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Cyclooxygenase and inducible nitric oxide synthase are key proteins in two different pathways that produce inflammation. In this study, we based on the principle of pharmacophore combination to obtain small molecules that can block the dual targets of COXs and iNOS. We screened two pharmacophores with anti-inflammatory activity, chromone ring and sulfonamide from clinical drugs, natural products and other compounds with outstanding biological activity, and synthesized 9 novel chromone-sulfonamide derivatives, among which compounds 4a, 4b, 4c, 4d and 4i exhibited different degrees of COXs and iNOS inhibition. In particular, compound 4i exhibited the most significant dual inhibitory effect, with an IC50 of 28.83 ± 0.06 μM for PGE2 and an IC50 of 36.95 ± 3.9 μM for NO content, which was superior to the positive drugs ibuprofen (IBU, IC50 = 246.5 ± 3.8 μM) and L-canavanine (L-Can., IC50 = 440.0 ± 7.9 μM). In addition, the research group used Discovery Studio to dock the target compounds with COX-1, COX-2 and iNOS, respectively, and the results showed that compound 4i had the best docking method (its -CDOCK INTERACTION ENERGY scores were 48.2967, 45.3519 and 43.4412, respectively, which were better than those of other compounds), which was consistent with the results of activity experiments, and the chromone ring and sulfonamide group could form hydrogen bonds between the two target proteins, conjugation and van der Waals interactions, indicating that the chromone ring and sulfonamide group are key pharmacophores. In addition, a preliminary study of the structure-activity relationship of the compound was carried out to identify the key factors affecting the anti-inflammatory activity, and 4i matched the structure-activity relationship, which indicated that 4i was a lead compound for the development of dual COXs/iNOS inhibition for the treatment of inflammatory diseases. [ABSTRACT FROM AUTHOR]

Depression is a common psychological disease with high morbidity and mortality. Recently, the involvement of synaptic plasticity in the pathogenesis of depression has shed light on the direction of developing novel antidepressants. Levomilnacipran is a newly approved medication for the treatment of adult major depressive disorder. However, the detailed mechanisms underlying its antidepressant-like effects have yet to be illuminated. In this study, we aimed to investigate the role of levomilnacipran in regulating synaptic plasticity and explore the possible molecular mechanisms of its antidepressant effects using a rat model of depression induced by lipopolysaccharide (LPS). The results demonstrated that levomilnacipran (30 mg/kg, i.p.) significantly ameliorated depression-like behaviors in rats, alleviated the dysregulation of synaptic plasticity, and suppressed neuroinflammation within hippocampus induced by LPS-treatment. Levomilnacipran increased the expression of postsynaptic dense 95 (PSD-95) and synaptophysin (Syn) and reversed the imbalance between pro- and anti-inflammatory cytokines within hippocampus of depressed rats. Additionally, levomilnacipran elevated expression level of brain-derived neurotrophic factor (BDNF), accompanied by increased tyrosine kinase B (TrkB), phosphorylated phosphatidylinositol 3-kinase (PI3K), phosphorylated protein kinase B (p-Akt), and phosphorylated mammalian target of rapamycin (p-mTOR). Taken together, these results suggest that levomilnacipran may exert antidepressant effects via upregulating BDNF/TrkB mediated PI3K/Akt/mTOR signaling pathway to improve synaptic plasticity. These findings reveal potential mechanisms for the antidepressant effects of levomilnacipran and offer new insights into the treatments for depression. [ABSTRACT FROM AUTHOR]

Deep learning methods have demonstrated remarkable success in recognizing geochemical anomalies for mineral exploration. Typically, these methods identify anomalies by reconstructing the geochemical background, which is marked by long-distance spatial variability, giving rise to long-range spatial dependencies within geochemical signals. However, current deep learning models for geochemical anomaly recognition face limitations in capturing intricate long-range spatial dependencies. Additionally, concerns emerge from the uncertainty associated with preprocessing in existing deep learning models, which involve generating interpolated images and topological graphs to represent the spatial structure of geochemical samples. In this paper, we present a novel end-to-end method for geochemical anomaly extraction based on the Transformer model. Our model utilizes self-attention mechanism to adequately capture both global and local interconnections among geochemical samples from a holistic perspective, enabling the reconstruction of geochemical background. Moreover, the self-attention mechanism allows the Transformer model to directly input free-form geochemical samples, eliminating the uncertainty associated with the employment of prior interpolation or graph generation typically required for geochemical samples. To align geochemical data with Transformer's architecture, we tailor a specialized data organization integrating learnable positional encoding and data masking. This enables the ingestion of entire geochemical data into the Transformer for anomaly recognition. Capitalizing on the flexibility afforded by the attention mechanism, we devise a contrastive loss for training, establishing a self-supervised learning scheme that enhances model generalizability for anomaly recognition. The proposed method is utilized to recognize geochemical anomalies related to Au mineralization in the northwest Jiaodong Peninsula, Eastern China. By comparison with anomalies identified by models of graph attention network and geographically weighted regression, it is demonstrated that the proposed method is more effective and geologically sound in identifying mineralization-associated anomalies. This superior performance in geochemical anomaly recognition is attributed to its ability to capture long-range dependencies within geochemical data. [ABSTRACT FROM AUTHOR]

The rapid development of electronic information technology makes the impact of electromagnetic waves on human life more and more prominent. Through electrospinning and high-temperature carbonization processes, we composited magnetic nanoparticles and carbon fibers and successfully embedded Fe–Ni nanoparticles into nanofibers uniformly. Through the comparative study of the alloy particle concentration in the composite material, we found that the Fe0.64Ni0.36@CNF composite material with an appropriate composition exhibits excellent microwave absorption performance. When the matching thickness is 4 mm, the minimum reflection loss can reach − 34.21 dB at 8.6 GHz frequency, the maximum EAB reaches 5 GHz (11.9–16.9 GHz), and the comprehensive EAB is 10.8 GHz. Our results show that magnetic nanoparticles can regulate the electromagnetic parameters of carbon materials to a certain extent, and reasonable compounding can make them have better impedance matching and attenuation characteristics. [ABSTRACT FROM AUTHOR]

With the rapid development of the economy, energy demand is more urgent. Microbial fuel cells (MFCs) have the advantages of non-toxic, safety, and environmental protection, and are considered the ideal choice for the next generation of energy storage equipment. However, the slow kinetics of oxygen reduction reaction (ORR) on MFC air cathodes and the high cost of traditional platinum (Pt) catalysts hinder their practical application, so there is a need to develop efficient, low-cost, and stable electrocatalysts as alternatives. Recently, metal–organic framework (MOFs) has attracted wide attention in electrocatalysis. Electrocatalysts prepared by the nanocomposite of MOFs and carbon nanomaterials have multiple advantages, such as adjustable chemical properties, high specific surface area, and good electrical conductivity, which have been proven to be a promising electrocatalytic material. In this paper, the latest research progress of metal–organic frames (MOFs) and carbon nanocomposites is reviewed, and the preparation methods and modification of MOFs and carbon nanofibers, carbon nanotubes, and graphene composites are introduced, respectively, as well as their applications in MFC cathode. Finally, the main prospects of MOFs/carbon nanocomposite catalysts are put forward. [ABSTRACT FROM AUTHOR]

Key message: Chrysanthemum morifolium MYB3 factors are transcriptional activators for the regulation of flavonol biosynthesis. Flavonol was not only the critical secondary metabolite participating in the growth and development of plants but also the main active ingredient in medicinal chrysanthemum. However, few pieces of research revealed the transcriptional regulation of flavonol biosynthesis in Chrysanthemum morifolium. Here, we isolated two CmMYB3 transcription factors (CmMYB3a and CmMYB3b) from the capitulum of Chrysanthemum morifolium cv 'Hangju'. According to the sequence characteristics, the CmMYB3a and CmMYB3b belonged to the R2R3-MYB subgroup 7, whose members were often reported to regulate flavonol biosynthesis positively. CmMYB3a and CmMYB3b factors were identified to localize in the nucleus by subcellular localization assay. Besides, both of them have obvious transcriptional self-activation activity in their C-terminal. After the overexpression of CmMYB3 genes in Nicotiana benthamiana and Arabidopsis thaliana, the flavonol contents in plants were increased, and the expression of AtCHS, AtCHI, AtF3H, and AtFLS genes in A. thaliana was also improved. Interestingly, the CmMYB3a factor had stronger functions in improving flavonol contents and related gene expression levels than CmMYB3b. The interaction analysis between transcription factors and promoters suggested that CmMYB3 could bind and activate the promoters of CmCHI and CmFLS genes in C. morifolium, and CmMYB3a also functioned more powerfully. Overall, these results indicated that CmMYB3a and CmMYB3b work as transcriptional activators in controlling flavonol biosynthesis. [ABSTRACT FROM AUTHOR]

The shapes of geological boundaries such as contacts and faults play a crucial role in the transportation, deposition and preservation of metals in magmatic and hydrothermal systems. Analyzing the shapes of geological boundaries, in particular those associated with mineralization, is an important step in 3D mineral prospectivity modeling. However, existing methods of shape analysis are limited in the adaptation of various shapes, scales and topologies of geological boundaries. This paper presents a general method of shape analysis based on mathematical morphology (MM), which is a generalization of the original MM method for shape analysis. The generalization extends the applicability of the original MM method from closed surfaces to general surfaces, while inheriting the real 3D and multi-scale analysis capabilities of the original method. This is achieved by regarding MM operations on 3D sphere structural elements as their equivalent operations, and redefining the operations to general surfaces. The generalized MM method enables us to handle complex 3D shapes such as overturned and/or recumbent geological boundaries as well as incomplete shapes due to weathering processes and data unavailability. The proposed method was applied to analyze the shape of an intrusive contact in the Fenghuangshan Cu ore field, Eastern China, whose shape was in the form of a non-closed surface. This analysis revealed a stronger spatial association between the large concave parts of the contact zone and the mineralization. Due to its enhanced adaptability to different shapes, the generalized MM method, compared with the original MM method, allows us to capture shape features that are more plausible for the geological setting. [ABSTRACT FROM AUTHOR]

The Xiadian orogenic deposit with ~ 100 t of gold resources, located in the Jiaodong Peninsula, Eastern China, shows an economically attractive gold mineralization that is spatially associated with the Zhaoping detachment fault. This study presents a combination of field investigation, 3D modeling, spatial analysis of models, and prospectivity modeling using a multi-layer perceptron deep neural network to understand the association between gold mineralization and structural deformation and to identify targets for deep exploration. The principal gold mineralization at Xiadian occurs as disseminated ore associated with strongly fractured rocks. Spatial analysis determined that gold mineralization is located primarily in convex segments (0–50 m) of the fault footwall within 150 m of the fault buffer where the dip is gentle (~ 35° to 55°). Sulfide vein ore with high Au grades is, by contrast, typically sited within steeply dipping fracture-fill distal to the Zhaoping detachment (150–250 m), consistently in areas with NE-strike and associated with steep segments of the detachment fault. The distribution of the orebodies is attributed to brittle–ductile deformation proximal to the detachment and distal brittle extension. Given the characteristics of syn-deformation mineralization and the stress regime (NW σ3, NE σ2, and vertical σ1), the NE-plunging ore shoots were interpreted as the result of auriferous fluid flow into oblique dilation zones formed by the coupled normal and dextral strike-slip movement of the Zhaoping fault. Six potential gold targets were identified sub-horizontal to, and NE-trending from, known orebodies. This study highlights the utility of 3D prospectivity modeling as a robust tool for understanding orogenic gold spatial distribution and related structural controls. [ABSTRACT FROM AUTHOR]

Diabetic peripheral neuropathy (DPN) is a chronic complication of diabetes, and its neural mechanisms underlying the pathogenesis remain unclear. Autophagy plays an important role in neurodegenerative diseases and nerve tissue injury. Lipin1 is a phosphatidic acid phosphatase enzyme that converts phosphatidic acid (PA) into diacylglycerol (DAG), a precursor of triacylglycerol and phospholipids which plays an important role in maintaining normal peripheral nerve conduction function. However, whether Lipin1 involved in the pathogenesis of DPN via regulation of autophagy is not elucidated. Here, we show that the Lipin1 expression was downregulated in streptozotocin (STZ)-induced DPN rat model. Interestingly, STZ prevented DAG synthesis, and resulted in autophagic hyperactivity, effects which may increase the apoptosis of Schwann cells and lead to demyelination in sciatic nerve in DPN rats. More importantly, upregulation of lipin1 in the DPN rats ameliorated autophagy disorders and pathological changes of the sciatic nerve, which associated with the increase of the motor nerve conductive velocity (MNCV) in DPN rats. In contrast, knockdown of lipin1 exacerbates neuronal abnormalities and facilitates the genesis of DPN phenotypes in rats. In addition, overexpression of lipin1 in RSC96 cells also significantly decreased the autophagic hyperactivity and apoptosis induced by hyperglycemia. These results suggest that lipin1 may exert neuroprotection within the sciatic nerve anomalies and may serve as a potential therapeutic target for the treatment of DPN. [ABSTRACT FROM AUTHOR]

Inhibition of α-glucosidase is considered as an effective approach to treat type 2 diabetes. Therefore, it is of great significance to study the inhibition of this enzyme. In the present study, the inhibitory activity of oleanolic acid (OA) on α-glucosidase and their interaction mechanism were investigated. The inhibition kinetic analysis showed that OA reversibly inhibited α-glucosidase activity in a mixed-type manner with an IC50 value of 3.04 ± 0.05 µM, and the inhibition followed a multi-phase kinetic process with a first-order reaction. The change of enthalpy and entropy indicated that the binding of OA to glucosidase was mainly driven by hydrophobic interaction and hydrogen bonding, and the binding distance was estimated at 3.51 nm. Synchronous fluorescence, circular dichroism (CD) and Fourier transform infrared spectra (FT-IR) showed that the binding of OA to α-glucosidase induced rearrangement and conformational changes of the enzymes. The molecular docking illustrated that OA entered the active center of α-glucosidase and interacted with the amino acid residues Asp-352 and ultimately inhibiting the enzyme activity. [ABSTRACT FROM AUTHOR]

Yavapaiite (KFe(SO)) is a new sulfate mineral with high potassium content, discovered in the oxidation zone of non-ferrous metal mining in the Tu-Ha Basin, Xinjiang Uygur Autonomous Region, northwestern China. Dating of this mineral by the K-Ar and Ar/Ar method allows us to study the time and process of the region's aridity, and further we can provide some insight into the influence of not only the Tibetan Plateau uplift but also formation and evolution of polar ice caps on climate of this region. However, as the temperature of this region is up to 60°C in summer, it is still questionable whether this high temperature causes the diffusive loss of Ar from yavapaiite in a long time, or whether the fine grain of the mineral can lead to diffusive loss of Ar from yavapaiite. These are important for interpreting the mineral age data. According to diffusion theory, we use Ar/Ar step heating experiment to determine the apparent Ar diffusivity. Then we present a simple model of diffusive loss and radiogenic in-growth to evaluate the effect of extreme high ambient temperature and the grain size upon the Ar age. The experimental results show that the diffusion parameters as follows: the activation energy E is 71.30 kcal/mol and the frequency factor log D/ a is 13.71/s, the corresponding closure temperature T is 294°C (assuming a cooling rate of 10°C/Ma), and the activation energy and closure temperature are very high. The simulation results show that the high ambient temperature and the grain size have no effect on the Ar age after yavapaiite was precipitated. Furthermore, the reproducibility of the age attests to the suitability of supergene yavapaiite for K-Ar and Ar/Ar dating. [ABSTRACT FROM AUTHOR]

The anion coordination complex, [Cl⊂Pt(bpt)4]Cl (bpt= N, N′-bis(3-pyridylmethyl)-2-thiourea), was synthesized and studied by X-ray crystal structure analysis, NMR and FAB mass spectra. In the solid state, the Pt(bpt)4 anion receptor adopts a cone conformation to bind the chloride anion through hydrogen bonds and electrostatic interaction in which the four branches of the thiourea ligands bind the chloride anion to form N-H⋯Cl− hydrogen bonds (3.49–3.81 Å). The entraped chloride anion is situated above the Pt(II) center at 3.52 Å. Further second-sphere coordination assemby from the Pt(bpt)4 core with 8 zinc(II) tetraphenylporphyrins (ZnPr) is discussed. [ABSTRACT FROM AUTHOR]

The complexes Co(BBP)Cl, Co(BBP)SO·HO, Co(BBP)(NO)·HO, Co(BBP)(ClO) and Co(BBP−H)· 2HO, where BBP is 2,6- bis(benzimidazol-2′-yl) pyridine, were prepared and characterized by elemental analysis, electrical conductance, i.r. and electronic spectra. The electrochemical behaviour of the complexes was recorded and the X-ray crystal structure of Co(BBP)Cl(MeOH) was determined. The geometry about cobalt is a distorted octahedron. [ABSTRACT FROM AUTHOR]

The deployment of wireless sensor networks, or WSNs, in industrial domains has attracted much attention over the past few years. An increasing number of applications have been developed such as for condition monitoring in the railway industry. Nevertheless, compared with traditional WSNs, the industrial environment is harsher, noisier, and more complex, which poses a higher requirement for the network security especially in terms of data trustiness and which further deters WSN practical integration in industrial applications. The main contribution of this research is to partially address the security issues by means of providing trusted data for industrial WSNs. To this end, a negative binomial distribution-based trust scheme combined with the D-S belief theory and a noise filter method is proposed and designed for industrial WSNs. In this paper, we first discuss the trust theory in WSNs and the disadvantages of traditional trust schemes for industrial applications, then analyze and evaluate the proposed method, and finally compare the performance of our method with some classic trust schemes. Through simulation tests about temperature readings of a factory workshop, it shows that the proposed method can improve the data trustiness, reliability, and robustness in the trust evaluation process under industrial environments and ensure the security of the network. [ABSTRACT FROM AUTHOR]

Carboxylic acid functionalized graphene oxide-copper (II) sulfide nanoparticle composite (GO-COOH-CuS) was prepared from carboxylated graphene oxide and copper precursor in dimethyl sulfoxide (DMSO) by a facile synthesis process at room temperature. The high-effective combination, the interaction between GO-COOH sheets and CuS nanoparticles, and the enhanced visible light absorption were confirmed by transmission electron microscopy (TEM), field emission scanning electron microscopy (FESEM), X-ray powder diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), thermo gravimetric analysis (TGA), X-ray photoelectron spectroscopy (XPS), UV-vis diffuse reflectance spectra (DRS) and Photoluminescence (PL) spectra. The as-synthesized GO-COOH-CuS nanocomposite exhibited excellent photocatalytic degradation performance of phenol and rhodamine B, high antibacterial activity toward E. coli and B. subtilis, and good recovery and reusability. The influence of CuS content, the synergistic reaction between CuS and GO-COOH, and the charge-transfer mechanism were systematically investigated. The facile and low-energy synthesis process combined with the excellent degradation and antibacterial performance signify that the GO-COOH-CuS has a great potential for water treatment application. [ABSTRACT FROM AUTHOR]

A novel copper(II) complex of mixed ligands 2-acetylpyridine and N-ethylene(2-acetylpyridineimine) has been prepared by condensation and its crystal structure determined by XRD. The central copper(II) atom of the complex anion is coordinated to one oxygen of 2-acetylpyridine and four nitrogen atoms of the Schiff base in a distorted square pyramidal geometry. It has a similar coordination geometry to that found in Cu/Zn-SOD. [ABSTRACT FROM AUTHOR]