Magnetic Resonance in Medicine

Quantitative microstructural magnetic resonance imaging (MRI) can noninvasively characterize tissue configuration at micrometer scales, but clinical uptake is limited by validation and optimization in human-relevant scenarios. Organoids are powerful human-relevant tissue models, yet translation is hampered by lack of non-destructive, longitudinal microstructural assessment. Bridging these gaps, microstructural MRI of living organoids can accelerate MRI biomarker and organoid development and validation. Here, we address key obstacles to enable organoid microstructural MRI. First, we use a unique 28.2 T MRI system to achieve spatial resolution with adequate signal-to-noise ratio and feasible scan times. Second, we implement flexible acquisitions with fast readouts to expand multivariate experimental capacity. Third, we develop a workflow combining 3D MRI and 3D lightsheet microscopy for cross-modality anatomical comparison beyond 2D. Using this platform, we demonstrate microstructural MRI of cortical organoids with resolutions down to (20 {micro}m)3, revealing anisotropy, heterogeneity, maturation-dependent differences, and temporal changes in cortical organoids. Correlative lightsheet microscopy confirms correspondence to axonal and nuclear architecture. This platform enables live-organoid MRI as a complementary tool to human- and animal imaging for robust microstructural assessment.

Conflicting evidence on scatter correction (SC) methods plagues quantitative myocardial perfusion SPECT (MPI), hindering standardized clinical protocols. This simulation study, utilizing the SIMIND Monte Carlo program and a highly realistic 4D XCAT phantom, systematically evaluates Dual Energy Window (DEW, with k=0.5) and Triple Energy Window (TEW) SC techniques. We uniquely investigate their performance across various photopeak window widths (2, 4, and 6 keV) and novel overlapped/non overlapped configurations specifically for Tc 99m MPI parameters largely unexplored in realistic cardiac models. Images were reconstructed with OSEM under uncorrected (UC), SC, and combined attenuation and scatter corrected (ACSC) conditions. Quantitative analysis focused on signal to noise ratio (SNR), contrast to noise ratio (CNR), defect contrast, and relative noise to background (RNB). Our findings consistently show ACSC's superior performance in CNR, SNR, and defect contrast, confirming its critical role. Interestingly, SC alone reduced noise but compromised defect contrast relative to UC, highlighting a potential trade-off without attenuation correction. Crucially, this study reveals minimal influence of photopeak window width and overlap configuration on image quality, and no significant difference between DEW and TEW across most metrics. These results provide essential evidence for optimizing quantitative MPI protocols, suggesting that for Tc 99m, the choice between DEW and TEW, and specific window settings, may be less critical than ensuring robust attenuation correction.

Real-time functional magnetic resonance imaging (fMRI) offers a powerful means of studying brain function adaptively, enabling experimental parameters to be updated dynamically in response to ongoing neural activity. However, current approaches remain limited by complex infrastructure requirements, bespoke implementations, and a lack of flexible frameworks for closed-loop neuroimaging, with many primarily focusing on neurofeedback experimental designs. Here we present AutoNeuro, an open-source framework for real-time fMRI acquisition, preprocessing, feature extraction, and adaptive experimental control. AutoNeuro connects directly to the MRI scanner, receiving reconstructed slices as soon as they become available, and streams them into a modular analysis pipeline designed for low-latency processing. Neural features are estimated at the temporal resolution of acquisition and are passed to a Bayesian optimisation agent that selects task conditions to maximise a user-defined objective function. Experimental conditions are represented within a bounded "experiment space", allowing heterogeneous conditions to be explored within a common coordinate system. We demonstrate AutoNeuro in a real-time fMRI experiment in which the system adaptively sampled task conditions to obtain a continuous map of brain response to the range of conditions contained within the experimental space. The system operated within the temporal constraints of real-time preprocessing and analysis, maintaining stable model estimates across iterations, converging on experimental conditions most relevant to the measured brain metric. These results establish AutoNeuro as a flexible platform for closed-loop neuroimaging, supporting hypothesis-driven optimisation as well as exploratory mapping of brain metrics across large experimental spaces.

Regional volumetric assessment of perinatal brain development is currently limited by the lack of consistent high quality multi-regional segmentation methods applicable to both fetal and neonatal MRI. We present Multi-BOUNTI, a deep learning pipeline for automated multi-lobe segmentation of fetal and neonatal T2w brain MRI. The method is based on a dedicated 43-label parcellation protocol and a 3D Attention U-Net trained on brain MRI datasets of subjects spanning 21-44 weeks gestational/postmenstrual age. The pipeline integrates preprocessing, segmentation and volumetric analysis, and was evaluated on independent datasets, demonstrating fast (< 10 min/case) and accurate performance with high agreement to manually refined labels. We demonstrate the application of the framework with 267 fetal and 593 neonatal MRI datasets from the developing Human Connectome Project without reported clinically significant brain anomalies to derive normative volumetric growth models across 21-44 weeks GA/PMA. These models were used to characterise developmental trajectories, assess differences between fetal and preterm neonatal cohorts, and analyse longitudinal changes. The resulting normative models were integrated into an automated reporting framework enabling subject-specific volumetric assessment via centiles and z-scores. Multi-BOUNTI provides a unified and scalable approach for perinatal brain segmentation and volumetry, supporting large-scale studies and facilitating future clinical translation. The full pipeline is publicly available at https://github.com/SVRTK/perinatal-brain-mri-analysis.

Harmonisation is widely used to mitigate site- and scanner-related batch variability in multisite neuroimaging studies and is particularly critical in longitudinal clinical trials, where detection of subtle biological or treatment-related changes depends on reliable measurement across scanners and timepoints. However, the effectiveness of harmonisation in small, heterogeneous clinical datasets remains insufficiently understood, particularly in relation to subject-level variability and consistency across acquisition settings, and its impact on both removal of technical variability and preservation of biological variation in pooled multisite analyses. We systematically evaluated a range of image-based and statistical harmonisation methods using a clinically realistic multisite, multiscanner structural T1-weighted (T1w) MRI test-retest dataset comprising three controlled acquisition scenarios: repeatability, intra-scanner reproducibility and inter-scanner reproducibility. Methods were applied under different batch specifications (site, scanner, or both) and performance was assessed within each scenario and in pooled data using a multi-metric framework capturing both technical and biological variability in volumetric imaging-derived phenotypes (IDPs) relevant to aging and dementia research. Across IDPs, before harmonisation variability was lowest in the repeatability scenario (median variability=0.6 to 2.7%, rank consistency {rho} [&ge;]0.9), with modest increases under intra-scanner reproducibility (0.5 to 3.2%, {rho}=0.5 to 1.0) and substantially greater variability under inter-scanner reproducibility conditions (1.7 to 19.2%, {rho} =-0.1 to 0.9). These results offer important information to consider for multisite study design, including sample size calculation in clinical trials. Harmonisation performance was strongly context dependent, with clearer benefits emerged in inter-scanner scenarios where both variability reduction and improvements in subject-level consistency were observed. In pooled data, approaches that explicitly modelled site as batch and accounted for repeated-measure structure showed greater consistency across IDPs in batch effect mitigation and more accurately reflected underlying biological variation. Our evaluation metrics enabled disentangling the removal of global batch effect while highlighting residual variability at the phenotype-specific or multivariate levels. These findings demonstrate that harmonisation cannot be treated as a one-size-fits-all solution and must be interpreted relative to the acquisition context, dataset structure, and downstream analytic goals. Multi-metric evaluation under realistic clinical constraints is essential to support reliable and translatable neuroimaging inference by ensuring appropriate correction of batch effects while preserving longitudinal biological signals and sensitivity to clinically meaningful change in multisite studies.

Injectable biomaterials with aligned microstructures play a critical role in tissue engineering and drug-delivery applications where control over the position and orientation of cells and nano/micron-scale architectures enhance intervention efficacy. Patients are often subject to MRI scans; for patient safety and treatment efficacy, we investigated the effects of MRI on a biomaterial treatment consisting of aligned magnetic microstructures being developed for guiding cell growth. Under MRI exposure, potential movement of aligned structures could be detrimental to nearby cells, and potential MRI-induced heating could adversely affect traumatized tissue. In this work, the alignment state and heat conduction of such a treatment were studied using a 9.4 T preclinical MRI. The treatment comprises short magnetic rod-shaped polycaprolactone fibers (rods) with embedded magnetic nanoparticles in a surrounding hydrogel (gelatin methacrylate), with rod alignment observed before and after a 45-minute MRI scan. No change in rod alignment state was observed, and no heat generation was measured. A theoretical framework was developed which supports the experimental observation that the biomaterial is stable under MRI. This work can be extended to other biomaterial systems with aligned architectures used in tissue engineering applications such as spinal cord, muscle and tendon.

Purpose: To develop an interpretable feature-based Deep Parametric Response Mapping (PRMD) method that combines wavelet scattering convolution networks and machine learning to spatially detect and quantify functional small airways disease (fSAD) and emphysema on paired inspiratory-expiratory CT scans, with enhanced noise robustness. Materials and Methods: In this retrospective analysis of prospectively acquired data (2007-2017), we developed and validated a deep learning-based PRM approach using paired CT scans from 8,972 tobacco-exposed COPDGene participants ([&ge;]10 pack-years; mean age 60.1 {+/-} 8.8 years; 46.5% women), including controls with normal spirometry (n = 3,872; controls), PRISm (n = 1,089), GOLD 1-4 COPD (n = 4,011). Data were stratified into training, validation, and testing sets (24:6:70). PRMD extracts translation-invariant image features using a wavelet scattering network and applies a subspace learning classifier to classify voxels as emphysema or non-emphysematous air trapping (fSAD). PRMD was compared with conventional density-based PRM for voxel-wise agreement, correlation with pulmonary function, robustness to noise, and sensitivity to misregistration using Pearson correlation, Bland-Altman analysis, and paired t tests. Results: PRMD achieved 95% voxel-wise agreement with standard PRM (r = 0.98) while demonstrating significantly greater robustness under noise. PRMD showed stronger correlations with FEV1; (emphysema: r = - 0.54; fSAD: r = - 0.51; P < 0.0001) than standard PRM (r = - 0.42 for both; P < 0.0001). Under simulated high-noise conditions, standard PRM overestimated disease by ~15%, whereas PRMD limited error to < 5% (P < 0.001). Conclusion: PRMD provides an interpretable, feature-driven and noise-resilient alternative to traditional PRM for emphysema and fSAD classification, enhancing the reliability of CT-based COPD phenotyping for multi-center studies and low-dose imaging applications.

Objective and RationaleBrain biomechanics is a rapidly evolving field, with mechanical properties influencing both normal development and pathological conditions such as cancer. Brillouin microscopy, a non-contact optical technique, offers a promising approach for studying the biomechanics of fresh brain tumors and organoids at subcellular resolution. However, challenges such as tissue heterogeneity and signal attenuation necessitate an in-depth evaluation of measurement strategies and potential confounding factors. MethodsFresh human brain tumor samples and tumor organoids were analyzed using Brillouin microscopy with 780 nm excitation. Measurements in the form of maps of various size were performed, and the impact of focal position, tissue heterogeneity and blood contamination on Brillouin data was assessed. Complementary Raman spectroscopy was performed as reference for tissue composition. ResultsBrillouin signal intensity decreased exponentially with depth, with valid measurements achievable up to 80 {micro}m. Low signal intensities at greater depths compromised data reliability due to fitting algorithm limitations. Structural heterogeneity, including different cell types, differentially affected signal attenuation. Blood contamination was identified as a major confounder, leading to erroneous biomechanical readings. Brillouin intensity maps provided essential quality control for accurate data interpretation. Raman spectroscopy identified the presence of blood and tissue-specific biochemical signatures, reinforcing the importance of multimodal analysis. ConclusionsBrillouin microscopy can effectively probe biomechanical properties of fresh brain tumors but is influenced by tissue heterogeneity and contaminants. Proper sample preparation, strategic focal positioning, and complementary techniques like Raman spectroscopy are critical for ensuring reliable data. These findings contribute to refining Brillouin microscopy protocols for neuro-oncological research and potential future clinical applications.

International guidelines for low-frequency electromagnetic field exposure (LF EMF) are primarily intended to prevent substantiated adverse effects. In the frameworks, limits on internal electric fields are linked to external exposure levels through computational dosimetry. However, the relationship between internal electric fields and these adverse effects remains incompletely understood. In particular, current approaches often overlook the morphological complexity and diversity of cortical neurons, which may limit the realism of neuronal activation estimates used to support these assessments. This study evaluates LF EMF-induced neural activation using 25 morphologically realistic neuron models spanning all cortical layers, embedded within 11 detailed human head models. The internal electric fields were simulated for uniform magnetic field exposures (100 Hz-100 kHz) along the three anatomical directions, and excitation thresholds were computed using a multi-scale framework combining voxel-based dosimetry with biophysical neuron simulations. A real-world exposure scenario involving a child near an acousto-magnetic article-surveillance deactivator was also analyzed. Thresholds varied across cell type, morphology, cortical location, subject anatomy, frequency, and exposure direction, with L2/3 pyramidal, L4 basket, and L5 thick-tufted pyramidal cells showing the lowest thresholds. Despite this variability, all simulated thresholds were conservative with respect to the basic restrictions and dosimetric reference limits set by IEEE ICES and ICNIRP. The smallest margin occurred at 100 kHz, where the threshold remained a factor of 2.8 above the corresponding limit. These findings indicate that current LF EMF exposure limits remain conservative when evaluated using highly detailed, morphology-based CNS activation models.

Continuous, non-invasive cardiovascular monitoring is limited by the superficial sensing depth of Photoplethysmography (PPG), which is susceptible to peripheral artifacts. This study evaluates a wearable dual-modality prototype integrating dryelectrode Impedance Plethysmography (IPG) and PPG within a smartwatch form factor. Results from a pilot study (N=2) demonstrate that IPG signals exhibit a temporal lead over PPG across ventral and dorsal sites, supporting its greater penetration depth. During brachial artery modulation, IPG showed superior sensitivity to arterial recovery on the ventral forearm. Furthermore, 60-minute napping sessions revealed that while PPG remained morphologically stable, IPG signals underwent significant evolution, capturing distinct pulsewave archetypes. These findings suggest that wearable IPG provides a high-fidelity window into deep systemic hemodynamics typically reserved for clinical instrumentation.

We investigate the effects of skin pigmentation and light source characteristics on the performance of reflective Pulse oximetry (PO) devices used in healthcare and well-being applications. We use Monte Carlo (MC) simulations to compare ideal monochromatic and realistic LED spectral emission profiles and tolerance-related wavelength shifts. The simulation covers photon transport in skin models with melanin concentrations (2.55% to 30.5%) and arterial oxygen saturations SaO2 (70% to 100%.) Accuracy was assessed by SpO2 error, root-mean-square error RMSE (Arms), and percentile tail-errors (P90, P95, and P99). Monochromatic spectral emission yielded the lowest SpO2 error (RMSE = 1.32), while LED spectral emission profiles increased errors (RMSE = 2.10). Infrared wavelength tolerances increased SpO2 RMSE by 1.1 {+/-} 0.3. SpO2 error increased with melanin concentration, from underestimation (-1.8 {+/-} 0.1%) at 2.55% melanin concentration to overestimation (+3.9 {+/-} 1.2%) at 30.5% for low SaO2 (70%) and LED spectral emission profiles. At 30.5% melanin concentration, P95 and P99 exceeded FDA and DIN EN ISO 80601-2-61 thresholds, in particular at low SaO2 (70%). Clipping SpO2 estimates at 100% resulted in an apparent RMSE decrease of up to 3%, reflecting error masking rather than real error reduction. In conclusion, LED spectral emission profiles and wavelength tolerances can amplify melanin-related bias in SpO2 estimates. Monochromatic emission and tighter wavelength control can reduce SpO2 error and should be considered in device design and regulation. Regulatory standards should discourage clipping SpO2 estimates at 100% and mandate additional metrics as RMSE fails to reflect clinically critical percentile error thresholds, i.e. P95 and P99.

Myelin is a highly complex membranous structure wrapped around axons by oligodendrocytes or Schwann cells in the central and peripheral nervous system, respectively. Fluorescent labeling is widely used to study the structure and dynamics of myelin. Combining structural with functional imaging requires labeling of myelin with red fluorescence, as many functional sensors, including Ca2+ indicators and genetically encoded metabolite sensors, fluoresce in the green spectral range. However, in vivo tools enabling red fluorescent labeling of myelinating cells and their myelin sheaths remain limited. Here, we generated a set of seven transgenic mouse lines expressing a membrane-targeted variant of the red fluorescent protein tdTomato in myelinating oligodendrocytes and Schwann cells throughout the nervous system. The mouse lines provide a variety of expression patterns ranging from wide-spread labeling of myelin to a rather sparse expression, the latter enabling visualization of individual oligodendrocytes and their associated myelin sheaths. In the peripheral nervous system, the pattern of fluorescence in sciatic nerves indicates predominant localization of tdTomato to non-compact myelin compartments including the inner and outer tongues, paranodal loops and Schmidt-Lanterman incisures. In summary, our work provides a set of novel mouse lines with myelin labeled by red fluorescence, which are compatible with diverse imaging modalities in the green spectral range enabling integrated structural and functional imaging. Main PointsO_LITransgenic mouse lines expressing membrane-targeted tdTomato in myelin enable imaging of myelin in the red spectral range C_LIO_LIDistinct expression patterns range from wide-spread labeling to sparse single-cell resolution, supporting diverse imaging applications C_LI

1.Quantitative neuropathology has advanced through whole-slide imaging and digital histology platforms. Yet, these measurements rarely align with neuroimaging coordinate frameworks that may be useful for spatial modeling and other applications. QNPtoVox, short for quantitative neuropathology to voxels, is a reproducible, modular pipeline that transforms quantitative metrics generated by digital pathology software (HALO) into voxel-based maps registered to a standard common coordinate (MNI) template. The workflow integrates digital histopathology, gross tissue photography, ex-vivo MRI, and nonlinear registration to generate spatially standardized 3D pathology representations. This Methods article provides a complete procedural description, including required materials, step-wise instructions, operator-dependent checkpoints, expected outputs, reproducibility evaluation, and troubleshooting. QNPtoVox enables voxel-level integration of neuropathology with neuroimaging tools, unlocking existing histopathology datasets for computational modeling and cross-cohort harmonization.

Time domain Dynamic full-field optical coherence tomography (D-FFOCT) is a powerful label-free imaging modality that enables functional visualization of cellular activity in living tissues with subcellular resolution. However, its sensitivity remains a major limitation for imaging highly scattering three-dimensional (3D) biological models such as retinal organoids, where incoherent background and inefficient optical flux distribution reduce dynamic contrast and limit imaging depth. In this work, we introduce a ratio-free optical configuration for time-domain D-FFOCT that enables continuous tuning of the sample-to-reference field ratio while minimizing photon losses and suppressing parasitic reflections. This polarization-based architecture allows optimal redistribution of optical flux according to sample scattering conditions and improves sensitivity under both power-limited and dose-limited conditions. Compared with conventional non-polarizing beam splitter configurations, the proposed approach provides a [Formula]-fold (3 dB) sensitivity improvement through optical optimization alone. In addition, we investigate for the first time the use of partial field illumination (PFI) in time-domain D-FFOCT to reduce incoherent background arising from multiple scattering. In retinal organoids imaged at 120 {micro}m depth, PFI yields up to a 14.5-fold (23.2 dB) increase in dynamic signal sensitivity, while preserving functional contrast. When combined, ratio-free detection and PFI provide a cumulative sensitivity improvement of 20.5-fold (26.2 dB). These gains enable improved visualization of photoreceptor precursor organization, rosette structures, and Muller glial cell dynamics in both 3D retinal organoids and 2D cell cultures. This work establishes a practical framework for sensitivity optimization in D-FFOCT and expands its potential for functional imaging, disease modelling, and live-cell monitoring in complex biological systems. O_FIG O_LINKSMALLFIG WIDTH=195 HEIGHT=200 SRC="FIGDIR/small/719402v1_ufig1.gif" ALT="Figure 1"> View larger version (123K): org.highwire.dtl.DTLVardef@1c20dc7org.highwire.dtl.DTLVardef@116b0d4org.highwire.dtl.DTLVardef@b330e8org.highwire.dtl.DTLVardef@4fd9f6_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundTau aggregation is the defining feature of tauopathies, however, the mechanisms by which distinct tau strains drive disease-specific responses remain unclear. Existing models largely rely on recombinant tau seeding or tau overexpression, which fail to capture the biochemical diversity of pathological tau. The aim of this study was to develop a robust and reproducible human cell-based model of disease-specific tau pathology and to use this model to determine how tau from unique diseases impact tau accumulation and lysosomal dysfunction. MethodsPatient-derived tau aggregates were enriched from post-mortem brain tissue obtained from sporadic Alzheimers disease (AD), Picks disease (PiD), progressive supranuclear palsy (PSP), and control cases using phosphotungstic acid precipitation. Patient-derived tau preparations were biochemically characterised by immunoblotting and mass spectrometry and normalised for tau content prior to seeding. Patient-derived tau aggregates were seeded into multiple human immortalised cell lines (SH-SY5Y, M03.13, U-87 MG, and U-118 MG cells) and iPSC-derived astrocytes. Tau seeding efficiency, aggregate morphology, and integrity of the autophagy-lysosomal pathway was assessed using quantitative imaging approaches. ResultsPatient-derived tau seeds retained disease-specific phosphorylation patterns and isoform composition and led to reproducible, dose-dependent insoluble tau accumulation in all cell lines tested. Despite equivalent tau input and similar background protein composition, PiD-derived tau had the most aggressive pathological signature, showing the highest number of tau aggregates per cell and inducing system wide disruptions in the autophagy lysosomal system including increased SQSTM1 puncta and lysosomal damage markers. Seeding with AD-derived tau led to a high number of tau aggregates per cell and more specifically depleted the lysosomal protease CTSD and uniquely co-seeded A{beta} pathology. Seeding with PSP-derived tau resulted in only a moderate number of tau aggregates per cell and uniquely caused increased lysosomal biogenesis. ConclusionsTogether, these results demonstrate that intrinsic properties of human tau strains drive disease-specific cellular responses and establish a scalable, physiologically relevant platform for dissecting tau-cell interactions and screening therapeutics across tauopathies.

We have curated and annotated the topologic determinants for all human membrane proteins made at the endoplasmic reticulum (ER). This census of 4,863 proteins allowed us to systematically analyze the physical properties of their 20,546 TMDs and flanking soluble regions. Single-pass proteins house the majority of large exoplasmic and cytosolic domains, whereas multipass proteins overwhelmingly contain short loops and tails. All classes of transmembrane domains (TMDs) have positively charged cytosolic flanks, but negatively charged exoplasmic flanks feature primarily on TMDs inserted by Oxa1-family insertases. The TMD-pair, a topologic unit of two TMDs with a short exoplasmic loop, is the dominant building block of multipass proteins. TMD-pairs accommodate high-hydrophilicity and charge-containing TMDs crucial for multipass protein functions. We interpret these context-dependent TMD features in light of current mechanistic models for membrane protein biogenesis and function. Our findings have implications for the evolution of membrane proteomes and for engineering new membrane proteins.

Diabetes mellitus is characterized by chronic hyperglycemia and loss of pancreatic {beta}-cell function and mass. Current therapies focus on {beta}-cell protection and regeneration, led by GLP-1 receptor agonists. The G protein -subunit (Gs) acts as a key signaling node downstream of numerous GPCRs, integrating diverse signals that impact {beta}-cell mass and function. Elucidating the integrative role of pancreatic Gs signaling is thus crucial for understanding {beta}-cell biology. Our map of the pancreatic Gs-coupled GPCR landscape reveals sophisticated, cell-type-specific networks, positioning Gs as a central hub for intra-pancreatic communication. Previous studies in mice with {beta}-cell-specific or whole-pancreatic Gs deletion demonstrated reduced {beta}-cell mass, impaired insulin secretion, and glucose intolerance. The stronger phenotype in the whole-pancreas model--marked by -cell expansion and abnormal distribution--points to a crucial role for Gs in differential control of postnatal - and {beta}-cell proliferation. Here, we analyze the organ-wide consequences of Gs deletion using pancreas-specific Gs knockout mice (PGsKO). Consistent with prior findings, PGsKO mice exhibit reduced weight gain from four weeks and severe diabetes due to decreased {beta}-cell mass and concomitant -cell expansion. Furthermore, Gs loss induces profound architectural and functional defects in the exocrine pancreas, linked to YAP reactivation in acinar cells. Importantly, we observed attempted {beta}-cell regeneration in PGsKO mice. Although insufficient to reverse diabetes, our results delineate the full pancreatic phenotype that may facilitate these regenerative efforts and suggest that strategically biasing GPCR signaling network away from Gs could be a viable strategy to promote {beta}-cell regeneration from other pancreatic cell types. ARTICLE HIGHLIGHTSO_LIGs is a central signaling hub that integrates diverse GPCR inputs across pancreatic cell types, yet its organ-wide role remained poorly defined. C_LIO_LIWe addressed how pancreas-wide Gs deletion disrupts both endocrine and exocrine compartments, and whether regenerative programs are engaged. C_LIO_LIGs loss caused severe diabetes through {beta}-cell loss and -cell expansion, induced profound exocrine defects with YAP reactivation, and triggered attempted {beta}-cell regeneration from ducts and potentially other cell types. C_LIO_LIOur findings suggest that strategically biasing GPCR signaling away from Gs could promote regeneration from non-{beta}-cell sources, offering new therapeutic avenues for diabetes. C_LI

Cellular organelle content is fairly constant within a given cell type. This is accomplished in part by ensuring equitable organelle partitioning during division. Much of our understanding of organelle inheritance has come from investigating cells that divide in half producing two daughter cells. However, more elaborate division strategies that give rise to multiple daughters are not uncommon in nature. Here, we present the first characterization of organelle inheritance in a fungus that grows by multi-budding, producing several (2-20) daughter cells in a single cell cycle. We find that some organelles (mitochondria and ER) are evenly delivered to all growing buds, while others (vacuole and peroxisomes) are more variably inherited. We discuss the implications of even and uneven inheritance for this polyextremotolerant fungus capable of growing in dynamic, and diverse, environments.

The theory of island biogeography and its trophic extensions predict that both species richness and food-web complexity should increase with increasing ecosystem surface area. Accordingly, Species-Area Relationships (SARs) and Network-Area Relationships (NARs) are often observed to be positively-sloped, an observation that came to be considered as a law, and on which rest many area-based conservation plans for biodiversity. However, our mechanistic understanding of the driving mechanisms of SARs and NARs slopes remains limited, undermining our ability to predict how biodiversity will respond to habitat gain or loss. We show in 180 rural ponds sampled across five years that invasive alien predators reversed the SAR and NARs from positive in invader-free ponds, to negative in invaded ponds. Relationship reversal resulted from a higher prevalence of invasive alien predators driving magnified prey extinctions and simplified food webs in larger ponds. The ability of invasive alien predators to reverse SAR and NARs presumably reflected disproportionately high predation rates combined with a low sensitivity to prey extinction conferred by a wide trophic generalism. In a world where virtually all ecosystems face biological invasions, omnipresent invasive alien predators stress the pivotal role played by predation in shaping biocomplexity-area relationships, and highlight a growing need to preserve small ecosystems where invasive alien predators are less prevalent.

Intestinal epithelial cells are central players in mucosal barrier integrity and host-microbe interactions. Genetic studies have revealed that epithelial dysfunction is a key contributor to the pathogenesis of inflammatory bowel disease. Non-SMC condensin II complex subunit D3 (NCAPD3) is essential for chromatin organization and stability. NCAPD3 also promotes antimicrobial defense and autophagy responses in vitro. NCAPD3 expression is decreased in intestinal epithelial cells from patients with ulcerative colitis; however, it is not known whether loss of NCAPD3 expression drives intestinal barrier dysfunction or is a result of disease-associated inflammation. To investigate this relationship in vivo, a tissue-specific approach was required, as global constitutive knockout of NCAPD3 is embryonic lethal. Therefore, a transgenic mouse line with doxycycline-inducible expression of a short hairpin RNA targeting NCAPD3 restricted to villin-expressing cells was generated (NCAPD3KD mice) to enable the study of NCAPD3 function in the intestinal epithelium. Treatment of NCAPD3KD mice with 9-tert-butyl doxycycline resulted in [~]75% reduction of NCAPD3 protein in EpCAM intestinal cells. Short-term epithelial NCAPD3 knockdown did not induce spontaneous colitis but was associated with increased serum amyloid A and a trend towards increased intestinal permeability. Upon dextran sodium sulfate or Salmonella enterica serovar Typhimurium {Delta}AroA challenge, NCAPD3KD mice exhibited exacerbated weight loss, higher disease activity, increased histopathological damage, abnormal colonic cytokines and chemokines, and significantly increased intestinal permeability. These results indicate that NCAPD3 expression in the intestinal epithelium is required for optimal barrier maintenance and antimicrobial defense under chemical or microbial stress. These findings support prior in vitro observations and solidify NCAPD3 as a regulator of intestinal epithelial barrier function and mucosal host defense. Author SummaryNCAPD3 is a multifunctional protein with established roles in chromatin organization, genome stability, mitochondrial function, and antimicrobial defense. Dysregulated NCAPD3 is implicated in human diseases, such as inflammatory bowel disease (IBD) and microcephaly; however, due to its essential role in cellular division, determination of whether NCAPD3 loss drives these pathologies in vivo has been lacking. Using a new transgenic mouse model that selectively reduces NCAPD3 expression in intestinal epithelial cells, our study establishes NCAPD3 as an epithelial regulator of the mammalian intestine that enhances epithelial barrier resilience and antimicrobial defense during stress. Although dispensable for short-term basal homeostasis, NCAPD3 function becomes critical during epithelial injury and enteric infection. Reduced NCAPD3 expression may therefore lower the threshold for inflammatory disease by weakening barrier integrity, amplifying inflammatory cascades, and impairing antimicrobial defenses. These findings position NCAPD3 as a potential modulator of IBD susceptibility and highlight chromatin organization as an important, previously underappreciated layer of intestinal epithelial regulation.