Search

Abstract Local injection of anti-inflammatory drugs for osteoarthritis emerged as a promising administration in the clinic, and sustained-release dosage forms have great potential for future therapeutic applications. Controlling the response of patients only in the acute inflammatory phase is currently the focus of therapeutic interventions. To relieve acute pain in patients and to improve the long-term prognosis effect of osteoarthritis treatment, we designed a two-pronged approach in this research: an injectable double-layer microsphere containing a “nonsteroidal anti-inflammatory drug - macrophage polarizing factor” was constructed. The results indicated that microspheres could regulate the intra-articular environment by inhibiting local inflammatory cytokine production, promoting macrophage polarization to the M2-phenotype, and increasing the expression of cartilage repair factors. Polymers chosen could govern the biocompatibility of microspheres and control the release sequence of the two drugs. Injection of microspheres into the degenerative articular cavity of rats leads to suppressed inflammation and well-promoted cartilage regeneration.

Abstract Background Observational studies have elucidated the associations between dietary factors and hypertension. Nevertheless, the exploration of these relationships using Mendelian randomization remains scarce currently. Methods The Mendelian randomization approach investigated the potential causal relationships between 16 dietary factors and hypertension. To achieve this, we identified genetic variants associated with these dietary factors by utilizing data from European-descent genome-wide association studies with a stringent significance threshold (P

The leakage of leachate is a crucial but often overlooked hydrological process in the landfill water cycle. The concealed leakage of leachate not only leads to soil and groundwater pollution in surrounding areas but also affects the distribution of water and the metabolism of organic matter within the landfill. To accurately quantify this concealed hydrological process, we propose a method for detecting leachate leakage based on joint inversion of multi-source geophysical exploration data. By integrating multiple geophysical exploration data (resistivity and self-potential information), we reconcile the spatial differences in different exploration data to improve the accuracy of leachate and its pollution plume imaging. Additionally, we introduce an efficient alternating iteration technique within the joint inversion framework to ensure convergence of separately inverted models toward similar spatial structures. Simulation results indicate that: (1) for the early detection of small-scale high-concentration leachate pollution, the proposed confidence-induced joint inversion framework (CI-JIF) improves precision by 15.6 % compared to separate inversions. (2) for the detection of leachate long-term diffusion, CI-JIF accurately delineates the distribution of widespread high-concentration leachate, improving precision by 17.4 % compared to separate inversions. Further on-site experiments demonstrate that CI-JIF can more accurately reconstruct the distribution of leachate.

Previous studies have demonstrated an association between lymphatic vessels and diseases caused by bacterial infections. Listeria monocytogenes (LM) bacterial infection can affect multiple organs, including the intestine, brain, liver and spleen, which can be fatal. However, the impacts of LM infection on morphological and functional changes of lymphatic vessels remain unexplored. In this study, we found that LM infection not only induces meningeal and mesenteric lymphangiogenesis in mice, but also impairs meningeal lymphatic vessels (MLVs)-mediated macromolecules drainage. Interestingly, we found that the genes associated with lymphatic vessel development and function, such as Gata2 and Foxc2, were downregulated, suggesting that LM infection may affect cellular polarization and valve development. On the other hand, photodynamic ablation of MLVs exacerbated inflammation and bacterial load in the brain of mice with LM infection. Overall, our findings indicate that LM infection induces lymphangiogenesis and may affect cell polarization, cavity formation, and valve development during lymphangiogenesis, ultimately impairing MLVs drainage.

Objective: The effects of lactic acid bacteria on the hypoglycemic and antioxidant activities of fermented goat milk were studied. Methods: Three lactic acid bacteria with hypoglycemic and antioxidant functions preserved in the laboratory and commercial yoghurt starters Lactobacillus bulgaricus (LB) and Streptococcus thermophiles (ST) were used as strain starters. The goat milk was fermented by single strain fermentation and mixed fermentation with commercial starters. The antioxidant and hypoglycemic functions of goat yoghurt fermented by different lactic acid bacteria were analyzed in vitro. Results: The results showed that in vitro antioxidant and hypoglycemic activities of goat milk fermented by single and mixed fermentation were improved. The goat yoghurt fermented by Pediococcus acidilactici GC215 had the highest DPPH clearance rate and reducing activity, which were 87.35% and 359.17 μmmoL/L L-cysteine reduction equivalent respectively. And its PTIO free radical clearance rate was 11.25%. Compared with unfermented goat milk, the inhibition rate of α-glucosidase activity of goat milk fermented by Liquorilactobacillus mali L31 increased by 44.08%. The goat yoghurt fermented by Lactobacillus brevis PC-2 mixed with LB and ST had the highest inhibition on α-amylase activity, which the activity inhibition rate was 82.30%. Conclusion: Functional lactic acid bacteria fermentation of goat milk could improve the antioxidant and hypoglycemic activities of goat yogurt in vitro. The research results would provide reliable strain resources for functional fermentation of goat milk and a new direction for the development of functional products of goat milk at the same time.

Territorial spatial planning requires thoughtful consideration of the scientific layout and synergistic control of production, living, and ecological spaces (PLESs). However, research in this field often neglects the human perspective and fails to account for people’s demands and behavioral characteristics. This study evaluates the level and spatial characteristics of residents’ production, living, and ecological behavioral (PLEB) flow, as well as the spatial pattern of the PLES functions, within the framework of the human–land coupling system. Therefore, to analyze the behavior–space coupling coordination relationship, the coupling coordination model is applied. The results indicate that the overall level of residents’ PLEB flow in rural–urban fringe areas is at a lower middle level and the functionality of the PLES is at a medium level, with a spatial distribution pattern of high in the northern and low in the southern areas. Most of the behavior–space matching types are in a state of mismatch between supply and demand. Meanwhile, the PLEB–PLES coupling coordination relationship is generally unbalanced, which is particularly noticeable in the production space. Regardless of whether the behavior–space matching type is a supply deficit or a supply surplus, the mismatch between supply and demand leads to uncoordinated and unreasonable spatial utilization. Overall, the findings of the study provide guidance for future research endeavors about PLESs and suggest embracing a human-centered scientific paradigm. Such a paradigm can promote high-quality, sustainable development of territorial spatial planning while strengthening the capacity and effectiveness of spatial governance and control.

Essential hypertension (EH) is a leading cause of cardiovascular morbidity and mortality. Fructus Tribuli (FT), as a traditional medicine, has been frequently used for thousands of years. The crude Fructus Tribuli (CFT), decoction pieces being processed to remove impurities, have been listed as an important medicine for the treatment of hypertension in the elderly. According to the theory of traditional Chinese medicine, the CFT can enhance the EH treatment after being stir-fried into stir-fried Fructus Tribuli (SFT). At present, whether the SFT can enhance the EH treatment and its potential pharmacodynamic substances and mechanism are unknown. In this study, an integrated ''spectrum-effect relationship-network pharmacology-metabolomics'' strategy was used. Using male spontaneously hypertensive rats as an experimental model, we compared the therapeutic effects of CFT and SFT on EH. Subsequently, to define the pharmacodynamic material basis of SFT in enhancing the EH treatment, the steroidal saponins (main active components of FT) were selected for spectrum-effect relationship analysis. Furthermore, we applied the joint pathway analysis of network pharmacology and metabolomics to explore the underlying mechanism of SFT in enhancing the EH treatment. Results showed that SFT was better than CFT in the EH treatment. The steroidal saponins transformed by stir-frying were the potential pharmacodynamic substances that SFT could enhance the EH treatment. And the mechanism of action might be associated with regulating glycerophospholipid metabolism and arachidonic acid metabolism, especially arachidonic acid metabolism. This study provided a scientific basis for the clinical use of SFT as an important medicine for the EH treatment.

Abstract Background Bone is the most common site of metastasis of prostate cancer (PCa). PCa invasion leads to a disruption of osteogenic-osteolytic balance and causes abnormal bone formation. The interaction between PCa and bone stromal cells, especially osteoblasts (OB), is considered essential for the disease progression. However, drugs that effectively block the cancer-bone interaction and regulate the osteogenic-osteolytic balance remain undiscovered. Methods A reporter gene system was constructed to screen compounds that could inhibit PCa-induced OB activation from 631 compounds. Then, the pharmacological effects of a candidate drug, Procoxacin (Pro), on OBs, osteoclasts (OCs) and cancer-bone interaction were studied in cellular models. Intratibial inoculation, micro-CT and histological analysis were used to explore the effect of Pro on osteogenic and osteolytic metastatic lesions. Bioinformatic analysis and experiments including qPCR, western blotting and ELISA assay were used to identify the effector molecules of Pro in the cancer-bone microenvironment. Virtual screening, molecular docking, surface plasmon resonance assay and RNA knockdown were utilized to identify the drug target of Pro. Experiments including co-IP, western blotting and immunofluorescence were performed to reveal the role of Pro binding to its target. Intracardiac inoculation metastasis model and survival analysis were used to investigate the therapeutic effect of Pro on metastatic cancer. Results Luciferase reporter gene consisted of Runx2 binding sequence, OSE2, and Alp promotor could sensitively reflect the intensity of PCa-OB interaction. Pro best matched the screening criteria among 631 compounds in drug screening. Further study demonstrated that Pro effectively inhibited the PCa-induced osteoblastic changes without killing OBs or PCa cells and directly killed OCs or suppressed osteoclastic functions at very low concentrations. Mechanism study revealed that Pro broke the feedback loop of TGF-β/C-Raf/MAPK pathway by sandwiching into 14–3-3ζ/C-Raf complex and prevented its disassociation. Pro treatment alleviated both osteogenic and osteolytic lesions in PCa-involved bones and reduced the number of metastases of PCa in vivo. Conclusions In summary, our study provides a drug screening strategy based on the cancer-host microenvironment and demonstrates that Pro effectively inhibits both osteoblastic and osteoclastic lesions in PCa-involved bones, which makes it a promising therapeutic agent for PCa bone metastasis. Graphical Abstract

With the rapid growth of electric vehicle (EV) ownership, the problem of increased peak loads on distribution networks due to large-scale EV integration needs to be addressed. This study proposes an active distribution network multi-objective optimization scheduling method. It takes into account the charging demands of large-scale EVs and aims to minimize distribution network operating costs, reduce net load variance, and maximize the photovoltaic (PV) consumption rate. First, the Monte Carlo sampling method is used to analyze the charging load demands of a large number of EVs. Next, we construct a multi-objective optimization scheduling model for the active distribution network. This model integrates the charging demands of EVs with the operating constraints of the distribution network. To tackle the multi-objective optimization problem, we propose the NSGAII-NDAX algorithm. Additionally, we employ a fuzzy theory-based method to select the Pareto optimal solution set, addressing the challenge of decision-making complexity posed by the large size and information-rich content of the optimal solution set. Finally, the effectiveness of the proposed method in the comparative analysis of multiple scenarios is verified by an improved IEEE 33-node example. The experimental results show that the proposed model and method can effectively utilize EV charging load optimization to reduce the peak-to-valley difference in the system load while ensuring the system’s economic operation and the maximum PV consumption rate. Compared with the other algorithms, the NSGAII-NDAX algorithm has stronger optimization ability and can better handle multi-objective optimization problems.

Summary: Upon recognizing danger signals produced by virally infected neurons, macrophages in the central nervous system (CNS) secrete multiple inflammatory cytokines to accelerate neuron apoptosis. The understanding is limited about which key effectors regulate macrophage-neuron crosstalk upon infection. We have used neurotropic-virus-infected murine models to identify that vascular endothelial growth factor receptor 3 (VEGFR-3) is upregulated in the CNS macrophages and that virally infected neurons secrete the ligand VEGF-C. When cultured with VEGF-C-containing supernatants from virally infected neurons, VEGFR-3+ macrophages suppress tumor necrosis factor α (TNF-α) secretion to reduce neuron apoptosis. Vegfr-3ΔLBD/ΔLBD (deletion of ligand-binding domain in myeloid cells) mice or mice treated with the VEGFR-3 kinase inhibitor exacerbate the severity of encephalitis, TNF-α production, and neuron apoptosis post Japanese encephalitis virus (JEV) infection. Activating VEGFR-3 or blocking TNF-α can reduce encephalitis and neuronal damage upon JEV infection. Altogether, we show that the inducible VEGF-C/VEGFR-3 module generates protective crosstalk between neurons and macrophages to alleviate CNS viral infection.

We report a novel 2 × 2 broadband 3 dB coupler based on fast adiabatic mode evolution with a compact footprint and large bandwidth. The working principle of the coupler is based on the rapid adiabatic evolution of local eigenmodes of fishbone-like grating waveguides. Different from a traditional adiabatic coupling method realized by the slow change of the cross-section size of a strip waveguide, a fishbone waveguide allows faster adiabatic transition with proper structure and segment designs. The presented 3 dB coupler achieves a bandwidth range of 168 nm with an imbalance of no greater than ±0.1 dB only for a 9 μm coupling region which significantly improves existing adiabatic broadband couplers.

With the development of the dairy industry, the safety of milk quality had attracted much attention. Top-brand dairy products with specific origins or grass-fed claims were emerging in an endless stream, so the traceability of the milk origin had also become an urgent need. In this study, four stable isotope ratios of δ13C, δ15N, δ2H, δ18O in milk samples of Heilongjiang Province, Yunnan Province, Hebei Province, Gansu Province and Inner Mongolia Autonomous Region were determined respectively, as well as three mineral elements mass concentration of calcium, iron and zinc. Data models combined with multivariate statistical analysis of 5 milk regions was established. This research explored the application prospects of stable isotopes and mineral elements in the milk traceability and developed a milk traceability technology based on them. The results showed that the stable isotope ratios δ13C, δ15N, δ2H, δ18O and the mineral elements calcium and zinc in milk had significant differences based on regions (P0.05). Cluster analysis and principal component analysis could effectively distinguish the samples from Gansu Province, but there was a certain crossover among other regions. All regions could be effectively distinguished through discriminant analysis, the original discrimination rate was 100% and 96% in cross-validation. Traceability technology of milk origin developed by this research could realize effective origin traceability, and provide strong technical support for controlling milk sources and boosting consumer confidence.

Analyzing customers' characteristics and giving the early warning of customer churn based on machine learning algorithms, can help enterprises provide targeted marketing strategies and personalized services, and save a lot of operating costs. Data cleaning, oversampling, data standardization and other preprocessing operations are done on 900,000 telecom customer personal characteristics and historical behavior data set based on Python language. Appropriate model parameters were selected to build BPNN (Back Propagation Neural Network). Random Forest (RF) and Adaboost, the two classic ensemble learning models were introduced, and the Adaboost dual-ensemble learning model with RF as the base learner was put forward. The four models and the other four classical machine learning models-decision tree, naive Bayes, K-Nearest Neighbor (KNN), Support Vector Machine (SVM) were utilized respectively to analyze the customer churn data. The results show that the four models have better performance in terms of recall rate, precision rate, F1 score and other indicators, and the RF-Adaboost dual-ensemble model has the best performance. Among them, the recall rates of BPNN, RF, Adaboost and RF-Adaboost dual-ensemble model on positive samples are respectively 79%, 90%, 89%,93%, the precision rates are 97%, 99%, 98%, 99%, and the F1 scores are 87%, 95%, 94%, 96%. The RF-Adaboost dual-ensemble model has the best performance, and the three indicators are 10%, 1%, and 6% higher than the reference. The prediction results of customer churn provide strong data support for telecom companies to adopt appropriate retention strategies for pre-churn customers and reduce customer churn.

Drug and target discovery for advanced liver disease are hampered by a lack of suitable models for clinical translation. Here the authors present a human liver cell-based system modeling a clinical prognostic signature allowing to propose nizatidine for treatment of advanced liver fibrosis and hepatocellular carcinoma prevention.

Macropinocytosis, a unique endocytosis pathway characterized by nonspecific internalization, has a vital role in the uptake of extracellular substances and antigen presentation. It is known to have dual effects on cancer cells, depending on cancer type and certain microenvironmental conditions. It helps cancer cells survive in nutrient-deficient environments, enhances resistance to anticancer drugs, and promotes invasion and metastasis. Conversely, overexpression of the RAS gene alongside drug treatment can lead to methuosis, a novel mode of cell death. The survival and proliferation of cancer cells is closely related to macropinocytosis in the tumor microenvironment (TME), but identifying how these cells interface with the TME is crucial for creating drugs that can limit cancer progression and metastasis. Substantial progress has been made in recent years on designing anticancer therapies that utilize the effects of macropinocytosis. Both the induction and inhibition of macropinocytosis are useful strategies for combating cancer cells. This article systematically reviews the general mechanisms of macropinocytosis, its specific functions in tumor cells, its occurrence in nontumor cells in the TME, and its application in tumor therapies. The aim is to elucidate the role and therapeutic potential of macropinocytosis in cancer treatment.

ObjectivesThe first objective of this study was to probe the effects of genkwanin (GKA) on osteoclast. The second goal of this study was to study whether GKA can protect lipopolysaccharide (LPS) and ovariectomized (OVX) induced bone loss.Materials and MethodsVarious concentrations of GKA (1 and 10 mg/kg) were injected into mice. Different concentrations of GKA (1 and 5 μM) were used to detect the effects of GKA on osteoclast and osteoblast.Key FindingsGKA attenuated the osteoclast differentiation promoted by RANKL and expression of marker genes containing c-fos, ctsk as well as bone resorption related gene Trap and to the suppression of MAPK signaling pathway. In addition, GKA induced BMMs cell apoptosis in vitro. Moreover, GKA prevented LPS-induced and ovariectomized-induced bone loss in mice.ConclusionOur research revealed that GKA had a potential to be an effective therapeutic agent for osteoclast-mediated osteoporosis.

Eight species of the genus Ischnothyreus Simon, 1893 from Xishuangbanna, Yunnan, China are recognized, including six new species: I. cristiformis Tong & Li, sp. nov. (♂♀), I. mangun Tong & Li, sp. nov. (♂♀), I. mengyang Tong & Li, sp. nov. (♂♀), I. peltifer (Simon, 1892), I. qidaoban Tong & Li, sp. nov. (♂♀), I. qiuxing Tong & Li, 2020 (♂♀), I. sijiae Tong & Li, sp. nov. (♀) and I. xiaolongha Tong & Li, sp. nov. (♂♀). The male of I. qiuxing Tong & Li, 2020 is described for the first time. Photos of the habitus and copulatory organs are provided.

LiDAR has attracted increasing attention because of its strong anti-interference ability and high resolution. Traditional LiDAR systems rely on discrete components and face the challenges of high cost, large volume, and complex construction. Photonic integration technology can solve these problems and achieve high integration, compact dimension, and low-cost on-chip LiDAR solutions. A solid-state frequency-modulated continuous-wave LiDAR based on a silicon photonic chip is proposed and demonstrated. Two sets of optical phased array antennas are integrated on an optical chip to form a transmitter–receiver interleaved coaxial all-solid-state coherent optical system which provides high power efficiency, in principle, compared with a coaxial optical system using a 2 × 2 beam splitter. The solid-state scanning on the chip is realized by optical phased array without a mechanical structure. A 32-channel transmitter–receiver interleaved coaxial all-solid-state FMCW LiDAR chip design is demonstrated. The measured beam width is 0.4° × 0.8°, and the grating lobe suppression ratio is 6 dB. Preliminary FMCW ranging of multiple targets scanned by OPA was performed. The photonic integrated chip is fabricated on a CMOS-compatible silicon photonics platform, providing a steady path to the commercialization of low-cost on-chip solid-state FMCW LiDAR.

With the continuous development of electronic skin (e-skin), multifunctional e-skin is approaching, and in some cases even surpassing, the capabilities of real human skin, which has garnered increasing attention. Especially, if e-skin processes eye’s function, it will endow e-skins more powerful advantages, such as the vision reparation, enhanced security, improved adaptability and enhanced interactivity. Here, we first study the photodetector based on CsPbBr3 quantum dots film and the pressure sensor based on PEDOT: PSS-coated cellulose paper, respectively. On the base of these two kinds of sensors, a light/pressure bifunctional sensor was successfully fabricated. Finally, flexible bifunctional sensors were obtained by using a flexible interdigital electrode. They can simultaneously detect light and pressure stimulation. As e-skin, a high photosensitivity with a switching ratio of 168 under 405 nm light at a power of 40 mW/cm2 was obtained and they can also monitor human motions in the meantime. Our work showed that the strategy to introduce perovskite photodetectors into e-skins is feasible and may open a new way for the development of flexible multi-functional e-skin.

Bone homeostasis only exists when the physical function of osteoblast and osteoclast stays in the balance between bone formation and resorption. Bone resorption occurs when the two processes are uncoupled, shifting the balance in favour of bone resorption. Excessive activation of osteoclasts leads to a range of osteolytic bone diseases including osteoporosis, aseptic prosthesis loosening, rheumatoid arthritis, and osteoarthritis. Receptor activator of nuclear factor kappa-B ligand (RANKL) and its downstream signaling pathways are recognized as key mediators that drive the formation and activation of osteoclastic function. Hence, osteoclast formation and/or its function remain as dominant targets for research and development of agents reaching the treatment towards osteolytic diseases. Chrysin (CHR) is a flavonoid with a wide range of anti-inflammatory and anti-tumor effects. However, its effect on osteoclasts remains unknown. In this study, we found the effects of CHR on inhibiting osteoclast differentiation which were assessed in terms of the number and size of TRAcP positive multinucleated osteoclasts (OCs). Further, the inhibitory effects of CHR on bone resorption and osteoclast fusion of pre-OC were assessed by hydroxyapatite resorption pit assay and F-actin belts staining; respectively. Western blotting analysis of RANKL-induced signaling pathways and immunofluorescence analysis for p65 nuclear translocation in response to RANKL-induced osteoclasts were used to analyze the mechanism of action of CHR affecting osteoclasts. Lastly, the murine calvarial osteolysis model revealed that CHR could protect against particle-induced bone destruction in vivo. Collectively, our data strongly suggested that CHR with its promising anti-tumor effects would also be a potential therapeutic agent for osteolytic diseases.

Acacia catechu (L.f.) Willd, a leguminous plant, is included in the 2020 edition of the Chinese Pharmacopoeia and is mainly used to treat eczema, mouth ulcers, diarrhea, bruising, and traumatic hemorrhage. However, there are imported and domestic Acacia catechu samples available in China, and their quality and price are very different, which seriously affects the safety and stability of their clinical application. Importantly, there is no simple and effective method for identifying or classifying grades of Acacia catechu. In this study, 47 batches of commercial Acacia catechu were used for identifying or classifying grades of Acacia catechu using high performance liquid chromatography (HPLC) combined with chemometric analysis. Firstly, gradient elution was adopted with 0.05% phosphoric acid water (A)-methanol (B) as the mobile phase to establish chromatographic conditions. The HPLC chromatograms of 47 batches of Acacia catechu samples were analyzed by the “Similarity Evaluation System for Chromatographic Fingerprint of TCM” software (version 2012A). The common peaks of Acacia catechu were identified to evaluate the similarity. Based on the determination results of fingerprint chromatographic peak area, the quality of the collected Acacia catechu was evaluated by chemometric methods such as CA, PCA, and OPLS-DA. The results showed that the collected Acacia catechu samples were significantly divided into three categories. The first-class samples were all imported Acacia catechu except S9 sample, which was domestic Acacia catechu; the second-class samples were partly domestic Acacia catechu and partly imported Acacia catechu; and the third-class samples were all domestic Acacia catechu. Moreover, OPLS-DA of 47 batches of samples showed that the contents of catechin and the total contents of catechin and epicatechin could be used as key indicators for assessing the quality of Acacia catechu. The developed HPLC fingerprint and quantitative analysis method of multi-indicator components can be used for classification and quality evaluation of market Acacia catechu, which has a significant reference value for developing Acacia catechu grade quality standards.

One effective treatment for postmenopausal osteoporosis is to inhibit osteoclasts and subsequent bone resorption. In our study, we demonstrated that acacetin, a flavone with potential therapeutic effects in infections, cancers, and several metabolic disorders, inhibited osteoclast differentiation and bone resorption in vitro. For improving the efficacy of acacetin in vivo, we developed an acid-sensitive bone-targeting delivery system composed of an acid-sensitive linker (N-ε-maleimidocaproic acid hydrazide, EMCH) for ensuring an effective release of acacetin at the site of action and a hydrophilic aspartic acid hexapeptide ((Asp)6, D6) as the effective bone targeting agent. Our results revealed that Acacetin-EMCH-D6 specifically bound to the bone surface once administrated in vivo, prolonged the retention time in bone and released acacetin at the osteoclastic bone resorption sites where the acidity is higher. We further demonstrated that, in ovariectomy-induced osteoporosis mice, treatment with Acacetin-EMCH-D6 inhibited osteoclast formation and increased trabecular bone mass. On the contrary, neither acacetin nor EMCH-D6 with the same dosage alone showed significant anti-osteoporosis effects in vivo. Mechanistically, targeted delivery of acacetin to the bone resorption sites by Acacetin-EMCH-D6 inhibited autophagy through activating PI3K/AKT/mTOR pathway in osteoclasts, while the activation of autophagy by rapamycin partially reversed the inhibitory effects of acacetin in vitro and in vivo. In summary, our study, for the first time, showed that the acid-sensitive bone-targeting delivery system carrying acacetin was effective for the treatment of postmenopausal osteoporosis. Thus, targeted delivery of acacetin using Acacetin-EMCH-D6 to bone resorption sites is a promising therapy for osteoporosis.

The forecasting of electricity sales is directly related to the power generation planning of power enterprises and the progress of the generation tasks. Aiming at the problem that traditional forecasting methods cannot properly deal with the actual data offset caused by external factors, such as the weather, season, and spatial attributes, this paper proposes a method of electricity sales forecasting based on a deep spatio-temporal residual network (ST-ResNet). The method not only relies on the temporal correlation of electricity sales data but also introduces the influence of external factors and spatial correlation, which greatly enhances the fitting degree of each parameter of the model. Moreover, the residual module and the convolution module are fused to effectively reduce the damage of the deep convolutional process to the training effectiveness. Finally, the three comparison experiments of the ultra-short term, short term and medium term show that the MAPE forecasted by the ST-ResNet model is at least 2.69% lower than that of the RNN and other classical Deep Learning models, that its RMSE is at least 36.2% lower, and that its MAD is at least 34.2% lower, which is more obvious than the traditional methods. The effectiveness and feasibility of the ST-ResNet model in the short-term forecasting of electricity sales are verified.

Osteolytic bone disease is characterized by excessive osteoclast bone resorption leading to increased skeletal fragility and fracture risk. Multinucleated osteoclasts formed through the fusion of mononuclear precursors are the principle cell capable of bone resorption. Pregnenolone (Preg) is the grand precursor of most if not all steroid hormones and have been suggested to be a novel anti-osteoporotic agent. However, the effects of Preg on osteoclast biology and function has yet to be shown. Here we examined the effect of Preg on receptor activator of nuclear factor kappa B ligand (RANKL)-induced osteoclast formation and bone resorption in vitro, and potential therapeutic application in inflammatory bone destruction and bone loss in vivo. Our in vitro cellular assays demonstrated that Preg can inhibit the formation of TRAP+ve osteoclast formation as well as mature osteoclast bone resorption in a dose-dependent manner. The expression of osteoclast marker genes CTSK, TRAP, DC-STAMP, ATP6V0d2, and NFATc1 were markedly attenuated. Biochemical analyses of RANKL-induced signaling pathways showed that Preg inhibited the early activation of extracellular regulated protein kinases (ERK) mitogen-activated protein kinase (MAPK) and nuclear factor-κB, which consequently impaired the downstream induction of c-Fos and NFATc1. Using reactive oxygen species (ROS) detection assays, we found that Preg exhibits anti-oxidant properties inhibiting the generation of intracellular ROS following RANKL stimulation. Consistent with these in vitro results, we confirmed that Preg protected mice against local Lipopolysaccharide (LPS)-induced inflammatory bone destruction in vivo by suppressing osteoclast formation. Furthermore, we did not find any observable effect of Preg on osteoblastogenesis and mineralization in vitro. Finally Preg was administered to ovariectomy (OVX)-induced bone loss and demonstrated that Preg prevented systemic OVX-induced osteoporosis. Collectively, our observations provide strong evidence for the use of Preg as anti-osteoclastogenic and anti-resorptive agent for the potential treatment of osteolytic bone conditions.

Topological phases of matter with robust edge states have revolutionized the fundamental intuitions for wave control. The recent development of higher-order topological insulators (HOTIs) realizes even lower dimensional topological states that enable versatile wave manipulations (e.g., light imaging). However, in conventional HOTIs, the topological states are usually protected by certain crystalline symmetries and therefore bounded at specific locations, hindering their applications in modern digital ears, which often prefer tunability and reconfigurability. Here, we report the reconfigurable light imaging based on topological corner states and anti-chiral edge states in a two-dimensional (2D) photonic HOTI with a honeycomb lattice of yttrium iron garnet (YIG, a ferrite material) rods. Sublattices A and B are applied with magnetic fields in opposite directions, which realize the so-called modified Haldane model that hosts anti-chiral edge modes. By further breaking the lattice’s inversion symmetry via adjusting the radii of A and B rods, topological edge states with valley degrees of freedom emerge, which not only exhibit valley-dependence but also surprisingly show anti-chiral behaviors. In the valley edge gap, which is of nontrivial higher-order topology, corner states appear. With different combinations of corner states and anti-chiral edge states, versatile reconfigurable light imaging can be realized. As examples, a multiplexing waveguide-resonator device, a pine tree imaging that can be lit up or put out at will and selective imaging for partial objects in a two-heart pattern are demonstrated. The proposed HOTI shows high potential in future intelligent devices with exciting tunable and reconfigurable functions, which may inspire a wide range of applications such as topological switching, imaging processing, and nonreciprocal integrated photonics.

Abstract Development of ovarian cancer involves the co-evolution of neoplastic cells together with the adjacent microenvironment. Steps of malignant progression including primary tumor outgrowth, therapeutic resistance, and distant metastasis are not determined solely by genetic alterations in ovarian cancer cells, but considerably shaped by the fitness advantage conferred by benign components in the ovarian stroma. As the dynamic cancer topography varies drastically during disease progression, heterologous cell types within the tumor microenvironment (TME) can actively determine the pathological track of ovarian cancer. Resembling many other solid tumor types, ovarian malignancy is nurtured by a TME whose dark side may have been overlooked, rather than overestimated. Further, harnessing breakthrough and targeting cures in human ovarian cancer requires insightful understanding of the merits and drawbacks of current treatment modalities, which mainly target transformed cells. Thus, designing novel and precise strategies that both eliminate cancer cells and manipulate the TME is increasingly recognized as a rational avenue to improve therapeutic outcome and prevent disease deterioration of ovarian cancer patients.

Layered double hydroxide (LDH) materials have shown charming photo-Fenton capability for the treatment of refractory organic wastewater. In this study, CuFe-LDH hybridized with N-doped carbon quantum dots (N-CQDs) was investigated to further enhance the photo-Fenton capability. The results showed that the assembly techniques of coprecipitation and the hydrothermal method could synthesize the target material, CuFe-LDH/N-CQDs, successfully. CuFe-LDH/N-CQDs could possess a 13.5% higher methylene blue (MB) removal rate than CuFe-LDH in 30 min due to the accelerated redox cycles of Fe(III)/Fe(II) and Cu(III)/Cu(II), resulting from the photo-induced electron transfer from N-CQDs to CuFe-LDH via a d–π conjugation electronic bridge. Moreover, CuFe-LDH/N-CQDs has excellent photo-Fenton capability in the pH range of 2–11, even after being reused five times. This study would provide an efficient and stable photo-Fenton catalyst for the treatment of refractory organic wastewater.

Supply disruption may cause strong complaints of customers, which is a cost loss for the firms in the supply chain. Obviously, if realizing that there is the disruption risk, the members in a supply chain will adjust their decisions. For analyzing the influence, we consider a popular supply chain mode with dual channels, where one manufacturer has its direct sales channel and one traditional retailer channel. The manufacturer may suffer a supply disruption so that all ordered products by the retailer or the direct retail channel will be lost, and the members in supply chain will bear the corresponding disruption penalty from the customers. By considering four structures with different market power relations, the closed-form optimal price decisions of the four models are given. We found that the disruption factor improves the sales prices for any member structure as compared to the supply chain without the disruption. And the direct retail prices in the different modes are the same as each other, but the price of the traditional channel is influenced by the market share. And the sorts of the sales prices under different structures are given. We also conduct some extensive numerical analysis and compare the results under different structures. We observe that the expected optimal profits of considering the external penalty are smaller than those of no external penalty, and we give a sort of the optimal expected profits. And we also provide the effects of some parameters on the optimal decisions and the optimal expected profits.

To make service convenient and improve user experience degrees, recommendation service has become more and more important to users in the location-based social network（LBSN）. An improved potential friends recommendation in LBSN, which is based on the relationship among friends and the similarity of locations, was proposed. First of all, the user interest pointsin each position weight with friends' relationship, check-in feature and historical recordwere calculated. Then position weight and the friend relationship were used to calculate the friends' similarity and location similarity. Finally, potential friends to user based on the friends' similarity and location similarity were recommended. The experimental results show that the proposed model is effective.

In the article the authors discuss light detection and ranging (LiDAR) for automotive applications and the potential roles Si photonics can play in practice. The authors review published research work on Si photonics optical phased array (OPA) and other relevant devices in the past decade with in-depth technical analysis with respect to practical system design considerations. The commercialization status of certain LiDAR technologies is briefly introduced.

A good understanding of the mechanism of interaction between inhaled pollutant nanoparticles (NPs) and the pulmonary surfactant monolayer is useful to study the impact of fine particulate matter on human health. In this work, we established coarse-grained models of four representative NPs with different hydrophilicity properties in the air (i.e., CaSO4, C, SiO2, and C6H14O2 NPs) and the pulmonary surfactant monolayer. Molecular dynamic simulations of the interaction during exhalation and inhalation breathing states were performed. The effects of NP hydrophilicity levels, NP structural properties, and cholesterol content in the monolayer on the behaviors of NP embedment or the transmembrane were analyzed by calculating the changes in potential energy, NP displacement, monolayer orderliness, and surface tension. Results showed that NPs can inhibit the ability of the monolayer to adjust surface tension. For all breathing states, the hydrophobic C NP cannot translocate across the monolayer and had the greatest influence on the structural properties of the monolayer, whereas the strongly hydrophilic SiO2 and C6H14O2 NPs can cross the monolayer with little impact. The semi-hydrophilic CaSO4 NP can penetrate the monolayer only during the inhalation breathing state. The hydrophilic flaky NP shows the best penetration ability, followed by the rod-shaped NP and spherical NP in turn. An increase in cholesterol content of the monolayer led to improved orderliness and decreased fluidity of the membrane system due to enhanced intermolecular forces. Consequently, difficulty in crossing the monolayer increased for the NPs.

Oocyte deformation during injection is a major cause of potential cell damage which can lead to failure in the Intracytoplasmic Sperm Injection (ICSI) operation used as an infertility treatment. Injection speed plays an important role in the deformation creation. In this paper the effect of different speeds on deformation of zebrafish embryos is studied using a specially designed experimental set-up. An analytical model is developed in order to link injection force, deformation, and injection speed. A finite element (FE) model is also developed to analyse the effect of injection speed, allowing the production of additional information that is difficult to obtain experimentally, e.g., deformation and stress fields on the oocyte. The numerical model is validated against experimental results. Experimental results indicate that by increasing the injection speed, the deformation decreases. However, higher speeds cause higher levels of injection force and force fluctuation, leading to a higher vibration during injection. For this reason, an optimum injection speed range is determined. Finally, the FE model was validated against experimental results. The FE model is able to predict the force-deformation variation during injection for different speeds. This proves to be useful for future studies investigating different injection conditions.

Establishing a heterojunction for two kinds of semiconductor catalysts is a promising way to enhance photocatalytic activity. In this study, nanodiamond (ND) and CuFe-layered double hydroxide (LDH) were hybridized by a simple coprecipitation method as a novel heterojunction to photoactivate H2O2. The ND/LDH possessed a hydrotalcite-like structure, large specific surface area (SBET = 99.16 m2/g), strong absorption of visible-light and low band gap (Eg = 0.94 eV). Under the conditions of ND/LDH dosage 0.0667 g/L, H2O2 concentration 19.6 mmol/L, and without initial pH adjustment, 93.5% of 10 mg/L methylene blue (MB) was degraded within 120 min, while only 78.3% of MB was degraded in the presence of LDH instead of ND/LDH. The ND/LDH exhibited excellent stability and maintained relatively high activity, sufficient to photoactivate H2O2 even after five recycles. The mechanism study revealed that in the heterojunction of ND/LDH, the photoelectrons transferred from the valence band of LDH (Cu/Fe 3d t2g) to the conduction band of LDH (Cu/Fe 3d eg) could spontaneously migrate onto the conduction band of ND, promoting the separation of photo-induced charges. Thus, the photoelectrons had sufficient time to accelerate the redox cycles of Cu3+/Cu2+ and Fe3+/Fe2+ to photoactivate H2O2 to produce hydroxyl radicals, resulting in excellent photo-Fenton efficiency on MB degradation.

The rate of hepatitis C virus (HCV) related liver cirrhosis and subsequent cancer development is increasing and raising the risk of related mortality and morbidity. To address this issue, we aimed to develop a prognostic index that can be used to stratify patients for risk of disease progression. This index was developed in part by using a gene signature test implemented in a clinically applicable digital transcript counting platform (NanoString nCounter system). A cohort of 145 U.S. patients with HCV-related early-stage cirrhosis was analyzed by using the assay. This dataset (GEO accession number GPL17230) provides information of expression levels of the prognostic genes in the cohort.

This paper studies the coordination issue of a supply chain consisting of one retailer and two suppliers, a main supplier and a backup supplier. The main supplier’s yield is subject to disruption and the retailer faces a random demand. We determine the retailer’s optimal ordering policy and the main supplier’s production quantity that maximize expected profit of the centralized supply chain. We also analyze the decentralized scenario, and a combination of overproduction risk sharing and buy-back contracts with a side payment from/to the backup supplier is provided to coordinate the supply chain. Numerical examples are given to gain some qualitative insights.

As an effective way of decreasing production cost, remanufacturing has attracted more and more attention from firms. However, it also brings many difficulties to firms, especial when firms remanufacture products which they produce. A primary problem for the case is how to acquire the used product sold by the firm itself. In this paper, we consider a return compensation policy for acquiring used product from customers. Under this policy, the return quantity of used product is a proportion of demand. We study an inventory replenishment and production planning problem for a two-period inventory system with dependent return and demand. We formulate the problem into a three-stage stochastic programming problem, where the firm needs to make decisions on the replenishment quantity of new raw material inventory in each period and the production quantities of manufacturing and remanufacturing ways. We give the optimal production policy of manufacturing and remanufacturing ways for the realized demand and prove the objective function for each stage to be concave in the inventory replenishment quantity. Moreover, we prove that the basic inventory policy is still optimal for each period and give the analytical conditions of the optimal inventory levels which are unrelated to acquisition price. Finally, we investigate numerical studies to analyze managerial insights.

Prediction accuracies of estimated breeding values for economically important traits are expected to benefit from genomic information. Single nucleotide polymorphism (SNP) panels used in genomic prediction are increasing in density, but the Markov Chain Monte Carlo (MCMC) estimation of SNP effects can be quite time consuming or slow to converge when a large number of SNPs are fitted simultaneously in a linear mixed model. Here we present an EM algorithm (termed "fastBayesA") without MCMC. This fastBayesA approach treats the variances of SNP effects as missing data and uses a joint posterior mode of effects compared to the commonly used BayesA which bases predictions on posterior means of effects. In each EM iteration, SNP effects are predicted as a linear combination of best linear unbiased predictions of breeding values from a mixed linear animal model that incorporates a weighted marker-based realized relationship matrix. Method fastBayesA converges after a few iterations to a joint posterior mode of SNP effects under the BayesA model. When applied to simulated quantitative traits with a range of genetic architectures, fastBayesA is shown to predict GEBV as accurately as BayesA but with less computing effort per SNP than BayesA. Method fastBayesA can be used as a computationally efficient substitute for BayesA, especially when an increasing number of markers bring unreasonable computational burden or slow convergence to MCMC approaches.