Identification of fibronectin 1 (FN1) and complement component 3 (C3) as immune infiltration-related biomarkers for diabetic nephropathy using integrated bioinformatic analysis

Immune cell infiltration (ICI) plays a pivotal role in the development of diabetic nephropathy (DN). Evidence suggests that immune-related genes play an important role in the initiation of inflammation and the recruitment of immune cells. However, the underlying mechanisms and immune-related biomarkers in DN have not been elucidated. Therefore, this study aimed to explore immune-related biomarkers in DN and the underlying mechanisms using bioinformatic approaches. In this study, four DN glomerular datasets were downloaded, merged, and divided into training and test cohorts. First, we identified 55 differentially expressed immune-related genes; their biological functions were mainly enriched in leukocyte chemotaxis and neutrophil migration. The CIBERSORT algorithm was then used to evaluate the infiltrated immune cells; macrophages M1/M2, T cells CD8, and resting mast cells were strongly associated with DN. The ICI-related gene modules as well as 25 candidate hub genes were identified to construct a protein-protein interactive network and conduct molecular complex detection using the GOSemSim algorithm. Consequently, FN1, C3, and VEGFC were identified as immune-related biomarkers in DN, and a related transcription factor–miRNA–target network was constructed. Receiver operating characteristic curve analysis was estimated in the test cohort; FN1 and C3 had large area under the curve values (0.837 and 0.824, respectively). Clinical validation showed that FN1 and C3 were negatively related to the glomerular filtration rate in patients with DN. Six potential therapeutic small molecule compounds, such as calyculin, phenamil, and clofazimine, were discovered in the connectivity map. In conclusion, FN1 and C3 are immune-related biomarkers of DN.</p

Grazing offsets the stimulating effects of nitrogen addition on soil CH₄ emissions in a meadow steppe in Northeast China - Fig 5

Dependence of average CH4 flux on (a) aboveground biomass (AGB), (b) belowground biomass (BGB) and (c) litter mass in 2018. Values of R2 and P are provided.</p

Grazing offsets the stimulating effects of nitrogen addition on soil CH₄ emissions in a meadow steppe in Northeast China - Fig 3

Effects of the experimental treatments (CK: control, G: grazing, N: nitrogen addition, NG: grazing and nitrogen addition) on aboveground biomass (a), belowground biomass (b) and litter mass (c) in 2017 and 2018. Data are reported as the arithmetic mean ± 1 standard error (n = 4).</p

Grazing offsets the stimulating effects of nitrogen addition on soil CH₄ emissions in a meadow steppe in Northeast China - Fig 4

Effects of the experimental treatments (CK: control, G: grazing, N: nitrogen addition, NG: grazing and nitrogen addition) on 0–10 cm soil temperature (a), 0–10 cm soil water filled pore space (WFPS) (b), content of soil NH4+-N (c) and content of soil NO3--N (d) from 2017 to 2018. Results of two-way ANOVA for the effects of grazing, N addition and their interactions on soil temperature, soil WFPS, soil NH4+-N and soil NO3--N are provided. Data are reported as the arithmetic mean ± 1 standard error (n = 4).</p

Grazing offsets the stimulating effects of nitrogen addition on soil CH₄ emissions in a meadow steppe in Northeast China - Fig 6

Dependence of CH4 flux on (a) soil water filled pore space (WFPS) and (b) soil temperature for each of the four experimental treatments (CK: control, G: grazing, N: nitrogen addition, NG: grazing and nitrogen addition). The CH4 fluxes (enclosed in a red square) from August to September in 2017 were not included in the regression analysis. Dependence of CH4 flux on (c) soil NH4+-N and (d) soil NO3--N and (e) soil pH across the four treatments. Values of R2 and P are provided.</p

Grazing offsets the stimulating effects of nitrogen addition on soil CH₄ emissions in a meadow steppe in Northeast China - Fig 2

Seasonal variations (a), monthly average (b), annual average (c) and annual cumulative (d) of CH4 flux for the four experimental treatments (CK: control, G: grazing, N: nitrogen addition, NG: grazing and nitrogen addition) from April 2017 to September 2018). Results of two-way ANOVA for the effects of grazing, N addition and their interactions on average CH4 flux are provided. Data are reported as the arithmetic mean ± 1 standard error (n = 4).</p

Grazing offsets the stimulating effects of nitrogen addition on soil CH₄ emissions in a meadow steppe in Northeast China - Fig 1

Variation in air temperature (a) and precipitation (a) from April 2017 to September 2018. Dynamics of soil temperature (b) and soil water filled pore space (c) in the different treatments (CK: control, G: grazing, N: nitrogen addition, NG: grazing and nitrogen addition) during the experimental period. Data are reported as the arithmetic mean ± 1 standard error (n = 4).</p

Eye-Readable and Wearable Colorimetric Sensor Arrays for <i>In Situ</i> Monitoring of Volatile Organic Compounds

Wearable sensors utilize changes in color as a response to physiological stimuli, making them easily recognizable by the naked eye. These colorimetric wearable sensors offer benefits such as easy readability, rapid responsiveness, cost-effectiveness, and straightforward manufacturing techniques. However, their applications in detecting volatile organic compounds (VOCs) in situ have been limited due to the low concentration of complex VOCs and complicated external interferences. Aiming to address these challenges, we introduced readable and wearable colorimetric sensing arrays with a microchannel structure and highly gas-sensitive materials for in situ detection of complex VOCs. The highly gas-sensitive materials were designed by loading gas-sensitive dyes into the porous metal–organic frameworks and further depositing the composites on the electrospun nanofiber membrane. The colorimetric sensor arrays were fabricated using various gas-sensitive composites, including eight dye/MOF composites that respond to various VOCs and two Pd2+/dye/MOF composites that respond to ethylene. This enables the specific recognition of multiple characteristic VOCs. A microfluidic channel made of polydimethylsiloxane (PDMS) was integrated with different colorimetric elements to create a wearable sensor array. It was attached to the surface of fruits to collect and monitor VOCs using the DenseNet classification method. As a proof of concept, we demonstrated the feasibility of the wearable sensing system in monitoring the ripening process of fruits by continuously measuring the VOC emissions from the skin of the fruit

Copper-Catalyzed Synthesis of Quinoxalines with <i>o-</i>Phenylenediamine and Terminal Alkyne in the Presence of Bases

A novel way of synthesizing quinoxalines efficiently through cyclization of o-phenylenediamine and terminal alkyne by Cu(II) and bases is developed. This reaction proceeds smoothly to give the products in moderate to good yields

Microbial Degradation of Zearalenone by a Novel Microbial Consortium, NZDC-6, and Its Application on Contaminated Corncob by Semisolid Fermentation

A novel microbial consortium (NZDC-6) was screened and characterized to detoxify the estrogenic mycotoxin zearalenone (ZEA), which commonly contaminates maize and is a major threat to food and health security. We found NZDC-6 to be thermophilic and highly effective, with a 90.3% ZEA degradation ratio at an optimum temperature of 60 °C. NZDC-6 was also effective at degrading the more estrogenic ZEA cognates, α-zearalenol (α-ZAL) and β-zearalenol (β-ZAL), with >90% degradation ratios. To evaluate a practical application, ZEA-contaminated corncobs were treated with NZDC-6 via semisolid fermentation. Measurements of physicochemical parameters and 16S microbial diversity and redundancy analysis (RDA) indicated that ZEA removal was most efficient at a low corncob solid content (< 5%), as a high solid content overwhelmed the microbial metabolic load, leading to increased dissolved oxygen and lowered pH. Our results demonstrate that the control of environmental variables is crucial for effective ZEA microbial removal in practical applications