Higher Risks of Copper Toxicity in Turbid Waters: Quantifying the Bioavailability of Particle-Bound Metals to Set Site-Specific Water Quality Criteria

In coastal waters, particulate metals constitute a substantial fraction of the total metals; however, the prevalent water quality criteria are primarily based on dissolved metals, seemingly neglecting the contribution of particulate metals. Here we developed a method to quantify the toxicity risk of particulate metals, and proposed a way to calculate modifying factors (MFs) for setting site-specific criteria in turbid waters. Specifically, we used a side-by-side experimental design to study copper (Cu) bioaccumulation and toxicity in an estuarine clam, Potamocorbula laevis, under the exposure to “dissolved only” and “dissolved + particulate” 65Cu. A toxicokinetic-toxicodynamic model (TK-TD) was used to quantify the processes of Cu uptake, ingestion, assimilation, egestion, and elimination, and to relate mortality risk to tissue Cu. We find that particulate Cu contributes 40–67% of the Cu bioaccumulation when the suspended particulate matter (SPM) ranges from 12 to 229 mg L–1. The Cu-bearing SPM also increases the sensitivity of organisms to internalized Cu by decreasing the internal threshold concentration (CIT) from 141 to 76.8 μg g–1. MFs were derived based on the TK-TD model to consider the contribution of particulate Cu (in the studied SPM range) for increasing Cu bioaccumulation (MF = 1.3–2.2) and toxicity (MF = 2.3–3.9). Water quality criteria derived from dissolved metal exposure need to be lowered by dividing by an MF to provide adequate protection. Overall, the method we developed provides a scientifically sound framework to manage the risks of metals in turbid waters

Higher Risks of Copper Toxicity in Turbid Waters: Quantifying the Bioavailability of Particle-Bound Metals to Set Site-Specific Water Quality Criteria

In coastal waters, particulate metals constitute a substantial fraction of the total metals; however, the prevalent water quality criteria are primarily based on dissolved metals, seemingly neglecting the contribution of particulate metals. Here we developed a method to quantify the toxicity risk of particulate metals, and proposed a way to calculate modifying factors (MFs) for setting site-specific criteria in turbid waters. Specifically, we used a side-by-side experimental design to study copper (Cu) bioaccumulation and toxicity in an estuarine clam, Potamocorbula laevis, under the exposure to “dissolved only” and “dissolved + particulate” 65Cu. A toxicokinetic-toxicodynamic model (TK-TD) was used to quantify the processes of Cu uptake, ingestion, assimilation, egestion, and elimination, and to relate mortality risk to tissue Cu. We find that particulate Cu contributes 40–67% of the Cu bioaccumulation when the suspended particulate matter (SPM) ranges from 12 to 229 mg L–1. The Cu-bearing SPM also increases the sensitivity of organisms to internalized Cu by decreasing the internal threshold concentration (CIT) from 141 to 76.8 μg g–1. MFs were derived based on the TK-TD model to consider the contribution of particulate Cu (in the studied SPM range) for increasing Cu bioaccumulation (MF = 1.3–2.2) and toxicity (MF = 2.3–3.9). Water quality criteria derived from dissolved metal exposure need to be lowered by dividing by an MF to provide adequate protection. Overall, the method we developed provides a scientifically sound framework to manage the risks of metals in turbid waters

Synthesis, crystal structure, and DFT study of (<i>E</i>)-<i>N²</i>,<i>N</i>²-dimethyl-6-styryl-1,3,5-triazine-2,4-diamine and (<i>E</i>)-<i>N</i>-(4-(dimethylamino)-6-styryl-1,3,5-triazin-2-yl) acetamide

(E)-N2,N2-dimethyl-6-styryl-1,3,5-triazine-2,4-diamine and (E)-N-(4-(dimethylamino)-6-styryl-1,3,5-triazin-2-yl) acetamide are important intermediates for the synthesis of triazine compounds. The structure of the target compounds were confirmed using 1H NMR, 13C NMR, HRMS and FT-IR spectroscopy. The precise structure of (E)-N2,N2-dimethyl-6-styryl-1,3,5-triazine-2,4-diamine and (E)-N-(4-(dimethylamino)-6-styryl-1,3,5-triazin-2-yl) acetamide were analyzed using single-crystal X-ray diffraction. The molecular structures were further calculated using density functional theory (DFT), which were compared with the X-ray diffraction value. The results of the conformational analysis indicate that the molecular structures optimized by DFT were consistent with the crystal structures determined by single crystal X-ray diffraction. In addition, the molecular electrostatic potential and frontier molecular orbitals of the title compounds were further investigated by DFT, and some physicochemical properties of the compounds are revealed.</p

The Updated Phylogenies of the Phasianidae Based on Combined Data of Nuclear and Mitochondrial DNA

<div><p>The phylogenetic relationships of species in the Phasianidae, Order Galliformes, are the object of intensive study. However, convergent morphological evolution and rapid species radiation result in much ambiguity in the group. Further, matrilineal (mtDNA) genealogies conflict with trees based on nuclear DNA retrotransposable elements. Herein, we analyze 39 nearly complete mitochondrial genomes (three new) and up to seven nuclear DNA segments. We combine these multiple unlinked, more informative genetic markers to infer historical relationships of the major groups of phasianids. The nuclear DNA tree is largely congruent with the tree derived from mt genomes. However, branching orders of mt/nuclear trees largely conflict with those based on retrotransposons. For example, <i>Gallus/Bambusicola/Francolinus</i> forms the sister-group of <i>Coturnix/Alectoris</i> in the nuclear/mtDNA trees, yet the tree based on retrotransposable elements roots the former at the base of the tree and not with the latter. Further, while peafowls cluster with <i>Gallus/Coturnix</i> in the mt tree, they root at the base of the phasianids following <i>Gallus</i> in the tree based on retrotransposable elements. The conflicting branch orders in nuclear/mtDNA and retrotransposons-based trees in our study reveal the complex topology of the Phasianidae.</p></div

Phylogenetic hypotheses from the mitochondrial (mt) genome and retrotransposable elements for the Phasianidae.

<p>(a) Topology based on mt genomes (Shen <i>et al</i>. 2010); (b) topology based on insertion events of CR1 retrotransposable nuclear DNA elements <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095786#pone.0095786-Kaiser1" target="_blank">[6]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095786#pone.0095786-Liu1" target="_blank">[17]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095786#pone.0095786-Kriegs1" target="_blank">[20]</a>; (C) topology based on nuclear DNA segments (Crowe et al., 2006).</p

Phylogenetic hypotheses based on the complete mitochondrial genomes and nuclear segments for the Phasianidae.

<p>(a) Mt genomes; newly sequenced mt genomes denoted in bold. (b) Nuclear segments. Bayesian posterior probabilities >70%, and maximum likelihood bootstrap proportions >50% were indicated on the branches.</p

Data_Sheet_1_Comprehensive analysis of vulnerability status and associated affect factors among prehospital emergency patients: a single-center descriptive cross-sectional study.pdf

BackgroundPrehospital emergency care is a critical but often understudied aspect of healthcare. Patient vulnerability in this setting can significantly impact outcomes. The aim of this study was to investigate the vulnerability status and to determine associated affect factors among prehospital emergency patients in China.MethodsIn this cross-sectional study conducted in China, from April 2023 to July 2023, we assessed the vulnerability of prehospital emergency patients using the Safety in Prehospital Emergency Care Index (SPECI) scale. We conducted a detailed questionnaire-based survey to gather demographic and disease-related information. We employed the SPECI scale, consisting of two subscales, to evaluate patient vulnerability. Statistical analyses, including t-tests, ANOVA, and multiple linear regression, were used to identify factors associated with vulnerability.ResultsThe study included a total of 973 prehospital emergency patients, with a response rate of 81.9%. These patients exhibited a low-to-moderate level of vulnerability, with an average SPECI score of 14.46 out of 40. Vulnerability was significantly associated with age (particularly those aged 60 and above), disease severity (severe conditions increased vulnerability), disease type (circulatory diseases correlated with higher vulnerability), alterations in consciousness, and chronic diseases. Unexpectedly, digestive system diseases were negatively correlated with vulnerability.ConclusionAddressing patient vulnerability in prehospital care is essential. Tailored interventions, EMS provider training, and interdisciplinary collaboration can mitigate vulnerability, especially in older patients and those with severe conditions.</p

Polymorphism statistics and neutral tests in both the BM and CID populations.

<p>Note:</p>1<p> The number of chromosome; ² Number of segregating sites; ³ Nucleotide diversity.</p><p>Polymorphism statistics and neutral tests in both the BM and CID populations.</p

Median-joining network showing the genealogy of the BM Block 3 haplotypes in the BM population.

<p>Each haplotypes is shown as a circle with the size of the circle representing the haplotype frequency. Nucleotide differences between haplotypes are shown on the branches of the network.</p

The distribution of three population genetic statistics and the information of coalescent simulations.

<p>(A) Distribution of Tajima's D values for the 9 segments of the <i>CDH2</i> gene region in the BM and CID populations. (B) Standard coalescent simulations under a neutral model for the genealogy of the BM. Part I is the genealogy of BM and parts II-IV are standard coalescent simulations for segments S4, S5, S6, respectively, under different values for N5 (50,000 and 100,000) in the BM population. P_mean is the mean of the P values for the Tajima D test. (C) SNP heterozygosity distribution in the <i>CDH2</i> gene region in the BM and CID populations. (D) Frequency distribution of heterozygotes for each SNP in the BM and CID populations.</p