Screening of the Key Genes and Signalling Pathways for Diabetic Nephropathy Using Bioinformatics Analysis

BackgroundThis study aimed to identify biological markers for diabetic nephropathy (DN) and explore their underlying mechanisms.MethodsFour datasets, GSE30528, GSE47183, GSE104948, and GSE96804, were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified using the “limma” package, and the “RobustRankAggreg” package was used to screen the overlapping DEGs. The hub genes were identified using cytoHubba of Cytoscape. Logistic regression analysis was used to further analyse the hub genes, followed by receiver operating characteristic (ROC) curve analysis to predict the diagnostic effectiveness of the hub genes. Correlation analysis and enrichment analysis of the hub genes were performed to identify the potential functions of the hub genes involved in DN.ResultsIn total, 55 DEGs, including 38 upregulated and 17 downregulated genes, were identified from the three datasets. Four hub genes (FN1, CD44, C1QB, and C1QA) were screened out by the “UpSetR” package, and FN1 was identified as a key gene for DN by logistic regression analysis. Correlation analysis and enrichment analysis showed that FN1 was positively correlated with four genes (COL6A3, COL1A2, THBS2, and CD44) and with the development of DN through the extracellular matrix (ECM)–receptor interaction pathway.ConclusionsWe identified four candidate genes: FN1, C1QA, C1QB, and CD44. On further investigating the biological functions of FN1, we showed that FN1 was positively correlated with THBS2, COL1A2, COL6A3, and CD44 and involved in the development of DN through the ECM–receptor interaction pathway. THBS2, COL1A2, COL6A3, and CD44 may be novel biomarkers and target therapeutic candidates for DN

How Human Activities Affect Heavy Metal Contamination of Soil and Sediment in a Long-Term Reclaimed Area of the Liaohe River Delta, North China

Heavy metal pollution in soils and sediments is becoming a matter of wide concern, this study was carried out in Dawa County of the Liaohe River Delta, with the aim of exploring the impacts of land use levels on heavy metal contamination of soil and sediment. A total of 129 soil samples were collected in different land use intensities (LUI). Soil metals (Fe, Mn, Cd, Cr, Cu, Ni, Pb and Zn) and soil salinity, pH, soil organic carbon (SOC), nitrate nitrogen (NO3−-N), available phosphorus (AP) and grain sizes were analyzed. Correlation analysis indicated that SOC and grain size played important roles in affecting the heavy metal distribution. The factor analysis results indicated that heavy metal contamination was most probably caused by industrial and agricultural wastewater discharges, domestic sewage discharge and atmospheric deposition. Using ANOVA, it found that human activities significantly changed soil physic-chemical properties through soil erosion, leaching and fertilizer application, further affecting the behaviors of heavy metals in the soil and sediments. The anthropogenic factors could lead to potential environmental risk, as indicated by the Geo-accumulation index (Igeo) results of heavy metals. Overall, the heavy metals generally had approached or even exceeded moderately polluted (0 < Igeo < 1, 1 < Igeo < 2), but the Pb and Cu pollution level was low (Igeo < 0), and the Cd pollution level was moderately or strongly polluted (2 < Igeo < 3, 3 < Igeo < 4) in the five land use levels. This study will provide valuable information for appropriately determining how land should be used in future reclamation areas, as well as for the sustainable management of estuarine areas around the world

Complete chloroplast genome of Ulva prolifera, the dominant species of green macroalgal blooms in Yellow Sea, China

Ulva prolifera is the dominant species of green macroalgal blooms in the Yellow Sea, China. In this study, we sequenced and annotated the complete chloroplast genome of U. prolifera (GenBank accession number: KX342867). The genome of circular chromosomes consists of 93,066 including 66 protein-encoding genes, 26 tRNA genes, and 3 rRNA genes. Compared with the 16 species from Chlorophyta, it has eight genes in expansion and 15 genes in shrink. Phylogenetic analysis shows positioned U. prolifera with U. linza, while Ulva sp.UNA00071828 is closely allied with Ulva fasciata

The space cold atom interferometer for testing the equivalence principle in the China Space Station

Abstract The precision of the weak equivalence principle (WEP) test using atom interferometers (AIs) is expected to be extremely high in microgravity environment. The microgravity scientific laboratory cabinet (MSLC) in the China Space Station (CSS) can provide a higher-level microgravity than the CSS itself, which provides a good experimental environment for scientific experiments that require high microgravity. We designed and realized a payload of a dual-species cold rubidium atom interferometer. The payload is highly integrated and has a size of $$460\,{\rm{mm}}\times 330\,{\rm{mm}}\times 260\,{\rm{mm}}$$ 460 mm × 330 mm × 260 mm . It will be installed in the MSLC to carry out high-precision WEP test experiment. In this article, we introduce the constraints and guidelines of the payload design, the compositions and functions of the scientific payload, the expected test precision in space, and some results of the ground test experiments

Systematic evaluation of a targeted gene capture sequencing panel for molecular diagnosis of retinitis pigmentosa

<div><p>Background</p><p>Inherited eye diseases are major causes of vision loss in both children and adults. Inherited eye diseases are characterized by clinical variability and pronounced genetic heterogeneity. Genetic testing may provide an accurate diagnosis for ophthalmic genetic disorders and allow gene therapy for specific diseases.</p><p>Methods</p><p>A targeted gene capture panel was designed to capture exons of 283 inherited eye disease genes including 58 known causative retinitis pigmentosa (RP) genes. 180 samples were tested with this panel, 68 were previously tested by Sanger sequencing. Systematic evaluation of our method and comprehensive molecular diagnosis were carried on 99 RP patients.</p><p>Results</p><p>96.85% targeted regions were covered by at least 20 folds, the accuracy of variants detection was 99.994%. In 4 of the 68 samples previously tested by Sanger sequencing, mutations of other diseases not consisting with the clinical diagnosis were detected by next-generation sequencing (NGS) not Sanger. Among the 99 RP patients, 64 (64.6%) were detected with pathogenic mutations, while in 3 patients, it was inconsistent between molecular diagnosis and their initial clinical diagnosis. After revisiting, one patient’s clinical diagnosis was reclassified. In addition, 3 patients were found carrying large deletions.</p><p>Conclusions</p><p>We have systematically evaluated our method and compared it with Sanger sequencing, and have identified a large number of novel mutations in a cohort of 99 RP patients. The results showed a sufficient accuracy of our method and suggested the importance of molecular diagnosis in clinical diagnosis.</p></div

Inconsistent result between NGS and Sanger in four patients.

<p>Inconsistent result between NGS and Sanger in four patients.</p

Correlation of coverage rate and sequencing depth on consensus targeted exons.

<p>The graph shows pair-wise Pearson correlation coefficients for both sequencing coverage (top-left triangle) and depth rate (bottom-right triangle) based on 4381 exons targeted by our eye chips. A. Correlation of sequencing coverage and depth rate on consensus targeted exons of the samples of the 4 targeted capture experiments. B. Correlation of sequencing coverage and depth rate on consensus targeted exons of 67 samples.</p