Frequency of pollutants listed by section 303(d) of the Clean Water Act for catchments in networks 5, 8, and 9.

<p>The counts of sediment/siltation and temperature are likely due to incompatible forestry.</p

Dendrogram showing hierarchical division of estuary networks and agglomeration schedule.

<p>The hierarchical clustering identified nine substantive networks at a Euclidean distance of 2.5. Major divisions are by development (Network 2; d = 16), impaired inflows (Networks 1, 5, 8; d = 10), and approved shellfish growing areas (Networks 4; d = 7.5).</p

Geographic summary statistics for each estuary network.

<p>Standard distance is a measure of the spatial dispersion of the network, lower values are compact, higher values are spread out. The proportion area is the total area of the network divided by the total area of all estuaries in the study. Proportion sample is the number of estuaries in the network divided by the total number in the study.</p

Mean values for threat variables for each network (development, shoreline development and armoring, port facilities, toxics release, agriculture, dams, shellfish aquaculture, clearcutting, 303(d) streams, precipitation reduction).

<p>High values for any threat indicates relatively more stress on the estuary.</p

Map of estuary networks in the study region.

<p>Networks were created using hierarchical cluster analysis of 11 variables that represent stresses to estuaries in the region.</p

Conceptual diagram showing estuary stresses mapped from land and sea sources combined using cluster analysis to create regional networks.

<p>These networks can ideally inform local conservation actions.</p

Regioselective C–H Bond Alkynylation of Carbonyl Compounds through Ir(III) Catalysis

Selective C–H bond alkynylation toward modular access to material and pharmaceutical molecules is of great desire in modern organic synthesis. Reported herein is Ir­(III)-catalyzed regioselective C–H alkynylation of ketones and esters, which is generally applicable for the rapid construction of molecular complexity. This protocol provides a complementary process for conventional alkyne synthesis. Further functionalization of carbonyl-derived material molecules and pharmaceuticals demonstrates the potential synthetic utility of this methodology

Manganese-Loaded Dual-Mesoporous Silica Spheres for Efficient T1- and T2-Weighted Dual Mode Magnetic Resonance Imaging

A novel class of manganese-based dual-mode contrast agents (DMCAs) based on the core–shell structured manganese-loaded dual-mesoporous silica spheres (Mn-DMSSs) for simultaneous T1- and T2-weighted magnetic resonance imaging (MRI) has been successfully reported. The in vitro MR tests demonstrate that the Mn-based DMCAs display an excellent simultaneous T1-weighted and T2-weighted MR imaging effect with a noticeably high T1 relaxivity (<i>r</i>₁) of 10.1 mM^–1s^–1 and a moderately high T2 relaxivity (<i>r</i>₂) of 169.7 mM^–1s^–1. The Mn-based DMCAs exhibit negligible cytotoxicity with >80% cell viability at a concentration of up to 200 μg/mL in human liver carcinoma (HepG2) and mouse macrophage (RAW264.7) cells after 24 h. Confocal laser scanning microscopy (CLSM) results show that the Mn-DMSSs were internalized via endocytosis and located in the cytoplasm but not in the nucleus. The in vivo experiment shows that the signals of rat liver increased by 29% under T1-weighted imaging mode and decreased by 28% under T2-weighted imaging mode in 5 min postinjection of Mn-DMSSs, which reveal that the novel Mn-loaded DMSSs can be used as both positive (T1-weighted) and negative (T2-weighted) MR contrast agents in further biomedical applications

Baseline patient characteristics (n = 124).

<p>Abbreviations: IQR, interquartile range; KPS, Karnofsky performance status; BMI, body mass index; BSA, body surface area; SM, skeletal muscle; VAT, visceral adipose tissue; SAT, subcutaneous adipose tissue; HU, Hounsfield unit.</p><p>Baseline patient characteristics (n = 124).</p

Cox regression models analyzing the potential influence of body composition variables on OS times.

<p>Abbreviations: HR, hazard ratio; VATI, visceral adipose tissue index; SATI, subcutaneous adipose tissue index; SMI, skeletal muscle index; BMI, body mass index; BSA, body surface area; VATD, visceral adipose tissue density; SATD, subcutaneous adipose tissue density; SMD, skeletal muscle density</p><p>* interaction term with BMI was included</p><p>Cox regression models analyzing the potential influence of body composition variables on OS times.</p