The differences in main components, enzyme activity, and microbial composition between substandard and normal jiuyao.

BACKGROUND: Jiuyao is a critical fermenting agent in traditional huangjiu brewing and it affects the quality of huangjiu. To assess and monitor the quality of jiuyao effectively we determined the differences between two common types of substandard jiuyao and normal jiuyao, with emphasis on the comparison of the main components, enzymatic activity, volatile substances, and microbial community structure. RESULTS: The water and starch content, acid protease activity, and esterification capability of type I substandard jiuyao were significantly lower than those of the normal jiuyao, and the protein contents, liquefaction capability, glycation capability, and neutral protease activity were substantially higher than those of the normal jiuyao. Type II substandard jiuyao had significantly lower indices than the normal group except for the starch and free amino acid content, which were significantly higher than those of the normal jiuyao. Significant differences were observed between substandard and normal jiuyao in the content of 21 volatile compounds. 2-Pentylfuran could be used as a marker of substandard jiuyao. Type I substandard jiuyao contained a higher abundance of aerobic Pediococcus and Marivita in comparison with the normal jiuyao. Type II substandard jiuyao consisted of a greater abundance of anaerobic Mucor and Staphylococcus. CONCLUSION: The quality of jiuyao was significantly affected by the water content. Due to the different abundances of aerobic and anaerobic bacteria in jiuyao, oxygen may also be an important parameter affecting the quality of jiuyao. We believe that the present study offers a theoretical basis for the evaluation and control of the quality of jiuyao. © 2023 Society of Chemical Industry.

Insights into the Effect of the Adsorption Preference of Additives on the Anisotropic Growth of ZSM-5 Zeolite.

Invited for the cover of this issue are Zaiku Xie, Jiawei Teng, Chuanming Wang, and co-workers at the SINOPEC Shanghai Research Institute of Petrochemical Technology, Liaoning Petrochemical University and University of Science and Technology of China. The image depicts the effect of eight organic additives on the anisotropic growth of classical ZSM-5 zeolite at the molecular level. Read the full text of the article at 10.1002/chem.202201781.

Insights into the Effect of the Adsorption Preference of Additives on the Anisotropic Growth of ZSM-5 Zeolite.

Zeolite morphology plays a crucial role in affecting catalytic performance, while is persistently challenging to tailor through crystal anisotropic growth. It has been recognized that specific additives can be introduced into the synthesis of zeolites to achieve anisotropic growth, however their role and the underlying mechanism are not well understood. Herein, the effect of eight specific additives on the anisotropic growth of the ZSM-5 zeolite is unveiled within the framework of crystallization engineering. Either an inhibition effect or a promotion effect is revealed for each additive according to the crystallization kinetics. The adsorption preference of typical additives on different surfaces was demonstrated by total internal reflection fluorescence microscopy (TIRFM) and transmission X-ray microscopy (TXM) together with 3D reconstruction. The calculated adsorption energy difference between MFI [100]/[101] and [010] surfaces was proposed as a key descriptor to estimate the possible morphology induced by additive. ZSM-5 zeolites varying from sphere-like, plate-like to noodle-like morphology could be synthesized by employing specific additives with increasing adsorption strength difference on distinct surfaces.

MXene-Derived Nanocomposites as Earth-Abundant Efficient Electrocatalyst for Nitrogen Reduction Reaction under Ambient Conditions.

NH3, as one of the most massively used chemical products in the world, not only serves as the main nitrogen source of chemical fertilizers but also is considered as a promising renewable energy source. Most ammonia in industry is produced by the Haber-Bosch process under extremely high temperature and pressure conditions, which is intensively energy consuming and environmentally unfriendly. Electrocatalytic nitrogen reduction reaction (NRR) has been regarded as a promising way to produce NH3 under ambient conditions in recent years, but the research for efficient earth-abundant electrocatalysts is still highly limited. In this work, different TiO2 phases (anatase and rutile)/carbon nanocomposites with a sandwich architecture are produced by annealing MXene at different temperatures, which shows excellent electrocatalytic NRR performance. In 0.1 M Na2SO4, anatase TiO2/C composites show better NRR performance than the rutile ones, which achieve a large NH3 yield of 14.0 µg h-1 cm-2, a high Faradaic efficiency of 13.3% at -0.2 V vs a reversible hydrogen electrode, and a high electrochemical stability. The sandwich architecture of anatase TiO2 nanoparticles well-dispersed on the surface of carbon layers could increase the conductivity of TiO2 and the exposure of active sites, which could explain the improved NRR activity of anatase TiO2/C composites compared with previous work. Density functional theory calculations suggest that the energy barrier of most steps for the surface of anatase TiO2 is relatively lower than that of rutile TiO2, which could explain the better electrocatalytic NRR performance for anatase TiO2/C composites compared with the rutile ones.

Increased expression of microRNA-31-5p inhibits cell proliferation, migration, and invasion via regulating Sp1 transcription factor in HepG2 hepatocellular carcinoma cell line.

Accumulating evidence has suggested that microRNA-31-5p (miR-31-5p) is dysfunctional in hepatocellular carcinoma (HCC). However, the molecular mechanism of HCC remains unclear. In this study, we investigated the role of miR-31-5p in tumor formation and development of HCC. The expression of miR-31-5p was detected in HCC tissues, corresponding adjacent tissues, normal liver tissues, and HCC cell lines. miR-31-5p mimics and an inhibitor were transfected into HepG2 cells to assess the effects of miR-31-5p on cell proliferation, apoptosis, cell cycle, migration, and invasion assays. Western blotting was used to detect the expression of Sp1 transcription factor (SP1), cyclin D1, and survivin in transfected HCC cells and control cells. The expression of miR-31-5p was significantly decreased in HCC cells and HCC tissues. Overexpression of miR-31-5p inhibited HCC cell growth, migration, and invasion. Overexpression of miR-31-5p reduced the expression of SP1 and cyclin D1, and knockdown of SP1 decreased cyclin D1 expression. The dual luciferase assay showed that miR-31-5p directly targeted SP1 in HepG2. Together, the results suggested that miR-31-5p acted as a tumor suppressor to regulate SP1, and that miR-31-5p could be used as a therapeutic target for the treatment of HCC.

Enhanced photocatalytic performance of sandwiched ZnO@Ag@Cu2O nanorod films: the distinct role of Ag NPs in the visible light and UV region.

Sandwiched ZnO@Ag@Cu2O nanorod films were synthesized by successive electrodeposition, magnetron sputtering and the second electrodeposition. The as-synthesized composites were characterized by x-ray diffraction patterns, field emission scanning electron microscopy, low- and high-resolution transmission electron microscopy and a UV-vis spectrophotometer. Their photocatalytic performance was estimated by the degradation of a methyl orange solution under UV or visible-light irradiation, respectively. In the visible region, due to localized surface plasmon resonance absorption of Ag NPs, ZnO@Ag@Cu2O showed a significantly enhanced photocatalytic performance. The enhancement factor of Ag NPs on the catalytic performance of ZnO@Ag@Cu2O was estimated as a function of the Cu2O deposition time, and the corresponding enhancement mechanism was also evaluated by the monochromatic photocatalytic experiment and discrete dipole approximation simulation. In the UV region, due to the formation of a Schottky junction (e.g. Ag/ZnO, Ag/Cu2O), a limited enhanced photocatalytic performance was also realized for ZnO@Ag@Cu2O photocatalysts.

Non-destructive and fast identification of cotton-polyester blend fabrics by the portable near-infrared spectrometer.

A series of 376 cotton-polyester (PET) blend fabrics were studied by a portable near-infrared (NIR) spectrometer. A NIR semi-quantitative-qualitative calibration model was established by Partial Least Squares (PLS) method combined with qualitative identification coefficient. In this process, PLS method in a quantitative analysis was used as a correction method, and the qualitative identification coefficient was set by the content of cotton and polyester in blend fabrics. Cotton-polyester blend fabrics were identified qualitatively by the model and their relative contents were obtained quantitatively, the model can be used for semi-quantitative identification analysis. In the course of establishing the model, the noise and baseline drift of the spectra were eliminated by Savitzky-Golay(S-G) derivative. The influence of waveband selection and different pre-processing method was also studied in the qualitative calibration model. The major absorption bands of 100% cotton samples were in the 1400~1600 nm region, and the one for 100% polyester were around 1600~1800 nm, the absorption intensity was enhancing with the content increasing of cotton or polyester. Therefore, the cotton-polyester's major absorption region was selected as the base waveband, the optimal waveband (1100~2500 nm) was found by expanding the waveband in two directions (the correlation coefficient was 0.6, and wave-point number was 934). The validation samples were predicted by the calibration model, the results showed that the model evaluation parameters was optimum in the 1100~2500 nm region, and the combination of S-G derivative, multiplicative scatter correction (MSC) and mean centering was used as the pre-processing method. RC (relational coefficient of calibration) value was 0.978, RP (relational coefficient of prediction) value was 0.940, SEC (standard error of calibration) value was 1.264, SEP (standard error of prediction) value was 1.590, and the sample's recognition accuracy was up to 93.4%. It showed that the cotton-polyester blend fabrics could be predicted by the semi-quantitative-qualitative calibration model.

The establishment and external validation of NIR qualitative analysis model for waste polyester-cotton blend fabrics.

A series of 354 polyester-cotton blend fabrics were studied by the near-infrared spectra (NIRS) technology, and a NIR qualitative analysis model for different spectral characteristics was established by partial least squares (PLS) method combined with qualitative identification coefficient. There were two types of spectrum for dying polyester-cotton blend fabrics: normal spectrum and slash spectrum. The slash spectrum loses its spectral characteristics, which are effected by the samples' dyes, pigments, matting agents and other chemical additives. It was in low recognition rate when the model was established by the total sample set, so the samples were divided into two types of sets: normal spectrum sample set and slash spectrum sample set, and two NIR qualitative analysis models were established respectively. After the of models were established the model's spectral region, pretreatment methods and factors were optimized based on the validation results, and the robustness and reliability of the model can be improved lately. The results showed that the model recognition rate was improved greatly when they were established respectively, the recognition rate reached up to 99% when the two models were verified by the internal validation. RC (relation coefficient of calibration) values of the normal spectrum model and slash spectrum model were 0.991 and 0.991 respectively, RP (relation coefficient of prediction) values of them were 0.983 and 0.984 respectively, SEC (standard error of calibration) values of them were 0.887 and 0.453 respectively, SEP (standard error of prediction) values of them were 1.131 and 0.573 respectively. A series of 150 bounds samples reached used to verify the normal spectrum model and slash spectrum model and the recognition rate reached up to 91.33% and 88.00% respectively. It showed that the NIR qualitative analysis model can be used for identification in the recycle site for the polyester-cotton blend fabrics.

Tumor microenvironment-regulated drug delivery system combined with sonodynamic therapy for the synergistic treatment of breast cancer.

Co-loading of sonosensitizers and chemotherapeutic drugs into nanocarriers can improve the biocompatibilities, stabilities, and targeting of drugs and reduce the adverse reactions of drugs, providing a robust platform to orchestrate the synergistic interplay between chemotherapy and sonodynamic therapy (SDT) in cancer treatment. In this regard, biodegradable manganese dioxide (MnO2) has attracted widespread attention because of its unique properties in the tumor microenvironment (TME). Accordingly, herein, MnO2 nanoshells with hollow mesoporous structures (H-MnO2) were etched to co-load hematoporphyrin monomethyl ether (HMME) and doxorubicin (DOX), and DOX/HMME-HMnO2@bovine serum albumin (BSA) obtained after simple BSA modification of DOX/HMME-HMnO2 exhibited excellent hydrophilicity and dispersibility. H-MnO2 rapidly degraded in the weakly acidic TME, releasing loaded HMME and DOX, and catalysed the decomposition of H2O2 abundantly present in TME, producing oxygen (O2) in situ, significantly increasing O2 concentration and downregulating the hypoxia-inducible factor 1α (HIF-1α). After irradiation of the tumor area with low-frequency ultrasound, the drug delivery efficiency of DOX/HMME-HMnO2@BSA substantially increased, and the excited HMME generated a large amount of reactive oxygen species (ROS), which caused irreversible damage to tumor cells. Moreover, the cell death rate exceeded 60% after synergistic SDT-chemotherapy. Therefore, the pH-responsive nanoshells designed in this study can realize drug accumulation in tumor regions by responding to TME and augment SDT-chemotherapy potency for breast cancer treatment by improving hypoxia in tumors. Thus, this study provides theoretical support for the development of multifunctional nanocarriers and scientific evidence for further exploration of safer and more efficient breast cancer treatments.

Mechanism underlying the effects of exercise against type 2 diabetes: A review on research progress.

Exercise has emerged as one of the important and effective non-drug therapies used for management of type 2 diabetes (T2D) in certain nations. The present report summarizes the latest findings from the research on the beneficial effect of exercise on T2D. The objectives were to provide references for the theoretical study and the clinical practice of exercise-based management of T2D, in addition to identify the limitations of the existing literature, thereby provide direction for future research in this field.

Tensor product model transformation based adaptive integral-sliding mode controller: equivalent control method.

This paper proposes new methodologies for the design of adaptive integral-sliding mode control. A tensor product model transformation based adaptive integral-sliding mode control law with respect to uncertainties and perturbations is studied, while upper bounds on the perturbations and uncertainties are assumed to be unknown. The advantage of proposed controllers consists in having a dynamical adaptive control gain to establish a sliding mode right at the beginning of the process. Gain dynamics ensure a reasonable adaptive gain with respect to the uncertainties. Finally, efficacy of the proposed controller is verified by simulations on an uncertain nonlinear system model.

Proteomics and network pharmacology of Ganshu Nuodan capsules in the prevention of alcoholic liver disease.

Introduction: Ganshu Nuodan is a liver-protecting dietary supplement composed of Ganoderma lucidum (G. lucidum) spore powder, Pueraria montana (Lour.) Merr. (P. montana), Salvia miltiorrhiza Bunge (S. miltiorrhiza) and Astragalus membranaceus (Fisch.) Bunge. (A. membranaceus). However, its pharmacodynamic material basis and mechanism of action remain unknown. Methods: A mouse model of acute alcohol liver disease (ALD) induced by intragastric administration of 50% alcohol was used to evaluate the hepatoprotective effect of Ganshu Nuodan. The chemical constituents of Ganshu Nuodan were comprehensively identified by UPLC-QTOF/MS, and then its pharmacodynamic material basis and potential mechanism of action were explored by proteomics and network pharmacology. Results: Ganshu Nuodan could ameliorate acute ALD, which is mainly manifested in the significant reduction of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) in serum and malondialdehyde (MDA) content in liver and the remarkably increase of glutathione (GSH) content and superoxide dismutase (SOD) activity in liver. Totally 76 chemical constituents were identified from Ganshu Nuodan by UPLC-QTOF/MS, including 21 quinones, 18 flavonoids, 11 organic acids, 7 terpenoids, 5 ketones, 4 sterols, 3 coumarins and 7 others. Three key signaling pathways were identified via proteomics studies, namely Arachidonic acid metabolism, Retinol metabolism, and HIF-1 signaling pathway respectively. Combined with network pharmacology and molecular docking, six key targets were subsequently obtained, including Ephx2, Lta4h, Map2k1, Stat3, Mtor and Dgat1. Finally, these six key targets and their related components were verified by molecular docking, which could explain the material basis of the hepatoprotective effect of Ganshu Nuodan. Conclusion: Ganshu Nuodan can protect acute alcohol-induced liver injury in mice by inhibiting oxidative stress, lipid accumulation and apoptosis. Our study provides a scientific basis for the hepatoprotective effect of Ganshu Nuodan in acute ALD mice and supports its traditional application.

2,2'-(Ethane-1,2-di-yl)bis-(1H-benzimidazole).

The complete mol-ecule of the title compound, C(16)H(14)N(4), is generated by crystallographic inversion symmetry. In the crystal, mol-ecules are linked by N-H⋯N hydrogen bonds, generating (001) sheets. Weak aromatic π-π stacking inter-actions [centroid-centroid distances = 3.7383 (13) and 3.7935 (14) Å] are also observed.

Research on Online Rapid Sorting Method of Waste Textiles Based on Near-Infrared Spectroscopy and Generative Adversity Network.

In this paper, aiming at the application of online rapid sorting of waste textiles, a large number of effective high-content blending data are generated by using generative adversity network to deeply mine the combination relationship of blending spectra, and A BEGAN-RBF-SVM classification model is constructed by compensating the imbalance of negative samples in the data set. Various experiments show that the model can effectively extract the spectrum of pure textile samples. The classification model has high robustness and high speed, reaches the performance of similar products in the world, and has a broad application market.

Source analysis and ecological risk assessment of heavy metals in farmland soils around heavy metal industry in Anxin County.

Studying the pollution status, spatial distribution characteristics, and sources of heavy metals in farmland soil in Anxin County will provide a method basis for the next step of soil remediation. This study investigates the contents of Zn, Cu, Pb, Cd, and Ni in wheat grains and soil samples. Moreover, different methods are used to evaluate soil heavy metal pollution. The results show that the soil in the study area is weakly alkaline. Cu, Zn, and Ni contents in the ground are lower than the risk screening values for soil contamination of agricultural land. In comparison, Cd and Pb contents are higher than the screening value of soil pollution risk of agricultural land, and the proportion of points lower than the control value of soil pollution risk of agricultural land are 64.58% and 16.67%, respectively. The farmland with high Cd and Pb content is mainly distributed near roads and factories and concentrated primarily on 0-20 cm topsoil. The Cd content in wheat grains meets the standard, but 4.17% of the samples are close to 0.1 mg kg-1 (more than 0.09 mg kg-1). The Pb content of 50% of the wheat grain samples exceeds the lead limit in the standard. The evaluation results of the single factor pollution index and geoaccumulation index show that the pollution degree of heavy metals in the soil is Cd > Pb > Cu > Zn > Ni. The potential ecological risk index in the study area is 288.83, and the soil heavy metal pollution is at a moderate-considerable ecological risk level. The average value of Cd's single-factor environmental risk index is 233.51, which belongs to the high environmental risk and is the main influencing factor. Cd and Pb in soil are significantly disturbed by the production activities of heavy metal processing enterprises around the farmland. It is speculated that there are two primary sources of soil heavy metal pollution in the study area. Cd, Pb, Zn, and Cu are mainly industrial and mobile sources, and Ni is primarily agricultural and natural sources.

Tensor based stacked fuzzy neural network for efficient data regression.

Random vector functional link and extreme learning machine have been extended by the type-2 fuzzy sets with vector stacked methods, this extension leads to a new way to use tensor to construct learning structure for the type-2 fuzzy sets-based learning framework. In this paper, type-2 fuzzy sets-based random vector functional link, type-2 fuzzy sets-based extreme learning machine and Tikhonov-regularized extreme learning machine are fused into one network, a tensor way of stacking data is used to incorporate the nonlinear mappings when using type-2 fuzzy sets. In this way, the network could learn the sub-structure by three sub-structures' algorithms, which are merged into one tensor structure via the type-2 fuzzy mapping results. To the stacked single fuzzy neural network, the consequent part parameters learning is implemented by unfolding tensor-based matrix regression. The newly proposed stacked single fuzzy neural network shows a new way to design the hybrid fuzzy neural network with the higher order fuzzy sets and higher order data structure. The effective of the proposed stacked single fuzzy neural network are verified by the classical testing benchmarks and several statistical testing methods.

Poly[(µ(2)-4,4'-bipyridine-κN:N')bis-(µ(2)-2-phen-oxy-propionato-κO:O')cobalt(II)].

In the polymeric title compound, [Co(C(9)H(9)O(3))(2)(C(10)H(8)N(2))](n), the Co(II) ion is located on a twofold rotation axis and is six-coordinated by two N atoms from two 4,4'-bipyridine (4,4'-bipy) ligands in axial positions and by four O atoms from four 2-phen-oxy-propionate (POPA) anions in equatorial positions, defining a slightly distorted octa-hedral geometry. The carboxyl-ate group of the POPA anion displays a bis-monodentate mode, linking pairs of Co(II) ions into a chain parallel to [001]. Adjacent chains are connected in a perpendicular manner through 4,4'-bipy ligands into layers parallel to (100). The 4,4'-bipy ligand is likewise located on a twofold rotation axis, with a dihedral angle between the two pyridine rings of 57.05 (7)°. C-H⋯O hydrogen-bonding inter-actions are present within the layers. π-π stacking inter-actions between the POPA benzene rings of neighbouring layers [centroid-to-centroid distance = 3.976 (3) Šand plane-to-plane distance = 3.618 (3) Å] stabilize the packing of the structure.

Tetra-kis(µ(2)-2-phen-oxy-propionato)-κO,O':O';κO:O,O';κO:O'-bis-[(1,10-phenanthroline-κN,N')(2-phen-oxy-propionato-κO,O')cerium(III)].

In the centrosymmetric binuclear title complex, [Ce(2)(C(9)H(9)O(3))(6)(C(12)H(8)N(2))(2)], the two Ce(III) ions are linked by four 2-phen-oxy-propionate groups in bi- and tridentate bridging modes. Each Ce(III) ion is nine-coordinated by one 1,10-phenanthroline mol-ecule, two O atoms from a chelating carboxyl-ate, two O atoms derived from a µ(3)-carboxylate and two O atoms derived from two µ(2)-carboxylate ligands in a distorted CeN(2)O(7) monocapped square-anti-prismatic geometry.

Tetra-kis(µ(2)-2-phen-oxy-propionato)-κO,O':O';κO:O,O';κO:O'-bis-[(1,10-phenanthroline-κN,N')(2-phen-oxy-propionato-κO,O')gadolinium(III)].

In the centrosymmetric binuclear title complex, [Gd(2)(C(9)H(9)O(3))(6)(C(12)H(8)N(2))(2)], the two Gd(III) ions are linked by four 2-phen-oxy-propionate (L) groups in bi- and tridentate bridging modes. Each Gd(III) ion is nine-coordinated by one 1,10-phenanthroline mol-ecule, one bidentate chelating carboxyl-ate group and four bridging carboxyl-ate groups in a distorted GdN(2)O(7) monocapped square-anti-prismatic geometry.

Bis(µ-2-phen-oxy-propionato-κO:O')bis-[(1,10-phenanthroline-κN,N')bis-(2-phen-oxy-propionato-κO,O')samarium(III)].

The dimeric title compound, [Sm(2)(C(9)H(9)O(3))(6)(C(12)H(8)N(2))(2)], is centrosymmetric and is composed of six 2-phen-oxy-propionate anions and two 1,10-phenanthroline ligands. The Sm(III) atom is coordinated by two O atoms from two bridging anions, four O atoms from two chelating anions and the N atoms of the N-heterocycle in a distorted dodeca-hedral geometry.