Eur J Radiol. 2025 Jan 29;184:111957. doi: 10.1016/j.ejrad.2025.111957. Online ahead of print.

ABSTRACT

OBJECTIVES: To convert 1D spectra into 2D images using the Gramian angular field, to be used as input for convolutional neural network for classification tasks such as glioblastoma versus lymphoma.

MATERIALS AND METHODS: Retrospective study including patients with histologically confirmed glioblastoma and lymphoma between 2009-2020 who underwent preoperative MR spectroscopy, using single voxel spectroscopy acquired with a short echo time (TE 30). We compared: 1) the Fourier-transformed raw spectra, and 2) the fitted spectra generated during post-processing. Both spectra were independently converted into images using the Gramian angular field, and then served as inputs for a pretrained neural network. We compared the classification performance using data from the Fourier-transformed raw spectra and the post-processed fitted spectra.

RESULTS: This feasibility study included 98 patients, of whom 65 were diagnosed with glioblastomas and 33 with lymphomas. For algorithm testing, 20 % of the cases (19 in total) were randomly selected. By applying the Gramian angular field technique to the Fourier-transformed spectra, we achieved an accuracy of 73.7 % and a sensitivity of 92 % in classifying glioblastoma versus lymphoma, slightly higher than the fitted spectra pathway.

CONCLUSION: Spectroscopy data can be effectively transformed into distinct color graphical images using the Gramian angular field technique, enabling their use as input for deep learning algorithms. Accuracy tends to be higher when utilizing data derived from Fourier-transformed spectra compared to fitted spectra. This finding underscores the potential of using MR spectroscopy data in neural network-based classification purposes.

PMID:39892374 | DOI:10.1016/j.ejrad.2025.111957

Med Image Anal. 2025 Jan 23;101:103474. doi: 10.1016/j.media.2025.103474. Online ahead of print.

ABSTRACT

Current deep learning-based solutions for image analysis tasks are commonly incapable of handling problems to which multiple different plausible solutions exist. In response, posterior-based methods such as conditional Diffusion Models and Invertible Neural Networks have emerged; however, their translation is hampered by a lack of research on adequate validation. In other words, the way progress is measured often does not reflect the needs of the driving practical application. Closing this gap in the literature, we present the first systematic framework for the application-driven validation of posterior-based methods in inverse problems. As a methodological novelty, it adopts key principles from the field of object detection validation, which has a long history of addressing the question of how to locate and match multiple object instances in an image. Treating modes as instances enables us to perform mode-centric validation, using well-interpretable metrics from the application perspective. We demonstrate the value of our framework through instantiations for a synthetic toy example and two medical vision use cases: pose estimation in surgery and imaging-based quantification of functional tissue parameters for diagnostics. Our framework offers key advantages over common approaches to posterior validation in all three examples and could thus revolutionize performance assessment in inverse problems.

PMID:39892221 | DOI:10.1016/j.media.2025.103474

Cell Signal. 2025 Jan 30:111635. doi: 10.1016/j.cellsig.2025.111635. Online ahead of print.

ABSTRACT

Idiopathic pulmonary fibrosis (IPF) is a terminal lung disease with high mortality rate. Although Nintedanib (Nin) is an effective treatment for IPF, its precise mechanism of action remains unclear. In this study, we performed an integrated analysis of single-cell sequencing and RNA-seq data from lung tissues of both fibrotic and Nin-treated fibrotic mice to uncover new therapeutic mechanisms of Nin in IPF. Our results revealed an increase in interstitial macrophages following bleomycin (BLM) treatment. We used Monocle2, Cellchat, and in vivo experiments to demonstrate that Nin can inhibit Clec7a in interstitial macrophages, thereby suppressing the SPP1-mediated profibrotic pathway. Additionally, we utilized Scenic to predict transcription factors and identified NFκB as a major transcription factor in interstitial macrophages. In the in vitro experiments, we found that inhibiting Clec7a improved the secretion of SPP1 by M2 macrophages through the NFκB pathway. In subsequent in vivo experiments, we found that inhibiting of Clec7a improves pulmonary fibrosis through the NFκB/SPP1 pathway, and Nin alleviated BLM-induced pulmonary fibrosis by inhibiting Clec7a in interstitial macrophages. In summary, our study indicates that interstitial macrophages are upregulated in pulmonary fibrosis, and Nin reduces fibrosis by inhibiting Clec7a in interstitial macrophages, which in turn diminishes the NFκB /SPP1 pathway. These findings provided a new perspective on the mechanism of action of Nin in treating pulmonary fibrosis.

PMID:39892726 | DOI:10.1016/j.cellsig.2025.111635

Respir Investig. 2025 Jan 31;63(2):216-223. doi: 10.1016/j.resinv.2025.01.007. Online ahead of print.

ABSTRACT

BACKGROUND: Idiopathic interstitial pneumonias (IIPs) may remain unclassifiable owing to inadequate, nonspecific, or conflicting clinical, radiological, or histopathological findings despite multidisciplinary discussion (MDD). Unclassifiable IIP (UCIIP) is a heterogeneous disease that can present with progressive pulmonary fibrosis (PPF). This study aimed to investigate the prevalence and clinical features of PPF in patients with UCIIP.

METHODS: In this post hoc analysis of a prospective multicenter registry of 222 patients with IIPs, 71 with UCIIP diagnosed using MDD were enrolled. PPF was defined based on worsening symptoms and radiological and physiological progression using the guideline criteria within 12 months or the criteria from the INBUILD trial within 24 months.

RESULTS: The median age was 72 years, and surgical lung biopsy was performed in 19.7%. Of the 66 patients with adequate follow-up data, 30 (45.5%) met either criterion and were diagnosed with PPF. UCIIP patients with PPF had significantly higher serum surfactant protein-D level and percentage of bronchoalveolar fluid neutrophils, lower %forced vital capacity and %diffusing capacity for carbon monoxide, and a higher proportion of honeycombing on high-resolution computed tomography and desaturation on exertion than those without PPF. Additionally, they had significantly more anti-fibrotic therapy and long-term oxygen therapy, a higher incidence of acute exacerbation, and a poorer prognosis than those without PPF. Cox proportional hazards analysis revealed that PPF was a significant poor prognostic factor, regardless of the criteria.

CONCLUSIONS: PPF is common and associated with poor prognosis in patients with UCIIP. Appropriate evaluation and management of PPF are essential for UCIIP.

PMID:39892159 | DOI:10.1016/j.resinv.2025.01.007

Nat Commun. 2025 Feb 1;16(1):1247. doi: 10.1038/s41467-025-56535-0.

ABSTRACT

Recent advances in spatial epigenomic techniques have given rise to spatial assay for transposase-accessible chromatin using sequencing (spATAC-seq) data, enabling the characterization of epigenomic heterogeneity and spatial information simultaneously. Integrative analysis of multiple spATAC-seq samples, for which no method has been developed, allows for effective identification and elimination of unwanted non-biological factors within the data, enabling comprehensive exploration of tissue structures and providing a holistic epigenomic landscape, thereby facilitating the discovery of biological implications and the study of regulatory processes. In this article, we present INSTINCT, a method for multi-sample INtegration of Spatial chromaTIN accessibility sequencing data via stochastiC domain Translation. INSTINCT can efficiently handle the high dimensionality of spATAC-seq data and eliminate the complex noise and batch effects of samples through a stochastic domain translation procedure. We demonstrate the superiority and robustness of INSTINCT in integrating spATAC-seq data across multiple simulated scenarios and real datasets. Additionally, we highlight the advantages of INSTINCT in spatial domain identification, visualization, spot-type annotation, and various downstream analyses, including motif enrichment analysis, expression enrichment analysis, and partitioned heritability analysis.

PMID:39893190 | DOI:10.1038/s41467-025-56535-0

Nat Commun. 2025 Feb 1;16(1):1253. doi: 10.1038/s41467-025-56383-y.

ABSTRACT

We reported that an acquired miR-142 deficit transforms chronic phase (CP) chronic myeloid leukemia (CML) leukemic stem cells (LSCs) into blast crisis (BC) LSCs. Given the role of miR-142 in the development and activity of the immune system, we postulated that this deficit also promotes LSC immune escape. Herein, we report on IL-6-driven miR-142 deficit occurring in T cells during BC transformation. In CML murine models, miR-142 deficit impairs thymic differentiation of lymphoid-primed multipotent progenitors (LMPP) into T cells and prevents T cells' metabolic reprogramming, thereby leading to loss of T cells and leukemia immune escape. Correcting miR-142 deficit with a miR-142 mimic compound (M-miR-142), alone or in combination with immune checkpoint antibodies, restores T cell number and immune activity, leading to LSC elimination and prolonged survival of BC CML murine and patient-derived xenograft models. These observations may open new therapeutic opportunities for BC CML and other myeloid malignancies.

PMID:39893171 | DOI:10.1038/s41467-025-56383-y

J Genet Genomics. 2025 Jan 30:S1673-8527(25)00032-3. doi: 10.1016/j.jgg.2025.01.017. Online ahead of print.

ABSTRACT

The liver performs several vital functions such as metabolism, toxin removal, and glucose storage through the coordination of various cell types. With the recent breakthrough of the single-cell/single-nucleus RNA-seq (sc/snRNA-seq) techniques, there is a great opportunity to establish a reference cell map of the liver at single-cell resolution with transcriptome-wise features. In this study, we build a unified liver cell atlas uniLIVER (http://lifeome.net/database/uniliver) by integrative analysis of a large-scale sc/snRNA-seq data collection of normal human liver with 331,125 cells and 79 samples from 6 datasets. Moreover, we introduce LiverCT, a novel machine learning based method for mapping any query dataset to the liver reference map by introducing the definition of "variant" cellular states analogy to the sequence variants in genomic analysis. Applying LiverCT on liver cancer datasets, we find that the "deviated" states of T cells are highly correlated with the stress pathway activities in hepatocellular carcinoma, and the enrichments of tumor cells with the hepatocyte-cholangiocyte "intermediate" states significantly indicate poor prognosis. Besides, we find the tumor cells of different patients have different zonation tendencies and this zonation tendency is also significantly associated with the prognosis. This reference atlas mapping framework can also be extended to any other tissues.

PMID:39892777 | DOI:10.1016/j.jgg.2025.01.017

Protein Expr Purif. 2025 Jan 30:106678. doi: 10.1016/j.pep.2025.106678. Online ahead of print.

ABSTRACT

SOG1, a transcription factor consisting of a folded NAC (NAM-ATAF-CUC2) domain and an intrinsically disordered C-terminal domain (CTD), co-ordinates the DNA damage response in plants. Here we compare different methods to express and purify recombinant full length Arabidopsis thaliana SOG1. Expression in Sf9 insect cells results in a protein that contains a phosphorylated site that is possibly located on the T423 site in the CTD. This site is reported to be phosphorylated in planta upon aluminium toxicity stress and may affect the transcriptional activity of SOG1 in an yet undetermined way. Expression of SOG1 in E. coli BL21 (DE3) leads to the formation of inclusion bodies, a problem that is resolved by using a cleavable SUMO solubility tag. The resulting protein is not phosphorylated and represents the transcriptional inactive state of SOG1. Both protein preparations show similar CD spectra and melting temperatures. SEC-MALS determined that the proteins, like other NAC transcription factors, form a dimer in solution. Both proteins are also highly non-globular as determined by analytical SEC and are likely stretched out due to their disordered CTD. In electromobility shift assays, both insect and E. coli purified SOG1 proteins bind to a DNA fragment from the promoter region of SMR5, a well established target gene of SOG1, showing the functionality of both purified proteins.

PMID:39892530 | DOI:10.1016/j.pep.2025.106678

Mol Cell. 2025 Jan 28:S1097-2765(25)00003-6. doi: 10.1016/j.molcel.2025.01.003. Online ahead of print.

ABSTRACT

Amplification of chromosomal material derived from 12q13-15 is common in human cancer and believed to result in overexpression of multiple collaborating oncogenes. To define the oncogenes involved, we overexpressed genes recurrently amplified in human liposarcoma using a zebrafish model of the disease. We found several genes whose overexpression collaborated with AKT in sarcomagenesis, including the tRNA methyltransferase METTL1. This was surprising, because AKT phosphorylates METTL1 to inactivate its enzymatic activity. Indeed, phosphomimetic S27D or catalytically dead alleles phenocopied the oncogenic activity of wild-type METTL1. We found that METTL1 binds the multi-tRNA synthetase complex, which contains many of the cellular aminoacyl-tRNA synthetases and promotes tRNA aminoacylation, polysome formation, and protein synthesis independent of its methyltransferase activity. METTL1-amplified liposarcomas were hypersensitive to actinomycin D, a clinical inhibitor of ribosome biogenesis. We propose that METTL1 overexpression promotes sarcomagenesis by stimulating tRNA aminoacylation, protein synthesis, and tumor cell growth independent of its methyltransferase activity.

PMID:39892392 | DOI:10.1016/j.molcel.2025.01.003

Cell Genom. 2025 Jan 30:100764. doi: 10.1016/j.xgen.2025.100764. Online ahead of print.

ABSTRACT

Tumor hypoxia drives metabolic shifts, cancer progression, and therapeutic resistance. Challenges in quantifying hypoxia have hindered the exploitation of this potential "Achilles' heel." While gene expression signatures have shown promise as surrogate measures of hypoxia, signature usage is heterogeneous and debated. Here, we present a systematic pan-cancer evaluation of 70 hypoxia signatures and 14 summary scores in 104 cell lines and 5,407 tumor samples using 472 million length-matched random gene signatures. Signature and score choice strongly influenced the prediction of hypoxia in vitro and in vivo. In cell lines, the Tardon signature was highly accurate in both bulk and single-cell data (94% accuracy, interquartile mean). In tumors, the Buffa and Ragnum signatures demonstrated superior performance, with Buffa/mean and Ragnum/interquartile mean emerging as the most promising for prospective clinical trials. This work delivers recommendations for experimental hypoxia detection and patient stratification for hypoxia-targeting therapies, alongside a generalizable framework for signature evaluation.

PMID:39892389 | DOI:10.1016/j.xgen.2025.100764

Microbiol Res. 2025 Jan 30;293:128087. doi: 10.1016/j.micres.2025.128087. Online ahead of print.

ABSTRACT

Erwinia amylovora (Ea) is a devastating bacterial pathogen that causes fire blight disease in Rosaceae family plants, including apples and pears. The use of bacteriophages is an alternative strategy to antibiotics for managing bacterial pathogens. In this study, the Ea-specific virulent phiEaSP1 phage was characterized, and its biocontrol efficacy against Ea was evaluated in apple seedlings. Genomic analyses revealed that phiEaSP1 belongs to the family Chaseviridae, subfamily Cleopatravirinae, and genus Loessnervirus. Most phiEaSP1 particles bound to the host cell surface within 5 min, and one virion made 68 progenies within 20 min of infection. The phage rapidly lysed Ea cells in vitro and maintained its lytic activity after incubation under different environmental conditions, including temperature, pH, and UV-A, as well as in the soil, with surfactants, and on apple seedlings. Receptor analysis using the Tn5 random mutant library of Ea TS3128 demonstrated that phiEaSP1 recognizes lipopolysaccharide as a receptor, whereas phiEaP-8 and phiEaP-21 recognize cellulose as a receptor. Protective efficacy against fire blight was tested on apple seedlings pretreated with the single phiEaSP1 or a phage cocktail containing phiEaSP1, phiEaP-8, and phiEaP-21. No or only weak symptoms were observed in the phage-treated seedlings. The application of a phage cocktail showed better control efficacy, indicating the potential of the phage cocktail, including phiEaSP1, as a preventive agent. Taken together, these results suggest that the use of a phage cocktail containing phiEaSP1 could be a potential strategy for the biocontrol of fire blight disease in apples.

PMID:39892321 | DOI:10.1016/j.micres.2025.128087

Eur J Med Chem. 2025 Jan 2;287:117234. doi: 10.1016/j.ejmech.2024.117234. Online ahead of print.

ABSTRACT

Despite the significant roles of solute carrier (SLC) and ATP-binding cassette (ABC) transporters in human health and disease, most remain poorly characterized as intrinsic and/or xenobiotic ligands are unknown, rendering them as 'undruggable'. Polypharmacology, defined as the simultaneous engagement of multiple targets by a single ligand, offers a promising avenue for discovering novel lead compounds addressing these emerging pharmacological challenges - a major focus in contemporary medicinal chemistry. While common structural motifs among phylogenetically diverse proteins have been proposed to underlie polypharmacology through the concept of 'multitarget binding sites', a comprehensive analysis of these functional and structural aspects from a medicinal chemistry perspective has yet to be undertaken. In our study, we synthesized 65 distinct indazole derivatives and evaluated their activity across a broad biological assessment platform encompassing 17 specific and polyspecific SLC and ABC transporters. Notably, ten indazoles exhibited cross-target activity against challenging transporter targets associated with neurodegeneration (ABCA1), metabolic reprogramming (MCT4), and cancer multidrug resistance (ABCC10). Furthermore, molecular blind docking experiments and advanced binding site analyses revealed, for the first time, conserved binding motifs across monocarboxylate transporters (MCTs), organic anion transporting polypeptides (OATPs), organic cation transporters (OCTs), and ABC transporters, characterized by specific and recurring residues of tyrosine, phenylalanine, serine, and threonine. These findings highlight not only the potential of polypharmacology in drug discovery but also provide insights into the structural underpinnings of ligand binding across membrane transporters.

PMID:39892094 | DOI:10.1016/j.ejmech.2024.117234

Cancer Immunol Immunother. 2025 Feb 1;74(3):90. doi: 10.1007/s00262-025-03943-2.

ABSTRACT

Imiquimod (IMQ), a drug from aminoquinoline group, is the toll-like receptor 7 (TLR7) agonist. It acts as an immunostimulant and radio-sensitizing agent. IMQ stimulates both innate and adaptive immune response. Despite studies conducted, there are no unambiguous data showing how IMQ affects the condition of tumor blood vessels. Tumor vasculature plays the main role in tumor progression. Formation of abnormal blood vessels increases area of hypoxia which recruits suppressor cells, blocks tumor infiltration by CD8+ T lymphocytes, inhibits efficacy of chemoterapeutic drug and leads to cancer relapse. Normalization is a type of therapy targeted at abnormal tumor blood vessels. Here, we demonstrated that 50 µg of IMQ inhibits the growth of melanoma tumors more efficiently, compared to other tested doses and the control group. Dose escalation did not improve the therapeutic antitumor potential of TLR7 agonist. A dose of 50 µg of IMQ most effectively reduced tumor blood vessel density. Imiquimod normalized tumor vasculature both structurally (by reducing vessel tortuosity and increasing pericyte coverage) and functionally (by improving tumor perfusion) in a dose-dependent manner. Hypoxia regions in tumors of treated mice were significantly reduced after IMQ administration. A dose of 50 µg of IMQ had also the greatest impact on the changes in tumor-infiltrating T lymphocytes levels. TLR7 agonist inhibited angiogenesis in treated mice. Functional vascular normalization by IMQ increases the effectiveness of low dose of doxorubicin. Higher dose of IMQ showed worse effects than lower doses including decreased tumor perfusion, increased tumor hypoxia and immunosuppression. This knowledge may help to optimize the combination of the selected IMQ dose with e.g. chemotherapy or radiotherapy to elicit synergistic effect in cancer treatment. To conclude, we outline IMQ repurposing as a vascular normalizing agent. Our research results may contribute to expanding the therapeutic indications for the use of IMQ in anticancer therapy in the future.

PMID:39891776 | DOI:10.1007/s00262-025-03943-2

Clin Transl Sci. 2025 Feb;18(2):e70136. doi: 10.1111/cts.70136.

ABSTRACT

High-dose methotrexate (HD-MTX) infusions are commonly used to consolidate remission in children with acute lymphoblastic leukemia (ALL). We investigate the potential role of candidate polymorphisms in SLCO1B1 (rs4149056 and rs2306283), ABCB1 (rs1045642), ABCC2 (rs717620), ABCC3 (rs9895420), and ABCC4 (rs7317112) drug transporters genes on HD-MTX pharmacokinetics and patients' outcome (meant both as relapse and drug-related toxicities) in an Italian cohort of 204 ALL pediatric patients treated according to the AIEOP-BFM ALL 2009 protocol. TaqMan SNP genotyping assays determined patient's genotypes. Measurements of HD-MTX plasma concentration were available for 814 HD-MTX courses in 204 patients; MTX clearance was estimated by a two-compartmental linear pharmacokinetic model with first-order elimination and a Bayesian approach, via ADAPT. Independent contributions of age and ABCC4 SNP rs7317112 (A>G, intronic) on MTX clearance were detected in a multivariate analysis (p = 1.57 × 10-8 and p = 2.06 × 10-5, respectively), suggesting a delayed elimination of the drug in older patients and an accelerated one in carriers of the variant GG genotype. After multiple corrections, the association between ABCC2 SNP rs717620 (-24 C>T) and severe hematological toxicity was found (p < 0.005). Moreover, SLCO1B1 SNP rs4149056 (c.521T>C, p.V174A) affected patients' outcomes: carriers of the variant C allele presented a reduced risk of relapse compared to wild-type TT (hazard risk: 0.27, 95% confidence interval [CI]: 0.08-0.90, p = 0.037). Taken together, these data highlighted the importance of variants in drug transporters genes on HD-MTX disposition in the AIEOP-BFM ALL 2009 protocol consolidation phase, and their putative role as predictive markers of outcome.

PMID:39891427 | DOI:10.1111/cts.70136

Clin Pharmacol Ther. 2025 Jan 31. doi: 10.1002/cpt.3572. Online ahead of print.

ABSTRACT

Ritonavir-boosted atazanavir is a victim of drug-drug interaction with rifampicin, a key component of antitubercular treatment. In a recent dose escalation clinical trial, we showed that increasing atazanavir/ritonavir to 300/100 mg b.i.d. compensates for reduced drug exposure in plasma due to rifampicin, but the intracellular effects remained unexplored. This sub-study investigated the intracellular penetration of atazanavir/ritonavir and dolutegravir into peripheral blood mononuclear cells (PBMC). Twenty-six healthy volunteers living with HIV, virologically suppressed, and taking atazanavir/ritonavir containing regimens were enrolled. The trial consisted of four sequential periods: PK1, participants were on atazanavir/ritonavir 300/100 mg q.d.; at PK2, rifampicin 600 mg q.d. and dolutegravir 50 mg b.i.d. were added (2 weeks); at PK3, atazanavir/ritonavir dose was increased to 300/100 mg b.i.d. (1 week); at PK4, rifampicin dose was doubled (1 week). Atazanavir, ritonavir, and dolutegravir were quantified in plasma and PBMC using LC-MS/MS methods to evaluate steady-state concentrations at the end of each period. Atazanavir/ritonavir dose escalation successfully restored intracellular concentrations comparable to those observed without rifampicin, with a geometric mean ratio of 0.99 (CI90 0.72-1.41) for atazanavir at PK3 compared with PK1. The intracellular concentration of dolutegravir increased significantly with atazanavir/ritonavir dose escalation, similar to plasma. Finally, further, increasing the rifampicin dose did not show an additional impact on atazanavir/ritonavir concentrations in PBMC. The study confirms that increasing the ATV/r dose can be an effective strategy for compensating rifampicin effects even at the intracellular level, supporting its use in clinical settings.

PMID:39891354 | DOI:10.1002/cpt.3572

Ther Adv Respir Dis. 2025 Jan-Dec;19:17534666251317200. doi: 10.1177/17534666251317200.

ABSTRACT

BACKGROUND: Cardiovascular disease (CVD) risks are increasing in people with cystic fibrosis (pwCF). While cholesterol levels were historically low in pwCF, higher levels after initiating highly effective modulator therapy (HEMT) have been reported. Mechanisms are unclear and there is little guidance on screening.

OBJECTIVES: To evaluate serum lipid changes at multiple timepoints after ivacaftor initiation, and to assess current screening practices for CVD risk factors among CF providers.

DESIGN: This was a post-hoc correlative analysis of prospectively collected clinical data and serum samples from the GOAL cohort study. Cross-sectional survey methodology was also employed.

METHODS: We evaluated serum lipids (total cholesterol (TC), low-density lipoprotein (LDL), and high-density lipoprotein (HDL)) at baseline, 3- and 18 months after ivacaftor initiation using samples from the GOAL study biorepository. We also surveyed CF providers across the United States on their CVD risk screening practices.

RESULTS: Fifty GOAL participants' samples were analyzed. Using the repeated measures model, TC significantly varied by visit (p = 0.004), driven by a significant increase from baseline at 3 months (mean difference 9.4 mg/dL). This difference diminished by 18 months. BMI was a significant covariate for TC. No significant differences by visit were detected in LDL or HDL. Seventy-five respondents participated in the survey (response rate 5.6%; 41 adult providers, 18 pediatric providers, and 10 providers caring for both) with 67% reporting no lipid screening policy existed in their center. In the past year, 29% of adult providers prescribed lipid-lowering therapy, 54% started anti-hypertensive medications, and 48% initiated ischemic cardiac evaluations for pwCF.

CONCLUSION: TC significantly increased within 3 months of initiating ivacaftor, but subsequently diminished toward baseline by 18 months. Lipid screening practices among CF providers were variable and providers are increasingly being confronted with managing CVD risk factors. Partnering with primary care providers is likely to become increasingly important in CF care models.

PMID:39891563 | DOI:10.1177/17534666251317200

MAGMA. 2025 Feb 1. doi: 10.1007/s10334-024-01222-2. Online ahead of print.

ABSTRACT

OBJECT: Spatio-temporal MRI methods offer rapid whole-brain multi-parametric mapping, yet they are often hindered by prolonged reconstruction times or prohibitively burdensome hardware requirements. The aim of this project is to reduce reconstruction time using deep learning.

MATERIALS AND METHODS: This study focuses on accelerating the reconstruction of volumetric multi-axis spiral projection MRF, aiming for whole-brain T1 and T2 mapping, while ensuring a streamlined approach compatible with clinical requirements. To optimize reconstruction time, the traditional method is first revamped with a memory-efficient GPU implementation. Deep Learning Initialized Compressed Sensing (Deli-CS) is then introduced, which initiates iterative reconstruction with a DL-generated seed point, reducing the number of iterations needed for convergence.

RESULTS: The full reconstruction process for volumetric multi-axis spiral projection MRF is completed in just 20 min compared to over 2 h for the previously published implementation. Comparative analysis demonstrates Deli-CS's efficiency in expediting iterative reconstruction while maintaining high-quality results.

DISCUSSION: By offering a rapid warm start to the iterative reconstruction algorithm, this method substantially reduces processing time while preserving reconstruction quality. Its successful implementation paves the way for advanced spatio-temporal MRI techniques, addressing the challenge of extensive reconstruction times and ensuring efficient, high-quality imaging in a streamlined manner.

PMID:39891798 | DOI:10.1007/s10334-024-01222-2

Environ Monit Assess. 2025 Feb 1;197(2):219. doi: 10.1007/s10661-025-13627-0.

ABSTRACT

Water quality prediction is crucial for water resource management, as accurate forecasting can help identify potential issues in advance and provide a scientific basis for sustainable management. To predict key water quality indicators, including chemical oxygen demand (COD), suspended solids (SS), total phosphorus (TP), pH, total nitrogen (TN), and ammonia nitrogen (NH₃-N), we propose a novel model, CA-TCN-BiGRU, which combines channel attention mechanisms with temporal convolutional networks (TCN) and bidirectional gated recurrent units (BiGRU). The model, which uses a multi-input multi-output (MIMO) architecture, is capable of simultaneously predicting multiple water quality indicators. It is trained and tested using data from a wastewater treatment plant in Huizhou, China. This study investigates the impact of data preprocessing and the channel attention mechanism on model performance and compares the predictive capabilities of various deep learning models. The results demonstrate that data preprocessing significantly improves prediction accuracy, while the channel attention mechanism enhances the model's focus on key features. The CA-TCN-BiGRU model outperforms others in predicting multiple water quality indicators, particularly for COD, TP, and SS, where MAE and RMSE decrease by approximately 23% and 26%, respectively, and R2 improves by 5.85%. Moreover, the model shows strong robustness and real-time performance across different wastewater treatment plants, making it suitable for short-term (1-3 days) water quality prediction. The study concludes that the CA-TCN-BiGRU model not only achieves high accuracy but also offers low computational overhead and fast inference speed, making it an ideal solution for real-time water quality monitoring.

PMID:39891761 | DOI:10.1007/s10661-025-13627-0

Eur Radiol. 2025 Feb 1. doi: 10.1007/s00330-025-11399-2. Online ahead of print.

ABSTRACT

OBJECTIVES: To exploit the capability of super-resolution deep learning reconstruction (SR-DLR) to save radiation exposure from coronary CT angiography (CCTA) and assess its impact on image quality, coronary plaque quantification and characterization, and stenosis severity analysis.

MATERIALS AND METHODS: This prospective study included 50 patients who underwent low-dose (LD) and subsequent ultra-low-dose (ULD) CCTA scans. LD CCTA images were reconstructed with hybrid iterative reconstruction (HIR) and ULD CCTA images were reconstructed with HIR and SR-DLR. The objective parameters and subjective scores were compared. Coronary plaques were classified into three components: necrotic, fibrous or calcified content, with absolute volumes (mm3) recorded, and further characterized by percentage of calcified content. The four main coronary arteries were evaluated for the presence of stenosis. Moreover, 48 coronary segments in 9 patients were evaluated for the presence of significant stenosis, with invasive coronary angiography as a reference.

RESULTS: Effective dose decreased by 60% from LD to ULD CCTA scans (2.01 ± 0.84 mSv vs. 0.80 ± 0.34 mSv, p < 0.001). ULD SR-DLR was non-inferior or even superior to LD HIR in terms of image quality and showed excellent agreements with LD HIR on the plaque volumes, characterization, and stenosis analysis (ICCs > 0.8). Moreover, there was no evidence of a difference in detecting significant coronary stenosis between the LD HIR and ULD SR-DLR (AUC: 0.90 vs. 0.89; p = 1.0).

CONCLUSIONS: SR-DLR led to significant radiation dose savings from CCTA while ensuring high image quality and excellent performance in coronary plaque and stenosis analysis.

KEY POINTS: Question How can radiation dose for coronary CT angiography be reduced without compromising image quality or affecting clinical decisions? Finding Super-resolution deep learning reconstruction (SR-DLR) algorithm allows for 60% dose reduction while ensuring high image quality and excellent performance in coronary plaque and stenosis analysis. Clinical relevance Dose optimization via SR-DLR has no detrimental effect on image quality, coronary plaque quantification and characterization, and stenosis severity analysis, which paves the way for its implementation in clinical practice.

PMID:39891682 | DOI:10.1007/s00330-025-11399-2

Eur Radiol. 2025 Feb 1. doi: 10.1007/s00330-025-11367-w. Online ahead of print.

ABSTRACT

OBJECTIVE: To estimate the developmental trends of quantitative parameters obtained from chest computed tomography (CT) and to provide normative values on dimensions of bronchi and arteries, as well as bronchus-artery (BA) ratios from preschool age to young adulthood.

MATERIALS AND METHODS: Two independent radiologists screened a dataset of 1160 chest CT scans, initially reported as normal, from participants aged 0 to 24 years. Using an automated deep learning-based algorithm, we computed the following bronchus and artery parameters: bronchial outer diameter (Bout), bronchial inner diameter (Bin), adjacent pulmonary artery diameter (A), bronchial wall thickness (Bwt), bronchial wall area (BWA), and bronchial outer area (BOA). From these parameters, we computed the following ratios: Bout/A, Bin/A, Bwt/A, Bwt/Bout, and BWA/BOA. Furthermore, mean lung density, total lung volume, and the square root of wall area of bronchi with a 10-mm lumen perimeter (Pi10) were obtained. The effects on CT parameters of age, sex, and iodine contrast were investigated using mixed-effects or regression model analyses.

RESULTS: 375 normal inspiratory chest CT scans (females / males = 156 / 219; mean age [SD] 12.7 [5.0] years) met the inclusion criteria. Bout and Bin progressively increased with age (all p < 0.05), but Bwt, Bout/A, Bin/A, Bwt/A, Bwt/Bout, or BWA/BOA did not. Total lung volume and mean lung density continuously increased with age (both p < 0.001), while Pi10 did not exhibit such a trend. Bout, total lung volume, and mean lung density were the only parameters that differed between males and females, all higher in males than females (all p < 0.03). The presence of iodinated contrast led to greater values for Bwt, Bwt/Bout, and BWA/BOA, but lower values for Bin, Bout/A, Bin/A, and Bwt/A (all p < 0.01).

CONCLUSION: Quantitative CT parameters of both lung parenchyma and bronchi exhibit growth-related changes, but from 6 to 24 years ratios between bronchus and artery dimensions remain constant. Contrast-enhanced CT scans affect the assessment of lung parenchyma and bronchial size. We propose age and technique-dependent normative values for bronchial dimensions and wall thickness.

KEY POINTS: Question What are the developmental trends of quantitative lung CT parameters in patients from childhood into young adulthood? Findings The ratio between bronchus and pulmonary artery dimensions demonstrates consistent values across age groups, indicating synchronized growth between bronchi and paired pulmonary arteries. Clinical relevance Our findings highlight the importance of standardized CT protocol and volume acquisition, and emphasize the need for ongoing collection of normal chest CT scans to refine the proposed reference values.

PMID:39891681 | DOI:10.1007/s00330-025-11367-w