Search

Background: Keloid is a disease characterized by proliferation of fibrous tissue after the healing of skin tissue, which seriously affects the daily life of patients. However, the clinical treatment of keloids still has limitations, that is, it is not effective in controlling keloids, resulting in a high recurrence rate. Thus, it is urgent to identify new signatures to improve the diagnosis and treatment of keloids. Method: Bulk RNA seq and scRNA seq data were downloaded from the GEO database. First, we used WGCNA and MEGENA to co-identify keloid/immune-related DEGs. Subsequently, we used three machine learning algorithms (Randomforest, SVM-RFE, and LASSO) to identify hub immune-related genes of keloid (KHIGs) and investigated the heterogeneous expression of KHIGs during fibroblast subpopulation differentiation using scRNA-seq. Finally, we used HE and Masson staining, quantitative reverse transcription-PCR, western blotting, immunohistochemical, and Immunofluorescent assay to investigate the dysregulated expression and the mechanism of retinoic acid in keloids. Results: In the present study, we identified PTGFR, RBP5, and LIF as KHIGs and validated their diagnostic performance. Subsequently, we constructed a novel artificial neural network molecular diagnostic model based on the transcriptome pattern of KHIGs, which is expected to break through the current dilemma faced by molecular diagnosis of keloids in the clinic. Meanwhile, the constructed IG score can also effectively predict keloid risk, which provides a new strategy for keloid prevention. Additionally, we observed that KHIGs were also heterogeneously expressed in the constructed differentiation trajectories of fibroblast subtypes, which may affect the differentiation of fibroblast subtypes and thus lead to dysregulation of the immune microenvironment in keloids. Finally, we found that retinoic acid may treat or alleviate keloids by inhibiting RBP5 to differentiate pro-inflammatory fibroblasts (PIF) to mesenchymal fibroblasts (MF), which further reduces collagen secretion. Conclusion: In summary, the present study provides novel immune signatures (PTGFR, RBP5, and LIF) for keloid diagnosis and treatment, and identifies retinoic acid as potential anti-keloid drugs. More importantly, we provide a new perspective for understanding the interactions between different fibroblast subtypes in keloids and the remodeling of their immune microenvironment. [ABSTRACT FROM AUTHOR]

Background: This meta-analysis investigated the influence of exercise on cognitive function in people living with diabetes. Methods: Stringent criteria for literature inclusion and exclusion were defined. Searches were conducted across four English databases to gather randomized controlled trials investigating exercise interventions for cognitive function in people living with diabetes. Outcome indicators from 1193 subjects across 12 articles were analyzed using RevMan 5.4 software. Results: Exercise intervention demonstrated the ability to mitigate cognitive decline in people living with diabetes, with a combined effect size (standardized mean difference) of 0.91, 95% CI: 0.28, 1.54, P < 0.00001. The intervention effect showed significant modulation by intervention content (I2 = 95%), intervention duration (I2 = 95%), intervention frequency (I2 = 95%), and intervention cycle (I2 = 96%). Among these factors, multi-component exercise, sessions >40 minutes, exercise frequency >4 times per week, and sustained exercise for >6 months were paramount, all with P < 0.05. Conclusion: Exercise intervention emerges as a viable strategy for delaying cognitive decline in people living with diabetes. Its efficacy is subject to modulation by various variables. Optimal intervention includes multi-component exercise, individual sessions lasting 40–60 minutes, exercising >4 times a week, and continuous exercise for over 6 months. [ABSTRACT FROM AUTHOR]

Based on the land economic density of 892 town units, the spatial pattern of the land economic density in Zhejiang Province is analyzed using the coefficient of variation, spatial classification, and spatial correlation methods, and the influencing factors are analyzed using a spatial regression model. The results are as follows: (1) The coefficients of variation were 2.6 and 3.1 in 2014 and 2019, respectively, indicating that the degree of imbalance of the town's industrial economy at the county level increased. (2) The distribution of the high-level agglomeration areas was characterized by one core area and two sub-core areas. The main core area was located at the junction of Hangzhou City, Shaoxing City, and Jiaxing City, and the two sub-core areas were located in Yuyao City and the main urban area of Ningbo City. In addition, several small-scale agglomeration areas composed of medium and high-level units were distributed in Wenzhou City. (3) The high-value agglomeration and low-value agglomeration distribution in the spatial correlation patterns was identified using the spatial auto-correlation method. The hot spots and sub-hot spots were distributed in Northern Zhejiang, and the cold spots formed a large-scale agglomeration in Quzhou City, Lishui City, Taizhou City, and several other cities in Southern Zhejiang. (4) Compared with the county scale, the spatial scope of the high-level areas in Northern Zhejiang shrunk significantly at the township scale, and the high-level agglomeration areas along the southeast coast changed into a cluster of several townships. (5) According to the geographically weighted regression (GWR) model, the importance of influencing factors is as follows: population density > regional area > industrial output value per capita > total population > proportion of secondary and tertiary personnel > total employees. [ABSTRACT FROM AUTHOR]

Objective To investigate the effects of Hes1 gene on the proliferation, migration and invasion of hepatocellular carcinoma cell line Hep1-6. Methods Cell proliferation, cell colony formation, migration and invasion were measured after Hes1 gene were overexpressed in Hep1-6 cells mediated by recombinant adenovirus. Results The clone numbers of Hep1-6 cells infected with Ad-Hes1 were significantly less than the control group infected with Ad-GFP (P < 0.001). Six days after Ad-Hes1 infection, OD450nm of Hep1-6 cells were significantly lower than that of control group (P < 0.01). The wound healing rates of Hep1-6 cells infected with Ad-Hes1 at 24h and 48h were significantly lower than those of the control group (P < 0.001). The number of Hep1-6 cells infected with Ad-Hes1 migrating into the lower chamber of Transwell after 48 h of culture was significantly lower than that of the control group (P < 0.001). The number of Hep1-6 cells infected with Ad-Hes1 invading into the lower chamber of Transwell after 48h of culture was significantly lower than that in the control group (P < 0.01). Conclusion Hes1 could suppress the proliferation, migration and invasion of Hep1-6 cells.

Fabricating highly oriented 2D nanosheet arrays is crucial for boosting their performance in electronics, catalysis, optics, and energy conversion, while it remains a challenge due to the high surface energy often leads to random aggregation or interlaced structure. In this study, it is found that the exposed facet of Fe2O3 can greatly influence the interface growth arrangement of bimetallic hydroxide (NiCo(OH)2) nanosheets. The NiCo(OH)2 nanosheets tend to parallel‐standing on the cubic and spindle Fe2O3 while random‐ and interlaced‐standing on the Fe2O3 hexagonal nanoplates and microspheres. The theoretical simulation further indicates the orientation of deposited hydroxide sheets is decided explicitly by the interfacial lattice match/mismatch. Compared to the common interlaced structure of nanosheets, the parallel‐standing nanosheet arrays reduce grain boundaries and improve the charge transfer efficiency. As a result, the derived NiCoP cages exhibit a promising oxygen evolution reaction performance with an overpotential of 255 mV at 10 mA cm−2, and the maximum current density of 400 mA cm−2 with the overpotential of 319 mV. [ABSTRACT FROM AUTHOR]

The massive use of fossil fuels releases a great amount of CO2, which substantially contributes to the global warming. For the global goal of putting CO2 emission under control, effective utilization of CO2 is particularly meaningful. Electrocatalytic CO2 reduction reaction (eCO2RR) has great potential in CO2 utilization, because it can convert CO2 into valuable carbon‐containing chemicals and feedstock using renewable electricity. The catalyst design for eCO2RR is a key challenge to achieving efficient conversion of CO2 to fuels and useful chemicals. For a typical heterogeneous catalyst, surface and interface engineering is an effective approach to enhance reaction activity. Herein, the development and research progress in CO2 catalysts with focus on surface and interface engineering are reviewed. First, the fundaments of eCO2RR is briefly discussed from the reaction mechanism to performance evaluation methods, introducing the role of the surface and interface engineering of electrocatalyst in eCO2RR. Then, several routes to optimize the surface and interface of CO2 electrocatalysts, including morphology, dopants, atomic vacancies, grain boundaries, surface modification, etc. are reviewed and representative examples are given. At the end of this review, we share our personal views in future research of eCO2RR. [ABSTRACT FROM AUTHOR]