Value of Community Partnership for Understanding Stress and Coping in Rural Yup’ik Communities: The CANHR Study

Stress and trauma can compromise physical and mental health. Rural Alaska Native communities have voiced concern about stressful and traumatic events and their effects on health. The goal of the Yup’ik Experiences of Stress and Coping Project is to develop an in-depth understanding of experiences of stress and ways of coping in Yup’ik communities. The long-range goal is to use project findings to develop and implement a community-informed and culturally grounded intervention to reduce stress and promote physical and mental health in rural Alaska Native communities. This paper introduces a long-standing partnership between the Yukon-Kuskokwim Regional Health Corporation, rural communities it serves, and the Center for Alaska Native Health Research at the University of Alaska Fairbanks. Within the context of the Stress and Coping project, we then discuss the value and challenges of taking a CBPR approach to advance science and address a priority community concern, and share strategies to respond to challenges. Focus groups were conducted to culturally adapt an existing structured interview and daily diary protocol to better fit Yup’ik ways of knowing. As modified, these interviews increased understanding of stress and coping particular to two Yup’ik communities. Challenges included the geographical nature of Yup’ik communities, communication barriers, competing priorities, and confidentiality issues. Community participation was central in the development of the study protocol, helped ensure that the research was culturally appropriate and relevant to the community, and facilitated access to participant knowledge and rich data to inform intervention development

Psychosocial Factors and Functional Capacity Evaluation Among Persons with Chronic Pain

Psychosocial factors have been found to have a significant impact on functional activity, particularly among persons with chronic pain. While various systems have been developed to assess functional limitations through functional capacity evaluation (FCE), assessment of psychosocial factors that may impact function have been largely ignored. This paper examines the existing literature on psychosocial factors and FCE performance. Given that there are few studies that have directly addressed this issue, the paper also examines psychosocial factors that have been found to influence function in persons with pain. The results of the literature review indicate that few psychosocial factors have been found to be directly associated with FCE and functional measures, although many are related to various measures of disability. The strongest evidence that psychosocial factors are related to functional performance is based on the studies examining the association between functional activity and pain-related fear, self-efficacy, and illness behavior. Psychosocial factors have also been shown to influence measures of sincerity of effort often obtained during FCE. Proposals for modifying FCE assessment are given based on the available data, as well as suggestions for future research.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45009/1/10926_2004_Article_475080.pd

Enabling precision medicine in neonatology, an integrated repository for preterm birth research.

Preterm birth, or the delivery of an infant prior to 37 weeks of gestation, is a significant cause of infant morbidity and mortality. In the last decade, the advent and continued development of molecular profiling technologies has enabled researchers to generate vast amount of 'omics' data, which together with integrative computational approaches, can help refine the current knowledge about disease mechanisms, diagnostics, and therapeutics. Here we describe the March of Dimes' Database for Preterm Birth Research (http://www.immport.org/resources/mod), a unique resource that contains a variety of 'omics' datasets related to preterm birth. The database is open publicly, and as of January 2018, links 13 molecular studies with data across tens of thousands of patients from 6 measurement modalities. The data in the repository are highly diverse and include genomic, transcriptomic, immunological, and microbiome data. Relevant datasets are augmented with additional molecular characterizations of almost 25,000 biological samples from public databases. We believe our data-sharing efforts will lead to enhanced research collaborations and coordination accelerating the overall pace of discovery in preterm birth research

Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy.

MotivationMultiple biological clocks govern a healthy pregnancy. These biological mechanisms produce immunologic, metabolomic, proteomic, genomic and microbiomic adaptations during the course of pregnancy. Modeling the chronology of these adaptations during full-term pregnancy provides the frameworks for future studies examining deviations implicated in pregnancy-related pathologies including preterm birth and preeclampsia.ResultsWe performed a multiomics analysis of 51 samples from 17 pregnant women, delivering at term. The datasets included measurements from the immunome, transcriptome, microbiome, proteome and metabolome of samples obtained simultaneously from the same patients. Multivariate predictive modeling using the Elastic Net (EN) algorithm was used to measure the ability of each dataset to predict gestational age. Using stacked generalization, these datasets were combined into a single model. This model not only significantly increased predictive power by combining all datasets, but also revealed novel interactions between different biological modalities. Future work includes expansion of the cohort to preterm-enriched populations and in vivo analysis of immune-modulating interventions based on the mechanisms identified.Availability and implementationDatasets and scripts for reproduction of results are available through: https://nalab.stanford.edu/multiomics-pregnancy/.Supplementary informationSupplementary data are available at Bioinformatics online

An immune clock of human pregnancy

The maintenance of pregnancy relies on finely tuned immune adaptations. We demonstrate that these adaptations are precisely timed, reflecting an immune clock of pregnancy in women delivering at term. Using mass cytometry, the abundance and functional responses of all major immune cell subsets were quantified in serial blood samples collected throughout pregnancy. Cell signaling-based Elastic Net, a regularized regression method adapted from the elastic net algorithm, was developed to infer and prospectively validate a predictive model of interrelated immune events that accurately captures the chronology of pregnancy. Model components highlighted existing knowledge and revealed previously unreported biology, including a critical role for the interleukin-2-dependent STAT5ab signaling pathway in modulating T cell function during pregnancy. These findings unravel the precise timing of immunological events occurring during a term pregnancy and provide the analytical framework to identify immunological deviations implicated in pregnancy-related pathologies

Clinical Impact of Ceftriaxone Resistance in Escherichia coli Bloodstream Infections: A Multicenter Prospective Cohort Study

BACKGROUND: Ceftriaxone-resistant (CRO-R) Escherichia coli bloodstream infections (BSIs) are common. METHODS: This is a prospective cohort of patients with E coli BSI at 14 United States hospitals between November 2020 and April 2021. For each patient with a CRO-R E coli BSI enrolled, the next consecutive patient with a ceftriaxone-susceptible (CRO-S) E coli BSI was included. Primary outcome was desirability of outcome ranking (DOOR) at day 30, with 50% probability of worse outcomes in the CRO-R group as the null hypothesis. Inverse probability weighting (IPW) was used to reduce confounding. RESULTS: Notable differences between patients infected with CRO-R and CRO-S E coli BSI included the proportion with Pitt bacteremia score ≥4 (23% vs 15%, P = .079) and the median time to active antibiotic therapy (12 hours [interquartile range {IQR}, 1-35 hours] vs 1 hour [IQR, 0-6 hours]; P \u3c .001). Unadjusted DOOR analyses indicated a 58% probability (95% confidence interval [CI], 52%-63%) for a worse clinical outcome in CRO-R versus CRO-S BSI. In the IPW-adjusted cohort, no difference was observed (54% [95% CI, 47%-61%]). Secondary outcomes included unadjusted and adjusted differences in the proportion of 30-day mortality between CRO-R and CRO-S BSIs (-5.3% [95% CI, -10.3% to -.4%] and -1.8 [95% CI, -6.7% to 3.2%], respectively), postculture median length of stay (8 days [IQR, 5-13 days] vs 6 days [IQR, 4-9 days]; P \u3c .001), and incident admission to a long-term care facility (22% vs 12%, P = .045). CONCLUSIONS: Patients with CRO-R E coli BSI generally have poorer outcomes compared to patients infected with CRO-S E coli BSI, even after adjusting for important confounders

Clinical Impact of Ceftriaxone Resistance in Escherichia coli Bloodstream Infections: A Multicenter Prospective Cohort Study

Background: Ceftriaxone-resistant (CRO-R) Escherichia coli bloodstream infections (BSIs) are common. Methods: This is a prospective cohort of patients with E coli BSI at 14 United States hospitals between November 2020 and April 2021. For each patient with a CRO-R E coli BSI enrolled, the next consecutive patient with a ceftriaxone-susceptible (CRO-S) E coli BSI was included. Primary outcome was desirability of outcome ranking (DOOR) at day 30, with 50% probability of worse outcomes in the CRO-R group as the null hypothesis. Inverse probability weighting (IPW) was used to reduce confounding. Results: Notable differences between patients infected with CRO-R and CRO-S E coli BSI included the proportion with Pitt bacteremia score ≥4 (23% vs 15%, P =. 079) and the median time to active antibiotic therapy (12 hours [interquartile range {IQR}, 1-35 hours] vs 1 hour [IQR, 0-6 hours]; P <. 001). Unadjusted DOOR analyses indicated a 58% probability (95% confidence interval [CI], 52%-63%) for a worse clinical outcome in CRO-R versus CRO-S BSI. In the IPW-adjusted cohort, no difference was observed (54% [95% CI, 47%-61%]). Secondary outcomes included unadjusted and adjusted differences in the proportion of 30-day mortality between CRO-R and CRO-S BSIs (-5.3% [95% CI, -10.3% to -.4%] and -1.8 [95% CI, -6.7% to 3.2%], respectively), postculture median length of stay (8 days [IQR, 5-13 days] vs 6 days [IQR, 4-9 days]; P <. 001), and incident admission to a long-term care facility (22% vs 12%, P =. 045). Conclusions: Patients with CRO-R E coli BSI generally have poorer outcomes compared to patients infected with CRO-S E coli BSI, even after adjusting for important confounders

Multiomics Characterization of Preterm Birth in Low- and Middle-Income Countries.

Importance: Worldwide, preterm birth (PTB) is the single largest cause of deaths in the perinatal and neonatal period and is associated with increased morbidity in young children. The cause of PTB is multifactorial, and the development of generalizable biological models may enable early detection and guide therapeutic studies. Objective: To investigate the ability of transcriptomics and proteomics profiling of plasma and metabolomics analysis of urine to identify early biological measurements associated with PTB. Design, Setting, and Participants: This diagnostic/prognostic study analyzed plasma and urine samples collected from May 2014 to June 2017 from pregnant women in 5 biorepository cohorts in low- and middle-income countries (LMICs; ie, Matlab, Bangladesh; Lusaka, Zambia; Sylhet, Bangladesh; Karachi, Pakistan; and Pemba, Tanzania). These cohorts were established to study maternal and fetal outcomes and were supported by the Alliance for Maternal and Newborn Health Improvement and the Global Alliance to Prevent Prematurity and Stillbirth biorepositories. Data were analyzed from December 2018 to July 2019. Exposures: Blood and urine specimens that were collected early during pregnancy (median sampling time of 13.6 weeks of gestation, according to ultrasonography) were processed, stored, and shipped to the laboratories under uniform protocols. Plasma samples were assayed for targeted measurement of proteins and untargeted cell-free ribonucleic acid profiling; urine samples were assayed for metabolites. Main Outcomes and Measures: The PTB phenotype was defined as the delivery of a live infant before completing 37 weeks of gestation. Results: Of the 81 pregnant women included in this study, 39 had PTBs (48.1%) and 42 had term pregnancies (51.9%) (mean [SD] age of 24.8 [5.3] years). Univariate analysis demonstrated functional biological differences across the 5 cohorts. A cohort-adjusted machine learning algorithm was applied to each biological data set, and then a higher-level machine learning modeling combined the results into a final integrative model. The integrated model was more accurate, with an area under the receiver operating characteristic curve (AUROC) of 0.83 (95% CI, 0.72-0.91) compared with the models derived for each independent biological modality (transcriptomics AUROC, 0.73 [95% CI, 0.61-0.83]; metabolomics AUROC, 0.59 [95% CI, 0.47-0.72]; and proteomics AUROC, 0.75 [95% CI, 0.64-0.85]). Primary features associated with PTB included an inflammatory module as well as a metabolomic module measured in urine associated with the glutamine and glutamate metabolism and valine, leucine, and isoleucine biosynthesis pathways. Conclusions and Relevance: This study found that, in LMICs and high PTB settings, major biological adaptations during term pregnancy follow a generalizable model and the predictive accuracy for PTB was augmented by combining various omics data sets, suggesting that PTB is a condition that manifests within multiple biological systems. These data sets, with machine learning partnerships, may be a key step in developing valuable predictive tests and intervention candidates for preventing PTB

Ovicidal Activity of Organophosphate, Oxadiazine, Neonicotinoid and Insect Growth Regulator Chemistries on Northern Strain Plum Curculio, Conotrachelus nenuphar

An in vitro method was developed for assessing ovicidal effects of the organophosphate azinphos-methyl, the neonicotioids thiacloprid, thiamethoxam and clothianidin, the oxadiazine indoxacarb and the insect growth regulators novaluron and pyriproxifen on the plum curculio, Conotrachelus nenuphar (Herbst)(Coleoptera: Curculionidae). The baseline survivorship of this method was 88 percent. Plum curculio eggs were most sensitive to azinphos-methyl. Thiacloprid, clothianidin and the chitin synthesis inhibitor, novaluron, had LC50 values below 100 ppm. Thiamethoxam, indoxacarb and pyriproxifen were not ovicidal at 100 ppm. Octanol-water partitioning coefficients, log Kow, appeared to be an important indicator of ovicidal activity within the neonicotinoids. This new bioassay method eliminates the confounding of the insect-chemical and plant-chemical interactions and the results highlight the utility of a post-infestation curative approach to plum curculio management