Glutamine metabolism-related genes and immunotherapy in nonspecific orbital inflammation were validated using bioinformatics and machine learning.

BACKGROUND: Nonspecific orbital inflammation (NSOI) is an idiopathic, persistent, and proliferative inflammatory condition affecting the orbit, characterized by polymorphous lymphoid infiltration. Its pathogenesis and progression have been linked to imbalances in tumor metabolic pathways, with glutamine (Gln) metabolism emerging as a critical aspect in cancer. Metabolic reprogramming is known to influence clinical outcomes in various malignancies. However, comprehensive research on glutamine metabolism's significance in NSOI is lacking. METHODS: This study conducted a bioinformatics analysis to identify and validate potential glutamine-related molecules (GlnMgs) associated with NSOI. The discovery of GlnMgs involved the intersection of differential expression analysis with a set of 42 candidate GlnMgs. The biological functions and pathways of the identified GlnMgs were analyzed using GSEA and GSVA. Lasso regression and SVM-RFE methods identified hub genes and assessed the diagnostic efficacy of fourteen GlnMgs in NSOI. The correlation between hub GlnMgs and clinical characteristics was also examined. The expression levels of the fourteen GlnMgs were validated using datasets GSE58331 and GSE105149. RESULTS: Fourteen GlnMgs related to NSOI were identified, including FTCD, CPS1, CTPS1, NAGS, DDAH2, PHGDH, GGT1, GCLM, GLUD1, ART4, AADAT, ASNSD1, SLC38A1, and GFPT2. Biological function analysis indicated their involvement in responses to extracellular stimulus, mitochondrial matrix, and lipid transport. The diagnostic performance of these GlnMgs in distinguishing NSOI showed promising results. CONCLUSIONS: This study successfully identified fourteen GlnMgs associated with NSOI, providing insights into potential novel biomarkers for NSOI and avenues for monitoring disease progression.

[Study on mechanism of icariin-induced ferroptosis in HepG2 hepatoma carcinoma cells through PPARG/FABP4/GPX4 pathway].

The aim of this study was to explore the mechanism of icaritin-induced ferroptosis in hepatoma HepG2 cells. By bioinformatics screening, the target of icariin's intervention in liver cancer ferroptosis was selected, the protein-protein interaction(PPI) network was constructed, the related pathways were focused, the binding ability of icariin and target protein was evaluated by molecular docking, and the impact on patients' survival prognosis was predicted and the clinical prediction model was built. CCK-8, EdU, and clonal formation assays were used to detect cell viability and cell proliferation; colorimetric method and BODIPY 581/591 C1 fluorescent probe were used to detect the levels of Fe~(2+), MDA and GSH in cells, and the ability of icariin to induce HCC cell ferroptosis was evaluated; RT-qPCR and Western blot detection were used to verify the mRNA and protein levels of GPX4, xCT, PPARG, and FABP4 to determine the expression changes of these ferroptosis-related genes in response to icariin. Six intervention targets(AR, AURKA, PPARG, AKR1C3, ALB, NQO1) identified through bioinformatic analysis were used to establish a risk scoring system that aids in estimating the survival prognosis of HCC patients. In conjunction with patient age and TNM staging, a comprehensive Nomogram clinical prediction model was developed to forecast the 1-, 3-, and 5-year survival of HCC patients. Experimental results revealed that icariin effectively inhibited the activity and proliferation of HCC cells HepG2, significantly modulating levels of Fe~(2+), MDA, and lipid peroxidation ROS while reducing GSH levels, hence revealing its potential to induce ferroptosis in HCC cells. Icariin was found to diminish the expression of GPX4 and xCT(P<0.01), inducing ferroptosis in HCC cells, potentially in relation to inhibition of PPARG and FABP4(P<0.01). In summary, icariin induces ferroptosis in HCC cells via the PPARG/FABP4/GPX4 pathway, providing an experimental foundation for utilizing the traditional Chinese medicine icariin in the prevention or treatment of HCC.

[Experimental study on treatment of retinitis pigmentosa by inducing Müller cell reprogramming with Lycii Fructus and Salviae Miltiorrhizae Radix et Rhizoma].

This study aims to explore the effect of Lycii Fructus and Salviae Miltiorrhizae Radix et Rhizoma(LFSMR), a drug pair possesses the function of nourishing Yin, promoting blood circulation, and brightening the eyes, in treating retinitis pigmentosa(RP)by inhibiting the gliosis of Müller cells(MCs) and inducing their reprogramming and differentiation into various types of retinal nerve cells. Twelve C57 mice were used as the normal control group, and 48 transgenic RP(rd10) mice were randomly divided into the model group, positive control group, and low and high dose LFSMR groups, with 12 mice in each group. HE staining was used to detect pathological changes in the retina, and an electroretinogram was used to detect retinal function. Retinal optical coherence tomography was used to detect retinal thickness and perform fundus photography, and laser speckle perfusion imaging was used to detect local retinal blood flow. Digital PCR was used to detect gene expression related to retinal nerve cells, and immunofluorescence was used to detect protein expression related to retinal nerve cells. LFSMR could significantly improve the pathological changes, increase the amplitude of a and b waves, increase the retinal thickness, restore retinal damage, and increase retinal blood flow in mice with RP lesions. LFSMR could also significantly inhibit the m RNA expression of the glial fibrillary acidic protein( GFAP) during the pathogenesis of RP and upregulate m RNA expression of sex determining region Y box protein 2(SOX2), paired box protein 6(Pax6),rhodopsin, protein kinase C-α(PKCα), syntaxin, and thymic cell antigen 1. 1(Thy1. 1). LFSMR could significantly inhibit GFAP protein expression and enhance protein expression of SOX2, Pax6, rhodopsin, PKCα, syntaxin, and Thy1. 1. It could also reverse the pathological changes in the retina of rd10 mice, improve retinal function and fundus performance, increase retinal thickness, enhance local retinal blood flow, and exert therapeutic effects on RP. The mechanism of action of LFSMR may be related to inhibiting the gliosis of MCs and promoting their reprogramming and differentiation into various types of retinal nerve cells.

Astragaloside IV ameliorates peritoneal fibrosis by promoting PGC-1α to reduce apoptosis in vitro and in vivo.

Prolonged exposure of the peritoneum to high glucose dialysate leads to the development of peritoneal fibrosis (PF), and apoptosis of peritoneal mesothelial cells (PMCs) is a major cause of PF. The aim of this study is to investigate whether Astragaloside IV could protect PMCs from apoptosis and alleviate PF. PMCs and rats PF models were induced by high glucose peritoneal fluid. We examined the pathology of rat peritoneal tissue by HE staining, the thickness of rat peritoneal tissue by Masson's staining, the number of mitochondria and oxidative stress levels in peritoneal tissue by JC-1 and DHE fluorescence staining, and mitochondria-related proteins and apoptosis-related proteins such as PGC-1α, NRF1, TFAM, Caspase3, Bcl2 smad2 were measured. We used hoechst staining and flow cytometry to assess the apoptotic rate of PMCs in the PF model, and further validated the observed changes in the expressions of PGC-1α, NRF1, TFAM, Caspase3, Bcl2 smad2 in PMCs. We further incubated PMCs with MG-132 (proteasome inhibitor) and Cyclohexylamine (protein synthesis inhibitor). The results demonstrated that Astragaloside IV increased the expression of PGC-1α by reducing the ubiquitination of PGC-1α. It was further found that the protective effects of Astragaloside IV on PMCs were blocked when PGC-1α was inhibited. In conclusion, Astragaloside IV effectively alleviated PF both in vitro and in vivo, possibly by promoting PGC-1α to enhance mitochondrial synthesis to reduce apoptotic effects.

Mitochondrial dysfunction: a new molecular mechanism of intervertebral disc degeneration.

OBJECTIVE: Intervertebral disc degeneration (IVDD) is a chronic degenerative orthopedic illness that causes lower back pain as a typical clinical symptom, severely reducing patients' quality of life and work efficiency, and imposing a significant economic burden on society. IVDD is defined by rapid extracellular matrix breakdown, nucleus pulposus cell loss, and an inflammatory response. It is intimately related to the malfunction or loss of myeloid cells among them. Many mechanisms have been implicated in the development of IVDD, including inflammatory factors, oxidative stress, apoptosis, cellular autophagy, and mitochondrial dysfunction. In recent years, mitochondrial dysfunction has become a hot research topic in age-related diseases. As the main source of adenosine triphosphate (ATP) in myeloid cells, mitochondria are essential for maintaining myeloid cell survival and physiological functions. METHODS: We searched the PUBMED database with the search term "intervertebral disc degeneration and mitochondrial dysfunction" and obtained 82 articles, and after reading the abstracts and eliminating 30 irrelevant articles, we finally obtained 52 usable articles. RESULTS: Through a review of the literature, it was discovered that IVDD and cellular mitochondrial dysfunction are also linked. Mitochondrial dysfunction contributes to the advancement of IVDD by influencing a number of pathophysiologic processes such as mitochondrial fission/fusion, mitochondrial autophagy, cellular senescence, and cell death. CONCLUSION: We examine the molecular mechanisms of IVDD-associated mitochondrial dysfunction and present novel directions for quality management of mitochondrial dysfunction as a treatment approach to IVDD.

Apigenin inhibits angiogenesis in retinal microvascular endothelial cells through regulating of the miR-140-5p/HDAC3-mediated PTEN/PI3K/AKT pathway.

BACKGROUND: Diabetic retinopathy (DR) is a common cause of visual impairment. Apigenin has been shown to have antiangiogenic effects in various diseases. Our study aimed to investigate the role of apigenin in DR and elucidate the underlying mechanism. METHODS: Human retinal microvascular endothelial cells (HRMECs) were exposed to high glucose (HG) to establish a DR model. HRMECs were treated with apigenin. Then we knocked down or overexpressed miR-140-5p and HDAC3, and added PI3K/AKT inhibitor LY294002. The expression levels of miR-140-5p, HDAC3, and PTEN were measured using qRT-PCR. Western blot analysis was performed to assess the expression of HDAC3, PTEN, and PI3K/AKT pathway-related proteins. Finally, cell proliferation and migration were evaluated using MTT, wound-healing assay, and transwell assay, while angiogenesis was examined using the tube formation assay. RESULTS: HG treatment resulted in reduced miR-140-5p expression and overexpression of miR-140-5p suppressed proliferation, migration, and angiogenesis of the HG-induced HRMECs. Apigenin treatment significantly restored the decreased level of miR-140-5p caused by HG treatment and inhibited proliferation, migration, and angiogenesis of the HG-induced HRMECs by upregulating miR-140-5p. Moreover, miR-140-5p targeted HDAC3, and overexpression of miR-140-5p reversed the HG-inducted upregulation of HDAC3 expression. HDAC3 was found to bind to the promoter region of PTEN, inhibiting its expression. Knockdown of HDAC3 suppressed the PI3K/AKT pathway by elevating PTEN expression. Furthermore, apigenin inhibited angiogenesis in DR cell models through the regulating of the miR-140-5p/HDAC3-mediated PTEN/PI3K/AKT pathway. CONCLUSIONS: Apigenin effectively suppressed angiogenesis in HG-induced HRMECs by modulating the miR-140-5p/HDAC3-mediated PTEN/PI3K/AKT pathway. Our study may contribute to the development of novel therapeutic approaches and identification of potential targets for the treatment of DR.

In Silico Identification of Natural Product-Based Inhibitors Targeting IL-1ß/IL-1R Protein-Protein Interface.

IL-1ß mediates inflammation and regulates immune responses, cell proliferation, and differentiation. Dysregulation of IL-1ß is linked to inflammatory and autoimmune diseases. Elevated IL-1ß levels are found in patients with severe COVID-19, indicating its excessive production may worsen the disease. Also, dry eye disease patients show high IL-1ß levels in tears and conjunctival epithelium. Therefore, IL-1ß signaling is a potential therapeutic targeting for COVID-19 and aforementioned diseases. No small-molecule IL-1ß inhibitor is clinically approved despite efforts. Developing such inhibitors is highly desirable. Herein, a docking-based strategy was used to screen the TCM (Traditional Chinese Medicine) database to identify possible IL-1ß inhibitors with desirable pharmacological characteristics by targeting the IL-1ß/IL-1R interface. Primarily, the docking-based screening was performed by selecting the crucial residues of IL-1ß interface to retrieve the potential compounds. Afterwards, the compounds were shortlisted on the basis of binding scores and significant interactions with the crucial residues of IL-1ß. Further, to gain insights into the dynamic behavior of the protein-ligand interactions, MD simulations were performed. The analysis suggests that four selected compounds were stabilized in an IL-1ß pocket, possibly blocking the formation of an IL-1ß/IL-1R complex. This indicates their potential to interfere with the immune response, making them potential therapeutic agents to investigate further.

Astragalus polysaccharides suppresses high glucose-induced metabolic memory in retinal pigment epithelial cells through inhibiting mitochondrial dysfunction-induced apoptosis by regulating miR-195.

BACKGROUND: Metabolic memory contributes to the development of diabetic retinopathy (DR), which is the complication of diabetes. But it's still unknown how to prevent the metabolic memory to treat the DR. In our study, we want to examine the function of Astragalus polysaccharides (APS) in the metabolic memory of retinal pigment epithelium (RPE) pretreated with high glucose (HG). METHODS: ARPE-19 and PRPE cells were exposed to HG followed by normal glucose (NG) treatment with or without APS. QPCR was used to examine the levels of miR-195 and Bcl-2. MDA and SOD detection assays were used to examine the oxidative stress level. Western blotting and immunostaining were applied to detect the protein level of mitochondrial damage and apoptotic signaling pathway. Flow cytometry and TUNEL staining were used to analyze cell apoptosis. Luciferase assay was used to examine the direct target of miR-195. RESULTS: APS treatment significantly decreased the expression of miR-195, while increased the expression of Bcl-2 with optimized dosages which were induced by HG treatment, even after replacing the HG with NG. And we found Bcl-2 was the direct target of miR-195. APS alleviated the oxidative stress, mitochondrial damage and cell apoptosis induced by HG and HG + NG treatments in RPE cells via regulating miR-195. Furthermore, we found overexpression of miR-195 abolished the alleviated effects of APS on the HG-treated RPE cells. CONCLUSIONS: APS suppressed high glucose-induced metabolic memory in retinal pigment epithelial cells through inhibiting mitochondrial dysfunction-induced apoptosis by regulating miR-195.

Acidic Preconditioning Protects Against Ischemia-Reperfusion Lung Injury Via Inhibiting the Expression of Matrix Metalloproteinase 9.

BACKGROUND: Acidic preconditioning (APC) has been demonstrated to protect against ischemia-reperfusion (IR)-induced lung injury, which could occur during lung transplantation or cardiopulmonary bypass. However, the pathophysiological mechanisms underlying IR lung injury and APC protection are not completely understood. The key factors responsible for the protective effects of APC are not clear. In this study, bioinformatics was used to predict the potential key factor in IR lung injury and explore the important mediator of the APC protective effect in IR lung injury. METHODS: First, we screened GSE6730, which is related to both lung injury and IR in Gene Expression Omnibus, and STRING was used later to select the genes in GSE6730 needed in the future. Animal models were established and classified to validate the effect of matrix metalloproteinase 9 (MMP-9) on lung injury after IR by adding a selective inhibitor (4-phenoxyphenylsulfonyl) methylthiirane, MMP-9 inhibitor. Next, for better understanding of APC inhibition of the expression of MMP-9 in lung injury, assessment of lung tissues, Western blot analysis, and RNA extraction and reverse transcription quantitative polymerase chain reaction were conducted. RESULTS: MMP-9 was identified to be overexpressed after IR according to the analysis on GSE67370. MMP-9 was an unknown gene in relation to acute lung injury and found to be associated with interleukin (IL)-1B, IL-6, and IL-8. The expressions of these inflammatory factors, including MMP-9, were all elevated in IR. Furthermore, lung injury was ameliorated, and the level of MMP-9 was lower when an MMP-9 inhibitor, (4-phenoxyphenylsulfonyl) methylthiirane, was added. Compared with group IR, APC reversed the ischemia-induced lung injury, and the level of MMP-9 was lower, and the concentrations of IL-1ß, IL-6, and IL-8 were decreased. CONCLUSIONS: Our findings reveal a novel mechanism indicating that IR induces higher expression of MMP-9 in lung injury by increasing the expression of inflammation-related factors. APC might protect against IR lung injury by inhibiting the expression of MMP-9.

LncRNA-MEG3 alleviates high glucose induced inflammation and apoptosis of retina epithelial cells via regulating miR-34a/SIRT1 axis.

BACKGROUND: Diabetic retinopathy (DR) is the serious complication of diabetes, which could lead to blindness. Inflammation and apoptosis are hallmark of DR, but mechanism of their regulation is little known. LncRNA-MEG3 is associated with multiple biological processes including proliferation, apoptosis and inflammation response, and is dramatically decreased in DR. However, the role and underlying mechanism of MEG3 in DR is unclear. This study is aimed to reveal the signaling mechanisms of MEG3 in inflammation and apoptosis of DR. METHODS: ARPE-19 cells were applied for this research. MEG3 was cloned into pcDNA3.1. miR-34a was overexpressed and inhibited by transfecting with mimics and inhibitor, respectively. The expression level was detected by qRT-PCR and western blotting. The targeted regulatory relationship was analyzed by dual luciferase assay. Cytokine secretion, cell viability and apoptosis were detected by ELISA assay, MTT assay and flow cytometry analysis, respectively. RESULTS: High glucose (HG) inhibited MEG3 and SIRT1 expression and enhanced miR-34a expression. MEG3 could promote SIRT1 expression by targeting miR-34a. MEG3 overexpression and miR-34a knockdown could inhibit HG-induced apoptosis and secretion of inflammation cytokines including IL-1ß, IL-6 and TNF-α, but miR-34a overexpression alleviated such effects of MEG3. Furthermore, MEG3 overexpression also inhibited NF-κB signaling pathway and increased Bcl-2/Bax ratio via down-regulating miR-34a. CONCLUSION: MEG3 could alleviate HG-inducing apoptosis and inflammation via inhibiting NF-κB signaling pathway by targeting miR-34a/SIRT1 axis. This finding illustrated the function and mechanism of MEG3 in DR, and MEG3 might serve as potential therapeutic target for DR.

Cocaine- and amphetamine-regulated transcript peptide in the nucleus accumbens shell inhibits cocaine-induced locomotor sensitization to transient over-expression of α-Ca2+ /calmodulin-dependent protein kinase II.

Cocaine- and amphetamine-regulated transcript (CART) peptide is a widely distributed neurotransmitter that attenuates cocaine-induced locomotor activity when injected into the nucleus accumbens (NAc). Our previous work first confirmed that the inhibitory mechanism of the CART peptide on cocaine-induced locomotor activity is related to a reduction in cocaine-enhanced phosphorylated Ca2+ /calmodulin-dependent protein kinaseIIα (pCaMKIIα) and the enhancement of cocaine-induced D3R function. This study investigated whether CART peptide inhibited cocaine-induced locomotor activity via inhibition of interactions between pCaMKIIα and the D3 dopamine receptor (D3R). We demonstrated that lentivirus-mediated gene transfer transiently increased pCaMKIIα expression, which peaked at 10 days after microinjection into the rat NAc shell, and induced a significant increase in Ca2+ influx along with greater behavioral sensitivity in the open field test after intraperitoneal injections of cocaine (15 mg/kg). However, western blot analysis and coimmunoprecipitation demonstrated that CART peptide treatment in lentivirus-transfected CaMKIIα-over-expressing NAc rat tissues or cells prior to cocaine administration inhibited the cocaine-induced Ca2+ influx and attenuated the cocaine-increased pCaMKIIα expression in lentivirus-transfected CaMKIIα-over-expressing cells. CART peptide decreased the cocaine-enhanced phosphorylated cAMP response element binding protein (pCREB) expression via inhibition of the pCaMKIIα-D3R interaction, which may account for the prolonged locomotor sensitization induced by repeated cocaine treatment in lentivirus-transfected CaMKIIα-over-expressing cells. These results provide strong evidence for the inhibitory modulation of CART peptide in cocaine-induced locomotor sensitization. Cover Image for this issue: doi: 10.1111/jnc.14187.

Identification of potential diagnostic biomarkers of acute pancreatitis by serum metabolomic profiles.

Acute pancreatitis (AP) is defined as an acute inflammation of pancreas that may cause damage to other tissues and organs depending upon the severity of symptoms. The diagnosis of AP is usually made by detection of raised circulating pancreatic enzyme levels, but there are occasional false positive and false negative diagnoses and such tests are often normal in delayed presentations. More accurate biomarkers would help in such situations. In this study, the global metabolites' changes of AP patients (APP) were profiled by using gas chromatography-mass spectrometry (GC-MS). Multivariate pattern recognition techniques were used to establish the classification models to distinguish APP from healthy participants (HP). Some significant metabolites including 3-hydroxybutyric acid, phosphoric acid, glycerol, citric acid, d-galactose, d-mannose, d-glucose, hexadecanoic acid and serotonin were selected as potential biomarkers for helping clinical diagnosis of AP. Furthermore, the metabolite changes in APP with severe and mild symptoms were also analyzed. Based on the selected biomarkers, some relevant pathways were also identified. Our results suggested that GC-MS based serum metabolomics method can be used in the clinical diagnosis of AP by profiling potential biomarkers.

[Chemical constituents from hypoglycemic active part of Plantaginis Semen].

The chemical constituents of Plantaginis Semen with hypoglycemic effect was investigated in this paper. The previous results of the in vivo hypoglycemic effect showed that 60% ethanol extract of Plantaginis Semen decreased the levels of FBG and improved the glucose tolerance in high fat diet(HFD)-induced diabetic C57BL/6 mice. Then, in the present study, the above potential bioactive extract was separated and purified by silica gel, ODS, Sephadex LH-20 column chromatography, medium pressure liquid chromatography(MPLC)and preparative HPLC. The structures of isolated compounds were identified by physicochemical properties and spectral analyses. Eight compounds were obtained and identified as 4, 4a, 5, 7a-tetrahydro-7-(hydroxymethyl)cyclopenta[c]pyran-3(1H)-one(1), iridolactone(2), pedicularislacton(3), rehmaglutin C(4), geniposidic acid(5), p-hydroxylphenylglycerol(6), 1, 2-benzenediol-4-(2-hydroxyethyl)(7), and 3-buten-2-one-4-[3-(ß-D-glucopyranosyloxy)-4-hydroxyphenyl](8). Among them, compounds 1-5 were iridoids, and 6-8 were phenolic acids. Compound 1 was a new natural product, and compounds 2-4, 6 and 8 were isolated from the Plantaginaceae family for the first time.

Three New Sesquiterpenoids and One New Sesquiterpenoid Derivative from Chinese Eaglewood.

Three new sesquiterpenoids (1-3) and one new sesquiterpenoid derivative (4), along with three known sesquiterpenoids (5-7), were isolated from the 95% ethanolic extract of Chinese eaglewood [Aquilaria sinensis (Lour.) Gilg]. The structures of these compounds were elucidated through extensive analysis of spectroscopic data including IR, NMR, HRESIMS, and X-ray diffraction experiments. In addition, the above new compounds were detected for their bioactivities against LPS-induced NO production in RAW 264.7 cells. Among them, compound 2 exhibited obvious anti-inflammatory activity with an IC50 value of 8.1 µM.

The shared mechanism and potential diagnostic markers for premature ovarian failure and dry eye disease.

Premature ovarian failure (POF), which is often comorbid with dry eye disease (DED) is a key issue affecting female health. Here, we explored the mechanism underlying comorbid POF and DED to further elucidate disease mechanisms and improve treatment. Datasets related to POF (GSE39501) and DED (GSE44101) were identified from the Gene Expression Omnibus (GEO) database and subjected to weighted gene coexpression network (WGCNA) and differentially expressed genes (DEGs) analyses, respectively, with the intersection used to obtain 158 genes comorbid in POF and DED. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses of comorbid genes revealed that identified genes were primarily related to DNA replication and Cell cycle, respectively. Protein-Protein interaction (PPI) network analysis of comorbid genes obtained the 15 hub genes: CDC20, BIRC5, PLK1, TOP2A, MCM5, MCM6, MCM7, MCM2, CENPA, FOXM1, GINS1, TIPIN, MAD2L1, and CDCA3. To validate the analysis results, additional POF- and DED-related datasets (GSE48873 and GSE171043, respectively) were selected. miRNAs-lncRNAs-genes network and machine learning methods were used to further analysis comorbid genes. The DGIdb database identified valdecoxib, amorfrutin A, and kaempferitrin as potential drugs. Herein, the comorbid genes of POF and DED were identified from a bioinformatics perspective, providing a new strategy to explore the comorbidity mechanism, opening up a new direction for the diagnosis and treatment of comorbid POF and DED.

Bioinformatic validation and machine learning-based exploration of purine metabolism-related gene signatures in the context of immunotherapeutic strategies for nonspecific orbital inflammation.

Background: Nonspecific orbital inflammation (NSOI) represents a perplexing and persistent proliferative inflammatory disorder of idiopathic nature, characterized by a heterogeneous lymphoid infiltration within the orbital region. This condition, marked by the aberrant metabolic activities of its cellular constituents, starkly contrasts with the metabolic equilibrium found in healthy cells. Among the myriad pathways integral to cellular metabolism, purine metabolism emerges as a critical player, providing the building blocks for nucleic acid synthesis, such as DNA and RNA. Despite its significance, the contribution of Purine Metabolism Genes (PMGs) to the pathophysiological landscape of NSOI remains a mystery, highlighting a critical gap in our understanding of the disease's molecular underpinnings. Methods: To bridge this knowledge gap, our study embarked on an exploratory journey to identify and validate PMGs implicated in NSOI, employing a comprehensive bioinformatics strategy. By intersecting differential gene expression analyses with a curated list of 92 known PMGs, we aimed to pinpoint those with potential roles in NSOI. Advanced methodologies, including Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA), facilitated a deep dive into the biological functions and pathways associated with these PMGs. Further refinement through Lasso regression and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) enabled the identification of key hub genes and the evaluation of their diagnostic prowess for NSOI. Additionally, the relationship between these hub PMGs and relevant clinical parameters was thoroughly investigated. To corroborate our findings, we analyzed expression data from datasets GSE58331 and GSE105149, focusing on the seven PMGs identified as potentially crucial to NSOI pathology. Results: Our investigation unveiled seven PMGs (ENTPD1, POLR2K, NPR2, PDE6D, PDE6H, PDE4B, and ALLC) as intimately connected to NSOI. Functional analyses shed light on their involvement in processes such as peroxisome targeting sequence binding, seminiferous tubule development, and ciliary transition zone organization. Importantly, the diagnostic capabilities of these PMGs demonstrated promising efficacy in distinguishing NSOI from non-affected states. Conclusions: Through rigorous bioinformatics analyses, this study unveils seven PMGs as novel biomarker candidates for NSOI, elucidating their potential roles in the disease's pathogenesis. These discoveries not only enhance our understanding of NSOI at the molecular level but also pave the way for innovative approaches to monitor and study its progression, offering a beacon of hope for individuals afflicted by this enigmatic condition.

Bibliometric and visualized analysis of DME from 2012 to 2022.

BACKGROUND: Diabetic macular edema (DME) is the main cause of irreversible vision loss in patients with diabetes mellitus (DM), resulting in a certain burden to patients and society. With the increasing incidence of DME, more and more researchers are focusing on it. METHODS: The papers related to DME between 2012 and 2022 from the Web of Science core Collection were searched in this study. Based on CiteSpace and VOS viewer, these publications were analyzed in terms of spatiotemporal distribution, author distribution, subject classification, topic distribution, and citations. RESULTS: A total of 5165 publications on DME were included. The results showed that the research on DME is on a steady growth trend. The country with the highest number of published documents was the US. Wong Tien Yin from Tsinghua University was the author with the most published articles. The journal of Retina, the Journal of Retinal and Vitreous Diseases had a large number of publications. The article "Mechanisms of macular edema: Beyond the surface" was the highly cited literature and "Aflibercept, bevacizumab, or ranibizumab for diabetic macular edema" had the highest co-citation frequency. The treatment, diagnosis, pathogenesis, as well as etiology and epidemiological investigation of DME, have been the current research direction. Deep learning has been widely used in the medical field for its strong feature representation ability. CONCLUSIONS: The study revealed the important authoritative literature, journals, institutions, scholars, countries, research hotspots, and development trends in in the field of DME. This indicates that communication and cooperation between disciplines, universities, and countries are crucial. It can advance research in DME and even ophthalmology.

The roles of IRF8 in nonspecific orbital inflammation: an integrated analysis by bioinformatics and machine learning.

BACKGROUND: Nonspecific Orbital Inflammation (NSOI) represents a persistent and idiopathic proliferative inflammatory disorder, characterized by polymorphous lymphoid infiltration within the orbit. The transcription factor Interferon Regulatory Factor 8 (IRF8), integral to the IRF protein family, was initially identified as a pivotal element for the commitment and differentiation of myeloid cell lineage. Serving as a central regulator of innate immune receptor signaling, IRF8 orchestrates a myriad of functions in hematopoietic cell development. However, the intricate mechanisms underlying IRF8 production remain to be elucidated, and its potential role as a biomarker for NSOI is yet to be resolved. METHODS: IRF8 was extracted from the intersection analysis of common DEGs of GSE58331 and GSE105149 from the GEO and immune- related gene lists in the ImmPort database using The Lasso regression and SVM-RFE analysis. We performed GSEA and GSVA with gene sets coexpressed with IRF8, and observed that gene sets positively related to IRF8 were enriched in immune-related pathways. To further explore the correlation between IRF8 and immune-related biological process, the CIBERSORT algorithm and ESTIMATE method were employed to evaluate TME characteristics of each sample and confirmed that high IRF8 expression might give rise to high immune cell infiltration. Finally, the GSE58331 was utilized to confirm the levels of expression of IRF8. RESULTS: Among the 314 differentially expressed genes (DEGs), some DEGs were found to be significantly different. With LASSO and SVM-RFE algorithms, we obtained 15 hub genes. For biological function analysis in IRF8, leukocyte mediated immunity, leukocyte cell-cell adhesion, negative regulation of immune system process were emphasized. B cells naive, Macrophages M0, Macrophages M1, T cells CD4 memory activated, T cells CD4 memory resting, T cells CD4 naive, and T cells gamma delta were shown to be positively associated with IRF8. While, Mast cells resting, Monocytes, NK cells activated, Plasma cells, T cells CD8, and T cells regulatory (Tregs) were shown to be negatively linked with IRF8. The diagnostic ability of the IRF8 in differentiating NSOI exhibited a good value. CONCLUSIONS: This study discovered IRF8 that are linked to NSOI. IRF8 shed light on potential new biomarkers for NSOI and tracking its progression.

A novel approach for intelligent diagnosis and grading of diabetic retinopathy.

Diabetic retinopathy (DR) is a severe ocular complication of diabetes that can lead to vision damage and even blindness. Currently, traditional deep convolutional neural networks (CNNs) used for DR grading tasks face two primary challenges: (1) insensitivity to minority classes due to imbalanced data distribution, and (2) neglecting the relationship between the left and right eyes by utilizing the fundus image of only one eye for training without differentiating between them. To tackle these challenges, we proposed the DRGCNN (DR Grading CNN) model. To solve the problem caused by imbalanced data distribution, our model adopts a more balanced strategy by allocating an equal number of channels to feature maps representing various DR categories. Furthermore, we introduce a CAM-EfficientNetV2-M encoder dedicated to encoding input retinal fundus images for feature vector generation. The number of parameters of our encoder is 52.88 M, which is less than RegNet_y_16gf (80.57 M) and EfficientNetB7 (63.79 M), but the corresponding kappa value is higher. Additionally, in order to take advantage of the binocular relationship, we input fundus retinal images from both eyes of the patient into the network for features fusion during the training phase. We achieved a kappa value of 86.62% on the EyePACS dataset and 86.16% on the Messidor-2 dataset. Experimental results on these representative datasets for diabetic retinopathy (DR) demonstrate the exceptional performance of our DRGCNN model, establishing it as a highly competitive intelligent classification model in the field of DR. The code is available for use at https://github.com/Fat-Hai/DRGCNN.