Heterogeneous Composition Research Articles

Abstract 2367: Changes in breast hormone signaling and inflammation underlie radiologic features of cancer risk

Abstract Background: Image-based features of the normal breast such as mammographic density and background parenchymal enhancement (BPE) on contrast-enhanced breast magnetic resonance imaging (MRI) are independent breast cancer risk factors. Both are associated with estrogen signaling and respond to endocrine therapy. Yet, molecular and cellular mechanisms underlying these risk factors remain unclear. We aimed to investigate such mechanisms with the goal of identifying novel approaches for cancer risk stratification and personalized prevention. Methods: Single-nucleus RNA sequencing on a 10x Chromium platform was performed on normal human breast tissues from 28 women undergoing prophylactic mastectomies (n = 11), lumpectomies (n = 10), or mastectomies for breast cancer (n = 7) who consented to our biobanking protocol. Differences in cell composition and signaling pathways between individuals with different breast densities and BPE levels were determined. Additionally we assessed estrogen responsiveness in patient-derived organoid (PDOs) from women with different levels of BPE using qRT-PCR. Evaluation of immune infiltration as potential mediator of BPE is underway using immunofluorescence and spatial transcriptomics. Results: 12, 377 nuclei from 28 women were analyzed, including 16 with low (minimal or mild) and 12 with high (moderate or marked) BPE levels on MRI, and 5 cases with not dense and 23 with dense breasts on mammography. All main breast epithelial and stromal cell types were represented in our data. We observed great heterogeneity in cell composition between patients. Samples from BPE-high patients contained luminal secretory cells with reduced expression of differentiation markers and luminal hormone sensing cells with higher expression of estrogen response genes like PGR and GREB1. In agreement with this, we observed increased response to estrogen signaling in PDOs from high (n = 5) versus low BPE cases (n = 5). Moreover, luminal cells from BPE-high samples expressed significantly higher levels of CD74 which has been correlated with immune infiltration in cancer. Supporting this, interactions between luminal cells with macrophages via CD74 and APP/COPA were predicted in BPE-high but not in low samples. Comparing samples with distinct mammographic densities, we observed a higher proportion of luminal secretory cells, basal cells, and fibroblasts in patients with high mammographic densities suggesting that distinct mechanisms mediate BPE levels and breast density. Conclusions: Our findings indicate that BPE is influenced by two distinct mechanisms: estrogen-mediated changes in cellular composition and chronic inflammation, both potentially increasing breast cancer susceptibility. Understanding the basis of modifiable breast cancer risk factors will enable risk stratification and personalized treatment, ultimately reducing breast cancer incidence in high-risk populations. Citation Format: Nadine Goldhammer, Marin Bont, Michael Choi, Shruti Warhadpande, Heather Greenwood, Soumi Gottipati, Tam Binh Bui, Michael Bruck, Shoko Emily Abe, Michael Alvarado, Cheryl Ewing, Karen Goodwin, Rita Mukhtar, Jasmine Wong, Laura van't Veer, Nola Hylton, Laura J. Esserman, Jennifer M. Rosenbluth. Changes in breast hormone signaling and inflammation underlie radiologic features of cancer risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2367.

Abstract 5186: Organoids from patient-derived xenograft (PDXO) for preclinical therapeutic predictions

Tumors exhibit heterogeneity, comprising diverse cell clones, necessitating the use of preclinical models that accurately replicate clinical properties for cancer research and antitumor efficacy prediction. Patient-derived xenograft (PDX) models recapitulate key characteristics of human tumors, but are cost-intensive and time-consuming, thus unsuitable for large-scale screenings. Here, we evaluated the biological equivalence of organoid models derived from patient-derived xenograft tumors (PDXO) to PDXs. PDX organoids (PDXO) are small, organized three-dimensional structures developed from PDX tissue fragments in specialized in vitro culturing systems, enabling early-stage assessment of drugs. We have demonstrated that PDXOs are similar to their corresponding PDX counterparts in multiple aspects. Pathological staining (HE & IHC) data confirmed the heterogeneity of tissue architecture, cellular composition, and microenvironment interactions inherited from PDX. Genomic analysis showed the preservation of molecular and biological characteristics. In vitro pharmacological studies demonstrated that the sensitivity of PDXOs to drugs was similar to that of the original PDX models. Furthermore, in some cases where pairs of PDXs were established from the same patient before and after targeted treatment, the corresponding PDXOs reproduced the sensitivity differences observed during in vivo studies, as well as similar mechanisms of resistance development. These clinically analogous results highlight the potential of PDXOs for preclinical and clinical drug testing, enabling more precise predictions of therapeutic outcomes. Citation Format: Chao Zhang, Xiaoying Zhuang, Lu Yin, Xiaoyi Xing, Sen Wang, Zizhuo Chen, Lei Jin, Qiangqiang Fan, Jiaping Sun, Fuyang Wang, Wenjie Gao, Qingyang Gu. Organoids from patient-derived xenograft (PDXO) for preclinical therapeutic predictions [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5186.

Abstract 6845: Evaluation of individual drug response to tyrosine kinase inhibitor treatment in precision-cut tumor slices of gastrointestinal stroma tumors

Abstract Gastrointestinal stromal tumors (GIST) are the most prevalent mesenchymal tumor entity of the gastrointestinal tract and serve as a key example for targeted therapies with tyrosine kinase inhibitors (TKI) such as imatinib, in tumors with the most frequent mutations in PDGFRA or c-Kit. Although TKIs have significantly improved the overall survival rates of GIST patients, there are currently no treatment options for imatinib-resistant tumors and tumors without identifiable driver mutations. So far, current sarcoma research mostly relies on expensive mouse models or 2D cell culture that do not integrate the tumor microenvironment (TME). Therefore, clinically relevant, patient-derived 3D GIST models that include cells of the TME are urgently needed. In this study, we tested the feasibility of precision-cut tumor slices (PCTS) as a preclinical model for personalized GIST research. PCTS are patient-derived 3D tissue slices that enable the study of interactions between tumor cells and cells of the surrounding TME. For this, primary GIST tumors were cut into 250µm thick slices and cultured for up to two weeks with or without standard TKI treatment. Tumor morphology and cell composition was analyzed via immunohistochemical (IHC) and multiplex immunofluorescence (mIF) staining, which enabled the simultaneous detection of up to six different markers on one FFPE tissue section. The downstream analysis included a machine-learning based workflow that allowed the comparison of biomarker expression and spatial immune cell distribution in the PCTS stromal and tumor areas before and after treatment. Comparison between primary tumor and PCTS revealed a preserved tumor morphology and heterogeneous cell composition throughout culture. In addition, serum levels of various cytokines were assessed with LEGENDPlex assays and correlated with the PCTS cell composition. The in vitro response of PCTS to TKI-based therapies was analyzed via IHC staining and ATP-based viability assays. PCTS from tumors with PDGFRA mutations were expected to be imatinib-resistant, while PCTS from tumors with c-KIT mutations were considered imatinib-sensitive. Sequencing analyses determined the PDGFRA or c-KIT mutational status showing that all patients harbored either a PDGFRA or a c-KIT mutation. PCTS treatment response was compared to the mutational status and if available to clinical follow-up data. Of all PCTS that responded to imatinib therapy, two cases matched the anticipated clinical outcome. PCTS provide a clinically relevant new model system for GIST to explore the development of therapy response to TKI-based treatment and to investigate novel GIST treatments such as immunotherapies and combination treatments. The work is supported by the Robert Bosch Stiftung, Stuttgart, Germany Citation Format: Dina Mönch, Julia Thiel, Meng Dong, Annika Maaß, Annette M. Staiger, Katrin Kurz, German Ott, Philipp Renner, Tobias Leibold, Thomas Mürdter, Matthias Schwab, Marc-Hendrik Dahlke, Jana Koch. Evaluation of individual drug response to tyrosine kinase inhibitor treatment in precision-cut tumor slices of gastrointestinal stroma tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6845.

Abstract 6247: Artificial intelligence predicts 2021 WHO glioma subtypes from whole slide images

Abstract Diagnosis of diffuse glioma according to the WHO 2021 classification criteria mandate the integration of histologic features with molecular profiling. However, molecular profiling is expensive, time-demanding, and when not available leads to the ‘not-otherwise-specified' status. We seek interpretable AI-based classification of glioma, as oligodendroglioma, astrocytoma, or glioblastoma, from H&E-stained slides alone. We identified 2, 114 multi-institutional whole slide images (WSIs), from two independent retrospective glioma collections, following reclassification according to the WHO 2021 criteria: a) TCGA-GBM/TCGA-LGG (nWSI=1, 320, npatients=654) & b) EBRAINS (nWSI=npatients=794). TCGA data are used for model development, whereas EBRAINS as hold-out data. Each WSI undergoes comprehensive curation to account for any artifacts, such as tissue foldings, glass reflections, and pen markings. We then conduct a quantitative performance evaluation across: i) eight pathology-specific AI foundation models (FM) and an ImageNet-trained AI model that facilitate robust feature extraction, and ii) nine multiple-instance learning (MIL) approaches that are used to aggregate features into slide-level representations, to differentiate across the three glioma classes. Finally, we take into account magnification level combinations of the WSIs (2.5x, 5x, 10x, 20x), in an attempt to mimic the approach that expert neuropathologists follow to histologically assess tissue slides. Our approach yields AUCTCGA=0.979 over a 10-fold cross-validation schema, and generalizable performance on the independent validation (AUCEBRAINS=0.963), for the best performing FM and MIL in the multi-magnification setting. Our key findings indicate: i) domain-specific FMs outperform the ImageNet model, ii) MILs yield larger performance contributions when used with ImageNet models than with FMs, iii) Fusion of multiple magnifications adds value on both development and validation datasets. Interpretability analysis through attention heatmaps highlights distinct identifiable morphology features for each glioma class. Oligodendroglioma show uniform, round nuclei with perinuclear halos, microcystic and gemistocytic cells. Astrocytomas contain cells resembling astrocytes with irregular, elongated shaped nuclei and fibrillary cytoplasmic processes. Glioblastomas display highly heterogeneous cellular composition, pleomorphic astrocyte cells, microvascular proliferation, multinucleated giant cells, and pseudo palisading necrotic regions. Determination of glioma classes directly from routine clinically acquired H&E slides can obviate the need for molecular profiling, expedite conclusive diagnosis and hence clinical decision-making, even in underserved regions. Interpretability analysis towards distilled human-identifiable features can contribute in disease understanding. Citation Format: Shubham Innani, W. Robert Bell, MacLean Nasrallah, Bhakti Baheti, Spyridon Bakas. Artificial intelligence predicts 2021 WHO glioma subtypes from whole slide images [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6247.

Petrogenesis of the Rantila meteorite fall and implications for the origin of aubrites

AbstractAubrites are rare meteorites from highly reduced differentiated parent bodies. The Rantila meteorite was recovered soon after falling on 17 August 2022 at Rantila and Ravel villages in Gujarat state, India. We report the petrography, mineralogy, chemical composition, oxygen‐ and chromium‐isotope compositions, along with reflectance spectroscopy, all showing that Rantila is an aubrite. Coarse enstatite and diopside grains constitute the main mass of Rantila, while mm‐wide fracture domains pervade the coarse enstatites. In the fractures, comminuted enstatite, diopside blebs, olivine, a plagioclase–silica assemblage, sulfides, and metals occur. Rantila consists of enstatite (>85 vol%), diopside (~8 vol%), forsterite, albite, and silica along with various sulfides and Fe‐Ni alloys. The concentration of rare earth elements is ~1–2 × CI, consistent with main group aubrites. Noble gas and nitrogen isotopic analyses reveal young exposure ages (13.81 ± 6.47 Ma), a heterogeneous nitrogen isotopic composition, and a major K‐Ar resetting event around 3.2 ± 0.4 Ga in the parent body of Rantila. The bulk oxygen isotope values are within the range of aubrites. The chromium isotopic values of Rantila are consistent with main group aubrites. The mineral assemblages, texture, and crystallization modeling suggest that Rantila had an igneous origin. The mineral assemblages in fractures indicate the involvement of external melt possibly during an impact‐fracturing event, which aligns well with the heterogeneous N isotopic composition. Additionally, Rantila shows a wider range of oxygen isotopes than other aubrites suggesting some extent of O isotopic heterogeneity, likely stemming from exogenous processes. The variation in intra‐sample bulk O and N isotope values implies inherent heterogeneity within the main group aubrites, potentially caused by late‐stage impact contamination.

Abstract 2181: Establishing a multi-modal, cell therapy characterization workflow to identify cell subsets with heightened cytotoxicity

Cell therapies have been groundbreaking for B-cell lymphomas but optimizing efficacy for solid tumors remains challenging. Lack of consensus on potency measures, unknowns about novel engineering strategies, and product heterogeneity drive extensive characterization to discover product-specific mechanisms of action (MoAs). This process is costly and limited by variable results from simple molecular assays and need to infer relationships between data from disparate technologies. Thus, we created a multi-modal technology with which to establish a multi-functional, longitudinal cellular characterization workflow. With a single sample input, this workflow evaluates multiple live phenotypes from the same individual cells across tens of thousands of cells at once. We leveraged TALL-104 cells before validating compatibility with clinical-stage cell therapies with AIC100 - a Phase 1 CAR-T product targeting thyroid cancer (NCT04420754). Cellanome’s technology enables multi-modal evaluation of live, cellular behavior at the resolution of single cells or single-cell interactions. Within an 8-lane flow cell, tens of thousands of single TALL-104 cells were enclosed with K562 target cells in bio-compatible hydrogel compartments called CellCage™ enclosures (CCEs). These CCEs enable longitudinal monitoring of single TALL-104 cells interacting with K562 cells for hours to days with time-lapse imaging. During this period, imaging-based evaluation of surface markers, cytokine secretion, and cytotoxicity are integrated from the same single T-cells. Our analysis pipeline links target cell death to single T cells in CCEs, enabling cell killing to be studied with unprecedented resolution. Similar to flow cytometry via CD107 as a surrogate for killing, with Cellanome’s technology, we could identify cytotoxic T cells (∼85%). Uniquely, we can directly evaluate killing by single TALL-104 cells and further segment them into groups. Group 1 consists of strong killers (killing 100% of targets), Group 2 of medium killers (50-99%), and Group 3 of weaker killers (0-49%). We next characterized single AIC100 cells enclosed with HeLa as targets and observed that, unlike TALL-104 cells where Group 2 was the largest, for AIC100, Group 3 was the largest, suggesting distinct killing mechanisms. Thus, we asked whether AIC100’s heterogeneous composition of CD4 / 8 cells impacts product efficacy. We configured this workflow to test killing by ∼100 combinations of CD4:CD8 AIC100 cells in a single experiment. Preliminarily, more killing occurred in CCEs containing a mixture of CD4 and CD8 T cells relative to CCEs containing only CD4 or CD8 cells. We are continuing to identify the optimal CD4:CD8 compositions for greater potency. We envision multi-modal characterization of clinical products with our platform, pre and post-patient infusion, will inform efforts to advance cell therapies for solid tumors. Citation Format: Richard Yau, Shreya Deshmukh, JangKeun Kim, Jiwoon Park, Yanping Yang, Makenzie Sacca, Shan Sabri, Teresa Ai, Pier Federico Gherardini, Gary Schroth, Christopher E. Mason, Moonsoo M. Jin. Establishing a multi-modal, cell therapy characterization workflow to identify cell subsets with heightened cytotoxicity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2181.

Self-Assembly at Oil-Water Interfaces Driven by Solubility Differences and Polar-Hydrophobic Interactions: An Insight into a Highly Mechanical Performance Gel with Gradients.

Interfacial self-assembly offers a promising route to fabricate functional materials, yet achieving robust mechanical performance remains challenging. Here, the self-assembly of nonionic surfactant polyoxyethylene monoalkyl ether (AEO-9) at oil-water interfaces was systematically investigated to form a high-strength interfacial gel. During the self-assembly process, the mechanical strength of the interfacial gel progressively increased, reaching a maximum equilibrium value of 4200 Pa after 24 h. Furthermore, significant gradients in the composition, microstructure, and micromechanical properties of the interfacial gel along the sample height were revealed by fluorescence microscopy, small-angle X-ray scattering (SAXS), and atomic force microscopy (AFM). This unique interfacial self-assembly behavior was further studied via dynamic light scattering and molecular simulations. The solubility differences and polar-hydrophobic interactions are the key factors. Directional migration of AEO-9 from the oil phase (low solubility) to the aqueous phase (high solubility), driven by solubility differences, was found to establish a transient interfacial concentration gradient. This gradient facilitated interfacial enrichment of AEO-9, which was subsequently organized into gradient lamellar liquid crystals (LC) through compositional heterogeneity and polar-hydrophobic interactions. The gradient variations in micromechanical properties were correlated with the gradient structural packing. Moreover, the effects of AEO-9 concentration, brine, temperature, and oil type on the gel's mechanical properties were examined, highlighting their roles in modulating the polar-hydrophobic balance. This study reveals the dual control of solubility-driven migration and interfacial interactions on gradient formation, establishing a framework for the design of high-performance interfacial materials.

MOF-Derived Hollow Fe/FeN/C Heterogeneous Composites for Broad-Band and Efficient Microwave Absorption.

The construction of hollow structures and the incorporation of metal nanoparticles have been shown to be two potential approaches to achieving high-performance microwave absorption. In this study, a hollow polyhedron material featuring an FeN/Fe-doped carbon matrix was synthesized by an acidification corrosion and pyrolysis strategy. The formation of heterojunctions, coupled with the design of hollow structures, significantly improved the dielectric loss capacity of the material. Furthermore, the incorporation of magnetic metal nanoparticles not only increased the magnetic loss but also enriched the loss mechanisms of the material, leading to an overall improvement in the magnetic loss. Under the synergistic effects of these factors, the material exhibited exceptional microwave absorption properties. In particular, at a material thickness of only 2.3 mm, the minimum reflection loss value of the FeN/Fe@HC nanocomposite reached -64.5 dB with an effective absorption bandwidth of 5.1 GHz. These results further highlight the importance of a hollow structure design and metal atom doping in improving microwave absorption performance.

Thermo-Mechanical Properties and Oxidation Behavior of FeCrAl Alloys with Si and Y Addition

The chemical composition of FeCrAl alloy significantly influences its thermal-mechanical as well as anti-corrosive properties. This study investigates the impact of silicon and yttrium additions on the thermal-mechanical properties and high-temperature oxidation resistance of FeCrAl alloy. The results indicate that thermal conductivity gradually decreases with the incorporation of Y or Si into the lattice, whereas the mechanical strength of the alloy can be enhanced through the addition of Y. A trace amount of Y can improve the alloy’s high-temperature oxidation resistance by mitigating the spallation of the surface oxidation film and promoting the growth of the film, characterized by heterogeneous chemical composition and microstructure. It is observed that Y possesses a higher charge density than FeCrAl, suggesting that Y can lose electrons more readily than other elements, which implies a reduction in oxygen diffusion.

Bird and hoverfly communities are impacted by vegetation heterogeneity in wood-pastures in the Swiss Jura

Abstract Wood-pastures are a type of agroforestry system consisting of assemblages of cattle-grazed pastures and scattered trees. They maintain biodiversity because of their environmental heterogeneity due to irregular tree cover that promotes diversity of resources and habitats. Agricultural intensification threatens the fragile balance of these traditional systems. Thus, we aimed to assess which factors associated with trees, shrubs and pasture heterogeneity within wood-pastures influence the community composition and diversity of different groups of animal species. We selected 45 wood-pasture sites of 20 ha along a gradient of tree density in the Swiss Jura mountains. In each site, we used remote sensing data and agricultural inventories to characterize the tree, shrub and herb layers’ structural and compositional heterogeneity. In study sites we also conducted survey of birds and hoverflies (Syrphidae) and evaluated the relationships between species composition and diversity with environmental variables. Tree density and tree spatial distribution were the main drivers of differences in community specific composition for the two groups of species. For hoverflies, botanically rich pastures and elevation were also driving differences in species composition between communities. Increased tree density showed a generally positive effect on birds and Syrphidae diversity indices. Moreover, for birds, scattered trees’ spatial distribution and a high percentage of deciduous trees also promoted species diversity. In this study, we highlight the importance of trees in pastures for bird and hoverfly diversity, as well as the necessity for trees to be heterogeneously distributed across the pastures and composed of a mix of deciduous and coniferous species.

Strong evidence for the evolution of decreasing compositional heterogeneity in SARS-CoV-2 genomes during the pandemic

The rapid evolution of SARS-CoV-2 during the pandemic was characterized by the fixation of a plethora of mutations, many of which enable the virus to evade host resistance, likely altering the virus’ genome compositional structure (i.e., the arrangement of compositional domains of varying lengths and nucleotide frequencies within the genome). To explore this hypothesis, we summarize the evolutionary effects of these mutations by computing the Sequence Compositional Complexity (SCC) in random stratified datasets of fully sequenced genomes. Phylogenetic ridge regression of SCC against time reveals a striking downward evolutionary trend, suggesting the ongoing adaptation of the virus’s genome structure to the human host. Other genomic features, such as strand asymmetry, the effective number of K-mers, and the depletion of CpG dinucleotides, each linked to the virus’s adaptation to its human host, also exhibit decreasing phylogenetic trends throughout the pandemic, along with strong phylogenetic correlations to SCC. We hypothesize that viral CpG depletion (throughout C➔U changes), promoted by directional mutational pressures exerted on the genome by the host antiviral defense systems, may play a key role in the decrease of SARS-CoV-2 genome compositional heterogeneity, with specific adaptation to the human host occurring as a form of genetic mimicry. Overall, our findings suggest a decelerating evolution of reduced compositional complexity in SCC, whereas the number of K-mers and the depletion of CpG dinucleotides are still increasing. These results indicate a genome-wide evolutionary trend toward a more symmetric and homogeneous genome compositional structure in SARS-CoV-2, which is partly still ongoing.

ZTE MRI improves detection of calcific deposits and differentiation between resorptive and formative phases in calcific tendinitis of shoulder

The purpose of study was to evaluate the diagnostic value of the ZTE sequence of shoulder MRI in patients with calcific tendinitis by comparing conventional sequences. Seventy-nine patients (43 patients with calcific tendinitis and 36 control group) who underwent both radiography and MRI including ZTE sequence were enrolled in our study. Two radiologists assessed the SNR, image quality, presence, size, multiplicity, shape, margin, signal intensity, composition, and location of calcific deposits on ZTE image, FSPDWI, and T2WI. The diagnostic performance was calculated with radiography as the standard of reference. The inter-reader agreement and differentiation of the resorptive phase and formative phase on ZTE were compared to that on FSPDWI and T2WI. A total 59 calcific deposits in 43 patients were found on radiography and classified into type 1 resorptive phases (n = 20) and type 2 formative phases (n = 39). ZTE image quality was for diagnostic use with substantial inter-reader agreement. Sensitivity and detection rate of ZTE image was better than those of FSPDWI and T2WI. The inter-reader agreement of ZTE image was equal to FSPDWI and better than T2WI. The features of calcific deposits on ZTE images were significantly different between two phases. In the resorptive phase, a greater percentage of calcific deposits showed irregular shapes, ill-defined margin, heterogeneous compositions on ZTE images. In conclusion, ZTE sequence may provide useful information for the diagnosis of calcific tendinitis of the shoulder.

Revealing Stress Granule Compositional Heterogeneity through Antibody-Guided Proximity Labeling.

Stress granules (SGs), transient nonmembranous cytoplasmic condensates that formed in response to cellular stresses, require precise characterization to unravel their cell-type and stress-specific protein compositions. This study introduced a G3BP1 antibody-guided proximity labeling (Ab-PL) method to explore the composition and diversity of SGs, overcoming the challenges of traditional enzyme-mediated proximity labeling techniques across various cell types, especially for the immune cells. Application of Ab-PL to HeLa and RAW264.7 cells under heat shock (HS), sodium arsenate (AS), and sodium chloride stress (SS) revealed two categories of SG proteins: "SG-core" and "SG-shell," characterized by their different abilities to undergo phase separation. The core proteins form the SG scaffold with strong self-segregation, while shell proteins are dynamically recruited based on the type of stress. Cell- and stress-specific SG proteins were also identified, highlighting compositional heterogeneity. Intriguingly, unique nuclear-cytoplasmic shuttling behaviors of SG components were observed under varying conditions, uncovering over 10 novel SG proteins, including REXO4, RBM28, and OGFR. This study provides a versatile tool for SG analysis across diverse cell types and offers insights into SG heterogeneity, which has potential implications for human diseases, paving the way for future studies on RNA metabolism, ribosome assembly, and immune regulation.

Heterogeneous-Interface-Induced Charge Redistribution Toward Fe-Based Polyanion Cathode for Advanced Sodium-Ion Batteries.

Na4Fe3(PO4)2P2O7 (NFPP) is gradually developing into one of the most commercially prospective cathode materials for sodium-ion batteries. However, the inactive phase maricite-NaFePO4 (m-NFP) normally tends to be formed during the synthesis process of NFPP, as well as the intrinsic poor electronic conductivity, which impacts the realization of high Na-storage performance. Herein, for the first time, we have constructed a heterostructure in Fe-based polyanionic cathode materials by fine-tuning the stoichiometric ratio of the Na site; the inactive phase m-NFP is fully transformed to the active Na2FeP2O7 or NFPP. In NFPP-NFPO heterogeneous composites, density functional theory calculations reveal that the charge redistribution occurs at the heterogeneous interface, leading to stronger and more uniform interactions that can strengthen the structural stability and enhance the charge transport kinetics. Benefiting from the heterogeneous intergrowth structure and the formation of the electrochemically active phase, a high discharge specific capacity, ultralong cycle life (71.4% capacity retention after 10,000 cycles at 50 C), ultrafast rate capability (60.2 mAh g-1 at 200 C), and impressive high-temperature tolerance have been achieved. This work achieves heterogeneous composites by manipulation of the phase composition, providing a new approach for designing high-performance polyanionic cathodes for sodium-ion batteries.

Tumor Immune Microenvironment in Pancreatic Ductal Adenocarcinoma revisited - Exploring the "Space".

Tumor Immune Microenvironment in Pancreatic Ductal Adenocarcinoma revisited - Exploring the "Space".

Organic pollutant degradation via novel ZnCo2O4-embedded grafted waste polystyrene foam as heterogeneous catalysts for PMS activation

This study aimed to design and fabricate high-performance heterogeneous polymeric composites via in-situ polymerization, utilizing waste polystyrene-co-methacrylic acid functionalized with zinc cobalt oxide (ZC) at varying loadings (10, 15 and 30 wt %), designated as m-WZC10, m-WZC15 and m-WZC30 respectively. Additionally, waste polystyrene (W) underwent methacrylic acid grafting in the absence of zinc cobalt oxide, serving as a control reference material, denoted as m-W, to evaluate the impact of ZC incorporation on the composite’s structural and catalytic properties. The synthesized polymers were employed for poroxymonosulfate activation (PMS) in the catalytic removal of methylene blue (MB) from wastewater streams. Through systematic experimentation, we compared three different loadings of m-WZC composites (m-WZC10, m-WZC15, and m-WZC30) by optimizing key degradation parameters, including PMS dose, pH, temperature, initial MB concentration, and the effect of ions. Among them, m-WZC15 exhibited the optimal performance, achieving 99.89% MB removal within just 10 min at an initial MB concentration of 20 mg/L. Under the optimal conditions of m-WZC15, the study further expanded its scope by investigating its efficacy in degrading other pollutants, methyl red (MR), methyl orange (MO), rhodamine B (RB), and p-nitrophenol (PNP). The catalysis exhibited excellent degradation activity, achieving removal rates of 99.76%, 99.0%, 98.3%, and 97.8% for these pollutants, respectively. Stability experiments revealed that the MB degradation rate achieved by the m-WZC15 remained consistently high, reaching 97% even after 5 cycles. Furthermore, no noticeable changes were observed in the crystalline phase structure throughout the experimental cycles. The synthesized m-WZC15 under these established conditions, demonstrated remarkable versatility and emerged as a promising candidate for water purification endeavors.

Geochemical-process extraction and interpretation using matrix factorization: a framework for verifying effectiveness through forward modeling and inversion analysis

Matrix factorization techniques, such as principal component analysis (PCA) and independent component analysis (ICA), are widely used to extract geological processes from geochemical data. However, their effectiveness in accurately identifying geological processes remains uncertain due to the heuristic nature of these methods. This study introduces a synthetic data-based framework to evaluate the validity of matrix factorization for geochemical process extraction. By constructing a forward model that simulates geochemical weathering, we generated synthetic datasets replicating real-world geochemical compositions, incorporating both the elemental leaching during fluid-rock interactions and the compositional heterogeneity of the original rocks. These datasets were analyzed using PCA and ICA, with preprocessing steps that included standardization and log-ratio transformation to address the challenges posed by compositional data. The results indicate that PCA and ICA effectively extracted the two key geological processes -elemental leaching and original rock heterogeneity-from the synthetic datasets. Among these methods, ICA combined with log-ratio transformation provided the most accurate separation of independent geochemical processes, particularly under ideal conditions with sufficient samples. To quantitatively validate the extracted basis vectors, we estimated elemental mobility parameters during weathering and compared them with known values in the synthetic dataset, demonstrating the applicability of our approach in quantifying geological processes. This study highlights the advantages of a bilateral approach that integrates forward modeling and inversion analysis to enhance the reliability of geochemical process interpretation. The proposed framework offers a systematic methodology for identifying and quantifying underlying geological processes from high-dimensional geochemical data, with potential applications in geochemistry, environmental science, and resource exploration.

Potash Ore Processing: Technology Research and Physicochemical Properties

The Republic of Kazakhstan is endowed with a distinctive endowment of potash ores, concentrated in the West Kazakhstan and Aktobe regions. These reserves are regarded as one of the largest in the world. The proven reserves are estimated at approximately 6 billion tons and are distributed across four major deposits: These are the Zhilyanskoye, Satimola, Inderskoye and Chelkar deposits. The article provides a concise overview of the major potassium salt deposits and the chemical composition of the associated minerals. Notwithstanding the existence of these deposits, the production of potash salts in the country, for which there is an ever-increasing demand, is yet to be established, resulting in a high level of demand. In light of this, it is imperative to conduct a comprehensive investigation into the mineralogical and chemical composition of these promising potash ores, with a view to identifying viable methods for processing natural salt systems into products that meet the high demand both within the domestic fertiliser and salt market and abroad. The Satimola deposit represents one of the largest silvinite basins yet to be sufficiently studied, and its industrial development has yet to commence. The analysis of raw materials and products was conducted using a combination of spectral microscopy, X-ray analysis, and differential thermal analysis. A comprehensive study of the composition of the silvinite ore from the Satimola deposit has been conducted. The elemental composition and the ratio of potassium and sodium salts in the mineral were established. The ore was found to have a heterogeneous composition, with sodium chloride representing the dominant component.

Development of a Single-Cell Spatial Metabolomics Method for the Characterization of Cell-Cell Metabolic Interactions.

Tumor microenvironment (TME) is characterized by complex cellular composition and high molecular heterogeneity. Characterizing the metabolic interactions between different cells in the TME is important for understanding the molecular signatures of tumors and identifying potential metabolic vulnerabilities for tumor treatment. In this research, we develop a single-cell spatial metabolomics method to profile cell-specific metabolic signatures and cell-cell metabolic interactions using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). Different low-molecular-weight metabolites and lipids including glutamate, aspartate, glutamine, taurine, phenylalanine, glutathione, fatty acids, phospholipids, etc. were successfully detected and imaged after optimizing cell culture conductive slides, cell washing, and fixation procedures. Subsequently, we carried out single-cell spatial metabolomics on H460 large-cell lung cancer cells, HT-29 colorectal cancer cells, A549 lung cancer cells, HUH-7 liver cancer cells, and cancer-fibroblasts coculture system. We revealed that the metabolic profiles of both cancer cells and fibroblasts were altered after cell coculture. Glutamate and aspartate significantly increased in fibroblasts after coculture with cancer cells, corresponding to their indispensable roles in the creation of pro-cancer microenvironment. In addition, we discovered that the expressions of fatty acids and phospholipids in tumor cells and fibroblasts were also changed after cell coculture, which is closely related to the competition for energy and nutrient metabolites between different cells. We anticipate this single-cell analysis method to be broadly used in the investigations of diverse cellular models and cell-cell metabolic interactions.

Comprehensive Rheological Study of Post‐Consumer Recycled Polypropylene: Analyzing the Influence of Waste Origin on Material Flow Properties

ABSTRACTRecycling of post‐consumer waste has emerged as a key strategy to reduce environmental impact and conserve resources, particularly in the production of sustainable polymers. The development of high‐quality recycled polypropylene (rPP) from household waste, such as the Systalen recyclate produced by Der Grüne Punkt (Green Dot), exemplifies this progress. Systalen is manufactured using a patented purification and recycling process designed to produce consistent, high‐quality rPP from post‐consumer waste streams, significantly reducing CO2 emissions compared to virgin plastics. This study provides a comprehensive rheological characterization of Systalen rPP, focusing on the influence of its waste origin on the material's flow properties. Advanced rheological methods, including oscillatory shear and rotation rheometry, were used to evaluate viscoelastic properties, flow stability, and processing behavior. Results reveal notable variations in flow characteristics due to the heterogeneous composition and potential contaminants inherent to post‐consumer waste, impacting shear thinning behavior, complex viscosity, and relaxation times. This research highlights the necessity of optimized processing strategies tailored to such recyclates to ensure their consistent performance. The findings emphasize the potential of Systalen rPP as a reliable secondary raw material for a wide range of applications (e.g., textile industry), supporting circular economy initiatives and reducing reliance on virgin resources.