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IR data of the compounds published in "Synthesis and Reactivity of Molybdenum and Tungsten Alkyne Complexes Containing 6-Methylpyridine-2-thiolate Ligands"

Here, the uploaded data are associated with the manuscript "Synthesis and Reactivity of Molybdenum and Tungsten Alkyne Complexes Containing 6-Methylpyridine-2-thiolate Ligands," published in Helvetica Chimica Acta under the following DOI: https://doi.org/10.1002/hlca.202100137 The .dpt files represent IR spectra of the compounds published in the manuscript. The labeling used consists of two parts, e.g., 1b – ME162, where 1b represents the label of the compound as presented in the manuscript, and ME162 represents the crystallographic label found in the supplementary information (SI).

opencc-by-4.0May 2018View details →

Figure 3 in Chemotaxis of Caenorhabditis elegans Toward Volatile Organic Compounds from Stropharia rugosoannulata Induced by Amino Acids

Figure 3: Chemotaxis (percent attracted) and mortality (percent of attracted worms dead) in the groups supplemented with L-phenylalanine or L-tryptophan and the control without amino acids. The error bars indicate standard deviation. The statistical differences were analyzed using one-way ANOVA, *P <0.05, **P <0.01.

opencc-by-4.0May 2018View details →

Figure 2 in Chemotaxis of Caenorhabditis elegans Toward Volatile Organic Compounds from Stropharia rugosoannulata Induced by Amino Acids

Figure 2: GC-MS total ion chromatography of different samples. A: L-phenylalanine alone, strain 1.202 alone and strain cultured on water agar plus L-phenylalanine, benzaldehyde was increased and 1-Octen-3-ol was newly produced from strain 1.2052 cultures added L-phenylalanine; B: strain 1.202 alone, L-tyrosine alone and strain cultured on water agar plus L-tyrosine, benzaldehyde was decreased and 1-Octen-3-ol and indole were newly produced were produced from strain 1.2052 cultures added L-tyrosine.

opencc-by-4.0May 2018View details →

Figure 1 in Chemotaxis of Caenorhabditis elegans Toward Volatile Organic Compounds from Stropharia rugosoannulata Induced by Amino Acids

Figure 1: Chemotaxis (percent attracted) of Caenorhabditis elegans toward Stropharia rugosoannulata stain 1.2052 cultured on water agar supplemented with amino acids. Controls are phenylalanine or tyrosine alone and strain 1.2052 alone. The error bars indicate standard deviation. The statistical differences were analyzed using one-way ANOVA, *P<0.05, **P<0.01.

Spectroscopic data for the compounds and reactions published in "Vinyl-pyrazole as a biomimetic acetaldehyde surrogate"

Here, the uploaded data are associated with the manuscript "Vinyl-pyrazole as a biomimetic acetaldehyde surrogate" published in Chem. Comm. under the following DOI: https://doi.org/10.1039/D4CC01305K The .dpt files represent IR spectra of the compounds published in the manuscript. The .scv files represent NMR spectra of the compounds published in the manuscript. HPLC-MS data is presented as .pdf files. The labeling of the compounds and reactions follows the one in the published manuscript.

Spectroscopic data for the compounds and reactions published in "Nucleophiles Target the Tungsten Center Over Acetylene in Biomimetic Models"

Here, the uploaded data are associated with the manuscript "Nucleophiles Target the Tungsten Center Over Acetylene in Biomimetic Models" published in Inorg. Chem. under the following https://doi.org/10.1021/acs.inorgchem.4c00286 The .dpt files represent IR spectra of the compounds published in the manuscript. Gas IR spectrum is reported as .scv file. The .scv files represent NMR spectra of the compounds and reactions published in the manuscript. Line Shape Analysis calculation is presented in the excel file. The labeling of the compounds and reactions follows the one in the published manuscript.

Spectroscopic data of the compounds published in "The Effect of Selenium-Based Ligands on Tungsten Acetylene Complexes"

Here, the uploaded data are associated with the manuscript "The Effect of Selenium-Based Ligands on Tungsten Acetylene Complexes" published in Inorg. Chem. under the following doi/10.1021/acs.inorgchem.4c01636 The .dpt files represent IR spectra of the compounds published in the manuscript. The .scv files represent NMR spectra of the compounds and reactions published in the manuscript. The labeling of the compounds and reactions follows the one in the published manuscript.

Figure 1 in Exploring chemical control of 2,4-D-resistant wild radish (Rophonus rophonistrum) with auxin-related compounds

Figure 1. Compounds used as potential 2,4-D synergists or substitutes,and how they fit into the schemes of auxin biology.The compounds used in the current study are shown in shaded ovals, with blue representing the auxin biosynthesis pathway, green representing auxin signaling and transport, and orange representing auxin response. Abbreviations: ACC, 1-aminocyclopropane-1-carboxylic acid; BAP, 6-benzylaminopurine; CdRP, 1-(O-carboxylphenylamino)1-deoxyribulose-5-phosphate; EGTA, ethylene glycol bis(2-aminoethyl)tetraacetic acid; IAD, indole-3-acetaldehyde; IAM, indole-3-acetamide; IAN, indole-3-acetonitrile; IAOx, indole-3-acetaldoxime; IGP, indole glycerol phosphate; IPyA, indole-3-pyruvic acid; MA, methylanthranilate; PRA, phosphoribosylanthranilate; SAM, S-adenosylmethionine.

Figure 4 in Exploring chemical control of 2,4-D-resistant wild radish (Rophonus rophonistrum) with auxin-related compounds

Figure 4. Assessment of auxinic herbicides applied preemergence to suspected and confirmed 2,4-D–resistant Rophonus rophonistrum populations. Field-collected populations with suspected resistance to 2,4-D (11 populations) and the confirmed resistant,2,4-D–selected populations (populations R1–R11) were sprayed preemergence with 560 g ha−1 2,4- D, 570 g ha−1 MCPA, or 750 g ha−1 dicamba, and the field-collected populations were also sprayed postemergence as part of the same experiment (dark blue bars). Values are means ± SE (n = 11, with each population representing one replicate), and different letters above bars denote significant (P <0.05) differences between means. For visual comparison, the averaged data for populations R1–R11 sprayed postemergence with 500 g ha−1 2,4-D or dicamba or 600 g ha−1 MCPA were also included, along with the pre- and postemergence data for the pooled susceptible (S1 and S2) populations (light blue bars). Data for the postemergence 2,4-D and dicamba treatments of populations R1–R11 were taken from Goggin et al. (2018: supplementary table S3) and from the current glasshouse study for the postemergence MCPA treatment.

Figure 3 in Exploring chemical control of 2,4-D-resistant wild radish (Rophonus rophonistrum) with auxin-related compounds

Figure 3. Response of 2,4-D–resistant Rophonus rophonistrum populations to MCPA and mecoprop. Populations at the 2-leaf stage were sprayed with MCPA, mecoprop, or a 1:1 mix of each herbicide, and their survival was assessed after 21 d. (A) Survival in the glasshouse following treatment with 1,200 g ai ha−1 MCPA or mecoprop standalone, or 600 þ 600 g ha−1 MCPA þ mecoprop.As there were no significant differences among treatments within each population, the data were pooled,and means are shown as wide gray bars behind the blue bars that represent each individual herbicide treatment.Different letters above bars denote significant (P <0.05) differences among populations in response to the pooled treatments (values are means ± SE; n = 3). (B) Dose of MCPA or mecoprop or a 1:1 mix required to kill 50% of individuals (ED50) in an outdoor dose–response experiment. Different letters above bars denote significant differences in ED50 values within and among populations.

Figure 2. Interaction between 2,4-D in Exploring chemical control of 2,4-D-resistant wild radish (Rophonus rophonistrum) with auxin-related compounds

Figure 2. Interaction between 2,4-D and other auxin-related compounds in 2,4-D–susceptible (S1) or 2,4-D–resistant (R2 or R3) Rophonus rophonistrum populations. Seedling radicle elongation on agar in the presence of 2,4-D, a potential synergist, or both, was measured, and the interaction between chemicals was assessed using a Colby analysis. Values are means ± SE of three replicates. Asterisks denote an interaction (Iij) significantly different from an additive interaction, with negative values indicating synergism and positive values indicating antagonism. Abbreviations: ABA, abscisic acid; ACC, 1-aminocyclopropane-1-carboxylic acid; Aden, adenosine; BAP, 6-benzylaminopurine; 1-But, 1- butanol; Cyclan, cyclanilide; EGTA, ethylene glycol-bis(β-aminoethyl ether)-N,N,N 0,N 0-tetraacetic acid; IAM, indole-3-acetamide; DL-Met, DL-methionine; MA, methyl anthranilate; Trypt, tryptamine.

Dataset for "Electrodeposited p-Cu2O Films – Role of Redox-Active Compounds Under Photoelectrochemical Operation Revisited"

The p-type semiconducting copper oxides CuO and Cu2O are of interest for the conversion of solar energy due to their medium wide bandgap. The position of their conduction band should allow for reductive processes in junctions with electrolytes under irradiation. In this work, on Cu2O, the efficiency of several such processes in competition with self-reduction was studied. Thin films of Cu2O were synthesised via potentiostatic electrodeposition on FTO (fluorine doped SnO2 on glass) using aqueous electrolytes. Deposition parameters (electrolyte composition, electrode potential, temperature) had a great influence on electrode properties (phase purity, preferential orientation). Electrodeposited Cu2O films were p-type. In junctions with aqueous electrolytes, under electrical bias, cathodic and photocathodic currents passed which increased dramatically when reducible redox compounds were added. The influence of various redox couples (O2, H2O2, methylviologen) and their concentration in the electrolyte on the stability of the electrodes was studied. Long time experiments showed that oxygen saturated and H2O2 containing electrolytes gave rise to constant photocurrents and no alteration of the electrodes was found by XRD. With the investigated redox couples, no product of interest was produced.

opencc-by-4.0Dec 2022View details →

Figure 5 in Phenolic compound and fatty acid properties of some microalgae species isolated from Erbil City

Figure 5. Scatterplot matrix shows the correlation between palmitic acid, stearic acid, oleic acid and linoleic acid in a- Spirogyra sp. b- Spirulina sp. c- Chara sp. d- Chlorella sp.

opencc-by-4.0Dec 2022View details →

Figure 3 in Phenolic compound and fatty acid properties of some microalgae species isolated from Erbil City

Figure 3. The distribution of DPPH and total phenol shows the same across categories of Treatment, Independent-Samples KruskalWallis Test and rejects the hypothesis on the base of Null Hypothesis with highly significant levels. A- Spirogyra sp., b-Spirulina sp. c- Chlorell sp. a d- Chara sp.

opencc-by-4.0Dec 2022View details →

Figure 1 in Phenolic compound and fatty acid properties of some microalgae species isolated from Erbil City

Figure 1. Morphology of Algal genera isolated from Erbil City (a-Spirogyra, b-Spirulina, C-Chlorella d- Chara).

opencc-by-4.0Jun 2015View details →

Fig. 2 in Morphometry of compound eyes of three Bactrocera (Diptera: Tephritidae) species

Fig. 2. SEM micrographs of the compound eye of 3 Bactrocera species showing the shapes of the ommatidia (square and hexagonal), central region (A, C, E) and dorsal region (B, D, F). Scale bar = 20 µm A, B: B. cucurbitae C, D: B. tau E, F: B. dorsalis.

opencc-by-4.0Jun 2015View details →

Fig. 1 in Morphometry of compound eyes of three Bactrocera (Diptera: Tephritidae) species

Fig. 1. Light micrographs of the compound eyes of the 3 Bactrocera species. Scale bar = 100 µm. A: Female B. cucurbitae B: Male B. cucurbitae C: Female B. tau D: Male B. tau E: Female B. dorsalis F: Male B. dorsalis.

opencc-by-4.0Jul 2024View details →

Volatile organic compounds (BVOCs and AVOCs) that were measured at the Eastern Mediterranean coast (Ramat Hanadiv, Israel)

Volatile organic compounds (BVOCs and AVOCs), which were measured at the Eastern Mediterranean coast (Ramat Hanadiv, Israel) in 2015 using a PTR-ToF-MS, and have been published. The publication is available at: <a href="https://acp.copernicus.org/articles/20/12741/2020/acp-20-12741-2020.html" target="_new" rel="noreferrer">https://acp.copernicus.org/articles/20/12741/2020/acp-20-12741-2020.html</a>

opencc-by-4.0Apr 2018View details →

Compound profiling matrices extracted from screening data

Compound profiling matrices record assay results for compound libraries tested against panels of targets. In addition to their relevance for exploring structure-activity relationships, such matrices are of considerable interest for chemoinformatic and chemogenomic applications. For example, profiling matrices provide a valuable data resource for the development and evaluation of machine learning approaches for multi-task activity prediction. However, experimental compound profiling matrices are rare in the public domain. Although they are generated in pharmaceutical settings, they are typically not disclosed. Herein, we present an algorithm for the generation of large profiling matrices, for example, containing more than 100,000 compounds exhaustively tested against 50 to 100 targets. The new methodology is a variant of bi-clustering algorithms originally introduced for large-scale analysis of genomics data. Our approach is applied here to assays from the PubChem BioAssay database and generates profiling matrices of increasing assay or compound coverage by iterative removal of entities that limit coverage. Weight settings control final matrix size by preferentially retaining assays or compounds. In addition, the methodology can also be applied to generate matrices enriched with active entries representing above-average assay hit rates.