Skeletal Muscle

Spinal muscular atrophy (SMA) is characterized by motor neuron degeneration caused by deficiency of the survival motor neuron (SMN) protein. However, evidence increasingly supports broader systemic involvement. This study aimed to examine cardiac pathology in SMA patients and to investigate how reduced SMN levels impact cardiomyocyte homeostasis. We analyzed postmortem data from 14 SMA type I patients from the pre-treatment era, integrating gross anatomical, histopathological, and clinical findings. To investigate cardiomyocyte-intrinsic effects of SMN deficiency, healthy human cardiomyocytes were subjected to SMN knockdown and assessed using metabolic assays and transcriptomic profiling. Key findings were further investigated in vivo using the Smn2B/- mouse model of SMA. We found heterogeneous cardiac involvement in SMA patients, including cardiomegaly, variable fat deposition and interstitial fibrosis. SMN knockdown in human cardiomyocytes induced a metabolic shift and widespread transcriptional dysregulation, with pathway analyses identifying selective upregulation of PTEN signaling. Elevated PTEN protein levels were observed in a subset of human SMA hearts and in early postnatal hearts of Smn2B/- mice. Our results demonstrate that the heart remains a biologically relevant target of SMN deficiency and highlights cardiomyocyte-specific metabolic and PTEN signaling alterations as potential contributors to cardiac involvement in SMA.

DNA methylation is a key epigenetic mechanism influencing gene regulation and cellular identity. In skeletal muscle, methylation contributes to fiber-type specification, metabolic programming, and satellite cell function, with evidence of sex-specific differences. Here, we investigated whether spatial regionalization of gene expression along the proximal-distal axis of the tibialis anterior (TA) is mirrored by corresponding patterns of DNA methylation. Using MeDseq on TA sections from muscles previously analyzed by spatial transcriptomics, we profiled methylation across transcriptional start sites (TSS), gene bodies, and regulatory elements. Despite robust spatial differences in transcriptomes, methylation patterns were largely uniform along the proximal-distal axis, indicating that DNA methylation does not underlie regional gene expression in adult TA muscle. In contrast, sex emerged as the primary determinant of methylation variation. Male muscles exhibited widespread hypermethylation at TSS, gene-bodies and regulatory regions, corresponding with sex-specific transcriptional programs, including glycolytic fiber enrichment in males and oxidative fiber markers in females. Notably, chromatin- and methylation-associated regulators such as Setd7, Gsk3a, and Bmyc were upregulated in males, suggesting mechanisms linking transcriptional control to epigenetic state. These findings highlight that while spatial gene expression is transcriptionally driven, sex-specific epigenetic programs dominate adult skeletal muscle, underscoring the need to consider sex in multi-omic studies of muscle biology.

Optimized histological techniques are crucial for visualizing cellular morphology across zebrafish tissues. Here, we report a rapid and reliable hematoxylin and Oil Red O (H-ORO) staining protocol for frozen sections that can be completed in less than three minutes. Mayers hematoxylin is used for nuclear staining, followed by Oil Red O (ORO) to visualize lipid-rich structures such as the endomysium surrounding myofibers, white matter of the brain, and myelin layers of major axonal tracts. Importantly, our optimized H-ORO protocol preserves tissue integrity and minimizes artifacts such as myofiber shrinkage commonly observed with ethanol-based hematoxylin and eosin (H&E) staining in both frozen and paraffin sections.

Muscle mass significantly influences skeletal muscle behaviour, potentially explaining why traditional massless Hill-type models struggle to predict the forces generated by larger muscles during dynamic, submaximal contractions. However, the applicability of mass-enhanced Hill-type models in human locomotion remains unexplored. Here, we compared the predicted force from a 1D mass-enhanced Hill-type muscle model with a traditional 1D massless Hill-type muscle model across a range of experimentally measured human movements. Kinematic and electromyographic data were collected from twenty participants performing locomotor tasks and supplemented with existing cycling data. Muscle size was geometrically scaled by factors from 0.1 to 10, which causes lengths to be scaled proportionally, cross-sectional area and peak isometric force F0 with the square, and mass with the cube of the factor. Muscle tissue mass (inertia) and cadence increased the differences between mass-enhanced and massless predictions of force and power. At high cadence and the largest scale, the normalized root mean square difference between force traces reached 7% of F0, (averaged across muscles). However, differences between models were minimal (<1%) at human-sized scale 1. Real muscle additionally deforms in 3D, we still do not know the extent to which this extra dimensionality affects muscle forces for these human movements.

Quantitative histological analysis of skeletal muscle morphometry provides critical insights into muscle physiology but remains labor-intensive and technically demanding. While recent developments in machine-learning-based image segmentation techniques have facilitated large-scale tissue analysis, existing tools that automate muscle morphometry analysis are largely tailored to mammalian models, with limited applicability to teleosts. Moreover, there is a lack of effective tools for visualizing spatial organization and morphometric variability of teleost muscle fibers, a feature that is important for understanding hyperplastic muscle growth dynamics in teleosts. In this study, we show that cytoplasmic staining combined with deep learning-based cell segmentation offers a robust and accurate approach for automated muscle morphometry analysis in developing zebrafish. We also introduce a FIJI2 plugin, implemented in Jython, that streamlines both morphometric analysis and visualization. This tool accommodates shallow and deep learning-based segmentation techniques and incorporates novel quantification and visualization methods suited to teleost-specific muscle features, including mosaic hyperplasia dynamics. The plugin features an intuitive graphical user interface and is designed for flexibility, with minimal constraints regarding species, image quality, or staining protocol. Its modular architecture allows it to be used as a baseline for automated muscle morphometry analysis, while permitting integration with other tools and workflows.

Collagen organisation within the tumour microenvironment plays a critical role in tumour progression and has emerged as an important structural biomarker in cancer. Second Harmonic Generation (SHG) microscopy enables label-free visualisation and quantitative assessment of fibrillar collagen architecture; however, its high cost, specialised instrumentation, and limited field-of-view restrict routine clinical application. In this study, we evaluated whether collagen features quantified from digitally scanned Masson-Goldners Trichrome-stained histopathological sections can approximate measurements obtained from SHG microscopy. Formalin-fixed paraffin-embedded breast tumour tissues, including benign and invasive ductal carcinoma (IDC) samples with varying collagen content, were analysed using SHG microscopy and whole-slide brightfield imaging. Matched regions of interest were analysed using two independent digital image analysis approaches: a conventional ImageJ-based workflow (TWOMBLI) and a machine learning-based computational pipeline. Collagen structural parameters including collagen deposition area, fibre number, and alignment metrics were quantified and compared across imaging modalities using correlation analysis. SHG signals were consistently detected from trichrome-stained sections, confirming compatibility of SHG imaging. Quantitative comparison demonstrated significant concordance between SHG-derived collagen metrics and those obtained from digital image analysis pipelines, particularly for collagen area and fibre alignment. These findings demonstrate that computational analysis of routine histopathological images can capture key spatial features of collagen organisation comparable to SHG microscopy. Digital pathology-based collagen quantification therefore, represents a scalable and clinically accessible approach for assessing extracellular matrix architecture in tumour tissues.

Accurate quantification of transplanted cardiac spheroids requires three-dimensional localisation within intact myocardium, yet this remains technically challenging. Optical clearing and light-sheet microscopy enable volumetric imaging of injection sites, but automated segmentation is difficult when transplanted spheroids and host tissue are labelled with the same fluorescent markers and cannot be separated by simple thresholding. We developed a random forest based pixel classification workflow for 3D detection of injected hiPSC derived cardiomyocyte and H9c2 spheroids in optically cleared rabbit myocardium. A supervised classifier trained on intensity, edge, and texture features generated a segmentation then grouped pixels via connected component analysis to reconstruct individual spheroids. The method showed good agreement with manual annotation and enabled automated extraction of spheroid size and spatial metrics. This accessible workflow enables reproducible three-dimensional quantification of transplanted spheroids in large light-sheet microscopy datasets and provides a practical route from volumetric imaging to spatial metrics in cardiac regeneration studies.

BackgroundPeri-synaptic astrocyte processes (PAPs) play a fundamental role in synapse formation and function. Central afferent synapse loss and astrocyte dysfunction greatly impede sensory-motor circuitry in spinal muscular atrophy (SMA) disease progression, however mechanisms underpinning tripartite synapse dysfunction remains to be fully elucidated. The aims of this study were to further define PAP and motor neuron synaptic defects in human SMA disease pathology and implement a therapeutic intervention strategy to improve motor neuron function. MethodsWe derived astrocyte monocultures and motor neuron astrocyte co-cultures from healthy and SMA patient induced pluripotent stem cell (iPSC) lines to assess intrinsic astrocyte filopodia defects and phenotypes occurring at the synapse-PAP interface, respectively, using cell surface capture mass spectrometry proteomics, confocal and super resolution microscopy, synaptogliosome isolation, and electrophysiology. ResultsSMA astrocytes demonstrated intrinsic filopodia actin defects featuring low abundance of actin-associated cell surface N-glycoproteins, and decreased filopodia density and CDC42-GTP levels after actin remodeling stimulation. This phenotype is likely driven by the significant reduction of CD44 and phosphorylated ezrin, radixin and moesin ERM proteins (pERM) within SMA astrocyte filopodia. The dual combination of SMN1 gene therapy and forskolin treatment, an adenylyl cyclase activator leading to increased cyclic adenosine monophosphate (cAMP) levels and actin signaling pathway stimulation, led to extensive branching and increased filopodia density of SMA astrocytes during actin remodeling. SMA patient-derived motor neuron and astrocyte co-cultures, particularly samples derived from male patient iPSC lines, demonstrated a significant decrease in synapse number, actin-associated pre-synaptic neurotransmitter release protein, synapsin I (SYN1), and PAP-associated expression of pERM and glutamate transporter, EAAT1. Our astrocyte-targeted SMN1 augmentation and forskolin treatment paradigm restored SYN1 protein levels within the SMA synaptogliosome, resulting in significant increases in motor neuron synapse formation and function, but did not fully restore PAP-associated proteins levels at the synapse. ConclusionsSMA astrocytes demonstrate intrinsic actin-associated defects within filopodia, which correlates with decreased pERM levels at tripartite motor neuron synapses. We also define a SMN- and cAMP-targeted treatment paradigm that significantly increases pre-synaptic neurotransmitter release protein levels to improved SMA motor neuron synapse formation and function. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=117 SRC="FIGDIR/small/714618v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@1257ab8org.highwire.dtl.DTLVardef@19c0010org.highwire.dtl.DTLVardef@c84552org.highwire.dtl.DTLVardef@3f1e62_HPS_FORMAT_FIGEXP M_FIG C_FIG

Non-front-fanged snakes are abundant, diverse and represent approximately 70% of extant snakes. However, there is limited knowledge about most species and their venoms, in part due to the technical and welfare challenges associated with venom extraction, low venom yields, and the lack of cellular models available. Organoids represent an excellent opportunity to overcome these challenges. Here, we establish, for the first time, venom gland organoids from snakes of the Colubridae family and demonstrate the in vitro production of toxins.

In "Experiment-free exoskeleton assistance via learning in simulation", Luo et al. [1] present an ambitious framework for developing exoskeleton controllers through reinforcement learning exclusively in computer simulation. The authors report that a control policy trained on a small dataset from one subject was directly transferred to physical hardware, reducing human metabolic cost during walking, running, and stair climbing by more than any prior device. If confirmed, this would represent a major breakthrough for the field of wearable robotics and their clinical applications. However, a close examination of the published materials casts doubt on these claims. The reported experimental results violate physiological limits on the relationship between mechanical power and muscle energy use during gait2,3,4. The algorithmic claims are surprising and cannot be verified; in contrast with established replicability standards in machine learning5,6, executable code has not been made available. We conclude that the goals of this study have not yet been verifiably achieved and make recommendations for avoiding publication errors of this type in the future.

Quality and price of fetal bovine serum (FBS) are traditionally determined by geographical origin and parameters listed in the Certificate of Analysis (CoA). Despite its central role in cell culture, selecting suitable FBS batches remains costly and labor-intensive due to substantial batch-to-batch variation. We propose a molecular assessment strategy based on transcriptomic and cytokine profiling of cells cultured in different FBS batches to evaluate performance more reliably. Analysis of differential gene expression in three cell lines - MRC-5, Jurkat, and THP-1 - enables batch grouping and reveals pathway-specific effects, with immune-related pathways showing the most pronounced variability. Although CoA parameters can stratify batches by origin, they do not consistently correlate with cytokine secretion or gene expression across cell lines. These findings demonstrate that geographical origin is an inadequate predictor of functional FBS performance and that molecular profiling provides a more robust and informative assessment.

Microscopy-based analysis of red blood cell (RBC) morphology is widely used to study phenotypes in sickle cell disease (SCD). Although AI models have been developed to automate classification, most are trained on pre-cropped single-cell images and thus struggle with full-scope microscopic images containing densely packed cells and diverse morphologies, which require both accurate detection and fine-grained classification. We propose an end-to-end computational framework to identify individual RBCs in full-scope microscopy images and classify them into five morphological categories: discocytes (DO), echinocytes (E), elongated and sickle-shaped cells (ES), granular cells (G), and reticulocytes (R). We first evaluate advanced detection-classification models, including You Only Look Once (YOLO) and Detection Transformers (DETR), and demonstrate that while these models effectively detect cells, their classification performance falls short of specialized classifiers trained on single-cell images, particularly for minority phenotypes. To address this limitation, we introduce a two-step framework in which a YOLO-based detector localizes and crops individual cells from full-scope images, followed by a fine-tuned DenseNet121 ensemble classifier that assigns each cell to one of the five morphological categories. The proposed framework achieves a detection-level F1-score of 0.9661 and a weighted-average classification F1-score of 0.9708, with an overall classification accuracy of 97.06%. Compared with the single-step YOLO26n baseline, the two-step pipeline yields a macro-average F1-score improvement of +0.1675, with particularly substantial gains for minority classes (E: +0.1623; G: +0.2774; R: +0.2603). Overall, this hybrid framework demonstrates a practical strategy for adapting fast, general-purpose detection models to domain-specific biomedical tasks by combining them with specialized classifiers, delivering both efficiency and high accuracy for scientific and clinical image analysis.

Endurance (END) or resistance exercise (RE) training results in adaptations that give rise to distinct skeletal muscle phenotypes. Hallmarks of RE include increases in muscle fibre and muscle cross-sectional area and strength, whereas END increases mitochondrial content. Such distinct phenotypes arise from differential metabolic and mechanical signal transduction, transcriptional, and protein translation pathways, culminating in exercise mode-specific adaptations in the muscle proteome. However, little empirical data exist on the protein-specific dynamic responses underlying training-mode-specific adaptations in humans. Using a model of unilateral exercise combined with stable isotope labelling with deuterium oxide, we measured changes in synthesis and abundance from baseline and during early (week 1) and later (week 10) periods of adaptation to END and RE training in young healthy adults (n = 14; 8 female, 6 male; 20 {+/-} 1 y, 70 {+/-} 10 kg). We quantified changes in the abundance (n = 1146 proteins) and synthesis (n = 247 proteins) profiles of skeletal muscle across a 5-day pre-training baseline period and during early and later adaptation to RE and END. Abundance profiling revealed mode-specific proteome remodelling, whereby RE increased ribosomal and contractile protein networks, whereas END increased mitochondrial inner membrane proteins after 10 weeks of training. The protein-specific synthesis rates of 119 proteins showed training-induced differences (P < 0.1 and log2 fold change > 1), including subsets of structural proteins that responded differently to RE and END training modes. Notably, distinct Z-disc proteins, such as XIRP1 (RE-specific) and LDB3 (END-specific), exhibited mode-specific regulation despite sharing a similar subcellular localisation. We report, for the first time, that divergent phenotypic adaptations to RE and END extend beyond changes in bulk fraction-specific synthesis rates and are regulated by training-mode-specific adaptations in distinct protein subsets within similar subcellular protein locations.

Spinal muscular atrophy (SMA) is caused by insufficient levels of the survival motor neuron (SMN) protein and clinically manifests as profound weakness due to motor neuron degeneration. While recent evidence suggests it is a multisystem disorder, the pathological programs in neural and peripheral tissues are poorly understood. We applied spatial transcriptomics to cross-sections from the entire lumbar region of pre-symptomatic SMA and control mice to define early, tissue-wide transcriptional consequences of SMN deficiency. This approach enabled spatially preserved analysis of spinal cord, dorsal root ganglia, muscle, bone, cartilage, bone marrow, adipose, and connective tissues within their native anatomical context. Within the SMA spinal cord, motor neuron associated regions and ventral interneurons exhibited upregulation of neurofilaments, tubulin isoforms, and microtubule transport machinery. Neurofilament changes were largely restricted to motor neurons, and tubulin dysregulation extended broadly across ventral regions. Multiple tissues displayed collagen and extracellular matrix gene dysregulation at post-natal day 4. Skeletal muscle demonstrated fiber type-specific stress responses, including induction of atrophy-associated genes, while bone displayed an osteoclast-dominant transcriptional signature, consistent with accelerated resorption and a pro-osteoporotic state. Bone marrow transcriptomes indicated activation of neutrophil degranulation, innate immune signaling, and osteoclastogenic pathways, identifying bone marrow as an active inflammatory and skeletal regulatory niche in SMA. Adipose tissue exhibited extracellular matrix dysregulation, complement activation, profibrotic TGF-{beta} signaling, and stress-induced lipolysis. These findings reveal that SMN deficiency drives early transcriptional reprogramming across multiple tissues well before motor neuron loss and identify non-neuronal pathological programs that offer therapeutic targets for improving long-term outcomes in SMA.

Heat-related illnesses pose a significant public health challenge in Europe, resulting in increased mortality. Although cold water immersion (CWI) is the most effective treatment for heat stroke, its clinical use is limited. A better understanding of temperature changes in the peripheral body regions can lead to more effective CWI application. Nevertheless, most muscle temperature measurement techniques are invasive. This study evaluated magnetic resonance spectroscopy (MRS) for non-invasive assessment of intramuscular temperature during cold stress and rewarming. Nine healthy volunteers (7 men, 2 women) participated in three 3T MRI sessions: baseline (PRE), immediately after 15 minutes of CWI at 10 degrees to the iliac crest (POST-CWI), and following 100-Watt cycling (POST-cycling). Each scan session included T1w and localized spectroscopy acquisitions in the right thigh. Absolute temperature was estimated from the proton resonance frequency shift between water and creatine peaks. The measurements were split into three groups of voxels, defined as follows: close to the top (TL), bottom (BL), or central (DL) thigh positions. Measurement depth showed a location main effect (p<0.001, p^2=0.40), with DL (35.4[5.9] mm) significantly deeper than TL (22.5[4.2] mm) and BL (25.3[5.1] mm), remaining constant across phases. Temperature decreased significantly from PRE to POST-CWI across all locations (TL: p<0.001, d=2.74; BL: p<0.001, d=1.84; DL: p<0.005, d=1.14). Post-cycling temperature increased at all sites compared to POST-CWI (DL: p=0.040, d=1.06; TL: p<0.001, d=1.7; BL: p<0.001, d=1.80), though TL remained lower than PRE (p<0.017, d=1.48). During POST-CWI, DL showed a significantly higher temperature than TL (p<0.001, d=2.13) and BL (p<0.001, d=2.06). These findings demonstrate that MRS-based temperature mapping provides unique anatomical and thermal characterization of muscle during thermoregulatory stress. While results are promising for understanding CWI mechanisms, validation in larger cohorts is necessary to establish clinical reliability and reproducibility for heat illness management.

Cetacean pathology is a cornerstone for population and marine ecosystem health monitoring, allowing clear differentiation among natural and anthropogenic threats. Previous studies in the Canary Islands reported natural causes of death in 59.4% (1999-2005) and 81% (2006-2012) of stranded cetaceans, versus anthropogenic causes in 33.3% and 19%, respectively. This study aimed to determine the causes of death (CD), pathologic findings, and epidemiological patterns of 316 cetaceans stranded in the Canary Islands between 2013 and 2018. The CDs were classified in pathologic entities (PEs) emphasizing natural versus anthropic origins. Of 316 animals, 224 (70.9%) from 18 species were suitable for pathological investigations. Among natural PEE, natural pathology associated with good nutritional status (NP-GNS) and natural pathology associated with significant loss of nutritional status (NP-LNS) represented 43/224 (19.2%) and 36/224 (16%) cases, respectively. Natural pathology with undetermined nutritional status (NP-UNS) occurred in 19/224 (8.5%) animals. Intra- and interspecific traumatic interactions (ITI) represented 30/224 (13.4%) cases, followed by neonatal/perinatal pathology (NPN) 19/224 (8.5%) and live-stranding stress and/or capture myopathy (LS-CM) 18/224 (8%). Infectious and parasitic diseases predominated in natural PEs. Anthropogenic PEs included interaction with fishing activities (IFA) in 17/224 (7.6%) cases, vessel collisions (VC) in 9/22 (4%) cases, and foreign body-associated pathology (FBAP) in 3/224 (1.3%) animals. Overall, anthropogenic causes accounted for 12.9% of deaths, natural causes for 73.6%, and the CD could not be established in 30/194 (13.4%) cases. This study reaffirms the trends concerning recognized PEs (NP-GNS, NP-LNS, NP-UNS, ITI, NPN, LS-CM, IFA, VC, and FBAP), expands the body of knowledge on cetacean pathology in the Canary Islands, and reports novel findings including mixed infections, clostridiosis in uncommon species, uremic syndrome secondary to urethral nematodiasis, gas embolism in unusual species, epibiont stomatitis, congenital musculo-skeletal malformations, or neoplastic processes. These findings advance understanding of cetacean mortality patterns and support conservation and management strategies.

Myeloproliferative neoplasms (MPNs) are characterized by progressive myelofibrosis that drives morbidity and mortality. Liquid biopsy approaches to noninvasively monitor fibrotic progression remain limited. We performed comparative transcriptomic profiling of CD45-depleted platelet-enriched and CD45+ leukocyte-enriched fractions from matched peripheral blood samples of 76 individuals (27 primary myelofibrosis, 17 polycythemia vera, 14 essential thrombocythemia, 18 healthy controls). Platelet RNA sequencing was performed in 2018-2020 on Illumina HiSeq 4000, while WBC RNA sequencing was conducted in 2023 on Illumina NovaSeq 6000 from cryopreserved CD45+ enriched fractions of specimens obtained at the identical time and from the same blood sample as the platelet RNA. Despite comparable library preparation protocols and higher sequencing depth in WBC samples, platelet transcriptomes exhibited 5.1-fold more differential expression in myelofibrosis (3,453 versus 681 genes, adjusted p<0.05, |log2FC|>1). Platelet signatures were enriched for proteostasis pathways including endoplasmic reticulum stress and unfolded protein response, reflecting megakaryocyte dysfunction in the fibrotic bone marrow niche. WBC signatures predominantly featured immune activation and proliferative pathways, indicating systemic inflammatory responses. Multinomial LASSO classification demonstrated superior performance of platelet-based models for myelofibrosis diagnosis (AUROC 0.85) compared to WBC-based (AUROC 0.77) or clinical models (AUROC 0.59). Combined platelet+WBC models did not improve performance (AUROC 0.80), indicating complementary but non-additive information. These findings establish platelet transcriptomic profiling as a superior noninvasive biomarker platform for monitoring myelofibrosis in MPNs, capturing megakaryocyte-driven fibrogenesis with greater sensitivity than peripheral leukocyte-based approaches. HighlightsUsing matched WBC and platelet RNA-seq from MPN patients, we identify myelofibrosis-associated transcriptomic signatures specifically enriched in platelets. Multinomial LASSO modeling highlights platelet-derived gene expression as a dominant and predictive biomarker of myelofibrosis, outperforming clinical parameters and WBC signatures. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=75 SRC="FIGDIR/small/714941v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1d695aborg.highwire.dtl.DTLVardef@fc250forg.highwire.dtl.DTLVardef@1e52e8eorg.highwire.dtl.DTLVardef@15378e3_HPS_FORMAT_FIGEXP M_FIG C_FIG

Vision-language models (VLMs) provide a unified framework for multimodal reasoning, yet their representations are primarily learned from natural image-text corpora and often exhibit semantic misalignment when transferred to histopathology, particularly under data-limited diagnostic settings. To address this limitation, we propose HistoSB-Net, a semantic bridging network designed to adapt pre-trained VLMs to multimodal histopathological diagnosis while preserving their original semantic structure. HistoSB-Net introduces a constrained semantic bridging (CSB) module that operates within the self-attention projection space of both vision and text encoders. Instead of employing explicit cross-attention or full fine-tuning, CSB adaptively modulates pre-trained attention projections through a lightweight nonlinear semantic bottleneck, enabling structured cross-modal regulation with limited additional parameters. The framework supports both patch-level and whole-slide image (WSI)-level diagnosis within a unified architecture. Experiments on six pathology benchmarks, comprising two WSI-level and four patch-level datasets, demonstrate consistent improvements over zero-shot inference across 36 backbone-dataset combinations under limited supervision. Further analysis of prototype-based margin distributions and confusion matrices shows that these improvements are accompanied by enhanced intra-class compactness and increased inter-class separation in the embedding space. These results indicate that CSB provides an effective and computationally manageable strategy for adapting pre-trained VLMs to data-limited digital pathology tasks.

AimsThe activation of inflammatory cells, particularly macrophages, plays a pivotal role in the pathogenesis of cardiac remodelling and heart failure. Emerging evidence indicates that extracellular traps released from inflammatory immune cells contribute to the progression of various pathologies. However, the clinical relevance and mechanistic role of macrophage extracellular traps (METs) in heart failure remain to be elucidated. Methods and ResultsEndomyocardial biopsy specimens from 69 patients with heart failure were analysed by fluorescent immunostaining to identify and quantify METs. The numbers of METs per myocardial tissue area in patients with heart failure showed a negative correlation with left ventricular (LV) ejection fraction and a positive correlation with LV end-diastolic diameter. Patients with higher MET counts had significantly lower event-free survival from the composite cardiac events. In a murine model of pressure overload by transverse aortic constriction (TAC), METs were most abundantly observed at 3 days post-TAC and remained detectable throughout the 4-week observation period. In vitro, time-dependent MET formation was induced by an intrinsic trigger of mitochondrial DNA in bone marrow-derived macrophages from wild-type (WT) mice, but not in peptidyl arginine deiminase 4 (PAD4)-deficient macrophages, indicating that PAD4 activity is indispensable for MET formation. The recipient mice transplanted with bone marrow cells from PAD4 knockout mice showed more preserved cardiac function, reduced myocardial fibrosis, and improved survival in response to TAC, compared to those transplanted with WT mice. Ex vivo analyses demonstrated that conditioned medium containing METs from WT macrophages induced fibroblast-to-myofibroblast transition via Toll-like receptor 4 signalling. ConclusionsPAD4-dependent MET formation from bone marrow-derived macrophages represents a novel driver of cardiac remodelling. Targeting MET formation may offer a potential therapeutic strategy for heart failure. Translational PerspectiveMacrophage extracellular traps (METs) are abundant in myocardial tissue from patients with heart failure with reduced ejection fraction and are associated with adverse left ventricular remodelling and worse clinical outcomes. These findings support myocardial MET burden as a potential tissue biomarker to improve risk stratification in heart failure patients. In mice, pressure overload induces MET formation, and hematopoietic PAD4 deficiency suppresses myocardial METs, attenuates fibrosis, preserves cardiac function, and improves survival. Mechanistically, mitochondrial DNA-enriched cardiomyocyte-derived exophers trigger PAD4-dependent METs, which activate cardiac fibroblasts through TLR4 signalling. Suppressing METs represents a potential therapeutic strategy to attenuate the progression of heart failure. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/711858v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@1c6a637org.highwire.dtl.DTLVardef@caa356org.highwire.dtl.DTLVardef@1a994bforg.highwire.dtl.DTLVardef@6493bb_HPS_FORMAT_FIGEXP M_FIG C_FIG

Aging is associated with a progressive loss of skeletal muscle function, known as sarcopenia; however, the molecular mechanisms coordinating cellular stress responses and structural adaptations permissive of sarcopenia remain incompletely understood. In our previous studies, we found aging differentially impacted mitochondrial networks by muscle, suggesting unique stress thresholds and response activation. Here, we investigate the role of activating transcription factor 4 (ATF4), a master regulator of the integrated stress response (ISR), in aged quadriceps muscle using complementary patient and aging mouse models. Older adults exhibited a marked decrease in aerobic capacity, muscle strength, and endurance when compared with young participants. These results paralleled findings in aged mice, with significant loss of muscle mass across multiple hindlimb muscles. Ultrastructural analysis revealed substantial age-related changes in mitochondrial morphology, including increased volume, surface area, and branching index, as well as a shift toward larger, more complex mitochondria. Our data indicate that ATF4 binds directly to the promoter region of the gene encoding TFAM, suggesting a transcriptional regulatory relationship to support DNA stability. These structural and transcriptional changes likely impair oxidative capacity and drive a feed-forward cycle of mitochondrial dysfunction and ISR activation. Our findings indicate that ATF4 coordinates transcriptomic and structural adaptations in aging muscle, identifying the ISR pathway as a potential therapeutic target for preserving muscle function in older adults.