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Compared to integrated large screen displays, the splicing scheme that uses multiple display units for splicing has significant advantages in various aspects to achieve large screen displays. This article is based on MLCD (Mini LCD) display scheme that combines LCD and LED, and proposes various algorithms to improve the image quality of the splicing. It effectively solves the image quality problems that occur in MLCD display schemes, while taking into account the advantages of cost and maintenance, it can also fully leverage the image quality advantages. The splicing image quality improvement algorithm not only fills the gap in display effect improvement methods in the splicing display field, but also provides new ideas for the development of large screen image quality improvement technology.

Current in vitromodels for osteosarcoma investigation and drug screening, including two-dimensional (2D) cell culture and tumour spheroids (i.e. cancer stem-like cells), lack extracellular matrix (ECM). Therefore, results from traditional models may not reflect real pathological processes in genuine osteosarcoma histological structures. Here, we report a three-dimensional (3D) bioprinted osteosarcoma model (3DBPO) that contains osteosarcoma cells and shrouding ECM analogue in a 3D frame. Photo-crosslinkable bioinks composed of gelatine methacrylamide and hyaluronic acid methacrylate mimicked tumour ECM. We performed multi-omics analysis, including transcriptomics and DNA methylomics, to determine differences between the 3DBPO model and traditional models. Compared with 2D models and tumour spheroids, our 3DBPO model showed significant changes in cell cycle, metabolism, adherens junctions, and other pathways associated with epigenetic regulation. The 3DBPO model was more sensitive to therapies targeted to the autophagy pathway. We showed that simulating ECM yielded different osteosarcoma cell metabolic characteristics and drug sensitivity in the 3DBPO model compared with classical models. We suggest 3D printed osteosarcoma models can be used in osteosarcoma fundamental and translational research, which may contribute to novel therapeutic strategy discovery.

To evaluate the interbody fusion efficacy and biocompatibility of a graft-free cage made of polyetheretherketone/calcium silicate composite/porous tantalum (PEEK/CS/pTa cage) compared with a PEEK/CS cage with an autogenous bone graft in a goat model.

Osteoarthritis (OA) is a chronic joint disease characterized by progressive degeneration of articular cartilage. A challenge in the development of disease-modifying drugs is effective delivery to chondrocytes. The unique structure of the joint promotes rapid clearance of drugs through synovial fluid, and the dense and avascular cartilage extracellular matrix (ECM) limits drug penetration. Here, we show that poly(lactide-co-glycolic acid) nanoparticles coated in chondrocyte membranes (CM-NPs) were preferentially taken up by rat chondrocytes ex vivo compared with uncoated nanoparticles. Internalization of the CM-NPs was mediated primarily by E-cadherin, clathrin-mediated endocytosis, and micropinocytosis. These CM-NPs adhered to the cartilage ECM in rat knee joints in vivo and penetrated deeply into the cartilage matrix with a residence time of more than 34 days. Simulated synovial fluid clearance studies showed that CM-NPs loaded with a Wnt pathway inhibitor, adavivint (CM-NPs-Ada), delayed the catabolic metabolism of rat and human chondrocytes and cartilage explants under inflammatory conditions. In a surgical model of rat OA, drug-loaded CM-NPs effectively restored gait, attenuated periarticular bone remodeling, and provided chondroprotection against cartilage degeneration. OA progression was also mitigated by CM-NPs-Ada in a canine model of anterior cruciate ligament transection. These results demonstrate the feasibility of using chondrocyte membrane–coated nanoparticles to improve the pharmacokinetics and efficacy of anti-OA drugs.

Spin orbit torque (SOT) of spin current has provided an efficient manipulation of ferromagnet order, antiferromagnet order, and exchange bias field for various spintronic applications. Here, in contrast to the external magnetic field which is very hard to apply locally, we propose to utilize the local control characteristic of SOT on the macro-nano-meter scale to set four different directions of exchange bias field at the IrMn/CoFe interface on one chip simultaneously. Moreover, with this fully electrical control technology to replace the existing various complex processes based on magnetic field annealing, we fabricate monolithic dual-axis full Wheatstone-bridge magnetoresistance sensors to detect two-dimensional magnetic field vector, which exhibit very high detection sensitivity of 9.45 nT·Hz−1/2and 12.3 nT·Hz−1/2at 10 Hz for X-axis and Y-axis sensing, respectively. This work provides a paradigm to simultaneously implement function configurations of spintronic devices by using the local control characteristic of SOT.

Systemic chemotherapy for treating tumors often leads to serious systemic side effects and affects patient compliance. Although the emerging technology of drug delivery systems (DDSs) can deliver the required cargo to tumor sites, DDSs are limited due to insufficient targeting ability or deficient pharmacokinetics. Herein, we assembled a novel targeting DDS for precision tumor therapy by applying a tumor-targeting polypeptide cyclic RGD (cRGD)-modified erythrocyte membrane (eM-cRGD) cloaked on zeolitic imidazolate framework-8 (ZIF-8) nanoparticles (NPs) with encapsulated doxorubicin (DOX). For a mass ratio of ZIF-8:DOX = 1:1, the loading capacity was up to 49%. The nanoscale-sized targeting DDS promoted NP accumulation in tumor tissues via enhanced permeability and retention (EPR) effects, and the NPs actively targeted ligands and were then transferred to endosomes. The pH-sensitive carriers released higher DOX levels under the low pH mimicking that of a tumor microenvironment and tumor intracellular organelles, allowing enhanced inhibition of cancer cell growth. The cumulative release rate of DOX from DOX@ZIF-8 NPs reached 82.8% at 48 h in acidic conditions of pH = 5.0, while the cumulative release rate of DOX from the DOX@ZIF-8 NPs reached only 24.92% at pH = 7.4. The internalization of the DDS was approximately 44.35% that of the unmodified DDS by immune cells, as confirmed by flow cytometry. In vivostudies verified that the RGD-modified DDS had the ability to prolong blood circulation (t1/2= 6.81 h), enhancing the tumor-specific accumulation of NPs by means of the integrin αvβ3 receptor-mediated pathway, which was further valuated in mice bearing human cervical cancer (HeLa) cells, and yielding a significant antitumor effect; the tumor inhibition rate was as high as 85.46%. Under the same conditions, the blood circulation half-life of the unmodified DDS was only 3.22 h, and the tumor inhibition rate of free DOX was 81.34%. Moreover, the RGD modified with a carrier could achieve a satisfactory chemotherapeutic effect while minimizing side effects. In summary, our novel targeting DDS could contribute to the development of intelligent DDSs for tumor precision therapy.

A good AI algorithm can make accurate predictions and provide reasonable explanations for the field in which it is applied. However, the application of deep models makes the black box problem, i.e., the lack of interpretability of a model, more prominent. In particular, when there are multiple features in an application domain and complex interactions between these features, it is difficult for a deep model to intuitively explain its prediction results. Moreover, in practical applications, multiorder feature interactions are ubiquitous. To break the interpretation limitations of deep models, we argue that a multiorder linearly separable deep model can be divided into different orders to explain its prediction results. Inspired by the interpretability advantage of tree models, we design a feature representation mechanism that can consistently represent the features of both trees and deep models. Based on the consistent representation, we propose a multiorder feature-tracking strategy to provide a prediction-oriented multiorder explanation for a linearly separable deep model. In experiments, we have empirically verified the effectiveness of our approach in two binary classification application scenarios: education and marketing. Experimental results show that our model can intuitively represent complex relationships between features through diversified multiorder explanations.

Diabetic osteoporosis (DOP) is the leading complication continuously threatening the bone health of patients with diabetes. A key pathogenic factor in DOP is loss of osteocyte viability. However, the mechanism of osteocyte death remains unclear. Here, we identified ferroptosis, which is iron-dependent programmed cell death, as a critical mechanism of osteocyte death in murine models of DOP. The diabetic microenvironment significantly enhanced osteocyte ferroptosis in vitro, as shown by the substantial lipid peroxidation, iron overload, and aberrant activation of the ferroptosis pathway. RNA sequencing showed that heme oxygenase-1 (HO-1) expression was notably upregulated in ferroptotic osteocytes. Further findings revealed that HO-1 was essential for osteocyte ferroptosis in DOP and that its promoter activity was controlled by the interaction between the upstream NRF2 and c-JUN transcription factors. Targeting ferroptosis or HO-1 efficiently rescued osteocyte death in DOP by disrupting the vicious cycle between lipid peroxidation and HO-1 activation, eventually ameliorating trabecular deterioration. Our study provides insight into DOP pathogenesis, and our results provide a mechanism-based strategy for clinical DOP treatment.

A nanovaccine based on bacterial cytoplasmic membranes and cell membranes from resected tumor tissue prevents tumor recurrence in mice.