On sensitivity analysis: Let’s use it more!

The key factors that influence the population growth rate can be identified with sensitivity analysis. Caswell presented an algorithm based on vector calculus that speeds up, and improves the practicality of the application of the sensitivity analysis, by calculating the derivatives of the explicit elements from the population Leslie matrix. Despite the usefulness of the sensitivity analysis, it is still barely applied to empirical data, partially due to requirements of high quality demographic data and failure of compatibility between time intervals of field data collection and organism’s life stage timing. This can result in the absence of a certain vital rate as a separated element in the population projection matrix, and thus intricacy in obtaining its sensitivity. In this note we call the attention for the applied value of sensitivity analysis, and also we point to a simple formula that is easily implemented in Caswell Matlab algorithm, to calculate the sensitivity of a vital rate that is not explicit as a matrix element.     

Carbon isotope effects during precipitation of barium carbonate: implications for environmental studies

Here we demonstrate that precipitation of dissolved inorganic carbon (DIC) to at pH 10.26, 11.38 and 12.11 does not cause measurable carbon isotope fractionation. However, NaOH solution prepared under standard laboratory procedure and used to increase pH value for precipitation of BaCO₃ can be contaminated by atmospheric CO₂. In our experiment, δ¹³C value in the contaminant DIC was −24.30‰, which resulted in decrease in the δ¹³C(DIC) value by 0.03, 0.07 and 0.22 at pH 10.26, 11.38 and 12.11, respectively.     

Single-cell sequencing and mini-sequencing for preimplantation genetic diagnosis

There is increasing interest in the use of preimplantation genetic diagnosis (PGD) as an alternative to routine prenatal diagnosis. However, the costs associated with development and testing of new PGD protocols have forced some PGD centres to limit the number of diseases for which PGD is offered. One of the main factors in the design of new protocols, which affects cost and accuracy, is the choice of the mutation-detection technique. We have assessed the reliability of DNA sequencing and mini-sequencing for clinical diagnosis at the single-cell level and have found them to be rapid and accurate. Extensive optimisation for individual mutations is not usually necessary when employing these versatile techniques and consequently a smaller investment of time and resources should be required during development of new protocols. Additionally, we report single-cell protocols for the diagnoses of cystic fibrosis, sickle cell anaemia and β-thalassaemia, which utilise mini-sequencing. Unlike most mutation-detection techniques, mini-sequencing permits analysis of very small DNA fragments. Small amplicons experience low allele dropout (ADO) rates, and consequently this approach could potentially improve the reliability of PGD. Copyright © 2003 John Wiley & Sons, Ltd.     

Itaconic Acid Grafted Starch Hydrogels as Metal Remover: Capacity,Selectivity and Adsorption Kinetics

Hydrogels were synthesized by free radical graft copolymerization of itaconic acid (IA) onto corn starch (S-g-IA). For this purpose, potassium permanganate (KMnO₄)-sodium bisulfite (NaHSO₃) was used as redox initiation system. The formation of grafted starches was confirmed by Fourier transform infrared spectroscopy, wide angle X-ray scattering, thermogravimetric analysis and scanning electron microscopy. The effect of monomer concentration, neutralization, addition of crosslinking agent, N,N-bismetilenacrilamide (MBAm), and initiator concentration on grafting efficiency and adsorption capacity of the starch hydrogels was investigated. It was demonstrated that the introduction of carboxyl and carbonyl groups promoted starch hydration and swelling. Grafting degree increased with the decrease of monomer concentration, increase of initiator concentration, grade of neutralization and the addition of MBAm without neutralization. Remarkably the resulting materials exhibited water absorption capacities between 258 and 1878% and the ability to adsorb metal ions. It was experimentally confirmed the metal uptake, obtaining the higher adsorption capacity (q _e  = 35 mg/g) for the product prepared with the pre-oxidation and lower initiator concentration. The removal capacity order was Pb²⁺>Ni²⁺>Zn²⁺>Cd²⁺. Moreover, the experimental kinetic and the equilibrium adsorption data for Ni²⁺ and Pb²⁺ were best fitted to the pseudo-second order and Freundlich isotherm models, respectively. This work describes for the first time the preparation of metal removal hydrogels based on starch and itaconic acid using the pair redox system KMnO₄/NaHSO₃, which avoids the starch hydrolysis and allows itaconic acid grafting incorporation without the requirement of more reactive comonomers.     

Human-, Ovine-, and Bovine-Specific Viral Source Tracking Tools to Discriminate Between the Major Fecal Sources in Agricultural Waters

This study evaluated the sources of fecal contamination in different river catchments, using a combination of microbial source tracking tools, for human, ruminant, ovine and bovine livestock, in order to define appropriate water management strategies. Every source of waterway pollution was evaluated in river water samples from one urban river catchment and two important farming regions in New Zealand. Fecal pollution was initially measured by testing Escherichia coli and evaluating the presence of human- and ruminant-associated DNA markers of Bacteroidales (BiAdo, BacHum-UCD, BacH, and BacR) and human and ruminant fecal sterols/stanols ratios. Then specific fecal pollution sources were assessed with previously reported quantitative PCR assays targeting human-, bovine-, and ovine-specific viruses: human adenoviruses (HAdV), human JC polyomaviruses, bovine polyomaviruses (BPyV), and ovine polyomaviruses (OPyV). High level of ruminant fecal contamination was detected all over the farming areas, whereas no ruminant sources were identified in the urban river sampling sites. BacR was the most frequently observed ruminant marker and OPyV and BPyV allowed the identification of ovine and bovine fecal sources. The human fecal viral marker (HAdV) was the most frequently observed human marker, highly abundant in the urban sites, and also present in farming areas. This is the first study using simultaneously the ovine and the bovine viral markers to identify and quantify both bovine and ovine fecal pollution.     

Domestic versus foreign energy use: an analysis for four European countries

Environment, Development and Sustainability - In order to adequately assess energy policies and set clear objectives, a key preliminary step is to know the energy use patterns of the different...     

Essential and non-essential trace metals in scalp hair of men chronically exposed to volcanogenic metals in the Azores, Portugal

Volcanoes produce and release large amounts of toxicants, and the concentration of metals in hair can be used as a biomarker of exposure to trace metals. In order to investigate whether humans exposed to volcanic emissions demonstrate higher concentrations of essential and non-essential trace metals, scalp hair of men (3-89 years) living in two areas of the Azores, one exposed to volcanic emissions and the other not, was sampled, and their content in Cd, Cu, Pb, Rb, Se, and Zn was quantified by using High Resolution Inductively Coupled Plasma Mass Spectrometry. In average, men exposed to volcanic emissions presented higher concentrations of Cd (96.9 ppb), Cu (16.2 ppm), Pb (3417.6 ppb), Rb (216.3 ppb), and Zn (242.8 ppm), but not Se (469.6 ppb). Also, strong and significant correlations were found between Cd-Rb and Pb-Rb in the exposed men. In conclusion, humans living chronically exposed to volcanic emissions show high concentrations of essential and non-essential trace metals in scalp hair, and is suggested that this type of exposure may be as harmful as living close to industrial facilities.     

How to evaluate models: Observed vs. predicted or predicted vs. observed?

A common and simple approach to evaluate models is to regress predicted vs. observed values (or vice versa) and compare slope and intercept parameters against the 1:1 line. However, based on a review of the literature it seems to be no consensus on which variable (predicted or observed) should be placed in each axis. Although some researchers think that it is identical, probably because r² is the same for both regressions, the intercept and the slope of each regression differ and, in turn, may change the result of the model evaluation. We present mathematical evidence showing that the regression of predicted (in the y-axis) vs. observed data (in the x-axis) (PO) to evaluate models is incorrect and should lead to an erroneous estimate of the slope and intercept. In other words, a spurious effect is added to the regression parameters when regressing PO values and comparing them against the 1:1 line. Observed (in the y-axis) vs. predicted (in the x-axis) (OP) regressions should be used instead. We also show in an example from the literature that both approaches produce significantly different results that may change the conclusions of the model evaluation.