Review and Literature Mining on Proteostasis Factors and Cancer

Background: Many antibiotics have a high potential for having an interaction with drugs, as perpetrator and/or victim, in critically ill patients, and particularly in sepsis patients. Methods: The aim of this review is to summarize the pharmacokinetic drug-drug interaction (DDI) of 45 antibiotics commonly used in sepsis care in China. Literature mining was conducted to obtain human pharmacokinetics/dispositions of the antibiotics, their interactions with drug metabolizing enzymes or transporters, and their associated clinical drug interactions. Potential DDI is indicated by a DDI index > 0.1 for inhibition or a treated-cell/untreated-cell ratio of enzyme activity being > 2 for induction. Results: The literature-mined information on human pharmacokinetics of the identified antibiotics and their potential drug interactions is summarized. Conclusion: Antibiotic-perpetrated drug interactions, involving P450 enzyme inhibition, have been reported for four lipophilic antibacterials (ciprofloxacin, erythromycin, trimethoprim, and trimethoprim-sulfamethoxazole) and three lipophilic antifungals (fluconazole, itraconazole, and voriconazole). In addition, seven hydrophilic antibacterials (ceftriaxone, cefamandole, piperacillin, penicillin G, amikacin, metronidazole, and linezolid) inhibit drug transporters in vitro. Despite no reported clinical PK drug interactions with the transporters, caution is advised in the use of these antibacterials. Eight hydrophilic antibacterials (all β-lactams; meropenem, cefotaxime, cefazolin, piperacillin, ticarcillin, penicillin G, ampicillin, and flucloxacillin), are potential victims of drug interactions due to transporter inhibition. Rifampin is reported to perpetrate drug interactions by inducing CYP3A or inhibiting OATP1B; it is also reported to be a victim of drug interactions, due to the dual inhibition of CYP3A4 and OATP1B by indinavir. In addition, three antifungals (caspofungin, itraconazole, and voriconazole) are reported to be victims of drug interactions because of P450 enzyme induction. Reports for other antibiotics acting as victims in drug interactions are scarce.

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Preliminary Study on the Mechanism of Carvacrol Regulating Hepatocellular Carcinoma Based on Network Pharmacology

Letters in Drug Design & Discovery ◽

10.2174/1570180816666190516105906 ◽

2019 ◽

Vol 16 (11) ◽

pp. 1286-1295

Author(s):

Sha Li ◽

Haixia Zhao ◽

Lidao Bao

Keyword(s):

Hepatocellular Carcinoma ◽

Western Blot ◽

Target Prediction ◽

Network Pharmacology ◽

Literature Mining ◽

Active Compounds ◽

Prediction Server ◽

Preliminary Study ◽

Alignment Analysis ◽

Endogenous Interactions

Objective: To predict and analyze the target of anti-Hepatocellular Carcinoma (HCC) in the active constituents of Safflower by using network pharmacology. Methods: The active compounds of safflower were collected by TCMSP, TCM-PTD database and literature mining methods. The targets of active compounds were predicted by Swiss Target Prediction server, and the target of anti-HCC drugs was collected by DisGeNET database. The target was subjected to an alignment analysis to screen out Carvacrol, a target of safflower against HCC. The mouse HCC model was established and treated with Carvacrol. The anti-HCC target DAPK1 and PPP2R2A were verified by Western blot and co-immunoprecipitation. Results: A total of 21 safflower active ingredients were predicted. Carvacrol was identified as a possible active ingredient according to the five principles of drug-like medicine. According to Carvacrol's possible targets and possible targets of HCC, three co-targets were identified, including cancer- related are DAPK1 and PPP2R2A. After 20 weeks of Carvacrol treated, Carvacrol group significantly increased on DAPK1 levels and decreased PPP2R2A levels in the model mice by Western blot. Immunoprecipitation confirmed the endogenous interaction between DAPK1 and PPP2R2A. Conclusion: Safflower can regulate the development of HCC through its active component Carvacrol, which can affect the expression of DAPK1 and PPP2R2A proteins, and the endogenous interactions of DAPK1 and PPP2R2A proteins.

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Large-scale literature mining to assess the relation between anti-cancer drugs and cancer types

Journal of Translational Medicine ◽

10.1186/s12967-021-02941-z ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Chris Bauer ◽

Ralf Herwig ◽

Matthias Lienhard ◽

Paul Prasse ◽

Tobias Scheffer ◽

...

Keyword(s):

Text Mining ◽

Knowledge Base ◽

Survival Data ◽

Scientific Literature ◽

Entity Recognition ◽

Literature Mining ◽

Cancer Drugs ◽

Classical Text ◽

Anti Cancer ◽

Cancer Types

Abstract Background There is a huge body of scientific literature describing the relation between tumor types and anti-cancer drugs. The vast amount of scientific literature makes it impossible for researchers and physicians to extract all relevant information manually. Methods In order to cope with the large amount of literature we applied an automated text mining approach to assess the relations between 30 most frequent cancer types and 270 anti-cancer drugs. We applied two different approaches, a classical text mining based on named entity recognition and an AI-based approach employing word embeddings. The consistency of literature mining results was validated with 3 independent methods: first, using data from FDA approvals, second, using experimentally measured IC-50 cell line data and third, using clinical patient survival data. Results We demonstrated that the automated text mining was able to successfully assess the relation between cancer types and anti-cancer drugs. All validation methods showed a good correspondence between the results from literature mining and independent confirmatory approaches. The relation between most frequent cancer types and drugs employed for their treatment were visualized in a large heatmap. All results are accessible in an interactive web-based knowledge base using the following link: https://knowledgebase.microdiscovery.de/heatmap. Conclusions Our approach is able to assess the relations between compounds and cancer types in an automated manner. Both, cancer types and compounds could be grouped into different clusters. Researchers can use the interactive knowledge base to inspect the presented results and follow their own research questions, for example the identification of novel indication areas for known drugs.

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Poster: Distinguishing scientific abbreviations and genes in bio-medical literature mining

2011 IEEE 1st International Conference on Computational Advances in Bio and Medical Sciences (ICCABS) ◽

10.1109/iccabs.2011.5729906 ◽

2011 ◽

Author(s):

Guozhen Liu ◽

Han Zhang ◽

George Quellhorst

Keyword(s):

Medical Literature ◽

Literature Mining

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Microarray analysis reveals novel gene expression changes associated with erectile dysfunction in diabetic rats

Physiological Genomics ◽

10.1152/physiolgenomics.00112.2005 ◽

2005 ◽

Vol 23 (2) ◽

pp. 192-205 ◽

Cited By ~ 34

Author(s):

Chris J. Sullivan ◽

Thomas H. Teal ◽

Ian P. Luttrell ◽

Khoa B. Tran ◽

Mette A. Peters ◽

...

Keyword(s):

Gene Expression ◽

Smooth Muscle ◽

Erectile Dysfunction ◽

Splice Variants ◽

Full Range ◽

Diabetic Rats ◽

Differentially Expressed ◽

Diabetic Rat ◽

Literature Mining ◽

Mrna Levels

To investigate the full range of molecular changes associated with erectile dysfunction (ED) in Type 1 diabetes, we examined alterations in penile gene expression in streptozotocin-induced diabetic rats and littermate controls. With the use of Affymetrix GeneChip arrays and statistical filtering, 529 genes/transcripts were considered to be differentially expressed in the diabetic rat cavernosum compared with control. Gene Ontology (GO) classification indicated that there was a decrease in numerous extracellular matrix genes (e.g., collagen and elastin related) and an increase in oxidative stress-associated genes in the diabetic rat cavernosum. In addition, PubMatrix literature mining identified differentially expressed genes previously shown to mediate vascular dysfunction [e.g., ceruloplasmin ( Cp), lipoprotein lipase, and Cd36] as well as genes involved in the modulation of the smooth muscle phenotype (e.g., Kruppel-like factor 5 and chemokine C-X3-C motif ligand 1). Real-time PCR was used to confirm changes in expression for 23 relevant genes. Further validation of Cp expression in the diabetic rat cavernosum demonstrated increased mRNA levels of the secreted and anchored splice variants of Cp. CP protein levels showed a 1.9-fold increase in tissues from diabetic rats versus controls. Immunohistochemistry demonstrated localization of CP protein in cavernosal sinusoids of control and diabetic animals, including endothelial and smooth muscle layers. Overall, this study broadens the scope of candidate genes and pathways that may be relevant to the pathophysiology of diabetes-induced ED as well as highlights the potential complexity of this disorder.

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A Review of Recent Advancement in Integrating Omics Data with Literature Mining towards Biomedical Discoveries

International Journal of Genomics ◽

10.1155/2017/6213474 ◽

2017 ◽

Vol 2017 ◽

pp. 1-10 ◽

Cited By ~ 15

Author(s):

Kalpana Raja ◽

Matthew Patrick ◽

Yilin Gao ◽

Desmond Madu ◽

Yuyang Yang ◽

...

Keyword(s):

Text Mining ◽

High Throughput ◽

Literature Mining ◽

Biological Knowledge ◽

Omics Data ◽

Huge Number ◽

Automated Generation ◽

The Past ◽

Independent Information ◽

Recent Advancement

In the past decade, the volume of “omics” data generated by the different high-throughput technologies has expanded exponentially. The managing, storing, and analyzing of this big data have been a great challenge for the researchers, especially when moving towards the goal of generating testable data-driven hypotheses, which has been the promise of the high-throughput experimental techniques. Different bioinformatics approaches have been developed to streamline the downstream analyzes by providing independent information to interpret and provide biological inference. Text mining (also known as literature mining) is one of the commonly used approaches for automated generation of biological knowledge from the huge number of published articles. In this review paper, we discuss the recent advancement in approaches that integrate results from omics data and information generated from text mining approaches to uncover novel biomedical information.

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Omics multi-layers networks and identification of genes involved in fat storage and metabolism in poultry using interactomics approach

10.21203/rs.3.rs-30697/v1 ◽

2020 ◽

Author(s):

abolfazl bahrami ◽

Farzad Ghafouri ◽

Mostafa Sadeghi ◽

Seyed Reza Miraei-Ashtiani

Keyword(s):

Adipose Tissue ◽

Signaling Pathway ◽

High Throughput Screening ◽

Broiler Chickens ◽

Unsaturated Fatty Acids ◽

Holistic Approach ◽

High Rate ◽

Literature Mining ◽

Ampk Signaling ◽

Ppar Signaling

Abstract Background Fatty acid metabolism in animals has a major impact on production and disease resistance traits. According to the high rate of interactions between lipid metabolism and its regulating properties, a holistic approach is necessary. Methods To study multi-omics layers of adipose tissue and identification of genes involved in fat metabolism, storage and endocrine signaling pathways in two groups of broiler chickens with high and low abdominal fat, high-throughput screening (HTS) techniques were used. The Gene-miRNA interacting bipartite and metabolic-signaling networks were reconstructed using their interactions. Results In the analysis of microarray and RNA-Seq data, 1835 genes were detected by comparing the identified genes with significant expression differences. Then, by comparing, 34 genes and 19 miRNAs were detected as common and main nodes. The literature mining approach was used and 7 genes were identified and added to the common gene set. Module finding revealed three important and functional modules. The detected modules 1, 2, and 3 were involved in the PPAR signaling pathway, biosynthesis of unsaturated fatty acids, and Alzheimer's disease metabolic pathway, adipocytokine, insulin, PI3K-Akt, mTOR and AMPK signaling pathway. Conclusions This approach revealed a new insight for a better understanding of the biological processes associated with adipose tissue.

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Case analysis on indirect economic benefits of industrial building construction

MATEC Web of Conferences ◽

10.1051/matecconf/202133609020 ◽

2021 ◽

Vol 336 ◽

pp. 09020

Author(s):

Yuan Qi ◽

Ning Kang

Keyword(s):

Economic Benefits ◽

Industrial Building ◽

Literature Mining ◽

Economic Returns ◽

Building Models ◽

Modeling Software ◽

The Index System ◽

The Impact ◽

Assembly Rate ◽

Prefabricated Building

In this paper, the economic benefits of prefabricated buildings which are not directly reflected in the economic returns of investors are called indirect economic benefits. Based on the literature mining of the indirect economic relationship of a large number of prefabricated buildings, this paper constructs an analysis framework of indirect environment and social and economic benefits. Through BIM modeling software, the three prefabricated building models are modified into traditional building models. The indirect economic benefits of the project are calculated by using the index system. The functional relationship between the indirect economic benefits of prefabricated buildings and the assembly rate is established by using the SSPS statistical data processing software, which more intuitively shows the law of the indirect economic benefits of prefabricated buildings with the assembly rate It shows the impact of prefabricated building on environment and society, which is of great significance for the harmony between prefabricated building and society and environment, and the healthy and sustainable development of construction industry.

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The function of SIRT3 explored through the substrate interaction network

10.1101/2020.12.10.414995 ◽

2020 ◽

Author(s):

Jarmila Nahálková

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Interaction Network ◽

Literature Mining ◽

Biological Functions ◽

Alcoholic Fatty Liver ◽

Pathway Enrichment ◽

Substrate Interaction ◽

Lysine Deacetylase ◽

Brown Adipose

AbstractSIRT3 is the mitochondrial protein lysine deacetylase with a prominent role in the maintenance of mitochondrial integrity vulnerable in the range of diseases. The present study examines the SIRT3 substrate interaction network for the identification of its biological functions in the cellular anti-aging mechanisms. The pathway enrichment, the protein function prediction, and the protein node prioritization analysis were performed based on 407 SIRT3 substrates, which were collected by the data mining. The substrates are interlinked by 1230 direct protein-protein interactions included in the GeneMania database. The analysis of the SIRT3 substrate interaction network highlighted Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), and non-alcoholic fatty liver disease (NAFLD) as the most associated with SIRT3 lysine deacetylase activity. The most important biological functions of SIRT3 substrates are within the respiratory electron transport chain, tricarboxylic acid cycle and fatty acid, triacylglycerol, and ketone body metabolism. In brown adipose tissue, SIRT3 activity contributes to the adaptive thermogenesis by the increase of energy production of the organisms. SIRT3 exhibits several modes of neuroprotective actions in the brain and liver including prevention of the mitochondrial damages due to the respiratory electron transfer chain failure, the quenching of ROS, the inhibition of the mitochondrial membrane potential loss, and the regulation of mitophagy. Related to its role in Alzheimer’s disease, SIRT3 activation performs as a repressor of BACE1 through SIRT3-LKB1-AMPK-CREB-PGC-1α-PPARG-BACE1 (SIRT3-BACE1) pathway, which was created based on the literature mining and by employing Wikipathways application. The pathway enrichment analysis of the extended interaction network of the SIRT3-BACE1 pathway nodes displayed the functional relation to the circadian clock, which also deteriorates during the progress of AD and it is the causative of AD, PD, and HD. The use of SIRT3 activators in combination with the stimulating effect of regular exercise is further discussed as an attractive option for the improvement of cognitive decline during aging and the progressive stages of neurodegeneration.

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