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Identification of SOCS3 and PTGS2 as new biomarkers for the diagnosis of gout by cross-species comprehensive analysis

Background

Gout is the most common inflammatory arthritis in adults. Gout is an arthritic disease caused by the deposition of monosodium urate crystal (MSU) in the joints, which can lead to acute inflammation and damage adjacent tissue. Hyperuricemia is the main risk factor for MSU crystal deposition and gout. With the increasing burden of gout disease, the identification of potential biomarkers and novel targets for diagnosis is urgently needed.

Methods

For the analysis of this subject paper, we downloaded the human gout data set GSE160170 and the gout mouse model data set GSE190138 from the GEO database. To obtain the differentially expressed genes (DEGs), we intersected the two data sets. Using the cytohubba algorithm, we identified the key genes and enriched them through GO and KEGG. The gene expression trends of three subgroups (normal control group, intermittent gout group and acute gout attack group) were analyzed by Series Test of Cluster (STC) analysis, and the key genes were screened out, and the diagnostic effect was verified by ROC curve. The expression of key genes in dorsal root nerve and spinal cord of gout mice was analyzed. Finally, the clinical samples of normal control group, hyperuricemia group, intermittent gout group and acute gout attack group were collected, and the expression of key genes at protein level was verified by ELISA.

Result

We obtained 59 co-upregulated and 28 co-downregulated genes by comparing the DEGs between gout mouse model data set and human gout data set. 7 hub DEGs(IL1B, IL10, NLRP3, SOCS3, PTGS2) were screened out via Cytohubba algorithm. The results of both GO and KEGG enrichment analyses indicate that 7 hub genes play a significant role in regulating the inflammatory response, cytokine production in immune response, and the TNF signaling pathway. The most representative hub genes SOCS3 and PTGS2 were screened out by Series Test of Cluster, and ROC analysis results showed the AUC values were both up to 1.000. In addition, we found that PTGS2 expression was significantly elevated in the dorsal root ganglia and spinal cord in monosodium urate(MSU)-induced gout mouse model. The ELISA results revealed that the expression of SOCS3 and PTGS2 was notably higher in the acute gout attack and intermittent gout groups compared to the normal control group. This difference was statistically significant, indicating a clear distinction between the groups.

Conclusion

Through cross-species comprehensive analysis and experimental verification, SOCS3 and PTGS2 were proved to be new biomarkers for diagnosing gout and predicting disease progression.

Flexible Actuators with Hygroscopic Adaptability for Smart Wearables and Soft Grippers

Flexible actuators have garnered significant interest in the domains of biomedical devices, human-machine interfaces, and smart wearables. However, the mechanical properties of existing materials are not sufficiently robust, and the expensive and time-consuming pretreatment process and the ambiguous high-degree-of-freedom deformation mechanism make it difficult to meet the demands of industrialized production. Hence, drawing inspiration from the adaptable movement of living organisms in the natural world, this research created and engineered a fully textile-based humidity-sensitive flexible actuator (TbHs-FA) using high-cost-effective viscose/PET fibers as raw materials. The breakthrough development in actuation performance is covered, including substantial contraction force (92.53 cN), high actuation curvature (16.78 cm-1), and fast response (264 cN s-1 and 46.61 cm-1 s-1). Additionally, the programmable stiffness system and weave structure give TbHs-FAs low hysteresis and fatigue resistance, narrowing the gap between the conceptual laboratory-scale design of existing fully textile-based humidity-sensitive flexible actuators and actual textiles. The high-degree-of-freedom and large bending deformation mechanisms are elucidated for the first time by combining microscopic mechanical structure simulation and macroscopic energy conversion analysis. The novel humidity-sensitive flexible actuator possesses strong mechanical qualities, making it suitable for applications such as flexible robots, medicinal devices, and smart wearables.

Moisture-Electric-Moisture-Sensitive Heterostructure Triggered Proton Hopping for Quality-Enhancing Moist-Electric Generator

Moisture-enabled electricity (ME) is a method of converting the potential energy of water in the external environment into electrical energy through the interaction of functional materials with water molecules and can be directly applied to energy harvesting and signal expression. However, ME can be unreliable in numerous applications due to its sluggish response to moisture, thus sacrificing the value of fast energy harvesting and highly accurate information representation. Here, by constructing a moisture-electric-moisture-sensitive (ME-MS) heterostructure, we develop an efficient ME generator with ultra-fast electric response to moisture achieved by triggering Grotthuss protons hopping in the sensitized ZnO, which modulates the heterostructure built-in interfacial potential, enables quick response (0.435 s), an unprecedented ultra-fast response rate of 972.4 mV s-1, and a durable electrical signal output for 8 h without any attenuation. Our research provides an efficient way to generate electricity and important insight for a deeper understanding of the mechanisms of moisture-generated carrier migration in ME generator, which has a more comprehensive working scene and can serve as a typical model for human health monitoring and smart medical electronics design.

Self-Assembled Porous-Reinforcement Microstructure-Based Flexible Triboelectric Patch for Remote Healthcare

Realizing real-time monitoring of physiological signals is vital for preventing and treating chronic diseases in elderly individuals. However, wearable sensors with low power consumption and high sensitivity to both weak physiological signals and large mechanical stimuli remain challenges. Here, a flexible triboelectric patch (FTEP) based on porous-reinforcement microstructures for remote health monitoring has been reported. The porous-reinforcement microstructure is constructed by the self-assembly of silicone rubber adhering to the porous framework of the PU sponge. The mechanical properties of the FTEP can be regulated by the concentrations of silicone rubber dilution. For pressure sensing, its sensitivity can be effectively improved fivefold compared to the device with a solid dielectric layer, reaching 5.93 kPa-1 under a pressure range of 0-5 kPa. In addition, the FTEP has a wide detection range up to 50 kPa with a sensitivity of 0.21 kPa-1. The porous microstructure makes the FTEP ultra-sensitive to external pressure, and the reinforcements endow the device with a greater deformation limit in a wide detection range. Finally, a novel concept of the wearable Internet of Healthcare (IoH) system for real-time physiological signal monitoring has been proposed, which could provide real-time physiological information for ambulatory personalized healthcare monitoring.