J Autoimmun. 2025 Aug 7;156:103471. doi: 10.1016/j.jaut.2025.103471. Online ahead of print.

ABSTRACT

BACKGROUND: Interstitial lung disease (ILD) is associated with morbidity and mortality in idiopathic inflammatory myopathies (IIM). Predicting ILD progression remains a significant challenge, as conventional diagnostic tools such as pulmonary function tests (PFTs) and high-resolution computed tomography (HRCT) have limited prognostic accuracy. This study evaluated whether 68Ga-labelled inhibitor of Fibroblast-Activation-Protein (FAPI) based PET/CT at baseline predicts ILD evolution over two years.

MATERIAL AND METHODS: In this prospective observational study, n = 19 individuals with IIM (n = 14 with ILD) underwent [68Ga] Ga-FAPI PET/CT at baseline. ILD progression was defined by three criteria: (1) FVC decline ≥10 % or FVC 5-9 % plus DLCO decline ≥15 %, (2) INBUILD criteria, and (3) a composite endpoint including INBUILD plus therapy escalation, hospitalization, or mortality. Pulmonary tracer uptake was quantified by calculating the maximum and mean target-to-background ratios across the whole lung (wlTBRmax and wlTBRmean, respectively), derived from standardized uptake values corrected for blood pool activity, and their predictive value was analysed.

RESULTS: Over two years, n = 4 (28.6 %) patients met PFT-based progression criteria, while n = 6 (42.9 %) fulfilled INBUILD criteria, and n = 8 (57.1 %) reached the composite endpoint. Baseline wlTBRmax was significantly higher in INBUILD progressors compared to non-progressors (2.68 ± 1.06 vs. 1.59 ± 0.80, p = 0.04), as was wlTBRmean (0.58 ± 0.22 vs. 0.34 ± 0.10, p = 0.04). Similarly, patients meeting the composite endpoint had higher wlTBRmax (2.63 ± 1.04 vs. 1.30 ± 0.31; p < 0.01) and wlTBRmean (0.55 ± 0.20 vs. 0.31 ± 0.09; p = 0.01). Logistic regression analysis showed that incorporating pulmonary wlTBRmax and wlTBRmean enhanced the predictive accuracy over PFT and HRCT alone.

CONCLUSION: FAPI PET/CT may serve as a non-invasive biomarker for early prediction of ILD progression in IIM, supporting personalized disease management. However, given the small, single-centre cohort, these findings should be considered as preliminary and require validation in larger, multi-centre studies.

PMID:40780057 | DOI:10.1016/j.jaut.2025.103471

Nat Methods. 2025 Aug 8. doi: 10.1038/s41592-025-02785-1. Online ahead of print.

NO ABSTRACT

PMID:40781363 | DOI:10.1038/s41592-025-02785-1

BMC Plant Biol. 2025 Aug 9;25(1):1047. doi: 10.1186/s12870-025-07032-5.

ABSTRACT

BACKGROUND: Paeonia lactiflora Pall. is a traditional medicinal plant widely used in East Asia, particularly for its roots, which are processed into various herbal remedies. With the advancement of omics technologies, significant genomic, transcriptomic, proteomic, and metabolomic data related to P. lactiflora have been generated. To facilitate the utilization of this wealth of information for research and applications, a multi-omics database specific to P. lactiflora was developed.

RESULTS: This comprehensive multi-omics database includes genomic, transcriptomic, and proteomic datasets, as well as chemical compound profiles identified in various tissues and growth stages. The database also features data on key biosynthetic pathways, including those associated with monoterpenoid glycosides such as paeoniflorin, and provides tools for analyzing protein structures and interactions. Additionally, it summarizes P. lactiflora's major active compounds, and highlights reported pharmacological effects. The database is organized into key functional modules: Home, Genome, Transcriptome, Proteome, Tools, Biosynthetic Pathways, Chemical Compounds, and Publications. Notably, the "Tools" module supports sequence alignment, pathway enrichment analysis (including Kyoto Encyclopedia of Genes and Genomes, KEGG), protein structure prediction, and primer design.

CONCLUSIONS: The multi-omics database (URL: http://210.22.121.250:8888/cosd/home/indexPage ) of P. lactiflora integrates extensive molecular and chemical data, providing a robust platform for researchers. It serves as a valuable resource for advancing studies on the cultivation, breeding, and molecular pharmacognosy of P. lactiflora and supports the development of its medicinal applications.

PMID:40781280 | DOI:10.1186/s12870-025-07032-5

Nat Commun. 2025 Aug 8;16(1):7317. doi: 10.1038/s41467-025-62739-1.

ABSTRACT

Phosphatidylserine externalization on the surface of dying cells is a key signal for their recognition and clearance by macrophages and is mediated by members of the X-Kell related (Xkr) protein family. Defective Xkr-mediated scrambling impairs clearance, leading to inflammation. It was proposed that activation of the Xkr4 apoptotic scramblase requires caspase cleavage, followed by dimerization and ligand binding. Here, using a combination of biochemical approaches we show that purified monomeric, full-length human Xkr4 (hXkr4) scrambles lipids. CryoEM imaging shows that hXkr4 adopts a novel conformation, where three conserved acidic residues create a negative electrostatic surface embedded in the membrane. Molecular dynamics simulations show this conformation induces membrane thinning, which could promote scrambling. Thinning is ablated or reduced in conditions where scrambling is abolished or reduced. Our work provides insights into the molecular mechanisms of hXkr4 scrambling and suggests the ability to thin membranes might be a general property of active scramblases.

PMID:40781244 | DOI:10.1038/s41467-025-62739-1

Transl Psychiatry. 2025 Aug 8;15(1):272. doi: 10.1038/s41398-025-03490-5.

ABSTRACT

The entorhinal cortex and hippocampus are interconnected brain regions required for episodic learning and memory. For this functional encoding, correct assembly of specific synaptic connections across this circuit is critical during development. To guide the connection specificity between neurons, a multitude of circuit building molecular components are required, including the latrophilin family of adhesion G protein-coupled receptors (Lphn1-3; gene symbols Adgrl1-3). Within this genetic family, Adgrl2 exhibits a unique topographical and cell-type specific expression patterning in the entorhinal cortex and hippocampus that mirrors connectivity. To investigate the role of Adgrl2 in a cell-type specific fashion for this circuit, we here created a transgenic mouse (Adgrl2fl/fl;pOxr1-Cre) with targeted and selective Adgrl2 deletion in medial entorhinal cortex layer III neurons (MECIII). Using these mice, we find two major input/output circuitry pathways to be topographically shifted with Adgrl2 deletion in MECIII neurons. These neural connectivity impacts include MECIII axon projections to contralateral MEC layer I, and presubiculum axons to ipsilateral MEC layer III. To test the behavioral consequences of these circuitry alterations, we investigated varying entorhinal cortex dependent behaviors, revealing selective deficits in spatial-temporal sequence learning. Taken together, this study demonstrates that Adgrl2 expression in MECIII neurons is necessary for the accurate assembly of MEC topographical circuits that support episodic learning.

PMID:40781236 | DOI:10.1038/s41398-025-03490-5

Nat Commun. 2025 Aug 8;16(1):7329. doi: 10.1038/s41467-025-62837-0.

ABSTRACT

Temporal properties of molecules within signaling networks, such as sub-cellular changes in protein abundance, encode information that mediate cellular responses to stimuli. How dynamic signals relay and process information is a critical gap in understanding cellular behaviors. In this work, we investigate transmission of information about changing extracellular cytokine concentrations from receptor-level supramolecular assemblies of IKK kinases downstream to the NF-κB transcription factor. In a custom robot-controlled microfluidic cell culture, we simultaneously measure input-output encoding of IKK-NF-κB in dual fluorescent-reporter cells. When compared with single cytokine pulses, dose-conserving pulse trains prolong IKK assemblies and lead to disproportionately enhanced retention of nuclear NF-κB. Using particle swarm optimization, we demonstrate that a mechanistic model does not recapitulate this emergent property. By contrast, invoking mechanisms for NF-κB-dependent chromatin remodeling to the model recapitulates experiments, showing how temporal dosing that prolongs IKK assemblies facilitates switching to permissive chromatin that sequesters nuclear NF-κB. Remarkably, using simulations to resolve single-cell receptor data accurately predicts same-cell NF-κB time courses for more than 80% of our single cell trajectories. Our data and simulations therefore suggest that cell-to-cell heterogeneity in cytokine responses are predominantly due to mechanisms at the level receptor-associated protein complexes.

PMID:40781077 | DOI:10.1038/s41467-025-62837-0

Cell Signal. 2025 Aug 6:112052. doi: 10.1016/j.cellsig.2025.112052. Online ahead of print.

ABSTRACT

Microtubule stability is critical for maintaining cytoskeletal integrity and is finely tuned by post-translational modifications of tubulin and its associated regulatory factors. However, it remains unclear how microtubules become destabilized under stress or disease conditions and contribute to pathogenesis. Here, we identify TRIM10β, a previously uncharacterized splice variant of TRIM10, as a microtubule-associated protein that disrupts the interaction between tubulin and End Binding protein 1 (EB1), which plays a critical role in microtubule stabilization. Moreover, TRIM10β promotes tubulin SUMOylation and cleavage of LIM domain kinase 1 (LIMK1), both of which contribute to microtubule destabilization. TRIM10β binds to calmodulin-regulated spectrin-associated protein 2 (CAMSAP2), a key regulator of non-centrosomal microtubules, and modulates its protein levels via its E3 ligase activity. Notably, TRIM10β depletion attenuates p38 phosphorylation in erythroblasts, which is essential for microtubule disassembly and polarization during enucleation, whereas its ectopic expression aberrantly enhances p38 activity, promoting microtubule disassembly in non-erythroid cells. Importantly, persistent overexpression of TRIM10β is recognized as a proteotoxic burden and rapidly degraded via the unfolded protein response (UPR) under cellular stress, thereby serving as a protective mechanism. Our findings reveal a novel role for TRIM10β in microtubule dynamics and highlight a potential regulatory mechanism in maintaining proteostasis, with its low endogenous expression possibly reflecting an evolutionary strategy to minimize proteostatic stress.

PMID:40780618 | DOI:10.1016/j.cellsig.2025.112052

Clin Gastroenterol Hepatol. 2025 Aug 6:S1542-3565(25)00660-3. doi: 10.1016/j.cgh.2025.07.040. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: Germline genetic factors influence the clinical features of colorectal cancer (CRC); however, these factors remain underexplored in Taiwan. This study aims to evaluate the pathogenicity of germline variants and investigate their associations with familial risk and early-onset CRC.

METHODS: Whole-exome sequencing of 600 Taiwanese CRC patients was analyzed, assessing variant pathogenicity using American College of Medical Genetics and Genomics (ACMG) guidelines. Comparative analysis with 1,492 controls identified candidate genes, and clinical features were correlated with genetic variants.

RESULTS: We identified several novel candidate genes, including CCDC18 and CEP135. A total of 24 pathogenic variants in hereditary cancer genes were found in 5.2% of Taiwanese CRC patients, with the highest prevalence observed in early-onset cases (8.2%). Notably, a novel stop-gain variant in POLD1 (p.Y594X) was detected in a 26-year-old patient, suggesting dysfunction of the polymerase catalytic domain. The risks associated with ATM (1.3%) and the MUTYH (c.850-2A>G) variant were also highlighted. Additionally, 25.5% of rare-risk variants were novel, with 41 candidate pathogenic variants linked to familial and early-onset CRC.

CONCLUSION: These findings improve our understanding of germline genetics in Taiwanese CRC, support better screening and management strategies, and highlight the need to expand Asian variant databases for improved risk assessment and care.

PMID:40780402 | DOI:10.1016/j.cgh.2025.07.040

Biol Psychol. 2025 Aug 6:109101. doi: 10.1016/j.biopsycho.2025.109101. Online ahead of print.

ABSTRACT

Consciousness remains a multifaceted phenomenon that is difficult to be measured by traditional quantification methods. Here we propose the intrinsic probability density function (iPDF) as a quantitative method to evaluate the dynamic inter-cortical interactions that underlie conscious states. First, the method utilizes empirical mode decomposition to derive intrinsic mode functions (IMFs) from EEG signals. Then, the method generates scale-dependent probability density functions for successive partial sums of IMFs that can capture subtle variations in neural modulation patterns. We tested the iPDF analysis across various consciousness states such as general anesthesia, distinct sleep stages (wakefulness, REM, and deep sleep), sensory conditions (eyes open versus eyes closed), and between dementia patients and healthy subjects. Our findings reveal that active neural interactions or modulations during wakefulness and REM sleep are characterized by super-Gaussian iPDF patterns. By contrast, the reduced interactions observed in anesthesia and deep sleep yield near-Gaussian iPDF profiles. We also present a classification model built on iPDF features that achieved an accuracy of approximately 87% in distinguishing dementia patients from health controls, demonstrating the iPDF as a potential biomarker in clinical screening. This study supports the idea that consciousness emerges from complex, scale-dependent neural processes and presents a robust, quantitative framework that may enhance both our theoretical understanding and practical assessment of various states of consciousness.

PMID:40780318 | DOI:10.1016/j.biopsycho.2025.109101

Chaos. 2025 Aug 1;35(8):083116. doi: 10.1063/5.0273776.

ABSTRACT

The Fokker-Planck (FP) equation governs the probabilistic response of diffusion processes driven by stochastic differential equations (SDEs). Gaussian mixture models and deep learning solvers are two state-of-the-art methods for solving the FP equation. Although mixture models mostly depend on empirical sampling strategies and predefined Gaussian components, deep learning techniques suffer from inherent interpretability deficits and require excessively large training samples. To address these challenges, we propose an adaptive normalizing flow framework for solving FP equations (ANFFP). Normalizing flows are generative models that produce tractable distributions to approximate the complex target distributions. The ANFFP architecture inherently preserves probabilistic interpretability while enabling efficient exact sampling advantages that significantly enhance its applicability to probabilistic response modeling under small sample conditions. Numerical examples involving one-dimensional, two-dimensional, and four-dimensional SDEs demonstrate the effectiveness of the method. In addition, the computational complexity of the ANFFP method is discussed in more detail. This work provides a new paradigm for solving high-dimensional FP equations with theoretical guarantees and practical scalability.

PMID:40779784 | DOI:10.1063/5.0273776

PLoS Comput Biol. 2025 Aug 8;21(8):e1013345. doi: 10.1371/journal.pcbi.1013345. Online ahead of print.

ABSTRACT

High-resolution posture tracking of C. elegans has applications in genetics, neuroscience, and drug screening. While classic methods can reliably track isolated worms on uniform backgrounds, they fail when worms overlap, coil, or move in complex environments. Model-based tracking and deep learning approaches have addressed these issues to an extent, but there is still significant room for improvement in tracking crawling worms. Here we train a version of the DeepTangle algorithm developed for swimming worms using a combination of data derived from Tierpsy tracker and hand-annotated data for more difficult cases. DeepTangleCrawl (DTC) outperforms existing methods, reducing failure rates and producing more continuous, gap-free worm trajectories that are less likely to be interrupted by collisions between worms or self-intersecting postures (coils). We show that DTC enables the analysis of previously inaccessible behaviours and increases the signal-to-noise ratio in phenotypic screens, even for data that was specifically collected to be compatible with legacy trackers including low worm density and thin bacterial lawns. DTC broadens the applicability of high-throughput worm imaging to more complex behaviours that involve worm-worm interactions and more naturalistic environments including thicker bacterial lawns.

PMID:40779582 | DOI:10.1371/journal.pcbi.1013345

PLoS One. 2025 Aug 8;20(8):e0328867. doi: 10.1371/journal.pone.0328867. eCollection 2025.

ABSTRACT

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common cause of chronic liver disease worldwide, affecting over 30% of the global general population. Its progressive nature and association with other chronic diseases makes early diagnosis important. MRI Proton Density Fat Fraction (PDFF) is the most accurate noninvasive method for quantitatively assessing liver fat but is expensive and has limited availability; accurately quantifying liver fat from more accessible and affordable imaging could potentially improve patient care. This proof-of-concept study explores the feasibility of inferring liver MRI-PDFF values from contrast-enhanced computed tomography (CECT) using deep learning. In this retrospective, cross-sectional study, we analyzed data from living liver donor candidates who had concurrent CECT and MRI-PDFF as part of their pre-surgical workup between April 2021 and October 2022. Manual MRI-PDFF analysis was performed following a standard of clinical care protocol and used as ground truth. After liver segmentation and registration, a deep neural network (DNN) with 3D U-Net architecture was trained using CECT images as single channel input and the concurrent MRI-PDFF images as single channel output. We evaluated performance using mean absolute error (MAE) and root mean squared error (RMSE), and mean errors (defined as the mean difference of results of comparator groups), with 95% confidence intervals (CIs). We used Kappa statistics and Bland-Altman plots to assess agreement between DNN-predicted PDFF and ground truth steatosis grades and PDFF values, respectively. The final study cohort was of 94 patients, mean PDFF = 3.8%, range 0.2-22.3%. When comparing ground truth to segmented reference (MRI-PDFF), our model had an MAE of 0.56, an RMSE of 0.77, and a mean error of 0.06 (-1.75,1.86); when comparing medians of the predicted and reference MRI-PDFF images, our model had an MAE, an RMSE, and a mean error of 2.94, 4.27, and 1.28 (-4.58,7.14), respectively. We found substantial agreement between categorical steatosis grades obtained from DNN-predicted and clinical ground truth PDFF (kappa = 0.75). While its ability to infer exact MRI-PDFF values from CECT images was limited, categorical classification of fat fraction at lower grades was robust, outperforming other prior attempted methods.

PMID:40779568 | DOI:10.1371/journal.pone.0328867

IEEE Trans Med Imaging. 2025 Aug 8;PP. doi: 10.1109/TMI.2025.3596957. Online ahead of print.

ABSTRACT

Computed tomography (CT) is one of the most widely used non-invasive imaging modalities for medical diagnosis. In clinical practice, CT images are usually acquired with large slice thicknesses due to the high cost of memory storage and operation time, resulting in an anisotropic CT volume with much lower inter-slice resolution than in-plane resolution. Since such inconsistent resolution may lead to difficulties in disease diagnosis, deep learning-based volumetric super-resolution methods have been developed to improve inter-slice resolution. Most existing methods conduct single-image super-resolution on the through-plane or synthesize intermediate slices from adjacent slices; however, the anisotropic characteristic of 3D CT volume has not been well explored. In this paper, we propose a novel cross-view texture transfer approach for CT slice interpolation by fully utilizing the anisotropic nature of 3D CT volume. Specifically, we design a unique framework that takes high-resolution in-plane texture details as a reference and transfers them to low-resolution through-plane images. To this end, we introduce a multi-reference non-local attention module that extracts meaningful features for reconstructing through-plane high-frequency details from multiple in-plane images. Through extensive experiments, we demonstrate that our method performs significantly better in CT slice interpolation than existing competing methods on public CT datasets including a real-paired benchmark, verifying the effectiveness of the proposed framework. The source code of this work is available at https://github.com/khuhm/ACVTT.

PMID:40779378 | DOI:10.1109/TMI.2025.3596957

IEEE Trans Med Imaging. 2025 Aug 8;PP. doi: 10.1109/TMI.2025.3597026. Online ahead of print.

ABSTRACT

Choroidal thickness variations serve as critical biomarkers for numerous ophthalmic diseases. Accurate segmentation and quantification of the choroid in optical coherence tomography (OCT) images is essential for clinical diagnosis and disease progression monitoring. Due to the small number of disease types in the public OCT dataset involving changes in choroidal thickness and the lack of a publicly available labeled dataset, we constructed the Xuzhou Municipal Hospital (XZMH)-Choroid dataset. This dataset contains annotated OCT images of normal and eight choroid-related diseases. However, segmentation of the choroid in OCT images remains a formidable challenge due to the confounding factors of blurred boundaries, non-uniform texture, and lesions. To overcome these challenges, we proposed a mixed attention-guided multiscale feature fusion network (MAMFF-Net). This network integrates a Mixed Attention Encoder (MAE) for enhanced fine-grained feature extraction, a deformable multiscale feature fusion path (DMFFP) for adaptive feature integration across lesion deformations, and a multiscale pyramid layer aggregation (MPLA) module for improved contextual representation learning. Through comparative experiments with other deep learning methods, we found that the MAMFF-Net model has better segmentation performance than other deep learning methods (mDice: 97.44, mIoU: 95.11, mAcc: 97.71). Based on the choroidal segmentation implemented in MAMFF-Net, an algorithm for automated choroidal thickness measurement was developed, and the automated measurement results approached the level of senior specialists.

PMID:40779377 | DOI:10.1109/TMI.2025.3597026

IEEE Trans Image Process. 2025 Aug 8;PP. doi: 10.1109/TIP.2025.3595408. Online ahead of print.

ABSTRACT

Autoencoders (AEs) have received extensive attention in hyperspectral anomaly detection (HAD) due to their capability to separate the background from the anomaly based on the reconstruction error. However, the existing AE methods routinely fail to adequately exploit spatial information and may precisely reconstruct anomalies, thereby affecting the detection accuracy. To address these issues, this study proposes a novel Multi-scale Autoencoder Suppression Strategy (MASS). The underlying principle of MASS is to prioritize the reconstruction of background information over anomalies. In the encoding stage, the Local Feature Extractor, which integrates Convolution and Omni-Dimensional Dynamic Convolution (ODConv), is combined with the Global Feature Extractor based on Transformer to effectively extract multi-scale features. Furthermore, a Self-Attention Suppression module (SAS) is devised to diminish the influence of anomalous pixels, enabling the network to focus more intently on the precise reconstruction of the background. During the process of network learning, a mask derived from the test outcomes of each iteration is integrated into the loss function computation, encompassing only the positions with low anomaly scores from the preceding detection round. Experiments on eight datasets demonstrate that the proposed method is significantly superior to several traditional methods and deep learning methods in terms of performance.

PMID:40779374 | DOI:10.1109/TIP.2025.3595408

FEBS Lett. 2025 Aug 8. doi: 10.1002/1873-3468.70138. Online ahead of print.

ABSTRACT

Over the past few decades, research on polyextremophiles has revealed a diverse range of organisms adapted to multiple extreme conditions, such as combinations of high and low temperatures, acidity, pressure, salinity, and radiation. Under multiple extremes, a key survival mechanism is the production of exopolysaccharides (EPSs) via cell wall-associated or extracellular glycosyltransferases (GTs). EPSs not only protect cells against environmental extremes, desiccation, phage attacks, phagocytosis, and antibiotics; they also play important roles in inter- and intra-microbial interactions, quorum sensing, virulence, energy storage, and biofilm formation. Despite extensive studies on EPSs from extremophiles, knowledge on EPS production in polyextremophiles remains limited, particularly for psychrophiles, halophiles, and piezophiles. This review focuses on the adaptive strategies of polyextremophiles under multiple stress conditions, emphasizing the functional significance of EPS production. By providing an integrated perspective on polyextremophiles and their survival mechanisms, this work highlights the critical role of EPSs in their adaptation to extreme habitats and their potential biotechnological applications.

PMID:40779692 | DOI:10.1002/1873-3468.70138

Sci Immunol. 2025 Aug 8;10(110):eadt0688. doi: 10.1126/sciimmunol.adt0688. Epub 2025 Aug 8.

ABSTRACT

Pulmonary conventional dendritic cells (cDCs) are functionally and phenotypically heterogeneous antigen-presenting cells essential for orchestrating adaptive immune responses in the lung. Here, we define a cell-intrinsic role for granulocyte-macrophage colony-stimulating factor (GM-CSF) signaling in the development of a CD301b+ subset of terminally differentiated cDC2s, in addition to CD103+XCR1+ cDC1s. Unbiased single-cell transcriptomic profiling of CD11c+ cells identified both immature and differentiated lung cDC populations. GM-CSF deficiency disrupted antiapoptotic Bcl2a1 up-regulation and impaired progression to the CD301b+ transcriptional state. Despite the positioning of CD301b+ cDC2s in lymphoid cell-rich adventitial cuff areas, hematopoietic GM-CSF was dispensable for their development. Instead, alveolar epithelial type 2 cell-derived GM-CSF was required for CD301b+ cDC2 formation and pulmonary type 2 immune responses, highlighting the central role of GM-CSF signaling in shaping the pulmonary myeloid landscape.

PMID:40779647 | DOI:10.1126/sciimmunol.adt0688

Sci Adv. 2025 Aug 8;11(32):eadu3858. doi: 10.1126/sciadv.adu3858. Epub 2025 Aug 8.

ABSTRACT

Active restoration strategies targeting corals with elevated heat tolerance have the potential to enhance reef resistance under a warming climate. While stress-tolerant corals have been documented in extreme systems such as mangrove lagoons, it is critical to assess the ability of these corals to maintain tolerance when moved to a more benign habitat. Here, we translocated corals from a mangrove lagoon to an adjacent reef and evaluated the thermal thresholds of corals from both locations before translocation and after 1 year. We demonstrate that mangrove colonies have higher thermal tolerance than reef corals, and, critically, mangrove colonies exhibited no loss in thermal tolerance following 1-year translocation to a less extreme reef habitat. Up-regulation of genes associated with DNA repair, metabolism, and homeostasis indicates the importance of these pathways in helping mangrove corals mitigate thermal stress. Our findings suggest the use of heat tolerant corals from extreme systems holds promise as part of intervention strategies aiming to increase reef resistance.

PMID:40779617 | DOI:10.1126/sciadv.adu3858

Exp Physiol. 2025 Aug 8. doi: 10.1113/EP092677. Online ahead of print.

ABSTRACT

Electrical pulse stimulation (EPS) of skeletal muscle cells is increasingly used to model exercise In vitro. The murine C2C12 myotube system has become a common platform for such studies, yet wide variability in EPS protocols hampers reproducibility and cross-study comparisons. In this technical review, we analysed 54 peer-reviewed studies that employed EPS in C2C12 and extracted used EPS protocols to provide an overview of the most commonly used settings for the EPS parameters (pulse duration, frequency, voltage and stimulation duration). Additionally, we summarized the biological processes investigated in these studies to illustrate the range of research topics typically addressed using this model. The majority of studies used 2 ms pulses at 1 Hz and moderate voltages (10-20 V), often over 24 h of stimulation. Glucose uptake was the most commonly assessed endpoint, followed by AMPK activation, inflammation and mitochondrial adaptations. Correlation analyses revealed interdependence between pulse duration, voltage and EPS duration, indicating that these parameters are often balanced to avoid excessive or suboptimal stimulation. While frequency was largely standardized, voltage and pulse duration showed greater variation. Our findings underscore the need for more detailed parameter reporting and deliberate protocol design aligned with specific experimental objectives, such as mimicking endurance- or resistance-type exercise stimuli. This review serves as a resource for selecting EPS parameters tailored to specific biological processes and encourages standardization to improve translational relevance.

PMID:40779409 | DOI:10.1113/EP092677

Ter Arkh. 2025 Jul 31;97(7):593-599. doi: 10.26442/00403660.2025.07.203352.

ABSTRACT

The article presents a clinical case of Fabry disease in a woman, characterized by multisystemic lesions, late onset and predominant clinical picture of heart failure. The features of this pathology are described in detail with an emphasis on instrumental studies of the cardiovascular system, and the progressive course of Fabry disease is analyzed. This clinical observation illustrates the importance of family screening and detailed anamnesis, shows the process of supervision of a patient with an orphan disease by a cardiologist of a regional hospital in real clinical practice, thereby increasing awareness of the Russian medical community about this pathology.

PMID:40778921 | DOI:10.26442/00403660.2025.07.203352