Interface Focus

Maternal thermal strain is associated with adverse pregnancy outcomes, yet fetal temperatures cannot currently be directly measured, limiting quantification of fetal thermal strain. Here, we develop two steady-state models for estimating internal temperatures in a near-term fetus. First, we improve the only previously published human fetal thermoregulation model, deriving a closed-form solution within its simplified uniform-cylinder representation. Second, we introduce a multilayer, anatomically segmented model that resolves tissue-specific temperatures. Both couple the fetal body to central blood pool and amniotic fluid compartments and incorporate a new placenta-umbilical cord heat-exchanger representation. Predictions agree with available intrauterine scalp measurements, with fetal core and head-center temperatures approximately 0.5{degrees}C and 0.8{degrees}C above maternal core, respectively. Physiologically plausible changes in umbilical cord heat-exchanger effectiveness or blood flow increased fetal temperatures by approximately 0.3{degrees}C. These models enable estimation of otherwise inaccessible temperatures, while the multilayer formulation lays a foundation for transient, coupled maternal-fetal thermoregulation modeling.

Background Tumor hypoxia and abnormal vasculature are closely associated with aggressiveness in solid tumors. Therefore, noninvasive assessment of these features in primary breast cancer is needed. Photoacoustic (PA) imaging is an emerging modality that enables real-time visualization of vascular architecture and hemoglobin oxygenation. Methods Breast PA imaging was performed in patients with primary breast cancer using a bed-type PA imaging system equipped with a hemispherical sensor and a flat specimen holder enabling mild breast compression. Three independent evaluators assessed predefined characteristics of tumor-associated vasculature: centripetal/disrupted vessels and intratumoral vessel-like signals. Oxygenation (S-factor) of tumor-associated vessels was estimated using dual-wavelength laser irradiation at 756 and 797 nm. Results PA imaging was performed in 9 tumors from 8 patients. Eight tumors were evaluable, after the exclusion of 1 tumor with segmental bloody discharge. Centripetal/disrupted vessels were identified in 7 tumors (87.5%). Intratumoral vessel-like signals were observed in all tumors (100%), with higher signal density than in surrounding tissue in 5 lesions (62.5%). Increased intratumoral signal density was associated with a higher Ki67-labeling index (two-sided P = .01). Mean intratumoral S-factor level (76.9% {+/-} 9.1%) was significantly lower than that of peritumoral vessels at 5 mm (86.4% {+/-} 5.9%) and 20 mm (88.5% {+/-} 4.9%) from the tumor margin (two-sided P < .01). Conclusion PA imaging with a flat specimen holder enables noninvasive visualization of tumor-associated vasculature with reduced oxygenation in primary breast cancer. This approach may provide a novel imaging platform for the early detection and functional assessment of breast cancer.

Cerebral aneurysms are abnormal outpouchings of arteries within the brain and occur in [~]1 in 30 adults. Their initiation, growth, and rupture have been linked to focal blood flow abnormalities--often termed "disturbed" or "hostile" hemodynamics--but commonly-used hemodynamic metrics yield conflicting associations with pathology and lack a unifying mechanistic interpretation. Building on a theoretically-grounded link between wall shear stress and near-wall vorticity, we hypothesized that a topology-based description of near-wall flow can operationalize the concept of hostile hemodynamics in a reproducible way. Inspired by atmospheric tornadic phenomena, we sought a principled taxonomy of coherent near-wall fluid structures with potential mechanobiological and clinical implications. Using high-fidelity computational fluid dynamics simulations in anatomically realistic geometries, we identified coherent near-wall fluid structures whose organization mirrors well-studied atmospheric phenomena: tornado-like columnar rotating cores; downburst-like nonrotating wall-impinging jets with tangential outflow, roll-cloud-like tangential vortices; and mixed configurations. These tornadic events on the aneurysm luminal surface were identified from wall shear stress topology, consistent with its theoretical connection to near-wall vorticity kinematics. The presence of tornadic phenomena--and their imprints on the aneurysm wall--was independently observed in vivo using 4D flow magnetic resonance imaging. By translating concepts from atmospheric physics into vascular biomechanics, this topology-based framework yields a unified mechanistic language for describing near-wall hemodynamics, resolving blood flow complexity into interpretable and reproducible coherent fluid structures, enabling standardized hemodynamic phenotyping, and supporting hypothesis-driven studies of aneurysms and other cardiovascular diseases where greater fluid-mechanical specificity and interpretability may strengthen links between mechanobiology and clinical risk.

IntroductionPreeclampsia is characterized by a pro-inflammatory, anti-migratory and anti-angiogenic placental phenotype. Impaired spiral artery remodeling stemming from trophoblast dysfunction is a key pathogenic mechanism. Little is known about the processes that govern trophoblast function normally and in preeclampsia. In preeclampsia, placental Let-7b-5p is reduced. The objectives of this study were to determine the normal function of Let-7b-5p in human trophoblast cells, to examine whether the ssRNA sensors, Toll-like receptor (TLR) 7 and/or TLR8 are mediators of trophoblast Let-7b-5p function, and whether disruption of this pathway promotes a preeclampsia-like phenotype in the trophoblast. MethodsThe human first trimester trophoblast cell line, Sw.71, was transfected with a Let-7b- 5p mimic, a Let-7b-5p inhibitor, or scramble control. Cells were treated with or without the TLR7 inhibitor IRS661 or the TLR8 inhibitor CUCPT9a. Trophoblast migration was measured using a two-chamber assay and interactions with human endometrial endothelial cells (HEECs) was measured using a 3D matrigel model. Trophoblast anti-angiogenic sFlt-1 release was measured by ELISA and sFLT1 mRNA measured by RT-qPCR. ResultsTransfection of trophoblast cells with a Let-7b-5p mimic elevated migration through activation of TLR7 and TLR8, while in a TLR7-dependent manner, the Let-7b-5p mimic negatively regulated sFlt-1 production. Furthermore, inhibition of trophoblast Let-7b-5p reduced migration, elevated FLT1 mRNA expression and sFlt-1 release, and reduced trophoblast-endometrial endothelial cell interactions. ConclusionsThis study highlights a role for TLR7/TLR8-activating Let-7b-5p in promoting normal trophoblast function and endothelial interactions and that disruption in this miR-driven signaling pathway may be relevant to processes driving a pre-eclamptic placental phenotype. HighlightsTrophoblast migration is positively driven by Let-7b-5p activating TLR7 and TLR8 Let-7b-5p, via TLR7, negatively regulates trophoblast anti-angiogenic sFlt-1 production. Inhibition of trophoblast Let-7b-5p reduces trophoblast migration and normal interactions with endometrial endothelial cells, while sFlt-1 production is elevated. TLR7/TLR8-activating Let-7b-5p promotes normal trophoblast function and endothelial interactions and disruption in this miR-driven signaling pathway may promote a preeclamptic placental phenotype.

Direct experimental analysis of the mammalian oviduct is constrained by limited tissue access and the short lifespan of ex vivo preparations. Extracellular matrix-embedded three-dimensional epithelial organoids provide longer-term in vitro models. However, their inward-facing apical surface and the absence of supporting stromal cells limit physiological studies of the oviduct, including ciliary activity and maternal-embryonic interactions. Here, we provide a step-wise protocol detailing the generation of mouse and human oviductal assembloids in which epithelial cells form an outward-facing (apical-out) layer around a stromal core. Epithelial and stromal cells from adult mouse oviducts or human Fallopian tubes are isolated, expanded separately, and subsequently aggregated in a rotational culture system. The protocol also outlines morphological and immunostaining criteria for confirming cellular organization, whole-mount detection of external cilia, measurement of ciliary beat frequency, and co-culture of mouse assembloids with preimplantation embryos. Mouse and human assembloids retained epithelial and stromal identity and displayed cilia at the accessible outer surface. In a proof-of-concept experiment, embryos co-cultured with the assembloids developed to blastocysts at a rate similar to that of in vivo-derived blastocysts. This reductionist system provides a straightforward and tractable model to investigate oviduct physiology and embryo-maternal communication while allowing direct manipulation and observation of the epithelial interface. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=148 SRC="FIGDIR/small/743297v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@1917a7borg.highwire.dtl.DTLVardef@41d7org.highwire.dtl.DTLVardef@e2bf98org.highwire.dtl.DTLVardef@90c9f3_HPS_FORMAT_FIGEXP M_FIG C_FIG SummaryThe protocol for generating mouse and human oviductal assembloids by combining epithelial and stromal cells for studying oviductal function in an in vitro setting.

Objective: Tumor protein D52 (TPD52) is aberrantly expressed in various malignancies; however, its systematic expression profile, prognostic significance, tumor microenvironment associations, and functional mechanisms in breast cancer remain poorly defined. Methods: GEO and TCGA breast cancer expression datasets were integrated to identify differentially expressed genes (DEGs). We evaluated the diagnostic performance of TPD52 via protein-protein interaction (PPI) network analysis, GO/KEGG enrichment analysis and eleven machine learning algorithms. Immunohistochemistry verified TPD52 protein expression in clinical specimens, and Kaplan-Meier analysis assessed its prognostic significance. Analysis of single-cell transcriptomic data (GSE176078) revealed the cell-type-specific distribution of TPD52 and its intercellular communication network in the breast cancer microenvironment. Weighted gene co-expression network analysis (WGCNA) explored relationships between TPD52 and tumor microbiome, hypoxia signatures as well as microsatellite instability. Moreover, TPD52 was knocked down by siRNA in MCF7 cells, and its impacts on cell migration, invasion, proliferation and the MAPK/ERK signaling pathway were examined through wound healing, Transwell, CCK-8 and Western blot assays. Results: TPD52 was significantly overexpressed in breast cancer tissues at both the mRNA and protein levels. A random forest-based diagnostic model demonstrated high accuracy across multiple datasets. Kaplan-Meier analysis revealed that elevated TPD52 expression was associated with longer overall survival in specific subgroups, including the basal-like subtype, invasive lobular carcinoma, and N0/N1 stages. Single-cell analysis showed that TPD52 was predominantly expressed in tumor epithelial cells, which occupied a central position within the intercellular communication network. WGCNA further identified a positive correlation between TPD52 and a hypoxia-associated microbial module, as well as a negative correlation with a microsatellite instability module. In vitro functional assays confirmed that TPD52 knockdown significantly suppressed the migration, invasion, and proliferation of MCF7 cells, and led to reduced p-ERK1/2 protein levels. Conclusion: TPD52 promotes the malignant phenotypes of breast cancer cells through activation of the MAPK/ERK signaling pathway, yet its prognostic significance is subtype- and microenvironment-dependent. These findings establish TPD52 as both a diagnostically valuable biomarker and a mechanistically defined potential therapeutic target.

Cellular systems must act robustly to maintain organismal health, including maintaining biophysical properties that allow for appropriate cellular function, and adapting these properties through changes such as those that occur during cell division. However, we still lack tools to measure many of these physical properties with precision in the living cell. For example, the mechanical properties of the nucleoplasm, the fluid-like substance that fills the nucleus, have not been fully characterized. To investigate these properties, we have turned to the fission yeast Schizosaccharomyces pombe (S. pombe), a well-established, genetically tractable model organism that has been used extensively for studying a variety of cell biophysical processes and structures, including the cytoskeleton and cell division. It is an apt system for studying how the nucleus adapts over the course of the cell cycle, since it undergoes closed mitosis, where the nuclear envelope remains intact during cell division. Studying nucleoplasm properties over the course of closed mitosis may help reveal how nuclear volume, shape, surface area expansion, and chromosome segregation are linked and coordinated. To measure nucleoplasm material properties in S. pombe, we have paired Fluorescence Correlation Spectroscopy (FCS) with a photoswitchable fluorophore, enabling fine control over fluorescent intensity inside live cells. We infer material properties from FCS measurements, while the photoswitchable probe enables confocal imaging in conjunction with these measurements, yielding corresponding information about cellular state and dynamics. Interestingly, we find that nucleoplasm material properties do not vary significantly over the cell cycle. Future studies will use this tool to examine how diverse molecular and genetic perturbations alter nucleoplasmic properties, providing insight into how these properties maintain nuclear function and protect genomic integrity over the cell cycle and during development.

Global incidence and outcomes of glioma have been found to vary significantly by region, however research into the disease continues to lack diversity. Here we investigated epigenetic patterns in glioma subtypes from cohorts collected from China and the USA. We retrospectively analysed the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) datasets following reclassification of glioma subtypes based on the WHO 2021 central nervous system (CNS) tumour classification. We used DNA methylation and transcriptomics data to identify methylation-driven cancer genes in the CGGA cohort, assessed their prognostic value and compared against the non-Hispanic White cohort in the TCGA database to consider ethnic influence. Furthermore, we used machine learning classification and clustering techniques to identify methylation patterns in glioma subgroups. Here, we showed that DNA methylation profiles of CGGA glioblastomas have a methylation signature more similar to TCGA high-grade astrocytomas: 58.1% of CGGA glioblastomas were identified as high-grade astrocytomas using classification modelling. Assessment of survival revealed that CGGA glioblastoma patients had a significantly better survival rate than non-Hispanic White glioblastoma patients (p = 0.037). Four key methylation-driven genes were identified in the CGGA glioblastoma samples: GLDN, PRKDC, S100A1 and NCAPH. Hypermethylation of GLDN significantly suppressed gene expression in all glioma subtypes in only the East Asian cohort; a gene that has not been previously described as a driver in gliomas. Together these data suggest alternative epigenetic mechanisms occurring in glioma subtypes of different ethnic populations, which is important for our understanding of glioma and strategies for personalized treatment.

BackgroundEpidermal growth factor receptor (EGFR) amplification occurs in [~]50% of IDH-wildtype glioblastoma (GBM) cases, frequently accompanied by expression of the oncogenic EGFRvIII variant. Although EGFR represents an attractive therapeutic target, EGFR-directed therapies have shown limited clinical efficacy in GBM. Resistance to kinase inhibitors is frequently attributed to activation of compensatory signaling pathways ("kinome rewiring"). We therefore investigated whether EGFR inhibition in GBM induces broad adaptive kinase responses that could be co-targeted to overcome resistance. MethodsWe molecularly profiled 29 patient-derived GBM cell lines for EGFR status and selected five representative models spanning EGFR amplification states for functional analyses. Cells were treated with EGFR inhibitors and responses were assessed using viability assays, time-resolved immunoblotting, and phosphoproteomics (LC-MS/MS) with kinase activity inference. ResultsEGFR inhibitors preferentially impaired viability in EGFR-driven models and transiently reduced EGFR phosphorylation during the initial response. However, partial restoration of EGFR phosphorylation and downstream signaling occurred after 24 hours of inhibitor exposure. Phosphoproteomics revealed no evidence of broad kinome rewiring within this timeframe but instead identified increased EGFR abundance, associated with partial restoration of EGFR pathway activity. The phosphorylated-to-total EGFR ratio remained stable, indicating that increased EGFR abundance may enable persistent residual kinase activity despite continued, but incomplete, target inhibition. ConclusionsEarly responses to EGFR inhibition in GBM were not characterized by broad kinome rewiring but by restoration of EGFR signaling associated with increased EGFR abundance. These findings suggest that adaptive signaling remains largely EGFR-dependent despite inhibitor exposure, identifying regulation of EGFR abundance as a potential contributor to therapeutic resistance. Key points- Early responses to EGFR inhibition occur without evidence of broad kinome rewiring. - EGFR signaling is restored during sustained inhibitor exposure. - Increased EGFR abundance is associated with restoration of pathway activity. Importance of the studyAdaptive resistance to EGFR-targeted therapies in GBM is commonly attributed to activation of alternative signaling pathways. Using patient-derived GBM models and phosphoproteomic profiling, we show that early adaptive responses to EGFR inhibition are not characterized by broad kinome signaling rewiring but instead remain centered on reactivation of EGFR signaling. Our findings suggest that increased EGFR abundance in response to inhibitor exposure may enhance residual EGFR signaling sufficiently to partially restore downstream pathway activity. These results indicate that early adaptive responses to EGFR inhibition may remain largely EGFR-dependent, potentially limiting the effectiveness of strategies primarily aimed at co-targeting alternative signaling pathways. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/744581v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@8d4ea3org.highwire.dtl.DTLVardef@125e3eeorg.highwire.dtl.DTLVardef@9742c0org.highwire.dtl.DTLVardef@9f4fa8_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundPlatelet activation in flowing blood is a multiscale process in which vessel-scale hemodynamics, red blood cell (RBC) mechanics, adhesive receptor interactions, and intracellular signalling jointly determine thrombotic risk. Individual components are well studied, but a single reduced description that carries each explicitly from vessel-scale flow to mechanosensitive calcium entry, with dimensionally consistent couplings, remains uncommon. ObjectivesWe develop and analyse a reduced, six-module mechanobiological framework for platelet priming spanning the cascade from hemodynamic shear to mechanosensitive calcium entry, and we delineate which elements are supported by existing evidence and which are new, testable hypotheses. MethodsThe framework comprises six coupled modules: (I) hemodynamic forcing from the incompressible Navier-Stokes equations, with an objective principal-strain-rate measure for extensional flow; (II) RBC-mediated platelet margination and near-wall delivery, closed by a near-wall arrival flux; (III) von Willebrand factor (VWF) activation with a bounded kernel and glycoprotein Ib (GPIb) catch-slip capture, resolved through an explicit contact area and a bond-dependent mobility that progressively immobilises wall-interacting platelets; (IV) a single-load membrane-stimulus formulation; (V) mechanosensitive gating and a dimensionally consistent cytosol-store calcium model with extracellular influx; and (VI) a phenomenological mechanical-memory state. We formally derive that the single-platelet stochastic dynamics and the continuum population balance form a Fokker-Planck pair, with the spatially varying diffusivity handled by an explicit drift correction. ResultsThe framework yields a family of mechanochemical dimensionless groups delineating priming regimes. Its central prediction is reformulated as a falsifiable, history-sensitive signature: in a conditioning-test protocol, a low-tension conditioning block charges the memory state, and a fixed sub-threshold test pulse then reports a delay-dependent calcium facilitation that decays on the memory time{tau} m and is distinguishable from no-memory gating, channel adaptation, and residual-calcium priming. We show explicitly that the previously proposed pulsatile-versus-monotone contrast is a nonlinear convexity/thresholding effect of the gating nonlinearity--its difference-in-differences is approximately zero-- and is therefore not a valid test of memory; the conditioning-test signature is. A second prediction links RBC stiffening to reduced near-wall delivery and captured-platelet calcium response, upstream of intrinsic platelet signalling. ConclusionsThe framework provides a dimensionally consistent, mechanistically grounded and hypothesis-generating description linking hemodynamic forcing to mechanosensitive calcium entry. It demonstrates how history-dependent platelet priming may arise from a phenomenological sensitisation state and proposes a conditioning-test protocol for comparison against adhesive, channel and intracellular-store persistence. The framework is calibratable rather than validated, and the quantitative outputs shown use representative uncalibrated parameters.

Scientific agents can produce plausible answers while remaining unable to establish whether the computation behind an answer is executable, recoverable, or reproducible. We present BloClaw, an AI4S workstation built around a simple principle: a scientific agent should know what it can do, show how it did it, and state what remains unvalidated. Each capability declares an execution state, input constraints, dependencies, expected outputs, and scientific limitations. Natural-language requests are translated into structured tasks, validated against this registry, executed through scientific tools, and recorded in a provenance-aware Living Lab Notebook. The system is designed to detect invalid inputs, failed tool calls, missing dependencies, and remote timeouts, and to route them to repair, retry, or escalation. The implemented and tested scope comprises RDKit-based molecular property and rule screening, protein structure analysis, docking-pose inspection, 3D visualization, and structured reporting. We demonstrate the workflow on a PubChem-retrieved osimertinib structure and a supplied 6LU7 docking artifact: the former yields deterministic descriptors (molecular weight 499.619 Da, cLogP 4.5098, TPSA 87.55 A^2), while the latter contains 2,387 protein ATOM records, 309 residues, and nine pose records. These examples are workflow demonstrations, not efficacy or affinity studies. Beyond retrospective prediction, the manuscript specifies a prior-minimized constructive mode in which a desired function is compiled into explicit physical, chemical, and systems constraints, candidate mechanisms are simulated, and observations are reintroduced for calibration and falsification; this is a proposed extension rather than a result of the present case studies. We describe an evaluation protocol that compares BloClaw with a standard single-agent workflow and fixed-script execution using task completion, scientific correctness, recovery success, provenance completeness, reproducibility, human review time, latency, and cost. This manuscript reports the system design, verified capability boundary, deterministic software artifacts, and a reproducible evaluation protocol; it does not claim benchmark improvements before those experiments are run. BloClaw is an execution and accountability layer for AI-assisted research, complementing expert review and experimental validation rather than replacing them.

Background: Although PSEN1 is best known for its role in Alzheimer's disease, it also regulates neural development and cerebellar morphogenesis. Medulloblastoma (MB) is the most common malignant pediatric brain tumor and arises from disrupted cerebellar developmental programs. The clinical significance of PSEN1 in MB remains unknown. We investigated the prognostic value and transcriptional correlates of PSEN1 expression across molecular subgroups and subtypes of MB. Methods: Public bulk and single-cell transcriptomic datasets were used to examine PSEN1 expression, associations with overall survival (OS), and transcriptional correlates in MB. The SHH -associated transcriptional pattern was evaluated in an independent cohort, and PSEN1 expression was further examined in the developing human cerebellum and across pediatric brain tumor types. Genes strongly correlated with PSEN1 in SHH MB were subjected to Gene Ontology (GO) enrichment analysis. Results: High PSEN1 expression was consistently associated with significantly longer OS exclusively in SHH MB. The PSEN1-associated transcriptional pattern was reproduced in an independent SHH cohort. PSEN1 was expressed across developing cerebellar cell populations and pediatric brain tumor types, with MB showing intermediate expression among the tumor entities examined. In SHH MB, PSEN1 was associated with a coordinated transcriptional program enriched for RNA homeostasis, intracellular membrane trafficking, protein quality control, lipid and calcium signaling, and developmental pathways. Conclusions: High PSEN1 expression identifies a favorable-prognosis subset of SHH MB and is associated with a distinct transcriptional program related to endomembrane organization and cellular homeostasis rather than canonical SHH signaling. These findings suggest that PSEN1 may mark a developmentally distinct tumor state and generate new hypotheses regarding subtype-specific developmental programs in MB.

Tumors consist of heterogeneous phenotypic cells, such as normoxic cells, which are highly proliferative, and hypoxic cells, which are less proliferative. Their phenotypic switching depends on tumor microenvironmental factors, such as oxygen and nutrient concentrations supplied by local blood vessels. However, during ongoing angiogenesis, the process of sprouting new blood vessels at the tumor site from pre-existing blood vessels, and how this phenotypic switching affects and impacts tumor growth, remains poorly understood. In this article, we formulate a mathematical model to elucidate the crosstalk between vasculature and tumor cellular heterogeneity during tumor progression. The model results show a strong agreement with the experimental data. Our simulation results demonstrate that ongoing angiogenesis increases tumor growth rate. In addition, we observe that the influence of hypoxic cells on phenotypic switching from normoxic to hypoxic is more pronounced than their influence on the transition from hypoxic to normoxic. Furthermore, we perform a global sensitivity analysis using the Sobol's method to assess the importance of the model's parameters. It highlights that the volume at which blood vessels attain half-maximal rate has the maximum effect on the model.

Preeclampsia (PE) is a hypertensive pregnancy-specific disorder and a leading cause of maternal and fetal mortality. A common feature of PE placentas and maternal plasma is dyslipidemia, or abnormal lipid levels, which can increase oxidative stress and endothelial dysfunction. However, the precise transcriptional, post-transcriptional, and epigenetic mechanisms underlying these abnormalities remain poorly characterized. Identifying such changes may clarify disease mechanisms and identify lipid-related PE biomarkers. We conducted a large-scale meta-analysis integrating public placental datasets from NCBI GEO, comprising four DNA methylation (DNAm) datasets (n = 172), three RNA-sequencing datasets (n = 92), and an independent RNA microarray validation cohort (n =146). We evaluated differential DNAm (limma), gene expression (DESeq2), transcript-level shifts (Swish), and alternative splicing (rMATS) in PE versus control placentas, with all analyses stratified by fetal sex via an interaction term model. We also performed placental cell-type deconvolution to quantify PE-associated cell-type proportion changes. Our results demonstrated that lipid-related regulation changes in PE placentas occur primarily at the gene and transcript level, with DNAm showing no changes. We also identified significant isoform switching in PE that were undetected by differential gene expression analysis, and primarily driven by alternative transcription initiation and termination sites rather than alternative splicing. A subset of these isoform switches mapped to pathways dysregulated in PE and were predicted to cause functional protein changes. An interaction term model identified several sex-specific differentially expressed genes (DEGs) in PE, including a subset of male-specific downregulated genes involved in oxidative metabolism. However, many of the remaining sex-specific DEGs across both sexes were previously uncharacterized in the literature. These findings suggest that transcriptional and isoform-level regulation play a role in PE-associated dyslipidemia, with certain regulatory pathways displaying fetal sex-specific patterns. Highlights- Preeclampsia-associated dyslipidemia manifests at the gene and transcript level - Reciprocal isoform switches were missed by standard gene-level analyses - Alternative transcript initiation and termination drove isoform switching - Sex-interaction modeling identified sex-specific transcriptional shifts in PE

Based on our experimental observation of activation state oscillations of different frequencies used to communicate information by the master human stress response regulator protein p38 MAPK 1, we develop a simple graphical approach for understanding and predicting the behavior of complex biological networks acting upon signals carrying information as different frequency waves of chemicals. This approach uses the same techniques used for analyzing and understanding information transmission using waves of electrical currents and fields used in electrical alternating current (AC) circuits. We show how biological components can be organized to behave as standard components found in electronic telecommunications circuits. Finally, we demonstrate how such components can be organized into complex biological signaling cascades whose behavior can be qualitatively and quantitatively understood, and whose output resembles that experimentally observed in p38.

Decellularized extracellular matrix (dECM) scaffolds are increasingly used in regenerative medicine, yet the extent to which processed placental dECM retains properties capable of influencing cellular responses remains unclear. This study combines functional cell assays with deep learning-enabled quantitative imaging to determine how dehydrated placental ECM regulates cellular behavior across multiple human cell lineages. Human dermal fibroblasts, cardiac fibroblasts, and osteoblasts were cultured on dehydrated placental ECM or standard cell culture surfaces and assessed for cell attachment, viability, extracellular matrix production, and nuclear morphology. Placental dECM supported attachment and survival across all three cell types, while Pro-Collagen I Alpha 1 secretion varied by cell lineage relative to negative controls. To identify structural responses associated with scaffold culture, an automated imaging pipeline combining Cellpose-based nuclear segmentation with nuclear morphometric analysis was used to quantify nuclear area, eccentricity, and circularity. Quantitative profiling of hundreds of nuclei revealed scaffold-dependent remodeling of nuclear morphology that was not apparent by conventional microscopy. Cells cultured on placental dECM exhibited reduced nuclear area and increased nuclear eccentricity, while cardiac fibroblasts and osteoblasts showed alterations in nuclear circularity. These lineage-dependent morphological responses demonstrate that placental dECM provides more than a permissive substrate for cell attachment and is associated with measurable changes in cellular architecture following processing. Together, these findings support the biological relevance of processed placental dECM as a regenerative biomaterial and demonstrate the utility of quantitative single-cell morphometric analysis for detecting cell-material interactions that may not be apparent through qualitative imaging alone, guiding the rational design of regenerative therapies.

Introduction: Metastatic spinal lesions substantially alter vertebral mechanical properties and increase fracture risk. Computed tomography (CT) based finite element (FE) models can estimate vertebral strength, but their accuracy depends on how CT derived material properties are represented. This study evaluated the effect of two material grouping strategies on simulated strength and stiffness in metastatic vertebrae. Methods: We compared Adaptive Clustering (AC) with Uniform fixed width grouping in 44 vertebrae from 11 donors (8 osteolytic, 12 osteoblastic, 12 mixed, 12 no observed lesion (NOL)). FE models were generated based on CT scans with 2 to 500 material groups and compared for material mapping error and simulated strength and stiffness. Overall and lesion stratified agreement with experimental measurements was assessed in an exploratory analysis. Results: AC showed significantly lower Young's modulus root mean square error than Uniform (p < 0.05). Simulated strength and stiffness stabilised by 50 material groups. At 50 groups, simulated strength showed moderate correlation with experimental strength overall (R2 = 0.57), strongest in NOL vertebrae (R2 = 0.82) and lower in lesion-bearing vertebrae (R2 = 0.4-0.59). Stiffness showed weaker correlation overall (R2 = 0.27), highest in NOL vertebrae (R2 = 0.48) and negligible in mixed lesions (R2 = 0.007). Bland Altman analyses indicated systematic underestimation of experimental fracture load. Discussion: AC improved material-mapping fidelity, whereas increasing material groups beyond 50 had little influence on simulated strength or stiffness. Numerical stabilisation therefore did not imply experimental accuracy. Lesion stratified findings were exploratory and should be interpreted cautiously because of limited subgroup sizes.

Abstract Background: Intraductal papillary mucinous neoplasms (IPMNs) are recognized as precursor lesions to pancreatic ductal adenocarcinoma (PDAC). However, the molecular programs underlying progression from low-grade dysplasia to advanced disease remain incompletely characterized. Herein, we performed an integrated plasma and tissue-proteomic analyses coupled with spatial and single-cell transcriptomics to identify biologically coherent remodeling programs reflected in circulation that distinguish IPMN by dysplasia grade and invasive disease. Methods: Using the O-link proximity extension assay platform, a panel of 1,104 proteins were quantified in plasma samples collected from patients with low-grade (LG) IPMN (n=30), high-grade (HG) IPMN with or without associated PDAC (IPMN/PDAC; n=40) and PDAC without IPMN (n=8). Predictive performance of individual biomarkers were assessed; likelihood ratio testing was performed to identify protein biomarkers that were complementarity with CA19-9 for risk of malignancy of IPMN. Findings were intersected with available spatial (N= 13) and single-cell (N= 6) transcriptomic datasets of IPMN tissues as well as mass spectrometry-based proteomic profiles of an independent set of resected human IPMN tissues (N= 9). Results: A total of 28, 43, and 35 circulating proteins were found to be differential in HG, IPMN/PDAC, and HG + IPMN/PDAC cases compared to LG IPMN. Among differential proteins were known PDAC-associated markers CEACAM5, CTRC, and REG3A as well as several biomarkers reflecting cytoskeletal and extracellular matrix remodeling and inflammatory processes. Focusing on cytoskeletal and ECM-related proteins and using likelihood ratio testing, an OR rule considering CA19-9, BGN, and ITGB1BP1 achieved overall sensitivity of 48.7% for HG + IPMN/PDAC, including 38.1% sensitivity for HG IPMN, at an overall specificity of 90%, which was improved compared to that of CA19-9 alone (overall sensitivity of 28.2%; McNemar Exact test 1-sided p-value: 0.011). Integrated proteomic and spatial transcriptomic datasets of IPMN tissues revealed coordinated alterations cytoskeletal and ECM remodeling and elevated matrix stiffness as prominent features associated with IPMN/PDAC, which paralleled concordant increases in BGN and ITGB1BP1. Cell-type of origin analyses based on spatial and single-cell data further revealed fibroblasts and myeloid cells as primary contributors to expression levels of BGN whereas ITGB1BP1 was primarily expressed in neoplastic epithelium. Conclusion: Advanced IPMN dysplasia and invasive disease are characterized by coordinated tissue remodeling programs that are systemically reflected in circulating proteomic profiles. Blood-based biomarkers identified through our study, such as BGN and ITB1BP1, have potential to improve upon CA19-9 for risk stratification of IPMN to better guide clinical management.

Microbial fuel cells (MFCs) have been widely investigated as decentralized bioelectrochemical systems capable of converting organic substrates into electricity. However, their long-term autonomous operation is constrained by substrate depletion in the anode compartment, leading to metabolic starvation of electroactive biofilms and a decline in power output. Conventional MFC design treats substrate crossover through the membrane separator as a parasitic loss that reduces coulombic efficiency. In this work, we propose a conceptual inversion of this paradigm by considering controlled cathodic-to-anodic substrate crossover as a passive mechanism to sustain basal microbial metabolism during periods of substrate scarcity. A transport-reaction framework is developed to quantify the balance between membrane-mediated substrate flux and microbial maintenance demand within the anode biofilm. Based on this balance, a dimensionless maintenance crossover Damkohler number (Dam) is introduced to define three operational regimes: starvation-dominated (Dam >> 1), balanced autonomous (Dam {approx} 1), and crossover-dominated (Dam << 1). The framework integrates membrane transport theory with biofilm kinetics to evaluate the effects of separator properties, substrate gradients, and current-dependent electro-osmotic transport on system stability. Order-of-magnitude analysis indicates that achievable crossover fluxes span several orders of magnitude depending on separator characteristics, suggesting that membrane properties critically influence system behavior. This perspective reframes substrate crossover from a loss mechanism to a potential design variable, offering a conceptual tool for enhancing resilience and guiding separator selection in MFCs intended for long-duration, and low-maintenance operation. HighlightsO_LIControlled crossover can sustain microbial metabolism in MFCs C_LIO_LIIntroduces maintenance crossover Damkohler number (Dam) C_LIO_LIIdentifies regimes for autonomous and starvation operation C_LIO_LILinks membrane properties to long-term system stability C_LIO_LIReframes crossover as a design variable, not only a loss C_LI

Background: Low-dose computed tomography (LDCT) screening reduces lung cancer mortality but is limited by low uptake and associated with high rates of false-positives and indeterminate-nodules. Breath volatile organic compound (VOC) analysis is a non-invasive candidate biomarker approach that could complement LDCT, but prior work has relied on laboratory-based high-resolution mass spectrometry (HRMS), limiting point-of-care deployment. Methods: In this pilot study, breath samples were collected from 40 patients with treatment-naive, pathologically confirmed non-small cell lung cancer (NSCLC) and 25 lung-cancer-screening-eligible healthy controls. Paired samples were analyzed via a compact point-of-care GC-MS platform (CLARION) and a laboratory HRMS reference. Diagnostic classification models were built independently for each platform using elastic net logistic regression with leave-one-out cross-validation, and performance was evaluated by area under the receiver operating characteristic curve (AUC). Results: CLARION identified 103 VOCs across breath specimens, compared to over 900 identified by HRMS. Despite this difference in panel size, CLARION achieved diagnostic performance nearly identical to HRMS for distinguishing NSCLC cases from controls (AUC 0.864 vs. 0.863). Compared to controls, performance statistics were similar for early-stage NSCLC (AUC 0.854 vs. 0.841) and adenocarcinoma (AUC 0.770 vs. 0.787). VOCs of interest include p-cymene, phenol, propylbenzene, tetradecane, {beta}-ocimene, 2,3-dihydro-indole, and 1-methylthio-(Z)-1-propene. Conclusion: A compact, point-of-care breath GC-MS platform achieved diagnostic performance for NSCLC detection comparable to a laboratory HRMS reference despite a substantially smaller detected VOC panel. These findings support continued development of point-of-care breath VOC testing as a non-invasive, field-deployable complement to LDCT-based lung cancer screening.