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Imbalances in bone formation and resorption cause osteoporosis. Mounting evidence supports that brain-derived neurotrophic factor (BDNF) implicates in this process. 7,8-Dihydroxyflavone (7,8-DHF), a plant-derived small molecular TrkB agonist, mimics the functions of BDNF. We show that both BDNF and 7,8-DHF promoted the proliferation, osteogenic differentiation, and mineralization of MC3T3-E1 cells. These effects might be attributed to the activation of the Wnt/β-catenin signaling pathway as the expression of cyclin D1, phosphorylated-glycogen synthase kinase-3β (p-GSK3β), β-catenin, Runx2, Osterix, and osteoprotegerin (OPG) was all significantly up-regulated. Knockdown of β-catenin restrained the up-regulation of Runx2 and Osterix stimulated by 7,8-DHF. In particular, blocking TrkB by its specific inhibitor K252a suppressed 7,8-DHF-induced osteoblastic proliferation, differentiation, and expression of osteoblastogenic genes. Moreover, BDNF and 7,8-DHF repressed osteoclastic differentiation of RAW264.7 cells. The transcription factor c-fos and osteoclastic genes such as tartrate-resistant acid phosphatase (TRAP), matrix metalloprotein-9 (MMP-9), Adamts5 were inhibited by 7,8-DHF. More importantly, 7,8-DHF attenuated bone loss, improved trabecular microarchitecture, tibial biomechanical properties, and bone biochemical indexes in an ovariectomy (OVX) rat model. The current work highlights the dual regulatory effects that 7,8-DHF exerts on bone remodeling.

Objective: 7,8-Dihydroxyflavone (7,8-DHF), a small molecular mimetic of brain-derived neurotrophic factor (BDNF), alleviates high-fat diet-induced obesity in female mice in a sex-specific manner by activating muscular tropomyosin-related kinase B (TrkB). However, the underlying molecular mechanism for this sex difference is unknown. Moreover, muscular estrogen receptor α (ERα) plays a critical role in metabolic diseases. Impaired ERα action is often accompanied by metabolic syndrome (MetS) in postmenopausal women. This study investigated whether muscular ERα is involved in the metabolic effects of 7,8-DHF. Methods: For the in vivo studies, 72 female C57BL/6J mice were given a low-fat diet or high-fat diet, and both received daily intragastric administration of vehicle or 7,8-DHF for 24 weeks. The hypothalamic-pituitary-ovarian (HPO) axis function was assessed by investigating typical sex-related serum hormones and the ovarian reserve. Indicators of menopausal MetS, including lipid metabolism, insulin sensitivity, bone density, and serum inflammatory cytokines, were also evaluated. The expression levels of ERα and other relevant signaling molecules were also examined. In vitro, the molecular mechanism involved in the interplay of ERα and TrkB receptors was verified in differentiated C2C12 myotubes using several inhibitors and a lentivirus short hairpin RNA-knockdown strategy. Results: Long-term oral administration of 7,8-DHF acted as a protective factor for the female HPO axis function, protecting against ovarian failure, earlier menopause, and sex hormone disorders, which was paralleled by the alleviation of MetS coupled with the production of ERα-rich, TrkB-activated, and uncoupling protein 1 (UCP1) high thermogenic skeletal muscle tissues. 7,8-DHF-stimulated transactivation of ERα at serine 118 (S118) and tyrosine 537 (Y537), which was crucial to activate the BDNF/TrkB signaling cascades. In turn, activation of BDNF/TrkB signaling was also required for the ligand-independent activation of ERα, especially at the Y537 phosphorylation site. In addition, Src family kinases played a core role in the interplay of ERα and TrkB, synergistically activating the signaling pathways related to energy metabolism. Conclusions: These findings revealed a novel role of 7,8-DHF in protecting the function of the female HPO axis and activating tissue-specific ERα, which improves our understanding of this sex difference in 7,8-DHF-mediated maintenance of metabolic homeostasis and provides new therapeutic strategies for managing MetS in women.

The use of bamboo leaf flavonoids (BLF) as functional food and cosmetic ingredients is limited by low bioavailability and difficulty in being absorbed by the intestine or skin. The aim of this study was to prepare BLF-loaded alginate-chitosan coated nanoliposomes (AL-CH-BLF-Lip) to overcome these challenges. The nanocarriers were characterized by dynamic light scattering, high performance liquid chromatography, Fourier transform infrared spectroscopy and differential scanning calorimetry. The biological activity was analyzed by in vitro antioxidant activity, transdermal absorption, cytotoxicity and AAPH induced HaCaT cell senescence model. The results showed that the size of nanocarriers ranged from 152.13 to 228.90 nm and had a low polydispersity index (0.25–0.36). Chitosan (CH) and alginate (AL) were successfully coated on BLF-loaded nanoliposomes (BLF-Lip), the encapsulation efficiency of BLF-Lip, BLF-loaded chitosan coated nanoliposomes (CH-BLF-Lip) and AL-CH-BLF-Lip were 71.31%, 78.77% and 82.74%, respectively. In addition, BLF-Lip, CH-BLF-Lip and AL-CH-BLF-Lip showed better in vitro release and free radical scavenging ability compared with naked BLF. In particular, the skin permeability of BLF-Lip, CH-BLF-Lip, and AL-CH-BLF-Lip increased 2.1, 2.4 and 2.9 times after 24 h, respectively. Furthermore, the use of nanoliposomes could significantly improve the anti-senescence activity of BLF (p < 0.01). Conclusively, alginate-chitosan coated nanoliposomes are promising delivery systems for BLF that can be used in functional foods and cosmetics.

Low bioavailability and stability of 7,8-dihydroxyflavone (7,8-DHF) hinder its potential application in prevention of humans’ disease. 7,8-DHF loaded nanoliposomes decorated by original, crosslinked and glycosylated lactoferrin (LF) were fabricated. The mean particle size of spherical crosslinked and glycosylated LF coating liposomes were larger than uncoated liposomes with a low polydispersity index, and the former had higher encapsulation efficiency (Above 98%). Crosslinked and glycosylated LF coating liposomes had higher antioxidant activity, storage stability, slow-release ability, bioaccessibility and transepithelial transport compared to free 7,8-DHF and 7,8-DHF loaded liposome. Effective hydrogen bonding between phospholipid and 7,8-DHF, while electrostatic interaction and hydrogen bonding between LF proteins and phospholipid existed. The encapsulated 7,8-DHF was in an amorphous state rather than a crystalline form as detected by differential scanning calorimetry. Collectively, crosslinked or glycosylated LF coating liposomes are promising delivery systems for protecting and transporting 7,8-DHF or other relative bioactive components.

With the global escalation of the aging process, the research on aging mechanisms and anti-aging strategies has become a hot spot. As the most external organ of the human body, skin can be used as an ideal organ for the study of endogenous and exogenous aging. Bamboo leaf flavonoids (BLF) possess a variety of biological effects such as antioxidant, anti-bacterial, anti-inflammatory, lipid-lowering, anti-radiation, and anti-aging. However, it is still unclear whether they can delay skin aging. This study aimed to analyze the inhibitory effect of BLF on skin aging and explore their molecular mechanisms. We found that 10–40 μg/mL BLF significantly inhibited the senescence of HaCaT cells induced by AAPH, which might be related to their antioxidant and anti-inflammatory abilities. Further mechanism studies showed that mitogen-activated protein kinase (MAPK), especially the p38 MAPK pathway, was the key to BLF to alleviate the senescence of HaCaT cells. In addition, autophagy was also involved in the anti-senescence effect of BLF. The results were also verified in UVB-induced photoaging mice. Therefore, BLF can be used as a potential therapeutic agent to intervene skin aging in vitro and in vivo.

In the current study, further chemical investigation of the fruiting bodies of Fomes officinalis led to isolate seven new 24-methyl-lanostane triterpenoids, named officimalonic acids I−O (1–7). Their structures were elucidated based on the analysis of spectroscopic data (HR-MS, 1D and 2D NMR, UV, IR). Compounds 1−3 possessed an unusual C-23 spirostructure moiety, while compounds 4−7 had 23,26-lactone unit. Anti-inflammatory assay revealed that compounds 3 and 5 exhibited significant inhibitory activities against NO production in LPS-induced RAW 264.7 cells and cyclooxygenase (COX-2).

Knowing how functional diversity varies across environmental gradients is crucial in investigating biodiversity formation and community assembly processes. The majority of studies concerning functional diversity are based on one fixed plot size, resulting in weakened sensitivity of the spatial patterns to sampling resolution. This weakness may obscure the true mechanisms behind community assemblage. In this study, we utilized hyperspectral imagery collected by Orbita hyperspectral satellites (OHS) to explore the spatial distribution patterns of functional traits and diversity in alpine meadows at four sampling radii (25 m, 50 m, 100 m, 200 m). We examined how functional traits and their diversity responded to variations in climatic and soil conditions at different sampling resolutions. Our findings revealed a significant influence of solar radiation and soil depth on the patterns of functional traits in alpine meadows. Scale dependency was evident in the functional richness (FRic), functional evenness (FEve), and functional dispersion (FDis) of different traits, indicated by a notable difference from the null model. In the presence of stronger soil nutrient and water limitation, chlorophyll a content (CAC), specific leaf area (SLA), leaf thickness (LT), and plant height (Height) exhibited increased clustering and convergence at larger sampling resolutions, illustrating environmental filtering in habitat patch assembly in the alpine meadow. For the first time, this study explores scale dependency in functional diversity patterns in alpine meadows using satellite-based hyperspectral imagery. It unveils the environmental filtering effect of soil nutrient limitation on shaping vegetation patch structures at a landscape level from a remote sensing perspective. The study underscores the significance of accounting for sampling resolution in future related research.

Climate variability is an important factor leading to spatial and temporal changes in structure and functions of plant communities. Exploring the temporal stability of communities in response to climate variability is essential for further evaluating the impacts of climate change to ecosystem functions and services. Current research on climate variability mainly focuses on plot-scale experiments (alpha scale), while how it impacts the long-term stability of a metacommunity (gamma scale) still needs further study. We analyzed the effects of climate variability on the temporal stability of plant communities at alpha and gamma scales based on a long-term observation of plant cover from 1938 to 1968 in a mixed-grass prairie in Kansas, western United States. The results demonstrated that precipitation variability strengthened alpha and gamma stability of plant cover, while the temporal mean of temperature has opposite effects on them. Precipitation variability enhanced alpha stability directly and indirectly by increasing species asynchrony, though its positive effects were weak. Alpha stability combined with spatial asynchrony further promoted gamma stability. We therefore concluded that precipitation variability had a weak but significant stabilizing effect on community structure. These findings reveal the role of precipitation variability in temporal stability of community structure at alpha and gamma scales over decades, which could contribute to a more comprehensive understanding of the conservation of biodiversity and ecosystem functioning under the future climate change. Our study emphasized that both temporal mean and standard variation of climate should be considered when exploring the effects of climate change on ecosystem functions.

Long-term and large scale spatiotemporal patterns of planted forests are essential for evaluating local plantation effectiveness and to promote sustainable afforestation. Satellite remote sensing data provide broad spatial coverage and increasingly long-term and large scale records for spatiotemporal analysis of planted forests. In this study, we developed a dynamic and conversion extraction (DCE) framework by combining the similarity of Landsat normalized difference vegetation index (NDVI) time-series with a change detection algorithm. This framework allows the analysis of spatiotemporal dynamics of planted forests. The proposed framework can be used to extract the planting year and conversion patterns of planted forests by performing the Mann-Kendall (MK) statistic test on the inter-annual Landsat NDVI time-series and measuring the similarity of the intra-annual time-series, respectively. Therefore, it can be applied to addressing the key questions on where, when, and how planted forests conversions have occurred. Took the Loess Plateau in China as an example, we applied the DCE framework to illustrate how planted forests have changed over time and space and have been converted from other land cover types from 1986 to 2021. The producer and user accuracies for the mapping of planted forests were 88.22% and 87.11% in 2021, respectively, and the accuracy of identifying planted forests conversions was 80.25%. The results showed that the newly planted forests experienced four phases: a slow rise from 1986 to 2000, a sharp increase during 2001–2004, a fluctuating pattern from 2005 to 2013, and a reduction until 2020, resulting in a total planted forest area of 7.13 Mha in 2021. In addition, 83.51% of the planted forest pixels underwent conversion from grasslands (58.19% or 4.15 Mha) or croplands (25.32% or 1.81 Mha) during 1986–2021. These results indicate the capability of the DCE framework to capture essential information (planting year and conversion patterns) to support the spatiotemporal analysis of planted forests at large scales.

A high-performance microwave absorber with simultaneously ultra-broadband microwave absorption, mechanical flexibility and high optical transparency is proposed. A patterned indium–tin–oxide (ITO) conductive metasurface is used as the upper surface resonance layer. ANSYS HFSS 15.0 was used for the infinite period structures of the absorber simulation, and the Floquet port, master-slave boundary condition and adaptive meshing were set in the software. As a result, the absorber features >90% broadband absorption, which covers a wide frequency range of 17.6 GHz (21.6-39.2 GHz) and includes part of the K and Ka frequency bands. What is more, the absorption is above 99% in the range from 30 GHz to 33.6 GHz. The optical transmittance of the absorber in the visible light band is 85%. The thickness of the absorber is only 0.1 times of the wavelength corresponding to the lowest absorption frequency (13.89 mm). Furthermore, the absorber maintains stable absorption at different incident and polarization angles due to the quadruple centrosymmetric pattern.

In this paper, a metamaterial absorber with a checkerboard patterned ITO (indium tin oxide) film as the surface is obtained by using flexible and optically transparent wave-absorbing material ITO–PET (polyethylene terephthalate), and a coding arrangement of two basic coding units based on the APS-PSO (Array Pattern Synthesis -Particle Swarm Optimization) algorithm. The surface structure of the absorber consists of ITO rectangular patch structures and ITO circular patch structures (110 Ω/sq). The ITO rectangular patch structures and ITO circular patch structures are symmetrical. The middle layer is made up of two layers of PET and one layer of PMMA, and the bottom surface is covered with a layer of low square resistance ITO film (8 Ω/sq). The experimental results, which are consistent with the simulation results, show that the absorber has superior performance: over 90% absorptance in the 5.06–9.01 GHz band, high transmittance, and a −10 dBsm RCS (radar cross-section) reduction in the 5.3–8.7 GHz band. This design also has polarization insensitivity and angular stability.

Plant functional traits at the community level (plant community traits hereafter) are commonly used in trait-based ecology for the study of vegetation–environment relationships. Previous studies have shown that a variety of plant functional traits at the species or community level can be successfully retrieved by airborne or spaceborne imaging spectrometer in homogeneous, species-poor ecosystems. However, findings from these studies may not apply to heterogeneous, species-rich ecosystems. Here, we aim to determine whether unmanned aerial vehicle (UAV)-based hyperspectral imaging could adequately estimate plant community traits in a species-rich alpine meadow ecosystem on the Qinghai–Tibet Plateau. To achieve this, we compared the performance of four non-parametric regression models, i.e., partial least square regression (PLSR), the generic algorithm integrated with the PLSR (GA-PLSR), random forest (RF) and extreme gradient boosting (XGBoost) for the retrieval of 10 plant community traits using visible and near-infrared (450–950 nm) UAV hyperspectral imaging. Our results show that chlorophyll a, chlorophyll b, carotenoid content, starch content, specific leaf area and leaf thickness were estimated with good accuracies, with the highest R2 values between 0.64 (nRMSE = 0.16) and 0.83 (nRMSE = 0.11). Meanwhile, the estimation accuracies for nitrogen content, phosphorus content, plant height and leaf dry matter content were relatively low, with the highest R2 varying from 0.3 (nRMSE = 0.24) to 0.54 (nRMSE = 0.20). Among the four tested algorithms, the GA-PLSR produced the highest accuracy, followed by PLSR and XGBoost, and RF showed the poorest performance. Overall, our study demonstrates that UAV-based visible and near-infrared hyperspectral imaging has the potential to accurately estimate multiple plant community traits for the natural grassland ecosystem at a fine scale.

Planted forests provide a variety of meaningful ecological functions and services, which is a major approach for ecological restoration, especially in arid areas. However, mapping planted forests with remote-sensed data remains challenging due to the similarities in canopy spectral and structure characteristics and associated phenology features between planted forests and other vegetation types. In this study, taking advantage of the Google Earth Engine (GEE) platform and taking the Ningxia Hui Autonomous Region in northwestern China as an example, we developed an approach to map planted forests in an arid region by applying long-term features of the NDVI derived from dense Landsat time series. Our land cover map achieved a satisfactory accuracy and relatively low uncertainty, with an overall accuracy of 93.65% and a kappa value of 0.92. Specifically, the producer (PA) and user accuracies (UA) were 92.48% and 91.79% for the planted forest class, and 93.88% and 95.83% for the natural forest class, respectively. The total planted forest area was estimated as 3608.72 km2 in 2020, accounting for 20.60% of the study area. The proposed mapping approach can facilitate assessment of the restoration effects of ecological engineering and research on ecosystem services and stability of planted forests.

Legumes are characterized as keeping stable nutrient supply under nutrient-limited conditions. However, few studies examined the legumes' stoichiometric advantages over other plants across various taxa in natural ecosystems. We explored differences in nitrogen (N) and phosphorus (P) stoichiometry of different tissue types (leaf, stem, and root) between N2-fixing legume shrubs and non-N2-fixing shrubs from 299 broadleaved deciduous shrubland sites in northern China. After excluding effects of taxonomy and environmental variables, these two functional groups differed considerably in nutrient regulation. N concentrations and N:P ratios were higher in legume shrubs than in non-N2-fixing shrubs. N concentrations were positively correlated between the plants and soil for non-N2-fixing shrubs, but not for legume shrubs, indicating a stronger stoichiometric homeostasis in legume shrubs than in non-N2-fixing shrubs. N concentrations were positively correlated among three tissue types for non-N2-fixing shrubs, but not between leaves and non-leaf tissues for legume shrubs, demonstrating that N concentrations were more dependent among tissues for non-N2-fixing shrubs than for legume shrubs. N and P concentrations were correlated within all tissues for both functional groups, but the regression slopes were flatter for legume shrubs than non-N2-fixing shrubs, implying that legume shrubs were more P limited than non-N2-fixing shrubs. These results address significant differences in stoichiometry between legume shrubs and non-N2-fixing shrubs, and indicate the influence of symbiotic nitrogen fixation (SNF) on plant stoichiometry. Overall, N2-fixing legume shrubs are higher and more stoichiometrically homeostatic in N concentrations. However, due to excess uptake of N, legumes may suffer from potential P limitation. With their N advantage, legume shrubs could be good nurse plants in restoration sites with degraded soil, but their P supply should be taken care of during management according to our results.