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Eurofins sequencing methods 366
Sequencing Methods 366, supplied by Eurofins, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Article Title: Characterization of Pseudomonas monteilii CCM 3423 and its physiological potential for biodegradation of selected organic pollutants.
Article Snippet: Pseudomonas monteilii CCM 3423 bacterial strain, deposited at the Czech Collection of Microorganisms, was originally isolated by Haľama and Augustín (1980) as a bacterium degrading aromatic hydrocarbons and derivates.. A detailed study supported by a molecular genetics method of sequence analyses of rrs and rpoD genes was used to reclassify the strain, originally stored as ‘Pseudomonas putida’.. The physiological characteristics of the strain are complemented with research in the capacity to utilize selected organic pollutants (anthracene, benz[a]anthracene, benzo[b]fluoranthene, benzo[k]fluoranthene, benzo[a]pyrene, fluorene, naphthalene, phenanthrene).

Article Title: Pseudomonas prosekii sp. nov., a novel psychrotrophic bacterium from Antarctica.
Article Snippet: During Czech expeditions at James Ross Island, Antarctica, in the years 2007–2009, the bacterial diversity of the genus Pseudomonas was studied.. Twelve fluorescent Pseudomonas strains were isolated from various samples and were subjected to a detailed taxonomic study.. A polyphasic approach included genotypic and phenotypic analyses.

Article Title: Automated phenotyping empowered by deep learning for genomic prediction of body size in the tiger pufferfish, Takifugu rubripes
Article Snippet: Library preparation and sequencing procedures were performed by Eurofins Genomics, Inc. (Tokyo, Japan). .. Library preparation and sequencing procedures were performed by Eurofins Genomics, Inc. (Tokyo, Japan). ..

Article Title: Active and passive biosorption of Pb(II)using live and dead biomass of marine bacterium Bacillus xiamenensis PbRPSD202: Kinetics and isotherm studies.
Article Snippet: A highly lead(II) resistant (up to 2200mg/l) bacterium PbRPSD202 was selected among 210 lead resistant bacteria isolated from marine environment of Paradeep Port, Odisha for possible biosoption of toxic Pb (II) ions from metals polluted environments.. The bacterium was identified as Bacillus xiamenensis following the phenotypic as well as 16S rRNA gene sequence analysis.. In addition to Pb(II), it also showed resistance towards other heavy metals like Cd(II), Cr(VI), As(III), Cu(II), Ni(II) and Zn(II).

Article Title: Description of Pseudomonas jessenii subsp. pseudoputida subsp. nov., amended description of Pseudomonas jessenii and description of Pseudomonas jessenii subsp. jessenii subsp. nov.
Article Snippet: Fluorescent Pseudomonas putida CCM 3656 (ATCC 11250) was analysed according to the methods of polyphasic approach which were based on sequence analyses involving the rpoB and rrs genes, manual ribotyping using endonuclease HindIII, DNA base composition determination and DNA–DNA hybridization.. The results obtained by these genotyping methods showed that the strain CCM 3656 is distant from P. putida taxon, which was supported with phenotype characterization represented by whole-cell protein profile analysis, matrix-assisted laser desorption/ionization–time-of-flight mass spectrometry profiling and extended biotyping.. The DNA–DNA hybridization experiments performed between the strain CCM 3656 and the closest relatives revealed 77 % similarity with Pseudomonas jessenii.



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USP18 Acts as a Key ROS-Responsive Mediator Driving Cisplatin Resistance in Ovarian Cancer. a Mechanisms and incidence of platinum resistance in ovarian cancer (Icons created with BioRender.com ). b Representative images of ROS detection using DCFH-DA probe in cisplatin-resistant and parental SKOV3 cells. Scale bar: 50 μm; GSEA analysis of ROS response genes based on transcriptome <t>sequencing</t> data in cisplatin-resistant and parental SKOV3 cells. c Representative images of ROS detection using DCFH-DA probe in SKOV3 cells treated with vehicle control, cisplatin (20 μM), or cisplatin plus NAC (10 μM) + mito-TEMPO (10 μM). Scale bar: 50 μm; Cell proliferation curves by Real-time cell analysis (RTCA) system (bottom left); LDH release assay in SKOV3 cells treated with cisplatin (20 μM) or cisplatin plus NAC (10 μM) + mito-TEMPO (10 μM) (bottom right). d Representative Immunohistochemistry (IHC) images showing pyroptosis (Cleaved-Caspase-1), apoptosis (Cleaved-Caspase-3), ferroptosis (GPX4), necroptosis (p-MLKL), and autophagy (p62) markers in cisplatin-resistant ovarian cancer PDX model (OV9419) tissues. Scale bar: 100 μm. e Protein expression levels of various cell death markers in OVCAR-3 cells treated with vehicle control, cisplatin (20 μM), or cisplatin plus NAC (10 μM) + mito-TEMPO (10 μM): pyroptosis (Cleaved-Caspase-1), apoptosis (Cleaved-Caspase-3), ferroptosis (GPX4), necroptosis (p-MLKL), and autophagy (LC3 II/LC3 I). f Schematic of DUB screening for cisplatin resistance: DUB plasmid library transfected into A2780 cells, treated with cisplatin (10 μM) after 24h, and cell viability measured by CCK8 after another 48h. Scatter plot shows relative cell viability compared to control. g Protein expression levels of USP18, USP37, and USP39 in parental and cisplatin-resistant SKOV3 cells. h Protein expression levels of USP18, USP37, and USP39 in OVCAR-3 cells treated with vehicle control, cisplatin (20 μM), or cisplatin (20 μM) plus NAC (10 μM) + mito-TEMPO (10 μM). i Protein expression levels of USP18, USP37, and USP39 in tissues from cisplatin-sensitive (n = 4) and -resistant (n = 4) ovarian cancer patients. j Analysis of USP18 expression in ovarian cancer versus normal ovarian tissues using data from The Cancer Genome Atlas (TCGA) ( www.aclbi.com ) k Survival analysis of patients with differential USP18 using data from TCGA. Analysis was performed via the KM-plotter platform ( https://kmplot.com/ ). l Representative IHC staining of USP18 shows its expression patterns in ovarian cancer tissues compared with paired adjacent tissues, and in therapy-sensitive versus resistant cases. Scale bar: 100 μm. Patients were stratified into high and low USP18 expression groups based on the median IHC score, and the distribution was compared using the Chi-squared test. m Analysis of USP18 expression in ovarian cancer patients stratified by response to platinum-based therapy using the ROC plot online platform ( https://rocplot.com/ ). n Protein expression levels of USP18 in ovarian cancer cell lines. o Cisplatin IC 50 values in ovarian cancer cell lines. p Pearson correlation analysis between USP18 protein levels (n) and cisplatin IC 50 (o). Data presented as mean ± SD. Significance calculated by unpaired two-tailed t -test (c). ∗∗P < 0.01; ∗∗∗∗P < 0.0001.
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CD32b distinguishes transcriptionally and functionally distinct GM-DC subsets derived from MDPs and GMPs. (A) Principal component analysis (PCA) of <t>bulk</t> <t>RNA-seq</t> data from GM-DCs sorted on day 7 and day 21. DCs were generated from cultures of whole bone marrow (BM), sorted MDPs, or sorted GMPs with GM-CSF. (B) Heatmap showing the expression of genes upregulated and downregulated in MDP GM-DCs at day 7, identified through Venn diagram analysis and mapped onto BM GM-DCs at both time points. (C) Volcano plot of differentially expressed genes (DEGs) between MDP GM-DCs (day 7) and GMP GM-DCs (day 21). The thresholds for significance (dotted lines) are set at a log 2 (fold change) ≥ 3 or raw p -value ≤ 10 -16 . (D) Flow cytometric validation of selected surface marker candidates identified in the volcano plot (C) . Normalized Mean fluorescence intensity (MFI) of four representative markers is shown for each DC subset. Normalized MFI was calculated by subtracting the isotype control mean fluorescence from the sample mean fluorescence, and then dividing the result by the isotype control mean. Representative histograms are shown below the bar graphs, with the isotype control overlaid in gray. Data are representative of two independent experiments.
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CD32b distinguishes transcriptionally and functionally distinct GM-DC subsets derived from MDPs and GMPs. (A) Principal component analysis (PCA) of <t>bulk</t> <t>RNA-seq</t> data from GM-DCs sorted on day 7 and day 21. DCs were generated from cultures of whole bone marrow (BM), sorted MDPs, or sorted GMPs with GM-CSF. (B) Heatmap showing the expression of genes upregulated and downregulated in MDP GM-DCs at day 7, identified through Venn diagram analysis and mapped onto BM GM-DCs at both time points. (C) Volcano plot of differentially expressed genes (DEGs) between MDP GM-DCs (day 7) and GMP GM-DCs (day 21). The thresholds for significance (dotted lines) are set at a log 2 (fold change) ≥ 3 or raw p -value ≤ 10 -16 . (D) Flow cytometric validation of selected surface marker candidates identified in the volcano plot (C) . Normalized Mean fluorescence intensity (MFI) of four representative markers is shown for each DC subset. Normalized MFI was calculated by subtracting the isotype control mean fluorescence from the sample mean fluorescence, and then dividing the result by the isotype control mean. Representative histograms are shown below the bar graphs, with the isotype control overlaid in gray. Data are representative of two independent experiments.
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CD32b distinguishes transcriptionally and functionally distinct GM-DC subsets derived from MDPs and GMPs. (A) Principal component analysis (PCA) of <t>bulk</t> <t>RNA-seq</t> data from GM-DCs sorted on day 7 and day 21. DCs were generated from cultures of whole bone marrow (BM), sorted MDPs, or sorted GMPs with GM-CSF. (B) Heatmap showing the expression of genes upregulated and downregulated in MDP GM-DCs at day 7, identified through Venn diagram analysis and mapped onto BM GM-DCs at both time points. (C) Volcano plot of differentially expressed genes (DEGs) between MDP GM-DCs (day 7) and GMP GM-DCs (day 21). The thresholds for significance (dotted lines) are set at a log 2 (fold change) ≥ 3 or raw p -value ≤ 10 -16 . (D) Flow cytometric validation of selected surface marker candidates identified in the volcano plot (C) . Normalized Mean fluorescence intensity (MFI) of four representative markers is shown for each DC subset. Normalized MFI was calculated by subtracting the isotype control mean fluorescence from the sample mean fluorescence, and then dividing the result by the isotype control mean. Representative histograms are shown below the bar graphs, with the isotype control overlaid in gray. Data are representative of two independent experiments.
Generation Sequencing Procedures Amplified Cdna, supplied by Psomagen Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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CD32b distinguishes transcriptionally and functionally distinct GM-DC subsets derived from MDPs and GMPs. (A) Principal component analysis (PCA) of <t>bulk</t> <t>RNA-seq</t> data from GM-DCs sorted on day 7 and day 21. DCs were generated from cultures of whole bone marrow (BM), sorted MDPs, or sorted GMPs with GM-CSF. (B) Heatmap showing the expression of genes upregulated and downregulated in MDP GM-DCs at day 7, identified through Venn diagram analysis and mapped onto BM GM-DCs at both time points. (C) Volcano plot of differentially expressed genes (DEGs) between MDP GM-DCs (day 7) and GMP GM-DCs (day 21). The thresholds for significance (dotted lines) are set at a log 2 (fold change) ≥ 3 or raw p -value ≤ 10 -16 . (D) Flow cytometric validation of selected surface marker candidates identified in the volcano plot (C) . Normalized Mean fluorescence intensity (MFI) of four representative markers is shown for each DC subset. Normalized MFI was calculated by subtracting the isotype control mean fluorescence from the sample mean fluorescence, and then dividing the result by the isotype control mean. Representative histograms are shown below the bar graphs, with the isotype control overlaid in gray. Data are representative of two independent experiments.
Sequencing Methods 366, supplied by Eurofins, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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CD32b distinguishes transcriptionally and functionally distinct GM-DC subsets derived from MDPs and GMPs. (A) Principal component analysis (PCA) of <t>bulk</t> <t>RNA-seq</t> data from GM-DCs sorted on day 7 and day 21. DCs were generated from cultures of whole bone marrow (BM), sorted MDPs, or sorted GMPs with GM-CSF. (B) Heatmap showing the expression of genes upregulated and downregulated in MDP GM-DCs at day 7, identified through Venn diagram analysis and mapped onto BM GM-DCs at both time points. (C) Volcano plot of differentially expressed genes (DEGs) between MDP GM-DCs (day 7) and GMP GM-DCs (day 21). The thresholds for significance (dotted lines) are set at a log 2 (fold change) ≥ 3 or raw p -value ≤ 10 -16 . (D) Flow cytometric validation of selected surface marker candidates identified in the volcano plot (C) . Normalized Mean fluorescence intensity (MFI) of four representative markers is shown for each DC subset. Normalized MFI was calculated by subtracting the isotype control mean fluorescence from the sample mean fluorescence, and then dividing the result by the isotype control mean. Representative histograms are shown below the bar graphs, with the isotype control overlaid in gray. Data are representative of two independent experiments.
Sequencing Related Procedures, supplied by Beijing Genomics Institute Shenzhen, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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CD32b distinguishes transcriptionally and functionally distinct GM-DC subsets derived from MDPs and GMPs. (A) Principal component analysis (PCA) of <t>bulk</t> <t>RNA-seq</t> data from GM-DCs sorted on day 7 and day 21. DCs were generated from cultures of whole bone marrow (BM), sorted MDPs, or sorted GMPs with GM-CSF. (B) Heatmap showing the expression of genes upregulated and downregulated in MDP GM-DCs at day 7, identified through Venn diagram analysis and mapped onto BM GM-DCs at both time points. (C) Volcano plot of differentially expressed genes (DEGs) between MDP GM-DCs (day 7) and GMP GM-DCs (day 21). The thresholds for significance (dotted lines) are set at a log 2 (fold change) ≥ 3 or raw p -value ≤ 10 -16 . (D) Flow cytometric validation of selected surface marker candidates identified in the volcano plot (C) . Normalized Mean fluorescence intensity (MFI) of four representative markers is shown for each DC subset. Normalized MFI was calculated by subtracting the isotype control mean fluorescence from the sample mean fluorescence, and then dividing the result by the isotype control mean. Representative histograms are shown below the bar graphs, with the isotype control overlaid in gray. Data are representative of two independent experiments.
Rna Sequencing Procedures, supplied by Sangon Biotech, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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CD32b distinguishes transcriptionally and functionally distinct GM-DC subsets derived from MDPs and GMPs. (A) Principal component analysis (PCA) of <t>bulk</t> <t>RNA-seq</t> data from GM-DCs sorted on day 7 and day 21. DCs were generated from cultures of whole bone marrow (BM), sorted MDPs, or sorted GMPs with GM-CSF. (B) Heatmap showing the expression of genes upregulated and downregulated in MDP GM-DCs at day 7, identified through Venn diagram analysis and mapped onto BM GM-DCs at both time points. (C) Volcano plot of differentially expressed genes (DEGs) between MDP GM-DCs (day 7) and GMP GM-DCs (day 21). The thresholds for significance (dotted lines) are set at a log 2 (fold change) ≥ 3 or raw p -value ≤ 10 -16 . (D) Flow cytometric validation of selected surface marker candidates identified in the volcano plot (C) . Normalized Mean fluorescence intensity (MFI) of four representative markers is shown for each DC subset. Normalized MFI was calculated by subtracting the isotype control mean fluorescence from the sample mean fluorescence, and then dividing the result by the isotype control mean. Representative histograms are shown below the bar graphs, with the isotype control overlaid in gray. Data are representative of two independent experiments.
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USP18 Acts as a Key ROS-Responsive Mediator Driving Cisplatin Resistance in Ovarian Cancer. a Mechanisms and incidence of platinum resistance in ovarian cancer (Icons created with BioRender.com ). b Representative images of ROS detection using DCFH-DA probe in cisplatin-resistant and parental SKOV3 cells. Scale bar: 50 μm; GSEA analysis of ROS response genes based on transcriptome sequencing data in cisplatin-resistant and parental SKOV3 cells. c Representative images of ROS detection using DCFH-DA probe in SKOV3 cells treated with vehicle control, cisplatin (20 μM), or cisplatin plus NAC (10 μM) + mito-TEMPO (10 μM). Scale bar: 50 μm; Cell proliferation curves by Real-time cell analysis (RTCA) system (bottom left); LDH release assay in SKOV3 cells treated with cisplatin (20 μM) or cisplatin plus NAC (10 μM) + mito-TEMPO (10 μM) (bottom right). d Representative Immunohistochemistry (IHC) images showing pyroptosis (Cleaved-Caspase-1), apoptosis (Cleaved-Caspase-3), ferroptosis (GPX4), necroptosis (p-MLKL), and autophagy (p62) markers in cisplatin-resistant ovarian cancer PDX model (OV9419) tissues. Scale bar: 100 μm. e Protein expression levels of various cell death markers in OVCAR-3 cells treated with vehicle control, cisplatin (20 μM), or cisplatin plus NAC (10 μM) + mito-TEMPO (10 μM): pyroptosis (Cleaved-Caspase-1), apoptosis (Cleaved-Caspase-3), ferroptosis (GPX4), necroptosis (p-MLKL), and autophagy (LC3 II/LC3 I). f Schematic of DUB screening for cisplatin resistance: DUB plasmid library transfected into A2780 cells, treated with cisplatin (10 μM) after 24h, and cell viability measured by CCK8 after another 48h. Scatter plot shows relative cell viability compared to control. g Protein expression levels of USP18, USP37, and USP39 in parental and cisplatin-resistant SKOV3 cells. h Protein expression levels of USP18, USP37, and USP39 in OVCAR-3 cells treated with vehicle control, cisplatin (20 μM), or cisplatin (20 μM) plus NAC (10 μM) + mito-TEMPO (10 μM). i Protein expression levels of USP18, USP37, and USP39 in tissues from cisplatin-sensitive (n = 4) and -resistant (n = 4) ovarian cancer patients. j Analysis of USP18 expression in ovarian cancer versus normal ovarian tissues using data from The Cancer Genome Atlas (TCGA) ( www.aclbi.com ) k Survival analysis of patients with differential USP18 using data from TCGA. Analysis was performed via the KM-plotter platform ( https://kmplot.com/ ). l Representative IHC staining of USP18 shows its expression patterns in ovarian cancer tissues compared with paired adjacent tissues, and in therapy-sensitive versus resistant cases. Scale bar: 100 μm. Patients were stratified into high and low USP18 expression groups based on the median IHC score, and the distribution was compared using the Chi-squared test. m Analysis of USP18 expression in ovarian cancer patients stratified by response to platinum-based therapy using the ROC plot online platform ( https://rocplot.com/ ). n Protein expression levels of USP18 in ovarian cancer cell lines. o Cisplatin IC 50 values in ovarian cancer cell lines. p Pearson correlation analysis between USP18 protein levels (n) and cisplatin IC 50 (o). Data presented as mean ± SD. Significance calculated by unpaired two-tailed t -test (c). ∗∗P < 0.01; ∗∗∗∗P < 0.0001.

Journal: Redox Biology

Article Title: Redox-triggered USP18 confers cisplatin resistance in ovarian cancer by selectively activating a non-canonical FSP1-dependent ferroptosis escape pathway

doi: 10.1016/j.redox.2026.104179

Figure Lengend Snippet: USP18 Acts as a Key ROS-Responsive Mediator Driving Cisplatin Resistance in Ovarian Cancer. a Mechanisms and incidence of platinum resistance in ovarian cancer (Icons created with BioRender.com ). b Representative images of ROS detection using DCFH-DA probe in cisplatin-resistant and parental SKOV3 cells. Scale bar: 50 μm; GSEA analysis of ROS response genes based on transcriptome sequencing data in cisplatin-resistant and parental SKOV3 cells. c Representative images of ROS detection using DCFH-DA probe in SKOV3 cells treated with vehicle control, cisplatin (20 μM), or cisplatin plus NAC (10 μM) + mito-TEMPO (10 μM). Scale bar: 50 μm; Cell proliferation curves by Real-time cell analysis (RTCA) system (bottom left); LDH release assay in SKOV3 cells treated with cisplatin (20 μM) or cisplatin plus NAC (10 μM) + mito-TEMPO (10 μM) (bottom right). d Representative Immunohistochemistry (IHC) images showing pyroptosis (Cleaved-Caspase-1), apoptosis (Cleaved-Caspase-3), ferroptosis (GPX4), necroptosis (p-MLKL), and autophagy (p62) markers in cisplatin-resistant ovarian cancer PDX model (OV9419) tissues. Scale bar: 100 μm. e Protein expression levels of various cell death markers in OVCAR-3 cells treated with vehicle control, cisplatin (20 μM), or cisplatin plus NAC (10 μM) + mito-TEMPO (10 μM): pyroptosis (Cleaved-Caspase-1), apoptosis (Cleaved-Caspase-3), ferroptosis (GPX4), necroptosis (p-MLKL), and autophagy (LC3 II/LC3 I). f Schematic of DUB screening for cisplatin resistance: DUB plasmid library transfected into A2780 cells, treated with cisplatin (10 μM) after 24h, and cell viability measured by CCK8 after another 48h. Scatter plot shows relative cell viability compared to control. g Protein expression levels of USP18, USP37, and USP39 in parental and cisplatin-resistant SKOV3 cells. h Protein expression levels of USP18, USP37, and USP39 in OVCAR-3 cells treated with vehicle control, cisplatin (20 μM), or cisplatin (20 μM) plus NAC (10 μM) + mito-TEMPO (10 μM). i Protein expression levels of USP18, USP37, and USP39 in tissues from cisplatin-sensitive (n = 4) and -resistant (n = 4) ovarian cancer patients. j Analysis of USP18 expression in ovarian cancer versus normal ovarian tissues using data from The Cancer Genome Atlas (TCGA) ( www.aclbi.com ) k Survival analysis of patients with differential USP18 using data from TCGA. Analysis was performed via the KM-plotter platform ( https://kmplot.com/ ). l Representative IHC staining of USP18 shows its expression patterns in ovarian cancer tissues compared with paired adjacent tissues, and in therapy-sensitive versus resistant cases. Scale bar: 100 μm. Patients were stratified into high and low USP18 expression groups based on the median IHC score, and the distribution was compared using the Chi-squared test. m Analysis of USP18 expression in ovarian cancer patients stratified by response to platinum-based therapy using the ROC plot online platform ( https://rocplot.com/ ). n Protein expression levels of USP18 in ovarian cancer cell lines. o Cisplatin IC 50 values in ovarian cancer cell lines. p Pearson correlation analysis between USP18 protein levels (n) and cisplatin IC 50 (o). Data presented as mean ± SD. Significance calculated by unpaired two-tailed t -test (c). ∗∗P < 0.01; ∗∗∗∗P < 0.0001.

Article Snippet: All sequencing procedures were performed by Annoroad Gene Tech. (Beijing) Co., Ltd.

Techniques: Sequencing, Control, Cell Analysis, Lactate Dehydrogenase Assay, Immunohistochemistry, Expressing, Plasmid Preparation, Transfection, Two Tailed Test

Elevated ROS levels upregulate c-JUN expression, which transcriptionally activates downstream USP18 in cisplatin-resistant ovarian cancer cells. a GSEA analysis of hallmark ROS pathway genes from transcriptome sequencing in OVCAR-3 cells overexpressing USP18 plasmid and vector. b Heatmap of transcriptome sequencing expression values for ROS pathway-related genes in A2780 cells overexpressing USP18 plasmid and vector. c Differentially expressed genes in OVCAR-3 cells treated with sodium arsenite (NaAsO2, 0.5 mM) versus vehicle control. d Differentially expressed genes in SKOV3 cells treated with cisplatin (20 μM) vs vehicle control. e Venn diagram of ROS pathway-related upregulated transcription factors identified from transcriptome sequencing data in c and d. f Analysis of JUN expression in ovarian cancer patients stratified by response to platinum-based therapy using the ROC plot online platform. g Survival analysis of patients with differential JUN expression using data from TCGA. Analysis was performed via the KM-plotter platform. h Protein expression levels of c-JUN and USP18 in OVCAR-3 cells treated with vehicle control, cisplatin (20 μM), or cisplatin (20 μM) plus NAC (10 μM) + mito-TEMPO (10 μM). i Protein expression levels of c-JUN and USP18 in OVCAR-3 cells treated with vehicle control, NaAsO2 (0.5 mM), or NaAsO2(0.5 mM) plus NAC (10 μM) + mito-TEMPO (10 μM). j Cell viability measured by CCK8 assay in OVCAR-3 and A2780 cells overexpressing USP18 and treated with cisplatin (10 μM) plus NAC (10 μM) + mito-TEMPO (10 μM) k RT-qPCR analysis of USP18 mRNA expression levels in OVCAR-3 cells treated with vehicle control, cisplatin (10 μM), or cisplatin combined with c-JUN knockdown. l Schematic of predicted c-JUN binding sites in the USP18 promoter region ( https://jaspar.elixir.no/ ). m ChIP assay in CAOV3 cells validating c-JUN binding to USP18. n-p Dual-luciferase reporter assay confirming c-JUN binding and transcriptional regulation of USP18. n Schematic diagram of the dual-luciferase reporter assay. o Overexpression of c-JUN activates the USP18 promoter. OVCAR-3/CAOV3 cells were co-transfected with the USP18 promoter reporter construct and a c-JUN expression plasmid (or empty vector control). p OVCAR-3 cells transfected with the USP18 promoter reporter were treated with vehicle control, cisplatin (10 μM), or cisplatin (10 μM) combined with c-JUN knockdown (sic-JUN). Data presented as mean ± SD. Significance calculated by unpaired two-tailed t -test (j, k, m, o, p). ∗P < 0.05; ∗∗P < 0.01; ∗∗∗P < 0.001; ∗∗∗∗P < 0.0001.

Journal: Redox Biology

Article Title: Redox-triggered USP18 confers cisplatin resistance in ovarian cancer by selectively activating a non-canonical FSP1-dependent ferroptosis escape pathway

doi: 10.1016/j.redox.2026.104179

Figure Lengend Snippet: Elevated ROS levels upregulate c-JUN expression, which transcriptionally activates downstream USP18 in cisplatin-resistant ovarian cancer cells. a GSEA analysis of hallmark ROS pathway genes from transcriptome sequencing in OVCAR-3 cells overexpressing USP18 plasmid and vector. b Heatmap of transcriptome sequencing expression values for ROS pathway-related genes in A2780 cells overexpressing USP18 plasmid and vector. c Differentially expressed genes in OVCAR-3 cells treated with sodium arsenite (NaAsO2, 0.5 mM) versus vehicle control. d Differentially expressed genes in SKOV3 cells treated with cisplatin (20 μM) vs vehicle control. e Venn diagram of ROS pathway-related upregulated transcription factors identified from transcriptome sequencing data in c and d. f Analysis of JUN expression in ovarian cancer patients stratified by response to platinum-based therapy using the ROC plot online platform. g Survival analysis of patients with differential JUN expression using data from TCGA. Analysis was performed via the KM-plotter platform. h Protein expression levels of c-JUN and USP18 in OVCAR-3 cells treated with vehicle control, cisplatin (20 μM), or cisplatin (20 μM) plus NAC (10 μM) + mito-TEMPO (10 μM). i Protein expression levels of c-JUN and USP18 in OVCAR-3 cells treated with vehicle control, NaAsO2 (0.5 mM), or NaAsO2(0.5 mM) plus NAC (10 μM) + mito-TEMPO (10 μM). j Cell viability measured by CCK8 assay in OVCAR-3 and A2780 cells overexpressing USP18 and treated with cisplatin (10 μM) plus NAC (10 μM) + mito-TEMPO (10 μM) k RT-qPCR analysis of USP18 mRNA expression levels in OVCAR-3 cells treated with vehicle control, cisplatin (10 μM), or cisplatin combined with c-JUN knockdown. l Schematic of predicted c-JUN binding sites in the USP18 promoter region ( https://jaspar.elixir.no/ ). m ChIP assay in CAOV3 cells validating c-JUN binding to USP18. n-p Dual-luciferase reporter assay confirming c-JUN binding and transcriptional regulation of USP18. n Schematic diagram of the dual-luciferase reporter assay. o Overexpression of c-JUN activates the USP18 promoter. OVCAR-3/CAOV3 cells were co-transfected with the USP18 promoter reporter construct and a c-JUN expression plasmid (or empty vector control). p OVCAR-3 cells transfected with the USP18 promoter reporter were treated with vehicle control, cisplatin (10 μM), or cisplatin (10 μM) combined with c-JUN knockdown (sic-JUN). Data presented as mean ± SD. Significance calculated by unpaired two-tailed t -test (j, k, m, o, p). ∗P < 0.05; ∗∗P < 0.01; ∗∗∗P < 0.001; ∗∗∗∗P < 0.0001.

Article Snippet: All sequencing procedures were performed by Annoroad Gene Tech. (Beijing) Co., Ltd.

Techniques: Expressing, Sequencing, Plasmid Preparation, Control, CCK-8 Assay, Quantitative RT-PCR, Knockdown, Binding Assay, Luciferase, Reporter Assay, Over Expression, Transfection, Construct, Two Tailed Test

CD32b distinguishes transcriptionally and functionally distinct GM-DC subsets derived from MDPs and GMPs. (A) Principal component analysis (PCA) of bulk RNA-seq data from GM-DCs sorted on day 7 and day 21. DCs were generated from cultures of whole bone marrow (BM), sorted MDPs, or sorted GMPs with GM-CSF. (B) Heatmap showing the expression of genes upregulated and downregulated in MDP GM-DCs at day 7, identified through Venn diagram analysis and mapped onto BM GM-DCs at both time points. (C) Volcano plot of differentially expressed genes (DEGs) between MDP GM-DCs (day 7) and GMP GM-DCs (day 21). The thresholds for significance (dotted lines) are set at a log 2 (fold change) ≥ 3 or raw p -value ≤ 10 -16 . (D) Flow cytometric validation of selected surface marker candidates identified in the volcano plot (C) . Normalized Mean fluorescence intensity (MFI) of four representative markers is shown for each DC subset. Normalized MFI was calculated by subtracting the isotype control mean fluorescence from the sample mean fluorescence, and then dividing the result by the isotype control mean. Representative histograms are shown below the bar graphs, with the isotype control overlaid in gray. Data are representative of two independent experiments.

Journal: Frontiers in Immunology

Article Title: CD32b defines distinct dendritic cell lineages generated from the culture of bone marrow with GM-CSF

doi: 10.3389/fimmu.2026.1703978

Figure Lengend Snippet: CD32b distinguishes transcriptionally and functionally distinct GM-DC subsets derived from MDPs and GMPs. (A) Principal component analysis (PCA) of bulk RNA-seq data from GM-DCs sorted on day 7 and day 21. DCs were generated from cultures of whole bone marrow (BM), sorted MDPs, or sorted GMPs with GM-CSF. (B) Heatmap showing the expression of genes upregulated and downregulated in MDP GM-DCs at day 7, identified through Venn diagram analysis and mapped onto BM GM-DCs at both time points. (C) Volcano plot of differentially expressed genes (DEGs) between MDP GM-DCs (day 7) and GMP GM-DCs (day 21). The thresholds for significance (dotted lines) are set at a log 2 (fold change) ≥ 3 or raw p -value ≤ 10 -16 . (D) Flow cytometric validation of selected surface marker candidates identified in the volcano plot (C) . Normalized Mean fluorescence intensity (MFI) of four representative markers is shown for each DC subset. Normalized MFI was calculated by subtracting the isotype control mean fluorescence from the sample mean fluorescence, and then dividing the result by the isotype control mean. Representative histograms are shown below the bar graphs, with the isotype control overlaid in gray. Data are representative of two independent experiments.

Article Snippet: RNA sequencing (RNA-seq) procedure and analysis were performed by Macrogen (Seoul, Korea).

Techniques: Derivative Assay, RNA Sequencing, Generated, Expressing, Biomarker Discovery, Marker, Fluorescence, Control