Treatment strategies for hard tissue defects aim to establish a mineralized microenvironment that facilitates tissue remodeling. As a mineralized tissue, cementum shares a similar structure with bone and exhibits an excellent capacity to resist resorption under compression. Macrophages are crucial for mineralized remodeling; however, their functional alterations in the microenvironment of cementum remain poorly understood. Therefore, this study explores the mechanisms by which cementum resists resorption under compression and the regulatory roles of cementoblasts in macrophage functions. As a result, extracellular vesicles from compression-loaded cementoblasts (Comp-EVs) promote macrophage M2 polarization and enhance the clearance of apoptotic cells (efferocytosis) by 2- to 3-fold. Local injection of Comp-EVs relieves cementum destruction in mouse root resorption model by activating the tissue repair function of macrophages. Moreover, Comp-EV-loaded hydrogels achieve significant bone healing in calvarial bone defect. Unexpectedly, under compression, EV secretion in cementoblasts is reduced by half. RNA-Seq analysis and verification reveal that Rab35 expression decreases by 60% under compression, thereby hampering the release of EVs. Rab35 overexpression is proposed as a modification of cementoblasts to boost the yield of Comp-EVs. Collectively, Comp-EVs activate the repair function of macrophages, which will be a potential therapeutic strategy for hard tissue repair and regeneration.

UNASSIGNED: In this study, we aim to describe the radiological characteristics of degenerative cervical kyphosis (DCK) with cervical spondylotic myelopathy (CSM) and discuss the relationship between DCK and the pathogenesis of spinal cord dysfunction.
UNASSIGNED: In total, 90 patients with CSM hospitalized in our center from September 2017 to August 2022 were retrospectively examined in this study; they were then divided into the kyphosis group and the nonkyphosis group. The patients\' demographics, clinical features, and radiological data were obtained, including gender, age, duration of illness, cervical Japanese Orthopaedic Association (JOA) score, cervical lordosis (CL), height of intervertebral space, degree of wedging vertebral body, degree of osteophyte formation, degree of disc herniation, degree of spinal cord compression, and anteroposterior diameter of the spinal cord. In the kyphosis group, kyphotic segments, apex of kyphosis, and segmental kyphosis angle were recorded. Radiological characteristics between the two groups were also compared. Correlation analysis was performed for different spinal cord compression types.
UNASSIGNED: As per our findings, the patients in the kyphosis group showed more remarkable wedging of the vertebral body, more severe anterior compression of the spinal cord, and a higher degree of disc herniation, while the posterior compression of the spinal cord was relatively mild when compared with the nonkyphosis group. CL was related to the type of spinal cord compression, as cervical kyphosis is an independent risk factor for anterior spinal cord compression.
UNASSIGNED: DCK might play a vital role in the pathogenesis of spinal cord dysfunction. In patients with DCK, it was determined that the anterior column is less supported, and more severe anterior spinal cord compression is present. The anterior approach is supposed to be preferred for CSM patients with DCK.

UNASSIGNED: Digital radiography (DR) is a common and widely available examination. However, spinal DR cannot detect bone marrow edema, therefore, determining vertebral compression fractures (VCFs), especially fresh VCFs, remains challenging for clinicians.
UNASSIGNED: We trained, validated, and externally tested the deep residual network (DRN) model that automated the detection and identification of fresh VCFs from spinal DR images. A total of 1,747 participants from five institutions were enrolled in this study and divided into the training cohort, validation cohort and external test cohorts (YHDH and BMUH cohorts). We evaluated the performance of DRN model based on the area under the receiver operating characteristic curve (AUC), feature attention maps, sensitivity, specificity, and accuracy. We compared it with five other deep learning models and validated and tested the model internally and externally and explored whether it remains highly accurate for an external test cohort. In addition, the influence of old VCFs on the performance of the DRN model was assessed.
UNASSIGNED: The AUC was 0.99, 0.89, and 0.88 in the validation, YHDH, and BMUH cohorts, respectively, for the DRN model for detecting and discriminating fresh VCFs. The accuracies were 81.45% and 72.90%, sensitivities were 84.75% and 91.43%, and specificities were 80.25% and 63.89% in the YHDH and BMUH cohorts, respectively. The DRN model generated correct activation on the fresh VCFs and accurate peak responses on the area of the target vertebral body parts and demonstrated better feature representation learning and classification performance. The AUC was 0.90 (95% confidence interval [CI] 0.84-0.95) and 0.84 (95% CI 0.72-0.93) in the non-old VCFs and old VCFs groups, respectively, in the YHDH cohort (p = 0.067). The AUC was 0.89 (95% CI 0.84-0.94) and 0.85 (95% CI 0.72-0.95) in the non-old VCFs and old VCFs groups, respectively, in the BMUH cohort (p = 0.051).
UNASSIGNED: In present study, we developed the DRN model for automated diagnosis and identification of fresh VCFs from spinal DR images. The DRN model can provide interpretable attention maps to support the excellent prediction results, which is the key that most clinicians care about when using the model to assist decision-making.

Thermal-mechanical coupling during the molding process can cause compressive yield in the polymer foam core and then affect the molding quality of the sandwich structure. This work investigates the compressive mechanical properties and failure mechanism of polymethacrylimide (PMI) foam in the molding temperature range of 20-120 °C. First, the DMA result indicates that PMI foam has minimal mechanical loss in the 20~120 °C range and can be regarded as an elastoplastic material, and the TGA curve further proves that the PMI foam is thermally stable within 120 °C. Then, the compression results show that compared with 20 °C, the yield stress and elastic modulus of PMI foam decrease by 22.0% and 17.5% at 80 °C and 35.2% and 31.4% at 120 °C, respectively. Meanwhile, the failure mode changes from brittle fracture to plastic yield at about 80 °C. Moreover, a real representative volume element (rRVE) of PMI foam is established by using Micro-CT and Avizo 3D reconstruction methods, and the simulation results indicate that PMI foam mainly shows brittle fractures at 20 °C, while both brittle fractures and plastic yield occur at 80 °C, and most foam cells undergo plastic yield at 120 °C. Finally, the simulation based on a single-cell RVE reveals that the air pressure inside the foam has an obvious influence of about 6.7% on the yield stress of PMI foam at 80 °C (brittle-plastic transition zone).

The mechanical properties of porcupine quills have attracted the interest of researchers due to their unique structure and composition. However, there is still a knowledge gap in understanding how these properties can be utilized to design biomimetic structures with enhanced performance. This study delves into the nanomechanical and macro-mechanical properties of porcupine quills, unveiling varied elastic moduli across different regions and cross sections. The results indicated that the elastic moduli of the upper and lower epidermis were higher at 8.13 ± 0.05 GPa and 7.71 ± 0.14 GPa, respectively, compared to other regions. In contrast, the elastic modulus of the mid-dermis of the quill mid-section was measured to be 7.16 ± 0.10 GPa. Based on the micro- and macro-structural analysis of porcupine quills, which revealed distinct variations in elastic moduli across different regions and cross sections, various biomimetic porous structures (BPSs) were designed. These BPSs were inspired by the unique properties of the quills and aimed to replicate and enhance their mechanical characteristics in engineering applications. Compression, torsion, and impact tests illustrated the efficacy of structures with filled hexagons and circles in improving performance. This study showed enhancements in maximum torsional load and crashworthiness with an increase in filled structures. Particularly noteworthy was the biomimetic porous circular structure 3 (BPCS_3), which displayed exceptional achievements in average energy absorption (28.37 J) and specific energy absorption (919.82 J/kg). Finally, a response surface-based optimization method is proposed to enhance the design of the structure under combined compression-torsion loads, with the goal of reducing mass and deformation. This research contributes to the field of biomimetics by exploring the potential applications of porcupine quill-inspired structures in fields such as robotics, drive shafts, and aerospace engineering.

Objective.Recently, the demand for wearable devices using electroencephalography (EEG) has increased rapidly in many fields. Due to its volume and computation constraints, wearable devices usually compress and transmit EEG to external devices for analysis. However, current EEG compression algorithms are not tailor-made for wearable devices with limited computing and storage. Firstly, the huge amount of parameters makes it difficult to apply in wearable devices; secondly, it is tricky to learn EEG signals\' distribution law due to the low signal-to-noise ratio, which leads to excessive reconstruction error and suboptimal compression performance.Approach.Here, a feature enhanced asymmetric encoding-decoding network is proposed. EEG is encoded with a lightweight model, and subsequently decoded with a multi-level feature fusion network by extracting the encoded features deeply and reconstructing the signal through a two-branch structure.Main results.On public EEG datasets, motor imagery and event-related potentials, experimental results show that the proposed method has achieved the state of the art compression performance. In addition, the neural representation analysis and the classification performance of the reconstructed EEG signals also show that our method tends to retain more task-related information as the compression ratio increases and retains reliable discriminative information after EEG compression.Significance.This paper tailors an asymmetric EEG compression method for wearable devices that achieves state-of-the-art compression performance in a lightweight manner, paving the way for the application of EEG-based wearable devices.

Although many risk factors for residual pain following percutaneous vertebroplasty or kyphoplasty (PVP or PKP) have been reported in many studies, research methods and cohorts differ greatly. A previous meta-analysis identified patient- and operation-specific risk factors for residual pain. This study aimed to examine the available data and identify significant risk factors for residual pain after PVP or PKP.
PubMed, EMBASE, Web of Science, and the Chinese Wanfang Database were searched for relevant research in English and Chinese, and full-text publications including patients with and without residual pain were compared. Only studies presenting odds ratios from multivariate analysis of residual pain data were considered. To evaluate the impact of the results of the selected articles, Review Manager 5.4 was used.
Twelve publications including a total of 3120 patients met the requirements. The meta-analysis examined 10 factors associated with residual pain and categorized them as either patient- or operation-associated factors. Thoracolumbar fascia injury, intravertebral vacuum cleft, depression, and number of fractured vertebrae were all significant patient-associated parameters for residual pain. Significant operation-associated risk factors included bone cement distribution and intraoperative facet joint injury.
In this meta-analysis, we identified several significant risk factors for residual pain after PVP or PKP. These findings may be helpful for patient counseling and surgical planning.

Mandarin is vulnerable to a range of external loads during processing and shipping, which can cause interior mechanical damage that can happen right away or over time and cause serious rotting when kept in storage. In this study, mandarin was treated to a certain quantity of compression load that did not result in a noticeable rupture of the peel. The interior pulp structure of mandarin was examined for damage prior to peel damage using CT scanning and image reconstruction. An image segmentation method based on mask processing was then used to calculate the pulp damage rate. We examined the variations in physiological activities and internal components between the test group that underwent compression load and the control group that did not undergo this type of stress during storage. The aim was to investigate the factors that contributed to the faster decay of mandarin following mechanical damage. Regression analysis was also used to establish a quantifiable relationship between the amount of compression deformation and the rates of damage and decay of mandarin during storage. The findings demonstrated that mandarin pulp exhibited visible mechanical damage when compression deformation exceeded 8 mm. This led to the disruption of physiological processes like respiration and polysaccharide breakdown, which in turn decreased the hardness of the fruit and sped up its rotting. This study identifies the critical range of compression deformation that leads to the beginning of pulp damage in mandarins. Additionally, it clarifies the quality deterioration mechanism of mandarins that have been subjected to compression damage during the storage period. Therefore, in practical production, various methods of picking, sorting, and collecting mandarins can be optimized to control the amount of compression deformation within a suitable range. This will reduce the probability of pulp damage. According to the study\'s conclusions, storage conditions can be optimized to regulate the physiological activities of mandarins in a targeted manner. This can minimize the probability of fruit decay and reduce economic losses.

Achieving the real mechanical performance of construction materials is significantly important for the design and engineering of structures. However, previous researchers have shown that contact friction performs an important role in the results of uniaxial compression tests. Strong discreteness generally appears in concrete-like construction materials due to the random distribution of the components. A numerical meso-scale finite-element (FE) method provides the possibility of generating an ideal material with the same component percentages and distribution. Thus, a well-designed meso-FE model was employed to investigate the effect of friction on the mechanical behavior and failure characteristics of concrete under uniaxial compression loading. The results showed that the mechanical behavior and failure profiles of the simulation matched well with the experimental results. Based on this model, the effect of friction was determined by changing the contact friction coefficient from 0.0 to 0.7. It was found that frictional contact had a slight influence on the elastic compressive mechanical behavior of concrete. However, the nonlinear hardening behavior of the stress-strain curves showed a fairly strong relationship with the frictional contact. The final failure profiles of the experiments showed a \"sand-glass\" shape that might be expected to result from the contact friction. Thus, the numerical meso-scale FE model showed that contact friction had a significant influence on both the mechanical performance and the failure profiles of concrete.

In the handling or processing process, fruits are easily crushed by external loads. This type of damage in fruit often leads to the internal pulp browning and rotting, with the severity largely dependent on the fruit tissue\'s geometric and mechanical properties. In kiwifruits, with their thin skin and dark-colored flesh, it is particularly challenging to observe and analyze the damage caused by extrusion through traditional experimental methods. The objective of this research is to construct a multi-scale finite element model encompassing the skin, flesh, and core by measuring the geometric and mechanical properties of kiwifruit, to assess and predict the damage characteristics under compression, and to verify the accuracy of the finite element model through experiments. The results indicated that kiwifruits demonstrated different compressive strengths in different directions during compression. The compressive strength in the axial direction was higher than that in the radial direction, and there was little difference between the long and short radial directions. The flesh tissue is the most vulnerable to mechanical damage under external compression, followed by the core. At strain levels below 5%, there was no noticeable damage in the axial or radial directions of the kiwifruit. However, when strain exceeded 5%, damage began to manifest in some of the flesh tissue. To maintain fruit quality during storage and transportation, the stacking height should not exceed 77 fruits in the axial direction, 48 in the long direction, and 53 in the short direction. The finite element analysis showed that the established model can effectively simulate and predict the internal damage behavior of kiwifruits under compression loads, which is helpful for a deeper understanding of the mechanical properties of fruits and provides a theoretical basis and technical guidance for minimizing mechanical damage during fruit handling.