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96
Proteintech nox4
Nox4, supplied by Proteintech, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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ABclonal Biotechnology primary antibodies against nox4
Alterations in oxidative stress and apoptosis-related markers following α-pinene treatment in the in vitro mTBI model. ( A ) mRNA expressions of <t>NOX4</t> and p22phox. ( B ) Representative Western blot images and quantitative analyses of Bax and Bcl-2 protein expression normalized to β -actin as well as protein expression of the Bax/Bcl-2 ratio. ( C ) Representative immunofluorescence image and quantitative analyses of NOX4 expression in neuronal cells following α-pinene treatment. Scale bar: 500 μm, *** p < 0.005 and **** p < 0.001. Data represent mean ± standard error of the mean (SEM).
Primary Antibodies Against Nox4, supplied by ABclonal Biotechnology, used in various techniques. Bioz Stars score: 95/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Wanleibio anti nox4
Alterations in oxidative stress and apoptosis-related markers following α-pinene treatment in the in vitro mTBI model. ( A ) mRNA expressions of <t>NOX4</t> and p22phox. ( B ) Representative Western blot images and quantitative analyses of Bax and Bcl-2 protein expression normalized to β -actin as well as protein expression of the Bax/Bcl-2 ratio. ( C ) Representative immunofluorescence image and quantitative analyses of NOX4 expression in neuronal cells following α-pinene treatment. Scale bar: 500 μm, *** p < 0.005 and **** p < 0.001. Data represent mean ± standard error of the mean (SEM).
Anti Nox4, supplied by Wanleibio, 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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ABclonal Biotechnology rabbit anti nadph oxidase 4 nox4
TD139 rescues PV interneurons from LPS-induced oxidative injury. For immunofluorescence analyses, bar graphs summarize pooled data from the dorsal and ventral hippocampus. A Quantitative analysis of MDA content in hippocampus ( n = 5 / group). B Quantitative analysis of T-AOC content in hippocampus ( n = 5 / group). C Western blot analysis of PV and <t>NOX4</t> ( n = 6 / group). D epresentative immunofluorescence images and quantification of interactions between PV interneurons and microglia in the vCA1 region. Analyses include the relative soma distance between PV + and Iba-1 + cells, and the number of microglia surrounding PV + cells ( n = 4 /group with 4 slices / mouse). Scale bar = 50 μm and 10 μm, respectively. E , F Representative immunofluorescence images and quantification of 8-OH-dG and γH2AX within PV-interneurons in the vCA1 region ( N = 4 of the Saline + Vehicle and the Saline + TD139 groups, n = 6 of the LPS + Vehicle, and n = 5 of the LPS + TD139 groups). Scale bar = 50 μm. Data are presented as the mean ± SEM. Statistical analysis was performed using two-way ANOVA with Tukey’s post hoc test. * P < 0.05, ** P < 0.01, *** P < 0.001
Rabbit Anti Nadph Oxidase 4 Nox4, supplied by ABclonal Biotechnology, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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ABclonal Biotechnology rabbit anti nox4
TD139 rescues PV interneurons from LPS-induced oxidative injury. For immunofluorescence analyses, bar graphs summarize pooled data from the dorsal and ventral hippocampus. A Quantitative analysis of MDA content in hippocampus ( n = 5 / group). B Quantitative analysis of T-AOC content in hippocampus ( n = 5 / group). C Western blot analysis of PV and <t>NOX4</t> ( n = 6 / group). D epresentative immunofluorescence images and quantification of interactions between PV interneurons and microglia in the vCA1 region. Analyses include the relative soma distance between PV + and Iba-1 + cells, and the number of microglia surrounding PV + cells ( n = 4 /group with 4 slices / mouse). Scale bar = 50 μm and 10 μm, respectively. E , F Representative immunofluorescence images and quantification of 8-OH-dG and γH2AX within PV-interneurons in the vCA1 region ( N = 4 of the Saline + Vehicle and the Saline + TD139 groups, n = 6 of the LPS + Vehicle, and n = 5 of the LPS + TD139 groups). Scale bar = 50 μm. Data are presented as the mean ± SEM. Statistical analysis was performed using two-way ANOVA with Tukey’s post hoc test. * P < 0.05, ** P < 0.01, *** P < 0.001
Rabbit Anti Nox4, supplied by ABclonal Biotechnology, used in various techniques. Bioz Stars score: 95/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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ABclonal Biotechnology antibodies against nox4
Development, validation, and experimental verification of a senescence- and circadian rhythm-related prognostic risk model in CRC. (A) Forest plot of univariate Cox proportional hazards regression analysis showing the associations between <t>NOX4,</t> CXCL1, CDKN2A, and SIX1 expression and overall survival in the training cohort. (B) Kaplan-Meier survival curves comparing overall survival between the high-SCore group (HSG) and low-SCore group (LSG) in the training cohort. (C) Time-dependent receiver operating characteristic (ROC) curves evaluating the predictive performance of the risk model in the training cohort, with area under the curve (AUC) values shown for 1-, 2-, and 3-year overall survival. (D) Kaplan-Meier survival curves comparing overall survival between the HSG and LSG in the external validation cohort GSE12945 . (E) Time-dependent ROC curves assessing the predictive accuracy of the prognostic model in GSE12945 , with AUC values shown for 1-, 2-, and 3-year overall survival. (F, G) Relative mRNA expression levels of the four prognostic genes in the normal colon epithelial cell line NCM460 and CRC cell lines DLD1, SW480, HCT15, HT29, and RKO, as measured by reverse transcription-quantitative PCR (RT-qPCR): NOX4 (F) , CXCL1 (G) . (H, I) Quantitative immunohistochemical validation of NOX4 and CXCL1 expression in the SYSUCC-CRC tissue microarray. IHC scores were significantly higher in colorectal cancer tissues than in paired adjacent non-tumor tissues (n = 120). (J) Spearman correlation heatmap among prognostic genes. The heatmap displays pairwise expression correlations among the four prognostic genes (CXCL1, CDKN2A, NOX4, SIX1). Color gradient represents the magnitude of Spearman correlation coefficients, with red indicating positive correlation and blue indicating negative correlation. Numerical values within cells indicate correlation coefficients. Significance annotation: *P < 0.05, **P < 0.01, ***P < 0.001. All P values were adjusted by the Benjamini−Hochberg (BH) method for multiple testing. (K) Spearman correlation heatmap between prognostic gene expression and pathway activity. The heatmap displays correlations between the expression levels of the four prognostic genes and the GSVA activity scores of the oxidative stress and SASP inflammatory response pathways. Color gradient represents the magnitude of Spearman correlation coefficients, with red indicating positive correlation and blue indicating negative correlation. Numerical values within cells indicate correlation coefficients. Significance annotation: *P < 0.05, **P < 0.01, ***P < 0.001. All P values were adjusted by the BH method for multiple testing.
Antibodies Against Nox4, supplied by ABclonal Biotechnology, used in various techniques. Bioz Stars score: 95/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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ABclonal Biotechnology anti nox4
Development, validation, and experimental verification of a senescence- and circadian rhythm-related prognostic risk model in CRC. (A) Forest plot of univariate Cox proportional hazards regression analysis showing the associations between <t>NOX4,</t> CXCL1, CDKN2A, and SIX1 expression and overall survival in the training cohort. (B) Kaplan-Meier survival curves comparing overall survival between the high-SCore group (HSG) and low-SCore group (LSG) in the training cohort. (C) Time-dependent receiver operating characteristic (ROC) curves evaluating the predictive performance of the risk model in the training cohort, with area under the curve (AUC) values shown for 1-, 2-, and 3-year overall survival. (D) Kaplan-Meier survival curves comparing overall survival between the HSG and LSG in the external validation cohort GSE12945 . (E) Time-dependent ROC curves assessing the predictive accuracy of the prognostic model in GSE12945 , with AUC values shown for 1-, 2-, and 3-year overall survival. (F, G) Relative mRNA expression levels of the four prognostic genes in the normal colon epithelial cell line NCM460 and CRC cell lines DLD1, SW480, HCT15, HT29, and RKO, as measured by reverse transcription-quantitative PCR (RT-qPCR): NOX4 (F) , CXCL1 (G) . (H, I) Quantitative immunohistochemical validation of NOX4 and CXCL1 expression in the SYSUCC-CRC tissue microarray. IHC scores were significantly higher in colorectal cancer tissues than in paired adjacent non-tumor tissues (n = 120). (J) Spearman correlation heatmap among prognostic genes. The heatmap displays pairwise expression correlations among the four prognostic genes (CXCL1, CDKN2A, NOX4, SIX1). Color gradient represents the magnitude of Spearman correlation coefficients, with red indicating positive correlation and blue indicating negative correlation. Numerical values within cells indicate correlation coefficients. Significance annotation: *P < 0.05, **P < 0.01, ***P < 0.001. All P values were adjusted by the Benjamini−Hochberg (BH) method for multiple testing. (K) Spearman correlation heatmap between prognostic gene expression and pathway activity. The heatmap displays correlations between the expression levels of the four prognostic genes and the GSVA activity scores of the oxidative stress and SASP inflammatory response pathways. Color gradient represents the magnitude of Spearman correlation coefficients, with red indicating positive correlation and blue indicating negative correlation. Numerical values within cells indicate correlation coefficients. Significance annotation: *P < 0.05, **P < 0.01, ***P < 0.001. All P values were adjusted by the BH method for multiple testing.
Anti Nox4, supplied by ABclonal Biotechnology, used in various techniques. Bioz Stars score: 95/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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ABclonal Biotechnology nox4
Ipriflavone ameliorated hypoxia‐induced ferroptosis by inhibiting HIF‐α‐triggered PUFA‐PLs, <t>NOX4,</t> and ALOX5 in NGEC and HIEC. Under hypoxia (1% O 2 ), HIEC was incubated for 24 h and then treated with ipriflavone (10 µM) for another 24 h. In experiments with siRNA targeting HIF‐α , HIEC was transfected with siNC, siHIF‐1α, or siHIF‐2α under normoxia for 24 h and then subjected to hypoxia (1% O 2 ) for 48 h. (A) Volcano plots showing the changes in PUFA‐PLs and SFA/MUFA‐PLs, including PC, PE, and PI, between the indicated groups ( n = 3). The blue boxes indicate the PUFA‐PC and PUFA‐PE with consistent changes after ipriflavone treatment and HIF‐α ( HIF‐1α or HIF‐2α ) knockdown under hypoxia. NGEC and HIEC were transfected with a control vector or HIF‐1α or HIF‐2α plasmid under normoxia for 24 h, followed by hypoxia (1% O 2 ) for 24 h. The cells were then treated with DMSO or ipriflavone (10 µM) under hypoxia for another 24 h. (B) HIF‐1α, HIF‐2α, NOX4, and ALOX5 levels were assessed by Western blot. NGEC and HIEC were transfected with either a blank control vector or plasmids containing HIF‐1α or HIF‐2α under normoxic conditions for 24 h, followed by exposure to hypoxia (1% O 2 ) for 24 h. The cells were then treated with DMSO, zileuton (an ALOX5 inhibitor, 10 µM), or GLX351322 (a NOX4 inhibitor, 10 µM) for an additional 24 h under hypoxic conditions. (C) 4‐HNE levels ( n = 4) were then assessed using an enzyme‐linked immunosorbent assay (ELISA). NGEC and HIEC were transfected with a blank control vector or plasmids encoding NOX4 or ALOX5 for 24 h under normoxia, prior to a 24‐h exposure to hypoxia (1% O 2 ). Following this, the cells were incubated with DMSO or ipriflavone (10 µM) for an additional 24 h under hypoxia. (D) 4‐HNE levels ( n = 4) by ELISA. Representative replicates of three independent experiments are shown in B–D. One‐way ANOVA: hypoxia + NOX4, hypoxia + ALOX5, or hypoxia + NOX4 + ALOX5 versus hypoxia control, a p < 0.05 or less, and hypoxia + NOX4 + ipriflavone, hypoxia + ALOX5 + ipriflavone, or hypoxia + NOX4 + ALOX5 + ipriflavone versus hypoxia + ipriflavone, b p < 0.0001 (in D). * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001; ns, not significant. MUFAs, monounsaturated fatty acids; PCs, phosphatidylcholines; PEs, phosphatidylethanolamines; PIs, phosphatidylinositols; PLs, phospholipids; PUFAs, polyunsaturated fatty acids; SFAs, saturated fatty acids.
Nox4, supplied by ABclonal Biotechnology, used in various techniques. Bioz Stars score: 95/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Huabio Inc anti nox4 antibody
Ipriflavone ameliorated hypoxia‐induced ferroptosis by inhibiting HIF‐α‐triggered PUFA‐PLs, <t>NOX4,</t> and ALOX5 in NGEC and HIEC. Under hypoxia (1% O 2 ), HIEC was incubated for 24 h and then treated with ipriflavone (10 µM) for another 24 h. In experiments with siRNA targeting HIF‐α , HIEC was transfected with siNC, siHIF‐1α, or siHIF‐2α under normoxia for 24 h and then subjected to hypoxia (1% O 2 ) for 48 h. (A) Volcano plots showing the changes in PUFA‐PLs and SFA/MUFA‐PLs, including PC, PE, and PI, between the indicated groups ( n = 3). The blue boxes indicate the PUFA‐PC and PUFA‐PE with consistent changes after ipriflavone treatment and HIF‐α ( HIF‐1α or HIF‐2α ) knockdown under hypoxia. NGEC and HIEC were transfected with a control vector or HIF‐1α or HIF‐2α plasmid under normoxia for 24 h, followed by hypoxia (1% O 2 ) for 24 h. The cells were then treated with DMSO or ipriflavone (10 µM) under hypoxia for another 24 h. (B) HIF‐1α, HIF‐2α, NOX4, and ALOX5 levels were assessed by Western blot. NGEC and HIEC were transfected with either a blank control vector or plasmids containing HIF‐1α or HIF‐2α under normoxic conditions for 24 h, followed by exposure to hypoxia (1% O 2 ) for 24 h. The cells were then treated with DMSO, zileuton (an ALOX5 inhibitor, 10 µM), or GLX351322 (a NOX4 inhibitor, 10 µM) for an additional 24 h under hypoxic conditions. (C) 4‐HNE levels ( n = 4) were then assessed using an enzyme‐linked immunosorbent assay (ELISA). NGEC and HIEC were transfected with a blank control vector or plasmids encoding NOX4 or ALOX5 for 24 h under normoxia, prior to a 24‐h exposure to hypoxia (1% O 2 ). Following this, the cells were incubated with DMSO or ipriflavone (10 µM) for an additional 24 h under hypoxia. (D) 4‐HNE levels ( n = 4) by ELISA. Representative replicates of three independent experiments are shown in B–D. One‐way ANOVA: hypoxia + NOX4, hypoxia + ALOX5, or hypoxia + NOX4 + ALOX5 versus hypoxia control, a p < 0.05 or less, and hypoxia + NOX4 + ipriflavone, hypoxia + ALOX5 + ipriflavone, or hypoxia + NOX4 + ALOX5 + ipriflavone versus hypoxia + ipriflavone, b p < 0.0001 (in D). * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001; ns, not significant. MUFAs, monounsaturated fatty acids; PCs, phosphatidylcholines; PEs, phosphatidylethanolamines; PIs, phosphatidylinositols; PLs, phospholipids; PUFAs, polyunsaturated fatty acids; SFAs, saturated fatty acids.
Anti Nox4 Antibody, supplied by Huabio 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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Image Search Results


Alterations in oxidative stress and apoptosis-related markers following α-pinene treatment in the in vitro mTBI model. ( A ) mRNA expressions of NOX4 and p22phox. ( B ) Representative Western blot images and quantitative analyses of Bax and Bcl-2 protein expression normalized to β -actin as well as protein expression of the Bax/Bcl-2 ratio. ( C ) Representative immunofluorescence image and quantitative analyses of NOX4 expression in neuronal cells following α-pinene treatment. Scale bar: 500 μm, *** p < 0.005 and **** p < 0.001. Data represent mean ± standard error of the mean (SEM).

Journal: Life

Article Title: Therapeutic Effect of Alpha-Pinene on In Vitro and In Vivo Models of Mild Traumatic Brain Injury

doi: 10.3390/life16071110

Figure Lengend Snippet: Alterations in oxidative stress and apoptosis-related markers following α-pinene treatment in the in vitro mTBI model. ( A ) mRNA expressions of NOX4 and p22phox. ( B ) Representative Western blot images and quantitative analyses of Bax and Bcl-2 protein expression normalized to β -actin as well as protein expression of the Bax/Bcl-2 ratio. ( C ) Representative immunofluorescence image and quantitative analyses of NOX4 expression in neuronal cells following α-pinene treatment. Scale bar: 500 μm, *** p < 0.005 and **** p < 0.001. Data represent mean ± standard error of the mean (SEM).

Article Snippet: Primary antibodies against NOX4 (Abclonal, Woburn, MA, USA), Bax (Cell signaling Technology, Danvers, MA, USA), Bcl-2 (Cell signaling Technology, Danvers, MA, USA), and β-actin (Santa Cruz Biotechnology, Dallas, TX, USA) were diluted 1:1000 in 5% BSA buffer and applied to the membranes overnight at 4 °C.

Techniques: In Vitro, Western Blot, Expressing, Immunofluorescence

Glia activation and NOX4 expression following α-pinene treatment in the in vivo mTBI model. ( A – E ) Representative immunofluorescence staining and quantitative analysis of NOX4 expression in GFAP- or Iba-1-positive cells. ( F , G ) Representative Western blot analysis of NOX4 in the brain tissues and its quantification. Non-adjacent lanes from the same original membrane were spliced for presentation. Splice sites are indicated by thin dividing lines. * p < 0.05, ** p < 0.01, and *** p < 0.005. Data represent mean ± standard error of the mean (SEM).

Journal: Life

Article Title: Therapeutic Effect of Alpha-Pinene on In Vitro and In Vivo Models of Mild Traumatic Brain Injury

doi: 10.3390/life16071110

Figure Lengend Snippet: Glia activation and NOX4 expression following α-pinene treatment in the in vivo mTBI model. ( A – E ) Representative immunofluorescence staining and quantitative analysis of NOX4 expression in GFAP- or Iba-1-positive cells. ( F , G ) Representative Western blot analysis of NOX4 in the brain tissues and its quantification. Non-adjacent lanes from the same original membrane were spliced for presentation. Splice sites are indicated by thin dividing lines. * p < 0.05, ** p < 0.01, and *** p < 0.005. Data represent mean ± standard error of the mean (SEM).

Article Snippet: Primary antibodies against NOX4 (Abclonal, Woburn, MA, USA), Bax (Cell signaling Technology, Danvers, MA, USA), Bcl-2 (Cell signaling Technology, Danvers, MA, USA), and β-actin (Santa Cruz Biotechnology, Dallas, TX, USA) were diluted 1:1000 in 5% BSA buffer and applied to the membranes overnight at 4 °C.

Techniques: Activation Assay, Expressing, In Vivo, Immunofluorescence, Staining, Western Blot, Membrane

TD139 rescues PV interneurons from LPS-induced oxidative injury. For immunofluorescence analyses, bar graphs summarize pooled data from the dorsal and ventral hippocampus. A Quantitative analysis of MDA content in hippocampus ( n = 5 / group). B Quantitative analysis of T-AOC content in hippocampus ( n = 5 / group). C Western blot analysis of PV and NOX4 ( n = 6 / group). D epresentative immunofluorescence images and quantification of interactions between PV interneurons and microglia in the vCA1 region. Analyses include the relative soma distance between PV + and Iba-1 + cells, and the number of microglia surrounding PV + cells ( n = 4 /group with 4 slices / mouse). Scale bar = 50 μm and 10 μm, respectively. E , F Representative immunofluorescence images and quantification of 8-OH-dG and γH2AX within PV-interneurons in the vCA1 region ( N = 4 of the Saline + Vehicle and the Saline + TD139 groups, n = 6 of the LPS + Vehicle, and n = 5 of the LPS + TD139 groups). Scale bar = 50 μm. Data are presented as the mean ± SEM. Statistical analysis was performed using two-way ANOVA with Tukey’s post hoc test. * P < 0.05, ** P < 0.01, *** P < 0.001

Journal: Journal of Neuroinflammation

Article Title: Microglial galectin-3 disrupts parvalbumin interneurons and hippocampal synchrony, driving cognitive deficits

doi: 10.1186/s12974-026-03889-x

Figure Lengend Snippet: TD139 rescues PV interneurons from LPS-induced oxidative injury. For immunofluorescence analyses, bar graphs summarize pooled data from the dorsal and ventral hippocampus. A Quantitative analysis of MDA content in hippocampus ( n = 5 / group). B Quantitative analysis of T-AOC content in hippocampus ( n = 5 / group). C Western blot analysis of PV and NOX4 ( n = 6 / group). D epresentative immunofluorescence images and quantification of interactions between PV interneurons and microglia in the vCA1 region. Analyses include the relative soma distance between PV + and Iba-1 + cells, and the number of microglia surrounding PV + cells ( n = 4 /group with 4 slices / mouse). Scale bar = 50 μm and 10 μm, respectively. E , F Representative immunofluorescence images and quantification of 8-OH-dG and γH2AX within PV-interneurons in the vCA1 region ( N = 4 of the Saline + Vehicle and the Saline + TD139 groups, n = 6 of the LPS + Vehicle, and n = 5 of the LPS + TD139 groups). Scale bar = 50 μm. Data are presented as the mean ± SEM. Statistical analysis was performed using two-way ANOVA with Tukey’s post hoc test. * P < 0.05, ** P < 0.01, *** P < 0.001

Article Snippet: The blots were blocked in 5% non-fat milk in 1× TBS with 1% Tween-20 (TBST) for 1 h at room temperature (RT) and then incubated at 4 °C overnight with the following primary antibodies at a concentration of 1:1000: mouse anti-Gal3 (60207-1-Ig, Proteintech, Wuhan, China), rabbit anti-CD11 antigen-like family member B (CD11b) (ab184307, Abcam), rabbit anti-ionized calcium-binding adapter molecule 1 (Iba1) (016-20001, Wako, Osaka, Japan; 680023, Zenbio, Chengdu, China), rat anti-CD68 (MCA1957GA, Bio-rad, California, USA), rabbit anti-lysosomal associated membrane protein 1 (LAMP1) (ab208943, Abcam), mouse anti-NLRP3 (68102-1-Ig, Proteintech), mouse anti-absent in melanoma 2 (AIM2) (sc-293174, Santa Cruz Biotechnology, Texas, USA), rabbit anti-apoptosis-associated speck-like protein containing a CARD (ASC) (10500-1-AP, Proteintech), rabbit anti-Caspase-1 (24232, CST, Massachusetts, USA), rabbit anti-IL-1β (ab234437, Abcam), rabbit anti-TLR2 (DF7002, Affinity Biosciences, Cincinnati, USA), rabbit anti-IL-18 (57058, CST), rabbit anti-Caspase-11 ( R23724 , Zenbio), rabbit anti-IL-6 (500286, Zenbio), rabbit anti-TNFα (346654, Zenbio), rabbit anti-PV (ab181086, Abcam), rabbit anti-cathepsin B (CatB) (A0967, ABclonal, Wuhan, China). rabbit anti-cathepsin D (CatD) (ab75852, Abcam), rabbit anti-gasdermin D (GSDMD) (ab219800, Abcam), rabbit anti-NADPH oxidase 4 (NOX4) (1:1000, A22149, Abclonal), rabbit anti-βIII tubulin (R011968, Epizyme Biotech), rabbit anti-β actin (20536-1-AP, Proteintech; LF202, Epizyme Biotech), and mouse anti-GAPDH (60004-1-Ig, Proteintech).

Techniques: Immunofluorescence, Western Blot, Saline

Development, validation, and experimental verification of a senescence- and circadian rhythm-related prognostic risk model in CRC. (A) Forest plot of univariate Cox proportional hazards regression analysis showing the associations between NOX4, CXCL1, CDKN2A, and SIX1 expression and overall survival in the training cohort. (B) Kaplan-Meier survival curves comparing overall survival between the high-SCore group (HSG) and low-SCore group (LSG) in the training cohort. (C) Time-dependent receiver operating characteristic (ROC) curves evaluating the predictive performance of the risk model in the training cohort, with area under the curve (AUC) values shown for 1-, 2-, and 3-year overall survival. (D) Kaplan-Meier survival curves comparing overall survival between the HSG and LSG in the external validation cohort GSE12945 . (E) Time-dependent ROC curves assessing the predictive accuracy of the prognostic model in GSE12945 , with AUC values shown for 1-, 2-, and 3-year overall survival. (F, G) Relative mRNA expression levels of the four prognostic genes in the normal colon epithelial cell line NCM460 and CRC cell lines DLD1, SW480, HCT15, HT29, and RKO, as measured by reverse transcription-quantitative PCR (RT-qPCR): NOX4 (F) , CXCL1 (G) . (H, I) Quantitative immunohistochemical validation of NOX4 and CXCL1 expression in the SYSUCC-CRC tissue microarray. IHC scores were significantly higher in colorectal cancer tissues than in paired adjacent non-tumor tissues (n = 120). (J) Spearman correlation heatmap among prognostic genes. The heatmap displays pairwise expression correlations among the four prognostic genes (CXCL1, CDKN2A, NOX4, SIX1). Color gradient represents the magnitude of Spearman correlation coefficients, with red indicating positive correlation and blue indicating negative correlation. Numerical values within cells indicate correlation coefficients. Significance annotation: *P < 0.05, **P < 0.01, ***P < 0.001. All P values were adjusted by the Benjamini−Hochberg (BH) method for multiple testing. (K) Spearman correlation heatmap between prognostic gene expression and pathway activity. The heatmap displays correlations between the expression levels of the four prognostic genes and the GSVA activity scores of the oxidative stress and SASP inflammatory response pathways. Color gradient represents the magnitude of Spearman correlation coefficients, with red indicating positive correlation and blue indicating negative correlation. Numerical values within cells indicate correlation coefficients. Significance annotation: *P < 0.05, **P < 0.01, ***P < 0.001. All P values were adjusted by the BH method for multiple testing.

Journal: Frontiers in Immunology

Article Title: Senescence-circadian interplay stratifies patient prognosis and reveals immune remodeling heterogeneity in colorectal cancer

doi: 10.3389/fimmu.2026.1804974

Figure Lengend Snippet: Development, validation, and experimental verification of a senescence- and circadian rhythm-related prognostic risk model in CRC. (A) Forest plot of univariate Cox proportional hazards regression analysis showing the associations between NOX4, CXCL1, CDKN2A, and SIX1 expression and overall survival in the training cohort. (B) Kaplan-Meier survival curves comparing overall survival between the high-SCore group (HSG) and low-SCore group (LSG) in the training cohort. (C) Time-dependent receiver operating characteristic (ROC) curves evaluating the predictive performance of the risk model in the training cohort, with area under the curve (AUC) values shown for 1-, 2-, and 3-year overall survival. (D) Kaplan-Meier survival curves comparing overall survival between the HSG and LSG in the external validation cohort GSE12945 . (E) Time-dependent ROC curves assessing the predictive accuracy of the prognostic model in GSE12945 , with AUC values shown for 1-, 2-, and 3-year overall survival. (F, G) Relative mRNA expression levels of the four prognostic genes in the normal colon epithelial cell line NCM460 and CRC cell lines DLD1, SW480, HCT15, HT29, and RKO, as measured by reverse transcription-quantitative PCR (RT-qPCR): NOX4 (F) , CXCL1 (G) . (H, I) Quantitative immunohistochemical validation of NOX4 and CXCL1 expression in the SYSUCC-CRC tissue microarray. IHC scores were significantly higher in colorectal cancer tissues than in paired adjacent non-tumor tissues (n = 120). (J) Spearman correlation heatmap among prognostic genes. The heatmap displays pairwise expression correlations among the four prognostic genes (CXCL1, CDKN2A, NOX4, SIX1). Color gradient represents the magnitude of Spearman correlation coefficients, with red indicating positive correlation and blue indicating negative correlation. Numerical values within cells indicate correlation coefficients. Significance annotation: *P < 0.05, **P < 0.01, ***P < 0.001. All P values were adjusted by the Benjamini−Hochberg (BH) method for multiple testing. (K) Spearman correlation heatmap between prognostic gene expression and pathway activity. The heatmap displays correlations between the expression levels of the four prognostic genes and the GSVA activity scores of the oxidative stress and SASP inflammatory response pathways. Color gradient represents the magnitude of Spearman correlation coefficients, with red indicating positive correlation and blue indicating negative correlation. Numerical values within cells indicate correlation coefficients. Significance annotation: *P < 0.05, **P < 0.01, ***P < 0.001. All P values were adjusted by the BH method for multiple testing.

Article Snippet: The sections were then incubated overnight at 4 °C with primary antibodies against NOX4 (ABclonal, China, Cat# A11274), CDKN2A (Proteintech, China, Cat# 10883-1-AP), CXCL1 (Proteintech, China, Cat# 12335-1-AP), and SIX1 (Proteintech, China, Cat# 10709-1-AP).

Techniques: Biomarker Discovery, Expressing, Reverse Transcription, Real-time Polymerase Chain Reaction, Quantitative RT-PCR, Immunohistochemical staining, Microarray, Gene Expression, Activity Assay

Somatic mutation landscape and pathway enrichment analyses in high- and low-SCore CRC groups. (A) Oncoplot showing the somatic mutation landscape of CRC patients in the high-SCore group (HSG). Each column represents one patient and each row represents a gene; colors indicate mutation types. (B) Oncoplot depicting the somatic mutation profile of CRC patients in the low-SCore group (LSG). (C) Forest plot comparing mutation frequencies of differentially mutated genes between the HSG and LSG. (D) Distribution of consensus molecular subtypes (CMS1-CMS4) between the HSG and LSG. (E) Comparison of SCore distributions among CMS subtypes, *P < 0.05, **P < 0.01, ***P < 0.001, ns represents not significant. (F) Gene set enrichment analysis (GSEA) showing commonly enriched pathways in the HSG and LSG. (G-J) GSEA enrichment plots illustrating the top enriched pathways associated with NOX4 (G) , CXCL1 (H) , CDKN2A (I) , and SIX1 (J) .

Journal: Frontiers in Immunology

Article Title: Senescence-circadian interplay stratifies patient prognosis and reveals immune remodeling heterogeneity in colorectal cancer

doi: 10.3389/fimmu.2026.1804974

Figure Lengend Snippet: Somatic mutation landscape and pathway enrichment analyses in high- and low-SCore CRC groups. (A) Oncoplot showing the somatic mutation landscape of CRC patients in the high-SCore group (HSG). Each column represents one patient and each row represents a gene; colors indicate mutation types. (B) Oncoplot depicting the somatic mutation profile of CRC patients in the low-SCore group (LSG). (C) Forest plot comparing mutation frequencies of differentially mutated genes between the HSG and LSG. (D) Distribution of consensus molecular subtypes (CMS1-CMS4) between the HSG and LSG. (E) Comparison of SCore distributions among CMS subtypes, *P < 0.05, **P < 0.01, ***P < 0.001, ns represents not significant. (F) Gene set enrichment analysis (GSEA) showing commonly enriched pathways in the HSG and LSG. (G-J) GSEA enrichment plots illustrating the top enriched pathways associated with NOX4 (G) , CXCL1 (H) , CDKN2A (I) , and SIX1 (J) .

Article Snippet: The sections were then incubated overnight at 4 °C with primary antibodies against NOX4 (ABclonal, China, Cat# A11274), CDKN2A (Proteintech, China, Cat# 10883-1-AP), CXCL1 (Proteintech, China, Cat# 12335-1-AP), and SIX1 (Proteintech, China, Cat# 10709-1-AP).

Techniques: Mutagenesis, Comparison

Single-cell transcriptomic analysis in CRC. (A) Identification of highly variable genes (HVGs) in the GSE132465 single-cell dataset. (B) Principal component analysis (PCA) significance testing using JackStraw analysis. (C) PCA scree plot showing the variance explained by each principal component. (D) t-distributed stochastic neighbor embedding (t-SNE) plot showing clustering of single cells based on selected principal components. (E) Dot plot displaying canonical marker gene expression across the 12 clusters for cell type annotation. (F) Dot plot summarizing marker gene expression across annotated major cell types. (G) Annotated t-SNE diagram, with different colors representing different clusters. (H) Bar plot comparing the proportions of different cell types between CRC tumor and normal samples. (I) Violin plots showing expression levels of CDKN2A, CXCL1, NOX4, and SIX1 across major cell types in tumor and normal samples, *P < 0.05, **P < 0.01, ***P < 0.001, NS represents not significant.

Journal: Frontiers in Immunology

Article Title: Senescence-circadian interplay stratifies patient prognosis and reveals immune remodeling heterogeneity in colorectal cancer

doi: 10.3389/fimmu.2026.1804974

Figure Lengend Snippet: Single-cell transcriptomic analysis in CRC. (A) Identification of highly variable genes (HVGs) in the GSE132465 single-cell dataset. (B) Principal component analysis (PCA) significance testing using JackStraw analysis. (C) PCA scree plot showing the variance explained by each principal component. (D) t-distributed stochastic neighbor embedding (t-SNE) plot showing clustering of single cells based on selected principal components. (E) Dot plot displaying canonical marker gene expression across the 12 clusters for cell type annotation. (F) Dot plot summarizing marker gene expression across annotated major cell types. (G) Annotated t-SNE diagram, with different colors representing different clusters. (H) Bar plot comparing the proportions of different cell types between CRC tumor and normal samples. (I) Violin plots showing expression levels of CDKN2A, CXCL1, NOX4, and SIX1 across major cell types in tumor and normal samples, *P < 0.05, **P < 0.01, ***P < 0.001, NS represents not significant.

Article Snippet: The sections were then incubated overnight at 4 °C with primary antibodies against NOX4 (ABclonal, China, Cat# A11274), CDKN2A (Proteintech, China, Cat# 10883-1-AP), CXCL1 (Proteintech, China, Cat# 12335-1-AP), and SIX1 (Proteintech, China, Cat# 10709-1-AP).

Techniques: Single Cell, Marker, Gene Expression, Expressing

Cell-cell communication, pseudotime dynamics, and functional characteristics of T cells in CRC. (A, B) Global cell-cell communication networks inferred from ligand-receptor interactions in normal colorectal tissues (A) and CRC tumor tissues (B) . Node size indicates the number of interactions, and edge thickness reflects interaction strength. (C, D) T cell-centered communication networks in normal tissues (C) and CRC tumor tissues (D) . (E,3F) Bubble plots showing ligand-receptor interactions between T cells and other cell types in normal tissues (E) and CRC tumor tissues (F) . (G) Pseudotime trajectory analysis of T cells, depicting differentiation into 11 cellular states along pseudotime. (H) Heatmap showing dynamic expression patterns of prognostic genes (SIX1, NOX4, CDKN2A, and CXCL1) along the T-cell pseudotime trajectory. (I) Dot plot illustrating activity levels of multiple metabolic pathways across different cell types. (J) Integrated pathway enrichment analysis (irGSEA) across multiple algorithms for different cell types.

Journal: Frontiers in Immunology

Article Title: Senescence-circadian interplay stratifies patient prognosis and reveals immune remodeling heterogeneity in colorectal cancer

doi: 10.3389/fimmu.2026.1804974

Figure Lengend Snippet: Cell-cell communication, pseudotime dynamics, and functional characteristics of T cells in CRC. (A, B) Global cell-cell communication networks inferred from ligand-receptor interactions in normal colorectal tissues (A) and CRC tumor tissues (B) . Node size indicates the number of interactions, and edge thickness reflects interaction strength. (C, D) T cell-centered communication networks in normal tissues (C) and CRC tumor tissues (D) . (E,3F) Bubble plots showing ligand-receptor interactions between T cells and other cell types in normal tissues (E) and CRC tumor tissues (F) . (G) Pseudotime trajectory analysis of T cells, depicting differentiation into 11 cellular states along pseudotime. (H) Heatmap showing dynamic expression patterns of prognostic genes (SIX1, NOX4, CDKN2A, and CXCL1) along the T-cell pseudotime trajectory. (I) Dot plot illustrating activity levels of multiple metabolic pathways across different cell types. (J) Integrated pathway enrichment analysis (irGSEA) across multiple algorithms for different cell types.

Article Snippet: The sections were then incubated overnight at 4 °C with primary antibodies against NOX4 (ABclonal, China, Cat# A11274), CDKN2A (Proteintech, China, Cat# 10883-1-AP), CXCL1 (Proteintech, China, Cat# 12335-1-AP), and SIX1 (Proteintech, China, Cat# 10709-1-AP).

Techniques: Functional Assay, Expressing, Activity Assay

NOX4 knockdown attenuates inflammatory and immunoregulatory outputs, reduces intracellular ROS levels, and impairs migratory capacity in CRC cells. (A–D) Validation of NOX4 knockdown efficiency in SW480 and SW620 cells. (A, C) Relative NOX4 mRNA expression measured by qPCR. (B, D) Western blot analysis of NOX4 and PD-L1 protein levels. (E, F) Transcriptional changes in inflammatory and immunoregulatory genes following NOX4 knockdown. (E) SW480 cells; (F) SW620 cells. Genes analyzed include IL-6, CCL2, TGFB1, MIF, PD-L1, and PD-1. (G–L) Cytokine secretion in culture supernatants measured by ELISA after NOX4 knockdown. (G, H) IL-6; (I, J) TGF-β1; (K, L) MIF. (M, N) Relative intracellular reactive oxygen species (ROS) levels in SW480 and SW620 cells following NOX4 knockdown. (O, P) Quantification of ROS fluorescence intensity. (O) SW480 cells; (P) SW620 cells. (Q, R) Transwell migration assays showing reduced migratory capacity upon NOX4 knockdown. (Q) SW480 cells; (R) SW620 cells. ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

Journal: Frontiers in Immunology

Article Title: Senescence-circadian interplay stratifies patient prognosis and reveals immune remodeling heterogeneity in colorectal cancer

doi: 10.3389/fimmu.2026.1804974

Figure Lengend Snippet: NOX4 knockdown attenuates inflammatory and immunoregulatory outputs, reduces intracellular ROS levels, and impairs migratory capacity in CRC cells. (A–D) Validation of NOX4 knockdown efficiency in SW480 and SW620 cells. (A, C) Relative NOX4 mRNA expression measured by qPCR. (B, D) Western blot analysis of NOX4 and PD-L1 protein levels. (E, F) Transcriptional changes in inflammatory and immunoregulatory genes following NOX4 knockdown. (E) SW480 cells; (F) SW620 cells. Genes analyzed include IL-6, CCL2, TGFB1, MIF, PD-L1, and PD-1. (G–L) Cytokine secretion in culture supernatants measured by ELISA after NOX4 knockdown. (G, H) IL-6; (I, J) TGF-β1; (K, L) MIF. (M, N) Relative intracellular reactive oxygen species (ROS) levels in SW480 and SW620 cells following NOX4 knockdown. (O, P) Quantification of ROS fluorescence intensity. (O) SW480 cells; (P) SW620 cells. (Q, R) Transwell migration assays showing reduced migratory capacity upon NOX4 knockdown. (Q) SW480 cells; (R) SW620 cells. ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

Article Snippet: The sections were then incubated overnight at 4 °C with primary antibodies against NOX4 (ABclonal, China, Cat# A11274), CDKN2A (Proteintech, China, Cat# 10883-1-AP), CXCL1 (Proteintech, China, Cat# 12335-1-AP), and SIX1 (Proteintech, China, Cat# 10709-1-AP).

Techniques: Knockdown, Biomarker Discovery, Expressing, Western Blot, Enzyme-linked Immunosorbent Assay, Fluorescence, Migration

Ipriflavone ameliorated hypoxia‐induced ferroptosis by inhibiting HIF‐α‐triggered PUFA‐PLs, NOX4, and ALOX5 in NGEC and HIEC. Under hypoxia (1% O 2 ), HIEC was incubated for 24 h and then treated with ipriflavone (10 µM) for another 24 h. In experiments with siRNA targeting HIF‐α , HIEC was transfected with siNC, siHIF‐1α, or siHIF‐2α under normoxia for 24 h and then subjected to hypoxia (1% O 2 ) for 48 h. (A) Volcano plots showing the changes in PUFA‐PLs and SFA/MUFA‐PLs, including PC, PE, and PI, between the indicated groups ( n = 3). The blue boxes indicate the PUFA‐PC and PUFA‐PE with consistent changes after ipriflavone treatment and HIF‐α ( HIF‐1α or HIF‐2α ) knockdown under hypoxia. NGEC and HIEC were transfected with a control vector or HIF‐1α or HIF‐2α plasmid under normoxia for 24 h, followed by hypoxia (1% O 2 ) for 24 h. The cells were then treated with DMSO or ipriflavone (10 µM) under hypoxia for another 24 h. (B) HIF‐1α, HIF‐2α, NOX4, and ALOX5 levels were assessed by Western blot. NGEC and HIEC were transfected with either a blank control vector or plasmids containing HIF‐1α or HIF‐2α under normoxic conditions for 24 h, followed by exposure to hypoxia (1% O 2 ) for 24 h. The cells were then treated with DMSO, zileuton (an ALOX5 inhibitor, 10 µM), or GLX351322 (a NOX4 inhibitor, 10 µM) for an additional 24 h under hypoxic conditions. (C) 4‐HNE levels ( n = 4) were then assessed using an enzyme‐linked immunosorbent assay (ELISA). NGEC and HIEC were transfected with a blank control vector or plasmids encoding NOX4 or ALOX5 for 24 h under normoxia, prior to a 24‐h exposure to hypoxia (1% O 2 ). Following this, the cells were incubated with DMSO or ipriflavone (10 µM) for an additional 24 h under hypoxia. (D) 4‐HNE levels ( n = 4) by ELISA. Representative replicates of three independent experiments are shown in B–D. One‐way ANOVA: hypoxia + NOX4, hypoxia + ALOX5, or hypoxia + NOX4 + ALOX5 versus hypoxia control, a p < 0.05 or less, and hypoxia + NOX4 + ipriflavone, hypoxia + ALOX5 + ipriflavone, or hypoxia + NOX4 + ALOX5 + ipriflavone versus hypoxia + ipriflavone, b p < 0.0001 (in D). * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001; ns, not significant. MUFAs, monounsaturated fatty acids; PCs, phosphatidylcholines; PEs, phosphatidylethanolamines; PIs, phosphatidylinositols; PLs, phospholipids; PUFAs, polyunsaturated fatty acids; SFAs, saturated fatty acids.

Journal: MedComm

Article Title: Ipriflavone From Aquilaria malaccensis Lam. Exosome‐Like Nanoparticles Targets Prolyl Hydroxylase Domain Protein 2 (PHD2) to Enhance Hypoxia‐Inducible Factor‐α (HIF‐α) Hydroxylation Thereby Alleviating Hypoxia‐Induced Gastrointestinal Mucosal Ferroptosis

doi: 10.1002/mco2.70722

Figure Lengend Snippet: Ipriflavone ameliorated hypoxia‐induced ferroptosis by inhibiting HIF‐α‐triggered PUFA‐PLs, NOX4, and ALOX5 in NGEC and HIEC. Under hypoxia (1% O 2 ), HIEC was incubated for 24 h and then treated with ipriflavone (10 µM) for another 24 h. In experiments with siRNA targeting HIF‐α , HIEC was transfected with siNC, siHIF‐1α, or siHIF‐2α under normoxia for 24 h and then subjected to hypoxia (1% O 2 ) for 48 h. (A) Volcano plots showing the changes in PUFA‐PLs and SFA/MUFA‐PLs, including PC, PE, and PI, between the indicated groups ( n = 3). The blue boxes indicate the PUFA‐PC and PUFA‐PE with consistent changes after ipriflavone treatment and HIF‐α ( HIF‐1α or HIF‐2α ) knockdown under hypoxia. NGEC and HIEC were transfected with a control vector or HIF‐1α or HIF‐2α plasmid under normoxia for 24 h, followed by hypoxia (1% O 2 ) for 24 h. The cells were then treated with DMSO or ipriflavone (10 µM) under hypoxia for another 24 h. (B) HIF‐1α, HIF‐2α, NOX4, and ALOX5 levels were assessed by Western blot. NGEC and HIEC were transfected with either a blank control vector or plasmids containing HIF‐1α or HIF‐2α under normoxic conditions for 24 h, followed by exposure to hypoxia (1% O 2 ) for 24 h. The cells were then treated with DMSO, zileuton (an ALOX5 inhibitor, 10 µM), or GLX351322 (a NOX4 inhibitor, 10 µM) for an additional 24 h under hypoxic conditions. (C) 4‐HNE levels ( n = 4) were then assessed using an enzyme‐linked immunosorbent assay (ELISA). NGEC and HIEC were transfected with a blank control vector or plasmids encoding NOX4 or ALOX5 for 24 h under normoxia, prior to a 24‐h exposure to hypoxia (1% O 2 ). Following this, the cells were incubated with DMSO or ipriflavone (10 µM) for an additional 24 h under hypoxia. (D) 4‐HNE levels ( n = 4) by ELISA. Representative replicates of three independent experiments are shown in B–D. One‐way ANOVA: hypoxia + NOX4, hypoxia + ALOX5, or hypoxia + NOX4 + ALOX5 versus hypoxia control, a p < 0.05 or less, and hypoxia + NOX4 + ipriflavone, hypoxia + ALOX5 + ipriflavone, or hypoxia + NOX4 + ALOX5 + ipriflavone versus hypoxia + ipriflavone, b p < 0.0001 (in D). * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001; ns, not significant. MUFAs, monounsaturated fatty acids; PCs, phosphatidylcholines; PEs, phosphatidylethanolamines; PIs, phosphatidylinositols; PLs, phospholipids; PUFAs, polyunsaturated fatty acids; SFAs, saturated fatty acids.

Article Snippet: The membranes were incubated overnight at 4°C with the following primary antibodies at a dilution of 1:1000: HIF‐1α (ab179483; Abcam, Waltham, MA, USA), HIF‐2α (PA1‐16510; Invitrogen, Carlsbad, CA, USA), HIF‐1α (hydroxyl P564, ab308637; Abcam), PHD1 (ab113077; Abcam), PHD2 (ab226890; Abcam), PHD3 (ab184714; Abcam), SLC7A11 (ab307601; Abcam), GPX4 (ab125066; Abcam), AKT (ab8805; Abcam), P‐AKT (ab38449; Abcam), ERK (ab184699; Abcam), P‐ERK (ab201015; Abcam), IκBα (ab32518; Abcam), NOX4 (A22149; ABclonal, Wuhan, Hubei, China), ALOX5 (A2877; ABclonal), VHL (A21083; ABclonal), and GR (ab183127; Abcam).

Techniques: Incubation, Transfection, Knockdown, Control, Plasmid Preparation, Western Blot, Enzyme-linked Immunosorbent Assay

Oral ipriflavone attenuated hypoxia‐induced gastric and small intestinal mucosal ferroptosis in vivo. Mice were placed in a hypoxic chamber for 3 days ( n = 6 mice per group). The mice were given control solvents or ipriflavone (5, 10, or 15 mg/kg) intragastrically on Day 1 and euthanized on Day 3. Food intake (A), body weight (B), diarrheal severity scores (C), and fecal occult blood test scores (D) of the indicated groups ( n = 6). (E) Representative images of the gastrointestinal tract and gastric mucosa. (F) Representative H&E‐stained images of murine stomachs and small bowels (40×, scale bar: 500 µm) and corresponding histopathological scores ( n = 6). (G) Serum FITC concentrations of the indicated groups were used to evaluate gastrointestinal permeability ( n = 3). ROS and 4‐HNE levels in gastric (H) and small intestinal (I) mucosa ( n = 6). Protein levels of HIF‐1α, HIF‐2α, NOX4, and ALOX5 in the mucosa of the murine stomachs (J) and small bowels (K). Green or purple asterisks denote significant differences between ipriflavone treatment groups (10 or 15 mg/kg) and the control group subjected to hypoxia (A–D). The mice received 15 mg/kg of ipriflavone (E–K). Data are represented as mean ± SEM. One‐way ANOVA (F–I) and two‐way ANOVA (A–D): * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001; ns, not significant.

Journal: MedComm

Article Title: Ipriflavone From Aquilaria malaccensis Lam. Exosome‐Like Nanoparticles Targets Prolyl Hydroxylase Domain Protein 2 (PHD2) to Enhance Hypoxia‐Inducible Factor‐α (HIF‐α) Hydroxylation Thereby Alleviating Hypoxia‐Induced Gastrointestinal Mucosal Ferroptosis

doi: 10.1002/mco2.70722

Figure Lengend Snippet: Oral ipriflavone attenuated hypoxia‐induced gastric and small intestinal mucosal ferroptosis in vivo. Mice were placed in a hypoxic chamber for 3 days ( n = 6 mice per group). The mice were given control solvents or ipriflavone (5, 10, or 15 mg/kg) intragastrically on Day 1 and euthanized on Day 3. Food intake (A), body weight (B), diarrheal severity scores (C), and fecal occult blood test scores (D) of the indicated groups ( n = 6). (E) Representative images of the gastrointestinal tract and gastric mucosa. (F) Representative H&E‐stained images of murine stomachs and small bowels (40×, scale bar: 500 µm) and corresponding histopathological scores ( n = 6). (G) Serum FITC concentrations of the indicated groups were used to evaluate gastrointestinal permeability ( n = 3). ROS and 4‐HNE levels in gastric (H) and small intestinal (I) mucosa ( n = 6). Protein levels of HIF‐1α, HIF‐2α, NOX4, and ALOX5 in the mucosa of the murine stomachs (J) and small bowels (K). Green or purple asterisks denote significant differences between ipriflavone treatment groups (10 or 15 mg/kg) and the control group subjected to hypoxia (A–D). The mice received 15 mg/kg of ipriflavone (E–K). Data are represented as mean ± SEM. One‐way ANOVA (F–I) and two‐way ANOVA (A–D): * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001; ns, not significant.

Article Snippet: The membranes were incubated overnight at 4°C with the following primary antibodies at a dilution of 1:1000: HIF‐1α (ab179483; Abcam, Waltham, MA, USA), HIF‐2α (PA1‐16510; Invitrogen, Carlsbad, CA, USA), HIF‐1α (hydroxyl P564, ab308637; Abcam), PHD1 (ab113077; Abcam), PHD2 (ab226890; Abcam), PHD3 (ab184714; Abcam), SLC7A11 (ab307601; Abcam), GPX4 (ab125066; Abcam), AKT (ab8805; Abcam), P‐AKT (ab38449; Abcam), ERK (ab184699; Abcam), P‐ERK (ab201015; Abcam), IκBα (ab32518; Abcam), NOX4 (A22149; ABclonal, Wuhan, Hubei, China), ALOX5 (A2877; ABclonal), VHL (A21083; ABclonal), and GR (ab183127; Abcam).

Techniques: In Vivo, Control, Staining, Permeability