The furan microsolvation blind challenge for quantum chemical methods: First steps

© 2018 Author(s). Herein we present the results of a blind challenge to quantum chemical methods in the calculation of dimerization preferences in the low temperature gas phase. The target of study was the first step of the microsolvation of furan, 2-methylfuran and 2,5-dimethylfuran with methanol. The dimers were investigated through IR spectroscopy of a supersonic jet expansion. From the measured bands, it was possible to identify a persistent hydrogen bonding OH-O motif in the predominant species. From the presence of another band, which can be attributed to an OH-π interaction, we were able to assert that the energy gap between the two types of dimers should be less than or close to 1 kJ/mol across the series. These values served as a first evaluation ruler for the 12 entries featured in the challenge. A tentative stricter evaluation of the challenge results is also carried out, combining theoretical and experimental results in order to define a smaller error bar. The process was carried out in a double-blind fashion, with both theory and experimental groups unaware of the results on the other side, with the exception of the 2,5-dimethylfuran system which was featured in an earlier publication

Season of Sampling and Season of Birth Influence Serotonin Metabolite Levels in Human Cerebrospinal Fluid

BACKGROUND: Animal studies have revealed seasonal patterns in cerebrospinal fluid (CSF) monoamine (MA) turnover. In humans, no study had systematically assessed seasonal patterns in CSF MA turnover in a large set of healthy adults. METHODOLOGY/PRINCIPAL FINDINGS: Standardized amounts of CSF were prospectively collected from 223 healthy individuals undergoing spinal anesthesia for minor surgical procedures. The metabolites of serotonin (5-hydroxyindoleacetic acid, 5-HIAA), dopamine (homovanillic acid, HVA) and norepinephrine (3-methoxy-4-hydroxyphenylglycol, MPHG) were measured using high performance liquid chromatography (HPLC). Concentration measurements by sampling and birth dates were modeled using a non-linear quantile cosine function and locally weighted scatterplot smoothing (LOESS, span = 0.75). The cosine model showed a unimodal season of sampling 5-HIAA zenith in April and a nadir in October (p-value of the amplitude of the cosine = 0.00050), with predicted maximum (PC(max)) and minimum (PC(min)) concentrations of 173 and 108 nmol/L, respectively, implying a 60% increase from trough to peak. Season of birth showed a unimodal 5-HIAA zenith in May and a nadir in November (p = 0.00339; PC(max) = 172 and PC(min) = 126). The non-parametric LOESS showed a similar pattern to the cosine in both season of sampling and season of birth models, validating the cosine model. A final model including both sampling and birth months demonstrated that both sampling and birth seasons were independent predictors of 5-HIAA concentrations. CONCLUSION: In subjects without mental illness, 5-HT turnover shows circannual variation by season of sampling as well as season of birth, with peaks in spring and troughs in fall

Median concentrations of monoamine metabolites (in nmol/L) in cerebrospinal fluid with standard deviations (S.D.), per season (italics indicate totals).

<p>Median concentrations of monoamine metabolites (in nmol/L) in cerebrospinal fluid with standard deviations (S.D.), per season (italics indicate totals).</p

Median CSF 5-HAA Concentrations (in nmol/L) are plotted against Month of Birth.

<p>Bold line represents cosine, thin line represents LOESS and dashed lines represent 95% CIs of the cosine. Whiskers indicate 95% CIs of 5-HIAA concentrations.</p

Median CSF 5-HAA Concentrations (in nmol/L) are plotted against Month of CSF Sampling.

<p>Bold line represents cosine, thin line represents LOESS and dashed lines represent 95% CIs of the cosine. Whiskers indicate 95% CIs of 5-HIAA concentrations.</p

Amplitude of the best fitting models per metabolite with significance levels (in bold: Bonferroni-corrected significant results).

<p>T-statistic of the amplitudes, tmax (month during which levels peak), tmin (month during which levels are at their lowest), and best-fitting model based on deviance calculations. Feb = February; Nov = November; Sept = September; Dec = December.</p