A study was conducted to determine the reliability and repeatability of antibiotic resistance analysis as a method of identifying the sources of fecal pollution in surface water and groundwater. Four large sets of isolates of fecal streptococci (from 2,635 to 5,990 isolates per set) were obtained from 236 samples of human sewage and septage, cattle and poultry feces, and pristine waters. The patterns of resistance of the isolates to each of four concentrations of up to nine antibiotics were analyzed by discriminant analysis. When isolates were classified individually, the average rate of correct classification (ARCC) into four possible types (human, cattle, poultry, and wild) ranged from 64 to 78%. When the resistance patterns of all isolates from each sample were averaged and the resulting sample-level resistance patterns were classified, the ARCCs were much higher (96 to 100%). These data confirm that there are measurable and consistent differences in the antibiotic resistance patterns of fecal streptococci isolated from various sources of fecal pollution and that antibiotic resistance analysis can be used to classify and identify these sources.
We develop a mechanistic mathematical model of the G-protein coupled signaling pathway responsible for generating current responses in frog olfactory receptor neurons. The model incorporates descriptions of ligand-receptor interaction, intracellular transduction events involving the second messenger cAMP, effector ion-channel activity, and calcium-mediated feedback steps. We parameterized the model with respect to suction pipette current recordings from single cells stimulated with multiple odor concentrations. The proposed model accurately predicts the receptorcurrent response of the neuron to brief and prolonged odorant exposure and is able to produce the adaptation observed under repeated or sustained stimulation.mathematical model ͉ receptor neuron ͉ olfaction ͉ signal transduction ͉ cilia S ensory transduction of odors occurs in olfactory receptor neurons (ORNs) located in the olfactory epithelium of vertebrates and the antennal structures of invertebrates (1). The first step in transduction is the binding of an odorant molecule to a seven-transmembrane-domain receptor protein in the cilia of an ORN. This interaction triggers a G-protein-coupled cascade that activates the enzyme adenylyl cyclase, resulting in an increase in intraciliary adenosine-3Ј,5Ј-cyclic monophosphate (cAMP). When cAMP increases, it opens cyclic nucleotidegated (CNG) channels, allowing calcium and other extracellular cations into the cilia and generating an inward current. Elevated Ca 2ϩ levels in the cilia activate Ca 2ϩ -gated chloride [Cl(Ca)] channels, creating an outward flow of Cl Ϫ ions and producing amplification of the inward current (2-4) that results in membrane depolarization and the generation of action potentials in the cell soma (5). This increase in intracellular calcium initiates termination and adaptation of the cell's response by means of deactivation and feedback mechanisms, including interactions mediated by Ca 2ϩ -calmodulin (CaCaM) and Ca 2ϩ ͞calmodulin-kinase II (CaMK) (6-10). The Cl(Ca) channels remain open until enough calcium is extruded from the cilia via the Na͞Ca exchanger (NCX) (11).After stimulation, an ORNЈs response to subsequent stimuli becomes attenuated. Short-term adaptation is observed as a decrease in responsiveness to odor presentations that occur within a few seconds after a brief stimulus (7); it may be mediated in part by CaCaM inhibition of the CNG channel (12). Desensitization occurs when an odor is experienced for a sustained interval of at least several seconds: the ORNЈs response declines while the stimulus continues to be present (13,14). In this case, several aspects of the response to a subsequent stimulus are altered, including a decrease in the slope of the rising phase, as well as an increase in the speed of decay, of the stimulus-induced inward current (7, 13). Experiments (15) have demonstrated that the molecular mechanisms responsible for desensitization are likely to act upstream of cAMP production; inhibition of adenylyl cyclase activity by CaMK is a possible mechanism (13). L...
In many biological science and food processing applications, it is very important to control or modify pH. However, the complex, unknown composition of biological media and foods often limits the utility of purely theoretical approaches to modeling pH and calculating the distributions of ionizable species. This paper provides general formulas and efficient algorithms for predicting the pH, titration, ionic species concentrations, buffer capacity, and ionic strength of buffer solutions containing both defined and undefined components. A flexible, semi-mechanistic, partial buffering (SMPB) approach is presented that uses local polynomial regression to model the buffering influence of complex or undefined components in a solution, while identified components of known concentration are modeled using expressions based on extensions of the standard acid-base theory. The SMPB method is implemented in a freeware package, (pH)Tools, for use with Matlab. We validated the predictive accuracy of these methods by using strong acid titrations of cucumber slurries to predict the amount of a weak acid required to adjust pH to selected target values.
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