Regiospecificity in the reaction of [Fe2(η-C5H5)2(CO)4-n(CNMe)n] (n  02) with mercury(II) halides

The reactions of [Fe₂(η-C₅H₅)₂(CO)₂(L)(CNMe)] (L  CO or CNME) with HgX₂ (X  Cl, Br or I) give [Fe(η-C₅H₅)(CO)₂HgX] and [Fe(η-C₅H₅)(L)-(CNMe)X] as the sole products in ca. quantitative yields; this is consistent with the previously proposed mechanism for the reactions of electrophiles with polynuclear metal carbonyl derivatives.     

Palladium(II) Pyridinecarboxaldimine Complexes Derived from Unsaturated Amines

Pyridinecarboxaldimines (N–N′) derived from pyridin-2-ylcarboxaldehydes and unsaturated amines add to [PdCl₂(coe)]₂ (coe = cis-cyclooctene) to give complexes of the type PdCl₂(N–N′) in moderate yields. The palladium complexes have been investigated as substrates for hydroboration reactions and as antifungal agents against Aspergillus niger, A. flavus, Candida albicans, and Saccharomyces cerevisiae.     

One class classification as a practical approach for accelerating π–π co-crystal discovery

The implementation of machine learning models has brought major changes in the decision-making process for materials design. One matter of concern for the data-driven approaches is the lack of negative data from unsuccessful synthetic attempts, which might generate inherently imbalanced datasets. We propose the application of the one-class classification methodology as an effective tool for tackling these limitations on the materials design problems. This is a concept of learning based only on a well-defined class without counter examples. An extensive study on the different one-class classification algorithms is performed until the most appropriate workflow is identified for guiding the discovery of emerging materials belonging to a relatively small class, that being the weakly bound polyaromatic hydrocarbon co-crystals. The two-step approach presented in this study first trains the model using all the known molecular combinations that form this class of co-crystals extracted from the Cambridge Structural Database (1722 molecular combinations), followed by scoring possible yet unknown pairs from the ZINC15 database (21 736 possible molecular combinations). Focusing on the highest-ranking pairs predicted to have higher probability of forming co-crystals, materials discovery can be accelerated by reducing the vast molecular space and directing the synthetic efforts of chemists. Further on, using interpretability techniques a more detailed understanding of the molecular properties causing co-crystallization is sought after. The applicability of the current methodology is demonstrated with the discovery of two novel co-crystals, namely pyrene-6H-benzo[c]chromen-6-one (1) and pyrene-9,10-dicyanoanthracene (2).

Machine learning using one class classification on a database of existing co-crystals enables the identification of co-formers which are likely to form stable co-crystals, resulting in the synthesis of two co-crystals of polyaromatic hydrocarbons.     

Efficient delivery of Cre-recombinase to neurons in vivo and stable transduction of neurons using adeno-associated and lentiviral vectors

Background

As development proceeds the human embryo attains an ever more complex three dimensional (3D) structure. Analyzing the gene expression patterns that underlie these changes and interpreting their significance depends on identifying the anatomical structures to which they map and following these patterns in developing 3D structures over time. The difficulty of this task greatly increases as more gene expression patterns are added, particularly in organs with complex 3D structures such as the brain. Optical Projection Tomography (OPT) is a new technology which has been developed for rapidly generating digital 3D models of intact specimens. We have assessed the resolution of unstained neuronal structures within a Carnegie Stage (CS)17 OPT model and tested its use as a framework onto which anatomical structures can be defined and gene expression data mapped.

Results

Resolution of the OPT models was assessed by comparison of digital sections with physical sections stained, either with haematoxylin and eosin (H&E) or by immunocytochemistry for GAP43 or PAX6, to identify specific anatomical features. Despite the 3D models being of unstained tissue, peripheral nervous system structures from the trigeminal ganglion (~300 μm by ~150 μm) to the rootlets of cranial nerve XII (~20 μm in diameter) were clearly identifiable, as were structures in the developing neural tube such as the zona limitans intrathalamica (core is ~30 μm thick). Fourteen anatomical domains have been identified and visualised within the CS17 model. Two 3D gene expression domains, known to be defined by Pax6 expression in the mouse, were clearly visible when PAX6 data from 2D sections were mapped to the CS17 model. The feasibility of applying the OPT technology to all stages from CS12 to CS23, which encompasses the major period of organogenesis for the human developing central nervous system, was successfully demonstrated.

Conclusion

In the CS17 model considerable detail is visible within the developing nervous system at a minimum resolution of ~20 μm and 3D anatomical and gene expression domains can be defined and visualised successfully. The OPT models and accompanying technologies for manipulating them provide a powerful approach to visualising and analysing gene expression and morphology during early human brain development.     

Perturbing a product of stable flows

Suppose that and are axiom A flows with attractors and . Then the attractor for the product flow on the product manifold is no longer hyperbolic (although there is a hyperbolic action of ).

It is easy to see that the attractor cannot explode but we show here that it cannot implode: for any flow sufficiently close to any attractor whose basin is not too thin is -dense in .

     

Permetalloplumbanes: Preparation of [Pb{Co(CO)3(L)}4] and [Pb{Fe(CO)2(NO)(L)}4].: Complexes containing four transition metal to lead bonds (L = tertiary arsine,phosphine or phosphite).

The sole and unexpected products from the reactions of a variety of lead (II) and lead (IV) compounds with [Co₂(CO)₆(L)₂] complexes (L = tertiary arsine, phosphine, or phosphite) in refluxing benzene solution are the blue, air-stable percobaltoplumbanes [Pb{Co(CO)₃(L)}₄]. These have also been obtained from the reaction of Na[Co(CO)₃(L)] (L  PBu₃ⁿ) with lead (II) acetate which with Na[Fe(CO)₂(NO)(L)] forms the isoelectronic [Pb{Fe(CO)₂(NO)(L)}₄] [L  P(OPh)₃]. The IR spectra of the complexes in the v(CO) and v(NO) regions are consistent with tetrahedral PbCo₄ or PbFe₄ fragments, trigonal bipyramidal coordination about the cobalt or iron atoms and linear PbCoAs, PbCoP, or PbFeP systems. Unlike [Pb{Co(CO)₄}₄], our complexes do not dissociate to [Co(CO)₃(L)]^? or [Fe(CO)₂(NO)(L)]^? ions when dissolved in donor solvents.     

Investigation of aluminum interferences using the stabilized temperature platform furnace

Al was determined in the stabilized temperature platform furnace with very few interferences. No interferences were found for several metal nitrates, sulfates or phosphates, or for NaCl. The Al absorbance signal was delayed in the presence of MgCl₂ but there was no interference. This led to the use of 50 μg Mg(NO₃)₂ as a matrix modifier for Al. There were no interferences for CaCl₂ but it was particularly important to use new pyrolytically coated tubes to avoid “aging” effects. CuCl₂ provided a very persistent interference that was reduced when the Mg(NO₃)₂ matrix modifier was used that permitted a char temperature of 1700°C. Perchloric acid interferences were severe with improperly coated graphite tubes but did not exist up to 0.5 M HClO₄ when the new pyrolytically coated tubes were used. A serum Al method was tested briefly and no problems were found. Al was determined in seawater with no influence from the salinity of the sample and less than 0.6 μg/1 Al in seawater could be detected.