Additional file 3: Figure S1. of Anti-allodynic effect of Buja in a rat model of oxaliplatin-induced peripheral neuropathy via spinal astrocytes and pro-inflammatory cytokines suppression

Spinal microglia activation was not suppressed by Buja. (A) Representative images of Iba-1 positive cells in the spinal dorsal horn of group1: Vehicle + DW (a), group2: Vehicle + Buja (b), group3: Oxaliplatin + DW (c) and group4: Oxaliplatin + Buja (d). Note the increased number of Iba-1 positive cells and the altered morphology (somatic hypertrophy with thick processes) in the group3 (c), indicating activation of microglia. (B) Quantification result of Iba-1 positive cells. Six lumbar spinal cord section images from single animal were averaged. N = 6 rats/group. Data are presented as mean ± SEM. *** p < 0.001, vs. group1; ### p < 0.001, vs. group3, by one-way ANOVA followed by Bonferroni’s post-test. (PDF 260 kb

Ortholist 2: A new comparative genomic analysis of human and caenorhabditis elegans genes

OrthoList, a compendium of Caenorhabditis elegans genes with human orthologs compiled in 2011 by a meta-analysis of four orthology-prediction methods, has been a popular tool for identifying conserved genes for research into biological and disease mechanisms. However, the efficacy of orthology prediction depends on the accuracy of gene-model predictions, an ongoing process, and orthology-prediction algorithms have also been updated over time. Here we present OrthoList 2 (OL2), a new comparative genomic analysis between C. elegans and humans, and the first assessment of how changes over time affect the landscape of predicted orthologs between two species. Although we find that updates to the orthology-prediction methods significantly changed the landscape of C. elegans–human orthologs predicted by individual programs and—unexpectedly—reduced agreement among them, we also show that our meta-analysis approach “buffered” against changes in gene content. We show that adding results from more programs did not lead to many additions to the list and discuss reasons to avoid assigning “scores” based on support by individual orthology-prediction programs; the treatment of “legacy” genes no longer predicted by these programs; and the practical difficulties of updating due to encountering deprecated, changed, or retired gene identifiers. In addition, we consider what other criteria may support claims of orthology and alternative approaches to find potential orthologs that elude identification by these programs. Finally, we created a new web-based tool that allows for rapid searches of OL2 by gene identifiers, protein domains [InterPro and SMART (Simple Modular Architecture Research Tool], or human disease associations ([OMIM (Online Mendelian Inheritence in Man], and also includes available RNA-interference resources to facilitate potential translational cross-species studies

Additional file 2: Figure S3. of Anti-allodynic effect of Buja in a rat model of oxaliplatin-induced peripheral neuropathy via spinal astrocytes and pro-inflammatory cytokines suppression

Representative co-immunolabeling image of GFAP and Iba-1 positive cells in the spinal dorsal horn. Co-immunolabeling in the same section showed the spatially different distribution of astrocytes (GFAP-positive cells) and microglia (Iba-1 positive cells) in the spinal dorsal horn (a). Separated images for astrocytes (b) and microglia (c) were also presented, respectively. (PDF 236 kb

Additional file 1: Figure S2. of Anti-allodynic effect of Buja in a rat model of oxaliplatin-induced peripheral neuropathy via spinal astrocytes and pro-inflammatory cytokines suppression

Intensity of immunoreactivity (IM) of GFAP and Iba-1 positive cells. Intensity of IM of GFAP and Iba-1 positive cells increased in group3. In group4, IM of GFAP positive cells were significantly decreased, whereas little changes of Iba-1 positive cells IM was observed. Data indicate that relative mean immunofluorescence intensity of a single cell (n = 10). Data are presented as mean ± SEM. *** p < 0.001, vs. group1; ### p < 0.001, vs. group3, by one-way ANOVA followed by Bonferroni’s post-test. group1: Vehicle + DW, group2: Vehicle + Buja, group3: Oxaliplatin + DW and group4: Oxaliplatin + Buja. (PDF 7 kb

Ortholist 2: A new comparative genomic analysis of human and caenorhabditis elegans genes

OrthoList, a compendium of Caenorhabditis elegans genes with human orthologs compiled in 2011 by a meta-analysis of four orthology-prediction methods, has been a popular tool for identifying conserved genes for research into biological and disease mechanisms. However, the efficacy of orthology prediction depends on the accuracy of gene-model predictions, an ongoing process, and orthology-prediction algorithms have also been updated over time. Here we present OrthoList 2 (OL2), a new comparative genomic analysis between C. elegans and humans, and the first assessment of how changes over time affect the landscape of predicted orthologs between two species. Although we find that updates to the orthology-prediction methods significantly changed the landscape of C. elegans–human orthologs predicted by individual programs and—unexpectedly—reduced agreement among them, we also show that our meta-analysis approach “buffered” against changes in gene content. We show that adding results from more programs did not lead to many additions to the list and discuss reasons to avoid assigning “scores” based on support by individual orthology-prediction programs; the treatment of “legacy” genes no longer predicted by these programs; and the practical difficulties of updating due to encountering deprecated, changed, or retired gene identifiers. In addition, we consider what other criteria may support claims of orthology and alternative approaches to find potential orthologs that elude identification by these programs. Finally, we created a new web-based tool that allows for rapid searches of OL2 by gene identifiers, protein domains [InterPro and SMART (Simple Modular Architecture Research Tool], or human disease associations ([OMIM (Online Mendelian Inheritence in Man], and also includes available RNA-interference resources to facilitate potential translational cross-species studies

Supplemental Material for Kim et al., 2018

Figure S1: Changes in gene content in Ensembl Compara v87, v88 and v89. The Ensembl Compara database was updated three times while we were compiling OL2. In this time-span we noticed that the landscape of worm genes with predicted human orthologs changed after each update, so that each version had ~2% of genes unique to it, while another ~2-4% of genes were found in only two of the three versions (see also Materials and Methods).Figure S2: Updated OL1. We updated OL1 by addressing changes in worm gene structure, classification and nomenclature for the genes present in our original compendium. We then combined results from the corrected OL1 programs. The Venn diagram (A) shows overlap in corrected gene content between the four programs, while the table (B) gives an overall measure of how many genes were found by one or more programs (regardless of which one(s) found them). Table S1: Data sources for orthology-prediction programs used to compile OL2. The source data for each program is found at each program’s website. File S1: Changed OL1 worm genes. This file lists genes whose classification, or ID, changed since the release of OL1. Type I changes correspond to genes that were re-classified as pseudogenes, ncRNA, being transposon-derived, or killed due to lack of evidence. Type II changes results from combining, or “merging” two or more genes that had each, separately, been found to have a human ortholog in OL1. Type III changes represent genes that were assigned new IDs, either because experimental evidence suggested that they should be merged with genes previously not in OL1 (marked red), or due to addition of previously unpredicted gene segments (denoted as a red “?”) File S2: Corrected C. elegans genes in OL1. All corrected worm genes found by each OL1-era version of orthology prediction methods are shown in tab (A). Tab (B) shows the distribution of results between OL1-era orthology-prediction methods, while tab (C) shows the corrected OL1 as well as the distribution of genes by support class (supported by one, two, three or all methods). File S3: Changed OL1 human genes. Human ENSG gene IDs from OL1 are listed for each orthology-prediction method in tab (A). This tab also shows the 574 ENSG IDs that are no longer found in current versions of the Ensembl genome browser. Tab (B) shows the Ensembl-provided history for the 574 lost ENSG IDs, showing that most are now just classified as “retired”. Tab (C) shows a randomly selected subset of 20 IDs that were “retired”. Note that the gene name (HGNC-approved symbol) associated with the “retired” ENSG ID is always associated with current ENSG IDs, demonstrating that curation of ENSG IDs rarely links “retired” IDs with their current counterparts. Tab (D) lists the sixteen human ENSG IDs that we could confirm were deprecated. File S4: C. elegans genes in OL1.1. Tab (A) shows the worm genes found to have human orthologs by updated versions of prediction methods used in OL1. Tab (B) shows the distribution of results between orthology-prediction methods. Tab (C) shows the final OL1.1, as well as the distribution of genes by support class (supported by one, two, three or all methods). Tab (D) lists those genes found only in OL1 (termed “lost”), and those added upon update to OL1.1. File S5: C. elegans OMA and OrthoInspector results, their relationship to OL1.1 and genes not supported by current versions of orthology-prediction methods. Tab (A) shows the worm genes found to have human orthologs by OMA, OrthoInspector and those already in OL1.1. Tab (B) shows the distribution of results amongst these three sets. Tab (C) lists all worm genes with human orthologs supported by current orthology-prediction methods (OL2) as well as those no longer supported (the “legacy” set). File S6: the “legacy” set. Tab (A) lists the 256 C. elegans genes previously-predicted to have human orthologs, but not supported by current versions of orthology-prediction methods, and their predicted protein domains determined by SMART and InterPro. Tab (B) lists the human “legacy” set: 165 human genes that were previously predicted to have worm orthologs, but for whom orthology is no longer supported. File S7: OL2 and legacy master list. This file, which underlies the database hosted at ortholist.shaye-lab.org, contains all orthology predictions (current and legacy), with C. elegans and human gene identifiers, as well as associated protein domain (SMART and InterPro) and human disease (OMIM) information. File S8: Freeze of code used to compile OrthoList 2. The code was downloaded from https://github.com/danshaye/OrthoList2 at the time of submission.</div

Table2_The involvement of the noradrenergic system in the antinociceptive effect of cucurbitacin D on mice with paclitaxel-induced neuropathic pain.docx

Paclitaxel (sold under the brand name Taxol) is a chemotherapeutic drug that is widely used to treat cancer. However, it can also induce peripheral neuropathy, which limits its use. Although several drugs are used to attenuate neuropathy, no optimal treatment is available to date. In this study, the effect of cucurbitacins B and D on paclitaxel-induced neuropathic pain was assessed. Multiple paclitaxel injections (a cumulative dose of 8 mg/kg, i. p.) induced cold and mechanical allodynia from days 10 to 21 in mice, and the i. p. administration of 0.025 mg/kg of cucurbitacins B and D attenuated both allodynia types. However, as cucurbitacin B showed a more toxic effect on non-cancerous (RAW 264.7) cells, further experiments were conducted with cucurbitacin D. The cucurbitacin D dose-dependently (0.025, 0.1, and 0.5 mg/kg) attenuated both allodynia types. In the spinal cord, paclitaxel injection increased the gene expression of noradrenergic (α1-and α2-adrenergic) receptors but not serotonergic (5-HT1A and 3) receptors. Cucurbitacin D treatment significantly decreased the spinal α1- but not α2-adrenergic receptors, and the amount of spinal noradrenaline was also downregulated. However, the tyrosine hydroxylase expression measured via liquid chromatography in the locus coeruleus did not decrease significantly. Finally, cucurbitacin D treatment did not lower the anticancer effect of chemotherapeutic drugs when co-administered with paclitaxel in CT-26 cell-implanted mice. Altogether, these results suggest that cucurbitacin D could be considered a treatment option against paclitaxel-induced neuropathic pain.</p

Table1_The involvement of the noradrenergic system in the antinociceptive effect of cucurbitacin D on mice with paclitaxel-induced neuropathic pain.docx

Paclitaxel (sold under the brand name Taxol) is a chemotherapeutic drug that is widely used to treat cancer. However, it can also induce peripheral neuropathy, which limits its use. Although several drugs are used to attenuate neuropathy, no optimal treatment is available to date. In this study, the effect of cucurbitacins B and D on paclitaxel-induced neuropathic pain was assessed. Multiple paclitaxel injections (a cumulative dose of 8 mg/kg, i. p.) induced cold and mechanical allodynia from days 10 to 21 in mice, and the i. p. administration of 0.025 mg/kg of cucurbitacins B and D attenuated both allodynia types. However, as cucurbitacin B showed a more toxic effect on non-cancerous (RAW 264.7) cells, further experiments were conducted with cucurbitacin D. The cucurbitacin D dose-dependently (0.025, 0.1, and 0.5 mg/kg) attenuated both allodynia types. In the spinal cord, paclitaxel injection increased the gene expression of noradrenergic (α1-and α2-adrenergic) receptors but not serotonergic (5-HT1A and 3) receptors. Cucurbitacin D treatment significantly decreased the spinal α1- but not α2-adrenergic receptors, and the amount of spinal noradrenaline was also downregulated. However, the tyrosine hydroxylase expression measured via liquid chromatography in the locus coeruleus did not decrease significantly. Finally, cucurbitacin D treatment did not lower the anticancer effect of chemotherapeutic drugs when co-administered with paclitaxel in CT-26 cell-implanted mice. Altogether, these results suggest that cucurbitacin D could be considered a treatment option against paclitaxel-induced neuropathic pain.</p

Data_Sheet_1_Cost-effectiveness of rhythm control strategy: Ablation versus antiarrhythmic drugs for treating atrial fibrillation in Korea based on real-world data.PDF

BackgroundAblation-based treatment has emerged as an alternative rhythm control strategy for symptomatic atrial fibrillation (AF). Recent studies have demonstrated the cost-effectiveness of ablation compared with medical therapy in various circumstances. We assessed the economic comparison between ablation and medical therapy based on a nationwide real-world population.Methods and findingsFor 192,345 patients with new-onset AF (age ≥ 18 years) identified between August 2015 and July 2018 from the Korean Health Insurance Review and Assessment Service (HIRA) database, medical resource use data were collected to compare AF patients that underwent ablation (N = 2,131) and those administered antiarrhythmic drugs (N = 8,048). Subsequently, a Markov chain Monte Carlo model was built. The patients had at least one risk factor for stroke, and the base-case used a 20-year time horizon, discounting at 4.5% annually. Transition probabilities and costs were estimated using the present data, and utilities were derived from literature review. The costs were converted to US $(2019). Sensitivity analyses were performed using probabilistic and deterministic methods. The net costs and quality-adjusted life years (QALY) for antiarrhythmic drugs and ablation treatments were$37,421 and 8.8 QALYs and $39,820 and 9.3 QALYs, respectively. Compared with antiarrhythmic drugs, incremental cost-effectiveness ratio of ablation was$4,739/QALY, which is lower than the willingness-to-pay (WTP) threshold of $32,000/QALY.ConclusionIn symptomatic AF patients with a stroke risk under the age of 75 years, ablation-based rhythm control is potentially a more economically attractive option compared with antiarrhythmic drug-based rhythm control in Korea.</p

Image1_The involvement of the noradrenergic system in the antinociceptive effect of cucurbitacin D on mice with paclitaxel-induced neuropathic pain.jpeg

Paclitaxel (sold under the brand name Taxol) is a chemotherapeutic drug that is widely used to treat cancer. However, it can also induce peripheral neuropathy, which limits its use. Although several drugs are used to attenuate neuropathy, no optimal treatment is available to date. In this study, the effect of cucurbitacins B and D on paclitaxel-induced neuropathic pain was assessed. Multiple paclitaxel injections (a cumulative dose of 8 mg/kg, i. p.) induced cold and mechanical allodynia from days 10 to 21 in mice, and the i. p. administration of 0.025 mg/kg of cucurbitacins B and D attenuated both allodynia types. However, as cucurbitacin B showed a more toxic effect on non-cancerous (RAW 264.7) cells, further experiments were conducted with cucurbitacin D. The cucurbitacin D dose-dependently (0.025, 0.1, and 0.5 mg/kg) attenuated both allodynia types. In the spinal cord, paclitaxel injection increased the gene expression of noradrenergic (α1-and α2-adrenergic) receptors but not serotonergic (5-HT1A and 3) receptors. Cucurbitacin D treatment significantly decreased the spinal α1- but not α2-adrenergic receptors, and the amount of spinal noradrenaline was also downregulated. However, the tyrosine hydroxylase expression measured via liquid chromatography in the locus coeruleus did not decrease significantly. Finally, cucurbitacin D treatment did not lower the anticancer effect of chemotherapeutic drugs when co-administered with paclitaxel in CT-26 cell-implanted mice. Altogether, these results suggest that cucurbitacin D could be considered a treatment option against paclitaxel-induced neuropathic pain.</p