Silencing miR-146a-5p protects against injury-induced osteoarthritis in mice

Osteoarthritis (OA), the most prevalent joint disease and the leading cause of disability, remains an incurable disease largely because the etiology and pathogenesis underlying this degenerative process are poorly understood. Low-grade inflammation within joints is a well-established factor that disturbs joint homeostasis and leads to an imbalance between anabolic and catabolic processes in articular cartilage; however, the complexity of the network between inflammatory factors that often involves positive and negative feedback loops makes current anti-cytokine therapy ineffective. MicroRNAs (miRNAs) have emerged as key regulators to control inflammation, and aberrant miRNAs expression has recently been linked to OA pathophysiology. In the present study, we characterized transcriptomic profiles of miRNAs in primary murine articular chondrocytes in response to a proinflammatory cytokine, IL-1β, and identifie

Enhancing Generalizable 6D Pose Tracking of an In-Hand Object with Tactile Sensing

While holding and manipulating an object, humans track the object states through vision and touch so as to achieve complex tasks. However, nowadays the majority of robot research perceives object states just from visual signals, hugely limiting the robotic manipulation abilities. This work presents a tactile-enhanced generalizable 6D pose tracking design named TEG-Track to track previously unseen in-hand objects. TEG-Track extracts tactile kinematic cues of an in-hand object from consecutive tactile sensing signals. Such cues are incorporated into a geometric-kinematic optimization scheme to enhance existing generalizable visual trackers. To test our method in real scenarios and enable future studies on generalizable visual-tactile tracking, we collect a real visual-tactile in-hand object pose tracking dataset. Experiments show that TEG-Track significantly improves state-of-the-art generalizable 6D pose trackers in both synthetic and real cases

The therapeutic effects of low-intensity pulsed ultrasound in musculoskeletal soft tissue injuries: Focusing on the molecular mechanism

Musculoskeletal soft tissue injuries are very common and usually occur during both sporting and everyday activities. The intervention of adjuvant therapies to promote tissue regeneration is of great importance to improving people’s quality of life and extending their productive lives. Though many studies have focused on the positive results and effectiveness of the LIPUS on soft tissue, the molecular mechanisms standing behind LIPUS effects are much less explored and reported, especially the intracellular signaling pathways. We incorporated all research on LIPUS in soft tissue diseases since 2005 and summarized studies that uncovered the intracellular molecular mechanism. This review will also provide the latest evidence-based research progress in this field and suggest research directions for future experiments

DNA methylation-mediated Rbpjk suppression protects against fracture nonunion caused by systemic inflammation

Challenging skeletal repairs are frequently seen in patients experiencing systemic inflammation. To tackle the complexity and heterogeneity of the skeletal repair process, we performed single-cell RNA sequencing and revealed that progenitor cells were one of the major lineages responsive to elevated inflammation and this response adversely affected progenitor differentiation by upregulation of Rbpjk in fracture nonunion. We then validated the interplay between inflammation (via constitutive activation of Ikk2, Ikk2ca) and Rbpjk specifically in progenitors by using genetic animal models. Focusing on epigenetic regulation, we identified Rbpjk as a direct target of Dnmt3b. Mechanistically, inflammation decreased Dnmt3b expression in progenitor cells, consequently leading to Rbpjk upregulation via hypomethylation within its promoter region. We also showed that Dnmt3b loss-of-function mice phenotypically recapitulated the fracture repair defects observed in Ikk2ca-transgenic mice, whereas Dnmt3b-transgenic mice alleviated fracture repair defects induced by Ikk2ca. Moreover, Rbpjk ablation restored fracture repair in both Ikk2ca mice and Dnmt3b loss-of-function mice. Altogether, this work elucidates a common mechanism involving a NF-κB/Dnmt3b/Rbpjk axis within the context of inflamed bone regeneration. Building on this mechanistic insight, we applied local treatment with epigenetically modified progenitor cells in a previously established mouse model of inflammation-mediated fracture nonunion and showed a functional restoration of bone regeneration under inflammatory conditions through an increase in progenitor differentiation potential

The loss of plant functional groups increased arthropod diversity in an alpine meadow on the Tibetan Plateau

Plant species loss, driven by global changes and human activities, can have cascading effects on other trophic levels, such as arthropods, and alter the multitrophic structure of ecosystems. While the relationship between plant diversity and arthropod communities has been well-documented, few studies have explored the effects of species composition variation or plant functional groups. In this study, we conducted a long-term plant removal experiment to investigate the impact of plant functional group loss (specifically targeting tall grasses and sedges, as well as tall or short forbs) on arthropod diversity and their functional groups. Our findings revealed that the removal of plant functional groups resulted in increased arthropod richness, abundance and the exponential of Shannon entropy, contrary to the commonly observed positive correlation between plant diversity and consumer diversity. Furthermore, the removal of different plant groups had varying impacts on arthropod trophic levels. The removal of forbs had a more pronounced impact on herbivores compared to graminoids, but this impact did not consistently cascade to higher-trophic arthropods. Notably, the removal of short forbs had a more significant impact on predators, as evidenced by the increased richness, abundance, the exponential of Shannon entropy, inverse Simpson index and inverse Berger-Parker index of carnivores and abundance of omnivores, likely attributable to distinct underlying mechanisms. Our results highlight the importance of plant species identity in shaping arthropod communities in alpine grasslands. This study emphasizes the crucial role of high plant species diversity in controlling arthropods in natural grasslands, particularly in the context of plant diversity loss caused by global changes and human activities

Research Progress and Application of Single-Atom Catalysts: A Review

Due to excellent performance properties such as strong activity and high selectivity, single-atom catalysts have been widely used in various catalytic reactions. Exploring the application of single-atom catalysts and elucidating their reaction mechanism has become a hot area of research. This article first introduces the structure and characteristics of single-atom catalysts, and then reviews recent preparation methods, characterization techniques, and applications of single-atom catalysts, including their application potential in electrochemistry and photocatalytic reactions. Finally, application prospects and future development directions of single-atom catalysts are outlined

A highly sensitive fluorescent turn-on biosensor for glycoproteins based on boronic acid functional polymer capped Mn-doped ZnS quantum dots

A simple fluorescence turn-on sensor has been designed for the highly sensitive detection of glycoproteins on the basis of boronic acid functional polymer capped Mn-doped ZnS quantum dots (QDs@MPS@AAPBA). In the absence of glycoproteins, the fluorescence emission intensity of the QDs@MPS@AAPBA was relatively weaker due to the effective electronic transfer from the QDs to the boron moieties on its surface. While the glycoproteins were introduced into the system, an obvious fluorescence enhancement was observed. It was attributed to the boron moieties covalent binding gly-cans of the glycoproteins resulting in the electronic transfer process being inhibited. Under the optimal conditions, this fluorescent probe not only could be applied in a wide pH range of 5.0-9.0, but also the binding constants and detection limits of the QDs@MPS@AAPBA for horseradish peroxidase (HRP) and transferrin (TRF) were up to 7.23 x 10(6) M-1, 1.53 x 10(7) M-1 and 1.44 x 10(-10) M, 3.36 x 10(-10) M, respectively. Finally, this proposed method has also been utilized for the TRF determination in serum without any complicated pretreatment and the recovery was in the range of 95.7%-103.0%. As a result, it is promising for application on the glycoproteins detection in complex biological samples. (C) 2017 Elsevier B.V. All rights reserved

Optimization Design of Injection Strategy for Surfactant-Polymer Flooding Process in Heterogeneous Reservoir under Low Oil Prices

Surfactant–polymer (SP) flooding has significant potential to enhance oil recovery after water flooding in mature reservoirs. However, the economic benefit of the SP flooding process is unsatisfactory under low oil prices. Thus, it is necessary to reduce the chemical costs and improve SP flooding efficiency to make SP flooding more profitable. Our goal was to maximize the incremental oil recovery of the SP flooding process after water flooding by using the equal chemical consumption cost to ensure the economic viability of the SP flooding process. Thus, a systematic study was carried out to investigate the SP flooding process under different injection strategies by conducting parallel sand pack flooding experiments to optimize the SP flooding design. Then, the comparison of the remaining oil distribution after water flooding and SP flooding under different injection strategies was studied. The results demonstrate that the EOR efficiency of the SP flooding process under the alternating injection of polymer and surfactant–polymer (PASP) is higher than that of conventional simultaneous injection of surfactant and polymer. Moreover, as the alternating cycle increases, the incremental oil recovery increases. Based on the analysis of fractional flow, incremental oil recovery, and remaining oil distribution when compared with the conventional simultaneous injection of surfactant and polymer, the alternating injection of polymer and surfactant–polymer (PASP) showed better sweep efficiency improvement and recovered more remaining oil trapped in the low permeability zone. Thus, these findings could provide insights into designing the SP flooding process under low oil prices

Colorimetric sensor based on 4-mercaptophenylboronic modified gold nanoparticles for rapid and selective detection of fluoride anion

A highly selective and sensitive colorimetric sensor based on aggregation-induced color change of 4-mercaptophenylboronic modified gold nanoparticles was designed for the determination of fluoride anion. The 4-mercaptophenylboronic modified gold nanoparticles were synthesized by a simple one-pot reaction. The aggregation process occurred when interaction between fluoride anion and 4-mercaptophenylboronic on the surface of gold nanoparticles took place; as a result, fluoroborate anions were formed coupled with changes in the electronic properties of the AuNPs. The change can be measured by UV-Vis absorption spectra. The sensor shows good selectivity and sensitivity for fluoride anion. The linear range is 10.0-30.0 mu M for fluoride and the detection limit of fluoride is 3.45 x 10(-7) Maccording to IUPAC criteria (3 sigma rule). Furthermore, the sensor has been used for the detection of fluoride anion in tap water, ground water and human serum samples, the recovery can achieve 94.0%-103.3%, 94.7%-101.0% and 89.8-100.9%, respectively. The excellent performance of colorimetric sensor in the detection of the fluoride anion demonstrated the potential application in the detecting fluoride anion present in the complex environmental and biological samples. (C) 2019 Elsevier B.V. All rights reserved

A multi-agent reinforcement learning-based method for server energy efficiency optimization combining DVFS and dynamic fan control

With the rapid development of the digital economy and intelligent industry, the energy consumption of data centers (DCs) has increased significantly. Various optimization methods are proposed to improve the energy efficiency of servers in DCs. However, existing solutions usually adopt model-based heuristics and best practices to select operations, which are not universally applicable. Moreover, existing works primarily focus on the optimization methods for individual components, with a lack of work on the joint optimization of multiple components. Therefore, we propose a multi-agent reinforcement learning-based method, named MRDF, combining DVFS and dynamic fan control to achieve a trade-off between power consumption and performance while satisfying thermal constraints. MRDF is model-free and learns by continuously interacting with the real server without prior knowledge. To enhance the stability of MRDF in dynamic environments, we design a data-driven baseline comparison method to evaluate the actual contribution of a single agent to the global reward. In addition, an improved Q-learning is proposed to deal with the large state and action space of the multi-core server. We implement MRDF on a Huawei Taishan 200 server and verify the effectiveness by running benchmarks. Experimental results show that the proposed method improves energy efficiency by an average of 3.9% compared to the best baseline solution, while flexibly adapting to different thermal constraints