Objective Iodothyronine deiodinases (DIOs) are important selenoproteins that play a key role in the bone and joint diseases. Osteoarthritis (OA) is the most prevalent joint disease especially in elders. This bioinformatic analysis was performed to explore the role of DIOs in OA pathogenesis. Methods The biological functions of selenoprotein DIOs were analyzed by bioinformatic techniques, including GenCLip 3.0, Database for Annotation, Visualization and Integrated Discovery (DAVID), STRING, Cytoscape, and Network Analyst. The expression of DIOs in the healthy individuals and OA patients was determined by mining OA-related microarray data in the gene expression omnibus (GEO) database of National Center for Biotechnology Information and performing a Meta-analysis of the data with Review Manager 5.3. Results Cluster analysis revealed that the function of the DIOs was associated with thyroid hormone receptor and iodothyronine; GO analysis showed that DIOs were mainly involved in biological processes, such as ethanol metabolism and phenol-containing compound metabolism and primarily involved in the cytochrome P450 metabolism of exogenous organisms and thyroid hormone signaling; SULT1A1 was the core node of the PPI network; miRNAs and thyroid hormones had some iterations with 

Biological Functions of Selenoprotein Iodothyronine Deiodinase and its Expression in Osteoarthritis.

Levodopa-induced dyskinesia frequently complicates long-term Parkinson's disease. More in-depth knowledge regarding the role of genetic factors in dyskinesia development may be important to identify parkinsonian patients who are more prone to developing dyskinesia and clarify the molecular mechanisms underlying this condition. For this reason, we systematically reviewed studies investigating genetic factors involved in dyskinesia.
A systematic search of genetic factors in Parkinson's disease dyskinesia was performed using the MEDLINE (through PubMed up to June 2019) and EMBASE databases according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A meta-analysis was conducted using a random effect model.
The literature search retrieved 33 studies assessing genes and variants possibly associated with dyskinesia in Parkinson's disease. The studies were published between 1984 and 2019 and included a total of 27,092 subjects of different ethnicities. Overall, 37 genes were analyzed in the studies reviewed, of which 22 were possibly associated with dyskinesia. The studies reported a total of 158 variants, of which 94 were possibly related to dyskinesia.
The studies reviewed demonstrated inconsistent results, possibly due to differences in screening methods and in the comparison of clinical data in a large variety of genetically- and ethnically-diverse populations. The meta-analysis failed to demonstrate any association between the rs6280 in the DRD3 gene, rs1799836 in the MAO-B, rs4680 in the COMT gene, rs34637584 in the LRRK2 gene and LID susceptibility. The role of genetic factors in LID susceptibility is still unclear and further studies are required.

Genetic variants in levodopa-induced dyskinesia (LID): A systematic review and meta-analysis.

Shenmai injection is frequently utilized in China to clinically treat granulocytopenia in oncology patients following chemotherapy. Despite this, the drug's therapeutic benefits remain a topic of contention, and its active components and potential treatment targets have yet to be established. The present study utilizes a network pharmacology approach to investigate the drug's active ingredients and possible therapeutic targets, and to evaluate the effectiveness of Shenmai injection in treating granulocytopenia through meta-analysis.
In our subject paper, we utilized the TCMID database to investigate the active ingredients present in red ginseng and ophiopogon japonicus. To further identify molecular targets, we employed SuperPred, as well as OMIM, Genecards, and DisGeNET databases. Our focus was on targets associated with granulocytopenia. The DAVID 6.8 database was utilized to perform gene ontology functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Additionally, a protein-protein interaction network was established. The resulting "drug-key component-potential target-core pathway" network was used to predict the mechanism of action of Shenmai injection in the treatment of granulocytopenia. In order to evaluate the quality of the studies included in our analysis, we utilized the Cochrane Reviewers' Handbook. We then conducted a meta-analysis of the clinical curative effect of Shenmai injection for granulocytopenia, utilizing the Cochrane Collaboration's RevMan 5.3 software.
After conducting a thorough screening, the study identified 5 primary ingredients of Shenmai injection - ophiopogonoside a, β-patchoulene, ginsenoside rf, ginsenoside re, and ginsenoside rg1-that can potentially target 5 essential proteins: STAT3, TLR4, PIK3CA, PIK3R1, and GRB2. Additionally, Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that Shenmai injection can be beneficial in treating granulocytopenia by interacting with pathways such as HIF-1 signaling, T-cell receptor signaling, PI3K-Akt signaling, chemokine signaling, and FoxO signaling. The results of meta-analysis indicate that the treatment group exhibited superior performance in terms of both efficiency and post-treatment leukocyte count when compared to the control group.
In summary, studies in network pharmacology demonstrate that Shenmai injection exerts an impact on granulocytopenia via various components, targets, and mechanisms. Additionally, evidence-based studies provide strong support for the effectiveness of Shenmai injection in preventing and treating granulocytopenia.

Network analysis to explore the pharmacological mechanism of Shenmai injection in treating granulocytopenia and evidence-based medicine approach validation.

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