PURPOSE:Treadmill exercise promotes bone growth and remodeling in mice. Exosomes are key mediators of intercellular communication; bone or osteocyte-derived exosomes deliver miRNAs to osteoblasts to influence osteogenesis. Therefore, the study aims to profile miRNAs in femoral bone-derived exosomes of mice trained on a treadmill, and the exosomal osteogenesis-related miRNAs were identified through bioinformatics analysis and molecular biology experiments. METHODS:Mice underwent treadmill training, after which exosomes were extracted from femoral bone and characterized, and miRNA expression profiles were analyzed using RNA sequencing. Thereafter, bioinformatics analysis of these differentially expressed miRNAs in the exosomes was performed, and two osteogenesis-related candidates, miR-3960 and miR-2137, were transfected into osteoblasts separately to validate their osteogenic effects. RESULTS:Treadmill exercise markedly enhanced bone formation and improved bone microstructure. Bone-derived exosomes promoted osteogenesis, nine differentially expressed miRNAs were identified, with potential mechanistic links to bone morphometric parameters; their predicted target genes were enriched in pathways related to cellular growth, osteogenesis, axonal development, muscle tissue formation, and key signaling cascades such as PI3K/AKT and MAPK. Notably, the exosomal miR-3960 and miR-2137 were osteogenesis-related; qPCR analysis confirmed that both miRNAs were upregulated, consistent with the miRNA sequencing results. Further, transfection of miR-3960 or miR-2137 into osteoblasts enhanced osteogenesis. CONCLUSIONS:The miRNAs in exosomes from femur (almost osteocytes) of treadmill-trained mice participated not only in osteogenic differentiation (notably miR-3960 and miR-2137), but also showed potential in neural development and muscle growth. The findings offer novel insights into how running exercise benefits skeletal, muscular, and neural health.

Fluorescence lifetime imaging (FLIM) has established itself as a pivotal tool for investigating biological processes within living cells. However, the extensive imaging duration necessary to accumulate sufficient photons for accurate fluorescence lifetime calculations poses a significant obstacle to achieving high-resolution monitoring of cellular dynamics. In this study, we introduce an image reconstruction method based on the edge-preserving interpolation method (EPIM), which transforms rapidly acquired low-resolution FLIM data into high-pixel images, thereby eliminating the need for extended acquisition times. Specifically, we decouple the grayscale image and the fluorescence lifetime matrix and perform an individual interpolation on each. Following the interpolation of the intensity image, we apply wavelet transformation and adjust the wavelet coefficients according to the image gradients. After the inverse transformation, the original image is obtained and subjected to noise reduction to complete the image reconstruction process. Subsequently, each pixel is pseudo-color-coded based on its intensity and lifetime, preserving both structural and temporal information. We evaluated the performance of the bicubic interpolation method and our image reconstruction approach on fluorescence microspheres and fixed-cell samples, demonstrating their effectiveness in enhancing the quality of lifetime images. By applying these techniques to live-cell imaging, we can successfully obtain high-pixel FLIM images at shortened intervals, facilitating the capture of rapid cellular events.

A multifunctional fluorescence imaging system based on LabVIEW has been developed, which can perform fluorescence intensity scanning imaging, and fluorescence lifetime imaging (FLIM). The system utilizes software based on LabVIEW to control a data acquisition (DAQ) card, time-correlated single photon counting (TCSPC) card, and galvanometer to achieve point-scan imaging. The FLIM module integrates dynamic link libraries (DLLs) for galvanometer control, allowing simultaneous management of the galvanometer while outputting clock synchronization signals from the DAQ card as trigger signals for FLIM. This feature facilitates TCSPC FLIM. In addition, by integrating related DLLs and introducing a 3D sample stage, the system can manipulate the 3D sample stage to perform fluorescence imaging at different depths, thereby generating 3D images of the samples and achieving 3D scanning imaging. Ultimately, the system seamlessly integrates LabVIEW software, confocal scanning system, DAQ card, 3D sample stage, and TCSPC card into a single platform for multifunctional fluorescence imaging. All imaging operations are perform within a single software interface, which outputs image data for further processing. Compared to commercial FLIM systems that run on multiple independent software platforms, our system minimizes unexpected errors and delays caused by inter- software communication and file transfer, successfully achieving multifunctional imaging.

One of the most significant advances in stimulated emission depletion (STED) super-resolution microscopy is its capacity for dynamic super-resolution imaging of living cells, including the long-term tracking of interactions between various cells or organelles. Consequently, the multicolor STED plays a pivotal role in biological research. Despite the emergence of numerous fluorescent probes characterized by low toxicity, high stability, high brightness, and exceptional specificity, enabling dynamic imaging of living cells with multicolor STED, practical implementation of multicolor STED for live-cell imaging is influenced by several factors. These factors include the power and wavelength of the STED beam, the duration of imaging, the size of the imaging area, and the complexity of sample preparation. Presently, a major limitation of multicolor STED is the requirement for high STED power, which hinders the monitoring of interactions between different cells or organelles due to the associated irreversible optical damage. To address this issue, this paper emphasizes research findings based on the digitally enhanced STED (DE-STED) technique. This method overcomes the aforementioned challenge by utilizing low STED laser power to achieve prolonged two-color STED super-resolution imaging of living cells, effectively mitigating phototoxic effects and enhancing the capacity to observe intracellular dynamics. With a depletion laser power of less than 1 mW, we achieved a resolution of about 87 nm, close to that achievable with conventional high-power STED technology.

Large Language Models (LLMs) have already demonstrated excellent performance in code generation tasks. However, their proficiency varies considerably among different programming languages, performing well in languages like Python, but struggling with languages such as C++ and Java. This discrepancy limits their utility in scenarios requiring multi-language support. Existing methods aimed at enhancing the code generation capabilities of LLMs typically emphasize general performance improvements while overlooking discrepancies between languages, resulting in suboptimal outcomes for less proficient languages. To address this challenge, we propose MetaCoder. Given a task description, MetaCoder first generates code in high-proficiency language, and then summarizes the code. Finally, MetaCoder generates target code using the task description, generated code, and summary. Additionally, MetaCoder detects and corrects syntax errors in the target code. We evaluate MetaCoder on HumanEval-x, and compared with Zero-Shot, the Pass@1 in generating C++ and Java code has improved by up to 13.09% and 16.98%, respectively.

Bone mass loss resulting from mechanical unloading in a microgravity environment constitutes a primary impediment to the advancement of space exploration for astronauts. However, the underlying mechanism remains unclear. In this study, we primarily investigated the impact of pyroptosis on osteoblasts under simulated microgravity and its influence on osteoblast functionality. A rotary cell culture system was employed to establish a simulated microgravity environment. The proliferation of osteoblasts was assessed by cell counting kit-8 (CCK-8) assay. Lactate dehydrogenase (LDH) Release Assay Kit was used to measure cell necrosis. Osteoblast differentiation and mineralization were evaluated using an ALP kit and alizarin red staining. Fluorescence Hoechst/PI double staining and scanning electron microscopy (SEM) were used to detect pyroptosis, and a caspase-1 kit measured caspase-1 activity. The expression of NLRP3, caspase-1, GSDMD, IL-1β, IL-18, OCN, and COL-I was analyzed by qPCR and Western blot. Additionally, ELISA was used to quantify the release of IL-1β and IL-18. The PI fluorescence in osteoblasts exhibited significant enhancement under simulated microgravity conditions, accompanied by increased membrane pore formation, decreased cell proliferation, and elevated LDH release. Moreover, the expression levels of NLRP3, caspase-1, GSDMD, IL-1β, and IL-18 were upregulated while caspase-1 activity was increased. Treatment with MCC950 and VX-765 effectively attenuated pyroptosis levels as well as caspase-1 activity while reducing the expression of NLRP3, GSDMD, IL-1β, and IL-18. Notably, this treatment significantly enhanced the expression of OCN and COL-I. Under simulated microgravity conditions, pyroptosis occurs in osteoblasts and alters their osteogenic differentiation function. Pyroptosis modulates the functionality of osteoblasts and contributes to the mechanical response process, potentially serving as one of the mechanisms underlying mechanical-regulated osteoblast function in a microgravity environment. This finding may offer a novel approach for addressing bone tissue damage and repair under extreme mechanical conditions. Not applicable.

BACKGROUND:Bone loss is a significant health concern during spaceflight and mechanical unloading. Simulated microgravity (SMG) disrupts bone homeostasis by inhibiting osteoblast proliferation and differentiation while promoting apoptosis. Although these functional effects have been reported, the underlying mechanisms remain unclear. Mitochondrial quality control, particularly mitophagy involving the PINK1/Parkin pathway, may play a key role. This study aimed to investigate the relationship between osteogenic dysfunction and mitochondrial damage under SMG conditions and preliminarily validate the potential link using the small molecule probe icariin (ICA). METHODS:An SMG model was established using a rotary cell culture system. Cell proliferation was assessed by CCK-8 assay, apoptosis was analyzed via flow cytometry, and osteogenic differentiation was evaluated by alkaline phosphatase (ALP) and Alizarin Red staining. Expression levels of relevant genes and proteins were measured by qPCR and Western blot. Mitochondrial function was assessed through ATP content, reactive oxygen species (ROS) levels, JC-1 staining for mitochondrial membrane potential, and transmission electron microscopy (TEM) for ultrastructural observation. Additionally, cells were treated with the mitochondrial function-related small molecule icariin (ICA) to observe its regulatory effects on mitophagy markers (PINK1, Parkin, p62, LC3B) expression and osteogenic function. RESULTS:SMG significantly inhibited osteoblast proliferation and differentiation and induced apoptosis. These changes were accompanied by impaired mitochondrial function and downregulated expression of mitophagy-related genes. TEM revealed mitochondrial swelling and disrupted cristae structure. Treatment with ICA partially restored mitochondrial function and mitophagy marker expression, along with improved expression of osteogenic markers and cell viability. CONCLUSIONS:SMG induces osteogenic dysfunction, mitochondrial damage, and downregulation of mitophagy-related gene expression. The results suggest that impaired mitophagy may be a key mechanism underlying unloading-induced bone loss, and ICA, as a small molecule modulator, holds potential as a therapeutic intervention. CLINICAL TRIAL NUMBER:Not applicable.

Preeclampsia (PE) is a common pregnancy complication and the leading cause of maternal and perinatal mortality. Unfortunately, the early diagnostic methods for PE are still rare. Fluorescence lifetime imaging (FLIM) technology has proven to be applicable for diagnosis of various diseases. Here, we explore the possibility of the FLIM technique for PE early diagnosis and severity prediction with Nile Blue probe as biosensor. 23 placental slices and 162 third-trimester-collected maternal peripheral blood serum samples were stained with Nile blue and imaged by FLIM system. Fluorescence lifetimes of the probe increased significantly as the disease worsened (p < 0.0001). Characterization of the probe showed an increasing tendency in lifetimes under lower polarity conditions and revealed that the reason for the lifetime differences in serum sample was polarity changes caused by abnormal lipid metabolism in serum. For early diagnosis, we investigated 42 12th-week-collected chronic hypertension (CH) serum samples and successfully distinguished PE patients from pregnant women. With the functions of measuring fluorescence lifetime and detecting polarity changes caused by an abnormal lipid microenvironment in maternal peripheral blood, FLIM technology, together with Nile Blue probe, presents a feasible and advantageous approach for PE early noninvasive diagnosis and severity prediction.

Background Repairation of bone defects remains a major clinical problem. Constructing bone tissue engineering containing growth factors, stem cells, and material scaffolds to repair bone defects has recently become a hot research topic. Nerve growth factor (NGF) can promote osteogenesis of bone marrow mesenchymal stem cells (BMSCs), but the low survival rate of the BMSCs during transplantation remains an unresolved issue. In this study, we investigated the therapeutic effect of BMSCs overexpression of NGF on bone defect by inhibiting pyroptosis. Methods The relationship between the low survival rate and pyroptosis of BMSCs overexpressing NGF in localized inflammation of fractures was explored by detecting pyroptosis protein levels. Then, the NGF + /BMSCs-NSA-Sca bone tissue engineering was constructed by seeding BMSCs overexpressing NGF on the allograft bone scaffold and adding the pyroptosis inhibitor necrosulfonamide(NSA). The femoral condylar defect model in the Sprague-Dawley (SD) rat was studied by micro-CT, histological, WB and PCR analyses in vitro and in vivo to evaluate the regenerative effect of bone repair. Results The pyroptosis that occurs in BMSCs overexpressing NGF is associated with the nerve growth factor receptor (P75NTR) during osteogenic differentiation. Furthermore, NSA can block pyroptosis in BMSCs overexpression NGF. Notably, the analyses using the critical-size femoral condylar defect model indicated that the NGF + /BMSCs-NSA-Sca group inhibited pyroptosis significantly and had higher osteogenesis in defects. Conclusion NGF + /BMSCs-NSA had strong osteogenic properties in repairing bone defects. Moreover, NGF + /BMSCs-NSA-Sca mixture developed in this study opens new horizons for developing novel tissue engineering constructs.

Stimulated emission depletion (STED) microscopy holds tremendous potential and practical implications in the field of biomedicine. However, the weak anti-bleaching performance remains a major challenge limiting the application of STED fluorescent probes. Meanwhile, the main excitation wavelengths of most reported STED fluorescent probes were below 500 nm or above 600 nm, and few of them were between 500-600 nm. Herein, we developed a new tetraphenyl ethylene-functionalized rhodamine dye (TPERh) for mitochondrial dynamic cristae imaging that was rhodamine-based with an excitation wavelength of 560 nm. The TPERh probe exhibits excellent anti-bleaching properties and low saturating stimulated radiation power in mitochondrial STED super-resolution imaging. Given these outstanding properties, the TPERh probe was used to measure mitochondrial deformation, which has positive implications for the study of mitochondria-related diseases.

Bone is the main site of metastasis from prostate cancer; therefore, it is important to investigate the microRNAs (miRNAs) and mRNA associated with bone metastases from prostate cancer. Since an appropriate mechanical environment is important in the growth of bone, in the present study, the miRNA, mRNA, and long non-coding RNA (lncRNA) profiles of mechanically strained osteoblasts treated with conditioned medium (CM) from PC-3 prostate cancer cells were studied. MC3T3-E1 osteoblastic cells were treated with the CM of PC-3 prostate cancer cells and were simultaneously stimulated with a mechanical tensile strain of 2,500 µε at 0.5 Hz; the osteoblastic differentiation of the MC3T3-E1 cells was then assessed. In addition, the differential expression levels of mRNA, miRNA and lncRNA in MC3T3-E1 cells treated with the CM of PC-3 cells were screened, and some of the miRNAs and mRNAs were verified by reverse transcription-quantitative PCR (RT-qPCR). The signal molecules and signaling pathways associated with osteogenic differentiation were predicted by bioinformatics analysis. The CM of PC-3 prostate cancer cells suppressed osteoblastic differentiation of MC3T3-E1 cells. A total of seven upregulated miRNAs and 12 downregulated miRNAs were selected by sequencing and further verified using RT-qPCR, and related differentially expressed genes (11 upregulated and 12 downregulated genes) were also selected by sequencing and further verified using RT-qPCR; subsequently, according to the enrichment of differentially expressed genes in signaling pathways, nine signaling pathways involved in osteogenic differentiation were screened out. Furthermore, a functional mRNA-miRNA-lncRNA regulatory network was constructed. The differentially expressed miRNAs, mRNAs and lncRNAs may provide a novel signature in bone metastases of prostate cancer. Notably, some of the signaling pathways and related genes may be associated with pathological osteogenic differentiation caused by bone metastasis of prostate cancer.

Fluorescence correlation spectroscopy (FCS) is a powerful technique that combines single-molecule fluorescence detection technology with statistical spectroscopy methods. It utilizes confocal fluorescence measurement optical design and single-photon counting methods to measure the fluctuation of fluorescence signals caused by the movement of fluorescent molecules in a small detection volume. By analyzing the correlation function of these fluctuations, important parameters such as the rate of diffusion and the average number of molecules in the detection space can be obtained. This technique is widely used in various fields including biomedicine, biophysics, and chemistry due to its high resolution and sensitivity. In 1993, Rigler et al. demonstrated that FCS can be used for single-molecule detection, which opened the doors for the single-point FCS application in the biological field. Initially, single-point FCS could only be applied to a single community, but the development of fluorescence cross-correlation spectroscopy (FCCS) made it possible to measure interactions between different species. However, parameters such as labeling efficiency and binding stoichiometry can introduce artifacts in FCCS. Sweeping FCS overcomes the limitation of single-point FCS, which is suitable only for the measurement of slowly diffusing substances or biological structures. Moreover, when combined with stimulated emission depletion (STED) imaging techniques, it enables the study of molecular diffusion patterns at spatial scales below the diffraction limit of light. Bifocal FCS avoids recalibration of the system by defining two overlapping laser spots at fixed distances. Multi-parallel FCS (mp FCS) maximizes data utilization and enables analysis of different FCS techniques in a single measurement. Scanning FCS is widely used for measuring membrane proteins and distinguishing specific protein domains based on different diffusion coefficients. Combined with STED technology, it can directly observe nanoscale dynamics of membrane lipids in living cells. FCS has also been employed to investigate the impact of chromatin on the diffusion of inert fluorescent tracers, specifically GFP oligomers, of varying sizes. This analysis provides insights into cell permeability and microstructures. In order to determine the oligomeric state of fluorescent proteins, it is occasionally required to conduct PCH and N&B analyses. FCCS is often utilized to study protein-protein interactions, protein-nucleic acid interactions, and nucleus-nucleic acid interactions. However, caution is necessary when interpreting enzyme kinetics using FCS, as enhanced enzyme diffusion may be related to average FCS measurements. FCS can be combined with light sheet microscopy to measure 3D samples including cells and small organisms. Despite its usefulness, FCS also faces challenges. Firstly, FCS is restricted to a specific concentration range. Secondly, the interpretation of the correlation function relies on fitting it to a theoretical model, the selection of which may be ambiguous. Lastly, the data quantity in the multiplexed FCS model poses difficulties in both fitting the data and providing explanations. FCS has experienced significant expansion and has been customized to address specific biological inquiries. This diverse growth enables the measurement of molecular interactions in living samples, granting accessibility to a broader range of researchers. It is our belief that these advancements in FCS technology will continue to contribute significantly to the field of life sciences, facilitating the resolution of complex biological problems.

The interpretation of semi-airborne transient electromagnetic data is mainly based on a one-dimensional inversion algorithm. The continuity of the resistivity profile is generally poor when the data noise is strong because the resistivity is laterally unconstrained, and the constraint between the resistivity in the vertical distribution is usually taken as the L2 norm regular term. However, the main disadvantage of this regularization constraint is that it over-smoothens the model and cannot effectively describe the interface information of an abrupt electrical change. To address these issues, this paper proposes a mixed norm spatially constrained inversion (SCI) algorithm that adopts the L1 norm regularization term for the vertical spatial constraint and the L2 norm regularization term for the lateral spatial constraint. The Gauss-Newton iterative method is used to solve the objective function. Fixed and adaptive strategies are proposed for the regularization factors, and a parameter is used to adjust the weights of the two constraints. The influence of different constraint weights on the results is analyzed. The inversion of noisy synthetic data verifies that the proposed SCI algorithm has a higher resolution for electrical interfaces and better noise suppression effect than the L2 norm SCI algorithm. The inversion of field data shows a good effect and practicability.

3D convolution can fully utilize the spectral-spatial characteristics of hyperspectral image (HSI), and stacked blocks with deep layers are capable of extracting hidden features and utilizing discriminant information for classification. Naturally, a 3D convolutional neural network (CNN) based on stacked blocks named SB-3D-CNN is presented for HSI classification. Moreover, the proposed network introduces the attention mechanism before the fully connected layer, which can filter out interfering information effectively. Then we optimized the architecture to obtain optimal results on three commonly used datasets of Indian Pines, Salinas and Pavia University. Experimental results demonstrate that the optimized architecture achieves better classification rates than related recent works. Because the classification accuracies on the three datasets have reached saturation, we transferred the optimized architecture to a more complex dataset adopting the airborne hyperspectral data, which obtains from Guangxi province in south China. The results show that the optimized architecture achieves superior classification accuracies compared with other state-of-the-art methods. These results also demonstrate the optimized SB-3D-CNN has the advantages of validity and portability to more complex data.

Although conventional fluorescence intensity imaging can be used to qualitatively study the drug toxicity of nanodrug carrier systems at the single-cell level, it has limitations for studying nanodrug transport across membranes. Fluorescence correlation spectroscopy (FCS) can provide quantitative information on nanodrug concentration and diffusion in a small area of the cell membrane; thus, it is an ideal tool for studying drug transport across the membrane. In this paper, the FCS method was used to measure the diffusion coefficients and concentrations of carbon dots (CDs), doxorubicin (DOX) and CDs-DOX composites in living cells (COS7 and U2OS) for the first time. The drug concentration and diffusion coefficient in living cells determined by FCS measurements indicated that the CDs-DOX composite distinctively improved the transmembrane efficiency and rate of drug molecules, in accordance with the conclusions drawn from the fluorescence imaging results. Furthermore, the effects of pH values and ATP concentrations on drug transport across the membrane were also studied. Compared with free DOX under acidic conditions, the CDs-DOX complex has higher cellular uptake and better transmembrane efficacy in U2OS cells. Additionally, high concentrations of ATP will cause negative changes in cell membrane permeability, which will hinder the transmembrane transport of CDs and DOX and delay the rapid diffusion of CDs-DOX. The results of this study show that the FCS method can be utilized as a powerful tool for studying the expansion and transport of nanodrugs in living cells, and might provide a new drug exploitation strategy for cancer treatment in vivo.

A multilayer graphene frequency doubler (GFD) with inductance–capacitor resonators (LCRs) and microstrip reflective stubs (MRS) is proposed in this paper. Graphene has strong nonlinear characteristics. Under the excitation of electromagnetic waves, the output power of odd harmonic of graphene is greater than that of even harmonic. Under the joint excitation of electromagnetic wave and bias voltage, the even harmonic output power of graphene is enhanced and the odd harmonic is suppressed, which is very suitable for making GFD. On the basis of analyzing the conductivity of graphene, the symbolically defined device model of multilayer graphene is established, and the model is applied to GFD circuit, the simulation results are basically consistent with the experimental data. The multiplier efficiency of graphene can be effectively improved by the bias voltage and LCR and the MRS. At an operating frequency of 0.65–1.15 GHz, the minimum conversion loss (CL) of the GFD is 20.57 dB when the input power is 16 dBm.

目的 筛选骨细胞分泌因子相关力学响应微小RNA(microRNA,miRNA).方法 分别向体外培养骨细胞和成骨细胞施加周期性张应变(ε=2.5,f=0.5 Hz),采用miRNA芯片筛选出仅在骨细胞中差异表达的miRNA.通过生物信息学技术,从这些miRNA中进一步筛选出靶基因为胰岛素样生长因子1(insulin-like growth factor-1)、NO合成酶(nitric oxide synthesase,NOS)、成纤维细胞生长因子23(fibroblast growth factor 23,FGF23)和硬骨素(sclerostin,SOST)等分泌因子的miRNA,与小鼠跑台锻炼后芯片检测出的小鼠股骨组织差异表达miRNA进行比较,然后随机选4个miRNA进行定量PCR验证.结果 仅在体外经力学刺激的骨细胞中差异表达的77个miRNA中,筛选出22个靶基因为4种分泌因子(IGF-1、NOS、FGF23、SOST)的miRNA,并进一步筛选出11个在跑台锻炼后的小鼠骨组织中以同样趋势差异表达的miRNA,其中随机选出的miR-361-3p、miR-3082-5p、miR-6348和miR-706,也在骨细胞和骨组织中以同样趋势同样差异表达.结论 诸如miR-361-3p、miR-3082-5p、miR-6348和miR-706仅在骨细胞中差异表达的力学响应miRNA,很可能通过调节分泌因子影响成骨分化或骨代谢.

We report a deep penetration microscopic imaging method with a non-diffracting Airy beam. The direct mapping of volume imaging in free space shows that the axial imaging range of the Airy beam is approximately 4 times that of the traditional Gaussian beam along the axial direction while maintaining a narrow lateral width. Benefiting from its non-diffracting property, the microscopic imaging with Airy beam illumination can acquire image structures through turbid medium and capture a volumetric image in a single frame. We demonstrate the penetration ability of the Airy microscopic imaging through a strongly scattering environment with 633 nm and 780 nm lasers. The performances of the volumetric imaging method were evaluated using HeLa cells and isolated mouse kidney tissue. The thick sample was scanned layer by layer in the Gaussian mode, however, in the Airy mode, the three-dimensional (3D) structure information was projected onto a two-dimensional (2D) image, which vastly increased the volume imaging speed. To show the characteristics of the Airy microscope, we performed dynamic volumetric imaging on the isolated mouse kidney tissue with two-photon.

The rapid development of remote sensing technologies has yielded a large amount of high-resolution remote sensing (HRRS) data. However, effectively extracting information from these large datasets is a significant challenge. In this study, a state-of-the-art convolutional neural network was extended for HRRS image classification by establishing an integrated structure including three branches of a pruned DenseNet, a decoder, and an encoder (PDDE-Net). PDDE-Net initially combines deep-level features extracted from the pruned DenseNet with middle-level features extracted from the designed encoder. Subsequently, the designed decoder branch extracts the merged features to obtain more feature expressions. In addition, the earlystop strategy is used to prevent overfitting during the training process. Experiments performed on an aerial image dataset demonstrated that the proposed network can achieve favorable overall accuracy and Kappa values of 90% and 0.897, respectively. Further, under the condition of imbalanced data, two merging methods—concatenation and summation—were applied to test the sensitivity of the integrated PDDE-Net to the feature size. The results on the remote sensing image classification benchmark datasets revealed little difference between the two merging methods, both of which exhibited accuracies greater than 95%. Moreover, the integrated PDDE-Net was tested on hyperspectral remote sensing data, and it achieved a high classification accuracy comparable to those of other advanced methods, which also demonstrated the generalizability of the proposed model.

骨细胞是骨组织主要的力学感受及转导细胞,它们通过众多突触结构相互连接,形成庞大的骨稳态细胞调控网络,联系着成骨细胞、破骨细胞等骨基质表面细胞.骨细胞通过旁分泌途径影响成骨细胞骨形成和破骨细胞骨吸收来调节骨代谢,维持骨更新.针对骨细胞在受到力学刺激后分泌或释放的一些信号分子或蛋白因子对成骨细胞和破骨细胞生长分化的影响,本文综述近年来关于受力学刺激的骨细胞如何与成骨/破骨细胞进行通讯,为骨细胞生物力学研究提供新思路.