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Tendon is a connective tissue that produces movement by transmitting the force produced by muscle contraction to the bones. Most tendinopathy is caused by prolonged overloading of the tendon, leading to degenerative disease of the tendon. When overloaded, the oxygen demand of tenocytes increases, and the tendon structure is special and lacks blood supply, which makes it easier to form an oxygen-deficient environment in tenocytes. The production of reactive oxygen species due to hypoxia causes elevation of inflammatory markers in the tendon, including PGE2, IL-1β, and TNF-α. In the process of tendon healing, inflammation is also a necessary stage. The inflammatory environment formed by cytokines and various immune cells play an important role in the clearance of necrotic material, the proliferation of tenocytes, and the production of collagen fibers. However, excessive inflammation can lead to tendon adhesions and hinder tendon healing. Some important and diverse biological functions of the body originate from intercellular signal transduction, among which cytokine mediation is an important way of signal transduction. In particular, NF-κB, NLRP3, p38/MAPK, and signal transducer and activator of transcription 3, four common signaling pathways in tendinopathy inflammatory response, play a crucial role in the regulation and transcription of inflammatory factors. Therefore, summarizing the specific mechanisms of inflammatory signaling pathways in tendinopathy is of great significance for an in-depth understanding of the inflammatory response process and exploring how to inhibit the harmful part of the inflammatory response and promote the beneficial part to improve the healing effect of the tendon.

Vascular calcification is a prominent manifestation of advanced atherosclerosis. Tumor necrosis factor-receptor-associated factors (TRAFs) were reported to participate in atherosclerosis development. In this study, the role and mechanism of TRAF6 in vascular calcification were explored. To induce the vascular calcification, oxidized low-density lipoprotein (Ox-LDL) was applied to treat vascular smooth muscle cells (VSMCs). TRAF6 protein expression in VSMCs was assessed by western blotting. Osteogenic differentiation of VSMCs was assessed by alkaline phosphatase activity analysis. Mineral deposition in VSMCs was evaluated by von Kossa staining. VSMC proliferation, migration, apoptosis, inflammation, and reactive oxygen species (ROS) generation were detected using cell counting kit-8, Transwell, flow cytometry, reverse transcriptase quantitative polymerase chain reaction (RT-qPCR), and dichlorodihydrofluorescein diacetate staining, respectively. Luciferase reporter assay was utilized to identify the binding relationship between miR-146-5p and TRAF6 in VSMCs. We found that Ox-LDL administration induced the calcification of VSMCs and elevated the TRAF6 level. TRAF6 knockdown restrained VSMC calcification, proliferation, migration, inflammation, and ROS generation caused by Ox-LDL. Mechanically, TRAF6 was targeted by miR-146-5p in VSMCs. Furthermore, TRAF6 overexpression offset the inhibitory effects of miR-146-5p upregulation on vascular calcification in VSMCs under the Ox-LDL condition. Overall, miR-146-5p restrains the calcification of VSMCs by suppressing TRAF6.

Trivariate joint modeling for longitudinal count data, recurrent events, and a terminal event for family data has increased interest in medical studies. For example, families with Lynch syndrome (LS) are at high risk of developing colorectal cancer (CRC), where the number of polyps and the frequency of colonoscopy screening visits are highly associated with the risk of CRC among individuals and families. To assess how screening visits influence polyp detection, which in turn influences time to CRC, we propose a clustered trivariate joint model. The proposed model facilitates longitudinal count data that are zero‐inflated and over‐dispersed and invokes individual‐specific and family‐specific random effects to account for dependence among individuals and families. We formulate our proposed model as a latent Gaussian model to use the Bayesian estimation approach with the integrated nested Laplace approximation algorithm and evaluate its performance using simulation studies. Our trivariate joint model is applied to a series of 18 families from Newfoundland, with the occurrence of CRC taken as the terminal event, the colonoscopy screening visits as recurrent events, and the number of polyps detected at each visit as zero‐inflated count data with overdispersion. We showed that our trivariate model fits better than alternative bivariate models and that the cluster effects should not be ignored when analyzing family data. Finally, the proposed model enables us to quantify heterogeneity across families and individuals in polyp detection and CRC risk, thus helping to identify individuals and families who would benefit from more intensive screening visits. [ABSTRACT FROM AUTHOR]

Cell‐based microarrays are widely used in the fields of drug discovery and toxicology. Precise gradient generation and automated drug feeding are essential for high‐throughput screening of live cells in tiny droplets. However, most existing technologies either require sophisticated robotic equipment or cause mechanical/physiological interference with cells. Here, a heterogeneous organohydrogel is presented for automated gradient drug feeding, while ensuring minimal interference with cells. The heterogeneous organohydrogel comprises three crucial components. The bottom surface can automatically generate gradients functioning as a gradient generator, the organohydrogel bulk allows unidirectional transport of drugs without backflow, and the top surface with hydrophilic arrays can firmly anchor the cell‐based droplet array to evaluate the concentration‐dependent bioeffects of drugs accurately. Such a unique structure enables universal screening of different cell types and drugs dissolved in different solvents, requiring neither additional accessories nor arduous drug functionalization. The heterogeneous organohydrogel with unprecedented automation and non‐interference possesses the enormous potential to be a next‐generation platform for drug screening. [ABSTRACT FROM AUTHOR]

BackgroundUnderstanding how landscape factors, including suites of geographic and environmental variables, and both historical and contemporary ecological and evolutionary processes shape the distribution of genetic diversity is a primary goal of landscape and conservation genetics and may be particularly consequential for species involved in ecological restoration. In this study, we examine the factors that shape the distribution of genetic variation in a leguminous shrub (Caragana microphylla) important for restoration efforts on the Mongolian Plateau in China. This region houses several major bioclimatic gradients, and C. microphylla is an important restoration species because it stabilizes soils and prevents advancing desertification on the Inner Mongolia Plateau caused by ongoing climate change.ResultsWe assembled an expansive genomic dataset, consisting of 22 microsatellite loci, four cpDNA regions, and 5788 genome-wide SNPs from ten populations of C. microphylla. We then applied ecological niche modelling and linear and non-linear regression techniques to investigate the historical and contemporary forces that explain patterns of genetic diversity and population structure in C. microphylla on the Inner Mongolia Plateau. We found strong evidence that both geographic and environmental heterogeneity contribute to genetic differentiation and that the spatial distribution of genetic diversity in C. microphylla appears to result partly from the presence of a glacial refugium at the southwestern edge of its current range.ConclusionsThese results suggest that geographic, environmental, and historical factors have all contributed to spatial genetic variation in this ecologically important species. These results should guide restoration plans to sustain genetic diversity during plant translocations.

As the era of sixth-generation (6G) communications approaches, there will be an unprecedented increase in the number of wireless internet-connected devices and a sharp rise in mobile data traffic. Faced with the scarcity of spectrum resources in traditional communication networks and challenges such as rapidly establishing communications after disasters, this study leverages unmanned aerial vehicles (UAVs) to promote an integrated multi-hop communication system combining free-space optical (FSO) communication, terahertz (THz) technology, and intelligent reflecting surface (IRS). This innovative amalgamation capitalizes on the flexibility of UAVs, the deployability of IRS, and the complementary strengths of FSO and THz communications. We have developed a comprehensive channel model that includes the effects of atmospheric turbulence, attenuation, pointing errors, and angle-of-arrival (AOA) fluctuations. Furthermore, we have derived probability density functions (PDFs) and cumulative distribution functions (CDFs) for various switching techniques. Employing advanced methods such as Gaussian–Laguerre quadrature and the central limit theorem (CLT), we have calculated key performance indicators including the average outage probability, bit error rate (BER), and channel capacity. The numerical results demonstrate that IRS significantly enhances the performance of the UAV-based hybrid FSO/THz system. The research indicates that optimizing the number of IRS elements can substantially increase throughput and reliability while minimizing switching costs. Additionally, the multi-hop approach specifically addresses the line-of-sight (LoS) dependency limitations inherent in FSO and THz systems by utilizing UAVs as dynamic relay points. This strategy effectively bridges longer distances, overcoming physical and atmospheric obstacles, and ensures stable communication links even under adverse conditions. This study underscores that the enhanced multi-hop FSO/THz link is highly effective for emergency communications after disasters, addressing the challenge of scarce spectrum resources. By strategically deploying UAVs as relay points in a multi-hop configuration, the system achieves greater flexibility and resilience, making it highly suitable for critical communication scenarios where traditional networks might fail. [ABSTRACT FROM AUTHOR]

Inflammatory myofibroblastic tumors (IMTs) are characterized by myofibroblast proliferation and an inflammatory cell infiltrate. Little is known about the molecular pathways that precipitate IMT formation. Here, we report the identification of somatic mutations in UPF1, a gene that encodes an essential component of the nonsense-mediated RNA decay (NMD) pathway, in 13 of 15 pulmonary IMT samples. The majority of mutations occurred in a specific region of UPF1 and triggered UPF1 alternative splicing. Several mRNA targets of the NMD pathway were upregulated in IMT samples, indicating that the UPF1 mutations led to reduced NMD magnitude. These upregulated NMD targets included NIK mRNA, which encodes a potent activator of NF-κB. In human lung cells, UPF1 depletion increased expression of chemokine-encoding genes in a NIK-dependent manner. Elevated chemokines and IgE class switching events were observed in IMT samples, consistent with NIK upregulation in these tumors. Together, these results support a model in which UPF1 mutations downregulate NMD, leading to NIK-dependent NF-κB induction, which contributes to the immune infiltration that is characteristic of IMTs. The molecular link between the NMD pathway and IMTs has implications for the diagnosis and treatment of these tumors.