Uranium (U) waste, generated at a variety of mines and nuclear production sites, migrates in the subsurface, posing a serious threat to contaminate groundwater systems. In this study, batch equilibrium and kinetic experiments , geochemical modeling and solid phase characterization were conducted to investigate the impact of Cr(VI), a common co-contaminant, on the adsorption of U(VI) to quartz, plagioclase feldspar, and carbonate-dominated sediment (≤2 mm). Batch experiments were performed under slightly alkaline conditions (7.80 ± 0.18) and in the presence of major groundwater components (Ca 2+ , Mg 2+ , Na + , K + , carbonate, chloride, and sulfate) at different U(VI):Cr(VI) molar ratios 10:1, 1:1, and 1:10 at lower U(VI) concentration (10.5 μM [2.5 mg/ L]) and at U(VI):Cr(VI) molar ratios of 168:1.05, 168:10.5, 168:105, 1:1, and 1:10 at higher U(VI) concentration (168 μM [40 mg/L]). At the low U(VI) concentration (10.5 μM [2.5 mg/L]), the distribution coefficients (K d) were unchanged for the 10:1 and 1:1 U:Cr molar ratios indicating an excess of available U(VI) adsorption sites on the sediment. However, the U(VI) K d values in the presence of Cr(VI) at the 1:10 M ratio decreased suggesting competition between U(VI) and Cr(VI) for adsorption sites. At the higher U(VI) concentration (168 μM [40 mg/ L]), the K d values were unaffected by U(VI):Cr(VI) molar ratios of 168:1.05, 168:10.5, 168:105, again indicating an excess of available sediment adsorption sites. At U:Cr molar ratios 1:1 and 1:10, there was a slight increase in K d for U(VI) possibly reflecting an increase in inner-sphere binding of uranyl carbonate complexes. The adsorption process followed pseudo second-order kinetic parameters. These results indicate the sediment affinity for U(VI) adsorption appears to be largely independent of Cr(VI) under our experimental conditions. The intraparticle diffusion modeling of U(VI) adsorption to the sediment suggests a multi-step process, including film and intraparticle diffusion. The intraparticle diffusion stage remained constant in the presence of Cr(VI) suggesting the rate determining factors for overall equilibrium adsorption process for U(VI) was independent of Cr (VI). Understanding the mobility of U(VI) under natural conditions as simulated in our study is critical in developing effective remediation strategies and effective monitored natural attenuation (MNA) following the remediation of contaminated sites.
Background: First responders have experienced increased levels of stress, anxiety, and depression due to job-related pressures associated with the COVID-19 pandemic. However, little is known about the factors associated with first responder drug and alcohol use during this time. Methods: We conducted a nationwide survey of first responders (n = 2801) to understand the relationship between work pressures, workplace support strategies, and problematic substance use during the early stages of the COVID-19 pandemic. We employed structural equation modeling to analyze whether burnout mediated these relationships. Results: Descriptive statistics showed that 60.8 % reported no concerns with substance use. While general workplace support strategies were negatively associated with problematic substance use, specific COVID-related strategies, such as providing compensation during quarantine, were positively associated with problematic substance use. Burnout fully mediated relationships between workplace support strategies and problematic substance use. Finally, providing spaces at work to decompress was negatively associated with problematic substance use and burnout. Conclusion: Although work pressures increased burnout and problematic substance use among first responders, general workplace support strategies (e.g., decompression spaces) reduced problematic substance use while some COVID-related strategies (e.g. compensation during quarantine) increased problematic substance use. Policy interventions to address problematic substance use should focus on providing spaces for first responders to decompress at work, as well as implementing strategies (e.g., access to mental health services, time off) to reduce burnout. However, organizations should be mindful that not all interventions will have their intended impact and some interventions may unintentionally contribute to negative employee outcomes.
The tumor cell population in cancer tissue has distinct molecular characteristics and exhibits different phenotypes, thus, resulting in different subpopulations. This phenomenon is known as Intratumor Heterogeneity (ITH), a major contributor to drug resistance, poor prognosis, etc. Therefore, quantifying the levels of ITH in cancer patients is essential, and many algorithms do so in different ways, using different types of omics data. DEPTH2 algorithm utilizes transcriptomic data to assess ITH scores and exhibits promising performance. However, it quantifies ITH using all genes, limiting the identification of ITH-related prognostic genes. We hypothesize that a subset of key genes is sufficient to quantify the ITH level, and this subset of key genes could be ITH-related prognostic genes. To prove our hypothesis, we propose an unsupervised deep learning-based framework using Concrete Autoencoder (CAE) to select a subset of cancer-specific key genes for ITH evaluation. For the experiment, we used gene expression profile data of breast, kidney, and lung cancer tumor cohorts from the TCGA repository. Multi-run CAE identified three sets of key genes for each cancer cohort. Comparing ITH scores derived from all genes and CAE-selected key genes showed similar prognostic outcomes. Subtypes of lung cancer displayed consistent ITH distributions for both gene sets. Based on these observations, it can be concluded that a subset of key genes, instead of all, is sufficient for ITH quantification. Our results also showed that many key genes are prognostically significant and can be used as therapeutic targets.
This paper extends the paradigm of "mobile edge learning (MEL)" by designing an energy-aware optimal task allocation scheme for training a machine learning (ML) model in a semi-asynchronous manner across multiple learners connected via the resource-constrained wireless edge network. The tasks are allocated such that the local dataset size selected at each learner ensures completion within a given global delay constraint and a local maximum energy consumption limit. Hence, the designed method is heterogeneity aware (HA) because it offers a trade-off between resource consumption and MEL performance by directly relating the time and energy consumption to the heterogeneous communication/computational capabilities of learners. Because the resulting optimization is an NP-hard quadratically-constrained integer linear program (QCILP), a two-step suggest-and-improve (SAI) solution is proposed. The proposed HA semi-asynchronous (HA-Asyn) approach is compared against the HA synchronous (HA-Sync) scheme and the heterogeneity unaware (HU) synchronous/asynchronous (HU-Sync/Asyn) equal batch allocation schemes. Results from a system of 20 learners tested for various completion time and energy consumption constraints show that the proposed HA-Asyn method works better than the HU-Sync/Asyn approaches and can even provide gains of up-to 25% compared to the HA-Sync scheme.
A workshop was held at the Massachusetts Institute of Technology (MIT) on July 25th and 26th, 2022. The objective was to develop a blueprint for educating next-generation engineers and scientists about nuclear waste management and disposal, which requires knowledge from diverse disciplines, including nuclear, chemical, civil, environmental, and geological science and engineering. The 49 participants included university professors, researchers , industry experts, and government officials from different areas. First, we have developed a list of key fundamental knowledge on waste management and disposal across the nuclear fuel cycle. In addition, we discussed strategies on how to teach students with diverse backgrounds through innovative teaching strategies as well as how to attract students into this area. Through the workshop, we identified the critical needs to (1) develop community resources for nuclear waste education; (2) synthesize historical perspectives, including past contamination and the management of general hazardous waste; (3) emphasize a complete life-cycle perspective, including proper waste management as the key component for energy sustainability; (4) teach students how to communicate about the key facts and risks to technical and non-technical audiences; and (5) accelerate the use of the state-of-art-technologies to attract and retain a young workforce. Furthermore, we aim to build a diverse, inclusive community that supports students in developing their own narratives about nuclear waste, particularly in recognizing that antagonistic views have been important to improving safety and protecting public health and the environment.
Plasmonic molecular junctions can harvest visible light and effectively catalyze chemical reactions. The strong light field concentrated in the plasmonic junction also enables the application of surface enhanced Raman spectroscopy (SERS) to probe the catalyzed chemical reactions in situ and in real time down to single-molecule resolution. The benzyl radical produced from the aromatic methyl group through the dehydrogenation reaction is an important precursor for a large variety of reactions. Here, we used time-resolved SERS to conduct a mechanistic study of the plasmon-driven dehydrogenation reaction of the aromatic methyl group under ambient conditions under the illumination of red light on the apex of a gold nanoelectrode. Transient spectral changes with intensity bursts are frequently observed. Based on density functional theory and picocavity based local electric field enhancement calculations, they result from the plasmon mediated dehydrogenation reaction of aromatic methyl groups. The dehydrogenation reaction produces a benzyl radical, which is consequently converted to a benzyl anion. The benzyl anion is stabilized through strong interactions with gold, leading to the formation of dynamic gold adatoms and picocavities. In addition to the benzyl anion, we found spectral evidence that the benzyl radical generates dimers through a self-reaction. Furthermore, we demonstrated that the dehydrogenation reaction could be facially modulated by changing the electrode potential, which is attributed to the modulated inductive effect.
Background People with HIV (PWH) are at increased risk for COVID-19 complications and thus can significantly benefit from COVID-19 vaccination. PWH are also more likely to belong to racial/ethnic minority groups that have been underrepresented among vaccinated individuals. The objective of this analysis was to identify Health Belief Model (e.g., perceived susceptibility to and severity of COVID-19, perceived barriers, and benefits of COVID-19 vaccination) and Social Ecological Model (i.e., intrapersonal, interpersonal, and community/institutional-level) factors associated with vaccine uptake among PWH. Methods The cross-sectional survey was administered by telephone in English, Spanish or Haitian Creole from January–March 2022 to a sample of 299 adult PWH receiving medical case management services through the Miami-Dade County Ryan White Program (MDCRWP). Participants who received a primary vaccine series were classified as fully vaccinated, and those that received only 1 dose of a 2-dose vaccine series or no doses were classified as not fully vaccinated. Multivariable logistic regression was used to estimate adjusted odds ratios (aORs) of full vaccination with 95% confidence intervals (CIs). The final adjusted model included all sociodemographic characteristics selected a priori, as well as covariates with a p-value < 0.2 in bivariate analyses. Analyses were weighted to be representative of the race/ethnicity and sex distribution of clients in the MDCRWP. Results The weighted percentages for full vaccination was 83.8% for the entire group, and 88.9% among Hispanics, 72.0% among African Americans, and 67.5% among Haitians. Being fully vaccinated was associated with Hispanic compared with African American race/ethnicity (aOR 5.44; 95% CI 1.50-19.77), not endorsing any misconceptions about COVID-19 vaccines (aOR 8.26; 95% CI 1.38-49.64), reporting encouragement to get vaccinated from their sources of information (aOR 20.82; 95% CI 5.84-74.14), and perception that ≥ 50% of social network was vaccinated (aOR 3.35; 95% CI 1.04-10.71) (Table 1). Conclusion Results highlight the importance of promoting accurate information from sources deemed trustworthy, and social networks in COVID-19 vaccine uptake among PWH. Disclosures All Authors: No reported disclosures
Understanding how individuals flourish is critical to understanding adaptation to daily life stressors or the stress of major global and historical life events such as the COVID-19 pandemic. The present qualitative study explored the meaning and functions of play and playfulness in the lives of adults. A total of 837 adult participants (Mage = 23.52, SD = 6.28) provided detailed answers to the question “What does it mean to you to be playful?” Using thematic analyses, five main themes emerged: A Positive Outlook, Activities, Relationships, Humor, and Experiencing Life. From these themes we propose that adult play and playfulness are ways of experiencing life that are often motivated by the experience of positive emotions, humor, and engagement in activities that promote relationships and that relate to positive mental health outcomes. Our findings show the integral role that being playfulness provides in adults’ lives, and provide guideposts for future research on play and playfulness as essential strengths that enable individuals to thrive and make meaning and emotional connections with others in their lives.
The success of microbial endosymbionts, which reside naturally within a eukaryotic “host” organism, requires effective microbial interaction with, and manipulation of, the host cells. Fluorescence microscopy has played a key role in elucidating the molecular mechanisms of endosymbiosis. For 30 years, fluorescence analyses have been a cornerstone in studies of endosymbiotic Wolbachia bacteria, focused on host colonization, maternal transmission, reproductive parasitism, horizontal gene transfer, viral suppression, and metabolic interactions in arthropods and nematodes. Fluorescence-based studies stand to continue informing Wolbachia-host interactions in increasingly detailed and innovative ways.
The current work-up of the primary tumor site of a head and neck squamous cell carcinoma of unknown primary is not standardized and results in several time-consuming procedures that delay treatment initiation. This article seeks to consolidate contemporary strategies used to identify the primary tumor site of an unknown primary head and neck squamous cell carcinoma and offer recommendations based on current literature review.
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused a global health crisis with significant clinical morbidity and mortality. While angiotensin-converting enzyme 2 (ACE2) is the primary receptor for viral entry, other cell surface and extracellular matrix proteins may also bind to the viral receptor binding domain (RBD) within the SARS-CoV-2 spike protein. Recent studies have implicated heparan sulfate proteoglycans, specifically perlecan LG3, in facilitating SARS-CoV-2 binding to ACE2. However, the role of perlecan LG3 in SARS-CoV-2 pathophysiology is not well understood. In this study, we investigated the binding interactions between the SARS-CoV-2 spike protein RBD and perlecan LG3 through molecular modeling simulations and surface plasmon resonance (SPR) experiments. Our results indicate stable binding between LG3 and SARS-CoV-2 spike protein RBD, which may potentially enhance RBD-ACE2 interactions. These findings shed light on the role of perlecan LG3 in SARS-CoV-2 infection and provide insight into SARS-CoV-2 pathophysiology and potential therapeutic strategy for COVID-19. This article is protected by copyright. All rights reserved.
Crocodylians globally face considerable challenges, including population decline and extensive habitat modification. Close monitoring of crocodylian populations and their habitats is imperative for the timely detection of population trends, especially in response to management interventions. Here we use eDNA metabarcoding to identify the Critically Endangered Crocodylus rhombifer and the Vulnerable C. acutus , as well as vertebrate community diversity, in Cuba’s Zapata Swamp. We tested four different primer sets, including those used previously in Crocodylus population genetic and phylogenetic research, for their efficiency at detecting crocodylian eDNA. We detected C. rhombifer eDNA in 11 out of 15 sampled locations within its historical geographic distribution. We found that data analyses using the VertCOI primers and the mBRAVE bioinformatics pipeline were the most effective molecular marker and pipeline combination for identifying this species from environmental samples. We also identified 55 vertebrate species in environmental samples across the four bioinformatics pipelines— ~ 85% known to be present in the Zapata ecosystem. Among them were eight species previously undetected in the area and eight alien species, including known predators of hatchling crocodiles (e.g., Clarias sp.) and egg predators (e.g., Mus musculus ). This study highlights eDNA metabarcoding as a powerful tool for crocodylian biomonitoring within fragile and diverse ecosystems, particularly where fast, non-invasive methods permit detection in economically important areas and will lead to a better understanding of complex human-crocodile interactions and evaluate habitat suitability for potential reintroductions or recovery programs for threatened crocodylian species.
In the Amazon, the world's largest river basin, migrations within freshwater habitats are one of the predominant life history strategies for fishes. The flood pulse and the extensive river network provide aquatic organisms with temporal and spatial accessibility to a mosaic of freshwater habitats. Although migratory fish species are central to freshwater ecosystems and fisheries, the knowledge of species and migratory patterns has traditionally relied on anecdotal and scattered information, lacking a unifying methodological and conceptual framework. We quantitatively synthesize the evidence about this biological phenomenom in the Amazon basin through a systematic literature review. We constructed a reference database of migratory events in the Amazon basin, including species, life stages, purposes, direction, habitats and subbasins. We found that 223 species were documented in 90 references as performing migrations distributed across eight orders and 31 families. Migration is a conserved trait in the evolutionary history of Amazonian fish fauna, suggesting that ~41% of migratory species are likely unreported. We noted a geographical bias in the report of migratory events towards 13 of the 27 major subbasins of the Amazon. We found a significant association between the hydrological timing at the beginning and end of migrations across species, including reproduction as the most commonly reported purpose. However, most species lack the application of robust methods (e.g. telemetry, otolith microchemistry) to classify them as migratory, relying upon secondary sources of information (i.e. reviews or species checklists). Further, we discuss future opportunities and challenges to continue the study of fish migrations in the Amazon basin. 2 | HERRERA-R et al.
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