The mechanisms that control extracellular serotonin levels in vivo are not well-defined. This shortcoming makes it very challenging to diagnose and treat the many psychiatric disorders in which serotonin is implicated. Fast-scan cyclic voltammetry (FSCV) can measure rapid serotonin release and reuptake events but cannot report critically important ambient serotonin levels. In this Article, we use fast-scan controlled adsorption voltammetry (FSCAV), to measure serotonin’s steady-state, extracellular chemistry. We characterize the “Jackson” voltammetric waveform for FSCAV and show highly stable, selective, and sensitive ambient serotonin measurements in vitro. In vivo, we report basal serotonin levels in the CA2 region of the hippocampus as 64.9 ± 2.3 nM (n = 15 mice, weighted average ± standard error). We electrochemically and pharmacologically verify the selectivity of the serotonin signal. Finally, we develop a statistical model that incorporates the uncertainty in in vivo measurements, in addition to electrode variability, to more critically analyze the time course of pharmacological data. Our novel method is a uniquely powerful analysis tool that can provide deeper insights into the mechanisms that control serotonin’s extracellular levels.

A multivariate kinetic model of aqueous fipronil photodegradation was developed as a function of dissolved organic matter (DOM), bicarbonate, and nitrate at concentrations that bracketthose commonly observed in natural waters (ca. 0-10 mg/L). Several pathways were available for fipronil photodegradation in this system, including direct photolysis and indirect photooxidation by species produced during the illumination of natural waters (e.g., 3NOM*, 1O2*, *OH, *CO3(1-), *OOR, *OOH, e(aq)-, O2(*-)). Product studies indicated thatfipronil was quantitatively converted to fipronil desulfinyl, a product that is associated with direct photolysis alone. DOM was the only variable that affected fipronil degradation; it decreased the rate of fipronil photodegradation primarily through competitive light absorption (i.e., attenuation) and the quenching of fipronil*. The addition of sodium chloride (30 percent per thousand) resulted in a more rapid rate (approximately 20%) of fipronil loss in comparison to equivalent experiments performed without sodium chloride, implying that fipronil may be more photolabile in marine environments.

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The unreliability of multivariate outlier detection techniques such as Mahalanobis distance and hat matrix leverage has been known in the statistical community for well over a decade. However, only within the past few years has a serious effort been made to introduce robust methods for the detection of multivariate outliers into the chemical literature. Techniques such as the minimum volume ellipsoid (MVE), multivariate trimming (MVT), and M-estimators (e.g., PROP), and others similar to them, such as the minimum covariance determinant (MCD), rely upon algorithms that are difficult to program and may require significant processing times. While MCD and MVE have been shown to be statistically sound, we found MVT unreliable due to the method's use of the Mahalanobis distance measure in its initial step. We examined the performance of MCD and MVT on selected data sets and in simulations and compared the results with two methods of our own devising. Both the proposed resampling by the half-means method and the smallest half-volume method are simple to use, are conceptually clear, and provide results superior to MVT and the current best-performing technique, MCD. Either proposed method is recommended for the detection of multiple outliers in multivariate data.

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