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Cartilage oligomeric matrix protein (COMP) is an extracellular matrix (ECM) glycoprotein that is critical for collagen assembly and ECM stability. Mutations of COMP cause endoplasmic reticulum stress and chondrocyte apoptosis, resulting in rare skeleton diseases. The bouquet-like structure of COMP allows it to act as a bridging molecule that regulates cellular phenotype and function. COMP is able to interact with many other ECM components and binds directly to a variety of cellular receptors and growth factors. The roles of COMP in other skeleton diseases, such as osteoarthritis, have been implied. As a well-established biochemical marker, COMP indicates cartilage turnover associated with destruction. Recent exciting achievements indicate its involvement in other diseases, such as malignancy, cardiovascular diseases, and tissue fibrosis. Here, we review the basic concepts of COMP and summarize its novel functions in the regulation of signaling events. These findings renew our understanding that COMP has a notable function in cell behavior and disease progression as a signaling regulator. Interestingly, COMP shows distinct functions in different diseases. Targeting COMP in malignancy may withdraw its beneficial effects on the vascular system and induce or aggravate cardiovascular diseases. COMP supplementation is a promising treatment for OA and aortic aneurysms while it may induce tissue fibrosis or cancer metastasis.

Constructing a stable artificial solid-electrolyte interphase has become one of the most effective strategies to overcome the poor reversibility of lithium metal anode, yet the protection role is still insufficient at elevated current densities over 10 mA cm −2 and large areal capacities over 10 mAh cm −2 . Herein, we propose a dynamic gel with reversible imine groups, which is prepared via a cross linking reaction between flexible dibenzaldehyde-terminated telechelic poly(ethylene glycol) and rigid chitosan, to fabricate a protective layer for Li metal anode. The as-prepared artificial film shows combined merits of high Young’s modulus, strong ductility and high ionic conductivity. When the artificial film is fabricated on a lithium metal anode, the thin protective layer shows a dense and uniform surface owing to the interactions between the abundant polar groups and lithium metal. Besides, the polar groups in the artificial film can homogenize the distribution of Li + at the electrode/electrolyte interface. As a result, cycle stability over 3200 h under an areal capacity of 10 mAh cm −2 and a current density of 10 mA cm −2 has been obtained for the protected lithium metal anodes. Moreover, cycling stability and rate capability has been also improved in the full cells. Achieving stable lithium metal anodes under large current densities over 10 mA cm −2 and area capacities over 10 mAh cm −2 remains a critical challenge. Here, authors propose a dynamic gel as protect layer for lithium metal anode to facilitate with the Young’s modulus, flexibility and ionic conductivity, thus to stabilize the lithium metal anode.

This paper explores the use of machine learning (ML) in medicine, emphasizing how important it is to enhance patient outcomes and diagnostic precision. As medical data grows in complexity and volume, advanced ML techniques are increasingly necessary. The research focuses on leveraging Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Ensemble Methods, and Transfer Learning to enhance medical diagnostics. Specifically, these techniques are applied to large-scale datasets, to address tasks like disease detection, patient outcome prediction, and managing uncertainty in medical data. According to the study, CNNs performs substantially better when handling uncertainty when using the U-Multiclass technique, as seen by the largest Area Under the Curve (AUC) for Cardiomegaly detection. When it comes to diabetes prediction, Ensemble Methods outperform other approaches, and Transfer Learning works well for modifying trained models for use in novel medical applications. The research holds practical value since it can improve patient care and productivity within the healthcare industry. By integrating these ML techniques, the study contributes valuable insights into improving diagnostic processes and optimizing patient outcomes.

In today’s increasingly competitive market climate, brand alliance strategy has emerged as one of the most essential approaches for businesses to acquire market advantage through resource integration. The joint example of Luckin Coffee and Kweichow Moutai, a milestone cross-category collaboration, provides substantial practical insight into the brand’s joint approach. This paper investigates the rationale, implementation process, successes, and problems of brand alliances using the case study of Luckin Coffee and Kweichow Moutai. The example demonstrates how Luckin was able to increase the value of its brand by using Moutai’s high-end brand image and long-standing cultural legacy. At the same time, Moutai has used this chance to broaden its customer base and market reach. However, the two parties’ brand alliance introduces dangers such as mismatched brand representations, contradictory strategic aims, and customer acceptance. The study also offered risk identification, assessment, and response tactics, with the goal of serving as a reference and advice for similar brand joint programs.

Parkinson's disease is the second most common neurodegenerative disorder. Although the pathogenesis of Parkinson's disease is not entirely clear, the aberrant aggregation of α-synuclein has long been considered as an important risk factor. Elucidating the mechanisms that influence the aggregation of α-synuclein is essential for developing an effective diagnostic, preventative and therapeutic strategy to treat this devastating disease. The aggregation of α-synuclein is influenced by several post-translational modifications. Here, we summarized the major post-translational modifications (phosphorylation, ubiquitination, truncation, nitration, -GlcNAcylation) of α-synuclein and the effect of these modifications on α-synuclein aggregation, which may provide potential targets for future therapeutics.

Osteoarthritis (OA) is one of the most frequent musculoskeletal diseases characterized by degeneration of articular cartilage, subchondral bone remodeling, and synovial membrane inflammation, which is a leading cause of global disability, morbidity, and decreased quality of life. Interpreting the potential mechanisms of OA pathogenesis is essential for developing novel prevention and disease-modifying therapeutic interventions. Gut microbiota is responsible for a series of metabolic, immunological, and structural and neurological functions, potentially elucidating the heterogeneity of OA phenotypes and individual features. In this narrative review, we summarized research evidence supporting the hypothesis of a “gut-joint axis” and the interaction between gut microbiota and the OA-relevant factors, including age, gender, genetics, metabolism, central nervous system, and joint injury, elucidating the underlying mechanisms of this intricate interaction. In the context, we also speculated the promising manipulation of gut microbiota in OA management, such as exercise and fecal microbiota transplantation (FMT), highlighting the clinical values of gut microbiota. Additionally, future research directions, such as more convincing studies by the interventions of gut microbiota, the gene regulation of host contributing to or attributed to the specific phenotypes of gut microbiota related to OA, and the relevance of distinct cell subgroups to gut microbiota, are expected. Moreover, gut microbiota is also the potential biomarker related to inflammation and gut dysbiosis that is able to predict OA progression and monitor the efficacy of therapeutic intervention.

Osteosarcoma (OS) is the most common primary bone malignancy, predominantly affecting children and adolescents. Current treatment approaches have limited efficacy, with a 5-year survival rate of approximately 60%. Epithelial-mesenchymal transition (EMT) plays a key role in the onset, progression, and metastasis of OS, potentially influencing patient prognosis. We screened EMT-related genes from multiple transcriptomic datasets of OS and performed unsupervised consensus clustering of EMT-related gene sets. Key EMT-related genes were identified using weighted gene co-expression network analysis (WGCNA) and intersected with differentially expressed genes (DEGs) between OS and normal tissue samples. The least absolute shrinkage and selection operator (LASSO) algorithm was applied to screen candidate genes for developing a prognostic model. Single-cell RNA-Seq (scRNA-Seq) analysis was conducted on OS samples to identify cell populations expressing model genes. Functional validation was performed using si-GPC3 in the MG-63 cell line. The EMT-based prognostic model demonstrated strong predictive capacity across several validation cohorts. The model effectively predicted immune-related features and immunotherapy responses in high-risk and low-risk patient groups. Seven primary cell types were identified from scRNA-Seq data of OS samples, with the osteoblast population showing the highest proportion of cells positive for model genes. The OS_C3 subpopulation exhibited significantly higher scores and included nine gene modules associated with metabolism, structural integrity, proliferation, differentiation, adhesion, migration, immune responses, inflammatory reactions, and signal transduction. The model genes also demonstrated prognostic value across various cancer types. Knockdown of GPC3 in MG-63 cells resulted in decreased proliferation and migration ability. This study provides new insights into the potential mechanisms of EMT in OS and its impact on the tumor immune microenvironment and response to immunotherapy. These findings may pave the way for novel personalized treatment strategies for OS patients.

Charge separation of particulate photocatalysts has been considered as the rate-determining step in artificial photocatalysis since the finding of Honda-Fujishima effect, whose efficiency is generally much lower than that of natural photosynthesis. To approach its upper limit, it requires the photoexcited electrons and holes be efficiently transferred to the spatially separated redox reaction sites over a single photocatalyst particle. Herein, it is demonstrated the spatial charge separation among facets of BiVO 4 :Mo can be notably promoted by creating an electron transfer layer. It not only favors electrons to transfer to its surface, but also promotes the built-in electric field intensity of the inter-facet junction by over 10 times. Consequently, the charge separation efficiency of the modified BiVO 4 :Mo with loading of CoFeO x oxidation cocatalyst exceeds 90% at 420 nm, comparable to that of the natural photosynthesis system, over which notably enhanced photocatalytic activities are achieved. Our findings demonstrate the effectiveness of electron transfer layer in intensifying charge separation of particulate photocatalysts. Efficient charge separation plays a crucial role in enhancing artificial photocatalysis. Here, the authors report an alkali etching method to construct an electron transfer layer on BiVO 4 :Mo photocatalysts, leading to a charge separation efficiency exceeding 90% at 420 nm.

This study aimed to explore the characteristics of online health information-seeking behavior and the influencing factors among young and middle-aged Chinese patients with stroke. The participants of this study were 230 young and middle-aged patients with stroke enrolled from a Class III Grade A hospital in Shandong Province, China, using convenience sampling from October 31, 2023, to May 15, 2024. Based on relevant theories and literature reviews, a self-administered questionnaire was used to analyze the influencing factors regarding six aspects: general demographic characteristics, disease factors, psychological factors, environmental factors, information factors, and information technology factors. Univariate, Correlation, and multivariate analyses were conducted to explore the factors affecting online health information-seeking behavior. The results showed that age, literacy level, stroke course, hospitalizations, treatment methods, number of combined chronic diseases, perceived usefulness, perceived ease of use, e-health literacy, self-efficacy, perceived benefit, health anxiety, quality of information, social influence, perceived risk, and privacy of information were all factors that influenced the online health information-seeking behavior in young and middle-aged patients with stroke. Age, perceived risk, and information privacy were negatively associated with online health information-seeking behavior, whereas the other variables were positively correlated. This study provides scientific insights into the intervention of online health information-seeking behavior in young and middle-aged patients with stroke and contributes to the enhancement of online health information literacy.

Clay-type muddy interlayer is a key control factor leading to the instability of layered slopes, and it is of great significance to carry out the research on the shear characteristics of clay-type muddy interlayer for the safety and stability of layered slope projects. In this paper, the shear characteristics of clay-type muddy interlayer under different conditions of dry density and water moisture content are investigated by improving the test apparatus and data processing method. The results show that: the internal friction angle of clay-type muddy interlayer decreases with the increase of dry density under the condition of low moisture content, while the cohesion increases with the increase of dry density; at medium moisture content, both of them fluctuate with the dry density, but the amplitude is not large; at high moisture content, the response effect with dry density is not obvious. Therefore, higher dry density improves the shear properties of the soil by strengthening the friction and occlusion between particles, while increasing moisture content tends to weaken the shear properties, mainly due to the reduction of the lubrication effect of water, which gradually reduces the cementation between soil particles and the force of water film connection. On the one hand, the research results can enrich the complex mechanical response mechanism of clay-type muddy interlayer in different conditions, and on the other hand, it also provides a certain theoretical basis for the disaster prevention and early warning assessment of this kind of slope engineering.