Texture analysis of poly-adenylated mRNA staining following global brain ischemia and reperfusion

Szymanski, Jeffrey J.; Jamison, Jill T.; DeGracia, Donald J.

doi:10.1016/j.cmpb.2011.03.005

Cited by 12 publications

(5 citation statements)

References 37 publications

(58 reference statements)

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“…It is significantly negatively correlated with dendritic cells resting, mast cells resting, monocyte, T cells CD4 memory resting and B cells memory. Our study was based on drug sensitivity data from the GDSC database to further explore the risk score and sensitivity to common chemotherapeutic agents [ 30 ]. We found that risk score significantly affected the sensitivity of patients to metformin, mitomycine C and gefitinib.…”

Section: Discussionmentioning

confidence: 99%

Selective poly adenylation predicts the efficacy of immunotherapy in patients with lung adenocarcinoma by multiple omics research

Zhong

et al. 2022

Anti-Cancer Drugs

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The aim of this study was to find the application value of selective polyadenylation in immune cell infiltration, biological transcription function and risk assessment of survival and prognosis in lung adenocarcinoma (LUAD). The processed original mRNA expression data of LUAD were downloaded, and the expression profiles of 594 patient samples were collected. The (APA) events in TCGA-NA-SEQ data were evaluated by polyadenylation site use Index (PDUI) values, and the invasion of stromal cells and immune cells and tumor purity were calculated to group and select the differential genes. Lasso regression and stratified analysis were used to examine the role of risk scores in predicting patient outcomes. The study also used the GDSC database to predict the chemotherapeutic sensitivity of each tumor sample and used a regression method to obtain an IC50 estimate for each specific chemotherapeutic drug treatment. Then CIBERSORT algorithm was used to conduct Spearman correlation analysis, immune regulatory factor analysis and TIDE immune system function analysis for gene expression level and immune cell content. Finally, the Kaplan-Meier curve was used to analyze the correlation between stromal score and the immune score of LUAD. In this study, APA's LUAD risk score prognostic model was constructed. KM survival analysis showed that immune score affected the prognosis of LUAD patients (P = 0.027) but the matrix score was not statistically significant (P = 0.1). We extracted 108 genes with APA events from 827 different genes and based on PUDI clustering and heat map, the survival rate of patients in the four groups was significantly different (P = 0.05). Multiple omics studies showed that risk score was significantly positively correlated with Macrophages M0, T cells Follicular helper, B cells naive and NK cells resting. It is significantly negatively correlated with dendritic cells resting, mast cells resting, monocyte, T cells CD4 memory resting and B cells memory. We further explored the relationship between the expression of immunosuppressor genes and risk score and found that ADORA2A, BTLA, CD160, CD244, CD274, CD96, CSF1R and CTLA4 genes were highly correlated with the risk score. Selective poly adenylation plays an important role in the development and progression of LUAD, immune invasion, tumor cell invasion and metastasis and biological transcription, and affects the survival and prognosis of LUAD patients.

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Section: Discussionmentioning

confidence: 99%

Selective poly adenylation predicts the efficacy of immunotherapy in patients with lung adenocarcinoma by multiple omics research

Zhong

et al. 2022

Anti-Cancer Drugs

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“…mRNA granules do not form during global ischemia (unpublished result), but require reperfusion and depend upon polysome dissociation [36]. It is therefore reasonable to ask how mRNA granules could form following pMCAO.…”

Section: Discussionmentioning

confidence: 99%

mRNA Redistribution during Permanent Focal Cerebral Ischemia

Lewis

Jamison

Dunbar

et al. 2013

Transl. Stroke Res.

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Translation arrest occurs in neurons following focal cerebral ischemia and is irreversible in penumbral neurons destined to die. Following global cerebral ischemia, mRNA is sequestered away from 40S ribosomal subunits as mRNA granules, precluding translation. Here, we investigated mRNA granule formation using fluorescence in situ histochemistry out to 8 h permanent focal cerebral ischemia using middle cerebral artery occlusion in Long Evans rats with and without diabetes. Neuronal mRNA granules colocalized with PABP, HuR, and NeuN, but not 40S or 60S ribosomal subunits, or organelle markers. The volume of brain with mRNA granule-containing neurons decreased exponentially with ischemia duration, and was zero after 8 h permanent focal cerebral ischemia or any duration of ischemia in diabetic rats. These results show that neuronal mRNA granule response has a limited range of insult intensity over which it is expressed. Identifying the limits of effective neuronal stress response to ischemia will be important for developing effective stroke therapies.

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“…With a specialized software called Mazda [28], 296 texture features are computed for each element in the training set. Various approaches have demonstrated the effectiveness of this software in extracting textural features from different types of medical images [29][30][31][32][33].…”

Section: Proposed Methodsmentioning

confidence: 99%

Texture Classification of Proteins Using Support Vector Machines and Bio-inspired Metaheuristics

Fernández-Lozano

Seoane

Mesejo

et al. 2014

Biomedical Engineering Systems and Technologies

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International audienceIn this paper, a novel classification method of two-dimensional poly-acrylamide gel electrophoresis images is presented. Such a method uses textural features obtained by means of a feature selection process for whose implementation we compare Genetic Algorithms and Particle Swarm Optimization. Then, the selected features, among which the most decisive and representative ones appear to be those related to the second order co-occurrence matrix, are used as inputs for a Support Vector Machine. The accuracy of the proposed method is around 94%, a statistically better performance than the classification based on the entire feature set. This classification step can be very useful for discarding over-segmented areas after a protein segmentation or identification process

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Texture analysis of poly-adenylated mRNA staining following global brain ischemia and reperfusion

Cited by 12 publications

References 37 publications

Selective poly adenylation predicts the efficacy of immunotherapy in patients with lung adenocarcinoma by multiple omics research

Selective poly adenylation predicts the efficacy of immunotherapy in patients with lung adenocarcinoma by multiple omics research

mRNA Redistribution during Permanent Focal Cerebral Ischemia

Texture Classification of Proteins Using Support Vector Machines and Bio-inspired Metaheuristics

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