BMC Musculoskelet Disord. 2025 Apr 17;26(1):378. doi: 10.1186/s12891-025-08631-x.

ABSTRACT

RATIONALE AND OBJECTIVES: To establish an automated osteoporosis detection model based on low-dose abdominal CT (LDCT). This model combined a deep learning-based automatic segmentation of the proximal femur with a radiomics-based bone status classification.

MATERIALS AND METHODS: A total of 456 participants were retrospectively included and were divided into a development cohort comprising 355 patients, with a 7:3 ratio randomly assigned to the training and validation cohorts, and a test cohort comprising 101 patients. The automatic segmentation model for the proximal femur was trained using VB-Net. The Dice similarity coefficient (DSC) and volume difference (VD) were employed to evaluate the performance of the segmentation model. A three-classification predictive model for assessing bone mineral status was constructed utilizing radiomic analysis. The diagnostic performance of the radiomics model was assessed using the area under the curve (AUC), sensitivity, and specificity.

RESULTS: The automatic segmentation model for the proximal femur demonstrated excellent performance, achieving DSC values of 0.975 ± 0.012 and 0.955 ± 0.137 in the validation and test cohorts, respectively. In the test cohort, the radiomics model utilizing the random forest (RF) classifier achieved AUC values, sensitivity, and specificity of 0.924 (95% CI: 0.854-0.967), 0.846 (95% CI: 0.719-0.931), and 0.837 (95% CI: 0.703-0.927) for the identification of normal bone mass. For the identification of osteoporosis, the corresponding metrics were 0.960 (95% CI: 0.913-1.000), 0.947 (95% CI: 0.740-0.999), and 0.963 (95% CI: 0.897-0.992). In the case of osteopenia, the corresponding metrics were 0.828 (95% CI: 0.747-0.909), 0.767 (95% CI: 0.577-0.901), and 0.746 (95% CI: 0.629-0.842).

CONCLUSION: A three-classification predictive model combining a deep learning-based automatic segmentation of the proximal femur and a radiomics-based bone status classification on LDCT images can be used for the opportunistic detection of osteoporosis.

PMID:40241032 | DOI:10.1186/s12891-025-08631-x

Sci Rep. 2025 Apr 16;15(1):13074. doi: 10.1038/s41598-025-97842-2.

ABSTRACT

Deep learning-based image processing methods are commonly used for bridge crack detection. Aiming at the problem of missed detections and false positives caused by light, stains, and dense cracks during detection, this paper proposes a bridge crack detection algorithm based on the improved YOLOv8n model. Firstly, enhancing the model's feature extraction capabilities by incorporating the global attention mechanism into the Backbone and Neck to gather additional crack characterization information. And optimizing the original feature fusion model through Gam-Concat to enhance the feature fusion effect. Subsequently, in the FPN-PAN structure, replacing the original upsample module with DySample promotes the full fusion of high- and low-resolution feature information, enhancing the detection capability for cracks of different scales. Finally, adding MPDIoU to the Head to optimize the bounding box function loss, enhancing the model's ability to evaluate the overlap of dense cracks and better reflecting the spatial relationships between the cracks. In ablation and comparison experiments, the improved model achieved increases of 3.02%, 3.39%, 2.26%, and 0.81% in mAP@0.5, mAP@0.5:0.95, precision, and recall, respectively, compared to the original model. And the detection accuracy is significantly higher than other comparative models. It has practical application value in bridge inspection projects.

PMID:40240806 | DOI:10.1038/s41598-025-97842-2

Sci Rep. 2025 Apr 16;15(1):13075. doi: 10.1038/s41598-025-97407-3.

ABSTRACT

Multi-Criteria Recommender Systems (MCRSs) improve personalization by incorporating multiple user preferences. However, their application in Technology-Enhanced Learning (TEL) remains limited due to challenges such as data sparsity, over-specialization, and cold-start problems. Traditional techniques, such as Singular Value Decomposition (SVD) and SVD + + , struggle to effectively model the complex interactions within multi-criteria rating data, leading to suboptimal recommendations. This paper introduces a hybrid DeepFM-SVD + + model, which integrates deep learning and factorization-based techniques to improve multi-criteria recommendations. The model captures both low-order feature interactions using factorization machines and high-order dependencies through deep neural networks, enabling more adaptive recommendations. To evaluate its performance, the model is tested on two multi-criteria datasets: ITM-Rec (TEL domain) and Yahoo Movies (non-TEL domain). The experimental results show that DeepFM-SVD + + consistently outperforms the traditional techniques across multiple evaluation metrics. The findings highlight significant improvements in accuracy, demonstrating the model's effectiveness in sparse datasets and its generalization across domains. By addressing the limitations of existing MCRS techniques, this study contributes to advancing personalized learning recommendations in TEL and expands the applicability of deep learning-based MCRS beyond educational contexts.

PMID:40240805 | DOI:10.1038/s41598-025-97407-3

Sci Rep. 2025 Apr 16;15(1):13171. doi: 10.1038/s41598-025-96035-1.

ABSTRACT

X-ray image-based prohibited item detection plays a crucial role in modern public security systems. Despite significant advancements in deep learning, challenges such as feature extraction, object occlusion, and model complexity remain. Although recent efforts have utilized larger-scale CNNs or ViT-based architectures to enhance accuracy, these approaches incur substantial trade-offs, including prohibitive computational overhead and practical deployment limitations. To address these issues, we propose Xray-YOLO-Mamba, a lightweight model that integrates the YOLO and Mamba architectures. Key innovations include the CResVSS block, which enhances receptive fields and feature representation; the SDConv downsampling block, which minimizes information loss during feature transformation; and the Dysample upsampling block, which improves resolution recovery during reconstruction. Experimental results demonstrate that the proposed model achieves superior performance across three datasets, exhibiting robust performance and excellent generalization ability. Specifically, our model attains mAP50-95 of 74.6% (CLCXray), 43.9% (OPIXray), and 73.9% (SIXray), while demonstrating lightweight efficiency with 4.3 M parameters and 10.3 GFLOPs. The architecture achieves real-time performance at 95.2 FPS on the GPUs. In summary, Xray-YOLO-Mamba strikes a favorable balance between precision and computational efficiency, demonstrating significant advantages.

PMID:40240781 | DOI:10.1038/s41598-025-96035-1

Neuroinformatics. 2025 Apr 16;23(2):28. doi: 10.1007/s12021-025-09724-7.

ABSTRACT

Brain slicing is a commonly used technique in brain science research. In order to study the spatial distribution of labeled information, such as specific types of neurons and neuronal circuits, it is necessary to register the brain slice images to the 3D standard brain space defined by the reference atlas. However, the registration of 2D brain slice images to a 3D reference brain atlas still faces challenges in terms of accuracy, computational throughput, and applicability. In this paper, we propose the SlicesMapi, an interactive 3D registration method for brain slice sequence. This method corrects linear and non-linear deformations in both 3D and 2D spaces by employing dual constraints from neighboring slices and corresponding reference atlas slices and guarantees precision by registering images with full resolution, which avoids the information loss of image down-sampling implemented in the deep learning based registration methods. This method was applied to deal the challenges of unknown slice angle registration and non-linear deformations between the 3D Allen Reference Atlas and slices with cytoarchitectonic or autofluorescence channels. Experimental results demonstrate Dice scores of 0.9 in major brain regions, highlighting significant advantages over existing methods. Compared with existing methods, our proposed method is expected to provide a more accurate, robust, and efficient spatial localization scheme for brain slices. Therefore, the proposed method is capable of achieving enhanced accuracy in slice image spatial positioning.

PMID:40240690 | DOI:10.1007/s12021-025-09724-7

Doc Ophthalmol. 2025 Apr 16. doi: 10.1007/s10633-025-10019-0. Online ahead of print.

ABSTRACT

PURPOSE: The electroretinogram (ERG) records the functional response of the retina. In some neurological conditions, the ERG waveform may be altered and could support biomarker discovery. In heterogeneous or rare populations, where either large data sets or the availability of data may be a challenge, synthetic signals with Artificial Intelligence (AI) may help to mitigate against these factors to support classification models.

METHODS: This approach was tested using a publicly available dataset of real ERGs, n = 560 (ASD) and n = 498 (Control) recorded at 9 different flash strengths from n = 18 ASD (mean age 12.2 ± 2.7 years) and n = 31 Controls (mean age 11.8 ± 3.3 years) that were augmented with synthetic waveforms, generated through a Conditional Generative Adversarial Network. Two deep learning models were used to classify the groups using either the real only or combined real and synthetic ERGs. One was a Time Series Transformer (with waveforms in their original form) and the second was a Visual Transformer model utilizing images of the wavelets derived from a Continuous Wavelet Transform of the ERGs. Model performance at classifying the groups was evaluated with Balanced Accuracy (BA) as the main outcome measure.

RESULTS: The BA improved from 0.756 to 0.879 when synthetic ERGs were included across all recordings for the training of the Time Series Transformer. This model also achieved the best performance with a BA of 0.89 using real and synthetic waveforms from a single flash strength of 0.95 log cd s m-2.

CONCLUSIONS: The improved performance of the deep learning models with synthetic waveforms supports the application of AI to improve group classification with ERG recordings.

PMID:40240677 | DOI:10.1007/s10633-025-10019-0

Eur Radiol. 2025 Apr 16. doi: 10.1007/s00330-025-11546-9. Online ahead of print.

ABSTRACT

OBJECTIVES: To evaluate the performance of high-resolution deep learning-based hip MR imaging (CSAI) compared to standard-resolution compressed sense (CS) sequences using hip arthroscopy as standard of reference.

METHODS: Thirty-two patients (mean age, 37.5 years (± 11.7), 24 men) with femoroacetabular impingement syndrome underwent 3-T MR imaging prior to hip arthroscopy. Coronal and sagittal intermediate-weighted TSE sequences with fat saturation were obtained using CS (0.6 × 0.8 mm) and high-resolution CSAI (0.3 × 0.4 mm), with 3 mm slice thickness and similar acquisition times (3:55-4:12 min). MR scans were independently assessed by three radiologists and a hip arthroscopy specialist for labral and cartilage abnormalities. Sensitivity, specificity, and accuracy were calculated using arthroscopy as reference standard. Statistical comparisons between CS and CSAI were performed using McNemar's test.

RESULTS: Labral abnormality detection showed excellent sensitivity for radiologists (CS and CSAI: 97-100%) and the surgeon (CS: 81%, CSAI: 90%, p = 0.08), with 100% specificity. Overall cartilage lesion sensitivity was significantly higher with CSAI versus CS (42% vs. 37%, p < 0.001). Highest sensitivity was observed in superolateral acetabular cartilage (CS: 81%, CSAI: 88%, p < 0.001), while highest specificity was found for the anteroinferior acetabular cartilage (CS and CSAI: 99%). Sensitivity was lowest for the assessment of the anteroinferior and posterior acetabular zones, and inferior and posterior femoral zones (CS and CSAI < 6%).

CONCLUSION: CS and CSAI MR imaging showed excellent diagnostic performance for labral abnormalities. Despite CSAI's improved cartilage lesion detection, overall diagnostic performance for cartilage assessment remained suboptimal.

KEY POINTS: Question Accurate preoperative detection of labral and cartilage lesions in femoroacetabular impingement remains challenging, with current MRI protocols showing variable diagnostic performance. Findings High-resolution deep learning-based and standard-resolution compressed sense MRI demonstrate comparable diagnostic performance, with high accuracy for labral defects but limited sensitivity for cartilage lesions. Clinical relevance Current MRI protocols, regardless of resolution optimization, show persistent limitations in cartilage evaluation, indicating the need for further technical advancement to improve diagnostic confidence in presurgical planning.

PMID:40240555 | DOI:10.1007/s00330-025-11546-9

Sci Rep. 2025 Apr 16;15(1):13188. doi: 10.1038/s41598-025-97374-9.

ABSTRACT

Jin Bei oral liquid (JBOL) is a Chinese medicinal preparation for the treatment of idiopathic pulmonary fibrosis (IPF), Clinical trials have shown that IPF patients using JBOL have improved their lung function indicators FVC% and DLCO% by approximately 2.10% and 7.74%, suggesting that the agent has a positive effect in slowing disease progression. In this study, the active volatile components of JBOL were systematically identified and analyzed using gas chromatography-mass spectrometry (GC-MS), network pharmacology and molecular docking techniques. It was found that JBOL contains a variety of compounds with antifibrotic potential, which act through multi-target and multi-pathway mechanisms. Network pharmacological analyses revealed multiple targets of JBOL associated with key pathological processes in IPF, and key active ingredients were screened based on degree values (including Sedanolide, Ligustilide, Senkyunolide H, Senkyunolide I, α-Terpineol, and 4-Terpineol). Molecular docking results showed that these compounds have high affinity for target proteins. Finally, suitable quantitative methods were established and methodologically validated for these six compounds, and these methods were used to determine the content of 8 batches of JBOL and analyze the differences in content between batches.The present study provides a scientific basis for the quality control and standardization of its JBOL by identifying and analyzing its active volatile components.

PMID:40240792 | DOI:10.1038/s41598-025-97374-9

Toxicol Appl Pharmacol. 2025 Apr 14:117342. doi: 10.1016/j.taap.2025.117342. Online ahead of print.

ABSTRACT

Idiopathic pulmonary fibrosis (IPF) is a debilitating lung disease characterized by excessive extracellular matrix deposition, leading to irreversible lung scarring. This study explores the underlying molecular mechanisms of IPF and delves into membrane-anchored synergism between EGFR and AnxA2, which amplifies fibrotic stress and plays a pivotal role in promoting pulmonary fibroblast activation and fibrosis. Indeed, these interactions create a synergistic effect that promotes the loss of epithelial traits and the transition to a mesenchymal phenotype, thereby contributing to fibrotic stress and disease progression. In addition, this study also explores the potential of butyrate, a short-chain fatty acid, as a therapeutic agent in reducing fibrotic stress by modulating AnxA2-EGFR signaling. Pre-treatment with butyrate significantly dampens AnxA2-EGFR signaling and Galectin-3 expression, effectively curbing prolonged EGFR phosphorylation. The suppression of upstream signaling leads to a reduction in the angiogenic marker VEGF and a decrease in pro-inflammatory mediators such as TNF-α and IL-6. Collectively, our findings highlight the critical role of EGFR-AnxA2 signaling and Galectin 3 in the pathogenesis of IPF, and highlight butyrate as a potential therapeutic agent for alleviating fibrotic stress.

PMID:40239744 | DOI:10.1016/j.taap.2025.117342

Sci Data. 2025 Apr 16;12(1):645. doi: 10.1038/s41597-025-04968-z.

ABSTRACT

Bougainvillea glabra is an ornamental tree or shrub with nearly 200 years of application in gardening and landscapes globally. Recently, the growing research interest in the applications of B. glabra extracts, such as medicinal applications, and synthetic materials for nutraceuticals, has led to the development of new techniques to be utilized for studying B. glabra. Moreover, the formations of polymorphic coloration and the mechanism of metamorphic bracts in B. glabra cultivars are worthy of study. However, the multi-omics information for B. glabra cultivars is lacking which hinders the progress of gene-level research and genetic applications. We sequenced the bracts transcriptomes of 22 B. glabra accessions and generated more than 80 Gb clean data. After de novo assembly and optimization, 174,758 unigenes (E90N50 = 2,473 bp) and annotation data were obtained. In addition, a total of 100,115 CDSs were detected. On average, each variety has 69,990 unigenes containing SNPs, among which 35,682 were annotated per variety. These transcriptome data are valuable for gene mining and expression experiments or other scientific areas.

PMID:40240768 | DOI:10.1038/s41597-025-04968-z

Nat Plants. 2025 Apr 16. doi: 10.1038/s41477-025-01979-x. Online ahead of print.

ABSTRACT

Short-read RNA-seq studies of grafted plants have led to the proposal that thousands of messenger RNAs (mRNAs) move over long distances between plant tissues1-7, potentially acting as signals8-12. Transport of mRNAs between cells and tissues has been shown to play a role in several physiological and developmental processes in plants, such as tuberization13, leaf development14 and meristem maintenance15; yet for most mobile mRNAs, the biological relevance of transport remains to be determined16-19. Here we perform a meta-analysis of existing mobile mRNA datasets and examine the associated bioinformatic pipelines. Taking technological noise, biological variation, potential contamination and incomplete genome assemblies into account, we find that a high percentage of currently annotated graft-mobile transcripts are left without statistical support from available RNA-seq data. This meta-analysis challenges the findings of previous studies and current views on mRNA communication.

PMID:40240650 | DOI:10.1038/s41477-025-01979-x

Nat Rev Cancer. 2025 Apr 16. doi: 10.1038/s41568-025-00818-7. Online ahead of print.

NO ABSTRACT

PMID:40240643 | DOI:10.1038/s41568-025-00818-7

Cell Death Dis. 2025 Apr 16;16(1):307. doi: 10.1038/s41419-025-07623-y.

ABSTRACT

The von Hippel-Lindau (VHL) tumor suppressor is a substrate-defining component of E3 ubiquitin ligase complexes that target cellular substrates for proteasome-mediated degradation. VHL inactivation by mutation or transcriptional silencing is observed in most sporadic cases of clear cell renal cell carcinoma (ccRCC). VHL loss in ccRCC leads to constitutive stabilization of E3 ligase substrates, including hypoxia inducible factor α (HIFα). HIFα stabilization upon VHL loss is known to contribute to ccRCC development through transactivation of hypoxia-responsive genes. HIF-independent VHL targets have been implicated in oncogenesis, although those mechanisms are less well-defined than for HIFα. Using proximity labeling to identify proteasomal-sensitive VHL interactors, we identified retinoblastoma protein (pRb) as a novel substrate of VHL. Mechanistically, VHL interacts with pRb in a proteasomal-sensitive manner, promoting its ubiquitin-mediated degradation. Concordantly, VHL-inactivation results in pRb hyperstabilization. Functionally, loss of pRb in ccRCC led to increased cell death, transcriptional changes, and loss of oncogenic properties in vitro and in vivo. We also show that downstream transcriptional changes induced by pRb hyperstabilization may contribute to ccRCC tumor development. Together, our findings reveal a novel VHL-related pathway which can be therapeutically targeted to inhibit ccRCC tumor development.

PMID:40240354 | DOI:10.1038/s41419-025-07623-y

Trends Immunol. 2025 Apr 15:S1471-4906(25)00077-8. doi: 10.1016/j.it.2025.03.003. Online ahead of print.

ABSTRACT

The Molecular Mechanisms of Immune Cell Development and Function (MMICDF) meeting sponsored by the Federation of American Societies of Experimental Biology (FASEB) occupies a special niche because of its focus on the molecular mechanisms that underpin immunological processes. This biennial meeting with small groupings of participants and interactive nature has provided a forum for intense, informative, and influential scientific discussions. The meeting is unique for its focus on molecular mechanisms that control the exceptional processes of DNA recombination, somatic hypermutation (SHM), and gene expression during immune cell development, activation, and differentiation. The organizers of the foundational meeting reflect on the coalescence of scientific advances that catalyzed its origin, review meeting highlights to celebrate its 20th anniversary, and project into the future.

PMID:40240192 | DOI:10.1016/j.it.2025.03.003

Cell. 2025 Apr 14:S0092-8674(25)00346-0. doi: 10.1016/j.cell.2025.03.028. Online ahead of print.

ABSTRACT

How developmental signals program gene expression in space and time is still poorly understood. Here, we addressed this question for the plant master regulator, auxin. Transcriptional responses to auxin rely on a large multigenic transcription factor family, the auxin response factors (ARFs). We deconvoluted the complexity of ARF-regulated transcription using auxin-inducible synthetic promoters built from cis-element pair configurations differentially bound by ARFs. We demonstrate using cellular systems that ARF transcriptional properties are not only intrinsic but also depend on the cis-element pair configurations they bind to, thus identifying a bi-layer ARF/cis-element transcriptional code. Auxin-inducible synthetic promoters were expressed differentially in planta showing at single-cell resolution how this bi-layer code patterns transcriptional responses to auxin. Combining cis-element pair configurations in synthetic promoters created distinct patterns, demonstrating the combinatorial power of the auxin bi-layer code in generating diverse gene expression patterns that are not simply a direct translation of auxin distribution.

PMID:40239648 | DOI:10.1016/j.cell.2025.03.028

Cell. 2025 Apr 12:S0092-8674(25)00349-6. doi: 10.1016/j.cell.2025.03.031. Online ahead of print.

ABSTRACT

Polyglutamine (polyQ) expansion is associated with pathogenic protein aggregation in neurodegenerative disorders. However, long polyQ tracts are also found in many transcription factors (TFs), such as FOXP2, a TF implicated in human speech. Here, we explore how FOXP2 and other glutamine-rich TFs avoid unscheduled assembly. Throughout interphase, DNA binding, irrespective of sequence specificity, has a solubilizing effect. During mitosis, multiple phosphorylation events promote FOXP2's eviction from chromatin and supplant the solubilizing function of DNA. Further, human-specific amino acid substitutions linked to the evolution of speech map to a mitotic phospho-patch, the "EVO patch," and reduce the propensity of the human FOXP2 to assemble. Fusing the pathogenic form of Huntingtin to either a DNA-binding domain, a phosphomimetic variant of this EVO patch, or a negatively charged peptide is sufficient to diminish assembly formation, suggesting that hijacking mechanisms governing solubility of glutamine-rich TFs may offer new strategies for treatment of polyQ expansion diseases.

PMID:40239647 | DOI:10.1016/j.cell.2025.03.031

Cell Rep Med. 2025 Apr 15;6(4):102045. doi: 10.1016/j.xcrm.2025.102045.

ABSTRACT

We present the clinical results of a phase 2 trial combining neoadjuvant docetaxel, cisplatin, 5 Flourouracil, and the PD-L1 inhibitor avelumab in locally advanced gastro-esophageal adenocarcinoma (GEA). Fifty-one patients receive neoadjuvant therapy with 50 proceeding to surgery. Grade 3-4 adverse events occur in 40%; complete/major pathological response is found in 7/50 (14%) and 9/50 (18%), with 2-year disease-free survival of 67.5%. There is no correlation between tumor regression and PD-L1 or mismatch repair (MMR) status. Multiplex immunohistochemistry and longitudinal single-cell transcriptomic profiling reveal alterations in certain innate immune cell populations, particularly noting an M2-tumor-associated macrophage (M2-TAM) proliferation in non-responding tumors. These findings describe the effective nature of this treatment regimen for GEA and reveal associated features of the inflammatory milieux associated with response to chemo-immunotherapy. The specific character of the inflammatory environment in non-responders may, in the future, help personalize treatment. This study was registered at ClinicalTrials.gov (NCT03288350).

PMID:40239627 | DOI:10.1016/j.xcrm.2025.102045

Cell Rep Med. 2025 Apr 15;6(4):102049. doi: 10.1016/j.xcrm.2025.102049.

ABSTRACT

In this interview for the Cell Reports Medicine 5-year anniversary special issue, Dr. Baloni talks with us about her scientific journey, the importance of mentorship, ongoing challenges and successes in the fields of translational neuroscience and neurodegenerative disease, and the power of systems biology to contribute to clinical and translational research.

PMID:40239622 | DOI:10.1016/j.xcrm.2025.102049

Int J Pediatr Otorhinolaryngol. 2025 Apr 15;193:112358. doi: 10.1016/j.ijporl.2025.112358. Online ahead of print.

ABSTRACT

BACKGROUND: Genetic factors are important causes of congenital hearing loss. To better understand hereditary hearing loss, we performed in-depth clinical and molecular analysis of families with congenital hearing loss and a new disease-related gene, IQGAP3, was identified in this process. This gene encodes a protein that belongs to the IQGAP family which is well known as a GTPase-activating protein involved in various cellular functions. However, there is no research on the relationship between IQGAP3 and the auditory system.

METHOD: This study was conducted at Guangzhou Women and Children's Medical Center and Nantong University from 2019 to 2023 to confirm the relationship between defective IQGAP3 and hearing loss, and further explore the underlying molecular mechanism. We constructed the iqgap3 knockdown zebrafish model, primary mouse inner progenitor cell model and IQGAP3-knockout HEK293T cell line for this research.

RESULT: We found that IQGAP3 deficiency led to abnormal development of the auditory system and impaired auditory function in zebrafish. In vitro studies showed that loss of this gene's function resulted in a 40.29 % reduction in EdU-positive cells and a 44.25 % decrease in Ki67-positive cells in mouse inner ear progenitor cells, indicating reduced proliferation. This can be linked with inhibition of CDC42 enzymatic activity and the blockade of the Wnt-catenin pathway.

CONCLUSION: We identified IQGAP3 as a novel potential causative gene in hereditary hearing loss. Our findings provide important insights into the molecular basis of hereditary hearing loss.

PMID:40239295 | DOI:10.1016/j.ijporl.2025.112358

Eye (Lond). 2025 Apr 16. doi: 10.1038/s41433-025-03808-z. Online ahead of print.

ABSTRACT

PURPOSE: To investigate primary suspect drugs and identify a potential association between medication use and Tubulointerstitial Nephritis and Uveitis (TINU).

METHODS: A retrospective pharmacovigilance study was conducted using the Food and Drug Administration (FDA) Adverse Events Database (FAERS) from Q1 2004 to Q2 2024, focusing on patient demographics and statistical signal detection. A qualitative analysis assessed patient demographics. To ascertain if these reports yielded statistically significant signals, we used the proportional reporting ratio (PRR), chi-squared with Yates' correction (χ2), reporting odds ratio (ROR), empirical Bayes geometric mean (EBGM), and information component (IC).

RESULTS: One hundred twenty-six adverse reports for TINU were identified, along with 37 primary suspect drugs from the FAERS database. The mean age of patients was 30.05 ± 20.88 years. Most reports were of female patients (n = 67, 53%). Of the 37 primary suspect drugs, lamotrigine (n = 35, 27%) and diclofenac (n = 15, 12%) were the most frequently reported suspect drugs. The signal detection analysis also identified positive signals and potential causality for both drugs. Lamotrigine demonstrated the strongest positive signal (PRR = 90.09, χ2 = 3001.58, ROR 95% CI: 124.35 [84.20-183.66], EBGM [EBGM05]: 70.98 [50.21], IC [IC05]: 5.32 [4.83]), followed by diclofenac (PRR = 24.21, χ2 = 312.49, ROR 95% CI: 27.35 [15.95-46.90], EBGM [EBGM05]: 4.11 [2.47], IC [IC05]: 3.79 [2.99]).

CONCLUSION: Our study identified 37 primary suspect drugs associated with TINU, with lamotrigine and diclofenac showing the strongest statistical signals. Lamotrigine demonstrated the highest association, suggesting a potential drug-related risk for developing TINU, particularly in younger patients and females. Further research is warranted to explore causality and underlying mechanisms in these associations.

PMID:40240507 | DOI:10.1038/s41433-025-03808-z