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Building extraction aims to extract building pixels from remote sensing imagery, which plays a significant role in urban planning, dynamic urban monitoring, and many other applications. UNet3+ is widely applied in building extraction from remote sensing images. However, it still faces issues such as low segmentation accuracy, imprecise boundary delineation, and the complexity of network models. Therefore, based on the UNet3+ model, this paper proposes a 3D Joint Attention (3DJA) module that effectively enhances the correlation between local and global features, obtaining more accurate object semantic information and enhancing feature representation. The 3DJA module models semantic interdependence in the vertical and horizontal dimensions to obtain feature map spatial encoding information, as well as in the channel dimensions to increase the correlation between dependent channel graphs. In addition, a bottleneck module is constructed to reduce the number of network parameters and improve model training efficiency. Many experiments are conducted on publicly accessible WHU,INRIA and Massachusetts building dataset, and the benchmarks, BOMSC-Net, CVNet, SCA-Net, SPCL-Net, ACMFNet, MFCF-Net models are selected for comparison with the 3DJA-UNet3+ model proposed in this paper. The experimental results show that 3DJA-UNet3+ achieves competitive results in three evaluation indicators: overall accuracy, mean intersection over union, and F1-score. The code will be available at https://github.com/EnjiLi/3DJA-UNet3Plus. [ABSTRACT FROM AUTHOR]

Stone matrix asphalt and asphalt concrete mixture with 13.2 mm nominal maximum aggregate size (named SMA13 and AC13, respectively) are widely used in the surface course of asphalt pavement in China. Generally, the pavement performance of SMA13 is superior to that of AC13, while the cost of the former is significantly higher than that of the latter. The objective of this paper was to develop a new hot mix asphalt (named SMAC13) whose performance and cost are between SMA13 and AC13. A boundary sieve size (BSS) of 2.36 mm was selected between fine and coarse aggregates. Based on the union set of aggregate gradation ranges of SMA13 and AC13, the family of gradation curves in the forms of S shapes were designed in terms of the BSS passing rate. According to the evaluation of the skeleton interlock of coarse aggregate of the gradation curve family, the aggregate gradation range of SMAC13 was determined. Also, the performance of three kinds of asphalt mixtures were compared through laboratory tests. The results indicated that SMA13 shows the best rutting resistance, followed by SMAC13 then AC13, while in terms of low-temperature performance in resistance to cracking, the sequence is SMAC13, AC13, and SMA13. The sequence of water stability is AC13, SMAC13, and SMA13. Furthermore, the cost of SMAC13 is 25% less than that of SMA13. Therefore, SMAC13 can be used as an alternative for the surface course of asphalt pavement in terms of performance and cost. [ABSTRACT FROM AUTHOR]

Currently, the planting of 'Qi-Nan' is continuously increasing, yet a substantial amount of 'Qi-Nan' leaves have not been properly exploited. To improve the 'Qi-Nan' tree 's utilization value, 'Qi-Nan' leaves were used as a raw material. An ultrasound-assisted method was performed to obtain the flavonoids from the 'Qi-Nan' leaves, followed by optimization of the extraction factors using a one-way and response surface methodology to enhance the extraction of flavonoids. Subsequently, the composition of the flavonoids, as well as their bioactive abilities, were analyzed by ultra-high-performance liquid chromatography–mass spectrometry (UHPLC-MS) and in vitro activity testing methods. The findings demonstrated that a 1:50 material-to-liquid ratio, 60% ethanol concentration, and ultrasound-assisted extraction time of 30 min were the ideal procedures for extracting flavonoids (flavonoid content: 6.68%). Meanwhile, the 'Qi-Nan' leaves possessed the antioxidant and medicinal potential to prevent diabetes and Alzheimer 's disease, as evidenced by the semi-inhibitory concentrations (IC50 values) of flavonoid extracts for scavenging DPPH• free radicals, scavenging ABTS•+ free radicals, inhibiting acetylcholinesterase, and inhibiting α-glucosidase, which were 12.64 μg/mL, 66.58 μg/mL, 102.31 μg/mL, and 38.76 μg/mL, respectively, which indicated that the 'Qi-Nan' leaves possessed the properties of antioxidant and medicinal potential for the prevention of Alzheimer 's disease and diabetes. [ABSTRACT FROM AUTHOR]

Doxorubicin (DOX) is a broad-spectrum antineoplastic agent that widely used in clinic. However, its application is largely limited by its toxicity in multiple organs. Fibroblast growth factor 1 (FGF1) showed protective potential in various liver diseases, but the role of endogenous FGF1 in DOX-induced liver damage is currently unknown. Both wild-type (WT) and FGF1 knockout (FGF1-KO) mice were treated with DOX. DOX induced loss of body weight and liver weight and elevation of ALT and AST in WT mice, which were aggravated by FGF1 deletion. FGF1 deletion exacerbated hepatic oxidative stress mirrored by further elevated 3-nitrosative modification of multiple proteins and malondialdehyde content. These were accompanied by blunted compensatively antioxidative responses indicated by impaired upregulation of nuclear factor erythroid 2-related factor 2 and its downstream antioxidant gene expression. The aggravated oxidative stress was coincided with exacerbated cell apoptosis in DOX-treated FGF1-KO mice reflected by further increased TUNEL positive cell staining and BCL-2-associated X expression and caspase 3 cleavage. These detrimental changes in DOX-treated FGF1-KO mice were associated with worsened intestinal fibrosis and increased upregulation fibrotic marker connective tissue growth factor and α-smooth muscle actin expression. However, DOX-induced hepatic inflammatory responses were not further affected by FGF1 deletion. These results demonstrate that endogenous FGF1 deficiency aggravates DOX-induced liver damage and FGF1 is a potential therapeutic target for treatment of DOX-associated hepatoxicity. [ABSTRACT FROM AUTHOR]

Dielectric microspheres naturally possess unique optical properties by which the light's focus and confinement can be manipulated on a microscale. Combining microspheres and optical or Raman microscopy, super‐resolution imaging beyond the diffraction limit and enhancement of Raman signals are demonstrated to provide abundant spectroscopic information on materials. However, microsphere‐aided super‐resolution scanning photocurrent imaging remains challenging to date. Here, based on the photonic nanojet mechanism, a super‐resolution photocurrent and spectral microscopy equipped with a scanning tip with silica dielectric microspheres are presented. With such microsphere‐aided microscopy, order of magnitude enhancements for single‐point Raman and photoluminescence signals can be achieved, and the spatial resolutions for photocurrent and spectral mapping surpass the best resolution of the original confocal system restricted by the diffraction limit. This versatile system enables correlative super‐resolution spectral and photocurrent imaging, serving as a reliable tool for comprehensively understanding and uncovering the optoelectronic properties of materials. [ABSTRACT FROM AUTHOR]

This study examines the impact of bio-organic fertilizers on the physiological characteristics and leaf nutrient content of "Qi-Nan" agarwood seedlings. The aim is to provide a theoretical foundation for the efficient cultivation of "Qi-Nan". The experiment was conducted under field conditions using a Randomized complete block design. The control group received no fertilization, while the three fertilizer-treated groups received vermicompost, sheep manure, or microbial organic fertilizer. The results indicate that the application of bio-organic fertilizer significantly promoted the growth of plant height and diameter, increased the contents of soluble proteins, soluble sugar, chlorophyll, and leaf nutrients; and decreased the contents of free proline, peroxidase, malondialdehyde, and other stress indices. Redundancy analysis showed that the main factors affecting the seedlings height and diameter were free proline, chlorophyll, total nitrogen, and total potassium. Principal component analysis and membership function analysis revealed significant variations in growth, physiological characteristics, and nutrient content among the three fertilizer groups and the control group, with vermicompost > microbial organic fertilizer > sheep manure > no fertilization. In conclusion, biological organic fertilizer significantly promotes the growth of "Qi-Nan" seedlings, and vermicompost is the most effective fertilizer in this experiment. [ABSTRACT FROM AUTHOR]

Continuous innovation in artificially-induced agarwood technology is increasing the amount of agarwood and substantially alleviating shortages. Agarwood is widely utilized in perfumes and fragrances; however, it is unclear whether the overall pharmacological activity of induced agarwood can replace wild agarwood for medicinal use. In this study, the volatile components, total chromone content, and the differences in the overall activities of wild agarwood and induced agarwood, including the antioxidant, anti-acetylcholinesterase, and anti-glucosidase activity were all determined. The results indicated that both induced and wild agarwood's chemical makeup contains sesquiterpenes and 2-(2-phenylethyl)chromones. The total chromone content in generated agarwood can reach 82.96% of that in wild agarwood. Induced agarwood scavenged 1,1-diphenyl-2-picrylhydrazyl (DPPH) radicals and 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS+) radicals and inhibited acetylcholinesterase activity and α-glucosidase activity with IC50 values of 0.1873 mg/mL, 0.0602 mg/mL, 0.0493 mg/mL, and 0.2119 mg/mL, respectively, reaching 80.89%, 93.52%, 93.52%, and 69.47% of that of wild agarwood, respectively. Accordingly, the results distinguished that induced agarwood has the potential to replace wild agarwood in future for use in medicine because it has a similar chemical makeup to wild agarwood and has comparable antioxidant, anti-acetylcholinesterase, and anti-glucosidase capabilities. [ABSTRACT FROM AUTHOR]

Learning discriminative features is of vital importance for automatic facial expression recognition (FER) in the wild. In this article, we propose a novel Slide-Patch and Whole-Face Attention model with SE blocks (SPWFA-SE), which jointly perceives the discriminative locality characteristics and informative global features of the face for effective FER. Specifically, the well-designed slide patches are proposed to extract local features. Different from the existing methods, our slide patches not only can maintain the information at the edge area of patches, but also do not need to detect facial landmarks. Moreover, to make the model adaptively focus on the distinguishable regions, an attention module is proposed in the patch level to learn the weight of each patch. Furthermore, squeeze-and-excitation blocks are explored in the channel level to learn the weight of each channel. As such, the proposed multi-level feature extraction and attention mechanisms can enhance the representative ability of the learned features. Extensive experiments on five challenging datasets demonstrate that our method can achieve state-of-the-art performance. Cross database experiments on another three databases show the superior generalization performance of our model. Furthermore, complexity analysis results show that our model contains fewer parameters with fast training advantages than other competing models. [ABSTRACT FROM AUTHOR]

The impairment in endothelial progenitor cell (EPC) functions results in dysregulation of vascular homeostasis and dysfunction of the endothelium under diabetic conditions. Improving EPC function has been considered as a promising strategy for ameliorating diabetic vascular complications. Liraglutide has been widely used as a therapeutic agent for diabetes. However, the effects and mechanisms of liraglutide on EPC dysfunction remain unclear. The capability of liraglutide in promoting blood perfusion and angiogenesis under diabetic conditions was evaluated in the hind limb ischemia model of diabetic mice. The effect of liraglutide on the angiogenic function of EPC was evaluated by cell scratch recovery assay, tube formation assay, and nitric oxide production. RNA sequencing was performed to assess the underlying mechanisms. Liraglutide enhanced blood perfusion and angiogenesis in the ischemic hindlimb of db/db mice and streptozotocin-induced type 1 diabetic mice. Additionally, liraglutide improved tube formation, cell migration, and nitric oxide production of high glucose (HG)-treated EPC. Assessment of liraglutide target pathways revealed a network of genes involved in antioxidant activity. Further mechanism study showed that liraglutide decreased the production of reactive oxygen species and increased the activity of nuclear factor erythroid 2-related factor 2 (Nrf2). Nrf2 deficiency attenuated the beneficial effects of liraglutide on improving EPC function and promoting ischemic angiogenesis under diabetic conditions. Moreover, liraglutide activates Nrf2 through an AKT/GSK3β/Fyn pathway, and inhibiting this pathway abolished liraglutide-induced Nrf2 activation and EPC function improvement. Overall, these results suggest that Liraglutide represents therapeutic potential in promoting EPC function and ameliorating ischemic angiogenesis under diabetic conditions, and these beneficial effects relied on Nrf2 activation. [ABSTRACT FROM AUTHOR]

Facial Expression Recognition (FER) is a long-standing but challenging research problem in computer vision. Existing approaches mainly focus on single-label emotional prediction, which cannot handle the complex multi-label FER task because of the coupling behavior of multiple emotions on a single facial image. To this end, in this paper, we propose a novel Self-supervised Exclusive-Inclusive Interactive Learning (SEIIL) method to facilitate discriminative multi-label FER in the wild, which can effectively handle the coupled multiple sentiments with limited unconstrained training data. Specifically, we construct an emotion disentangling module to capture the inclusive and exclusive characteristics of facial expressions, which can decouple the compound numerous emotions on an image. Moreover, an adaptively-weighted ensemble technique is conceived to aggregate category-level latent exclusive embeddings, and then a conditional adversarial interactive learning module is designed to fully leverage the complementary between the inclusive and formulated latent representations. Furthermore, to tackle the insufficient data for training, we introduce a self-supervised learning strategy to augment the amount and diversity of facial images, which can endow the model with advanced generalization ability. Under this strategy, the proposed two modules can be concurrently utilized in our SEIIL to jointly handle the coupled emotions and alleviate the overfitting problem. Extensive experimental results on six databases illustrate the superb performance of our method against state-of-the-art baselines. [ABSTRACT FROM AUTHOR]

The informativeness and discriminativeness of features collaboratively ensure high-accuracy Facial Expression Recognition (FER) in the wild. Most of existing methods use the single-path deep convolutional neural network with softmax loss for basic FER, while they cannot deal with the challenging situations of the compound FER in the wild, because they fail to learn informative and discriminative features in a targeted manner. To this end, we present an Informative and Discriminative Feature Learning (IDFL) framework that consists of two key components: the Multi-Path Attention Convolutional Neural Network (MPACNN) and Balanced Separate loss (BS loss), for both basic and compound high-accuracy FER in the wild. Specifically, MPACNN leverages different paths to learn diverse features. These features are then adaptively fused into informative ones via an attention module, such that the model can adequately capture detailed information for both basic and compound FER. The BS loss maximizes the inter-class distance of features and minimizes the intra-class one. In this way, the features are discriminative enough for high-accuracy FER in the wild. Particularly, the BS loss is invoked as the objective function of MPACNN, so the model can learn informative and discriminative features at the same time, yielding better performance. Seven databases are utilized to evaluate the proposed method, and the results demonstrate that our method achieves state-of-the-art performance on both basic and compound expressions with good generalization ability. Moreover, our model contains fewer parameters and can be trained faster than other related models. [ABSTRACT FROM AUTHOR]

Automated multi-label chest X-ray (CXR) image classification has recently made significant progress in clinical diagnosis based on the advanced deep learning techniques. However, most existing methods mainly focus on analyzing locality visual cues from a single image but fail to leverage the underlying explicit correlations among different images for precise disease diagnosis. By contrast, an experienced radiologist expertizes in transferring knowledge from previous tasks to diagnose the present radiograph. To enable the machine like a radiologist, this paper proposes a novel Semantic Similarity Graph Embedding (SSGE) framework, which explicitly explores the semantic similarities among images to optimize the visual feature embedding for improving the performance of multi-label CXR images classification. Specifically, the proposed SSGE framework contains three main components: the image feature embedding (IFE) module, similarity graph construction (SGC) module, and semantic similarity learning (SSL) module. To realize interactive teaching and learning between visual and semantic information, the proposed SSGE framework is built on the “Teacher-Student” (semantic-visual) learning mechanism. With the guidance and supervision of the cross-image similarity graph generated by the SGC module, the SSL module leverages Graph Convolutional Network (GCN) to adaptively recalibrate the multi-image feature representations extracted from the IFE module, which guarantees their semantic consistency. Furthermore, we propose a novel re-weighting strategy to learn a more optimal semantic-similarity graph for the information propagation of the GCN layers. Extensive experiments on two benchmark datasets demonstrate the effectiveness of the proposed method in comparison with some state-of-the-art baselines. [ABSTRACT FROM AUTHOR]

Berberine (BBR), an important quaternary benzylisoquinoline alkaloid, has been used in Chinese traditional medicine for over 3,000 years. BBR has been shown in both traditional and modern medicine to have a wide range of pharmacological actions, including hypoglycemic, hypolipidemic, anti-obesity, hepatoprotective, anti-inflammatory, and antioxidant activities. The unregulated reaction chain induced by oxidative stress as a crucial mechanism result in myocardial damage, which is involved in the pathogenesis and progression of many cardiovascular diseases (CVDs). Numerous researches have established that BBR protects myocardium and may be beneficial in the treatment of CVDs. Given that the pivotal role of oxidative stress in CVDs, the pharmacological effects of BBR in the treatment and/or management of CVDs have strongly attracted the attention of scholars. Therefore, this review sums up the prevention and treatment mechanisms of BBR in CVDs from in vitro , in vivo , and finally to the clinical field trials timely. We summarized the antioxidant stress of BBR in the management of coronary atherosclerosis and myocardial ischemia/reperfusion; it also analyzes the pathogenesis of oxidative stress in arrhythmia and heart failure and the therapeutic effects of BBR. In short, BBR is a hopeful drug candidate for the treatment of CVDs, which can intervene in the process of CVDs from multiple angles and different aspects. Therefore, if we want to apply it to the clinic on a large scale, more comprehensive, intensive, and detailed researches are needed to be carried out to clarify the molecular mechanism and targets of BBR. [ABSTRACT FROM AUTHOR]

The object of this study is the wood of Phoebe bournei (Hemsl.) Yang. Firstly, the macroscopic and microscopic structural characteristics of P. bournei wood were studied, and then the wood was compared with other species of the same genus. Through GC-MS technology, the volatile substance composition of P. bournei wood was studied, and the common volatile substance compositions were analyzed by using correlation analysis, principal component analysis (PCA), and orthogonal partial least square discriminant model analysis (OPLS-DA) models. The purpose of this study was to determine the significantly different components of P. bournei wood in comparison to three similar species in the same genus and explore whether these can be used as a chemical pattern recognition method for this wood. The results showed that 11 common components were found in all the P. bournei wood samples. Through the correlation analysis between the samples of P. bournei from different sources, they had a strong interrelation and high correlation coefficient. P. bournei wood could be initially distinguished from the wood of the other three similar species of the same genus by PCA. Through OPLS-DA modeling and calculation the classification effect of the model was more obvious. The variable information used to analyze the experimental model was more complete, and the model had a strong prediction ability. With the combination of the load diagram (S-plot) and variable contribution index (VIP), variable components were preliminarily screened, and then inter-group t-test and variable content analysis were conducted for the samples. The results show that the OPLS-DA model analysis of valerianol and agarspirol has obvious differences, which can be used to distinguish wood of P. bournei from three other tree species of the same genus. [ABSTRACT FROM AUTHOR]

Most film coatings in the pharmaceutical industry are prepared using organic solvents or aqueous solvents. Due to different film-formation mechanisms, their properties are significantly different from each other. Curing can alter the microstructure of films by improving the coalescence of polymer particles for aqueous dispersion-based films or accelerating macromolecule relaxation for organic solvent-based films. The aim of this study was to investigate the effects of preparation methods and curing on the physicochemical properties of Kollicoat® SR30D and Kollicoat® MAE100P films. The film’s properties, including water diffusion coefficient, mechanical properties, plasticizer loss, swelling behavior, and contact angle, were measured for uncured or cured aqueous dispersion-based or organic solvent-based films. The results indicated that curing decreased water diffusivities in films and increased film’s tensile strength. Curing resulted in plasticizer loss from SR30D films but not from MAE100P films due to strong interaction between plasticizer and MAE100P. The surface of organic solvent-based films was more hydrophobic than that of aqueous dispersion-based films. The contact angle of organic solvent-based films was increased after curing possibly because curing decreased roughness of the film surface. Organic solvent-based SR30D films had better mechanical properties than the corresponding aqueous dispersion-based films because of higher degree of polymer-polymer entanglement in the organic solvent-based films. However, contradictory phenomena were observed in MAE100P films possibly due to a “core-shell” structure reserved in the aqueous dispersion-based MAE100P films. In summary, casting methods and curing have significant impact on the film properties due to different film structures, coalescence, or film relaxation, and other concurrent effects including evaporation of residue solvent and plasticizers. [ABSTRACT FROM AUTHOR]

This paper focuses on the input-to-state stability for a general class of stochastic multi-group models with multi-dispersal. By incorporating graph theory with Lyapunov method as well as stochastic analysis techniques, novel sufficient criteria are derived, which are in the form of Lyapunov-type theorem and coefficient-type criterion, respectively. Moreover, to show the applicability of our findings, we employ coefficient-type criterion to analyze the input-to-state stability for stochastic coupled oscillators. Finally, a numerical example and its simulations are offered to demonstrate the validity and feasibility of the theoretic results. [ABSTRACT FROM PUBLISHER]

Background In most patients, acute kidney injury (AKI) represents the combined effects of ischemic, toxic and inflammatory insults. No effective pharmacologic interventions have been developed to prevent AKI or to improve outcomes to date. Cyclosporine A (CsA) is a calcineurin inhibitor that mediates T-cell receptor signaling, suppresses inflammatory cytokine expression and inhibits leukocyte migration. It is also a potent inhibitor of mitochondrial permeability, protecting cells from death. These properties make it a potentially valuable drug to prevent or treat AKI. It does, however, carry a significant risk of nephrotoxicity, especially with chronic use. By contrast, a single dose of CsA may be protective while limiting the risk of nephrotoxicity. Methods We conducted a controlled animal experiment in male CD-1 mice. Specifically, mice were subjected to folic acid (FA)-induced AKI and then randomly assigned to sham operation or one of three dosage of CsA treatment groups. Results Intraperitoneal injection of FA consistently induced AKI. Serum interleukin (IL)-6 and urinary neutrophil gelatinase-associated lipocalin (NGAL) rose 1 day after FA injection. Compared to sham treatment, one dose (1 and 5 mg/kg body weight) of CsA significantly reduced kidney tubular cell apoptosis, serum creatinine, blood urea, serum IL-6 and urinary NGAL 2 days after FA injection. It was also shown to block the inflammatory mediator tumor necrosis factor (TNF)-like weak inducer of apoptosis (TWEAK) expression, nuclear factor kappa-B (NFκB) activation, inflammatory cell infiltration and interstitial fibrosis 14 days after treatment in a dose-dependent fashion. By contrast, a dose of 10 mg/kg body weight CsA resulted in nephrotoxicity in the setting of FA-induced AKI. Conclusions A single dose of CsA, currently used for organ transplant, significantly protects mice from FA-induced AKI, presumably through inhibition of cell death, inflammatory reaction, interstitial cell infiltration and fibrosis. The protective effects have the potential to open a completely new line of investigation in the prevention and treatment of AKI. [ABSTRACT FROM AUTHOR]

In this study, we analyzed the mechanism and the process of fungal-induced agarwood formation in Aquilaria sinensis and studied the functional changes in the xylem structure after the process. The microscopic structure of the white zone, transition zone, agarwood zone, and decay zone of 12-and 18-months of inoculation A. sinensis xylem was studied. The distribution of nuclei, starch grains, soluble sugars, sesquiterpenes, fungal propagules, and mycelium in xylem tissues was investigated by histochemical analysis. The results show that the process of agarwood formation was accompanied by apoptosis of parenchyma cells such as interxylary phloem, xylem rays, and axial parenchyma. Regular changes in the conversion of starch grains to soluble sugars, the production of sesquiterpenoids, and other characteristic components of agarwood in various types of parenchyma cells were also observed. The material transformation was concentrated in the interxylary phloem, providing a structural and material basis for the formation of agarwood. It is the core part of the production of sesquiterpenoids and other characteristic products of agarwood. Compared with the A. sinensis inoculated for 12 months, the xylem of the A. sinensis inoculated for 18 months was more vigorous. There were no significant differences between the 12 and 18 months of inoculation in terms of sugars and agarwood characteristic products. In production, harvesting after 12 months of inoculation can improve harvesting efficiency. [ABSTRACT FROM AUTHOR]

The main stem oil constituents include elemicin (39.9%), methyl eugenol (14.3%), benzaldehyde (12.0%), cinnamaldehyde, and ( I E i )-(8.9%) and ( I Z i )-methyl isoeugenol (6.1%), see Table 1. The main components are elemicin and methyl eugenol [[4]]. [Extracted from the article]

Agarwood is a highly economically important medicinal herb with widespread uses; however, the difference between the biological activities of artificial and wild agarwood is unclear. In this study, the alcohol-soluble extracts of agarwood produced by fungi and natural agarwood were used to determine the differences between the overall biological activities. The antioxidant ability (the clearance rates of 1,1-diphenyl-2-picrylhydrazyl (DPPH) and 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS+) radicals, and total reducing power), anti-acetylcholinesterase, and anti-α-glucosidase activity were determined by ultraviolet-visible spectrophotometry. The results indicated that with 2 mg/mL alcohol-soluble extracts, the scavenging DPPH radical rates of the artificial agarwood samples were 93.74–102.31% of that of the wild agarwood, and the ABTS+ radical clearance rates of the artificial agarwood samples were 75.38–95.52% of that of the natural agarwood. With 3.5 mg/mL alcohol-soluble extracts, the artificial agarwood samples had a total reducing power of 63.07–80.29% of that of the wild agarwood. With 4 mg/mL alcohol-soluble extract, the acetylcholinesterase activity inhibition rates of the artificial agarwood samples were 102.56–109.16% of that of the wild agarwood. With 1 mg/mL alcohol soluble extracts, the α-glucosidase effect inhibitions rates of the artificial agarwood samples were 68.32–100.39% of that of the wild agarwood. [ABSTRACT FROM AUTHOR]

Heartwood has a high economic value because of its natural durability, beautiful color, special aroma, and richness in active ingredients used in traditional Chinese medicine. However, the mechanism of heartwood formation remains unclear. Dalbergia odorifera was selected as the object of research to analyze this variation in the chemical composition of sapwood, transition zone, and heartwood as well as to elucidate the relationship between this variation and the formation of heartwood. The variation of secondary metabolites was analyzed using gas chromatography-mass spectrometry and ultra-high performance liquid chromatography–mass spectrometry, the variation of lignin was analyzed using Fourier transform infrared spectroscopy and ultraviolet visible spectrophotometry, and the variation law of mineral elements was analyzed using atomic absorption spectrophotometry. The results demonstrated that contents of characteristic secondary metabolites in Dalbergia odorifera were mainly distributed in heartwood (84.3–96.8%), increased from the outer to inner layers of the xylem, and sudden changes occurred in the transition zone (the fourth growth ring). The Dalbergia odorifera lignin can be identified as typical "syringyl–guaiacyl (S–G)" lignin, and the color darkened from the outside to the inside. The results demonstrated that there were more benzene rings and conjugated C=O structures in the heartwood. Additionally, the variation of minerals in the xylem was related to elemental types; the average concentrations of Mg, Ca, Fe and Sr were higher in the heartwood than in the sapwood, whereas the concentrations of K and Zn were higher in the sapwood than in the heartwood owing to the reabsorption of elements. The concentrations of Na and Cu were similar in the heartwood and sapwood. The composition and structural characteristics of secondary metabolites, lignin, and mineral elements in the three typical xylem regions (sapwood, transition zone and heartwood) of Dalbergia odorifera changed. The most abrupt change occurred in the narrow xylem transition zone, which is the key location involved in heartwood formation in Dalbergia odorifera. [ABSTRACT FROM AUTHOR]