Nat Metab. 2025 Mar 24. doi: 10.1038/s42255-025-01284-z. Online ahead of print.

NO ABSTRACT

PMID:40128614 | DOI:10.1038/s42255-025-01284-z

Nat Commun. 2025 Mar 24;16(1):2870. doi: 10.1038/s41467-025-58288-2.

NO ABSTRACT

PMID:40128545 | DOI:10.1038/s41467-025-58288-2

Sci Data. 2025 Mar 24;12(1):492. doi: 10.1038/s41597-025-04832-0.

ABSTRACT

Spheroids are widely used in oncology for testing drugs, but models composed of a single cell line do not fully capture the complexity of the in vivo tumours targeted by chemotherapy. Developing 3D in vitro models that better mimic tumour architecture is a crucial step for the scientific community. To enable more reliable drug testing, we generated multiculture spheroids and analysed cell morphology and distribution over time. This dataset is the first publicly available single-cell light-sheet fluorescence microscopy image collection of 3D multiculture tumour models comprising of three different cell lines analysed at different time points. Specifically, we created models composed of one cancer cell line (melanoma, breast cancer, or osteosarcoma) alongside two stromal cell lines (fibroblasts and endothelial cells). Then, we acquired single-cell resolution light-sheet fluorescence 3D images of the spheroids to analyse spheroid morphology after 24, 48, and 96 hours. The image collection, whole spheroid annotations, and extracted features are publicly available for further research and can support the development of automated analysis models.

PMID:40128531 | DOI:10.1038/s41597-025-04832-0

Discov Oncol. 2025 Mar 25;16(1):386. doi: 10.1007/s12672-025-02121-1.

ABSTRACT

Growth differentiation factor-15 (GDF15) is a cytokine/growth factor that belongs to the Transforming growth factor-ß (TGF-ß) protein family. The expression of GDF15 is low in most human organs under normal conditions. GDF15 is a stress-responsive cytokine primarily produced by macrophages in response to inflammatory stimuli. The altered expression of GDF15 is associated with many cancers due to the inflammation caused by the disease. GDF15 triggers the activity through its receptor Glial-derived neurotrophic factor-family receptor α-like (GFRAL) and mediates multiple downstream signaling cascades, which are involved in the progression of cancers. Considering the biological importance of GDF15 in different cancers, we applied data mining techniques to systematically compile and analyze the signaling events associated with GDF15 using NetPath criteria. This resulted in constructing a detailed GDF15-mediated signaling pathway map, enhancing our understanding of its molecular mechanisms in cancer. Furthermore, proteins linked to colorectal and breast cancer identified in our pathway map were cross-referenced with established cancer pathway databases to identify unannotated proteins, highlighting gaps in the current annotations. To investigate potential therapeutic strategies, we performed molecular docking simulations and identified Vitisifuran B as a novel inhibitor that could block the GDF15-GFRAL interaction. These findings suggest that Vitisifuran B could effectively modulate GDF15 signaling, offering a promising avenue for cancer therapeutics. This study underscores the power of computational approaches, such as data mining and molecular docking, in enhancing our understanding of GDF15 signaling in cancer and identifying potential inhibitors for therapeutic development.

PMID:40128491 | DOI:10.1007/s12672-025-02121-1

EMBO Rep. 2025 Mar 24. doi: 10.1038/s44319-025-00415-7. Online ahead of print.

ABSTRACT

Actin-based motility is required for the transmission of malaria sporozoites. While this has been shown biochemically, filamentous actin has remained elusive and has not been directly visualised inside the parasite. Using focused ion beam milling and electron cryo-tomography, we studied dynamic actin filaments in unperturbed Plasmodium falciparum cells for the first time. This allowed us to dissect the assembly, path and fate of actin filaments during parasite gliding and determine a complete 3D model of F-actin within sporozoites. We observe micrometre long actin filaments, much longer than expected from in vitro studies. After their assembly at the parasite's apical end, actin filaments continue to grow as they are transported down the cell as part of the glideosome machinery, and are disassembled at the basal end in a rate-limiting step. Large pores in the IMC, constrained to the basal end, may facilitate actin exchange between the pellicular space and cytosol for recycling and maintenance of directional flow. The data also reveal striking actin bundles in the nucleus. Implications for motility and transmission are discussed.

PMID:40128412 | DOI:10.1038/s44319-025-00415-7

Nat Methods. 2025 Mar 24. doi: 10.1038/s41592-025-02632-3. Online ahead of print.

ABSTRACT

Maintenance of genome integrity is paramount to molecular programs in multicellular organisms. Throughout the lifespan, various endogenous and environmental factors pose persistent threats to the genome, which can result in DNA damage. Understanding the functional consequences of DNA damage requires investigating their preferred genomic distributions and influences on gene regulatory programs. However, such analysis is hindered by both the complex cell-type compositions within organs and the high background levels due to the stochasticity of damage formation. To address these challenges, we developed Paired-Damage-seq for joint analysis of oxidative and single-stranded DNA damage with gene expression in single cells. We applied this approach to cultured HeLa cells and the mouse brain as a proof of concept. Our results indicated the associations between damage formation and epigenetic changes. The distribution of oxidative DNA damage hotspots exhibits cell-type-specific patterns; this selective genome vulnerability, in turn, can predict cell types and dysregulated molecular programs that contribute to disease risks.

PMID:40128288 | DOI:10.1038/s41592-025-02632-3

Nat Commun. 2025 Mar 24;16(1):2879. doi: 10.1038/s41467-025-58200-y.

ABSTRACT

Inorganic phosphate (Pi) is essential for life, and its intracellular levels must be tightly regulated to avoid toxicity. XPR1, the sole known phosphate exporter, is critical for maintaining this balance. Here we report cryo-EM structures of the human XPR1-KIDINS220 complex in substrate-free closed and substrate-bound outward-open states, as well as an XPR1 mutant in a substrate-bound inward-facing state. In the presence of inositol hexaphosphate (InsP6) and phosphate, the complex adopts an outward-open conformation, with InsP6 binding the SPX domain and juxtamembrane regions, indicating active phosphate export. Without phosphate or InsP6, the complex closes, with transmembrane helix 9 blocking the outward cavity and a C-terminal loop obstructing the intracellular cavity. XPR1 alone remains closed even with phosphate and InsP6. Functional mutagenesis shows that InsP6, whose levels vary with Pi availability, works with KIDINS220 to regulate XPR1 activity. These insights into phosphate regulation may aid in developing therapies for ovarian cancer.

PMID:40128258 | DOI:10.1038/s41467-025-58200-y

Expert Opin Drug Saf. 2025 Mar 24. doi: 10.1080/14740338.2025.2484474. Online ahead of print.

ABSTRACT

BACKGROUND: Drug-induced sinusitis has been widely reported as an adverse drug reaction in recent years, yet the pharmacogenetic mechanisms and risk factors associated with sinusitis remain elusive.

OBJECTIVE: We aimed to identify the major drugs reported in the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) in relation to sinusitis and to analyze their pharmacogenetic mechanisms through drug target analysis.

METHODS: We conducted a review of the publicly available FAERS database from 2004 to the third quarter of 2023. We extracted genetic tools corresponding to each drug, utilized colocalization analysis, Mendelian randomization (MR) analysis, and cross-tissue drug target analysis to predict the impact of drug targets on sinusitis.

RESULTS: Following the validation of drug-related risks, a total of 13 medications were ultimately identified, including TNF inhibitors: pomalidomide (ROR: 14.77), certolizumab pegol(ROR: 8.21), etanercept (ROR: 7.961), lenalidomide (ROR: 6.998), adalimumab (ROR: 6.677), infliximab (ROR: 3.939); C4B-targeted drugs: human immunoglobulin G (ROR:3.846) and other risk drugs were commonly reported. Co-localization analysis and MR analysis suggests associations between TNF, C4B, and LTA and sinusitis.

CONCLUSION: We demonstrated the risk of sinusitis associated with 13 drugs, including pomalidomide, and the impact of TNF and C4B drugs on sinusitis, which provides guidance for the use of related drugs and the prevention of sinusitis.

PMID:40128146 | DOI:10.1080/14740338.2025.2484474

Function (Oxf). 2025 Mar 24:zqaf016. doi: 10.1093/function/zqaf016. Online ahead of print.

ABSTRACT

Extracellular ATP is a signaling molecule that acts as a paracrine and autocrine modulator of cell function. Here we characterized the role of luminal ATP in the regulation of epithelial principal cells (PCs) in the epididymis, an understudied organ that plays crucial roles in male reproduction. We previously showed that ATP secretion by PCs is part of a complex communication system that ensures the establishment of an optimal luminal acidic environment in the epididymis. However, the molecular mechanisms regulating ATP release and the role of ATP-mediated signaling in PCs acidifying functions are not fully understood. In other cell types, Pannexin 1 (PANX-1) has been associated with ATP-induced ATP release through interaction with the purinergic P2 × 7 receptor. Here, we show that PANX-1 and P2 × 7 are located in the apical membrane of PCs in the mouse epididymis. Functional analysis using the immortalized epididymal PCs cell line (DC2) and the mouse epididymis perfused in vivo showed that: 1) PANX-1 and P2 × 7 participate in ATP release by DC2 cells, together with Cystic Fibrosis Transmembrane Conductance Regulator (CFTR); 2) Several ATP-activated P2Y and P2X purinergic receptors are expressed in DC2 cells; 3) The non-hydrolysable ATP analogue ATPγS induces a dose-dependent increase in intracellular Ca2+ concentration in DC2 cells, a process that is mainly mediated by P2 × 7; and 4) Perfusion of the epididymal lumen in vivo with ATPγS induces the internalization of apical sodium-hydrogen exchanger 3 (NHE3) in PCs. Altogether, this study shows that luminal ATP, regulated by CFTR, PANX-1 and P2 × 7, modulates sodium-proton exchange in PCs in an autocrine-manner through activation of purinergic receptor-mediated intracellular calcium signaling.

PMID:40128095 | DOI:10.1093/function/zqaf016

Medicine (Baltimore). 2025 Mar 21;104(12):e41907. doi: 10.1097/MD.0000000000041907.

ABSTRACT

There was currently no bibliometric analysis available regarding to bladder cancer (BCa) imaging. The aim of this study was to conduct a comprehensive bibliometric analysis of relevant literature on the imaging of BCa and elucidate global research hotspots and further trends in this field. All relevant literature on the imaging of BCa published between 1981 and 2023 were retrieved from the Web of Science Core Collection. VOSviewer, Bibliometrix, and Citespace were utilized for bibliometric analysis of publications, countries, authors, institutions, journals, references, and keywords. A total of 4462 articles were retrieved. The research in this field has been increasing consistently since 1981. The United States of America was the most productive country and most productive institutions were from it. Shariat SF was the most productive author with 36 articles and the author with the highest co-citations was Herr HW (472). Journal of Urology was the most productive journal and Frontiers in Oncology, Abdominal Radiology and Cancers exhibited heightened activity in recent years. A study by Siegel RL, published in CA-A Cancer Journal for Clinicians in 2019, had the highest number of co-citations. Further analysis of the keyword analysis and timeline view revealed that "radiomics," "deep learning," "multiparametric MRI," "VI-RADS," "muscle-invasive bladder cancer," "immunotherapy," and "long term outcome" were the most recent hotspots. In totally, in the period of 1981 to 2023 year, the USA occupies a critical position in the field of BCa imaging. It is anticipated that MRI-based imaging-reporting and data system and deep learning will be the research hotspots in the future.

PMID:40128048 | DOI:10.1097/MD.0000000000041907

Medicine (Baltimore). 2025 Mar 21;104(12):e41927. doi: 10.1097/MD.0000000000041927.

ABSTRACT

Brain ultrasonography has emerged as a key tool in neurocritical care. This study aimed to investigate the global research trends and future research directions in the application of brain ultrasonography for craniocerebral diseases using quantification and visualization approaches. Publications on brain ultrasonography published between 2004 and 2024 retrieved from the Web of Science Core Collection database were screened against predetermined inclusion and exclusion criteria and analyzed. The data were processed using VOSviewer and CiteSpace to identify core countries/regions, institutions, authors, journals, collaborations, and research trends. Over the past 2 decades, 1251 articles focusing on brain ultrasonography as the primary subject were published across 455 journals by 5655 authors from 1619 institutions in 84 countries/regions. Publications exhibited a fluctuating and gradually progressive trend, with the number of publications per year peaking between 2019 and 2021. The USA, the United Kingdom, and Germany emerged as leading countries in this field, demonstrating robust cooperation with other countries/regions. Additionally, the University of Leicester and Panerai RB was the most prolific institution and author, respectively. The clinical applications of brain ultrasonography have progressively broadened from neurocritical care to encompass the general intensive care unit and emergency department. Finally, recent scholarly attention has primarily been directed toward the "deep learning framework" and "hypoxic-ischemic brain injury." Globally, publications focusing on brain ultrasonography displayed a fluctuating and gradually progressive trend over the past 2 decades. Moreover, primary clinical applications and techniques have been constantly expanding. Overall, the findings of our study expanded our understanding of the current status of brain ultrasonography, potentially guiding future development directions in this field.

PMID:40128044 | DOI:10.1097/MD.0000000000041927

AJNR Am J Neuroradiol. 2025 Mar 24:ajnr.A8748. doi: 10.3174/ajnr.A8748. Online ahead of print.

ABSTRACT

BACKGROUND AND PURPOSE: The purpose of this study was to evaluate the ability of high-resolution (HR), ultra-high-resolution (UHR) with and without deep learning reconstruction (DLR), and cone-beam (CB) CT scanners to image the stapes using micro-CT as a reference.

MATERIALS AND METHODS: 11 temporal bone specimens were imaged using all imaging modalities. Subjective image analysis was performed by grading image quality on a Likert scale, and objective image analysis was performed by taking various measurements of the stapes superstructure and footplate. Image noise and radiation dose were also recorded.

RESULTS: The global image quality scores were all worse than micro-CT (P ≤ 0.01). UHR-CT with and without DLR had the second-best global image quality scores (P > 0.99), which were both better than CB-CT (P = 0.01 for both). CB-CT had a better global image quality score than HR-CT (P = 0.01). Most of the measurements differed between HR-CT and micro-CT (P ≤ 0.02), but not between UHR-CT with and without DLR, CB-CT, and micro-CT (P > 0.06). The air noise value of UHR-CT with DLR was not different from CB-CT (P = 0.49), but HR-CT and UHR-CT without DLR exhibited higher values than UHR-CT with DLR (P ≤ 0.001). HR-CT and UHR-CT with and without DLR yielded the same effective radiation dose values of 1.23 ± 0.11 (1.13-1.35) mSv, which was four times higher than that of CB-CT (0.35 ± 0 mSv, P ≤ 0.01).

CONCLUSION: UHR-CT with and without DLR offers comparable objective image analysis to CB-CT while providing superior subjective image quality. However, this is achieved at the cost of a higher radiation dose. Both CB-CT and UHR-CT with and without DLR are more effective than HR-CT in objective and subjective image analysis.

ABBREVIATIONS: CB: Cone beam; CT: Computed tomography; DLR: Deep learning reconstruction; HR: High-resolution; UHR: Ultra-high resolution.

PMID:40127966 | DOI:10.3174/ajnr.A8748

J Neurosci. 2025 Mar 24:e1187242025. doi: 10.1523/JNEUROSCI.1187-24.2025. Online ahead of print.

ABSTRACT

Calcium imaging is a key method to record the spiking activity of identified and genetically targeted neurons. However, the observed calcium signals are only an indirect readout of the underlying electrophysiological events (single spikes or bursts of spikes) and require dedicated algorithms to recover the spike rate. These algorithms for spike inference can be optimized using ground truth data from combined electrical and optical recordings, but it is not clear how such optimized algorithms perform on cell types and brain regions for which ground truth does not exist. Here, we use a state-of-the-art algorithm based on supervised deep learning (CASCADE) and a non-supervised algorithm based on non-negative deconvolution (OASIS) to test spike rate inference in spinal cord neurons. To enable these tests, we recorded specific ground truth from glutamatergic and GABAergic somatosensory neurons in the superficial dorsal horn of spinal cord in mice of both sexes. We find that CASCADE and OASIS algorithms that were designed for cortical excitatory neurons generalize well to both spinal cord cell types. However, CASCADE models re-trained on our ground truth further improved the performance, resulting in a more accurate inference of spiking activity from spinal cord neurons. We openly provide re-trained models that can be applied to spinal cord data with variable noise levels and frame rates. Together, our ground-truth recordings and analyses provide a solid foundation for the interpretation of calcium imaging data from spinal cord dorsal horn and showcase how spike rate inference can generalize between different regions of the nervous system.Significance Statement Calcium imaging is a powerful method for measuring the activity of genetically identified neurons. However, accurate interpretation of calcium transients depends on having a detailed understanding of how neuronal activity correlates with fluorescence. Such calibration recordings have been performed for cerebral cortex but not yet for most other CNS regions and neuron types. Here, we obtained ground truth data in spinal cord by conducting simultaneous calcium and electrophysiology recordings in excitatory and inhibitory neurons. We systematically investigated the transferability of cortical algorithms to spinal neuron subpopulations and generated inference algorithms optimized to excitatory and inhibitory neurons. Our study provides a foundation for the rigorous interpretation of calcium imaging data from spinal cord.

PMID:40127941 | DOI:10.1523/JNEUROSCI.1187-24.2025

J Subst Use Addict Treat. 2025 Mar 22:209685. doi: 10.1016/j.josat.2025.209685. Online ahead of print.

ABSTRACT

BACKGROUND: Despite effective treatments for opioid use disorder (OUD), relapse and treatment drop-out diminish their efficacy, increasing the risks of adverse outcomes, including death. Predicting important outcomes, including non-prescribed opioid use (NPOU) and treatment discontinuation among persons receiving medications for OUD (MOUD) can provide a proactive approach to these challenges. Our study uses ecological momentary assessment (EMA) and deep learning to predict momentary NPOU, medication nonadherence, and treatment retention in MOUD patients.

METHODS: Study participants included adults receiving MOUD at a large outpatient treatment program. We predicted NPOU (EMA-based), medication nonadherence (Electronic Health Record [EHR]- and EMA-based), and treatment retention (EHR-based) using context-sensitive EMAs (e.g., stress, pain, social setting). We used recurrent deep learning models with 7-day sliding windows to predict the next-day outcomes, using Area Under the ROC Curve (AUC) for assessment. We employed SHapley additive ExPlanations (SHAP) to understand feature latency and importance.

RESULTS: Participants comprised 62 adults with 14,322 observations. Model performance varied across EMA subtypes and outcomes with AUCs spanning 0.58-0.97. Recent substance use was the best performing predictor for EMA-based NPOU (AUC = 0.97). Life-contextual factors performed best for EMA-based medication nonadherence (AUC = 0.68) and retention (AUC = 0.89), and substance use risk factors (e.g., nicotine and alcohol use) performed best for predicting EHR-based medication nonadherence (AUC = 0.79). SHAP revealed varying latencies between predictors and outcomes.

CONCLUSIONS: Findings support the effectiveness of EMA and deep learning for forecasting actionable outcomes in persons receiving MOUD. These insights will enable the development of personalized dynamic risk profiles and just-in-time adaptive interventions (JITAIs) to mitigate high-risk OUD outcomes.

PMID:40127869 | DOI:10.1016/j.josat.2025.209685

Genomics. 2025 Mar 22:111037. doi: 10.1016/j.ygeno.2025.111037. Online ahead of print.

ABSTRACT

One common post-transcriptional modification that is essential to biological activities is RNA 5-methylcytosine (m5C). A large amount of RNA data containing m5C modification sites has been gathered as a result of the rapid development of high-throughput sequencing technology. While there are a lot of machine learning based techniques available for identifying m5C alteration sites, these models' accuracy still has to be raised. This study proposed a novel method, Feadm5C, which predicts m5C based on fusing molecular graph features and sequencing information together. 10-fold cross-validation was used to assess the model's predictive performance. In addition, we used t-SNE visualization to assess the model's stability and effectiveness. While keeping feature encoding and model structure straightforward, the approach suggested in this work outperforms the most recent approaches in use. The dataset and code of the model can be downloaded from GitHub (https://github.com/LiangYu-Xidian/Feadm5C).

PMID:40127825 | DOI:10.1016/j.ygeno.2025.111037

Int J Biol Macromol. 2025 Mar 22:142309. doi: 10.1016/j.ijbiomac.2025.142309. Online ahead of print.

ABSTRACT

Cas proteins (CRISPR-associated protein) are the core components of the CRISPR-Cas system, playing critical roles in defending against foreign DNA and RNA invasions. Identifying Cas proteins can provide deeper insights into the immune mechanisms of the CRISPR-Cas system and help uncover the functional mechanisms of Cas proteins. In this study, we developed a computational tool named CasPro-ESM2, which combines the Pre-trained Protein Language Model ESM-2, multi-scale convolutional neural networks, and evolutionary information from protein sequences to identify Cas proteins. Experimental results demonstrate that CasPro-ESM2 outperforms existing models in Cas protein identification, achieving the highest values in metrics such as ACC, SP, SN, and MCC on two different datasets. Furthermore, we deployed this tool on a web server to enable direct access for users (http://www.bioai-lab.com/CasProESM-2).

PMID:40127793 | DOI:10.1016/j.ijbiomac.2025.142309

J Nucl Cardiol. 2025 Mar 22:102195. doi: 10.1016/j.nuclcard.2025.102195. Online ahead of print.

ABSTRACT

BACKGROUND: [18F]-fluorodeoxyglucose ([18F]FDG) positron emission tomography (PET) plays a central role in diagnosing and managing cardiac sarcoidosis. We propose a fully automated pipeline for quantification of [18F]FDG PET activity using deep learning (DL) segmentation of cardiac chambers on computed tomography (CT) attenuation maps and evaluate quantitative approaches based on this framework.

METHODS: We included consecutive patients undergoing [18F]FDG PET/CT for suspected cardiac sarcoidosis. DL segmented left atrium, left ventricle (LV), right atrium, right ventricle, aorta, LV myocardium, and lungs from CT attenuation scans. CT-defined anatomical regions were applied to [18F]FDG PET images automatically to target to background ratio (TBR), volume of inflammation (VOI) and cardiometabolic activity (CMA) using full sized and shrunk segmentations.

RESULTS: A total of 69 patients were included, with mean age of 56.1 ± 13.4 and cardiac sarcoidosis present in 29 (42%). CMA had highest prediction performance (area under the receiver operating characteristic curve [AUC] 0.919, 95% confidence interval [CI] 0.858 - 0.980) followed by VOI (AUC 0.903, 95% CI 0.834 - 0.971), TBR (AUC 0.891, 95% CI 0.819 - 0.964), and maximum standardized uptake value (AUC 0.812, 95% CI 0.701 - 0.923). Abnormal CMA (≥1) had a sensitivity of 100% and specificity 65% for cardiac sarcoidosis. Lung quantification was able to identify patients with pulmonary abnormalities.

CONCLUSION: We demonstrate that fully automated volumetric quantification of [18F]FDG PET for cardiac sarcoidosis based on CT attenuation map-derived volumetry is feasible, rapid, and has high prediction performance. This approach provides objective measurements of cardiac inflammation with consistent definition of myocardium and background region.

CONDENSED ABSTRACT: We developed a fully automated pipeline for [18F]-fluorodeoxyglucose ([18F]FDG) PET quantification in patients with suspected cardiac sarcoidosis. A previously validated deep learning model segmented cardiac chambers from computed tomography, followed by quantification of target to background ratio, volume of inflammation and cardiometabolic activity (CMA). A total of 69 patients were included, with cardiac sarcoidosis present in 29 (42%). CMA had highest area under the receiver operating characteristic curve (0.919, 95% confidence interval 0.858 - 0.980). Fully automated volumetric quantification of [18F]FDG PET is feasible and has high prediction performance for cardiac sarcoidosis.

PMID:40127777 | DOI:10.1016/j.nuclcard.2025.102195

Neural Netw. 2025 Mar 22;187:107397. doi: 10.1016/j.neunet.2025.107397. Online ahead of print.

ABSTRACT

Existing neural network models to learn Hamiltonian systems, such as SympNets, although accurate in low-dimensions, struggle to learn the correct dynamics for high-dimensional many-body systems. Herein, we introduce Symplectic Graph Neural Networks (SympGNNs) that can effectively handle system identification in high-dimensional Hamiltonian systems, as well as node classification. SympGNNs combine symplectic maps with permutation equivariance, a property of graph neural networks. Specifically, we propose two variants of SympGNNs: (i) G-SympGNN and (ii) LA-SympGNN, arising from different parameterizations of the kinetic and potential energy. We demonstrate the capabilities of SympGNN on two physical examples: a 40-particle coupled Harmonic oscillator, and a 2000-particle molecular dynamics simulation in a two-dimensional Lennard-Jones potential. Furthermore, we demonstrate the performance of SympGNN in the node classification task, achieving accuracy comparable to the state-of-the-art. We also empirically show that SympGNN can overcome the oversmoothing and heterophily problems, two key challenges in the field of graph neural networks.

PMID:40127578 | DOI:10.1016/j.neunet.2025.107397

Talanta. 2025 Mar 22;292:127937. doi: 10.1016/j.talanta.2025.127937. Online ahead of print.

ABSTRACT

Rare earth elements like lanthanum (La), cerium (Ce), and neodymium (Nd) are vital for high-tech industries, and their real-time quantitative analysis is crucial for refining rare earth ores. Laser induced breakdown spectroscopy (LIBS) is an effective tool for such analysis but faces challenges due to the matrix effects and spectral overlaps. This paper proposes a LIBS quantitative analysis model based on the iTransformer-Bidirectional long short-term memory (iTBi) deep learning algorithm, and further integrates the iTBi model with the random forest (RF) algorithm to form the iTBi-RF-LIBS ensemble model. These methods uses 35 samples, with concentration ranges for La, Ce, and Nd from 0wt% to 1.924wt%, 0wt% to 2.917wt%, and 0wt% to 1.492wt%, respectively. Compared to univariate analysis, BiLSTM, RF, and backpropagation neural network models, the iTBi-LIBS and iTBi-RF-LIBS models show significant advantages. The iTBi-LIBS model achieves calibration coefficients (R2) of 0.989, 0.983, and 0.994 for La, Ce, and Nd, respectively, with mean absolute prediction errors (MAEP) of 0.075wt%, 0.167wt%, and 0.067wt%, and root mean square prediction errors (RMSEP) of 0.095wt%, 0.225wt%, and 0.083wt%, respectively. The R2 values for the iTBi-RF-LIBS model are improved to 0.993, 0.992, and 0.996 for La, Ce, and Nd, respectively, with MAEP reduced to 0.059wt%, 0.135wt%, and 0.053wt%, and RMSEP reduced to 0.075wt%, 0.184wt%, and 0.069wt%, respectively. These results indicate that both the iTBi-LIBS model and the iTBi-RF-LIBS ensemble model effectively reduce matrix effects and spectral overlap interferences, providing a feasible technical pathway for the precise determination of La, Ce, and Nd element concentrations in rare earth ores.

PMID:40127553 | DOI:10.1016/j.talanta.2025.127937

Kidney Int. 2025 Mar 22:S0085-2538(25)00255-8. doi: 10.1016/j.kint.2025.02.027. Online ahead of print.

ABSTRACT

Human kidney organoids derived from embryonic stem cells (ESCs) or induced pluripotent stem cells (iPSCs) have become novel tools for studying various kidney pathologies. Here, we transplanted ESC-derived kidney organoids into humanized mice with a mature human adaptive immune system developed through thymic education. As judged by histology and immunophenotyping, the transplanted HLA-mismatched kidney organoids trigged a robust alloimmune response, characterized by a dense immune cell infiltrate and enhanced memory T cell phenotype in the allograft 30 days post-transplantation. Multiplexed immunofluorescence revealed expression of functional markers of various immune cell infiltrates in response to organoid allografts, mimicking the T cell-mediated rejection process in humans. This validated our model as a novel platform to study various therapeutic strategies to control alloimmunity. Splenocytes isolated from organoid-transplanted hosts showed an alloantigen-specific memory response against 2D kidney organoids ex vivo. Overall, our study indicates that transplanting kidney organoids in humanized mice may be a valuable tool for studying human allogeneic immunity.

PMID:40127865 | DOI:10.1016/j.kint.2025.02.027