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Implant-supported dentures are widely used in patients with defect or loss of dentition because these have higher chewing efficiency and do not damage the adjacent teeth compared with fixed or removable denture. An implant-supported denture carries the risk of failure in some systemic diseases, including osteoporosis, because of a non-ideal local microenvironment. Clinically common physical and chemical modifications are used to change the roughness of the implant surface to promote osseointegration, but they have limitations in promoting osteoinduction and inhibiting bone resorption. Recently, many researchers have focused on the study of bioactive modification of implants and have achieved promising results. Herein we have summarized the progress in bioactive modification strategy to promote osseointegration by regulating the local osteoporotic microenvironment.

EphrinB2, a membrane protein regulating bone homeostasis, has been demonstrated to induce osteogenic gene expression in periodontal ligament fibroblasts. The aim of this study was to explore the effects of ephrinB2 on osteogenic differentiation of periodontal ligament stem cells and on alveolar bone regeneration in vivo. We assessed the osteogenic gene expression and osteogenic differentiation potential of ephrinB2-modified human and canine periodontal ligament stem cells, in which ephrinB2 expression was upregulated via lentiviral vector transduction. EphrinB2-modified canine periodontal ligament stem cells combined with PuraMatrix were delivered to critical-sized alveolar bone defects in beagles to evaluate bone regeneration. Results showed that ephrinB2 overexpression enhanced osteogenic gene transcription and mineral deposition in both human and canine periodontal ligament stem cells. Animal experiments confirmed that ephrinB2-modified canine periodontal ligament stem cells + PuraMatrix resulted in greater trabecular bone volume per tissue volume and trabecular thickness compared with other groups. Our study demonstrated that ephrinB2 promoted osteogenic differentiation of periodontal ligament stem cells and alveolar bone repair in beagles, highlighting its therapeutic potential for the treatment of alveolar bone damage.

Background Alveolar bone loss is a frequent occurrence. Dental pulp stem cells (DPSCs) which have invasive accessibility and high osteogenic potential is a promising source for cell-based bone regeneration. EphrinB2 is involved in bone homeostasis and osteogenesis. The aim of this study was to investigate the effect and mechanism of ephrinB2 overexpression on osteogenic differentiation of DPSCs and bone defect repair. Methods EphrinB2 expression was analyzed during osteogenic induction of human DPSCs (hDPSCs). Endogenous ephrinB2 expression in hDPSCs was then upregulated using EfnB2 lentiviral vectors. The effect of ephrinB2 overexpression on osteogenic differentiation capacity of hDPSCs was investigated in vitro, and activation of ephrinB2-EphB4 bidirectional signaling in ephrinB2-overexpressing hDPSCs was detected. In vivo, a canine alveolar bone defect model was established and canine DPSCs (cDPSCs) were cultured, characterized, EfnB2-tranfected, and combined with a PuraMatrix scaffold. Micro-CT analysis was performed to evaluate the therapeutic effect of ephrinB2-overexpressing cDPSCs on bone defect repair. Results EphrinB2 was upregulated after osteogenic induction of hDPSCs. EphrinB2 overexpression enhanced osteogenic differentiation capacity of hDPSCs in vitro. Moreover, p-ephrinB2 instead of p-EphB4 was upregulated by ephrinB2 overexpression, and activation of ephrinB2-mediated reverse signaling promoted osteogenic differentiation of hDPSCs. In a canine bone defect model, ephrinB2 overexpression in cDPSCs significantly improved trabecular bone volume per tissue volume (BV/TV) and trabecular thickness, as demonstrated by radiographic analysis. Conclusions EphrinB2 overexpression enhanced osteogenic potential of DPSCs partially via upregulation of ephrinB2-mediated reverse signaling and effectively promoted alveolar bone defect repair.

Background and objective The emergence of peri-implant diseases has prompted various methods for decontaminating the implant surface. This study compared the effectiveness of three different approaches, chlorhexidine digluconate (CHX) combined with erbium-doped yttrium–aluminum–garnet (Er:YAG) laser, photodynamic therapy (PDT), and CHX only, for reducing biofilm vitality from implant-like titanium surfaces. Study design/Materials and methods The study involved eight volunteers, each receiving a custom mouth device containing eight titanium discs. The volunteers were requested to wear the device for 72 h for biofilm development. Fluorescence microscopy was used to evaluate the remaining biofilm with a two-component nucleic acid dye kit. The vital residual biofilm was quantified as a percentage of the surface area using image analysis software. Sixty-four titanium discs were assigned randomly to one of four treatment groups. Results The percentage of titanium disc area covered by vital residual biofilm was 43.9% (7.7%), 32.2% (7.0%), 56.6% (3.6%), and 73.2% (7.8%) in the PDT, Er:YAG, CHX, and control groups, respectively (mean (SD)). Compared to the control group, the treatment groups showed significant differences in the area covered by residual biofilm ( P  < 0.001). CHX combined with Er:YAG laser treatment was superior to CHX combined with PDT, and CHX only was better than the control. Conclusion Within the current in vitro model's limitations, CHX combined with Er:YAG laser treatment is a valid method to reduce biofilm vitality on titanium discs.

Osteoporosis is a major challenge to oral implants, and this study focused on improving the osseointegration ability of titanium (Ti) implants in osteoporosis environment via surface modification, including doping of strontium ion and preparation of nanoscale surface feature. Our previous studies have shown that strontium (Sr) ions can enhance osteogenic activity. Therefore, we aimed to comprehensively evaluate the effect of hydrothermal treatment of Sr-doped titanium implant coating on bone-binding properties in the microenvironment of osteoporosis in this study. We fabricated Sr-doped nanocoating (AHT-Sr) onto the surface of titanium implants via hydrothermal reaction. The rough Sr-doping had good biological functions and could apparently promote osteogenic differentiation of osteoporotic bone marrow mesenchymal stem cells (OVX-BMSCs). Most importantly, AHT-Sr significantly promoted bone integration in the osteoporosis environment. This study provides an effective approach to implant surface modification for better osseointegration in an osteoporotic environment.

Memtransistors that integrate memristor and transistor functionalities are promising candidates for scalable, energy-efficient neuromorphic computing. However, achieving high performance in memtransistor arrays—particularly in terms of resistive switching ratio, uniformity, and scalability—remains a significant challenge for practical deployment in artificial neural networks. Here, we present scalable memtransistor arrays based on transition metal dichalcogenides (TMDCs), where the Schottky barrier is precisely controlled by modulating vacancy distribution and migration behavior. This approach enables a substantial improvement in the resistive switching ratio, reaching 10 5 through gate modulation. The device-to-device variation is maintained below 6.8%, and the power consumption is as low as 1 pJ per operation. These devices demonstrate high performance in artificial neural network applications, achieving greater than 98% accuracy in image recognition tasks. Furthermore, the devices exhibit remarkable scalability, with a cell size as small as 4.65  F ², and can be further miniaturized by adjusting the channel size without affecting the switching performance. This work highlights the potential of TMDC-based memtransistor arrays for energy-efficient, high-performance artificial neural networks, offering a scalable solution for next-generation neuromorphic computing hardware. 2D memtransistors are promising candidates for energy-efficient neuromorphic computing, but their scalability remains challenging. Here, the authors report the fabrication of 2D MoS 2 memtransistor arrays with controllable Schottky barrier, demonstrating device-to-device variation <6.8% and high performance for image recognition tasks.

The intricate kinematics of the human hand enable simultaneous grasping and manipulation of multiple objects, essential for tasks such as object transfer and in-hand manipulation. Despite its significance, the domain of robotic multi-object grasping is relatively unexplored and presents notable challenges in kinematics, dynamics, and object configurations. This paper introduces MultiGrasp, a novel two-stage approach for multi-object grasping using a dexterous multi-fingered robotic hand on a tabletop. The process consists of (i) generating pre-grasp proposals and (ii) executing the grasp and lifting the objects. Our experimental focus is primarily on dual-object grasping, achieving a success rate of 44.13%, highlighting adaptability to new object configurations and tolerance for imprecise grasps. Additionally, the framework demonstrates the potential for grasping more than two objects at the cost of inference speed.

Generating dexterous grasping has been a long-standing and challenging robotic task. Despite recent progress, existing methods primarily suffer from two issues. First, most prior arts focus on a specific type of robot hand, lacking the generalizable capability of handling unseen ones. Second, prior arts oftentimes fail to rapidly generate diverse grasps with a high success rate. To jointly tackle these challenges with a unified solution, we propose GenDexGrasp, a novel hand-agnostic grasping algorithm for generalizable grasping. GenDexGrasp is trained on our proposed large-scale multi-hand grasping dataset MultiDex synthesized with force closure optimization. By leveraging the contact map as a hand-agnostic intermediate representation, GenDexGrasp efficiently generates diverse and plausible grasping poses with a high success rate and can transfer among diverse multi-fingered robotic hands. Compared with previous methods, GenDexGrasp achieves a three-way trade-off among success rate, inference speed, and diversity. Code is available at https://github.com/tengyu-liu/GenDexGrasp.

In this work, we tackle the problem of learning universal robotic dexterous grasping from a point cloud observation under a table-top setting. The goal is to grasp and lift up objects in high-quality and diverse ways and generalize across hundreds of categories and even the unseen. Inspired by successful pipelines used in parallel gripper grasping, we split the task into two stages: 1) grasp proposal (pose) generation and 2) goal-conditioned grasp execution. For the first stage, we propose a novel probabilistic model of grasp pose conditioned on the point cloud observation that factorizes rotation from translation and articulation. Trained on our synthesized large-scale dexterous grasp dataset, this model enables us to sample diverse and high-quality dexterous grasp poses for the object point cloud.For the second stage, we propose to replace the motion planning used in parallel gripper grasping with a goal-conditioned grasp policy, due to the complexity involved in dexterous grasping execution. Note that it is very challenging to learn this highly generalizable grasp policy that only takes realistic inputs without oracle states. We thus propose several important innovations, including state canonicalization, object curriculum, and teacher-student distillation. Integrating the two stages, our final pipeline becomes the first to achieve universal generalization for dexterous grasping, demonstrating an average success rate of more than 60\\% on thousands of object instances, which significantly outperforms all baselines, meanwhile showing only a minimal generalization gap.

【目的】探究种植模式对水稻的根系特性、氮素吸收和产量的影响。【方法】以水稻为供试材料，设置移栽淹灌（TFR）、旱直播淹灌（DDSF）和旱直播干湿交替灌溉（DDSA）3种种植模式，研究不同种植模式下水稻0~20 cm土层根系形态、根系生理、氮素吸收量和产量及其相互关系。【结果】①在主要生育期，直播模式较移栽模式增加了根干物质量、根直径和0~10 cm土层根分布，减少了10~20 cm土层根系分布；DDSA处理增加了旱直播稻的根干物质量、根直径、0~10 cm土层根分布，减少了10~20 cm土层根分布；②在幼穗分化期后，直播模式降低了根系活力等指标；DDSA处理增加旱直播稻的根系活力等指标。③各处理抽穗期和成熟期的总氮素积累量、花后氮素吸收量和产量表现为：TFR处理＞DDSA处理＞DDSF处理。移栽模式较直播模式有更深的根系分布和相对较高的根系活力，是其氮素积累量多和产量高的主要原因；旱直播干湿交替灌溉模式增加旱直播稻的深层土壤根系分布，提升了根系活力，进而促进了氮素吸收，提高了产量。【结论】综上可知，旱直播干湿交替灌溉有望提高旱直播水稻氮素利用效率及产量。