Detection of lard adulteration in 3 kinds of vegetable oils by liquid chromatography-mass spectrometry with porous graphite carbon column.

Liquid chromatography‒mass spectrometry employing porous graphite carbon columns and an n-octane-isopropanol mobile phase was utilized for the separation of triacylglycerols (TAGs) in various edible oils, aiming to identify lard adulteration in soybean, corn, and sunflower seed oils. Experiments were conducted using a Hypercarb column (2.1 mm × 100 mm, 5 µm) and an n-octane-isopropanol (70:30, V/V) mobile phase at a flow rate of 0.25 mL· min-1 and a column temperature of 60 °C. Detection was achieved through atmospheric pressure chemical ionization-mass spectrometry. Analysis of diverse edible oil samples revealed that oils of the same type shared similar TAG compositions, while different types exhibited distinct TAG profiles. Distinct variations in triglyceride composition were observed across different edible oils. Based on liquid chromatography‒mass spectrometry analysis, the characteristic component 1-stearic acid-2-palmitic acid-3-oleic acid glyceride (SPO), which may also include PSO, was identified in lard through principal component analysis and orthogonal partial least squares discriminant analysis. This component served as a marker for detecting as low as 0.1% lard adulteration in soybean, corn, and sunflower seed oils. The technique offers a precise and effective approach for the identification of lard adulteration in these edible oils.

De novo biosynthesis of 2-hydroxyterephthalic acid, the monomer for high-performance hydroxyl modified PBO fiber, by enzymatic Kolbe-Schmitt reaction with CO2 fixation.

BACKGROUND: High-performance poly(p-phenylenebenzobisoxazole) (PBO) fiber, with excellent mechanical properties (stiffness, strength, and toughness), high thermal stability combined and light weight, are widely employed in automotive and aerospace composites, body armor and sports goods. Hydroxyl modified PBO (HPBO) fiber shows better photostability and interfacial shear strength. 2-Hydroxyterephthalic acid (2-HTA), the monomer for the HPBO fiber, is usually synthesized by chemical method, which has poor space selectivity and high energy consumption. The enzymatic Kolbe-Schmitt reaction, which carboxylates phenolic substrates to generate hydroxybenzoic acids with bicarbonate/CO2, was applied in de novo biosynthesis of 2-HTA with CO2 fixation. RESULTS: The biosynthesis of 2-HTA was achieved by the innovative application of hydroxybenzoic acid (de)carboxylases to carboxylation of 3-hydroxybenzoic acid (3-HBA) at the para-position of the benzene carboxyl group, known as enzymatic Kolbe-Schmitt reaction. 2,3-Dihydroxybenzoic acid decarboxylase from Aspergillus oryzae (2,3-DHBD_Ao) were expressed in recombinant E. coli and showed highest activity. The yield of 2-HTA was 108.97 ± 2.21 µg/L/mg protein in the whole-cell catalysis. In addition, two amino acid substitutions, F27G and T62A, proved to be of great help in improving 2,3-DHBD activity. The double site mutation F27G/T62A increased the production of 2-HTA in the whole-cell catalysis by 24.7-fold, reaching 2.69 ± 0.029 mg/L/mg protein. Moreover, de novo biosynthetic pathway of 2-HTA was constructed by co-expression of 2,3-DHBD_Ao and 3-hydroxybenzoate synthase Hyg5 in S. cerevisiae S288C with Ura3, Aro7 and Trp3 knockout. The engineered strain synthesized 45.40 ± 0.28 µg/L 2-HTA at 36 h in the CO2 environment. CONCLUSIONS: De novo synthesis of 2-HTA has been achieved, using glucose as a raw material to generate shikimic acid, chorismic acid, and 3-HBA, and finally 2-HTA. We demonstrate the strong potential of hydroxybenzoate (de)carboxylase to produce terephthalic acid and its derivatives with CO2 fixation.

A Highly Sensitive Model Based on Graph Neural Networks for Enzyme Key Catalytic Residue Prediction.

Determining the catalytic site of enzymes is a great help for understanding the relationship between protein sequence, structure, and function, which provides the basis and targets for designing, modifying, and enhancing enzyme activity. The unique local spatial configuration bound to the substrate at the active center of the enzyme determines the catalytic ability of enzymes and plays an important role in the catalytic site prediction. As a suitable tool, the graph neural network can better understand and identify the residue sites with unique local spatial configurations due to its remarkable ability to characterize the three-dimensional structural features of proteins. Consequently, a novel model for predicting enzyme catalytic sites has been developed, which incorporates a uniquely designed adaptive edge-gated graph attention neural network (AEGAN). This model is capable of effectively handling sequential and structural characteristics of proteins at various levels, and the extracted features enable an accurate description of the local spatial configuration of the enzyme active site by sampling the local space around candidate residues and special design of amino acid physical and chemical properties. To evaluate its performance, the model was compared with existing catalytic site prediction models using different benchmark datasets and achieved the best results on each benchmark dataset. The model exhibited a sensitivity of 0.9659, accuracy of 0.9226, and area under the precision-recall curve (AUPRC) of 0.9241 on the independent test set constructed for evaluation. Furthermore, the F1-score of this model is nearly four times higher than that of the best-performing similar model in previous studies. This research can serve as a valuable tool to help researchers understand protein sequence-structure-function relationships while facilitating the characterization of novel enzymes of unknown function.

Electroenzymatic Reduction of Furfural to Furfuryl Alcohol by an Electron Mediator and Enzyme Orderly Assembled Biocathode.

The electroenzymatic valorization of biomass derivatives into valuable biochemicals has a promising outlook. However, bottlenecks including poor electron transfer between the electrode surface and oxidoreductase, inefficient regeneration of cofactors, and high cost of enzymes and electron mediators hindered the realistic applications of the technique. Herein, to address the above technical barriers, a novel bio-electrocatalytic system that integrates the electrochemical NADH regeneration and enzymatic reaction was constructed, using an orderly assembled composite bioelectrode consisting of an outer immobilized enzyme layer and a sandwiched redox mediator rhodium complex layer. The as-prepared composite bioelectrode was further applied for the highly selective hydrogenation of furfural into furfural alcohol. Results indicated that the enzyme activity was significantly improved, while the furfural valorization was promoted by effective interfacial electron transition and co-factor regeneration on the composite bioelectrode. Considerable high furfural conversion (96.4%) can be achieved accompanied by a furfural alcohol selectivity of 90.0% at -1.2 V (vs Ag/AgCl). The novel composite bioelectrode also showed good stability and reusability. Up to 85.1% of the original furfural alcohol selectivity can be preserved after 10 times of recycling. This work presents a promising green alternative for the valorization of furfural, which also shows great potential extending to the valorization of other biomass compounds.

A one-dimensional convolutional neural network based deep learning for high accuracy classification of transformation stages in esophageal squamous cell carcinoma tissue using micro-FTIR.

Among the most frequently diagnosed cancers in developing countries, esophageal squamous cell carcinoma (ESCC) ranks among the top six causes of death. It would be beneficial if a rapid, accurate, and automatic ESCC diagnostic method could be developed to reduce the workload of pathologists and improve the effectiveness of cancer treatments. Using micro-FTIR spectroscopy, this study classified the transformation stages of ESCC tissues. Based on 6,352 raw micro-FTIR spectra, a one-dimensional convolutional neural network (1D-CNN) model was constructed to classify-five stages. Based on the established model, more than 93% accuracy was achieved at each stage, and the accuracy of identifying proliferation, low grade neoplasia, and ESCC cancer groups was achieved 99% for the test dataset. In this proof-of-concept study, the developed method can be applied to other diseases in order to promote the use of FTIR spectroscopy in cancer pathology.

Prediction of Plasticizer Property Based on an Improved Genetic Algorithm.

Different plasticizers have obvious differences in plasticizing properties. As one of the important indicators for evaluating plasticization performance, the substitution factor (SF) has great significance for product cost accounting. In this research, a genetic algorithm with "variable mutation probability" was developed to screen the key molecular descriptors of plasticizers that are highly correlated with the SF, and a SF prediction model was established based on these filtered molecular descriptors. The results show that the improved genetic algorithm greatly improved the prediction accuracy in different regression models. The coefficient of determination (R2) for the test set and the cross-validation both reached 0.92, which is at least 0.15 higher than the R2 of the unimproved genetic algorithm. From the results of the selected descriptors, most of the descriptors focused on describing the branching of the molecule, which is consistent with the view that the branching chain plays an important role in the plasticization process. As the first study to establish the relationship between plasticizer SF and plasticizer molecular structure, this work provides a basis for subsequent plasticizer performance and evaluation system modeling.

Rapid and sensitive detection of esophageal cancer by FTIR spectroscopy of serum and plasma.

Fourier transform infrared (FTIR) spectroscopy, as a platform technology for cancer detection, must be up to the challenge of clinical transformation. To this end, detection of esophageal squamous cell carcinoma (ESCC) was hereby explored using serum and plasma scrape-coated on barium fluoride (BaF2) disk by transmission FTIR method, and the classification model was built using six multivariate statistical analyses, including support vector machine (SVM), principal component linear discriminant analysis (PC-LDA), decision tree (DT), k-nearest neighbor (KNN) classification, ensemble algorithms (EA) and partial least squares for discriminant analysis (PLS-DA). All statistical analyses methods demonstrated that late-stage cancer could be well classified from healthy people employing either serum or plasma with different anticoagulants. Resulting PC-LDA model differentiated late-stage cancer from normal group with an accuracy of 99.26%, a sensitivity of 98.53%, and a specificity of 100%. The accuracy and sensitivity reached 97.08% and 91.43%, respectively for early-stage cancer discrimination from normal group. This pilot exploration demonstrated that transmission FTIR provided a rapid, cost effective and sensitive method for ESCC diagnosis using either serum or plasma.

Simple and fast colorimetric and electrochemical methods for the ultrasensitive detection of glucose.

Developing ultrasensitive and user-friendly methods for the detection glucose has attracted more and more attention. By virtue of high selectivity and sensitivity, enzyme-based glucose sensor plays a key role in point-of-care sensing technology for detecting glucose concentration. In this study, Amplex Red (AR), as both indicator and mediator, was investigated to detect glucose in presence of glucose oxidase (GOx) enzymes using colorimetric and electrochemical methods. Without using any advanced techniques and sophisticated nanomaterials, 1 µM glucose can be easily detected through simply detecting the solution color with a visual colorimetric method. On the other hand, the electrochemical method can provide much higher sensitivity for the detection of glucose, which achieves a linear range spanning from 20 nM to 3.56 µM with a limit of 7.3 nM (signal-to-noise ratio SNR = 3). It is also found that the presence of other sugars such as fructose, lactose, and maltose have very limited interference effects on the detection of glucose. More importantly, a bare GC electrode was used in all these electrochemical measurements without any electrode surface modification, guaranteeing a simple and fast operation. The analytical platforms for the detection of glucose presented here not only provide simple, fast, and ultrasensitive methods, but also have the potential to advance the sensing technology in the application of other health diagnostic research areas. Amplex Red (AR) was reported as both an indicator and mediator for the sensitive and specific determination of glucose using the colorimetric and electrochemical methods. The detection limit was 1 µM glucose by the visual colorimetric methods. A bare glassy carbon electrode without any functional modification was employed for the detection as low as 20 nM glucose with LOD of 7.3 nm (SNR = 3) in the electrochemical method.

Blood plasma resonance Raman spectroscopy combined with multivariate analysis for esophageal cancer detection.

We herein report a novel, reliable and inexpensive method for detecting esophageal cancer using blood plasma resonance Raman spectroscopy combined with multivariate analysis methods. The blood plasma samples were divided into late stage cancer group (n = 164), early stage cancer group (n = 35) and normal group (n = 135) based on clinical pathological diagnosis. Using a specially designed quartz capillary tube as sample holder, we obtained higher quality resonance Raman spectra of blood plasma than existing method. The study demonstrated that the carotenoids levels in blood plasma were reduced in esophageal cancer patients. The area under the receiver operating characteristic curve (and 95% confidence interval) calculated by wavenumber selection and principal component analysis combined with linear discriminant analysis (PC-LDA) algorithm were 0.894 (0.858-0.929), 0.901 (0.841-0.960) and 0.871 (0.799-0.942) for differentiating late cancer from normal, late cancer from early cancer, and early cancer from normal respectively. The contribution from the two carotenoids wavenumber regions of 1155 and 1515 cm-1 were more than 84.2%. The results show that the plasma carotenoids could be a potential biomarker for screening esophageal cancer using resonance Raman spectroscopy combined with wavenumber selection and PC-LDA algorithms.

The key roles of Fe-bearing minerals on arsenic capture and speciation transformation during high-As bituminous coal combustion: Experimental and theoretical investigations.

The conversion of As vapor released from coal combustion to less hazardous solids is an important process to alleviate As pollution especially for high-As coal burning, but the roles of key ash components are still in debate. Here, we used multiple analytical methods across the micro to bulk scale and density functional theory to provide quantitative information on As speciation in fly ash and clarify the roles of ash components on As retention. Fly ash samples derived from the high-As bituminous coal-fired power plants showed a chemical composition of typical Class F fly ash. In-situ electron probe microanalysis (EPMA) was for the first time used to quantify and distinguish the inter-particle As distribution difference within coal fly ash. The spatial distribution of As was consistent with Fe, O, and sometimes with Ca. Grain-scale distribution of As in coal fly ash was quantified and As concentrations in single ash particles followed the order of Fe-oxides > aluminosilicates > unburned carbon > quartz. Sequential extraction and Wagner chemical plot of As confirmed that Fe minerals rather than Al-/Ca-bearing minerals played a vital role in capturing and oxidizing As3+ into solid phase (As5+). Magnetite content in fly ash well-correlated with the increase ratio of As before and after magnetic separation, suggesting magnetite enhanced As enrichment in fly ash. Density functional theory (DFT) indicated that the bridges O sites of octahedral structure on Fe3O4 (111) surface were likely strong active sites for As2O3 adsorption. This study highlights the importance of magnetite on As transformation during bituminous or high-rank coal combustion in power plants and has great implications for developing effective techniques for As removal.

Micro-FTIR combined with curve fitting method to study cellulose crystallinity of developing cotton fibers.

This study aimed to use micro-FTIR with transmission mode to investigate cellulose crystallinity of developing cotton fibers. Compared with ATR-FTIR method, we found that micro-FTIR can obtain more information of cellulose inside of the developing cotton fibers, especially in high wavenumber of 2800-3000 cm-1 region. Combined with curve fitting method, a new IR crystallinity index (CI) method named wax crystallinity index (WCI) was introduced to evaluate the cellulose crystallinity in the development of cotton fibers based on the peak and area ratios of 2900 cm-1/2850 cm-1 and 2900 cm-1/2920 cm-1. The obtained WCI values demonstrated an excellent coefficient of determination with X-ray diffraction (XRD) CI method with the value up to 0.99. This study suggested that micro-FTIR was an effective technique to qualitatively analyze the crystallinity in developing cotton fibers combined with curve fitting method.

Reprogramming of sugar transport pathways in Escherichia coli using a permeabilized SecY protein-translocation channel.

In the initial step of sugar metabolism, sugar-specific transporters play a decisive role in the passage of sugars through plasma membranes into cytoplasm. The SecY complex (SecYEG) in bacteria forms a membrane channel responsible for protein translocation. The present work shows that permeabilized SecY channels can be used as nonspecific sugar transporters in Escherichia coli. SecY with the plug domain deleted allowed the passage of glucose, fructose, mannose, xylose, and arabinose, and, with additional pore-ring mutations, facilitated lactose transport, indicating that sugar passage via permeabilized SecY was independent of sugar stereospecificity. The engineered E. coli showed rapid growth on a wide spectrum of monosaccharides and benefited from the elimination of transport saturation, improvement in sugar tolerance, reduction in competitive inhibition, and prevention of carbon catabolite repression, which are usually encountered with native sugar uptake systems. The SecY channel is widespread in prokaryotes, so other bacteria may also be engineered to utilize this system for sugar uptake. The SecY channel thus provides a unique sugar passageway for future development of robust cell factories for biotechnological applications.

Fine-Tuning of Crystal Packing and Charge Transport Properties of BDOPV Derivatives through Fluorine Substitution.

Molecular packing in organic single crystals greatly influences their charge transport properties but can hardly be predicted and designed because of the complex intermolecular interactions. In this work, we have realized systematic fine-tuning of the single-crystal molecular packing of five benzodifurandione-based oligo(p-phenylenevinylene) (BDOPV)-based small molecules through incorporation of electronegative fluorine atoms on the BDOPV backbone. While these molecules all exhibit similar column stacking configurations in their single crystals, the intermolecular displacements and distances can be substantially modified by tuning of the amounts and/or the positions of the substituent fluorine atoms. Density functional theory calculations showed that the subtle differences in charge distribution or electrostatic potential induced by different fluorine substitutions play an important role in regulating the molecular packing of the BDOPV compounds. Consequently, the electronic couplings for electron transfer can vary from 71 meV in a slipped stack to 201 meV in a nearly cofacial antiparallel stack, leading to an increase in the electron mobility of the BDOPV derivatives from 2.6 to 12.6 cm(2) V(-1) s(-1). The electron mobility of the five molecules did not show a good correlation with the LUMO levels, indicating that the distinct difference in charge transport properties is a result of the molecular packing. Our work not only provides a series of high-electron-mobility organic semiconductors but also demonstrates that fluorination is an effective approach for fine-tuning of single-crystal packing modes beyond simply lowering the molecular energy levels.

A Cofacially Stacked Electron-Deficient Small Molecule with a High Electron Mobility of over 10 cm(2) V(-1) s(-1) in Air.

A strong, electron-deficient small molecule, F4 -BDOPV, has a lowest unoccupied molecular orbital (LUMO) level down to -4.44 eV and exhibits cofacial packing in single crystals. These features provide F4 -BDOPV with good ambient stability and large charge-transfer integrals for electrons, leading to a high electron mobility of up to 12.6 cm(2) V(-1) s(-1) in air.

[Determination of minor elements in stainless steel by laser-induced plasma spectroscopy (LIPS)].

Laser-induced plasma spectroscopy (LIPS) is characterized by its non-contact and real-time analysis. Its application to the determination of steel composition can meet the need of high-speed, continuous and automatic production in large steel companies. In the present article the minor elements concentrations of aluminum, manganese, cobalt, molybdenum, and titanium in a series of stainless steel 1Cr18Ni9Ti samples were determinate by laser-induced plasma spectroscopy, based on a Nd : YAG Q-switched solid laser with wavelength 1 064 nm as an exciting source and ICCD as detector. In the experiment the working delay time and gate time of ICCD were set suitably to get high signal-to-noise ratio emission spectral lines, and the internal standardization method related to matrix effect was used to deal with spectral data. Experiment results show that the concentration ratios of all the measured elements versus the reference element ferrum have a good linear relationship with the intensity ratios of them, the detection limits of the five tested elements are within 150 microg x g(-1).

[X-ray fluorescence analysis in archaeometry: application and expectation].

This article describes the applications of X-ray fluorescence in archaeology research, including the appraisal, dating, provenance and mine material origin analysis of cultural relic, the study of manufacturing technics and production of cultural relic, etc. It also suggests some expectation and problems, in order to draw attention of X-ray fluorescence analysts and archaeologists, promote the in-depth development of X-ray fluorescence analysis application in archaeology research, and further make more contributions to Chinese archaeology research.