Mixed-Model Network: Sampling point Correlations and OTU probability distribution across samples.

<p>Sampling point nodes are coloured by farming practice: Biodynamic (Green), Conventional (Red) and IPW (Aqua). Sampling point node sizes are scale by degree and OTU nodes by the probability of occurring in the adjacent sampling point. White nodes represent OTUs most likely to be isolated from a given sampling point.</p

Ecological diversity indices determined using the yeast isolates obtained from the conventional (CONV), integrated (IPW) and biodynamic (BD) vineyard.

<p>Ecological diversity indices determined using the yeast isolates obtained from the conventional (CONV), integrated (IPW) and biodynamic (BD) vineyard.</p

Principal component analysis based on fungal community structure assessed by ITS1-5.8S-ITS2 rRNA gene ARISA profiles.

<p>Biodynamic vineyard (Green), Conventional (Red), IPW (Blue).</p

The Vineyard Yeast Microbiome, a Mixed Model Microbial Map

<div><p>Vineyards harbour a wide variety of microorganisms that play a pivotal role in pre- and post-harvest grape quality and will contribute significantly to the final aromatic properties of wine. The aim of the current study was to investigate the spatial distribution of microbial communities within and between individual vineyard management units. For the first time in such a study, we applied the Theory of Sampling (TOS) to sample gapes from adjacent and well established commercial vineyards within the same terroir unit and from several sampling points within each individual vineyard. Cultivation-based and molecular data sets were generated to capture the spatial heterogeneity in microbial populations within and between vineyards and analysed with novel mixed-model networks, which combine sample correlations and microbial community distribution probabilities. The data demonstrate that farming systems have a significant impact on fungal diversity but more importantly that there is significant species heterogeneity between samples in the same vineyard. Cultivation-based methods confirmed that while the same oxidative yeast species dominated in all vineyards, the least treated vineyard displayed significantly higher species richness, including many yeasts with biocontrol potential. The cultivatable yeast population was not fully representative of the more complex populations seen with molecular methods, and only the molecular data allowed discrimination amongst farming practices with multivariate and network analysis methods. Importantly, yeast species distribution is subject to significant intra-vineyard spatial fluctuations and the frequently reported heterogeneity of tank samples of grapes harvested from single vineyards at the same stage of ripeness might therefore, at least in part, be due to the differing microbiota in different sections of the vineyard.</p> </div

Probability network of OTU found at different sampling points.

<p>Sampling point nodes are coloured by farming practice: Biodynamic (Green), Conventional (Red) and IPW (Aqua). White nodes indicate OTUs common in the three vineyards.</p

A correlation network of vineyard samples based on culturable yeast species.

<p>Nodes are coloured by farming practice: Biodynamic (Green), Conventional (Red) and IPW (Aqua).</p

The occurrence and percentage distribution of yeasts associated with grape berries in the conventional (CONV), integrated (IPW) and biodynamic (BD) vineyards.

<p>The occurrence and percentage distribution of yeasts associated with grape berries in the conventional (CONV), integrated (IPW) and biodynamic (BD) vineyards.</p

Role of Regioisomeric Bicyclo[3.3.0]octa-2,5-diene Ligands in Rh Catalysis: Synthesis, Structural Analysis, Theoretical Study, and Application in Asymmetric 1,2- and 1,4-Additions

In order to study the impact of regioisomeric diene ligands on the formation and catalytic activity of Rh complexes, a series of <i>C</i>₂- and <i>C</i>_<i>S</i>-symmetric 2,5-disubstituted bicyclo[3.3.0]­octa-2,5-dienes <i>C</i>₂-L and <i>C</i>_<i>S</i>-L, respectively, were synthesized from Weiss diketone by simultaneous deprotonation/electrophilic trapping of both oxo functions, and the catalytic behavior was studied in the presence of [RhCl­(C₂H₄)₂]₂. Complexes [RhCl­(<i>C</i>₂-L)]₂ bearing <i>C</i>₂-symmetric ligands catalyzed effectively the asymmetric arylation of <i>N</i>-tosylaldimines to (<i>S</i>)-diarylamines with yields and ee values up to 99%. In Hayashi–Miyaura reactions, however, the complexes showed poor catalytic activity. When complexes [RhCl­(C_S-L)]₂ with <i>C</i>_<i>S</i>-symmetric ligand or mixtures of [RhCl­(<i>C</i>₂-L)]₂ and [RhCl­(<i>C</i>_<i>S</i>-L)]₂ were employed in 1,2-additions, racemic addition products were observed, suggesting a CC isomerization of the diene ligands. X-ray crystal structure analysis of both Rh complexes formed from the [RhCl­(C₂H₄)₂]₂ precursor and ligands <i>C</i>₂-L and <i>C</i>_<i>S</i>-L revealed that only the <i>C</i>₂-symmetric ligand <i>C</i>₂-L coordinated to the Rh, whereas <i>C</i>_<i>S</i>-L underwent a Rh-catalyzed CC isomerization to <i>rac</i>-<i>C</i>₂-L, which then gave the racemic [RhCl­(<i>rac</i>-<i>C</i>₂-L)]₂ complex. DFT calculations of the relative stabilities of the Rh complexes and the proposed intermediates provided a mechanistic rationale via Rh-mediated hydride transfer

Factors Governing P‑Glycoprotein-Mediated Drug–Drug Interactions at the Blood–Brain Barrier Measured with Positron Emission Tomography

The adenosine triphosphate-binding cassette transporter P-glycoprotein (ABCB1/Abcb1a) restricts at the blood–brain barrier (BBB) brain distribution of many drugs. ABCB1 may be involved in drug–drug interactions (DDIs) at the BBB, which may lead to changes in brain distribution and central nervous system side effects of drugs. Positron emission tomography (PET) with the ABCB1 substrates (<i>R</i>)-[¹¹C]­verapamil and [¹¹C]-<i>N</i>-desmethyl-loperamide and the ABCB1 inhibitor tariquidar has allowed direct comparison of ABCB1-mediated DDIs at the rodent and human BBB. In this work we evaluated different factors which could influence the magnitude of the interaction between tariquidar and (<i>R</i>)-[¹¹C]­verapamil or [¹¹C]-<i>N</i>-desmethyl-loperamide at the BBB and thereby contribute to previously observed species differences between rodents and humans. We performed <i>in vitro</i> transport experiments with [³H]­verapamil and [³H]-<i>N</i>-desmethyl-loperamide in ABCB1 and Abcb1a overexpressing cell lines. Moreover we conducted <i>in vivo</i> PET experiments and biodistribution studies with (<i>R</i>)-[¹¹C]­verapamil and [¹¹C]-<i>N</i>-desmethyl-loperamide in wild-type mice without and with tariquidar pretreatment and in homozygous <i>Abcb1a/1b^(−/−)</i> and heterozygous <i>Abcb1a/1b^(+/−)</i> mice. We found no differences for <i>in vitro</i> transport of [³H]­verapamil and [³H]-<i>N</i>-desmethyl-loperamide by ABCB1 and Abcb1a and its inhibition by tariquidar. [³H]-<i>N</i>-Desmethyl-loperamide was transported with a 5 to 9 times higher transport ratio than [³H]­verapamil in ABCB1- and Abcb1a-transfected cells. <i>In vivo</i>, brain radioactivity concentrations were lower for [¹¹C]-<i>N</i>-desmethyl-loperamide than for (<i>R</i>)-[¹¹C]­verapamil. Both radiotracers showed tariquidar dose dependent increases in brain distribution with tariquidar half-maximum inhibitory concentrations (IC₅₀) of 1052 nM (95% confidence interval CI: 930–1189) for (<i>R</i>)-[¹¹C]­verapamil and 1329 nM (95% CI: 980–1801) for [¹¹C]-<i>N</i>-desmethyl-loperamide. In homozygous <i>Abcb1a/1b^(−/−)</i> mice brain radioactivity distribution was increased by 3.9- and 2.8-fold and in heterozygous <i>Abcb1a/1b^(+/−)</i> mice by 1.5- and 1.1-fold, for (<i>R</i>)-[¹¹C]­verapamil and [¹¹C]-<i>N</i>-desmethyl-loperamide, respectively, as compared with wild-type mice. For both radiotracers radiolabeled metabolites were detected in plasma and brain. When brain and plasma radioactivity concentrations were corrected for radiolabeled metabolites, brain distribution of (<i>R</i>)-[¹¹C]­verapamil and [¹¹C]-<i>N</i>-desmethyl-loperamide was increased in tariquidar (15 mg/kg) treated animals by 14.1- and 18.3-fold, respectively, as compared with vehicle group. Isoflurane anesthesia altered [¹¹C]-<i>N</i>-desmethyl-loperamide but not (<i>R</i>)-[¹¹C]­verapamil metabolism, and this had a direct effect on the magnitude of the increase in brain distribution following ABCB1 inhibition. Our data furthermore suggest that in the absence of ABCB1 function brain distribution of [¹¹C]-<i>N</i>-desmethyl-loperamide but not (<i>R</i>)-[¹¹C]­verapamil may depend on cerebral blood flow. In conclusion, we have identified a number of important factors, i.e., substrate affinity to ABCB1, brain uptake of radiolabeled metabolites, anesthesia, and cerebral blood flow, which can directly influence the magnitude of ABCB1-mediated DDIs at the BBB and should therefore be taken into consideration when interpreting PET results