Bioinformatic analysis of retinal gene function and expression in diabetic rats

Reduced light exposure mitigates streptozotocin-induced vascular changes and gliosis in diabetic retina by an anti-inflammatory effect and increased retinal cholesterol turnover

Diabetic retinopathy is not cured efficiently and changes of lifestyle measures may delay early retinal injury in diabetes. The aim of our study was to investigate the effects of reduced daily light exposure on retinal vascular changes in streptozotocin (STZ)-induced model of DM with emphasis on inflammation, Aqp4 expression, visual cycle and cholesterol metabolism-related gene expression in rat retina and RPE. Male Wistar rats were divided into the following groups: 1. control; 2. diabetic group (DM) treated with streptozotocin (100 mg/kg); 3. group exposed to light/dark cycle 6/18 h (6/18); 4. diabetic group exposed to light/dark cycle 6/18 h (DM+6/18). Retinal vascular abnormalities were estimated based on lectin staining, while the expression of genes involved in the visual cycle, cholesterol metabolism, and inflammation was determined by qRT-PCR. Reduced light exposure alleviated vasculopathy, gliosis and the expression of IL-1 and TNF-α in the retina with increased perivascular Aqp4 expression. The expression of genes involved in visual cycle and cholesterol metabolism was significantly up-regulated in RPE in DM+6/18 vs. DM group. In the retina only the expression of APOE was significantly higher in DM+6/18 vs. DM group. Reduced light exposure mitigates vascular changes and gliosis in DM via its anti-inflammatory effect, increased retinal cholesterol turnover and perivascular Aqp4 expression.

Two ferroptosis-specific expressed genes NOX4 and PARP14 are considered as potential biomarkers for the diagnosis and treatment of diabetic retinopathy and atherosclerosis

OBJECTIVES

Both Diabetic retinopathy (DR) and Atherosclerosis (AS) are common complications in patients with diabetes, and they share major pathophysiological similarities and have a common pathogenesis. Studies performed to date have demonstrated that ferroptosis plays a vital part in the occurrence and development of DR and AS, but its mechanism in the two diseases remains poorly understood.

METHODS

DR Chip data (GSE60436 and GSE102485) and AS chip data (GSE100927 and GSE57691) were obtained from the Gene Expression Omnibus (GEO) database. The screening of the differential expression genes (DEGs) was analyzed using the limma package, and the genes related to ferroptosis were obtained from the FerrDb V2 database. Two key genes (NOX4 and PARP14) were identified through external datasets validation and receiver operating characteristic (ROC) curve analysis. Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) were used to conduct a functional enrichment analysis, and miRNA-mRNA networks were established. The CIBERSORT algorithm was applied to identify the immune cell infiltration between the disease group and control group. Next, the correlations between key genes and infiltrating immune cells were investigated by the Spearman method. Finally, the correlation between 2 key genes and ferroptosis markers was confirmed.

RESULTS

Nine ferroptosis differentially expressed genes (DE-FRGs) between DR and AS were identified in this study. NOX4 and PARP14 were selected as key genes for further analysis by external datasets and ROC curve analysis. The key genes NOX4, PARP14 and their correlated genes (such as CYBA, NOX1, NOX3, CYBB, PARP9, PARP10, and PARP15) are mainly enriched in oxidoreductase activity, protein ADP-ribosylation, superoxide metabolic process, reactive oxygen species metabolic process, PID pathway, and VEGFA-VEGFR2 pathway. A miRNA-mRNA network was constructed, and we got 12 miRNAs correlated with the target gene NOX4, 38 miRNAs correlated with the target gene PARP14. Three common miRNAs (hsa-miR-1-3p, hsa-miR-129-2-3p, and hsa-miR-155-5p) were observed in the network. Immune infiltration analysis displayed that activated B cell, MDSC, and Type 17 T helper cell are the common immune cells involved in the immune infiltration process of DR and AS. The results revealed that there are significant correlations between two key genes and most ferroptosis marker genes no matter in DR or AS.

CONCLUSION

Ferroptosis-related genes NOX4 and PARP14 may be common biomarkers of DR and AS. Both were associated with immune infiltration in patients with DR and AS. Our data provide a theoretical basis for the early diagnosis and immunotherapy of the two diseases.

Six potential biomarkers in septic shock: a deep bioinformatics and prospective observational study

Background

Septic shock occurs when sepsis is related to severe hypotension and leads to a remarkable high number of deaths. The early diagnosis of septic shock is essential to reduce mortality. High-quality biomarkers can be objectively measured and evaluated as indicators to accurately predict disease diagnosis. However, single-gene prediction efficiency is inadequate; therefore, we identified a risk-score model based on gene signature to elevate predictive efficiency.

Methods

The gene expression profiles of GSE33118 and GSE26440 were downloaded from the Gene Expression Omnibus (GEO) database. These two datasets were merged, and the differentially expressed genes (DEGs) were identified using the limma package in R software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments of DEGs were performed. Subsequently, Lasso regression and Boruta feature selection algorithm were combined to identify the hub genes of septic shock. GSE9692 was then subjected to weighted gene co-expression network analysis (WGCNA) to identify the septic shock-related gene modules. Subsequently, the genes within such modules that matched with septic shock-related DEGs were identified as the hub genes of septic shock. To further understand the function and signaling pathways of hub genes, we performed gene set variation analysis (GSVA) and then used the CIBERSORT tool to analyze the immune cell infiltration pattern of diseases. The diagnostic value of hub genes in septic shock was determined using receiver operating characteristic (ROC) analysis and verified using quantitative PCR (qPCR) and Western blotting in our hospital patients with septic shock.

Results

A total of 975 DEGs in the GSE33118 and GSE26440 databases were obtained, of which 30 DEGs were remarkably upregulated. With the use of Lasso regression and Boruta feature selection algorithm, six hub genes (CD177, CLEC5A, CYSTM1, MCEMP1, MMP8, and RGL4) with expression differences in septic shock were screened as potential diagnostic markers for septic shock among the significant DEGs and were further validated in the GSE9692 dataset. WGCNA was used to identify the co-expression modules and module-trait correlation. Enrichment analysis showed significant enrichment in the reactive oxygen species pathway, hypoxia, phosphatidylinositol 3-kinases (PI3K)/Protein Kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling, nuclear factor-κβ/tumor necrosis factor alpha (NF-κβ/TNF-α), and interleukin-6 (IL-6)/Janus Kinase (JAK)/Signal Transducers and Activators of Transcription 3 (STAT3) signaling pathways. The receiver operating characteristic curve (ROC) of these signature genes was 0.938, 0.914, 0.939, 0.956, 0.932, and 0.914, respectively. In the immune cell infiltration analysis, the infiltration of M0 macrophages, activated mast cells, neutrophils, CD8 T cells, and naive B cells was more significant in the septic shock group. In addition, higher expression levels of CD177, CLEC5A, CYSTM1, MCEMP1, MMP8, and RGL4 messenger RNA (mRNA) were observed in peripheral blood mononuclear cells (PBMCs) isolated from septic shock patients than from healthy donors. Higher expression levels of CD177 and MMP8 proteins were also observed in the PBMCs isolated from septic shock patients than from control participants.

Conclusions

CD177, CLEC5A, CYSTM1, MCEMP1, MMP8, and RGL4 were identified as hub genes, which were of considerable value in the early diagnosis of septic shock patients. These preliminary findings are of great significance for studying immune cell infiltration in the pathogenesis of septic shock, which should be further validated in clinical studies and basic studies.

Probable Treatment Targets for Diabetic Retinopathy Based on an Integrated Proteomic and Genomic Analysis

Purpose

Using previously approved medications for new indications can expedite the lengthy and expensive drug development process. We describe a bioinformatics pipeline that integrates genomics and proteomics platforms to identify already-approved drugs that might be useful to treat diabetic retinopathy (DR).

Methods

Proteomics analysis of vitreous humor samples from 12 patients undergoing pars plana vitrectomy for DR and a whole genome dataset (UKBiobank TOPMed-imputed) from 1330 individuals with DR and 395,155 controls were analyzed independently to identify biological pathways associated with DR. Common biological pathways shared between both datasets were further analyzed (STRING and REACTOME analyses) to identify target proteins for probable drug modulation. Curated target proteins were subsequently analyzed by the BindingDB database to identify chemical compounds they interact with. Identified chemical compounds were further curated through the Expasy SwissSimilarity database for already-approved drugs that interact with target proteins.

Results

The pathways in each dataset (proteomics and genomics) converged in the upregulation of a previously unknown pathway involved in DR (RUNX2 signaling; constituents MMP-13 and LGALS3), with an emphasis on its role in angiogenesis and blood-retina barrier. Bioinformatics analysis identified U.S. Food and Drug Administration (FDA)-approved medications (raltitrexed, pemetrexed, glyburide, probenecid, clindamycin hydrochloride, and ticagrelor) that, in theory, may modulate this pathway.

Conclusions

The bioinformatics pipeline described here identifies FDA-approved drugs that can be used for new alternative indications. These theoretical candidate drugs should be validated with experimental studies.

Translational Relevance

Our study suggests possible drugs for DR treatment based on an integrated proteomics and genomics pipeline. This approach can potentially expedite the drug discovery process by identifying already-approved drugs that might be used for new indications.

Verification of genetic differences and immune cell infiltration subtypes in the neuroblastoma tumour microenvironment during immunotherapy

Background

Improved understanding of the tumour microenvironment (TME) has enabled remarkable advancements in research on cancer progression in the past few years. It is crucial to understand the nature and function of the TME because precise treatment strategies, including immunotherapy, for managing specific cancers have received widespread attention. The immune infiltrative profiles of neuroblastoma (NB) have not yet been completely illustrated. The purpose of this research was to analyse tumour immune cell infiltration (ICI) in the microenvironment of NB.

Methods

We applied the CIBERSORT and ESTIMATE algorithms to evaluate the ICI status of 438 NB samples. Three ICI models were selected, and ICI scores were acquired. Subgroups with high ICI scores determined based on the presence of immune activation signalling pathways had better overall survival.

Results

Genes involved in the immunosuppressive heparan sulphate glycosaminoglycan biosynthesis signalling pathway were markedly enriched in the low ICI score subgroup. It was inferred that patients with high ICI NB subtypes were more likely to respond to immunotherapy and have a better prognosis than those of patients with low ICI NB subtypes.

Conclusion

Notably, our ICI data not only provide a new clinical and theoretical basis for mining NB prognostic markers related to the microenvironment but also offer new ideas for the development of NB precision immunotherapy methods.

Integrated bioinformatic analysis of key biomarkers and signalling pathways in psoriasis

BACKGROUND AND AIMS

Psoriasis is a relatively common autoimmune inflammatory skin disease with a chronic etiology. Since psoriasis is still incurable, it is necessary to identify the molecular mechanisms of psoriasis. The present study was designed to detect novel biomarkers and pathways associated with psoriasis incidence, and provide new insights into treatment of psoriasis.

METHODS AND RESULTS

Differentially expressed genes (DEGs) associated with psoriasis in the Gene Expression Omnibus (GEO) database were identified, and their functional roles and interactions were then annotated and evaluated through GO, KEGG, and gene set variation (GSVA) analyses. In total 197 psoriasis-related DEGs were identified and found to primarily be associated with the NOD-like receptor, IL-17, and cytokine-cytokine receptor interaction signalling pathways. GSVA revealed significant differences between normal and lesional groups (P < 0.05), while PPI network analyses identified CXCL10 as the hub gene with the highest degree value, whereas IRF7, IFIT3, OAS1, GBP1, and ISG15 were promising candidate genes for the therapeutic treatment of psoriasis.

CONCLUSION

The findings of the present integrated bioinformatics may enhance our understanding of the molecular events occurring in psoriasis, and these candidate genes and pathways together may prove to be therapeutic targets for psoriasis.

Identification of novel key molecular signatures in the pathogenesis of experimental diabetic retinopathy

Deep mining of the molecular mechanisms underlying diabetic retinopathy (DR) is critical for the development of novel therapeutic targets. This study aimed to identify key molecular signatures involved in experimental DR on the basis of integrated bioinformatics analysis. Four datasets consisting of 37 retinal samples were downloaded from the National Center of Biotechnology Information Gene Expression Omnibus. After batch-effect adjustment, bioinformatics tools such as Networkanalyst, Enrichr, STRING, and Metascape were used to evaluate the differentially expressed genes (DEGs), perform enrichment analysis, and construct protein-protein interaction networks. The hub genes were identified using Cytoscape software. The DEGs of interest from the meta-analysis were confirmed by quantitative reverse transcription-polymerase chain reaction in diabetic rats and a high-glucose-treated retinal cell model, respectively. A total of 743 DEGs related to lens differentiation, insulin resistance, and high-density lipoprotein (HDL) cholesterol metabolism were obtained using the meta-analysis. Alterations of dynamic gene expression in the chloride ion channel, retinol metabolism, and fatty acid metabolism were involved in the course of DR in rats. Importantly, H3K27m3 modifications regulated the expression of most DEGs at the early stage of DR. Using an integrated bioinformatics approach, novel molecular signatures were obtained for different stages of DR progression, and the findings may represent distinct therapeutic strategies for DR patients.

Bioinformatics analysis reveals the landscape of immune cell infiltration and immune-related pathways participating in the progression of carotid atherosclerotic plaques

Atherosclerosis is a systemic disease associated with inflammatory cell infiltration and activation of immune-related pathways. In our study, we aimed to uncover immune-related changes and explore novel immunological features in the development of carotid atherosclerotic plaques. First, we applied integrated bioinformatics methods, including CIBERSORT and gene set enrichment analysis (GSEA). The gene expression matrices GSE28829, GSE41571, and GSE43292 were obtained from the Gene Expression Omnibus (GEO) dataset. After a series of data pre-processing steps, the resulting combined expression matrices were analysed using the CIBERSORT, GSEA, and Cluster Profiler packages. After the comparison and analysis between the carotid atherosclerotic plaques in the early and advanced stages, we discovered that there is a higher percentage of activated memory CD4 T cells and a lower percentage of resting memory CD4 cells in advanced-stage plaques. Moreover, activation of memory CD4 T cells can promote the development of carotid atherosclerotic plaques. Additionally, FOXP3⁺ Treg cell maturation can also participate in the progression of carotid plaques.

Photoreceptor cells and RPE contribute to the development of diabetic retinopathy

Diabetic retinopathy (DR) is a leading cause of blindness. It has long been regarded as vascular disease, but work in the past years has shown abnormalities also in the neural retina. Unfortunately, research on the vascular and neural abnormalities have remained largely separate, instead of being integrated into a comprehensive view of DR that includes both the neural and vascular components. Recent evidence suggests that the most predominant neural cell in the retina (photoreceptors) and the adjacent retinal pigment epithelium (RPE) play an important role in the development of vascular lesions characteristic of DR. This review summarizes evidence that the outer retina is altered in diabetes, and that photoreceptors and RPE contribute to retinal vascular alterations in the early stages of the retinopathy. The possible molecular mechanisms by which cells of the outer retina might contribute to retinal vascular damage in diabetes also are discussed. Diabetes-induced alterations in the outer retina represent a novel therapeutic target to inhibit DR.

Therapeutic Potential of Tpl2 (Tumor Progression Locus 2) Inhibition on Diabetic Vasculopathy Through the Blockage of the Inflammasome Complex

OBJECTIVE

Diabetic retinopathy, one of retinal vasculopathy, is characterized by retinal inflammation, vascular leakage, blood-retinal barrier breakdown, and neovascularization. However, the molecular mechanisms that contribute to diabetic retinopathy progression remain unclear. Approach and Results: Tpl2 (tumor progression locus 2) is a protein kinase implicated in inflammation and pathological vascular angiogenesis. Nε-carboxymethyllysine (CML) and inflammatory cytokines levels in human sera and in several diabetic murine models were detected by ELISA, whereas liquid chromatography-tandem mass spectrometry analysis was used for whole eye tissues. The CML and p-Tpl2 expressions on the human retinal pigment epithelium (RPE) cells were determined by immunofluorescence. Intravitreal injection of pharmacological inhibitor or NA (neutralizing antibody) was used in a diabetic rat model. Retinal leukostasis, optical coherence tomography, and H&E staining were used to observe pathological features. Sera of diabetic retinopathy patients had significantly increased CML levels that positively correlated with diabetic retinopathy severity and foveal thickness. CML and p-Tpl2 expressions also significantly increased in the RPE of both T1DM and T2DM diabetes animal models. Mechanistic studies on RPE revealed that CML-induced Tpl2 activation and NADPH oxidase, and inflammasome complex activation were all effectively attenuated by Tpl2 inhibition. Tpl2 inhibition by NA also effectively reduced inflammatory/angiogenic factors, retinal leukostasis in streptozotocin-induced diabetic rats, and RPE secretion of inflammatory cytokines. The attenuated release of angiogenic factors led to inhibited vascular abnormalities in the diabetic animal model.

CONCLUSIONS

The inhibition of Tpl2 can block the inflammasome signaling pathway in RPE and has potential clinical and therapeutic implications in diabetes-associated retinal microvascular dysfunction.

Identification of candidate biomarkers and pathways associated with psoriasis using bioinformatics analysis

Background

The aim of this study was to identify the candidate biomarkers and pathways associated with psoriasis. GSE13355 and GSE14905 were extracted from the Gene Expression Omnibus (GEO) database. Then the differentially expressed genes (DEGs) with |logFC| > 2 and adjusted P < 0.05 were chosen. In addition, the Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses for DEGs were performed. Then, the GO terms with P < 0.05 and overlap coefficient greater than 0.5 were integrated by EnrichmentMap. Additionally, risk subpathways analysis for DEGs was also conducted by using the iSubpathwayMiner package to obtain more psoriasis-related DEGs and pathways. Finally, protein-protein interaction (PPI) network analysis was performed to identify the hub genes, and the DGIdb database was utilized to search for the candidate drugs for psoriasis.

Results

A total of 127 DEGs which were mostly associated with keratinization, keratinocyte differentiation, and epidermal cell differentiation biological processes were identified. Based on these GO terms, 3 modules (human skin, epidermis and cuticle differentiation, and enzyme activity) were constructed. Moreover, 9 risk subpathways such as steroid hormone biosynthesis, folate biosynthesis, and pyrimidine metabolism were screened. Finally, PPI network analysis demonstrated that CXCL10 was the hub gene with the highest degree, and CXCR2, CXCL10, IVL, OASL, and ISG15 were the potential gene targets of the drugs for treating psoriasis.

Conclusion

Psoriasis may be mostly caused by keratinization, keratinocyte differentiation, and epidermal cell differentiation; the pathogeneses were more related with pathways such as steroid hormone biosynthesis, folate biosynthesis, and pyrimidine metabolism. Besides, some psoriasis-related genes such as SPRR genes, HSD11B1, GGH, CXCR2, IVL, OASL, ISG15, and CXCL10 may be important targets in psoriatic therapy.

Immune signature of T follicular helper cells predicts clinical prognostic and therapeutic impact in lung squamous cell carcinoma

Lung cancer is the leading reason of cancer-related death from cancer globally for both men and women. Recently, tumor immune heterogeneity has been implicated in cancer clinical outcome. However, this prognostic significance of immune cell types in lung squamous cell carcinoma (LUSC) is unclear and should be systematically investigated. Two microarray datasets (GSE67061 and GSE2088) from the Gene Expression Omnibus (GEO) database were downloaded and then integrated to estimate the fraction of 22 immune cell types by CIBERSORT algorithm. To validate the estimation for LUSC, the data of LUSC TCGA were also assessed in order to determine specific infiltrating immune cell type closely correlated with LUSC patients' survival determined by Cox regression analyses. Immunotherapeutic and chemotherapeutic response between the LUSC patients were also evaluated. T follicular helper cells were obtained by Cox regression analysis to develop the prognostic signature. According to this immune prognostic risk score, immune signature of T follicular helper cells is an independent and specific prognostic signature for predictions of LUSC patient overall survival. Moreover, high-risk group exhibited less expression of N6-methyladenosine (m⁶A) RNA methylation regulator including ALKBH5, METTL3, HNRNPC and KIAA1429 and was much more sensitive to immunotherapy and chemotherapy. This study suggests that this immune signature is important determinants of prognosis in LUSC and may provide potential prognostic biomarker or therapeutic target for immunotherapeutic and chemotherapeutic development.

Identification for Exploring Underlying Pathogenesis and Therapy Strategy of Oral Squamous Cell Carcinoma by Bioinformatics Analysis

BACKGROUND Oral squamous cell carcinoma (OSCC), one of the most common cavity-associated cancers, has a high incidence and worldwide mortality. However, the cause and underlying molecular mechanisms of OSCC remain unclear. MATERIAL AND METHODS Three microarray datasets (GSE23558, GSE34105, and GSE74530) from the Gene Expression Omnibus (GEO) database were downloaded and then integrated to gain differentially expressed genes (DEGs). We performed Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments of DEGs in order to elucidate DEGs' biological roles. Protein-protein interaction (PPI) networks were established in order to identify hub genes. To validate the gene markers for OSCC, the data of TCGA OSCC were also assessed. RESULTS Together, 651 DEGs containing 288 upregulated genes and 363 downregulated genes were screened out, which could completely distinguish between OSCC and normal control tissues by principal component analysis (PCA). The GO analysis indicated the DEGs were enriched in chemokine activity in the biological process group. The molecular functions of DEGs included growth factor activity. The molecular functions included oxidoreductase activity. The main DEG-associated cellular components included extracellular exosome. The KEGG pathway analysis indicated the DEGs were mainly participated in the cytokine-cytokine receptor interaction, metabolism of xenobiotics by cytochrome P450 and glutathione metabolism signal pathway. The co-expression network identified core genes from the PPI network. Additionally, Kaplan-Meier survival analysis showed that CSF2 and EGF genes were significantly correlated with OSCC patients' overall survival. CONCLUSIONS Our study using an integrated bioinformatics analysis might provide valuable information for exploring potential new molecular biomarkers and therapeutic targets for OSCC.

Transcriptomic analysis of immune response to bacterial lipopolysaccharide in zebra finch (Taeniopygia guttata)

BACKGROUND

Despite the convergence of rapid technological advances in genomics and the maturing field of ecoimmunology, our understanding of the genes that regulate immunity in wild populations is still nascent. Previous work to assess immune function has relied upon relatively crude measures of immunocompetence. However, with next-generation RNA-sequencing, it is now possible to create a profile of gene expression in response to an immune challenge. In this study, captive zebra finch (Taeniopygia guttata; adult males) were challenged with bacterial lipopolysaccharide (LPS) or vehicle to stimulate the innate immune system. 2 hours after injection, birds were euthanized and hypothalami, spleen, and red blood cells (RBCs) were collected. Taking advantage of the fully sequenced genome of zebra finch, total RNA was isolated, sequenced, and partially annotated in these tissue/cells.

RESULTS

In hypothalamus, there were 707 significantly upregulated transcripts, as well as 564 and 144 in the spleen and RBCs, respectively, relative to controls. Also, 155 transcripts in the hypothalamus, 606 in the spleen, and 61 in the RBCs were significantly downregulated. More specifically, a number of immunity-related transcripts (e.g., IL-1β, RSAD2, SOCS3) were upregulated among tissues/cells. Additionally, transcripts involved in metabolic processes (APOD, LRAT, RBP4) were downregulated.

CONCLUSIONS

These results suggest a potential trade-off in expression of genes that regulate immunity and metabolism in birds challenged with LPS. This finding is consistent with a hypothermic response to LPS treatment in small birds. Unlike mammals, birds have nucleated RBCs, and these results support a novel transcriptomic response of avian RBCs to immune challenge.

New Lipid Mediators in Retinal Angiogenesis and Retinopathy

Retinal diseases associated with vascular destabilization and the inappropriate proliferation of retinal endothelial cells have major consequences on the retinal vascular network. In extreme cases, the development of hypoxia, the upregulation of growth factors, and the hyper-proliferation of unstable capillaries can result in bleeding and vision loss. While anti-vascular endothelial growth factor therapy and laser retinal photocoagulation can be used to treat the symptoms of late stage disease, there is currently no treatment available that can prevent disease progression. Cytochrome P450 enzymes metabolize endogenous substrates (polyunsaturated fatty acids) to bioactive fatty acid epoxides that demonstrate biological activity with generally protective/anti-inflammatory and insulin-sensitizing effects. These epoxides are further metabolized by the soluble epoxide hydrolase (sEH) to fatty acid diols, high concentrations of which have vascular destabilizing effects. Recent studies have identified increased sEH expression and activity and the subsequent generation of the docosahexaenoic acid-derived diol; 19,20-dihydroxydocosapentaenoic acid, as playing a major role in the development of diabetic retinopathy. This review summarizes current understanding of the roles of cytochrome P450 enzyme and sEH–derived PUFA mediators in retinal disease.

Transcriptome analysis reveals the mechanism of the effect of flower tea Coreopsis tinctoria on hepatic insulin resistance

Non-Camellia tea and herbal medicine help prevent the development of diabetes and other metabolic diseases. Previous studies revealed that Coreopsis tinctoria (CT) flower tea increases insulin sensitivity and, in some high-fat diet (HFD)-fed rats, even prevents hepatic metabolic disorders. However, the molecular mechanisms by which CT improves insulin resistance are not known. In this study, six-week-old rats were fed a normal diet (ND), an HFD or an HFD supplemented with CT for 8 weeks. Serum samples were collected, and the livers were extracted for RNA-seq gene expression analysis. Real-time PCR and western blotting further verified the RNA-seq results. In our results, dietary CT ameliorated HFD-induced hepatosteatosis, glucose intolerance, and insulin resistance. In the HFD group, 1667 differentially expressed genes (DEGs) were identified compared with the ND group. In the CT group, 327 DEGs were identified compared with the HFD group. Some of these DEGs were related to insulin signalling, hepatic lipogenesis and glucose homeostasis. This study suggested that insulin resistance with hyperinsulinaemia, and not insulin insufficiency, is an early problem in HFD-fed rats, and CT downregulates insulin secretion genes (e.g., Rasd1, Stxbp1 and Sfxn1). Hepatic gene and protein expression analyses indicated that the regulatory effects of CT on glucose and lipid homeostasis are likely mediated via the Akt/FoxO1 signalling pathway and are regulated by the transcription factors hairy and enhancer of split 1 (HES1) and small heterodimer partner (SHP). Our study provides transcriptomic evidence of the complex pathogenic mechanism involved in hepatic insulin resistance and proves that supplementation with CT improves insulin resistance at a global scale.

Analysis of the miRNA and mRNA involved in osteogenesis of adipose-derived mesenchymal stem cells

Mesenchymal stem cells (MSCs) are bone marrow stromal cells capable of differentiating into different tissue types. Osteoblastic differentiation is a complex process that is critical for bone formation. An increasing number of studies have suggested that microRNAs (miRNAs) may serve important roles in various biological processes, including osteogenesis of MSCs. However, less is known about the participation of particular miRNAs in the osteogenic differentiation of adipose-derived stem cells (ADSCs). In order to identify functional miRNAs and the key genes involved in the osteogenesis of MSCs, the present study reconstructed a global network using data from the National Center for Biotechnology Information Gene Expression Omnibus. Meanwhile, gene ontology and pathway analysis were performed using the Cytoscape plug-in BinGO and the Database for Annotation, Visualization, and Integration Discovery, respectively. An miRNA-mRNA network composed of 72 mRNA and nine miRNA nodes advised by bioinformatics analysis was constructed. These mRNAs and miRNAs were predicted to be involved in the regulation of osteogenic differentiation of ADSCs according to the gene microarray. In the present study, six miRNAs (miR-143-3p, miR-135a-5p, miR-31-5p, miR-22-3p, miR-193b-3p and let-7i-5p) were observed to be highly associated with the osteogenesis of ADSCs, and dihydropyrimidinase like 3 was identified as a novel regulator in this process. These results provide support for further investigations into the management of bone regeneration-associated diseases.

Integrated bioinformatic changes and analysis of retina with time in diabetic rats

Diabetic retinopathy (DR) is the most common chronic complication of diabetes. It can cause impaired vision and even blindness. However, the pathological mechanism of DR is still unknown. In the present study, we use bioinformatic analysis to reveal the pathological changes of early DR in a streptozotocin (STZ) induced diabetes rat model. The dataset GSE28831 was downloaded from the Gene Expression Omnibus (GEO) database. To clarify the pathological mechanism of early DR, genes which were up-regulated (UP group) or down-regulated (DOWN group) over time were identified. One hundred eighty six genes in the UP group and 85 genes in the DOWN group were defined. There were in total 28 Gene ontology (GO) terms with a P value lower than 0.05 in UP group, including astrocyte development, neutrophil chemotaxis, neutrophil aggregation, mesenchymal cell proliferation and so on. In the DOWN group, there were totally 14 GO terms with a P value lower than 0.05, including visual perception, lens development in camera-type eye, camera-type eye development, bicellular tight junction and so on. Signaling pathways were analyzed with all genes in the UP and DOWN groups, and leukocyte transendothelial migration and tight junction were selected. Protein–protein interaction (PPI) network was constructed and six hub genes Diras3, Actn1, Tssk6, Cnot6l, Tek and Fgf4 were selected with connection degree ≥5. S100a8, S100a9 and Tek may be potential targets for DR diagnosis and treatment. This study provides the basis for the diagnosis and treatment of DR in the future.