with increased odds of overall preterm birth (OR: 1.44 [95% CI: 1.00, 2.06]), and the association with spontaneous preterm birth was similar in magnitude but not statistically significant (OR: 1.45 [95% CI: 0.96, 2.20]). We did not detect associations between other biomarkers and preterm birth, or between biomarkers and timing of overall or spontaneous delivery in accelerated failure time models.ConclusionsOur data suggest that increased oxidative stress, as indicated by the 8-iso-PGF2α metabolite, may be associated with preterm birth. In contrast to previous studies, associations were similar among individuals with spontaneous versus non-spontaneous presentation for delivery.

This article discusses a study published in the Journal of Neurology, Neurosurgery & Psychiatry that examines the association between persistent organic pollutants (POPs) and amyotrophic lateral sclerosis (ALS) risk and survival. The study found that higher plasma concentrations of POPs, specifically organochlorine pesticides (OCPs), were associated with greater ALS risk and shorter survival. The authors suggest that these findings support the idea that POPs may play a role in the development and progression of ALS, and that quantitative assessments of environmental pollutants could help identify individuals at risk for ALS and other neurodegenerative diseases. The article also provides information about the authors, ethical considerations, data availability, and references to other relevant studies. [Extracted from the article]

To identify associations between occupational settings and self-reported occupational exposures on amyotrophic lateral sclerosis (ALS) survival and phenotypes. All patients seen in the University of Michigan Pranger ALS Clinic were invited to complete an exposure assessment querying past occupations and exposures. Standard occupational classification (SOC) codes for each job and the severity of various exposure types were derived. Cox proportional hazards models associated all-cause mortality with occupational settings and the self-reported exposures after adjusting for sex, diagnosis age, revised El Escorial criteria, onset segment, revised ALS Functional Rating Scale (ALSFRS-R), and time from symptom onset to diagnosis. Multinomial logistic regression models with three categories, adjusted for age, assessed the association between occupational settings and exposures to onset segment. Among the 378 ALS participants (median age, 64.7 years; 54.4% male), poorer survival was associated with work in SOC code "Production Occupations" and marginally with work in "Military Occupation"; poor survival associated with self-reported occupational pesticide exposure in adjusted models. Among onset segments: cervical onset was associated with ALS participants having ever worked in "Buildings and Grounds Cleaning and Maintenance Occupations," "Construction and Extraction Occupations," and "Production Occupations"; bulbar onset with self-reported occupational exposure to radiation; and cervical onset with exposure to particulate matter, volatile organic compounds, metals, combustion and diesel exhaust, electromagnetic radiation, and radiation. Occupational settings and self-reported exposures influence ALS survival and onset segment. Further studies are needed to explore and understand these relationships, most advantageously using prospective cohorts and detailed ALS registries. [ABSTRACT FROM AUTHOR]

Introduction/Aims: Body mass index (BMI) is linked to amyotrophic lateral sclerosis (ALS) risk and prognosis, but additional research is needed. The aim of this study was to identify whether and when historical changes in BMI occurred in ALS participants, how these longer term trajectories associated with survival, and whether metabolomic profiles provided insight into potential mechanisms. Methods: ALS and control participants self‐reported body height and weight 10 (reference) and 5 years earlier, and at study entry (diagnosis for ALS participants). Generalized estimating equations evaluated differences in BMI trajectories between cases and controls. ALS survival was evaluated by BMI trajectory group using accelerated failure time models. BMI trajectories and survival associations were explored using published metabolomic profiling and correlation networks. Results: Ten‐year BMI trends differed between ALS and controls, with BMI loss in the 5 years before diagnosis despite BMI gains 10 to 5 years beforehand in both groups. An overall 10‐year drop in BMI associated with a 27.1% decrease in ALS survival (P =.010). Metabolomic networks in ALS participants showed dysregulation in sphingomyelin, bile acid, and plasmalogen subpathways. Discussion: ALS participants lost weight in the 5‐year period before enrollment. BMI trajectories had three distinct groups and the group with significant weight loss in the past 10 years had the worst survival. Participants with a high BMI and increase in weight in the 10 years before symptom onset also had shorter survival. Certain metabolomics profiles were associated with the BMI trajectories. Replicating these findings in prospective cohorts is warranted. See Editorial on pages 191‐192 in this issue [ABSTRACT FROM AUTHOR]

Survival analysis represents an important outcome measure in clinical research and clinical trials; further, survival ranking may offer additional advantages in clinical trials. In this study, we developed a non-parametric ranking-based technique to transform patients' survival data into a linear space of hazard ranks. The transformation enables the utilization of machine learning base-learners including Gaussian process regression, Lasso, and random forest on survival data. The method was submitted to the DREAM Amyotrophic Lateral Sclerosis (ALS) Stratification Challenge. Ranked first place, the model gave more accurate ranking predictions on the PRO-ACT ALS dataset in comparison to Cox proportional hazard model. By utilizing right-censored data in its training process, the method demonstrated its state-of-the-art predictive power in ALS survival ranking. Its feature selection identified multiple important factors, some of which conflicts with previous studies. [ABSTRACT FROM AUTHOR]

Social and economic disadvantage are hypothesized to increase the risk of disease and death via accelerated biological aging. Given that US blacks are socially and economically disadvantaged relative to whites, health disparities scholars expected that blacks would have shorter telomere length-a biomarker of cell aging-than whites. Yet the majority of studies have found that blacks have longer telomere length than whites. Using data from the National Health and Nutrition Examination Survey (n = 3,761; 28.3% non-Hispanic black, 71.7% non-Hispanic white), we found that leukocyte telomere length was 4.00% (95% CI: 1.12%, 6.87%) longer among blacks compared to whites in the full sample, but differences were greatest among those with lower SES (5.66%; 95% CI: 0.10%, 10.32%), intermediate among those with middle SES (4.14%; 95% CI: 0.05%, 8.24%), and smallest among those with higher SES (2.33%; 95% CI: -3.02%, 7.67%). These results challenge purely genetic explanations for race differences in telomere length and point to a potential social-environmental cause of longer telomere length in US blacks.