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

Modifications of Vitis vinifera L. cv. Petit Verdot grape flavonoids as affected by the different rootstocks in eastern China

Rootstocks are widely used in viticulture because of their strong ability to resist biotic and abiotic stress. In two-successive years (2016−2017), the effects of five rootstocks (101-14MGt, 1103P, Beta, 5BB, and SO4) on the berry flavonoid profiles of Petit Verdot were evaluated by HPLC-MS. The results showed that there was limited influence of rootstocks affecting the technological ripening of Petit Verdot. With respect to flavonoid compounds, 1103P and Beta tended to increase the concentrations of anthocyanin in grape skins in the two seasons. 101-14MGt and 1103P enhanced the flavonol concentrations, whereas Beta showed a detrimental effect on the biosynthesis of flavonols except for syringetin. Additionally, despite the season factor dominating the effect on flavan-3-ols, 101-14MGt tended to show a slight increase in flavan-3-ol concentrations in skins and seeds. In conclusion, based on the evaluation of physicochemical indicators and flavonoid compounds of mature berries, the current study provided data for grafting of Petit Verdot on various rootstocks in eastern China

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

Automatic Assembly of Bolts and Nuts Based on Machine Vision Recognition

Abstract In this study, based on the computer vision technology, we developed a recognition system for nuts positioning to complete the automatic bolt assembly part of the automatic production line. The actual image of the nut was captured by an industrial camera, which would be processed by the following edge detection and Hough circle transformation. After that, the coordinates of the nuts were obtained in the pixel scale. Finally, the real position of nuts would be fed back to the robot arm, according to which the automatic assembly of the bolt would be completed. This computer vision based recognition system is an indispensable part for the efficiency and accuracy improvement of automatic production line.</jats:p

Improving Anticompression Robustness of JPEG Adaptive Steganography Based on Robustness Measurement and DCT Block Selection

With the development of the Internet, social network platforms (SNPs) have become the most common channel for image sharing. As a result, transmitting stego images in the public channels gives steganographers the best opportunity to transmit secret messages with behavioral security preserved. However, the SNPs typically compress uploaded images and damage the weak signal of steganography. In this study, a robust JPEG steganographic scheme based on robustness measurement and cover block selection (CBSRS) is proposed. We first design a deep learning-based model to fit the blockwise change rate of coefficients after JPEG recompression. Then, a cover block selection strategy is proposed to improve the robustness by optimizing the joint distortion function of transmission costs and classic costs. Moreover, by embedding indicator of cover block selection in chrominance channels of JPEG images, a shareable cover construction scheme is designed to solve the problem of auxiliary information transmission. The experimental results show that our proposed framework improves robustness while maintaining statistical security. Comparing with state-of-the-art methods, the framework achieves better performance under given recompression channels.</jats:p