Search Results (558)

Background/Objectives: Sleep and circadian disturbances are common in neurodevelopmental conditions, yet the developmental cortical programs linking clock-related transcriptional regulators to disease vulnerability remain unclear. Methods: Here, we integrated human developmental brain transcriptomes, weighted gene co-expression network analysis (WGCNA), human and mouse cortical single-cell atlases, prenatal immune activation transcriptomes, and ASD postmortem brain datasets to characterize the developmental architecture of BrainSpan-derived cortical programs and examine their behavior in perturbational and disease contexts. Results: In the BrainSpan frontal cortex, canonical clock-related genes followed structured but heterogeneous developmental trajectories rather than behaving as a coordinated oscillator-like unit. WGCNA identified a postnatal-rising BrainSpan-derived primary developmental module that was strongly associated with developmental age and enriched for synaptic signaling, neurotransmitter transport, ion transport, membrane excitability, cellular respiration, metabolic regulation, and proteostatic processes. Network analysis placed multiple canonical clock-related and clock-regulatory genes, including NPAS2, BHLHE40, BHLHE41, PER family members, RORA, NR1D1/2, and CLOCK, within a broader neuronal and homeostatic co-expression architecture, although their module-membership strengths varied substantially. Projection onto a human cortical developmental single-cell atlas revealed a non-uniform distribution of the corrected BrainSpan-derived developmental signature, with relatively higher scores in excitatory and inhibitory neuronal populations and lower scores in neuroblast and radial glial populations. A mouse cortical developmental single-cell atlas provided a comparative view of the stage- and cell-type-dependent expression of clock-related genes and the transferred developmental signature during corticogenesis. In a Poly(I:C)-based maternal immune activation dataset, litter-aware reanalysis identified stage-resolved genome-wide transcriptional responses following E12.5 exposure. However, neither the aggregate core clock-gene expression score nor the independently transferred BrainSpan-derived developmental signature showed a significant overall treatment effect or collection-stage-by-treatment interaction, indicating that this bulk dataset provides a perturbational context rather than evidence for selective disruption of the developmental program. An exploratory region-stratified analysis of GSE28521 yielded near-null effects for the BrainSpan-derived developmental signature, with confidence intervals crossing zero across all examined regions. These ASD postmortem findings were therefore treated as a boundary assessment rather than evidence of ASD-specific convergence. Conclusions: Collectively, these findings position clock-related genes as components of a developmentally regulated cortical maturation program enriched for neuronal signaling, synaptic maturation, metabolic regulation, and stress-response processes. Full article

Background: Lung adenocarcinoma (LUAD) is the most common subtype of non-small-cell lung cancer and is one of the leading causes of cancer-related deaths globally. Despite current developments, reliable biomarkers for effective diagnosis, prognosis, and patient stratification are still lacking. Methods: We analyzed publicly available TCGA-LUAD and GEO datasets using integrative bioinformatics approaches, including differential gene expression, weighted gene co-expression network analysis (WGCNA), survival modeling, mutation profiling, immune cell infiltration scores, machine learning, and bulk-RNA and single-cell RNA sequencing. Results: A total of 5581 deregulated genes were identified, with the turquoise module (298 genes) showing strong correlation with LUAD (Corr = −0.79, p < 2.2 × 10⁻³⁰⁸). The integration of two analyses yielded 281 overlapping genes, out of which nine candidates (ANO2, CHIAP2, CPED1, DNASE1L3, GSTM5, HTR3C, PRKCE, SLC14A1, and WNT3A) were selected via LASSO Cox regression to build a prognostic risk model. High-risk patients have significantly worse survival (log-rank p = 0.0027). CPED1 exhibited the highest mutation frequency, with 41% of TCGA-LUAD samples harboring mutations. Among all CPED1 mutation events, missense mutations were the most common (47%). GSEA and KEGG analysis revealed significant enrichment of pathways such as nucleocytoplasmic transport, oxidative phosphorylation, protein processing in the endoplasmic reticulum, ribosome, and ribosome biogenesis in high-risk patients. Immune infiltration analysis indicated differences in immune cell infiltration scores between high- and low-immune-score groups, with M1 macrophages showing strong statistical correlation with aDC, monocytes, and CD4⁺ naïve T cells. Machine learning confirmed that the combined Enet+PLS model predicted CPED1 as a core predictor, and CPED1 was successfully validated in independent GEO datasets (GSE43458 and GSE31210), showing strong diagnostic accuracy (AUCs up to 0.98). Finally, single-cell RNA sequencing revealed that CPED1 was mostly expressed in fibroblasts and myeloid cells, with CPED1 significantly downregulated in LUAD compared with normal samples. Conclusions: This study integrates multi-omics and machine learning to highlight CPED1 as a promising candidate biomarker, with potential diagnostic and prognostic relevance in LUAD. The nine-gene risk signature stratified patients by survival outcomes in the TCGA cohort. Genomic and immune analyses revealed features associated with the high-immune-score group. As the study is entirely computational and the prognostic model lacks external survival validation, these findings should be regarded as preliminary and hypothesis-generating, requiring future independent validation and functional studies to confirm the biological significance and clinical utility of CPED1 and related genes. Full article

Radiological emergencies necessitate biomarkers that not only estimate absorbed ionizing radiation (IR) dose but also guide timely interventions to prevent or delay multi-organ injury. Conventional LC–MS-based metabolomics of bulk plasma is constrained by matrix effects that mask low-abundance species. Extracellular vesicles (EVs) constitute a metabolically enriched, underexplored compartment that can provide complementary insight into systemic metabolic and redox responses to IR. Female WAG/RijCmcr rats were exposed to 13.0 Gy leg-out partial-body X-rays and treated with one of three activated protein C (APC) variants—rat wild-type (WT), rat 3K3A-APC, or human WT APC—administered 24- and 48 h post-irradiation. Longitudinal plasma collections (days 1, 14, 30, and 90) were subjected to metabolomic and lipidomic profiling of whole plasma and matched EV-enriched fractions to define signatures of acute radiation syndrome (ARS) and delayed effects of acute radiation exposure (DEARE), and their modulation by APC. ARS was marked by early dyslipidemia and widespread metabolic disruption, evolving into DEARE with persistent alterations in energy metabolism, and nucleotide biosynthesis, consistent with sustained oxidative and inflammatory stress. EV profiles showed matrix-specific, time-dependent trajectories distinct from plasma, with prominent lipid dysregulation and enrichment of fatty acid β-oxidation, sphingolipid, and cholesterol pathway metabolites at day 90. Rat 3K3A-APC promoted early EV metabolic normalization, whereas rat WT APC more effectively mitigated late DEARE-associated changes. Elevated sphingomyelins in plasma EVs at day 90 may suggest a compensatory or anti-inflammatory lipid response. These findings suggest that plasma-derived EVs may provide a sensitive matrix for radiation biomarker discovery and may help elucidate APC-mediated modulation of IR-induced metabolic and redox disturbances. Full article

Accurate battery state estimation is essential for electric-vehicle battery management systems (BMSs), directly improving their safety, durability, and operational reliability. This study proposes an integrated degradation-diagnosis framework that is, to our knowledge, among the first to combine electrochemical impedance spectroscopy (EIS), direct-current internal resistance (DCIR), and state of health (SoH) within a single, quantitative, low-complexity analysis of a hybrid-vehicle NCM811 lithium-ion battery module. Cycling-test data measured at 0, 400, 800, and 1200 cycles were reanalyzed using power-law regression, end-of-life (EOL) extrapolation, and cross-metric correlation analysis; the dataset was then extended to 2000 cycles (six checkpoints in total) to test the reliability of long-term lifetime prediction. Three findings are experimentally demonstrated. First, the ohmic resistance remained essentially constant during cycling, whereas the interfacial resistance increased by +422.7%, identifying interfacial (not bulk) resistance growth as the dominant degradation pathway. Second, power-law models substantially outperformed conventional exponential models for RE, DCIR, and SoH (R² = 0.998, 0.999, and 0.990, respectively, vs. R² = 0.870 for the exponential SoH model); extending the dataset from four to six checkpoints narrowed the resulting EOL model-form uncertainty from a 3.5-fold to a 1.6-fold discrepancy (2776 vs. 9831 cycles, narrowing to 3124 vs. 4908 cycles). Third, a strong linear relationship between DCIR and SoH (R² = 0.956) was obtained, indicating that resistance-only monitoring can approximate SoH without full impedance measurement. Beyond these demonstrated results, the proposed framework offers potential value for SoH estimation, battery condition diagnosis, and state-estimation algorithm development in advanced BMSs; these broader applications have not been experimentally validated in this study and are discussed as directions for future work. Full article

Vanadium dioxide (VO₂) is a prominent active material for reconfigurable nanophotonics because its reversible metal-insulator transition produces large changes in complex refractive index and electrical conductivity. The usable phase contrast, however, is not an intrinsic constant: it is governed by defect type and location, vanadium valence, oxygen stoichiometry, strain, crystallographic orientation, dimensionality, and the chemical, electrical, optical, and thermal boundary conditions imposed by interfaces. This focused narrative review develops a defect- and interface-centred framework linking VO₂ phase physics to device-level optical modulation. Bulk, surface, grain-boundary, and heterointerface defects are distinguished, together with their effects on carriers, V-V bonding, phase stability, optical loss, and cycling reliability. Epitaxial and polycrystalline films, ultrathin layers, and nanostructures are compared across the visible, near-infrared, mid-infrared, and terahertz ranges. Thermal, optical, electrical, electrostatic, electrochemical, ionic, strain, and ferroelectric activation pathways are then compared according to volatility, speed, retention, reversibility, and endurance. Representative free-space metasurfaces, guided-wave modulators, adaptive emitters, and photonic memories are benchmarked separately to avoid mixing incomparable performance definitions. The resulting analysis shows that optical modulation, insertion loss, thermal overhead, ambient stability, and endurance are coupled through the same defect and interface landscape. Progress, therefore, requires coordinated control of phase purity, local chemistry, interface energetics, thermal transport, and architecture-specific performance reporting. Full article

Background/Objectives: Interleukin-27 (IL-27) is an obligate EBI3–p28 heterodimer, yet sepsis studies commonly measure and target the axis as a single entity. We tested whether both subunit transcripts are coordinately induced in septic monocytes and whether the axis has functional consequences. Methods: We integrated 272,993 whole-blood single-cell transcriptomes from 39 individuals, six additional single-cell cohorts and eight bulk cohorts, with two human macrophage datasets, a tolerant-like THP-1 model and caecal ligation and puncture in male C57BL/6 mice. Results: Across three cohorts (166 donor records), EBI3 ranked 137th of 13,872 genes whereas IL-27 ranked 9413th. Against post-cardiac-surgery controls, detection odds ratios (ORs) were 11.0 for EBI3 and 0.78 for IL-27 (ratio 13.3). Thirteen of 7164 septic monocytes carried both transcripts, matching the chance expectation (co-detection odds ratio 0.91, 95% CI 0.48–1.75) against 5.6–346.7 for concordantly transcribed benchmark complexes; the receiver-side module estimate was β = −0.0151. The imbalance was reproduced in human macrophages. In tolerant-like THP-1 cells, IL-27-associated immunoreactivity retained 79.3% of its acute value versus 14.7% for tumour necrosis factor (TNF). p28-directed intervention increased murine 120 h survival from 10% to 45%. Conclusions: Human sepsis shows marked IL-27 subunit discordance across producer and receiver compartments while retaining functional sensitivity of the p28-associated axis, defining a molecular-attribution gap between pathway activity and intact heterodimeric IL-27. Full article

Background: Diabetic cardiomyopathy (DCM) is a serious cardiovascular complication specific to diabetes mellitus, with rising global prevalence. Ferroptosis, an iron-dependent form of regulated cell death driven by lethal lipid peroxidation, has been implicated in the pathogenesis of DCM. However, the key regulatory genes remain poorly characterized. This study aimed to identify and validate ferroptosis-related signature genes in DCM. Methods: Three murine transcriptomic datasets (GSE123975, GSE155377, and GSE210611) were retrieved from GEO and merged after batch correction. Differentially expressed genes were intersected with weighted gene co-expression network analysis disease-associated module genes and FerrDb ferroptosis annotations to define the ferroptosis-related differentially expressed gene candidate pool. LASSO regression and random forest selection then prioritized hub genes, defined operationally as candidates consistently prioritized by both machine-learning algorithms rather than by network-topological centrality. Classification performance was evaluated by ROC analysis and validated in two independent cohorts (GSE161931 and GSE274500). mMCPcounter estimated immune and stromal infiltration. ScRNA-seq (GSE290095) and spatial transcriptomic (GSE290094) profiling characterized cellular distribution, predicted cardiomyocyte network perturbations and tissue-level expression patterns. High-fat diet/streptozotocin (HFD/STZ)-induced DCM rat models provided experimental validation. Results: Acot1 and Txnip were identified as hub genes, with strong discriminatory performance in the discovery cohort (AUC = 1.000 and 0.988; in-sample estimates, n = 26) and independent external validation (AUC = 0.951 and 0.988). Immune profiling linked both genes inversely with vessel scores, and Txnip was also linked with eosinophils. Single-cell analysis localized Acot1 enrichment to cardiomyocytes and endothelial cells, while Txnip was broadly expressed across multiple cell types, with elevated levels in DCM. In silico knockout analysis predicted distinct cardiomyocyte network perturbation profiles for Acot1 and Txnip, and spatial transcriptomics revealed modest but disease-specific spatial associations between hub gene expression and ferroptosis driver scores (Acot1: rho = 0.123; Txnip: rho = 0.154). Both genes were significantly upregulated at mRNA and protein levels in HFD/STZ-induced DCM rats, with concurrent GPX4 depletion, ACSL4 accumulation, and FTH1 reduction consistent with ferroptosis activation. Conclusions: This study identifies Acot1 and Txnip as ferroptosis-related molecular signatures in DCM and provides multistep prioritization and validation spanning bulk transcriptomics, single-cell and spatial transcriptomics, and in vivo experimental verification, offering potential targets for ferroptosis-targeted therapeutic intervention. Full article

Background/Objectives: Therapeutic cancer vaccination requires innate sensing, antigen presentation, lymphocyte priming, tumor access, cytotoxicity, and persistence. Prophylactic studies cannot demonstrate these antitumor functions but can compare systemic formulation responses. We tested whether blood transcription extended beyond innate responses to cancer-immunity-cycle programs. Methods: From 385 GEO records, we retained six human blood cohorts (five bulk-RNA and one sorted-cell) and one mouse blood/lymph-node study. We percentile-ranked 23 modules and compared baseline changes across 17 formulation questions. A separate screen of 35 poly-ICLC cancer-vaccine studies yielded NCT01204684; all arms received a tumor-lysate-pulsed dendritic-cell vaccine. Results: At 24 h after dose 2, AS01B, AS01E, and AS03 increased type I interferon-associated transcription relative to aluminum salt; the AS04 change was negligible. MF59 increased this score by 3.2 points (95% confidence interval, 1.2–5.1) relative to unadjuvanted antigen. Responsive comparisons also showed higher transcription of genes associated with antigen-presenting-cell costimulation, type 1 conventional dendritic cells, and MHC-I antigen processing/presentation. Yellow fever 17D produced a multicomponent trajectory, but the comparison did not isolate viral replication, antigen persistence, viral sensing, or tissue distribution. Of 390 evaluable module–formulation combinations, 278 had no result after false discovery rate (FDR) correction. Sensitivity estimates agreed (r = 0.998; 97.8% directional agreement). In NCT01204684, poly-ICLC recipients showed within-arm interferon and antigen-processing changes, but none of 46 agonist-versus-placebo module contrasts survived FDR correction. Conclusions: Early systemic transcription differed among formulations, whereas later cancer-immunity programs were infrequently detected in bulk blood RNA. Therapeutic studies should add draining-node or tumor measurements and antigen-specific functional assays. Full article

Vascular calcification is a hallmark of vascular aging that is accelerated by hyperlipidemia and contributes to adverse cardiovascular outcomes. Although vascular smooth muscle cells (VSMCs) are key mediators of vascular calcification, the signaling pathways linking aging-associated stress to osteogenic remodeling remain incompletely understood. To define the role of MAPK14 (p38α) in vascular aging, we integrated bulk RNA sequencing of young and aged mouse aortas with published single-nucleus RNA sequencing data from VSMC-specific Mapk14 knockout (KO) mice. Bulk RNA-seq identified age-associated activation of extracellular matrix remodeling, calcification, inflammatory, and senescence-associated gene programs, accompanied by increased p38 MAPK signaling. Single-nucleus RNA-seq further demonstrated that Mapk14 KO attenuated proliferative, inflammatory, fibrotic, and ossification-associated gene modules in VSMCs. Consistent with these transcriptomic findings, RUNX2 expression was markedly increased in aged aortas, whereas aged Mapk14 KO mice exhibited reduced RUNX2 expression together with attenuated vascular calcification, fibrosis, and inflammatory cell infiltration compared with wild-type controls. Collectively, these results identify VSMC MAPK14 as an important regulator of vascular calcification during hyperlipidemic aging and demonstrate that MAPK14 deficiency is associated with reduced RUNX2 expression and attenuated fibro-inflammatory vascular remodeling. These findings support MAPK14 as a potential therapeutic target for limiting vascular calcification and associated pathological remodeling during aging. Full article

Hepatic ischemia–reperfusion injury (HIRI) is not only a common complication of liver transplantation and major hepatic surgery but also a critical determinant of postoperative prognosis. Lactate metabolic reprogramming has been observed in HIRI, yet the role of lactate and its related lactylation in the pathogenesis of HIRI remains unclear. To address this, we integrated single-cell and bulk RNA-seq data with multiple bioinformatic approaches. Five single-cell gene set activity scoring methods (AUCell, UCell, singscore, ssGSEA, and AddModuleScore) were applied to evaluate lactylation activity across cell types, followed by differentially expressed gene (DEG) analysis and high-dimensional Weighted Correlation Network Analysis (hdWGCNA) to identify lactylation-associated genes. Five machine learning algorithms (Random Forest, Boruta, LASSO, GBM, and Decision Tree) were used to screen optimal feature genes, with SHAP analysis further explaining their importance. Bulk RNA sequencing data from the Gene Expression Omnibus (GEO) database were used for validation. Furthermore, NR4A3-related inhibitors were screened using the ChEMBL online tool and assessed by docking and molecular dynamic simulation. We observed significant heterogeneity in lactate metabolism activity across cell types in hepatic ischemia–reperfusion injury (HIRI), with higher activity levels observed for hepatocytes and mononuclear phagocytes. The integration of SHAP and machine learning identified PFKFB3, ZYX, and NR4A3 as closely associated with high lactylation after HIRI, and cross-analysis with bulk RNA data confirmed their consistent upregulation. Candidate gene expression was experimentally validated in a murine liver IRI model through Western blotting and RT-qPCR. Although lactylation has been previously reported in HIRI, this study’s unique contribution is to reveal the cell-type heterogeneity of lactylation-related gene expression at the single-cell level through multi-omics integration and machine learning. The identification of NR4A3, PFKFB3, and ZYX as lactylation-associated regulators proposes novel therapeutic targets for improving graft survival in liver transplantation. Full article

Commercial carbon-based electrodes such as graphite felt and carbon felt in all-vanadium redox flow batteries suffer from inherent drawbacks, including slow vanadium ion redox kinetics, insufficient intrinsic catalytic activity, fiber corrosion, and functional group loss under strong acidic oxidative conditions, significantly limiting battery energy efficiency and long-term operational reliability. Rare-earth elements, with their unique 4f electron shell structure, tunable electronic levels, abundant surface oxygen vacancy defects, and strong coordination ability, offer a dual pathway—electronic and microstructural modulation—to optimize the interfacial electrocatalytic behavior of carbon electrodes, providing a novel materials system to overcome electrode performance bottlenecks in vanadium batteries. This review systematically summarizes recent advances in rare-earth-functionalized carbon electrodes and electrocatalysts for vanadium redox flow batteries, elaborating on core modification strategies, performance enhancement trends, and synergistic catalytic mechanisms. It also presents quantitative experimental results from the literature to clearly demonstrate the benefits: CeO₂-modified graphite felt at 0.2 wt% shows a 10.8% increase in energy efficiency compared to pristine graphite felt at a current density of 200 mA·cm⁻², while multi-rare-earth co-doped carbon electrodes achieve a 65% reduction in charge transfer resistance relative to unmodified electrodes. The review systematically categorizes two dominant modification routes—surface nano-decoration with rare-earth oxides and lattice bulk doping with rare-earth elements—and summarizes design principles and enhancement mechanisms of diverse composite catalytic systems, including rare-earth–carbon nanocomposites, rare-earth-based heterojunctions, and porous rare-earth catalysts. It further analyzes critical challenges in current research, such as unclear long-term stability mechanisms, high costs of high-purity rare-earth raw materials, immature large-scale fabrication processes, and limited in situ dynamic characterization techniques. Compared with existing reviews, this work clearly distinguishes between surface loading and lattice doping as two distinct rare-earth modification approaches, clarifying their differences in active site formation, electronic regulation logic, and cycling stability. It establishes a comprehensive theoretical framework for the coupled electronic–geometric effects in rare-earth-modified carbon electrodes, linking the intrinsic physicochemical properties of rare earths, material microstructure design, and battery electrochemical performance. Moreover, it innovatively proposes a pathway toward full-lifecycle recycling and reuse of rare-earth-based catalytic electrodes for industrial implementation. This review provides a complete theoretical foundation for developing high-performance, long-cycle, low-cost vanadium redox flow battery electrode materials and supports their engineering scale-up, contributing to the development of large-scale, long-duration energy storage technologies. Full article

Polymeric biomaterials do not degrade in vivo through isolated chemical or mechanical events. Hydrolysis, oxidation, enzymatic cleavage, fatigue, wear, protein adsorption, and lipid uptake often interact across the material surface, bulk, and surrounding biological environment, producing time-dependent changes in both structure and function. Here, we propose a conceptual framework for organizing polymer degradation under biomedical conditions as a directional network of coupled mechanisms, emphasizing how established degradation pathways can influence one another and collectively contribute to time-dependent functional loss. The framework distinguishes degradation reactions from interfacial modulators and links molecular damage to functionality retention, defined according to application-specific endpoints such as mechanical strength, mass retention, dimensional stability, or interfacial performance. We introduce a qualitative interaction matrix to describe how individual mechanisms can amplify or modulate downstream pathways, and we use this matrix to identify recurrent degradation archetypes across major biomedical polymer classes, including polyesters, polyolefins, polyamides, polyurethanes, silicones, polyacrylates, polyvinyl polymers, polyimides, and natural polymers. This perspective emphasizes that material optimization strategies rarely eliminate degradation; instead, they shift the hierarchy of active pathways. By reframing biocompatibility as a dynamic, functionality-dependent property, the proposed framework provides a structured basis for comparing polymeric biomaterials, designing more realistic in vitro tests, and developing future data-driven models of long-term implant performance. Full article

Consensus molecular subtype 4 (CMS4) colorectal cancer (CRC) is associated with an aggressive clinical course and poor survival, yet the biological basis of heterogeneity within this subtype remains incompletely understood. DNA methylation is an epigenetic mechanism involved in transcriptional regulation, cellular differentiation, and colorectal tumorigenesis. Here, we integrated single-cell RNA sequencing (scRNA-seq), bulk data, and promoter DNA methylation data to characterize CMS4-associated cancer cell states and methylation-related features. Using the scAB algorithm, we integrated scRNA-seq with bulk CMS4 data and identified CMS4-related cells distributed across multiple patients. Single-cell analyses of cell–cell communication and transcriptional regulation revealed a CMS4-related cancer cell population characterized by macrophage migration inhibitory factor (MIF)-centered intercellular communication, enhanced caudal type homeobox 1 (CDX1) and Kruppel-like factor 5 (KLF5) regulon activity, and gene modules enriched in differentiation-related pathways. CytoTRACE analysis further stratified CMS4 cancer cells into poorly and well-differentiated states, yielding 802 differentially expressed genes (DEGs). Linking these differentiation-associated DEGs with bulk expression and promoter methylation data identified 218 methylation-associated DEGs showing significant inverse methylation expression correlations, suggesting a link between differentiation-related heterogeneity and promoter methylation. Univariable Cox regression followed by LASSO regression further prioritized eight genes for construction of the methylation and differentiation-related prognostic model (MeDiff-PM). MeDiff-PM consistently stratified overall survival in the TCGA CMS4 cohort and two independent validation cohorts, with cutoff-independent continuous Cox analyses further supporting its prognostic association across cohorts. And MeDiff-PM remained prognostically significant after adjustment for available clinical variables. High MeDiff-PM risk scores were associated with activation of P53, WNT, and ubiquitin-mediated proteolysis pathways and with consistent predicted drug response differences for compounds across three CMS4 cohorts. While individual in silico knockout analysis suggested links between MeDiff-PM genes and metallothionein-related and immune-associated transcriptional responses. Collectively, these findings indicate that methylation-associated differentiation features represent a molecular dimension of intra-CMS4 heterogeneity and provide a biologically informed framework for prognostic stratification within CMS4 CRC. Full article

Two 4-piperazine-1,8-naphthalimides were designed as fluorescent probes for exploring the local polarity and proton concentration at the interface of micelles. Designed with an anchor₁-fluorophore-spacer-receptor-anchor₂ layout, the hydrophobicity of the pH probes was tuned by substitution of the anchor modules with different alkyl chains (methyl, butyl and octyl) to facilitate the micellar penetration depth. Fluorescence switching ‘on’ in methanol/water media upon protonation of the piperazine receptor is driven by a competition between solvent polarity and photoinduced charge transfer. The solvatochromic properties were investigated to enhance visual naked-eye communication. The fluorescent probes were tasked with reporting on the local polarity and proton content within sodium dodecyl sulphate (SDS), cetyltrimethylammonium chloride (CTAC) and Triton X-100 micelles. The dimethyl-substituted probe reported on the environment about the micelle/bulk water interface. The more hydrophobic octyl-butyl-substituted probe explored deeper into the micelles. Insight was gained into the local polarity and proton gradients inside micelles, as corroborated by emission wavelength, fluorescence quantum yield and ΔpK_a values. The findings are discussed in the context of the benzofurazan polarity–ΔpK_a maps reported by Uchiyama and de Silva. Full article

Suppressing thermally driven morphological evolution while preserving efficient charge transport pathways remains a critical challenge for improving the long-term stability of organic photovoltaics (OPVs). Herein, a soft polymeric matrix strategy based on gel-related soft material concepts is demonstrated for stabilizing bulk heterojunction (BHJ) morphology and simultaneously improving the efficiency and thermal durability of OPVs. The incorporation of an optimal 5 wt% polystyrene-block-poly(ethylene-ran-butylene)-block-polystyrene (SEBS) as a soft polymeric matrix component into a PM6:Y6 blend modulates the nanoscale morphology and local packing characteristics of the acceptor phase. These changes improve charge-transport balance and charge collection, increasing the power conversion efficiency (PCE) from 14.27% to 15.22%, corresponding to a 6.7% relative enhancement over the control device. More importantly, after 10 days of thermal aging at 85 °C, the SEBS device retains 87.1% of its initial PCE, compared with 72.5% for the control device. Complementary morphological and spectroscopic analyses reveal suppressed thermally induced structural evolution and aggregation in the SEBS-containing films. These findings demonstrate that a gel-related soft polymeric matrix can regulate BHJ organization and mitigate thermally driven morphological evolution, providing a simple strategy for addressing the efficiency–stability trade-off and realizing thermally robust OPVs. Full article