Concentration and Distribution of Six Trace Metals in Northern Kentucky Soils

Concentration and distribution of cadmium (Cd), chromium (Cr), copper (Cu), nickel (Ni), lead (Pb), and zinc (Zn) were determined in 26 soil profiles (n = 78) of northern Kentucky in response to environmental concerns about increasing anthropogenic inputs in a fast-paced urbanizing area. The selected sites represent alluvial, glacial till or residual soils that have not received any biosolid- or industrial-waste applications. Mean concentrations of Zn (53.8 mg kg^?1) and Ni (25.9 mg kg^?1) were the highest in the soil profile, whereas Cd (0.21 mg kg^?1) was present only in trace amounts. All metals were within the low to middle range of baseline concentrations reported for US soils, suggesting minimal anthropogenic inputs. The distribution of Cu, Cr, Ni, and Zn increased with soil depth, whereas Cd and Pb concentrations were unaffected throughout the soil profile. Alluvial soils had the highest overall metal accumulations, particularly in surface soil horizons, indicating potential metal enrichment through depositional processes. The presence of a fragipan horizon or depth to bedrock did not significantly affect metal retention. Single correlation and multiple regression analyses indicated OM and pH as the most influential soil parameters for metal retention, followed by cation exchange capacity (CEC) and CEC/clay. Single correlations among metals suggested strong covariance of Zn with most metals throughout the soil profile, but weaker for Pb and Ni.     

A rapid LAMP-based colorimetric assay with quick DNA extraction for on-site identification of Drosophila suzukii Matsumura

The spotted wing drosophila, Drosophila suzukii Matsumura (Diptera: Drosophilidae), distributes in most soft-skinned fruit areas in China, is an economically important pest of fresh cherries during Sino-European trade and is considered a quarantine pest in A2 list by European and Mediterranean Plant Protection Organization. Loop-mediated isothermal amplification (LAMP) is an accurate, quick and convenient molecular identification method, applied to distinguish D. suzukii from other fruit flies. This method can be used for inspection in the field, and at the points of entry (POEs), because its results can be detected with the naked eye due to colour changes. In our study, first, we reported a simple and fast LAMP colorimetric detection method for molecular identification of D. suzukii. We designed primer sets for D. suzukii based on mitochondrial cytochrome oxidase I (COI) sequences. The specificity and sensitivity of the primers were tested by using target and non-target fruit flies in the family Drosophilidae and Tephritidae, usually intercepted during the Sino-European cherry trade. Second, for detection in the field and at POEs, the adoption of a quick DNA extraction method could save the total time of LAMP identification to about 90 min. Taken together, this accurate, quick and convenient LAMP-based colorimetric identification assay combined with a quick DNA extraction method could visually detect clearly with just one portable heating device, which will be useful for rapid on-site identification and inspection for D. suzukii by the quarantine department.     

U-Shaped Dose-Response Relationships for Mutation and Cancer

A biologically based mutation model that can be parameterized to reflect U-shaped behavior at low doses of genotoxic substances is derived. The U-shaped behavior results from an efficient, adaptive DNA repair process, by which some endogenous DNA damage that would not be repaired in the absence of the genotoxic substance is repaired when low levels of the substance are present. Hence, the model embodies a type of hormesis. The dose response is U shaped even though the genotoxic mechanism is additive to an existing background mutation process. The risk-assessment implications regarding possible hormetic effects, instead of the generally expected low-dose-linear effects, for agents that are both genotoxic and additive to background are discussed.     

Forest productivity recovery or collapse? Model-data integration insights on drought-induced tipping points

More frequent and severe droughts are driving increased forest mortality around the globe. We urgently need to describe and predict how drought affects forest carbon cycling and identify thresholds of environmental stress that trigger ecosystem collapse. Quantifying the effects of drought at an ecosystem level is complex because dynamic climate–plant relationships can cause rapid and/or prolonged shifts in carbon balance. We employ the CARbon DAta MOdel fraMework (CARDAMOM) to investigate legacy effects of drought on forest carbon pools and fluxes. Our Bayesian model-data fusion approach uses tower observed meteorological forcing and carbon fluxes to determine the response and sensitivity of aboveground and belowground ecological processes associated with the 2012–2015 California drought. Our study area is a mid-montane mixed conifer forest in the Southern Sierras. CARDAMOM constrained with gross primary productivity (GPP) estimates covering 2011–2017 show a ~75% reduction in GPP, compared to negligible GPP change when constrained with 2011 only. Precipitation across 2012–2015 was 45% (474 mm) lower than the historical average and drove a cascading depletion in soil moisture and carbon pools (foliar, labile, roots, and litter). Adding 157 mm during an especially stressful year (2014, annual rainfall = 293 mm) led to a smaller depletion of water and carbon pools, steering the ecosystem away from a state of GPP tipping-point collapse to recovery. We present novel process-driven insights that demonstrate the sensitivity of GPP collapse to ecosystem foliar carbon and soil moisture states—showing that the full extent of GPP response takes several years to arise. Thus, long-term changes in soil moisture and carbon pools can provide a mechanistic link between drought and forest mortality. Our study provides an example for how key precipitation threshold ranges can influence forest productivity, making them useful for monitoring and predicting forest mortality events.     

Obesity and diabetes, the built environment, and the ‘local’ food economy in the United States, 2007

Obesity and diabetes are increasingly attributed to environmental factors, however, little attention has been paid to the influence of the ‘local’ food economy. This paper examines the association of measures relating to the built environment and ‘local’ agriculture with U.S. county-level prevalence of obesity and diabetes. Key indicators of the ‘local’ food economy include the density of farmers’ markets and the presence of farms with direct sales. This paper employs a robust regression estimator to account for non-normality of the data and to accommodate outliers. Overall, the built environment is associated with the prevalence of obesity and diabetes and a strong local’ food economy may play an important role in prevention. Results imply considerable scope for community-level interventions.     

Insights into the area under the receiver operating characteristic curve (AUC) as a discrimination measure in species distribution modelling

Aim The area under the receiver operating characteristic (ROC) curve (AUC) is a widely used statistic for assessing the discriminatory capacity of species distribution models. Here, I used simulated data to examine the interdependence of the AUC and classical discrimination measures (sensitivity and specificity) derived for the application of a threshold. I shall further exemplify with simulated data the implications of using the AUC to evaluate potential versus realized distribution models. Innovation After applying the threshold that makes sensitivity and specificity equal, a strong relationship between the AUC and these two measures was found. This result is corroborated with real data. On the other hand, the AUC penalizes the models that estimate potential distributions (the regions where the species could survive and reproduce due to the existence of suitable environmental conditions), and favours those that estimate realized distributions (the regions where the species actually lives). Main conclusions Firstly, the independence of the AUC from the threshold selection may be irrelevant in practice. This result also emphasizes the fact that the AUC assumes nothing about the relative costs of errors of omission and commission. However, in most real situations this premise may not be optimal. Measures derived from a contingency table for different cost ratio scenarios, together with the ROC curve, may be more informative than reporting just a single AUC value. Secondly, the AUC is only truly informative when there are true instances of absence available and the objective is the estimation of the realized distribution. When the potential distribution is the goal of the research, the AUC is not an appropriate performance measure because the weight of commission errors is much lower than that of omission errors.     

The Use of Biomarker Expression to Characterize Neoplastic Processes

Biomarkers have been used by pathologists to aid the diagnosis of tumors for almost three decades. Their use has resulted in the re-evaluation and reclassification of several types of tumors. Currently, biomarkers are required to differentiate certain specific tumors with similar histologic patterns. Additional uses of biomarkers in the characterization of neoplastic processes are discussed including their use in prognosis, detecting early neoplastic processes, identifying tumor recurrence, measuring the effectiveness of various therapies (surrogate end point biomarkers), and identifying targets for novel therapies including immunotherapy and gene therapy. We propose that these newer uses of biomarkers will be just as important to pathology in the future as the uses of biomarkers in diagnosis have been over the past two decades.     

D1-Like Dopamine Receptor-Mediated Function in Congenic Mutants with D1 vs. D5 Receptor “Knockout”

Current understanding of the functional roles of individual dopamine D₁-like [D₁, D₅] and D₂-like [D_2L/S, D₃, D₄] receptor subtypes remains incomplete. In particular, the lack of pharmacological agonists and antagonists able to distinguish between D₁ and D₅ receptors means that any differential roles in the regulation of behavior are poorly understood. Mutant mice with targeted gene deletion (“knockout”) of individual dopamine receptor subtypes offer an important alternative approach to resolving these functional roles. In congenic D₁ mutants examined ethologically, progressive increases in specific topographies of behavior over wildtypes were considerably greater than those in D₁ mutants on a mixed genetic background; D₁ knockout appears to influence the neuronal substrate(s) of habituation to disrupt sculpture of the changing topography of behavior from initial exploration through to quiescence. Similarly, the D₁ receptor appears to regulate specific topographies of orofacial movement in the mouse as these are “sculpted” in a time-dependent manner. Although the well-recognized role of the D₁-like family in regulating several aspects of behavioral topography has been assumed to involve primarily D₁ receptors, this presumption may require modification to accommodate a subtle but not negligible role for their D₅ counterparts as evidenced in the phenotype of congenic D₅ mutants.