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Mechano growth factor (MGF), an isoform of insulin-like growth factor 1 (IGF-1), is recognized as a typical mechanically sensitive growth factor and has been shown to play an indispensable role in the skeletal system. In the joint cavity, MGF is highly expressed in chondrocytes, especially in the damaged cartilage tissue caused by trauma or degenerative diseases such as osteoarthritis (OA). Cartilage is an extremely important component of joints because it functions as a shock absorber and load distributer at the weight-bearing interfaces in the joint cavity, but it can hardly be repaired once injured due to its lack of blood vessels, lymphatic vessels, and nerves. MGF has been proven to play an important role in chondrocyte behaviors, including cell proliferation, migration, differentiation, inflammatory reactions and apoptosis, in and around the injury site. Moreover, under the normalized mechanical microenvironment in the joint cavity, MGF can sense and respond to mechanical stimuli, regulate chondrocyte activity, and maintain the homeostasis of cartilage tissue. Recent reports continue to explain its effects on various cell types and sport-related tissues, but its role in cartilage development, homeostasis and disease occurrence is still controversial, and its internal biological mechanism is still elusive. In this review, we summarize recent discoveries on the role of MGF in chondrocytes and cartilage defects, including tissue repair at the macroscopic level and chondrocyte activities at the microcosmic level, and discuss the current state of research and potential gaps in knowledge.

In this study, we tested the feces of children with ASD and those of healthy children, and the overall changing of the community was observed in ASD children compared with controls. However, there were no abundant fungi populations showed significant variations between the ASD and Control group both at phylum and class level. Among the 507 genera identified, "Saccharomyces" and "Aspergillus" showed significant differences between ASD (59.07%) and Control (40.36%), indicating that they may be involved in the abnormal gut fungal community structure of ASD. When analyzed at the species level, a decreased abundance in "Aspergillus versicolor" was observed while "Saccharomyces cerevisiae" was increased in children with ASD relative to controls. Overall, this study characterized the fungal microbiota profile of children with ASD and identified potential diagnostic species closely related to the immune response in ASD.

It is well recognized that mitochondrial dynamics plays a vital role in cartilage physiology. Any perturbation in mitochondrial dynamics could cause disorders in cartilage metabolism and even lead to the occurrence of cartilage diseases such as osteoarthritis (OA). TGF‐β3, as an important growth factor that appears in the joints of OA disease, shows its great potential in chondrocyte growth and metabolism. Nevertheless, the role of TGF‐β3 on mitochondrial dynamics is still not well understood. Here we aimed to investigate the effect of TGF‐β3 on mitochondrial dynamics of chondrocytes and reveal its underlying bio‐mechanism. By using transmission electron microscopy (TEM) for the number and morphology of mitochondria, western blotting for the protein expressions, immunofluorescence for the cytoplasmic distributions of proteins, and RNA sequencing for the transcriptome changes related to mitochondrial dynamics. We found that TGF‐β3 could increase the number of mitochondria in chondrocytes. TGF‐β3‐enhanced mitochondrial number was via promoting the mitochondrial fission. The mitochondrial fission induced by TGF‐β3 was mediated by AMPK signaling. TGF‐β3 activated canonical p‐Smad3 signaling and resultantly mediated AMPK‐induced mitochondrial fission. Taken together, these results elucidate an understanding of the role of TGF‐β3 on mitochondrial dynamics in chondrocytes and provide potential cues for therapeutic strategies in cartilage injury and OA disease in terms of energy metabolism. [ABSTRACT FROM AUTHOR]

Aim: To explore the influence of PDGF‐AA on cell communication between human dental pulp stem cells (DPSCs) by characterizing gap junction intercellular communication (GJIC) and its potential biomechanical mechanism. Methodology: Quantitative real‐time PCR was used to measure connexin family member expression in DPSCs. Cell migration and CCK‐8 assays were utilized to examine the influence of PDGF‐AA on DPSC migration and proliferation. A scrape loading/dye transfer assay was applied to evaluate GJIC triggered by PDGF‐AA, a PI3K/Akt signalling pathway blocker (LY294002) and a PDGFR‐α blocker (AG1296). Western blotting and immunofluorescence were used to test the expression and distribution of the Cx43 and p‐Akt proteins in DPSCs. Scanning electron microscopy (SEM) and immunofluorescence were used to observe the morphology of GJIC in DPSCs. Results: PDGF‐AA promoted gap junction formation and intercellular communication between human dental pulp stem cells. PDGF‐AA upregulates the expression of Cx43 to enhance gap junction formation and intercellular communication. PDGF‐AA binds to PDGFR‐α and activates PI3K/Akt signalling to regulate cell communication. Conclusions: This research demonstrated that PDGF‐AA can enhance Cx43‐mediated GJIC in DPSCs via the PDGFR‐α/PI3K/Akt axis, which provides new cues for dental pulp regeneration from the perspective of intercellular communication. [ABSTRACT FROM AUTHOR]

Bearing‐only containment control means to achieve containment using only the bearing information, rather than the complete relative position information including both the bearing and the distance. Compared with the most existing relative position based containment control algorithms, the bearing‐only containment control algorithm is nonlinear due to the nonlinearity of the bearing, which renders the stability analysis challenging. In this article, the bearing‐only containment control problem of multi‐agent systems with dynamically changing topologies is investigated for two cases, where the leaders are stationary or dynamic. First, when the leaders are stationary, it is shown that the nonlinearity of the bearing leads to the unknown nonlinear time‐varying parameters in the system. Based on the boundedness of the nonlinear parameters and the connectivity of the switching directed sensing graphs, it is proven that all the followers converge to the stationary convex hull formed by the leaders asymptotically. Second, when the leaders are dynamic, a distributed estimator is proposed for each follower to keep a local estimate of the velocity of the leaders. Based on the optimality of the projection and the shift invariance of the normal cone, it is proven that all the followers converge to the dynamic convex hull formed by the leaders asymptotically under the conditions on the switching directed sensing and communication graphs. It is shown from the two cases that the distance information is not necessary for containment control, and containment can be achieved as long as the bearing information is provided. Numerical examples are presented to illustrate the theoretical results. [ABSTRACT FROM AUTHOR]

Due to the lack of accurate labels for the airborne synthetic aperture radar altimeter (SARAL), the use of deep learning methods is limited for estimating the above ground level (AGL) of complicated landforms. In addition, the inherent additive and speckle noise definitely influences the intended delay/Doppler map (DDM); accurate AGL estimation becomes more challenging when using the feature extraction approach. In this paper, a generalized AGL estimation algorithm is proposed, based on a fully supervised altimetry enhancement network (FuSAE-net), where accurate labels are generated by a novel semi-analytical model. In such a case, there is no need to have a fully analytical DDM model, and accurate labels are achieved without additive noises and speckles. Therefore, deep learning supervision is easy and accurate. Next, to further decrease the computational complexity for various landforms on the airborne platform, the network architecture is designed in a lightweight manner. Knowledge distillation has proven to be an effective and intuitive lightweight paradigm. To significantly improve the performance of the compact student network, both the encoder and decoder of the teacher network are utilized during knowledge distillation under the supervision of labels. In the experiments, airborne raw radar altimeter data were applied to examine the performance of the proposed algorithm. Comparisons with conventional methods in terms of both qualitative and quantitative aspects demonstrate the superiority of the proposed algorithm. [ABSTRACT FROM AUTHOR]