TOLOMEO,a Novel Machine Learning Algorithm to Measure Information and Order in Correlated Networks and Predict Their State

We present ToloMEo (TOpoLogical netwOrk Maximum Entropy Optimization), a program implemented in C and Python that exploits a maximum entropy algorithm to evaluate network topological information. ToloMEo can study any system defined on a connected network where nodes can assume N discrete values by approximating the system probability distribution with a Pottz Hamiltonian on a graph. The software computes entropy through a thermodynamic integration from the mean-field solution to the final distribution. The nature of the algorithm guarantees that the evaluated entropy is variational (i.e., it always provides an upper bound to the exact entropy). The program also performs machine learning, inferring the system’s behavior providing the probability of unknown states of the network. These features make our method very general and applicable to a broad class of problems. Here, we focus on three different cases of study: (i) an agent-based model of a minimal ecosystem defined on a square lattice, where we show how topological entropy captures a crossover between hunting behaviors; (ii) an example of image processing, where starting from discretized pictures of cell populations we extract information about the ordering and interactions between cell types and reconstruct the most likely positions of cells when data are missing; and (iii) an application to recurrent neural networks, in which we measure the information stored in different realizations of the Hopfield model, extending our method to describe dynamical out-of-equilibrium processes.     

3,6‐Bis(dimethylamino)‐10‐(10‐iododecyl)acridinium iodide

In the title compound, C₂₇H₃₉IN₃⁺·I^?, the acridinium system shows the usual approximate mirror symmetry about the central C?N line, and the corresponding bond lengths and angles in the two halves agree within experimental error. The alkyl chain at the ring N atom is initially perpendicular to the ring plane and then bends sharply at the fourth C atom. Pairs of centrosymmetrically related cations overlap two of their rings and the di­methyl­amino groups are also partly involved in the overlap. Each I^? ion is involved in short‐range interactions with two cations. These interactions give rise to a 14‐membered cyclic structure, which involves pairs of cations and anions across an inversion centre.     

Optimized switch-over between CHNS abundance and CNS isotope ratio analyses by elemental analyzer-isotope ratio mass spectrometry: Application to six geological reference materials

Rationale

Elemental abundances and isotopic ratios of carbon, nitrogen, sulfur and hydrogen have become important tools for reconstructing the evolution of Earth and life over geologic timescales, requiring accurate and precise analytical methods with high sample throughput. However, these measurements may require separate instruments for each task, such as an elemental analyzer (EA) with a thermal conductivity detector (TCD) for elemental abundances and an EA interfaced with a mass spectrometer for isotopic ratios.

Methods

To improve sample throughput and laboratory up-time, we developed a switch that allows converting an EA IsoLink™ system from a standalone mode using only a TCD to a mode for isotope ratio mass spectrometry (IRMS) within minutes. This permits accurate measurements of elemental abundances and isotopic ratios with high throughput and lower cost. We validated this method with six shale standards from the US Geological Survey (USGS) and compared our abundance data with those from another laboratory.

Results

Our results show that (a) abundance data agree well between the different laboratories and setups; (b) reproducible isotopic data can be obtained before and after the switch-over from EA standalone mode; and (c) the USGS rock standards cover a wide range in CHNS abundances and CNS isotopes, making them ideal reference materials for future geochemical studies.

Conclusions

This ideal analytical setup has the advantage that abundance measurements can be performed to determine optimal sample amounts for later isotopic analyses, ensuring higher data quality. Our setup eliminates the need for a separate EA while freeing up the mass spectrometer for other tasks during abundance measurements.

     

Sample preparation and determination of ginkgo terpene trilactones in selected beverage, snack, and dietary supplement products by liquid chromatography with evaporative light-scattering detection

Ginkgo biloba leaf extract has been widely used in dietary supplements and more recently in some foods and beverages. Sample preparation procedures for determination of ginkgo terpene trilactones (including bilobalide and ginkgolides A, B, C, and J) in various sample matrixes were developed in this study. Ginkgo leaves and capsules were extracted with 5% KH2PO4 aqueous solution under sonication. Tea bags were extracted with boiling water, whereas drink samples were taken directly from the bottles. After filtration and the addition of NaCl to approximately 30% (w/v), the terpene trilactones in aqueous solutions were quantitatively extracted with ethyl acetate-tetrahydrofuran (4 + 1, v/v). Puff samples (a cereal-based fried snack item) were first defatted by using hexane or by using supercritical fluid extraction and then extracting under sonication with methanol-acetic acid (99 + 1, v/v). After evaporation of the organic phase, the terpene trilactones were redissolved in methanol and determined on a C18 reversed-phase column by liquid chromatography (LC) with evaporative light-scattering detection. The method of standard additions and gas chromatography with flame ionization detection were used for method validation. For most samples, the relative standard deviation was <10%. The identities of target compounds in ginkgo leaves and drink samples were confirmed by LC/electrospray ionization-tandem mass spectrometry.     

Stability and cations coordination of DNA and RNA 14-mer G-quadruplexes: a multiscale computational approach

Molecular dynamics simulations have been used to study the differences between two DNA and RNA 14-mer quadruplexes of analogous sequences. Their structures present a completely different fold: DNA forms a bimolecular quadruplex containing antiparallel strands and diagonal loops; RNA forms an intrastrand parallel quadruplex containing a G-tetrad and an hexad, which dimerizes by hexad stacking. We used a multiscale computational approach combining classical Molecular dynamics simulations and density functional theory calculations to elucidate the difference in stability of the 2-folds and their ability in coordinating cations. The presence of 2'-OH groups in the RNA promotes the formation of a large number of intramolecular hydrogen bonds that account for the difference in fold and stability of the two 14-mers. We observe that the adenines in the RNA quadruplex play a key role in conserving the geometry of the hexad. We predict the cation coordination mode of the two quadruplexes, not yet observed experimentally, and we offer a rationale for the corresponding binding energies involved.     

Influence of nitrogen speciation on the TDN measurement in fresh waters by high temperature catalytic oxidation and persulfate digestion

Analytical methodologies for the determination of total dissolved nitrogen (TDN) in waters are based on a conversion step able to transform selectively all the nitrogen species into a compound that is then quantified. A crucial requirement to meet accuracy is the quantitative recovery of all organic and inorganic nitrogen species during the conversion step. In this work, the N recoveries of two widely employed methodologies that use different conversion steps (high temperature catalytic oxidation (HTCO) and persulfate digestion (PD)) were assessed on a set of organic nitrogen compounds, representative of the structures of both dissolved organic matter (DOM) and anthropogenic contaminants. Low recoveries are due to poor selectivity during the conversion step, with the formation of nitrogen compounds other than nitrogen oxide (HTCO) and nitrate (PD). The results show that in many instances the TDN measurements give systematically low results depending on N speciation. PD could give lower results than HTCO even for samples containing only DOM of biological origin. In particular (i) low N recovery was always observed with compounds having two or more contiguous N atoms; (ii) the HTCO method is very effective for TDN quantification in the presence of s-triazine rings while PD method did not yield satisfactory N recovery; (iii) a full N recovery was observed with compounds having amido or amino groups or nitrogen atoms in imidazole, indole and pyrimidine rings; and (iv) the N recoveries for purine derivatives are almost complete with HTCO, but give systematically low results by PD.

Finally, the estimation of dissolved organic nitrogen (DON) fluxes and pools from TDN measurements can be affected by uncertainties larger than previously thought as a consequence of (i) the lower N recovery for some nitrogen compounds and (ii) the differences in the N recovery as a function of the adopted analytical methods.