Journal: Bioactive Materials

Article Title: Smart microenvironment-adaptive nanocatalytic hydrogel for sequential antibacterial, anti-inflammatory, and regenerative therapy of biofilm-infected wounds

doi: 10.1016/j.bioactmat.2026.02.043

Figure Lengend Snippet: Characterization, and Cytocompatibility Validation of HCOC. (A) Schematic illustration of the development of HCOC. (B) FTIR spectrum of OSA, CMCS and OC hydrogel. (C) Time-dependent evolution of gelation of OC and HCOC. (D) SEM images of HCOC and EDS mapping images of C, N, O and Cu for HCOC. (E) FTIR spectra of HC, OC and HCOC. (F) Dynamic frequency sweep measurements of OC and HCOC. (G) Frequency-dependent viscoelastic behavior of OC and HCOC. (H) Alternating strain sweep with alternating strains of 1% and 1000% at 100s intervals and (I) Self-healing behavior of HCOC. (J) Live/dead staining showing the metabolic activity of L929 and RAW 264.7 cells after treatment with HCOC for 48 h. Rates of proliferation of (K) L929 cells and (L) RAW 264.7 cells after treatment with PBS or HCOC. (∗P < 0.05, ∗∗P < 0.01, ∗∗∗P < 0.001).

Article Snippet: Following the protocol of the DMAO/PI Bacterial Live/Dead Staining Kit (Beyotime Biotechnology), the bacteria were incubated with a working solution containing both DMAO and PI dyes in the dark at room temperature for 15-20 min. Fluorescence microscopy imaging was subsequently carried out.

Techniques: Biomarker Discovery, Staining, Activity Assay

Journal: Bioactive Materials

Article Title: Smart microenvironment-adaptive nanocatalytic hydrogel for sequential antibacterial, anti-inflammatory, and regenerative therapy of biofilm-infected wounds

doi: 10.1016/j.bioactmat.2026.02.043

Figure Lengend Snippet: pH Self-Adaptive Antioxidant Capacity of HCOC (Stage II: anti-inflammation). Cu ion release behavior of (A) HC (1 mg/mL) and (B) HCOC (1 mg/mL) at different pH levels. (C) ABTS + and (D) H 2 O 2 scavenging activity at different pH of Cu 5.4 O, HC and HCOC. (E) O 2 ∙ - , (F)∙OH scavenging activity of Cu 5.4 O, HAs, HC, HCOC. (G) SOD-like, (H) CAT-like and (I) GPx-like activities of HCOC. (J) Fluorescence images showing intracellular ROS detection by DCFH-DA staining, live/dead staining images and (K) cell viability of L929 cells with different treatments (All groups received 500 μM H 2 O 2 and different HCOC concentrations (I: PBS; II: 0; III: 0.25; IV: 0.50; V: 1.0 mg/mL HCOC). (L) Quantitative analysis of the cells under different treatments. (∗P < 0.05, ∗∗P < 0.01, ∗∗∗P < 0.001, ∗∗∗∗P < 0.0001) (M) Schematic illustration of pH-responsive activity and ROS scavenging and alleviating cellular oxidative stress of HCOC.

Article Snippet: Following the protocol of the DMAO/PI Bacterial Live/Dead Staining Kit (Beyotime Biotechnology), the bacteria were incubated with a working solution containing both DMAO and PI dyes in the dark at room temperature for 15-20 min. Fluorescence microscopy imaging was subsequently carried out.

Techniques: Activity Assay, Fluorescence, Staining

Journal: bioRxiv

Article Title: Targeting DNMT1 augments anti-tumor CD8⁺ T cell function

doi: 10.64898/2026.07.03.736412

Figure Lengend Snippet: (A) Timeline for tumor injection and drug treatments. Tumor cells were injected on d0. (B) Tumor growth in individual mice treated with DNMTi (RG108) alone, ICI (anti-CTLA4) alone, or dual therapy (ICI+DNMTi). (C) Overall survival of mice receiving ICI (anti-CTLA4), DNMT1i (RG108 or GSK32), or ICI+DNMT1i (RG108 or GSK32) (log-rank Mantel Cox test). (D) UMAP reduction of identified clusters from 4 treatment groups (DNMTi alone (RG108), ICI (anti-CTLA4) alone, dual therapy, and control) with 3 mice per condition and 2 tissues (tdLN and tumor) from each mouse. (E) UMAP reduction of total CD8+ T cells from tdLN from all 4 treatment groups. (F) Dot plot showing expression of key markers defining each CD8 cluster. (G) UMAP reduction of total CD8+ T cells from tdLN from all 4 treatment groups using Monocle3 for trajectory analysis and (H) trajectory analysis colored by pseudotime. (I) Pseudobulk quantification of the proportion of CD8⁺ T cells in the naïve-like cluster (left) and T PEX cluster (right) (n=3).

Article Snippet: On day 7, live CD8+ T cells were enriched using a dead-cell removal kit (Miltenyi) and added to tumor cells at a 1:10 T-cell:tumor ratio.

Techniques: Injection, Control, Expressing

Journal: bioRxiv

Article Title: Targeting DNMT1 augments anti-tumor CD8⁺ T cell function

doi: 10.64898/2026.07.03.736412

Figure Lengend Snippet: (A) Schematic of in vitro primary P14 CD8+ T cell culture model. (B) Schematic describing abbreviated nomenclature for in vitro cell states (T M , T EX , T EX+D , T M* , T EX* , T EX+D* ). (C) P14 CD8⁺ T cells were isolated on d7 of culture and restimulated with gp33 peptide for flow cytometry analysis of IFNγ and TNFα production (left) or co-cultured with gp33-expressing mouse melanoma line YUMM-G1-gp33 to assess tumor cell killing (right) by flow cytometry (n=3). (D) Chronic stimulation promotes proliferation of CD8+ T cells as shown by CellTrace Violet dilution (left) and quantified as proportion of cells in each generation (right) (n=3). (E-F) Violin plots showing differentially expressed genes between T EX+D and T EX (E) and between T EX+D* and T EX* (F) with RG108 (left) or with GSK32 (right). An adjusted p-value cutoff of 0.05 and log2FC cutoff of 0.5 were used. (G) UMAP depicting clusters obtained using PhenoGraph for concatenated samples (top left) and density plots for TEX* (top right), TEX+D* (GSK-32) (bottom left), and TEX+D* (RG108). (H) Proportion of live, CD45+ cells in MC4 (left) and MC14 (right) across samples. (I) Heatmap representing the relative expression of markers across clusters. (J) Schematic showing consensus nonnegative matrix factorization (cNMF) matrices. (K) Gene by program matrix from cNMF showing loadings for genes in the top 150 ranked gene list for each module. (L) Comparison of T EX vs T EX+D usage of Program S (left) and Program E1(right). (M) Comparison of T EX vs T EX+D usage of Program E2 (left) and Program E3 (right). (N) Comparison of T EX* vs T EX+D* usage of Program E1 (left) and Program E3 (right).

Article Snippet: On day 7, live CD8+ T cells were enriched using a dead-cell removal kit (Miltenyi) and added to tumor cells at a 1:10 T-cell:tumor ratio.

Techniques: In Vitro, Cell Culture, Isolation, Flow Cytometry, Expressing, Comparison

Journal: Neoplasia (New York, N.Y.)

Article Title: A MYC family switch: L-MYC drives and maintains neuroendocrine lineage programs in prostate cancer

doi: 10.1016/j.neo.2026.101307

Figure Lengend Snippet: MYCL reduces proliferation while promoting migration and cytoskeletal remodeling and decreasing cell adhesion in prostate cancer cells (A) Proliferation assay. Real-time Incucyte analysis showing cell proliferation of C4-2B control (Ctrl) and C4-2B-MYCL cells measured as confluence (%) over time. Quantification using area under the curve (AUC) demonstrates reduced proliferative capacity following MYCL overexpression. (B) Proliferation assay. Real-time Incucyte analysis showing cell proliferation of PC3 control (Ctrl) and PC3-MYCL cells measured as confluence (%) over time. Quantification using area under the curve (AUC) demonstrates reduced proliferative capacity following MYCL overexpression. (C) Left: Cell cycle analysis of C4-2B and PC3 cells following MYCL overexpression. In PC3 cells, MYCL reduces the G1 population and increases S-phase, indicating altered cell cycle progression, whereas changes in C4-2B cells are minimal. Right: Apoptosis analysis by Annexin V/7-AAD staining. MYCL overexpression in PC3 cells increases the early apoptotic population, with little or no significant change in C4-2B cells. (D) Cell adhesion assay. Cell adhesion was assessed by crystal violet staining and quantified by measuring absorbance at 595 nm at 18, 24, 48, and 72 h following seeding. MYCL-overexpressing C4-2B cells exhibited significantly decreased adhesion compared with control cells. Representative phase-contrast images acquired 48 h after seeding show reduced cell attachment and increased cell clustering in MYCL-expressing cells. (E) Molecular validation. RT-qPCR analysis of adhesion-related genes (ITGB1, ITGAV) in control (Ctrl) and MYCL-overexpressing C4-2B, LNCaP and PC3 cells. (F) Migration assay. Wound-healing analysis measuring relative wound density (%) over time demonstrates moderately enhanced migratory capacity in PC3-MYCL cells. AUC quantification confirms increased migration upon MYCL expression. (G) Cytoskeletal transcriptional programs. Heatmap showing differential expression of genes meeting thresholds of |log₂FC| ≥ 0.5 and adjusted p-value (FDR) < 0.05. Differentially regulated genes are associated with Ephrin-EPH signaling, Rho-Rac signaling, cytoskeletal organization, cell-cell junctions, extracellular matrix (ECM) interactions, and epithelial-mesenchymal transition (EMT) regulators, indicating MYCL-driven cytoskeletal remodeling signatures.

Article Snippet: For live-cell proliferation analysis, cells were seeded in 96-well plates and monitored using the IncuCyte® Live-Cell Analysis System (Sartorius).

Techniques: Migration, Proliferation Assay, Control, Over Expression, Cell Cycle Assay, Staining, Cell Adhesion Assay, Cell Attachment Assay, Expressing, Biomarker Discovery, Quantitative RT-PCR, Quantitative Proteomics

Journal: Neoplasia (New York, N.Y.)

Article Title: A MYC family switch: L-MYC drives and maintains neuroendocrine lineage programs in prostate cancer

doi: 10.1016/j.neo.2026.101307

Figure Lengend Snippet: MYCL reduces proliferation while promoting migration and cytoskeletal remodeling and decreasing cell adhesion in prostate cancer cells (A) Proliferation assay. Real-time Incucyte analysis showing cell proliferation of C4-2B control (Ctrl) and C4-2B-MYCL cells measured as confluence (%) over time. Quantification using area under the curve (AUC) demonstrates reduced proliferative capacity following MYCL overexpression. (B) Proliferation assay. Real-time Incucyte analysis showing cell proliferation of PC3 control (Ctrl) and PC3-MYCL cells measured as confluence (%) over time. Quantification using area under the curve (AUC) demonstrates reduced proliferative capacity following MYCL overexpression. (C) Left: Cell cycle analysis of C4-2B and PC3 cells following MYCL overexpression. In PC3 cells, MYCL reduces the G1 population and increases S-phase, indicating altered cell cycle progression, whereas changes in C4-2B cells are minimal. Right: Apoptosis analysis by Annexin V/7-AAD staining. MYCL overexpression in PC3 cells increases the early apoptotic population, with little or no significant change in C4-2B cells. (D) Cell adhesion assay. Cell adhesion was assessed by crystal violet staining and quantified by measuring absorbance at 595 nm at 18, 24, 48, and 72 h following seeding. MYCL-overexpressing C4-2B cells exhibited significantly decreased adhesion compared with control cells. Representative phase-contrast images acquired 48 h after seeding show reduced cell attachment and increased cell clustering in MYCL-expressing cells. (E) Molecular validation. RT-qPCR analysis of adhesion-related genes (ITGB1, ITGAV) in control (Ctrl) and MYCL-overexpressing C4-2B, LNCaP and PC3 cells. (F) Migration assay. Wound-healing analysis measuring relative wound density (%) over time demonstrates moderately enhanced migratory capacity in PC3-MYCL cells. AUC quantification confirms increased migration upon MYCL expression. (G) Cytoskeletal transcriptional programs. Heatmap showing differential expression of genes meeting thresholds of |log₂FC| ≥ 0.5 and adjusted p-value (FDR) < 0.05. Differentially regulated genes are associated with Ephrin-EPH signaling, Rho-Rac signaling, cytoskeletal organization, cell-cell junctions, extracellular matrix (ECM) interactions, and epithelial-mesenchymal transition (EMT) regulators, indicating MYCL-driven cytoskeletal remodeling signatures.

Article Snippet: Cell migration was evaluated using a wound-healing assay performed with the IncuCyte® system following the manufacturer’s (Sartorius) protocol.

Techniques: Migration, Proliferation Assay, Control, Over Expression, Cell Cycle Assay, Staining, Cell Adhesion Assay, Cell Attachment Assay, Expressing, Biomarker Discovery, Quantitative RT-PCR, Quantitative Proteomics