181 research outputs found

    From UV to NIR: A Full-Spectrum Metal-Free Photocatalyst for Efficient Polymer Synthesis in Aqueous Conditions

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    Photo‐mediation offers unparalleled spatiotemporal control over controlled radical polymerizations (CRP). Photo‐induced electron/energy transfer reversible addition–fragmentation chain transfer (PET‐RAFT) polymerization is particularly versatile owing to its oxygen tolerance and wide range of compatible photocatalysts. In recent years, broadband‐ and near‐infrared (NIR)‐mediated polymerizations have been of particular interest owing to their potential for solar‐driven chemistry and biomedical applications. In this work, we present the first example of a novel photocatalyst for both full broadband‐ and NIR‐mediated CRP in aqueous conditions. Well‐defined polymers were synthesized in water under blue, green, red, and NIR light irradiation. Exploiting the oxygen tolerant and aqueous nature of our system, we also report PET‐RAFT polymerization at the microliter scale in a mammalian cell culture medium

    Progress and Perspectives Beyond Traditional RAFT Polymerization.

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    The development of advanced materials based on well-defined polymeric architectures is proving to be a highly prosperous research direction across both industry and academia. Controlled radical polymerization techniques are receiving unprecedented attention, with reversible-deactivation chain growth procedures now routinely leveraged to prepare exquisitely precise polymer products. Reversible addition-fragmentation chain transfer (RAFT) polymerization is a powerful protocol within this domain, where the unique chemistry of thiocarbonylthio (TCT) compounds can be harnessed to control radical chain growth of vinyl polymers. With the intense recent focus on RAFT, new strategies for initiation and external control have emerged that are paving the way for preparing well-defined polymers for demanding applications. In this work, the cutting-edge innovations in RAFT that are opening up this technique to a broader suite of materials researchers are explored. Emerging strategies for activating TCTs are surveyed, which are providing access into traditionally challenging environments for reversible-deactivation radical polymerization. The latest advances and future perspectives in applying RAFT-derived polymers are also shared, with the goal to convey the rich potential of RAFT for an ever-expanding range of high-performance applications

    Mobility, Expansion and Management of a Multi-Species Scuba Diving Fishery in East Africa

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    Background: Scuba diving fishing, predominantly targeting sea cucumbers, has been documented to occur in an uncontrolled manner in the Western Indian Ocean and in other tropical regions. Although this type of fishing generally indicates a destructive activity, little attention has been directed towards this category of fishery, a major knowledge gap and barrier to management. Methodology and Principal Findings: With the aim to capture geographic scales, fishing processes and social aspects the scuba diving fishery that operate out of Zanzibar was studied using interviews, discussions, participant observations and catch monitoring. The diving fishery was resilient to resource declines and had expanded to new species, new depths and new fishing grounds, sometimes operating approximately 250 km away from Zanzibar at depths down to 50 meters, as a result of depleted easy-access stock. The diving operations were embedded in a regional and global trade network, and its actors operated in a roving manner on multiple spatial levels, taking advantage of unfair patron-client relationships and of the insufficient management in Zanzibar. Conclusions and Significance: This study illustrates that roving dynamics in fisheries, which have been predominantly addressed on a global scale, also take place at a considerably smaller spatial scale. Importantly, while proposed management of the sea cucumber fishery is often generic to a simplified fishery situation, this study illustrates

    Association between maternal occupational exposure to cleaning chemicals during pregnancy and childhood wheeze and asthma

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    BackgroundAsthma is a leading cause of childhood morbidity in the U.S. and a significant public health concern. The prenatal period is a critical window during which environmental influences, including maternal occupational exposures, can shape child respiratory health. Cleaning chemicals are commonly encountered in occupational settings, yet few studies have examined the potential link between prenatal occupational exposures to cleaning chemicals and risk of childhood wheeze and asthma.MethodsWe evaluated the potential influence of maternal occupational exposure to cleaning chemicals during pregnancy on pediatric asthma and wheeze at child age 4–6 years in 453 mother-child pairs from two longitudinal pregnancy cohorts, TIDES and GAPPS, part of the ECHO prenatal and early childhood pathways to health (ECHO-PATHWAYS) consortium. Maternal occupational exposure to cleaning chemicals was defined based on reported occupation and frequency of occupational use of chemicals during pregnancy. Child current wheeze and asthma outcomes were defined by parental responses to a widely-used, standardized respiratory outcomes questionnaire administered at child age 4–6 years. Multivariable Poisson regression with robust standard errors was used to estimate relative risk (RR) of asthma in models adjusted for confounding. Effect modification by child sex was assessed using product interaction terms.ResultsOverall, 116 mothers (25.6%) reported occupational exposure to cleaning chemicals during pregnancy, 11.7% of children had current wheeze, and 10.2% had current asthma. We did not identify associations between prenatal exposure to cleaning chemicals and current wheeze [RRadjusted 1.03, 95% confidence interval (CI): 0.56, 1.90] or current asthma (RRadjusted 0.89, CI: 0.46, 1.74) in the overall sample. Analyses of effect modification suggested an adverse association among females for current wheeze (RR 1.82, CI: 0.76, 4.37), compared to males (RR 0.68, CI: 0.29, 1.58), though the interaction p-value was >0.05.ConclusionWe did not observe evidence of associations between maternal prenatal occupational exposure to cleaning chemicals and childhood wheeze or asthma in the multi-site ECHO-PATHWAYS consortium. We leveraged longitudinal U.S. pregnancy cohorts with rich data characterization to expand on limited and mixed literature. Ongoing research is needed to more precisely characterize maternal occupational chemical exposures and impacts on child health in larger studies

    Systems Biology of the qa Gene Cluster in Neurospora crassa

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    An ensemble of genetic networks that describe how the model fungal system, Neurospora crassa, utilizes quinic acid (QA) as a sole carbon source has been identified previously. A genetic network for QA metabolism involves the genes, qa-1F and qa-1S, that encode a transcriptional activator and repressor, respectively and structural genes, qa-2, qa-3, qa-4, qa-x, and qa-y. By a series of 4 separate and independent, model-guided, microarray experiments a total of 50 genes are identified as QA-responsive and hypothesized to be under QA-1F control and/or the control of a second QA-responsive transcription factor (NCU03643) both in the fungal binuclear Zn(II)2Cys6 cluster family. QA-1F regulation is not sufficient to explain the quantitative variation in expression profiles of the 50 QA-responsive genes. QA-responsive genes include genes with products in 8 mutually connected metabolic pathways with 7 of them one step removed from the tricarboxylic (TCA) Cycle and with 7 of them one step removed from glycolysis: (1) starch and sucrose metabolism; (2) glycolysis/glucanogenesis; (3) TCA Cycle; (4) butanoate metabolism; (5) pyruvate metabolism; (6) aromatic amino acid and QA metabolism; (7) valine, leucine, and isoleucine degradation; and (8) transport of sugars and amino acids. Gene products both in aromatic amino acid and QA metabolism and transport show an immediate response to shift to QA, while genes with products in the remaining 7 metabolic modules generally show a delayed response to shift to QA. The additional QA-responsive cutinase transcription factor-1β (NCU03643) is found to have a delayed response to shift to QA. The series of microarray experiments are used to expand the previously identified genetic network describing the qa gene cluster to include all 50 QA-responsive genes including the second transcription factor (NCU03643). These studies illustrate new methodologies from systems biology to guide model-driven discoveries about a core metabolic network involving carbon and amino acid metabolism in N. crassa

    The Relative Role of Perceived Partner Risks in Promoting Condom Use in a Three-City Sample of High-Risk, Low-Income Women

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    We examined the effect of women’s perceptions of sexual partner risks on condom use. Women from three US cities (n = 1,967) were recruited to provide data on HIV risks. In univariate models, increased odds of condom use were associated with perceiving that partners had concurrent partners and being unaware of partners': (a) HIV status, (b) bisexuality, (c) concurrency; and/or (d) injection drug use. In multivariate models, neither being unaware of the four partner risk factors nor perceiving a partner as being high risk was associated with condom use. Contextual factors associated with decreased odds of condom use were having sex with a main partner, homelessness in the past year, alcohol use during sex, and crack use in the past 30 days. Awareness of a partner’s risks may not be sufficient for increasing condom use. Contextual factors, sex with a main partner in particular, decrease condom use despite awareness of partner risk factors

    Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies

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    Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner’s ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person’s own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships
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