Cyclization-Carbonylation of 2-Alkynyl Primary Benzamides using p-Benzoquinone under Neutral Conditions.

A palladium-catalyzed cyclization-carbonylation of 2-alkynyl primary benzamides 1 afforded methyl 3-substituted 1-methoxyisoquinoline-4-carboxylates 6 in good to moderate yields. In the case of mesylate 1r, 12 was obtained directly via a cyclization-carbonylation-cyclization cascade. Compounds 6 were converted to isoquinolin-1(2H)-ones 8 in good yields under microwave irradiation. In the case of the mesylate 6q, tricyclic isoquinolinone 10 was obtained in good yield. The reactions of thiophene-2-carboxamide derivatives also proceeded well.

MonteCat: A Basin-Hopping-Inspired Catalyst Descriptor Search Algorithm for Machine Learning Models.

Proposing relevant catalyst descriptors that can relate the information on a catalyst's composition to its actual performance is an ongoing area in catalyst informatics, as it is a necessary step to improve our understanding on the target reactions. Herein, a small descriptor-engineered data set containing 3289 descriptor variables and the performance of 200 catalysts for the oxidative coupling of methane (OCM) is analyzed, and a descriptor search algorithm based on the workflow of the Basin-hopping optimization methodology is proposed to select the descriptors that better fit a predictive model. The algorithm, which can be considered wrapper in nature, consists of the successive generation of random-based modifications to the descriptor subset used in a regression model and adopting them depending on their effect on the model's score. The results are presented after being tested on linear and Support Vector Regression models with average cross-validation r2 scores of 0.8268 and 0.6875, respectively.

Platelet-activating factor contracts guinea pig esophageal muscularis mucosae by stimulating extracellular Ca2+ influx through diltiazem-insensitive Ca2+ channels.

Platelet-activating factor (PAF) is expected to increase esophageal motility. However, to the best of our knowledge, this has not been examined. Thus, we investigated the contractile effects of PAF on guinea pig (GP) esophageal muscularis mucosae (EMM) and the extracellular Ca2+ influx pathways responsible. PAF (10-9-10-6 M) contracted EMM in a concentration-dependent manner. PAF (10-6 M)-induced contractions were almost completely suppressed by apafant (a PAF receptor antagonist, 3 × 10-5 M). In EMM strips, PAF receptor and PAF-synthesizing/degrading enzyme mRNAs were detected. PAF (10-6 M)-induced contractions were abolished by extracellular Ca2+ removal but were not affected by diltiazem [a voltage-dependent Ca2+ channel (VDCC) inhibitor, 10-5 M]. PAF (10-6 M)-induced contractions in the presence of diltiazem were significantly suppressed by LOE-908 [a receptor-operated Ca2+ channel (ROCC) inhibitor, 3 × 10-5 M], SKF-96365 [an ROCC and store-operated Ca2+ channel (SOCC) inhibitor, 3 × 10-5 M], and LOE-908 plus SKF-96365. Among the tested ROCC/SOCC-related mRNAs, Trpc3, Trpc6, and Trpv4/Orai1, Orai3, and Stim2 were abundantly expressed in EMM strips. These results indicate that PAF potently induces GP EMM contractions that are dependent on extracellular Ca2+ influx through ROCCs/SOCCs, and VDCCs are unlikely to be involved.

High-throughput calculation for the screening of formamidinium halide perovskite for solar cells.

128 organic halide perovskites are systematically investigated using high-throughput first principles calculations where Ge and Sn-based materials are searched. The results revealed that all calculated materials exhibited exothermic reactions. Notably, a correlation between the heat of formation and X-site ions is identified. Six specific compounds, namely FA-Ge-I-I-I, FA-Sn-F-I-I, FA-Sn-Cl-I-I, FA-Sn-Br-Br-I, FA-Sn-Br-I-I, and FA-Sn-I-I-I, where FA stands for formamidinium, are found to have a bandgap ranging from 1.0 to 2.0 eV, characterized by a direct bandgap in their band structure. Electronic structure analysis indicated that the CBM (conduction band minimum) is influenced by the B-site p-orbital, while the VBM (valence band maximum) is influenced by the X-site p-orbitals. This study underscores the capability of high-throughput calculations to unveil hidden trends in perovskite materials, offering an effective approach for the exploration of promising perovskite materials.

Water Purification by 2-Dimensional Dodecagonal Nitride and Graphenylene via First Principles Calculations.

2 dimensional (2D) dodecagonal boron nitride (D_BN) and graphenylene are being investigated to understand their potential applications in water purification. First principle calculations are performed to evaluate the water purification properties of D_BN and graphenylene. It is found that Na+ exothermically adsorbs on pores in D_BN, where the transition state energy via pores is calculated to be 0.03 eV. This indicates that Na+ can pass through D_BN pores more selectively than water molecules and other ions. In contrast, in the case of graphenylene, Na+ is repelled, and H2 O exothermically adsorbs on pores, where the transition state energy via pores is calculated to be 1.00 eV. Therefore, this demonstrates that D_BN exhibits an excellent potential for ion-sieving membranes, while graphenylene exhibits an excellent potential for reverse osmosis membranes. Consequently, this study provides valuable insights into the potential use of D_BN and graphenylene in water purification applications.

Synthesis of Heterogeneous Catalysts in Catalyst Informatics to Bridge Experiment and High-Throughput Calculation.

The coupling of high-throughput calculations with catalyst informatics is proposed as an alternative way to design heterogeneous catalysts. High-throughput first-principles calculations for the oxidative coupling of methane (OCM) reaction are designed and performed where 1972 catalyst surface planes for the CH4 to CH3 reaction are calculated. Several catalysts for the OCM reaction are designed based on key elements that are unveiled via data visualization and network analysis. Among the designed catalysts, several active catalysts such as CoAg/TiO2, Mg/BaO, and Ti/BaO are found to result in high C2 yield. Results illustrate that designing catalysts using high-throughput calculations is achievable in principle if appropriate trends and patterns within the data generated via high-throughput calculations are identified. Thus, high-throughput calculations in combination with catalyst informatics offer a potential alternative method for catalyst design.

Unveiling the reaction pathways of hydrocarbons via experiments, computations and data science.

Reaction networks of hydrocarbons are explored using first principles calculations, data science, and experiments. Transforming hydrocarbon data into networks reveals the prevalence of the formation and reaction of various molecules. Graph theory is implemented to extract knowledge from the reaction network. In particular, centralities analysis reveals that H+, CCC, CH3+, CC, and [CH2+]C have high degrees and are thus very likely to form or react with other molecules. Additionally, H+, CH3+, C2H5+, C8H15+, C8H17+, and C6H11+ are found to have high control throughout the network and lead towards a series of additional reactions. The constructed network is also validated in experiments while the shortest path analysis is implemented for further comparison between experiment and the network. Thus, combining network analysis with first principles calculations uncovers key points in the development of various hydrocarbons that can be used to improve catalyst design and targeted synthesis of desired hydrocarbons.

Unveiling gas-phase oxidative coupling of methane via data analysis.

Unveiling the details of the mechanisms of a chemical reaction is a difficult task as reaction mechanisms are strongly coupled with reaction conditions. Here, catalysts informatics combined with high-throughput experimental data is implemented to understand the oxidative coupling of methane (OCM) reaction. In particular, pairwise correlation and data visualization are performed to reveal the relation between reaction conditions and selectivity/conversion. In addition, machine learning is used to fill the gap between experimental data points; thus, a more detailed understanding of the OCM reaction against reaction conditions can be achieved. Therefore, catalysts informatics is proposed for understanding the details of the reaction mechanism, thereby aiding reaction design.

A Futile Metabolic Cycle of Fatty Acyl-CoA Hydrolysis and Resynthesis in Corynebacterium glutamicum and Its Disruption Leading to Fatty Acid Production.

Fatty acyl-CoA thioesterase (Tes) and acyl-CoA synthetase (FadD) catalyze opposing reactions between acyl-CoAs and free fatty acids. Within the genome of Corynebacterium glutamicum, several candidate genes for each enzyme are present, although their functions remain unknown. Modified expressions of the candidate genes in the fatty acid producer WTΔfasR led to identification of one tes gene (tesA) and two fadD genes (fadD5 and fadD15), which functioned positively and negatively in fatty acid production, respectively. Genetic analysis showed that fadD5 and fadD15 are responsible for utilization of exogenous fatty acids and that tesA plays a role in supplying fatty acids for synthesis of the outer layer components mycolic acids. Enzyme assays and expression analysis revealed that tesA, fadD5, and fadD15 were co-expressed to create a cyclic route between acyl-CoAs and fatty acids. When fadD5 or fadD15 was disrupted in wild-type C. glutamicum, both disruptants excreted fatty acids during growth. Double disruptions of them resulted in a synergistic increase in production. Additional disruption of tesA revealed a canceling effect on production. These results indicate that the FadDs normally shunt the surplus of TesA-generated fatty acids back to acyl-CoAs for lipid biosynthesis and that interception of this shunt provokes cells to overproduce fatty acids. When this strategy was applied to a fatty acid high-producer, the resulting fadDs-disrupted and tesA-amplified strain exhibited a 72% yield increase relative to its parent and produced fatty acids, which consisted mainly of oleic acid, palmitic acid, and stearic acid, on the gram scale per liter from 1% glucose.IMPORTANCE The industrial amino acid producer Corynebacterium glutamicum has currently evolved into a potential workhorse for fatty acid production. In this organism, we obtained evidence showing the presence of a unique mechanism of lipid homeostasis, namely, a formation of a futile cycle of acyl-CoA hydrolysis and resynthesis mediated by acyl-CoA thioesterase (Tes) and acyl-CoA synthetase (FadD), respectively. The biological role of the coupling of Tes and FadD would be to supply free fatty acids for synthesis of the outer layer components mycolic acids and to recycle their surplusage to acyl-CoAs for membrane lipid synthesis. We further demonstrated that engineering of the cycle in a fatty acid high-producer led to dramatically improved production, which provides a useful engineering strategy for fatty acid production in this industrially important microorganism.

Rising Sun Envelope Method: An Automatic and Accurate Peak Location Technique for XANES Measurements.

The lack of theoretical understanding of X-ray absorption near-edge structure (XANES) spectroscopy necessitates the development of analysis tools for its study. Here, an algorithm for judicious choice of local minima and maxima points of the XANES spectrum (experimental or simulated) is proposed, without any loss of information neither on the peak location nor on the peak strength. The method is named the Rising Sun Envelope Method and is based on successive regularizations of the spectral measurement that, according to parameter choices that are intrinsic to the measurements, keep the peak location and strength as invariants. This is the first method that finds peaks in XANES automatically, without depending on first derivative information. Nevertheless, a direct computation of the absorption edge is provided, overcoming the low quality and poor information given by inflection point computations based on the XANES second derivative: computations of inflection points from a higher quality cubic spline approximation are used instead. To illustrate its use, the algorithm is applied to XANES, electron energy-loss spectroscopy, and Raman spectra.

An Endergonic Synthesis of Single Sondheimer-Wong Diyne by Local Probe Chemistry.

Recent advances in scanning probe microscopy on surface enable not only direct observation of molecular structures but also local probe reactions, in which unstable short-lived products have been synthesized and analyzed. Now, an endergonic reaction to synthesize a single Sondheimer-Wong diyne from 6,13-dibromopentaleno[1,2-b:4,5-b']dinaphthalene by local probe chemistry on a ultra-thin film of NaCl formed on a Cu(111) surface at 4.3 K is presented. The structures of the precursor, two intermediates, and the final product were directly identified by the differential conductance imaging with a CO functionalized tip. DFT calculations revealed that the multiple-step reaction, being endergonic overall, is facilitated by temporal charging and discharging of the molecule placed in the nanometric junction between the Cu tip and the Cu substrate underneath the ultra-thin NaCl film. This local probe reaction expands possibilities to synthesize nanocarbon materials in a bottom-up manner.

Asymmetric Cyclizative Dimerization of (ortho-Alkynyl Phenyl) (Methoxymethyl) Sulfides with Palladium(II) Bisoxazoline Catalyst.

The first example of an asymmetric cyclization-dimerization of (ortho-alkynyl phenyl) (methoxymethyl) sulfides with a palladium(II) bisoxazoline (box) catalyst has been developed. The box ligand enhances the alkynophilicity of benzothienyl palladium(II) intermediate A and thus promotes coordination of the second alkyne substrate, leading to the dimerization. The characteristic properties of the box ligand were supported by density functional theory (DFT) calculations of the intermediate. Axially chiral bibenzothiophenes were obtained in good yields with good enantioselectivities.

Total Synthesis of (-)-Graminin A Based on Asymmetric Cyclization Carbonylation of Propargyl Acetate.

The first total synthesis of (-)-graminin A is described. Key features of our synthetic approach involve a palladium-catalyzed asymmetric cyclization carbonylation of prochiral propargylic acetate, conversion of the orthoester product into methyl 4-oxo-3-furancarboxylate, and copper complex-mediated aldol condensation of (+)-gregatin B bearing a diene moiety. A new synthesis of (+)-gregatin B and the first synthesis of (-)-graminin A were achieved.

PdII catalyzed ligand controlled synthesis of bis(3-furanyl)methanones and methyl 3-furancarboxylates.

The PdII catalyzed carbonylation of allenyl ketones has been investigated. Carbonylative dimerization predominantly proceeded to afford bis(3-furanyl)methanones 2 as the major products. The use of DMSO strikingly changed the course of the reaction, affording methyl 3-furancarboxylates 3 as the major products. DFT calculations revealed that DMSO stabilized the methanol-coordinated intermediate, leading to methoxycarbonylation. Substituted furans 2 and 3 were selectively synthesized from the same allenyl ketone substrate.

Ingestion of difructose anhydride III partially suppresses the deconjugation and 7α-dehydroxylation of bile acids in rats fed with a cholic acid-supplemented diet.

Difructose anhydride III (DFAIII) is a prebiotic involved in the reduction of secondary bile acids (BAs). We investigated whether DFAIII modulates BA metabolism, including enterohepatic circulation, in the rats fed with a diet supplemented with cholic acid (CA), one of the 12α-hydroxylated BAs. After acclimation, the rats were fed with a control diet or a diet supplemented with DFAIII. After 2 weeks, each group was further divided into two groups and was fed diet with or without CA supplementation at 0.5 g/kg diet. BA levels were analyzed in aortic and portal plasma, liver, intestinal content, and feces. As a result, DFAIII ingestion reduced the fecal deoxycholic acid level via the partial suppression of deconjugation and 7α-dehydroxylation of BAs following CA supplementation. These results suggest that DFAIII suppresses production of deoxycholic acid in conditions of high concentrations of 12α-hydroxylated BAs in enterohepatic circulation, such as obesity or excess energy intake. Abbreviation: BA: bile acid; BSH: bile salt hydrolase; CA: cholic acid; DCA: deoxycholic acid; DFAIII: difructose anhydride III; MCA: muricholic acid; MS: mass spectrometry; NCDs: non-communicable diseases; LC: liquid chromatography; SCFA: short-chain fatty acid; TCA: taurocholic acid; TCDCA: taurochenodeoxycholic acid; TDCA: taurodeoxycholic acid; TUDCA: tauroursodeoxychlic acid; TαMCA: tauro-α-muricholic acid; TßMCA: tauro-ß-muricholic acid; TωMCA: tauro-ω-muricholic acid.

Rapid estimation of activation energy in heterogeneous catalytic reactions via machine learning.

Estimation of activation energies within heterogeneous catalytic reactions is performed using machine learning and catalysts dataset. In particular, descriptors for determining activation energy are revealed within the 788 activation energy dataset. With the implementation of machine learning and chosen descriptors, activation energy can be instantly predicted with over 90% accuracy during cross-validation. Thus, rapid estimation of activation energies within heterogeneous catalytic reactions can be made achievable via machine learning, leading toward the acceleration of catalysts design and characterization. © 2018 Wiley Periodicals, Inc.

Uncovering Periodicity and Hidden Trends Responsible for Predicting the Magnetic Moment of Body Centered Cubic Crystal.

Prediction of the magnetic moment of binary body centered cubic (BCC) is explored in terms of first principle calculations and data science. A dataset of 1,541 binary BCC materials constructed by first principle calculations is implemented for data mining. Descriptors for determining the magnetic moment are explored using machine learning, where classification and regression models are both implemented. Data mining reveals that two descriptors are responsible for classifying whether the materials have zero or nonzero magnetic moments and can also classify which groups of magnetic moments they belong to (µB <1, 1≤µB <2, or 2≤µB <3) where the average scores produced in cross validation indicate 80 % and 91 % accuracy, respectively. Furthermore, the direct prediction of magnetic moments is performed using a regression model where eight descriptors are revealed with an average score of 74 % accuracy. The inverse problem - from a given magnetic moment to corresponding material - is successfully addressed where the stability of the predicted materials are confirmed by further first principle calculations. Thus, descriptors for the magnetic moment in BCC materials are revealed and can be seen as the base descriptor set for the magnetic moments of further complex materials.

Redesigning the Materials and Catalysts Database Construction Process Using Ontologies.

Materials and catalyst informatics are emerging fields that are a result of shifts in terms of how materials and catalysts are discovered in the fields of materials science and catalysis. However, these fields are not reaching their full potential due to issues related to database creation and curation. Issues such as lack of uniformity, data selectivity, and the presence of bias affect the quality and usefuless of materials databases, especially when attempting to search for materials descriptors. Without uniform rules and frameworks, databases are limited in use outside of the intent of the creators of the database. Ontologies are therefore investigated as a means of redesigning the way materials and catalysts databases are designed and created. In particular, an ontology consisting of information found within the periodic table as well as commonly used related data is constructed and applied toward the search for materials descriptors. Additional ontologies are also developed for two databases-a database consisting of computational data related to perovskites and a database consisting of experimental data related to oxidative coupling of methane (OCM) catalysts-in order to investigate the impact of merging ontologies.

Unique phagocytic properties of hemocytes of Pacific oyster Crassostrea gigas against yeast and yeast cell-wall derivatives.

For a marine bivalve mollusk such as Pacific oyster Crassostrea gigas, the elimination of foreign particles via hemocyte phagocytosis plays an important role in host defense mechanisms. The hemocytes of C. gigas have a high phagocytic ability for baker's yeast (Saccharomyces cerevisiae) and its cell-wall product zymosan. C. gigas hemocytes might phagocytose yeast cells after binding to polysaccharides on the cell-wall surface, but it is unknown how and what kinds of polysaccharide molecules are recognized. We conducted experiments to determine differences in the phagocytic ability of C. gigas hemocytes against heat-killed yeast (HK yeast), zymosan and zymocel, which are similarly sized and shaped but differ in the polysaccharide composition of their particle surface. We found that both the agranulocytes and granulocytes exerted strong phagocytic ability on all tested particles. The phagocytic index (PI) of granulocytes for zymosan was 9.4 ± 1.7, which significantly differed with that for HK yeast and zymocel (P < 0.05). To evaluate the PI for the three types of particles, and especially to understand the outcome of the much higher PI for zymosan, PI was gauged in increments of 5 (1-5, 6-10, 11-15, and ≥16), and the phagocytic frequencies were compared according to these increments. The results show that a markedly high PI of ≥16 was exhibited by 18.1% of granulocytes for zymosan, significantly higher than 1.7% and 3.9% shown for HK yeast and zymocel, respectively (P < 0.05). These findings indicate that the relatively high PI for zymosan could not be attributed to a situation wherein all phagocytic hemocytes shared a high mean PI, but rather to the ability of some hemocytes to phagocytose a larger portion of zymosan. To determine whether the phagocytosis of these respective particles depended on the recognition of specific polysaccharide receptors on the hemocyte surface, C. gigas hemocytes were pretreated with soluble α-mannan or ß-laminarin and then allowed to phagocytose the three types of the particles. The percentage of phagocytic cells of ß-laminarin-treated granulocytes decreased significantly for zymosan and zymocel, but not for yeast. These results suggest that C. gigas might possess at least two types of hemocytes, and that one type of the hemocytes (granulocytes) is more active for phagocytosis. The granulocytes were found to have multiple subtypes with different phagocytic abilities and multiple phagocytic receptors. Some of the granulocyte subtypes revealed a much stronger phagocytic ability, depending on the presence of ß-glucan receptors for phagocytosis.

Descriptors for predicting the lattice constant of body centered cubic crystal.

The prediction of the lattice constant of binary body centered cubic crystals is performed in terms of first principle calculations and machine learning. In particular, 1541 binary body centered cubic crystals are calculated using density functional theory. Results from first principle calculations, corresponding information from periodic table, and mathematically tailored data are stored as a dataset. Data mining reveals seven descriptors which are key to determining the lattice constant where the contribution of descriptors is also discussed and visualized. Support vector regression (SVR) technique is implemented to train the data where the predicted lattice constants have the mean score of 83.6% accuracy via cross-validation and maximum error of 4% when compared to experimentally determined lattice constants. In addition, trained SVR is successful in predicting material combinations from a desired lattice constant. Thus, a set of descriptors for determining the lattice constant is identified and can be used as a base descriptor for lattice constants of further complex crystals. This would allow for the acceleration of the search for lattice constants of desired atomic compositions as well as the prediction of new materials based on a specified lattice constant.