Evaluation of the Systemic Inflammation in Patients with Pterygium

Belviranlı, Selman; Oltulu, Refik; Gündoğan, Ali Osman; Mirza, Enver; Okka, Mehmet

doi:10.4103/meajo.meajo_75_21

Cited by 3 publications

(1 citation statement)

References 28 publications

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“…Pterygium is a fibrovascular degenerations of the conjunctiva that extends into the corneal limbus [ 1 ]. It can cause significant damage to visual function, triggering irritation [ 2 ], inflammation [ 3 ] and astigmatism [ 4 ]. Currently, there is no effective drug or conservative treatment for advanced pterygium, and surgery remains the best treatment option.…”

Section: Introductionmentioning

confidence: 99%

Resveratrol inhibits TGF-β1–induced fibrotic effects in human pterygium fibroblasts

Fan,

Wei,

Zhang

et al. 2023

Environ Health Prev Med

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Background Resveratrol is a polyphenolic phytoalexin which has the properties of anti-oxidant, anti-inflammatory and anti-fibrotic effects. The aim of this study was to investigate the anti-fibrotic effects of resveratrol in primary human pterygium fibroblasts (HPFs) and elucidate the underlying mechanisms. Method Profibrotic activation was induced by transforming growth factor-beta1 (TGF-β1). The expression of profibrotic markers, including type 1 collagen (COL1), α-smooth muscle actin (α-SMA), and fibronectin, were detected by western blot and quantitative real-time-PCR after treatment with various concentrations of resveratrol in HPFs to investigate the anti-fibrotic effects. Relative signaling pathways downstream of TGF-β1 were detected by Western blot to assess the underlying mechanism. Cell viability and apoptosis were assessed using CCK-8 assay and flow cytometry to evaluate proliferation and drug-induced cytotoxicity. Cell migration and contractile phenotype were detected through wound healing assay and collagen gel contraction assay. Results The expression of α-SMA, FN and COL1 induced by TGF-β1 were suppressed by treatment with resveratrol in dose-dependent manner. The Smad3, mitogen-activated protein kinase (p38 MAPK) and phosphatidylinositol-3-kinase (PI3K) / protein kinase B (AKT) pathways were activated by TGF-β1, while resveratrol attenuated those pathways. Resveratrol also inhibited cellular proliferation, migration and contractile phenotype, and induced apoptosis in HPFs. Conclusions Resveratrol inhibit TGF-β1-induced myofibroblast activation and extra cellular matrix synthesis in HPFs, at least partly, by regulating the TGF-β/Smad3, p38 MAPK and PI3K/AKT pathways.

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Section: Introductionmentioning

confidence: 99%

Resveratrol inhibits TGF-β1–induced fibrotic effects in human pterygium fibroblasts

Fan,

Wei,

Zhang

et al. 2023

Environ Health Prev Med

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Monocyte-to-high-density lipoprotein ratio and systemic immune-inflammation index: Potential parameters for the evaluation of disease activity and severity in Graves’ ophthalmopathy?

Yılmaz Tuğan,

Ergen,

Özkan

2024

Int Ophthalmol

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The potential of high-order features of routine blood test in predicting the prognosis of non-small cell lung cancer

Tan

Zhao

et al. 2023

BMC Cancer

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Background Numerous studies have demonstrated that the high-order features (HOFs) of blood test data can be used to predict the prognosis of patients with different types of cancer. Although the majority of blood HOFs can be divided into inflammatory or nutritional markers, there are still numerous that have not been classified correctly, with the same feature being named differently. It is an urgent need to reclassify the blood HOFs and comprehensively assess their potential for cancer prognosis. Methods Initially, a review of existing literature was conducted to identify the high-order features (HOFs) and classify them based on their calculation method. Subsequently, a cohort of patients diagnosed with non-small cell lung cancer (NSCLC) was established, and their clinical information prior to treatment was collected, including low-order features (LOFs) obtained from routine blood tests. The HOFs were then computed and their associations with clinical features were examined. Using the LOF and HOF data sets, a deep learning algorithm called DeepSurv was utilized to predict the prognostic risk values. The effectiveness of each data set’s prediction was evaluated using the decision curve analysis (DCA). Finally, a prognostic model in the form of a nomogram was developed, and its accuracy was assessed using the calibration curve. Results From 1210 documents, over 160 blood HOFs were obtained, arranged into 110, and divided into three distinct categories: 76 proportional features, 6 composition features, and 28 scoring features. Correlation analysis did not reveal a strong association between blood features and clinical features; however, the risk value predicted by the DeepSurv LOF- and HOF-models is significantly linked to the stage. Results from DCA showed that the HOF model was superior to the LOF model in terms of prediction, and that the risk value predicted by the blood data model could be employed as a complementary factor to enhance the prognosis of patients. A nomograph was created with a C-index value of 0.74, which is capable of providing a reasonably accurate prediction of 1-year and 3-year overall survival for patients. Conclusions This research initially explored the categorization and nomenclature of blood HOF, and proved its potential in lung cancer prognosis.

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Evaluation of the Systemic Inflammation in Patients with Pterygium

Cited by 3 publications

References 28 publications

Resveratrol inhibits TGF-β1–induced fibrotic effects in human pterygium fibroblasts

Resveratrol inhibits TGF-β1–induced fibrotic effects in human pterygium fibroblasts

Monocyte-to-high-density lipoprotein ratio and systemic immune-inflammation index: Potential parameters for the evaluation of disease activity and severity in Graves’ ophthalmopathy?

The potential of high-order features of routine blood test in predicting the prognosis of non-small cell lung cancer

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