Nuclear Magnetic Resonance Spectroscopy Data Research Articles

Exceptional Photochemical Interface: Creation of a p-n Junction and Enhanced Photoreduction Ability.

The interface of substances at the photoexcited state is completely different from that at the ground state, which gives a chance to create some unprecedented physical and chemical properties. These interface-dominated properties can significantly improve carrier transport kinetics. Herein, we report a special photochemical strategy for constructing a heterogeneous interface. We synthesized a series of catalysts involving SnS2 and Zn2AgInS4 (ZAIS), providing an example of constructing a photochemical interface between n-type and p-type two-dimensional substances. Zeta potential confirmed that the photoinduced surface charge of ZAIS changed from negative to positive. This change in charge sign created the possibility of combining ZAIS with SnS2 carrying negative charges. First-principles calculations certified that the photochemical interface is thermodynamically feasible. Nuclear magnetic resonance (NMR) and X-ray photoelectron spectroscopy (XPS) data confirmed that the interface in the heterogeneous catalysts of ZAIS/SnS2 was formed during the photo-illumination process. Owing to the promoted fast separation of photogenerated carriers, the catalyst possessing a p-n junction photochemical interface exhibits optimal Cr(VI) photoreduction and photocatalytic H2 evolution performance as well as good stability. Photochemistry provides a universal methodology for constructing exceptional interfaces and guiding the synthesis of interfacial functional materials.

Fertilization effects on soil organic matter chemistry

Despite the close interactions between carbon (C) and nutrients like nitrogen (N), phosphorus (P), and potassium (K), the consequences of N fertilization alone or in combination with P and K on soil organic matter (SOM) chemical composition remain unclear. Using solid-state 13C nuclear magnetic resonance spectroscopy data from 45 field studies, we meta-analyzed the effects of N alone and NPK fertilization on SOM content and chemical composition. Generally, mineral fertilization affects the SOM content and composition via three indirect processes: i) increasing litter input and rhizodeposition, ii) accelerating microbial decomposition of SOM, and iii) modifying the preservation of SOM by soil minerals. NPK fertilization (+12 %) increased organic C content more than N fertilization alone (+8.6 %). Alkyl and O-alkyl C increased at low-N rates (<50 kg N ha−1 yr−1) or after short-term (0–5 yrs) N fertilization alone, likely because improved N availability promoted bacterial residues rich in long-chain aliphatic C formation and carbohydrate-rich matter inputs. High-rate (>200 kg N ha−1 yr−1) or long-term (>25 yrs) NPK fertilization increased alkyl C but decreased aromatic C, likely due to reduced nutrient limitations and acidification. These factors promote aliphatic C-rich microbial biomass, accelerate the decomposition of stable compounds, and decrease the mineral protection of aromatic acids. The SOM chemical composition (excluding aromatic C) response to NPK fertilization decreased with increasing initial level. In contrast, the response of SOM raised with increasing initial content under N fertilization alone. The increase in organic C content was strongly linked to changes in SOM chemistry under NPK fertilization but not under N fertilization alone. In conclusion, NPK fertilization modified SOM chemistry and increased organic C accumulation more effectively than N fertilization alone, which was mediated by increasing plant growth, raising microbial biomass and activity, altering mineral protection, and initial soil C levels. Our findings provide critical insights for optimizing fertilization strategies to improve soil C sequestration capacity and fertility.

Oleanolic acid purified from the stem bark of Olax subscorpioidea Oliv. inhibits the function and catalysis of human 17β-hydroxysteroid dehydrogenase 1

Cancer is a leading cause of global death. Medicinal plants have gained increasing attention in cancer drug discovery. In this study, the stem bark extract of Olax subscorpioidea, which is used in ethnomedicine to treat cancer, was subjected to phytochemical investigation leading to the isolation of oleanolic acid (OA). The structure was elucidated by 1-dimensional and 2-dimensional nuclear magnetic resonance spectroscopic (NMR) data, and by comparing its data with previously reported data. Molecular docking was used to investigate the interactions of OA with nine selected cancer-related protein targets. OA docked well with human 17β-hydroxysteroid dehydrogenase type-1 (17βHSD1), caspase-3, and epidermal growth factor receptor tyrosine kinase (binding affinities: −9.8, −9.3, and −9.1 kcal/mol, respectively). OA is a triterpenoid compound with structural similarity to steroids. This similarity with the substrates of 17βHSD1 gives the inhibitor candidate an excellent opportunity to bind to 17βHSD1. The structural and functional dynamics of OA-17βHSD1 were investigated by molecular dynamics simulations at 240 ns. Molecular mechanics/Poisson-Boltzmann surface area (MMPBSA) studies showed that OA had a binding free energy that is comparable with that of vincristine (–52.76, and −63.56 kcal/mol, respectively). The average C-α root mean square of deviation (RMSD) value of OA (1.69 Å) compared with the unbound protein (2.01 Å) indicated its high stability at the protein’s active site. The binding energy and stability at the active site of 17βHSD1 recorded in this study indicate that OA exhibited profound inhibitory potential. OA could be a good scaffold for developing new anti-breast cancer drugs.

In vitro spectroscopic analysis of the chemical interaction between calcium hypochlorite and chlorhexidine.

This study aimed to identify the chemical composition resulting from the chemical interaction between calcium hypochlorite [Ca(OCl)2] and chlorhexidine (CHX) using different 1H and 13C nuclear magnetic resonance spectrometry (NMR), correlated two-dimensional spectroscopy (2D COSY), heteronuclear single quantum coherence (HSQC), and Fourier Transform Infrared Spectroscopy (FTIR) experiments. The 5.25% Ca(OCl)2 was mixed with 2% CHX in a 1:1 ratio, obtaining an orange-brown precipitate that was filtered, washed in ultrapure water, dried and characterized by 1H and 13C NMR, 2D COSY, HSQC and FTIR. One-dimensional and two-dimensional NMR spectra demonstrated the chemical changes around the protons and carbon atoms of the initial CHX and after reacted with Ca(OCl)2. These techniques and FTIR show that the interaction generated two by-products from the degradation of CHX, none of which were parachloroaniline (PCA) despite both products obtained being substituted benzene compounds. Using NMR and FTIR data together with a previously proposed catalytic cleavage degradation mechanism for CHX, the products appear to be parachlorophenylurea (PCU) and parachlorophenylguanidyl-1,6-diguanidyl-hexane (PCGH). Therefore, this in vitro study demonstrated that the precipitate formed from the chemical interaction between Ca(OCl)₂ and CHX results in two by-products, PCU and PCGH, neither of which is PCA. Due to the absence of cytotoxicity studies on the products generated from the combination of Ca(OCl)₂ and CHX, an intermediate rinse with an inert solution is recommended to remove these compounds from the root canals.

The Insecticidal Activity of Secondary Metabolites Produced by Streptomyces sp. SA61 against Trialeurodes vaporariorum (Hemiptera: Aleyrodidae).

Trialeurodes vaporariorum Westwood poses a significant threat to vegetable and ornamental crops in temperate zones, resulting in notable reductions in yield and substantial economic burdens. In order to find compounds with high insecticidal activity against T. vaporariorum, five compounds were isolated and identified from the crude extract of Streptomyces sp. SA61. These include three new polyketides, named strekingmycins F-H (1-3); one new diterpenoid, named phenalinolactone CD8 (4); and one known compound, strekingmycin A (5). Their structures were analyzed using high-resolution electrospray ionization mass spectrometry and one-dimensional and two-dimensional nuclear magnetic resonance spectroscopy data and by comparing them with previously reported data. The insecticidal activities of compounds 1-5 against T. vaporariorum were evaluated. Among them, compound 5 exhibited the highest insecticidal activity, with an LC50 of 6.949 mg/L against T. vaporariorum at 72 h using the leaf-dip method. Lower insecticidal activities were found in compounds 1-4, with LC50 values of 22.817, 19.150, 16.981 and 41.501 mg/L, respectively. These data indicate that strekingmycin could be a potential candidate for a novel insecticide to control T. vaporariorum.

Surface chemistry and catalytic activity in H2O2 decomposition of pyrolytically fluoralkylated activated carbons.

According to the proposed pyrolytic method, granular activated carbon (AC) Norit 830 W was functionalized by thermal treatment of AC in hydrofluorocarbon (HFC) gases, pentafluoroethane and 1,1,1,2-tetrafluoroethane, at 400-800 °C. This method does not require activation by plasma and photons. Chemical and elemental analysis showed that the pyrolytic treatment provides a loading of 2.95 mmol (5.6 wt%) of fluorine per gram of AC. Nitrogen adsorption measurements indicated that the microporous structure contracted when AC was treated with HFC at temperatures above 400 °C. Thermogravimetry, Fourier transform infrared spectroscopy (FTIR) with attenuated total reflectance (ATR), and X-ray photoelectron spectroscopy (XPS) demonstrated the evolution of oxygen-containing and fluorine-containing groups to more thermostable groups with treatment temperature. The fluorine-containing groups grafted at high temperature, above 600 °C exhibited the highest thermal stability up to 1250 °C in dry argon. From the data of XPS and solid-state 19F nuclear magnetic resonance spectroscopy data, the grafted fluorine exists in several types of grafted F-containing groups, the HFC residues. By changing the thermal regime of fluorination, the composition of fluorine-containing groups on a carbon surface can be regulated. Isolated fluoroalkyl groups can be grafted at temperatures of 400-500 °C, while at 600 °C and above, the semi-ionic fluorine groups increase significantly. The hydrophobized surface demonstrated the ability to effectively decompose H2O2 in methanol solutions.

Three new diterpenoids, plectalibertellenones A–C, isolated from endolichenic fungi Pseudoplectania sp. EL000327

Three new pimarane diterpenoids, plectalibertellenones A−C (1–3), along with six known compounds, 9α-hydroxy-1,8(14),15-isopimaratrien-3,7,11-trione (4), 9α-hydroxy-1,8(14),15-isopimaratrien-3,11-dione (5), phomenone B (6), (−)-pestalotin (7), (+)-pestalotin (8), and 6-pentyl-4-methoxy-pyran-2-one (9) were isolated from the crude extract of an endolichenic fungus, Pseudoplectania sp. EL000327. The planar structures of metabolites 1–3 were elucidated using UV, mass spectrometry (MS), and nuclear magnetic resonance (NMR) spectroscopic data. The relative and absolute configurations of 1–3 were deduced from an interpretation of circular dichroism (CD) spectroscopic data, application of an advanced Mosher’s method, DP4+ calculations, and combination of NMR spectroscopic methods. Compounds 1–9 did not display any significant anti-bacterial activity; however, compounds 1–4 were cytotoxic to Caco2 cells, with IC50 values 54.8, 80.7, 76.4, and 19.6 µM, respectively.

Measuring the water content of polymer electrolyte membranes using double points of proton magic angle spinning nuclear magnetic resonance data

Although the water content in polymer electrolyte membranes (PEMs) is a very important parameter for controlling their performance, measuring it is difficult because strong acidic groups such as sulfonic acid in PEMs make them very hygroscopic. In this study, we demonstrate that the proton magic-angle-spinning nuclear magnetic resonance spectroscopic data of a Nafion PEM accompanied by weight data measured for two different water contents can be used to determine the water content of dry as well as swollen PEM. The advantages of this method are that completely dry-PEM weight can be obtained without perfectly removing water from the PEM and no specific drying condition is required. Further, the advantages and disadvantages of the proposed method and calibration curve methods are discussed. The proposed method can be applied to various PEMs provided accurate equivalent-weight values for the PEMs are available.

Self-organizing maps for exploration and classification of nuclear magnetic resonance spectra for untargeted metabolomics of breast cancer

Metabolomics has emerged as a powerful tool for identifying biomarkers of disease, and nuclear magnetic resonance (NMR) spectroscopy allows for the simultaneous detection of a wide range of metabolites. However, due to complex interactions within metabolic networks, metabolites often exhibit high correlation and collinearity. To address this challenge, self-organizing maps (SOMs) of Kohonen maps and counter propagation-artificial neural networks (CP-ANN) were employed in this study to model proton nuclear magnetic resonance spectroscopic (1HNMR) data from control samples and breast cancer (BC) patients. Blood serum samples from a control group (n=24) and BC patients (n=18) were used to extract metabolites using methanol and chloroform solvents in optimum extraction conditions. The 1HNMR data was preprocessed by performing phase, baseline, and shift corrections. Subsequently, the preprocessed data was modeled using Kohonen network as an unsupervised technique and CP-ANN as a supervised technique. In this regard, the model built with CP-ANN successfully distinguished between the two classes with an accuracy of 100 % for both group and sensitivity of 96 % and 100 % for control group and BC patients, respectively. Additionally, CP-ANN algorithm demonstrated predictive capabilities by accurately classifying test samples with 90 % sensitivity, 98 % specificity, and 96 % accuracy for control group and 100 % sensitivity, 90 % specificity, and 96 % accuracy for BC patients. Furthermore, analysis of the resulting topological map revealed 14 significant variables (biomarkers) such as sarcosine, lysine, trehalose, tryptophan, and betaine that effectively differentiated between healthy individuals and BC patients.

Machine learning-enabled fatty acid quantification and classification of pork from autochthonous breeds using low-field 1H NMR spectroscopic data

Traditional pig breeds, known for their sustainability and superior meat quality, are experiencing growing consumer preference. The lipid fraction composition of these meats plays a fundamental role in their health benefits and excellent organoleptic properties. Accordingly, accurate characterisation of intramuscular fat is crucial for maintaining quality standards and combating fraudulent practices. This study employs benchtop nuclear magnetic resonance (NMR) spectroscopy to delineate the lipidic profiles of various cuts from two emblematic Spanish autochthonous pig breeds. The implementation of chemometric and machine learning models enabled the classification of pork samples based on cut and breed of origin. Moreover, this investigation pioneers the coupling of benchtop NMR with machine learning models for quantitative purposes, achieving precise quantification of polyunsaturated, monounsaturated and saturated fatty acids in intramuscular fat. This novel approach holds promise for enhancing the traceability and authentication of traditional pig products, fostering consumer confidence and promoting sustainable livestock practices.

Interfacial Decomposition Behaviour of Triethyl Phosphate‐Based Electrolytes for Lithium‐Ion Batteries

Triethyl phosphate (TEP) is a cheap, environmentally benign, and non‐flammable electrolyte solvent, whose implementation in lithium‐ion batteries is held back by its co‐intercalation into graphite anodes, resulting in exfoliation of the graphite structure. In this work, the electrode‐electrolyte interface behaviour of electrolytes containing up to 100% TEP was investigated and correlated to electrochemical performance. High capacity and stable cycling are maintained with up to 30% TEP in carbonate ester‐based electrolytes, but above this threshold the reversibility of Li+ intercalation into graphite drops sharply to almost zero. This represents a potential route to improved battery safety, while TEP can also improve safety indirectly by enabling the use of lithium bis(oxalato borate), a fluorine‐free salt with limited solubility in traditional electrolytes. To understand the poor performance at TEP concentrations of &gt;30%, its solvation behaviour and interfacial reaction chemistry were studied. Nuclear magnetic resonance spectroscopy data confirms changes in the Li+ solvation shell above 30% TEP, while operando gas analysis indicates extensive gas evolution from TEP decomposition at the electrode above the threshold concentration, which is almost entirely absent below it. X‐ray photoelectron spectroscopy depth profiling of electrodes demonstrates poor passivation by the solid electrolyte interphase above 30% TEP and significant graphite exfoliation.

Sunflower Origin Identification Based on Multi-Source Information Fusion Technique of Kernel Extreme Learning Machine

This study constructs a model for the rapid identification of the origins of edible sunflower (Helianthus) using Kernel Extreme Learning Machine (KELM) with multi-source information fusion technology. Near-infrared spectroscopy (NIRS) and nuclear magnetic resonance spectroscopy (NMRS) were utilized to analyze 180 sunflower samples from the Xinjiang, Heilongjiang, and Inner Mongolia regions. Initially, the identification models for the origin of sunflowers using NIR and NMR data were compared between two algorithms: the Extreme Learning Machine (ELM) and KELM, combined with various spectral preprocessing methods. The experiment found that the NIR spectral model preprocessed with standard normal variate (SNV) using the KELM algorithm was the most accurate, achieving accuracies of 98.7% in the training set and 97.2% in the test set. The spin-echo NMR spectral model preprocessed with non-local means (NLMs) using the KELM algorithm was the second best, with accuracies of 98.4% in the training set and 96.4% in the test set. To further improve the accuracy of the identification models, innovative sunflower origin identification models were developed based on data layer fusion and feature layer fusion using NIRS and NMRS. In the data layer fusion model, the KELM algorithm model was optimal, achieving a test set accuracy and F1 score of 98.2% and 98.18%, respectively, an improvement of 1.0% over the best single data source model. In the feature layer fusion model, four types of feature-layer information-fusion identification models were established using two feature extraction algorithms, Competitive Adaptive Reweighted Sampling (CARS) and Variable Importance Projection (VIP), combined with joint feature and simple merging feature strategies. The CARS-KELM algorithm combined with the joint feature method was found to be the best, achieving 100% accuracy in both the training and test sets, an improvement of 2.8% over the best single data source model. Identifying the origin of edible sunflower using NIRS and NMRS is demonstrated as feasible by the results. The best single-spectrum sunflower origin identification model was achieved using the KELM algorithm with SNV preprocessing. The feature layer fusion method combining NIRS and NMRS data is suitable for handling the task of sunflower origin identification. This method significantly improves the recognition accuracy of the model compared to a single model, achieving fast and accurate origin identification of edible sunflowers. The research results provide a new method for rapid identification of sunflower origin.

Parallel β-Sheet Structure and Structural Heterogeneity Detected within Q11 Self-Assembling Peptide Nanofibers.

Q11 peptide nanofibers are used as a biomaterial for applications such as antigen presentation and tissue engineering, yet detailed knowledge of molecular-level structure has not been reported. The Q11 peptide sequence was designed using heuristics-based patterning of hydrophobic and polar amino acids with oppositely charged amino acids placed at opposite ends of the sequence to promote antiparallel β-sheet formation. In this work, we employed solid-state nuclear magnetic resonance spectroscopy (NMR) to evaluate whether the molecular organization within Q11 self-assembled peptide nanofibers is consistent with the expectations of the peptide designers. We discovered that Q11 forms a distribution of molecular structures. NMR data from two-dimensional (2D) 13C-13C dipolar-assisted rotational resonance indicate that the K3 and E9 residues between Q11 β-strands are spatially proximate (within ∼0.6 nm). Frequency-selective rotational echo double resonance (fsREDOR) on K3 Nζ and E9 Cδ-labeled sites showed that approximately 9% of the sites are close enough for salt bridge formation to occur. Surprisingly, dipolar recoupling measurements revealed that Q11 peptides do not assemble into antiparallel β-sheets as expected, and structural analysis using Fourier-transform infrared spectroscopy and 2D NMR alone can be misleading. 13C PITHIRDS-CT dipolar recoupling measurements showed that the most abundant structure consists of parallel β-sheets, in contrast to the expected antiparallel β-sheet structure. Structural heterogeneity was detected from 15N{13C} REDOR measurements, with approximately 22% of β-strands having antiparallel nearest neighbors. We cannot propose a complete structural model of Q11 nanofibers because of the complexity involved when examining structurally heterogeneous samples using NMR. Altogether, our results show that while heuristics-based patterning is effective in promoting β-sheet formation, designing a peptide sequence to form a targeted β-strand arrangement remains challenging.

Kinetic pathway of HIV-1 TAR cotranscriptional folding.

The Trans-Activator Receptor (TAR) RNA, located at the 5'-end untranslated region (5' UTR) of the human immunodeficiency virus type 1 (HIV-1), is pivotal in the virus's life cycle. As the initial functional domain, it folds during the transcription of viral mRNA. Although TAR's role in recruiting the Tat protein for trans-activation is established, the detailed kinetic mechanisms at play during early transcription, especially at points of temporary transcriptional pausing, remain elusive. Moreover, the precise physical processes of transcriptional pause and subsequent escape are not fully elucidated. This study focuses on the folding kinetics of TAR and the biological implications by integrating computer simulations of RNA folding during transcription with nuclear magnetic resonance (NMR) spectroscopy data. The findings reveal insights into the folding mechanism of a non-native intermediate that triggers transcriptional pause, along with different folding pathways leading to transcriptional pause and readthrough. The profiling of the cotranscriptional folding pathway and identification of kinetic structural intermediates reveal a novel mechanism for viral transcriptional regulation, which could pave the way for new antiviral drug designs targeting kinetic cotranscriptional folding pathways in viral RNAs.

Plant-Derived Caffeic Acid and Its Derivatives: An Overview of Their NMR Data and Biosynthetic Pathways.

In recent years, caffeic acid and its derivatives have received increasing attention due to their obvious physiological activities and wide distribution in nature. In this paper, to clarify the status of research on plant-derived caffeic acid and its derivatives, nuclear magnetic resonance spectroscopy data and possible biosynthetic pathways of these compounds were collected from scientific databases (SciFinder, PubMed and China Knowledge). According to different types of substituents, 17 caffeic acid and its derivatives can be divided into the following classes: caffeoyl ester derivatives, caffeyltartaric acid, caffeic acid amide derivatives, caffeoyl shikimic acid, caffeoyl quinic acid, caffeoyl danshens and caffeoyl glycoside. Generalization of their 13C-NMR and 1H-NMR data revealed that acylation with caffeic acid to form esters involves acylation shifts, which increase the chemical shift values of the corresponding carbons and decrease the chemical shift values of the corresponding carbons of caffeoyl. Once the hydroxyl group is ester, the hydrogen signal connected to the same carbon shifts to the low field (1.1~1.6). The biosynthetic pathways were summarized, and it was found that caffeic acid and its derivatives are first synthesized in plants through the shikimic acid pathway, in which phenylalanine is deaminated to cinnamic acid and then transformed into caffeic acid and its derivatives. The purpose of this review is to provide a reference for further research on the rapid structural identification and biofabrication of caffeic acid and its derivatives.

PREPARATION AND CHARACTERIZATION OF PERFLUOROETHYLSUBSTITUTED ALKYLAMMONIUM OLIGOFLUOROPHOSPHATES

Mono-, di-, triperfluoroethyl substituted fluorophosphate anions are building blocks in the molecular design of salts with onium cations, and are used to increase hydrophobicity, modify surfactant properties and electrical conductivity. The work proposes methods for the synthesis of superacid H+[PF3(C2F5)3]- by the reaction of tri(pentafluoroethyl)difluorophosphorane with a solution of hydrofluoric acid, as well as superacids H+[PF4(C2F5)2]- and H+[PF5C2F5]- by step-by-step removal of the pentafluoroethyl substituent by hydrolysis with subsequent treatment with HF solution. Ionic compounds were synthesized by metathesis of anions at 0 °C from the corresponding quaternary ammonium chloride based on the obtained superacids. The article presents NR4FAP-class ionic compounds with the tributylmethylammonium (TBMA) cation of the general formula [(C4H9)3NCH3]+[PF6-n(C2F5)n]-, where n = 1, 2, 3. The square bipyramidal structure of the three studied anions was confirmed by nuclear magnetic resonance (NMR) spectroscopy and X-ray diffraction (XRD) data. The study shows, the synthesized compounds are characterized by extremely low vapor pressure up to 300 °C, a wide range of the liquid state with a width of up to 310 K by the methods of differential scanning calorimetry (DSC) and synchronous thermal analysis (STA). Melting temperatures and enthalpies were determined. The TBMA salts belong to ionic liquids (IL's), including one type liquid at room temperature (RT-IL). The general patterns of compounds decomposition were analyzed by the analysis of evolved gases (STA-EGA); it was shown that in all cases, the decomposition of the studied ionic liquids begins with the destruction of the anion. The electrical resistance of a pure ionic liquid at room temperature was studied. The described characteristics of perfluoroethylsubstituted alkyl ammonium oligofluorophosphates open up prospects for their use as electro conducting and antistatic additives for petrochemicals, fuels and polymers. For citation: Mokrushin I.G., Pinegina O.A., Krasnovskikh M.P., Dmitriev M.V., Markin I.V., Kozen A.L. Preparation and characterization of perfluoroethylsubstituted alkylammonium oligofluorophosphates. ChemChemTech [Izv. Vyssh. Uchebn. Zaved. Khim. Khim. Tekhnol.]. 2024. V. 67. N 5. P. 54-61. DOI: 10.6060/ivkkt.20246705.6916.

From NMR to AI: Designing a Novel Chemical Representation to Enhance Machine Learning Predictions of Physicochemical Properties.

A novel approach to the utilization of nuclear magnetic resonance (NMR) spectroscopy data in the prediction of logD through machine learning algorithms is shown. In the analysis, a data set of 754 chemical compounds, organized into 30 clusters, was evaluated using advanced machine learning models, such as Support Vector Regression (SVR), Gradient Boosting, and AdaBoost, and comprehensive validation and testing methods were employed, including 10-fold cross-validation, bootstrapping, and leave-one-out. The study revealed the superior performance of the Bucket Integration method for dimensionality reduction, consistently yielding the lowest root mean square error (RMSE) across all data sets and normalization schemes. The SVR prediction models demonstrated remarkable computational efficiency and low cost, with the best RMSE value reaching 0.66. Our best model outperformed existing tools like JChem Suite's logD Predictor (0.91) and CplogD (1.27), and a comparison with traditional molecular representations yielded a comparable RMSE (0.50), emphasizing the robustness of our NMR data integration. The widespread availability of NMR data in pharmaceutical and industrial research presents an untapped resource for predictive modeling, highlighting the need for accessible methodologies like ours that complement the analytical toolbox beyond conventional 2D approaches. Our approach, designed to leverage the rich spatial data from NMR spectroscopy, provides additional insights and enriches drug discovery and computational chemistry with a freely accessible tool.

Comment on "Three New Dimers and Two Monomers of Phenolic Amides from the Fruits of Lycium barbarum and Their Antioxidant Activities".

This Comment critically addresses the article by Gao et al. (Gao, K., et al. J. Agric. Food Chem. 2015, 63, 1067-1075), providing the structural elucidation of three phenolamide dimers (neolignanamides) from the fruits of Lycium barbarum. A more recent article published by Chen et al. (Chen, H., et al. J. Agric. Food Chem. 2023, 71, 11080-11093) incorporates these structures into further research on the bioactivity of these compounds. Although the analytical techniques used by Gao et al. are adequate, in our opinion, the nuclear magnetic resonance (NMR) spectroscopic data have not been interpreted correctly, resulting in incorrect structures for three neolignanamides from the fruits of L. barbarum. In this Comment, an alternative interpretation of the NMR spectroscopic data and the corresponding structures are proposed. The proposed structures feature linkage types that are much more common for neolignanamides than the linkage types in the originally reported structures of these compounds.

Retinestatin, a Polyol Polyketide from a Termite Nest-Derived Streptomyces sp.

A new polyol polyketide, named retinestatin (1), was obtained and characterized from the culture of a Streptomyces strain, which was isolated from a subterranean nest of the termite Reticulitermes speratus kyushuensis Morimoto. The planar structure of 1 was elucidated on the basis of the cumulative analysis of ultraviolet, infrared, mass spectrometry, and nuclear magnetic resonance spectroscopic data. The absolute configuration of 1 at 12 chiral centers was successfully assigned by employing a J-based configuration analysis in combination with ROESY correlations, a quantum mechanics-based computational approach to calculate NMR chemical shifts, and a 3 min flash esterification by Mosher's reagents followed by NMR analysis. Biological evaluation of retinestatin (1) using an in vitro model of Parkinson's disease revealed that 1 protected SH-SY5Y dopaminergic cells from MPP+-induced cytotoxicity, indicating its neuroprotective effects.

Identification of Solvent Extraction of Au(III) by Cyanex 272 from Hydrochloric Acid Solutions

Bis(2,4,4-trimethylpentyl)phosphinic acid (Cyanex 272) is known to selectively extract Au(III) from dilute to concentrated hydrochloric acid solutions. Therefore, Cyanex 272 can be employed in the separation of Au(III) from the hydrochloric acid leaching solutions of secondary resources containing gold metal. This work identified the extraction reaction of Au(III) by Cyanex 272 from the hydrochloric acid solutions. Au(III) extraction data was obtained by varying the concentrations of HCl (1-9 M), Au(III) (0.1-1 g/L) and Cyanex 272 (0.01-0.1 M). Among the three variables, it was found that HCl concentration had the most pronounced effect on the extraction of Au(III), which increased with HCl concentration. The extraction reaction of Au(III) by Cyanex 272 is proposed by applying slope analysis method to the extraction data. Comparison of Fourier transform infrared spectroscopy results for the fresh and loaded Cyanex 272 revealed no change in the chemical structure of Cyanex 272 after the extraction. Nuclear magnetic resonance spectroscopic data showed a change in the characteristic peaks of the phosphorus atom of Cyanex 272, indicating the formation of a coordinative bond between Au(III) and Cyanex 272. FT-IR and NMR data together with application of slope analysis clearly verified that molecular Cyanex 272 takes parts in the extraction of Au(III).